optimisation of household slow sand filters

Optimisation ofhousehold Slow sand filters 3rd Year Research Project

Supervisor: Dr. Luiza C. Campos

Joana Valls and Philomene Rabu

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J.Valls, P.Rabu Optimisation of household SlowSand Filters 24/03/2011

Declaration and Personal Statement

The project has been carried out by Joana Valls and Philomene Rabu.

The authors have read and understood the College’s policy regarding plagiarism and the

submission of coursework. The authors confirm that, except for commonly understood ideas

and concepts, or where specific reference is made to the work of other authors, the contents of

this report are their own work. This dissertation is presented in 82 (60 without appendix) pages

including bibliography and appendices. It contains approximately 18,200 words, 36 figures

and 22 tables.

Statement by: …………………………………..:

I estimate that my contributions to the parts of the project are as follows:

Delete any of these that do not apply to your project %

literature review

theoretical development

computational work

experimental work

data analysis

report writing and production

average

Signature: …………………. Date: ………………………….

1 | P a g eUniversity College of London’11


Abstract

Waterborne diseases and lack of access to safe drinking water are still a major issue now a days.

Millions of people die each year, mostly children under 5 years old due to dehydration caused

by diarrhoea. Slow sand filtrations are easy, effective and low cost methods to provide clean

drinking water which can be implemented anywhere, mostly at a household level. Analysing the

performance of these systems and changing different variables, would help to understand their

different physical and biological processes undertook in these systems and how pollution and

changes in design parameters can affect the effluent fluid.

This assignment was chosen in order to carry out a research project joint with Engineers

Without Borders UK and to expand the knowledge on methods of treating water, one of the

main topics in the degree the authors are effectuating.

Acknowledgements

This report was written with the assistance and support of numerous individuals. First and

foremost, Dr Luiza C. Campos, supervisor and Director of the Environmental Engineering

program, for her support, help, review and assistance. Secondly, the authors would like to thank

Engineers Without Borders for their financial support and Dr Judith Zhou, Mr Ilan Adler and

Mr Ian Sturtevant, from the Environmental Engineering Laboratory of UCL, for the technical

assistance.

2 | P a g e University College of London’11


Table of Contents

Declaration and Personal Statement .............................................................................. 1

Abstract ............................................................................................................................ 2

Acknowledgements .......................................................................................................... 2

List of Abbreviations ........................................................................................................ 5

List of Units ...................................................................................................................... 6

List of Figures .................................................................................................................. 7

List of Tables .................................................................................................................... 8

List of Equations .............................................................................................................. 8

1. Slow sand filtration research project ....................................................................... 9

1.1 Introduction ................................................................................................................. 9

1.2 Objectives ................................................................................................................... 10

1.3 Simulation of the household SSF use ....................................................................... 10

2. Literature Review ................................................................................................... 11

2.1 Water Treatment ....................................................................................................... 11

2.2 History of slow sand filtration .................................................................................. 12

2.3 Features of biosand filtration tanks ......................................................................... 13 2.3.1 Advantages ........................................................................................................................... 13 2.3.2 Limitations ............................................................................................................................ 13 2.3.3 Accepted Drinking water guidelines by WHO & Environmental Agency ........................... 14 2.3.4 Biosand filter treatment according to CAWST ..................................................................... 14

2.4 How a slow sand filter works ................................................................................... 14 2.4.1 Mechanisms of filtration ....................................................................................................... 15 2.4.2 Factors affecting the tank effectiveness ................................................................................ 16

2.5 Operations, monitoring and maintenance............................................................... 16

3. Methodology ........................................................................................................... 17

3.1 Water Model .............................................................................................................. 17

3.2 Filter description ....................................................................................................... 18

3.3 Analysis and frequency of testing ............................................................................ 19

3.4 Preliminary tests ........................................................................................................ 20

3.5 Filer cleaning ............................................................................................................. 20

3.6 Maturation ................................................................................................................. 20

3.7 Testing process........................................................................................................... 21 3.7.1 pH ......................................................................................................................................... 21 3.7.2 Dissolved Oxygen................................................................................................................. 21 3.7.3 Head Loss ............................................................................................................................. 22 3.7.4 Temperature .......................................................................................................................... 22



3.7.5 Turbidity ............................................................................................................................... 22 3.7.6 UV 254 testing ...................................................................................................................... 24 3.7.7 Bacterial Testing ................................................................................................................... 25 3.7.8 Pesticide ................................................................................................................................ 28

4. Results & Discussion .............................................................................................. 31

4.1 pH ............................................................................................................................... 32

4.2 Temperature .............................................................................................................. 33

4.3 DO ............................................................................................................................... 34

4.4 Head loss .................................................................................................................... 37

4.5 Turbidity .................................................................................................................... 39

4.6 UV light ...................................................................................................................... 41

4.7 Bacteria ...................................................................................................................... 44

4.8 Pesticides .................................................................................................................... 48

4.9 Hydraulics of filtration ............................................................................................. 51

4.10 General Problems occurred ...................................................................................... 52

5. Conclusion .............................................................................................................. 53 5.1.1 Parameters ............................................................................................................................ 53 5.1.2 Bacteria ................................................................................................................................. 55 5.1.3 Pesticides .............................................................................................................................. 55

5.2.1. Where the objectives met? .................................................................................... 56 5.2.1.1. Raw water in maturation .................................................................................................. 56 5.2.1.2. Frequency of filtration ...................................................................................................... 56 5.2.1.3. The effect of detention time ............................................................................................. 57 5.2.1.4. Stagnant water variation ................................................................................................... 57 5.2.1.5. Removal of pesticides with biological mechanism .......................................................... 57

6. Future work & Recommendations ........................................................................ 58

6.1 Future work ............................................................................................................... 58

6.2 Recommendations for future .................................................................................... 58

7. References ............................................................................................................... 60

8. Glossary .................................................................................................................. 62

9. Appendix ................................................................................................................. 64 5.2.1.6. Tables of experimentation ................................................................................................ 67



List of Abbreviations

ADI – Acceptable Daily Intake

CAWST – Centre for Affordable Water and Sanitation Technology

CFU - Colony Forming Units

CO2 – Carbon dioxide

DO – Dissolved Oxygen

DCM - Dichloromethane

E.COLI - Escherichia coli

EWB – Engineers without Borders

GDP – Gross Domestic Product

GC - gas chromatography

GLAAS – Global Annual Assessment of Sanitation and drinking water

LEDCs – Less economically developed countries

MEDCs – More economically developed countries

MS - Mass spectrometry

NOx – Nitrogen oxide

NTU - Nephelometric Turbidity Units

pH – potential/power hydrogen

PPE – Personal Protective Equipment – gloves, glasses, white coat

SIR - Selected ion R

SSF – Slow sand filtration

TC – Total coliform

TNTC – Too Many To Count

UCL – University College of London

UN – United Nations

UV – Ultraviolet (light)

WHO – World Health Organisation


http://en.wikipedia.org/wiki/Dichloromethane


List of Units

Dissolved oxygen – mg/L

Turbidity – NTU

Bacteria – colonies (CFU)

Temperature - °C

Head loss – cm

UV 254 – % Light absorbed

Weight – g

Concentration – kg/m3



List of Figures

Figure 1 UNICEF report .............................................................................................................................. 9 Figure 2 Drawing from what 19th century people believed was in the "soup" (Nakamoto, 2009) ............ 12 Figure 3 Google maps satellite picture of the location of the collection point........................................... 17 Figure 4 Photograph of the two tanks used during the experimentation .................................................... 17 Figure 5 Description of Tank ..................................................................................................................... 18 Figure 6 Picture of pH sensing electrode ................................................................................................... 21 Figure 7 Turbidimeter ................................................................................................................................ 23 Figure 8 Computer used for measuring UV 254 ........................................................................................ 24 Figure 9 Autoclaving .................................................................................................................................. 26 Figure 10 Pesticide testing process ............................................................................................................ 30 Figure 11 Changes in pH in Seeded tank ................................................................................................... 32 Figure 12 Changes in pH in Unseeded tank ............................................................................................... 32 Figure 13 Changes in Temperature in Seeded tank ................................................................................... 33 Figure 14 Changes in Temperature in Unseeded Tank .............................................................................. 33 Figure 15 Dissolved oxygen dependence on Temperature ......................................................................... 34 Figure 16 Change in DO between Regents Park water and filtered .......................................................... 35 Figure 17 Change in DO in seeded tank .................................................................................................... 36 Figure 18 Change in DO over Seeded Tank ............................................................................................... 36 Figure 19 Head Loss change over seeded tank .......................................................................................... 37 Figure 20 Head loss change over Unseeded Tank ..................................................................................... 38 Figure 21 Development of second biofilm in unseeded tank ...................................................................... 39 Figure 22 Change in turbidity over time .................................................................................................... 39 Figure 23 Change of turbidity over time in the Unseeded tank .................................................................. 40 Figure 24 Change in turbidity over time in seeded tank ............................................................................ 40 Figure 25 Change in Light Absorbed by UV 254 Method over time .......................................................... 42 Figure 26 Change in Light Absorbed by UV 254 Method over time in unseeded tank .............................. 42 Figure 27 Change in Light Absorbed by UV 254 Method over time in seeded tank .................................. 43 Figure 28 Percentage of total coliform removed from water over time in unseeded tank ......................... 44 Figure 29 Percentage of total coliform removed from water over time in seeded tank ............................. 44 Figure 30 Percentage E.coli removal over time ......................................................................................... 45 Figure 31 E.coli removal over 2 weeks after ‘24h’ .................................................................................... 46 Figure 32 % E.coli removal over time in seeded tank ................................................................................ 47 Figure 33 Percentage E.coli removal over time in unseeded tank ............................................................. 47 Figure 34 Average Pesticide concentrations during GCMS run ................................................................ 49 Figure 35 % removal of Metaldehyde in second run GCMS ...................................................................... 49



List of Tables

Table 1 Total volume and source of water used during the experiments so far ......................................... 18 Table 2 Change in variables ....................................................................................................................... 19 Table 3 Water residence time in the filter and time of sampling ................................................................ 19 Table 4 Water residence time in the filter and time of sampling ................................................................ 19 Table 5 Identification of each sample in graphs ........................................................................................ 31 Table 6 Average values of UV 254 ............................................................................................................. 43 Table 7 Mean values for E.coli removal *Excluding all possible errors, i.e. % rates under 50. ............... 45 Table 8 Percentage removal of Metaldehyde in first run GCMS ............................................................... 49 Table 9 Percentage removal of Metaldehyde in second run GCMS ........................................................... 50 Table 10 Health Effects of Methaldehyde (INCHEM, 1996) ...................................................................... 50 Table 11 Dimension parameters of tanks ................................................................................................... 51 Table 12 Parameters used to calculate resistance ..................................................................................... 51 Table 13 Resistance, H ............................................................................................................................... 51 Table 14 Average values for all the parameters measured everyday ......................................................... 54 Table 15 E.coli & Total coliform removal ................................................................................................. 67 Table 16 Dissolved oxygen ......................................................................................................................... 71 Table 17 UV 254......................................................................................................................................... 72 Table 18 pH ................................................................................................................................................ 73 Table 19 Head loss ..................................................................................................................................... 74 Table 20 Temperature change .................................................................................................................... 75 Table 21 Pesticides first run ................................................................................................................... 64-0 Table 22 Pesticides second run .............................................................................................................. 64-0 Table 23 Pesticides ................................................................................................................................. 65-0

List of Equations

Equation 1 pH ............................................................................................................................................ 21 Equation 2 Photosynthesis ......................................................................................................................... 21 Equation 3 Calculate % removal................................................................................................................ 25 Equation 4 Used to calculate Resistance.................................................................................................... 51



1. Slow sand filtration research project

1.1 Introduction Diarrhoea is the second leading contributor to global burden disease, mostly children under 5

years (Figure 1). Unclean unsafe water is the main cause of this disease in regions lacking of

access to treated water supply. In order to solve this situation in developing countries, measures

such as a household biosand filters or Slow sand filtration (SSF) can be used to improve the

quality of water. Using appropriate technology is essential to achieve sustainable development

in Less economically developed countries (LEDCs) and factors such as culture, economic

situation and religion are of major importance in this areas.

Figure 1 UNICEF report

The quality of drinking-water is a powerful environmental determinant of health. Water is

essential to life, everyone should have access to safe and clean water. Preventing the spread of

diseases and reducing the risks of getting waterborne diseases in less economically developed

countries is the reason why this project was chosen. UCL engineering students are required to

work on a research project in pairs in third year. Thus to make the best use of this opportunity,

doing a project in collaboration with Engineers Without Borders (EWB) was more appealing

than any of the proposed options by the University, as it potentially could benefit a community

overseas.



The initial idea was to conduct a project where SSF to provide clean safe water to the

inhabitants of a village in Ecuador, but due to several circumstances, this project had to be

changed. The second option was proposed by our supervisor was to continue the work done by

Outhwaite (2010), also a project supported by EWB UK. By using two household SSF tanks

(one seeded and another one un-seeded), he analyzed the effects of filtering raw water from

Regent’s Park in order to implement these tanks in the future in a South American country.

Following his recommendations on how to make the tank more efficient and testing more in

depth the different parameters, it was decided to carry on with his investigation with the

financial support of EWB UK.

1.2 Objectives The objective of this work was to evaluate the performance of the household slow sand filters to

remove pesticides. The specific objectives were:

- To evaluate the effect of the raw water on the maturation period of the filter

- To determine the effect of filtration frequency on efficiency removal

- To evaluate the effect of the detention time of water on removal

- To assess the effect of the depth of the minimum level of water above the filter

- To correlate the removal of pesticides with biological mechanisms

1.3 Simulation of the household SSF use The project aimed to simulate a real case scenario where a family in a Less Economically

developed country (LEDC) uses a household SSF (same as the ones from our research) to

acquire safe water for drinking and household purposes. Due to time limitation, the water

treatment was assumed to take place only few times a week, simulating the case of when family

leave the house for a day or few days.



2. Literature Review

2.1 Water Treatment The advances of now a days technology provide good quality water from most sources,

although the economic factor limits a large amount of people to access clean and safe drinking

water.

In 2008, over 2.6 billion people were living without access to improved sanitation facilities and

nearly 900 million weren’t receiving safe drinking water (GLAAS, 2010). Everyday their life

and health is affected by contaminated water; they are missing on a basic human right.

Diarrhoea is the second leading contributor to global burden of disease, 2.5 billion cases occur

in children under 5 and every year about 1.5 million die from it (WHO & UNICEF, 2000). Poor

sanitation and water leads to different illnesses, which keeps children from school and parents

from work. Improving drinking water and sanitation could reduce nearly 90% of the diarrhoeal

cases and death of children to 2.2 million (WHO, 2010). This would lead to a reduction of costs

in health care and gain in GDP by bringing very large economic returns. Another result from

drinking this water is vulnerability of children, which may be already sick from other diseases

or unnourished. This at the same time leads to low life expectancy, low level of working

population, high dependency rates and a bad economic situation. In order to solve this situation

in LEDCs, using appropriate technology is essential.

Household SSF are simple economically feasible systems to improve sanitation and drinking

water in these areas. Improving the quality of the water would decrease death level rates as well

as to improve the quality of life of people and progress.

Providing clean and safe water is one of the Millennium Goals set in 2000 by the United Nation

(UN) together with providing primary education, sustainable scalable & repeatable incentives

and providing knowledge and skills. It is also the first step towards sustainable communication

and end of poverty.

In order to obtain cheap efficient treatment for safe water, different factors had to be considered

as well as the usage of appropriate technology, depending on where the plant could be

implemented. Other factors to take into consideration;

• Future demand • Social, economic & political situation. • Potential hazards • Type of soil

• Source of water • The effects of improving the water i.e.

population growth and thus greater requirements from the members of the population


2.2 History of slow sand filtration (Nakamoto, 2009 & CAWST, 2010)

Water began to be treated on 1804, when John Gibb designed and built an experimental slow

sand filter in Scotland.

On 1829, James Simpson improved the method of Gibb and installed it to treat the water

supplied by the Chelsea Water Company in London. In 1852, all the water from the River

Thames was delivered to the inhabitants of the capital after being treated with slow sand.

As a result of the industrial Revolution and the invention of the steam engine, the population of

most major cities increased. This led to the degradation of the quality of the water of the River

Thames that provided water to everyone in the city. This water started being called ‘monsters

soup’(Figure 2.1) due to the high amount of different bacteria and other living organisms

moving in the water seen using a microscope. At the same time, cholera spread out.

By the end of the 19th century, John Snow found out that this disease was transmitted and

caused by the low quality of water that the citizen of London were drinking. By filtrating this

water, the ‘materies morbi’ (material transmitting infections) and other solids were removed.

Throughout the years, scientists discovered and examined more in depth bacteria, developing

new methods to get rid of them and to control the amounts of these within water.

During the last 19th Century slow sand filters were widespread and introduced in Europe leading

to a significant change in drinking water quality and reduction of waterborne diseases and

transmission. No coagulants or disinfectants were used at the time to achieve better results,

although the physical processes were observed, but not completely understood, even now a days

the biological interactions within this filters still lack of comprehension (Graham &

Collins,1996).

Figure 2 Drawing from what 19th century people believed was in the "soup" (Nakamoto, 2009)

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2.3 Features of biosand filtration tanks

Slow sand filters are gravity tanks; open box tanks drained at the bottom and partly filled every

time they are used to filter water. Raw water or mixed is allowed through spaces between each

sand grain and flows downwards. The treated water is discharged through the outlet piping

system controlled by a valve. Suspended solids and colloidal matter are deposited at the top of

the bed where a bio layer is formed which does not require frequent cleaning. A depth of 1/2 cm

of sand needs to be removed after several months or weeks to achieve good results in effluent

water once again.

2.3.1 Advantages

The advantages of using a slow sand filter to purify water are mainly the improvement in

quality of the effluent water discharged; decreased in turbidity, particles and removal of odours

and smells within raw water.

It is a simple and easy to build system, which does not require any specific skills. Monitoring

and operations are not complicated either. Daily tasks include reading and recording head loss,

turbidity, pH and temperatures.

Another advantage from SSF, is that this method does not necessitate constant supervisor and

materials (sand, gravel and concrete) for its fabrication can be found locally. If the user is scared

about the tank contamination, a lid can be place which won’t affect the efficacy of the treatment

system, but will prevent external contamination if the tanks are placed outside.

A SSF combines chemical, biological and physical processes to improve the quality of water.

2.3.2 Limitations

1. “Continuous” filtration; tank needs water to go through to keep biological activity

active – pauses of more than 48h will reduce the effectiveness of the system.

2. Initial costs

3. Water with fine clays not easily treated

4. Less effective on removing particles within cold temperatures (lower bed activity)

5. Algae may interfere with results

6. Severe and sudden changes in quality due to temperature changes, toxic industrial

waste, etc



2.3.3 Accepted Drinking water guidelines by WHO & Environmental Agency

• Turbidity <1 NTU

• Coliforms 1-3 log units

• Biodegradable Dissolved organic carbon 50%

• Dissolved organic carbon 15-25%

• Heavy metals; Zu, Cu, Cd, Pb (95-99%) Fe, Mn (>67%) As (<47%)

• Bacteria 90-99%

• pH: 6.5-9.5

2.3.4 Biosand filter treatment according to CAWST

• Bacteria up to 96.5%

• Viruses 70-99%

• Protozoa 99%

• Helminths up to 100%

• Turbidity 95% or <1NTU

2.4 How a slow sand filter works

A slow sand filtration is a biological treatment process which uses fine grain and a flow rate of

between 0.1-0.4m/L to filtrate water (MWH, 2005). The fine media and low filtration rates

encourage the capture of large particulate matter (e.g. algae) and the development of a straining

layer called schmutzdecke. Head loss, the biofilm growth and filtering of particles takes place

within the first 20-30mm of the sand media (Graham and Collins,1996). This is a filter skin that

traps some organisms before the water continues its way through the sand. It is intensely active

and threats different sorts of life such as plankton, protozoa, diatoms or bacteria. Dead algae and

bacteria are consumed and processed into simple salts. At the same time, nitrogen and other

chemical nutrients are broken down and oxidized, colour and odour are removed and suspended

particles are strained out (WHO, 2008)

A sample of water enters the tank passing through a diffuser of approximately 5 mm allowing

the water to go to the inlet reservoir zone. If the valves are open, filtering takes place allowing

water to go through the granular media where the biolayer has developed. After passing through

the schmutzdecke, the water enters the filtering sand layer. Here, absorption takes place from

electrical forces, chemical bonding and mass attraction. Flow rate decreases in this medium due

to the small pores and sedimentation takes place on the nearest grain. This layer holds most of

the ‘food’ necessary for bacteria and biolayer to stay alive (WHO, 2008).



The flow throughout the layer is laminar and constantly changing direction due to the

interaction between sand grains. Each time the water enters a new pore in between the sand

grains, it slows down resulting in sedimentation basins near the sand grains and bacteria and

viruses are brought into contact with surface of sand to which they attach resulting in coated and

sticky surfaces similar to the schmutzdecke but without algae and same particles.

After going through the granular media, water goes through a fine and coarse layer of gravel,

where sand is filtered and settlement of the left over bacteria takes place.

2.4.1 Mechanisms of filtration

Biological filtration is accomplished by passing raw water through a bed of sand where

particulate impurities are brought into contact with the surface of the grains and held in position

there. Inert material is retained until eventually removed when the filter is cleaned (ripening).

The processes that take place within the SSF can be separated into transport mechanisms,

attachment and purification (Huismans and Wood, 1974).

During the transport mechanism, the particles are brought into contact with the sand grains by

screening, sedimentation, mass attraction, several forces and diffusion. Sedimentation is the

process where large particles are retained by the diffuser and the granular media. The formation

of the schmuztdecke increases the efficiency of screening of the bed enhancing the deposition in

the grains that gradually affects the resistance within the pores indicating that the cleaning of the

bed has to take place. Sedimentation refers to the action within the pores where suspended

matter is deposited in the bottom of the layer. Inertia and centrifugal forces act on the particles

at a specific gravity which results in these leaving the water.

The second mechanism is attachment, where electrostatic forces and mass attraction takes place

attaching the particles to the grains. The most important process of these mechanism is the

adhesion that is originated within the upper surface of the granular media where a bed of

bacteria and other organisms is formed, the so called schmuztdecke; gelatinous sticky film

which acts as a filter. Purification takes place in a series of biological process. Dissimilation is

the process where bacteria oxidize part of the food (dead matter) to provide energy for the

metabolism of bacteria which assimilates these for growth purposes and converting dead

substance into living ones. Another process is mineralization, where raw water degrades organic

matter to produce sulphates, nitrates and phosphates which could later on be discharged in the

effluent water. 20-30mm under the surface (Graham & Collins, 1996), food becomes scarcer

and hardly any organisms are found, microbial degradation occurs and amino acids are turned

into ammonia, nitrites and nitrates and finally oxidation occurs decreasing the numbers of

coliforms found in the water.



2.4.2 Factors affecting the tank effectiveness

• Temperature; Low temperatures decrease the level of effectiveness of the tank as well

as decreasing the level of activity within it thus increasing the rate of survival of

bacteria entering the surface.

• Retention time

• Sand size and head – better with fine and low head

• Volume of water inserted

• Turbidity and quality of raw water

• Flow rate of water filtered

• Water level above tank

• Outlet pipe system performance

• Frequency of filtration

• Algae

o Photosynthesis reduces growth and increases oxygen contend

o Change in DO entering and exiting

o Affect supernatant water and require supervision

o Reduces chances of survival of bacteria

o Contributes to schmuzdecke formation

o Requires more cleaning

2.5 Operations, monitoring and maintenance SSFs do not require continuous cleaning. Measuring head loss, bacteria and other parameters

proving that the quality of water is not improving after being filtered would permit to know

when the tanks need to be cleaned .

Cleaning takes place depending on the raw water’s quality that can be every two weeks or even

yearly. This can be done by scrapping the upper layer of filter bed, about 1/2cm of it. There are

four ways in which cleaning of a SSF can be done;

1. Using a geo-textile material on the top layer

2. Chlorinating

3. Wet harrowing – lowering water to just above the schmutzdecke, stiming the sand and

suspending any solids held in that layer and throwing the water to waste. This is the

faster way.

4. Dry harrowing – scrapping the top layer, water is inserted back and new schmutzdecke

is formed.



3. Methodology

3.1 Water Model

Initially 50L of Regents Park lake (Figure 3) water was collected and filtered in the filters

(Figure 4) once a week during 2 weeks. After this period, 24 L of Regents Park water was

collected and mixed with either rainwater or filtered water (water recycled from the filters) once

a week for a period of 3 weeks. Table 1 shows the total amount and source of water used as

influent to the household filters during maturation and normal operation. Table 1 describes the

variables that are being investigated.

Figure 3 Google maps satellite picture of the location of the collection point

Figure 4 Photograph of the two tanks used during the experimentation

Unseeded Filter Seeded Filter

Collection point



50mm of fine g 50mm of coarse g

Table 1 Total volume and source of water used during the experiments so far

Date Regents Park Rainwater Recycled water

Maturation test 15/11/10 – 30/11/10 24L 24L

Filtration tests 15/11/10 – 30/11/10 24L 24L

1/12/10 - 17/12/10 24L 24L

10/01/11 – 01/03/2011 24L 24L

3.2 Filter description Following the recommendations of the CAWST 2009 Biosand Filter Manual, the two biosand

filters used were constructed to the dimensions of approximately 900mm tall and 300mm wide,

in order for it to be used in a normal household. The manual recommended the filter should be

constructed with either with concrete or plastic. In this particular case, to allow easier inspection

of the sand layers and the biolayer, the filters were constructed from Perspex plastic. The layers

of sand used were made up of 50mm of deep coarse gravel, 50 mm deep fine gravel, and

400mm deep fine sand (Figure 5). The deep fine sand layer was installed already wet into a bit

of water to prevent any air bubbles forming. The type of sand used is RH45 sand from WBB

Minerals’ quarry in Redhill, Surrey.

50mm stagnant water - keeps sand wet while letting oxygen pass to biolayer

400mm Sand bed – biological activity on the top and non-bio activity on the rest where there’s

Diffuser - prevents disturbing and protects biolayer

Valve controlling flow

Inlet reservoir zone – where water was poured

Membrane to stop gravel

Figure 5 Description of Tank



3.3 Analysis and frequency of testing 24L were filtered every day to simulate the usage of the tanks by a family; this would provide

enough water for the family to drink and cook every day. Water was collected after pouring

after 10 minutes and 1h30min for analysis of several parameters (see sections 3.7 onwards for

more details on these). The water collected after 10 minutes represented the water poured in the

filter on the day before, in the case of Mondays after 96h and Thursdays after 48h. This allowed

to investigate the effects of water residence time on the quality of water (Table 2).

Table 2 Change in variables

Weeks Variables

Stagnant water on top of sand Pesticide removal

Week 20 to 21 10 cm None

Week 22 to 24 5cm None

Week 25 to 29 5 cm 10mg

Table 3 Water residence time in the filter and time of sampling

Sampling time after adding the water to the

filters at each filtration

10 min 45 min

Water residence time 1 week 45min

Sample representation Previous filtration Current filtration

A flow rate of 0.267 L/min based on the dye tests previously carried out by Outhwaite (2010).

Flow rate was monitored by the use of stopwatch and measuring cylinder. Water samples (Table

3) were taken based on the residence times determined by Outhwaite (2010).

Table 4 Water residence time in the filter and time of sampling

Day of filtration in the week

Monday Tuesday Thursday

Sampling time after

adding the water to the

filters at each filtration

10 min 45 min 10 min 45 min 10 min 45 min

Water residence time 72 hours 45 min 24 hours 45 min 48 hours 45 min

Sample representation Previous

filtration

Current

filtration

Previous

filtration

Current

filtration

Previous

filtration

Current

filtration



3.4 Preliminary tests

A series of tests were initially conducted to determine the amount of bacteria in the raw water in

order to find out if bacteria inoculation would be necessary, and to implement the methodology

for bacteria determination..

Two litres of raw water of Regent’s Park were collected three times a week to count the amount

of bacteria to determine the appropriate dissolution to be carried out later on. A mix of 100mL

of raw and de-ionized water was used following the E.coli testing method (HACH, 2010). For

good results, the range had to be between 20 to 80 colonies (HACH, 2010). After mixing 5mL,

7.5mL, 10mL and 20mL of raw water with distilled water, it was concluded that the best mixing

was using 10 mL of raw water model with 90mL of distilled water. For the filtered water, it was

used 20mL filtered seeded and unseeded effluent water and 80mL of distilled

3.5 Filer cleaning

Cleaning of the tank was done by removing one or two cm of the surface layer of the sand bed

after drying out as much as possible the system and getting rid of the stagnant water above the

sand.

3.6 Maturation

Recently cleaned biosand filters do not effectively remove bacteria, in order for these to do so, a

period of ripening is needed. This term refers to the necessary time for the biological

community or biofilm to mature i.e. reach the optimum particle and bacteria removal (90-99%)

and the development of the . This can take up to 30 days (CAWST, 2010) depending on the

amount of contaminants, bacteria and particles in the water. It is important to allow this process

to take place in order to obtain the optimum results during our experimentation. As shown in

Table 1 in section 3.1, it took 15 days for the two tanks to obtain good results and develop a

‘dirty’ layer, i.e. a schmutzdecke.



3.7 Testing process

3.7.1 pH

Water in the environment contains a series of inorganic and organic ionic dissolved constituents

and comopounds, colloidal and suspended particles and gases. Several chemically related

measures can be undertaken to indicate the properties of water supply such as measuring the

hydrogen ion concentration, i.e. pH. This measures acid base properties of a solution (Eq. 1).

Equation 1 pH

pH=-log10[H+] (MWH, 2005)

In the beginning of the experimentation, this parameter was measured

with pH papers and indicator solutions which change colour varying

from red to purple. These need to be compared to compared to the

colour of a blank paper or using a solution established by the

standards. During the second semester, pH was measured using a

HANNA pH sensing electrode (Figure 6), HI 9812, calibrated with

distilled water which provided more accurate results.

3.7.2 Dissolved Oxygen

Dissolved oxygen refers to the amount of oxygen dissolved by aeration and photosynthesis

(Equation 2) of plants in water, essential for aquatic organisms and affects the odour, taste and

clarity of the fluid.

Equation 2 Photosynthesis

CO2+H2OO2+C6H12O6

Carbon dioxide+WaterOxygen+Glucose

This can be measured as a percentage of mass over volume (mg/L). DO content of water

depends on the source, raw water temperature, treatment and chemical or biological processes

through which water have to go through. By measuring DO, the aggregate amount of organic

material in the fluid can be quantified (Nazaroff, 2004).

This was measured using a Jenway DO meter calibrated with de-ionized water.

Figure 6 Picture of pH sensing electrode



3.7.3 Head Loss

Slow sand filters can operate during a long time but it is required to carry on continuous checks

of to monitor the performance and quality of effluent water to be aware of when the filter needs

to be cleaned. Head loss aids to determine when the tank is clogged, i.e. cleaning of system is

required, when the levels are too high.

Head loss is the difference in height between the water level inside the tank above the sand bed

and the water in the see-through tube to the right hand side of both tanks. This parameter was

measured every time water was poured in the tank and after 45 minutes of the first filtration

took place.

3.7.4 Temperature

Temperature was measured using a mercury thermometer during the first half of the

experimentation and then with a Jenway DO meter, providing more precise values and easing

the recordings in the park.

3.7.5 Turbidity

Turbidity refers to the level of cloudiness of the fluid which is caused by the presence of

suspended particles that reduce the clarity of the water, some invisible to human eyesight.

Government has set standards no more than 1 NTU is allowed on any drinking water to impede

any gastrointestinal diseases. Turbidity is caused by phytoplankton, disturbed land by

construction, industries or runoffs, rainwater or other contamination produced by humans or

animals.

“An expression of the optical property that causes light to be scattered and absorbed rather than

transmitted with no change in direction or flux level through the sample” (Standard Methods,

2005)

Measurements require a light source and a sensor, located at 90°C to the light source, to

measure the scattered light (MWH, 2005). Turbidity is expressed in nephelometric turbidity

units (NTU) and increases with scattered light and decreases as numbers of particles increases

above a certain amount of scattered light taking place which increases incident light.



Method of testing turbidity:

Figure 7 Turbidimeter

Equipment for testing:

• Sample

• Standard solution glass bottle for calibration (18, 180 or 1800NTU)

• Pipette

• Empty small glass to put raw water.

• Beaker

• Turbidimeter (Figure 7)

Process of testing:

1. Pour sample into an empty glass to test.

2. Turn the turbidimeter on (see Figure 7)

3. Shake standard solution before inserting it into the apparatus

4. Calibrate for a few seconds with either 18 or 180NTU standards – if the level of NTU is

below 18NTU carry experiment with this standard, if its above switch to 180.

5. Shake sample and place it inside the apparatus for testing.

6. Rapid readings to impede the sedimentation of particles and improve accuracy



3.7.6 UV 254 testing

The UV light was carried out to measure the amount of light that can go through the sample of

water – thus quantifying the amount of contaminants, organic compounds and water UV light

absorbed by the water.

The absorbance of a solution is a measure of the amount of light absorbed by the constituents of

the sample solution at a specific wavelength, set at 254 typically for water testing procedures.

According to Beer Lambert Law, the amount of light absorbed by water is proportional to the

concentration of molecules and the path length the light takes in passing through water (width

of cuvette, 1cm). De-ionized water is used as a reference in the method before measuring the

samples. In order to test the absorbance of UV 254 light through the sample a

spectrophotometer is used calibrated, as mentioned before, with de-ionised water.

Equipment needed for testing:

• Spectrophotometer controlled by computer (Figure 8)

• Cuvette

• Small measuring cylinder

• Paper to dry cuvette sides

• Computer

• Beaker of de-ionised water

• Pipette Figure 8 Computer used for measuring UV 254

Process of testing:

1. Pre warm the machine for 30 minutes before using.

2. Fix the wavelength on the computer at 254 on the computer (Figure 8).

3. Set the machine to zero by inserting a cuvette with de-ionised water inside the machine.

4. The cuvette should be filled carefully to the top with a sterilized pipette and the

transparent sides should be dried to let the light through when in the machine. Only the

translucent sides are to be held with hands. The side with a narrow should face the door

of the laboratory.

5. After 30 seconds, record readings and place inside the machine another cuvette with the

sample to record the amount of UV 254.

6. Switch off machine when all testing is done.



3.7.7 Bacterial Testing

Water can easily spread diseases as it is exposed to most of the World’s population. Depending

on the pathogen, this can be more or less virulent. Eliminating the transport of pathogens will

decrease the amount of waterborne diseases, although not completely as some of those

pathogens can also be transmitted through other routes such as food (Salmonella). Pathogenic

Escherichia coli (E.coli) belongs to the Entero-bacteria family and is normally found in the

colon of warm blooded animals around 4 days after birth (MWH, 2005). E.coli, are bacteria that

are naturally found. A large amount of these in drinking water can cause food poisoning or

diarrhoea in humans.

E.coli provides guaranteed evidence of recent faecal pollution and should not be present in

drinking water. In order to cause infection a median dose of 100,000 E.coli has to be ingested.

These should not be found in drinking water and in order to make sure no diseases are spread,

this bacteria is tested before and after filtration takes place within treatment system. In general,

SSFs remove around 95% of these pathogens from water - 16000000 bacteria/ml (Unknown,

2011).

Bacteria removal had to be tested within 6h after the samples were collected to avoid growth to

take place. A broth solution was used to count the amount of colonies lying in the water before

and after being treated. Dots, i.e. colonies, of blue (E.coli) or red colours (Other coliforms) were

counted to calculate the amount of removal of total coliforms and E.coli:

Equation 3 Calculate % removal

%Removal =100*(Change in concentration before and after filtration/ concentration before filtration)

Equipment necessary for testing:

• mColiBlue 24®broth (Hach) bottle

• Plastic mColiBlue ampules (2ml) (Hach)

• Petri dishes

• Filter paper

• Absorbent pads

• Phosphate Buffered saline solution – pH 7.2 GIBCO

• Vacuum

• Millipore EZ-PAK®Sterile Membrane Filters

• Forceps

• Measuring cylinder



• Incubator/oven at 35-37°C

• Conical flask of distilled water

• Beaker for waste

• Pipettes

• Glass sample bottle

The procedure for testing bacteria colonies follows the methodology set by USEPA Membrane

Filtration Method;

1. Put on appropriate PPE to impede any interference in the results.

2. Wrap with aluminium all the equipment; measuring cylinders, conical flask with de-

ionised water, forceps and glass pipettes; to impede external contamination after

autoclaving (Figure 9)

3. Sterilize equipment to be used in chamber at 121°C for 50’-1h30 in autoclaving

machine. Note: Only glass and metallic equipment can be autoclaved as the heat can

deteriorate or melt the equipment. The plastic petri dishes and pipettes should already

be sterile. If the de-ionised water is autoclaved, it has to be left for about 30 -60 minutes

in the refrigerator to cool down before using – hot water kills bacteria and thus changes

the results.

4. Take the broth bottle or 2 ml ampules from the fridge and place it on the sterile

chamber.

5. Turn on fan and lights inside the sterilized room.

Figure 9 Autoclaving



6. After autoclaving, retire from the autoclaving machine all the equipment and place them

inside the sterile cabinet.

7. Dilute 20 ml of sample with 80 ml of de-ionised water in a measuring cylinder. The

dilution was carried out to enable the counting of colonies, if no dilution was done, too

many colonies would be shown in the petri dishes making it impossible to count.

8. Insert a single white pad with the aid of a forceps into each petri dish.

9. Impregnate pad with +/- 2ml of broth.

10. Close petri dish to impede any further contamination.

11. Join the filtering equipment together; the hard membrane filters between the waste

water storage glass and the U shaped container.

12. Switch on the vacuum and connect a see-through pipe to the vacuum valve. This pipe

will allow the absorption of water through the membrane and store any excess water in

a glass.

13. Put a membrane filter into the filter and close the container.

14. Rinse with de-ionised water or buffer solution

15. Turn vacuum on to allow rinsing solution to go through

16. Close valve (vacuum off)

17. Place white filter membrane in filtering media and close

18. Open vacuum until all dilution is filtered

19. With sterilized forceps and the petri dish lid of, gently lift the filter paper of from the

membrane container and place in with a rolling motion on the absorbent pad in the petri

dish. Make sure no air bubbles have been trapped in before putting the lid back on.

20. Invert the petri dish and put to incubate at 35°C for 24 hours in the oven.

21. After 24 hours, count the E.coli and total coliform colonies with a marker and under a

magnifier. The blue dots show the E.coli colonies and the red other coliform colonies so

total coliform is the red plus the blue dots. The maximum number of colonies to enable

counting is 100, if there are more, TNTC should be noted as a result.

This method permits to find 4 different types of bacteria (Millipore, 2011):

• E. cloacae (ATCC 23355) – red colour • E. coli (ATCC 25922) – blue colour • K. pneumoniae (ATCC 13883) – red colour • P. aeruginosa (ATCC 27853) – red colour



3.7.8 Pesticide

Metaldehyde is a pesticide that is mostly used to control slug and molluscs populations in

different crops. Therefore, it is considered a selective pesticide or a ‘molluscicide’. It is not

only used by farmers but also by the general public in their gardens. WHO classifies it as a class

II ‘moderately hazardous’ pesticide (Pesticide Action UK, 2001) which has recently raised the

Europeans attention as it is commonly found in water sources close to farming/agricultural

areas. In the UK (in the midlands, eastern and southern England) it has proven to be a seasonal

problem, as the levels increase in autumn when the pesticide is added to crops. The level that

should not be taken higher than is the ‘acceptable daily intake’ (ADI) and usually an average

sized person would need to drink 1000 litres of water to get to that level. Therefore this is

impossible to attain with people usually drinking 2 litres a day (Water UK, 2011). Our aim is to

determine whether slow sand filtration can be effective in treating this pesticide to reduce any

risk for health to households that might be in a rural area where this is used for example.

Equipment needed:

• Filter membranes

• Millipore filter

• Methanol

• Dichloromethane (DCM)

• Concentration vessel

• Glass pipettes

• De-ionised water

• Vacuum

• 10ml and 100ml measuring cylinder

• Pump

• Stock internal standard solution

• Bottle for concentrated solution

• GCMS machine



Concentration of sample (Environment Agency, 2009):

1. Filter 200 ml of sample (100 for testing, 100 for storage in case results are not the

expected) through filter membranes (same as bacteria ones)

2. Open vacuum to enable filtration

3. Filtrate 10ml of methanol in cartridge – always leave about 5ml height of liquid on

top of the filter after filtering

4. Filtrate 2ml of distilled water

5. Filter 100ml of sample pumped at a constant rate by pumping apparatus (900 rpm)

6. Filter 2ml of distilled water

7. Let dry for 45 minutes leaving the vacuum open

8. Place beakers under plate of cartridges

9. Add 2-3ml of DCM

10. Collect 2ml into small bottles

11. Measure weight of bottle for GCMS usage

12. Add the stock internal standard solution with the special measuring pipette

Note: A simplified description of the process is found in Figure 10

GCMS procedure:

1. The first process in GCMS is gas chromatography (GC) is used to vaporise the sample

and separate it into its different compounds.

2. With the samples placed in the machine in the form of the mini bottles, the autosampler

will use its syringe to measure out exactly 1 microlitre.

3. The autosampler will then inject the sample into the capillary column in the machine

through the septa to seal it. The temperature for injection should be controlled at 300°C.

4. The 30 m capillary column allows for a stationary phase to react with the different

compounds in the sample to separate them due to the different levels of absorbance.

The carrier gas that allows for this reaction to happen is helium and it is added at 1ml

per minute. The temperature also has to increase 50°C per minute going up to 260, to

allow better separation.

5. The next section is mass spectrometry and this is primarily for detection and

quantification of the fragments of the different compounds present in the sample.

6. The mass spectrometry section contains an iron source which is ignited and for the

electrode to pass an electric current through the different fragment s of our sample.



7. The different fragments will be charged and therefore a magnetic field will be turned on

and the iron source will bend at different angles according to the charge and molecular

weight. This allows for detection and to get the retention time.

8. The first mode used is the scan when the voltage is gradually increased from low to

high within a range. This will allow us to get the peaks of all the fragments in the

different compounds in order to know which peaks needs to be further analysed to

quantify the fragments that we need.

9. The next mode is the SIR (selected ion r) where only certain masses are scanned, which

allows for quantitative analysis of particular fragments.

10. To avoid a big peak at the start of SIR, caused but the volatility of the solvent used

compared to the fragment of compound we are interested in, the solvent delay needs to

be applied

GMS machine

Pumping apparatus

Scale

Membranes after filtering

Vacuum

Mini bottle

1st filtering equipment

Cartridge

2nd filtration

Vacuum on, filtering process

Figure 10 Pesticide testing process



4. Results & Discussion

In the following analysis, a series of graphs would be added to compare the results between

Raw water and effluent filtered water. Table 5 shows the abbreviations used for the

graphs/figures added in the discussion and in the graphs/figures.

Table 5 Identification of each sample in graphs

Identification of each sample in graphs

Name of in graph Actual sample

RW Raw water from Regents Park

RWS Seeded

RWU Unseeded

SF/UF Seeded Filtered/Unseeded Filtered after 24h

SF2/UF2 Seeded Filtered/Unseeded Filtered after 1h30



4.1 pH

The pH was measured using strips, tablets and a digital meter, thus it was hard to compare the

results. Strips and tablet methods were very subjective methods, where each person can interpret

the results in a different way. In December, a digital apparatus to measure pH was found and

used to obtain better results and ease the interpretation of the different waters. All the values

obtained of pH lied between the accepted values set by the Drinking Water Inspectorate of 6.5-

9.5, which means that in terms of pH, the water could be drank. The change of method to

measure pH led to a significant change seen in Figures 11 & 12.

Figure 11 Changes in pH in Seeded tank

Figure 12 Changes in pH in Unseeded tank

Values of pH of Regents Park Water were reduced by 3.5% after filtration took place with a

variation in values between 7.6 - 8.3. The strips used in the beginning of the testing provided

lower values than digitally, although they are all within the range of allowable drinking water

(Table 18).

7.4

7.6

7.8

8

8.2

8.4

8.6

8.8

20/11/10 20/12/10 19/1/11 18/2/11

pH

Date

RWS

SF

SF2

7.4

7.6

7.8

8

8.2

8.4

8.6

8.8

20/11/10 20/12/10 19/1/11 18/2/11

pH

Date

RWU

UF

UF2

Christmas

Christmas



4.2 Temperature

Temperature was recorded to have an idea of how this parameter could have an impact on the

bacterial activity; increase or decrease the level of growth of the coliforms later on counted. As

the weather gets colder, the bacterial activity decreases (Figure 13 & 14). The changes in

temperature between the source (lake) and the laboratory (16-20°C) will also affect the growth

of these. The recently autoclaved equipment at more than 100°C, will also affect the bacteria,

which is why the distilled water was left outside to cool if it had been autoclaves (which was not

always the case as it took too long to reach ambient temperature). The samples collected from

the filtered water will be collected in autoclaved equipment, although these have to cool down

before being used.

Figure 13 Changes in Temperature in Seeded tank

Figure 14 Changes in Temperature in Unseeded Tank

0

5

10

15

20

25

20/11/10 20/12/10 19/1/11 18/2/11

Tem

pera

ture

(°C)

Dates

RWS

SF

SF2

0

5

10

15

20

25

30/11/2010 30/12/2010 29/01/2011 28/02/2011

Tem

pera

ture

(°C)

Dates

RWU

UF

UF2

Christmas

Christmas



4.3 DO The decreased in DO levels are a good thing as this means that there has been a reduction in the

amount of live within the water which causes the dissolved oxygen to take place within water,

improvement in clarity of water and odour.

As Figure 15 shows, DO is temperature depended. The change of DO with temperature taking

the values of both parameters from Regents Park (Raw) and the water collected from the seeded

tank after 24h had passed since the last filtration. As we increase temperature, we decrease the

amount of DO found in water (MWH, 2005) i.e. DO content in water is influenced by water

temperature amongst other factors such as raw water or treatment process (WHO - Guidelines,

2010). DO depends on temperature, as it is stated on several biology books such as CliffsAP

Biology (Phillip E. Pack, 2005) or Corrosion tests and standards: application and interpretation

(Robert Baboian, 2005). DO also depends on the photosynthesis, respiration and salinity, which

is lower inside of the system than in the lake of Regents Park, where different types of fauna are

found under and over the water. Temperature will affect the amount of bacteria living and other

organisms found in the water (Lenntech, 2011)

Figure 15 Dissolved oxygen dependence on Temperature

0

2

4

6

8

10

12

0 5 10 15 20 25

DO (m

g/L)

Temperature (ºC)

Raw

Seeded after 24h

Linear (Raw)



The next three graphs (Figures 16-18) show the changes within DO over time. The first one

shows the reduced level of DO comparing raw water with effluent treated water. Lower levels

are found within water collected after 1h30 in both tanks, although even less within the

unseeded tank. Figure 16 shows how until February, water collected after 24h had higher values

than after 1h30, although this changed in the last month of experimentation. On the other hand,

DO levels in the unseeded (Figure 18) tank were more constant and led to the conclusion that

the longest time the water remained within the sand bed, the clearer and odourless the water is,

having less bubbles and oxygen levels on the effluent liquid.

Figure 16 Change in DO between Regents Park water and filtered

0

2

4

6

8

10

12

20/11/2010 20/12/2010 19/01/2011 18/02/2011

DO (m

g/L)

Date

RW

SF

UF

SF2

UF2Christmas



Figure 17 Change in DO in seeded tank

Figure 18 Change in DO over Seeded Tank

Water with high levels of DO has a better taste, although corrodes faster the pipes to distribute

water, which is why it is interesting to decrease the levels of DO during the treatment of water

(Freedrinkingwater, 2011).

0

1

2

3

4

5

6

7

8

9

10

20/11/2010 20/12/2010 19/01/2011 18/02/2011

DO (m

g/L)

Date

RWS

SF

SF2

28/02/2011, 7.22

28/02/2011, 4.02 28/02/2011, 4.47

0123456789

10

20/11/2010 20/12/2010 19/01/2011 18/02/2011

DO (m

g/L)

Date

Change DO Seeded Tank

RWU

UF

UF2Christmas

Christmas



4.4 Head loss

Figures 20 & 21 show how head loss linearly increases as the biofilm grows in the tank over

time. The seeded tank, having higher levels of head loss, led to a faster filtration to take place

in comparison to the unseeded tank, which in general provided lower differences. The equations

of the tread lines show that the difference in heights within the seeded tank was bigger and took

place faster than in the unseeded.

Figure 19 Head Loss change over seeded tank

0

5

10

15

20

25

30

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Head

Los

s (c

m)

Date

Seeded (24h)

Seeded(45')

Seeded(1h30)

Christmas



Figure 20 Head loss change over Unseeded Tank

Figure 21 shows the change in head losses within the unseeded tank which vary more greatly

than the seeded as the diffuser was not used when pouring the mix into the tank. This increased

the pressure over the sand creating a new biolayer which can be seen in Figure 22 and decreased

the levels of head loss, back to the same levels as the start of the experimentation. This fault

demonstrated the importance of the diffuser usage and demonstrated Darcy’s equation, which

states that head loss is determined by velocity, coefficient of hydraulic permeability and the

depth of the granular media.

0

5

10

15

20

25

30

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Head

Los

s (c

m)

Date

Seeded (24h)

Seeded(45')

Seeded(1h30)

0

5

10

15

20

25

30

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Head

Los

s (c

m)

Date

Unseeded (24h)

Unseeded (45')

Unseeded (1h30)

Christmas



𝑣 = 𝑘 ∗ 𝜕ℎ𝜕𝐿

4.5 Turbidity

Turbidity is one of the most important and simple indicators of suspended solids and amounts of

particle present in water. As expected, Regents park raw water provided the highest NTU

measurements due to the quantity of debris and particles lying within the raw water. The values

of raw water varied during the experimentation, the more wild life found in the park, the highest

values were obtained. Weather also seemed to play a role in the measurements obtained; these

varied from 8 to 23NTU, thus the usage of 2 different standard solutions were needed to

calibrate the equipment. In order to provide accepted drinking water as set by WHO and

CAWST, the level of turbidity had to be less than 1 NTU, which were obtained by the end of

the testing period (Figure 23).

Figure 22 Change in turbidity over time

0

2

4

6

8

10

12

14

16

18

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Turb

idity

(NTU

)

Date

RWS

RWU

SF

UF

SF2

UF2

Figure 21 Development of second biofilm in unseeded tank

Christmas



Better results were provided by the second collection, after 1h30 (See figures 24 & 25), leading

to the conclusions that the faster the filtered water is collected, the less turbidity takes place and

the longer the water remains in the sand bed, the more haziness the effluent water is going to be.

Figure 23 Change of turbidity over time in the Unseeded tank

Figure 24 Change in turbidity over time in seeded tank

0

0.5

1

1.5

2

2.5

20/11/2010 20/12/2010 19/01/2011 18/02/2011

tURB

IDIT

Y (N

TU)

Date

UF

UF2

0

0.5

1

1.5

2

2.5

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Turb

idity

(NTU

)

Date

SF

SF2

Christmas



The results obtained prove that both tanks perform well and achieve the goals set by the WHO

providing water with NTU lower than 1. The linear tread line and the equations were added to

show the different performances of tanks and turbidity reduction levels after the two filtration

times. The best tank in this tank proved to be the seeded one after 1h30.

4.6 UV light

The first UV light spectrophotometer used during the experimentation did not provide accurate

results as the values kept on increasing, which is why the all the values were recorded after 30

seconds, to allow comparison. The second, newer spectrophotometer used at the end of the

experimentation on the other hand, proved to be a better apparatus to use by more presenting

precise measurements.

In general, the amount of UV light going through the tank decreased in comparison between the

influent and effluent water (Figure 26); as the quality of water is improved which means that the

filtered water has, as expected, lower values of UV light going through. A decrease in UV light

passing through the sample meant that a reduction in particular matter took place within the

filtration and clearer water flowed out from the filtering systems.



Figure 25 Change in Light Absorbed by UV 254 Method over time

Figure 26 Change in Light Absorbed by UV 254 Method over time in unseeded tank

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Ligh

t Abs

orba

nce(

%)

Date

RWS

RWU

SF

UF

SF2

UF2

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Ligh

t Abs

orba

nce

(%)

Date

RWU

UF

UF2

Christmas

Christmas



Figure 27 Change in Light Absorbed by UV 254 Method over time in seeded tank

The performance of both tanks and filtration times had similar values, except during the

Christmas break, where values decrease, thus in order to enable better comparison, the average

of all values was taken. The lowest UV light results were provided by the unseeded tank after

24h and 1h30, which leads to the conclusion that clean sand decreases better the levels of

particulate matter allowing better UV light to go through. Table 6 shows an average of the

values obtained for Raw water of Regents park and the filtered. This shows a great decrease of

40% in the values, thus less particulate matter is found in the water which allows more light to

be absorbed. This table was drawn to support figures 27 & 28, which show the decrease

between the inserted water (mix between recycles water and Regents Park) and the leaving one.

Table 6 Average values of UV 254

Regents Park Seeded(24h) Unseeded(24h) Seeded(1h30) Unseeded(1h30)

Av (%) 0.2589 0.1645 0.1566 0.1647 0.1619

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Ligh

t abs

orba

nce

(%)

Date

RWS

SF

SF2

Christmas



4.7 Bacteria

It is important to measure the amount of bacteria found in water and to calculate the percentage

of removal of these organisms within water to quantify the performance of the treatment system.

Figures 29 and 30 show, there is no clear trend for total coliform removal, which indicates that

several errors have been done within the experimentation. The testing of these is a very delicate

process and it is probable that the some samples were contaminated during the process. Another

problem encountered that could have affected the results, was the usage of several occasions of

an oven instead of an incubator and damage of several apparatus used such as the vacuum and

the small autoclaving machine (took 45 minutes to autoclave, instead of 1h30 of the big one that

had to be used afterwards retarding the research). Another approach can also be taken, where it

can be concluded that there’s a growth of some kind of coliforms in the tank, which does not

necessarily have to be negative .

Figure 28 Percentage of total coliform removed from water over time in unseeded tank

Figure 29 Percentage of total coliform removed from water over time in seeded tank

0

20

40

60

80

100

120

29/11/06 29/12/06 28/1/07 27/2/07

TC %

rem

oval

Date

Total coliform % removalUnseeded 24h

Total coliform % removalUnseeded 1h30

0

20

40

60

80

100

120

30/11/10 30/12/10 29/1/11 28/2/11

TC %

rem

oval

Date

Total coliform % removalSeeded 24h

Total coliform % removalSeeded 1h30

Christmas

Christmas



From the graph above, we can conclude that in general the seeded tank worked better in

removing total coliforms than the unseeded which results in a decreasing treadline with a

negative slope.

Knowing the amount of coliforms removed by the system is important, but measuring the

amount of E.coli indicates more clearly if there’s any pollution within the effluent liquid, as not

all coliforms are harmful.

The table below shows the average removal rates of E.coli by the seeded and unseeded tanks.

Two averages where calculated, one with the actual averages of the resulting removals and

another one excluding the values under 50% assuming those were wrong (figure B1 shows the

variance ignoring the values below 50%). In any case, both averages show that 24h pause time

worked better for decreasing the amount of pathogenic bacteria.

Table 7 Mean values for E.coli removal *Excluding all possible errors, i.e. % rates under 50.

Seeded 24h Unseeded 24h Seeded 1h30 Unseeded 1h30

Mean 81.16 80.75 66.87 59.04

Mean* 97.4 97.57 93.2 83.38

Figure 30 Percentage E.coli removal over time

0

20

40

60

80

100

120

30/11/2010 30/12/2010 29/01/2011 28/02/2011

E co

li %

rem

oval

Date

Seeded 1h30

Seeded 24h

Unseeded 1h30

Unseeded 24h



Another factor which could have affected the results is that the pause time was not always 24h,

but 48h and 72h (weekend), as the filtering could not be realized every day. As set by CAWST,

the filtering of water on SSFs has to be realized with a pause time between 1h and 48h, if the

pause is too long the biolayer will consume all pathogens and nutrients and eventually die,

reducing the efficiency of the method.

This is reflected on the graph below (Figure 32), where the wrost removal rates of E.coli on the

supposed 24h pauses, where obtained after the weekend, i.e. after 96h, which is more than the

required in the usage of the treatment method.

Figure 31 E.coli removal over 2 weeks after ‘24h’

The following figures describe the performance in E.coli percentage removal on the two tanks

ignoring values under 50 (assumed to be wrong – Table 7). The slopes are all positive indicating

that the performance increases over time and the separate dots show how well a SSF performs,

most of the values range 90-100% and the performance appears to be more effective when the

water is collected after 24h (Figures 33 & 34).

0

20

40

60

80

100

120

E.coli %removalSeededE.coli %removalUnseeded

Monday

Tuesday Thursday Tuesday

Monday

Monday Thursday



Figure 32 % E.coli removal over time in seeded tank

Figure 33 Percentage E.coli removal over time in unseeded tank

0

20

40

60

80

100

120

10/11/2010 10/12/2010 09/01/2011 08/02/2011 10/03/2011

E.co

li %

rem

oval

Date

Seeded 1h30

Seeded 24h

0

20

40

60

80

100

120

20/11/2010 20/12/2010 19/01/2011 18/02/2011

Ecol

i % re

mov

al

Date

Unseeded 1h30

Unseeded 24h



4.8 Pesticides

Tables 21 found in the appendix and the graphs below (Figures 35-38) show the results for the

two runs of GCMS carried out to analyze the content of pesticide in the contaminated samples

in February.

Errors in manipulation of the equipment and missing samples led to a lack of data, which is the

reason why some of the values missing in the tables in the appendix. An average of all the

results obtained was taken for the comparison to take place (Figures 35-38), which led to the

conclusion that although not all the samples were present, the investigation could still be

realized.

RWS and RWU were samples collected as the mixed water was poured into the tanks, i.e. those

samples were water from the day before (or in the case of Mondays or Thursdays a few days

earlier), whilst SF2 and UF2 were samples taken 1h30min after the first filtration had taken

place.

It was expected to obtain better results with longer pause time, i.e. after 24h. However, this was

not the case (Table 21). After 1h30, the systems prove to reduce the levels of Metaldehyde

better than with longer pauses, which may be the result of an increase of the pesticide levels

over time, i.e. samples seizing Metaldehyde from previous filtrations. The high resistance of

this contaminant could have caused this, as it is hard to disintegrate and capture. The following

graphs demonstrate how the level of contaminant decrease as polluted water is filtered.

First run of GCMS:

The first run of GCMS test shows how the seeded filter decreases the levels of pesticide better

than the unseeded (Figure 35). As described on Tables 8 & 9, the percentage of removal of

Metaldehyde is around 75% within the Seeded, whilst on the Unseeded tank it’s 36-55%. The

following figures show that the best results are obtained on the second filtration (1h30), leading

to the conclusion that the shorter the retention time (water in the tanks without being extracted),

the better removal is achieved.



Figure 34 Average Pesticide concentrations during GCMS run

Table 8 Percentage removal of Metaldehyde in first run GCMS

Type Average Seeded (µg/ml) %Removal

Raw 0.487

RWS 0.230

SF2 0.053 76.9520687

SF 0.058 74.68522931

Type Average Unseeded (µg/ml) %Removal

Raw 0.487

RWU 0.217

UF2 0.098 55.08073361

UF 0.137 36.92364048

The second GCMS run shows the same trend:

Figure 35 % removal of Metaldehyde in second run GCMS

0.000

0.050

0.100

0.150

0.200

0.250

RWS SF2 SF

Conc

entr

atio

n (µ

g/m

l)

0.000

0.050

0.100

0.150

0.200

0.250

RWU UF2 UF

Conc

entr

atio

n (µ

g/m

l)

0.000

0.050

0.100

0.150

0.200

0.250

RWS SF2 SF

Conc

entr

atio

n (µ

g/m

l)

0.000

0.050

0.100

0.150

0.200

0.250

RWU UF2 UF

Conc

entr

atio

n (µ

g/m

l)

Less removal

Higher amount of metaldehyde than seeded

Lower concentration of Pesticide at first



Table 9 Percentage removal of Metaldehyde in second run GCMS

Type Average Seeded (µg/ml) %Removal

Raw 0.461

RWS 0.227

SF2 0.063 72.29206421

SF 0.126 44.48187211

Type Average Unseeded (µg/ml) %Removal

Raw 0.461

RWU 0.248

UF2 0.078 68.35282789

UF 0.166 32.92244446

Biosand filters prove to be efficient in removing pesticides from water, although the results

were not the expected (greater reductions or complete removal of pesticides were expected).

Higher decreases were obtained after 1h30 (tables 8 & 9), which leads to the conclusion that the

longer the water remains in the system; the lower removals rates are going to be present in the

effluent liquid. In order to improve the analysis, further analysis should be carried out, possibly

varying the levels of methaldehyde inserted in the raw water. On the other hand, the levels are

not meeting the drinking standards which require the water to be free of any pesticides. SSF are

able to reduce greatly the levels of pesticides, although not completely (CAWST – Pesticides,

2010). On the other hand, the resulting water is very unlikely going to create any harm (Table

10), as greater doses are needed. The European and UK standards set a maximum of 0.1µg/L

(WATER UK, 2011) acceptable daily intake (ADI) which are not met by our tanks..

Table 10 Health Effects of Methaldehyde (INCHEM, 1996)

Dose Health impact Toxicity

Up to 5mg/kg • Salivation

• Facial Flushing

• Fever

• Abdominal Pain

• Nauseas and Vomiting

Low

Up to 50mg/kg • Drowsiness

• Tachycardia

• Spasms

• Irritability

Medium

Up to 100-200mg/kg • Convulsions

• Tremor

• Hyperreflexia

High

Up to 400mg/kg • Coma

• Death

Very High



4.9 Hydraulics of filtration

In SSF the rate downwards of water wanted has to be slow in order to have a laminar flow

within the system. The resistance, H, of the tank is in accordance with Darcy’s Law;

Equation 4 Used to calculate Resistance (CAWST, 2010)

H=velocity*width/coefficient=(v/k)*h

In order to calculate the resistance of the SSF and the sphericity, the data was extracted from the

previous work realized by R. Outhwaite.

Table 11 Dimension parameters of tanks

Volume sand (m3) 0.0203

Total volume (m3) 0.036

Area (m2) 0.4*0.3 radius

Seeded diameter (mm) 0.202 0.101

Unseeded diameter (mm) 0.182 0.091

Coefficient of uniformity seeded 1.8

Coefficient of uniformity unseeded 1.65

Table 12 Parameters used to calculate resistance

Table 13 Resistance, H

Resistance, H (seeded) 40.53440204

Resistance, H (unseeded) 49.93254863

From the calculations carried out in excel (Tables 11-13 using equation 1), it was obtained that

the grains had a worn size and that the resistance of the seeded sand bed was lower than the

unseeded, which has lower diameter grains.

Velocity (m/h)

Flow rate (L/minute)

Flow rate (L/h)

width (m)

coefficient k (seeded)

coefficient k (unseeded)

porosity T (°C) sphericity

138.70 0.267 16.02 0.3 1.0265 0.83333198 0.415 18 0.81



4.10 General Problems occurred Throughout the experimentation a series of problems occurred affecting the results and the

analysis.

The first issue we had to deal with took place in the laboratory, where it was necessary to

schedule the equipment to use in order to be able to manipulate it whenever it was needed.

Another problem that occurred was the appropriate usage of pH meters. Three different methods

were used to measure this parameter; the first two during the first semester was too subjective,

i.e. the usage of strips and phenol red tables was not accurate enough, thus a pH electrical meter

started to be used.

Problems with the laboratory machinery took place several times. The autoclaving machine

broke with the bacteria testing material on one occasion; hence the usage of another, bigger and

slower, took place. The spectrophotometer was another machine, recently changed, which

caused trouble as the values provided by it were constantly increasing. The solution

implemented was to record the values after 30 seconds to be able to compare the results. The

last appliance which failed in several occasions were the vacuums. In order to test bacteria and

pesticides, both vacuums were needed. The one used for pesticides, released smoked which

caused head aches and in some occasions the avoidance of usage of such seemed like the best

idea. The other one, used for the bacteria testing, did not absorb the liquids sometimes, which

unable to filter the water used for bacteria counting.

Human error was also common, like in any experimental procedure. The major error, took place

in the beginning of the second trimester where the diffuser was not placed on top of the tank

before pouring the water, thus the granular bed surface and the schmutzdecke were disturbed,

leading to a decrease in head loss, change in effluent water quality and the creation of a second

biofilm.

The last issue faced, was the obstruction of the piping system at the end of the project, which

did not allowed the testing of rapid flow rate quality of effluent water. Coarse gravel exited the

layer and blocked the water to flow out as expected. This influenced the results and led to the

conclusion that the filters had to be changed for the next generation to use them.



5. Conclusion

The various parameters that were changed in order to understand to full functioning of the filter

was the different time of collection after filtration, the difference in the mix of the water to be

filtered and amount of water that was left on top of the filter to be stagnant. For the different

times of collection, these included after 1h30 and 24h, or 48h or 72h depending on which day of

the week the filtration was carried out in. The mix of water was changed from 12.5L of rain

water and 12.5L of raw Regents Park water, to 12.5L of already filtered water from before and

12.5L of raw Regents Park water. The stagnant water that is left after the water is filtered

through was also changed, testing at 5cm and 10cm above the biolayer.

One conclusion that could be made through one of the human errors encountered was the

importance of the diffuser that is placed above the filter as the water is poured into it for

filtration. Due to role in diffusing the water to allow for a lesser and more equal pressure

distribution on the biolayer, it means the biolayer is less disturbed along with the crucial

organisms it encompasses that filter the water. This error resulted in a decrease in filtered water

quality for a period of time, and an increase in head loss. A second biolayer was also formed

due to this as the first was disturbed and probably buried under some of the granular material of

the filter.

Overall, the SSF met the requirements of potable drinking set by the different institutions. The

variables that were changed in order to comprehend the limitations and advantages of the slow

sand filters better do not seem to have changed the results very much except for the different

times after which the filtered water was collected. However, as stated above, the guidelines that

have been set by the WHO for drinking water were attained.

5.1.1 Parameters

The WHO and CAWST set a series of allowable levels of the different parameters tested during

the research, which most were met.

At the end of the experiment, levels lower than 1 NTU of Turbidity (Table 14) were achieved,

although better results were obtained within the seeded tank. Although in the beginning better

results were achieved by the unseeded tank, the seeded did in general produce better results of

decreasing NTUs.

Levels of pH, light absorbance and DO were also reduced after the water was filtered (Table

14), as mentioned on the documents of the WHO, GLAAS, Outhwaite and CAWST, although

not being specified.



pH reduction shows that the filter is degrading the dissolved organic carbon found in Regents

Park water as stated by Zeng in 2007. This is organic material found in water from plants and

animals which is dissolved in the water and acts as aliment for aquatic organisms. Reducing the

levels of DOC means there is a reduction in organic acids in water (Zeng, 2007).

DO prove to be temperature depended and was confirmed with Figure 15, that different Biology

books used and other sources proved that this was right. The reductions were due to

photosynthesis of plants in the Raw water not taking place in the granular media and

temperatures increases due to ambient temperature of the laboratory.

Table 14 Average values for all the parameters measured everyday

RWS RWU SF UF SF2 UF2

DO (mg/L) 6.377 6.138 4.791 3.749 4.857 5.307

Turbidity (NTU) 7.283 6.96 0.984 0.883 0.846 0.897

UV 254 (% Abs) 0.213 0.209 0.165 0.159 0.166 0.165

Temperature 15.586 15.893 19.48 19.677 19.75 19.527

pH 8.303 8.307 8.071 8.039 8.061 8.052

0'S 0'U 45'S 45'U 1h30'S 1h30'U

Head Loss 7.723 6.129 9.419 7.845 7.016 5.955

On average, the unseeded tank achieved lower head losses than the seeded which is due to the

formation of a second biofilm on the surface of the granular bed. Before that, the seeded system

gave better results which may be due to diameter of grains greater than the unseeded ones, thus

providing a lower resistance (Section 4.9) in sand bed. Richard Outhwaite suggested that these

could also be due to microbial activity in the systems, greater in the seeded which becomes

faster matured than the unseeded.

The size of particles also affected the turbidity levels, which were reduced greater by the

unseeded tank which had particles of 0.182 diameter after the first filtration, although at the

second filtration (1h30) the reduction was lower within the seeded tank. This can leads to the

conclusion that fast filtrations provides better results in seeded tank and the other way around

for the unseeded.

To conclude, the dimensions of the system and the materials used on it have a great effect on the

resulting water, more analysis should be done to acquire a particle size that would achieve

greater results in every parameter.



5.1.2 Bacteria

From bacterial measured throughout the change of the different variables, we can conclude that

the time of collection after filtration after which the total coliform was most effective was after

1h30 but more importantly that it was after 24h that the E.coli removal was the best. The

indication given that possibly pathogenic E.coli was better removed after a filtration of 24h is

significant as it confirms previous hypothesis that the water would be better treated after a

longer time in the filter although not after more than 24h as the micro-organisms would

consume and die off again, comparatively increasing coliform and E.coli counts at times like

48h and 72h. The two other variables that were changed do not seem to have affected this

section of results particularly. Most importantly though, the biofilters on average can be

concluded to remove more than 90% of the bacteria present initially which is a standard that

need to be reached according to the WHO for drinking water and is a level which is also said to

be attained by slow sand filters by CAWST.

5.1.3 Pesticides

Regarding pesticide removal, it was found that a minimum of 36% of Metaldehyde was

removed. Taking averages from the values obtained in the first and second runs of the GCMS

(Table 9) , allowed to conclude that the best removals are achieved with low retention times.

Initially, filtered metaldehyde would seep back into the water if the water was left in the filter

for 24h (The initial amount of metaldehyde that was added to the raw water was 2 µg/ml). The

data obtained from the second run of GCMS machine were different probably due to a reduction

in concentrations of the samples, impeding a second run to take place for certain samples. The

values that were produced for the filtered water along with the raw water show a level that is

much higher to the 0.1 µg/l value set by the European Water Directive (Drinking Water

Inspectorate, 2010). Although this standard is not set according to health basis, studies have

shown that the acceptable daily update of 0.02 milligrams per kilogram of body weight per day

will only be attained if someone drinks 1000 litres a day which is improbable (Water UK,

2011). Even if these targets are not met, SSF do eliminate part of the pesticides found in water.

Perhaps other pesticides could have been removed, but it was not the case for Metaldehyde.

According to the Environmental Agency, Metaldehyde cannot be completely removed from

water by any treatment methods, even the ones used in More Economically Developed

Countries using ozone and granular activated carbon to treat water do not remove this pesticide.

On the 3rd Conference on British Water it was said that the best means to remove this was using

SSF, although its removal its limited (Anglian UK, 2011)



5.2.1. Were the objectives met?

5.2.1.1. Raw water in maturation The first objective was to evaluate the effect of raw water on the maturation period of the filters

and this was effectively done as the maturation period took place for both filters until the

bacterial removal reached 90% removal. It took 15 days for both filters to maturate and start

providing good results in the different parameter. Through the experiment however, a mix was

usually used with rainwater or recycled filtered water from the day before. Through these 15

days, an improvement of bacteria removal was clearly observed. Despite being matured, the

systems do not break down the pesticide inserted

It is also clear that the type of raw water affected the maturation, if only Regents Park water

would have been used, a faster maturation would have taken place. Adding nutrients would

have been another way to reach this stage faster, although these were not added.

During maturation, the levels of DO consumption, turbidity reduction and UV light absorbance

were not as good as the ones afterwards. Maturation took place in the seeded tank before the

unseeded although the Christmas break had a major impact on the removal of bacteria, giving

low results.

The disturbance of the unseeded tank, by not using the diffuser on one occasion created a

second schmutzdecke and gave similar results to the ones obtained in the maturation period in

terms of head loss and bacteria removal.

5.2.1.2. Frequency of filtration As can be seen in Figure 32, filtration time and date makes a great difference on the bacteria

removal. CAWST set in the design of the filters that the filtration pauses had to be between 1-

48h. The Figure shows that leaving it for longer, leads to lower removal rates.

Depending on the parameter, already discussed in Section 4, some are removed better after 1h30

and others after 24h, like pesticides so depending on the priorities of the researcher or the client,

one or the other should be used. It is recommended anyways to filter as often as possible to keep

biological activity alive and get better results.



5.2.1.3. The effect of detention time In terms of Turbidity and DO, better results were obtained after 1h30 detention. On the other

hand, better results in removing bacteria and pesticides were obtained after 24h, which leads to

the conclusion that the longer these remain on the system, the higher reductions are going to be

obtained on the effluent water.

5.2.1.4. Stagnant water variation

Varying the level of water above the tank did not give any different results in the reduction of

turbidity, bacteria or pH. Using 5cm or 10 cm provide the same results. This layer is necessary

to keep sand wet and allow oxygen to go through the system to always allow a minimum level

of DO to remain in the system (Lenntech, 2011). A minimum level of DO is necessary for

drinking water, respiration and keeping the system working.

5.2.1.5. Removal of pesticides with biological mechanism

Although the study of pesticides still needs to be carried out, a complete elimination of

Metaldehyde does not take place, same thing happens with E.coli, which kill millions of people

every year. Bacteria was greater reduced by using a pause of 24h, whilst pesticide after 1h30.

As the biofilter develops, a greater reduction of bacteria is obtained and same thing happens

with the pesticides, over time the reductions are better.

Testing of bacteria and pesticides were carried out during the same days, and although the water

was infected, bacteria removal did not showed any changes. This leads to the conclusion that

the presence of pesticides in water does not affect the activity of bacteria.



6. Future work & Recommendation

6.1 Future work

Future research should be carried out on testing different amounts of pesticides and the

performance of the treatment system in reducing the levels of other parameters such as iron or

copper to meet the drinking water standards.

More tests over a longer period of time should be done on bacteria removal to enable better

conclusions and results. Also, making sure there is always enough equipment and broth to carry

out the experiments would minimise any error in results and changes in trends observed.

The effect of putting smaller volumes of seeded tank should also be analysed, as these would

allow in the hypothesis to have more tanks to provide safe water. This would be interesting to

analyse the impacts on the effluent liquid.

6.2 Recommendations for future

After finishing the research project, the authors would like to recommend a few elements to

improve the quality of work and research for future researchers.

The first thing, if anyone is to carry out this experiment in the laboratory of the University

College of London, would be to empty the tanks to clean the walls and insert new layers of

gravel and sand to improve the quality of future results.

Another recommendation would be to make a Gantt chart which is going to be followed

properly taking into account the lectures, professional visits and work dead-lines, to impede the

interference of these with the investigation. Organising your timetable with other people

working in the laboratory is also important to allow the impossibility of usage of certain

equipment.

Regarding bacteria removal, it will be recommended to filter more often (between 1-48h as set

by CAWST) to improve the results.



More care and variations of parameters should be carried out to allow more comparison

between data, mostly for pesticide removal. Decreasing the amount of pesticide in the water

inserted should be compared with the values obtained in this experimentation to improve the

comparisons. Comparing different types of pesticides commonly found would be another good

idea, to ameliorate the analysis of removal of pesticides using a SSF.

The last item that should be addressed is the problem of gravel stones blocking the membrane

and impeding an easy flow out. This can be addressed by adding an extra membrane filter on

the tank, where the gravel layer finishes and gets into contact with the pipe.



7. References

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http://www.thefreedictionary.com/colloidal

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L. Huismans and W.E. Wood (1974) WHO, Slow sand filtration ISBN 92 4 154 037 0

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MWH (2005) Water treatment Principles and design 2nd Edition WILEY

Millipore http://www.millipore.com/catalogue/item/m00pmcb24 Accessed March 2011

Nigel Graham & Robin Collins (1996) Advances in Slow Sand and Biological Filtration, WILEY-Blackwell

Nobutada Nakamoto (2009) Produza vôce mesmo uma água saborosa - Ferrari ISBN 978 85 61306 21 2

Phillip E. Pack (2007) CliffsAP Biology – WILEY and Sons http://books.google.co.uk/books?id=CKl5ehk3xDoC&dq=dissolved+oxygen+decreases+with+temperature+increase&source=gbs_navlinks_s Accessed March 2011

Pesticide Action UK (2011) Metaldehyde http://www.pan-uk.org/pestnews/Actives/Metaldeh.htm,Accessed March 2011.

Realtech, Methods 8074, 8367, and 10029 Bacteria detection www.realtech.ca/RT_Port_SS_FA.pdf Accessed February 2011

Richard Outhwaite (2010) Optimisation of household scale Biosand Filters

Robert Baboian (2005) Corrosion tests and standards: application and interpretation, ASTM International http://books.google.co.uk/books?id=8C7pXhnqje4C&dq=dissolved+oxygen+decreases+with+temperature+increase&source=gbs_navlinks_s Accessed March 2011

Water UK (2011) Metaldehyde http://www.water.org.uk/home/policy/positions/metaldehyde-briefing/metaldehyde-briefing-jan-2011.pdf Accessed March 2011.

WHO (2008) Guidelines for drinking water – Third Edition, WHO, Geneva http://www.who.int/water_sanitation_health/publications/ssf3.pdf Accessed November 2010

WHO (2010) http://www.who.int/household_water/en/index.html Accessed November 2010

WHO & UNICEF (2000) Diarrhoea: why children are still dying and what can be done

William W Nazaroff & Lisa Alvarez Cohen (2004) Environmental Engineering Science WILEY, student edition


http://www.inchem.org/documents/pims/chemical/pim332.htm%23SectionTitle:3.3%20%20Physical%20properties

http://www.inchem.org/documents/pims/chemical/pim332.htm%23SectionTitle:3.3%20%20Physical%20properties

http://www.lenntech.com/why_the_oxygen_dissolved_is_important.htm

http://www.millipore.com/catalogue/item/m00pmcb24

http://books.google.co.uk/books?id=CKl5ehk3xDoC&dq=dissolved+oxygen+decreases+with+temperature+increase&source=gbs_navlinks_s

http://books.google.co.uk/books?id=CKl5ehk3xDoC&dq=dissolved+oxygen+decreases+with+temperature+increase&source=gbs_navlinks_s

http://www.pan-uk.org/pestnews/Actives/Metaldeh.htm

http://www.realtech.ca/RT_Port_SS_FA.pdf

http://books.google.co.uk/books?id=8C7pXhnqje4C&dq=dissolved+oxygen+decreases+with+temperature+increase&source=gbs_navlinks_s

http://books.google.co.uk/books?id=8C7pXhnqje4C&dq=dissolved+oxygen+decreases+with+temperature+increase&source=gbs_navlinks_s

http://www.water.org.uk/home/policy/positions/metaldehyde-briefing/metaldehyde-briefing-jan-2011.pdf

http://www.water.org.uk/home/policy/positions/metaldehyde-briefing/metaldehyde-briefing-jan-2011.pdf

http://www.who.int/water_sanitation_health/publications/ssf3.pdf

http://www.who.int/household_water/en/index.html


8. Glossary

(CAWST, 2010 – Biology dictionary – Free dictionary)

Adsorption When a contaminant attaches itself to the surface.

Bacteria Single celled microorganisms.

Biolayer Biological layer formed at the sand water interface of SSF. It is

colonized by microorganisms including bacteria, protozoa, algae and

diatoms. Also called schmutzdecke.

Contamination Pollution of water due to X causes.

Colloidal Having the character of a colloid, i.e. a system in which finely divided

particles, which are approximately 10 to 10,000 angstroms in size, are

dispersed within a continuous medium in a manner that prevents them

from being filtered easily or settled rapidly.

Disinfection Any process that removes, deactivates or kills pathogens.

Dissolved oxygen The concentration of oxygen dissolved in water, expressed in mg/l or as

percent saturation, where saturation is the maximum amount of oxygen

that can theoretically be dissolved in water at a given altitude and

temperature.

Dissolved solids Small particles which are dissolved in water which can’t be removed by

sedimentation

Filtration Process of allowing water to pass through layer of a porous material to

remove suspended solids and pathogens.

Flow rate (m3/s) Time it takes to fill a container

Gross Domestic Pr. Value of a country’s overall output of goods and services at market

prices, excluding income from abroad.

Head Loss (cm) The decrease in total head caused by friction

Median Dose Dose of pathogens required to infect 50% of the population


http://www.biology-online.org/dictionary/Concentration

http://www.biology-online.org/dictionary/Oxygen

http://www.biology-online.org/dictionary/Water

http://www.biology-online.org/dictionary/Saturation

http://www.biology-online.org/dictionary/Saturation

http://www.biology-online.org/dictionary/Maximum

http://www.biology-online.org/dictionary/Oxygen

http://www.biology-online.org/dictionary/Water

http://www.biology-online.org/dictionary/Given

http://www.biology-online.org/dictionary/Altitude

http://www.biology-online.org/dictionary/Temperature


Nutrient Any substance used by microorganisms to live and grow.

Pathogen Any living organism that causes disease.

pH The potential of hydrogen ions - a measure of acidity or alkalinity. It is

the log of the reciprocal of the hydrogen ion concentration. The pH

scale runs from 0 to 14, 0 being very acidic and 14 very alkaline.

Pore Small spaces between sand grains allowing water to go through.

Sanitation Maintain clean, hygienic conditions that help prevent disease through

services.

Sedimentation Process used to settle suspended solids under influence of gravity.

Supernatant water Water above sand layer

Suspended solids Small solid particles floating in water, causing turbidity.

Turbidity Caused by suspended solids, such as sand, silt and clay, floating in

water. It’s the amount of light that is reflected off these suspended

solids which make the water look cloudy or dirty. Measured in NTU.

UV 254 Indication of the amount of natural organic matter (NOM) in water and

wastewater

Virulence Severity of damage to host



9. Appendix

PROJECT RISK ASSESSMENT FORM

DEPARTMENT / UNIT / GROUP: Civil, Environmental and Geomatic Engineering

WORK / PROJECT TITLE: Removal of organics by household slow sand filters

LOCATION(S): Environmental Laboratory at UCL

DESCRIPTION OF WORK: Laboratory work based on testing on a house hold scale slow sand filter tank

different parameters to find out the optimum parameters and dimensions resulting in the cleaner and safer

drinking water. Different tests will be undertaken twice a week analyzing raw water of the Regents Park Lake.

The main aim is pesticides removal as well as to find the optimum levels of water used in the tank.

PERSONS INVOLVED: Philomene Rabu, Joana Valls, Luiza campos, Ian Sturtevant and Dr Judith Zhou

HAZARD IDENTIFICATION (state the hazards involved in the work)

a. Check workplace

b. Ask staff and supervisors

c. Check manufacturer’s instructions and laboratory staff for equipment and chemicals

d. Review accidents and health records

• Retrieving water from Regent’s Park lake

o Exposure to contaminated water

o Possibility of Weils disease or other water borne diseases

• Bringing water from Regent’s Park to UCL’s laboratory for testing

• Introducing water into tanks in laboratory

o Driving trolley with water

o Working with glassware

o Typing document

o Doing presentation

• Test water

o Glassware usage

o Equipment usage

o Removing schmutzdecke (biofilm) from the top of the sand during clearing

• Clean tanks



o Usage of cleaning products

o Removing schmutzdecke (biofilm) from the top of the sand during clearing

o Cleaning glassware

RISK ASSESSMENT ( high, medium or low risk)

i. Tripping - high

ii. Water borne Diseases or Illness - low

iii. Back pain from wrong position - high

iv. Falling objects - medium

v. Inadequate use of equipment leading to injuries, breaking material or affecting results - medium

vi. Drowning - low

vii. Cold, flu from bad weather - high

viii. Contaminate by throwing trash - high

ix. Disturb the inhabitants of water by pumping out water - medium

x. Accidently harm organisms - medium

xi. Disturb the environment - low

xii. Handling solvents – medium

xiii. Computer work – low

xiv. Handling sand – medium

xv. Breakage of glassware – medium

xvi. Direct exposure to contaminated water – high

xvii. Water samples to be analyzed – medium

xviii. Harrowing - medium

CONTROL MEASURES (state the control measures that are in place to protect staff and others from the

above risks. Put in place adequate control measures for any risks that have been identified as uncontrolled.)

• Wear Appropriate equipment and tools – adequate PPE (gloves, mask, glasses,…)

• Follow instructions of equipment and apparatus

• Follow experimental methods carefully

• Ask for advice or if any doubts arise

• Record carefully

• Clean and organize working space

• No rushing or stressing

• Getting briefed before starting any experiment that requires it

• Control site and review risk assessment

• No waste disposal

• Control and check with supervisor and staff



DECLARATION

I the undersigned have assessed the work, titled above, and declare that there is no significant risk / the risks

will be controlled by the methods stated on this form (delete as applicable) and that the work will be carried

out in accordance with Departmental codes of practice.

Name………Joana Valls and Philomene Rabu………………………………………..

Signed………………………………x……………………………

Date…26/11/2010…………………….



5.2.1.6. Tables of experimentation

Table 15 E.coli & Total coliform removal

E.coli Other Coliform Total coliform % removal

30/11/2010

A (rain) NA NA NA

B (mix) 48 6 54

C (raw) 49 24 73

D (right) 1 1 98.14815

E (left) 2 2 96.2963

F (right) 31 31 42.59259

G (left) 16 16 70.37037

01/12/2010

A (rain) 1 2

B (right) 21 42 22.22222

C (left) 7 14 74.07407

D (right) Too many to count TMTC 0

E (left) 17 17 0

07/12/2010

A (mix) 40 20 60

B (rain) 5 5

C (raw) 37 48 96

D (right) Too many too count TMTC 0

E (left) 13 13 0

F (right) 13 TMTC TMTC 0

G (left) 25 27 52 13.33333

08/12/2010

A (regents) 17 19 38

B (right) 119 119 0

C (left) 8 8 0

D (right) 11 11 71.05263

E (left) 18 1 19 84.03361

10/12/2010

A (regents) 48 28 76

B (right) 33 33 13.15789

C (left) 2 2 94.73684

D (right) 27 8 16 78.94737

E (left) 30 26 52 31.57895

15/12/2010

A (regents) 135 33 168

B (right) 4 1 5 68.75

C (left) 15 15 71.15385

D (right) 3 89 92 45.2381

E (left) 3 3 6 96.42857



11/01/2011

A (top R) 0 20 20

B (top L) 0 6 6

C (filtered R) 2 1 3

D (filtered L) 1 4 5

E (filtered R2) 1 20 21 0

F (filtered L2) 0 57 57 0

G (filtered R3) 2 57 59 0

H (filtered L3) 2 8 10 0

12/01/2011

A(raw) 43 13 56

B(right mixed) 33 22 55

C(left mixed) 20 24 44

D(right filterd) 3 3 6 70

E(left filterd) 5 13 18 0

F(R 1h30) 5 22 27 50.91

G(L 1h30) 6 55 61 0

14/01/2011

A(raw) 39 30 69



D(right filterd) 4 4 92.72727

E(left filterd) 12 12 72.72727

F(R 1h30) 9 2 11 70.27027

G(L 1h30) 50 50 12.2807

18/01/2011

A(raw) 105 71 176



D(right filterd) 12 3 15 59.45946

E(left filterd) 15 2 17 70.17544

F(R 1h30) 19 40 59 60.92715

G(L 1h30) 49 1 50 65.03497

19/01/2011

A(raw) 43 108 151





F(R 1h30) 8 8 86.44068

G(L 1h30) 1 60 61 32.96703

20/01/2011

A(raw) 52 53 105







F(R 1h30) 1 29 30 61.53846

G(L 1h30) 10 42 52 48

25/01/2011

A(raw) 111 65 176



D(right filterd) 7 1 8 89.74359

E(left filterd) 16 16 84

F(R 1h30) 8 8 92.07921

G(L 1h30) 64 64 30.43478

26/01/2011

A(raw) 28 53 81



D(right filterd) 1 21 22 78.21782


F(R 1h30) 1 20 21 78.78788

G(L 1h30) 52 52 41.57303

28/01/2011

A(raw) 5 14 19

B(right mixed) 49 49



E(left filterd) 1 30 31 65.16854

F(R 1h30) 3 58 61 0

G(L 1h30) 25 25 85.87571

02/02/2011

A(raw) 19 19





F(R 1h30) 29 2 31 0

G(L 1h30) 44 5 49 51

04/02/2011

A(raw) 87 6 93



D(right filterd) 51 51 0

E(left filterd) 22 22 78

F(R 1h30) 4 95 99 3.883495

G(L 1h30) 2 127 129 0

08/02/2011 A(raw) 69 4 73







F(R 1h30) 3 23 26 25.71429

G(L 1h30) 11 61 72 0

09/02/2011

A(raw) 15 22 37





F(R 1h30) 20 20 0

G(L 1h30) 2 55 57 3.389831

10/02/2011

A(raw) 49 11 60



D(right filterd)

113 113 0


F(R 1h30) 35 35 0

G(L 1h30) 7 44 51 0

15/02/2011

A(raw) 51 95 146




E(left filterd) 0 13 13 66.66667

F(R 1h30) 0 7 7 63.15789

G(L 1h30) 3 30 33 37.73585

17/02/2011

A(raw)


C(left mixed) 0


E(left filterd) 0 100

F(R 1h30) 20 20 16.66667

G(L 1h30) 0 100

25/02/2011

A(raw) 80 6 86


C(left mixed) 37 37


E(left filterd) 14 1 15 0

F(R 1h30) 19 5 24 11.11111

G(L 1h30) 14 14 62.16216



01/03/2011 A(raw) 50 1 51





F(R 1h30) 100 100 0

G(L 1h30) 8 33 41 18

Table 16 Dissolved oxygen

mg/L Raw Rain R (mix) L (mix) R (24h) L (24h) R (1h30) L (1h30) R (2h30) L

(2h30)

23/11/2010 7.7 5.36 6.14 6.14 4.65 4.65 6.55 6.46

25/11/2010 5.27 5.36 6.14 6.14 4.65 4.65 6.52 5.77

29/11/2010 8.84 6.45 7.07 7.07 4.67 1.55 4.57 6.34

01/12/2010 8.94 5.72 5.72 5.8 5.44 6.44 7.08

06/12/2010 8.56 8.05 5.72 5.72 5.7 1.68 6.23 6.24

07/12/2010 9.35 5.72 5.72 5.85 4.83 5.9 5.83

09/12/2010 9.14 5.72 5.72 4.45 2.9 6.72 6.27

14/12/2011 10.5 5.72 5.72 4.26 3.98 3.5 5.57

16/12/2011 9.15 5.72 5.72 5.4 2.8 5.4 4.29

17/12/2011 11 5.72 5.72 5.4 2.8 5.4 4.29

10/01/2011 11 5.23 5.26 2.61 2.45 2.86 3.36 5.1 5.59

11/01/2011 9.89 6.51 6.93 5.13 4.38 5.67 5.24

13/01/2011 8.83 7.66 6.31 4.87 4.23 5.79 5.79

17/01/2011 8.5 7.18 5.52 4.48 2.93 5.74 4.9

18/01/2011 7.96 6.72 6.09 4.79 4.41 5.74 4.9

20/01/2011 7.96 6.2 6.21 4.18 3.88 4.53 4.67

24/01/2011 7.33 5.35 5.29 3.86 3 4.62 4.95

25/01/2011 6.91 6.25 5.78 4.42 4.75 4.72 5.01

27/01/2011 8.38 5.57 5.26 3.74 2.91 4.08 5.06

31/01/2011 10.3 6.73 6.42 4.15 2.91 4.52 5.72

02/02/2011 8.73 6.54 6.3 5.6 4.5 4.52 5.72

03/02/2011 8.82 7.74 6.36 4.17 4.34 4.58 5.06

07/02/2011 7.2 5.71 5.8 4.49 3.07 4.16 5.05

08/02/2011 7.6 5.74 5.8 5.12 4.11 4.25 5.57

10/02/2011 6.69 5.56 5.75 5.29 3.98 3.39 4.31

15/02/2011 10.1 6.73 6.89 4.22 2.95 3.22 5.36

17/02/2011 8.9 7.25 6.25 5.25 3.97 3.56 5.42

21/02/2011 9.36 7.84 7.22 5.2 4.08 4.7 5.23

22/02/2011 9.54 7.22 6.96 5.6 5.35 4.34 6.07

24/02/2011 8.79 6.83 7.28 5.4 4.71 3.99 4.51

28/02/2011 10.8 7.75 7.22 5.12 4.02 4.37 4.47



Table 17 UV 254

UV Raw Rain R (mix) L (mix) R (24h) L (24h) R (1h30) L (1h30)

22/11/2010 0.252 0.144 0.144

23/11/2010 0.094 0.101 0.097

24/11/2010 0.195 0.195 0.12 0.12 0.106 0.105 0.112 0.107

25/11/2010 0.199 0.199 0.132 0.132 0.107 0.103 0.113 0.134

29/11/2010 0.2 0.041 0.126 0.126 0.113 0.12 0.119 0.114

01/12/2010 0.042 0.102 0.103 0.071 0.058

06/12/2010 0.235 0.052 0.1 0.1 0.051 0.053 0.073 0.07

07/12/2010 0.219 0.081 0.08 0.103 0.1

09/12/2010 0.214 0.116 0.119 0.165 0.18

14/12/2011 0.236 0.173 0.163 0.16 0.174

16/12/2011 0.255 0.163 0.164 0.171 0.191

17/12/2011 0.219

10/01/2011 0.16 0.08 0.14 0.073 0.121 0.075

11/01/2011 0.24 0.219 0.205 0.174 0.177 0.182 0.162

13/01/2011 0.24 0.223 0.219 0.186 0.16 0.184 0.167

17/01/2011 0.27 0.223 0.221 0.167 0.159 0.188 0.172

18/01/2011 0.35 0.268 0.255 0.171 0.17 0.188 0.172

20/01/2011 0.31 0.246 0.236 0.188 0.191 0.195 0.199

24/01/2011 0.263 0.215 0.238 0.194 0.18 0.197 0.19

25/01/2011 0.248 0.236 0.23 0.2 0.172 0.197 0.195

27/01/2011 0.217 0.214 0.209 0.183 0.188 0.196 0.194

31/01/2011 0.237 0.219 0.217 0.19 0.185 0.206 0.21

02/02/2011 0.275 0.22 0.228 0.198 0.197 0.208 0.205

03/02/2011 0.274 0.233 0.227 0.207 0.188 0.2 0.195

07/02/2011 0.289 0.245 0.238 0.195 0.19 0.205 0.203

08/02/2011 0.267 0.218 0.221 0.193 0.194 0.198 0.201

02/10/2011 0.269 0.223 0.226 0.181 0.184 0.094 0.092

15/02/2011 0.259 0.223 0.235 0.173 0.158 0.17 0.175

17/02/2011 0.289 0.245 0.228 0.193 0.192 0.205 0.212

21/02/2011 0.278 0.258 0.255 0.23 0.21 0.216 0.233

22/02/2011 0.313 0.272 0.287 0.221 0.207 0.222 0.218

24/02/2011 0.308 0.245 0.246 0.196 0.172 0.143 0.166

28/02/2011 0.3866 0.3175 0.3063 0.2394 0.2239 0.2459 0.2433



Table 18 pH

pH

Raw Rain R (mix) L (mix) R (24h) L (24h) R (1h30) L (1h30)

23/11/2010 8.2 8.2 8.2 8.2 8.2 8

25/11/2010 8.1 8 8 8.1 8

29/11/2010 8.2 8 8 8 8 8 7.9 7.8

01/12/2010 8 8 8 7.8 7.8 7.8 7.8

06/12/2010 8.2 8 8 8 7.6 7.8 7.8 7.6

07/12/2010 8.2 7.6 7.8 7.8 7.6

09/12/2010 8.2 7.8 7.6 8 8.1

14/12/2011 8.2 7.9 8 7.9 7.9

16/12/2011 7.9 7.7 7.6 7.9 7.9

17/12/2011 8.6

10/01/2011 8.6 8.5 7.8 7.9 7.9 8

11/01/2011 8.3 8.4 8.4 8.2 7.9 8.2 8.1

13/01/2011 8.3 8.4 8.4 8.3 8.1 8.2 8.2

17/01/2011 8.3 8.4 8.4 8.1 8.3 8.2 8

18/01/2011 8.2 8.4 8.3 8.2 8.1 8.2 8.2

20/01/2011 8.1 8.3 8.4 8.3 8.2 8.1 8.2

24/01/2011 8.2 8.3 8.4 8.3 8.1 8.1 8.2

25/01/2011 8.2 8.3 8.3 8.2 8.1 8.1 8.2

27/01/2011 8.3 8.3 8.2 8.1 8.1 8.1 8.1

31/01/2011 8.6 8.5 8.4 8.1 8 8 8.2

02/02/2011 8.3 8.1 8.1 8.1 8 8.1 8.2

03/02/2011 8.3 8.2 8.3 8.1 8.1 8.1 8.1

07/02/2011 8.3 8.4 8.4 8.2 8.1 8.1 8.2

08/02/2011 8.4 8.4 8.4 8.3 8.2 8.2 8.2

10/02/2011 8.5 8.4 8.4 8.3 8.3 8.1 8.1

15/02/2011 8.5 8.5 8.6 8.2 8.1 8 8

17/02/2011 8.5 8.5 8.6 8.2 8.1 8 8.1

21/02/2011 8.5 8.5 8.5 8.2 8.2 8.1 8

22/02/2011 8.5 8.4 8.4 8.2 8.2 8.4 8.3

24/02/2011 8.6 8.5 8.5 8.2 8.2 8.2 8.2

28/02/2011 8.6 8.4 8.5 8.2 8.2 8.2 8.1



Table 19 Head loss

Right (24h) Left (24h) Right (45') Left (45') Right (1h30) Left (1h30)

22/11/10

23/11/10 9.4 3.1 0.1 3.9

24/11/10 4.9 9.1 3.9 2.5

25/11/10 17.6 2 3.7 4.9

29/11/10 3.9 9 10 8.5 3.5 7

01/12/10 3 4.5 4.3 19.2

06/12/10 4.2 4.3 6 8.5

07/12/10 3.9 5.1 2.2 5.4

09/12/10 3.8 3.6 3.8 5.8

14/12/11 3.6 3.4 4.5 7.5 3.6 4.3

16/12/11 5.2 6.5 4 3.5 3.8 3.8

17/12/11

10/01/11 3.1 4 2.5 3 2.9 3.6

11/01/11 3.5 3.5 5.1 8.4 3.3 3.9

13/01/11 5 5.3 3.9 5.6

17/01/11 4.5 4.5 4.4 6.5

18/01/11 5.5 7.8 8.6 10.1 5.5 6.5

20/01/11 5.5 7 8 11 6.3 8.5

24/01/2011 6.6 6.4 6.3 7.1 5.8 7.3

25/01/2011 7.6 9.1 9 12 7 9

27/01/2011 7.5 4.5 10.5 6.5 5 2

31/01/2011 7.4 4.3 8.5 3

02/02/2011 9.5 2.3 11 6 8 3

03/02/2011 9.6 4.7 12.5 6.5 8.5 5.5

07/02/2011 11 5.5 16 7 10.5 5

08/02/2011 14.5 7 11.5 6

10/02/2011 14 6 14 6

15/02/2011 9.6 11.5 7.7 13

17-Feb

21-Feb 15 6 27 11 18.5 5

22-Feb 7.5 9.5 6 9 14 7

24/02/2011 6.5 8.5 16 10

28/02/2011 14.5 15 10 9



Table 20 Temperature change

Raw Rain R (mix) L (mix) R (24h) L (24h) R (1h30) L (1h30)

22/11/2011 6

23/11/2010 6 18 18 18.8 18.8

25/11/2010 5 13 13 17 17

29/11/2010 3 19 11 11 12 12 18 18

01/12/2010

06/12/2010 1.9 8.5 12 12 20.5 20.5 19.9 19.7

07/12/2010 2 20.7 20.5 20 19.8

09/12/2010 2 23.5 23.6 22 21.5

14/12/2011 3.5 22 22.6 19 18

16/12/2011 6.6 22 22 20.9 21

17/12/2011 1

10/01/2011 19.7 19.5 19.1 19.8 19.8 19.6

11/01/2011 4.7 16.2 16.3 19.8 20.5 21.1 21.1

13/01/2011 6 16 16.4 21 21 20.8 21.2

17/01/2011 9 16.7 19.7 20.7 20.4 20 20.2

18/01/2011 7.8 21.6 21.2 21.5 21.2 20 20.2

20/01/2011 6 16.2 18.8 21.2 21.2 20.3 20.5

24/01/2011 6 17.4 17.8 20.8 21 20.5 20.1

25/01/2011 6 19.6 18.9 22.4 22 20.4 20

27/01/2011 4.7 16.2 18.2 20.9 21.1 20.2 19.7

31/01/2011 2.5 15.3 15.6 20.2 20.2 21.4 21

02/02/2011 3.2 15.9 16.2 20.1 20.5

03/02/2011 8.7 17 18.4 21.3 21 20.4 21.1

07/02/2011 8 15.6 16 18.5 19.1 19.2 18.5

08/02/2011 11.5 17.8 16 19.6 20.8 19.8 19.2

10/02/2011 8 16.7 15.6 17.6 18.3 19.4 18.8

15/02/2011 6.9 14.3 14.3 18.4 18.5 18.1 18.4

17/02/2011

21/02/2011 5.5 14.1 13.6 16.7 17.6 19.7 17.5

22/02/2011 7 14.6 15 17.3 17.7 18.1 17.8

24/02/2011 10.7 16.2 17.6 19.6 19.5 19.5 19.3

28/02/2011 6.8 14.6 14.9 18.1 18.7 17.9 18


Table 21 Pesticides first run

Seeded Tank (µg/ml)

Type 05/02/2011 07/02/2011 08/02/2011 15/02/2011 17/02/2011 22/02/2011 24/02/2011 28/02/2011 Average

Raw 0.436 0.845 0.231 1.147 0.111 0.152 0.487

RM 0.171 0.497 0.485 0.153 0.044 0.150 0.113 0.230

RF2 0.028 0.317 0.015 0.002 0.002 0.005 0.002 0.053

RF 0.072 0.014 0.076 0.002 0.003 0.033

Unseeded Tank (µg/ml)

Type 05/02/2011 07/02/2011 08/02/2011 15/02/2011 17/02/2011 22/02/2011 24/02/2011 28/02/2011 Average

Raw 0.436 0.845 0.231 1.147 0.111 0.152 0.487

LM 0.171 0.474 0.288 0.172 0.071 0.126 0.217

LF2 0.019 0.351 0.015 0.068 0.064 0.115 0.051 0.098

LF 0.072 0.366 0.008 0.244 0.069 0.184 0.015 0.137

Table 22 Pesticides second run

Seeded Tank (µg/ml)

Type 05/02/2011 07/02/2011 08/02/2011 15/02/2011 17/02/2011 22/02/2011 24/02/2011 28/02/2011 Average

Raw 0.437 0.598 0.189 1.314 0.120 0.108 0.461

RM 0.103 0.482 0.556 0.161 0.035 0.153 0.101 0.227

RF2 0.028 0.362 0.034 0.003 0.003 0.007 0.003 0.063

RF 0.420 0.078 0.003 0.003 0.126

Unseeded Tank (µg/ml)

Type 05/02/2011 07/02/2011 08/02/2011 15/02/2011 17/02/2011 22/02/2011 24/02/2011 28/02/2011 Average

Raw 0.437 0.598 0.189 1.314 0.120 0.108 0.461

LM 0.200 0.602 0.346 0.159 0.094 0.087 0.248

LF2 0.019 0.348 0.008 0.069 0.051 0.027 0.027 0.078

LF 0.330 0.075 0.356 0.145 0.179 0.100 0.129 0.017 0.166

0 | P a g e


Table 23 Pesticides

S Date Type

W

(g) W (g) Volume

Retension Time (min) Area Concentration Conversion (µg/ml)

Internal Metaldehyde Internal Metaldehyde Internal Metaldehyde Internal Metaldehyde

1

5/2/07

Raw 0.000

2 RM 3.500 1.116 0.839 8.37 8.49 14983 89428 2.554 14.381 0.030 0.171

3 LM 3.461 1.077 0.810 8.37 8.50 9064 86283 1.614 13.881 0.020 0.171

4 RF

5 LF 3.448 1.064 0.800 8.38 8.50 46357 6481 7.538 1.203 0.094 0.015

6 RF2 3.168 0.784 0.589 8.37 8.49 65300 9354 10.548 1.660 0.179 0.028

7 LF2 2.830 0.446 0.336 8.37 8.49 212221 2979 33.888 0.647 1.010 0.019

8

7/2/07

Raw 3.744 1.360 1.023 8.37 8.49 7155 279734 1.310 44.614 0.013 0.436

9 RM 3.617 1.233 0.927 8.37 8.50 19851 288692 3.327 46.037 0.036 0.497

10 LM

11 RF

12 LF 3.528 1.144 0.860 8.37 8.50 8442 37692 1.515 6.162 0.018 0.072

13 RF2

14 LF2

15

8/2/07

Raw 3.777 1.393 1.048 8.36 8.47 15684 556384 2.665 88.564 0.025 0.845

16 RM 3.128 0.744 0.559 8.37 8.49 9656 169595 1.708 27.117 0.031 0.485

17 LM 3.180 0.796 0.598 8.37 8.50 11753 177314 2.041 28.343 0.034 0.474

18 RF 3.451 1.067 0.802 8.37 8.49 16627 5764 2.815 1.089 0.035 0.014

19 LF 3.372 0.988 0.742 8.37 8.49 10315 170147 1.812 27.204 0.024 0.366

20 RF2 3.480 1.096 0.824 8.37 8.50 9036 163429 1.609 26.137 0.020 0.317

21 LF2 3.492 1.108 0.833 8.37 8.49 9485 182807 1.680 29.215 0.020 0.351

22 15/2/07 Raw 3.773 1.389 1.044 8.37 8.49 7213 150511 1.319 24.085 0.013 0.231

65


23 RM 3.774 1.390 1.045 8.37 8.50 7305 99631 1.334 16.002 0.013 0.153

24 LM 3.521 1.137 0.855 8.37 8.50 7484 153966 1.363 24.634 0.016 0.288

25 RF 3.911 1.527 1.148 8.39 8.50 5543 53759 1.054 8.714 0.009 0.076

26 LF 3.964 1.580 1.188 8.37 8.49 10791 111865 1.888 17.945 0.016 0.151

27 RF2 3.429 1.045 0.786 8.38 8.50 46357 6481 7.538 1.203 0.096 0.015

28 LF2 3.459 1.075 0.808 8.37 8.49 212221 2979 33.888 0.647 0.419 0.008

29

17/2/07

Raw 3.241 0.857 0.644 8.37 8.50 10807 464223 1.890 73.923 0.029 1.147

30 RM

31 LM 4.065 1.681 1.264 8.39 8.50 6223 135620 1.162 21.719 0.009 0.172

32 RF

33 LF 3.672 1.288 0.968 8.39 8.50 9667 147608 1.709 23.624 0.018 0.244

34 RF2 4.336 1.952 1.467 8.37 8.49 4022 1021 0.813 0.336 0.006 0.002

35 LF2 4.762 2.378 1.788 8.37 8.49 5172 74928 0.995 12.077 0.006 0.068

36

22/2/07

Raw 4.001 1.617 1.216 8.37 8.50 5937 83743 1.117 13.478 0.009 0.111

37 RM 4.132 1.748 1.314 8.37 8.49 6314 35246 1.177 5.773 0.009 0.044

38 LM

39 RF 4.293 1.909 1.435 8.37 8.50 4579 691 0.901 0.283 0.006 0.002

40 LF 4.390 2.006 1.508 8.37 8.49 4160 64702 0.834 10.453 0.006 0.069

41 RF2 4.457 2.073 1.559 8.37 8.49 5176 474 0.996 0.249 0.006 0.002

42 LF2 4.387 2.003 1.506 8.39 8.50 5618 59670 1.066 9.653 0.007 0.064

43

24/2/07

Raw

44 RM 4.571 2.187 1.645 8.37 8.49 4267 153949 0.851 24.631 0.005 0.150

45 LM 4.393 2.009 1.511 8.37 8.49 4341 66794 0.863 10.785 0.006 0.071

46 RF

47 LF 4.347 1.963 1.476 8.37 8.49 10315 170147 1.812 27.204 0.012 0.184

48 RF2 4.181 1.797 1.351 8.37 8.49 5395 3253 1.031 0.690 0.008 0.005

49 LF2 4.323 1.939 1.458 8.39 8.50 4168 104114 0.836 16.714 0.006 0.115

65


50

28/2/07

Raw 4.573 2.189 1.646 8.37 8.49 3458 156041 0.723 24.963 0.004 0.152

51 RM 4.513 2.129 1.601 8.37 8.50 7661 112893 1.391 18.108 0.009 0.113

52 LM 4.302 1.918 1.442 8.37 8.50 7661 112893 1.391 18.108 0.010 0.126

53 RF 4.317 1.933 1.453 8.37 8.49 4981 1250 0.965 0.372 0.007 0.003

54 LF 4.296 1.912 1.438 8.37 8.50 4202 12282 0.841 2.125 0.006 0.015

55 RF2 4.137 1.753 1.318 8.37 8.49 3804 598 0.778 0.269 0.006 0.002

56 LF2 4.321 1.937 1.456 8.37 8.49 5171 45578 0.995 7.414 0.007 0.051

65


Sample Date Type W (g) W (g) Volume

Retension Time (min) Area Concentration Conversion (µg/ml)

Internal Metaldehyde Internal Metaldehyde Internal Metaldehyde Internal Metaldehyde

1

5/2/07

Raw 0.000

2 RM 3.500 1.116 0.839 8.370 8.500 10307 74595 1.477 8.676 0.018 0.103

3 LM 3.461 1.077 0.810 8.370 8.490 12471 141937 1.719 16.218 0.021 0.200

4 RF

5 LF 3.448 1.064 0.800 8.370 8.500 11587 233027 1.620 26.419 0.020 0.330

6 RF2 3.168 0.784 0.589 8.370 8.490 17152 12066 2.243 1.674 0.038 0.028

7 LF2 2.830 0.446 0.336 4.990 8.500 2213 2877 0.570 0.645 0.017 0.019

8

7/2/07

Raw 3.744 1.360 1.023 8.370 8.500 8219 396319 1.243 44.706 0.012 0.437

9 RM 3.617 1.233 0.927 8.370 8.500 22436 396059 2.835 44.677 0.031 0.482

10 LM

11 RF

12 LF 3.528 1.144 0.860 8.370 8.500 9815 54643 1.422 6.442 0.017 0.075

13 RF2

14 LF2

15

8/2/07

Raw 3.777 1.393 1.048 8.360 8.470 15684 556384 2.079 62.632 0.020 0.598

16 RM 3.128 0.744 0.559 8.370 8.490 13051 274995 1.784 31.119 0.032 0.556

17 LM 3.180 0.796 0.598 8.370 8.500 17593 318594 2.293 36.002 0.038 0.602

18 RF 3.451 1.067 0.802 8.370 8.500 14969 298389 1.999 33.739 0.025 0.420

19 LF 3.372 0.988 0.742 8.370 8.500 11587 233027 1.620 26.419 0.022 0.356

20 RF2 3.480 1.096 0.824 8.370 8.490 10705 263612 1.521 29.844 0.018 0.362

21 LF2 3.492 1.108 0.833 8.370 8.490 10841 255989 1.537 28.991 0.018 0.348

22

15/2/07

Raw 3.773 1.389 1.044 8.370 8.500 7015 173172 1.108 19.716 0.011 0.189

23 RM 3.774 1.390 1.045 8.370 8.500 9241 147008 1.357 16.786 0.013 0.161

24 LM 3.521 1.137 0.855 8.370 8.490 10923 261443 1.546 29.601 0.018 0.346

25 RF 3.911 1.527 1.148 8.370 8.490 6790 77007 1.083 8.947 0.009 0.078

26 LF 3.964 1.580 1.188 8.370 8.490 11395 150940 1.599 17.226 0.013 0.145

27 RF2 3.429 1.045 0.786 8.370 8.490 13752 20691 1.863 2.640 0.024 0.034 65


28 LF2 3.459 1.075 0.808 8.370 8.490 212221 2979 24.089 0.656 0.298 0.008

29

17/2/07

Raw 3.241 0.857 0.644 8.370 8.500 15849 753194 2.098 84.672 0.033 1.314

30 RM

31 LM 4.065 1.681 1.264 8.370 8.490 6613 176297 1.063 20.066 0.008 0.159

32 RF

33 LF 3.672 1.288 0.968 8.370 8.490 7714 151866 1.186 17.330 0.012 0.179

34 RF2 4.336 1.952 1.467 8.370 8.490 5374 1704 0.924 0.513 0.006 0.003

35 LF2 4.762 2.378 1.788 8.370 8.490 6755 106759 1.079 12.278 0.006 0.069

36

22/2/07

Raw 4.001 1.617 1.216 8.370 8.490 7576 127279 1.171 14.577 0.010 0.120

37 RM 4.132 1.748 1.314 8.370 8.500 5521 37697 0.941 4.544 0.007 0.035

38 LM

39 RF 4.293 1.909 1.435 8.370 8.490 5797 1123 0.972 0.448 0.007 0.003

40 LF 4.390 2.006 1.508 8.370 8.490 7780 131873 1.194 15.091 0.008 0.100

41 RF2 4.457 2.073 1.559 8.370 8.500 5797 752 0.972 0.407 0.006 0.003

42 LF2 4.387 2.003 1.506 8.370 8.490 5061 65259 0.889 7.631 0.006 0.051

43

24/2/07

Raw

44 RM 4.571 2.187 1.645 8.370 8.500 5281 221533 0.914 25.132 0.006 0.153

45 LM 4.393 2.009 1.511 8.370 8.490 6553 123656 1.056 14.171 0.007 0.094

46 RF

47 LF 4.347 1.963 1.476 8.370 8.490 6188 167060 1.016 19.032 0.007 0.129

48 RF2 4.181 1.797 1.351 8.370 8.490 7677 5611 1.182 0.951 0.009 0.007

49 LF2 4.323 1.939 1.458 8.370 8.490 4467 32741 0.823 3.989 0.006 0.027

50

28/2/07

Raw 4.573 2.189 1.646 8.370 8.490 3458 156041 0.710 17.798 0.004 0.108

51 RM 4.513 2.129 1.601 8.370 8.490 5612 141486 0.951 16.168 0.006 0.101

52 LM 4.302 1.918 1.442 8.370 8.490 6098 109093 1.005 12.540 0.007 0.087

53 RF 4.317 1.933 1.453 8.370 8.490 4981 1250 0.880 0.463 0.006 0.003

54 LF 4.296 1.912 1.438 8.370 8.490 5463 18918 0.934 2.441 0.006 0.017

55 RF2 4.137 1.753 1.318 8.370 8.490 5319 1148 0.918 0.451 0.007 0.003

56 LF2 4.321 1.937 1.456 8.370 8.490 4467 32741 0.823 3.989 0.006 0.027

65

optimisation of household slow sand filters

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