vegetable production with wastewater from akaki - hru-ir home

VEGETABLE PRODUCTION WITH WASTEWATER FROM AKAKI

RIVER IN ADDIS ABABA: PERCEPTIONS, RISKS, AND LOW-COST

REMEDIATION

PhD DISSERTATION

DESTA WOLDETSADIK DEMISSIE

NOVEMBER 2017

HARAMAYA UNIVERSITY, HARAMAYA



REMEDIATION

A PhD Dissertation submitted to the Postgraduate Program Directorate

(School of Natural Resources Management and Environmental Sciences)

HARAMAYA UNIVERSITY

In Partial Fulfillment of the Requirements for the Degree of

DOCTOR OF PHILOSOPHY IN SOIL SCIENCE

By

Desta Woldetsadik Demissie

November 2017

Haramaya University

ii

HARAMAYA UNIVERSITY

Postgraduate Program Directorate

We hereby certify that we have read and evaluated this dissertation titled “Vegetable Production

with Wastewater in Addis Ababa: Perceptions, Risks, and Low-Cost Remediation” prepared

under our guidance by Desta Woldetsadik Demissie. We recommend that it be submitted as

fulfilling the PhD dissertation requirement.

1. Pay Drechsel (PhD)

Chairman of the Advisory Committee Signature Date

2. Prof. Fisseha Itanna (PhD)

Member of the Advisory Committee Signature Date

3. Prof. Heluf Gebrekidan (PhD)


4. Bernard Keraita (PhD)


As a member of the Board of Examiners of the PhD Dissertation Open Defense Examination, we

certify that we have read and evaluated the Dissertation prepared by Desta Woldetsadik

Demissie and examined the candidate. We recommend that the Dissertation be accepted as it

fulfills the Dissertation requirements for the degree of Doctor of Philosophy (PhD) in Soil

Science.

1. _______________________ ______________ ____________

Chairperson Signature Date

2. ________________________ _______________ _____________

Internal Examiner Signature Date

3. ________________________ ______________ ______________

External Examiner Signature Date

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DEDICATION

This dissertation is dedicated to my beloved family.

iv

STATEMENT OF THE AUTHOR

By my signature below, I declare and affirm that this dissertation is my own work. I have

followed all ethical and technical principles of scholarship in the preparation, data collection,

data analysis and compilation of this Dissertation. Any scholarly matter that is included in the

Dissertation has been given recognition through citation.

This Dissertation is submitted in partial fulfillment of the requirements for a PhD degree at

Haramaya University. The Dissertation is deposited in the Haramaya University Library and is

made available to borrowers under the rules of the Library. I solemnly declare that this

Dissertation has not been submitted to any other institutions anywhere for the award of any

academic degree, diploma or certificate.

Brief quotations from this dissertation may be made without special permission provided that

accurate and complete acknowledgement of the source is made. Requests for permission for

extended quotations from or reproduction of this dissertation in whole or in part may be granted

by the Head of the School or Department when in his or her judgment the proposed use of the

material is in the interest of scholarship. In all other instances, however, permission must be

obtained from the author of the Dissertation.

Name: Desta Woldetsadik Demissie Signature: ________________

Place: Haramaya University, Haramaya

Date of Submission: __________________

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BIOGRAPHICAL SKETCH

The author was born on September 21, 1982 in Addis Ababa. He attended primary and

secondary educations at Werha Yekatit Primary and Abiyot Kirs Secondary Schools,

respectively, in Addis Ababa. In 2002, he joined Mekelle University and graduated in 2005 with

the degree of Bachelor of Education in Chemistry. After graduation, he was recruited as a

Graduate Assistant I by the Ministry of Education and granted postgraduate scholarship and

received the degree of master of science in Inorganic Chemistry (2007) from Addis Ababa

University. Prior to joining the PhD program, he served for three years (August 2007- October

2010) as a Lecturer in the Department of Chemistry at Jigjiga University.

.

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ACKNOWLEDGEMENTS

My sincere appreciation and profound gratitude goes to my major supervisor, Dr. Pay Drechsel,

for his excellent supervision, never ending guidance, support and encouragement, fruitful

discussion, and painstakingly reviewing all versions of the manuscripts. Certainly, he has

demonstrated a superb quality mentorship. I consider myself extremely lucky to have worked

with him and am forever indebted to him. I wish to extend my deepest gratitude to my co-

advisors, Prof. Fisseha Itanna and Dr. Bernard Keraita for their critical and keen supervision of

the PhD project. Thanks are also due to the late Prof. Heluf Gebrekidan for providing valuable

support during the early stages of the PhD project. He was always keen to offer advice and

support. May God rest his soul in peace!

Immense appreciation is also extended to, Prof. Bernd Marschner, the co-author of the

publications that have been compiled in this dissertation. He was very instrumental for the

successful accomplishment of the laboratory works at the Department of Soil Science/Soil

Ecology, Ruhr-Universitat Bochum, Bochum, Germany. I also duly acknowledge the kind

cooperation and assistance of Dr. Volker Haring, Julian Heitkotter and the staff of soil laboratory

at the department. I would also like to acknowledge the International Water Management

Institute (IWMI-CGIAR) under the water, Land and Ecosystems Research Program, and the

Ministry of Education of Ethiopia for financially supporting the PhD project.

I am also indebted to Haramaya University, the Soil Science program, Ruhr-Universitat Bochum,

National Soil Testing Center, Debre Ziet Agricultural Research Center, Aklilu Lemma Institute

of Pathobilogy and Akaki Basic Metals Industry for being instrumental in the successful

accomplishment of the PhD study. I also wish to acknowledge the unreserved support of

development agents (Biruk, Regassa, Wasehun, Albasework, Andualem, Merid, Alemayehu, and

Teshome) at various sub-city administrative areas of Addis Ababa. I have many colleagues and

brothers who have helped me in one or other way and would like to remember and thank some:

Abinet Haile, Dr. Tesfu Mengistu, Prof. Berhanu Erko, Samuel Feyissa, Dr. Birhan Asmame, Dr,

Araya Gebresilassie, Dr. Solomon Yared, Dr. Endale Amare, and Seid Mohammed. I am also

grateful to urban vegetable farmers of Addis Ababa for sharing their knowledge and experience

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about polluted water irrigation. I must not forget my home institute, Jigjiga University, for

granting me a study leave. I am extremely grateful.

I would like to thank my beloved parents, Woldetsadik Demissie and Emaweyesh Gebretsadik,

for their continuous prayers and unending moral support throughout the study period. I would

like to express my sincere and well deserved gratitude to my wife, Dr. Hillette Hailu, for her

encouragement, strong support, incredible patience and motivation. Finally, I am most grateful to

my son Hallelujah and his little sister Johanna, whose great love have always been a key driver

for all my efforts and achievements. Above all, I thank the almighty God who helped me to

finish the long journey.

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ACRONYMS AND ABBREVIATIONS

ANOVA Analysis of variance

BET Brunauer–Emmet–Teller

CEC Cation Exchange Capacity

CHB Coffee husk biochar

CGIAR Consultative Group for International Agricultural Research

CMB Cow manure biochar

CSA Central Statistical Agency

DOC Dissolved organic carbon

EC Escherichia coli

EDI Estimated daily intake

ES Egg shell

FAO Food and Agricultural Organization

FGD Focus Group Discussion

FMB Faecal matter biochar

FTIR Fourier Transform Infrared

GFAAS Graphite Furnace Atomic Absorption Spectrophotometer

ha hectare

HU Haramaya University

ICP-OES Inductively Coupled Plasma -Optical Emission Spectrometer

IWMI International Water Management Institute

LI Lime

LSD Least significant difference

LST Lauryl Sulfate Tryptose broth

MPN Most Probable Number

OC Organic Carbon

OM Organic Matter

PJB Prosopis juliflora biochar

PLB Poultry litter biochar

PTDI Provisional tolerable daily intake

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RML Recommended Maximum Limit

SAS Statistical Analysis System

SPSS Statistical Package for Social Sciences

SSA Sub-Saharan Africa

SSA Specific Surface Area

TC Total Carbon

THQ Target hazard quotient

TSA Total Surface Acidity

TSB Total Surface Basicity

TTHQ Total target hazard quotient

TN Total Nitrogen

UA Urban Agriculture

USEPA United States Environmental Protection Authority

UN United Nations

UNDP United Nations Development Program

WHO World Health Organization

WLE Water, Land and Ecosystems

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TABLE OF CONTENTS

STATEMENT OF THE AUTHOR IV

BIOGRAPHICAL SKETCH V

ACKNOWLEDGMENTS VI

ACRONYMS AND ABBREVIATIONS VIII

LIST OF PUBLICATIONS XI

ABSTRACT XII

1 GENERAL INTRODUCTION AND SITE DESCRIPTION 1

1.1 GENERAL INTRODUCTION 1

1.2 DESCRIPTION OF THE STUDY AREAS 8

1.3 REFERENCES 12

2 FARMERS' PERCEPTIONS ON IRRIGATION WATER

CONTAMINATION, HEALTH RISKS AND RISK MANAGEMENT

MEASURES IN PROMINENT WASTEWATER-IRRIGATED

VEGETABLE FARMING SITES OF ADDIS ABABA, ETHIOPIA

21

3 MICROBIOLOGICAL QUALITY OF LETTUCE (LACTUCA SATIVA)

IRRIGATED WITH WASTEWATER IN ADDIS ABABA, ETHIOPIA

AND EFFECT OF GREEN SALADS WASHING METHODS

34

4 HEAVY METAL ACCUMULATION AND HEALTH RISK

ASSESSMENT IN WASTEWATER-IRRIGATED URBAN VEGETABLE

FARMING SITES OF ADDIS ABABA, ETHIOIA

43

5 EFFECTS OF BIOCHAR AND ALKALINE AMENDMENTS ON

CADMIUM IMMOBILIZATION, SELECTED NUTRIENT AND

CADMIUM CONCENTRATIONS OF LETTUCE (LACTUCA SATIVA)

IN TWO CONTRASTING SOILS

56

6 EFFECT OF BIOCHAR DERIVED FROM FAECAL MATTER ON

YIELD AND NUTRIENT CONTENT OF LETTUCE (LACTUCA

SATIVA) IN TWO CONTRASTING SOILS

72

7 GENERAL SUMMARY AND CONCLUSIONS 84

8 APPENDICES 93

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LIST OF PUBLICATIONS

This dissertation is based on the following five published articles, which are referred by their

chapter numbers.

Chapter 2. Woldetsadik, D., Drechsel, P., Keraita, B., Itanna, F. and Gebrekidan H. 2017.

Farmers’ perceptions on irrigation water contamination, health risks and risk management

measures in prominent wastewater-irrigated vegetable farming sites of Addis Ababa,

Ethiopia. Environment Systems and Decisions, 37:4 doi.org/10.1007/s10669-017-9665-2

Chapter 3. Woldetsadik, D., Drechsel, P., Keraita, B., Itanna, F, Erko B. and Gebrekidan H.

2017. Microbiological quality of lettuce (Lactuca sativa) irrigated with wastewater in Addis

Ababa, Ethiopia and effect of green salads washing methods. International Journal of Food

Contamination, 4:3 doi:10.1186/s40550-017-0048-8.

Chapter 4. Woldetsadik, D., Drechsel, P., Keraita, B., Itanna, F. and Gebrekidan H. 2017. Heavy

metal accumulation and health risk assessment in wastewater-irrigated urban vegetable

farming sites of Addis Ababa, Ethiopia. International Journal of Food Contamination, 4:9

doi:10.1186/s40550-017-0053-y.

Chapter 5. Woldetsadik, D., Drechsel, P., Keraitia, B., Marschner, B., Itanna, F. and Gebrekidan

H. 2016. Effects of biochar and alkaline amendments on cadmium immobilization, selected

nutrient and cadmium concentrations of lettuce (Lactuca sativa) in two contrasting soils.

SpringerPlus, 5:397 doi:10.1186/s40064-016-2019-6.

Chapter 6. Woldetsadik, D., Drechsel, P., Keraitia, B., Marschner, B., Itanna, F. and Gebrekidan

H. 2016. Effect of biochar derived from faecal matter on yield and nutrient content of lettuce

(Lactuca sativa) in two contrasting soils. Environmental systems research, 6:2

doi:10.1186/s40068-017-0082-9.

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REMEDIATION

ABSTRACT

The use of wastewater to produce food crops particularly vegetables is very prevalent within and

outside the urban centers of developing countries. In the capital city of Ethiopia, Addis Ababa,

where irrigation water for cultivation of vegetables is commonly derived from the polluted Akaki

River, the practice has often been blamed for causing negative externalities to public health and

the environment. To address these issues, the studies of this doctoral dissertation mainly focused

on five aspects of wastewater and dried faecal matter biochar use in vegetable cropping system

of Addis Ababa. In the first study, data were collected on farm through 263 individual interviews

and 12 focus group discussions. The difference in perception to quality consideration of Akaki

River/irrigation water is highlighted by the result of Kruskal-Wallis H test analysis which shows

significant mean value (1.33) of positive perception towards the water quality by male farmers.

Among the perceived health risks, skin problems were top-rated health risk while eye burn, sore

feet and abdominal pains were rated low across the farming sites. Irrespective of the farming site

and gender differences, the most accepted health risk reduction measures were health promotion

programs and cessation of irrigation before harvesting. The requisite quantitative data on

contamination levels of irrigation water and selected leafy vegetables and potential health

implications were covered in study II and III. Lettuce was used as a test crop in study II

compared to additional two leafy vegetables (Swiss chard, and Ethiopian kale) in study III. At

this stage, an assessment was done to determine the faecal coliform, helminth eggs and heavy

metal levels of irrigation water and vegetables harvested from 10 urban vegetable farming sites.

Attempts were also made to assess the efficacy of common green salads washing methods and

potential health risk associated with the consumption of the analyzed vegetables via computing

estimated daily intakes (EDIs) and target hazard quotients (THQs) of heavy metals. The mean

faecal coliform levels of irrigation water ranged from 4.29-5.61 log10 MPN 100 ml−1

, while on

lettuce, the concentrations ranged from 3.46-5.03 log10 MPN 100 g−1

. Helminth eggs and larvae

were detected in 80% of irrigation water and 61% of lettuce samples. The helminth eggs

identified included those of Ascaris lumbricoides, Hookworm, Enterobius vermicularis, Trichuris

trichiura, and Taenia. Compared with the WHO recommendations and international standards,

the faecal coliform and helminth eggs levels in irrigation water and lettuce samples exceeded the

recommended levels. Irrespective of the tested washing methods, faecal coliform and helminth

eggs levels were significantly (p<0.05) reduced. However, the heavy metal concentrations in

irrigation water and irrigated soils did not exceed upper threshold limits. Moreover, Cd, Co, Cr,

Cu, Ni and Zn concentrations in all analyzed vegetables were lower than the recommended

maximum permissible limits. Results of two way ANOVA test showed that variation in metals

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concentrations were significant (p < 0.001) across farming site, vegetable type and site x

vegetable interaction. The EDI and THQ values showed that there would be no potential health

risk to local inhabitants due to intake of individual metal. To assess the efficacy of seven

treatments including biochars produced from dried faecal matter and manures as stabilizing

agents of Cd in Cd-spiked soils, lettuce was grown in glasshouse on two contrasting soils in

study IV. Ammonium nitrate (NH4NO3) extraction results indicated that faecal matter biochar,

cow manure biochar and lime significantly reduced bioavailable Cd by 84–87, 65–68 and 82–91

%, respectively, as compared to the spiked controls. The immobilization potential of faecal

matter biochar and lime were superior to the other treatments. On the basis of a preceding study,

the effect of dried faecal matter biochar, N fertilizer and their interaction on biomass production

and nutrient contents of lettuce was tested. Lettuce was grown over two growing cycles under

glasshouse on two contrasting soils amended once at the start with factorial combination of

faecal matter biochar at 4 rates (0, 10, 20 and 30 t ha−1

) with 0, 25 and 50 kg N ha−1

in

randomized complete block design. For both soils, maximum fresh yields were recorded with

biochar and combined application of biochar with N treatments. It was also observed that faecal

matter biochar application resulted in noticeable positive residual effects on lettuce yield and

tissue nutrient concentrations. Most nutrients analyzed (N, P, K, Mg, Cu and Zn) were within or

marginally above optimum ranges for lettuce under biochar amendment. In conclusion, the study

indicated that faecal contamination level of lettuce irrigated with contaminated irrigation water

is above the threshold of safe consumption, but in a range which can be addressed through

relatively simple and low-cost mitigation measures. Nevertheless, it is clear that heavy metals

pose relatively no risk to local inhabitants through the consumption of leafy vegetables grown on

polluted water- irrigated vegetable farming sites. On the other hand, application of faecal matter

biochar enhances Cd immobilization, yield and tissue nutrient concentrations of lettuce,

suggesting that faecal matter biochar could be used as an effective heavy metal stabilizing agent

and fertilizer for lettuce production.

Keywords: Wastewater, Irrigation, Addis Ababa, Faecal contamination, Heavy metals, Faecal

matter biochar, Low-cost remediation

1. GENERAL INTRODUCTION AND SITE DECRIPTION

1.1. GENERAL INTRODUCTION

Globally, urban population doubled between 2000 and 2015 (Tacoli et al., 2015; Gollin et al.,

2016). In 2015, Africa's urban population reached 396 million and by 2050, expected to rise to

579 million (Kessides, 2006; United Nations (UN), 2010; Tacoli et al., 2015). This phenomenal

growth is typical of sub-Saharan Africa where annual population growth in cities is the highest

(4 %) in the world (World Bank, 2009), whereby the major challenge is to feed the growing

population of mega cities. In Ethiopia, more than 20% of the population dwell in cities, of which

16.7% reside in the capital city, Addis Ababa (CSA, 2013). Meanwhile, much of the population

lives in poor quality and overcrowded housing that lacks access to the infrastructure and services

that urban city need including safe, regular water supplies and sanitation infrastructure, drainage

and health service. In reaction to increasing food demand, urban dwellers are practicing various

agricultural activities in and around urban areas.

The urbanization phenomenon has spurred urban agriculture, which is all forms of agricultural

production within and around cities, which mainly provide urban markets with food products and

for consumption by the city-dwelling growers (Bolan, 2005; van Veenhuizen and Danso, 2007).

It covers a range of production systems and techniques ranging from vegetable production,

animal husbandry and aquaculture (Drechsel and Dongus, 2010). Although the true scale of UA

is likely underestimated in several previous studies (Food and Agriculture Organization of the

United Nations (FAO), 1996); United Nations Development Program (UNDP), 1996 ), the

practice is growing into an important economic sector (Zezza and Tasciotti, 2010).

Urban agriculture cannot be seen separately from wastewater use. It is characterized by the use

of alternative water sources such as municipal and industrial wastewater (Qadir et al., 2010;

Drechsel and Hanjra, 2016). In most cities of sub-Saharan Africa, urban growth has outpaced the

development of sanitation infrastructure and waste disposal practices and large volumes of

wastewater, solid waste and excreta are released to natural water bodies. These natural water

bodies (rivers and streams) are traditionally used for irrigation (Drechsel et al., 2006). A very

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comprehensive recent estimate shows that more than 29 million ha of croplands are being

irrigated with untreated wastewater across the world (Thebo et al., 2017). The authors of this

truly comprehensive study suggest that the possibility of the food being contaminated by

wastewater is higher than one ever thought. In fact, around 885 million people (almost one in

nine) are consuming foods that have been irrigated with wastewater. This misbalance in favor of

untreated wastewater will continue to increase as long as the contamination of natural water

bodies, by effluents and solid wastes from growing urban population is not matched by treatment

facilities. Globally, the increasing scarcity of good quality water will turn wastewater irrigation

from an undesirable phenomenon into a necessity (Bos et al., 2010; Jiménez et al., 2010; Thebo

et al., 2017).

The use of wastewater in urban agriculture plays a significant role in combating urban food

shortages by supplying food crops mainly vegetables to meet the demand of the ever increasing

urban population. Where vegetables are the main commodity produced with wastewater, there

can be a significant aggregate benefit for the society in terms of a more balanced diet (Jiménez et

al., 2010). In Kumasi (Ghana), for example, more than 70% of lettuce, cabbage and spring

onions consumed are produced using wastewater (Cofie et al., 2003). In the case of Accra, more

than 200,000 people eat vegetables produced with wastewater every day (Amoah et al., 2007).

Similarly, in Dakar (Senegal), about 60% of the national vegetable consumption is produced

using wastewater in and around the city (Moustier and Mbaye, 1999). Across major cities in

Asia, between 50-70% of leafy vegetables consumed by urban dwellers are produced within or

close to the city (Ensink et al., 2004; De Bon et al., 2010) where much of the water used for

irrigation is polluted.

Besides combating food shortages, farming in urban vicinity offers market proximity and high

opportunities for income generation, especially for rural migrants with no other qualification

than farming, while the water is a reliable and free source and depending on the degree of

dilution might also replace the need for additional fertilizer application (Drechsel et al., 2006;

Raschid-Sally and Jayakody, 2008; Qadir et al., 2010). Drechsel et al. (2007) estimated a

monthly income between US$ 40 - 1160 per urban farm in Accra (Ghana), Bamako (Mali),

Cotonou (Benin), Lagos (Nigeria), and Ouagadougou (Burkina Faso). However, the same and

2

several other studies also report high levels of pathogen indicator organisms or also heavy metals

in vegetables grown with polluted urban water sources and significant potential risk for farmers

and consumers.

As in the case of many other African cities, considerable number of urban dwellers in several

Ethiopian cities have taken up urban agriculture (Axumite, 1994; Axumite et al., 1994; Dereje et

al., 2007; Alebel et al., 2009). Addis Ababa is a typical example (Alebel et al., 2011a,b). The use

of polluted water for urban vegetable production is a highly prevalent practice in the city. In

Addis Ababa, large volumes of untreated wastewater are released to water bodies which farmers

use for irrigation (Alebel et al., 2011a,b). According to Nuttal (2011), not only liquid waste

provides a challenge, but also solid waste dumped along Addis Ababa main river, near bridges

and shores of small tributaries where it is washed into the river. The increase in use of diluted or

even raw wastewater is thus in most cases not farmers' choice, as alternative sources are lacking.

Despite all potential risks, irrigated farming of high value crops is a source of livelihood for a

number of urban residents since it provides employment and income (Alebel Bayrau et al.,

2009). About 60% of the city’s vegetable consumption, particularly leafy vegetable, is supplied

by urban farmers who irrigate their crops using raw or diluted wastewater (Nuttal, 2011).

Several studies carried out in urban areas of developing countries revealed poor quality of

irrigation water sources (Amoah et al., 2005, 2007; Ensink et al., 2007). Consequently,

vegetables produced under such poor sanitation are vulnerable to microbial contamination

(Amoah et al., 2005, 2007; Ensink et al., 2007; Qadir et al., 2010; Blaak et al., 2015). In relation

to consumption related health risks, the primary concern is about vegetable eaten uncooked. Raw

eaten vegetables grown in contaminated water irrigated farms need to get special consideration

since potential pathogenic microorganisms that get in contact may survive for quite some time

and could pose potential health concerns for consumers (Aruscavage et al., 2006; Qadir et al.,

2010). Although it is a challenge to attribute diarrhoeal outbreaks to specific exposure routes due

to other contributing factors, several diarrhoeal outbreaks have been fully and partly associated

with wastewater irrigated vegetables (Shuval et al., 1984; World Health Organization (WHO),

2006; Mara and Sleigh, 2010). For example, in Kumasi (Ghana), Seidu et al. (2015) revealed the

considerable contribution of consuming wastewater-irrigated lettuce to the transmission of E.

3

coli O157:H7. A study by Peasey (2000) have shown higher Ascaris infections for both adults

and children consuming uncooked vegetables irrigated with wastewater. But the most affected

groups are farm workers due to the duration and intensity of their contact with wastewater and

contaminated soils (Blumenthal and Peasey, 2002; WHO, 2006; Pham-Duc et al., 2014). In

Hanoi (Vietnam), for instance, 35% diarrhoeal episodes have been reported for farmers using

wastewater for irrigation and aquaculture (Trang et al., 2007). A cross-sectional study by Pham-

Duc et al. (2013) have shown higher helminth infection (47%) for farmers using wastewater

(Pham-Duc et al., 2013). In Addis Ababa, however, information on the bacteriological and

parasitological aspects of wastewater cropping system and potential health risks associated with

the practice is scanty (Berhanu and Mogessie, 2010; Mahlet, 2011).

Aside excreta borne pathogens, heavy metals can also be potential risk factors where industrial

effluent enters common water sources (Abougrain et al., 2010; Qureshi et al., 2016). Potential

health risks to human from the consumption of crops can be due to heavy metal uptake from

contaminated soils as well as foliar deposition from the atmosphere (Zhuang et al., 2009; Singh

et al., 2010a). Heavy metals are very harmful because of their non-biodegradable nature, long

half-lives and their high bioaccumulation potential (Duruibe et al., 2007; Shah et al., 2012).

Several researchers reported that serious health problems may develop as a result of excessive

accumulation of heavy metals and even essential trace elements such as Cu and Zn in human

body (Jarup, 2003; Duruibe et al., 2007; Khan et al., 2014). In Addis Ababa, a number of

articles have been published on wastewater-irrigated soils and vegetables contaminated with

heavy metals starting from the 90's (Fisseha, 1998,2002; Tamiru, 2006; Yirgaalem et al., 2012;

Minbale et al., 2015). Similar, work has been reported about the use of wastewater for vegetable

production in eastern Ethiopia (Deribachew et al., 2014) However, an insight into assessment of

human health risks associated with the consumption of vegetable crops grown on wastewater-

irrigated soils is non-existent.

There is overwhelming epidemiological evidence that wastewater and excreta use pose

significant health risks if undertaken without effective risk management practices (Shuval et al.,

1984; Blumenthal and Peasey, 2002; Keratia et al., 2010). To safeguard human health and ensure

the sustainability of the practice, a wide range of measures for risk reductions have been

4

suggested (Keraita et al., 2008; Amoah et al., 2011). These include conventional wastewater

treatment, as well as on-farm and post-harvest practices which in combination can constitute a

multiple barriers (WHO, 2006). But it is necessary that farmers see the risks. Without risk

awareness it will be very difficult to promote a behavior change towards safer practices.

Awareness can be based on practical experience, but farmers also incorporate new information

and concepts from colleague farmers, agricultural development agents, health extension officers,

field schools, input suppliers, the media and others into their knowledge base (Keraita et al.,

2010). Farmers can play a significant role in this context and for successful risk reduction they

will have to change behavior (Keraita et al., 2008, 2010). Perceptions of risks are expected to

influence how risks are managed (Stewart and Cherrie, 1998). Many studies revealed that farm

based interventions have largely failed due to lack of farmer participation (Drechsel and Gyiele,

1998; Collinson, 2000). In this regard, it is crucial to undertake risk perceptions study (Frewer,

2003).

The potential toxicity and persistent nature of heavy metals make the process of remediating

contaminated soil very complex (Wu et al., 2004). A number of ex-situ remediation options are

available for remediating contaminated soils (Dermont et al., 2008). However, most of these

remediation options are expensive and damages soil quality (Alkorta et al., 2004; Gosh and

Singh, 2005). In situ chemical immobilization technologies are the best demonstrated and

promising alternatives to ex-situ remediation methods (Kumpiene et al., 2008; Hmid et al.,

2015). Chemical immobilization is based on alteration of contaminant and soil characteristics by

the addition of stabilizing agents. Numerous amendments including clay minerals, organic and

liming materials and phosphate minerals have been widely examined for reducing metal mobility

and availability in heavy metal contaminated soils (Cao et al., 2003; Ok et al., 2010). The

immobilization process is influenced by various mechanisms including adsorption, specific

binding of metal ions, cation exchange, precipitation and complexation (Ok et al., 2007; Hmid et

al., 2015).

Biochar, which is carbonized biomass, is increasingly discussed as soil ameliorant with high

potential (Lehman and Joseph, 2009). It has many heavy metal immobilization properties

including microporous structure, active functional groups, high pH and cation exchange capacity

5

(CEC) (Jiang et al., 2012). Biochar, originated from plant residues, have been applied to soils for

immobilization of heavy metal contaminants (Mohan et al., 2007). In addition, Phosphorous -

rich biochars have also shown great potential to reduce the mobility and availability of metals in

water and soils contaminated with heavy metals (Uchimiya et al., 2010). Accordingly, biochars

derived from animal wastes have been spotlighted as heavy metal stabilization agents in

contaminated soils (Cao and Harris, 2010).

The ability of biochar to affect the fertility, carbon storage and remediation of soil varies

however with its characteristics (type of feedstock) as well as the temperature for its creation

(Antal and Gronli, 2003; Singh et al., 2010b). As a result, some biochars may be better suited for

one or more specific purposes for example of agronomic performance, contaminant stabilization,

or carbon sequestration (Agegnehu et al., 2015; Subedi et al., 2016). The application of biochar

to agricultural land provides several potential benefits, including enhancing the CEC (Glaser et

al., 2001), water holding capacity (Gaskin et al., 2007), and improving organic carbon and

nutrient contents of soils (Glaser et al., 2001). In addition, biochar may also be used in

remediation of contaminated soil and water (Cao and Harris, 2010).

Using animal manure for biochar production as presented e.g. by Uzoma et al. (2011) and Hass

et al. (2012) was not considered beneficial in Ethiopian context as animal manure is too valuable

for this transformation. The use of animal as well as faecal matter has a long tradition in

agriculture system, partly in raw form, partly after composting to minimize microbial risks

(Guzha et al., 2005). The situation changed with increasing health regulations and household

connections to sewer systems which increased the likelihood of chemical contamination where

also industrial effluent feeds into the same sewage. However, rural and peri-urban households

not connected to sewers but local septic tanks offer a significantly safer product (septage) for

reuse than sewage sludge (Jamali et al., 2009). To address the possible stigma of fertilizer

derived from human excreta, biochar offers an interesting value proposition where the pyrolysis

process guaranties a 100% pathogen elimination, as well as significant reduction in transport and

storage weight and volume (Tagoe et al., 2008).

6

Consequently, the following sets of hypothesis were formulated:

The Akaki river water used for producing vegetable crops in Addis Ababa is polluted

with microbial and heavy metals which could pose health risks to farm workers and

eventual consumers.

Farmers have no awareness on the pollution of irrigation water and the risks it imposes

to them and consumers of vegetables.

Biochar and alkaline amendments could reduce the mobility and phytoavailability of Cd

in Cd spiked soils.

The co-application of faecal matter biochar with N fertilizer may enhance the growth,

yield and nutrient status of lettuce.

Therefore to test the above hypotheses this study was initiated with the general objectives of

assessing farmers' perceptions towards contamination, health risk and reduction measures, public

health concerns of irrigated vegetable production through the assessment of potential risk

pathways and levels and efficacy of low-cost remediation options to reduce potential health risks

along the production-consumption chain.

The specific objectives of this study were to:

explore farmers’ perceptions and awareness towards irrigation with potentially unsafe

water, causes and effects of irrigation water contamination and health risks and risk

management measures.

quantify the levels of faecal coliform and helminth eggs contamination of irrigation

water and lettuce produced on a representative range of Addis Ababa's urban vegetable

farming sites.

to evaluate the efficacy of one of the WHO recommended interventions along the farm

to food pathway, which is improving food hygiene through effective washing of

contaminated vegetables during food preparation.

quantify the concentrations of heavy metals in irrigation water, soils and selected

vegetables on a representative range of Addis Ababa's urban vegetable farming sites.

7

estimate the daily intake and target hazard quotient of heavy metals through

consumption of selected leafy vegetables harvested from polluted water-irrigated urban

farming sites.

evaluate the efficacy of biochars and alkaline amendments as stabilizing agents of Cd in

spiked soils.

investigate the co-application of faecal matter biochar and N fertilizer on the growth,

yield and nutrient status of a popular cash crop, lettuce.

1.2. DESCRIPTION OF THE STUDY AREAS

This study was conducted in Addis Ababa, Ethiopia, where urban farmers have been practicing

vegetable production at various urban farming sites along the Akaki River ('Tinishu' and 'Teleku'

Akaki Rivers). Currently, more than 800 ha of land is irrigated for vegetable production using

water from the Akaki River (Alebel and Meron,2011). The areas covered are ten prominent

vegetable farming sites, locally known as Sore Amba, Lekunda, Peacock- Urael, Peacock-Bole,

Kera, Mekanissa, Lafto, Hana-Mariam, Akaki 08, Akaki (Figure 1) located at five sub-city

administrative areas: Kolfe Keraniyo, Chirkos, Bole, Nefas Silk Lafto and Akaki Kaliti, which

lies in 038 o

41' E to 038047' E and 08

052' N to 9

o02' N. The streams in consideration are

highlighted with blue color.

Sore Amba and Lekunda sites: The sites are located in the North West part of the city. The farm

areas are located in the upper stream of 'Tinishu' Akaki river. The discharge of municipal waste

and effluents from few factories are released into the Akaki river. Vegetable production using the

polluted Akaki river started in late 1950s (around 58 years ago). There are two form vegetable

production: producers' cooperatives and individual bases (Alebel and Meron, 2011). Major

vegetable crops grown are lettuce, Swiss chard, Ethiopian kale and spring onion. At these

farming sites, the manual construction of traditional weirs using sand bags and coarse stones is

the most common method to block the water flow till it can enter a system of irrigation channels

which follow gravity to support farms further downstream. Furrow irrigation method, by

manually opening and closing furrows constructed within the farms is used for cultivation of

8

vegetable crops. In addition to furrow irrigation technique, flood irrigation, by which fields are

flooded in a controlled manner by manually opening and closing of a bund, is also practiced.

Peacock-Urael and Peacock-bole sites: These sites cover irrigation farms within the

administrative areas of Bole sub-city in the central part of the city. The farm areas are located in

the upper stream of 'Teleku' Akaki river. Vegetable production using the polluted Akaki river

started 54 years ago at household level. Currently, majority of farmers in these sites are

organized under producers’ cooperative called ‘Bulbula' and 'Kebena' Vegetable Producers’

Cooperative (Alebel and Meron, 2011). Major types of vegetable crops grown are lettuce, Swiss

chard, and Ethiopian kale. Also, construction of traditional weirs is very common and furrow and

flood irrigation methods are commonly practiced. Some farmers use watering cans to irrigate

their vegetable crops.

Kera site: Also, located in the central suburb of the city. The city's main and big abattoir is just

adjacent to the farm areas. The site is only 15 m away from the main road that connect 'Kera' and

'Sar bet'. In this site, vegetable production started some 59 years ago. Municipal wastewater drain

flows into water channels. Major vegetable crops grown are lettuce and Swiss chard. Furrow

irrigation method is commonly used.

9

Figure 1.1. Location map of the study site

Mekanissa, Lafto and Hana-Mariam sites: These sites cover irrigation farms within Nefas Silk

Lafto sub-city administrative areas of the city. They are mainly located in the middle stream of

'Tinishu' Akaki River. There are a number of factories located within the boundary of these sites

(Alebel and Meron, 2011).Vegetable is cultivated both at the household and cooperative levels.

Farmers producing vegetables within these sites are organized under a vegetable producers’

cooperative called "Mekanissa-Gofa-Saris' cooperative. At these farming sites, vegetable

production started 60 years ago. Major vegetable crops grown include Lettuce, Swiss chard,

carrot and Ethiopian kale. Similarly, furrow and flood irrigation methods are commonly used.

Some farmers at Lafto farming site extract water from the Akaki river using diesel motor pumps

to irrigate their farms.

10

Akaki 08 and Akaki: These sites cover irrigation farms within Akaki Kaliti sub-city

administrative areas of the city. Farmers in these sites use water from 'Tinish' Akaki river. Also,

vegetable is cultivated both at the household and cooperative levels and are the oldest (62 years)

vegetable farming sites in the city. Major vegetable crops grown include potato, carrot, Ethiopian

kale, Swiss chard, tomato and lettuce. At these farming sites, the vast majorities of farmers use

diesel motor pumps to extract water directly from the river and transport to farms using

connected plastic pipes. Furrow and flood are also the most common irrigation methods (Alebel

and Meron, 2011).

11

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20

Environment Systems and Decisions Environment Systems and Decisions

https://doi.org/10.1007/s10669-017-9665-2

Farmers’ perceptions on irrigation water contamination, health risks and risk management measures in prominent wastewater‑irrigated vegetable farming sites of Addis Ababa, Ethiopia

Desta Woldetsadik1 · Pay Drechsel2 · Bernard Keraita3 · Fisseha Itanna4 · Heluf Gebrekidan1

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Abstract

The use of wastewater to produce food crops particularly vegetables is very prevalent in Addis Ababa, Ethiopia. This practice

may pose health risks to farm workers and consumers. Hence, the study was designed to evaluate farmers’ perceptions on

irrigation water quality, health risks and health risk mitigation measures in four wastewater-irrigated urban vegetable farming

sites in Addis Ababa. Data were collected on farm through 263 individual interviews and 12 focus group discussions. The

findings showed that despite differences in levels of knowledge and awareness on health risks, farmers appear informed about

the contamination of their irrigation water. The difference in perception to quality consideration of Akaki River/irrigation

water is highlighted by the result of Kruskal–Wallis H test analysis which shows significant mean value (1.33) of positive

perception toward the water quality by male than female farmers. Interestingly, significant difference (p < 0.05) in mean

values of awareness toward problems of eating unwashed vegetables is also found between male and female farmers where

females seemed to be more aware. Conversely, no significant difference was found in mean value of perception and aware-

ness toward vegetables quality. Among the perceived health risks, skin problems were top-rated health risk while eye burn,

sore feet and abdominal pains were rated low across the four farming sites. Although statistically not significant, perception

toward consumption-related health risk differed with gender: females assigned relatively high mean score. Irrespective of

the farming site and gender differences, the most accepted health risk reduction measures were health promotion programs

and cessation of irrigation before harvesting. In view of crop restriction measures, females assigned significantly (p = 0.044)

low mean score to planting non-food produce. Akaki-Addis farmers suitability perceptions of planting non-food produce and

non-raw eaten crops were significantly (p < 0.001) higher than the other farming sites. Therefore, effective site and gender-

specific educational programs have the potential for clarifying farmers and consumers’ risks and risk management percep-

tions and improving practical knowledge, which in turn may help identify adoption barriers, opportunities and incentives.

Keywords Wastewater · Irrigation · Farmers’ perception · Health risks · Health risk reduction measures · Educational

programs

* Desta Woldetsadik

[email protected]

Pay Drechsel

[email protected]

Bernard Keraita

[email protected]

Fisseha Itanna

[email protected]

Heluf Gebrekidan

[email protected]

1 School of Natural Resources Management

and Environmental Sciences, Haramaya University, PO Box:

138, Dire Dawa, Ethiopia

2 International Water Management Institute, Colombo, Sri

Lanka

3 Department of Global Health, University of Copenhagen,

Copenhagen, Denmark

4 Department of Crop Science, University of Namibia,

Windhoek, Namibia

21

mailto:[email protected]












https://doi.org/10.1007/s10669-017-9665-2

1 Introduction

Globally, urban population doubled between 2000 and

2015 (Tacoli et al. 2015; Gollin et al. 2016). In 2015, Afri-

ca’s urban population reached 396 million and by 2050,

expected to rise to 579 million (Kessides 2006; UN 2010;

Tacoli et al. 2015). This phenomenal growth is typical of

sub-Saharan Africa (SSA) where annual population growth in

cities is the highest (4%) in the world (World Bank

2009), whereby the major challenge is to feed the growing

population of mega cities. In Ethiopia, more than 20% of

the population dwell in cities, of which 16.7% reside in the

capital city, Addis Ababa (CSA 2013). Meanwhile, much of

the population live in poor quality and overcrowded

housing that lacks access to the infrastructure and services

that urban city need including safe, regular water supplies

and sanitation, drainage and health service. In reaction to

increasing food demand, urban dwellers are producing crops

in and around urban areas.

The urbanization phenomenon has spurred urban agricul-

ture, which is all forms of agricultural production within and

around cities, which mainly provide urban markets with food

products and for consumption by the city-dwelling growers

(Bolan 2005; van Veenhuizen and Danso 2007). It covers a

range of production systems and techniques ranging from

vegetable production, animal husbandry and aquaculture

(Drechsel and Dongus 2010). Urban agriculture cannot be

seen separately from wastewater use. It is characterized by the

use of alternative water sources such as municipal and

industrial wastewater (Qadir et al. 2010; Drechsel and Hanjra

2016). Since urban growth has outpaced the development of

sanitation infrastructure and waste disposal practices, large

volumes of wastewater, solid waste and excreta are released to

natural water bodies in many parts of the developing world.

These natural water bodies (rivers and streams) are

traditionally used for irrigation (Drechsel et al. 2006).

A very comprehensive recent estimate shows that more

than 29 M ha of croplands are being irrigated with waste-

water across the world (Thebo et al. 2017). In fact, around

885 million people (almost one in nine) are consuming

foods that have been irrigated with wastewater. This mis-

balance in favor of untreated wastewater will continue to

increase as long as the contamination of natural water

bodies, by effluents and solid wastes from growing urban

population is not matched by treatment facilities. Globally,

the increasing scarcity of good quality water is changing

wastewater irrigation from an undesirable phenomenon

into a necessity (Bos et al. 2010; Jimenez et al. 2010;

Thebo et al. 2017).

Addis Ababa is a typical example (Weldesilassie et al.

2011a, b). The increase in use of diluted or even raw

wastewater is thus in most cases not farmers’ choice, as

alternative sources are lacking. Irrigated farming of high

value crops is livelihood to many urban residents of the city

since it provides employment and income (Welde- silassie

et al. 2009). About, 60% of the city’s vegetable

consumption, particularly leafy vegetable, is supplied by

urban farmers who irrigate their crops using polluted river

water or diluted wastewater (Nuttal 2011). However, sev-

eral studies also report high levels of pathogen indicator

organisms and heavy metals in vegetables grown with pol-

luted urban water sources and significant potential risk for

farmers and consumers (Guchi and Ashenafi 2010; Habtu

2011; Aschale et al. 2015).

To safe guard human health and ensure the sustainability of

the practice, a wide range of measures for risk reductions

have been suggested (Keraita et al. 2008; Amoah et al.

2011). But it is necessary that farmers see the risks first. The

risks associated with wastewater reuse can be viewed and

experienced differently, which implies differing opinions on

how to both measure and manage those risks (Keraita et al.

2008, 2010; Maria 2011; Mayilla et al. 2017). In reality,

risks are perceived and do not correspond with quantifiable

frequencies, and therefore are unique to each individual,

based on values, education, experiences, and stake in the

outcome (Slovic 1999). It has been documented that certain

demographics, such as gender, have intrinsic differences in

risk perception (Stewart and Cherrie 1998). This gender dif-

ference has been documented in several surveys of environ-

mental issues, and the difference becomes more pronounced in

instances where health risks are associated to a common

practice (Nancarrow et al. 2008).

Generally, the acceptance of health protection measures

associated with wastewater reuse by farmers is a key to the

success of the system and farmers’ acceptability survey is a

must before introducing health risk reduction measures.

Moreover, the management practices that have evolved in

relation to polluted water or wastewater reuse for agri-

culture in one place cannot be readily transferred to other

places (WHO 2006; Keraita et al. 2008; Mayilla et al. 2016).

Hence, risk management decisions must take into account the

political, social and ethical, as well as technical, aspects of the

policy problem (Stewart and Cherrie 1998; Frewer 2003).

Effective management of wastewater is required to mitigate

public health and environmental consequences, and the

perception of that management is equally important to provide

confidence that wastewater (treated) reuse is a sustainable

practice or at least an acceptable risk (Keraita et al. 2008;

Karg and Drechsel 2011). The aims of this study were therefore

to explore farmers’ perceptions and awareness toward (1)

irrigation with potentially unsafe water, and causes and effects

of irrigation water contamination and (2) to understand

perceptions of male and female farmers on health risks and

risk management measures and how these might differ among

farming sites.

22


https://doi.org/10.1007/s10669-017-9665-2

2 Materials and methods 2.1 Study areas

This study was conducted in Addis Ababa, Ethiopia, where

urban farmers have been practicing vegetable production for

55–62 years at various urban farming sites along the Akaki

River. Currently, more than 800 ha of land are irrigated for

vegetable production in the city (Weldesilassie and Nigussie

2011). The areas surveyed were four prominent vegetable

farming sites: Akaki-Addis, Lafto-Mekanissa, Peacock and

Kolfe (Fig. 1) located at five sub-city administrative areas:

Kolfe Keraniyo, Chirkos, Bole, Nefas Silk Lafto and Akaki

Kaliti.

With the exception of low-topography Akaki-Addis farm-

ing site downstream of the city, where water is pumped from the

river, at all other sites, traditional weirs are constructed using

sand bags and coarse stones to block the water flow till it can

enter a system of irrigation channels which follow gravity

to the vegetable farms. In these farming sites, mainly leafy

vegetable such as lettuce, Ethiopian Kale and Swiss chard, are

grown using furrow irrigation method, by manually opening

and closing furrows constructed within

the farms. In addition to furrow irrigation technique, flood

irrigation, by which fields are flooded in a controlled manner by

manually opening and closing of a bund, is also used at

Peacock and Kolfe farming sites. At Akaki-Addis farming

site, the vast majorities of farmers use diesel motor pumps to

extract water directly from the river and transport to farm (for

flood and furrow irrigation) using connected plastic pipes.

2.2 Research methods

The study combined individual questionnaire survey and

focus group discussions (FGDs).

Questionnaires: The survey used open and close ended

questions. Closed questions were in the form of binary nature

(Yes or No), multiple choice type as well as ranking (4-point

Likert-type scales). The survey was conducted among farmers

using Akaki River water to irrigate vegetable in the four major

urban farming sites. A proportion principle was followed to

determine the number of survey participants of each farming

site: Those sites with high number of farmers and large farm

size were more represented in the survey (Weldesilassie et

al. 2008). Accordingly, 115, 70, 45 and 33 farmers were

selected for the survey from Akaki-Addis,

Fig. 1 Map of sampling sites

23


https://doi.org/10.1007/s10669-017-9665-2

Lafto-Mekanissa, Peacock and Kolfe vegetable farming

sites, respectively. The survey helps to gather information on

the following matters:

• Demographic profile and farming characteristics

• Aversions and drivers toward the use of Akaki River

water for vegetable production

• Perception and awareness on contamination

• Perception on causes and effects of contamination

• Perception on health risks

• Perception toward WHO proposed health risk reduction

measures

Focus group discussion: 60 farmers interviewed in the

farmers’ survey were selected for FGDs to better understand

reasons for common answers. We conducted 12 FGDs and

each FGD had five participants. To maintain group varia-

tion gender, age, educational level and site were taken into

account in the process of selecting the participants.

2.3 Statistical analysis

Data from the questionnaire were entered into SPSS/SAS

database. Statistical analysis was done after testing the

assumption of normality. Normality was not met; hence, the

Kruskal–Wallis H test was applied using SPSS package.

Multivariate probit regression analysis was used to examine

the correlations between gender, age, farming site, educational

level and religion with selected farming features (Table 1).

Statistically, significant difference was assumed at the 5%

level.

3 Results 3.1 Demographic profile and farming

characteristics

Farmers that participated in the survey were mainly men

(72%, N = 190) (Table 2). Female farmers had lower years of

formal education. Farmers were on average 69% Chris-

tian and 31% Muslim and between 18 and 70 years old

(Table 2). Akaki-Addis and Peacock farmers were on average

7–13 years younger than those in Lafto-Mekanissa and

Kolfe farming sites. Only 35% of all farmers attended more

than junior secondary school. Although farmers at the vast

Akaki-Addis farming site out of town and farmers at Peacock

farming site had comparable age (mean), Peacock farmers had

higher years of formal education.

Farmers were first asked how they acquired the land they

use for farming. Almost 47% farmers mentioned that their

farmlands were inherited from family, while 29% stated

farmland allotment by sub-city administration as part of

employment generation responsibility was the mode of

acquiring farmlands. Among the farming sites, this form of

farmland holding was very common (43%) in Akaki-Addis.

Farmers were then asked three questions about amendment/

fertilizer use, irrigation frequency and decision associated

with what vegetable crops to grow. Survey responses of

certain questions exceeded the sample size, as each farmer

gave/choose more than one answer to the same question.

With regard to driving factors to select what to grow, more

than 95% farmers gave marketability as a key driving factor.

Own consumption needs and seasonality have lower effect on

the decision (< 15%).

The multivariate probit regression analysis showed asso-

ciation of gender, age, farming site, educational level and

Table 1 Description of variables. (Reproduced from Marenya and Barrett 2007)

Dependent variables

Decision on what to grow Decision on what to grow based on

consumption needs

1 = yes, 0 = otherwise

Irrigation frequency Irrigate more than 2 times per week 1 = yes, 0 = otherwise

Manure or compost Apply manure or compost 1 = yes, 0 = otherwise

Fertilizer Apply fertilizer Explanatory variables 1 = yes, 0 = otherwise

Gender Gender of farmers 1 = female, 0 = male

Age Framers older than 35 years 1 = older than 35 years, = 0 otherwise

Farming site Akaki-Addis farmer Dummy variable, = 1 if farmer was from Akaki-Addis farming site, = 0

otherwise

Education Minimum of high school education Dummy variable, = 1 if farmers had at least high school education, = 0

otherwise

Education Junior secondary school education Dummy variable, = 1 if farmers had at least but not more than junior sec-

ondary school education, = 0 otherwise

Religion Muslim farmer Dummy variable, = 1 if farmer is a Muslim, = 0 otherwise

24


https://doi.org/10.1007/s10669-017-9665-2

Gender

Akaki-Addis

(n = 115)

Lafto-Mekanissa

(n = 70)

Peacock

(n = 33)

Kolfe (n = 45)

Male (%) 71 70 73 76

Female (%) 29 30 27 24

Age

18–35 (%) 50 26 49 13

36–50 (%) 27 44 33 31

Above 50 (%) 23 30 18 56

Highest educational level

Primary school (%) 42 43 21 51

Junior secondary school (%) 22 18 30 31

High school and above (%) 36 39 49 18

Religion

Christian (%) 77 81 64 53

Muslim (%) 23 19 36 47

Table 2 Demographic profile of

survey participants

religion with decision on what to grow based on own con-

sumption needs (Table 3). Female farmers were 22% more

likely to consider consumption need for decision making

than male farmers. Similarly, the marginal effect values

indicated that farmers from Akaki-Addis site, and farmers

older than 35 years were more likely to consider own

consumption needs before deciding what to grow, but the

farming site effect is higher (p < 0.001, approximately 15%).

Between 72 and 83% farmers irrigate their farms twice per

week, 19% once per week. The marginal effect values

revealed that gender, age, farming site, educational level and

religion had approximately no association with high irriga-

tion frequency (more than two times per week) (Table 3).

When asked about organic amendment/fertilizer use, approx-

imately 43% mentioned they applied compost or manure while

62% preferred mineral fertilizer. Unlike Akaki-Addis and

Lafto-Mekanissa farmers, most Kolfe farmers (76%) applied

compost or manure to their farms. The marginal effect of

Akaki-Addis farming site on the probability of fertilizer

application was significantly (p < 0.01) higher than that for

the other farming sites (Table 3). However, Akaki-Addis

farmers were 23% less likely to apply manure or compost.

3.2 Perceptions and awareness of contamination

Perceptions and awareness toward irrigation water and veg-

etable contaminations were assessed through the responses of

6 binary (Yes or No) type questions (Table 4). For the

purpose of analysis, we used numerical values “2” for Yes and

“1” for No. The variation in responses by gender, farming

site, educational status and age were processed. The dif-

ference in perception to problems with Akaki River/irriga-

tion water is highlighted by the result of Kruskal–Wallis H

test analysis which shows significant mean value (1.33) of

positive perception toward the water quality by male than

female farmers. We also found that male and female farmers

differed significantly in perception toward the use of the irri-

gation water for washing vegetables immediately after har-

vest. Interestingly, significant difference (p < 0.05) in mean

values of awareness toward problems of eating unwashed

vegetables is found between male and female farmers where

females seemed to be more aware. In a focus group discus-

sion, a female farmer from Lafto-Mekanissa farming site

said: “When we were young, we used to eat produce on farm

without washing. We had never encountered food poisoning.

But now if we eat unwashed produce, we may suffer from

poisoning.” On the other hand, no significant differences

were found in mean values of perception and awareness

toward vegetable quality and disease or illness caused by

eating contaminated vegetable. Likewise, we found no sig-

nificant difference in mean values of perception toward using the

irrigation water for hand washing soon after farming- related

activities between the two gender groups.

Perceptions toward hand and vegetable washing practices

using the river/irrigation water varied significantly (p < 0.05

and p < 0.01 for hand and vegetable, respectively) among

farmers of different farming establishments; farmers from

Akaki-Addis assigned significantly high mean values com-

pared with farmers of Lafto-Mekanissa and Kolfe farming

sites (Table 4). We also conducted analysis to determine

whether significant differences existed on perceptions and

awareness toward quality considerations (irrigation water and

vegetable), disease or illness caused by contaminated

vegetable and problems associated with eating unwashed

vegetable among farmers residing in different farming sites. No

significant differences were observed. The mean values of

perceptions and awareness toward quality (river/irrigation

water and vegetable), washing practice using the river

25


https://doi.org/10.1007/s10669-017-9665-2

Table 3 Marginal effects from multivariate probit regression of selected farming features as a function of demographic variables

Variable Coeff. Std.error p value Marg.effect

Consumption needs

Constant − 2.217 0.350 0.000

Gender 1.106 0.223 0.000 0.220

Farmers older than 35 years 0.503 0.246 0.040 0.100

Farmers from Akaki-Addis site 0.737 0.218 0.000 0.147

High school education − 0.098 0.264 0.709 − 0.019

Junior secondary school education 0.144 0.267 0.581 0.028

Religion 0.326 0.235 0.166 0.065

Irrigation frequency

Constant − 0.938 0.424 0.305

Gender − 5.669 0.000 – − 0.011

Farmers older than 35 years − 0.252 0.348 0.468 0.000

Farmers from Akaki-Addis site − 0.634 0.357 0.075 − 0.001


Junior secondary school education − 0.441 0.410 0.282 − 0.000

Religion 0.040 0.332 0.902 0.000

Manure or compost use

Constant − 0.069 0.226 0.759

Gender 0.043 0.184 0.815 − 0.017

Farmers older than 35 years 0.154 0.178 0.386 0.061

Farmers from Akaki-Addis site − 0.578 0.164 0.000 − 0.229


Junior secondary school education 0.193 0.209 0.356 0.076

Religion 0.244 0.184 0.185 0.097

Fertilizer use

Constant − 0.140 0.277 0.536

Gender − 0.324 0.186 0.081 − 0.129

Farmers older than 35 years 0.087 0.178 0.622 − 0.035

Farmers from Akaki-Addis site 0.480 0.163 0.003 0.191

High school education 0.129 0.193 0.501 0.051

Junior secondary school education − 0.212 0.209 0.310 − 0.084

Religion − 0.061 0.183 0.737 − 0.024

Model statistic Consumption needs Irrigation frequency Manure or compost

use

Fertilizer use

Sample size 263 263 263 263

Pseudo R2 0.188 0.144 0.056 0.041

Percent of correct predictions 85.9 95.8 62.7 59.7

irrigation water (hand and vegetable) and diseases/illness/

problems associated with contaminated/unwashed vegetable

were compared to determine whether they differed among

educational status and age groups.

Looking at educational status and age differences, it is

interesting to note that the youngest age (18–35) and most

educated (high school or above) clearly had significant

awareness toward diseases/illness/problems associated

with contaminated/unwashed vegetable (Table 4). The

mean values of positive perceptions toward irrigation water

and vegetable quality gradually but significantly

decreased with educational status: minimum mean values

(1.08 and 1.70 for irrigation water and vegetable, respec-

tively) for the highest educational status (high school or

above) and the maximum mean values (1.41 and 1.95 for

irrigation water and vegetable, respectively) for the lowest

educational status (elementary or below). Similarly,

positive perceptions toward the use of river/ir rigation

water for washing purpose (hand and vegetable) signifi-

cantly decreased with educational status. Conversely, posi-

tive perceptions toward quality consideration (irrigation

water and vegetable) and washing practices significantly

26

Env

ironm

ent S

ystem

s and

Decisio

ns

Table 4 Perceptions and awareness of contamination by gender, site, educational level and age

Okay with Akaki river/irriga-

tion water

Akaki river water can be

used for hand washing

Akaki river water can be

used for washing vegetables

Vegetables produced using

Akaki river is of good

quality

Informed about diseases

associated with contami-

nated vegetables

Eating unwashed vegeta-

bles pose health risks

Yes No Mean Yes No Mean Yes No Mean Yes No Mean Yes No Mean Yes No Mean

Gender

M 62 127 1.33 41 148 1.22 21 168 1.11 156 33 1.83 178 11 1.94 158 31 1.84

F 9 65 1.12 18 56 1.24 19 55 1.26 58 16 1.78 72 2 1.97 70 4 1.96

p < 0.001 p > 0.05 p < 0.01 p > 0.05 p > 0.05 p < 0.05

Site AA 31 84 1.27 36 79 1.31 27 88 1.23 88 27 1.77 111 4 1.97 101 14 1.88

LM 18 52 1.26 9 61 1.13 5 65 1.07 57 13 1.81 66 4 1.94 60 10 1.86

PP 7 26 1.21 8 25 1.24 5 28 1.15 28 5 1.85 31 2 1.94 30 3 1.91

KK 15 30 1.33 6 39 1.13 2 43 1.04 41 4 1.91 42 3 1.93 37 8 1.82

p > 0.05 p < 0.05 p < 0.01 p > 0.05 p > 0.05 p > 0.05

Education PS 44 64 1.41 36 72 1.33 22 86 1.20 103 5 1.95 97 11 1.90 84 24 1.78

JSS 20 42 1.32 18 44 1.29 12 50 1.19 46 16 1.74 60 2 1.97 54 8 1.87

HS 7 86 1.08 5 88 1.05 6 87 1.06 65 28 1.70 93 0 2.00 90 3 1.97

p < 0.001 p < 0.001 p < 0.01 p < 0.001 p < 0.01 p < 0.001

Age 18–35 3 94 1.03 8 89 1.08 7 90 1.07 67 30 1.69 97 0 2.00 97 0 2.00

36–50 28 59 1.32 20 67 1.23 16 71 1.18 71 16 1.82 85 2 1.98 74 13 1.85

51–70 40 39 1.51 31 48 1.39 16 63 1.20 76 3 1.96 68 11 1.86 57 22 1.72

p < 0.001 p < 0.001 p < 0.05 p < 0.001 p < 0.001 p < 0.001

Site: AA Akaki-Addis, LM Lafto-Mekanissa, PP Peacock, KK Kolfe

Educational Status: PS No formal education to primary school, JSS Junior secondary school, HS High school and above

27


increased with age: The youngest age group (18–35) had

lowest mean value.

Only source of water

Free of cost

3.3 Aversions and driver

Among the survey questions two were designed to acquire

information as to which factors avert and drive farmers

toward the use of Akaki River water for vegetable pro-

duction. Majority of farmers (91%) declared vegetable

diseases a very important aversion factor (Fig. 2). Yet, a

High yield

Supplement food supply

Ease of accessibility

Rich in nutrients

0 20 40 60 80 100

Percent

clear majority of them (77%) claimed that consumers do

not have negative attitudes toward the practice and pro-

duce. However, it is striking that 72% farmers declared

local media negative attitudes toward the use of Akaki

River water for irrigation as the main aversion factor. “If

someone mentions how the River water and vegetables are

contaminated and raise about associated health concerns—

even if the person is not from the concerned offices and

does not know what is going on around, the local media

could get hold of it.” The majority of the overall par-

ticipants, in fact, 83% of them felt health concern was not an

aversion factor toward the use of Akaki River water for

irrigation.

With the exception of very few farmers (4%), all did not

consider reasons associated with religions as discouraging

factor toward the practice. Despite the aversions, these

same farmers noticed multiple drivers associated with the

use of the River/irrigation water for vegetable production

(Fig. 3). The main driving factors were only source of

water (94%) and free of cost (79%). It was also interest-

ing to find that 56% noted “supplement food supply” as

one driving factor. Sixty-eight percent have also noticed

“high yield” as one motivation factor, although 69% of

them tended not to distinguish “nutrient value” as another

driving factor. Moreover, ease of accessibility (38%) has

lower driving effect toward the practice.

Fig. 3 Driving factors toward the use of Akaki River water for irriga-

tion

3.4 Perceived causes and effects of contamination

Farmers who have problems with the River water were asked

about perceived causes of Akaki River/irrigation water con-

tamination. They generally believed solid wastes (96%) and

industrial chemicals (80%) posed a greater contamination

risk (Fig. 4). Likewise, 72 and 53% of them thought sewage

from toilet and gray water are other important causes of con-

tamination, respectively. A male farmer said: “When we go to

the river, it is common to see people defecate on the shore of

the river. When it rains, the fecal matter will be washed into

the river. This cause more contamination.” Perceived causes

of Akaki River/irrigation water contamination that were

mentioned by small number of farmers include medical waste

(3%), runoff (5%) and gasoline and oil (10%). They were

also asked what they perceive as negative effects of Akaki

River/irrigation water contamination.

As shown in Fig. 5, majority of them (90%) perceived

deterioration of produce health as the main effect of con-

tamination. A male farmer from Lafto-Mekanissa said: “I

think pathogens in the contaminated water is the main cause of

poor health of produce.” Besides, 69% of them perceived

farming constraints (land preparation and water application)

another important effect of contamination. A male farmer

Vegetable diseases

Local media negative attitudes

Consumers negative attitudes

Health concerns

Religious reasons

0 20 40 60 80 100

Percent

Solid waste (household)

Industrial chemicals

Sewage from toilet

Grey water (household wastewater)

Gasoline and oil

Run off

Medical waste

0 20 40 60 80 100

Percent

Fig. 2 Aversions factors toward the use of Akaki River water for irri-

gation

Fig. 4 Perceived causes of Akaki River water contamination

28


Effect on produce health

irritation.” Kolfe farmers assigned significant importance to Effect on land preparation and water… muscular pain than Akai-Addis and Peacock farmers. The

Effect on farm workers finding that Kolfe farmers ranked muscular pain and sore

Produce chemical load feet higher than farmers of other farming sites is probably

Effect on produce consumers the engagement of these farmers in strenuous activities like

Odor constructing traditional weir and canals four or more time

Produce microbial load per year. Moreover, a considerable number of farmers in this

Effect on soil quality farming site are old. This may be related to physical strain

0 20 40 60 80 100 strain and hence the higher rating by older farmers. Percent

Fig. 5 Perceived effects of Akaki River water contamination

from Akaki said: “I suppose the first thing that would come to

my mind in relation to effect of Akaki River contamination is

solid wastes that damage water pump.” Effect on farm workers

was mentioned by 26% of this group of farmers, while a

small number of them were concerned about soil quality,

produce consumers, odor and produce contamination

(microbial and chemical), not exceeding 15% each.

3.5 Perceived health risk

Farmers who have problems with the River water were also

asked to list health risks associated with consumption and

occupation and asked to rate the perceived health risks on a

Likert scale from 1 (no risk) to 4 (high risk). Table 5 shows

mean scores for the perceived health risks. Although

statistically not significant, health risks associated with

occupation differed with gender: females assigned lower mean

scores to muscular pains but higher scores to skin problems

and sore feet, and felt that health risk associated with

consumption was higher. Among the perceived health risks,

skin problems were top-rated health risk while eye burn, sore

feet and abdominal pains were rated low across the four

farming sites. In a focus group discussion, a male farmer from

Kolfe farming site said: “If I see that the color of the water

turns to dark gray, obviously there must be chemicals in it,

so working with it surely causes skin

3.6 Perceptions of farmers on health risk

management measures

Eleven WHO proposed health protection measures (WHO

2006) were presented to the farmers. They were asked to rate

each measure on a Likert scale from 1 (not suitable) to 4

(highly suitable) to express how suitable they considered each

measure. The Kruskal–Wallis H test revealed that females

considered safe sanitation and drinking water significantly (p =

0.049) suitable than males (Table 6). Although statistically

not significant, males assigned higher mean scores to

deworming and immunization compared with females. No

statistically significant (p = 0.414) difference was also found

between male and female farmers regarding the suitability of

health promotion programs. Looking at crop restriction

measures, female farmers were against planting non-food

produce. Conversely, they assigned lower but non-significant

mean score to planting non-raw eaten food crops. Although

not statistically significant, females assigned higher mean

scores to safer irrigation methods and cessation of irrigation

before harvesting as compared to males (Table 6). Across the

four farming sites, the risk management measure which

received very high mean score was health promotion program

(Table 6). The measure aimed at reducing human exposure:

Immunization was perceived least to non. Irrespective of the

farming sites, farmers also did not see deworming as suitable

measure with mean suitability scores ranging from 1.50 to

2.06. Farmers across the four farming sites assigned high mean

scores to cessation of

Table 5 Mean score for perceived health risks by gender and farming sites

Health risks Gender p value Farming sites p value

Male Female Akaki-Addis Lafto-Mekanissa Peacock Kolfe

Abdominal pains 1.65a (0.96)b 1.80 (1.06) 0.410 1.79 (0.98) 1.48 (0.92) 1.62 (0.90) 1.90 (1.18) 0.180

Skin problems 3.29 (1.02) 3.53 (1.14) 0.293 3.29 (1.19) 3.17 (1.06) 3.31 (1.01) 3.63 (0.61) 0.291

Muscular pains 2.02 (1.16) 1.95 (1.16) 0.554 1.39 (0.74) 2.52 (1.13) 1.73 (1.15) 3.03 (1.06) 0.001***

Sore feet 1.54 (0.97) 1.65 (1.01) 0.385 1.24 (0.67) 1.77 (1.11) 1.38 (0.70) 2.33 (1.18) 0.001***

Eye burn 1.29 (0.67) 1.26 (0.59) 0.907 1.27 (0.63) 1.25 (0.65) 1.19 (0.49) 1.43 (0.77) 0.564

*** Indicates a p value < 0.001 aMean computed on a scale 1 to 4: 1 = no risk, 2 = low risk, 3 = moderate risk and 4 = high risk bStandard deviation in parenthesis

29


Table 6 Mean score for WHO proposed health risk reduction measures by gender and farming sites

Health risk reduction measures Gender p value Farming sites p value

Male Female Akaki-Addis Lafto-Mekanissa Peacock Kolfe

Human exposure control

Protective clothing: gloves, boots

2.76a (1.03)b

2.49 (1.09)

0.095

2.94 (0.87)

2.75 (1.01)

2.35 (1.20)

2.07 (1.20)

0.002**

Safe sanitation and drinking water 2.55 (1.08) 2.73 (1.09) 0.049* 2.62 (1.26) 2.44 (0.78) 2.69 (1.09) 1.90 (0.84) 0.011*

Deworming 1.83 (0.92) 1.72 (0.94) 0.322 1.70 (0.90) 2.06 (1.06) 1.92 (0.93) 1.50 (0.63) 0.065

Immunization 1.57 (0.80) 1.48 (0.81) 0.313 1.55 (0.77) 1.75 (1.01) 1.54 (0.71) 1.13 (0.35) 0.020*

Health promotion programs for 3.65 (0.75) 3.55 (0.83) 0.414 3.68 (0.79) 3.58 (0.85) 3.69 (0.55) 3.47 (0.78) 0.149

farmers

Crop restriction measures

Planting non-food produce 1.86 (1.10) 1.52 (0.90) 0.044* 2.45 (1.17) 1.10 (0.30) 1.38 (0.64) 1.20 (0.48) 0.001***

Planting non-raw eaten crops 2.52 (1.23) 2.31 (1.12) 0.244 3.07 (1.12) 1.85 (1.04) 1.81 (0.98) 2.30 (0.95) 0.001***

Water application techniques

Safer irrigation methods 2.44 (1.16) 2.69 (1.20) 0.170 2.18 (1.13) 2.75 (1.15) 2.88 (1.18) 2.81 (1.13) 0.004**

Cessation of irrigation before

harvesting

Wastewater treatment

3.07 (1.06) 3.18 (1.09) 0.367 3.23 (0.97) 3.29 (1.04) 3.08 (1.06) 2.50 (1.22) 0.013*

Conventional 1.39 (0.72) 1.40 (0.77) 0.937 1.15 (0.42) 1.81 (0.97) 1.54 (0.81) 1.21 (0.55) 0.001***

Low-cost 2.03 (1.21) 2.01 (1.19) 0.953 1.64 (0.99) 2.29 (1.30) 2.73 (1.15) 2.03 (1.28) 0.001***

* Indicates a p value < 0.05

** Indicates a p value < 0.01

*** Indicates a p value < 0.001 aMean computed on a scale 1–4: 1 = not suitable, 2 = least suitable, 3 = moderately suitable and 4 = highly suitable bStandard deviation in parenthesis

irrigation before harvesting, indicating the low water appli-

cation frequencies followed by farmers of the surveyed sites.

Regarding measures related to wearing protective clothing,

safer irrigation methods and cessation of irrigation before

harvesting, significant differences were exhibited by farm-

ing sites. Akaki-Addis farmers suitability perceptions of

planting non-food produce and non-raw eaten crops were

significantly higher than the other farming sites. In a focus

group discussion, a female farmer from Lafto-Mekanissa

farming site said: “Allowing timber to grow for market value

will make us lose a portion of our farmland for quite long,

even those non-food produce which grow very quickly do not

have high market value, this is not suitable/acceptable at all.”

Peacock farmers also assigned significantly high mean score to

safe sanitation and drinking water where as the lowest mean

score was relegated by Kolfe farmers. Low cost water

treatment methods received little attention particularly by

Akaki-Addis and Kolfe farmers.

4 Discussion

Perception is influenced by a combination of personal fac-

tors that affect the way in which one understands and reacts to

issues (Furgal et al. 2005). Voluntary nature of exposure,

uncertainty about consequences of exposure, and the ease of

perception and understanding of the benefits associated with

exposure may also influence perceptions toward risks

(Pidgeon et al. 1992). Irrespective of the depth and level,

most farmers have general awareness about irrigation water

contaminations. In fact, females, young and educated groups

were somehow less confident in the quality of Akaki River

water. The comparison between water and vegetable quality

perceptions indicated that farmers tended to overestimate the

vegetable quality, little risk level from the water to the

produce.

Despite the aversions that discourage the practice of using Akaki

River water for irrigation, farmers were convinced that

motivational factors do outweigh aversions. It may be suggested

that the main factors that drive Addis Ababa farmers to use Akaki

River water for vegetable production are free source of water, and

need for food supply and high yield. However, it is striking that

more than 75% of farmers had some difficulty in acknowledging

the nutrient value of Akaki River/ irrigation water, while more

than 60% of farmers recognized increase in yield due to irrigation

with the river water. Other surveys have also observed that main

factors influencing the use of treated and untreated wastewater

includes sole water source, low cost and increase in yield

(Mojid et al. 2010; Carr et al. 2011; Weckenbrock et al. 2011;

Petousi

30


et al. 2015). Surprisingly, for Addis Ababa farmers, local

media complaint was a major discouraging factor toward the

practice. Increased local media coverage of complex and

controversial topics on the current vegetable production

practice using the river water made farmers more inclined to

aversion associated with such issue (Robinson et al. 2012).

Conversely, those farmers considering local media negative

attitudes to be a more important aversion factor tended to

downplay consumers negative attitudes.

Our results showed that farmers perceived solid wastes,

industrial effluents and sewage from toilet as important

source of Akaki River water contamination. These findings

were consistent with some studies that have examined the

perception of farmers toward causes of irrigation water con-

tamination (Mojid et al. 2010; Carr et al. 2011). For exam-

ple, a study by Silvano et al. (2005) indicated that farmers

perceived a number of anthropogenic inputs/land use prac-

tices including domestic sewage disposal and runoff of cattle

dung as important causes of water contamination. Moreover,

farming constraints (land preparation and water application)

were perceived as one main effect of water contamination.

The water contamination is also perceived to increase plant

pathogens that may enhance damage to vegetable crops. One

apparent observed contradiction concerning vegetable con-

tamination is that most farmers acknowledged problem asso-

ciated with contaminated vegetables, but at the same time

only some did acknowledge effect on produce consumers as

an impact of water contamination, because they did not want

to consider the health effect their produce may impose on

consumers.

According to Blumenthal and Peasey (2002), the greatest

risk for producers in the polluted water irrigated farming

derives from intestinal parasite infections and for produce

consumers from bacterial diseases infection. However, both

male and female farmers across the four farming sites

assigned high mean scores to skin problems. The finding

may be related with the perception of high chemical con-

taminant loads in the river water and therefore greater fear of

this health risk. Females perceived comparable health risks

associated with occupational health than males. Conversely,

Mayilla et al. (2017) found female farmers to be less averse to

most occupational risks than their male colleagues. Risk

management strategies involve providing information on key

issues to the farmers to improve awareness; however, the

method of delivery must take into account the demo-

graphics, particularly gender, of the farming community for

the perceived risks to be effectively managed (Slovic 1999;

Robinson et al. 2012). It has been documented in number

of surveys of health related issues that males and females

have intrinsic differences in risk perception (Dos- man et

al. 2001; Robinson et al. 2012). For example, females

perceive greater risks to health and safety from biosolids

recycling than males (Robinson et al. 2012). Yet, females

were observed to be more sensitive to the risks associated

with potable wastewater reuse than males (Nancarrow et al.

2008). The two perceived health risks which associate with

occupational health (muscular pain and sore feet) differed

significantly at 1% level (p < 0.001) by farming sites: Kolfe

farmers assigned higher mean risk scores to these health

risks compared with other farming establishments. This

could, in part, be a result of Kolfe farmers engagement in

strenuous activities. In agreement with the results of our

study, Accra farmers who spend much time in their fields,

engage in arduous farming activities, and who are old rated

occupational health risks higher than consumption-related

health risks (Drechsel et al. 2006; Keraita et al. 2008).

Irrespective of the farming sites and gender, health risk

reduction measures generally perceived suitable were health

promotion program, cessation of irrigation before harvest-

ing, and wearing protective clothing, while conventional

wastewater treatment was generally considered to be non-

suitable risk management tool. In previous studies of urban

farmers in few low-income countries (Keraita et al. 2008;

Mayilla et al. 2016), some of these measures were also per-

ceived suitable, even though perceptions on cessation of irri-

gation were quite different, indicating the suitability of each

measure depend on farming and climatic conditions of the

countries. Female farmers assigned significant importance

than male farmers to one health risk reduction measure: safe

sanitization and drinking water. The gender difference

concerning safe sanitization and drinking water could be

attributed to females’ socialization to the caregiver role and

structural position in the home (Blocker and Eckberg 1997).

Although not statistically significant, it appears that female

farmers assigned lower mean scores to protective clothing

than those of males. This may be attributed to heavy engage-

ment to specific cultivation related activities, weeding and

transplanting are commonly performed by females, which

make the use of protective clothing unfortunate. Moreover,

female farmers tended to perceive planting non-food pro-

duce least suitable than male farmers. The finding may be

related to females’ need to food supplements for household

from farms.

Our health risk reduction measure results showed a higher

suitability mean scores for planting non-food produce and

non-raw eaten crops in Akaki-Addis as compared with other

farming sites. The two crop restriction measures perceived

significantly suitable by Akaki-Addis farmers were actually

exercised on some surveyed farms of Akaki-Addis: the use of

small portion of farmlands for planting non-food produce and

considerable portion for non-raw eaten crops. The difference

may partly attributable to difference in farm size per farmer

between Akaki-Addis and the other farming sites

(Weldesilassie et al. 2008). The comparatively big farm size

in Akaki-Addis tended farmers to invest small portion of

land to cultivate non-food produce, especially fast growing

31


warm season grass. When deciding whether to assign high

suitability scores to health risk reduction measures, farmers

compare the extent of yield decline, investment and farm-

land needed. This would explain why farmers only account for

direct market benefit and opportunity, ignoring those that

benefit consumers and lack market value (Pearce 2001;

Silvano et al. 2005). Thus, educational efforts about health

risk reduction measures should start by addressing market-

related interests of farmers first, and risk reduction measures

second.

5 Conclusions

The use of Akaki River water (wastewater) for irrigation is a

very crucial agricultural economic activity in Addis Ababa

since it sustains the livelihoods of a large number of urban

community in the city. On the other hand, direct consumption

of food cultivated on land irrigated with wastewater is one

exposure pathway of pathogenic microorganisms. Farmers

can also acquire helminth diseases due to direct contact with

contaminated water and soils. However, both male and

female farmers across the four farming sites assigned low

mean scores to consumption-related health problem.

Therefore, indiscriminate training is highly required to

increase awareness among urban farming community about

the potential health risk of polluted water reuse.

The results of the present study revealed that farmers’

perceptions on health reduction measures significantly varied

among the study sites. Among the WHO proposed health risk

reduction measures, the most accepted measures were health

promotion programs and cessation of irrigation before

harvesting. Our health risk reduction measure results also

showed a higher suitability mean scores for two crop restric-

tion measures (planting non-food produce and non-raw eaten

crops) in Akaki-Addis as compared with other farming sites.

The difference may partly be attributable to difference in farm

size per farmer between Akaki-Addis and the other farming

sites. Hence, knowledge of motivators of risk reduction

measures is likely to help city authorities facilitate adoption by

steering efforts through considering specific motivators and

thereby recommend measure that suit a specific farming

site. Moreover, when deciding to assign low suitability scores

to health risk reduction measures, farmers consider extrinsic

barriers including the extent of yield decline, investment

and farmland needed. This would explain why farmers only

account for direct market benefit and opportunity, ignoring

those that benefit consumers but lack market value. Thus,

well-designed incentives (improved health of farmers,

higher economic returns for safer produce, and

institutional supports) could encourage farmers to reduce

the risks of using untreated wastewater by adopting safer

practices while maintaining a notable portion of the benefits

that accrue to farmers, consumers and the larger community.

Acknowledgements This work was supported by the International

Water Management Institute (IWMI-CGIAR) and the Ministry of

Education of Ethiopia. We wish to acknowledge the unreserved sup-

port of development agents at various sub-city administrative areas of

Addis Ababa. We are also grateful to urban farmers for sharing their

knowledge and experience about wastewater irrigation.

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Woldetsadik et al. International Journal of Food Contamination (2017) 4:3

DOI 10.1186/s40550-017-0048-8 International Journal

of Food Contamination

D A T A A R T I C L E Open Access

Microbiological quality of lettuce (Lactuca sativa) irrigated with wastewater in Addis Ababa, Ethiopia and effect of green salads washing methods

Desta Woldetsadik1*

, Pay Drechsel2

, Bernard Keraita3

, Fisseha Itanna4

, Berhanu Erko5

and Heluf Gebrekidan1

Abstract

Background: Wastewater irrigation is associated with several benefits including higher vegetable crop yields as it

provides not only water, but also essential nutrients. However, it also contains faecal pathogens that may cause diseases

to farm workers and consumers of wastewater-irrigated produce. In Addis Ababa, where irrigation water for vegetable

production is commonly derived from the highly polluted Akaki river, information on microbial contamination of water

and irrigated vegetable is scanty. An assessment was done to determine the microbiological quality of irrigation water

and lettuce harvested from 10 urban farming sites of Addis Ababa. The efficacy of 5 lettuce washing methods were

also assessed. A total of 210 lettuce and 90 irrigation water samples were analyzed for faecal coliform and helminth

eggs population levels.

Results: The mean faecal coliform levels of irrigation water ranged from 4.29-5.61 log10 MPN 100 ml−1

, while on

lettuce, the concentrations ranged from 3.46-5.03 log10 MPN 100 g−1

. Helminth eggs and larvae were detected in 80%

of irrigation water and 61% of lettuce samples. Numbers ranged from 0.9-3.1 eggs 1000 ml−1 and 0.8-3.7 eggs 100 g−1

wet weight for irrigation water and lettuce, respectively. The helminth eggs identified included those of Ascaris

lumbricoides, Hookworm, Enterobius vermicularis, Trichuris trichiura, Taenia and Strongloyides larvae. Ascaris lumbricoides

and Hookworm were most prevalent in both irrigation water and lettuce samples. Compared with the WHO

recommendations and international standards, the faecal coliform and helminth eggs levels in irrigation water and

lettuce samples exceeded the recommended levels. Irrespective of the tested washing methods, faecal coliform and

helminth eggs levels were somehow reduced. Among the washing methods, potable tap water washing - rinsing (2

min) followed by dipping in 15 000 ppm vinegar solution for a minute supported the highest faecal coliorm reduction

of 1.7 log10 units, whereas lowest reduction of 0.8 log10 units was achieved for the same procedure without vinegar.

Conclusion: Compared with international standards, both faecal coliform and helminth eggs levels exceeded

recommended thresholds in water and lettuce, but still in a potential risk range which can be easily mitigated if

farmers and households are aware of the potential risk. Aside preventing occupational exposure, potential risk

reduction programs should target households which have so far no guidance on how best to wash vegetables. The

result of the present study suggest that the vinegar based washing methods are able to reduce faecal coliform

towards low level while the physical washing with running water may help to substantially decrease potential risk of

helminth parasitic infections.

Keywords: Faecal coliform, Helminth eggs, Wastewater, Lettuce, Potential risk, Washing, Mitigation, WHO, Addis Ababa

* Correspondence: [email protected] 1School of Natural Resources Management and Environmental Sciences, Haramaya University, 138 Dire Dawa, Ethiopia Full list of author information is available at the end of the article

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0

International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

34


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Woldetsadik et al. International Journal of Food Contamination (2017) 4:3 Page 2 of 9

Background

In most urban and peri-urban cities of developing coun-

tries, the use of untreated, partially treated or diluted waste-

water for agriculture is a common practice (Scott et al.

2004; Raja et al. 2015). Market proximity, high opportun-

ities for income generation, reliable and free irrigation

water supply, and minimum artificial fertilizer requirement

are the often cited benefits of irrigation within cities

(Drechsel et al. 2006; Raschid-Sally and Jayakody 2008;

Qadir et al. 2010; Lyu et al. 2016). However, the same stud-

ies also report high levels of pathogen indicator organisms

or also heavy metals in vegetables grown with polluted

urban water sources.

The increase of ‘wastewater irrigation’ is however in most

cases not farmers’ choice (Raschid-Sally and Jayakody

2008). In Africa, the number of people without access to

adequate water and sanitation facilities has risen swiftly in

recent decades as the continent’s rapid urbanization out-

paced its capacity to provide the essential water and sanita-

tion services. In Addis Ababa, large volumes of untreated

wastewater are released to water bodies which farmers use

for irrigation (Weldesilassie et al. 2011a, b). According to

Nuttal (2011), not only liquid waste provides a challenge,

but also solid waste dumped along Addis Ababa main river,

near bridges and shores of small tributaries where it is

washed into the river. Despite all potential risks, irrigated

farming of high value crops is livelihood to many urban

residents since it provides employment and income

(Weldesilassie et al. 2009). About, 60% of the city’s vege-

table consumption, particularly lettuce, Swiss chard and

Ethiopian Kale, is supplied by urban farmers who irrigate

their crops using polluted river water or diluted wastewater

(Nuttal 2011). Hence, vegetables produced under such poor

sanitation are vulnerable for contamination (Heaton and

Jones 2008; Qadir et al. 2010; Blaak et al. 2015). Notably,

lettuce which is the main raw vegetable grown in contami-

nated water irrigated farms need to get special consider-

ation since potential pathogenic microorganisms that get in

contact may survive for quite some time and could pose

potential health concerns for consumers (Beuchat et al.

2001; Aruscavage et al. 2006; Qadir et al. 2010).

Information on the bacteriological and parasitological as-

pects of wastewater cropping system and potential health

risks associated with the practice is scanty (Guchi and

Ashenafi 2010; Habtu 2011). Aside excreta borne patho-

gens, also heavy metals can be a potential risk factor where

industrial effluent enters the common water sources as dis-

cussed by Itanna (1998, 2002), Fitamo et al. (2007) and

Weldegebriel et al. (2012). The data verify concentrations

of selected metals above irrigation water thresholds but

limited plant uptake due to high soil pH, cation exchange

capacity and clay content (Weldegebriel et al. 2012).

To assess potential pathogenic risk level, our study tried

to determine actual evidence of faecal coliform and

helminth eggs contamination of irrigation water and let-

tuce produced on a representative range of Addis Ababa’s

urban farming sites. To protect produce consumers,

WHO (2006) proposes multiple barrier management ap-

proaches that encompasses wastewater treatment, crop re-

strictions (planting non-food and non-raw eaten produce),

safer water application methods that reduce produce con-

tamination, improved food hygiene and better cooking of

food (Amoah et al. 2007b). In the present study, the effi-

cacy of one of the WHO recommended interventions

along the farm to food pathway, which is improving food

hygiene through effective washing of contaminated vege-

tables during food preparation, was evaluated.

Methods

Study area

This study was conducted in Addis Ababa, Ethiopia, where

urban farmers have been practicing vegetable production

for 55–60 years at various urban farming sites along the

Akaki River (‘Tinishu’ and ‘Teleku’ Akaki Rivers). The areas

covered are ten prominent vegetable farming sites, locally

known as Sore Amba, Lekunda, Peacock- Urael, Peacock-

Bole, Kera, Mekanissa, Lafto, Hana-Mariam, Akaki 08,

Akaki (Fig. 1) located at five sub-city administrative areas:

Kolfe Keraniyo, Chirkos, Bole, Nefas Silk Lafto and Akaki

Kaliti, which lies in 038 o41′ E to 038047′ E and 08052′ N

to 9°02′ N. Currently, more than 800 ha of land are

irrigated for vegetable production using water from the

Akaki River (Weldesilassie and Nigussie 2011).

With the exception of Akaki 08 and Akaki farming sites,

at all other sites the manual construction of traditional

weirs using sand bags and coarse stones is the most com-

mon method to block the water flow till it can enter a sys-

tem of irrigation channels which follow gravity to support

farms further downstream. In these farming sites, vege-

table crops, mainly leafy vegetable such as lettuce, Ethiop-

ian Kale and Swiss chard, are grown using furrow

irrigation method, by manually opening and closing fur-

rows constructed within the farms. In addition to furrow

irrigation technique, flood irrigation, by which fields are

flooded in a controlled manner by manually opening and

closing of a bund, is also used at Sore Amba, Lekunda,

Peacock- Urael, and Peacock-Bole farming sites. At Akaki

08 and Akaki farming sites, the vast majorities of farmers

use diesel motor pumps to extract water directly from the

river and transport to farm using connected plastic pipes.

Some farmers at Lafto farming sites also follow similar

water extraction methods. Among the farming sites, the

use of agricultural inputs such as inorganic fertilizers and

manures is very common at Sore Amba and Lekunda

farming sites. Lettuce was selected for this study since it is

the only raw eaten leafy vegetable produced in the study

area, i.e. the one crop with the highest potential risk for

consumers. Sampling was done from November 2013 to

35


Fig. 1 Map of the sampling sites

March 2014 which was the dry season when irrigation fre-

quency is highest.

Sample collection

At all farming sites, water was collected at a point where

farmers fetch/collect, or where it enters the farm via ca-

nals between 8 and 10 o’clock. From each of the farming

sites, 9 water samples, triplicate samples from three dif-

ferent fetching points/inlets to farm, were collected in

1 L sterilized glass bottles and transported in an

icebox to the laboratory where they were stored at 4

°C until faecal coliform and helminth eggs analysis.

At each farming site, which is depending on its size

operated by 5-25 farmers, 5 different vegetable farms

were selected and 75 lettuce samples (5 vegetable farms

* 3 plots per farm * 5 lettuce samples from each plot)

were harvested in the morning (8 to 10) and made into

15 composite samples. The lettuce samples were packed

in sterile polyethylene bags and transported in an icebox

to the laboratory where they were stored at 4 °C until

faecal coliform and helminth eggs analysis. Analysis for

faecal coliform and helminth eggs started within few

hours after collection.

During sample collection period (November 2013 to

March 2014), the mean minimum monthly temperature

ranged from 4.1 to 8.8 °C. Whereas, the mean maximum

monthly temperature ranged from 25.1 to 29.1 °C (Na-

tional Meteorological Agency of Ethiopia). Taking into

account the time of sample collection, the sampling

temperature might be a bit higher than the mean mini-

mum monthly temperature but much lower than the

maximum monthly temperature.

Consumer survey on common green salads

washing methods

Based on the analysis and recommendations from Guchi

and Ashenafi (2010) to thoroughly wash vegetables eaten

raw in Addis Ababa and/or to dip them in food grade

antibacterial chemicals for a considerable time, a short

survey of 200 households was undertaken to understand

how green salads are commonly washed at home. This

short survey was carried out in 5 sub-city administrative

areas (Kolfe Keraniyo, Chirkos, Bole, Nefas Silk Lafto

and Akaki Kaliti). Questionnaire interview were adminis-

tered to gather information on daily intake pattern of se-

lected leafy vegetables including lettuce and common

washing methods used before serving salad. Based on

the results, 5 pattern of green salads washing methods

emerged although concentration of sanitizers and time

used varied considerably among households (Table 1).

There was no particular (official) guidance in this matter

known, and practices were based on belief or recom-

mendations from peers. Among the 5 green salads wash-

ing methods used by survey respondents, four, which

reflect common habits, were selected. Conventional

laundry detergents are derived from petrochemicals and

often contain synthetic fragrances. In general, this type

of chemical entities are insoluble in water, easily leaving

residue onto the vegetable under washing. Consequently,

any residue which may accumulate in human organs

cause harmful effect to health overtime (Iovdijova and

Bencko 2010). Therefore, the results of laundry deter-

gent washing were not reported in this paper. Although

commercial vegetable washing agents, chlorine based

agents, have been authorized for use with food in

Ethiopia (Codex Alimentarius Commission, 2010), they

36


Table 1 Green salads washing methods used in five sub-city administrative areas of Addis Ababa

Washing methods Sub-city Administrative Areas/ percentage of respondents

Kolfe Keraniyo (n = 39)

Chirkos (n =32)

Bole (n = 27)

Nefas Silk Lafto (n =45)

Akaki Kaliti (n = 57)

Total

(%)

Potable tap water 44 69 26 51 49 47

Salt solution 18 12 11 9 16 14

Vinegar solution 8 0 19 7 5 6

Detergent solution 28 19 37 31 30 31

Commercial vegetable sanitizer 2 0 7 2 0 2

are very rarely used for vegetable washing. Hence, they

were not included in the washing trial. Accordingly,

concentrations of sanitizers and contact time were

compared with previous studies in West Africa (Amoah

et al. 2007b), the vinegar based washing method was

portioned into 2: one with salt (NaCl) and the other

without. Overall, 5 washing methods were tested but 4

were presented in this paper, excluding detergent wash-

ing. Lettuce samples were collected from two urban

farming sites in Addis Ababa. The lettuce samples were

pooled, homogenized and transported in an icebox to

the laboratory where they were stored at 4 °C until faecal

coliform and helminth eggs analysis. Lettuce leaves

weighting 125 g each were selected for washing trial.

Lettuce samples used to determine the initial faecal coli-

form and helminth eggs levels were also originated from

the same pool. Then, 125 g of each lettuce sample was

subjected to the following washing methods in bowls

(immersion) and compared with the pre-treatment con-

dition. Analysis for faecal coliform and helminth eggs

started within few hours after collection and immedi-

ately after washing.

T0: Control (unwashed)

T1: Potable tap water washing and rinsing (2 min)

T2: Potable tap water washing - rinsing (2 min)

followed by dipping in 40 ppm salt solution (1 min);

T3: Potable tap water washing - rinsing (2 min) followed

by dipping in 15 000 ppm vinegar solution (1 min)

and

T4: Potable tap water washing - rinsing (2 min)

followed by dipping in a combined 40 ppm salt

and 15 000 ppm vinegar solution (1 min).

The lettuce leaves were cut into pieces using a sterile

knife and disposable gloves were used during handling.

Following washing, samples were removed with the aid

of a sterile stainless steel spatula and dried for 3-5 min.

For faecal coliform analysis, 25 g of each lettuce sample

were washed by shaking thoroughly with 225 ml of 0.1%

sterile peptone water. For helminth eggs analysis, a por-

tion of lettuce sample was weighted (100 g) and washed

with 0.1% Tween 80 solution and the washing water was

left overnight for sedimentation to take place. The con-

trol samples were simultaneously analyzed with the

treated samples. Investigation of faecal coliform and hel-

minth eggs reductions on lettuce using the various

washing methods were performed in 10 batches at three

days interval. The lettuce samples were taken for ana-

lysis at day 1, day 4, day 7, day 10, day 13, day 16, day

19, day 22, day 25 and day 28. Briefly, the first batch of

lettuce samples were collected at day 1 and the last

batch at day 28. Overall, each washing method was

tested (replicated) ten times.

Bacteriological and parasitological analysis

The most probable number (MPN) method was used to

determine faecal colifrom concentrations of irrigation

water and lettuce samples. Seven fold serial dilutions were

made. Presumptive and confirmatory tests were per-

formed using 5 tubes per dilution. In the presumptive test,

a set of 5 tubes of Lauryl Sulfate Tryptose broth (LST)

was inoculated with samples from each dilution and incu-

bated in at 35 °C for 48 h in a thermo-regulated water

bath. Briefly, 1 ml of serial dilutions in 9 ml of 0.1% sterile

peptone water of the homogenate was inoculated in tubes

containing LST and durham tube. After incubation at 35 °

C for 48 h, a loopful of suspension (1 ml) from positive

tubes of LST broth was transferred to Escherichia coli

broth (EC) tubes and incubated at 45 °C for 24-48 h in a

thermo-regulated water bath. Tubes exhibiting acid or gas

production were considered positive. The number and

distribution of positive tubes were used to obtain the

population of faecal coliform in water and lettuce samples

from MPN table.

A modification of Bailenger method (Ayres and Mara

1996) was used for enumeration of helminth eggs. Briefly,

each lettuce sample (100 g) was washed with 0.1% Tween

80 solution. The washing water was left overnight for sedi-

mentation to take place and 90% of the supernatant was

discarded and the remaining washing water and sediment

were centrifuged at 1500 g for 5 min. The supernatant

was discarded, the sediment was suspended in equal vol-

ume of acetoacetic buffer, followed by the addition of two

volumes of ether, thoroughly mixed using vortex mixer

and centrifuged at 1000 g for 15 min. The volume of the

37


pellet containing the eggs was recorded and the rest of the

supernatant was discarded in one smooth action. The pel-

let was resuspended in five volume of ZnSO4 solution,

thoroughly mixed using vortex mixer and exhaustively ex-

amined under light microscope. The same method was

used to quantify helminth eggs in irrigation water samples.

The bench-aid for the diagnosis of intestinal parasites

(WHO 1994) was used for identification purpose.

Statistical analysis

oil or salt/lemon/vegetable oil are commonly used for

dressing purpose.

Faecal coliform concentrations in irrigation water and

lettuce

The irrigation water from the 10 farming sites had mean

faecal coliform concentrations ranging from 4.29-5.61

log10 MPN 100 ml−1

(Table 2). Analysis of variance re-

vealed that irrigation water collected from Lekunda farm-

ing site had significantly higher mean faecal coliform level (5.61 log10 MPN 100 ml ) than irrigation water

Faecal coliform concentrations were normalized by log

transformation before analysis of variance. One-way analysis

of variance and Duncan’s multiple range tests were

employed to compare mean of log transformed faecal

coliform levels and helminth eggs concentrations found

from lettuce and irrigation water by farming sites. For

lettuce washing methods, Kruskal-Wallis H test was

applied, a nonparametric multiple comparison test using

SPSS package since the statistical assumptions of normality

were not met. A statistically significant difference was

assumed at the 5% level.

other farming sites (Peacock-Bole, Mekanissa, Lafto,

Hana-Mariam and Akaki 08) while irrigation water from

Hana-Mariam, the mean faecal coliform counts were the

lowest. No significant differences (P > 0.05) were observed

in mean faecal coliform concentrations of irrigation water

from the five farming sites (Sore Amba, Lekunda, Peacock-

Urael, Kera and Akaki). Irrespective of the farming sites, the

values did not meet the WHO (1989) guide line value of ≤

103/100 ml in case of unrestricted irrigation for crops that are

likely to be eaten uncooked.

Results

Green salads washing methods used by respondents

Based on the results of the short survey, 5 pattern of

green salads washing methods emerged although

concentration of sanitizers and washing time used

varied considerably among households (Table 1).

Forty- seven percent of the respondents responded

that they only use potable tap water to wash salads

and more than 30% indicated that they prepare

detergent solution for washing purpose. Various types

of detergents/soaps were indicated by this group of

household. Fourteen percent of respondents reported

that they wash green salads using salt solution, yet 6%

use vinegar solution. However, only 2% use commercial

vegetable sanitizer. Further sanitization of green salads

is likely as vinegar/vegetable oil or salt/vegetable

The mean faecal coliform concentrations in lettuce

ranged from 3.46-5.03 log10 MPN 100 g−1

(Table 2). The

highest mean faecal coliform was recorded in lettuce from

Lafto farming site, while the lowest level was found from

Peacock-Bole. With the exception of the two farming sites,

lettuce collected from all other farming sites were simi-

larly contaminated with faecal coliform. All mean faecal

coliform values recorded on lettuce exceeded recom-

mended threshold of ≤ 10 3/100 g fresh weight.

Helminth eggs levels in irrigation water and

lettuce

The mean helminth eggs and larvae detected in irrigation

water ranged from 0.9 to 3.1 eggs 1000 ml−1

(Table 3).

Eighty percent of the irrigation water samples were found

to be contaminated with one or more helminth eggs. Ana-

lysis of variance revealed that the mean helminth eggs con-

centration (3.1 eggs 1000 ml−1

) found in irrigation water of

Lekunda farming site was significantly higher than that of

Table 2 Mean faecal coliform contamination levels of irrigation water and irrigated lettuce from ten farming sites in Addis Ababa

Sample type Farming sites

Sore Amba Lekunda Peacock-Urael Peacock-Bole Kera Mekanissa Lafto Hana-Mariam Akaki 08 Akaki

Irrigation water (N = 9 for each farming site)

Range 3.23–6.73 4.51–6.96

Mean 5.06 (1.01)abc

5.61 (0.70)a

3.65–5.54

5.02 (0.64)abc

2.83–6.23

4.67 (1.04)bc

3.04–6.73

4.82 (1.02)abc

3.59–5.67

4.57 (0.54)bc

3.51–7.20

4.52 (1.18)bc

2.96–5.64

4.29(0.70)c

3.58–5.41

4.58 (0.66)bc

3.51–6.15

5.24 (0.75)ab

(log10 MPN 100 ml

−1)

Lettuce (N = 15 for each farming site)

Range 2-81-4.72 2.66-5.18 3.04-6.96 2.83-4.30 3.04-5.67 2.96-5.32 3.23-6.96 2.83-5.15 2.65-4.64 3.15-7.20

Mean 3.91 (0.73)bc

4.18 (0.74)bc

4.10 (1.00)bc

3.46 (0.44)c 4.05(0.80)

bc 3.93 (0.84)

bc 5.03 (1.38)

a 3.69 (0.58)

bc 3.50 (0.59)

c 4.19 (1.01)

bc

(log10 MPN 100 g

−1)

Figures in parentheses represent standard deviation

Values in the same row with different letters differ significantly (p < 0.05)

38


Table 3 Mean helminth eggs contamination levels of irrigation water and irrigated lettuce from ten farming sites in Addis Ababa

Sample Type Farming Sites

Sore Amba Lekunda Peacock-Urael Peacock-Bole Kera Mekanissa Lafto Hana-Mariam Akaki 08 Akaki

Irrigation water (N = 9 for each farming site)

Ascaris lumbricoides

Hookworm

14

3

21

3

19

2

16

1

20

3

7

1

17

1

12

2

18

2

16

3

Enterobius vermicularis 0 1 2 1 0 0 0 1 1 0

Trichuris trichiura 1 1 1 0 1 0 0 1 0 0

Taenia 0 0 0 0 2 0 1 0 0 0

Heymenolepis nana 1 1 2 0 0 0 0 0 0 0

Strongloyides 0 1 0 0 0 0 1 0 0 1

Total 19 28 26 18 26 8 20 16 22 20

Meanx 2.1(1.2)ab 3.1(2.1)a 2.9(1.8)a 2.0(1.7)ab 2.9(1.9)a 0.9(0.8)b 2.2(1.6)a

b

1.8(1.6)ab 2.4(2.2)a

b

2.2(1.7)a

b Lettuce (N = 15 for each farming site)

Ascaris lumbricoides 20 28 25 17 20 16 42 25 10 31

Hookworm 1 2 2 3 4 2 5 4 2 3

Enterobius vermicularis 0 1 1 1 0 0 3 0 0 2

Trichuris trichiura 0 1 0 0 1 1 3 2 0 1

Taenia 0 0 0 0 1 0 2 0 0 0

Strongloyides 0 0 1 0 0 0 1 0 0 0

Total 21 32 29 21 26 19 56 31 12 37

Meany 1.4(1.4)bc 2.1(2.3)b 1.9(1.5)bc 1.4(0.9)bc 1.7(1.7)b

c

1.3(1.3)bc 3.7(2.2)a 2.1(1.8)bc 0.8(1.0)c 2.5(2.2)b x

Mean concentrations of helminth eggs and larvae 1000 ml−1

yMean concentrations of helminth eggs and larvae 100 g

−1


Values in the same row with different letters differ significantly (p < 0.05)

Mekanissa but statistically similar (P > 0.05) with the mean

values of the other farming sites. The identified helminth

eggs and larvae consisted of Ascaris lumbricoides, Hook-

worm, Enterobius vermicularis, Trichuris trichiura, Taenia,

Heymenolepis nana and Strongloyides. A. lumbricoides was

the predominant helminth egg. The mean helminth eggs

concentration of irrigation water from all farming sites

exceeded the WHO (1989) guide value of < 1 egg 1000 ml −1 for unrestricted irrigation except Mekanissa.

In lettuce, 61% of the total samples were positive for

one or more helminth eggs. Site wise, the highest mean

helminth eggs concentration (3.7 helminth eggs 100 g−1

)

was detected from Lafto farming site, while the lowest

(0.8 helminth eggs 100 g−1

) was from Akaki 08 farming

site. Ascaris lumbricoides, Hookworm, Enterobius vermi-

cularis, Trichuris trichiura, Taenia and Strongloyides

were detected in lettuce samples. A. lumbricoides was

most prevalent followed by Hookworm.

Effects of washing methods

Irrespective of washing methods, faecal coliform levels

of lettuce were reduced by 0.8 to 1.7 log10 units (Table 4).

As compared to the control, all washing methods were

able to support significant reduction of faecal coliform.

The vinegar based washing methods induced significant

faecal coliform reduction compared with potable tap

water washing methods (with or without salt). Similarly,

the washing methods induced helminth eggs reduction

by 1–2 eggs (Table 4).

Discussion

This study shows that irrespective of the farming sites,

almost all irrigation water samples had a poor microbio-

logical quality. In the studied sites, there are a number

of factors that might potentially cause contamination of

irrigation water with relatively high levels of faecal coli-

form, in particular the inflow from untreated wastewater

into the Akaki river (Weldesilassie et al. 2011b). The

highest faecal coliform concentration was exhibited in ir-

rigation water from Lekunda farming site. At Lekunda,

the proximity of farm lands to resident and cattle houses

coupled with almost null proper sanitation service po-

tentially impose an effect on faecal coliform levels in the

irrigation water. Thus, grey and black waters originated

from households appear to be the key source of faecal

contamination. This is consistent with the studies by

Fischer et al. (Fisher et al. 2000), Monaghan et al. (2009),

Wittman et al. (2013) and Schreiber et al. (2015) who

39


Table 4 Effect of washing methods on the reduction of faecal coliform and helminth eggs levels of lettuce irrigated with polluted

water (n = 10 for each method)

Indicator organisms Washing methods

T0 T1 T2 T3 T4

Faecal coliform (log10 MPN 100 g−1) 4.23x (0.71)a 3.43 (0.77)b

3.35 (0.61)b 2.54 (0.51)c

2.58 (0.43)c

Helminth eggs (eggs 100 g−1) 2.2y (1.93) 0.8 (1.14) 0.6 (0.70) 1.0 (1.33) 0.6 (0.97)

Actual egg count (range) 0–6 0–3 0–2 0–4 0–3

(T0): Control (unwashed) (T1) Potable tap water washing and rinsing (2 min); (T2): Potable tap water washing - rinsing (2 min) followed by dipping in 40 ppm salt solution (1

min); (T3): Potable tap water washing - rinsing (2 min) followed by dipping in 15 000 ppm vinegar solution (1 min); and (T4): Potable tap water washing - rinsing (2 min)

followed by dipping in a combined 40 ppm salt and 15 000 ppm vinegar solution (1 min) xActual mean faecal coliform level yActual mean egg count

Figures in parenthesis represent standard deviation

Values in the same row with different letters differ significantly (P < 0.05); range of detected helminth eggs too narrow for normal distribution, homogeneity, and

statistically significant differences

demonstrated the considerable impact of anthropogenic

inputs on microbial quality of river water.

As reflected by water quality, also the lettuce samples

from all farming sites had high faecal coliform levels ex-

ceeding recommended thresholds, similar to the findings in

other sub-Saharan cities (Keraita et al. 2002; Srikanth and

Naik 2004; Amoah et al. 2005, 2007a). Compared with

studies in Ghana (Amoah et al. 2005, 2007a), the faecal

coliform levels are lower in the case of Addis Ababa. The

reason can be several: a) the Akaki river offers more dilu-

tion than the smaller streams e.g. in Kumasi, b) furrow and

flood irrigation reduce leaf contact (Ghana: overhead irriga-

tion with watering cans), and c) irrigation frequency in

Addis (1-2 times per week) is much lower than in hot

Ghana where lettuce is irrigated twice a day which also al-

lows more natural die-off (Keraita et al. 2002; Amoah et al.

2011). Unfortunately, on some farming sites vegetables in-

cluding lettuce are washed by farmers and traders with the

water used for irrigation to remove soil residues and keep it

fresh until selling. As lettuce is not undergoing heat treat-

ment in kitchens salad eating consumers will be potentially

at risk. A similar practice was also reported from Ghana

(Amoah et al. 2011) and has to be controlled as part of

other potential post-harvest contamination risks.

The helminth eggs and larvae detected in irrigation

water and lettuce comprised of Ascaris lumbricoides,

Hookworm, Enterobius vermicularis, Trichuris trichiura,

Taenia and Strongloyides. This corresponds with similar

studies in West Africa (Drechsel and Keraita 2014). A

slightly higher helminth eggs percentage prevalence

(64%) in lettuce grown in 4 wastewater irrigated farming

sites of Addis Ababa was reported by Habtu (2011). In

neighboring Kenya, high prevalence of helminth eggs in

vegetable was reported Nyarango et al. (2008). Several

factors may contribute to difference in percentage preva-

lence of helminth eggs in vegetable including the quality

of irrigation water used, irrigation methods, post harvest

handling and methods of quantification (Kozan et al.

2005; Ezatpour et al. 2013; Gil et al. 2015).

This work does not address farmer exposure to waste-

water for which universal risk mitigation measures are

well known (WHO 2006), but focuses on potential mi-

crobial risks for consumers and washing methods for

bacterial and helminth eggs reductions. Our study re-

vealed that all the tested washing methods reported here

could somehow significantly reduce faecal coliform

levels but only the vinegar based washing support 1.6 to

1.7 log10 units reduction. This is less still than the 2-3

log10 units reduction (Amoah et al. 2007b) which are

possible by further optimizing the concentration and ex-

posure time. In this study, there were two vinegar based

washing methods (one with little salt and the other with-

out) and no significant faecal coliform reduction effect

was detected between them. There appears to be no

benefit from the practice of using little salt which will be

an important message to households.

According to Amoah et al. (2007b), longer contact

time and high concentration of sanitizers did promote

significant reduction of faecal coliform population.

However, they questioned the practicality of increas-

ing contact time and concentrations beyond some

levels in light of extra processing time, cost and qual-

ity (in terms of appearance and texture) of ready to

eat lettuce. Yet, boosting the concentration of salt

used in our study to reasonable level may not seem

to affect cost and quality. Alternatively, chlorine based

commercial vegetable and fruit sanitizers, are consid-

ered to be very effective to reduce/kill microbial path-

ogens. Where these are not easily available, often

imported and expensive, also household bleach (so-

dium hypochlorite) can be effective in sanitizing food,

as it is very common in Francophone Africa (Amoah

et al. 2007b). In Ethiopia, common bleach is however

sold without supplier recommendations for use in

food, which increases the risk of misuse. Locally pro-

duced vegetable sanitizer (for example, ‘G.Melaten’)

which is based on bleach should therefore get broader

promotion to raise potential risk awareness while

40


offering an option for potential risk mitigation. A

comparative cost analysis showed that with one

1000 ml bottle of ‘G.Melaten’ (0.7 USD) a household

can wash about 70 to 150 salad dishes depending on

the optimization of concentration versus a practically

(short) contact time, which is 7 to 40 as much as

with other (mostly imported) products on the market

(Woldetsadik, unpublished). Other factors (type and

physiology of the target organisms and characteristics

of produce surfaces) could also influence the efficacy

of the method used to reduce microbial population

(Materon 2003; Parish et al. 2003; Amoah et al.

2007b). Moreover, type of washing (running versus

immersion) influences the level of pathogen indicator

organisms on fresh produce and therefore influence

the final potential risk values. For instance, rinsing

under running tap water is considered more effective

than immersion, resulting in up to 2.2 log10 coli re-

ductions (Pangloli et al. 2009). In case of helminth

eggs, all treatments induced comparable reductions

effect, which is mostly based on the physical force of

washing and rinsing, not a chemical impact (Amoah

et al. 2007b; Fallah et al. 2012).

Conclusion

This study indicated that faecal contamination level of

lettuce irrigated with contaminated irrigation water is

above the threshold of safe consumption, but in a range

which can be addressed through relatively simple and

low-cost mitigation measures. The WHO is promoting a

multi-barrier approach and one of these barriers can be

washing of green salads at home. Post-harvest treatment

is important to address post-harvest contamination

which can start already on farm when harvested crops

are locally washed. The case of Addis Ababa showed in

general lower contamination levels than known from

West Africa, because of wastewater dilution, different ir-

rigation water application methods and frequency. Aside

preventing occupational exposure, potential risk reduc-

tion programs should target households which have so

far no guidance on how best to wash vegetables. In fact,

majority of the survey participants only use tap water

and detergent washing methods in spite of their limited

microbiological benefits and potential health concerns

associated with chemicals in commercial laundry deter-

gents. The result of the present study suggest that the

vinegar based washing treatments are able to reduce fae-

cal coliform towards low level while the physical wash-

ing with running water may help to substantially

decrease potential risk of helminth parasitic infections.

The 15,000 ppm vinegar solution is in simple terms ap-

proximately mixing one part vinegar with four parts

water. It should be noted however that such a ratio will

be expensive over time, while vinegar may change the

taste or texture of the lettuce leaves. In conclusion, the

2006 WHO guidelines for safe wastewater irrigation put

significant emphasis on mitigation of potential risks

along the farm to fork pathway, i.e. beyond strict but un-

achievable irrigation water quality thresholds which sup-

ports very well the needs as well as opportunities as

observed in Addis Ababa.

Acknowledgements

This work was supported by the International Water Management Institute

(IWMI-CGIAR) under the water, Land and Ecosystems Research Program, and

the Ministry of Education of Ethiopia. We are grateful to Philip Amoah and

Felix Grau for their valuable comments on the manuscript and the staff of

Soil Microbiology Laboratory at National Soil Testing Center, Addis Ababa,

Ethiopia for the laboratory assistance. We also wish to acknowledge the field

work support of development agents at various sub-city administrative areas

of Addis Ababa.

Authors’ contributions

DW, PD, BK, FI and BE conceived and designed the study. DW conducted the

study. DW, PD, BK, FI and BE contributed to the analysis and interpretation of

data. DW drafted the manuscript. DW, PD, BK, FI, BE and HG revised the draft

manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Author details

1School of Natural Resources Management and Environmental Sciences,

Haramaya University, 138 Dire Dawa, Ethiopia. 2International Water

Management Institute, Colombo, Sri Lanka. 3UNICEF, Eastern and Southern

Africa Regional Office, Nairobi, Kenya. 4Department of Crop Science,

University of Namibia, Windhoek, Namibia. 5Aklilu Lemma Institute of

Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia.

Received: 19 July 2016 Accepted: 12 January 2017

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http://www.unep.org/Documents.Multilingual/Default.Print.asp?DocumentID=664&ArticleID=8666&l=en



Woldetsadik et al. International Journal of Food Contamination (2017) 4:9

DOI 10.1186/s40550-017-0053-y International Journal

of Food Contamination

D A T A A R T I C L E Open Access

Heavy metal accumulation and health risk assessment in wastewater-irrigated urban vegetable farming sites of Addis Ababa, Ethiopia

Desta Woldetsadik 1*

, Pay Drechsel2

, Bernard Keraita3

, Fisseha Itanna4 and Heluf Gebrekidan

1

Abstract

Background: Consumption of food crops contaminated with heavy metals is a major food chain route for human

exposure. Wastewater irrigation for vegetable production is a highly prevalent practice in Addis Ababa and a number of

articles have been published on wastewater-irrigated soils and vegetables contaminated with heavy metals. However, to

the best of our knowledge, an insight into assessment of human health risks associated with the consumption of

vegetable crops grown on wastewater-irrigated soils is non-existent in the city. Long-term effect of wastewater irrigation

on the build-up of heavy metals in soils and selected vegetable crops in Addis Ababa urban vegetable farming sites (10)

was evaluated. By calculating estimated daily intakes (EDIs) and target hazard quotients (THQs) of metals, health risk

associated with the consumption of the analyzed vegetables was also evaluated.

Results: The heavy metal concentrations in irrigation water and soils did not exceed the maximum permissible limits

(MPLs). Moreover, Cd, Co, Cr, Cu, Ni and Zn concentrations in all analyzed vegetables were lower than the MPL standards.

In contrast, Pb concentrations were 1.4–3.9 times higher. Results of two way ANOVA test showed that variation in metals

concentrations were significant (p < 0.001) across farming site, vegetable type and site x vegetable interaction. The EDI

and THQ values showed that there would be no potential health risk to local inhabitants due to intake of individual metal

if one or more of the analyzed vegetables are consumed. Furthermore, total target hazard quotients (TTHQs) for the

combined metals due to all analyzed vegetables were lower than 1.

Conclusions: There is a great respite that toxic metals like Pb and Cd would not pose short term potential health risk

to local inhabitants if one or more of the analyzed vegetables are consumed. However, intermittent monitoring

of the metals from irrigation water, in soil and crops may be required to follow/prevent their build-up in the food chain.

Keywords: Vegetable farming, Wastewater irrigation, Heavy metal, Health risk, Target hazard quotient, Addis Ababa

Background

Wastewater (untreated, partially treated or diluted) has

been widely used for agriculture in most urban and

peri-urban cities of developing countries (Scott et al.

2004). Market proximity, high opportunities for income

generation, reliable and free irrigation water supply, and

minimum artificial fertilizer requirement are the often

cited benefits of irrigation within cities (Drechsel et al.

2006; Qadir et al. 2010). However, long-term application

of partially treated or untreated wastewater could result

in accumulation of heavy metals in the soil (Elgallal et al.

2016). Effluents from household and industries,

drainage water, atmospheric deposition, and traffic-

related emissions transported with storm water into

the sewage and/or irrigation system carry number of

pollutants and enrich the urban waste water with

heavy metals (Saha et al. 2015; Zia et al. 2016)

The consumption of food crops grown in waterwater- irrigated areas is one of the principal factor contributing human exposure to pathogens.* Correspondence: [email protected] 1School of Natural Resources Management and Environmental Sciences,

Haramaya University, PO Box: 138, Dire Dawa, Ethiopia

Full list of author information is available at the end of the article

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0

International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to

the Creative Commons license, and indicate if changes were made.

43




In addition, the cultivation of crops for human

consumption on wastewater-irrigated soil can potentially

lead to the uptake and accumulation of trace metals in the

edible plant parts resulting potential risk to human

(Rattan et al. 2005; Xue et al. 2012; Ahmad et al. 2016; Zia

et al. 2016). Heavy metals are very harmful because of

their non-biodggrdable nature, long half-lives and their

high bioaccumulation potential (Duruibe et al. 2007; Shah

et al. 2012). Several researchers reported that serious

health problems may develop as a result of excessive

accumulation of heavy metals and even essential trace

elements such as Cu and Zn in human body (Oliver 1997;

Jarup 2003; Kabata-Pendias and Mukherjee 2007; Luo

et al. 2011; Khan et al. 2015).

The increase of ‘wastewater irrigation’ is however in

most cases not farmers’ choice (Raschid-Sally and Jayak-

ody 2008). In Africa, the number of people without access

to adequate water and sanitation facilities has risen swiftly

in recent decades as the continent’s rapid urbanization

outpaced its capacity to provide the essential water and

sanitation services. In Addis Ababa, large volumes of un-

treated water are released to water bodies which farmers

use for irrigation (Weldesilassie et al. 2011a, 2011b).

According to Nuttal (2011), not only liquid waste

provides a challenge, but also solid waste dumped along

Addis Ababa main river, near bridges and shores of

small tributaries where it is washed into the river.

Despite all potential risks, irrigated farming of high value

crops is livelihood to many urban residents since it

provides employment and income (Weldesilassie et al.

2009). About, 60% of the city’s vegetable consumption,

particularly leafy vegetables, is supplied by urban farmers

who irrigate their crops using polluted river water (Nuttal

2011).

Wastewater irrigation for vegetable production is a

highly prevalent practice in the city and a number of

articles have been published on wastewater-irrigated

soils and vegetables contaminated with heavy metals

starting from the 90′s (Itanna 1998, 2002; Alemayehu

2006; Weldegebriel et al. 2012; Aschale et al. 2015;

Mekonnen et al. 2015). However, to the best of our

knowledge, an insight into assessment of human health

risks associated with the consumption of vegetable crops

grown on wastewater-irrigated soils is non-existent. It

has, for instance, been concluded from the data of heavy

metal concentrations in vegetable crops on human

health risk without analyzing the pattern for dietary

intakes of these metals (Weldegebriel et al. 2012;

Aschale et al. 2015). However, information about dietary

intake of metals is equally important for assessing their

potential risk to human health. Within this context our

study tried to quantify the concentrations of heavy

metals in irrigation water, soils and selected vegetables

on a representative range of Addis Ababa’s urban

vegetable farming sites and estimate daily intake and

target hazard quotient (THQ) of heavy metals through

consumption of these vegetables.

Methods

Study area

This study was conducted in Addis Ababa, Ethiopia,

where urban farmers have been practicing vegetable

production at various urban farming sites along the Akaki

River (‘Tinishu’ and ‘Teleku’ Akaki Rivers). The practice

has been started in late 1940s. There are two form vege-

table production: producers’ cooperatives and individual

bases. Currently, more than 800 ha of land are irrigated

for vegetable production using water from the Akaki River

(Weldesilassie and Nigussie 2011). The areas covered are

ten prominent vegetable farming sites, locally known as

Sore Amba, Lekunda, Peacock-Urael, Peacock-Bole, Kera,

Mekanissa, Lafto, Hana-Mariam, Akaki 08, Akaki (Fig. 1)

located at five sub-city administrative areas: Kolfe

Keraniyo, Chirkos, Bole, Nefas Silk Lafto and Akaki Kaliti,

which lies in 038° 41′ E to 038° 47′ E and 08° 52′ N to 9°

02′ N (Woldetsadik et al. 2017). The streams in consider-

ation are highlighted with blue color.

With the exception of Akaki 08 and Akaki farming

sites, at all other sites the manual construction of trad-

itional weirs using sand bags and coarse stones is the

most common method to block the water flow till it can

enter a system of irrigation channels which follow

gravity to support farms further downstream. In these

farming sites, vegetable crops, mainly leafy vegetable

such as lettuce, Ethiopian Kale and swiss chard, are

grown using furrow irrigation method, by manually

opening and closing furrows constructed within the

farms. In addition to furrow irrigation technique, flood

irrigation, by which fields are flooded in a controlled

manner by manually opening and closing of a bund, is

also used at Sore Amba, Lekunda, Peacock- Urael, and

Peacock-Bole farming sites. At Akaki 08 and Akaki

farming sites, the vast majorities of farmers use diesel

motor pumps to extract water directly from the river

and transport to farm using connected plastic pipes.

Some farmers at Lafto farming sites also follow similar

water extraction methods (Woldetsadik et al. 2017). Let-

tuce, swiss chard and Ethiopian kale were selected for

this study since they are the major vegetable crops

grown in the study sites.

Sample collection and preparation

At all farming sites, irrigation water was collected at a

point where farmers fetch/collect, or where it enters the

44


Fig. 1 Map of the sampling sites

farm via canals. From each site, quadruplicate composite

samples from 4 different fetching points/inlets to farm

were collected in 500 ml plastic bottles, pre-treated with

5 ml of concentrated HNO3 to prevent microbial degrad-

ation of heavy metals, and transported in an icebox to

laboratory where they were stored at 4 °C until analysis.

So a total of 40 irrigation water samples were collected.

At each farming site, 4 different farmers vegetable farms

were selected based on the type of vegetables they grow.

From each vegetable farm, 15 surface subsamples

(0–20 cm) (3 plots per farm * 5 subsamples from each

plot) were collected and made into a single composite

sample. So a total of 4 composite soil samples were made

per farming site and packed into polyethylene bags and

then transported to the laboratory for preparation. The

samples were air-dried, passed through a 2 mm sieve and

then put into zipped lock polyethylene bags and stored at

ambient temperature before further analysis.

Standing vegetable samples (Lactuca sativa var. crispa,

Brassica carinata A. Br. and Beta Vulgaris var. cicla)

were also collected from the same vegetable farms where

soils were collected. The same sampling technique was

followed except only 6 subsamples (for each vegetable

type) were used to prepare the composite samples in

case of vegetables. A total 120 composite samples (10

farming sites * 3 vegetables * 4 composite samples) were

collected, packed into polyethylene bags and transported

to the laboratory. Vegetable samples were properly

washed with deionized water to remove all visible soil

particles. After removing the extra water from the

surface of vegetables, the samples were then cut into

pieces with a knife. All the samples were then oven--

dried at 80 °C for 48 hours. Dried samples were pow-

dered using a pestle and mortar.

Analyses

Fifty ml of water sample was digested with HNO3

(10 ml) (APHA 2005). After cooling, the digested sample

was filtered and the digest was maintained to 50 ml with

distilled water. The digest was analyzed for heavy metals

with Graphite Furnace Atomic Absorption Spectropho-

tometer (GFAAS, Thermo Scientific, USA).

Soil particle size distribution was determined by

hydrometer method (Gee and Bauder 1986). Soil pH

(McLean 1982) was determined from a suspension of 1:

2.5 of soil: water ratio. The cation exchange capacity was

determined by leaching method with ammonium acetate

solution (1 M NH4OAc). The organic carbon was deter-

mined by dichromate oxidation method and subsequent

titration with ferrous ammonium sulphate (Walkley and

Black 1934). Soil organic matter (OM) was calculated by

multiplying soil organic carbon by 1.724 assuming that

average C concentration of organic matter is 58%. For

heavy metal analysis of soil, 0.25 g of samples were

placed into 50 ml vessels, followed by addition of 10 ml

concentrated HNO3. The mixtures were left to cold

digest in a fume cupboard over night and then heated in

1.6 KW microwave oven for 30 min. After cooling to

room temperature, 10 ml of double distilled water was

added into the vessel and filtered via a 0.45 μm cellulose

45


nitrate filter paper. Finally, the filtrate was subjected to the

total element analysis using ICP-OES (Ciros CCD, SPEC-

TRO Analytical Instruments GmbH, Kleve, Germany).

Nitric acid and H2O2 has been used to digest the vege-

table samples, 1 g of ground vegetable sample was

digested with 5 ml of nitric acid and 3 ml of hydrogen

peroxide. The extract was filtered, insolubles were

removed and finally the volume was made up to 50 ml

with distilled water. The concentration of heavy metals

in the filtrate was determined using Graphite Furnace

Atomic Absorption Spectrophotometer (GFAAS, Thermo

Scientific, USA).

Data analysis

Estimated daily intake (EDI) of heavy metals

The estimated daily intake (EDI) of heavy metals was de-

termined based on both the metal levels in crops and

the amount of consumption of the respective food crop.

The EDI of metals was evaluated according to the aver-

age concentrations of each metal in each food crops and

the respective daily consumption rate (Zhuang et al.

2009). The EDI of the metals for adults was determined

by the following equation:

EDI = Cmetal x Wfood /Bw

Where Cmetal is the concentration of heavy metals in

vegetable crops; Wfood represents the daily average con-

sumption of crops in the 5 sub-city administrative areas

and Bw is the body weight. A short survey was under-

taken to assess vegetable intake patterns of adults and

understand how green salads are commonly washed at

home. This short survey was carried out in 5 sub-city

administrative areas (Kolfe Keraniyo, Chirkos, Bole,

Nefas Silk Lafto and Akaki Kaliti). Questionnaire inter-

view were administered to gather information on daily

intake pattern of selected leafy vegetables and common

washing methods used before serving salad (Woldetsadik

et al. 2017). A total of 200 adults were involved in the

survey. The minimum and maximum age and body

weight record in the questionnaire survey for adults

were 18–73 years and 42–84 kg, respectively. Based on

the results, the average daily vegetables intakes for adults

ranged from 11.9 to 16.3, 27.4 to 36.7 and 22.3 to

37.2 g day−1 for Lactuca sativa var. crispa, Brassica

carinata A. Br.and Beta Vulgaris var. cicla, respectively.

The conversion factor to convert fresh green vegetable

weights to dry weights was 0.085 (Zhuang et al. 2009).

The metal intakes were compared with the tolerable

daily intakes of metals recommended by WHO (1993).

Target hazard quotient

The health risks to local inhabitants associated with the

intake of Cd, Cu, Ni, Co, Pb, Zn and Cr through the

consumptions of wastewater-irrigated vegetables (Lactuca

sativa var. crispa, Brassica carinata A. Br. and Beta

Vulgaris var. cicla) were based on Target Hazard Quo-

tients (THQs). The THQ is a ratio of determined dose of

a pollutant to a reference dose level. If the ratio is less than

1, the exposed population is unlikely to experience

obvious adverse effects. Non-carcinogenic health risks for

humans associated with the consumption of these vegeta-

bles were assessed by calculating THQ. The method to

estimate THQ was provided in USEPA Region III Risk--

Based Concentration Table (USEPA. Integrated Risk Infor-

mation System-database. Philadelphia PA, Washington

2007) and in Chien et al. (2002) and Zhuang et al. (2009):

THQ = Cn x I x10‐3 x Efr x ED/RfD x Bw x AT

where Cn represents the mean metal concentration in a specific vegetable on fresh weight basis (mg kg−1); I is in-

gestion rate (g person−1

d−1

); EFr is exposure frequency

(365 days year−1

); ED is exposure duration (70 years); RfD

is the oral reference dose (mg kg−1

d−1

); BW is the average

body mass, adult (65 kg); AT is averaging time for noncar-

cinogens (365 days year−1

× number of exposure years).


Data of heavy metal concentrations in vegetables were

checked for homogeneity of variance and normality. The

data of heavy metal concentrations in all analyzed vegeta-

bles across the various farming sites were subjected to two-

way analysis of variance (ANOVA) to assess the significance

of differences in heavy metal concentrations by site,

vegetable type and their interaction. Pearson correlation

analyses were also carried out to assess the relationships of

soil and vegetable metal concentrations. All statistical

analyses were computed with SPSS software version 16.

Results and discussion

Heavy metals in irrigation water

Mean concentrations of selected heavy metals in irriga-

tion water samples collected from various urban farming

sites of Addis Ababa are given in Table 1. Across the ten

sampling sites, the metals concentrations were far below

the maximum permissible limit for irrigation water set

by FAO (Ayers and Westcot 1985). The mean

concentrations of Cd, Co, Cr, Cu, Ni, Pb and Zn were

3.54–58.8, 2.11–13.6, 2.26–6.74, 2.78–29.3, 3.71–33.5, 105–938 and 17.8–48.8 times below the permissible

limit. As compared to the concentrations reported in

the present study, Aschale et al. (2015)) reported

lower mean ranges of Cd (0.04–0.06 μg L−1

), Co (2.1–2.7 μg L−1), Cu (3.3–6.6), Ni (3.9–6.5 μg L−1), Pb (1.4–5.1 μg L−1) and Zn (10.9–22.5 μg L−1) but higher mean range of Cr (2.4–255 μg L

−1) in irrigation water

samples of the same vegetable farming sites. Similarly,

46


Table 1 Mean heavy metal concentration of irrigation water of Addis Ababa vegetable farming sites

Site Total concentration (μg L−1)

Cd Co Cr Cu Ni Pb Zn

Sora Amba 0.43(0.05) 3.68(0.72) 17.7(2.27) 6.83(1.08) 11.5(2.08) 5.33(0.96) 40.9(6.35)

Lekunda 0.80(0.07) 14.6(1.55) 29.3(3.41) 38.6(3.62) 16.2(2.25) 21.8(2.28) 58.5(5.09)

Peacock-Urael 0.37(0.06) 7.28(0.92) 8.53(1.08) 30.7(3.42) 24.4(2.56) 6.82(0.58) 49.7(4.79)

Peacock-Bole 0.17(0.05) 5.48(0.94) 3.09(0.51) 8.04(1.31) 5.97(0.86) 13.8(3.06) 54.0(5.78)

Kera 2.82(0.62) 16.3(2.37) 44.2(6.38) 71.5(6.73) 29.6(3.55) 47.7(4.98) 88.4(12.9)

Mekanissa 0.81(0.05) 8.73(1.35) 19.8(2.75) 27.7(3.39) 53.9(5.50) 9.48(1.93) 112(16.4)

Lafto 1.48(0.26) 21.6(3.64) 14.2(1.15) 78.3(8.32) 36.5(3.68) 36.9(2.75) 56.9(5.12)

Hana-Mariam 1.05(0.25) 23.7(3.00) 35.1(4.92) 17.7(2.73) 9.48(1.90) 19.4(2.02) 69.6(2.45)

Akaki08 0.57(0.04) 3.38(0.64) 24.4(3.09) 49.2(6.22) 16.2(2.67) 18.6(2.32) 62.8(6.13)

Akaki 0.33(0.04) 5.57(0.47) 14.8(2.69) 36.1(4.10) 8.44(1.76) 16.8(2.00) 44.8(4.03)

MPL (μg L−1) 10 50 100 200 200 5000 2000


MPL Maximum Permissible Limit for irrigation water by FAO (Ayers and Westcot 1985)

Alemayehu (2006) reported lower levels of Cd, Co, Cr, Cu,

Ni and Zn in Akaki river/irrigation water. As a conse-

quence of very few localized industrial activities and the

dilution of wastewater with stream water, low levels of

metals in irrigation water samples were recorded. Further-

more, wastewater discharged into the river and irrigation

canals are more of domestic origins. Related study in

Accra has shown similar phenomena. Unlike the usual

trends of observing low levels of metals in irrigation water

of Addis Ababa’s urban vegetable farming sites (Itanna

1998; Alemayehu 2006; Aschale et al. 2015), Weldegebriel

et al. (2012) have reported Cd, Co, Cu, Ni and Zn concen-

trations as high as 33 μg L−1

, 626 μg L−1

, 370 μg L−1

,

216 μg L−1

and 618 μg L−1

, respectively. Despite the low

levels of metals in diluted wastewater, continuous use of

this water for irrigation could contribute the accumulation

of metals into the soil.

Heavy metals in soils

The physico-chemical parameters determined for waste-

water irrigated soils in urban vegetable farming sites of

Addis Ababa are listed in Table 2. Across the vegetable

farming sites, the mean values of soil pH varied from

5.99 to 7.16. The mean organic matter content was high-

est at Sore Amba (4.6%) followed by Lekunda (4.1%),

Mekanissa (3.8%) and lowest in soils from Akaki (2.6%).

The CEC value was highest in soils of Akaki 08 s i t e .

As compared to other vegetable farming sites, the lowest

CEC value (34.9) was exhibited from soils of Peacock-

Urael. The CEC results concurred the findings of

Weldegebriel et al. (2012). The mean clay content

ranged between 34.8 and 60.2%, with the highest and

lowest at Sore Amba and Peacock-Urael sites, respectively.

The mean Cd, Co, Cr, Cu, Ni, Pb and Zn concentrations

in soils from the sampling areas ranged 0.95–3.61, 28.6–

58.6, 55.9–140, 24.2–51.6, 31.5–61.7, 22.1–107 and 119–

203 mg kg−1

, respectively. With the exception of

Mean Cr(140 mg kg−1

) at Lekunda, Ni(61.7 mg kg−1

) at

Kera, Cd (3.61 mg kg−1

), and Pb (107 mg kg−1

) at Lafto,

the mean concentrations of the metals in soils of the

studied sites were below the threshold levels for agricultural

soils. For sewage-irrigated site (Lafto), greater levels of

metals were observed than those sites having no specific

application of sewage. But even the upper limits of the

metal concentrations (Co, Cr, Cu and Ni) were below

the maximum threshold levels. The mean levels of Cd,

Co, Cu, Ni, Pb and Zn recorded during the present

study were comparable or slightly higher than those

reported in previous studies (Itanna 1998, 2002; Weldegebriel

et al. 2012; Aschale et al. 2015). In the studied sites, the soils

had been irrigated by wastewater for more than 60 years,

which showed higher or comparable levels of metals com-

pared to wastewater-irrigated agricultural soils in other

African (Mapanda et al. 2005; Lente et al. 2012) and Asian

cities (Ahmad et al. 2016; Xue et al. 2012). Conversely, others

reported high levels of heavy metals in soils under waste-

water cropping system, e.g. in Kolkata city, India (Saha et

al. 2015) and Beijing city, China (Liu et al. 2005). High

metal levels were also obtained in soils irrigated with

wastewater in Harare, Zimbabwe (Muchuweti et al. 2006).

However, periodic monitoring of mobile fractions of

metals, together with physico-chemical properties of soils

and agricultural practices, is required to prevent excessive

uptake by vegetable crops.

Heavy metals in vegetables

Concentrations of heavy metals in edible parts of the an-

alyzed vegetables are summarized in Table 3. Mean Cd

concentrations were highest in vegetables harvested

from Kera and Lafto farming sites, with levels ranging

47

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Table 2 Physicochemical characteristics of soils irrigated with wastewater in urban vegetable farming sites

Total concentration (mg kg−1) pH (H2O) OM(%) CEC(cmol(+)kg−1) Particle size

Site Cd Co Cr Cu Ni Pb Zn Sand Silt Clay

Sora Amba 0.95(0.17) 28.6(2.14) 94.0(14.5) 24.2(1.57) 31.5(2.62) 22.1(1.87) 119(14.2) 6.51 4.6 42.9 11.8 28 60.2

Lekunda 2.72(0.20) 43.7(2.37) 140(10.3) 30.7(4.91) 60.3(4.10) 36.7(4.40) 150(12.1) 6.59 4.14 39.7 17.2 34.3 48.5

Peacock-Urael 2.58(0.21) 38.8(2.43) 67.4(3.42) 27.4(2.89) 46.2(2.50) 27.8(2.87) 157(6.41) 6.8 3.3 34.9 15 50.2 34.8

Peacock-Bole 1.55(0.10) 37.1(1.83) 55.9(6.52) 28.5(2.35) 46.0(3.99) 25.8(3.60) 120(9.69) 7.16 2.92 39.6 23.8 27 49.2

Kera 2.95(0.42) 58.6(3.74) 76.3(6.74) 49.9(6.20) 61.7(9.15) 81.1(10.9) 160(8.35) 6.11 3.22 43.9 16.7 43.3 40

Mekanissa 2.27(0.31) 38.6(3.58) 61.6(7.32) 43.3(4.41) 48.7(4.75) 29.6(3.59) 145(26.4) 6.57 3.79 39.5 25 31.2 43.8

Lafto 3.61(0.38) 44.9(3.15) 78.0(10.4) 51.6(8.26) 49.1(6.21) 107(10.7) 203(19.5) 5.99 3.62 44.7 16.8 42.5 40.7

Hana-Mariam 1.37(0.20) 28.8(3.27) 56.3(2.52) 38.3(4.92) 39.9(4.85) 33.1(1.88) 130(16.6) 6.63 3.06 40.3 23.2 25 51.8

Akaki08 1.99(0.24) 40.5(3.75) 66.2(5.26) 32.3(4.53) 43.8(5.97) 42.1(1.67) 156(10.2) 7.1 2.88 54.5 15.5 27.3 57.2

Akaki 1.19(0.27) 43.4(2.38) 69.1(8.51) 27.9(1.59) 46.6(3.27) 35.9(5.22) 154(28.1) 6.93 2.6 49.1 17.7 28.5 53.8

MPL a(mg kg−1) 3 50 100 100 50 100 300

Figures in parentheses represent standard deviation aSource: Ewers 1991

MPL Maximum Permissible Limit

48


Table 3 Metal concentrations in vegetables grown in wastewater-irrigated urban farming sites

Site Vegetable Mean concentration (mg kg−1)

Cd Co Cr Cu Ni Pb Zn

Sora Amba Lactuca sativa var. crispa 0.54(0.06) 0.42(0.08) 5.28(0.50) 23.9(0.69) 3.49(0.40) 10.5(0.88) 57.7(8.91)

Brassica carinata A. Br. 0.34(0.03) 0.32(0.03) 4.47(0.71) 12.0(1.26) 3.13(0.50) 7.16(1.03) 80.2(16.6)

Beta Vulgaris var. cicla 0.39(0.05) 0.54(0.08) 2.85(0.33) 17.0(1.16) 5.94(0.36) 8.63(0.74) 84.8(9.21)

Lekunda Lactuca sativa var. crispa 0.73(0.11) 0.70(0.07) 6.29(0.63) 34.3(1.54) 5.44(0.59) 10.7(0.82) 87.1(10.7)


Beta Vulgaris var. cicla 0.62(0.08) 0.91(0.06) 3.81(0.30) 38.9(1.42) 4.92(0.37) 12.6(1.50) 105(8.26)

Peacock-Urael Lactuca sativa var. crispa 0.56(0.11) 0.48(0.12) 2.38(0.18) 13.7(1.02) 3.28(0.46) 8.88(0.95) 63.4(5.22)



Peacock-Bole Lactuca sativa var. crispa 0.40(0.10) 0.53(0.07) 3.08(0.10) 23.2(1.03) 5.21(0.55) 12.9(0.61) 56.9(3.90)



Kera Lactuca sativa var. crispa 1.59(0.13) 0.81(0.06) 8.01(0.60) 36.2(1.67) 2.78(0.31) 12.7(0.87) 94.4(11.6)

Brassica carinata A. Br. 0.87(0.12) 0.78(0.07) 4.06(0.68) 21.5(1.54) 2.34(0.42) 8.57(0.63) 105(9.80)


Mekanissa Lactuca sativa var. crispa 0.78(0.08) 1.45(0.08) 5.07(0.67) 31.0(8.32) 7.86(0.58) 9.22(1.57) 67.7(4.93)



Lafto Lactuca sativa var. crispa 1.79(0.12) 1.30(0.15) 6.95(0.32) 35.0(1.30) 4.30(0.56) 8.46(1.47) 82.5(10.9)

Brassica carinata A. Br. 1.17(0.06) 0.71(0.10) 6.57(0.42) 27.8(2.58) 5.19(0.71) 9.50(1.57) 109(11.9)


Hana-Mariam Lactuca sativa var. crispa 0.49(0.15) 0.91(0.05) 5.40(0.80) 20.9(1.18) 7.08(0.41) 9.14(1.56) 72.2(7.84)



Akaki08 Lactuca sativa var. crispa 0.80(0.17) 0.78(0.08) 2.88(0.28) 24.7(1.36) 5.30(0.39) 9.23(0.65) 67.6(5.01)



Akaki Lactuca sativa var. crispa 1.05(0.14) 0.94(0.12) 5.39(0.62) 19.6(1.83) 4.42(0.92) 6.92(1.18) 79.8(8.87)



MPL (mg kg−1

dry weight)

2.35a 50b

27.1c 235d

800d 3.53a

588d

MPL; 0.085 was taken as conversion factor, to convert fresh green vegetable weight to dry weight (Qureshi et al. 2016)

Sources: a(FAO/WHO-codex alimentarius commission 2001; EC 2006) b(Pendias and Pendias 1992) c(Weigert 1991) d(Mapanda et al. (2007) based on UK and FAO/WHO standards)


from 0.87 mg kg−1

(Brassica carinata A. Br.) to

1.79 mg kg−1

(Lactuca sativa var. crispa) dry weights.

But even the highest concentrations did not exceed the

MPL standard. The high accumulation of Cd in vegeta-

bles at the two sites may be attributed to the acidic

nature of the soils (Table 2), resulting in greater Cd

availability (Kachenko and Singh 2006). This is further

supported by the significant correlations (p = 0.696–

0.748) of vegetable Cd concentrations with soil Cd.

Higher Cd levels which surpassed the maximum

permissible limit were reported by Weldegebriel et al.

(2012) in vegetables harvested from Kera and Goffa

urban vegetable farming sites. Conversely, lower levels of

Cd in vegetables at various vegetable farming sites of

Addis Ababa were reported by Aschale et al. (2015) and

Mekonnen et al. (2015). Cadmium levels exceeding the

49


Heavy metals

Cd

Farming site

138.56***

Vegetables

67.17***

Site x vegetable

7.75***

density as also shown in other studies (Baye and Hymete

2010; Osma et al. 2013; Teju et al. 2012). Since lead is

Co 107.86*** 330.23***

21.32*** not biodegradable, and highly immobile, once soil has

Cr 100.90*** 56.60***

19.73***

become contaminated, it remains a long-term source of

Cu 54.79*** 250.25***

20.44***

dust exposure, although lead-free gasoline dominates to-

Ni ***

66.08 ***

313.59 ***

17.60

leaves before analysis requires more attention, and has Pb 32.05***

168.79*** 7.67***

to go beyond the removal of visible dust particles.

Zn 22.61*** 59.37***

3.36*** Zinc accumulation varied in the vegetables across the

***Level of signific nce: p < 0.001 10 farming sites, from 57.7 for Lactuca sativa var. crispa

MPLs were reported by Mapanda et al. (2007) and

Gupta et al. (2010). Similar high level was also found in

Radish (Bigdeli and Seilsepour 2008). Results of two way

ANOVA test showed that variation in Cd concentrations

were significant across farming site, vegetable type and

site x vegetable interaction (Table 4). Among the ana-

lyzed vegetables, Cd accumulation was significantly high

(p < 0.05) in Lactuca sativa var. crispa. As a result, we

emphasize the differences in physiology of metal uptake,

exclusion, accumulation, as well as foliage deposition

and retention (Zurera et al. 1987; Cui et al. 2004; Zia et

al. 2016).

The results obtained in the present study showed that

the concentrations of Co in the vegetables were between

0.32 and 1.86 mg kg−1 DW (Table 3), the lowest concen-

tration was found in Brassica carinata A. Br. and highest

in Beta Vulgaris var. cicla. The concentrations were

substantially lower than its MPL. Yet, there were signifi-

cant differences in Co concentrations in the analyzed

vegetable (p < 0.05). Among the metals under the consid-

eration of the present study, Co showed minimum in all

vegetables next to Cd. Weldegebriel et al. (2012), Aschale

et al. (2015) and Mekonnen et al. (2015) have also found

lowest concentrations of Co as compared to Cr, Cu, Mn,

Ni, Pb and Zn. In the analyzed vegetables, concentrations

of Cr were substantially lower than the MPL standard.

Mean Cr concentrations among vegetable crops was in

the order of Lactuca sativa var. crispa > Beta Vulgaris var.

cicla > Brassica carinata A. Br.. The observed mean (over-

all) Cr concentrations were 5.1, 3.84 and 4.42 mg kg−1 in

Lactuca sativa var. crispa, Brassica carinata A. Br., Beta

Vulgaris var. cicla, respectively. Similar low levels were

also obtained in previous studies (Itanna 1998; Liu et

al. 2005; Aschale et al. 2015; Mekonnen et al. 2015;

Zia et al. 2016;). The two way ANOVA test revealed

significant differences by farming site, vegetable type

and their interaction (Table 4).

Mean concentrations of Cu in vegetables across the 10

vegetable farming sites were varied and all below the

MPL standard (Table 3). At Lekunda, the concentrations

Table 4 Results of two way ANOVA test for heavy metal levels in

vegetables harvested from wastewater-irrigated urban vegetable

farming sites

ranged from 16.0 (Brassica carinata A. Br.) to 38.9 (Beta

Vulgaris var. cicla) mg kg−1

, in Kera farming site they

ranged from 21.5 (Brassica carinata A. Br.) to 36.2

(Lactuca sativa var. crispa) mg kg−1

and in Akaki 08

they ranged from 22.9 (Brassica carinata A. Br.) to 44.3

(Beta Vulgaris var. cicla) mg kg−1

dry weights. An earlier

study by Weldegebriel et al. (2012) in vegetable farming

site around Goffa showed concentration of Cu in

Lactuca sativa that were twice that of those sampled in

the present study. Lower concentrations of Cu in various

vegetables were also reported in selected vegetable farm-

ing sites in Addis Ababa and its outskirts (Aschale et al.

2015; Mekonnen et al. 2015). Studies in other African

cities have shown varied results but all substantially

below the MPL standard. In Harare, Muchuweti et al.

(2006) showed elevated levels of Cu in various crops

while Lente et al. (2012) in Accra and Mapanda et al.

(2007) in Harare showed lower concentrations. Similarly,

concentrations of Ni were substantially lower than the

MPL standard. When the concentrations of Ni in Lac-

tuca sativa grown at wastewater -irrigated sites of Addis

Ababa, Ethiopia (Aschale et al. 2015) were compared

with the values recorded in the present study, the values

of the previous study were 2–4 fold lower. Similar lower

results were obtained in Accra (Lente et al. 2012) and

Varanasi, India (Ghosh et al. 2012).

Despite the relatively low analyzed Pb concentrations

in water and soil, marked differences were observed for

Pb accumulation in the leaves of the analyzed vegetables,

which exceeded 1.4–3.9 times the MPL standard of the

respective crops. This is in agreement with the previously

reported Pb levels of wastewater i r r i g a t e d vegetables in

Addis Ababa’s urban vegetable farming sites

(Weldegebriel et al. 2012) and with results reported

from other African cities (Muchuweti et al. 2006; Odai et

al. 2008; Lente et al. 2012). According to Hamilton et al.

(2005), plant roots can adsorb Pb but may not

translocate it to shoots, a possibility is that like in

Ghana, high Pb levels on wastewater as well as con-

trol sites (groundwater irrigated urban farms) are attrib-

utable more to vehicular exhaust fumes (Affum et al.

2008) than to irrigation water. In fact, high soil pH, clay

and organic matter content are not supporting Pb up-

take via roots. On the other hand, Kylander et al. (2003)

analyzed in Accra a Pb distribution following traffic

day’s market. This finding showed that the washing of

a

50


and 129 mg kg−1

for Beta Vulgaris var. cicla. The values

were 4.55–10.2 times lower than the RML standard.

Zinc concentrations in Kera farming site were consist-

ently higher than vegetables sampled over all other farm-

ing sites, ranging from 94.4 (Lactuca sativa var. crispa)

and 129 (Beta Vulgaris var. cicla) mg kg−1

dry weights.

In general, the level of metal accumulation in Beta

Vulgaris var. cicla was higher than the other vegetables.

Briefly, Beta Vulgaris var. cicla accumulated significantly

(p < 0.05) higher levels of Co, Cu, Ni, Pb and Zn, while

Lactuca sativa var. crispa exhibited significantly (p < 0.05)

higher levels of Cd and Cr.

Daily intake of metals and target hazard quotient

The estimated daily intakes (EDIs) of metals for adults

in wastewater -irrigated vegetable farming sites at 5 sub-

city administrative areas via the consumption of leafy

vegetable are presented in Table 5. The provisional toler-

able daily intakes (PTDIs) for Cd, Cr, Cu, Ni, Pb and Zn

are 0.06 mg, 0.2 mg, 3 mg, 0.3 mg, 0.214 mg and 60 mg,

respectively (National Research Council 1989). For each

individual metal measured in the present study, none of

the EDIs exceeded its corresponding PTDIs, nor did ap-

proach the doses. The highest EDI of Cd (0.122 μg d−1)

through the consumption of the analyzed vegetables was

from Nefas Silk Lafto sub-city administrative area.

The EDIs of Cd for Selected sub-city administrative

areas in Addis Ababa (0.046–0.122 μg d−1

) were sub-

stantially lower than the values reported for other

countries: Tanzania (21.6 μg d−1

) (Bahemuka and

Mubofu 1999), China (59 μg d−1

) (Zhuang et al.

2009), Pakistan (5.29 μg d−1

) (Mahmood and Malik

2014) and India (32 μg d−1

) (Chopra and Pathak

2015). This discrepancy could be partly attributed to

others (Bahemuka and Mubofu 1999; Zhuang et al.

2009; Mahmood and Malik 2014; Chopra and Pathak

2015) analyzing more vegetable types than we did in

the present study. The present study showed that the

contribution of these vegetables to the daily intake of

Cd was less than 0.3% of its corresponding PTDI. It

is, however, worth considering the contribution other

food groups to Cd or other metals dietary intakes.

The total EDIs of Co ranged from 0.052 to 0.116 μg d −1

, much lower than the values estimated in other coun-

tries: Ghana 5.3 μg d−1

(Lente et al. 2012) and Pakistan

541 μg d−1

(Mahmood and Malik 2014). In the present

study, the vegetable that contributed the greatest quan-

tity of Co to the intake was Beta Vulgaris var. cicla. In

Accra, cabbage grown on wastewater-irrigated site con-

tributed 3.14 μg to the daily intake (Lente et al. 2012).

Table 5 Estimated Daily Intake (EDI) for individual heavy metals caused by the consumption of different vegetables grown on

wastewater-irrigated soils at 5 sub-city administrative areas (mg d−1

)

Administrative areas Vegetable Cd Co Cr Cu Ni Pb Zn

Kolfe Keraniyo Lactuca sativa var. crispa 1.44E-05 1.27E-05 1.31E-04 6.59E-04 1.01E-04 2.40E-04 1.64E-03

Brassica carinata A. Br. 1.56E-05 1.65E-05 1.49E-04 5.50E-04 1.18E-04 2.69E-04 3.08E-03

Beta Vulgaris var. cicla 1.59E-05 2.28E-05 1.05E-04 8.79E-04 1.71E-04 3.34E-04 2.98E-03

Total 4.59E-05 5.20E-05 3.85E-04 2.09E-03 3.89E-04 8.43E-04 7.71E-03

Chirkos Lactuca sativa var. crispa 2.84E-05 1.44E-05 1.43E-04 6.46E-04 4.96E-05 2.27E-04 1.68E-03



Total 1.17E-04 1.04E-04 5.74E-04 2.76E-03 3.37E-04 1.32E-03 1.23E-02

Bole Lactuca sativa var. crispa 1.14E-05 1.20E-05 6.48E-05 4.38E-04 1.01E-04 2.58E-04 1.43E-03



Total 5.47E-05 6.77E-05 2.52E-04 2.29E-03 4.44E-04 1.07E-03 8.63E-03

Nefas Silk Lafto Lactuca sativa var. crispa 2.12E-05 2.54E-05 1.21E-04 6.02E-04 1.33E-04 1.86E-04 1.54E-03



Total 1.22E-04 1.61E-04 7.31E-04 3.51E-03 8.26E-04 1.10E-03 1.18E-02

Akaki Kaliti Lactuca sativa var. crispa 1.94E-05 1.80E-05 8.68E-05 4.65E-04 1.02E-04 1.69E-04 1.55E-03



Total 7.82E-05 1.16E-04 5.03E-04 3.20E-03 5.52E-04 8.88E-04 1.04E-02

51


The total EDIs of Cr, Cu and Ni ranged from 0.252– 0.731, 2.09–3.51, and 0.337–0.826 μg d

−1, respectively.

Similarly, the findings of the present study concerning

EDIs of these metals show that the values are sub-

stantially lower than their corresponding PTDIs and

are free of potential risk. Conversely, other estimates

made from other countries have shown that the daily

intakes for Cr, Cu and Ni were higher than their

corresponding PTDIs (Maleki and Zarasvand 2008;

Gupta et al. 2012). Although the concentrations of Pb

in all analyzed vegetables were far above the RML

standard, the total EDIs (0.094–1.32 μg d−1

) were

substantially lower than the PTDI standard. The high-

est total EDI of Pb (1.32 μg d−1

at Chirkos) was

found to contribute 0.6% to the PTDI. Higher dietary

exposure estimate for Pb through the consumption of

vegetables grown on wastewater-irrigated fields were

reported by Singh et al. (2010) and Mahmood and

Malik (2014). Thus, in the context of the present

study, intake of these contaminated (Pb) vegetables is

unlikely to induce health risks arising from Pb.

Based on the consumption of selected vegetables

grown on polluted river water-irrigated vegetable farm-

ing sites, the total EDIs of Zn (7.71–11.8 μg d−1

) were

relatively high as compared to the other metals. But

these EDI values contributed less than 0.02% to the

corresponding PTDI standard. Yet, it can be clearly ob-

served that our estimates for Zn are far lower than those

reported from other countries (Khan et al. 2008; Lente

et al. 2012; Mahmood and Malik 2014). Overall, a large

daily consumption of these vegetables is unlikely to pose

detrimental health risks to the consumer associated with

individual metal intake. However, it is worth considering

other food crops which may contribute to metal expos-

ure and further studies are required to completely

understand the risk involved.

The health risk associated with the consumption of se-

lected leafy vegetables grown on wastewater -irrigated

vegetable farming sites was evaluated using Target Haz-

ard Quotient (THQ). The THQ has been recognized as

a useful parameter for the evaluation of risk associated

with the consumption of contaminated (metals) food

crops (Zheng et al. 2007; Zhuang et al. 2009). Target

Hazard Quotient value of less than 1 indicates a relative

absence of health risk associated with the consumption

of metal contaminated food crops (USEPA 2007). The

THQ values via the consumption of the three vegtables

ranged from 0.042–0.108, 0.005–0.014,0.0002–0.0004,

0.048–0.078, 0.015–0.037, 0.194–0.298 and 0.026–0.037

for Cd, Co, Cr, Cu, Ni, Pb and Zn, respectively (Table

6). From the above data, it is apparent that the

consumption of the examined vegetables do not expose

local inhabitants to a potential health risk from dietary

Cd, Co, Cr, Cu, Ni, Pb and Zn in short term. The results

obtained in the present study did not concur with

values recorded by Zheng et al. (2007), Zhuang et al.

(2009) and Hu et al. (2014). Among the metals THQ

values, the greatest values were obtained for Pb for the

consumption of wastewater-irrigated vegetables at 5

sub-city administrative areas and were in the order:

Chirkos (0.298) > Nefas Silk Lafto (0.244) > Bole

(0.243) > Akaki Kaliti (0.197) > Kolfe Keraniyo (0.194).

The total metal THQ (sum of individual metal THQ

for the analyzed vegetables) is shown in Fig. 2. The

TTHQs of the metals ranged from 0.33 to 0.53. Compar-

ing sub-city administrative areas, the TTHQs of the

metals decrease in the order of Chirkos > Nefas Silk

Lafto > Akaki Kaliti > Bole > Kolfe Keraniyo. The present

result indicate that Pb and Cd were the major compo-

nent contributing to the TTHQs, in agreement with sep-

arate assessments for areas near Huludao Zinc plant in

Huludao, China (Zheng et al. 2007) and in the vicinity of

Dabaoshan mine in Shaoguan city, China (Zhuang et al.

2009). In the studied sites, the consumption of all ana-

lyzed vegetables resulted in TTHQ values of less than 1,

compared to the high TTHQ values obtained from

emerging economies (Abbasi et al. 2013; Qureshi et al.

2016). Compared with our previous study (Woldetsadik

et al. 2017) which focused on microbial hazards of

wastewater irrigation, it is clear that heavy metals may

not pose short term risk to local inhabitants through the

consumption of leafy vegetables grown on wastewater-

irrigated vegetable farming sites. However, it is worth

considering the effects that may result from the inter-

action of the metals.

Conclusions

From this study, it was evident that the concentrations

of metals in irrigation water and soil were lower than

the MPL standards. Wastewater dilution may be the im-

portant reason for lower levels of metals in irrigation

water. Based on 1:100 dilution, the process is predicted

to bring 3 mg kg−1metal level down to just 0.03 mg kg−1,

as compared to only 2 log units reduction for pathogens,

and still above thresholds, indicating metals discharged

to streams will dissipate by dilution and incorporate into

sediments. Hence, a more differentiated view is required

as the readers might associate the term wastewater with

raw effluent. Significant variations in metal concentra-

tions between the analyzed vegetables reflect the differ-

ence in their uptake capabilities. With the exception of

Pb, the concentrations of the other metals in all analyzed

vegetables were far below the various international MPL

standards. From the health point of view, the EDI and

THQ values showed that there would be no short term

potential health risk to local inhabitants due to intake of

individual metal if one or more of the analyzed

vegetables are consumed.

52


Table 6 Target hazard quotient for individual heavy metals through the consumption of different vegetables grown on wastewater-

irrigated soils at 5 sub-city administrative areas

Administrative areas Vegetable Cd Co Cr Cu Ni Pb Zn

Kolfe Keraniyo Lactuca sativa var. crispa 1.33E-02 1.17E-03 8.07E-05 1.52E-02 4.67E-03 5.54E-02 5.05E-03



Total 4.23E-02 4.80E-03 2.36E-04 4.82E-02 1.80E-02 1.94E-01 2.37E-02

Chirkos Lactuca sativa var. crispa 2.48E-02 1.26E-03 8.33E-05 1.41E-02 2.17E-03 4.95E-02 4.91E-03



Total 1.05E-01 9.46E-03 3.45E-04 6.21E-02 1.53E-02 2.98E-01 3.71E-02

Bole Lactuca sativa var. crispa 1.03E-02 1.08E-03 3.89E-05 9.86E-03 4.54E-03 5.82E-02 4.29E-03



Total 4.96E-02 6.15E-03 1.52E-04 5.19E-02 2.01E-02 2.43E-01 2.61E-02

Nefas Silk Lafto Lactuca sativa var. crispa 1.87E-02 2.23E-03 7.08E-05 1.32E-02 5.86E-03 4.09E-02 4.52E-03



Total 1.08E-01 1.42E-02 4.31E-04 7.77E-02 3.65E-02 2.44E-01 3.47E-02

Akaki Kaliti Lactuca sativa var. crispa 1.67E-02 1.55E-03 4.98E-05 1.00E-02 4.39E-03 3.65E-02 4.44E-03



Total 6.91E-02 1.03E-02 2.97E-04 7.09E-02 2.44E-02 1.97E-01 3.09E-02

These results emphasize the need for further

investigations of other crops from the study sites. Still,

health risk exposure of children through the

consumption of local vegetables should also be

investigated due to their high sensitivity to metal

exposure.

Our previous study indicated that faecal contamination

level of lettuce irrigated with wastewater is above the

threshold of safe consumption. Hence, it is imperative to

focus on and off farm mitigation measures including

proper vegetable washing that helps reduce potential

pathogenic risks. However, intermittent monitoring of

the metals from irrigation water, in soil and crops may be

required to follow/prevent their build-up in the food

chain.

Fig. 2 Total THQ values for metals at 5 sub-city administrative areas

53


Abbreviations

CEC: Cation exchange capacity; EDI: Estimated daily intake;

MPL: Maximum permissible limit; OM: Organic matter; THQ: Target

hazard quotient; TTHQ: Total target hazard quotient

Acknowledgements

This work was supported by the International Water Management

Institute (IWMI-CGIAR), Blacksmith Institute (Pure Earth) and the Ministry

of Education of Ethiopia. We are grateful to the staff of soil chemistry

laboratory at Debre Zeit Agricultural Research Center and to the staff of

soil laboratory in Bochum for the laboratory assistance. We also wish to

acknowledge the field work support of development agents at various

sub-city administrative areas of Addis Ababa.

Funding

This work was funded by the International Water Management Institute (IWMI-

CGIAR), Blacksmith Institute (Pure Earth) and the Ministry of Education of Ethiopia.

The International Water Management Institute (IWMI-CGIAR), Blacksmith Institute

(Pure Earth) and the Ministry of Education of Ethiopia had no role in the design,

data collection, analysis or publication of the manuscript.

Availability of data and materials

The data sets on which the conclusions of the paper rely is presented in the

main body of the manuscript.


DW, PD, BK, FI and HG conceived and designed the study. DW conducted

the study. DW, PD, BK and FI contributed to the analysis and interpretation

of data. DW drafted the manuscript. DW, PD, BK, FI and HG revised the draft

manuscript. All authors read and approved the final manuscript.

Competing interests


Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in

published maps and institutional affiliations.

Author details 1School of Natural Resources Management and Environmental Sciences,

Haramaya University, PO Box: 138, DireDawa, Ethiopia. 2International Water

Management Institute, Colombo, Sri Lanka. 3Department of Global Health,

University of Copenhagen, Copenhagen, Denmark. 4Department of Crop

Science, University of Namibia, Windhoek, Namibia.

Received: 17 February 2017 Accepted: 3 May 2017

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DOI 10.1186/s40064-016-2019-6

RESEAR CH

Effects of biochar and alkaline

Open Access

amendments on cadmium immobilization, selected nutrient and cadmium concentrations of lettuce (Lactuca sativa) in two contrasting soils

Desta Woldetsadik1*, Pay Drechsel2, Bernard Keraita3, Bernd Marschner4, Fisseha Itanna5 and Heluf Gebrekidan1

*Correspondence:

[email protected] 1 School of Natural

Resources Management

and Environmental Sciences,

Haramaya University, 138,

Dire Dawa, Ethiopia

Full list of author information

is available at the end of the

article

Abstract

Contamination of agricultural lands with heavy metals such as Cd and Pb is of worldwide

concern. To assess the efficiency of seven treatments including biochars produced from

dried faecal matter and manures as stabilizing agents of cadmium (Cd)-spiked soils, lettuce

was grown in a glasshouse on two contrasting soils. The soils used were moderately fer-

tile silty loam and less fertile sandy loam and the applied treatments were 7 % w/w. The

reduction of bioavailable Cd (ammonium nitrate extractable) and its phytoavailability for

lettuce were used as assessment criteria in the evaluation of stabilization performance of

each treatment. Moreover, the agronomic values of the treatments were also investigated.

Ammonium nitrate extraction results indicated that faecal matter biochar, cow manure

biochar and lime significantly reduced bioavailable Cd by 84–87, 65–68 and 82–91 %,

respectively, as compared to the spiked controls. Unpredictably, coffee husk biochar

induced significant increment of Cd in NH4NO3 extracts. The immobilization potential of

faecal matter biochar and lime were superior to the other treatments. However, lime and

egg shell promoted statistically lower yield and P, K and Zn concentrations response of

lettuce plants compared to the biochar treatments. The lowest Cd and highest P tissue

concentrations of lettuce plants were induced by faecal matter and cow manure biochar

treatments in both soils. Additionally, the greatest Cd phytoavailability reduction for

lettuce was induced by poultry litter and cow manure biochars in the silty loam soil. Our

results indicate that faecal matter and animal manure biochars have shown great potential

to promote Cd immobilization and lettuce growth response in heavily contaminated

agricultural fields.

Keywords: Biochar, Faecal matter, Cadmium, Immobilization, Phytoavailability, Lettuce

Background

Excessive accumulation of heavy metals in agricultural soils leads to elevated metal

uptake by crops and thus affect food quality and safety, which pose major public health

concern (Wang et al. 2005; Khan et al. 2008). The potential toxicity and persistent nature

of heavy metals make the process of remediating contaminated soil very complex (Wu

et al. 2004). A number of ex situ remediation options are available for contaminated soils

© 2016 Woldetsadik et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and

indicate if changes were made.

56



Woldetsadik et al. SpringerPlus (2016) 5:397 Page 2 of 16

including soil washing, excavation and electrokinetics (Virkutyte et al. 2002; Yeung and

Hsu 2005; Dermont et al. 2008; Peng et al. 2009). However, most of these remediation

options are expensive and damage soil quality (Mulligan et al. 2001; Alkorta et al. 2004;

Ghosh and Singh 2005).

In situ chemical immobilization technologies are the best demonstrated and promis-

ing alternatives to ex situ remediation methods (Diels et al. 2002; Kumpiene et al. 2008;

Chen et al. 2015; Hmid et al. 2015). Chemical immobilization is based on alteration of

contaminant and soil characteristics by the addition of stabilizing agents. Numerous

amendments including clay minerals, organic and liming materials and phosphate min-

erals have been widely examined for reducing metal mobility and availability in heavy

metal contaminated soils (Chen et al. 2000; Cao et al. 2003; Ok et al. 2010; Herath et al.

2015; Puga et al. 2015). The immobilization process is influenced by various mechanisms

including adsorption, specific binding of metal ions, cation exchange, precipitation and

complexation (Polo and Utrilla 2002; Ok et al. 2007; Uchimiya et al. 2010; Herath et al.

2015; Hmid et al. 2015).

Biochar has many heavy metal immobilization properties including microporous

structure, active functional groups, high pH and cation exchange capacity (CEC) (Chen

and Lin 2001; Jiang et al. 2012a, b). Biochar, originated from plant residues, have been

applied to soils for immobilization of heavy metal contaminants (Chun et al. 2004;

Mohan et al. 2007). In addition, Phosphorous (P)—rich biochars have also shown great

potential to reduce the mobility and availability of metals in water and soils contami-

nated with heavy metals (Cao et al. 2009a; Uchimiya et al. 2010). Accordingly, biochars

derived from animal wastes have been spotlighted as heavy metal stabilization agents

in contaminated soils (Cao and Harris 2010; Cao et al. 2011; Park et al. 2011a). Alkaline

amendments also used as immobilizing agents in contaminated soil may have profound

effects on reducing metal solubility and mobility via increasing soil pH and concomi-

tantly metal sorption to soil particles and formation of poorly soluble metal hydroxides

and carbonates (Filius et al. 1998; Kumpiene et al. 2008; Zeng et al. 2011). Recently, lime-

based waste materials have been assessed for their potential to stabilize heavy metals

and highlighted as an environmentally friendly immobilization approach (Ok et al. 2010,

2011a, b; Lee et al. 2013).

Although the immobilization of heavy metals using various organic and inorganic

amendments including plant and animal derived biochars and lime-based materials have

been well studied (Chun et al. 2004; Ok et al. 2010; Uchimiya et al. 2010; Liu et al. 2009;

Lee et al. 2013), little is known about the potential human faecal matter (FM), Prosopis

juliflora pods (PJ) and coffee husk (CH) biochars in reducing the mobility and bioavaila-

bility of heavy metals in contaminated soils. Therefore, the objective of this study was to

evaluate efficacy of biochars [FM, PJ, CH, cow manure (CM) and Poultry litter (PL)] and

alkaline amendments [egg shell (ES) and lime (LI)] as stabilizing agents of Cd in spiked

soils. The efficacy of immobilization was evaluated by the change in Cd concentration in

NH4NO3 extract and phytoavailability of the metal for lettuce.

57


Methods

Soil sampling and preparation

Soils of two different texture classes i.e. silty loam (PK) and sandy loam (BA), were col-

lected for greenhouse experiments from two sites i.e. a wastewater irrigated urban veg-

etable farming site in Addis Ababa and a rainfed peri-urban groundnut farming site in

Babile, Ethiopia. At each site, approximately 100 kg of composite soil sample was exca-

vated from the surface to a depth of 15 cm. The soil samples were transported to the

greenhouse in plastic bags. The samples were air-dried, homogenized, and sieved using

a <2 mm sieve.

Stabilization treatments

Faecal matter (FM) was collected from septage drying bed in Addis Ababa sewage treat-

ment plant. Samples were taken from 12 different locations at 10 cm depth, then mixed

into one composite sample. Poultry litter (PL) was also obtained from drying bed in a

commercial deep—bedded poultry farm in Bishoftu. Cow manure (CM) was collected

from a private milking facility. Prosopis juliflora (PJ) pods were collected from different

Prosopis juliflora invaded lands in a peri-urban area of Dire Dawa. Coffee husk (CH) was

also collected from raw coffee processing facility in Addis Ababa. Cow manure samples

underwent air-drying in a glasshouse for 10 days.

For pyrolysis, the feedstock samples were placed in aluminum furnace (FATALU-

MINUM S.p.A, ITALY). The heating rate was 15 ◦C/min. Heat treatments were per-

formed at 450 ◦C for FM, CM and PL, 480 ◦C for PJ and 375 °C for CH. The pyrolysis

temperature was maintained for 60 min for FM, CM and PL, for 62 min for PL and for

55 min for CH. After pyrolysis, the charred samples were removed from the canister and

allowed to cool to room temperature. The egg shell powder (ES) was also prepared with

waste egg shells collected from ELFORA plc in Bishoftu. The egg shells were washed

several times with hot water, then heated at 72 °C for 72 h to dry, subsequently pulver-

ized using a mortar and pestle to homogenized powder having <1 mm particle size (Ok

et al. 2011a). Lime (LI) was also obtained from National Soil Testing Center.

Experimental set up

Experimentation was done in a greenhouse. The treatments used in this study were FM,

CM, PL, PJ and CH biochars, ES and LI. Cadmium was applied to soil as solution of cad-

mium (II) nitrate tetrahydrate (Cd(NO3)2.4H2O) at the rate of 50 mg Cd/kg. Treatments

were homogenized with Cd spiked soils at the rate of 7 % w/w. Briefly, 3 kg of air-dried

Cd treated soil was thoroughly mixed with each treatment in plastic pot. For each soil

type, separate trial was conducted in a completely randomized design in triplicates. The

trial was carried out in a temperature controlled glasshouse with regular daily watering.

After 2 weeks, eight seeds of lettuce were sown in each pot and lettuce seedlings were

thinned to three per pot a week after emergence (only 3 or 4 seedlings were emerged in

the control and some treatments). Pots were placed on plastic saucers to prevent lea-

chate drainage. Ten weeks after sowing, the above ground biomass was cut down to soil

surface to determine shoot fresh weight. The above ground biomass was cleaned to avoid

the adhered soil particles. Dry weight was subsequently determined following oven dry-

ing to a constant weight at 65 °C for 72 h. The dried lettuce plants were ground, milled

58


to fine powder and stored for subsequent analyses. After harvesting, soil sample from

each pot was collected, ground to <2 mm and stored for pH and NH4NO3 extractable Cd

analyses. Phytoavailability was computed as follows (Cao et al. 2009b).

Phytoavailability (%)

= metal concentration

mg/kg

in plant × above ground biomass

kg/pot

metal concentration

mg/kg

in soil × soil mass

kg/pot

Analyses

First, the soil and biochar samples were ground to <2 mm. For total element, NH4NO3

extractable trace elements and Fourier Transform Infrared (FTIR) analyses, soils and

biochar samples were milled with a planetary ball mill to achieve a homogeneous fine

powder (Fritsch GmbH, Idar-Oberstein, Germany). The pH of biochar in water was

determined in 1:20 (w/v) ratio after occasionally stirring over 1 h (Cheng et al. 2006). The

pH of the soils in water suspensions were determined in 1:2.5 (w/v) ratio after shaking

over 2 h. The EC of biochar was determined after 1 h equilibration of 1 g of biochar with

20 ml of distilled water. The EC of the soil was determined after 2 h equilibration of 1 g

of soil with 2.5 ml of distilled water. Soil Particle size distributions were determined by

laser diffraction using an Analysette 22 MicroTec plus (Fritsch GmbH, Idar-Oberstein,

Germany) with a wet dispersion unit. For total element analysis, 0.25 g of biochar and

soil were placed into 50 ml vessels, followed by addition of 10 ml concentrated HNO3.

The mixtures were left to cold digest in a fume cupboard over night and then heated in

1.6 KW microwave oven for 30 min. After cooling to room temperature, 10 ml of dou-

ble distilled water was added into the vessel and filtered via a 0.45 µm cellulose nitrate

filter paper. Finally, the filtrate was subjected to the total element analysis using ICP-

OES (Ciros CCD, SPECTRO Analytical Instruments GmbH, Kleve, Germany). Olsen-P

(available P) were extracted by placing 1 g of soil and biochar in 20 ml of NaHCO3 for

30 min. The suspension was vacuum filtered via a 0.45 µm cellulose nitrate filter paper

and analyzed using ICP-OES (Ciros CCD, SPECTRO Analytical Instruments GmbH,

Kleve, Germany). For C and N analyses, about 3.5 mg of biochar and 40 mg of soil were

weighted into sample boats and determined using C and N analyzer (Elementar Analyse

GmbH, Hanau, Germany). Acetanilide was used as calibration standard. Total surface

acidity was determined by adding 0.15 g of biochar into 15 ml of 0.1 N NaOH and

shaken for 30 h. The suspension was vacuum filtered and 5 ml of 0.1 N NaOH aliquot

was transferred to 10 ml of 0.1 N HCl to completely neutralize the unreacted base. The

solution was back-titrated with 0.1 N NaOH using a Metrohm 725 Dosimat (Metrohm

AG, Herisau, Switzerland) fitted with a 691 pH meter (Metrohm AG, Herisau, Switzer-

land). Similarly, the surface basicity was measured by shaking 0.15 g of biochar with

15 ml of 0.1 N HCl for 30 h. The slurry was vacuum filtrated (0.45 µm) and an aliquot

of 5 ml of 0.1 N HCl was mixed with 10 ml of 0.1 N NaOH to neutralize the unreacted

acid. The solution was back-titrated with 0.1 N HCl. The total surface acidity and basic-

ity were determined by calculating the base and acid uptake of biochars (Goertzen

et al. 2010). For dissolved organic carbon (DOC) determination, extract was prepared

by shaking biochar with 0.01 M CaCl2 at 1:25 ration (w/v) for 1 h. The suspension was

vacuum filtered and measured by a Dimatoc 2000 (DIMATEC Analysentechnik GmbH,

59


Essen, Germany). The exchangeable cations and CEC of biochar were determined using

BaCl2 method. Briefly, 2.5 g of biochar was weighted into 50 ml centrifuge tube, fol-

lowed by addition of 30 ml of 0.1 M BaCl2. The tube was shaken for 1 h and then centri-

fuged at 5500 rpm for 10 min. After centrifugation, the supernatant was decanted into a

100 ml volumetric flask. This procedure was repeated three times. The collected super-

natants were made up to 100 ml with 0.1 M BaCl2 solution. The Na, Mg, Ca, K and Al

concentrations of the solution were determined using ICP-OES (Ciros CCD, SPECTRO

Analytical Instruments GmbH, Kleve, Germany). The same procedure was followed to

determine the water soluble Na, Mg, Ca, K and Al concentrations of biochar. Finally, the

concentration of exchangeable cations and CEC of biochar was computed by subtracting

the concentration of water soluble cations (Na, Mg, Ca and K) to the concentration of

cations extracted by 0.1 M BaCl2. For FTIR analyses of biochars, pellets were prepared

by mixing biochars with KBr powder and then analyzed using a Tensor 27 FTIR Spec-

trometer (Bruker optik GmbH, Ettlingen, Germany). Spectra were collected in the range

of 400–4000 cm−1 at 4 cm−1 and 120 scans per sample. Surface areas of the biochars

were determined using adsorption data of the adsorption isotherms of N2 at −196 °C

and calculated by the Brunauer–Emmet–Teller (BET) equation (Brunauer et al. 1938).

For biochar and post harvest soil samples, NH4NO3 (1 M) extractable fraction of Cd was

determined following the extraction procedure proposed by the German national stand-

ard (DIN 19730 2009). A milled plant sample was analyzed for total Cd, P, K, Ca, Mg and

Zn concentrations as previously described.


Data are presented as mean (standard deviation) and were computed using Microsoft

2007 excel software. Treatment effects were determined by analysis of variance accord-

ing the general linear model procedure of SAS. Different among means of treatment

effects were separated by least significant difference (LSD) at P < 0.05 using SAS 9.2

software.


Characterization of soils and stabilization treatments

Table 1 shows selected properties of PK and BA soils. PK soil was silty loam having

pH 6.71(H2O) and relatively high in exchangeable cations compared to BA soil. The

pH(H2O) of BA soil was 6.86 with a sandy loam texture. The total Cd concentration of

PK soil (2.58 mg/kg) was higher than BA soil (0.30 mg/kg). Soil carbon status of PK soil

was rated as moderate, whereas soil carbon concentration of BA soil was rated as very

low according to Tekalign (1991). Similarly, BA soil had a low total N content as com-

pared to the critical concentration reported in Peverill et al. (1999).

In contrast to the more alkaline pH(H2O) of CM, PJ and PL biochars, biochars from

CH and FM had slightly alkaline pH values (Additional file 1: Table S1). ES also had high

pH value of 9.28 and contained considerable amount of calcite (CaCO3) (Lee et al. 2013).

Similarly, biochars produced from PJ, PL and CM had high EC values, whereas, CH and

FC biochars exhibited low EC values. These were expected considering the high salt/

ash content in CM and PL biochars (Cantrell et al. 2012). The biochar treatments had

varied total C concentration, with FM < CM < PL < PJ < CH. Unlike CH biochar which

60

Wo

ldetsad

ik et a

l. Sp

ring

erPlu

s (20

16

) 5:3

97

Pag

e 6 o

f 16

Table 1 Selected properties of the soils

1 −1 −1Soil pH (H2O) EC (dS/m) Exchangeable cations [cmol(+)/kg] CEC [cmol(+)/kg] Total Cd (mg kg− ) Total C (g kg ) Total N (g kg ) Particle size

Ca Mg K Na Al % Sand % Silt % Clay

PKa 6.71 0.024 24 6.7 0.9 0.4 <0.02 32.2 2.58 19 1.8 19.1 73.6 7.2

BAa 6.86 0.006 4.2 1.1 0.3 0.02 <0.02 5.83 0.3 3.2 0.4 54.1 38.2 7.5

a PK soil: Silty loam soil; BA soil: Sandy loam soil

61


1

1

exhibited the highest concentration of total C and the lowest concentration of total N

typical feature of plant-based biochars (Gaskin et al. 2008; Singh et al. 2010), the other

biochar treatments including PJ had very high concentrations of total N (Additional

file 1: Table S1). Moreover, CH biochar had the highest surface area (206 m2/g). The total

surface acidity of the examined biochar treatments ranged from 0.42 to 3.24 mmol/g

(Additional file 1: Table S1). The acidic surface functionality might be caused by the

presence of carboxyl, phenolic and lactonic groups. Whereas, ketones, carbonates and

other alkaline species might be responsible for basic surface functionality (Mukerjee

et al. 2011). With the exception of CH biochar, total acidic surface functionalities of the

biochar treatments were less than their corresponding basic functionalities. These

observations were consistent with the study of Singh et al. (2010), who recorded high

total surface basicity than surface acidity in PL and CM biochars produced at 550 °C

with steam activation and Uras et al. (2012) who reported high surface acidity than

surface basicity in plant based biochars.

Although faecal matter and manure derived biochar treatments had high concen-

trations of total P and major cations, the total P, Fe, Al and Mg concentrations in FM

biochar were higher than the concentrations in other biochar treatments (Additional

file 1: Table S2). Yet again, the FM biochar had the highest total trace elements. How-

ever, CM and PJ biochars contained the highest concentrations of Ca (34 g kg−1) and

K (39.2 g kg−1), respectively. The high levels of P, K, Mg and Ca in the biochars were

consistent with the results of Song and Guo (2012), who reported very high concentra-

tions of these elements in PL biochars produced under various pyrolysis temperatures.

The highest exchangeable K (59.6 cmol(+) kg− ) was observed in PJ biochar, while the

lowest (1.60 and 1.61 cmol(+) kg− ) were recorded in CH and FM biochars, respectively.

However, CM and PL biochars exhibited the highest exchangeable Mg and Ca concen-

trations, respectively. Generally, the CEC of the biochar treatments were in the order

of PJ > CM > PL > FM > CH (Additional file 1: Table S3). In comparison, the CEC of

PL biochar was 12.2 % higher than similar biochar with an average value of 37 cmol(+)

kg−1 despite the fact that the methods of CEC measurement differed (Song and Guo

2012). There were also differences in Olsen-P (available P) concentrations of biochar

treatments, with CMB > FMB > PLB > PJ > CH (Additional file 1: Table S3). As expected

plant-based biochar treatments exhibited the lowest Olsen-P values of 28.1 mg kg−1

(CH) and 383 mg kg−1 (PJ). On the contrary to the total P, the highest available P

(1437 mg kg−1) was exhibited by CM biochar. Likewise, the study of Cao and Harris

(2010) showed very high water soluble P value of CM biochar produced under very low

pyrolysis temperature. Available P value of FM biochar decreased to higher degree to its

corresponding total P value, this was largely ascribed to the formation of stable P con-

taining compounds.

Biosolids are known to contain high total concentrations of trace and toxic elements,

which exist in more pronounced concentrations in charred product (Bridle and Pritchard

2004; Lu et al. 2013). However, the use of biochar from biosolid is highly limited by the

bioavailability nature of the trace and toxic elements than the total load. Ammonium

nitrate extractable fraction was used to estimate the bioavailability of heavy metals in the

examined biochar treatments. The mobile fractions of the metals in the biochar treat-

ments accounted very small portion of their corresponding total contents. For example,

62


for FM biochar treatment the bioavailable fractions were 0.83, 0.14, 0.03, 0.03, 0.04, 0.005

and 0.04 % of the total loads of Cd, Co, Cr, Cu, Ni, Pb and Zn, respectively (Additional

file 1: Tables S2, S3). Overall, the bioavailable fractions in the biochars were in the range

of 0.47–2.5, 0.14–0.85, 0.02–0.09, 0.015–0.11, 0.04–0.71, 0.005–0.76 and 0.04–7.76 % of

the total loads of Cd, Co, Cr, Cu, Ni, Pb and Zn, respectively (Additional file 1: Tables

S2, S3). FTIR spectra of FM and PL biochars were very similar (Additional file 1: Fig-

ure S1). The characteristics broad bands at 3419, 3442,3419, 3431 and 3466 cm−1 were

attributed to the stretching vibrations of hydrogen-bonded hydroxyl groups of FM, PL,

CM, PJ and CH biochars, respectively (Keiluweit et al. 2010). For all biochars, but CHB,

aromatic C=C ring stretching were observed between 1462 and 1433 cm−1.The presence

of C=O stretching vibrations (1700–1600) indicated the presence of carboxylic groups

and ketones. Considering the high P contents of faecal and manure derived biochars,

particularly FMB and CMB, the intense broad bands at 1038 cm−1 likely resulted from

P-containing functional groups, most importantly, P-O bond of phosphate functional

group (Jiang et al. 2004).

Effect of treatments on soil pH and growth of lettuce

As presented in Table 2, all stabilization treatments but CHB significantly increased soil

pH over the spiked control in PK soil. In BA soil, addition of FMB had non-significant

effect on soil pH, whereas all other treatments significantly increased the pH of the soil

compared to the spiked control. Similar to this study, the findings of several studies indi-

cated that the application of biochar and alkaline amendments enhanced soil pH (Chan

et al. 2007, 2008; Lee et al. 2008; Ok et al. 2011a, b). Among the stabilization treatments,

LI and ES promoted the greatest pH increase in both soils, mainly due to the alkaline

impact of LI and ES (lime-based material) containing CaCO3, which dissociate to Ca2+

2− 2− −and CO3 , consequently the reaction of CO3 with water liberate OH ions, thereby

resulting in soil pH increase (Ok et al. 2011a; Lee et al. 2013).

Table 2 The influence of stabilization treatments on pH and fresh weight (FW) shoot yield

of lettuce grown on PK and BA soils

Stabilization treatments PKa soil BAa soil

Soil pH Shoot yield (FW) Soil pH Shoot yield (FW)

FMB 7.04 (0.09)eb 144 (13.0)a 8.39 (0.09)bc 91.5 (3.69)a

CMB 7.02 (0.06)e 84.2(2.65)c 8.83 (0.25)a 37.6 (0.40)b

PLB 6.89 (0.04)f 25.1 (2.78)g 8.48 (0.20)b 20.5 (1.87)e

PJB 7.18 (0.10)d 31.8 (2.40)g 8.83 (0.39)a 24.0 (1.72)d

CHB 6.58 (0.03)g 55.9 (2.19)e 8.46 (0.14)b 31.1 (0.81)c

ES 7.74 (0.08)b 61.0 (1.90)e 8.88 (0.02)a 13.2 (1.34)f

LI 7.95 (0.05)a 43.2 (1.89)f 9.09 (0.23)a 10.0 (0.96)g

CON+ 6.51 (0.04)g 73.1 (3.57)d 8.11 (0.04)c 12.7 (0.36)fg

CON− 7.41 (0.02)c 106 (6.77)b 8.17 (0.06)bc 30.8 (2.70)c

FMB Faecal matter (Faecal cake) biochar, CMB cow manure biochar, PLB poultry litter biochar, PJB Prosopis juliflora pods

biochar, CHB Coffee husk biochar, ES Eggshell waste, LI Lime, CON+ spiked control, CON− non-spiked control


b Standard deviation in parentheses (n = 3), values for each soil with different letter within each column are significantly

different (P < 0.05)

63


With the exception of FMB and CMB, all other stabilizing treatments induced signifi-

cant shoot yield reduction of lettuce plants grown in PK soil compared to the spiked

control (Table 2). Faecal matter biochar promoted significant shoot yield response of let-

tuce plants, 97 %, compared to the spiked control. Likewise, a more profound effect of

FMB application in increasing shoot yield of lettuce plants as high as 620 % was also

observed in BA soil. The positive impact of FMB on the growth performance of lettuce,

compared to the controls, may be attributed to a combination of P nutrition and toxicity

reduction effects (Chen et al. 2006). This was evident from the high P concentration of

lettuce plants under this amendment. In agreement with this finding, applying biochar

from sewage sludge significantly improved garlic yields even at lower biochar-to-soil

ratios (Song et al. 2014). Moreover, significant increase in shoot yield of lettuce plants

grown in BA soil was also observed across all other biochar treatments, increasing by

196, 61, 89, and 145 % under CMB, PLB, PJB and CHB, respectively. Similarly, Park et al.

(2011a) and Karami et al. (2011) reported improved dry matter yield of Indian mustard

and ryegrass plants grown in heavy metal contaminated/spiked soils treated with CM

and green waste biochar, respectively, compared to no amendment control, suggesting

the potential of biochar to enhance fertility of soil and reduce phytotoxicity of the met-

als. Conversely, the addition of wood biochar to Cd spiked soil (sandy) didn’t promote

significant dry matter yield effect of maize (Namgay et al. 2010). Meanwhile, the results

of this study showed that the shoot yield of lettuce plants was significantly decreased as

a result of Cd spiking as compared to the non-spiked control, indicating phytotoxicity of

Cd to lettuce plants.

Ammonium nitrate extractability of Cd

The results of this study revealed significant effect of biochar and alkaline treatments,

not including CHB, on reducing NH4NO3 extractable Cd in both soils (Table 4). Com-

pared to the spiked controls, NH4NO3 extractability of soil Cd decreased by 50–88 %

under ES treatments. Similarly, the concentrations of Cd in NH4NO3 extracts were

reduced by 70–85 % under PLB treatment compared to the spiked controls. Compara-

tively, FMB and LI promoted statistically the greatest decrease in concentrations of

NH4NO3 extractable Cd in both soils (1.15–1.97 mg/kg DW). However, PJB and CMB

exerted significant, but relatively smaller, reduction in NH4NO3 extractable Cd (32–67

and 65–68 %), respectively. In field study using LI as a treatment, Gray et al. (2006)

reported significant reduction of Cd concentration in NH4NO3 extract. In previous

study, Uchimiya et al. (2010) recorded significant immobilization of Cd in

contaminated soil amended with manure derived biochars. Very recently, Hmid et

al. (2015) has reported considerable reductions of Ca(NO3)2 extractable Cd and other

metals with increasing rates of olive mill waste biochar. Immobilization of Cd and other

heavy metals by biochar and alkaline treatments presumed to occur by enormous

mechanisms such as ion exchange, electrostatic interaction, surface complexation,

precipitation of amorphous to poorly crystalline metal phosphate minerals, substitution

for Ca by Cd during co-precipitation (Cao et al. 2009a; Uchimiya et al. 2010; Beesley et al.

2011; Uchimiya et al. 2011b). However, it is not easy to quantify specific

immobilization mechanism and it appears that the combined effect of two or more

mechanisms leads to metal stabilization (Cao et al. 2003). Heavy metal immobilization

by alkaline amendments is mainly attributed to

64


soil pH rise, which increase negatively charged sites on soil particles and consequently

promote cationic metal adsorption (Bradl 2004; OK et al. 2007). Moreover, Cd precipi-

tate as Cd(OH)2 is highly probable at pH value above 8 (Lee et al. 2008). Several studies,

Hong et al. (2007), Ok et al. (2011b) and Ahmad et al. (2012), also used lime-rich materi-

als including those employed in our study to reduce the mobility and bioavailability of

heavy metals in contaminated soils. Among the biochar treatments, application of FMB

didn’t significantly affect the pH of the spiked soil consequently reduction of Cd bio-

availability may not b e induced by the pH change in BA soil. The application of FMB

most effectively reduced NH4NO3 extractable Cd by 84–87 %, while PJB showed the

least decrease compared to the spiked controls. Owing to the low SSA of FMB than the

other manure derived biochar treatments (Additional file 1: Table S1), this observation

wasn’t related to the surface adsorption. Likewise, rice straw biochar promoted the

greatest Cd stabilization effect in soils had the lowest SSA compared to husk and bran

biochars (Zheng et al. 2012).

Generally, the contribution of surface adsorption to Cd stabilization was limited

since PJB, PLB and FMB had very small SSA ranged from 0.79 to 3.36 m2/g (Additional

file 1: Table S1). However, sorption of Cd to surface of CMB may not be ignored.

Unlike the plant based biochars (PJ and CH), which had high % C (62–73 %), manure

derived biochars (FMB, CMB and PLB) exhibited low C contents (19.5–43.4 %) with the

remaining being ash. The result suggest that the ash portions of these biochars may be

responsible for immobilization of Cd. Moreover, one important mechanism for the

reduction of NH4NO3 extractable Cd is the formation of poorly soluble Cd phos-

phate precipitate via specific metal ligand complexation involving phosphate functional

groups on the surface of, or released by, P-rich amendments (Chen et al. 2007; Park

et al. 2011a, b). This was well supported by the presence of high Olsen—P value (Addi-

tional file 1: Table S3) and phosphate functional group in FTIR spectra of FM, CM and

PL biochars (Additional file 1: Figure S1). Previous studies have also demonstrated that

P-bearing materials promoted heavy metal immobilization via the formation of stable

phosphate minerals in contaminated soils (Cao et al. 2003, 2009a; Uchimiya et al. 2010).

Furthermore, for soils treated with FM biochar, the reduction of NH4NO3 extractable Cd

may also be associated with surface complexion of the metal with active carboxyl, lac-

tones and carbonyl functional groups, owing to the relatively high total surface acidity of

this biochar as compared to the other biochar treatments. Uchimiya et al. (2011a) noted

a role of cation exchange capacity in reducing chemically mobile metals under biochar

amendment via the release of K, Ca, Na and Mg. This may probably occurred in soils

amended with PJ, CM and PL biochars having high CEC values (Additional file 1: Table

S3). One unusual observation is that CHB with high SSA did show significant increment

of Cd concentrations in NH4NO3 extract by 102–115 % compared to the spiked controls.

This signifies other CHB characteristics that may greatly influence the mobility of Cd

in spiked soils. High bioavailable Cd concentration in spiked soils amended with CHB

may be associated with the relatively high NH4NO3 extractable Zn and DOC from the

biochar (Additional file 1: Tables S1, S3), with both DOC and bioavailable Zn influences

the mobility and bioavailability of Cd. In agreement with our study, Smilde et al. (1992)

reported significant raise of CaCl2 extractable Cd as a consequence of Zn application in

a loam soil. Furthermore, Beesley et al. (2010) reported mobilization of Cd and Zn with

increases in DOC. In earlier study, Antoniadis and Alloway (2002) also reported that

65


DOC application raised CaCl2 extractability of Cd in sewage sludge amended soils. This

effect may be explained in terms of displacement of Cd from the exchange complex.

Effect of treatments on Cd and nutrient concentrations on lettuce

Compared to the spiked controls, all stabilization treatments did show significant reduc-

tion of Cd concentrations of lettuce plants (Table 3). In both soils, tissue Cd concen-

trations of lettuce plants grown in Cd spiked soils amended with FMB was statistically

the lowest compared to the other treatments, but CMB application induced statistically

comparable Cd concentration in PK soil. Moreover, PLB application also resulted in

noticeable (71–83 %) reduction of Cd concentrations compared to the controls. Among

the treatments, ES promoted the lowest decrease (30–64 %) in Cd concentrations. Gen-

erally, the effect of the treatments in decreasing Cd concentrations followed the order:

CMB > FMB > PLB > CHB > PJB > LI > ES in PK soil and FMB > CMB > PLB > PJB > L

I > CHB > ES in BA soil. Overall, these findings may imply that application of stabilizing

treatments, except CHB, in spiked soils have resulted in reduction of NH4NO3 extract-

able Cd which was then reflected back in the decreased concentration of the metal in

shoot of lettuce plants. These results were supported by the findings of other investi-

gators (Karami et al. 2011; Park et al. 2011a; Houben et al. 2013), who reported cor-

responding heavy metal plant concentrations reduction as a consequence of a decrease

in bioavailable metal fractions in contaminated soils treated with various amendments.

Yet, reduced Cd concentration can also be attributed to dilution effect due to increas-

ing lettuce biomass under FMB treatment. Furthermore, the reduction in Cd concentra-

tion may also be associated with the sequestration of the metal in the roots of lettuce

plants grown in Cd spiked soils amended with the stated treatments, most importantly

under CHB treatment, with only small parts being translocated to above ground bio-

mass (Moreno-Caselles et al. 2000). Yang et al. (1996) found that Cd translocation to

shoot of ryegrass was negligible, very high concentration retained in the root. Phos-

phorous concentrations were significantly elevated in lettuce plants harvested from Cd

spiked soils amended with FMB and CMB as compared to the other stabilization treat-

ments. This was in good agreement with the high available P content of these treatments

(Additional file 1: Table S3). On the contrary, all biochar treatments including FMB and

CMB promoted significant reduction of Ca concentrations compared to the spiked con-

trols. Again, with the exception of FMB, all biochar treatments also induced significant

decrease of Mg concentrations of lettuce plants grown in BA soil. Nevertheless, addition

of alkaline amendments (ES and LI) significantly increased Ca concentrations over the

other stabilizing treatments in both soils. This corresponds with the high accumulation

of Ca in lime-rich materials (Ahmad et al. 2012; Ok et al. 2011b). Among all treatments,

PJB promoted the greatest K concentrations increase in both soils (Table 3). Similar to

this observation, Chan et al. (2007) and Gaskin et al. (2010) reported very high K con-

centrations of crops grown in soils amended with plant—based biochars.

Phytoavailability of Cd for lettuce

All stabilization treatments significantly reduced phytoavailability of Cd in both

soils (Table 4). In PK soil, the greatest reduction of Cd phytoavailability for lettuce

was exhibited following PLB (88 %) and CMB (82 %) treatments. In the same soil, the

66

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Table 3 Shoot dry weight (DW), Cd and selected nutrient tissue concentrations (DW) of lettuce grown on spiked soils under different stabilization treatments

FMB CMB PLB PJB CHB ES LI CON+ l.s.d

PKa soil

Biomass (g/pot)

8.69 (0.25)ab

5.63 (0.40)b

1.83 (0.14)f

2.05 (0.08)f

3.48 (0.19)d

3.68 (0.05)d

2.79 (0.12)e

4.42 (0.24)c

0.369

Cd (mg/kg) 5.50 (0.41)f 4.65 (0.15)f 9.40 (0.72)e 15.6 (0.96)c 14.2 (1.32)d 22.7 (0.95)b 16.4 (0.40)c 32.2 (0.77)a 1.37

P (g/kg) 8.15 (0.39)a 7.38 (0.30)b 6.80 (0.29)c 5.48 (0.21)d 4.21 (0.05)e 4.10 (0.17)e 4.37 (0.20)e 5.35 (0.18)d 0.422

Ca (g/kg) 13.4 (1.18)f 14.8 (0.38)ef 20.4 (0.77)c 16.2 (1.44)d 15.9 (0.21)de 24.0 (0.63)a 22.4 (0.70)b 19.7 (0.74)c 1.457

K (g/kg) 59.6 (1.21)cd 63.1 (1.50)b 61.3 (0.88)bc 68.4 (1.64)a 59.1 (0.98)cd 58.7 (1.97)d 58.0 (2.04)d 51.6 (1.11)e 2.555

Mg (g/kg) 6.83 (0.30)ab 6.31 (0.35)b 7.29 (0.47)a 5.32 (0.14)c 4.58 (0.15)d 6.64 (0.38)b 7.24 (0.31)a 4.87 (0.18)cd 0.532

Zn (mg/kg)

BAa soil

215 (11.7)c 298 (15.9)b 505 (5.21)a 192 (11.1)d 174 (10.2)e 61.4 (4.14)f 51.6 (5.15)f 58.4 (0.76)f 16.1

Biomass (g/pot) 5.67 (0.26)a 2.41 (0.04)b 1.36 (0.05)e 1.58 (0.09)d 1.81 (0.02)c 0.98 (0.04)f 0.87 (0.03)f 0.95 (0.03)f 0.178

Cd (mg/kg) 14.4 (0.66)e 20.1 (1.88)d 21.0 (0.09)d 22.1 (1.73)cd 43.4 (2.13)b 44.6 (3.52)b 24.1 (0.35)c 125 (0.33)a 3.011

P (g/kg) 5.90 (0.17)b 6.22 (0.26)a 4.56 (0.07)c 3.48 (0.08)d 2.42 (0.15)e 1.98 (0.08)f 1.29 (0.05)g 1.80 (0.03)f 0.227

Ca (g/kg) 7.10 (0.28)f 3.56 (0.35)g 8.59 (0.94)e 7.73 (0.37)ef 12.1 (0.15)d 38.8 (1.14)a 27.7 (0.48)d 16.7 (0.71)c 1.109

K (g/kg) 38.1 (0.74)c 59.6 (1.02)b 40.0 (0.76)c 62.8 (2.20)a 35.1 (1.58)d 28.8 (0.64)e 28.8 (1.21)e 30.6 (0.81)e 2.125

Mg (g/kg) 7.75 (0.37)b 5.32 (0.36)d 6.00 (0.26)c 3.47 (0.28)f 4.23 (0.28)e 7.25 (0.10)b 13.5 (0.61)a 7.45 (0.17)b 0.579

Zn (mg/kg) 50.7 (2.26)c 54.8 (1.73)c 60.4 (2.61)c 95.7 (6.33)b 175 (0.24)a 30.5 (2.58)d 28.0 (1.43)d 53.7 (2.41)c 19.99

FMB Faecal matter (Faecal cake) biochar, CMB cow manure biochar, PLB poultry litter biochar, PJB Prosopis juliflora pods biochar, CHB Coffee husk biochar, ES Eggshell waste, LI Lime, CON+ spiked control


b Standard deviation in parentheses (n = 3), values for each soil with different letter within each row are significantly different (P < 0.05)

67


Stabilization Cd

PKa soil BAa soil

NH4NO3 extractability Phytoavailability NH4NO3 extract‑ ability

Phytoavailability

FMB 0.339 (0.023)db 0.00030 (0.000022)cb

0.187 (0.009)e 0.00054 (0.000049)b

CMB 0.696 (0.027)c 0.000166 (0.000009)d 0.494 (0.038)d 0.00032 (0.000026)c

PLB 0.655 (0.016)c 0.000011 (0.000011)e 0.206 (0.011)e 0.00019 (0.000007)d

PJB 0.713 (0.012)c 0.00020 (0.000004)d 0.940 (0.067)c 0.00023 (0.000009)d

CHB 4.67 (0.152)a 0.00031 (0.000044)c 2.81 (0.314)a 0.00052 (0.000030)b

ES 0.261 (0.016)de 0.00053 (0.000029)b 0.689 (0.031)d 0.00029 (0.000011)c

LI 0.198 (0.004)e 0.00029 (0.000011)c 0.245 (0.012)e 0.00014 (0.000006)e

CON+ 2.17 (0.029)b 0.00090 (0.000032)a 1.39 (0.073)b 0.00079 (0.000027)a

Table 4 Effects of different stabilization treatments on NH4NO3 extractability (mg/kg)

of Cd and phytoavailability for lettuce on two spiked soils

treatments

FMB faecal matter (faecal cake) biochar, CMB cow manure biochar, PLB poultry litter biochar, PJB Prosopis juliflora pods

biochar, CHB Coffee husk biochar, ES eggshell waste, LI lime, CON+ spiked control


b Standard deviation in parentheses (n = 3), values for each soil with different letter within each column are significantly

different (P < 0.05)

lowest reduction of phytoavailability of Cd to the test crop was recorded under ES (41 %)

amendment. Conversely, greatest reduction of Cd phytoavailability for lettuce was

obtained under LI (82 %) amendment in BA soil. In comparison, biochar treatments had

pronounced effect in reduction of phytoavailability of Cd for lettuce in PK than BA soil.

Although FMB promoted statistically the lowest lettuce Cd concentration, the phytoa-

vailability of the metal for lettuce under this treatment was statistically lower or simi-

lar with the other stabilization treatments. This may be explained by the fact that the

reduction of lettuce Cd concentration could be offset by the biomass increase, resulting

in small change in phytoavailability. Other study has also reported similar observation

(Cao et al. 2009b).

Conclusion

All tested stabilization treatments, except CHB, have shown great potential to stabilize

Cd in spiked soils, significantly reducing Cd concentration in NH4NO3 extract and phy-

toavailability for lettuce. However, relatively low Cd stabilization of ES, combined with

low yield and nutrient concentrations response of alkaline amendments (LI and ES),

make firm conclusion as to the use of faecal matter and manure derived biochars for

remediation of heavy metal contaminated agricultural fields very definitive.

Generally, application of faecal matter and manure derived biochars to contaminated

agricultural lands may bring multi benefits: reuse of solid waste, pathogen elimination,

and stabilize heavy metals and make the soil clean and healthy which will ensure the

normal growth of crops. Therefore, biochar can be potentially an attractive alternative

to solve heavy metal pollution problem in urban and peri-urban farming faced by the

rapid urbanization and industrialization. Nevertheless, CHB application significantly

increased NH4NO3 extractable Cd, bioavailable Cd fraction in the spiked soils. Thus,

unintended effect of some biochars may be potential drawbacks of its indiscriminate

utilization. Moreover, immobilization technology does not alter the total heavy metal

68


concentration in soil. Therefore, it is crucial to investigate the long-term effects of bio-

chars on soil Cd and other heavy metal immobilization.

Additional file

Additional file 1. Chemical composition, surface and chemical properties of faecal matter, cow manure, poultry

litter, prosopis juliflora pods, and coffee husk biochars.

Authors’ contributions DW, PD, BK and BM conceived and designed the study. DW conducted the biochar, soil and plant analysis. DW, PD, BK

and BM contributed to the analysis and interpretation of data. DW drafted the manuscript. PD, BK, BM, FI, and HG revised

the draft manuscript. All authors read and approved the final manuscript.

Author details 1 School of Natural Resources Management and Environmental Sciences, Haramaya University, 138, Dire Dawa, Ethiopia. 2 International Water Management Institute, Colombo, Sri Lanka. 3 Department of Global Health, University of Copen-

hagen, Copenhagen, Denmark. 4 Department of Soil Science/Soil Ecology, Ruhr-University Bochum, Bochum, Germany. 5 Department of Crop Science, University of Nambia, Windhoek, Namibia.

Acknowledgements This work was sponsored by International Water Management Institute (IWMI, Colombo), Blacksmith Institute and Minis-

try of Education of Ethiopia. We wish to acknowledge the support rendered by Department of Soil Science/Soil Ecology,

Ruhr-University Bochum. The biochars were produced in Akaki Basic Metals Industry, Addis Ababa, Ethiopia. We would

also like to acknowledge National Soil Testing Center for allowing us to use their glasshouse.

Competing interests All authors declare that they have no competing interests.

Received: 5 September 2015 Accepted: 16 March 2016

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71

Woldetsadik et al. Environ Syst Res (2017) 6:2

DOI 10.1186/s40068-017-0082-9

RESEAR CH

Effect of biochar derived from faecal

Open Access

matter on yield and nutrient content of lettuce (Lactuca sativa) in two contrasting soils

Desta Woldetsadik1*, Pay Drechsel2, Bernd Marschner3, Fisseha Itanna4 and Heluf Gebrekidan1

Abstract

Background: Producing biochar from faecal matter through slow pyrolysis is a farm-based, value added approach to

recycle pathogenic organic waste. Faecal matter biochar offers an interesting value proposition where the pyrolysis

process guaranties a100% pathogen elimination, as well as significant reduction in transport and storage weight and

volume. Therefore, to evaluate the effect of (1) biochar produced from dried faecal matter from household based septic

tanks, and (2) N fertilizer, as well as their interaction on yield and nutrient status of lettuce (Lactuca sativa), lettuce was

grown over two growing cycles under glasshouse on two contrasting soils amended once at the start with factorial

combination of faecal matter biochar at four rates (0, 10, 20 and 30 t ha−1) with 0, 25 and 50 kg N ha−1 in randomized

complete block design.

Results: For both soils, maximum fresh yields were recorded with biochar and combined application of biochar with

N treatments. However, the greatest biochar addition effects (with or without N) with regard to relative yield were seen in

less fertile sandy loam soil. We have also observed that faecal matter biochar application resulted in noticeable positive

residual effects on lettuce yield and tissue nutrient concentrations in the 2nd growing cycle. For both soils, most nutrients

analyzed (N, P, K, Mg, Cu and Zn) were within or marginally above optimum ranges for lettuce under biochar amendment.

Conclusions: The application of faecal matter biochar enhances yield and tissue nutrient concentrations of lettuce in

two contrasting soils, suggesting that faecal matter biochar could be used as an effective fertilizer for lettuce production

at least for two growing cycles. Moreover, the conversion of the faecal matter feedstock into charred product may offer

additional waste management benefit as it offers an additional (microbiologically safe) product compared to the more

common co-composting.

Keywords: Biochar, Faecal matter, Waste management, Lettuce, Yield, Residual effects

Background

Biochar, which is carbonized biomass, is increasingly dis-

cussed as soil ameliorant with high potential (Lehmann

and Joseph 2009). The ability of biochar to affect the

fertility, carbon storage and remediation of soil var-

ies with its characteristics (type of feedstock) as well as

the temperature for its creation (Antal and Grønli 2003;

Singh et al. 2010). As a result, some biochars may be bet-

ter suited for one or more specific purposes for example

*Correspondence: [email protected] 1 School of Natural Resources Management and Environmental Sciences,

Haramaya University, 138, Dire Dawa, Ethiopia

Full list of author information is available at the end of the article

of agronomic performance, contaminant stabilization,

or carbon sequestration (Enders et al. 2012; Abbasi and

Anwar 2015; Agegnehu et al. 2015; Inal et al. 2015; Sub-

edi et al. 2016). The application of biochar to agricul-

tural land provides several potential benefits including

enhancing the cation exchange capacity (CEC) (Glaser

et al. 2001), water holding capacity (Gaskin et al. 2007),

and improving organic carbon and nutrient contents of

soils (Glaser et al. 2002). In addition, biochar may also be

used in remediation of contaminated soil and water (Cao

et al. 2009; Cao and Harris 2010). Most investigations

on the use of biochar for soil fertility management was

inspired by the occurrence of the anthropogenic Terra

© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,

provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,

and indicate if changes were made.

72



Woldetsadik et al. Environ Syst Res (2017) 6:2 Page 2 of 12

preta soil in Latin America (Glaser et al. 2001; Lehmann

et al. 2003; Sombroek et al. 2003).

Using faecal matter as feedstock was a deliberate deci-

sion given the increasing competition for crop residues

(mulching, livestock fodder, biogas, and composting),

as well as their only seasonal availability. Using ani-

mal manure for biochar production as presented e.g. by

Uzoma et al. (2011) and Hass et al. (2012) was not con-

sidered beneficial in Ethiopian context as animal manure

is too valuable for this transformation. The use of animal

as well as human manure has a long tradition in agricul-

ture system, partly in raw form, partly after composting

to minimize microbial risks (Powell et al. 1999; Guzha

et al. 2005). The situation changed with increasing health

regulations and household connections to sewer systems

which increased the likelihood of chemical contamination

where also industrial effluent feeds into the same sewage.

However, rural and peri-urban households not connected

to sewers but local septic tanks offer a significantly safer

product (septage) for reuse than sewage sludge (Muchu-

weti et al. 2006; Singh and Agrawal 2007; Jamali et al.

2009). To address the possible stigma of fertilizer derived

from human excreta, biochar offers an interesting value

proposition where the pyrolysis process guaranties a

100% pathogen elimination, as well as significant reduc-

tion in transport and storage weight and volume (Tagoe

et al. 2008). Moreover, compared with the long treatment

process of composting the pyrolysis technology requires

only few hours (Fytili and Zabaniotou 2008). On the other

hand, the pyrolysis leads to significant losses of nitrogen

(Calderón et al. 2006; Gaskin et al. 2008). Therefore, we

were interested to study the co-application of faecal mat-

ter biochar and N fertilizer on the growth, yield and nutri-

ent status of a popular cash crop, lettuce, used in urban

farming across sub-Saharan Africa.

Methods

Soils

As the effect of biochar can vary significantly with soil

characteristics, two different textural classes were tar-

geted, a silty loam (soil 1) and sandy loam (soil 2). The

soil material was collected for greenhouse experiments at

the depth of 0–15 cm from two sites: an urban vegetable

and a peri-urban groundnut farms in Addis Ababa and

Babile, Ethiopia, respectively. Soil 1 had a long history of

irrigated urban vegetable production using polluted river

water. Soil 2 had a long history of rainfed groundnut pro-

duction. The soils were each air-dried, sieved to 2 mm,

and homogenized.

Biochar

Faecal matter was collected at 12 locations from the top

10 cm of the septage drying area of the sewage disposal

facility in Addis Ababa, Ethiopia, and mixed into one

sample. For pyrolysis, the sample was placed in alu-

minum electric furnace (Fataluminum S.p.A, Italy). The

air-inlet was covered to ensure a low oxygen condition.

The heating rate was 15 °C/min. Heat treatment was per-

formed at 450 °C. The pyrolysis temperature was main-

tained for an hour. After pyrolysis, the charred sample

was removed from the canister and allowed to cool to

room temperature.

Pot trials

Two independent pot experiments (soil 1, soil 2) were

conducted in a temperature controlled glasshouse at

National Soil Testing Centre, Addis Ababa, Ethiopia. The

layout of each trial was 4 * 3 factorial involving 4 biochar

(0, 10, 20 and 30 t ha−1) and three N fertilizer rates (0,

25 and 50 kg N ha−1) in a randomized complete block

design. For each experiment, treatments were replicated

five times. Three kg of each soil was mixed with biochar

treatments. After 2 weeks of imposition on the corre-

sponding pots, each pot was watered and allowed to settle

for 5 days. After 5 days, 6 seeds of lettuce were sown per

pot and thinned to 3 seedlings after emergence. Pots were

placed on plastic saucers to prevent leachate drainage.

Nitrogen fertilizer solution was prepared by mixing speci-

fied amount of urea with distilled water. At sowing 1/3 of

the proposed N rates were added to the matching pots

and 2/3 of the proposed rates 6 weeks after emergence.

Two weeks after harvest, a second lettuce crop was

grown in the same pots starting again with 6 seeds, con-

tinuing with 3 as described above. In the 2nd growing

season, no treatment was applied but the required agro-

nomic practices, such as weeding and watering, were

maintained.

Agronomic parameters

At maturity, 9 weeks after sowing, lettuce plants were cut

down to soil surface to determine above ground biomass

(fresh weight). Therefore, leaves were cleaned from dust

and soil particles using distilled water. Dry weight was

subsequently determined following oven drying to a con-

stant weight at 65 °C for 72 h.

Analyses

The soils and biochar samples were ground to <2 mm

for all chemical analysis but for Brunauer-Emmet-Teller

(BET) specific surface area. For total element, C, N,

NH4NO3 extractable trace elements and Fourier Trans-

form Infrared (FTIR) analyses, samples were milled with

a planetary ball mill to achieve a homogeneous fine pow-

der (Fritsch GmbH, Idar-Oberstein, Germany). Simi-

larly, the completely dried lettuce (oven drying at 65 °C

for at least 72 h) was ground, ball-milled to achieve a

73


homogeneous fine powder. The pH of biochar in water

was determined in 1:20 (w/v) ratio after occasionally

stirring over an hour (Cheng et al. 2006). The pH of the

soils in water suspensions were determined in 1:2.5 (w/v)

ratio after shaking over 2 h. The EC of the biochar was

determined after an hour equilibration of 1 g of biochar

with 20 ml of distilled water. The EC of the soil samples

were determined after 2 h equilibration of 1 g of soil with

2.5 ml of distilled water. For total element analysis, 0.25 g

samples of biochar and plant were placed into 50 ml ves-

sels, followed by addition of 10 ml concentrated HNO3.

The mixtures were left over night and then heated in

1.6 kilowatts microwave oven for 30 min. After cooling

to room temperature, 10 ml of double distilled water

were added into the vessels and filtered via 0.45 µm cel-

lulose nitrate filter papers. Finally, the filtrates were sub-

jected to the total element analysis using ICP-OES (Ciros

CCD, SPECTRO Analytical Instruments GmbH, Kleve,

Germany). Olsen-P (available P) was extracted by plac-

ing 1 g sample of soil in 20 ml of NaHCO3 for 30 min.

Similar amount of biochar samples were placed in 20 ml

of NaHCO3 for 30 min. The suspensions were vacuum

filtered via 0.45 µm cellulose nitrate filter papers and

analyzed using ICP-OES (Ciros CCD, SPECTRO Ana-

lytical Instruments GmbH, Kleve, Germany). For C and

N analyses, 3.5 mg for biochar, 5 mg for plant and 40 mg

for soil, samples were weighted into sample boats and

determined using C and N analyzer (Elementar Analyse

GmbH, Hanau, Germany). The exchangeable cations and

CEC of biochar were determined using BaCl2 method.

The exchangeable cations and CEC of soils were deter-

mined using NH4Cl method. NH4NO3 (1 M) extractable

fractions of trace nutrients and toxic elements were also

determined following the extraction procedure proposed

by the German national standard (DIN ISO 10730 2009).

Soil particle size distributions were determined by laser

diffraction using an Analysette 22 MicroTec plus (Fritsch

GmbH, Idar-Oberstein, Germany) with a wet dispersion

unit. For FTIR analyses of biochar, pellets were prepared

by mixing biochar with potassium bromide (KBr) powder

and then analyzed using a Tensor 27 FTIR Spectrometer

(Bruker optik GmbH, Ettlingen, Germany). Spectra were

collected in the range of 400–4000 cm−1 at 4 cm−1 and

120 scans per sample. Surface area of the biochar was

determined using adsorption data of the adsorption iso-

therms of N2 at −196 °C and calculated by the Brunauer-

Emmet-Teller (BET) equation (Brunauer et al. 1938).

Total surface acidity (TSA) and basicity (TSB) were

determined by Boehm titration (Boehm 1994).

Statistical analyses

An ANOVA, PROC mixed of SAS was used to test

the significance of treatment effects on above ground

biomass (fresh and dry weights) and above ground bio-

mass nutrient concentrations. Data for 1st and 2nd grow-

ing cycles were analyzed separately. Orthogonal contrast

tests compared yield and nutrient content response

of N alone treatments (25, 50 kg N ha−1) together as a

class versus control (0 t ha−1 biochar + 0 kg N ha−1),

biochar alone treatments (10, 20, 30 t ha−1) together as

a class versus control, N alone treatments together as a

class versus biochar alone treatments together as a class,

biochar with N treatments (10 t ha−1 + 25 kg N ha−1,

10 t ha−1 + 50 kg N ha−1, 20 t ha−1 + 25 kg N ha−1,

20 t ha−1 + 50 kg N ha−1, 30 t ha−1 + 25 kg N ha−1,

30 t ha−1 + 50 kg N ha−1) together as a class versus bio-

char alone treatments together as a class and biochar

with N treatments together as a class versus N alone

treatments together as a class. Pearson’s correlation coef-

ficients were used to estimate relationships between fresh

yield and tissue nutrient concentrations under increasing

biochar levels with no N. Statistical tests with p < 0.05

were considered significant for treatment/class effects.


Characterization of the soils and faecal matter biochar

While soil 1 and 2 do not differ in their clay content

(around 7–8%) they differ significantly in the silt/sand

ratio with 74/19 (soil 1) to 38/54 (soil 2). Despite same

clay content soil 1 showed significantly higher levels of

exchangeable cations is thus a result of the several times

higher carbon content of soil 1 (1.9%) compared to soil 2

(0.3%). Available P (Olsen) follows the higher carbon lev-

els of soil 1 (Table 1), and the C/N ratio of both soils is

in the same narrow range of 8–10. Compared with litera-

ture thresholds, soil 1 can be classified as moderately fer-

tile while soil 2 misses several thresholds (Tadesse 1991;

Peverill et al. 1999). The higher silt and carbon content

of soil 1 can probably be related to its location which is a

river bank of the Akaki river within Addis Ababa.

In agreement with the alkaline pH (H2O) of manure

derived biochars (Cantrell et al. 2012; Zhang et al. 2013),

the faecal matter biochar had a pH (H2O) of 8.23 (Addi-

tional file 1: Table S1). Faecal matter biochar also had

low EC value (0.34 dS/m), whereas, biochar produced

from poultry litter exhibited high EC value (Cantrell et al.

2012). These were expected considering the high ash

content in manure derived biochars (Cantrell et al. 2012;

Zhang et al. 2013; Qiu et al. 2014). Unlike the typical

feature of plant based biochars, very high concentration

of total C and very low total N concentration (Enders

et al. 2012; Qiu et al. 2014; Woldetsadik et al. 2016), fae-

cal matter biochar had very low concentration of total C

(Additional file 1: Table S1). The total P, Fe, Al, Ca and

Mg concentrations of the biochar were high (Additional

file 1: Tables S1, S2) and so the total contents of trace and

74


toxic elements. However, with the exception of Zn, total

concentration of the trace and toxic elements were below

or marginally exceed the International Biochar Initiative

(IBI) accepted upper thresholds (IBI 2014) (Additional

file 1: Table S2). According to IBI (2014), the accepted

concentration range for Cd, Co, Cr, Cu, Ni and Pb were

1.4–39, 34–100, 93–1200, 143–6000, 47–420 and 121–

300 mg/kg, respectively. The biochar had high Olsen-P

value of 1298 mg/kg (Additional file 1: Table S3). Con-

currently, Fourier Transform Infrared (FTIR) analysis

showed that the biochar had intense peak at 1038 cm−1, 3−

N treatments without biochar led to slight increases with

no significant effect, compared to the control. For both

soils, the non-significant impact of low N levels on yield

of lettuce could be partly attributed to the high demand

of leafy vegetable including lettuce for N. Furthermore,

the problem is severe in carbon depleted soil 2 having low

clay and available P contents. For soil 2, the use of min-

eral fertilizers could not be viewed as a solution due to

the limited ability of the low clay soil to retain nutrients

due to low organic matter content (Lal 2006; Kimetu et al.

2008). In agreement with the findings of this study, Huett

attributed to abundant PO4 concentration (Additional (1989) reported low yield response of various vegetable

file 1: Figure S1) (Jiang et al. 2004). Yet again, faecal mat-

ter biochar had low ammonium nitrate extractable Zn

compared to the total load (Additional file 1: Tables S2,

S3). Ammonium nitrate extractable fraction was used to

estimate the bioavailability of heavy metals in the exam-

ined biochars.

Effect of biochar application on yield

In both experiments, above ground biomass, fresh and

dry weights, of lettuce was noticeably enhanced over

the control and N-alone (P < 0.05) with the application

of both treatments: biochar alone and biochar with N

(Figs. 1, 2). The effect was most pronounced on the less

fertile soil 2 and lasted over two growing cycles (Table 2).

Similarly, greenhouse studies using different biochars

showed that biochar application, with and without N,

resulted in greater yield than the controls (Chan et al.

2007; Hossain et al. 2010). However, our results contrast

with the findings of some investigators (Blackwell et al.

2010; Van Zwieten et al. 2010; Alburquerque et al. 2013)

who found no or little response of crop yield to the sole

use of biochar over the control and fertilized treatments.

The stated difference can be partly attributed to the

nutrient content of the original feedstock and pre-exist-

ing soil nutrient status. Nutrient-rich biochars like those

produced from manure may directly supply nutrients to

crops (Rajkovich et al. 2012). On the contrary, most stud-

ies on the crop production performance of plant-based

biochars have shown that the beneficial effect of such

biochars are most evident when biochar is combined

with mineral fertilizers (Asai et al. 2009; Van Zwieten

et al. 2010; Alburquerque et al. 2013).

The highest biochar and N (30 t ha−1 with 50 kg N ha−1)

combined application resulted in the greatest (statisti-

cally) fresh yield response of lettuce plants in the 1st

growing cycle, but equaled the impact of the lower N

enrichment in the second cycle. Again, in both experi-

ments, the highest biochar rate (30 t ha−1) significantly

increased fresh yields more than the 10 t ha−1 biochar

rate and as much or more than the 20 t ha−1 biochar rate,

with 0, 25 or 50 kg N ha−1 rates, over both growing cycles.

to low N addition. Decline in yield response of lettuce to

low N was also reported by Thompson and Doerge (1996)

and Sanchez (2000). Soil 1 which is a higher river bank

soil with periodic flooding and had relatively high C and

N contents, the crop N demand is probably covered by

the soil. The possibility that high water nutrient loads

improved soil fertility as e.g., reported by Kiziloglu et al.

(2008) appeared less likely as the Akaki water is, despite

its pollution, not comparable with untreated or prelimi-

nary treated wastewater.

In the soil 1 experiment, fresh yield increased linearly

with increasing biochar application in the 1st grow-

ing cycle (Fig. 1). In both growing cycles, increasing

levels of biochar positively correlated with fresh yields

(r = 0.72, P = 0.0018 for the 1st growing cycle and

r = 0.71, P = 0.0022 for the 2nd growing cycle). Also N

fertilization increased yields, but only with increasing

biochar application rates. Lettuce plants grown in pots

amended with biochar alone class produced significantly

(P < 0.001) higher fresh yield than lettuce plants from

N alone class over both growing cycles. Likewise, let-

tuce plants from biochar with N class was significantly

(P < 0.001) heavier in fresh and dry weights than plants

from N alone and control classes (Table 2). In addition,

fresh and dry matter yields were not significantly affected

by N alone class compared to the control. In the 1st

growing cycle, it was observed that the increase in fresh

yield of lettuce plants under biochar with N class was

statistically (P < 0.001) greater than biochar alone class

(significant difference between biochar with N versus

biochar alone class). Conversely, the fresh and dry matter

yield responses were not significant in the 2nd growing

cycle (Table 2). The residual effect of N was also non-

significant in yield responses, implying that the initial N

application was either taken up, not relevant and/or lost.

In the same experiment, fresh yield was positively corre-

lated with tissue P, K, and P/Zn and negatively correlated

with N/P, Cu and Zn under increasing rates of biochar

giving correlation coefficients of 0.78***, 0.68**, 0.83***,

−0.79***, −0.81*** and −0.36 ns, respectively, in the 1st

growing cycle. In the 2nd growing cycle, fresh yield was

75

+

Wo

ldetsad

ik et a

l. Enviro

n Syst R

es (20

17

) 6:2

P

age 5

of 1

2

Table 1 Selected properties of the soils

Soil pH (H2O) EC (dS/m) Exchangeable cations (cmol(+)/kg)

CEC (cmol( )/kg) Olsen-P (ppm) Total C (g kg−1) Total N (g kg

−1) Particle size

Ca Mg K Na Al % Sand % Silt % Clay

Soil 1 6.71 0.024 24.2 6.68 0.89 0.4 <0.02 32.2 27.7 19 1.8 19.1 73.6 7.2

Soil 2 6.86 0.006 4.2 1.14 0.25 0.02 <0.02 5.83 8.05 3.2 0.4 54.1 38.2 7.5

76


Fig. 1 Shoot yield (fresh weight) of lettuce grown on soil 1 under

different biochar and N application rates. Growing cycle 1 = GC1 and

Growing cycle 2 = GC2. Values for each growing cycle with different

letter within each bar are significantly different (P < 0.05)

Fig. 2 Shoot yield (fresh weight) of lettuce grown on soil 2 under

different biochar and N application rates. Growing cycle 1 = GC1 and

Growing cycle 2 = GC2. Values for each growing cycle with different

letter within each bar are significantly different (P < 0.05)

positively correlated with tissue P, K, and Zn and nega-

tively correlated with N/P and Cu. The dilution effect

and/or pH and P-induced Cu immobilization may be

attributed to the strong negative relationship between

yield and Cu content of lettuce plants. Responses of let-

tuce to concurrent use of biochar with less N were ben-

eficial in terms of fresh yield in this soil. The correlation

results suggested that addition of extra N may maintain

detrimental yield effect.

In the 1st growing cycle of the soil 2 experiment, biochar

alone class increased fresh yield by 211% relative to N alone

class (Table 2). However, the increase was only by 45% in

soil 1. Despite the fact that increasing biochar levels sig-

nificantly correlated with fresh yield in both soils over both

growing cycles, stronger correlation was observed in soil

2 than in soil 1 (r = 0.87, P < 0.0001 for the 1st growing

cycle and r = 0.91, P < 0.0001 for the 2nd growing cycle).

These results reflect the fact that the effect of biochar

depend on the fertility status of the soil (Alburquerque et al.

2013). Contrast tests also showed that the residual effect

of biochar alone class increased yield by 172% compared

to N alone class in soil 2. Much stronger than in soil 1, the

increase in fresh and dry matter yields under biochar with

N class/treatments were statistically (P < 0.001) greater

than biochar alone class/treatments in the 1st growing

cycle (Table 2; Fig. 2). The N alone and control treatments

produced statistically similar lettuce fresh weight over

both growing cycles (Fig. 2). In first growing cycle, fresh

yield positively correlated with tissue N, P, K, Mg, and P/

Zn in response to an increase in biochar levels giving cor-

relation coefficients of 0.47 ns, 0.87***, 0.69**, 0.82***, and

0.90, respectively, while negative correlation was observed

with Cu (r = −0.93, P < 0.0001), Zn (r = −0.25, P = 0.3461)

and N/P (r = −0.87, P < 0.0001). Previous pot experiment

has shown that biochar addition at higher rates positively

correlated with yield of Radish (Chan et al. 2007). This pre-

vious study also demonstrated the increased yield of Rad-

ish with increasing levels of biochar attributed to the

increased supply of P and K, but, unlike the current study,

depicted non-significant correlation of yield with tissue Mg

concentration. The results indicated that increasing biochar

levels significantly increased fresh yield and selected tissue

macro and micro nutrient contents and their ratios (P, K,

Mg, and P/Zn) but significant negative effect was observed

for tissue Cu and N/P. Hence, the very low yield in the con-

trol and N treatments may have resulted from the reduced

availability and uptake of P, K and Mg.

For soil 2, the tissue P concentration and 1000P/Zn

ratios for N alone and control treatments were below the

optimum range of 3.5–8.0 g/kg (dry weight), and 700–

930, respectively, (Ludwick 2002; Hartz and Johnstone

2007), whereas, the N/P ratio was far above the optimum

range, suggesting P availability was limiting. The tissue

P, P/Zn (few exceed the optimum range) and N/P ratios

for biochar treatments (biochar alone and biochar with

N) were within the optimum range. On the other hand,

data obtained from soil 1 study demonstrated that the tis-

sue P concentrations for all treatments but control were

within the optimum range, despite the significant differ-

ence in yield of lettuce plants grown under the biochar

treatments compared to N alone treatments. The yield

increment could be partly attributed to the added plant

nutrients, particularly P, K and Mg and corresponding

uptake by lettuce plants under biochar application. This

result is consistent with the findings of Johnstone et al.

(2005) who reported pronounced yield response of let-

tuce to P fertilizer in soil with high available P status. This

77


Table 2 Class means and contrasts of class for fresh yield and dry matter yield of lettuce grown in Soil 1 and 2 for two

growing cycles

Class comparison Soil 1 Soil 2

Fresh yield Dry matter yield Fresh yield Dry matter yield

GC1a GC2 GC1 GC2 GC1 GC2 GC1 GC2

Classes g/pot

Control 154 123 9.5 7.4 28 30 1.8 2.0

N alone 137 128 8.2 7.7 37 32 2.4 2.3

Biochar alone 198 163 11.7 9.7 115 87 7.0 5.5

Biochar with N

Contrastsb

230 161 13.4 9.4 138 90 8.2 5.5

Control versus biochar alone *** *** *** *** *** *** *** ***

Control versus N alone ns ns ns ns ns ns ns ns

Biochar alone versus N alone *** *** *** *** *** *** *** ***

Biochar with N versus biochar alone *** ns *** ns *** ns *** ns

Biochar with N versus N alone *** *** *** *** *** *** *** ***

a GC1 = Growing Cycle I and GC 2 = Growing Cycle II

b Classes compared comprise the following treatments: control = control; biochar alone = biochar alone treatments (10, 20 and 30 t ha−1)

N alone = N alone treatments (25, 50 kg N ha−1); biochar with N = combination of the different biochar rates with the two N levels

ns, not significant (P > 0.05); * P < 0.05; ** P < 0.01; *** P < 0.001), n = 5

is further confirmed by Cleaver and Greenwood (1975)

who reported high P fertilizer requirements of lettuce

than most other vegetables across a range of soils. There-

fore, on one hand, the increased lettuce yield in biochar

amended soils may have resulted from the fertilization

effect of the biochar in both soils (Sohi et al. 2010; Liu

et al. 2012). Nevertheless, several studies have demon-

strated the positive impact of biochar on crop yield via

restoring soil organic carbon (SOC) (Lal 2004, 2010; Spo-

kas et al. 2012; Biederman and Harpole 2013). Increasing

the SOC pool of degraded soils would increase crop yields

by influencing water retention capacity, nutrient exchange

capacity and soil structure and other physical proper-

ties (Lal 2006; Steiner et al. 2007; Novak et al. 2009; Pan

et al. 2009). For example, in Kenya, Kimetu et al. (2008)

have demonstrated a low level of 3 t maize grain ha−1 at

degraded sites despite full N–P–K fertilization (120–100–

100 kg ha−1). Conversely, application of organic resources

including biochar reversed the productivity decline by

increasing yields by 57–167%. The positive impact of bio-

char on maize grain yield at degraded sites were not fully

explained by nutrient availability, suggesting restoration

of SOC as improvement factor other than plant nutri-

tion. For low SOC calcareous soil, application of 40 t ha−1

biochar promoted significant maize grain yield increase

compared to the control with an increase in the 57.8%

SOC pool (Zhang et al. 2012b). Productivity gains are

large, especially when the organic feedstock source has

high quality in terms of nutrient load (Lal 2006; Kimetu

et al. 2008). Increases in SOC concentration enhance crop

productivity in soils with a clay content lower than 20 per

cent, and in soils of sandy-loam and loamy-sand texture

(Lal 2006). Hence, on the other hand, the increased let-

tuce yield in biochar amended soils with low clay con-

tents of around 7–8% may also partly resulted from the

improvement of soil organic matter, particularly in carbon

and nitrogen depleted soil 2.

Despite the 14 weeks elapsed between lettuce plants

removed and subsequent planting of a second lettuce

crop, residual effect of biochar, with or without N, signifi-

cantly increased fresh yield of lettuce compared with the

control and both N alone treatments. Our results were

similar to those of Vaccari et al. (2011) who reported that

the yield effect of biochar did continue into a subsequent

cropping season. Other biochar studies also revealed

that crop yields were the same as or greater than con-

trols in the second cropping cycle after biochar applica-

tion (Steiner et al. 2007; Gaskin et al. 2010; Zhang et al.

2012a). Unger and Killorn (2012), however, reported

non-significant yield increase from biochar residual

effect. The difference in feedstock origin, surface oxida-

tion and CEC of biochar seem to cause varied direct and

residual effects on growth and yield of crops (Liang et al.

2006). Consequently, such a significant residual yield

increment could partly be associated with a likely marked

increase of important plant macronutrients such as P, K

and Mg and to lesser extent possible N mineralization

in the soils. Moreover, having low CEC value for soil 2,

78


the biochar could possibly enhance ability of this soil to

retain cations.

Biosolids are known to contain high total concentra-

tions of trace and toxic elements, which exist in more

pronounced concentrations in charred product (Bri-

dle and Pritchard 2004; Lu et al. 2013). One detrimental

effect of biosolid including waste derived biochar use is

the accumulation of heavy metals with concomitant

reduction of crop growth at higher application rates

(Walter et al. 2006; Singh and Agrawal 2007).

Ammonium nitrate extractable fraction was used to

estimate the bioavailability of micro-nutrient/heavy

metals in the biochar which was used as an

amendment in this study. In our case, even the highest

biochar rate (30 t ha−1) did not induce reduction of

yields, as yields were always statistically (P < 0.05)

higher than or equal to the lower biochar rates, indicating

lower phytotoxicity effect as a consequence of very

low NH4NO3 extractable heavy metal fractions

(Additional file 1: Table S3) and phyto-availability of the

metals for the test crop. However it is crucial to investi-

gate the long-term effects of the biochar on dynamics of

heavy metal in amended soils (Woldetsadik et al. 2016).

Effect of biochar application on tissue nutrient

concentrations

In both experiments, with the exception of N alone

treatments, all other biochar alone and biochar with

N treatments promoted significant (P < 0.05) tissue P

concentrations in the 1st growing cycle (Tables 3, 4). In

soil 1 experiment, all treatments but the lowest biochar

alone level (10 t ha−1) induced significant residual tissue

P concentrations compared to the control. However, the

residual tissue P contents were not significantly affected

by N alone treatments in soil 2. Contrary to the stated

observations, results of recent studies revealed that

application of biochar hardly impact P levels of crops

(Kloss et al. 2014; Reibe et al. 2015). Earlier study by

Gaskin et al. (2010) also revealed that application of pine

chip biochar did not significantly affect tissue P content

of corn crop. Due to high available P load, the biochar

used in these experiments positively influenced lettuce

P content and yield. Likewise, P-rich soil amendments

including manure-derived biochars seem to represent a

significant source of P (Chan et al. 2008; Asai et al. 2009;

Uzoma et al. 2011). This was confirmed by the strong

correlations of increasing biochar levels with tissue P

concentrations and fresh yields. Overall, the biochar

had positive impact on tissue P concentration of lettuce

plants grown on the two contrasting soils, though the

magnitude of responses were quite different. We believed

that the difference on tissue P concentration responses

over the two soils might be attributed to the obtained dif-

ference in their available P contents. The relatively less

fertile sandy loam soil (soil 2) with low available P status

was expected to respond differently to biochar applica-

tion than the silty loam (soil 1) having optimum Olsen-P

value. In soil 1, the greatest (P < 0.05) tissue concentra-

tions of P were obtained by the combined application of

20 t ha−1 biochar with 50 kg N ha−1 and 30 t ha−1 with

25 kg N ha−1 over both growing cycles. However, in soil

2, the greatest (statistically) tissue P concentration was

recorded using the highest level combination of biochar

with N (30 t ha−1 with 50 kg N ha−1) over the 1st growing

cycle.

During the 1st growing cycle of soil 1, biochar applica-

tion (with or without N) significantly increased tissue K

concentration compared to N alone and control treat-

ments (Table 3). Addition of N in soil 2 did not provide

significant increase in tissue K concentration over both

growing cycles. However, N application promoted signifi-

cant tissue K concentration in soil 1. With the exception

of the lowest biochar level (10 t ha−1), all biochar treat-

ments, with and without N, induced significant residual

tissue K concentrations in both soils. For both soils, tis-

sue K concentrations of all biochar treatments but two

biochar with N combinations in the 1st growing cycle

of soil 2 (30 t ha−1 with 50 kg N ha−1 and 20 t ha−1 with

50 kg N ha−1) were within the optimum range (Ludwick

2002). These results imply that the biochar served as a

source of K beyond one cropping cycle likewise available

P. Generally, the increase in tissue K content in response

to biochar application in this study is in conformity with

the findings of several researchers (Chan et al. 2007;

Steiner et al. 2007; Chan et al. 2008; Gaskin et al. 2010),

who were able to establish that the increase was due to

high concentration of available K in biochars. Given the

high N content with a very low C to N ratio (C/N = 9.7)

of the biochar, the tissue N content of lettuce plants under

biochar application was expected to be high. However,

biochar application, without N, did not increase tissue N

content even at the highest rate of application (30 t ha−1)

compared to N alone applications in the 1st growing cycle

of both soils, indicating that N of biochar was not available

for uptake over the short term (12 weeks). These results

contrast with the findings of Chan et al. (2008) and Tagoe

et al. (2008) who reported that biochars derived from N

rich feedstock did furnish N for plants in the 1st cropping

cycle. During the 2nd growing cycle, with the exception

of the lowest N level (25 kg N ha−1) for soil 1 and biochar

level (10 t ha−1) for soil 2, all biochar treatments induced

significant residual tissue N concentrations compared

to the controls. In both experiments contrast tests also

showed that biochar with N class produced lettuce plants

of significantly lower tissue N concentration compared to

N alone class in the 1st growing cycle (Additional file 2:

Table 4S, 5S). Conversely, biochar with N class promoted

79


0

10

20

30

61.1abc 59.3abc 56.9bc

57.3bc 62.0abc 63.4ab

58.3bc 55.1c 66.7a

59.6abc 58.1bc 61.4abc

55.4bcd 54.4bcd 47.1d

57.0bcd 58.7abc 64.2ab

55.2bcd 54.1cd 67.9a

59.0abc 59.9abc 63.2abc

Table 3 Treatment means for mineral concentrations (dry weight) of lettuce grown in soil 1 from the 1st and the 2nd grow-

ing cycles

Biochar

(t/ha)

Nitrogen Fertilizer rate (kg N/ha)

1st growing cycle 2nd growing cycle

0 25 50 0 25 50 0 25 50 0 25 50

N P N P 0 35.3c 36.9bc 42.7a 3.44d 3.43d 3.74d 23.6g 25.8efg 30.9ab 3.29g 4.25ef 4.73de

10 30.1e 39.1b 33.8cd 4.13d 6.34bc 6.57bc 26.6def 30.2abc 32.1a 3.62fg 5.13d 5.30cd

20 33.6cd 30.6e 38.6b 6.91b 6.00c 7.59a 29.1bc 28.0cde 31.9a 5.35bcd 5.93bc 7.34a

30 30.7e 27.8f 31.8de 6.89b 8.20a 6.40bc 26.7def 24.3fg 28.6bcd 5.93bc 7.52a 6.10b

K Ca K Ca 0 35.2e 39.4d 39.6d 13.8fg 13.4f 12.0fg 29.1f 35.2de 37.5cd 9.05f 10.6efg 9.98efg

10 39.4d 61.5a 53.5bc 10.3g 18.7bc 18.9bc 31.3ef 38.8cd 47.8b 8.29g 13.4d 16.3bc

20 51.3c 59.1a 58.8a 17.1cd 15.6de 19.3ab 41.1c 41.8c 52.8ab 11.5def 12.4de 17.4ab

30 60.9a 55.4b 59.2a 16.4d 16.4d 21.2a 51.1b 50.0b 56.8a 14.0cd 13.6cd 19.5a

Mg Cu Mg Cu 0 4.84f 5.14ef 5.85cde 12.5a 11.9ab 10.1cd 3.96d 4.45cd 4.59cd 10.6a 9.86abc 9.04abcd

10 5.27def 5.13ef 6.22bc 10.6bc 9.76cd 10.9bc 4.42cd 4.52cd 5.15abc 9.55abc 7.68d 9.40abcd

20 6.85ab 5.91cd 7.30a 9.77cd 9.05d 9.68cd 5.21abc 5.08bc 5.75ab 8.86abcd 8.92abcd 8.84abcd

30 6.57abc 5.16ef 6.58abc 9.03d 9.33cd 9.13d 5.51abc 4.72bcd 6.24a 8.17bcd 8.49bcd 7.95cd

Zn Zn

Cu and Zn in mg/kg; all other nutrients in g/kg

Mean of four replicates. Mean value followed by different letters in the shaded block for each variable significantly differ at the 5% level, according to the adjusted

turkey test

Table 4 Treatment means for mineral concentrations (dry weight) of lettuce grown in soil 2 from the 1st and the 2nd grow-

ing cycles

Biochar

(t/ha)

Nitrogen Fertilizer rate (kg N/ha)

1st growing cycle 2nd growing cycle

0 25 50 0 25 50 0 25 50 0 25 50

N P N P 0 24.4ef 30.2b 29.8bc 2.60e 2.47e 2.83e 22.0f 26.0cd 26.7bc 2.55e 2.77e 2.97e

10 23.4f 26.0def 27.1d 6.44bc 5.93d 6.78b 21.4f 23.3e 23.4e 5.27cd 4.88d 5.17cd

20 27.5c 27.0d 32.9a 6.78b 6.31cd 6.13cd 25.3d 26.7bc 28.6a 6.05bc 6.10bc 6.42ab

30 27.1d 30.9ab 30.7ab 6.33bc 6.50bc 7.34a 23.9e 25.3d 27.3ab 6.16bc 6.66ab 7.30a

K Ca K Ca 0 28.0d 29.4d 28.1d 10.6de 11.0cd 12.5ab 27.4c 32.0bc 30.9bc 8.73ab 8.92ab 98.54b

10 33.3c 35.2bc 36.4bc 9.45ef 11.7bc 13.2a 32.0bc 30.0bc 33.1b 8.84ab 9.54ab 10.8ab

20 45.3a 36.4bc 27.6d 12.0abc 12.0abc 12.2abc 43.0a 33.0b 34.2b 10.3ab 10.6ab 9.19ab

30 37.5b 29.0d 28.4d 9.92df 9.34f 10.1def 402a 32.4b 40.2a 9.02ab 10.5ab 11.1a

Mg Cu Mg Cu 0 4.28e 4.86de 4.96de 13.5a 11.9b 9.66cde 3.87e 4.42de 4.55cde 11.9a 11.1a 9.22b

10 5.48cd 5.50cd 7.08b 10.3c 9.16e 10.0c 4.84cde 4.88cde 5.42bcd 10.5a 8.69b 8.64b

20 5.68c 5.80c 7.89a 9.91cd 10.0c 8.92e 5.28cd 5.12cd 6.44ab 9.48b 9.69b 8.25b

30 7.39ab 5.77c 7.45ab 8.78ef 9.23de 8.06f 6.62a 5.57abc 6.51a 8.46b 10.4a 8.37b

Zn Zn 0 59.3ab 63.9a 50.8cd 57.3a 57.3a 50.6ab

10 59.4ab 61.4a 59.5ab 53.2ab 49.7abc 52.9ab 20 63.4a 53.9bc 47.1d 49.6bc 41.1de 47.2bcde 30 53.6bc 57.9ab 40.9e 48.6bcd 42.3cde 39.6e

Cu and Zn in mg/kg; all other nutrients in g/kg

Mean of four replicates. Mean value followed by different letters in the shaded block for each variable significantly differ at the 5% level, according to the adjusted

turkey test

80


significantly higher residual tissue N content over N alone

class in soil 1. The observed change in residual tissue N

concentration under biochar application could indicate

mineralization was taking place in the 2nd growing cycle.

In both experiments, biochar with and without N classes

promoted significant tissue Mg concentration compared

with the control and N alone classes over both growing

cycles (Additional file 2: Table 4S, 5S). Similarly, Uzoma

et al. (2011) reported that cow manure biochar addition

at high application rate (20 t ha−1) significantly enhanced

maize grain Mg content. The concentrations of tissue Ca

were very high under biochar with N class in both soils

over both growing cycles (Additional file 2: Table 4S, 5S).

This result was in agreement with Gaskin et al. (2010) and

Kloss et al. (2014), who reported that combined applica-

tion of biochar with N significantly increased tissue Ca

concentration of plants.

Copper, an essential micronutrient, plays an important

role in a vast number of metalloenzymes and membrane

structure (Hansch and Mendel 2009). In the 1st growing

cycle of both experiments, the tissue Cu concentrations

of lettuce plants grown under all treatments, except the

highest biochar and N fertilizer combination (30 t ha−1

with 50 kg N ha−1) on soil 2, were slightly above the opti-

mum range (Tables 3, 4) (Hartz and Johnstone 2007).

For both soils, tissue Cu concentration of biochar alone

classes were significantly smaller than the controls (Addi-

tional file 2: Table 4S, 5S). In agreement with the find-

ings of the present study, Karami et al. (2011) and Park

et al. (2011) reported that the application of biochar led

to a reduction of plant Cu concentrations compared to

the controls. However, an increase in tomato Cu con-

centration under the application of wastewater sludge

biochar was reported by Hossain et al. (2010). The addi-

tion of P-rich soil amendments reduces the mobility of

various trace elements and corresponding accumulation

in plant tissue (Cao et al. 2002; Brown et al. 2004, 2005;

Kumpiene et al. 2008; Cao et al. 2009). For example, in

tall fescue, application of high dosages of P have resulted

in low tissue Zn concentration as compared to the con-

trol treatment (Brown et al. 2004). Similar result has been

obtained for rye grass under high P application (Brown

et al. 2005). In our case, despite the high P load of faecal

matter biochar there was no discernible trend towards

a decrease in tissue Zn concentration with increased

biochar application. This was partly attributed to the

accompanied Zn load (high) of the biochar. However, the

highest biochar and N fertilizer combination (30 t ha−1

with 50 kg N ha−1) induced statistically the lowest tis-

sue Zn concentrations in soil 2 over both growing cycles.

In the same soil, the tissue Zn concentration showed a

decreasing trend with increasing biochar level only at N

fertilizer application rate of 50 kg ha−1.

Although several studies have been conducted on the

agronomic performance of various biochars (Chan et al.

2007; Asai et al. 2009; Uzoma et al. 2011), all these stud-

ies assessing the effect of biochar on crop yield and tissue

nutrient concentrations were conducted using biochars

produced from plant and manure-based feedstocks. In

the current study, human excreta, which is commonly

disposed of and causes environmental and health hazards

in developing countries, was used as a feedstock for bio-

char production and its valuable nutrients and organic

compounds were returned to soils. Therefore, it can be

inferred that higher yield and tissue nutrient concentra-

tions of lettuce plants could be highly associated with

nutrient supplying potential of the faecal matter biochar,

particularly P, K and Mg.

Conclusion

The study showed that the greatest absolute yield effects

of faecal matter biochar addition (with or without N)

were seen in moderately fertile silty loam soil than

less fertile sandy loam soil. However, the greatest bio-

char addition effects (with or without N) with regard to

relative yield were seen in less fertile sandy loam soil.

For both soils, the biochar application rates of 20 and

30 t ha−1 with 50 kg N ha−1 were found to significantly

increase above ground biomass when compared to most

treatment combinations and control. Therefore, faecal

matter biochar application at a rate of 20 t ha−1 is rec-

ommended for considerable shoot yield under the condi-

tions of these experiments. Although both biochar alone

and biochar with N classes induced significant residual

yield increase, the yield response of the two classes was

non-significant, suggesting the low residual effect of N

in yield response of lettuce. Generally, our results sug-

gest that biochar from faecal matter could be used as an

effective fertilizer to achieve high yield of lettuce in less

fertile sandy loam and moderately fertile silty loam soils.

Moreover, the conversion of the faecal matter feedstock

into charred product may offer additional waste manage-

ment benefit as it offers an additional (microbiologically

safe) product compared to the more common co-com-

posting. However, cost assessments are required to cal-

culate the net benefit of the biochar production (on farm)

and applications from farmers’ perspective.

Additional files

Additional file 1. Surface and chemical properties of faecal matter

biochar.

Additional file 2. Class means and contrasts of class for mineral concen-

trations (dry weight) of lettuce grown in soil 1 and soil 2 over two growing

cycles.

81

http://dx.doi.org/10.1186/s40068-017-0082-9

http://dx.doi.org/10.1186/s40068-017-0082-9



DW, PD and BM conceived and designed the study. DW conducted the

biochar, soil and plant analysis. DW, PD and BM contributed to the analysis

and interpretation of data. DW drafted the manuscript. DW, PD, BM, FI, and

HG revised the draft manuscript. All authors read and approved the final

manuscript.

Author details 1 School of Natural Resources Management and Environmental Sciences,

Haramaya University, 138, Dire Dawa, Ethiopia. 2 International Water Manage-

ment Institute, Colombo, Sri Lanka. 3 Department of Soil Science/Soil Ecology,

Ruhr-Universitat Bochum, Bochum, Germany. 4 Department of Crop Science,

University of Nambia, Windhoek, Namibia.

Acknowledgements

This work was supported by the WLE program led by the International Water

Management Institute (IWMI-CGIAR), the Department of Soil Science/Soil

Ecology, Ruhr-Universitat Bochum, the Urban Food Plus project of the German

Federal Ministry of Education and Research and the Ministry of Education of

Ethiopia. Biochar was produced in Akaki Basic Metals Industry, Addis Ababa,

Ethiopia. We also wish to acknowledge National Soil Testing Center for allow-

ing us to use their glasshouse and are grateful to the staff of soil laboratory in

Bochum for their assistance. We would also like to thank the two anony-

mous reviewers for their constructive comments and improvements to the

manuscript.

Competing interests


Received: 17 March 2016 Accepted: 1 January 2017

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83

7. GENERAL SUMMARY AND CONCLUSIONS

The use of low quality irrigation water for food crop production in cities of developing countries

is very prevalent and its use is beneficial for vegetable growers in terms of income generation,

household food security and livelihood strategies but the contaminated water represented a

source of environmental pollution and produce contamination. As a result of rapid urbanization

and low level of sanitation, clean water supply and waste management services, a huge volume

of wastewater is being generated and disposed of without any kind of treatment, rivers and

streams flowing across the major cities of Ethiopia serve as a sink to the huge volume of

wastewater. This is very typical of Addis Ababa, the capital, where tributaries of the Akaki

River, the main river which cross from north to south of the city, are highly polluted with

domestic as well as industrial wastes. This does not hinder irrigated farming of high value crops

along the main river.

The use of Akaki River water (polluted water) for vegetable production is a very crucial

agricultural economic sector in Addis Ababa since it sustains the livelihoods of significant

number of urban community in the city. However, this practice may pose negative impacts on

the producers, consumers and the nearby community. In changing climate, where fresh water

sources are very scarce, the issue for policy makers in Addis Ababa should be maximizing the

benefits of wastewater reuse at minimum adverse effect on public health and the environment. In

order to properly aware and train farmers on potential health risks, and mitigation approaches

and design strategies that fit within their agriculture comprising livelihood systems,

understanding of farmers’ awareness and perceptions is a key factor. The first experiment,

therefore, attempts to address farmers' perceptions towards irrigation water contamination, health

risks and health risk reduction measures.

Accordingly, the study combined individual questionnaire survey and focus group discussions

(FGDs). The quantitative data comes from a household survey conducted among 263 farmers

using Akaki river water to irrigate vegetables in four major urban farming sites. To better

understand reasons for common answers, 60 farmers interviewed in the farmers' survey were

selected for FGDs. We investigated farmers' perceptions and awareness on Akaki River water

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and irrigated produce contamination using Kruskal-Wallis H test analysis. The variation in

responses by gender, farming site, educational status and age were processed. The results shows

significant positive perception towards the water quality were made by male than female

farmers. The comparison between water and vegetable quality perceptions indicated that farmers

tended to overestimate the vegetable quality, little risk level from the water to the produce.

The descriptive results show that, farmers generally believed solid wastes (96%) and industrial

chemicals (80%) posed a greater contamination risk of Akaki River/irrigation water. Likewise,

72% and 53% farmers thought sewage from toilet and grey water are other important causes of

contamination, respectively. Moreover, farming constraints were perceived as one main effect of

water contamination. The water contamination was also perceived to increase plant pathogens

that may enhance damage to vegetable crops. One apparent observed contradiction concerning

vegetable contamination was that most farmers acknowledged problem associated with

contaminated vegetables, but at the same time only some did acknowledge effect on produce

consumers as an impact of water contamination, because they did not want to consider the effect

their produce may impose on consumers. The most common perceived health risks reported by

farmers are muscular pains, skin problems , abdominal pains, sore feet and eye burn. Among the

perceived health risks, skin problems were top-rated health risk while eye burn, sore feet and

abdominal pains were rated low across the four farming sites. The two perceived health risks

which associate with occupational health differed significantly (p<0.001) by farming sites.

Eleven WHO proposed health protection measures were presented to the farmers. Irrespective of

the farming sites and gender, health risk reduction measures generally perceived suitable were

health promotion program, cessation of irrigation before harvesting, and wearing protective

clothing while conventional wastewater treatment was generally considered to be non-suitable

risk management tool. Farmers suitability perceptions of planting non-food produce and planting

non-raw eaten crops differed significantly among the farming sites. The two crop restriction

measures perceived significantly suitable by Akaki-Addis farmers were actually exercised on

some surveyed farms of Akaki-Addis: the use of small portion of farmlands for planting non-

food produce and considerable portion for non-raw eaten crops. The difference may partly

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attributable to difference in farm size per farmer between Akaki-Addis and the other farming

sites.

Despite the opportunities of ensuring year round cultivation (except in the rainy months of July,

August and September) associated with diluted wastewater (Akaki river water) irrigation in

urban vegetable farming sites of Addis Ababa, contamination with faecal indicator organisms

still remains a potential hazard for human health. Therefore, the second experiment of the study

deals the actual evidence of faecal coliform and helminth eggs contamination of irrigation water

and lettuce produced on a representative range of Addis Ababa's urban farming sites. This study

shows that irrespective of the farming sites, almost all irrigation water samples had a poor

microbiological quality. As reflected by irrigation water quality, also the lettuce samples from all

farming sites had high faecal coliform levels exceeding recommended thresholds. Yet, the mean

helminth eggs concentration of irrigation water from most urban farming sites exceeded the

WHO guide value of < 1 egg 1000 ml-1

for unrestricted irrigation. In the present study, the

helminth eggs and larvae identified in the irrigation water comprised Ascaris lumbricoides,

Hookworm, Enterobius vermicularis, Trichuris trichiura, Taenia, Heymenolepis nana and

Strongloyides; these were shown to contaminate lettuce, implying potential parasitic infection to

consumers. A. lumbricoides was the predominant. In lettuce, 61% of the total samples were

positive for one or more helminth eggs.

This experiment does not address farmer exposure to wastewater for which universal risk

mitigation measures are well known, but focuses on potential microbial risks for consumers and

washing methods for bacterial and helminth eggs reductions. It indicated that faecal coliform and

helminth eggs contamination levels of lettuce irrigated with contaminated irrigation water is

above the threshold of safe consumption, but in a range which can be addressed through

relatively simple and low-cost mitigation measures. The WHO is promoting a multi-barrier

approach and one of these barriers can be washing of green salads at home. The results of the

washing trials revealed that all the tested washing methods reported could somehow

significantly reduce faecal coliform levels but only the vinegar based washing support 1.6 to 1.7

log10 units reduction.

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In Addis Ababa, a vast number of studies have been conducted on heavy metal contamination of

Akaki river water, irrigated soils and vegetables. Prior to this study, however, information on

health risk assessment of heavy metals via the consumption of vegetables irrigated with diluted

wastewater in urban farming sites of Addis Ababa were unavailable. Within this context the

third experiment was designed to quantify the concentrations of heavy metals in irrigation water,

soils and selected leafy vegetables on a representative range of Addis Ababa's urban vegetable

farming sites and estimate daily intake and target hazard quotient of heavy metals through

consumption of these vegetables. In Addis Ababa, after more than 50 years of diluted wastewater

irrigation, heavy metal contamination is still uncritical. However, periodic monitoring of mobile

fractions of metals, together with physico-chemical properties of soils and agricultural practices,

is required to prevent excessive uptake by vegetable crops.

The accumulation of heavy metals in the soil and subsequent translocation to vegetables can

constitutes another potential health risk for consumers. In the present study, contrary to our

working hypothesis, no risks of Cu, Cd, Cr, Co, Ni and Zn contamination of leafy vegetables

were determined most likely due to very few localized industrial activities and the dilution of

wastewater with stream water. Despite the relatively low analyzed Pb concentrations in water

and soil, marked differences were observed for Pb accumulation in the leaves of the analyzed

vegetables (Lactuca sativa var. crispa, Beta Vulgaris var. cicla and Brassica carinata A. Br.),

which exceeded 1.4-3.9 times the MPL standard of the respective crops. Since Pb is not

biodegradable, and highly immobile, once soil has become contaminated, it remains a long-term

source of dust exposure, although lead-free gasoline dominates today's market.

In this study, health risk assessment was based on EDI and THQ of heavy metals. For each

individual metal measured in the present study, none of the total EDIs exceeded its

corresponding provisional tolerable daily intakes, nor did approach the doses. The THQ values

obtained via the consumption of all analyzed leafy vegetables ranged from 0.042-0.108, 0.005-

0.014, 0.0002-0.0004, 0.048-0.078, 0.015-0.037, 0.194-0.298 and 0.026-0.037 for Cd, Co, Cr,

Cu, Ni, Pb and Zn, respectively. From these data, it is apparent that the consumption of the

examined vegetables might not expose local inhabitants to a potential short term health risk from

dietary Cd, Co, Cr, Cu, Ni, Pb and Zn. Risk assessment followed reliable and accepted

87

methodology by studying intake of heavy metals through vegetable consumption. However, in

the present study risk associated with consumption of diluted wastewater irrigated vegetables

may have been underestimated since only three leafy vegetables are considered in the

contamination assessment and vegetable intake survey. Moreover, a critical assessment of health

hazard emanating from heavy metal contamination of food crops should include determination of

heavy metal in biological human samples like urine and blood serum. Generally, the results of the

present study may serve as a starting point for future studies on health risk assessment of heavy

metals originated from consuming food stuffs.

Excessive accumulation of heavy metals in agricultural soils, which is not the case in wastewater

irrigated farming sites of Addis Ababa, may lead to elevated metal uptake by crops and thus affect

food quality and safety. Hence, high concentrations of heavy metals in agricultural products is a

major issue all over the world. Accordingly, reducing the mobility and bioavailability of heavy

metals in contaminated agricultural soils using low-cost and environmentally friendly remediation

technique is very crucial. Biochar and alkaline amendments used as immobilizing agents in

contaminated soil have profound effects on reducing metal solubility and mobility. However, little is

known about the potential human faecal matter, Prosopis juliflora pods and coffee husk biochars in

reducing the mobility and bioavailability of heavy metals in contaminated soils. In the fourth

experiment, therefore, the Cd immobilization efficacy of these and other amendments was evaluated.

The key findings of this experiment was that biochars produced by the pyrolysis of poultry litter,

Prosopis juliflora pods, cow manure and faecal matter significantly reduced the mobility and

phytoavailability of Cd in Cd-spiked silty loam and sandy loam soils. Immobilization of Cd and

other heavy metals by biochar and alkaline treatments induced by enormous mechanisms including

ion exchange, electrostatic interaction, surface complexation, precipitation of amorphous to poorly

crystalline metal phosphate minerals, substitution for Ca by Cd during co-precipitation. However, it

is not easy to quantify specific immobilization mechanism and it appears that the combined effect of

two or more mechanisms leads to metal stabilization. One unusual observation is that coffee husk

biochar with high SSA did show significant increment of Cd concentrations in NH4NO3 extract by

102-115% compared to the spiked controls. This signifies other coffee husk biochar characteristics

that may greatly influence the mobility of Cd in spiked soils. Therefore, utilization of biochars as a

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soil amendment could contribute to agricultural productivity and environmental remediation,

however it is possible for some biochars to pose adverse effects to crop production and environment

and hence need to be adequately managed.

To complement the fourth experiment the agronomic benefits of best performing amendment (faecal

matter biochar) needs to be thoroughly understood at least under glass house condition. The

agronomic values of biochar derived from faecal matter have therefore been assessed in the final

experiment of the study. In both experiments using faecal matter as feedstock was a deliberate

decision given the increasing competition for crop residues (mulching, livestock fodder, biogas, and

composting), as well as their only seasonal availability. In general, the study showed that the greatest

absolute yield effects of faecal matter biochar addition (with or without N) were seen in moderately

fertile silty loam soil than less fertile sandy loam soil. However, the greatest biochar addition effects

(with or without N) with regard to relative yield were seen in less fertile sandy loam soil. For both

soils, the biochar application rates of 20 and 30 t ha-1

with 50 kg N ha-1

were found to significantly

increase above ground biomass when compared to most treatment combinations and control.

Although both biochar alone and biochar with N classes induced significant residual yield increase,

the yield response of the two classes did not differ significantly.

Similarly, in both soils, biochar application(with or without N) significantly increased tissue P, K

and Mg concentrations compared to N alone and control treatments in the1st growing cycle. With

the exception of the lowest biochar level (10 t ha−1

), all biochar treatments, with and without N,

induced significant residual tissue P, K and Mg concentrations in both soils. The findings of the

present study demonstrate that faecal matter biochar can represent an alternative value

proposition and also emphasizes the importance of its use to increase the yield and nutrient status

of lettuce. The result may motivate urban farmers to use faecal matter based biochar to increase

yield and nutritional quality of food crops.

89

Based on the results obtained, the following conclusions have been drawn:

Farmers' perceptions on contamination, health risks and protective measures could be starting

points to initiate dialogue among farmers, researchers, consumers, local media sources and

local authorities, which could help stakeholders to focus their educational programs and

optimize the efficacy of risk reduction measures.

The study showed that water sources used by urban vegetable producers in the study area

could be sources of microbiological contamination; and could potentially put farmers and

consumers at risk.

The study indicated that faecal and helminth eggs contamination levels of lettuce

irrigated with contaminated irrigation water is above the threshold of safe consumption.

The study further revealed that there is a high potential in the study area to strengthen

health risk reduction efforts through improved vegetable washing since the majority of

households wash their vegetables before consumption. The methods used widely vary but

tap water and detergent washing are very common and often applied ineffectively.

The study has confirmed that the concentrations of metals in irrigation water and irrigated

soil (with few exceptions) were lower than the maximum permissible limits.

With the exception of Pb, the concentrations of the other metals in all analyzed

vegetables were far below the various international MPL standards.

From the health point of view, the total EDI and THQ values showed that there might be

no potential short term health risk to local inhabitants due to intake of individual metal if

one or more of the analyzed vegetables are consumed.

The findings of this study suggest that prohibition of diluted wastewater use for crop

production in the study area is not a plausible option for various compelling reasons; the

practice is livelihood for many poor farm households and vegetable sellers, and supplement

the city's vegetables demand. Well designed incentives (improved health of farmers, higher

economic returns for safer produce, and institutional supports) could encourage farmers to

reduce the risks of using untreated wastewater by adopting safer practices, while maintaining

a notable portion of the benefits that accrue to farmers, consumers and the larger community.

90

All tested stabilization treatments, except coffee husk biochar, have shown great potential

to stabilize Cd in spiked soils, significantly reducing Cd concentration in NH4NO3 extract

and phytoavailability for lettuce.

Application of faecal matter and manure derived biochars to contaminated agricultural

lands could bring multi benefits: reuse of solid waste, pathogen elimination, and stabilize

heavy metals.

Our results suggest that biochar from faecal matter could be used as an effective fertilizer

to achieve high yield of lettuce in less fertile sandy loam and moderately fertile silty loam

soils. Moreover, the conversion of the faecal matter feedstock into charred product may

offer additional waste management benefit as it offers an additional (microbiologically

safe) product compared to the more common co-composting.

This technology could be important and useful for populations in rural, peri-urban and

urban areas especially in the developing countries where mineral fertilizers are expensive

and sometime even unavailable.

Although human excreta are not generally viewed as fertilizer, the resistance for using

charred product of faecal matter as a fertilizer may be small.

The following recommendations are emerged from the present study:

Targeted training may increase awareness among urban farming community about the

potential health risk of wastewater reuse and corresponding low-cost risk mitigation

measures.

Urban vegetable producers and consumers should therefore take advantage of low-cost

risk mitigation approaches that could substantially reduce the potential health risks,

provided that the loss of economical benefits and labour demands are not critical.

The city authority should strengthen the legal status of urban and peri-urban farmers.

The city authority should design a threshold toxic level of contaminants allowed to be

discharged into city streams and rivers.

The health risk assessment values emphasize the need for further investigations of other

crops from the study sites. Still, health risk exposure of children through the consumption

91

of local vegetables should also be investigated due to their high sensitivity to metal

exposure.

It is imperative to focus on and off farm mitigation measures including proper vegetable

washing that helps reduce potential pathogenic risks. However, intermittent monitoring of

the metals from irrigation water, in soil and crops may be required to follow/prevent their

build-up in the food chain.

Immobilization technology does not alter the total heavy metal concentration in soil.

Therefore, it is crucial to investigate the long-term effects of biochars on soil Cd and

other heavy metal mobility and bioavailability.

The impact of faecal matter biochar on lettuce productivity could only be tested to some

degree through pot trials. However, the relevance to application in wide range of crop and

soil types requires more extensive in-field trials to be demonstrated.

Cost assessments are also required to calculate the net benefit of the biochar production

(on farm) and applications from farmers’ perspective.

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7. APPENDICES

93

CHAPTER 2

Compressed Survey Questions

Section A: Demographic profile and farming characteristics

I. Name: ______________________

II. Sex:________________________

III. Age: _______________________

IV. Level of Education:____________________________

V. Marital status ________________________

VI. Religion_____________________________

1. How long have you been farming? Since ___________ year

2. How did you acquire the land that you use for farming? renting ( ) allotment by sub-city

administration ( ) buying ( ) inheritance ( ) informal holding ( )

3. How do you decide what vegetable crops to grow? easily marketable ( ) fast growing ( )

consumption needs ( ) seasonal ( )

4. How often do you irrigate your leafy vegetables particularly lettuce per week in the dry season?

only once ( ) twice ( ) three times ( )

5. What kind of organic amendments/fertilizers do you apply to your farm? compost/manures ( )

mineral fertilizers ( ) none ( )

Section B: Perception and awareness of contamination

6. Do you think Akaki river water is of good quality? Yes ( ) No ( )

7. Do you wash your hands with the river/irrigation water soon after farming-related activities?

Yes ( ) No ( )

8. Do you use the river water to wash vegetables immediately after harvest? Yes ( ) No ( )

9. Do you rate vegetables harvested from your farm as clean? Yes ( ) No ( )

10. Have you heard or read about diseases/illness caused by contaminated vegetables? ( ) No ( )

11. Do you think there is a problem associated with eating vegetables particularly raw-eaten one

without washing? Yes ( ) No ( )

94

Section C: Driver and aversion

12. What do you think are the driving factors towards the use of Akaki river water for vegetable

production? only source of water ( ) rich in nutrients ( ) free of cost ( ) ease of accessibility

( ) supplement food supply ( ) increase in yield ( )

13. What do you think are the discouraging factors towards the use of Akaki river water for

vegetable production? Consumers negative attitudes ( ) religious aversions ( ) vegetable

diseases ( ) local media negative attitudes ( ) health concerns ( )

Section D: Causes and effects of contamination

14. If your answer for question # 6 is "No", what do you think are the causes of Akaki river water/

irrigation water contamination?

15. If your answer for question # 6 is "No", what do you think are the effects/impacts of Akaki

River water/irrigation water contamination?

Section E: Health risks and WHO proposed health risk reduction measures

16. If your answer for question # 6 is "No", do you think working and/or producing with polluted

Akaki river/irrigation water may have a potential effect on the health of producers and

consumers? Yes ( ) No ( )

17. If your answer for the above question is "Yes", what kind of diseases can be contracted via the

use the river/irrigation water to grow vegetables and consumption of vegetable crops grown on

soil irrigated with the river/irrigation water and rate the perceived health risks using the risk

range: 1-no risk, 2-low, 3-moderate, and 4-high?

18. How do you rate the suitability of WHO proposed health risk reduction measures? Suitability

range: 1-not suitable, 1-least, 3- moderate and 4-high

Human exposure control

Protective clothing: gloves, boots ( )

Safe sanitation and drinking water ( )

Deworming ( )

95

Immunization ( )

Health promotion programs for farmers ( )

Crop restriction measures

Planting non-food produce ( )

Planting non-raw eaten crops( )

Water application techniques

Safer irrigation methods ( )

Cessation of irrigation before harvesting ( )

Wastewater treatment

Conventional ( )

Low-cost ( )

96

CHAPTER 3 & 4

General Instructions

Dear Respondent,

This short survey is aimed at estimating the daily intake of few leafy vegetable in Addis Ababa. The answers that

you are going to provide will be kept strictly confidential and used for academic purposes only. Answering all the

questions will be highly appreciated. Estimate if you are not sure. Images of the leafy vegetables in raw and

processed form with their specified amount are available for best estimate.

Household Information

* Interviewer, establish the identity of the adult who is in charge of supervising food preparation and /or preparing

foods for the household and who is also able to answer question about the income of the household and conduct this

interview with this person.

Name of the respondent: ________________________________________________

Age: ______

Sex: □ Male □ Female

Sub-city: ________________ Woreda: _____________ Kebele: _______________

Rough estimate of household monthly income: □< 1200 □ 1201 – `12000 □> 12000

** Interviewer, consider all forms of activities if income is generated in one way or other.

Religion: □ Orthodox Christian □ Muslim □ Protestant □ Catholic □ others

Which major fasts do you fast? (only for Orthodox Christian and Catholic)

a) Fast for Hudadi or Abiye Tsome (Lent), 56 days

b) The fast preceding Christmas, 40 days

c) The fast of Assumption, 16 days

d) The fast of Wednesday and Friday

Table 1: A simple bio data of the household members

S.No Full name of all the household members

(including relatives, maids, Guards and

others if they permanently reside in the

house and eat prepared foods regularly)

Age Sex Body

weight

(Kg)

Which major fasts do you

fast? (only for Orthodox

Christian and Catholic)

1

2

3

4

5

6

7

8

9

97

Survey Questions

1. How often did your family eat lettuce salads?

□ Never (Go to question # 7)

□ 1 time per week □ 5 times per week

□ 2 times per week □ 1 time per day

□ 3 times per week □ 2 times per day

□ 4 times per week □ other (mention) _________________

2. How often did your family eat lettuce salads in fasting period (only for Orthodox Christian and

Catholic)?





3. How much lettuce salads did you prepare for single serving?

□ 200 gram

□ 300 gram

□ 400 gram

□ 500 gram

□ Other (mention) ___________

4. How much lettuce salads did you prepare for single serving during fasting period (only for

orthodox Christians and Catholic)?

□ 200 gram

□ 300 gram

□ 400 gram

□ 500 gram

□ Other (mention) ___________

5. How many of the family members eat lettuce salads?

□ 2 □ 5

□ 3 □ Other (specify) ___________

□ 4

6. Indicate the person/persons who do not eat lettuce salads ______________________________

7. How often did your family eat cooked Ethiopian kale?


98




8. How often did your family eat Ethiopian kale in fasting period (only for Orthodox Christian and

Catholic)?





9. Each time you prepared Ethiopian kale, how much did you prepare for single /double serving?

□ half bundle (approximately 256 gram (wet weight) of edible portion)

for □ single or □ double serving

□ a single bundle (approximately 512 gram (wet weight) of edible portion)


□ double bundles (approximately 1024 gram (wet weight) of edible portion)


□ triple bundles (approximately 1536 gram (wet weight) of edible portion)


□ other (specify) _______________________________________________

Remarks

Most leafy vegetables are sold in bundles in most Ethiopian markets

The current market price of a half bundle Ethiopian kale, which is approximately 256

gram of edible portion, is 4 birrs. But the raw mass of a half bundle of Ethiopian kale

is 425 gram.

10. How much Ethiopian kale did you cook for single/ double serving during fasting period (only for

Orthodox Christians and Catholic)?








99


□ other (specify) _______________________________________________

11. How many of the family members eat cooked Ethiopian kale?

□ 2 □ 5

□ 3 □ other (specify) _________________

□ 4

12. Indicate the person/persons who do not eat Ethiopian kale ______________________________

13. How often did your family eat cooked Swiss chard?





14. How often did your family eat Ethiopian kale in fasting period (only for Orthodox Christians and

Catholic)?





15. Each time you prepared Swiss chard, how much did you prepare for single /double serving?









□ other (specify) _______________________________________________

NB: The raw mass of a half bundle of Swiss chard is 523 gram.

16. How much Swiss chard did you cook for single/ double serving during fasting period (only for

Orthodox Christians and Catholic)?









□ other (specify) _______________________________________________

100

17. How many of the family members eat cooked Swiss chard?

□ 2 □ 5

□ 3 □ other (specify) ____________

□ 4

18. Indicate the person/persons who do not eat Swiss chard ______________________________

19. Briefly describe the step by step procedures you use to wash lettuce?

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

101

Images of some leafy vegetables for intake estimation

I. A single bundle of lettuce II. Edible portion of a bundle of lettuce

342 gram of fresh weight ~ processed into 150 gram of edible portion

The current price of a bundle of lettuce (I ) is 5 birrs

III. A single bundle of Ethiopian Kale IV. Edible portion of a single bundle of Ethiopian Kale

850 gram of fresh weight Ethiopian Kale ~ processed into 512 gram of edible portion

The current price of a bundle of Ethiopian Kale (III ) is 8 birrs

V. A single bundle of Swiss chard VI. Edible portion of a bundle of Swiss chard

1046 gram of fresh weight Swiss chard ~ processed into 308 gram of edible portion

The current price of a bundle of Swiss chard (V ) is 8 birrs

102

CHAPTER 5

Table S1. pH, Electrical conductivity (EC), total carbon (TC), total nitrogen (TN), total surface

acidity (TSA), total surface basicity (TBA), BET surface area (SSA), dissolved organic carbon

(DOC) of FM, CM, PL, PJ and CH biochars (average of n = 4 per char).

FMB CMB PLB PJB CHB

pH(H2O) 8.23 10.1 9.32 9.81 7.38

pH(0.01 CaCl2) 7.6 9.29 8.84 9.07 6.81

EC(dS/m) 0.34 1.45 1.46 2.48 0.13

TC(g Kg-1

) 195 296 434 659 723

TN(g Kg-1

) 20.2 13.6 54.6 24.7 7.81

TSA(mmol/g) 2.75 0.83 1.91 0.42 3.24

TSB(mmol/g) 4.98 5.79 4.74 5.37 0.88

SSA (m2/g) 3.36 58.5 1.32 0.79 206

DOC (mg/l) 5.13 16.4 121 26.4 45.2

FMB: Faecal matter (Faecal cake) biochar; CMB: Cow manure biochar; PLB: Poultry litter

biochar; PJB: Prosopis juliflora pods biochar; CHB: Coffee husk biochar

103

Table S2. Mean value for total major and trace element (selected) concentrations of the 5

biochars (n=5)

FMB CMB PLB PJB CHB

P (g kg-1

) 42.7 25.4 23.7 4.59 0.62

Al (g kg-1) 17.6 12 5.78 1.28 0.59

Fe(g kg-1) 24.4 18.6 9.79 2.87 2.73

Na (g kg-1

) 5.73 4.2 7.27 1.45 0.69

Ca (g kg-1

) 32.8 21.3 34 18 3.75

K (g kg-1

) 8.21 37.7 26.8 39.2 2.72

Mg (g kg-1

) 28.9 16.7 10.9 3.67 0.94

Zn (g kg-1

) 28.4 9.9 26.3 13.7 7.72

Cd (mg kg-1

) 1.23 0.96 0.62 <0.31 <0.31

Co (mg kg-1

) 16.4 11.2 6.25 1.41 2.05

Cr (mg kg-1

) 39.5 26.5 13.5 3.68 2.16

Cu (mg kg-1

) 214 182 101 32.3 40.1

Ni (mg kg-1

) 84.4 30 26.3 8.35 7.7

Pb (mg kg-1

) 502 295 528 214 271

104

Table S3. Olsen-P, Exchangeable cations , CEC and NH4NO3 extractable (bioavailable)

trace elements of the different biochars (n = 3)

FMB CMB PLB PJB CHB

P (mg kg-1

) 1298 1437 607 383 28.1

Ca (cmol(+) kg-1

) 6.14 1.51 8.76 4.21 4.4

K (cmol(+) kg-1

) 1.61 43.9 31 59.6 1.6

Na (cmol(+) kg-1

) 5.62 1.05 2.83 0.23 0.25

Mg (cmol(+) kg-1

) 9.82 16.8 2.67 1.91 1.66

CEC(cmol(+) kg-1

) 23.2 63.3 45.3 65.9 7.91

Zn (mg kg-1

) 12.4 165 172 1064 337

Cd (mg kg-1

) 0.01 0.005 0.004 0.008 0.007

Co (mg kg-1

) 0.022 0.017 0.02 0.012 0.011

Cr (mg kg-1

) 0.01 < 0.005 < 0.005 <0.002 <0.002

Cu (mg kg-1

) 0.067 0.204 0.04 0.007 0.006

Mn (mg kg-1

) 5.62 3.25 4 1.74 10.4

Ni (mg kg-1

) 0.032 0.027 0.017 0.06 0.021

Pb (mg kg-1

) < 0.024 < 0.025 < 0.024 1.62 <0.024

105

Figure S1. FTIR spectra of FM, CM, PL, PJ, and CH biochars

0 500 1000 1500 2000 2500 3000 3500 4000 4500

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1433

1462

1038

1038

1270

1444 1596

1584

1700

1572

1467

3466

3442

3431

3419

3419

Absorbance

wave number (cm -1 )

FM

CM

PL

CH

PJ

1441

106

CHAPTER 6

Table S1. pH, Electrical conductivity (EC), total carbon (TC), total nitrogen (TN), total surface acidity (TSA), total surface basicity (TBA), BET

surface area (SSA), dissolved organic carbon (DOC) of FM, CM, PL, PJ and CH biochars (average of n = 4 per char)

pH(H2O) pH(0.01

CaCl2)

EC(dS/m) g kg-1

mmol/g SSA (m2/g) DOC (mg/l)

TC TN TSA TSB

Faecal matter biochar 8.23 7.6 0.34 195 20.2 2.75 4.98 3.36 5.13

Table S2. Mean value for total major and trace element (selected) concentrations of faecal matter biochar (n=5)

g kg-1

mg kg-1

P Al Fe Na Ca Mg K Zn Cd Co Cr Cu Ni Pb

Faecal matter biochar 42.7 17.6 24.4 5.73 32.8 8.21 28.9 28.4 1.23 16.4 39.5 214 84.4 502

Threshold (IBI) - - - - - - - 0.42-7.4 1.4-39 34-100 93-1200 143-6000 47-420 121-300

Table S3. Olsen-P, Exchangeable cations , CEC and NH4NO3 extractable (bioavailable) trace elements of the faecal matter biochar (n

= 3)

cmol(+) kg-1

mg kg-1

Ca K Na Mg CEC P Zn Cd Co Cr Cu Mn Ni Pb

Faecal matter biochar 6.14 1.61 5.62 9.82 23.2 1298 12.4 0.010 0.022 0.010 0.067 5.62 0.032 <0.024

107

Table 4S. Class means and contrasts of class for mineral concentrations (dry weight) of lettuce grown in soil 1 over two growing cycles. Cu and

Zn in mg/kg; all other nutrients in g/kg.

N P K Ca Mg Cu Zn

Class comparison aGC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2

Classes

Control 35.3 23.6 3.44 3.29 35.2 29.1 13.8 9.05 4.84 3.96 12.5 10.6 61.1 55.4

N alone 39.8 28.4 3.58 4.49 39.5 36.3 12.7 10.3 5.5 4.52 11 10.4 58.1 50.8

Biochar alone 31.6 27.5 5.98 4.97 50.5 41.2 14.6 11.3 6.23 5.05 9.79 8.86 58.4 57.1

Biochar with N 33.6 29.2 6.85 6.22 58 48 18.4 15.4 6.05 5.24 9.51 8.55 61.1 61.3

Contrastsb

Control Vs Biochar alone *** *** *** *** *** *** ns ** *** *** *** *** ns ns

Control Vs N alone *** *** ns *** *** *** * ns ** * *** * ns ns

Biochar alone Vs N alone *** ns *** ** *** *** *** ns *** * *** ns ns **

Biochar with N Vs Biochar alone *** *** *** *** *** *** *** *** ns ns ns ns * **

Biochar with N Vs N alone *** * *** *** *** *** *** *** *** *** *** ** * ***

aGC1 = Growing Cycle I and GC 2 = Growing Cycle II

bClasses compared comprise the following treatments: control = control; biochar alone = biochar alone treatments (10 t ha

-1, 20 t ha

-1 and 30 t ha

-1);

N alone = N alone treatments (25 kg N ha-1

, 50 kg N ha-1

); biochar with N = combination of the different biochar rates with the two N levels

ns, not significant (P>0.05);*P< 0.05;**P<0.01;***P<0.001), n = 4

108

Table 5S. Class means and contrasts of class for mineral concentrations (dry weight) of lettuce grown in soil 2 over two growing cycles. Cu and Zn in

mg/kg; all other nutrients in g/kg.

Class comparison N P K Ca Mg Cu Zn aGC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2 GC1 GC2

Control 24.4 22.0 2.60 2.55 28.0 27.4 10.6 8.73 4.28 3.87 13.5 11.9 59.3 57.3

N alone 30.0 26.3 2.65 2.87 28.7 31.4 11.8 8.73 4.91 4.48 10.8 10.2 57.4 53.9

Biochar alone 26.0 23.5 6.52 5.83 38.7 38.4 10.4 9.37 6.18 5.58 9.67 9.47 58.8 50.5

Biochar with N 29.1 25.8 6.50 6.09 32.2 33.8 11.4 10.3 6.58 5.66 9.23 9.00 53.5 45.5

Contrastsb

Control Vs Biochar alone * *** *** *** *** *** ns ns *** *** *** *** ns ***

Control Vs N alone *** *** ns ns ns ** *** ns *** * *** *** ns ns

Biochar alone Vs N alone *** *** *** *** *** *** *** ns *** *** *** * ns ns

Biochar with N Vs Biochar alone *** *** ns ns *** *** *** * *** ns *** ns *** ***

Biochar with N Vs N alone * ** *** *** *** ** ns *** *** *** *** *** *** *** aGC1 = Growing Cycle I and GC 2 = Growing Cycle II

bClasses compared comprise the following treatments: control = control; biochar alone = biochar alone treatments (10 t ha

-1, 20 t ha

-1 and 30 t ha

-1);

N alone = N alone treatments (25 kg N ha-1

, 50 kg N ha-1

); biochar with N = combination of the different biochar rates with the two N levels

ns, not significant (P>0.05);*P< 0.05;**P<0.01;***P<0.001), n = 4

109

Figure S1. FTIR spectrum of faecal matter biochar

0 500 1000 1500 2000 2500 3000 3500 4000 4500

0.2

0.4

0.6

0.8

1.0

1.21038

14621467

3419

Ab

so

rba

nce

Wave length (cm-1)

110