biodegradation of oil and grease in upflow anaerobic sludge
TRANSCRIPT
2005/2006
FOR PALM OIL MILL EFFLUENT TREATMENT
LEE CHEE SIANG
UPFLOW ANAEROBIC SLUDGE BLANKET REACTORBIODEGRADATION OF OIL AND GREASE IN
5th May 2006 5th May 2006
Prof. Ir. Dr. Zaini Ujang Melaka 75000 Melaka 41, Jalan Banda Kaba
“I hereby declare that I have read this project
report and in my opinion this project report is
sufficient in terms of scope and quality for the
award of the degree of Master of Engineering
(Civil- Environmental Management)”
Signature : .....
Name of Supervisor : Pro
Date : .....5th
...........................................
f. Ir. Dr. Zaini Ujang
.......................................... May 2006
BIODEGRADATION OF OIL AND GREASE IN UPFLOW ANAEROBIC SLUDGE
BLANKET REACTOR FOR PALM OIL MILL EFFLUENT TREATMENT
LEE CHEE SIANG
A project report submitted in partial fulfillment
of the requirements for the award of the degree
of Master of Engineering (Civil- Environmental
Management)
Faculty of Civil Engineering
Universiti Teknologi Malaysia
May 2006
I declare that this project report entitled “Biodegradation of Oil and Grease in Upflow
Anaerobic Sludge Blanket Reactor for Palm Oil Mill Effluent Treatment” is the result of
my own research except as cited in the references. The project report has not been
accepted for any degree and is not concurrently submitted in candidature of any other
degree.
Signature : .....
Name : Lee
Date : .....5th
...............................................
Chee Siang
............................................... May 2006
To my beloved mother and father
ACKNOWLEDGEMENT
In preparing this project report, I was in contact with many people, researchers,
academicians and practitioners. They have contributed towards my understanding and
thoughts. In particular, I wish to express my sincere appreciation to my main project
report supervisor, Professor Ir. Dr. Zaini Ujang, for encouragement, guidance, critics and
friendship. Without his continued support and interest, this project report would not have
been the same as presented here.
I am also indebted to Universiti Teknologi Malaysia (UTM) for provide facilities
for my master project. Librarians at UTM, also deserve special thanks for their assistance
in supplying the relevant literatures.
My fellow postgraduate students should also be recognized for their support. My
sincere appreciation also extends to all my colleagues and others who have provided
assistance at various occasions. Their views and tips are useful indeed. Unfortunately, it is
not possible to list all of them in this limited space. I am grateful to all my family
members.
ABSTRACT
The upflow anaerobic sludge blanket (UASB) reactor is a system in which substrate passes first through an expanded sludge bed containing a high concentration of biomass. The sludge in the reactor may exist in granular or flocculent form. Most of the substrate removal takes place in sludge bed and the remaining portion of the substrate passes through a less dense biomass, sludge blanket. UASB reactor is one of the innovative high rate anaerobic digester that able to biodegrade the oil and grease (O&G) in palm oil mill effluent (POME). This study aimed to evaluate the biodegradation of O&G in raw POME using UASB. The objectives of this study were to determine the O&G biodegradation and chemical oxygen demand (COD) removal efficiencies for the treatment of POME using UASB and evaluate the UASB’s performance in relation to various control variables. The characteristic of the raw POME were determined for 5 respective samples collected from Bukit Besar, Kulai. Hexane was used as the solvent for O&G extraction by using separatory funnel. The experiments of O&G biodegradation and COD removal were designed using full factorial design. The selected factors were hydraulic retention time (HRT), influent strength based on COD and influent pH. The steady state of the UASB was achieved after 26 days acclimatization with the COD removal constant at 62%. Then, the factorial designed experiments were conducted and percentage of O&G biodegradation and COD removal as the responses. The optimum combination of operating parameters was HRT 12.9 hrs, influent 5000 mg/L COD and influent pH 7 which success to remove 61.7% COD and biodegrade 62.9% O&G. Statistical analysis was used to study the UASB’s performance in relation to various control operating parameters. The main factors that have significant effect on O&G biodegradation and COD removal were defined statistically.
ABSTRAK
Pencerna lapisan enap cemar anaerobik alir-naik (UASB) adalah satu sistem di mana bahan pemula akan bergerak melalui satu lapisan kembangan enap cemar terpendam yang mengandungi biojisim yang tinggi kepekatannya. Biojisim yang ada dalam pencerna boleh wujud dalam bentuk butiran atau gumpalan. Kebanyakan pencernaan bahan pemula berlaku dalam biojisim terpendam dan baki bahan pemula bergerak melalui satu lapisan yang kurang tumpat, iaitu lapisan kembangan enap cemar. Pencerna lapisan enap cemar anaerobik alir-naik adalah salah satu pencerna anaerobik berkadar tinggi yang mampu membiodegradasi minyak dan lemak (O&G) yang terkandung dalam effluen kilang minyak sawit (POME). Kajian ini bertujuan untuk mengkaji biodegradasi bagi minyak dan lemak yang terkandung dalam effluen kilang minyak sawit mentah dengan menggunakan pencerna lapisan enap cemar anaerobik alir-naik. Objektif-objektif bagi kajian ini adalah menentukan kecekapan biodegradasi bagi minyak dan lemak dan pengurangan permintaan oksigen secara kimia (COD) dalam rawatan effluen kilang minyak sawit dan juga menaksir prestasi pencerna berhubung dengan pelbagai kawalan parameter-parameter operasi. Ciri-ciri bagi 5 sampel berlainan effluen kilang minyak sawit mentah dari Bukit Besar, Kulai ditentukan. Heksana digunakan sebagai pelarut untuk pengekstrakan minyak dan lemak dengan menggunakan corong pemisah. Eksperimen-eksperimen biodegradasi minyak dan lemak dan pengurangan permintaan oksigen secara kimia direka secara faktoria penuh. Faktor-faktor yang dipilih adalah masa penahanan hidrolik (HRT), kekuatan influen berdasarkan permintaan oksigen secara kimia and pH influen. Keadaan mantap bagi pencerna tersebut dicapai selepas 26 hari penyesuaian dengan pengurangan permintaan oksigen secara kimia malar pada 62%. Seterusnya, eksperimen-eksperimen yang direka mula dijalankan dan peratusan bagi biodegradasi minyak dan lemak serta pengurangan permintaan oksigen secara kimia sebagai reaksi-reaksinya. Kombinasi parameter-parameter operasi yang terbaik adalah HRT 12.9 jam, kekuatan influen 5,000 mg/L COD dan pH 7 di mana ia berjaya mengurangkan 62% COD dan sebanyak 63% minyak dan lemak terbiodegradasi. Analisis secara statistik digunakan untuk mengkaji pretasi pencerna berhubung dengan pelbagai kawalan parameter-parameter operasi. Faktor-faktor utama yang mempunyai kesan nyata dan penting kepada biodegradasi minyak dan lemak dan pengurangan permintaan oksigen secara kimia telah dikenalpasti secara statistik.
TABLE OF CONTENTS
CHAPTER TITLE PAGE
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENT iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES x
LIST OF FIGURES xii
LIST OF ABBREVIATIONS xiv
LIST OF SYMBOLS xvii
1 INTRODUCTION
1.1 The Palm Oil Industry in Malaysia 1
1.2 Properties of Palm Oil 5
1.3 Palm Oil Processing 8
1.4 Potential Adverse Environmental Impacts and Environmental
Improvement in Sustainable Development of Palm Oil
Industry 11
1.5 Problem Statements 12
1.6 Scopes of Study 13
1.7 Objectives of Study 13
2 LITERATURE REVIEWS
2.1 Palm Oil Mill Effluent in Perspective 14
2.2 Oil and Grease in Palm Oil Mill Effluent 17
2.2.1 Chemistry of Fats and Oils 18
2.2.2 Biochemistry of Fats and Oils 21
2.3 Anaerobic Fermentation and Oxidation 23
2.3.1 Process Description 24
2.3.2 Microbiology 26
2.3.3 Stoichiometry of Anaerobic Fermentation and
Oxidation 30
2.3.4 Growth Kinetics 31
2.3.5 Applicability of Anaerobic Treatment 32
2.3.6 Anaerobic Treatment of Palm Oil Mill Effluent 34
2.4 Upflow Anaerobic Sludge Blanket Reactor 35
2.4.1 Design Considerations 37
2.4.2 Gas Solids Separator Device 41
2.4.3 Anaerobic Sludge Granulation 42
3 RESEARCH METHODOLOGY
3.1 Upflow Anaerobic Sludge Blanket Reactor Setup 49
3.2 Sampling of Palm Oil Mill Effluent 51
3.3 Characterization of Palm Oil Mill Effluent 52
3.4 Upflow Anaerobic Sludge Blanket Reactor Startup 52
3.5 Design of Experiments 53
4 DATA COLLECTION AND ANALYSIS
4.1 Characterization of Palm Oil Mill Effluent 55
4.2 Upflow Anaerobic Sludge Blanket Reactor Startup 56
4.3 Design of Experiments 59
4.3.1 Chemical Oxygen Demand Removal 61
4.3.2 Oil and Grease Biodegradation 65
5 DISCUSSION OF RESULTS
5.1 Characterization of Palm Oil Mill Effluent 70
5.2 Upflow Anaerobic Sludge Blanket Reactor Startup 72
5.3 Statistical Designed Experiments 74
6 CONCLUSION AND RECOMMENDATIONS
6.1 Conclusion 76
6.2 Recommendations 76
REFERENCES 78
APPENDICES
Appendix A 81
Appendix B 84
Appendix C 85
LIST OF TABLES
TABLES NO. TITLE PAGE
1.1 Area of oil palm planting and growth in the decades
of the last century. 2
1.2 Palm oil expansion in production. 4
1.3 Percentage of fatty acid composition in palm kernel,
coconut and palm oil. 7
2.1 Characteristics of individual wastewater streams. 15
2.2 Characteristics of combined palm oil mill effluent. 16
2.3 Prevailing effluent discharge standard for crude
palm oil mills. 17
2.4 Acids of the fats and oils. 19
2.5 Acid content of fats and oils in percent. 19
2.6 Advantages and disadvantages of anaerobic
processes compared to aerobic processes. 33
2.7 Recommended volumetric COD loading for UASB
reactors at 30 °C to achieve 85% to 95% COD
removal. 38
2.8 Recommended volumetric organic loadings as a
function of temperature for soluble COD substrates
for 85 to 95% COD removal. 39
2.9 Applicable hydraulic retention times for treatment
of raw domestic wastewater in a 4 m high UASB
reactor. 39
2.10 Upflow velocities and reactor heights recommended
for UASB reactors. 40
2.11 Guidelines for sizing the area served by inlet feed
pipes for UASB reactor. 41
3.1 Dimension of the UASB reactor. 49
3.2 Operating parameters for the reactor startup. 53
3.3 Full factorial design of experiment with three
factors in two levels. 53
3.4 Experiments in different combination of treatment
factors in one replicate. 54
3.5 Operating parameters for the experiments in three
replicates. 54
4.1 Characteristics of raw palm oil mill effluent. 55
4.2 Data collected for the influents and effluents during
the reactor startup period. 57
4.3 Data of replicate 1 in factorial design experiment. 59
4.4 Data of replicate 2 in factorial design experiment. 59
4.5 Data of replicate 3 in factorial design experiment. 60
4.6 Data of the COD removal experiment. 61
4.7 Effect estimate summary for COD removal. 62
4.8 Analysis of variance for the COD removal data. 63
4.9 Data of the O&G biodegradation experiment. 66
4.10 Effect estimate summary for O&G biodegradation. 66
4.11 Analysis of variance for the O&G biodegradation
data. 67
LIST OF FIGURES
FIGURE NO. TITLE PAGE
1.1 The top four palm kernel oil production and exports
countries. 3
1.2 Solid fat content of cocoa butter, palm kernel oil
product and palm oil. 7
1.3 Flow diagram of palm oil extraction. 9
1.4 Refining processes for crude palm oil. 10
2.1 Anaerobic process schematic of hydrolysis,
fermentation, and methanogenesis. 25
2.2 Carbon and hydrogen flow in anaerobic digestion
process. 26
2.3 Microbial populations in anaerobic microbial
conversion of organic substrates to methane. 28
2.4 Anaerobic granules from the UASB reactor. 43
2.5 Schematic representation of the inert nuclei model. 46
2.6 Schematic representation of the multi-valence
positive ion-bonding model. 47
2.7 Schematic representation of the polymer or filament
bonding model. 47
2.8 Schematic representation of the multi-layer model. 48
3.1 Schematic diagram of the UASB reactor. 50
3.2 Front view of Kilang Sawit Bukit Besar, Kulai. 51
3.3 The sampling point of raw POME. 51
4.1 COD removal and effluent pH within the startup
period. 57
4.2 TSS and VSS removal within the startup period. 58
4.3 Scatter plot of COD removal and O&G
biodegradation in three replicates. 61
4.4 Main effects and interaction plots for COD removal. 64
4.5 2D contour plot for COD removal. 65
4.6 Main effects and interaction plots for O&G
biodegradation. 68
4.7 2D contour plot for O&G biodegradation. 69
LIST OF ABBREVIATIONS
(CH3)3N - Methylamine
2D - Two dimensions
ABR - Anaerobic baffled reactor
AMBR - Anaerobic migrating blanket reactor
Am-N - Ammoniacal nitrogen
BOD - Biochemical oxygen demand
C - Carbon
Ca(OH)2 - Calcium hydroxide
Ca5OH(PO4)3 - Calcium Hydroxide Phosphate
CaCO3 - Calcium carbonate
CB - Cocoa butter
CH3COOH - Acetic acid
CH3OH - Methanol
CH4 - Methane
CNO - Coconut oil
CO - Carbon monoxide
CO2 - Carbon dioxide
COD - Chemical oxygen demand
CPO - Crude palm oil
DS - Dissolved solids
ECP - Extracellular polymer
EQA - Environmental Quality Act
FAD - Flavin adenine dinucleotide
Fe - Ferum
FELCRA - Federal Land Consolidation and Rehabilitation Authority
FELDA - Federal Land Development Authority
FeS - Ferrous sulfide
FFB - Fresh fruit Bunch
GSS - Gas-solid separator
H2 - Hydrogen
H2O - Water
HA - Homoacetogen
HCOOH - Formic acid
HPKS 35 - Hydrogenated palm kernel stearin of melting point 35 ºC
HRT - Hydraulic retention time
IV - Iodine value
MARDI - Malaysian Agricultural Research Development Institute
Mn - Manganese
MPOB - Malaysian Palm Oil Board
NAD - Nicotinamide adenine dinucleotides
NaHCO3 - Natrium bicarbonate
NaOH - Natrium Hydroxide
NBD - Neutralized, bleached and deodorized
NH3 - Ammonia
NH4(HCO3) - Ammonium bicarbonate
NO3- - Nitrate
NRB - Nitrate reducing bacteria
O&G - Oil and grease
O2 - Oxygen
OHPA - Obligate hydrogen producing acetogens
PKO - Palm kernel oil
PKS - Palm kernel stearin
PO - Palm oil
POME - Palm oil mill effluent
PORIM - Palm Oil Research Institute of Malaysia
PORLA - Palm Oil Registration and Licensing Authority
R&D - Research and development
RBD - Refined, bleached and deodorized
RISDA - Rubber Industry Smallholders’ Development Authority
RM - Ringgit Malaysia
sCOD - Soluble chemical oxygen demand
Sdn. Bhd. - Sendirian Berhad
SFC - Solid fat content
SRB - Sulfate reducing bacteria
SRT - Solid retention time
SS - Suspended solids
SVI - Sludge volume index
TN - Total nitrogen
TPAD - Temperature phased anaerobic digestion
TVS - Total volatile solids
UASB - Upflow anaerobic sludge blanket
VFA - Volatile fatty acid
LIST OF SYMBOLS
v - Design upflow superficial velocity
% - Percent
< - Less than
> - More than
A - Reactor cross section area
atm - Atmosphere
cm - Centimeter
cm2 - Centimeter square
d - Day
Din - Inner diameter
g - Gram
g/L.d - Gram per liter per day
H - Height
hr - Hour
Kd - Endogenous decay coefficients
kg/m3.d - Kilogram per cubic meter per day
L - Liter
m - Meter
m2 - Meter square
m3 - Cubic meter
m3/d - Cubic meter per day
mg/L - Milligram per liter
mL/min - Milliliter per minutes
mm - Millimeter
Mp - Melting point
ºC - Degree of Celsius
Q - Influent flowrate
t - Tonne
Vr - Reactor volume
Vw - Working volume
Y - Synthesis yield
CHAPTER 1
INTRODUCTION
1.1 The Palm Oil Industry in Malaysia
The oil palm industry in Malaysia had a humble beginning. From a mere four
original palms introduced from West Africa to the Bogor Botanical Gardens, Indonesia in
1848, their seeds soon arrived on Malaysian shores in 1871 (Basiron and Chan, 2004).
Over the next four decades, the rubber companies in Malaysia saw their planters learning
how to grow the crop in the country. The R&D undertaken soon showed the potential of
the new crop. Following this effort, the first commercial planting was done in 1911 at
Tenammaran Estate, Kuala Selangor. There was the success of the crop that the area
expanded quickly, the most rapid increases occurring during the 1930s, 1970s and 1980s.
The growth in area during the various decades of the last century in Malaysia is shown in
Table 1.1. At the end of 2000, the area stood at 3.376 million hectares, producing 10.842
million tonnes of palm oil, 3.162 million tonnes of palm kernel, 1.384 million tonnes of
palm kernel oil and 1.639 million tonnes of palm kernel meal.
Table 1.1: Area of oil palm planting and growth in the decades of the last century (Basiron and Chan, 2004).
Years in decades Hectares % Growth
1870-1910 <350 - 1920 400 14.2 1930 20 600 5050.0 1940 31 400 52.4 1950 38 800 23.5 1960 54 638 40.8 1970 261 199 378.0 1980 1 023 306 291.8 1990 2 029 464 98.3 2000 3 376 664 66.3
In the early 1960s, the returns from oil palm were found to be better than rubber
and most of the plantation companies soon had a mix of both crops as their core business.
It was Tun Abdul Razak Hussein, the then Deputy Prime Minister of Malaysia, who
called for greater diversification into oil palm. With diminishing returns from the then
two major commodities of the country, tin and rubber, oil palm should be used as the
vehicle to eradicate rural poverty. The government’s three rural development agencies,
Federal Land Development Authority (FELDA), Federal Land Consolidation and
Rehabilitation Authority (FELCRA) and Rubber Industry Smallholders’ Development
Authority (RISDA) were responsible for planting oil palm with large areas of land that
were rehabilitated or newly opened (Basiron and Chan, 2004).
Landless people were placed as settlers in the newly opened land schemes.
Malaysian government provided them housing and infrastructure including community
halls, schools, health clinics, shops and roads. Initially, the government supported their
livelihoods until the oil palm matured when the income from the crop was sufficient to
pay off their loans. In doing so, the government was able to alleviate rural poverty using
the oil palm as the vehicle to do so.
Initial R&D into the crop was carried out by the government sector, the
Department of Agriculture. Together with the private research companies of the major
plantation groups, the work included collecting breeding materials and experimentation in
breeding, agronomy and palm oil chemistry. It was in 1969 when the Malaysian
Agricultural Research Development Institute (MARDI) was established that the mandate
for oil palm research was taken over from the Department of Agriculture. The task was
later handed to the Palm Oil Research Institute of Malaysia (PORIM) following its
establishment in 1979. On 1 May 2000, PORIM was merged with the Palm Oil
Registration and Licensing Authority (PORLA) to form the Malaysian Palm Oil Board
(MPOB) (Basiron and Chan, 2004). The mission of MPOB is to support the well-being
of the oil palm industry in Malaysia in all aspects of its activities through research,
development and services.
The oil palm only grows well in tropical climates and so all the palm kernel
producing countries are in Southeast Asia, Sub-Saharan Africa and South America
(Pantzaris and Ahmad, 2001). Figure 1.1 shows the production and exports of the top
four producing countries. The largest producer by far is Malaysia, which currently
accounts for more than 50% of world production. While two countries, Malaysia and
Indonesia together, account for about 80% of production and 88% of exports. No other
country produces more than 7% or exports more than 3% of the world total.
FA
igure 1.1: The top four palm kernel oil production and exports countries (Pantzaris and hmad, 2001).
Until the mid 1970s, Nigeria was the world’s largest producer of palm kernels
while Europe did most of the crushing and was effectively the world’s largest palm kernel
oil producer. But now all the crushing is done in the producing countries and Europe
does no palm kernel crushing at all. From 1977, Malaysia overtook both Nigeria and
Europe to become world’s biggest producer of palm kernels and of palm kernel oil.
However, in the last few years, her oleochemical industry has been absorbing very large
and increasing quantities of the oil and her lead in exports have been reduced. In fact,
Indonesia’s exports were higher than Malaysia’s in 2000 (Pantzaris and Ahmad, 2001).
The oil palm industry worldwide has provided the fastest increase in global oils
and fats supplies over the last four decades. World palm oil production increased 20-fold
from a mere 1.2 million tonnes in 1962 to 25.0 million tonnes in 2002 (Basiron et al.,
2004). The share of palm oil production in the world oils and fats complex has increased
markedly by five-fold from 4% in 1962 to 20.8% in 2002, as compared to the only two-
fold increase experienced by soybean oil during the same period. The spiky increase in
palm oil output was mostly triggered by continued worldwide expansion of the oil palm
planted area and the mature area coming into production as well as growing world
demand for vegetable oils as in Table 1.2.
Table 1.2: Palm oil expansion in production (Basiron et al., 2004).
Oils/fats 1962 (‘000 t)
% Share
2002 (‘000 t)
% Share
40yrs Average Growth p.a. (%)
World oils/fats production 30 779 - 120 477 - 3.5 Palm oil 1 234 4.0 25 034 20.8 7.8 Soybean oil 3 432 11.2 29 748 24.7 5.5 Rapeseed oil 1 163 7.5 13 326 11.1 6.3 Sunflower oil 2 294 3.4 7 611 6.3 3.0 Animal oils/fats 12 040 39.1 22 588 18.7 1.6
The status of palm oil as it is today in the world market is without doubt due to the
significant contribution by the Malaysian palm oil industry (Basiron et al., 2004). Both
Malaysia and Indonesia continue to remain the largest producers of palm oil, accounting
for 84% of the world production in 2002. In fact, the country has become a role model
for many other palm oil producing countries in their plans to urge economic development
in the agricultural sector as well as to gain foreign exchange through exports of surplus
production. In addition, oil palm is also featured as an important socio-economic crop in
most producing countries especially for alleviating rural poverty amongst poor farmers.
The raw materials used in the manufacture of oleochemicals were mainly tallow,
coconut oil or palm and palm kernel oils. Malaysia being the world’s largest producer of
palm oil and palm kernel oil is undeniably in a particularly favourable position to become
a major supplier of raw materials for both the local and overseas oleochemical industries
(Ooi and Yeong, 2000). The oleochemicals that produced from palm oil and its products
are widely used in lubricants, plastics, resins, soaps, surfactants, emulsifiers, cosmetics,
toiletries and textile chemicals.
Over the last three decades, the Malaysian palm oil industry has grown to become
an important agricultural based industry. Malaysian palm oil accounted for about 52% of
the world palm oil outputs and this industry generated RM 13 billion in export earnings
for the country (Ahmad et al., 2005). The palm oil industry faces the challenge of
balancing the environmental protection, its economic viability and sustainable
development. There is an urgent need to find a way to preserve the environment while
keeping the economy growing (Ahmad et al., 2003).
1.2 Properties of Palm Oil
The cultivation of palm oil tree Elaeis Guineensis has expanded significantly over
recent years as the demand for vegetable oils increases (Borja and Banks, 1994). The
female bunch bears about 2,500 to 3,000 fruits borne on 100 to 120 spikelets attached to a
peduncle from the axil of a frond. The fruits produce two main products, palm oil from
the outer mesocarp and palm kernel oil from the kernel within the nut (Basiron and Chan,
2004). This tree is generally believed to have originated in the jungle forests of East
Africa and there is some evidence that palm oil was used in Egypt at the time of the
Pharaohs, some 5000 years ago, but now its cultivation is confined mostly to Southeast
Asia. The variety cultivated in nearly all the world’s plantations is the hybrid Tenera, the
cross between Dura and Pisifera, which gives the highest yield of oil per hectare of any
crop (Pantzaris and Ahmad, 2001).
Generally, the oil palms in Southeast Asia yield about 4 tonnes of palm oil, 0.5
tonnes of palm kernel oil, and 0.5 tonnes of palm kernel meal, with the income equivalent
to more than 4.5 tonnes of oil. Nearly for every 8 tonnes of crude palm oil produced at
the mill, about 1 tonnes of palm kernel oil is produced. The palm fruit looks like a plum.
The outer fleshy mesocarp gives the palm oil, while the kernel, which is inside a hard
shell, gives the palm kernel oil and it is rather strange that the two oils from the same fruit
are entirely different in fatty acid composition and properties. Unfortunately, the two oils
had often been confused by nutritionists in earlier days.
In palm oil, most of the fatty acids are C16 and higher, while in palm kernel oil,
they are C14 and lower. Palm oil has iodine value (IV) 50 minimum, while palm kernel
oil has 21 maximum. Semi-solid in temperate climates, palm kernel oil can be
fractionated into solid and liquid fractions known as stearin and olein respectively. These
are then physically refined, bleached and deodorized or chemically neutralized, bleached
and deodorized to give the RBD and NBD grades used in the food industry (Pantzaris and
Ahmad, 2001). The process of fractionation can be carried out either before or after the
refining, according to conditions.
The major fatty acids in palm kernel oil are C12 (lauric acid) about 48%, C14
(myristic acid) about 16% and C18:1 (oleic acid) about 15%. No other fatty acid is
present at more than 10% and it is this heavy preponderance of lauric acid, which gives
palm kernel oil and coconut oil, their sharp melting properties, meaning hardness at room
temperature combined with a low melting point (Pantzaris and Ahmad, 2001). This is the
outstanding property of lauric oils, which determines their use in the edible field and
justifies their usually higher price compared with most other oils. Because of their low
unsaturation, the lauric oils are also very stable to oxidation. Table 1.3 shows the fatty
acid composition of palm kernel oil, its similarity to coconut oil and their differences
from palm oil, the co-product of palm kernel oil and typical non-lauric fat. Even after full
hydrogenation, the melting point of palm kernel oil does not rise much above mouth
temperature and fractionation gives a stearin which is even sharper melting.
Sharp melting fats leave a clean, cool, non-greasy sensation on the palate,
impossible to match by any of the common non-lauric oils. Figure 1.2 shows the melting
behavior in terms of solid fat content (SFC) values of palm kernel oil (PKO), palm kernel
stearin (PKS) and hydrogenated palm kernel stearin of melting point 35ºC (HPKS 35),
together with cocoa butter (CB) and palm oil (PO) for comparison.
Table 1.3: Percentage of fatty acid composition in palm kernel, coconut and palm oil (Pantzaris and Ahmad, 2001).
Fatty acids Palm kernel oil (PKO)1 Coconut oil (CNO)2 Palm oil (PO)3
C6 0.3 0.4 - C8 4.2 7.3 - C10 3.7 6.6 - C12 48.7 47.8 0.2 C14 15.6 18.1 1.1 C16 7.5 8.9 44.1 C18 1.8 2.7 4.4 C18:1 14.8 6.4 39.0 C18:2 2.6 1.6 10.6 Others 0.1 0.1 0.754
Notes: 1PORIM Survey 1984, n = 68. 2Leatherhead Food RA, Surrey, UK, Survey 1990, n = 35. 3PORIM Survey of RBD PO 1989, n = 244. 4Others = C18:3 0.37%, C20:0 0.38%.
Figure 1.2: Solid fat content of cocoa butter, palm kernel oil product and palm oil (Pantzaris and Ahmad, 2001).
Palm oil contains about 1% minor components. The major constituents are
carotenoids, vitamin E and sterols (Basiron and Chan, 2004). The carotene concentration
is around 500 to 700 ppm. Carotene has been concentrated from palm oil successfully.
The concentrate is rich in pro-vitamin A which is normally destroyed during processing.
The major carotenes in the carotenoid concentrate are alpha and beta-carotenes and they
can be diluted to various concentrations, from 1% to 30%. The vitamin E content in palm
oil is unique in that it is about 600 to 1,000 ppm. It is present as tocotrienols (70%) rather
than tocopherols (30%). It confers on the oil a natural stability against oxidation and a
longer shelf-life as well as a potent ability to reduce low density lipoprotein-cholesterol
and anti-cancer properties. Palm oil also contains 250 to 620 ppm sterols. Beta-sitosterol
is the major constituent at 60%. It is potentially hypocholesterolemic.
1.3 Palm Oil Processing
The process flow-sheet for palm oil extraction can be briefly described as follows.
The fresh fruit bunches (FFB) are harvested in bunches and sent to the mill for processing
as show in Figure 1.3. Each FFB consists of hundreds of fruitlets each containing a nut
surrounded by a bright orange pericarp which contains the palm oil (Borja and Banks,
1994). These bunches are steam sterilized at a pressure of 3 bar where the fruits soften
and are easily detached from the stalk. These detached fruits are further softened with
steam in digesters. The digester mash is then passed to the screw press where oil together
with the juice from the fruits is expressed. The crude oil slurry which is expressed may
contain approximately 48% oil, 45% water and 7% solids (Chow and Ho, 2000). Some of
the water in this slurry is actually steam condensate from the sterilization, digestion and
screw pressing where steam is injected into the respective machinery to maintain the high
temperature required throughout the milling process.
Hot water is further added to the crude oil slurry to reduce the viscosity so that the
oil will cream to the surface which assists in its separation in large clarification tanks
(Borja and Banks, 1994). The underflow from the lower section of the clarification tank
is centrifuged to remove as much of the heavier phase consisting of solids and water.
This watery phase or sludge is discharged and any oil found here constitutes oil loss as it
is discharged as effluent. The lighter phase from the centrifuge, which consists of oil and
water, is recycled to the clarification tank. The creamed palm oil from the surface of the
clarification tank is then skimmed and further purified, dried and sold as crude palm oil
(CPO) to the refinery for further processing.
Figure 1.3: Flow diagram of palm oil extraction (Chow and Ho, 2000).
In the refinery, the CPO is processed to remove most of the undesirable impurities
thus making the oil bland, colourless and chemically stable according to trade
specifications and consumer requirements. There are basically two types of refining
practiced by the Malaysian palm oil refiners, chemical and physical refining (Chow and
Ho, 2000). The two processes differ in treatment of the oil and result in differently
labeled oils as illustrated in Figure 1.4. In the mill, as the CPO is extracted there is no
continuous on-line monitoring of quality but the impurities present are only of botanical
origin from the palm fruits. In the final quality assessment when sold to the refineries,
only certain contractual specifications are measured. They are free fatty acid, moisture,
peroxide value, and impurities which determines the degree of oxidation.
Correspondingly, in the trading of refined palm oil, the same sets of contractual
specifications are required with the additional requirement of colour. These parameters
are used to assess not only the initial quality of CPO but also the amount of bleaching
earth required which is one of the major costs incurred in CPO refining. No form of
continuous monitoring is known in palm oil refining.
F
igure 1.4: Refining processes for crude palm oil (Chow and Ho, 2000).
1.4 Potential Adverse Environmental Impacts and Environmental Improvement in Sustainable Development of Palm Oil Industry
The potential for adverse environmental impacts of this rapid transformation of
natural forests to monoculture are primarily ecological. There are also the environmental
implications and typical environmental problems associated with plantation agriculture
such as soil erosion and loss of soil fertility during land preparation, water pollution due
to application of fertilizers and pesticides, and agricultural runoff and others. However, it
is in the processing of the oil palm crop or fresh fruit bunch (extraction of crude palm oil)
that this agro-industry was notable in the 60’s and 70’s for its adverse impact of extensive
pollution of the country’s surface water (Department of Environment, 1999).
A significantly large quantity of water is required in the palm oil extraction
(Ahmad et al., 2003). For this reason, palm oil mills are typically located close to rivers
and streams that provide them with the needed water supply. In addition, being a
plantation based industry, palm oil mills are primarily located within the estates that
supply the oil palm fruit and these estates may stretch far into the interior of the country.
Because of the interior location, the discharges of palm oil mill effluent (POME) have the
potential to pollute the receiving waterways from all the way upstream. Thus, riverine
communities and users of rivers and streams are very vulnerable to the adverse pollution
impact of indiscriminate discharges of POME.
The organic content of raw POME, as measured by the Biochemical Oxygen
Demand (BOD; 3 days, 30 °C), typically averages about 25,000 mg/L; the oil content of
the effluent may ordinarily exceed 6,000 mg/L. This highly polluting wastewater can
therefore cause severe pollution of waterways due to oxygen depletion and other related
effects. The daily POME volume and the population equivalent of the raw effluent BOD
load discharged by an average sized palm oil mill (30 tonnes FFB per hour) are 600 m3/d
and 300,000 persons, respectively (Department of Environment, 1999).
Palm oil mills use the palm fiber and shell as solid boiler fuel to co-generate
needed steam and electricity. In the past, palm oil mills also typically employed an
incinerator to burn the empty bunches and recover the residual potash for use as fertilizer
in the plantation. Poor control of the air emissions from these facilities often caused
localized problems of air pollution (Department of Environment, 1999). However, the oil
palm industry is presently using the empty fruit bunches waste for mulching and POME
as fertilizer. During replanting, the trunks and fronds are chipped and left in the inter-
rows as mulch under the zero-burn practice (Basiron and Chan, 2004).
Palm oil can be burnt directly as boiler fuel or as diesel for power generation and
vehicle propulsion. Besides, palm oil can be emulsified to palm diesel or methyl diesel.
The biomass from the mill, such as EFB, fiber and shell, can be used for electricity
generation. More than 10 out of the country’s 360 mills are applying to supply electricity
to Tenaga Nasional Berhad. New technologies are now available to harness the biogas
from effluent ponds for power generation. The total value of biogas energy available
from the mills is estimated to be RM 1 billion (Basiron and Chan, 2004). It is also
estimated that if all the biogas is used for the mill operation, then all the fiber and shell
can be freed for generating electricity for sale.
1.5 Problem Statements
The process to extract the oil requires significantly large quantities of water for
steam sterilizing the palm fruit bunches and clarifying the extracted oil. It is estimated
that for 1 tonne of crude palm oil produced, 5 to 7.5 tonnes of water are required, and
more than 50% of the water will end up as palm oil mill effluent (Ahmad et al., 2003).
Thus, while enjoying a most profitable commodity, the adverse environmental impact
from the palm oil industry cannot be ignored.
The oil and grease (O&G) content of POME is an important consideration in the
handling and treatment. O&G are singled out for special attention as their poor solubility
in water. Oil in wastewaters has to be removed in order to prevent interfaces in water
treatment units, reduce fouling in process equipment, avoid problems in biological
treatment stages and comply with water discharge requirements (Ahmad et al., 2005).
Hence the removal of residue oil from process or waste effluent becomes environmentally
important.
POME is an important source of inland water pollution when released into local
rivers or lakes without treatment. With increased cultivation and production of palm oil
in the region, the disposal of the processing waste is becoming a major problem that must
be appropriately addressed. Thus, the challenge of balancing the POME into a more
environmental friendly waste requires a sound and efficient treatment and disposal
approach.
1.6 Scopes of Study The laboratory scale upflow anaerobic sludge blanket (UASB) reactor being used
was the existing acrylic material made cylindrical reactor without three phase’s separator.
The sludge was taken from the previous UASB microbial study. The sludge volume in
the reactor was controlled between 4.0 to 4.5 L levels. The raw POME samples were
collected only from the Felda Palm Industries Sdn. Bhd., Kilang Sawit Bukit Besar, in
Kulai, Johor Darul Takzim. Tap water was used for raw POME samples dilutions. Large
and bulky materials in the raw POME samples were removed before the samples dilutions.
1.7 Objectives of Study
This study aimed to evaluate the biodegradation of oil and grease content in raw
POME using UASB reactor. The objectives of this study were as follows:
i. To determine the oil and grease (O&G) biodegradation for the treatment of raw
POME using UASB reactor,
ii. To determine chemical oxygen demand (COD) removal efficiencies for the
treatment of raw POME using UASB reactor,
iii. To evaluate the UASB’s performance in relation to various control variables with
the biodegradation of O&G and removal of COD as the responses of the variables.
CHAPTER 2
LITERATURE REVIEW
2.1 Palm Oil Mill Effluent in Perspective
Large quantities of water are consumed during the extraction of crude palm oil
from the fresh fruit bunch. About 50% of the water results in POME, the other 50%
being lost as steam, mainly through sterilizer exhaust, piping leakages, as well as wash
waters. The POME comprises a combination of the wastewaters which are principally
generated and discharged from the following major processing operations (Department of
Environment, 1999):
i. Sterilization of FFB-sterilizer condensate is about 36 % of total POME
ii. Clarification of the extracted crude palm oil-clarification wastewater is about 60%
of total POME
iii. Hydrocyclone separation of cracked mixture of kernel and shell-hydrocyclone
wastewater is about 4% of total POME.
The typical quality characteristics of the individual wastewater streams from the 3
principal sources of generation are presented in Table 2.1. In most mills, all three
wastewater streams amounting to about 3 tonnes per tonne of palm oil produced, are
combined together resulting in a viscous brown liquid containing fine suspended solids
(Borja and Banks, 1994). A well managed palm oil mill with very good housekeeping
practices will generate about 2.5 m3 of POME per tonne of CPO produced; in term of
FFB this amounts to about 0.5 m3 of POME per tonne of FFB processed. However, the
national average is about 3.5 m3 of POME per tonne of CPO, or 0.7 m3 per tonne FFB.
This shows that much water can be saved through good milling and housekeeping
practices (Department of Environment, 1999).
Table 2.1: Characteristics of individual wastewater streams (Department of Environment,
1999).
Parameters* Steriliser Condensate
Oil Clarification Wastewater
Hydrocyclone Wastewater
pH 5.0 4.5 - Oil & Grease (O&G) 4,000 7,000 300 Biochemical Oxygen Demand (BOD; 3 days, 30 °C) 23,000 29,000 5,000
Chemical Oxygen Demand (COD) 47,000 64,000 15,000 Suspended Solids (SS) 5,000 23,000 7,000 Dissolved Solids (DS) 34,000 22,000 100 Ammoniacal Nitrogen (Am-N) 20 40 - Total Nitrogen (TN) 500 1,200 100 Note: * All parameter’s units in mg/L except pH.
POME is a colloidal suspension of 95% to 96% water, 0.6% to 0.7% oil and 4% to
5% total solids including 2 to 4% suspended solids originating from the mixture of a
sterilizer condensate, separator sludge and hydrocyclone wastewater. It is thick brownish
in color liquid and discharged at temperature between 80 and 90 °C and fairly acidic
(Ahmad et al., 2003). The typical quality characteristics of the raw combined POME are
illustrated in Table 2.2.
It can be seen that the BOD : COD ratio of raw POME is approximately 1 : 2,
which means that POME is considered to be suitably treated by biological processes. It
can also be seen that the range of the general parameters are large, which varies
depending on the efficiency and modes of the mill operations. However, the typical
BOD : N : P ratio of 139 : 4 : 1 indicates the limitation of nutrient, which is required for
bacterial growth and metabolic requirements of biomass, to obtain optimum biological
processes under aerobic conditions, which requires 100 : 5 : 1. Nutrient deficiency can
lead to increasing the population of filamentous bacteria (Lim and Ujang, 2004).
Table 2.2: Characteristics of combined palm oil mill effluent (Department of Environment, 1999).
Parameters*
General Parameters Metals & Other Constituents
Mean Range pH 4.2 3.4-5.2 Phosphorous 180Oil & Grease (O&G) 6,000 150-18,000 Potassium 2,270Biochemical Oxygen Demand (BOD; 3 days, 30 °C) 25,000 10,000-44,000 Magnesium 615
Chemical Oxygen Demand (COD) 50,000 16,000-100,000 Calcium 440Total Solids (TS) 40,500 11,500-79,000 Boron 7.6Suspended Solids (SS) 18,000 5,000-54,000 Iron 47Total Volatile Solids (TVS) 34,000 9,000-72,000 Manganese 2.0Ammoniacal Nitrogen (Am-N) 35 4-80 Copper 0.9Total Nitrogen (TN) 750 80-1,400 Zinc 2.3Note: * All parameter’s units in mg/L except pH.
POME is the fiber-free non-oil components obtained from the clarification zone of
oil mill. POME consists of various suspended components including cell walls,
organelles, short fibers, a spectrum of carbohydrates ranging from hemicellulose to
simple sugars, a range of nitrogenous compounds from proteins to amino-acids, free
organic acids and an assembly of minor organic and mineral constituents (Ugoji, 1997).
Comprehensive environmental control of the crude palm oil industry commenced
soon after the enactment of the Environmental Quality Act, 1974 (EQA) and the
establishment of the Department of Environment in 1975. In order to regulate the
discharge of effluent from the crude palm oil industry as well as to exercise other
environmental controls, the Environmental Quality (Prescribed Premises) (Crude Palm
Oil) Order, 1977 and the Environment Quality (Prescribed Premises) (Crude Palm Oil)
Regulations, 1977 were promulgated under the EQA (Laws of Malaysia, 2003). These
were the first sets of industry specific subsidiary legislation to be promulgated under the
EQA for industrial pollution control. The current effluent discharge standard ordinarily
applicable to crude palm oil mills is presented in Table 2.3.
Table 2.3: Prevailing effluent discharge standard for crude palm oil mills (Laws of Malaysia, 2003).
Parameters Unit Parameter Limits
(Second Schedule) Remarks
Biochemical Oxygen Demand (BOD; 3 days, 30 °C) mg/L 100
Chemical Oxygen Demand (COD) mg/L * Total Solids (TS) mg/L * Suspended Solids (SS) mg/L 400 Oil & Grease (O&G) mg/L 50 Ammoniacal Nitrogen (Am-N) mg/L 150 Filtered sample Total Nitrogen (TN) mg/L 200 Filtered sample pH - 5-9 Temperature °C 45 Note: * No discharge standard after 1984. 2.2 Oil and Grease in Palm Oil Mill Effluent POME is an oily wastewater generated by the palm oil processing mills in
Malaysia. POME contains about 4000 to 6000 mg/l of oil and grease (Ahmad et al.,
2005). The oil droplets of POME can be found in two phases. They either suspend in the
supernatant or float on the upper layer of the suspension. The residue oil droplets in
POME were solvent extractable. The extract of the oil droplets consists of 84 wt%
neutral lipids and 16 wt% of complex lipids (6 wt% glygolipids and 10 wt%
phospholipids). The neutral lipids consist of 74.7% triglycerides, 8% diglycerides, 0.5%
monoglycerides and 0.8% free fatty acids. POME also distributes a high concentration of
surface active compounds like phospholipids (10 wt%) and glycolipids (6 wt%).
O&G in POME can be defined as residual oil that contained in the wastes that
generated from the process of palm oil extraction. The O&G in POME are produced
from combination of O&G in sterilizer effluent, hydrocyclone effluent, and centrifuge
effluent. Under the Environmental Quality (Prescribed Premises) (Crude Palm Oil) Order,
1977, and the Environmental Quality (Prescribed Premises) (Crude Palm Oil) Regulations,
1977, the concentration of O&G in POME for standard discharge limit by the Malaysian
Department of Environment is 50 mg/L (Laws of Malaysia, 2003).
Better understanding of fats and oils in palm oil is relatively important to the study
of biodegradation of O&G in POME. Thus, it will help to achieve the success in POME
treatment. In chemistry, fats, oils, and waxes are all esters. Fats and oils are esters of the
trihydroxy alcohol, glycerol, while waxes are esters of long chain monohydroxy alcohols.
All serve as food for humans as well as bacteria, since they can be hydrolyzed to the
corresponding fatty acids and alcohols.
2.2.1 Chemistry of Fats and Oils Oils are important nutrients and energy sources that are composed mostly of
triacylglycerols. Dietary triacylglycerols are composed of fatty acids that may vary in
their chain length, degree of unsaturation, isomeric orientation of double bonds and
position within the triacylglycerol molecule (Edem et al., 2003). The glycerides of fatty
acids that are liquid at ordinary temperatures are called oils and those that are solids are
called fats (Sawyer et al., 2003). Chemically, they are quite similar. The oils have a
predominance of short chain fatty acids or fatty acids with a considerable degree of
unsaturation, such as linoleic or linolenic.
The fatty acids in a given molecule of a glyceride may be all the same or they may
all be different. The principal acids composing the glycerides of fats and oils are shown
in Table 2.4. The relative amounts of the major fatty acids contained in various fats and
oils are shown in Table 2.5.
Palm oil, a triglyceride with a melting point 34.2 °C contains approximately 44%
palmitic acid and is 97% digestible (Edem et al., 2003). This oil is one of the richest
sources of β-carotene, is obtained from the fleshy orange-red mesocarp of the fruits.
Refined palm olein is the liquid fraction obtained from the refining, bleaching and
deodorization of the crude red palm oil. This fractionation brings about enrichment with
the monounsaturated oleic acid in addition to the concomitant reduction of palmitic acid,
the major saturated fatty acid.
Table 2.4: Acids of the fats and oils (Sawyer et al., 2003). Name Formula Mp, °C Source Butyric C3H7COOH -5.7 Butter Caproic C5H11COOH -3 Butter, coconut oil Caprylic C7H15COOH 16.3 Palm oil, butter Capric C9H19COOH 31.9 Coconut oil Lauric C11H23COOH 43.2 Coconut oil, spermaceti Myristic C13H27COOH 53.9 Nutmeg, coconut oil Palmitic C15H31COOH 63.1 Palm oil, animal fats Stearic C17H35COOH 69.6 Animal & vegetable fats, oils Arachidic C20H40O2 76.5 Peanut oil Behenic C22H44O2 81.5 Ben oil Oleic C18H34O2 13.4 Animal & vegetable fats, oils Erucic C22H42O2 34.7 Rape oil, mustard oil Linoleic C18H32O2 -12 Cottonseed oil Linolenic C18H30O2 -11 Linseed oil
Table 2.5: Acid content of fats and oils in percent (Sawyer et al., 2003). Name Oleic Linoleic Linolenic Stearic Myristic Palmitic Arachidic Butter 27.4 - - 11.4 22.6 22.6 - Mutton tallow 36.0 4.3 - 30.5 4.6 24.6 - Castor oil 9.0 3.0 - 3.0 - - - Olive oil 84.4 4.6 - 2.3 Trace 6.9 0.1 Palm oil 38.4 10.7 - 4.2 1.1 41.1 - Coconut oil 5.0 1.0 - 3.0 18.5 7.5 - Peanut oil 60.6 21.6 - 4.9 - 6.3 3.3 Corn oil 43.4 39.1 - 3.3 - 7.3 0.4 Cottonseed oil 33.2 39.4 - 1.9 0.3 19.1 0.6 Linseed oil 5.0 48.5 34.1 - - - - Soybean oil 32.0 49.3 2.2 4.2 - 6.5 0.7 Tung oil 14.9 - - 1.3 - 4.1 -
Like all oils, triacylglycerols are the major constituents of palm oil. Over 95% of
palm oil consists of mixtures of triacylglycerols that are glycerol molecules, each
esterified with three fatty acids. During oil extraction from the mesocarp, the
hydrophobic triacylglycerols attract other fat or oil soluble cellular components (Sundram,
2004). These are the minor components of palm oil such as phosphatides, sterols,
pigments, tocopherols, tocotrienols and trace metals. Other components in palm oil are
the metabolites in the biosynthesis of triacylglycerols and products from lipolytic activity.
These include the monoglycerols, diglycerols and free fatty acids (FFAs). The fatty acids
are any of a class of aliphatic acids, such as palmitic (16:0), stearic (18:0) and oleic (18:1)
in animal and vegetable fats and oils. The major fatty acids in palm oil are myristic
(14:0), palmitic, stearic, oleic and linoleic (18:2).
Palm oil has saturated and unsaturated fatty acids in approximately equal amounts.
Most of the fatty acids are present as triacylglycerols. The different placement of fatty
acids and fatty acid types on the glycerol molecule produces a number of different
triacylglycerols. There are 7% to 10% of saturated triacylglycerols, predominantly
tripalmitin. The fully unsaturated triacylglycerols constitute 6% to 12% (Sundram, 2004).
The Sn-2 position has specificity for unsaturated fatty acids. Therefore, more than 85%
of the unsaturated fatty acids are located in the Sn-2 position of the glycerol molecule.
The triacylglycerols in palm oil partially define most of the physical characteristics of the
palm oil such as melting point and crystallization behavior.
Fats and oils undergo three types of chemicals reactions of interest, hydrolysis,
addition and oxidation. Since fats and oils are esters, they undergo hydrolysis with more
or less ease. The hydrolysis may be induced by chemical means, usually by treatment
with NaOH, or by bacterial enzymes that split the molecule into glycerol plus fatty acids.
Hydrolysis with the aid of NaOH is called saponification (Sawyer et al., 2003).
Hydrolysis by bacterial action may produce rancid fats or oils and renders them
unpalatable. Rancid butter and margarine are notorious for their bad odor.
The fats and oils containing unsaturated acids add chlorine at the double bonds, as
other unsaturated compounds do. This reaction is often slow because of the relative
insolubility of the compounds. It may represent a significant part of the chlorine demand
of some wastes, and chlorinated organics will be produced during chlorination, some of
which may be of health concern.
Oils that contain significant amounts of oleic and linoleic acids may be converted
to fats by the process of hydrogenation (Sawyer et al., 2003). In this process hydrogen is
caused to add at the double bonds, and saturated acids result. Thus, low priced oils such
as soybean and cottonseed can be converted into margarine, which is acceptable as human
food. Many cooking fats or shortenings are made in the same manner. The
hydrogenation can be controlled to produce any degree of hardness desired in the product.
The oils with appreciable amounts of linoleic and linolenic acids or other highly
unsaturated acids, such as linseed and tung oil, are known as drying oils. In contact with
the air, oxygen adds at the double bonds and forms a resin like material. The drying oils
are the major component in all oil based paints.
2.2.2 Biochemistry of Fats and Oils
The degradation of or assimilation of fatty materials is sometimes restricted
because of their relative insolubility. This can be a serious problem in anaerobic sludge
digestion units. Because of their low specific gravity, the fatty materials tend to float and
complicate scum conditions. In the scum layer, these fatty materials may be rather
remote from the bacteria that are capable of utilizing them. Good mixing in a digester
can help reduce this problem. The biological degradation of fatty materials in its initial
phases is known to progress along similar lines under aerobic and anaerobic conditions.
The first step is hydrolysis, with the production of glycerol and fatty acids. The
free fatty acids derived from the hydrolysis of fatty materials, the deaminization of amino
acids, carbohydrate fermentation, and omega oxidation undergo further breakdown by
oxidation. Oxidation is believed to occur at the beta carbon atom in accordance with
Knoop’s theory, sometimes called the beta oxidation theory (Sawyer et al., 2003).
According to this theory, oxidation proceeds in a series of steps. Coenzyme A is known
to be active in these transformations. Oxidation is accomplished by enzymatic hydrogen
and electron removal and water addition, which are facilitated by the electron carriers,
FAD and NAD. The pathway of beta oxidation to a fatty acid molecule is showed from
Reactions (2.1) to (2.5).
(2.1)
(2.2)
(2.3)
(2.4)
(2.5)
R CH2 CH2 C
O
OH + HSCoAenzyme
R CH2 CH2 C
O
SCoA + H2O
Coenzyme Aβ−carbon
R CH2 CH2 C
O
SCoA + FAD+ enzymeR C C C
O
SCoA
H H
+ FADH + H+
R C C C
O
SCoA
H H
+ H2Oenzyme
R C C C
O
SCoA
OH H
H H
R C C C
O
SCoA
OH H
H H
+ NAD+ enzyme
enzyme
R C C C
O
SCoA
O H
H
+ NADH + H+
R C C C
O
SCoA
O H
H
+ 2H2O R C
O
OH + CH3COOH + HSCoA
In the ultimate step, rupture of the molecule occurs, with formation of one
molecule of acetic acid, and the original molecule of acid appears as a new acid derivative
with two less carbon atoms. Thus, by oxidation at the beta carbon atom, long chain fatty
acids are whittled into fragments consisting of acetic acid. During this oxidation four
hydrogen atoms, with corresponding electrons are removed for each acetic acid unit
produced. These electrons are contained in NADH and FADH. For example, hydrolysis
of palm oil may yield palmitic acid (C15H31COOH). Beta oxidation of this acid would
proceed by chopping off two carbons at a time in the form of acetic acid. Since the acid
has a total of 16 carbons, a total of 8 mol of acetic acid will be formed for each mole of
palmitic acid (Sawyer et al., 2003). By this stoichiometry, the net result would be same
as the Reaction (2.6) below:
(2.6) C15H31COOH + HSCoA + 7FAD+ + 7NAD+ + 14H2O 8CH3COOH + HSCoA + 7FADH + 7NADH + 14H+
Under aerobic conditions, the electrons now carried by FADH and NADH are
used to reduce molecular oxygen to water and produce energy. Under anaerobic
condition, however, it is not possible for the bacteria to rid themselves of the electrons in
this fashion, and another scheme must be used.
In aerobic systems, oxygen is the terminal electron acceptor and is reduced while
organic and inorganic electron donors are being oxidized. In the absence of oxygen, other
materials such as nitrate, Fe(III), Mn(IV), sulfate, and carbon dioxide may become
electron acceptors (Tchobanoglous et al., 2003). The use of sulfate and carbon dioxide
requires strictly anaerobic conditions. Nitrate can be used, however, by facultative
organisms living under intermediate conditions referred to as anoxic, which are
characterized by end products of carbon dioxide, water, and nitrogen gas. All are
inoffensive as opposed to products of methane and H2S formed under strictly anaerobic
conditions. Additionally, Fe(II) and Mn(II) formed from reduction of Fe(III) and Mn(IV)
represent potential water quality problems such as staining.
The reactions of sulfate reduction and methanogenesis can be carried out only by
highly specialized groups of anaerobic bacteria and cannot generally proceed in the
presence of O2, Fe(III), NO3-, or Mn(IV). Methanogenesis is the major process by which
wastes are stabilized in anaerobic digestion and is an important part of the stabilization
occurring in septic tank, lagoons, and sanitary landfills (Sawyer et al., 2003). The
methane gas released can be used as a fuel. About 70 percent of the methane resulting
from the complete methane fermentation of complex wastes results from fermentation of
acetic acid formed as an intermediate in the anaerobic fermentation of carbohydrates,
proteins, fats, and other organic compounds.
2.3 Anaerobic Fermentation and Oxidation Anaerobic biological treatment with concomitant production of methane has
distinct advantages has resulted in a broadening application and use of anaerobic
treatment processes throughout the world. From a microbial perspective, anaerobic
microorganisms are ubiquitous and occur in many natural ecosystems, as well as in the
process simulations used for waste management today (Malina and Pohland, 1992).
Anaerobic fermentation and oxidation processes are used primarily for the
treatment of waste sludge and high strength organic wastes. Nevertheless, applications
for dilute waste streams have also been demonstrated and are becoming more common.
Anaerobic fermentation processes are advantageous because of the lower biomass yield
and because energy, in the form of methane can be recovered from the biological
conversion of organic substrates.
Although most fermentation processes are operated in the mesophilic temperature
range (30 to 35 °C), there is increased interest in thermophilic fermentation alone or
before mesophilic fermentation. The latter is termed temperature phased anaerobic
digestion (TPAD). Thermophilic anaerobic digestion processes are used to accomplish
high pathogen kill to produce Class A biosolids, which can be used for unrestricted reuse
applications (Tchobanoglous et al., 2003).
For treating high strength industrial wastewater, anaerobic treatment has been
shown to provide a very cost effective alternative to aerobic processes with savings in
energy, nutrient addition, and reactor volume. Because the effluent quality in not as good
as that obtained with aerobic treatment, anaerobic treatment is commonly used as a pre-
treatment step prior to discharge to a municipal collection system or is followed by an
aerobic process.
2.3.1 Process Description
Three basic steps are involved in the overall anaerobic oxidation of a waste:
hydrolysis, fermentation (also known as acidogenesis), and methanogenesis. The three
steps are illustrated schematically on Figure 2.1. The starting point on the schematic for a
particular application depends on the nature of the waste to be processed.
Fm
c
t
i
f
s
T
p
p
(
(
a
t
igure 2.1: Anaerobic process schematic of hydrolysis, fermentation, and ethanogenesis (Tchobanoglous et al., 2003).
The first step for most fermentation processes, in which particulate material is
onverted to soluble compounds that can then be hydrolyzed further to simple monomers
hat are used by bacteria that perform fermentation, is termed hydrolysis. For some
ndustrial wastewaters, fermentation may be the first step in the anaerobic process.
The second step is fermentation (also referred to as acidogenesis). In the
ermentation process, amino acids, sugars, and some fatty acids are degraded further, as
hown in Figure 2.1. Organic substrates serve as both the electron donors and acceptors.
he principal products of fermentation are acetate, hydrogen, carbon dioxide, and
ropionate and butyrate. The propionate and butyrate are fermented further, to also
roduce hydrogen, carbon dioxide, and acetate. Thus, the final products of fermentation
acetate, hydrogen, and carbon dioxide) are precursors of methane formation
methanogenesis). The free energy change associated with the conversion of propionate
nd butyrate to acetate and hydrogen requires that hydrogen be at low concentrations in
he system (H2 <10-4 atm), or the reaction will not proceed (Tchobanoglous et al., 2003).
The third step, methanogenesis is carried out by a group of organisms known
collectively as methanogens. Two groups of methanogenic organisms are involved in
methane production. One group, termed aceticlastic methanogens, split acetate into
methane and carbon dioxide. The second group termed as hydrogen utilizing
methanogens, use hydrogen as the electron donor and carbon dioxide as the electron
acceptor to produce methane. Bacteria within anaerobic processes, termed acetogens, are
also able to use carbon dioxide to oxidize hydrogen and form acetic acid. However, the
acetic acid will be converted to methane, so the impact of this reaction is minor. As
shown in Figure 2.2, about 72% of the methane produced in anaerobic digestion is from
acetate formation.
Fa 2
b
i
F
i
t
igure 2.2: Carbon and hydrogen flow in anaerobic digestion process (Tchobanoglous et l., 2003).
.3.2 Microbiology
The anaerobic microbial conversion of organic substrates to methane is a complex
iogenic process involving a number of microbial populations, often linked by their
ndividual substrate and product specificities (Malina and Pohland, 1992). As shown in
igure 2.3, the overall conversion process may be described as involving both direct and
ndirect symbiotic associations between different groups of microorganisms. Although
hese associations have been illustrated in various ways, nine recognizable steps, each
mediated by a specific group of microorganisms and their enzyme complements can be
identified, including:
i. Enzymatic hydrolysis of organic polymers to intermediate organic monomers such
as sugars, fatty acids, and amino acids
ii. Fermentation of organic monomers to hydrogen (or formate), bicarbonate,
pyruvate, alcohols, and lower fatty acids (acetate, butyrate, and propionate)
iii. Oxidation of reduced organic products to hydrogen (formate), bicarbonate, and
acetate by obligate hydrogen producing acetogens (OHPA)
iv. Acetogenic respiration of bicarbonate by homoacetogens (HA)
v. Oxidation of reduced organic products (alcohols, butyric and propionic acids) to
bicarbonate and acetate by nitrate reducing bacteria (NRB) and sulfate reducing
bacteria (SRB)
vi. Oxidation of acetate to bicarbonate by nitrate reducing bacteria (NRB) and sulfate
reducing bacteria (SRB)
vii. Oxidation of hydrogen (formate) by nitrate reducing bacteria (NRB) and sulfate
reducing bacteria (SRB)
viii. Aceticlastic methane fermentation
ix. Methanogenic respiration of bicarbonate
The methanogenic bacteria are crucial to the anaerobic stabilization of a variety of
substrates, since they constitute a major final step in the transfer of electrons from the
various donor species. Unfortunately, known methanogens utilize only a narrow array of
relatively simple substrates for growth and metabolism, the most familiar and frequently
acknowledged of which are the hydrogen mediated reduction of carbon dioxide and the
aceticlastic cleavage of acetic acid. However, it is known that many methanogens may
also utilize formate, and to a lesser degree, alcohols or carbon monoxide, as electron
donors (Malina and Pohland, 1992). Therefore, in the presence of an abundant source of
organic substrate, approximately two-third of the methane produced during anaerobic
microbial conversion is derived from the methyl moiety of acetate, and about one-third is
derived from carbon dioxide reduction.
Fs
f
2
P
s
p
c
igure 2.3: Microbial populations in anaerobic microbial conversion of organic ubstrates to methane (Malina and Pohland, 1992).
The group of non-methanogenic microorganisms responsible for hydrolysis and
ermentation consists of facultative and obligate anaerobic bacteria (Tchobanoglous et al.,
003). Organisms isolated from anaerobic digesters include Clostridium spp.,
eptococcus anaerobus, Bifidobacterium spp., Desulphovibrio spp., Corynebacterium
pp., Lactobacillus, Actinomyces, Staphylococcus, and Escherichia coli. Other
hysiological groups present include those producing proteolytic, lipolitic, ureolytic, or
ellulytic enzymes.
The microorganisms responsible for methane production, classified as archaea, are
strict obligate anaerobes. Many of the methanogenic organisms identified in anaerobic
digesters are similar to those found in the stomachs of ruminant animals and in organic
sediments taken from lakes and rivers. The principal genera of microorganisms that have
been identified at mesophilic conditions include the rods (Methanobacterium, and
Methanobacillus) and spheres (Methanococcus, Methanothrix, and Methanosarcina).
Methanosarcina and Methanothrix (also termed Methasaeta) are the only
organisms able to use acetate to produce methane and carbon dioxide. The other
organisms oxidize hydrogen with carbon dioxide as the electron acceptor to produce
methane. The acetate utilizing methanogens were also observed in thermophilic reactors.
Some species of Methanosarcina were inhibited by temperature at 65°C, while others
were not, but no inhibition of Methanothrix was shown. For hydrogen utilizing
methanogens at temperatures above 60°C, Methanobacterium was found to be very
abundant (Tchobanoglous et al., 2003).
The methanogens and the acidogens form a syntrophic (mutually beneficial)
relationship in which the methanogens convert fermentation end products such as
hydrogen, formate, and acetate to methane and carbon dioxide. As the methanogens are
able to maintain an extremely low partial pressure of H2, the equilibrium of the
fermentation reactions is shifted toward the formation of more oxidized end products
(formate and acetate). The utilization of the hydrogen produced by the acidogens and
other anaerobes by the methanogens is termed interspecies hydrogen transfer. In effect,
the methanogenic organisms serve as a hydrogen sink that allows the fermentation
reactions to proceed. If process upsets occur and the methanogenic organisms do not
utilize the hydrogen produced fast enough, the propionate and butyrate fermentation will
be slowed with the accumulation of volatile fatty acids in the anaerobic reactor and a
possible reduction in pH (Borja et al., 1996).
Nuisance organisms in anaerobic operations are the sulphate reducing bacteria,
which can be a problem when the wastewater contains significant concentrations of
sulfate. These organisms can reduce sulfate to sulphide, which can be toxic to
methanogenic bacteria at high enough concentrations. Where high sulfide concentrations
occur, one solution is to add iron at controlled amounts to form iron sulfide precipitate.
Sulfate reducing bacteria, obligate anaerobes of the domain bacteria, are morphologically
diverse, but share the common characteristic of being able to use sulfate as an electron
acceptor and are divided into one of two groups depending on whether they produce fatty
acids or use acetate (Tchobanoglous et al., 2003). Group I sulfate reducers can use a
diverse array of organic compounds as their electron donor, oxidizing them to acetate and
reducing sulfate to sulfide. A common genus found in anaerobic biochemical operations
is Desulfovibrio. Group II sulfate reducers oxidize fatty acids, particularly acetate to
carbon dioxide, while reducing sulfate to sulfide. A bacteria commonly found in this
group is in the genus Desulfobacter.
2.3.3 Stoichiometry of Anaerobic Fermentation and Oxidation
A limited number of substrates are used by the methanogenic organisms and
reactions defined as carbon dioxide, and methyl group type reactions are shown as
follows, involving the oxidation of hydrogen, formic acid, carbon monoxide, methanol,
methylamine, and acetate, respectively in Reactions (2.7) to (2.12).
(2.7) (2.8) (2.9) (2.10) (2.11) (2.12)
4H2 + CO2 CH4 + 2H2O
4HCOO- + 4H+ CH4 + 3CO2 + 2H2O
4CO + 2H2O CH4 + 3CO2
4CH3OH 3CH4 + CO2 + 2H2O
4(CH3)3N + H2O 9CH4 + 3CO2 + 6H2O + 4NH3
CH3COOH CH4 + CO2
A COD balance can be used to account for the changes in COD during
fermentation. Instead of oxygen accounting for the change in COD, the COD loss in the
anaerobic reactor is accounted for by the methane production. By stoichiometry the COD
equivalent of methane can be determined. The COD of methane is the amount of oxygen
needed to oxidize methane to carbon dioxide and water (Tchobanoglous et al., 2003).
CH4 + 2O2 CO2 + 2H2O (2.13)
From the Reaction (2.13) above, the COD per mole of methane is 2(32 g O2/mole)
= 64 g O2/mole CH4. The volume of methane per mole at standard conditions (0 °C and 1
atm) is 22.414 L, so the CH4 equivalent of COD converted under anaerobic conditions is
22.414/64 = 0.35 L CH4/g COD.
2.3.4 Growth Kinetics
In anaerobic processes two rate limiting concepts are important, the hydrolysis
conversion rate and the soluble substrate utilization rate for fermentation and
methanogenesis. The hydrolysis of colloidal and solid particles does not affect the
process operation and stability but does affect the total amount of solids converted. In
anaerobic digestion processes used for municipal waste sludge, greater than 30 days
detention time is needed to approach full conversion of solids (Tchobanoglous et al.,
2003). The soluble substrate utilization kinetics is of great concern to develop a stable
anaerobic process.
Because of the relatively low free energy change for anaerobic reactions, growth
yield coefficients are considerably lower than the corresponding values for aerobic
oxidation. Typical synthesis yield and endogenous decay coefficients for fermentation
and methanogenic anaerobic reactions are Y = 0.10 and 0.04 g VSS/ g VSS and kd = 0.04
and 0.02 g VSS/ g VSS.d, respectively.
The process is more stable when the volatile fatty acid (VFA) concentrations
approach a minimal level, which can be taken as an indication that a sufficient
methanogenic population exists and sufficient time is available to minimize hydrogen and
VFA concentrations. The rate limiting step is the conversion of VFAs by the
methanogenic organisms and not the fermentation of soluble substrates by the fermenting
bacteria. Thus, the methanogenic growth kinetics is of most interest in anaerobic process
designs. Appropriate system solid retention times (SRTs) are selected based on kinetics
and treatment goals. At 20, 25, and 35 °C, the washout or SRTmin values for
methanogenesis are 7.8, 5.9, and 3.2 d, respectively (Tchobanoglous et al., 2003).
Methanogenesis is the rate limiting step due to the nature of the methanogens. In
the design of anaerobic digester units, due consideration must be given to this terminal
phase. The methanogens being a slow growing group must be retained within the system.
System optimization requires the highest possible SRT and therefore some means must be
found to recover the active methanogens from being lost from the system (Shaaban, 1990).
Anaerobic processes are sensitive to pH and inhibitory substances. A pH value
near neutral is preferred and below 6.8 the methanogenic activity is inhibited. Because of
the high carbon dioxide content in the gases developed in anaerobic processes (30 to 35%
CO2), a high alkalinity is needed to assure pH near neutrality. An alkalinity concentration
in the range of 3000 to 5000 mg/L as CaCO3 is often found. For sludge digestion
sufficient alkalinity is produced by the breakdown of protein and amino acids to produce
NH3, which combines with CO2 and H2O to form alkalinity as NH4(HCO3). For
industrial wastewater applications, especially for waste containing mainly carbohydrates,
it is necessary to add alkalinity for pH control (Malina and Pohland, 1992).
2.3.5 Applicability of Anaerobic Treatment
Anaerobic treatment of wastewater has been considered to have a number of
advantages over the conventional aerobic process. The rationale for and interest in the
use of anaerobic treatment processes can be explained by considering the advantages and
disadvantages of these processes. The principal advantages and disadvantages of
anaerobic treatment are listed in Table 2.6.
A further decision to develop an anaerobic treatment system may be made if
anaerobic treatment is economically advantageous in comparison to the available
alternatives and anaerobic treatment can achieve the wastewater treatment specifications
required (Malina and Pohland, 1992).
Table 2.6: Advantages and disadvantages of anaerobic processes compared to aerobic processes (Tchobanoglous et al., 2003).
Advantages Disadvantages
• Less energy required • Less biological sludge production • Fewer nutrients required • Methane production, a potential
energy source • Smaller reactor volume required • Elimination of off gas air
pollution • Rapid response to substrate
addition after long periods without feeding
• Longer startup time to develop necessary biomass inventory
• May require alkalinity addition • May require further treatment
with an aerobic treatment process to meet discharge requirements
• Biological nitrogen and phosphorus removal is not possible
• Much more sensitive to the adverse effect of lower temperatures on reaction rates
• May be more susceptible to upsets due to toxic substances
• Potential for production of odors and corrosive gases
An examination of the characteristics of the specific wastewater to be treated can
provide valuable information for screening the suitability of anaerobic treatment
technology, the type of anaerobic process to be selected, and perhaps the need for pre-
treatment of the wastewater. The factors to be considered for screening suitability of
anaerobic treatment technology are listed as follow:
i. Origin and nature of wastewater
ii. Concentration of organic pollutants
iii. Temperature of wastewater
iv. Concentration of suspended solids
v. Presence of toxic compounds
vi. Expected treatment efficiencies
vii. Biogas and sludge production
viii. Mass discharge rate of organic pollutants
As we know, anaerobic digestion processes offer great potential for the treatment
of many types of wastewaters. For that reason, anaerobic treatment presently is accepted
as a grown up technology. However, in many other countries this unfortunately still is
not the case. The reasons that obstinate the reluctance are (Malina and Pohland, 1992):
i. Lack of adequate information about the performance of installed anaerobic
treatment systems
ii. Lack of knowledge of the basis principles of the process in the established world
of sanitary engineering
iii. Commercial interest in the established wastewater control world
iv. Lack of academic status, particularly in engineering aspects
v. Lack of infrastructure, networks, research, and educational centers
vi. The fact that it is more biotechnology than civil/ sanitary engineering
vii. Acceptance problems for a technology which was not developed in their own
institute or company
2.3.6 Anaerobic Treatment of Palm Oil Mill Effluent Treatment of POME requires a sound and efficient system in facing the current
challenges. With the present situation where there are some mills still failing to comply
with the standard discharge limit even after they have applied the available treatment
system (Ahmad et al., 2003).
The increasingly stringent water quality regulations have forced factories to
investigate a wide range of approaches for the treatment of POME. These include simple
skimming devices, land disposal, use as animal fodder, ultrafiltration, chemical
coagulation and flotation, and various aerobic and anaerobic microbiological processes.
However, all systems have their disadvantages, due to incomplete treatment, large land
requirements or high capital and/or running costs (Borja and Banks, 1994). Anaerobic
biological systems offer greater potential for the treatment of POME, since these systems
do not have the high energy demand. The use of conventional anaerobic lagoons or
digesters to treat POME is characterized by long residence times, often in excess of 20
days, and thus large areas of land or large digesters are needed.
Several innovative treatment technologies have been developed and applied by
palm oil mills to treat POME; conventional biological treatments of anaerobic or
facultative digestion are the most commonly used (Department of Environment, 1999).
However, this biological treatment system needs proper maintenance and monitoring as
the processes rely solely on microorganisms to break down the pollutants. The
microorganisms are very sensitive to changes in the environment and thus great care has
to be taken to ensure that a conducive environment is maintained for the microorganisms
in which to thrive (Ahmad et al., 2003). It also generates vast amount of biogas which
contains methane, carbon dioxide and trace amounts of hydrogen sulfide. These gases are
corrosive and odorous. In addition, the treated wastewater cannot be reused in the plant,
and it is being discharged into the environment.
Little research has been reported regarding the application of modem high rate
anaerobic digester technologies such as upflow or downflow filters, fluidized beds,
UASB systems or upflow floc digesters for the disposal of POME. In 1994, the use of
UASB reactors for treating POME has been reported, which revealed the potential of
smaller and more efficient reactors technology in POME treatment (Borja and Banks,
1994). In that research study, the start-up of the UASB reactor was monitored and the
treatment efficiency in terms of COD reduction was evaluated. Over 80% COD was
removed at loading rates up to 10.6 g/L.d COD, and at the highest influent concentration
(42.5 g/L) reactor instability was observed. Later in 1996, anaerobic treatment of POME
in a two-stage UASB system using a pair of upflow anaerobic reactors to evaluate the
effect of a staged treatment on sludge granulation (Borja et al., 1996). The results
showed that it is possible to split the anaerobic digestion process into two distinct stages
in a pair of UASB reactors and granulation was observed in both reactors but their
morphological characteristics were distinct.
2.4 Upflow Anaerobic Sludge Blanket Reactor
There are several high rate treatment systems are presently available. Of these
systems the potential user obviously will prefer the most economical system, both in
terms of investment but particularly also in operation and maintenance. One of the most
notable developments in anaerobic treatment process technology was the UASB reactor
in the late 1970s in the Netherlands by Lettinga and his coworkers (Tchobanoglous et al.,
2003). Considering the present application of anaerobic treatment, apparently reactors
based on the UASB principle look most favourable. In the meantime the feasibility of the
UASB concept for treating mainly soluble wastewaters has been sufficiently
demonstrated at full scale, at demonstration scale, and at pilot plant scale (Malina and
Pohland, 1992).
The principal types of anaerobic sludge blanket processes include the original
UASB process and modification of the original design, the anaerobic baffled reactor
(ABR) and the anaerobic migrating blanket reactor (AMBR). Of these sludge blanket
processes, the UASB process is used most commonly, with over 500 installations treating
a wide range of industrial wastewaters (Tchobanoglous et al., 2003).
The influent wastewater is distributed at the bottom of the UASB reactor and
travels in an upflow mode through the sludge blanket. Critical elements of the UASB
reactor design are the influent distribution system, the gas-solid separator, and the effluent
withdrawal design. Modifications to the basic UASB design include adding a settling
tank or the use of packing material at the top of the reactor. Both modifications are
intended to provide better solids capture in the system and to prevent the loss of large
amounts of the UASB reactor solids due to process upsets or changes in the UASB sludge
blanket characteristics and density. The use of an external solids capture system to
prevent major losses of the system biomass is recommended.
The demand for high-rate anaerobic processes is still increasing and several lab-
scale studies are being carried out on the application, design, and operation of UASB
reactors. Advantages for the UASB process are the high loadings and relatively low
detention times possible for anaerobic treatment and the elimination of the cost of
packing material. Limitations of the process are related to the wastewater that are high in
solids content or where their nature prevents the development of the dense granulated
sludge (Tchobanoglous et al., 2003).
2.4.1 Design Considerations
In the engineering design of anaerobic bioreactor, factors to consider include
loadings, SRT, mixing and solid-liquid separation (Shaaban, 1990). Organic and
volumetric loadings rates will decide on the suitable operational range in order to avoid
failures due to organic and hydraulic overloads. A minimum SRT of 10 days is required
for a stable operation but in most cases SRT well in excess of 10 days is provided to
ensure trouble free operation and better system performance. Mixing can form an integral
part of a digestion system and it helps to bring about uniformity within the reactor and
since either mechanical impeller type or gas/sludge recirculation requires a high energy
input, serious thought must be given at the preliminary design stage. Effective solid-
liquid separation is critical in the recovery and recirculation of active biomass to obtain
high SRT values and hence maximum process efficiency.
Wastewaters that contain substances that can adversely affect the sludge
granulation, cause foaming, or cause scum formation are of concern. Wastewaters with
higher concentrations of protein and/ or fats tend to create more of the above problems.
The fraction of particulate versus soluble COD is important in determining the design
loadings for UASB reactors as well as determining the applicability of the process
(Tchobanoglous et al., 2003). As the fraction of solids in the wastewater increases, the
ability to form a dense granulated sludge decreases. At a certain solids concentration
(greater than 6 g TSS/L) anaerobic digestion and anaerobic contact processes may be
more appropriate.
Typical COD loadings as a function of the wastewater strength, fraction of
particulate COD in the wastewater and TSS concentrations in the effluent are summarized
in Table 2.7. Removal efficiencies of 90 to 95 % for COD have been achieved at COD
loadings ranging from 12 to 20 kg COD/m3.d on a variety of wastes at 30 to 35 °C with
UASB reactors. Values for hydraulic retention time (HRT) for high strength wastewater
have been as low as 4 to 8 h at these loadings. Where less than 90 % COD removal and
higher effluent TSS concentration are acceptable, higher upflow velocities can be used,
which will develop a more dense granulated sludge by flushing out other solids. Thus,
the higher volumetric COD loadings are shown for this condition.
Table 2.7: Recommended volumetric COD loading for UASB reactors at 30 °C to achieve 85 to 95% COD removal (Lettinga and Hulshoff Pol, 1991).
Volumetric loading, kg COD/m3.d
Wastewater COD, mg/L
Fraction as particulate
COD
Flocculent sludge
Granular sludge with high TSS removal
Granular sludge with little TSS removal
1000-2000 0.10-0.30 2-4 2-4 8-12 0.30-0.60 2-4 2-4 8-14 0.60-1.00 na na na
2000-6000 0.10-0.30 3-5 3-5 12-18 0.30-0.60 4-8 2-6 12-24 0.60-1.00 4-8 2-6 na
6000-9000 0.10-0.30 4-6 4-6 15-20 0.30-0.60 5-7 3-7 15-24 0.60-1.00 6-8 3-8 na
9000-18000 0.10-0.30 5-8 4-6 15-24 0.30-0.60 na 3-7 na 0.60-1.00 na 3-7 na
Recommended loadings as a function of temperature for wastewaters with mainly
soluble COD are presented in Table 2.8. These loadings apply to the sludge blanket
volume, and a reactor effectiveness factor of 0.8 to 0.9 as discussed below is used to
determine the reactor liquid below the gas collector. The higher loading recommendation
for the wastewater containing mainly volatile fatty acids (VFA) is based on the potential
of obtaining a more dense granulated sludge (Tchobanoglous et al., 2003).
Design HRT values are also given for the treatment of domestic wastewater in
Table 2.9 based on pilot plant experience. The HRT value needed is longer than that used
in aerobic processes for secondary treatment for BOD removal. In addition, an aerobic
polishing step would likely be needed. The economic benefits of energy savings and
lower sludge production would have to be sufficient to justify the higher capital costs for
liquid treatment with a UASB process.
Table 2.8: Recommended volumetric organic loadings as a function of temperature for soluble COD substrates for 85% to 95% COD removal (Tchobanoglous et al., 2003).
Volumetric loading, kg sCOD/m3.d
VFA wastewater Non VFA wastewater Temperature, °C Range Typical Range Typical
15 2-4 3 2-3 2 20 4-6 5 2-4 3 25 6-12 6 4-8 4 30 10-18 12 8-12 10 35 15-24 18 12-18 14 40 20-32 25 15-24 18
* Average sludge concentration is 25 g/L. Table 2.9: Applicable hydraulic retention times for treatment of raw domestic wastewater
in a 4 m high UASB reactor (Lettinga and Hulshoff Pol, 1991). Temperature, °C Average HRT, hr Maximum HRT, for 4 to 6 h peak, hr
16-19 10-14 7-9 22-26 7-9 5-7 >26 6-8 4-5
The upflow velocity based on the flowrate and reactor area, is a critical design
parameter that will affect the efficiency of upflow reactors. The upflow velocity affects
the sludge retention as it is based on the settling characteristics of sludge aggregates. The
upflow velocity should be high enough to provide good contact between substrate and
biomass. Higher upflow velocity is believed to facilitate the separation of gas bubbles
from the surface of biomass (Mahmoud et al., 2003).
Recommended design velocities are listed in Table 2.10. Temporary peak
superficial velocities of 6 m/hr and 2 m/hr can be allowed for soluble and partially soluble
wastewaters, respectively (Tchobanoglous et al., 2003). For weaker wastewaters the
allowable velocity and reactor height will determine the UASB reactor volume, and for
stronger wastewaters it will determined by the volumetric COD loading. As in Equation
(2.1), the upflow velocity is equal to the feed rate divided by the reactor cross section area.
AQv = Eq. (2.1)
where = design upflow superficial velocity, m/h v
Q = influent flowrate, m3/h
A = reactor cross section area, m2
Table 2.10: Upflow velocities and reactor heights recommended for UASB reactors (Tchobanoglous et al., 2003).
Upflow velocity, m/hr Reactor height, m
Wastewater type Range Typical Range Typical COD nearly 100% soluble 1.00-3.00 1.5 6-10 8 COD partially soluble 1.00-1.25 1.0 3-7 6 Domestic wastewater 0.80-1.00 0.7 3-5 5
The main physical features requiring careful consideration are the feed inlet, gas
separation, gas collection, and effluent withdrawal (Tchobanoglous et al., 2003). The
inlet and gas separation designs are unique to the UASB reactor. The feed inlet must be
designed to provide uniform distribution and accomplish an optimal contact between
sludge and wastewater. Channelling of the wastewater through the sludge bed and
formation of dead zones in the reactor should be avoided (Lettinga and Hulshoff Pol,
1991). The avoidance of channelling is more critical for weaker wastewaters, as there
would be less gas production to help mix the sludge blanket.
A number of inlet feed pipes are used to direct flow to different areas of the
bottom of the UASB reactor from a common feed source. Access must be provided to
clean the pipes in the event of clogging (Tchobanoglous et al., 2003). Guidelines for
determining the area served by the individual inlet feed pipes as a function of the sludge
characteristics and organic loading are provided in Table 2.11. Particularly in treating
partially soluble wastewaters one should realize that clogging of the nozzles may
represent a serious problem (Lettinga and Hulshoff Pol, 1991). Every inlet system should
be easy to clean, as always after some time of operation inlet pipes tend to become
partially clogged. This will result in an uneven distribution of the wastewater over the
reactor bottom.
Table 2.11: Guidelines for sizing the area served by inlet feed pipes for UASB reactor (Tchobanoglous et al., 2003).
Sludge type COD loading, kg/m3.d Area per feed inlet, m2
Dense flocculent sludge, < 1.0 0.5-1 > 40 kg TSS/m3 1-2 1-2 > 2 2-3
Medium flocculent sludge, < 1-2 1-2 20-40 kg TSS/m3 > 3 2-5
Granular sludge 1-2 0.5-1 2-4 0.5-2 > 4 > 2
Taking into consideration the slow growth rate of many anaerobic microorganisms
particularly methanogenic, the main objectives of the efficient reactor design must be
high retention time of bacterial cells with very little loss of bacteria from the bioreactor.
The technological challenge to improve the anaerobic digestion lies in enhancing the
bacterial activity together with good mixing to ensure a high rate of contact between the
cells and their substrate (Faisal and Unno, 2001).
2.4.2 Gas Solids Separator Device A gas-solid separator (GSS) device which should be installed at the top of an
UASB reactor is crucial equipment for retaining as much viable sludge as possible. The
GSS device can be simply and inexpensively designed (Bae and Shin, 1998). Relatively a
lot of research has been spent in recent years for developing new and more exclusive
systems. The last word on the design of the GSS device certainly has not yet been said.
It is an area of continuous innovation (Lettinga and Hulshoff Pol, 1991).
The GSS is designed to collect the biogas, prevent washout of solids, encourage
separation of gas and solid particles, allow for solids to slide back into the sludge blanket
zone, and help improve effluent solids removal (Tchobanoglous et al., 2003). A series of
upside down V-shaped baffles is used next to effluent weirs to accomplish the above
objectives. Guidelines for the GSS design are summarized below:
i. The slope of the settler bottom, the inclined wall of the gas collector should be
between 45° and 60°
ii. The surface area of the apertures between the gas collectors should not be smaller
than 15% to 20 % of the total reactor surface area
iii. The height of the gas collector should be between 1.5 to 2 m at reactor heights of
5 to 7 m
iv. A liquid-gas interface should be maintained in the gas collector to facilitate the
release and collection of gas bubbles and to control scum layer formation
v. The overlap of the baffles installed beneath the apertures should be 100 to 200
mm to avoid upward flowing gas bubbles entering the settler compartment
vi. Generally scum layer baffles should be installed in front of the effluent weirs
vii. The diameter of the gas exhaust pipes should be sufficient to guarantee the easy
removal of the biogas from the gas collection cap, particularly in the case where
foaming occurs
viii. In the upper part of the gas cap, antifoam spray nozzles should be installed in the
case where the treatment of the wastewater is accompanied by heavy foaming
The capability of the GSS device to separate biomass from rising gas bubbles can
be described by the difference of volatile suspended solid (VSS) concentration in the
blanket and effluent (Bae and Shin, 1998).
2.4.3 Anaerobic Sludge Granulation
The important parameters affecting the treatment efficiency of UASB reactors
include the granulation process in the reactor, the characteristics of the wastewater to be
treated, the selection of inoculum material, the influence of nutrients and several other
environmental factors. Among these parameters, the granulation process is believed to be
the most critical one (Show et al., 2004).
The formation of anaerobic granular sludge can be considered as the major reason
of the successful introduction of the UASB reactor concept for anaerobic treatment of
industrial effluents. Figure 2.4 shows the anaerobic granules from the UASB reactor.
The granular sludge has superior settling characteristic, settling velocities of granular
sludge of approximately 60 m/hr are common, whereas the superficial upflow velocities
in UASB reactors are usually kept below 2 m/hr, in practice (Hulshoff Pol et al., 2004).
This allows an extreme uncoupling of the hydraulic retention time from the sludge age.
SRTs of over 200 days can be achieved at HRTs of only 6 hr.
F
d
a
m
d
o
t
b
f
p
g
t
igure 2.4: Anaerobic granules from the UASB reactor (Hulshoff Pol et al., 2004). The granular sludge performs high specific methanogenic activities. It could be
emonstrated that high volumetric loading rates of over 50 kg COD/m3.d could be well
ccommodated under mesophilic conditions, with specific methanogenic activities of
ore than 2 kg COD/kg VSS.d. Studies on the micromorphology of the granules
emonstrated that colonies of acetogenic bacteria are closely linked with micro-colonies
f hydrogenotrophic methanogenic archaea allowing an efficient interspecies hydrogen
ransfer and as a result, high degradation rates.
The UASB process involves the anaerobic degradation of organic wastes using a
iomass which is not attached to a support medium but which aggregates, under
avourable conditions, to produce particles with good settlement characteristics. These
articles are known as granules, and their formation commonly termed granulation,
enerally enhances the efficiency of the process by producing high biomass retention
imes. Microbial granulation involves different trophic bacterial groups, and physico-
chemical and microbiological interactions (Yu et al., 2001). Sludge granules are dense,
multi-species, microbial communities, and none of the individual species in the granular
ecosystem is capable of degrading complex organic wastes (Liu et al., 2003).
The key feature of the UASB process that allows the use of high volumetric COD
loadings compared to other anaerobic processes is the development of a dense granulated
sludge. Because of the granulated sludge floc formation, the solids concentration can
range from 50 to 100 g/L at the bottom of the reactor and 5 to 40 g/L in a more diffuse
zone at the top of the UASB sludge blanket. The granulated sludge particles have a size
range of 1.0 to 3.0 mm and result in excellent sludge thickening properties with sludge
volume index (SVI) values less than 20 mL/g. Several months may be required to
develop the granulated sludge, and seed is often supplied from other facilities to
accelerate the system startup. Variations in morphology were observed for anaerobic
granulated sludge developed at 30 and 20 °C, but both exhibited similar floc size and
settling properties (Tchobanoglous et al., 2003).
The development of granulated sludge solids is affected by the wastewater
characteristics. Granulation is very successful with high carbohydrate or sugar
wastewaters, but less so with wastewaters high in protein, resulting in a more fluffy floc
instead. Other factors affecting the development of granulated solids are pH, upflow
velocity, and nutrient addition. The pH should be maintained near 7.0, and a
recommended COD : N : P ratio during startup is 300 : 5 : 1, while a lower ratio can be
used during steady state operation at 600 : 5 : 1 (Tchobanoglous et al., 2003). Control of
the upflow velocity is recommended during startup by having it high enough to wash out
nonflocculent sludge.
The presence of other suspended solids in the sludge blanket can also inhibit the
density and formation of granulated sludge. The formation of dense granulated sludge
floc particles is favoured under conditions of near neutral pH, a plug flow hydraulic
regime, a zone of high hydrogen partial pressure, a nonlimiting supply of NH4-N, and a
limited amount of the amino acid cysteine. With a high hydrogen concentration and
sufficient NH4-N, the bacteria responsible for granulation may produce other amino acids,
but their synthesis is limited by the cysteine supply. Some of the excess amino acids that
are produced are thought to be secreted to form extracellular polypeptides which, in turn,
will bind organisms together to form the dense pellets or floc granules (Tchobanoglous et
al., 2003).
Granulation may be initiated by bacterial adsorption and adhesion to inert matters,
inorganic precipitates and/or to each other through physico-chemical interactions and
syntrophic relationships. These substances serve as initial precursors (carriers or nuclei)
for new bacterial growth. These loosely adhered bacterial aggregates are strengthened by
extracellular polymers secreted by bacteria and form firmly attached initial granules.
These initial granules will grow continuously into compact mature granules, if favorable
conditions pertaining to bacteria are maintained (Yu et al., 2001).
It has been shown that divalent metal ions, such as Ca2+ and Fe2+, enhance the
granulation. Divalent ions were reported to play an important role in microbial
aggregation. It was found that extracellular polymers prefer to bind multivalent metals
due to the formation of stable complexes. It was observed that distinct improvement in
the biomass settleability and specific activity after replacing NaHCO3 as a neutralizing
agent by Ca(OH)2. At concentrations of 100 to 200 mg/L, calcium was found to exert a
positive impact on granulation (Yu et al., 2001). Mineral precipitates such as CaCO3,
Ca5OH(PO4)3, and FeS are formed, as a result of metabolic activities and physico-
chemical reactions, and are accumulated either inside or on the surface of granules.
However, there are also contradictory reports about the role of Ca2+ in granulation. Some
researchers have argued that Ca2+ does not induce granulation, or is not a key element in
granules, or is even detrimental to granule formation together with phosphate.
Introduction of Ca2+ at concentrations from 150 to 300 mg/L enhanced the
biomass accumulation and granulation process in UASB reactors. The specific activity of
granules decreased with increasing calcium concentration in the feed. For high calcium
concentrations, a large amount of minerals deposited within the granules. This along with
the significant decrease in the water content in granules and the toxicity of high
concentration calcium accumulated inside granules caused a lower bacterial specific
activity (Yu et al., 2001).
One major drawback of the UASB reactor is its extremely long start-up period,
which generally requires 2 to 8 months for the development of anaerobic granular sludge
(Liu et al., 2003). In order to reduce the space-time requirements of bioreactors and
eventually lead to a cheaper treatment of high strength wastes, strategies for expediting
granular formation are highly desirable. For achieving such a purpose, the mechanisms
for anaerobic granulation should be thoroughly understood.
In the presence of inert microparticles in an UASB reactor, anaerobic bacteria
could attach to the particle surfaces to form the initial biofilms, namely embryonic
granules as illustrated in Figure 2.5. Since bacteria have negatively charged surfaces
under usual pH conditions, a basic idea to expedite anaerobic granulation process is to
reduce electrostatic repulsion between negatively charged bacteria by introducing multi-
valence positive ion, such as calcium, ferric, aluminum or magnesium ions, into seed
sludge as shown in Figure 2.6. It had been reported that extracellular polymers (ECPs)
could change the surface negative charge of the bacteria, and thereby bridge two neighbor
cells physically to each other as well as with other inert particulate matters as illustrated
in Figure 2.7.
F
igure 2.5: Schematic representation of the inert nuclei model (Liu et al., 2003).
F( Fa
g
c
m
d
l
p
igure 2.6: Schematic representation of the multi-valence positive ion-bonding model
Liu et al., 2003).
igure 2.7: Schematic representation of the polymer or filament bonding model (Liu et l., 2003).
Based on the microscopic observations, a multi-layer model for anaerobic
ranulation was initially proposed. According to this model, the microbiological
omposition of granules is different in each layer. The inner layer mainly consists of
ethanogens that may act as nucleation centers necessary for the initiation of granule
evelopment. H2-producing and H2-utilizing bacteria are dominant species in the middle
ayer, and a mixed species including rods, cocci and filamentous bacteria takes
redominant position in the outermost layer as illustrated in Figure 2.8.
F
igure 2.8: Schematic representation of the multi-layer model (Liu et al., 2003).
CHAPTER 3
RESEARCH METHODOLOGY
3.1 Upflow Anaerobic Sludge Blanket Reactor Setup
The cylinder UASB reactor was made of acrylic material with an influent
distributor and six outlets. The dimension of UASB reactor was measured then the
reactor volume and working volume could be determined. Table 3.1 showed the
dimension of the UASB reactor. No gas-solid separator (GSS) device is installed in the
UASB reactor as the constraint of the existing reactor design and dimension. Then, the
UASB reactor was connected to the pumps and other tanks or containers with proper
pipelines. No leaking from the reactor and pipelines connections had been confirmed
before conducting any experiments. The schematic diagram of the UASB reactor was
demonstrated in Figure 3.1.
Table 3.1: Dimension of the UASB reactor.
Dimension Measurement value Inner diameter, Din 18.5 cm Height, H 52 cm Cross section area, A 268.8 cm2
Reactor volume, Vr 14 L Working volume, Vw 12.5 L
F
P
t
w
w
f
w
n
U
w
e
Pump 1
Pump 2
Influent Tank
Recycle
Effluent
Pump 1
Pump 2
Influent Tank
Recycle
Effluent
igure 3.1: Schematic diagram of the UASB reactor.
Two peristaltic pumps were used: Pump 1 for influent flow rate adjustment and
ump 2 for mixing and upflow velocity enhancements inside the reactor. Pump 1 was
uned to the desired flow rates and the Pump 2 was fixed at 250 mL/min. The influents
ere introduced from the bottom of the UASB reactor through the Pump 1. The influents
ere distributed evenly through a proper designed feed inlet to avoid channelling or the
ormation of dead zones. The avoidance of channelling was more critical for weaker
astewaters, as there would be less gas production to help mix the sludge blanket. A
umber of inlet points were used to direct flow to different areas of the bottom of the
ASB reactor from a common feed source. Pump 2 was functioned to recycle the
astewater internally, providing more contact of the wastewater to the biomass and
nhancing the upflow velocity of the reactor.
3.2 Sampling of Palm Oil Mill Effluent
The raw POME samples were collected from the Felda Palm Industries Sdn. Bhd.,
Kilang Sawit Bukit Besar, in Kulai. The cooperation from the palm oil mill and the
people in-charge, Mr. Razak Jaafar lead to smooth sampling frequency and time. POME
samples were freshly collected and preserved at 4°C in the cool room. Large and bulky
materials in the raw POME samples were removed before the dilution. Raw POME
samples were diluted using tap water. Figures 3.2 and 3.3 showed the front view of the
palm oil mill and the sampling point of raw POME.
Figure 3.2: Front view of Kilang Sawit Bukit Besar, Kulai. F
igure 3.3: The sampling point of raw POME.
3.3 Characterization of Palm Oil Mill Effluent
The characteristic of the raw POME, such as pH, oil and grease (O&G),
biochemical oxygen demand (BOD5), chemical oxygen demand (COD), soluble chemical
oxygen demand (sCOD), total solids (TS), total suspended solids (TSS), volatile
suspended solids (VSS), ammoniacal nitrogen (Am-N), and nitrate (NO3-) were
determined according to the Standard Methods for the Examination of Water and
Wastewater (APHA, 2000) and DR/4000 Spectrophotometer Procedures Manual. There
were 5 respective samples of raw POME were collected freshly and determined in the
laboratory. Hexane was used as the organic solvent for the O&G extraction by using
separatory funnel. Appendix A showed the procedures of O&G determination. The
characteristics of these 5 raw POME samples were illustrated in the range of minimum
and maximum detected concentrations. The characteristics of the POME were compared
to the given data as in Appendix B.
3.4 Upflow Anaerobic Sludge Blanket Reactor Startup
The strength of the influents were depends on the COD of the diluted POME. The
preparation of diluted POME samples as influent for the reactor startup were controlled at
5000 ± 1000 mg/L COD. To produce such strength of influents, about 2 L of raw POME
was diluted into 30 L. The pHs of influents were adjusted to neutral (pH 7 ± 0.10). The
working volume (Vw) for the UASB reactor was 12.5 L and the hydraulic retention time
(HRT) 12.9 hrs, the flow rate of Pump 1 could be determined. The influents were
continuously flowed into the reactor daily. Parameters such as pH, COD, TSS and VSS
of the both influent and effluent were determined. The analysis methods for the desired
parameters were referred to standard methods. The startup of the reactor was proceeding
until the steady state condition. Steady state condition was defined when the COD
removal was constant (not more than 5% difference). The controlled operating
parameters were illustrated in Table 3.2.
Table 3.2: Operating parameters for the reactor startup.
Operating Parameters Desired Value Influent COD 5000 mg/L Influent pH 7 HRT 12.9 hrs Organic loading 9.3 g/L.d COD Working volume 12.5 L Flow rate of Pump 1 (influent) 0.97 L/hr Flow rate of Pump 2 (recycle) 15.0 L/hr Upflow velocity 0.59 m/hr
3.5 Design of Experiments
The important factors such as strength of wastewater (based on COD), influent pH
and HRT were selected which may affect the response variables as in Table 3.3. As full
factorial design was chosen, the combination treatments of the factors in one repeat were
8 (23) as shown in Table 3.4. The experiments were conducted in three replicates and the
steady state should be achieved before the next replicate is started. The percentages of
O&G biodegraded and COD removed in effluents were the response variables. Table 3.5
showed the low and high levels of various control operating parameters.
Table 3.3: Full factorial design of experiment with three factors in two levels.
Factors Level (+) Level (-) A: HRT 12.9 hrs 3.3 hrs B: Influent COD 15,000 mg/L 5,000 mg/L C: Influent pH 7 3
Table 3.4: Experiments in different combination of treatment factors in one replicate.
Run HRT, hrs (A)
Influent COD, mg/L(B)
Influent pH(C)
Treatment Combination
1 3.3 5,000 3 1 2 12.9 5,000 3 a 3 3.3 15,000 3 b 4 12.9 15,000 3 ab 5 3.3 5,000 7 c 6 12.9 5,000 7 ac 7 3.3 15,000 7 bc 8 12.9 15,000 7 abc
Table 3.5: Operating parameters for the experiments in three replicates.
Operating Parameters Desired Value Influent COD (A) 5,000 @ 15,000 mg/L Influent pH (B) 3 @ 7 HRT (C) 3.3 @ 12.9 hrs Working volume, Vw 12.5 L Flow rate of Pump 1 (influent) 3.79 @ 0.97 L/hr Flow rate of Pump 2 (recycle) 15.0 L/hr Upflow velocity 0.70 @ 0.59 m/hr
The analysis of data from the 3 levels 2 factors full factorial designed experiments
(COD removal and O&G biodegradation) were conducted to investigate the main effects
which have large impacts on these response variables. The method and formula were
applied from Design and Analysis of Experiments (Montgomery, 2005).
CHAPTER 4
DATA COLLECTION AND ANALYSIS
4.1 Characterization of Palm Oil Mill Effluent
The characteristics of raw POME that collected from Kilang Sawit Bukit Besar
were determined. The determined parameters include pH, oil and grease, biochemical
oxygen demand (5 days), chemical oxygen demand, soluble chemical oxygen demand,
total solids, total suspended solids, volatile suspended solids, ammoniacal nitrogen and
nitrate. The results of 5 respective raw POME were analyzed and presented in Table 4.1
below.
Table 4.1: Characteristics of raw palm oil mill effluent.
Parameters Concentration (mg/L) pH 4.5 - 5.0 O&G 8,000 - 11,000 BOD5 18,000 - 21,000 COD 68,000 - 80,000 sCOD 33,000 - 41,000 TS 65,000 - 70,000 TSS 35,000 - 45,000 VSS 31,000 - 37,000 Am-N 280 - 460 NO3
- 300 - 510
The raw POME samples that collected from Bukit Besar, Kulai were the mixed
effluent from sterilizer condensate, clarification sludge and hydrocyclone discharged.
The detected parameters in each stage are given in Appendix B. The characteristic of the
raw POME above was considered the mixtures of the effluent from those three sources. It
was match with the data given in Appendix B.
From the range of the data obtained the raw POME samples had slightly different
compared to the reported typical quality of POME. This POME had higher strength than
the typical. However, the detected maximum and minimum concentrations do not vary
too much. Hence, it was able to control the strength of the influents for the digestion of
UASB reactor in this study.
4.2 Upflow Anaerobic Sludge Blanket Reactor Startup
During the reactor startup period, the reactor was flowed with the influents (5,000
mg/L COD, pH 7 and HRT 12.9 hrs) continuously. The influents were freshly prepared
while the effluents were collected on time. The parameters such as pH, COD, TSS and
VSS of the influents and effluents were determined daily. The data collected were
tabulated in the Table 4.2.
From the data in Table 4.2, the COD removal, TSS removal and VSS removal of
the reactor could be determined. The correlation of the COD removal and effluent pH
within startup period was plotted as in Figure 4.1. The TSS and VSS removal within the
startup period was also plotted as in Figure 4.2. Then, the steady state condition of the
reactor could be defined.
Table 4.2: Data collected for the influents and effluents during the reactor startup period.
pH COD (mg/L) TSS (mg/L) VSS (mg/L) Days In Out In Out In Out In Out
1 7.04 4.91 5390 3340 1850 850 1770 690 2 7.03 4.97 5210 3060 2060 740 1850 630 3 7.01 5.04 5640 3070 1710 700 1590 570 4 7.02 5.03 5270 2820 1630 600 1580 540 8 7.00 5.02 5750 3130 2420 490 1980 420 9 7.08 5.09 5720 2860 1810 430 1730 380 10 6.98 5.10 5670 2680 1860 360 1800 340 11 7.03 5.14 5340 2420 2540 480 2020 400 15 7.10 5.13 5810 2980 2830 640 2020 490 16 7.08 5.15 5070 2480 2220 690 1870 560 17 7.07 5.14 4970 2350 2120 700 1700 610 18 7.05 5.14 5460 2310 2710 530 2100 470 19 7.06 5.15 5350 2050 1940 460 1850 380 22 7.05 5.16 5210 1980 1920 430 1710 360 23 7.01 5.16 5180 1960 1890 430 1700 340 24 7.01 5.17 5090 1920 2010 490 1970 400 25 7.03 5.17 5200 1950 2130 530 2000 470 26 7.07 5.16 5060 1910 2080 500 1990 450
C o r r e la tio n o f C O D R e m o v a l & E fflu e n t p H W ith in S ta r tu p P e r io d
3 5 .0
4 0 .0
4 5 .0
5 0 .0
5 5 .0
6 0 .0
6 5 .0
1 2 3 4 8 9 1 0 1 1 1 5 1 6 1 7 1 8 1 9 2 2 2 3 2 4 2 5 2 6
D a y
CO
D R
emov
al, %
4 .9 0
4 .9 5
5 .0 0
5 .0 5
5 .1 0
5 .1 5
5 .2 0
Effluent pH
CO D Re mo v a l, %
Ef f lu e n t p H
Figure 4.1: COD removal and effluent pH within the startup period.
F
m
T
e
v
p
h
w
p
U
a
o
f
T
a
C o r r e la tio n o f T S S & V S S R e m o v a l W ith in S ta r tu p P e r io d
5 0 .0
5 5 .0
6 0 .0
6 5 .0
7 0 .0
7 5 .0
8 0 .0
8 5 .0
1 2 3 4 8 9 1 0 1 1 1 5 1 6 1 7 1 8 1 9 2 2 2 3 2 4 2 5 2 6
D a y
Rem
oval
, %
TS S Re mo v a l, %
V S S Re mo v a l, %
igure 4.2: TSS and VSS removal within the startup period.
The steady state condition was achieved after 26 days acclimatization with the
aximum COD removal varies in the range of 62% to 63%, which varies less than 5%.
he effluent pH presented the similar trend as the COD removal and the pH of the
ffluents varies from 5.15 to 5.17 in the steady state condition. In these range of pH
alues, the process of acidogenesis was more dominant than methanogenesis. In the
rocess of acidogenesis, O&G was hydrolyzed and fermented to produce acetate,
ydrogen, carbon dioxide, and propionate and butyrate. The propionate and butyrate
ere fermented further, to also produce hydrogen, carbon dioxide, and acetate as
recursors for methanogenesis.
The TSS and VSS removal showed the same trends within the startup period. The
ASB reactor was able to remove the TSS and VSS of the influents about 75% to 78%
nd 77% to 80% respectively at the steady state condition. The solids and particulate
rganic matters did not accumulated in the reactor but they were hydrolyzed and
ermented into soluble form as no significant increment of sludge volume was observed.
he sharp drops at day 3 and 17 were caused by the washout of the filamentous sludge
nd particulate of the scum layer at the top of reactor.
4.3 Design of Experiments
The data of COD, pH and O&G for the influents and effluents in three replicates
were collected and tabulated in Tables 4.3, 4.4 and 4.5. The percentages for COD and
O&G removal could also be calculated.
Table 4.3: Data of replicate 1 in factorial design experiment.
COD (mg/L) pH O&G (mg/L) Runs HRT (hrs)
In Out Removal, % In Out In Out Biodegradation, % 1 3.3 5090 3320 34.8 3.02 3.78 561 373 33.5 2 12.9 5080 2860 43.7 3.00 3.32 541 299 44.7 3 3.3 15340 10620 30.8 3.01 3.28 1713 1134 33.8 4 12.9 15120 8470 44.0 3.02 3.22 1643 955 41.9 5 3.3 5740 2440 57.5 7.02 5.76 540 268 50.4 6 12.9 5720 2170 62.1 7.01 5.13 529 196 63.0 7 3.3 14640 6350 56.6 7.03 5.48 1589 798 49.8 8 12.9 14840 5940 60.0 7.00 5.12 1623 610 62.4
Table 4.4: Data of replicate 2 in factorial design experiment.
COD (mg/L) pH O&G (mg/L) Runs HRT (hrs)
In Out Removal, % In Out In Out Biodegradation, % 1 3.3 5070 3330 34.3 3.03 3.95 542 358 33.9 2 12.9 5010 2800 44.1 3.01 3.33 533 292 45.2 3 3.3 14860 10170 31.6 3.03 3.29 1682 1108 34.1 4 12.9 15180 8580 43.5 3.05 3.24 1701 924 45.7 5 3.3 5670 2420 57.3 7.05 5.70 538 263 51.1 6 12.9 5370 2050 61.8 7.06 5.15 498 187 62.4 7 3.3 15320 6640 56.7 7.04 5.52 1613 805 50.1 8 12.9 14460 5930 59.0 7.03 5.16 1654 630 61.9
Table 4.5: Data of replicate 3 in factorial design experiment.
COD (mg/L) pH O&G (mg/L) Runs HRT (hrs)
In Out Removal, % In Out In Out Biodegradation, % 1 3.3 5200 3420 34.2 3.10 3.99 529 341 35.5 2 12.9 5130 2880 43.9 3.02 3.30 538 301 44.1 3 3.3 14980 10320 31.1 3.01 3.26 1699 1111 34.6 4 12.9 15290 8590 43.8 3.05 3.25 1665 931 44.1 5 3.3 5350 2290 57.2 7.00 5.72 551 271 50.8 6 12.9 5410 2100 61.2 7.09 5.17 531 195 63.3 7 3.3 14890 6550 56.0 7.01 5.50 1605 817 49.1 8 12.9 15050 6080 59.6 7.04 5.13 1633 644 60.6
From the results in these three replicates, the optimum combination of operating
parameters was HRT 12.9 hrs, influent 5,000 mg/L COD and influent pH 7 which success
to remove 61% to 62% COD and biodegrade 62% to 63% O&G in experiment Run 6.
However, the minimum COD removal was 31% and O&G biodegradation was 34% in
experiment Run 3, under operating parameters HRT 3.3 hrs, influent 15,000 mg/L COD
and influent pH 3. Other combinations of treatments responded to the intermediate COD
removal and O&G biodegradation.
The COD removal was considered linear to the O&G biodegradation as illustrated
by the scatter plot in Figure 4.3. The R2 is 0.8931, this show that the close relation
between COD removal and O&G biodegradation. Also, from the regression equation the
percent of O&G biodegradation could be predicted from the percent of COD removal or
vice versa.
F 4
t
Correlation of COD Removal and O&G Biodegradation
y = 1.0271x - 0.5107R2 = 0.8931
0
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70
O&G Biodegradation, %
CO
D R
emov
al, %
igure 4.3: Scatter plot of COD removal and O&G biodegradation in three replicates.
.3.1 Chemical Oxygen Demand Removal
The data of COD removal in the three replicates were rearranged as in Table 4.6
o ease for further calculations of effects estimation.
Table 4.6: Data of the COD removal experiment.
Labels COD Removal, %
Runs HRT (A)
Influent COD (B)
Influent pH (C) Average
(1) 1 3.3 5,000 3 34.4 a 2 12.9 5,000 3 43.9 b 3 3.3 15,000 3 31.2 ab 4 12.9 15,000 3 43.8 c 5 3.3 5,000 7 57.3 ac 6 12.9 5,000 7 61.7 bc 7 3.3 15,000 7 56.4 abc 8 12.9 15,000 7 59.5
The effect estimate, sum of squares and percent contribution of factors A, B, C
and their interactions were calculated and summarized in Table 4.7. These data were
used to determine the significant impacts and effects of the factors and/or their
interactions on COD removal. The formula and calculations of effects estimate were
shown in Appendix C.
Table 4.7: Effect estimate summary for COD removal.
Factors Effect Estimate Sum of Squares
Percent Contribution
A 7.38 327.08 11.1311 B -1.62 15.68 0.5336 C 20.43 2505.13 85.2540 AB 0.47 1.31 0.0446 AC -3.65 79.94 2.7205 BC 0.08 0.04 0.0014 ABC -1.10 7.26 0.2471 Pure Error - 1.99 0.0677 Total - 2938.43 -
The largest effects on COD removal were influent pH (C=20.43), HRT (A=7.38)
and HRT-influent pH interaction (AC= -3.65). The effect of AC was negative, this
suggested that increasing the HRT-influent pH interaction would decrease COD removal.
The influent COD (B= -1.62) and HRT-influent COD-influent pH interaction (ABC= -
1.10) did not appear to have as large impacts on COD removal deviation as the main
effects. The effect of B and ABC were negative, this suggested that increasing the
influent COD and HRT-influent COD-influent pH interaction would decrease COD
removal. The main effects C, A and AC dominated the COD removal accounting for
99% of the total variability, whereas the B and ABC interaction accounting for 0.8%.
The analysis of variance might be used to confirm the magnitude of these effects.
The degree of freedom, mean squares, Fo and P-Value for the factors and their
interactions were determined and listed in Table 4.8.
Table 4.8: Analysis of variance for the COD removal data.
Source of Variation
Sum of Squares
Degree of Freedom
Mean Square Fo P-Value
A 327.08 1 327.08 2725.67 <0.0001 B 15.68 1 15.68 130.67 <0.0001 C 2505.13 1 2505.13 20876.08 <0.0001 AB 1.31 1 1.31 10.92 0.0045 AC 79.94 1 79.94 666.17 <0.0001 BC 0.04 1 0.04 0.33 0.5736 ABC 7.26 1 7.26 60.50 <0.0001 Error 1.99 16 0.12 - - Total 2938.43 23 - - -
From Table 4.8, we note that the main effects (C, A and AC) on COD removal
were highly significant as all have very small P-Value. The other effects (B and ABC
interaction) on COD removal were also significant as their small P-Value.
The main effects of HRT (A), influent pH (C) and HRT-influent pH (AC)
interaction were plotted in Figure 4.4 (a, b and c). The A and C effects were positive, if
considered only these main effects, we would run these factors at the high level to
maximize the COD removal. However, it was always necessary to examine any
interactions that are important. The main effects did not have much meaning when they
were involved in significant interactions.
F
igure 4.4: Main effects and interaction plots for COD removal.
From the interaction (AC) plot, the two lines were not parallel so they would meet
and cross at higher level HRT. This indicated that the interaction of HRT-influent pH had
significant large impact on COD removal. The HRT effect was small when the influent
pH was at the low level (black line) but large when the influent pH was at the high level
(red line), with the best results obtained when HRT (A) and influent pH (C) were at the
high level.
This could be confirmed by the 2D contour plot in Figure 4.5. Notice that the
contours were curved lines as the model contains an interaction, HRT-influent pH (AC)
interaction. This contour plot could be used as a guide to control the factors, HRT (A)
and influent pH (C) to achieve optimum COD removal.
Influent pH
HR
T (h
rs)
6.86.46.05.65.24.84.44.03.63.2
6.86.46.05.65.24.84.44.03.63.2
12
11
10
9
8
7
6
5
4
12
11
10
9
8
7
6
5
4
COD
40 - 4545 - 5050 - 5555 - 60
> 60
< 3535 - 40
Contour Plot of COD Removal vs HRT (hrs), Influent pH Figure 4.5: 2D contour plot for COD removal. 4.3.2 Oil and Grease Biodegradation
The data of O&G biodegradation in the three replicates were rearranged as in
Table 4.9 to ease for further calculations of effects estimation.
Table 4.9: Data of the O&G biodegradation experiment.
Labels O&G Biodegradation, %
Runs HRT (A)
Influent COD (B)
Influent pH (C) Average
(1) 1 3.3 5,000 3 34.3 a 2 12.9 5,000 3 44.7 b 3 3.3 15,000 3 34.2 ab 4 12.9 15,000 3 43.9 c 5 3.3 5,000 7 50.8 ac 6 12.9 5,000 7 62.9 bc 7 3.3 15,000 7 49.7 abc 8 12.9 15,000 7 61.6
The effect estimate, sum of squares and percent contribution of factors A, B, C
and their interactions were calculated and summarized in Table 4.10. These data would
be used to determine the significant impacts and effects of the factors and/or their
interactions on O&G biodegradation. The calculations of effects estimate were similar to
that in COD removal experiment as in Appendix C.
Table 4.10: Effect estimate summary for O&G biodegradation.
Factors Effect Estimate Sum of Squares
Percent Contribution
A 11.05 732.62 29.4495 B -0.82 4.00 0.1608 C 16.98 1730.60 69.5657 AB -0.20 0.24 0.0096 AC 1.00 6.00 0.2412 BC -0.37 0.81 0.0326 ABC 0.12 0.08 0.0032 Pure Error - 13.37 0.5374 Total - 2487.72 -
The largest effects on O&G biodegradation were influent pH (C=16.98) and HRT
(A=11.05). The HRT-influent pH interaction (AC=1.00) and influent COD (B= -0.82)
did not appear to have as large impacts on O&G biodegradation deviation as the main
effects. The effect of B was negative, this suggested that increasing the influent COD
would decrease O&G biodegradation. The main effects C and A dominated the O&G
biodegradation accounting for 99% of the total variability, whereas the AC interaction
and B accounting for 0.4%.
The analysis of variance might be used to confirm the magnitude of these effects.
The degree of freedom, mean squares, Fo and P-Value for the factors and their
interactions were determined and listed in Table 4.11.
Table 4.11: Analysis of variance for the O&G biodegradation data.
Source of Variation
Sum of Squares
Degree of Freedom
Mean Square Fo P-Value
A 732.62 1 732.62 872.17 <0.0001 B 4.00 1 4.00 4.76 0.0444 C 1730.60 1 1730.60 2060.24 <0.0001 AB 0.24 1 0.24 0.29 0.5976 AC 6.00 1 6.00 7.14 0.0167 BC 0.81 1 0.81 0.96 0.3418 ABC 0.08 1 0.08 0.10 0.7559 Error 13.37 16 0.84 - - Total 2487.72 23 - - -
From Table 4.11, we note that the main effects (C, and A) on O&G
biodegradation were highly significant as all had very small P-Value. The AC interaction
and B was significant at about the 10 percent level, thus there was some mild interaction
between HRT and influent pH as well as influent COD on O&G biodegradation.
The main effects of HRT (A) and influent pH (C) as well as their interaction were
plotted in Figure 4.6 (a, b and c). The A and C effects were positive, if considered only
these main effects, we would run these factors at the high level to maximize the O&G
biodegradation. However, it was always necessary to examine any interactions that were
important.
F
igure 4.6: Main effects and interaction plots for O&G biodegradation.
From the interaction (AC) plot, the two lines were approximately parallel so they
would not meet and cross. This indicated that there was lack of interaction between
HRT-influent pH on O&G biodegradation. This could be confirmed by the 2D contour
plot in Figure 4.7. Notice that the contours were parallel straight lines as the model did
not contain an interaction. This contour plot could be used as a guide to control the
factors, HRT (A) and influent pH (C) to achieve optimum O&G biodegradation.
Influent pH
HR
T (h
rs)
6.86.46.05.65.24.84.44.03.63.2
6.86.46.05.65.24.84.44.03.63.2
12
11
10
9
8
7
6
5
4
12
11
10
9
8
7
6
5
4
O&G
40 - 4545 - 5050 - 5555 - 60
> 60
< 3535 - 40
Contour Plot of O&G Biodegradation vs HRT (hrs), Influent pH
Figure 4.7: 2D contour plot for O&G biodegradation.
CHAPTER 5
DISCUSSION OF RESULTS
5.1 Characterization of Palm Oil Mill Effluent The characteristics of the raw POME provide the feasibility of this wastewater to
be treated by UASB reactors. From the data obtained, the ratio of BOD to COD was 0.26
and the fraction of insoluble COD was 50% which indicated that raw POME was
categorized as less biodegradable or complex wastewater.
Industrial wastewaters that containing insoluble or potentially insoluble pollutants,
and compounds which give rise to inhibition or toxicity, to foaming, scaling and sludge
flotation can be designated as belonging to the category complex wastewaters (Lettinga
and Hulshoff Pol, 1991). Due to the presence of these compounds, a variety of problems
may manifest in the anaerobic treatment, depending on the type and concentration of the
complex compounds present.
The average O&G concentration of 9,500 mg/L was detected in raw POME, this
reflected that the unrecovered hydrophobic pollutants from the palm oil extraction
process. High concentration of O&G would lead to the formation of scum layers
consisting of floating substrate ingredients together with entrapped or attached active
sludge.
Particularly the presence of suspended fats and lipids will heavily promote the
tendency for sludge flotation, both flocculent and granular. This scum layer formation
may result in a more significant washout of active matter, as well as in the production of
considerable quantities of poorly stabilized excess scum layer sludge. Heavy foaming in
the reactor can only be avoided by operating the system under moderate loading rates and
maintaining good contact between sludge and wastewater (Lettinga and Hulshoff Pol,
1991).
On top of that, the average TSS concentration of 40,000 mg/L was detected in the
raw POME. High concentration of suspended solids (potentially precipitating matter)
presented in the wastewater would reduce the specific methanogenic activity of the sludge
in the case the suspended solids were poorly or non biodegradable and when it
accumulated in the sludge bed, either by a mechanism of mechanical entrapment or of
physical adsorption. Also, the attachment of newly generated bacterial matter to the
surface of suspended particles would, in the case when flocculent seed sludge was used,
slow down or even might completely counteract the formation of granular sludge.
When the suspended matter consisted of colloidal or poorly settleable matter, a
considerable part of newly formed bacterial matter would leave the reactor together with
this TSS fraction. This particularly would occur when the suspended solids consisted of
fibrous matter.
Apart from the characteristics of the TSS, also the concentration of the dispersed
matter is of big importance. It will be evident that beyond a certain TSS concentration,
depending on the characteristics of the TSS, an anaerobic treatment system like the
UASB reactor will become less feasible (Lettinga and Hulshoff Pol, 1991).
The characteristics of the raw POME would guide to the UASB reactor designs.
By knowing the high strength of the raw POME was not possible directly apply to the
UASB reactor, dilution of this raw POME was necessary in order to reduce the strength
of the original raw POME. The strength of the wastewater was depending on the COD
concentration.
5.2 Upflow Anaerobic Sludge Blanket Reactor Startup
Startup is often considered to be the most unstable and difficult phase in anaerobic
digestion. Its main task is to develop a highly active settleable sludge as quickly as
possible. While as anaerobic bacteria are slow growing microorganisms, major problems
encountered with UASB are the typical long reactor startup and spontaneous development
of biogranulation. Startup times for UASB reactors with digested sewage sludge usually
take several months (Show et al., 2004).
With the short startup period, the granular sludge is not able to be formed in the
UASB reactor. It generally requires 2 to 8 months for the development of anaerobic
granular sludge. In order to reduce the space-time requirements of bioreactors and
eventually lead to a cheaper treatment of high strength wastes, strategies for expediting
granular formation are highly desirable (Liu et al., 2003).
For the reactor startup, the steady state condition was achieved after 26 days
acclimatization with the maximum COD removal varies in the range of 62% to 63%.
Although the steady state was achieved, the startup period was relatively short. This had
lead to the used of flocculent sludge in this study.
Flocculent sludge performs less treatment efficiency than granular sludge for
UASB reactor (Hulshoff Pol et al., 2004). With the strength of influent COD 5,000 mg/L
and organic loading 9.3 g/L.d COD, these parameters were slightly higher than the
recommended in UASB design. For the strength of COD between 2,000 to 6,000 mg/L,
fraction of insoluble COD 30% to 60%, the applicable organic loading rate is 4 to 8 g/L.d
(Tchobanoglous et al., 2003). In this case, the COD removal had to be satisfied below
63% at steady state condition.
The effluent pH varies from 5.15 to 5.17 in the steady state condition was
observed. Anaerobic processes are sensitive to pH and inhibitory substances. A pH value
near neutral is preferred and below 6.8 the methanogenic activity is inhibited
(Tchobanoglous et al., 2003). In addition, a pH of around 6.0 appears to be the optimum
for acidogenic activity. If the pH is not controlled, the acidogenic biomass tends to buffer
itself to a pH that depends on the other environmental conditions in the reactor but mainly
on the nature of the wastewater (Borja et al., 1996). Therefore, the process of
acidogenesis was more dominant than methanogenesis in this UASB reactor. The gas
produced in the acidogenic reactor is primarily carbon dioxide and hydrogen
(Tchobanoglous et al., 2003).
The predominant volatile fatty acid found during this period is acetic acid.
Propionic, butyric and valeric acids are also detectable. These volatile fatty acids as
products of the acidogenesis can diffuse into the cells of anaerobic bacteria and ionize to
decrease the pH. This is generally recognized as inhibiting acidogenesis. The alkalinity
of the influent allows the neutralization of the free volatile fatty acids, preventing the fall
in pH from its optimum value both in the reactant influent and in the cells, while the
volatile fatty acids in the acidogenic UASB increased (Borja et al., 1996). In this study,
the influents that supplied into the UASB reactor were adjusted to pH 7 for the
neutralization purpose during the startup period.
In this study, the removals of TSS from 75% to 78% and VSS from 77% to 80%
were achieved at the steady state condition. The acidogenic reactor although tolerant to
an influent TSS concentration of 5,400 mg/L, showed a sign of reduced solids
liquification when the loading was increased and the TSS concentration was 10,800 mg/L
(Borja et al., 1996).
However, the concentration of TSS in the influents that supplied into the UASB
reactor during startup period varies from 1,630 to 2,830 mg/L. As a result, the solids and
particulate organic matters did not accumulated in the reactor but they were hydrolyzed
and fermented into soluble form as no significant increment of sludge volume was
observed.
For the wastewater that contains O&G substances, it can cause foaming and scum
formation (Tchobanoglous et al., 2003). The sharp drops of TSS and VSS removals at
day 3 and 17 were caused by the washout of the filamentous sludge and particulate of the
scum layer at the top of reactor.
5.3 Statistical Designed Experiments
Factorial designs are widely used in experiments involving several factors where
it is necessary to study the joint effect of the factors on a response. There are several
assumptions for factorial designs, the factors are fixed, the designs are completely
randomized and the usual normality assumptions are satisfied. The 2k design is
particularly useful in the early stages of experimental work, when there are likely to be
many factors to be investigated.
It provides the smallest number of runs with which k factors can be studied in a
complete factorial design. Consequently, these designs are widely used in factor
screening experiments. As there are only two levels for each factor, we assume that the
response is approximately linear over the range of the factor levels chosen. In many
factor screening experiments, when starting to study the process or system, this is often a
reasonable assumption and discuss what action to take if it is violated (Montgomery,
2005).
In the experiments of COD removal and O&G biodegradation, the optimum
combination of operating parameters was HRT 12.9 hrs, influent 5,000 mg/L COD and
influent pH 7 which success to remove 61% to 62% COD and biodegrade 62% to 63%
O&G. There was proved that the COD removal was considered linear to the O&G
biodegradation. From the statistical analysis, the main effects for both experiments were
HRT and influent pH as well as their interactions.
The operation of UASB reactor is not restricted by the microbial capacity but is
limited by hydraulic factors. As the upflow velocity in the settler may not exceed value
of 1.5 m/hr, the minimum retention time is 4 to 6 hrs (Weiland and Rozzi, 1991).
Shorter HRT will lead to operational problems like sludge bed flotation, excessive
foaming at the gas-liquid interface, as well as accumulation of undigested ingredients.
Then, the treatment efficiency deteriorates (Mahmoud et al., 2003). From the
experiments, the COD removal and O&G biodegradation were increasing from low level
of HRT (3.3 hrs) to high level of HRT (12.9 hrs). Longer HRT will provide longer
contact between wastewater and the biomass. Because of this reason, HRT plays as
major role to the COD removal and O&G biodegradation.
Since O&G are esters, they undergo hydrolysis with more or less ease. The
hydrolysis may be induced by chemical means, usually by treatment with NaOH, or by
bacterial enzymes that split the molecule into glycerol plus fatty acids. Hydrolysis with
the aid of NaOH is called saponification (Sawyer et al., 2003). Anaerobic processes are
sensitive to pH and inhibitory substances. A pH value near neutral is preferred for
optimum bacterial enzymes activities (Tchobanoglous et al., 2003).
From the experiments, the COD removal and O&G biodegradation were
increasing from low level of influent pH (3) to high level of influent pH (7). To achieve
the high level of pH, the influent pH was adjusted to neutral by the addition of NaOH. So,
the O&G was hydrolysed by chemical means (saponification) and bacterial enzymes
(anaerobic sludge in UASB). For that reasons, the influent pH was considered main
effect to COD removal and O&G biodegradation.
Although high level of HRT and influent pH would increase the COD removal
and O&G biodegradation, they might have the constraints to go higher levels. Higher
level of pH might be toxic to the biomass (acidogenesis and methanogenesis). This
would cause the low bioactivity and treatment efficiency. Then, for higher level of HRT
the UASB reactor might able to biodegrade the slowly biodegraded matters and achieve
better treatment efficiency. However, it might not be considered as a high rate anaerobic
treatment system.
CHAPTER 6
CONCLUSION AND RECOMMENDATIONS
6.1 Conclusion
The following conclusions have been proved in the study:
i. The steady state of the reactor was obtained at about 62% of COD removal after
26 days acclimatization.
ii. Under the designed operating parameters, the maximum O&G biodegradation was
63% and COD removal was 62% for the treatment of POME using UASB.
iii. The main factors that had statistically significant effect on COD removal were
influent pH, HRT and HRT-influent pH interaction.
iv. While, the main factors that had statistically significant effect on O&G
biodegradation were influent pH and HRT.
Thus it would be concluded that the objectives of the study had been achieved.
6.2 Recommendations
Some recommendations that can be suggested for the future study are as follows:
i. The COD removal in the steady state conditions should be improved so as to
increase the O&G biodegradation.
ii. Reactor design should comply with the recommended UASB reactor design
considerations.
iii. A gas-solid separator device should be installed at the top of an UASB reactor.
iv. Nutrients requirements, presence of toxic materials and inhibitors, and alkalinity
should be monitored and maintained for the reactor startup.
v. Anaerobic sludge granulation should be achieved in order to improve the
treatment efficiency.
vi. Biodegradation of O&G can also be increased by two stages UASB reactor.
vii. Last but not least, the advanced detection method of O&G should be applied in
order to have better understanding of O&G biodegradation.
REFERENCES
Ahmad, A. L., Bhatia, S., Ibrahim, N. and Sumathi, S. (2005). Adsorption of Residual Oil
from Palm Oil Mill Effluent Using Rubber Powder. Brazilian Journal of Chemical
Engineering. 22(3): 371-379.
Ahmad, A. L., Ismail, S. and Bhatia, S. (2003). Water Recycling from Palm Oil Mill
Effluent (POME) Using Membrane Technology. Desalination. 157: 87-95.
Ahmad, A. L., Sumathi, S. and Hameed, B. H. (2005). Adsorption of Residue Oil from
Palm Oil Mill Effluent Using Powder and Flake Chitosan: Equilibrium and
Kinetic Studies. Water Research. 39: 2483-2494.
APHA, AWWA and WEF, (2000). Standard Methods for the Examination of Water and
Wastewater, 20th Edition. APHA, AWWA and WEF. Washington, DC.
Bae, B. U. and Shin, H. S. (1998). Performance of An Inner Tube-type Gas-Solid
Separator Device in a UASB Reactor. Bioresource Technology. 63: 23-27.
Basiron, Y. and Chan, K. W. (2004). The Oil Palm and Its Sustainability. Journal of Oil
Palm Research. 16(1): 1-10.
Basiron, Y., Balu, N. and Chandramohan, D. (2004). Palm Oil: The Driving Force of
World Oils and Fats Economy. Oil Palm Industry Economic Journal. 4(1): 1-10.
Borja, R. and Banks, C. J. (1994). Anaerobic Digestion of Palm Oil Mill Effluent Using
an Up-flow Anaerobic Sludge Blanket Reactor. Biomass and Bioenergy. 6(5):
381-389.
Borja, R., Banks, C.J. and Sanchez, E. (1996). Anaerobic Treatment of Palm Oil Mill
Effluent in A Two-Stage Up-flow Anaerobic Sludge Blanket (UASB) System.
Journal of Biotechnology. 45: 125-135.
Chow, M. C. and Ho, C. C. (2000). Surface Active Properties of Palm Oil With Respect
To the Processing of Palm Oil. Journal of Oil Palm Research. 12(1): 107-116.
Department of Environment (1999). Industrial Processes & the Environment (Handbook
No. 3) Crude Palm Oil Industry. Malaysia: Aslita Sdn Bhd.
Edem, D. O., Eka, O. U., Umoh, I. B., Udoh, A. P. and Akpan, E. J. (2003). Effect of Red
Palm Oil and Refined Palm Olein on Nutrient Digestion in the Rat. Pakistan
Journal of Nutrition. 2(5): 271-278.
Faisal, M. and Unno, H. (2001). Kinetic Analysis of Palm Oil Mill Wastewater Treatment
by a Modified Anaerobic Baffled Reactor. Biochemical Engineering Journal. 9:
25-31.
Hulshoff Pol, L. W., de Castro Lopes, S. I., Lettinga, G. and Lens, P. N. L. (2004).
Anaerobic Sludge Granulation. Water Research. 38: 1376-1389.
Laws of Malaysia. (2003). Environmental Quality Act and Regulations. Malaysia: MDC
Publishers Sdn Bhd.
Lettinga, G. and Hulshoff Pol, L. W. (1991). UASB-Process Design for Various Types of
Wastewater. Wat. Sci. Tech. 24(8): 87-107.
Lim, L. P. and Ujang, Z. (2004). The Operating Strategy for Treatment of Digested Palm
Oil Mill Effluent (POME) in a Flat Sheet Aerobic Membrane Bioreactor Under
Tropical Conditions. ASIA WATER: 1-8
Liu, Y., Xu, H. L., Yang, S. F. and Tay, J. H. (2003). Mechanisms and Models for
Anaerobic Granulation in Upflow Anaerobic Sludge Blanket Reactor. Water
Research. 37: 661-673.
Mahmoud, N., Zeeman, G., Gijzen, H. and Lettinga, G. (2003). Solids Removal in
Upflow Anaerobic Reactors, a Review. Bioresource Technology. 90: 1-9.
Malina, Jr. J. F. and Pohland, F. G. (1992). Design of Anaerobic Processes for the
Treatment of Industrial and Municipal Wastes. Pennsylvania: Technomic
Publishing Company, Inc.
Montgomery, D. C. (2005). Design and Analysis of Experiments. Sixth Edition. USA:
John Wiley & sons, Inc.
Ooi, T. L. and Yeong, S. K. (2000). Studies on Factors Affecting the Colour Stability of
Some Commercial Palm Fatty Acids. Journal of Oil Palm Research. 12(2): 63-72.
Pantzaris, T. P. and Ahmad, M. J. (2001). Properties and Utilization of Palm Kernel Oil.
Palm Oil Developments. 35: 11-23.
Sawyer, C. N., McCarty, P. L. and Parkin, G. F. (2003). Chemistry for Environmental
Engineering and Science. 5th ed. New York: McGraw-Hill Companies, Inc.
Shaaban, M. G. (1990). Performance Comparison of Anaerobic Bioreactors: Initial Study
of Upflow Anaerobic Sludge Blanket (UASB) Process in the Treatment of Palm
Oil Mill Effluent (POME). Bulletin IEM: 5-10.
Show, K. Y., Wang, Y., Foong, S. F. and Tay, J. H. (2004). Accelerated Start-Up and
Enhanced Granulation in Upflow Anaerobic Sludge Blanket Reactors. Water
Research. 38: 2293-2304.
Sundram, K. (2004). Palm Oil: Chemistry and Nutrition Updates. Malaysian Palm Oil
Board (MPOB): 1-22.
Tchobanoglous, G., Burton, F.L. and Stensel, H.D. (2003). Wastewater Engineering:
Treatment and Reuse, Fourth Edition. New York: McGraw Hill Companies, Inc.
Ugoji, E. O. (1997). Anaerobic Digestion of Palm Oil Mill Effluent and Its Utilization As
Fertilizer for Environmental Protection. Renewable Energy. 10(2): 291-294.
Weiland, P. and Rozzi, A. (1991). The Start-Up, Operation and Monitoring of High Rate
Anaerobic Treatment System: Discusser’s Report. Wat. Sci. Tech. 24(8): 257-277.
Yu, H. Q., Fang, H. H. P. and Tay, J. H. (2001). Enhanced Sludge Granulation in Upflow
Anaerobic Sludge Blanket (UASB) Reactors by Aluminum Chloride.
Chemosphere. 44: 31-36.
Yu, H. Q., Tay, J. H. and Fang, H. H. P. (2001). The Roles of Calcium in Sludge
Granulation during UASB Reactor Start-Up. Water Research. 35(4): 1052-1060.
APPENDIX A
APPENDIX B
APPENDIX C 2k Factorial Design Examples-Chemical Oxygen Demand Removal
Factors Runs HRT Inf. COD Inf. pH R1 R2 R3 Total Factors
1 3.3 5000 3 34.8 34.3 34.2 103.3 (1) 2 12.9 5000 3 43.7 44.1 43.9 131.7 a 3 3.3 15000 3 30.8 31.6 31.1 93.5 b 4 12.9 15000 3 44.0 43.5 43.8 131.3 ab 5 3.3 5000 7 57.5 57.3 57.2 172.0 c 6 12.9 5000 7 62.1 61.8 61.2 185.1 ac 7 3.3 15000 7 56.6 56.7 56.0 169.3 bc 8 12.9 15000 7 60.0 59.0 59.6 178.6 abc
Total 1164.8
Using the totals under the treatment combinations shown in table above, we may estimate the factor effects as follows:
[ ]
[ ]
[ ]38.7
6.88121
3.1696.1780.1721.1855.933.1313.1037.131)3(4
1
,)1(41
=
=
−+−+−+−=
=−+−+−+−= replicateofnosnwherebcabccacbaban
A
[ ]
[ ]
[ ]62.1
4.19121
1.1850.1727.1313.1036.1783.1693.1315.93)3(4
1
,)1(41
−=
−=
−−−−+++=
=−−−−+++= replicateofnosnwhereaccaabcbcabbn
B
[ ]
[ ]
[ ]43.20
2.245121
3.1315.937.1313.1036.1783.1691.1850.172)3(4
1
,)1(41
=
=
−−−−+++=
=−−−−+++= replicateofnosnwhereabbaabcbcaccn
C
[ ]
[ ]
[ ]47.0
6.5121
0.1721.1853.1696.1783.1035.937.1313.131)3(4
1
,)1(41
=
=
+−−++−−=
=+−−++−−= replicateofnosnwherecacbcabcbaabn
AB
[ ]
[ ]
[ ]65.3
8.43121
6.1783.1691.1850.1723.1315.937.1313.103)3(4
1
,)1(41
−=
−=
+−+−−+−=
=+−+−−+−= replicateofnosnwhereabcbcaccabban
AC
[ ]
[ ]
[ ]08.0
0.1121
6.1783.1691.1850.1723.1315.937.1313.103)3(4
1
,)1(41
=
=
++−−−−+=
=++−−−−+= replicateofnosnwhereabcbcaccabban
BC
[ ]
[ ]
[ ]25.0
0.3121
8.1919.2296.1847.1887.1986.2669.1918.228)3(4
1
,)1(41
=
=
−++−+−−=
=−++−+−−= replicateofnosnwhereababcacbcabcn
ABC
The largest effects are for HRT (A=7.38), Influent pH (C=20.43) and HRT-
Influent pH interaction (AC=-3.65). The sums of squares are calculated as below:
( )n
ContrastSS8
2
=
( ) 08.327)3(8
6.88 2
==ASS
( ) 68.15
)3(84.19 2
=−
=BSS
( ) 13.2505)3(82.245 2
==CSS
( ) 31.1
)3(86.5 2
==ABSS
( ) 94.79
)3(88.43 2
=−
=ACSS
( ) 04.0
)3(80.1 2
==BCSS
( ) 26.7
)3(82.13 2
=−
=ABCSS
The total sum of squares is SST
= 2938.43 and by subtraction, SSE = 2.00. Table below summarizes the effect estimates and sum of squares. The column labeled “percent contribution” measures the percentage contribution of each model term to the total sum of squares.
Factors Effect Estimate Sum of Squares Percent Contribution A 7.38 327.08 11.1311 B -1.62 15.68 0.5336 C 20.43 2505.13 85.2540
AB 0.47 1.31 0.0446 AC -3.65 79.94 2.7205 BC 0.08 0.04 0.0014
ABC -1.10 7.26 0.2471 Pure Error - 1.99 0.0677
Total - 2938.43 -
Factors Sum of Squares
Degrees of Freedom
Mean Square
F0 P-Value
(A) 327.08 1 327.08 2725.67 <0.0001 (B) 15.68 1 15.68 130.67 <0.0001 (C) 2505.13 1 2505.13 20876.08 <0.0001 AB 1.31 1 1.31 10.92 0.0045 AC 79.94 1 79.94 666.17 <0.0001 BC 0.04 1 0.04 0.33 0.5736
ABC 7.26 1 7.26 60.50 <0.0001 Pure Error 1.99 16 0.12 - -
Total 2938.43 23 - - -