WTI-PROJECT REPORT ON Nano zerovalent Iron-Graphene oxide Composite for enhanced biodegradation of wastewater.pdf

A project report
on
Nano-zerovalent iron-graphene oxide composite for enhanced
biodegradation of dairy wastewater:
A novel strategy for boosting biogas production
Submitted to
Department of Science and Technology
Ministry of Science and Technology, Govt. of India
Technology Bhavan, New Mehrauli Road
New Delhi-110016
Name of Scheme: DST/TMD/EWD/WTI/2K19/EWFH/2019/312(C)
From 30/12/2020 to 28/12/2024
Submitted by
Project PI
Dr. Arvind Kumar, Associate Professor
Department of Chemical Engineering
National Institute of Technology Rourkela, Odisha-769008

Acknowledgment
By completing this project journey, I would like to acknowledge Department of Science
and Technology, Ministry of Science and Technology, Govt. of India, Newdelhi for
providing financial support me to execute the project. I am grateful for all the
constructive criticisms that helped me tune up this research work to be successful.
I, also would like to convey my gratitude to the National Institute of Technology,
Rourkela, for giving me necessary research facilities to carry out the research. Further, I
am obliged to Prof. K. Umamaheshwar Rao, Director, NIT Rourkela, for the
administrative support.
i

Abstract
Developmental and industrial activities have caused extensive environmental impacts
worldwide. Many proactive ‘clean-environment’ strategies have been proposed and
implemented with the support of UNEP. The peer pressure on the government has assured
more stringent regulations to reduce the burgeoning effect of atmospheric pollution and
improve environmental performance. To comply with environmental regulations, the
stakeholders may need to depend on more efficient and competitive waste treatment
methodologies.
Researches on sustainable wastewater treatment technologies are on an increasing trend.
Studies help to develop processes with eco-friendly reactants, less energy requirement,
easy residue management, and high efficiency. Incorporating nanosystems into
wastewater treatment methodologies has been observed to be highly efficient due to the
superior physicochemical properties of nanoparticles. Iron nanoparticles (INPs) are
preferred among the studied nanoparticles because iron is highly abundant, low cost, has
no secondary pollution, and has easy separation from aqueous media. But, INPs show a
high tendency for aggregate formation and scavenging effects when used alone.
Composites of INPs have been employed to alleviate these problems. This study analyzed
the impact of composites of nano zerovalent iron (NZVI) and nano Fe3O4 for wastewater
treatment.
A composite was developed with NZVI and reduced graphene oxide (RGO) and studied
the effect on the anaerobic digestion of dairy wastewater. There was 86.27 ± 2.8% more
CH4 production and 47.37 ± 1.3% improved COD removal. Comparing different ratios of
RGO-NZVI revealed that a proportion of 2:1 was beneficial for maximum CH4
generation. Further, the higher concentrations of the conductive additives could be fatal
for microbial metabolism. The metagenomic analysis showed that the diversification of
the microbial community and switching to direct interspecies electron transfer caused
higher CH4 generation.
The effect of pretreatment on dairy wastewater digestion was also evaluated. Ammonium
persulfate (APS) assisted photocatalytic pretreatment using RGO-NZVI catalyst and
anaerobic digestion were integrated and assessed at different operational parameters. The
maximum solubilization was found at an initial pH 5 until 4 h of pretreatment with an
ii

increase of 38.77±0.85% SCOD and 39.05±1.3% dissolved organic carbon (DOC).
Digestion with pretreatment and fresh composite addition showed 81.01±3.24% more
CH4 production and 72.99±2.84% more SCOD removal. The anaerobic digestion of
pretreated wastewater containing spent catalyst was also producing a better volume of
CH4.
Another experiment incorporated the composite made of NZVI, polypyrrole (PPy), and
carbon black (CB) in biogas production. A dosage of 0-0.8 g L
-1
of Ppy-CB was chosen.
The maximum cumulative biogas production and SCOD removal efficiency were 2185 ±
76 mL and 74.69%, respectively. A Ppy-CB-NZVI dosage of 0.4 g L
-1
(D3) caused
43.27% more biogas than the control digester. Similarly, the total CH4 production in D3
was about 1.79 times higher. The results of residual VFA analysis and corresponding CH4
generation illustrated that the ternary additive significantly influenced hydrolysis, fatty
acid metabolism and acetogenesis, leading to higher gas production.
After anaerobic digestion, the active functionality of sludge was utilized to develop a
low-cost adsorbent by magnetic modification of pretreated biogas slurry solids (BSS) to
remove heavy metals such as Cu
2+
, Cd
2+
and Pb
2+
. The temperature (423 K) and time (1.5
h) of pretreatment, BSS to KOH ratio (1:10 w/v) and the ratio of magnetic iron
nanoparticle (MIN) to pretreated BSS (PSS) (1:2 w/w) were optimized for the preparation
of adsorbent. The optimum conditions for the adsorption of heavy metals were obtained
from response surface methodology (RSM) incorporating Central Composite Design
(CCD). Model validation experiments for optimization of the adsorption process showed
comparable results with predicted values. The adsorption capacity at optimum conditions
from RSM analysis was 29.721 mg L
-1
, 28.551 mg L
-1
and 28.601 mg L
-1
for Cu
2+
,
Cd
2+
and Pb
2+
, respectively. The adsorption kinetics followed a pseudo-second-order
model with an R
2
value above 0.9 for all metals with a well-approaching equilibrium
pattern. The excellent fit of experimental data by the Langmuir isotherm model implied
monolayer adsorption. By this, the effluents containing heavy metal, which causes
contamination of water resources, may be remediated effectively.
iii

Keywords: NZVI; reduced graphene oxide; interspecies electron transport; anaerobic
digestion; dairy wastewater; conductive additives; photocatalytic pretreatment;
polypyrrole; heavy metals; magnetic adsorbent
Table of contents
Acknowledgment
Abstract
Table of contents
List of Tables
List of Figures
Acronyms and abbreviations
Units
Chapter 1 1
Introduction and Literature Review
1.1General aspects of water and water pollution 2
1.2Nanoparticles in wastewater treatment 6
1.3Iron and its composites as enhancing additives 6
1.4Nanomaterials in biological degradation applications 8
1.5Anaerobic digestion for wastewater treatment 10
1.5.1 Dairy wastewater as a substrate for anaerobic digestion11
1.5.2 Biogas for sustainability 12
1.5.3 Strategies for enhanced digestion 15
1.5.4 Anchoring materials 22
1.5.5 Polymers in anaerobic digestion 25
1.5.6 Pretreatment for high disintegration and solubility27
1.5.7 The fate of biogas intermediates and end products31
1.6Adsorption of heavy metals using processed sludge 31
1.6.1 RSM method of optimization of the adsorption 34
1.7Research gap 35
1.8Objectives 36
1.9Outline of the Thesis 37
iv

Chapter 2 39
Materials and Methods
2.1Chemicals and substrates 40
2.2Characteristics of wastewater and degradation parameters40
2.2.1 SCOD measurement of samples 41
2.2.2 Determination of Fe
2+
41
2.2.3 Spectrophotometric analysis of ammonia 41
2.2.4 Measurement of VFA accumulation 41
2.2.5 Determination of cellulose 42
2.2.6 Protein estimation by Lowry’s assay 42
2.2.7 Measurement of DOC 42
2.2.8 Cyclic voltammetry 43
2.3Analytical methods 43
2.3.1 Characterization of composites 43
2.3.2 Adsorbent characterization 44
2.4Anaerobic digestion methods 44
2.4.1 Methanogenic seed inoculum 44
2.4.2 RGO-NZVI nanocomposite synthesis 45
2.4.3 Synthesis of NZVI-Ppy-CB ternary composite 45
2.4.4 Sludge and synthetic wastewater 46
2.4.5 Effect of RGO-NZVI on anaerobic digestion of dairy wastewater46
2.4.6 EGSB Reactor operation 48
2.4.7 Pretreatment of dairy wastewater 50
2.4.8 Anaerobic digestion after pretreatment 50
2.4.9 Anaerobic digestion with PPy-CB-NZVI 52
2.4.10 Characteristics of wastewater and degradation parameters52
2.4.11 Kinetics of anaerobic digestion 53
2.5Adsorption of heavy metals using magnetic adsorbent 53
v

2.5.1 Preparation of adsorbent from biogas slurry solids53
2.5.2 Batch adsorption experiments 54
2.5.3 Optimization by CCD 55
2.5.4 Kinetics and isotherm models for adsorption 56
Chapter 3 57
RGO-NZVI conductive additive assisted methanogenesis from dairy wastewater
by enhancement of bio-electrochemical events
3.1Preface 58
3.2Structural properties and characteristics of RGO-NZVI composite58
3.3Optimization of operational parameters 61
3.3.1 Effect of pH, organic loading and dosage on CH4 production61
3.3.2 Effect of ratio of RGO and NZVI 62
3.3.3 Reduction of organic load in the feed 66
3.3.4 NH3 production during anaerobic digestion 70
3.4Kinetics of biomethane generation 71
3.5Effects of RGO-NZVI composite on Microorganisms 73
3.6Demonstration of the effect of additive in EGSB continuous reactor76
3.7Conclusions 79
Chapter 4 80
Photocatalytic pretreatment of dairy wastewater and benefits of the
photocatalyst as an enhancer of anaerobic digestion
4.1Preface 81
4.2Characteristics of spent RGO-NZVI catalyst 81
4.3Optimization of operational conditions of photodegradation83
4.4Effect of pretreatment on anaerobic digestion 85
4.5Modified Gompertz model fitting 89
4.6Conclusions 89
vi

Chapter 5 91
A ternary NZVI-polypyrrole composite facilitated improved anaerobic digestion
performance
5.1Preface 92
5.2Physico-chemical characteristics of the composite 92
5.3Effect of different PPy-CB-NZVI dosages 94
5.4Trend of pH, Fe
2+
, VFA and NH4
+
concentration during the process97
5.5Kinetics of digestion 100
5.6Conclusions 101
Chapter 6 103
Magnetic adsorbent developed with alkali-thermal pretreated biogas slurry
solids for the removal of heavy metals: optimization, kinetic and equilibrium
study
6.1Preface 104
6.2Physicochemical Characterization of Adsorbent 104
6.3Optimization of the conditions of pretreatment 109
6.4Optimization of adsorption using RSM 111
6.4.1 Effect of pH, time, dosage and Initial concentration on adsorption115
6.4.2 Validation of model variables 117
6.5Kinetic Study 118
6.6Equilibrium study 119
6.7Thermodynamic Study 122
6.8Mechanism of Adsorption 123
6.9Regeneration of adsorbent 124
6.10Conclusions 125
Chapter 7 127
Conclusions and Future Perspectives
7.1Summary 128
7.2Conclusions 129
7.3Future scope of the study 130
vii

Reference
List of Tables
viii

Table 1.1 Details of iron and its composites applied for removal of pollutants
through different processes
Table 1.2 Strategies to upgrade biogas production by modification of batch
anaerobic reactors
Table 1.3 The performance of different conductive materials on CH4 production
Table 1.4 The effectiveness of different conductive composite materials applied in
anaerobic digestion
Table 1.5 Different pretreatment methods applied to improve anaerobic digestion
Table 1.6 Efficiency of combined photocatalysis and biological degradation for
different types of wastewaters
Table 2.1 Constitution of synthetic dairy wastewater
Table 2.2 The properties of each component added to the digester
Table 2.3 Operating conditions of EGSB reactor
Table 2.4 The properties of dairy wastewater fed to different digesters
Table 2.5 The initial characteristics of the slurry taken for digestion
Table 3.1 A comparison between efficiencies of different additives in anaerobic
digestion
Table 3.2 Modified Gompertz model fitting parameters.
Table 4.1 Comparison of modified Gompertz model parameters obtained from non-
linear fitting of experimental data
Table 5.3 Modified Gompertz model fitting parameters for digesters
Table 6.1 Physicochemical characteristics of BSS
ix

Table 6.2 BET Characteristics of different materials involved throughout the
development of adsorbent
Table 6.3 Design values of influencing parameters and responses of adsorption study
Table 6.4 Results of ANOVA test for the experimental design data
Table 6.5 Predicted values of individual parameters and results of validation
experiment for three different metal ions Cu
2+
, Cd
2+
and Pb
2+
.
Table 6.6 Description of Kinetic and Isotherm model and calculated model
parameters by non-linear fitting
Table 6.7 Attributes of adsorption thermodynamics for heavy metal adsorption
Table 6.8 Comparison of heavy metal adsorption onto various adsorbents studied
List of Figures
Figure 1.1 Water stress in India (a), sector-specific polluted water generation in
India (b)
x

Figure 1.2 Features of UN- Sustainable Development Goals No. 6
Figure 1.3 Stages and the fate of substrates during anaerobic digestion
Figure 1.4 Indirect (a) and direct (b) electron transfer between species (Sp.) in an
anaerobic digestion system
Figure 1.5 Interspecies electron transport through conductive pili (a), cytochromes
(b), conductive additive (c and d)
Figure 1.6 General mechanism of ZVI (a) assisted reduction and abatement of
sulfide and phosphate (b) in anaerobic digestion system
Figure 1.7 Mechanism of DIET in the presence of conductive materials
Figure 1.8 Proposed mechanism of DIET with the assistance of polypyrrole
Figure 2.1 Batch reactor for the anaerobic degradation of dairy wastewater
Figure 2.2 Schematic diagram of continuous flow anaerobic reactor set-up
Figure 2.3 Batch digestor for the degradation of RGO-NZVI catalyst-laden
pretreated dairy wastewater
Figure 3.1 Characteristic spectra of RGO-NZVI composite by FTIR (a), XRD (b)
and Raman spectra (c) analysis
Figure 3.2 SEM images of RGO-NZVI
Figure 3.3 Effect of operational parameters pH (a & b), organic loading (c & d) and
dosage (e & f) on anaerobic digestion
Figure 3.4 The volume of biogas on each sampling (a) and cumulative volume of
biogas (b) produced from each batch reactor
Figure 3.5 Concentration (a) and volume (b) of CH4 produced from each batch
reactor during the digestion
xi

Figure 3.6 SCOD reduction (a) and variation of pH (b) in each batch reactor along
the duration of digestion
Figure 3.7 VFA concentration (a) and Fe
2+
release and conductivity of the media (b)
in digesters throughout the digestion
Figure 3.8 Electrochemical behavior of sludge material by cyclic voltammetry (a),
The concentration of individual VFA accumulated during anaerobic digestion (b) and
cumulative CH4 produced from each batch reactor over the duration of digestion (c)
Figure 3.9 NH4
+
accumulation (a) and nonlinear curve fit of experimental data to
modified Gompertz model
Figure 3.10 Relative abundance of main archaeal and bacterial species in R3 (a) and
control digesters (b)
Figure 3.11 The abundance of genes for major functionalities observed (a), phylum
level classification of microbes observed in control digester (b) and R3 (c)
Figure 3.12 Laboratory set-up of EGSB reactor
Figure 3.13 Performance of EGSB reactor and properties of the effluent.
Figure 4.1 The pattern obtained from XRD analysis (a), Raman spectra (b), FTIR
image of the spent catalyst (c), SEM images of RGO-NZVI composite before (d) and
after (e) photocatalysis.
Figure 4.2 Changes in SCOD and DOC with respect to time (pH= 4, dosage= 0.2 g)
(a) and influence of initial pH of the solution (dosage= 0.2 g, time= 4 h) (b)
Figure 4.3 Effect of different catalyst dosage (a) and initial organic loading (b) on
solubilization
Figure 4.4 Cumulative volume of biogas produced from each digester (a) and daily
CH4 composition of biogas (b)
xii

Figure 4.5 Efficiency in removing SCOD (a) and dissolution of Fe
2+
during the
digestion period (b)
Figure 4.6 Concentration of VFA (as acetic acid) during the digestion period (a) and
non-linear fitting of experimental data against modified Gompertz model derived
data (b)
Figure 5.1 Physico-chemical characterization of PPy-CB-NZVI a) XRD pattern, b)
Raman Spectra, c) FTIR spectra, d), e) FESEM images at resolutions 30 µ and 3 µ
respectively and f) images of surface elemental mapping
Figure 5.2 Performance of anaerobic digesters during 31-day digestion a)
cumulative volume of biogas produced, b) efficiency in removing SCOD, c) CH4
composition in biogas
Figure 5.3 Trend of pH in the anaerobic digesters during the digestion period
Figure 5.4 Leaching of Fe
2+
into the liquid media (a) and VFA accumulation in the
digestors (b)
Figure 5.5 NH4
+
concentration during the digestion (a) non-linear fitting curve for
experimental and model data for methanogenesis (b) and cyclic voltammetry curve
of sludge with and without PPy-CB-NZVI (c)
Figure 6.1 FE-SEM images of (a) BSS, (b) PSS, (c) MIN and (d) MMPSS and EDX
analysis spectrum of (e) BSS and (f) MMPSS
Figure 6.2 Characteristics of MMPSS: PZC (a), BET adsorption-desorption (b),
VSM plot of MIN (c) and MMPSS (d)
Figure 6.3 XRD and FTIR spectra of BSS, PSS, MIN and MMPSS adsorbent (intact
and spent)
Figure 6.4 Variation in adsorption capacity of adsorbent with respect to pretreatment
temperatures (a), time (b), BSS to KOH ratios (c) and different MIN to PSS ratios (d)
xiii

Figure 6.5 Graphical comparison of predicted responses by design and experimental
responses of adsorption capacity for heavy metals, a) Cu
2+
, b) Cd
2+
and c) Pb
2+
Figure 6.6 3D-interaction effect plots of pH and time for adsorption
Figure 6.7 3D-interaction effect plots of initial concentration and time for adsorption
Figure 6.8 3D-interaction plots of time and dosage for adsorption
Figure 6.9 Adsorption capacity of regenerated adsorbent; (a) 0.1 M HCl as eluent
and (b) 0.1 M NaOH as eluent
Acronyms and abbreviations
a.u. Arbitrary unit
BMP Biomethane potential
BOD Biochemical oxygen demand
BSS Biogas slurry solids
CB Carbon black
xiv

CCD Central composite design
COD Chemical oxygen demand
CV Cyclic voltammetry
DI Deionized
DIET Direct interspecies electron transfer
EDC N-ethyl-N′-(3-(dimethylamino)propyl)carbodiimide
FE-SEM Field emission scanning electron microscopy
FTIR Fourier transform infrared
I/S Inoculum to substrate ratio
INP Iron nanoparticles
LED Light emitting diode
MIN Magnetic iron nanoparticles
MMPSS Magnetically modified PSS
NHS N-hydroxy succinimide
NZVI Nano zerovalent iron
OCV Open Circuit Voltage
OLR Organic loading rate
PAC Powdered activated carbon
PPy Polypyrrole
PSS Pretreated slurry solids
RGO Reduced graphene oxide
RSM Response surface methodology
SCOD Soluble COD
SEM Scanning electron microscopy
SMP Soluble metabolic product
UNEP United Nation’s Environmental Program
UV Ultra-violet
WV Working volume
xv

Units
cm Centimeter
h Hour
K Kelvin
M Molar
min Minute
mL Milliliter
xvi

mM Millimolar
mm Millimeter
mW Milliwatts
nm Nanometer
s Second
V Applied potential
xvii

Chapter 1
Introduction and Literature Review

Chapter 1: Introduction and literature review
“Water is life’s matter and matrix, mother and medium. There is no life without
water.”
- Albert Szent-Gyorgyi
1.1General aspects of water and water pollution
The origin of life on earth has been elucidated with several physicochemical theories of
prebiotic reactions. Most of those theories are based on carbon-water interactions. In
essence, life would have been impossible without water on earth. As we can see, water is
the most abundant chemical compound in living beings. It serves as the media and
solvent for cellular activities to maintain the cell shape, transport metabolites and provide
structural support for many biomolecules [1]. Despite its chemical perspectives, the role
of water in the ecosystem is enormous. The existence of different geography on earth and
the formation of several ecosystems in freshwater and marine habitats is influenced by
the hydrological cycle [2]. On earth, 71% of the surface is covered by water. Out of that,
97% is salty and freshwater accounts for less than 3%. However, a significant part of the
existing fresh water resources is not accessible to humans [3].
In recent years, the rate of contamination of water resources by various pollutants has
been on an increasing trend [4]. Events of pollution unfavorably affect the environment
by drastically reducing the dissolved oxygen concentration and imparting high BOD and
COD, toxic compounds and pathogens [5]. Although natural water resources have self-
purification strategies, such as dilution, sedimentation, aeration, redox reactions and
filtration, they might not be sufficient for remediation in severe pollution scenarios. As a
result, the population lacks clean water and consumes unhealthy and unhygienic water
[6]. According to UN reports, globally, 2.2 billion people lack access to safely managed
drinking water resources [7]. Water-related calamities contributed to about 74% of natural
disasters between 2001 and 2018 [8]. Polluted water consumption and exposure have
caused high toxicity leading to cancers, skin diseases, infertility, cholera, trachoma,
gastrointestinal illness and other somatic impacts. Extinction of aquatic species, reduction
2

Chapter 1: Introduction and literature review
in high-value fish stocks and destruction of natural habitats and wildlife are other effects
of wastewater discharge [9]. Reduced photosynthetic efficiency and bioaugmentation of
pollutants in the food chain, even at low concentrations, also are the aftermath of
pollution [10].
Water pollution happens due to the discharges from domestic, industrial, agricultural and
other commercial activities [11]. However, some natural releases of pollutants (e.g.,
weathering of rocks) also account for water contamination [12]. Therefore, the sources
and characteristics of pollutants should be identified appropriately to propose suitable
treatment strategies.
Baseline water stress
(withdrawals/available supply )
Low
Low to Medium (10-20%)
Medium to High (20-40%)
High (40-80%)
Extremely High (>80%)
Arid & Low Water use
a) b)
0
100
200
300
400
500
Total units
Wastewater
generation
N
u
m
b
e
r
o
f
u
n
i
t
s
0
50
100
150
200
W
a
s
t
e
w
a
t
e
r
v
o
l
u
m
e
(
M
L
D
)
Figure 1.1 Water stress in India (a) (World Resources Institute India, 2015), sector-specific
polluted water generation in India (b)
(http://www.sulabhenvis.nic.in/Database/STST_wastewater_2090.aspx)
Rapid urbanization and industrialization are the major sources of extensive wastewater
discharge and pollution. Due to such activities, underdeveloped and developing countries
have faced a persistent problem of potable water deficiency [13]. The impacts of water
3

Chapter 1: Introduction and literature review
stress are magnified further by the abstraction of fresh water for agricultural, industrial
and other commercial purposes [6]. Figures 1.1a and b give a glimpse of India’s water
stress statistics and industry-wise generation of effluents. India has a prominent position
among the developing countries as a growing economy. India’s water conservation action
plans started in 1985 and the National River Conservation Plans have set several goals to
preserve the quality of freshwater resources [14]. However, India’s potable water scenario
continues to persist despite having strict regulations for effluent discharges. Considering
all these, wastewater treatment options must be diversified with advanced techniques.
Sustainable development is the only solution for resolving environmental problems due
to developmental activities. Goal number 6 of the sustainable development goals (SDG 6)
emphasizes the importance of water sanitation and reclamation (Figure 1.2). According
to the UN, all commercial activities must embed the global sustainability agenda to
address environmental impacts. Here, the 3 ‘R’ concept serves to be an effective strategy
to achieve SDG. However, the high cost of waste management remains to be a hurdle for
industries.
4

Chapter 1: Introduction and literature review
Figure 1.2 Features of UN- Sustainable Development Goals No. 6
(https://fr.ezshinepad.com/working-on-un-sustainable-development-goal-6-with-
ezshine_n212)
Conventionally, screening, coagulation, sedimentation and activated sludge process
covers the primary and secondary treatment. However, advanced cleansing might be
essential for industrial effluents containing persistent chemical pollutants and pathogens
before discharging [15]. Many organic and inorganic molecules are removed by
biological treatment methods utilizing microorganisms and plants by either degradation
or phase transport. Similarly, physicochemical treatments immobilize the pollutants or
transform them into less-toxic compounds. The mode of such tertiary treatment depends
on the category of contaminant to be removed [16].
The industries releasing less biodegradable effluents, such as textile processing and cork
boiling, are characterized by the low BOD to COD ratio and may adopt physicochemical
treatment methods. However, wastewater from food, paper and pulp industries is rich in
organic content and is biodegradable [17]. Biodegradation can be divided into aerobic,
anaerobic and anoxic methods depending on the mode of respiration. Aerobic microbes
utilize O2 for respiration, whereas anaerobes are capable of electron transport using other
moieties such as CO2 [18]. Aerobic methods need high energy for the operation and are
affected by slight fluctuations in environmental conditions. Anaerobic degradation is
preferred because of the energy efficiency and biogas generation. Anaerobic digestion
could be considered an efficient technology for recovering renewable energy and
reducing the dependency on rapidly depleting fossil fuels [19]. This reduces greenhouse
gas emissions during fuel generation and consumption and creates a circular economy
[20,21]. In these processes, pollutant removal efficiency is highly influenced by chemical
or biochemical reactions between the reactants, microbes and the pollutant. The inter-
microbial electron transfer and redox reactions are critical in pollutant removal.
Introducing nanosized reactants into wastewater treatment systems has shown extreme
performance and the advancement in scientific inventions and accessibility to modern
techniques has found various applications for nanoparticles in waste management.
5

Chapter 1: Introduction and literature review
The content of this chapter conveys the necessity of this research and a comprehensive
literature review that led to the successful conduct of the work. This chapter details the
following; features of nanosystems and the importance of iron nanoparticles (INP), the
mechanistic prospects of INPs in anaerobic biological processes, the feasibility of Fe
composite formation with conductive carbon materials and polymers, INP in
photodegradation of organic pollutants, value addition of waste sludge by combining with
INP and its affinity for priority pollutants.
1.2Nanoparticles in wastewater treatment
The prefix ‘Nano’ is a Greek terminology denoting the word dwarf and it represents one
in 10
-9
. Nanosystems are relatively mature remediation methods over macro-sized
materials because of their physicochemical properties. This includes electron
confinement, electron tunneling, near-field optical effects, quantum entanglement and
ballistic transport [22]. Further, nanomaterials in environmental applications are
recommended due to their hindered resistance towards diffusion, high reactivity, large
surface area with active sites at edges, vacancies, and corners and even distribution in a
suspension by forming micelles [23–25]. Given the good prospects, different metallic and
non-metallic nanomaterials are widely used as photocatalysts, chemical precipitants,
electrocatalysts and biocatalysts. Nanoparticles of Ag, Fe, Zn, Fe3O4, TiO2, MgO, NiO
and CeO2 are effective in pollutant remediation [26,27]. They are characterized by
chemical properties to oxidize, precipitate, reduce, and adsorb the pollutant molecules.
Among the nanomaterials used, iron-based nanoparticles are widely used in industrial
applications due to their low cost and abundance. Iron-based nanoparticles show lower
toxicity to organisms than other metal nanoparticles and cause less secondary pollution
[28].
1.3Iron and its composites as enhancing additives
Iron is the most abundant metal on earth after aluminium. Due to the tremendous
advantages, iron nanoparticles (INPs) are extensively employed in conventional
wastewater treatment processes such as adsorption, catalysis, membrane processes and
biodegradation to achieve superior efficiency [29]. Various forms of INPs used in
6

Chapter 1: Introduction and literature review
wastewater applications include zerovalent iron, oxides of iron and iron-containing ores
and waste products (e.g., fly ash).
Nano zerovalent iron (NZVI): Elemental iron atoms with zero net charge is termed
zerovalent iron. They are peculiarly adopted in wastewater treatment applications due to
their remarkable optical, mechanical, magnetic, electronic and catalytic properties [30]. A
diverse range of compounds such as nitrate and nitroaromatic compounds, chlorinated
and other halogenated organic pollutants, radio-active molecules, phosphates, phenols
and organic dyes can be remediated by NZVI [28]. Hydrogen peroxide formation by
donating electrons toward oxygen molecules is advantageous in catalytic reactions [31].
Despite the positive impacts, NZVI may become hazardous when present in undesired
locations and quantities. Further, difficulty in solid separation, particle agglomeration,
storage difficulties and decline in reactivity due to oxidation are disadvantages of NZVI.
Approaches, such as encapsulation and emulsification, doping or impregnation with other
metal or non-metal ions and scaffold conjugation, are solutions for these troubles [32].
Nano iron oxides: Oxides of iron are primarily, magnetite (Fe3O4), goethite (α-FeOOH),
maghemite (γ-Fe2O3), hematite (α-Fe2O3) and wüstite (FeO). Nano iron oxides are widely
utilized in environmental applications due to their prodigious advantages such as simple
and fast synthesis, less difficulty in storage, high specific surface area, high functionality
and short intra-particle diffusion distance. Nano iron oxides can be compressed and used
as a packed bed with no significant reduction in surface area and their kinetics is faster.
Adsorption of heavy metals, textile dyes, pharmaceuticals and pesticides has been
facilitated by intra-particle diffusion and surface complexation. Here, π-π stacking
interaction and pore-filling effect were responsible for organic contaminant removal [33–
37]. Most iron oxides are available as fine powder and the use of iron oxide powder is
limited by the difficulty in separating the solids from the solution [38]. The slow
conversion of Fe
3+
to Fe
2+
and ferric oxide sludge formation may cause trouble during the
processes. The formation of heterogenous reactants such as iron sulfide (FeS) and
composites may somewhat resolve this drawback [31].
7

Chapter 1: Introduction and literature review
In situ trials have shown that iron immobilizes heavy metals and decreases the potential
leaching into the surrounding water bodies [39]. In a study, high adsorption of
tetracycline (286 mg g
-1
) was observed with magnetic modified biochar compared to the
unmodified biochar with 1 g L
-1
adsorbent dosage [37]. In conventional treatments, Fe
acted as a reactive medium in permeable reactive barriers for the better removal of
chlorinated substances from contaminated groundwater [40]. A study compared the
surface area of iron at different size scales. The specific surface area of Fe nanoparticles
was found to be 33.5 m
2
g
−1
, whereas that of granular Fe was 0.9 m
2
g
−1
[41]. Heavy
metals such as Cr and As were removed with adsorption capacities of 63 and 4.9 mg g
-1
,
respectively. Also, 92% of Cu, 98% of Pb, 96% of Ni and 93% of Zn ions were removed
by adsorption, incorporating INPs [42–46]. In a study, alizarin R yellow dye was
removed effectively by biosynthesized nano iron oxides by producing OH· in the
presence of solar irradiation [41]. In another research, γ-Fe2O3 nanoparticles were applied
to oxidize methylene blue and rose bengal dyes by OH· and O2
-
reactive species [47].
Many studies have tried out composites of iron to compensate for the difficulty of
incorporating iron particles alone. Composite formation sum-up the benefits of each
component, including their superior electronic and physicochemical properties. Fe3O4-
SiO2-AgCl, NZVI-RGO and biochar-Fe3O4 are significantly efficient composites for the
removal of methyl orange (90%), cadmium (76%) and (98%), respectively [46,48,49].
Iron-based composites control biological processes. In a study, Fe-sludge biochar acted as
growth support for Bacillus Sp. in a hybrid system to remove methylene blue [50]. Table
1.1 shows the applicability of iron and its composites for different applications in detail.
But, in a few studies, reduction in pore area, thereby low adsorption, has been reported
due to partial filling and blockage of active sites by magnetic nanoparticles [35].
1.4Nanomaterials in biological degradation applications
Considering the immense potential of INPs, there has been a remarkable rise in their
biological and biochemical applications. Due to their quantum effect, the systems
involving nanosized materials demand low activation energy for chemical reactions.
Biocatalysis is one of the popular applications of INPs and high performance has been
8

Chapter 1: Introduction and literature review
observed while treating organic and inorganic recalcitrant compounds. INPs can support
microbial growth (at 14-18 g NZVI kg
-1
soil) by electron supply, scavenging inhibitory
elements or providing surface modifiers as carbon source and cause inhibition by
oxidative stress and disrupting the biomolecules to create a specific antimicrobial
environment at concentrations (at >17 g NZVI kg
-1
soil) [51]. In bioremediation, oxide-
coated NZVI can remove pollutants by week forces, allowing easy sorbent regeneration
[52].
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9

Chapter 1: Introduction and literature review
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He et al. (2017) observed that Fe3O4/biochar nanocomposite acted multifunctionally as a
carrier for photosynthetic bacteria and supported nutrient removal. Fe was found at the
active sites of the nitrogenase and hydrogenase, thus promoting their activities. Also,
reducing equivalents, which serve as chemical energy sources for all oxidative and
fermentative systems, were scavenged. Thereby, they have proposed a desirable
alternative to the conventional treatment [62]. In a similar study, the synergy of bacterial
degradation and NZVI reduction accelerated the degradation of polybrominated diphenyl
ether-contaminated mangrove sediment and there was a 51.15% higher degradation [63].
However, the negative impacts of NZVI on indigenous microbes while treating
chloroaromatic molecules were also reported [51]. The dehalogenation of the
organochloride compounds and its existence as an additional sorbate were the possible
causes for inhibition at an NZVI dosage of 10 g kg
-1
soil.
The applicability of INPs under aerobic process conditions is limited due to the high
corrosion rate, releasing Fe
2+
, causing diminished reactivity and recyclability. In this
regard, INPs are more suitable under an anaerobic environment, where the redox and
release of Fe
2+
happen slowly and effectively [64]. Among the biological wastewater
degradation methods, anaerobic digestion systems are more appealing due to their low
energy demand and slow corrosion rate.
10

Chapter 1: Introduction and literature review
1.5Anaerobic digestion for wastewater treatment
Anaerobic digestion has been appraised as successful in treating high-strength wastewater
such as textile, starch, sugar and swine wastewater. The range of target substrates
includes wastes from energy crop production, food processing, oil industry, livestock
industry, distillery, pulp and paper industry, and domestic food wastes [65]. Anaerobic
methods facilitate the transformation of low-cost organic matter into gaseous fuel and
sludge with enriched functionality [66].
Generally, anaerobic treatments are carried out either by anaerobic sludge blanket
reactors, completely mixed anaerobic digesters, anaerobic lagoons, anaerobic filter
reactors, or strengthen circulation anaerobic reactors. The most popular sludge blanket
reactors are UASB, EGSB or baffled reactors. In EGSBs, wastewater is pumped into the
bottom of the bioreactor containing granular sludge and this upward flow keeps the
granular biomass in a fluidized state. EGSB can handle higher loads of organics
compared to UASB, since, the wastewater recirculation promotes biomass-substrate
contact. By this, the rate of conversion into biogas improves. Although the performance
of UASB reactors is remarkable in treating organic wastewater, its use is limited in
treating low-strength wastewater and psychrophilic environments. Slow kinetics and poor
mixing cause dead zones inside the column and are accountable for the ineffectiveness in
some cases. EGSB reactors have intensified hydraulic conditions and better biochemical
kinetics. The superior substrate-biomass contact could be attributed to better interior
mixing due to high recirculation and considerable height-to-diameter ratio. EGSBs are
versatile to handle a wide range of domestic and industrial organic wastewater with broad
pollutant strength values. Though suspended solids are partially removed, the soluble
micro-organic fraction can be alleviated effectively through EGSB treatment [67].
In research, an anaerobic membrane bioreactor treated lipid-rich dairy wastewater with an
organic loading rate of 4.7 g COD L
-1
d
-1
and an SRT of 40 days. To gain a COD removal
of >99% while operating continuously for 200 d. The system could bring the final COD
to 3.1 g L
-1
and the VFA concentrations in the effluent were 26 mg VFA-COD L
−1
[68]. In
another study, pulp and paper industry waste was co-digested with cow dung and
observed a CH4 production rate of 269 mL g
-1
VS with an initial load of 41.28 g L
-1
[69].
11

Chapter 1: Introduction and literature review
Substrate availability is a critical parameter while planning a continuous digester because
it may exist as the rate-limiting step in digestion. So, it is essential to ensure abundant
raw material availability throughout the year.
1.5.1 Dairy wastewater as a substrate for anaerobic digestion
India contributes about 22% towards global milk production, positioning it as the largest
milk producer in the world [70]. The quantity of wastewater generated could be as high
as ten times the milk processed in the industry [71]. Techniques such as microbial
degradation, photocatalysis, electro-coagulation, constructed wetlands, precipitation and
membrane techniques were applied and studied to treat dairy wastewater [72–74]. These
methods need high investment as installation, operation and maintenance are expensive,
require many chemicals and high energy consumption [66,75].
Dairy waste possesses a high potential to serve as a substrate for microbial metabolism
and growth due to its rich composition with proteins, fats, carbohydrates and other
organic stabilizers [74,76]. Inorganic trace nutrients such as potassium, sodium, calcium,
magnesium, iron, phosphate, nitrate, nitrite, ammonium, and sulfate are also available in
dairy waste with a favorable pH range [71]. Improperly managing these wastes may lead
to the uncontrolled evolution of intermediates and degradation products into the
environment. So, dairy wastewater could be chosen as a substrate for anaerobic digestion
with good nutritional composition to feed the microbes [77].
1.5.2 Biogas for sustainability
Biogas, a valuable byproduct of anaerobic digestion, is formed through sequential
microbial degradation of organic substrates under an anaerobic environment. Reports
state that the energy generation from biogas technology may drastically rise since it has
climatic benefits and efficient waste valorization [78]. According to the World Biogas
Association’s report, there was a 90% increase in global electricity production from
biogas in just six years, from 2010 to 2016 [79]. The gaseous fuel produced through
anaerobic digestion could be utilized for domestic fuel substitution in remote
geographical areas where delivery of grid energy is uneconomical [66,80]. Biogas
12

Chapter 1: Introduction and literature review
technology offers low-carbon fuel by stabilizing organic waste, thereby reducing the
emission of greenhouse gases (GHG) from waste disposal sources [80,81]. CH4 is a
potent GHG and a menace when present in the atmosphere, but it has a heat value of 50-
55.5 MJ kg
-1
to be used as a good fuel [82].
4H
2
+CO
2
→CH
4
+2H
2
O 1.1
CH4 is produced through many convoluted syntrophic microbial pathways in which the
hydrolysis of complex molecules such as proteins, carbohydrates and lipids has
dominated the initial phase. Eventually, acidogenic and acetogenic microbes consume
hydrolytic organisms' metabolites to produce acetate, CO2 and various electron carriers,
viz., formate and hydrogen [83]. Finally, methanogenic microbes transform these
molecules to produce CH4 (Eq. 1.1). Figure 1.3 schematically shows the fate of
substrates during anaerobic digestion.
C
O
C
R R
Hydrolysis
C
O
C
R R
H
+
OH
-
H2OCarbohydrates
Proteins
Fat
Soluble Sugars
Fatty acids
Amino acids
Intermediate
products
Acetic acid
H2& CO2
Acidogenesis
CH
4
CO
2
Acetogenesis
Methanogenesis
Figure 1.3 Stages and the fate of substrates during anaerobic digestion
The usual composition of biogas is as follows; 55-60% CH4, 40-45% CO2 with minor
volumes of hydrogen sulfide (H2S), hydrogen (H2), nitrogen (N2) and water vapor [84]. At
the same time, compressed biogas has more than 92% CH4. The composition of CH4 in
13

Chapter 1: Introduction and literature review
the biogas is a measure of the anaerobic system’s performance. It is influenced by the
electron transfer interaction between methanogens, active fermenting bacteria, and
diffusive electron carriers [85]. The direct and indirect inter-species electron transfer is
shown in Figure 1.4.
b)
H
+
H
2
Sp.1 Sp.2
CH
4
CO
2
e
-
Sp.1 Sp.2
e
-
e
-
e
-
CH
4
CO
2
a)
Figure 1.4 Indirect (a) and direct (b) electron transfer between species (Sp.) in an
anaerobic digestion system [18]
H
+
mediated electron transfer (MIET) has been appraised as the major responsible
microbial mechanism for CH4 production (hydrogenotrophic process). But, direct
interspecies electron transfer (DIET) is a phenomenon that helps to achieve good
thermodynamic behavior and faster microbial degradation kinetics during digestion [86].
For example, some methanogenic species, such as Methanosarcina barkeri,
Methanothrix harundinacea and Methanosarcina horonobensis, can attract electrons
from the coexisting species. While, Geobacter metallireducens act as donor. When the
electron mediators are limited, Methanosarcina mazei produces CH4 under such an
electro-methanogenic pathway [87]. However, unfavorable physicochemical conditions
such as low C/N ratio, extremely low or high temperature, lack of buffering, and presence
of toxic and recalcitrant compounds disrupt the syntrophy or weaken the interacting
potential between the participating bacterial groups. Ultimately, this results in inefficient
digestion and accumulation of VFA in the media [85].
14

Chapter 1: Introduction and literature review
Figure 1.5 Interspecies electron transport through conductive pili (a), cytochromes (b),
conductive additive (c and d) Reprinted (adapted) with permission from Feng et al.
(2023); Copyright (2022) Elsevier [88]
It has been suggested that a few methanogens are capable of extracellular electron
transfers. For instance, Methanosarcina barkeri can directly capture electrons from the
coexisting microbial cells of other species. Methanothrix harundinacea and
Methanosarcina horonobensis retrieve electrons from Geobacter metallireducens via
direct interspecies electron transfer (DIET). A representation of different possible electron
transfers has been exhibited in Figure 1.5. Recently, Methanobacterium, designated
strain YSL, has been found to grow via DIET in the co-culture with Geobacter
metallireducens. Methanosarcina acetivorans can perform anaerobic CH4 oxidation and
respiratory growth relying on Fe
3+
reduction through extracellular electron transfer.
Methanosarcina mazei is capable of electro-methanogenesis under conditions where
electron-transfer mediators like H2 or formate are limited. The membrane-bound
multiheme c-type cytochromes and electrically-conductive cellular appendages have been
assumed to mediate the extracellular electron transfer in bacteria like Geobacter and
15

Chapter 1: Introduction and literature review
Shewanella species. These molecules or structures are rare but have been recently
identified in a few methanogens [87]. The proliferation of DIET-supporting species
would be favorable while treating wastewaters with high organic strength. By enhancing
electron transport, metabolism increases along with high degradation and subsequent
biogas production [89].
There are several successful strategies to improve the performance of the digestion
system. Methods that focus on enhancing the solubility of substrates, pH buffering and
enriching the microbial population would benefit the efficiency of anaerobic degradation.
1.5.3 Strategies for enhanced digestion
The total heat value of biogas depends on CH4 composition [84]. Some modification of
the conventional digestion process indirectly reduces CO2 evolution by converting it into
CH4. The methods proposed for enhancing the rate of waste degradation and biogas
production include pretreatment such as acid-based hydrolysis during ensiling,
incorporation of an electrochemical system, manipulation of operation pressure,
improving H2 to CO2 ratio and CO2 enrichment by bubbling [23,93–96]. Corbellini et al.
(2021) showed that higher H2 partial pressure could positively influence CH4 enrichment
by reducing CO2 [92]. But, hydrogenotrophic enrichment needs continuous monitoring of
conditions to avoid acetate accumulation and achieve the desired efficiency.
Additionally, the rise of media pH due to bicarbonate consumption has also been reported
[94]. But, acetoclastic methanogenesis consumes acetic acid directly to form acetyl CoA
and then converts it into CH4 [95]. Adding foreign materials, pretreatment of substrates
and integrating physico-chemical processes have made remarkable alterations in
methanogenic pathways [89].
Similarly, stable granular biomass is a crucial factor in the performance of continuous
processes such as an EGSB reactor, which usually comprises a consortium of aerobic and
anaerobic species. Much of the start-up period of a reactor is dedicated to the stable
multi-cellular granule formation while feeding substrate at low strength [96]. At this stage
of operation, the removal efficiencies are comparatively less. Monitoring and control of
factors such as quality of inoculum, C/N ratio, temperature, pH buffering, etc., may
16

Chapter 1: Introduction and literature review
positively influence firm granulation [5]. However, several strategies are investigated to
shorten the granulation period and enrich the efficient species and population diversity.
The strategy to induce amino acid secretion results in faster aggregation and efficient
granulation. The addition of activated carbon, metal nanoparticles, calcium chloride,
sodium chloride and tannin effectively accelerated the granulation inside the EGSB
reactor [92,99,100]. The DOC removal from synthetic sewage upon adding 250 mg L
-1
CaCl2 was observed to be more than 75% in an EGSB, which was superior to the results
obtained in the presence of NaCl and tannin. The results of this study recommended its
applicability for better granulation while not affecting VFA consumption. In a similar
investigation, the addition of Mn octahedral molecular sieve nanoparticles (OMS-2)
assisted in better COD removal and biogas production by 4% and 11%, respectively, with
93.28% COD removal. They have observed that 0.025 g L
-1
OMS-2 could support
granulation and increase the quantities of acetogenic bacteria and archaea. The steady-
state biogas production rate from the continuous operation was 2.44 L L
-1
d
-1
[97]. The
advantages of attached growth processes are simplicity and minimal operational
difficulties. A polypropylene support media in a UASB reactor with a specific surface
area of 6700 m
2
m
-3
was an excellent strategy to get TOC removal up to 95.85% and
61.5 L d
-1
CH4 production at 10 h HRT [98]. They have studied the effect of different
TOC loading on CH4 production and TOC removal. Higher TOC concentrations caused
shock loads on the microbes, causing substrate inhibition and diminished performance.
T
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17

Chapter 1: Introduction and literature review
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r
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6
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5
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1
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8

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3
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;
6
1
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3

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g

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1

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1
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6

g

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a
s
h
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l
l
;

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5
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6

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1

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I
/
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r
a
t
i
o
0
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1

(
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±

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(
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l
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4

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−
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±

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V
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9
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H
4
6
8
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7
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1
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O
D

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e
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4
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H
4
4
4
6
.
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m
L

(
g
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S

r
e
m
o
v
a
l
)
-
1
8
7
%

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e
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A
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5
.
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±

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9

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O
D
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1
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3
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r
e

C
H
4
p
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n
t
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a
l
1
5
.
2
%

m
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r
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s
o
l
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d

d
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t
r
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c
t
i
o
n
6
6
8
.
7
9

L

C
H
4
(
g
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S
)
-
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1
5
.
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m
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d
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l

6
9
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%
6
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4
4

h
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g
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r

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4
y
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d
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d
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w
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-
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t
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A
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y
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r
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t
r
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t
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w
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h
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c
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M
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B
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2
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2

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s
l
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e
Similarly, a multi-chamber anaerobic reactor has been developed and studied the
anaerobic digestion of vegetable waste. The study showed that differing environmental
18

Chapter 1: Introduction and literature review
conditions can alter the microbial community beneficially and can adjust the
performance. Here, a drop-down in the dissolved oxygen concentration in the successive
chambers caused the variation in Proteobacteria, Bacteroidetes, Thermotogae,
Spirochaetes and Chloroflexi communities with dominance of Bacteroidetes in the
primary chamber [105]. In a study, high organic load waste digestion was modified by
adding waste seashells as an alkaline additive. Slat growth and coupled syntrophic acetate
oxidation with hydrogenotrophic methanogens were observed with good pH buffering
[104]. Pumice, a porous support material, was also found to be boosting methanogenesis
from poultry manure with 71.2% CH4 and 68.4% COD removal. A 6.2 g L
-1
pumice
dosage and 9.19% TS were observed to be optimum for the process [100]. Table 1.2
shows a few practical techniques to improve methanogenesis.
As mentioned in section 1.5.2, electron transport between participating species is an
essential process in anaerobic digestion, which determines the substrate degradation rate
and CH4 composition in the product gas. Usually, electron transfer between the electron
donors and acceptor cells happens through conductive pili formed on the microbial cells
in the biomass aggregates [106]. The process is faster between adjacent microbes and
ions. Many studies focused on improving the conductivity of the media by adding
conductive compounds such as INPs, biochar and polymers such as polyaniline
[111,112]. Reducing property of metal oxides helps release Fe
2+
ions and improve
electron transport by providing a highly conducting medium between the species [86].
Studies showed that the reducibility of molecules such as choline and cysteine benefit
methanogenesis by proliferating hydrolysis and homoacetogenesis [113,114]. Table 1.4
represents the effect of different conductive composites which had an impact on CH4
production.
T
a
b
l
e
R
e
f
[
1
1
1
]
[
1
1
2
]
[
1
1
3
]
[
1
1
4
]
[
1
0
7
]
[
1
1
5
]
[
1
1
6
]
[
9
5
]
[
1
0
8
]
[
1
1
7
]
[
1
1
8
]
19

Chapter 1: Introduction and literature review
1
.
3

T
h
e

p
e
r
f
o
r
m
a
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c
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f

d
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H
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;

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m
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4
;

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8
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e
m
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v
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l
;

7
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%

C
H
4
;
8
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%

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S

r
e
m
o
v
e
d
5
0
%
,

2
0
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m
o
r
e

C
H
4

&

C
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r
e
m
o
v
a
l
;

8
0
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m
o
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a
c
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d
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c
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t
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o
n
2
8
.
7
7
%

&

~
2
.
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%

m
o
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e

C
H
4

&
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r
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m
o
v
a
l
3
6
.
5
%

m
o
r
e

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H
4
2
5
.
0
%
,

1
9
.
5
%

&

2
9
.
1
%

m
o
r
e
C
H
4

y
i
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l
d

a
n
d

r
a
t
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3
3
.
4
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%

m
o
r
e

C
H
4

p
o
t
e
n
t
i
a
l
2
9
.
2
%

l
e
s
s

l
a
g

t
i
m
e
;

8
5
.
7
%

o
f
t
h
e

t
h
e
o
r
e
t
i
c
a
l

C
H
4

r
e
c
o
v
e
r
e
d
7
9
.
4
%
C
H
4

c
o
n
t
e
n
t
;

3
5
.
4
%

m
o
r
e
C
H
4
3
5
.
5
2
 ±
 2
.
7
2
%

m
o
r
e

C
H
4
E
f
f
e
c
t
/

m
e
c
h
a
n
i
s
m
M
o
r
e

s
p
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c
i
f
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c

a
n
d

a
d
a
p
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d

n
a
r
r
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w
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r

m
i
c
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b
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n
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e
;
h
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h

c
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e
n
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y
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4
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0

a
n
d

i
m
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v
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d

D
I
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I
n
c
r
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a
s
e
d

c
o
n
v
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r
s
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n

o
f

p
r
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p
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n
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c

a
c
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d

i
n
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a
c
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t
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c

a
c
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d
;
i
m
p
r
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d

t
h
e

e
l
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t
r
o
n

t
r
a
n
s
f
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r

c
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e
f
f
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n
t

a
n
d

S
M
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i
g
h

p
r
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p
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n
a
t
e

c
o
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v
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r
s
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n

a
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s
t
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t
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g
r
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w
t
h
o
f

m
e
t
h
a
n
o
g
e
n
s
6
4
.
7
4
%

m
o
r
e

M
e
t
h
a
n
o
s
a
e
t
a

a
n
d

a
c
c
e
l
e
r
a
t
e
d
V
F
A
;
p
r
o
v
i
d
e
d

a

m
i
c
r
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e
n
v
i
r
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n
m
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n
t

f
o
r

D
I
E
T
I
m
p
r
o
v
e
d

t
h
e

H
+

p
a
r
t
i
a
l

p
r
e
s
s
u
r
e

a
n
d

p
r
o
m
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t
e
d

D
I
E
T
;
e
n
r
i
c
h
e
d

t
h
e

F
e
3
+
r
e
d
u
c
e
r
s

a
n
d

h
y
d
r
o
g
e
n
o
t
r
o
p
h
s
2
5
%

i
n
c
r
e
a
s
e
d

n
u
m
b
e
r

o
f

c
y
t
o
c
h
r
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e

c
;

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y
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r
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t
a
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n
d

S
y
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p
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b
a
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t
e
r

i
n
c
r
e
a
s
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d

b
y
1
0
2
%

a
n
d
1
5
1
%
S
e
l
e
c
t
i
v
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y

e
n
r
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d

e
t
h
a
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c
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s
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m
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g

s
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r
a
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s
;
e
n
r
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c
h
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t

o
f

D
I
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T

m
i
c
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s
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n
c
r
e
a
s
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d

a
c
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d
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s

t
h
r
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h

D
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;

h
i
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p
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d
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d
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+

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t
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o
x
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b
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∆
G
.
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a
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f

c
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F
4
2
0
;

3
4
.
4
8
%

m
o
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a
b
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d
a
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c
e

o
f

M
e
t
h
a
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;

p
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C
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The changes in microbial metabolism highly depend on the diversity of the population
and the chemical form of the additive [119]. Among the studied conductive materials,
20

Chapter 1: Introduction and literature review
remarkable effects on methanogenesis were observed in the presence of metallic
nanoparticles such as Fe and Cu [120]. Research indicated that Fe-based nanoparticles
showed excellent performance as an additive which not only supported the growth of
microbes but assisted in DIET, too [121].
As mentioned, zerovalent iron (ZVI) is a low-cost, non-toxic, highly reductive substance.
ZVI has been employed in soil and sediment remediation utilizing its reducibility. ZVI
tends to corrode at high CO2 concentrations by reacting with H2CO3 and HCO3
-
[122]. In
anaerobic environments, nano ZVI (NZVI) is oxidized to ferrous iron, producing
hydrogen (Eq. 1.2) [127,128]. Similarly, NZVI helps to remove free oxygen, lethal for
obligate anaerobes and sulfide, which improves the gas quality by reducing H2S, as
shown in Fig 1.6. Formation of the Fe-phosphate complex further aids in reducing the
lethal effect on microbes at shock loads of bioavailable PO4
2-
-laden feed [125].
Fe
0
+2H
2O→Fe
2+¿+H
2
+2OH
−¿∆G
0
=−5.02
KJ
mol
Fe
0
¿
¿ 1.2

a) b)
Figure 1.6 General mechanism of ZVI (a) assisted reduction and abatement of sulfide
and phosphate (b) in the anaerobic digestion system. (DMRB: dissimilatory metal-
reducing bacteria) Reprinted (adapted) with permission from Ye et al. (2021); Copyright
(2020) Elsevier [126]
21

Chapter 1: Introduction and literature review
In a study, micron-sized ZVI improved the hydrolysis process and regulated the
acidification process during the anaerobic treatment of domestic wastewater. Further, ZVI
could control pH and ORP and caused a higher propionate conversion rate [127]. Lizama
et al. (2019) showed that adding NZVI. In another research, ZVI has been used as a
biocathode in a bio-electrochemical system. This methanogenic cathode under voltage
supply could improve CH4 production to 2.9 times higher with a dosage of 2 g L
-1
. They
have proposed that under voltage fluctuations, this cathode could act as an electron donor
to the methanogens [122].

Figure 1.7 clearly shows the transport of electrons from
acetogens to methanogens through both conductive pili and additive. The abundance and
fast transport of electrons pace-up the mechanism of CH4 production from CO2.
Similarly, more redox events before the methanogenesis phase, beginning from
hydrolysis, could accelerate the conversion of VFAs into acetate. The produced acetate
can participate directly in methanogenesis through Acetyl-CoA catalysis, bypassing the
CO2 pathway [128].
Even though NZVI can improve microbial metabolism, there were instances of its
toxicity at higher dosages. Researchers showed both biological and physical inhibition
effects of NZVI, causing a reduction in methanogenesis. A dosage of 1 g L
-1
could be
lethal to E coli strain exposed for a duration of 1 h [129]. Methanogens are affected by
high NZVI, resulting in a reduction of acetate kinase and coenzyme F420 expression.
Further, released PO4
3-
reacts with Fe
2+
causing clogging of internal mass transfer
channels and a low rate of VFA conversion leads to a substantial decline in
methanogenesis [130]. Also, INPs have a great tendency for aggregate formation due to
inter-particle magnetic dipolar interaction, London attractive and van der Waals forces.
Studies reported that INPs anchored to non-aggregating materials might help to improve
stability and reactivity [134,135].
22

Chapter 1: Introduction and literature review
Figure 1.7 Mechanism of DIET in the presence of conductive materials Reprinted
(adapted) with permission from [128]. Copyright 2018 American Chemical Society
1.5.4 Anchoring materials
The incorporation of non-aggregating anchoring materials is a better way to introduce
degradation-boosting additives into treatment systems. Table 1.5 illustrates the
effectiveness of different conductive composite materials studied under an anaerobic
environment to improve microbial metabolism. Carbon-based conducting additives are
gaining attention these days as they buffer the system by resisting reduction in pH,
facilitate attached electroactive biofilm formation, act as alternatives for e-pili or
cytochrome-c, boost protein degradation and reduce lag time for methanogenesis
[88,136,137]. As discussed, biochar derived from sawdust in the digestion system as a
redox mediator showed excellent microbial proliferation resulting in high CH4
generation. The media was highly enriched with electro-active Syntrophomonas and
Methanosarcina and experienced DIET-driven methanogenesis rather than a hydrogen-
23

Chapter 1: Introduction and literature review
based syntrophic pathway [108]. Similar results were found by wang et al. (2020), where,
Methanothermobacter and Methanosaeta were the most enriched species and biochar
produced at 1003 K showed the best performance. Further, thermophilic digestion
seemed effective with 10 g L
-1
of biochar-amended anaerobic system. They have also
proposed that the redox-active metals in biochar may ease electron transfer [85]. The
methanation rate in a self-fluidized GAC reactor was 0.77 ± 0.02 g CH4-COD (g influent
COD)
-1
more at an organic loading rate of 1500 g COD m
-3
d
-1
and a temperature of 293
K. Promotion of DIET in the reactor was explained with the high concentrations of
medium-chain acyl-homoserine lactones, which is an indicator of the syntrophic
interactions between bacteria and archaea [135]. But, the additives with settling property
limits the substrate-particle contact inside the column reactors. In a study, activated
carbon-supported NZVI acted as a combination of multiple tiny micro-batteries for
phenol degradation [131].
Another conductive material, graphene, had significantly improved the rate of CH4
production up to 51.4% at a dosage as low as 30 mg L
-1
. The shifting of other pathways to
acetogenic methanogenesis and enriched Geobacter community were said to be
responsible for high product yield. But, the evidence for no electron shuttle by graphene
implies that DIET might not have been prominent in this case. Likewise, at low digestion
temperatures, graphene could inhibit digestion [136]. In a study, an anaerobic microbial
electrolysis cell used graphene's high surface area and electron mobility to stimulate
species diversification. Graphene’s influence on microbial communities brought more
ammonia-tolerant methanogen, Methanoculleus, into the system [111]. However, reports
stated the more positive effects of oxidized graphene (RGO) by causing changes in
dominant species in the media and increased production of extracellular polymeric
compounds. Unlike graphene, the addition of RGO has given some evidence for the
occurrence of DIET [137].
24

Chapter 1: Introduction and literature review
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25

Chapter 1: Introduction and literature review
RGO is a basal plane-structured organized carbon allotrope formed by reducing and
removing sp
3
carbon from graphene oxide. Its high conductivity (>15000 S m
-1
) and
superior properties are favored in applications such as battery and supercapacitors,
biomedical and environmental pollution sensors, graphene electronics and environmental
remediation. RGO is characterized by high catalytic activity and adsorption capacity
[143]. RGO-assisted anaerobic digestion exhibited immense potential by raising CH4
production by 65%. The syntrophic relation between hydrogenotrophic, Methanoculleus
and acetate oxidizing bacteria was established by adding RGO into the system [137]. The
application of conductive composites is a way of synergizing the advantages of two or
more materials to bring out more beneficial effects than a compound alone. In a research,
the inhibition caused by adding sharp RGO nanosheets was reduced using a magnetite-
RGO composite and ensued in superoxide anion-independent oxidation [132]. However,
in most studies, though more biogas was produced, the CH4 composition was not
substantially improved. So, the feasibility of such composite material needs to be
evaluated with proper optimization of digestion conditions to implement in continuous
digestion processes.
1.5.5 Polymers in anaerobic digestion
In biological processes, non-aggregated single-cell microorganisms have higher specific
productivity than attached or floating cell aggregates. Though yield is superior for non-
aggregated microbes, lack of granulation may result in biomass loss. The digester system
requires an additional solid separation unit to avoid the escape of biomass [144].
However, some enhancer materials can accelerate the production of extracellular
substances by boosting microbial metabolism and subsequently improving cell
granulation [145]. In that respect, granulation must be considered a critical parameter in
continuous-flow anaerobic reactors. The granules are composed of an outer aerobic shell
surrounding an inner anaerobic consortium. Liang et al. (2020) summarized the effect of
natural and synthetic polymers in the aggregate formation of anaerobic bacteria. The
report listed several compounds, such as chitosan, reetha extract and percol, which could
promote granulation, but have no direct influence on methanogenesis [146]. However,
conducting polymers influenced the digestion process in multi-dimension.
26

Chapter 1: Introduction and literature review
Polypyrrole (PPy) is a conductive polymer of synthetic nature with a conductivity of up
to 220 S cm
-1
, which could enhance electron transport and aggregate formation [147]. In a
study, 0.3 g L
-1
of PPy addition improved the CH4 production from waste-activated
sludge by 27.83%. During the initial stages, acidogenesis was enhanced by up to 18.40%
in the presence of PPy and the abundance of Firmicutes and Patescibacteria communities
was enriched. The high CH4 yield was assigned to DIET, while H
+
utilization for the
electron transfer was diminished [95]. Figure 1.8 represents the mechanism of PPy aid in
DIET. Another study reported the effect of Fe-PPy composite in the digestion of okra
waste. However, the composite was inefficient, with only a 2.7% increase in CH4.
Although the methanogenesis exhibited a boost in the presence of PPy, its action on
disintegration and hydrolysis was insignificant. Moreover, the investigation did not give
any insight into changes in the digestion mechanism or long-term exposure effects of PPy
[148,149]. In this regard, PPy combined with NZVI, which can promote hydrolysis and
methanogenesis, might be revolutionary for faster production of enriched biogas.
Ternary composites are gaining attention to synergize each component’s functional
properties to mediate physicochemical and biological processes [72]. Carbon black is a
highly conducting, abundantly available catalytic compound with minimal overpotential
and efficiency in enhancing anaerobic digestion. In a study, CB-carbon felt and Ni-Co-
CB-carbon felt could improve the CH4 production from an integrated AD-MEC with 0.30
and 0.34 m
3
CH4 kg COD
-1
yield, respectively. The CB dosage for the electrode
preparation was 0.04 g to obtain a maximum SCOD removal of 87% [150]. So, the
nanocomposite made from CB, PPy and NZVI, all of which possess peculiar roles in
enhancing anaerobic digestion, could be the subject of a study to understand the
mechanism and applicability. There are no reports of a ternary nanocomposite made from
PPy, CB and NZVI tested for improving AD.
27

Chapter 1: Introduction and literature review
Figure 1.8 Proposed mechanism of DIET with the assistance of polypyrrole. Reprinted
(adapted) with permission from Qian et al. (2022); Copyright (2022) Elsevier [95].
1.5.6 Pretreatment for high disintegration and solubility
Biodegradability highly influences the BMP of a particular biomass substrate.
Degradability is generally coined to determine the economics and efficiency of a process.
The substrate composed of large chain complex organics is less degradable compared to
the one with more of simpler organic molecules. As mentioned, the poorly soluble and
less biodegradable fat and lipid content in dairy wastewater contributes significantly to
the total hydrocarbons and has good BMP [79]. But, a layer of fat may cause clogging
and floatation, act as a recalcitrant barrier between microbes and other substrates and
reduce the mass transfer efficiency [76,151]. Decelerated mass transfer diminishes
hydrolysis, a major rate-limiting step in methanogenesis [152].
28

Chapter 1: Introduction and literature review
T
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29

Chapter 1: Introduction and literature review
Many physicochemical and other pretreatment approaches have been tried and succeeded
in accelerating the hydrolysis step. Pretreatment of substrates before anaerobic
degradation helps disrupt the recalcitrant linkages of complex compounds to form
simpler molecules, thus increasing biodegradability [161]. Ultrasound treatment, lipase
hydrolysis for difficult-to-degrade wastewater, application of garbage enzymes, and
thermal and chemical coagulation treatments are proven methods to improve the
efficiency of biogas production [152,158,159,162]. Researchers showed that the
pretreatment inactivated the resistive genes of pathogenic microbes and enhanced the
concentration of proton donors rather than just improving the solubility and
biodegradability [162]. In a study, peroxide oxidation of excess municipal sludge showed
better solid disintegration and benefitted in anaerobic digestion; however, the cost of
operation was not suitable to implement in the field. The wet sludge techniques are a
better way to achieve desirable disintegration efficiency [103]. Including these enhancing
mechanisms in AD results in the acceleration of hydrolysis and acidogenesis; hence, the
lag time for methanogenesis is reduced, resulting in a high biogas yield from the process
[156]. Table 1.5 details high-rate anaerobic digestion achieved by various pretreatment
techniques.
In a study, photocatalysis facilitated the rapid mineralization of certain pharmaceutical
compounds and nitrogen-containing organics compared to biological methods [163,164].
However, in many cases, the generation of toxic byproducts, high cost and dosage
requirements limit the applicability of catalysis [165–167]. A combination of
photocatalysis and biological degradation may be beneficial compared to the efficiency
and drawbacks of employing these de-pollution methods individually, such as incomplete
removal in biological processes and toxic product evolution in photodegradation
[168,169]. Table 1.6 gives the details of combined photocatalysis and biological
degradation for the treatment of different types of wastewater. The choice of a
photocatalyst depends on the energy levels of the conductive and valence bands, which
impacts the total energy required for pollutant degradation [170]. The nanostructured
metal oxides as catalysts hold a large active surface area, favorable band gap and good
thermal and chemical stability [27]. In a study, NZVI enhanced the photocatalytic activity
of TiO2 for the degradation of Cr
6+
under UV irradiation [171].
30

Chapter 1: Introduction and literature review
Also, the properties of RGO, such as
absorption under visible light, ability to
stimulate OH· and faster electron
transport, were beneficial for its use in
the photodegradation of organic
compounds [175,176]. The effectiveness
of both these catalysts was employed in
the sono-catalytic degradation of
nonylphenol and observed high
reusability of the catalyst [177].
Furthermore, previous research showed
that magnetic RGO composite could
enhance microbial activity to produce
biogas [35]. However, the RGO-NZVI
combined catalyst has not been tried for
dairy waste treatment. Moreover, the
effect of the spent catalyst after
photocatalytic pretreatment on
anaerobic digestion may differ from that
in the presence of fresh additives. So,
there is immense scope for an integrated
system where both processes benefit
from the same catalyst.
31
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2

Chapter 1: Introduction and literature review
1.5.7 The fate of biogas intermediates and end products
Anaerobic systems transform biomass into energy, intermediary compounds and simple
molecules. While the untreated organic substrates lead to deterioration of environmental
quality, the end products and intermediates formed in the anaerobic process can be
extracted and commercially utilized. Digested sludge from biogas production is a rich
source of nutrients and essential growth elements commercially used as a soil fertilizer.
The applications of digestate can be broadened by further research. Aerobic and
anaerobic biological sludge materials are characterized by abundant macromolecular
biopolymers. It is a complex mixture of proteins, polysaccharides, nucleic acids, humic-
like substances, uronic acids, and lipids, which imparts functionality to the sludge solids
with carboxyl, hydroxyl, amine and phosphoric groups. Many studies explored the
efficiency of processed and raw biological sludge in water and wastewater purification.
The low-cost and eco-friendly sludge material is a highly functional candidate for
wastewater treatment by adsorption [178].
1.6Adsorption of heavy metals using processed sludge
Discharges from industries such as electroplating, manufacture of batteries, mining,
tanneries, steel and paint production, contain heavy metal ions, Cu
2+
, Cd
2+
and Pb
2+
[42,179–181]. Pb
2+
and Cd
2+
are included in the ‘big three’ category by Gautam et al.,
2014 [13]. The class A permissible limits of these ions are 1.5 mg L
-1
, 10 µg L
-1
and 0.1
mg L
-1
for Cu
2+
, Cd
2+
and Pb
2+
, respectively, as per Indian surface water quality standards
(IS: 2296). When found as a part of the food chain, these ions cause a censorious
situation in the ecosystem [12]. Many health effects were reported, such as neurological
maladies, impaired hepatic function, and nephrotoxicity for metals Pb
2+
, Cu
2+
and Cd
2+
,
respectively [9,183–186]. The severity of the effects depends upon the concentration and
duration of exposure [181]. On these grounds, eliminating these elements has to be kept
on a priority basis [187].
There are many methods, including membrane techniques, ion exchange and chemical
precipitation, for removing heavy metals [188,189]. Implementation of these methods for
treating low concentrations causes high costs of operation [179]. Adsorption is an
32

Chapter 1: Introduction and literature review
economical way of treating heavy metal-contaminated water among the widely utilized
methods [190]. Adsorption is a versatile method because it allows the selection of
suitable adsorbents according to the type of contaminant to be removed, environmental
conditions, financial considerations, the scale of operation and the availability of raw
materials. The functional groups participate in the complexation during adsorption and
remove the pollutant molecules. The greater the abundance of functional moieties, the
higher the adsorption capacity. The simplicity of operation, high efficiency and the
minimum generation of waste sludge make it a more attractive method for heavy metal
remediation [11,191–193].
Finding alternatives for expensive precursors used in large-scale syntheses of commercial
adsorbents has been one of the major subjects of research [194]. The modification of
sludge solids enhances the binding of heavy metals. Sewage-activated sludge, dried
waste-activated sludge, aerobic digested activated sludge, alkali-modified sewage sludge,
flocculent sludge and aerobic granular sludge are good candidates for the development of
adsorbents with sufficient capacity to meet environmental compliance [34]. These
materials are economically feasible for the redemption of pollutants because of higher
surface area, ease of regeneration and plenty of chelating functional groups [11,190].
Studies showed that the presence of biopolymers and extracellular polymeric substances
due to microbial activity is beneficial for the adsorption onto the biosorbents made from
activated sludge. These heterogeneous biosorbents have enough functional groups, such
as –NH2, –COOH, etc., to interact with metal ions by electrostatic force, complex
formation and ionic exchange [195,196].
Further, negatively charged phosphoric amine and amido-cyanogen of proteins,
polysaccharides and phospholipids can also enhance complex formation with heavy
metals. Researchers have observed that nitrogen in amino-sugars and oxygen in hydroxyl
and carboxyl were the primary electron donor atoms, which were prone to preferentially
bind with soft metal cations of strong covalent characteristics and then form inner-sphere
complexes [196]. Several methods can improve this redox, including thermal,
hydrothermal, and physicochemical processes. Acid and alkali treatments imparted
COOH
-
and OH
-
functionalities on the adsorbent surface and assisted in the formation of
33

Chapter 1: Introduction and literature review
stable complexes under a neutral pH environment. Organometal complexes are formed by
this mechanism [196].
A modified activated sludge immobilized by polyvinylalcohol-carboxymethylcellulose
sodium salt adsorbent was prepared by Ramteke et al. (2016) for the removal of Cu
2+
and
Cr
6+
metals with 1 g L
-1
adsorbent loading. A maximum adsorption capacity of 752.13 mg
g
-1
was obtained with this adsorbent [178]. But, the efficiency reported in this work was
contributed by the presence of highly functional carboxymethyl cellulose. In another
study, raw biogas residual solids were used to remove Pb
2+
and achieved a capacity of 28
mg g
-1
. Later, this adsorbent was used for Cr
3+
removal with 85% efficiency at 4 g L
-1
concentration [197]. Formation of composites with magnetic nanoparticles such as INPs
and Ni has been observed to be better adsorbents with easy solids separation and reduces
mass loss. Their suitability as adsorbent for various pollutants has been explored in a few
studies. Maderova et al. (2016) investigated the efficiency of magnetically modified
activated sludge for removing aniline blue and other dyes to get a maximum of 768.2 mg
g
-1
adsorption capacity. They observed that both Sips isotherm and Langmuir isotherm
model fit the experimental space for the studied dyes, while kinetics followed the pseudo
second order model [34]. An ultra-high surface area carbon adsorbent was made from
activated sludge by alkali treatment for the adsorption of tetracycline. Here, the
adsorption process followed pseudo-second-order kinetic and the Langmuir model. The
adsorbent-adsorbate interaction was explained by H
+
bonding and π-π stacking interaction
and interfacial diffusion appeared to be the primary rate-control step in the adsorption
process. Here, alkaline treatment was carried out before pyrolysis to extract the
biopolymers in the sludge, improving the produced adsorbent characteristics [198]. Such
thermal treatment of sludge materials prepares the solids for selective as well as non-
selective adsorption of pollutants. Researchers explored this fact and showed in a study
that pyrolyzed sludge obtained from the pulp and paper industry’s treatment plant was a
good soil conditioner [199].
Biogas slurry solids (BSS) could be developed as a potential adsorbent since they possess
hydroxyl (OH
-
), ammonium (NH4
+
) and thiol (SH
-
) groups due to enzymatic hydrolysis
by anaerobic microbes with good surface properties [178].

The mechanism of adsorption
34

Chapter 1: Introduction and literature review
onto BSS detailing the interaction of different parameters is yet to be explored. Also,
there is no evidence of research stating the effectiveness of modified BSS for adsorption.
Reports indicated that alkali-thermal treated adsorbents had better adsorption capacity
owing to their improved surface properties [200]. The surface area of materials increases
when particle size reduces; thus, using nano-sorbents in environmental applications is
recommended due to high surface area and hindered resistance towards diffusion [24,25].
Fe3O4 nanoparticles are ideal for composite synthesis because of their high saturation
magnetization, easy phase separation under a magnetic field, proven efficiency in
sequestering heavy metals and easy synthesis from iron scrap [42,201,202]. However,
any nanocomposite made with BSS has not been reported for adsorbing heavy metals. So,
process optimization should be carried out to understand the favorable environmental
conditions for metal ion removal.
1.6.1 RSM method of optimization of the adsorption
The interaction of different environmental parameters affects the proper conduction of the
chemical process and thereby, the results. There are models which explain the mechanism
of adsorption chemically. Nevertheless, the environmental conditions are equally
important to predict the performance and scaling up the process. The efficiency of a
process could be amplified by finding the most influencing operational parameter and
interaction. The incorporation of a statistical model has succeeded in predicting the
simultaneous influence of multiple parameters on adsorption efficiency, which is
otherwise optimization [203]. The classical tool of optimization considering randomly
chosen environmental conditions does not contribute to the success of finding mutual
influences on efficiency [204]. Response surface methodology (RSM) is a robust method
that deduces an empirical model that fits the experimental data by comparing statistical
variables [205]. The main objective of RSM is to optimize the adsorption process to
ensure that the pollutant molecules utilize the maximum adsorbent surface in the reaction.
By this, the minimum cost of the process could be anticipated during scale-up. The
preliminary study refines the influencing factors and thus helps to accurately simulate the
process through the developed RSM model [206,207]. In research, the multivariate
statistical model gave compatible mathematical relations of independent variables for the
35

Chapter 1: Introduction and literature review
process studied [208]. These models compare multiple dependent and independent factors
at different levels rather than keeping only a single varying factor and other factors as
constants [205].
1.7Research gap
Many researchers emphasized the improvement of wastewater treatment driven by the
need to enhance remediation efficiency and reduce cost. In this regard, the ever-
expanding scope of binary and ternary hybrid nanosystems can be employed for
enhanced environmental remediation. INPs have abundancy as well as efficiency to
intensify the processes. Although the efficiency of NZVI in the anaerobic process has
seen advantages, there were difficulties in retainability. Composite with anchoring
material such as biochar and activated carbon have been reported. Although the gas
composition was improved, a very high dosage of these composites was required for
treating moderate-strength wastewater. So, effort should be taken to reduce the material
dosage. Also, some studies have focused on increased biogas volume, but CH4
composition remains unchanged even in the presence of conductive composites. Also, the
exact phase where these conductive materials assist in digestion is unclear. As per reports,
few composites act from the hydrolysis stage. However, some other materials act only as
DIET enhancers. Research has ascertained DIET as the only responsible phenomenon for
enhanced methanogenesis. This understudied action of conductive additives should be
emphasized in further analysis. Similarly, Geobacter species have been recognized to be
active DIET contributors. However, the knowledge of other DIET proliferating
microorganisms might help in developing active inoculums useful as efficient seed
material in the large-scale anaerobic treatment of dairy wastewater.
The choice of components in the composites is a prime factor in altering the mechanisms.
Until now, there have been almost no reports regarding the application of NZVI
combined with RGO or conductive polymers on anaerobic digestion. The electrical
properties of such composites can be highly superior to other carbon additives. RGO can
efficiently diminish electron recombination, which may affect the DIET during digestion.
Likewise, in the presence of additives, the hydrogenotrophic pathway can be partially
shifted to acetoclastic, reducing the accumulation of unutilized VFA. The pH elevation
36

Chapter 1: Introduction and literature review
due to bicarbonate consumption can be reduced by doing so. Since the range of
applicability of each component in the composite is different, the effect of composite
synthesized at different ratios of NZVI to RGO might be dissimilar. Owing to those
expectedly different results with varying operational conditions, the investigation of
microbial metabolism that supports DIET is necessary. Also, a trial in the presence of
polymer additives such as PPy combined with CB and NZVI is missing in the literature.
A detailed investigation of the system with polymer conductive material associated with
NZVI could establish a new domain for future studies as well.
After studying the effect of RGO-NZVI, one might see that NZVI and RGO have good
catalytic properties. Since the biodegradability of dairy wastewater can be improved by
preprocessing by enhancing the concentration of simpler organic compounds, the
feasibility of the RGO-NZVI catalyst may be tested for photocatalytic pretreatment
before the anaerobic process. Although pretreatments have been reported, the evidence of
the same reactants supporting both catalysis and the biological process has not been
reported.
Cessation of anaerobic treatment leaves the slurry solids behind. There has been little
evidence of studies with an adsorbent developed from biogas slurry solids in the
literature. Considering their good surface functionality, pretreated biogas sludge materials
combined with iron nanoparticles may have superior adsorption capacity. A combination
of magnetic nanoparticle-impregnated adsorbent matrix may show higher separability
and porosity to diffuse. The conduct of this study is essential for the design and
implementation of a treatment system with the prepared adsorbent in actual cases.
1.8Objectives
•To synthesize a conductive composite using NZVI and RGO and study its effect on
anaerobic digestion of dairy wastewater with varying operating parameters such as
organic loading, the dosage of conductive additive, the ratio of RGO to NZVI and the
initial pH of the media.
•To study the effects of the RGO-NZVI composite in a continuous digestion process
by incorporating the composite into an EGSB reactor treating dairy wastewater.
37

Chapter 1: Introduction and literature review
•To evaluate the digestion performance in the presence of PPy-CB-NZVI ternary
composite at different dosages.
•Photocatalytic pretreatment of dairy wastewater using RGO-NZVI catalyst and the
optimization of conditions such as initial pH, OLR, catalyst dosage and pretreatment
time.
–To study the effect of the spent photocatalyst (RGO-NZVI) to boost CH4
from dairy wastewater.
•To develop a magnetic adsorbent from pretreated biogas digestate and Fe3O4 to
remove heavy metals from aqueous media and to optimize batch adsorption
conditions by response surface methodology.
1.9Outline of the Thesis
Chapter 1 of the thesis is an introduction to the research topic and a comprehensive
literature review related to the research work. The materials and methodology of the
research have been included in Chapter 2. Chapter 3 comprises the results obtained
from the batch and experimental study of anaerobic digestion incorporating RGO-NZVI
and the discussion. The inferences from the pretreatment of dairy wastewater and
subsequent anaerobic digestion have been presented in Chapter 4. Chapter 5 is on the
efficiency of PPy-NZVI-assisted anaerobic digestion. The optimization of pretreatment
and operational parameters of adsorption are discussed in Chapter 6. Chapter 7
summarizes and concludes this study, listing major outcomes and future perspectives. The
last section is the list of references assisted in conducting this research work and
interpreting results.
38

Chapter 1: Introduction and literature review
Schematic representation of objectives
(+ Spent catalyst)
Iron
nanoparticles
NZVI Magnetite
Compositepreparation
CB-Ppy-NZVIRGO-NZVI
Anaerobic digestion of
dairy wastewater
Photodegradative
pretreatment
Magnetic biogas slurry
solid adsorbent
Heavy metal removal
Optimization
(Optimization by RSM)
39

Chapter 2
Materials and Methods

Chapter 2: Matreials and Methods
2.1Chemicals and substrates
All the chemicals used for the studies were of analytical grade and were used without
further purification unless mentioned. The organic coated NZVI (Nanofer 25DS) was
purchased from Nanoiron, Czech Republic and stored at 277 K in an oxygen-free
environment to retain stability. RGO was purchased from Techinstro (India) and used
after removing any impurities by acid treatment. EDC, NHS, (NH4)2S2O8, FeCl3, KI and
polypyrrole (20% by weight) doped carbon black (PPy-CB) with 30 mS conductivity
were purchased from Sigma Aldrich. Glucose, urea, NH4Cl, Na2HPO4.2H2O, KH2PO4,
MgSO4·7H2O, FeSO4.7H2O, MnSO4.H2O, CaCl2.H2O, NaHCO3, NaBH4, 25% NH4OH,
ethanol, HCl and NaOH were obtained from Himedia (India). KOH, glutaraldehyde
(25%), CuSO4, Pb(NO3)2 and CdCl2 were obtained from Thermo Fisher Scientific. Milk
powder (Amul, India) and edible yeast were purchased locally. Fresh cow dung was
obtained from a local cattle farm (Rourkela, India). BSS was collected from a local pilot-
scale biogas plant (Rourkela, India) having 1 m
3
capacity loaded with 30% Spent Tea
Waste and 70% Cow Manure. The pH adjustments were done with either 0.1M NaOH or
0.1M HCl.
2.2Characteristics of wastewater and degradation parameters
All the pH adjustments were made with the help of a pH meter (Systronics). The
degradation of dairy wastewater was evaluated based on the measured water quality
parameters. The pH and conductivity of the liquid samples collected from the digesters
were measured immediately after sampling using probe electrodes (EI instruments,
India). Biogas volume was recorded by the equivalent displacement of water saturated
with NaCl. The composition of biogas in terms of CH4 volume was measured using a
biogas analyzer (MM Automation, India). The parameters SCOD, NH4
+
, Fe
2+
and VFA
were measured after filtering the samples with 0.45 µ syringe filters and diluted
appropriately for each analysis. The triplicates of results were compared by analyses of
variance (ANOVA) and determined the statistical significance of each set of values.
The initial properties of the dairy wastewater, cow dung, methanogenic seed and feed
slurry were determined according to the standard procedures (APHA 2000a) [209].
41

Chapter 2: Materials and Methods
2.2.1 SCOD measurement of samples
SCOD was measured by dichromate method using a COD digester and analyzer (Hanna
Instruments, COD MR (16)) adopting US EPA 410.4 method. Briefly, 2 mL of diluted
sample was added carefully through the sides into the medium range (150-1500 mg L
-1
)
vials (Hanna instruments). The vials were then closed tightly and shaken well to mix the
contents properly. These vials were kept in the preheated digester (423 K) and digested
for 2 h. After the digestion, the vials were allowed to cool to room temperature and the
COD value measured from the multi-parameter photometer COD analyzer.
2.2.2 Determination of Fe
2+
1 mL hydroxylamine hydrochloride reagent and 5 mL of 1, 10-phenanthroline were added
to the 10 mL sample. This solution was buffered by adding 8 mL of acetic acid buffer.
After complete color development, the solution is diluted to 100 mL and mixed well.
Later, the absorbance was measured at 510 nm using a spectrophotometer. Fe
2+
concentration was obtained from the calibration curve (0-2 mg L
-1
).
2.2.3 Spectrophotometric analysis of ammonia
The sample was taken in a 10 mL volumetric flask and 500 μL of Nessler’s reagent was
added. The mixture was shaken well to develop a yellowish color. The absorbance of the
solution was recorded at 425 nm wavelength in a spectrophotometer. The calibration
curve was constructed as follows, the standard solutions of ammonium ion were prepared
in a range of 5-25 µg mL
-1
with NH4Cl. NH4Cl was dried in a hot air oven for 20 min at
378 K. The concentration of ammonia in collected samples was calculated using the
absorbance of the samples and the line equation of the calibration curve [210].
2.2.4 Measurement of VFA accumulation
The total VFA accumulation was measured spectrophotometrically following the
Montgomery method with slight modifications given by Siedlecka et al. (2008) [211].
Briefly, 1.5 mL ethylene glycol reagent and 0.2 mL of H2SO4 were added to 0.5 mL
sample and heated for 3 min. After cooling immediately, 0.5 mL of 10% hydroxylamine
hydrochloride, 10 mL of 10% ferric chloride solution and 2 mL of 4.5 N NaOH solution
42

Chapter 2: Materials and Methods
were added. After stabilizing, the absorbance was measured at 495 nm. Further, the
concentration of different organic acids, which constituted total VFA, was determined by
HPLC (ZORBAX 300Extend-C18, Agilent, USA) [212].
2.2.5 Determination of cellulose
Cellulose in the samples was measured by the Updegraff method. For this, centrifuge
tubes in triplicate were set up with 0.5 mL of samples and 3 mL of a mixture of acetic
acid/water/nitric acid (150 mL 80% acetic acid, 15 mL conc. nitric acid) reagent. This
mixture was heated under boiling for 30 min. Later, the tubes were cooled and
centrifuged at 2,500g for 3 min and the pellet was thoroughly dispersed in 5 mL of water.
It was then centrifuged and the supernatant was discarded. The centrifugation was
repeated twice. Into the pellet, 10 mL of 67% sulfuric acid was added and then incubated
for 1 h with intermittent vortexing (every 5–10 min). After cooling, the clear solution was
diluted to 10 mL with deionized water. The sample aliquots were diluted again 50 times
and 1 mL of ice-cold anthrone reagent (0.2% anthrone in conc. sulfuric acid) was added.
The mixture was heated for 15 min in a boiling water bath, cooled and absorbance was
measured at 620 nm against a reagent blank in a spectrophotometer. The standard curve
was prepared with carboxy methyl cellulose and adding anthrone reagent [213].
2.2.6 Protein estimation by Lowry’s assay
Protein content in the samples was determined spectrophotometrically using the Folin-
Ciocalteau reagent method. The calibration curve was prepared by dissolving bovine
serum albumin. To each 1 mL sample taken in test tubes, 4 mL distilled water was added.
To this, 5.5 mL of alkaline reagent was added and vortexed thoroughly. After 10 minutes
of incubation, 0.2 mL Folin-Ciocalteau reagent was added and incubated for 20 minutes
at 310 K. Finally, the absorbance was measured at 650 nm. A standard curve was
prepared using bovine serum albumin (0–250 µg/ml).
2.2.7 Measurement of DOC
Dissolved organic carbon (DOC) was determined by the spectrophotometric Mebius
method [214]. Firstly, 4 mL of 0.167 M K2Cr2O7 was added to 0.2 g sample. Into this
solution, 9.5 mL of concentrated H2SO4 was carefully added and mixed gently. The tubes
43

Chapter 2: Materials and Methods
were closed and heated at 423 K for 5 h. After taking from the digester, the samples were
cooled and 10.5 mL of distilled water was added. It was left to dissipate the heat
developed for some time, and the absorbance was measured at 590 nm. A standard curve
was prepared with glucose at different concentrations.
2.2.8 Cyclic voltammetry
The electrochemical activity of the control and the reactor containing the RGO-NZVI
composite was compared by the cyclic voltammetry curve obtained with the help of a
potentiostat (Corrtest, China) within a potential window of -1 to +1 V with 10 mV min
-1
scanning rate. The sludge samples collected were coated onto the graphite working
electrode with Nafion (5%, Alfa Aeser). Graphite was taken as the counter electrode
against the saturated calomel reference electrode. Similarly, the characteristic curve for
the electrochemical behavior of PPy-CB-NZVI-laden sludge was also obtained.
2.3Analytical methods
2.3.1 Characterization of composites
The texture analysis of the as-synthesized RGO-NZVI composite, spent RGO-NZVI
composite after photodegradation, NZVI-PPy-CB, BSS, PSS and MMPSS were done by
XRD (X-ray Diffractometer, Bruker D8 ADVANCE A25- with Texture Cradle).
Characteristic peaks corresponding to stretches and vibrations of RGO-NZVI composite,
spent RGO-NZVI composite after photodegradation, NZVI-PPy-CB were obtained from
Fourier transform infrared (FTIR) absorption spectra (Bruker, Alpha E) and that for BSS,
PSS and MMPSS from FTIR (Thermofisher, Nicolet iS10 FTIR spectrometer). The
morphology of RGO-NZVI composite at different durations of digestion and spent RGO-
NZVI composite after photodegradation were studied by Scanning Electron Microscopy
(JEOL JSM- 6480 LV, EDS: Oxford Instruments). The morphological study of NZVI-
PPy-CB and prepared MMPSS adsorbent and precursors were performed using Field
Emission Scanning Electron Microscope (FESEM) (Nova Nano SEM/FEI 450)
measurements. Images of the samples were recorded with beam landing energy down to
50 V and at a resolution of 1.4 nm at 1kV without beam deceleration. The surface
elements of each material were also quantified by energy-dispersive spectroscopy (EDS).
44

Chapter 2: Materials and Methods
2.3.2 Adsorbent characterization
The magnetic property of the developed adsorbents MMPSS and MIN particles was
studied by a vibrating sample magnetometer (VSM) (Lakeshore USA / Model 7404). The
total surface area and specific volume were measured by BET isotherm (Quantachrome
Instruments). The experiment was conducted at a degassing temperature of 473 K for 3 h.
The heavy metal content in BSS was obtained by acid digestion followed by Atomic
Absorption Spectrophotometry (AAS- Perkin Elmer, Analyst 200) analysis [215]. The
sample (2 g) was dried at 378 K and then made into ash at 723 K with a gradual
temperature increase (about 323 K h
-1
). Into this, 6 N HCl (1+1) was added and
evaporated the solution to completely dry. Then the residue is dissolved in 0.1 N HNO3
and the analytes are prepared by proper dilution to determine heavy metals. The salt
addition method was used to measure the point of zero charge of MMPSS [216]. For this,
0.1 M NaNO3 solution was added to 0.2 g adsorbent and adjusted the pH to 1, 2, 3, 4, 5,
6, 7, 8, 9 or 10 in different flasks using a pH meter (Systronics). The flasks were then
agitated in an orbital shaker for 24 h. Later, the final pH of the supernatant was measured
and estimated the difference between initial and final pH values (ΔpH). The point of zero
charge was the initial pH at which the curve intersects the x-axis in the plot of ΔpH v/s
initial pH values. The moisture, ash and gross calorific value were found by proximate
analysis. Bulk density was measured by measuring the weight of material occupied by 10
mL volume.
2.4Anaerobic digestion methods
2.4.1 Methanogenic seed inoculum
The methanogenic seed inoculum composed of anaerobically enriched cow dung was
prepared according to Dong et al. (2019) [131]. The fresh cow dung was the inoculum for
the enriched seed. Initially, 300 mL CD was added into a 1.25 L glass bottle with a
narrow mouth and 700 mL methanogenic nutrient medium was poured. The suspension
was then flushed with N2 gas for 20 minutes to get an anaerobic environment and sealed
with a rubber cork. To ensure complete closure, a resin-based seal was also applied. An
empty Tedlar bag (1 L) was connected to the bottle to release any pressure developed due
to the gas formation. The glass bottle was then incubated at 310 K. During this period, the
45

Chapter 2: Materials and Methods
contents were mixed twice daily by shaking manually. Once every five days, the
supernatant was discarded and replaced with an equal volume of nutrient medium. This
enrichment continued for two months and was used for the digestion experiments.
Methanogen enriching nutrient medium was composed of aminotriacetic acid (10 g L
-1
);
tryptone (2 g L
-1
); yeast extract (2 g L
-1
); MgCl2 (0.1 g L
-1
); K2HPO4 (0.4 g L
-1
); L-
cysteine (0.5 g L
-1
); The vitamin solution (10 mL L
-1
) composed of arginine (0.01 g L
-1
);
ascorbic acid (0.025 g L
-1
); riboflavin (0.025 g L
-1
); citric acid (0.02 g L
-1
); folic acid
(0.01 g L
-1
); p-aminobenzoic acid (0.01 g L
-1
); creatine (0.025 g L
-1
); The trace element
solution (10 mL L
-1
) composed of MnCl2 (0.01 g L
-1
); ZnCl2 (0.05 g L
-1
); H3BO3 (0.01 g L
-
1
); CaCl2 (0.01 g L
-1
); Na2MoO4 (0.01 g L
-1
); CoCl2∙6H2O (0.2 g L
-1
); AlK(SO4)2(0.01 g
L
-1
) and NiCl2∙6H2O (0.01 g L
-1
).
2.4.2 RGO-NZVI nanocomposite synthesis
The synthesis of RGO-NZVI composite by EDC-NHS crosslinking was carried out
according to the method given by [53] with minor modifications. First, RGO was treated
with 1.3 M HCl for 24 h to remove impurities [217]. It was then washed multiple times
with deionized (DI) water (18.2 Ω) until the pH of the filtrate turned neutral. In a three-
necked flask, 100 mg (or a proportionate quantity) of RGO was ultrasonically dispersed
in 150 mL water at 288 K. Further, 50 mg of EDC and 40 mg of NHS were added to the
solution and kept under stirring for 30 min at room temperature. The dispersion was then
closed and purged with N2 gas to flush out the oxygen and get an anaerobic environment.
Next, accurately measured NZVI was added to the bottle and stirred for 1 h at 353 K. The
weight of NZVI added varied as 200, 100, 50 and 20 mg to get different RGO to NZVI
ratios as 0.5:1, 1:1, 2:1 and 5:1. The suspension was then filtered and washed with
ethanol and DI water. Finally, the solids were dried at 338 K in a vacuum drier to get the
final product.
2.4.3 Synthesis of NZVI-Ppy-CB ternary composite
The NZVI-PPy-CB ternary composite was synthesized as follows. First, 0.5 g of Ppy-CB
was accurately weighed and added into 50 mL of 0.18 M FeSO4.7H2O solution taken in a
three-necked flask. The mixture was stirred for 15 minutes under an anaerobic
environment (N2 filled) to dissolve all the solids. To this mixture, 50 mL of 0.36 M
46

Chapter 2: Materials and Methods
NaBH4 was added dropwise and kept under stirring for another 20 minutes for the
reducing reaction. The NZVI was precipitated on PPy-CB during this period. Finally, the
solids were filtered and washed thoroughly with ethanol and vacuum dried. The dried
NZVI-PPy-CB ternary composite was stored in an envelope after vacuum suction to
remove the air present [218].
2.4.4 Sludge and synthetic wastewater
Synthetic dairy wastewater was prepared by dissolving the milk powder and the nutrients
for methanogen growth were added as per the composition given in Table 2.1 [219]. The
final pH of the given composition was 7.9±0.3. The C/N ratio of the media was adjusted
using glucose. The quantity of milk powder is varied in each case to get variable COD
values.
Table 2.7 Constitution of synthetic dairy wastewater
Component Concentration (g L
-1
)
Dried milk powder 20
Yeast 0.36
Glucose 22
Urea 0.2
NH4Cl 0.25
Na2HPO4·12H2O 0.445
KH2PO4 0.818
MgSO4·7H2O 0.6
FeSO4·7H2O 0.024
MnSO4·H2O 0.024
CaCl2·H2O 0.036
NaHCO3 1.56
2.4.5 Effect of RGO-NZVI on anaerobic digestion of dairy wastewater
The anaerobic digestion of dairy wastewater was carried out in 1.25 L borosil glass
bottles with 1L working volume and remaining head space (Figure 2.1). Tedlar gas
sampling bags of 1L capacity were used to collect the biogas formed. Initially, all the
47

Chapter 2: Materials and Methods
batch digesters were fed with 750 mL of dairy wastewater, 200 mL of fresh cow dung and
50 mL of seed to get a final SCOD of 35010 mg L
-1
and C/N ratio of 19.2. The properties
of the components in the feed are given in Table 2.2. The pH of the mixed slurry was
adjusted to 7.5 with 1M NaOH. Initially, the operational parameters, pH (3-9), organic
loading (10000-40000 mg L
-1
) and dosage of the composite (300-1500 mg L
-1
) were
optimized for maximum gas production. Later, the different RGO-NZVI composite ratios
0.5:1, 1:1, 2:1 and 5:1 were added to the R1, R2, R3 and R4 digesters, with 900 mg L
-1
additive. All the digesters were incubated in triplicates, including a control digester with
no additives. Each batch reactor loaded with feed was flushed with N2 gas for 15 minutes
to remove the oxygen in the liquid and incubated at 310 K. The digesters were shaken
every 12 h with slow rotations to mix the contents. Liquid and gas samples were collected
regularly from the digesters for the first two weeks and twice a week later on. The
statistical significance of each set of values was determined by analyses of variance
(ANOVA).
Figure 2.9 Batch reactor for the anaerobic degradation of dairy wastewater
48

Chapter 2: Materials and Methods
Table 2.8 The properties of each component added to the digester
Properties Dairy WWEnriched
seed sludge
Cowdung Slurry
SCOD (mg L
-1
) 27500 65900 51300 35010
BOD/SCOD 0.38 0.35 0.21 0.38
Total Nitrogen (mg L
-1
) 850 1200 0.44* 810
C/N ratio 16.82 19.96 21.75 19.2
pH 6.65 5.89 6.13 6.82
Total Solids (g L
-1
) 21.93 84.18 17.94* 58.63
Total Volatile Solids (g L
-1
)19.73 65.11 77.81** 47.36
Total Fixed Solids (g L
-1
) 2.20 19.05 22.19** 11.26
Total Suspended Solids (g L
-
1
)
4.05 49.070 61.40** 10.53
Total Dissolved Solids (g L
-1
)17.88 35.11 38.60** 48.10
Cellulose (x10
-3
g L
-1
) - 5.08 10.18* 18.29
Protein (g L
-1
) 5.83 8.26 4.75 7.86
*wt % (g/g); ** % of TS
2.4.6 EGSB Reactor operation
The schematic diagram of the reactor set up is given in Figure 2.2. EGSB reactor was
constructed using plexiglass material with an inner diameter of 6 cm for the narrow
column, 13 cm for the gas collection chamber and a total height of 116 cm. The heights
of the tapered inlet cone (1 in Figure inset), narrow column (3 in Figure inset) and wide
chamber (4 in Figure inset) were 10 cm, 93 cm and 13 cm, respectively. The total volume
of the reactor was 4.98 L with 2.9 L liquid volume; the remaining was kept as head space
for gas collection. The ports, P1 to P7, were 0.6 cm in diameter.
49

Chapter 2: Materials and Methods
+
-
% CH
4
P
1
P
5
P
3
P
4
P
2
P
6
P
7
Feed (DW)
Heating water
circulation
PP
1
PP
2
Feed inlet
Effluent
Gas analyzer
Gas outlet
1
2
3
4
Figure 2.10 Schematic diagram of continuous flow anaerobic reactor set-up
P1- biogas outlet; P2- effluent recirculation; P3 & P4- heating water recirculation; P5, P6 &
P7- effluent outlet and sampling ports; PP1& PP2- peristaltic pumps. Inset: 1) inlet
distributor; 2) outer jacket; 3) granule fluidization zone; 4) gas collection zone.
Initially, 250 mL cow dung, 250 mL seed and remaining feed dairy wastewater were
added to the column until the level of effluent outlet. Then the contents were purged with
N2 gas through the bottom and the bubbling continued for 30 minutes. After purging, the
effluent stream was kept under complete recirculation until the required HRT is attained.
The continuous operation was carried out for 180 days, dividing the whole period into 4
phases. During Phase I and Phase II, the reactor was operated without any additive.
Initially, a 30 days stabilization was allowed with the conditions as provided in Table 2.3.
Later at the start of Phase II, organic loading was increased to compare the performance
at shock loads. At the beginning of Phase III, 2.34 g of RGO-NZVI composite was added
to the column and the digestion continued. OLR and HRT were unchanged during Phase
III. Further, OLR was increased at the starting of Phase IV. The feed inlet was supplied
through the bottom of the column in an upward flow to get the sludge under a fluidized
50

Chapter 2: Materials and Methods
state. A portion of the treated effluent was recirculated to the reactor by controlled flow
using a peristaltic pump. The recirculation ratio (R/I) in the reactor was maintained to be
20. Mesophilic digestion was assured by providing the reactor with a heating water
recirculation through an outer jacket. The temperature of the recirculating water was
maintained to be 310 K using a thermostat-based heating system. Other parameters of the
continuous reactor are given in Table 2.3.
Table 2.9 Operating conditions of the EGSB reactor
PhaseDuration
(day)
Feed SCOD
(mg L
-1
)
OLR
(kg/m
3
. day)
HRT
(h)
Upflow velocity
(m h
-1
)
I 30 2000 2.21 21.6 0.89
II 50 4000 4.43 21.6 0.89
III 50 4000 4.43 21.6 0.89
IV 50 6000 6.64 21.6 0.89
2.4.7 Pretreatment of dairy wastewater
The photocatalytic pretreatment was carried out as follows; 200 mL of dairy wastewater
containing 2 mM ammonium persulfate (APS) oxidant was taken in a beaker and the
RGO-NZVI catalyst was added. The initial pH of the solution was adjusted in a range of
3-9 by dropwise addition of 0.1 N HCl or 0.1 N NaOH. The effect of other parameters,
dosage of the catalyst, initial organic loading and time were also investigated.
Photocatalysis was carried out in a photoreactor equipped with a 6W LED lamp and a
magnetic stirrer. No external aerator was employed to avoid oxidation of the catalyst. The
batch degradation was carried out under the visible spectrum and final samples were
collected to measure SCOD, DOC and final pH.
2.4.8 Anaerobic digestion after pretreatment
In the second phase of research, the anaerobic digestion of pretreated wastewater was
carried out in digesters D1 and D2, with and without the addition of 0.1 g RGO-NZVI
composite, respectively. A control digester (CD) was set up for comparison. To confirm
the effect of the spent catalyst, the RGO-NZVI catalyst was separated from the pretreated
effluent and added to the digester containing fresh dairy wastewater. The digester (Figure
51

Chapter 2: Materials and Methods
2.3) had a total working volume of 250 mL, composed of pretreated dairy wastewater
containing the catalyst, cow manure and methanogenic seed in a ratio of 31:8:1. Other
nutrients and 1 mL of trace element solution were added and purged with N2 gas. The
digesters were incubated at 310 K under agitation. The properties of the feed are given in
Table 2.4. The aliquots of digestate were collected regularly and the volume and
composition of biogas were measured. After the digestion for 35 days, the yield of CH4
and % SCOD removal was compared with the control.
Table 2.10 The properties of dairy wastewater fed to different digesters
Properties D1 D2 CD
TCOD (mg L
-1
) 8880 8880 9970
SCOD (mg L
-1
) 7100 7100 5850
DOC (mg L
-1
) 3250 3250 2550
BOD/SCOD 0.58 0.58 0.22
C/N ratio 12.82 12.82 14.58
Total Solids (g L
-1
) 5.81 5.81 5.19
Total Volatile Solids (g L
-1
) 5.2 5.2 4.13
Total Suspended Solids (g L
-1
) 0.91 0.91 3.40
Figure 2.11 Batch digestor for the degradation of RGO-NZVI catalyst-laden pretreated
dairy wastewater
52

Chapter 2: Materials and Methods
Table 2.11 The initial characteristics of the slurry taken for digestion
Characteristics Measured values
TCOD (mg L
-1
) 16100
Initial SCOD (mg L
-1
) 12250
BOD/SCOD 0.41
C/N ratio 17.63
Initial pH 7.1
Total solids (g L
-1
) 24.95
Total volatile solids (g L
-1
) 20.05
2.4.9 Anaerobic digestion with PPy-CB-NZVI
The anaerobic digestion was carried out in 250 mL glass digesters equipped with a gas
sampling Tedlar bag and a liquid sampling port. A working liquid volume of 200 mL and
the remaining volume of the digester was given as head space. The slurry in the digester
had a composition similar to that provided in section 2.2.8, except the wastewater was
non-pretreated. The initial characteristics of the slurry are given in Table 2.5. The dosage
of PPy-CB-NZVI in each digester was varied as 0, 0.2, 0.4 and 0.8 g L
-1
and termed as
D1, D2, D3 and D4, respectively. Another digester with 0.4 g L
-1
of Ppy-CB was also set
up for comparison. The triplicate of each digester was then flushed with nitrogen gas for
15 min to remove oxygen from the liquid media, sealed with a rubber cork and incubated
at 310 K under agitation. The liquid and gas samples were collected at regular intervals
and analyzed to measure their characteristics.
2.4.10 Characteristics of wastewater and degradation parameters
All the pH adjustments were made with the help of a pH meter (Systronics). The
degradation of dairy wastewater was evaluated based on the measured water quality
parameters. The pH and conductivity of the liquid samples collected from the digesters
53

Chapter 2: Materials and Methods
were measured immediately after sampling using probe electrodes (EI instruments,
India). Biogas volume was recorded by the equivalent displacement of water saturated
with NaCl. The composition of biogas in terms of CH4 volume was measured using a
biogas analyzer (MM Automation, India). The parameters SCOD, NH4
+
, Fe
2+
and VFA
were measured after filtering the samples with 0.45 µ syringe filters and diluted
appropriately for each analysis. The triplicates of results were compared by analyses of
variance (ANOVA) and determined the statistical significance of each set of values.
The initial properties of the dairy wastewater, cow dung, methanogenic seed and feed
slurry were determined according to the standard procedures (APHA 2000a) [209].
2.4.11 Kinetics of anaerobic digestion
The kinetics of anaerobic digestion was analyzed using a statistical model. For this, the
values of CH4 produced from the digesters were fitted against the modified Gompertz
model and inspected by the model parameters. Eqn. 2.1 represents the mathematical
representation of the model.
M
t=M
0exp{
−exp(
R
me
M
0
(λ−t)+1)}
2.3
Where M
t (mL) is the cumulative CH4 yield at time t; M
0is the maximum potential of
CH4 production (mL); R
mis the peak biomethane production rate (mL day
-1
); λ is the
duration of the lag phase (day); t is the time over the fermentation period (day); e is a
mathematical constant equivalent to 2.718 [109]. The nonlinear fitting of the
experimental data was carried out in OriginPro 2020b (OriginLab Corporation, MA,
USA) software and determined the values of the parameters, M
0, R
m and λ and the results
were converged. The iterations were carried out for maximum R
2
value and standard
deviations were also obtained.
2.5Adsorption of heavy metals using magnetic adsorbent
54

Chapter 2: Materials and Methods
2.5.1 Preparation of adsorbent from biogas slurry solids
The BSS was dried (353 K) and ground using a pestle and mortar. The particle size was
brought to 30-85 microns by sieving and stored in a desiccator. MIN was synthesized by
the Co-precipitation method given by Khalil (2015). Briefly, solutions of anhydrous
FeCl3 and KI were prepared by dissolving the salts in DI water and combining them to
get a ratio of 1:0.338 (w/w) in a beaker. The solution was stirred for 1h to reach
equilibrium. Subsequently, the iodine precipitate was removed by filtration. In the next
step, hydrolysis was done by dropwise adding 25% NH4OH into the filtrate to attain a pH
of 9-11. Later, the black precipitate appeared and was separated, washed and dried under
vacuum. For the pretreatment of slurry solids, 4 g of BSS was soaked in 15 mL of freshly
prepared 3M KOH for 15 min. The heating was done at varying temperatures such as 303
K, 323 K, 373 K, 423 K and 473 K. A set of controls was also kept by adding deionized
water instead of alkali solution. The time of pretreatment (0.5-3.5 h) and the quantity of
alkali solution in terms of BSS to KOH ratio (w/v) (1:2.5 to 1:25) were also optimized.
The sample, after pretreatment, was cooled and washed with deionized water until the pH
of the supernatant reached a neutral value. Further, washed solids were dried at 353 K
and stored. The pretreated BSS (PSS) was crosslinked with MIN in the presence of 10
mL of glutaraldehyde (25%) at a temperature of 323 K for 2 h [220]. Solids were washed,
separated under a magnetic field, dried at 353 K and labelled as MMPSS. Different
adsorbents were developed by crosslinking MIN to PSS in various ratios (w/w) (1:1 to
1:10). The optimum ratio was determined by comparing the adsorption capacities of each
adsorbent through batch tests.
2.5.2 Batch adsorption experiments
Adsorption of individual heavy metal ions (Pb
2+
, Cu
2+
and Cd
2+
) was carried out to
understand the influence of different pretreatment conditions. The heavy metal solutions
were prepared by dissolving the salts CuSO4, Pb(NO3)2 and CdCl2 in deionized water
(18.2 Ω). The batch tests were conducted in triplicates with 100 mL of heavy metal
solution in 250 mL Erlenmeyer flasks at 120 rpm and 310 K. Optimization of
pretreatment conditions was conducted with 0.5 g adsorbent and an initial concentration
of 100 mg L
-1
for a contact time of 2 h. The initial pH of the solution was adjusted by
55

Chapter 2: Materials and Methods
dropwise addition of 0.1 N HCl or 0.1 N NaOH. Other operational parameters were
varied according to the design of the experiments (as given in section 2.3.3). After
adsorption, the aliquots from the solutions were collected, filtered through 0.45 µ syringe
filters and diluted with DI water. The un-adsorbed heavy metal concentration was
measured by AAS. The adsorption capacity was calculated according to Eqn. 2.2. A
competitive adsorption study was also conducted to see the efficiency of simultaneous
adsorption of all three heavy metals. For this, 100 mL of heavy metal solution containing
50 mg L
-1
of each metal, Cu
2+
, Cd
2+
and Pb
2+,
was prepared and 0.5 g adsorbent was
added. The adsorption capacity and efficiency were calculated and reported.
q
e
=
(C
0−C)V
M
2.4
Where C0 - the initial concentration of heavy metal ion (mg L
-1
), C - the final
concentration (mg L
-1
), V - the volume (L) of heavy metal solution and M - the weight of
adsorbent used (g).
2.5.3 Optimization by CCD
The proper design of experiments and parameter optimization is crucial to determine the
range of operation for a process. In this study, five operational parameters were chosen
based on the literature survey and screened using the One Factor at a Time method. The
parameters selected for screening were initial pH, time of adsorption (min), Adsorbent
dosage (g), initial concentration of heavy metals (mg L
-1
) and temperature (K). Moreover,
their cause on heavy metal adsorption capacity and removal efficiency was analyzed. It
was observed that temperature had a very minimal cause on the output, therefore
eliminated while conducting further experiments. The conclusion was made based on the
statistical t-test carried out for experimental data of temperature versus qe.
This study aims to predict extreme responses, so the design must consider corner points.
Also, CCD has an embedded factorial design suitable for sequential experiments. It
involves a rationalized number of design points for handling the input variables within a
given range, and the lack of fit would be checked by the information obtained from the
56

Chapter 2: Materials and Methods
curvature estimation method [221]. Here, a full factorial run was experimented with in
CCD with four parameters. The method included 30 experiments with 24 trials for non-
center points and six for center points. The lower and upper limit was chosen so that the
software generates design within the limits of the experiment. The coded variables and
their corresponding limits are A) pH (5-7), B) time (40-90 min), C) dosage (0.4-0.7 g)
and D) initial concentration (75-125 mg L
-1
).
The RSM computations for this study were performed with the help of Design-Expert
software (Statease version 11). Statistical quadratic models consisting of interaction and
polynomial terms were developed for all response variables. The cause-effect can be
represented as given in Eqn 2.3.
Y=β
0
+∑
i=1
4
β
i
X
i
+∑
i=1
4
∑
j=i+1
4
β
ij
X
ij
+∑
i=1
4
β
ii
X
i
2
+e
2.5

Where Y is the response (removal efficiency and adsorption capacity), Xi is the levels of
the process variables, β0 is a constant, βi, βii and βij represent the linear, quadratic and
interaction coefficient, respectively, 'e’ stands for random error and ‘k’ is the total number
of variables used to optimize the adsorption process. The polynomial model with the
highest order was selected with the sequential p-value ≤ 0.05, the lack of fit p-value >
0.05 and maximum possible (<0.2) values for adjusted R² and predicted R². Further,
additional terms were inspected for significance and chose the model, which is not
aliased. The selected model was analyzed using Analysis Of Variance (ANOVA).
Consequently, the best-fit model was selected after checking for any requirement for
transformations to fit statistical assumptions from the Box-cox plot. Ultimately, the
interaction effects of the considered process parameters on the responses were explained
using a regression equation for the statistical model and RSM contour plots [25,222].
2.5.4 Kinetics and isotherm models for adsorption
The kinetics of adsorption details the minimum time required for optimum adsorption and
the mechanism of the process [223]. Kinetics was studied with an initial concentration of
150 mg L
-1
for 3 h. Three kinetic theories were considered: Lagergren’s first-order model,
57

Chapter 2: Materials and Methods
Pseudo second-order model and Intra particle diffusion theory. The adsorption process
attains equilibrium at a point where uptake equals the release of target ions and depends
on the quantity and type of material. In this study, four models were selected to match
equilibrium data of adsorption (with initial concentration from 25 to 250 mg L
-1
), such as
Langmuir, Freundlich, Temkin and Dubinin Rudushkevitch (DR) model. The
mathematical representation of each model is shown in Table 6.6.
58

Chapter 3
RGO-NZVI conductive additive assisted
methanogenesis from dairy wastewater by enhancement
of bio-electrochemical events
Gas
collect ion
Bag
Species 1
Species 2
e
-
e
-
e
-
e
-
e
-
Anaerobic Digestion
of dairy wastewater
RGO-NZVI
Mediated
e
-
Transport
R1 R2 R3 R4 Control
0
2000
4000
6000
8000
10000
12000
Digesters
Cum. CH
4
Cum. Biogas
T
o
t
a
l
g
a
s
v
o
l
u
m
e
(
m
L
)
40
50
60
70
80
% COD
C
O
D
r
e
d
u
c
t
i
o
n
(
%
)

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
3.1Preface
Efficient waste management and alternatives for waste reduction have been the prime
factors in achieving sustainable development goals. A wide range of waste biomass can
be transformed into energy by anaerobic fermentation. Conductive additives have shown
positive influences on anaerobic digestion. This study focused on improving the electron
transport in the anaerobic digestion of dairy wastewater by adding RGO-NZVI
composite. The effect of variations in parameters such as pH, organic loading and dosage
of the composite was studied. Further, the ratio (wt/wt) of RGO and NZVI were varied
while adding to the anaerobic digesters and monitored their effects on biogas volume,
composition, SCOD removal and VFA accumulation. The efficiency of the additives was
compared by analyzing the wastewater parameters and biogas composition. The
metagenomic analysis was conducted to know the variation in diversity of the microbial
community and the major mechanism that caused higher CH4 generation. The fit of
reaction kinetics towards the modified Gompertz model was also evaluated. Further, a
continuous granular sludge reactor was set-up and analyzed the performance at varying
OLR and with and without the presence of the conductive composite.
3.2Structural properties and characteristics of RGO-NZVI composite
Figure 3.1 represents the XRD, FTIR and Raman spectra patterns for the RGO-NZVI
composite. The as-synthesized RGO-NZVI nanocomposite was characterized by FTIR
spectroscopy, as shown in Figure 3.1a. Here the spectra contained characteristic peaks
for both RGO and NZVI. The bands at 679, 825 and 1059 cm
-1
represent distinct Fe-O
bonds, Fe–O–H bending vibration of Fe-OOH particle [53] present probably from the
oxidized outer surface of NZVI while exposure to the air and alkoxy (C-O) stretching
vibrations in the oxidized domains of RGO and due to H2O respectively [46,53]. The
peaks at 2152 and 2983 cm
-1
could indicate the alkynes in the unoxidized carbons in the
RGO and alkane stretch, respectively [224,225]. The minor peaks at 3118, 3610 and 3622
cm
-1
could be due to the free alcohol stretching and vibrations that remained due to
ethanol washing [30]. The peaks at 1540 cm
-1
,

1695 cm
-1
and a minor peak at 2270 cm
-1
support the presence of primary and secondary amine, amide functional group and
isocyanates due to crosslinking aided by EDC-NHS [226,227].
60

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
0 5001000150020002500300035004000
I
n
t
e
n
s
it
y
(
a
.u
.)
Raman Shift (cm
-1
)
4000350030002500200015001000
T
r
a
n
s
m
it
t
a
n
c
e
(
%
)
Wavenumber (cm
-1
)
a)
10 20 30 40 50 60 70 80 90
I
n
t
e
n
s
i
t
y

(
a
.
u
.
)
2q (degree)
b)
c)
Figure 3.12 Characteristic spectra of RGO-NZVI composite by FTIR (a), XRD (b) and
Raman spectra (c) analysis
The XRD analysis (Figure 3.1b) of the composite showed multiple peaks representing
RGO and two ionic forms of iron, i.e., zerovalent and trivalent. The sharp rise at 45.21°
and less intense peaks at 65.28° and 82.51° show the presence of NZVI in the composite
and confirmed with the pattern produced by Wu et al., 2017 [45]. Whereas the signals
obtained at 30.73°, 35.32°, 55.03° and 71.54° are an illustration of tri- and di-valent iron
molecules, formed sparingly on the surface of NZVI due to oxidation [53]. Thus the
composition of NZVI could be explained as a core structure with Fe
0
and a shell structure
made of iron oxides, which is formed via the oxidation of Fe
0
in the core by water and
oxygen during the synthesis process [124]. A wide curvature and a peak point at 20.19°
were consistent with the previously reported patterns of RGO [132].
As shown in Figure 3.1c, the Raman spectra exhibited two dominant peaks at 1350 and
1584 cm
-1
, representing D and G peaks of RGO, respectively. The 2D and G+D peaks
were also observed at 2700 and 2932 cm
-1
, respectively. Low-intensity curves at 220 and
285 cm
-1
represent the NZVI molecule [228].
61

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
Figure 3.13 SEM images of RGO-NZVI before adding to the digester (a) and attached
growth on the surface of the conductive composite after 36 days of digestion (b). EDX
mapping of iron on RGO-NZVI composite (c) and EDX spectrum of the RGO-NZVI
composite
The morphology analysis of the RGO-NZVI composite showed a precise formation of
NZVI onto the surface of RGO. The surface of RGO was decorated with small aggregates
of NZVI by amino functionality imparted by EDC-NHS crosslinking [53]. Intrinsic
agglomeration could be prevented by affixing NZVI in this way [229]. In Figure 3.2a,
the NZVI incorporated on the layers of RGO is encircled, which confirms the
crosslinking. EDX analysis also indicated similar results showing an iron content of
17.08%. The morphological variation of the spent composite, as shown in Figure 3.2b,
clearly demonstrates the active participation of the RGO-NZVI composite in anaerobic
digestion. Further, the surface is characterized by biofilm formation during anaerobic
digestion. This attached growth of bacteria possibly reduced the interspecies distance and
facilitated DIET resulting in more biogas production [230].
62

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
3.3Optimization of operational parameters
3.3.1 Effect of pH, organic loading and dosage on CH4 production
3 5 7 9
-10
0
10
20
30
40
50
60
70
10000 20000 30000 40000
50
60
70
300 600 900 1200 1500
50
60
70
3 5 7 9
0
1000
2000
3000
4000
Biogas volume
CH
4
Initial pH
B
i
o
g
a
s

v
o
l
u
m
e

(
m
L
)
a
0
500
1000
1500
2000
2500
3000
C
H
4

(
m
L
)
%

S
C
O
D

R
e
m
o
v
a
l
Initial pH
b
10000 20000 30000 40000
3000
4000
5000
6000
7000
8000
9000
B
i
o
g
a
s

v
o
l
u
m
e

(
m
L
)
Initial SCOD (mg L
-1
)
c
0
500
1000
1500
2000
2500
3000
C
H
4

(
m
L
)
%

S
C
O
D

R
e
m
o
v
a
l
Initial SCOD (mg L
-1
)
d
300 600 900 1200 1500
2000
3000
4000
5000
6000
7000
Dosage (mg L
-1
)
B
i
o
g
a
s

v
o
l
u
m
e

(
m
L
)
e
500
1000
1500
2000
2500
3000
C
H
4

(
m
L
)
%

S
C
O
D

R
e
m
o
v
a
l
q
e

(
m
g
/
g
)
Dosage (mg L
-1
)
f
Figure 3.14 Effect of operational parameters pH (a & b), organic loading (c & d) and
dosage (e & f) on anaerobic digestion
63

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
A batch cycle of 36 days duration was conducted with the RGO-NZVI composite and
optimized the process parameters. As shown in Figure 3.3, maximum biogas was formed
in the reactor in which the initial pH was neutral. A pH of 6.6 to 7.6 is the favorable range
for methanogens' growth and metabolism and other associated microorganisms. The
performance was minimal at pH 3. A lower pH stimulates the decay of methanogens,
whereas a higher H
+
enriches free NH3-N in the media [231].
Similarly, when the initial organic load of the media was increased, the biogas volume
increased while SCOD removal decreased steadily. Though CH4 volume improved
considerably till an initial SCOD of 30000 mg L
-1
, a further rise in organic load
diminished the CH4 composition. At high organic composition of media, acidogens
produce high VFA. However, these organic acids are not proportionately converted to
acetate, so the VFA accumulation increases and methanogenesis diminishes [232].
Likewise, the higher conductive composite addition assisted in better performance till a
dosage of 900 mg L
-1
and a further high concentration of RGO-NZVI caused a slight
reduction in the performance by lowering biogas volume and CH4. However, SCOD
removal at higher dosage values did not cause significant change compared to the
digesters with a dosage of 900 mg L
-1
.
3.3.2 Effect of ratio of RGO and NZVI
Figure 3.4 and Figure 3.5 represent the effect of RGO-NZVI composite addition on
biogas and CH4 production. R2, R3 and R4 gained better mineralization than the control
reactor. All the reactors produced a substantial volume of biogas (425-920 mL) on day
one and the reactor having an RGO-NZVI ratio of 2:1 (R3) yielded the highest volume of
gas (Figure 3.4a). On the other hand, the concentration of CH4 was minimal during the
initial stage due to the lag in the bacterial acclimatization when introduced into a new
growth environment having high organic loading (Figure 3.5a). The curves in Figure
3.5b implied that the control reactor containing no additives had less potential for CH4
production than R2, R3 and R4. The p-value of 0.005 from the paired t-test analysis
indicated a significant difference in the CH4 production between R3 and control.
64

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
On the contrary, R1 containing an RGO-NZVI ratio of 0.5:1 produced 34.14 ± 1.5% less
CH4 than the control reactor. The performance of R3 (3841.8 ± 145 mL CH4) at the end of
the digestion was remarkable when compared to R1, R2, R4 and the control reactor with
a total CH4 yield of 1358.15 ± 49 mL, 2892.5 ± 95 mL, 2802.8 ± 105 mL and 2062.4 ± 73
mL of CH4 respectively (Figure 3.8c). From the observations, it was clear that active
methanogenesis occurred from day 5 to 14 after an initial lag phase, contributing to more
than 75% of total CH4 production in each of the digesters. Eventually, after this period,
the biodegradation entered an idle phase with minimal CH4 and biogas production
(Figure 3.4b).
024681012141618202224262830323436
0
2000
4000
6000
8000
10000
12000
0
.5123456789
1
0
1
1
1
2
1
3
1
4
1
7
2
0
2
4
2
8
3
2
3
6
R1
R2
R3
R4
Control
B
a
t
c
h
r
e
a
c
t
o
r
Time (Days)
10
15.85
25.12
39.81
63.1
100
158.5
251.2
398.1
631
1000
Biogas volume (mL)
C
u
m
u
la
t
iv
e
b
io
g
a
s
p
r
o
d
u
c
t
io
n
(
L
)
Time (days)
R1
R2
R3
R4
Control
a) b)
Figure 3.15 The volume of biogas on each sampling (a) and cumulative volume of biogas
(b) produced from each batch reactor
Throughout anaerobic digestion, the highest daily production of CH4 in each of the
reactors was 221.4± 7.1 mL on day 6, 320.1± 4.4 on day 7, 429± 18.1 mL, 343.75± 7.5
mL and 290± 6.38 mL on day 6 from R1, R2, R3, R4 and control reactor respectively.
Highly enriched biogas was found in R3 with a CH4 content of 70 ± 2.8% on day 7, while
the control reactor contained only 52 ± 1.5% CH4 on the same day. Meanwhile, the
concentration of CH4 from R1, R2 and R4 were 48 ± 1.9%, 66 ± 0.9% and 59 ± 1.7%,
respectively, on day 7. 34.79 ± 1.3% of the total biogas generated in R3 (11040 ± 452.64
mL) was constituted by CH4. Though the CH4 composition of total biogas from control
was 41.58 ± 1.4%, the total volume of biogas at the end of the digestion period was 55.1
65

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
± 2.1% less than R3. Considering the specific CH4 production concerning COD, R3 could
yield 150.6 ± 7.2 mL per g of COD removed, dominating the performance of other
reactors R1, R2, R4 and the control reactor by 85.84 ± 3.9%, 14.07 ± 0.6%, 12.35 ± 0.6%
and 26.4 ± 1.1% respectively. A paired t-test of all the results obtained from R2 and R4
showed a very less significant difference (p>0.05) between the performances, implying
similar biochemical behavior of the digestion system [233].
The better CH4 production in R3 could be attributed to the synchronized effect of iron for
microbial growth and DIET supported by electrically active RGO-NZVI composite. The
composite facilitates the formation of short passages for electron movements and assists
in the intensified reduction of CO2 by hydrogen and the proliferation of methanogens
[230,234]. Moreover, the planar structure of RGO provides a high specific surface area
for the attached growth of anaerobic bacteria [133]. Further, the distribution of the
nanocomposite in the bulk media coordinates the optimum utilization of organic matter
by the attached microbes rather than the localized depletion of nutrients as by the settled
biomass sludge [235]. However, NZVI at high concentrations may disrupt cell structure,
oxidative stress and low consumption of intermediate metabolic products [63,112]. In this
study, R1 with higher NZVI (equivalent to ~400 mg L
-1
) tended to produce less volume
of CH4 and showed a low rate of CH4 enrichment compared to the control. This is a clear
indication of toxicity imparted by iron [236].
Meanwhile, optimum NZVI concentration in R2 (~300 mg L
-1
) and R3 (~200 mg L
-1
)
benefitted the metabolism and fostered CH4 concentration. Resemblance of Fe-C micro-
electrolysis compounds with micro and macro galvanic cells assists in faster conversion
of organic materials. However, a concentration below 200 mg NZVI L
-1
shows no
significant effect or the effect was diminished by higher RGO concentration.
Carbonaceous amendments have been reported to activate the electron-accepting redox
moieties and enable efficient IET between these materials and structures, such as
conductive pili or outer membrane cytochromes [237]. The difference in redox peak
current in the cyclic voltammogram shows (Figure 3.8a) that the sludge from R3 has
better redox properties than that from the control reactor. The presence of external
conductive materials improved the abundance of electroactive units, enhancing electron
66

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
transport [238]. Such a rapid establishment of cellular links reduces the energy demand
for filament growth; thereby, the available energy may be utilized for other cellular
activities [128].
Nevertheless, a rise of RGO to ~500 mg L
-1
of effective concentration was unfavorable,
showing less product gas compared to the results exhibited by R3. This could be related
to the theory of cytotoxicity imparted by carbonaceous materials causing oxidative stress
and perturbation on microbial cell membranes, discussed by Lin et al. (2017) [116].
Therefore, it is deduced that the dosage of NZVI and RGO influences CH4 production
and enrichment. This conclusion contradicts the results of [132], who demonstrated the
potential inhibition by RGO as dose-independent. However, the discussion by [116] and
[137] supports the dose-dependent toxicity observations of this study. However, it is
worth noting that many factors can influence efficiency since toxicity depends on the
concentration, size, chemical and physical structure, the grade of reduction or oxidation,
and the type of microorganisms present in the biological system [132]. In general, it has
been found that the addition of RGO-NZVI composite can impart negative or positive
effects on wastewater degradation and production of CH4 in anaerobic digestion
processes depending on the ratio of RGO to NZVI in the composite.
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200 0
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600 0
800 0
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120 00
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100
200
300
400
500
C
H
4
p
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o
d
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c
t
io
n
(
m
L
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R1
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R4
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3
6
R1
R2
R3
R4
Control
8.000
20.60
33.20
45.80
58.40
71.00
CH
4
concentration (%)
Time (Days)
Not measured
B
a
t
c
h
r
e
a
c
t
o
r
a)
a) b)
Figure 3.16 Concentration (a) and volume (b) of CH4 produced from each batch reactor
during the digestion
67

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
Table 3.1 compares the efficiencies of different additives in improving anaerobic
digestion. However, the convenience in comparison depends on experimental conditions
too. The reactor volume in each of the literature compared is 60 mL, 120 mL, 300 mL
and 1.5 L. In the first case, the optimum additive concentration was 50 mg L
-1
, whereas,
20 g L
-1
biochar was added in the second example. Similarly, 1 g L
-1
graphene and 1.5 g
g
-1
dry matter ash were used in other experiments, respectively. Moreover, stepwise
addition and alkaline pretreatment were followed in the later one. The continuous system
added with biochar had 57.9 g COD L
-1
of OLR. The result in each case is influential
given the differences in operational conditions. Even though, RGO-NZVI showed better
performance, to conclude, each material should be tested under similar experimental
conditions.
During the final stage of degradation, as shown in Figure 3.5b, most reactors exhibited
no significant gas production. The decline of substrates and the intolerable C/N ratio of
media could lead the biological system to reach a plateau of degradation [231]. Switching
to the nitrogen-consuming pathways and ammonia inhibition might have played a role in
reaching the stationary phase [239]. Also, the depletion of other trace nutrients was
reported to cause alterations in the ratio of methanogenic species and might contribute to
the lower yields of CH4 [240].
Table 3.12 A comparison between efficiencies of different additives in anaerobic
digestion
Additive used Substrate treated Efficiency Ref
RGO-Fe3O4
Enriched sludge with
mineral media
47 % more CH4 [132]
Biochar Food waste Shortened lag time by 29.2%[108]
Graphene Ethanol 25% more CH4 [116]
Ash Waste activated sludge 35.4% more CH4 [117]
RGO-NZVI Dairy wastewater 86% more CH4
This
study
68

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
3.3.3 Reduction of organic load in the feed
The SCOD of slurry during anaerobic digestion starts decreasing when the mineralization
of its biodegradable fraction commences [241]. Figure 3.6a shows the trend of SCOD
(%) in each reactor during digestion. The highest degradation was observed in R3 with
72.86 ± 2.2% removal and the final concentration of SCOD in R3 was 47.94 ± 1.9 %,
27.48 ± 1.1%, 32.62 ± 1.3% and 46.32 ± 2.2% less than that of R1, R2, R4 and control,
respectively. Anaerobic digestion begins with hydrolytic and acidogenic microorganisms,
decomposing complex substrates into products such as simple sugars, proteins and VFAs
[110]. The release of these compounds into the media stimulates acetogenic and
methanogenic archaea and eventually, the redox reactions between species and substrates
bring down the concentration of these intermediate products [114]. Figure 3.7a shows the
variation of total VFAs in the reactors during digestion. A high concentration of VFA
imparted more SCOD than the initial feed; however, initialization of aceto-cum-
methanogenesis consumed VFAs for growth and metabolism, causing a faster reduction
of SCOD [242,243]. Apart from consuming VFAs, the stabilization of sugars, proteins
and fats would also have contributed to the reduction of SCOD [244]. As depicted in
Figure 3.7a, R3 contained a high VFA of 390.828 ± 10.9 mg L
-1
on day 10 and got
diminished by further digestion. R1 accumulated VFA at a level higher than other
digesters after 8 days and reached a final concentration of 751.394 ± 16.1 mg L
-1
. Acetic
acid was the prominent VFA in all the reactors during the active methanogenesis period
(Figure 3.8b). Though propionic acid concentration was low on day 3 in R1, there was a
rise, reaching a higher concentration than acetic acid from day 8. The higher
concentration indicated less potential for propionic acid oxidation and conversion into
low carbon-chain acids in R1 [133]. The slow rate of propionate uptake due to high-level
iron inhibition caused this accumulation in the media [236]. Since the VFA concentration
progressively increased in R1, it is clear that the NZVI toxicity affected mainly acetogens
and methanogens than the microbes involved in hydrolysis and acidogens. The lesser
VFA accumulation in R3 than in the control reactor implied that the RGO-NZVI
composite had influenced the electron transport and faster consumption of these
intermediate compounds. Overall, high SCOD removal was found from R3 due to the
69

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
nanocomposite supplement and assisted in the maximum utilization of organic substrates
from the wastewater [245].
024681012141618202224262830323436
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0
10
20
30
40
50
60
70
80
024681012141618202224262830323436
5.8
6
6.2
6.4
6.6
6.8
7
7.2
7.4
7.6
7.8
%

S
C
O
D

r
e
d
u
c
t
i
o
n
Time (days)
p
H
Time (days)
R1
R2
R3
R4
Control
R1
R2
R3
R4
Control
a) b)
Figure 3.17 SCOD reduction (a) and variation of pH (b) in each batch reactor along the
duration of digestion
Figure 3.6b shows the trend of pH over the digestion period. The sudden decline of pH
from 7.3±0.1 to 6.2±0.06 in R3 until day 2 can be related to the accumulation of VFA in
the media due to fast hydrolysis and acidogenesis but delayed methanogenesis [246].
While comparing Figure 3.5b and Figure 3.6b, it is clear that the pH started to improve
favorably from the commencement of methanogenesis because of the subsidence of VFA
concentration and slow dissolution of iron [132]. The acetoclastic route could be the
dominant methanogenic mechanism in the initial period rather than the hydrogenotrophic
production, as the media pH appeared to be in the acidic range. However,
hydrogenotrophic CH4 production would have prevailed when pH in R3 increased [247].
Likewise, in the anaerobic systems with high NH3 concentration, methanogenesis shifts
from acetoclastic to hydrogenotropic pathway [245,248]. So, in this study, the
acetoclastic species contributed much toward initial biogas production and eventually
turned to hydrogenotropic methanogenesis. Here, the conductive nanocomposite
persuaded the methanogenic pathway by supporting electron transport rather than with
the mere assistance of hydrogen [133]. As shown in Figure 3.7a, though VFA
accumulation was consistent in R1, high NZVI caused the generation of more OH
-
and
thus buffered the reactor from day 6 [132]. However, the variation of mixed liquor pH in
70

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
R2 and R4 was insignificant. This could be attributed to the cumulative effect of the
VFAs and the mineralization of nitrogen and phosphorus into nitrites/nitrates and
orthophosphates [249].
4
8
12
00.51234567891011121314172024283236
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250
500
750
1000
250
500
750
10000
250
500
750
10000
250
500
750
10000
250
500
750
1000
R4
R3
R2
R1
V
F
A
C
o
n
c
e
n
tr
a
tio
n
(m
g
/L
)
Control
Time (Days)

00.51234567891011121314172024283236
0
50
100
0
50
100
0
50
100
0
50
100
0
50
100
R1
F
e
2
+

C
o
n
c
e
n
tr
a
tio
n
(m
g
/L
)
Time (days)

R2

R3

R4

Control
4
8
12
Control
4
8
12
R1
C
o
n
d
u
c
tiv
ity
(m
S
/c
m
)
4
8
12
R2
4
8
12
R3
4
8
12
R4
a) b)
Figure 3.18 VFA concentration (a) and Fe
2+
release and conductivity of the media (b) in
digesters throughout the digestion
Conductivity is an indirect measure of dissolved ions in a solution. The incubation of
anaerobic media with suspended RGO-NZVI composite for a long duration has caused
the leaching of iron into the liquid phase. At the end of the batch study, the concentration
of Fe
2+
was proportional to the iron ratio in the nanocomposite added, as shown in Figure
3.7b. The final concentrations were 99.53±4.1, 91.12±3.7, 76.01±2.3, 69.41±2.1 and
25.01±1.2 mg L
-1
in R1, R2, R3, R4 and control, respectively. The iron released into the
control reactor could be due to the mineralization of biomass containing iron, such as
plant-based cattle feed in cow dung [250]. The Fe
2+
concentration in other reactors would
be cumulative of leaching from the composite and co-release while mineralization of
biomass [249]. Figure 3.6b also contains the variation in conductivity measured during
the digestion in each of the digesters. Noticeably, the VFA concentration also influenced
the ionic density, increasing conductivity [251].
71

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
0 3 8 17 36
0
300
600
9000
300
600
9000
300
600
9000
300
600
9000
300
600
900
V
F
A
C
o
n
cen
tra
tio
n
(m
g
/L
)
Time (days)
acetic
propionic
butyric
valeric

R3
Control
R1
R2
R4

-
1
.
5
-
1
-
0
.
5 0
0
.
5 1
1
.
5
-0.01
0
0.01
0.02
0.03
C
u
r
r
e
n
t
(
A
/
c
m
2
)
Voltage (V)
Control
R3
024681012141618202224262830323436
0
2000
4000
6000
8000
10000
12000
14000
C
u
m
u
l
a
t
i
v
e

C
H4
(
m
L
)
Time (days)
R1
R2
R3
R4
B
3841.8
1358.2
2802.8
2892.5
2062.4
a)
c)
b)
Figure 3.19 Electrochemical behavior of sludge material by cyclic voltammetry (a), the
concentration of individual VFA accumulated during anaerobic digestion (b) and
cumulative CH4 produced from each batch reactor (c)
3.3.4 NH3 production during anaerobic digestion
NH3 is an inhibitory byproduct of anaerobic digestion. NH4
+
is relatively harmless to the
microorganisms in the biogas process and beneficial at concentrations less than 200 mg
L
-1
. The existence of NH3 in an ionized form is highly pH-dependent. At low pH, more
NH3 will be ionized to form NH4
+
[235]. Figure 3.9 depicts the production of NH4
+
in the
liquid media during microbial activity. In the case of R1, NH4
+
concentration was less
during the initial digestion period and since then, there has been a prominent rate of
increase in the ionic form of NH3. This high concentration of NH3 in R1 gives a glimpse
of the inhibition of microbial activity by NH3, resulting in less CH4 production [248]. The
reduced concentration of NH3 during the initial startup period might be due to the low
mineralization and ammonification of nitrogenous substrates such as amino acids,
proteins, uric acid and fat [133]. Further, the rising NH4
+
probably caused excessive
72

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
randomness of gene expressions influencing the energy metabolism and signal
transduction during microbial digestion in R1 [248].
On the other hand, NH4
+
concentrations in R2, R3 and R4 abruptly increased when pH
was reduced, but a rise in pH later on did not reduce the NH4
+
concentration [235]. The
combined effect of degradative evolution and the formation of the NH3-phosphate
complex would have played a role in maintaining the level in R3 [252]. By the end of the
digestion, the control reactor contained 1753.81 ± 54.3 mg L
-1
of NH3. By this, the overall
NH4
+
solubilization in R2, R3 and R4 was 41.2 ± 1.1%, 50.08 ± 2.9% and 42.39 ± 1.6%
less than control, respectively. NZVI in aqueous media reduces nitrate concentration by
forming nitrite and NH3[124]. The possibility of degradation of EPS and other
cytoplasmic organs in the debris of microbial biomass (due to NZVI inhibition) might
have contributed to the high nitrogen content, which is high in proteins and contribute to
ammonification in R1[253].
00.51234567891011121314172024283236
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5
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1
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0
1
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0
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024681012141618202224262830323436
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0
0 R1
GMP
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EXP
R2
GMP
R2
EXP
R3
GMP
R3
EXP
R4
GMP
R4
EXP
Control
GMP
Control
EXP
C
H
4
P
r
o
d
u
c
t
io
n
(
m
L
)
Time (days)
N
H
4
+
C
o
n
c
e
n
t
r
a
t
i
o
n

(
m
g
L
-
1
)
Time (days)
R1
R2
R3
R4
Control
a) b)
Figure 3.20 NH4
+
accumulation (a) and nonlinear curve fit of experimental data to
modified Gompertz model
3.4Kinetics of biomethane generation
The experimental space of anaerobic digestion of dairy wastewater fitted well to the
modified Gompertz equation and the parameters of nonlinear fitting are provided in
Table 3.2. Adding the nanocomposite in an RGO to NZVI ratio of 2:1 enhanced the CH4
production rate up to 86.4 ± 1.6% compared to the control digester. The control showed
73

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
better production by 52.18 ± 1.8% than R1 due to the possible iron toxicity imparted
towards methanogenesis. According to the model, the difference in the lag phase time (λ)
calculated for each digester is insignificant. However, the values of λ varied as
R3>R4>control>R2>R1, providing no inference regarding the influence of additives on
λ. This result contradicts the observations by Abdelsalam et al., 2017, who stated that iron
additives reduced the lag phase compared to the control [254]. According to the model,
the daily CH4 yield was highest in R3, with 42.66 ± 1.1% more than the control and
lowest in R1, with 34.47 ± 1.2% less than the control digester. Figure 3.9b depicts the
nonlinear fitting of experimental and calculated CH4 production. The near to unity values
of R
2
and suitable regression parameters demonstrate that the model can fit well and
describe the CH4 volumes obtained from the experiments. The higher peaks of R3
compared to the control reactor in the cyclic voltammetry curve implied that the
conductive molecules may activate the redox reactions among the species and substrate
molecules and mediate the electron shuttle [85]. Though higher quantities of the
conductive conduits impart better electron transport, biocompatibility is a factor that
needs to be considered when applied for microbial co-digestion. Faster redox reactions
with less trouble of toxicity and improved electron shuttle exhibited in R3 make it a
better anaerobic digestion environment. In this study, the optimum ratio of RGO and
NZVI was concluded to be 2:1.
Table 3.13 Modified Gompertz model fitting parameters.
Model
parameter
M0, exp (mL) M0 (mL) Rmax (mL/day)λ (Day) R
2
R1 1358.15±40 1344.35 ± 12137.33± 42.13 ± 0.10.996
R2 2892.5±57.852873.61± 21.46241.08 ± 5.372.15± 0.120.998
R3 3841.8±188.243814.35 ± 28.33365.51± 8.902.56 ± 0.120.998
R4 2802.8±70.072786.35 ± 18.29264.64± 5.662.22± 0.110.998
Control2062.4±72.252045.82 ± 13.43209.57± 4.742.18 ± 0.110.998
Dairy wastewater contains large quantities of fats and proteins, nitrogen-rich substrates.
At higher temperatures, the dissolution of organic nitrogen increases; thus, the release
74

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
rate of nitrogen might be unfavorable for maintaining the C/N ratio to get optimum
performance. High temperatures may increase the chances of deionizing ammonium to
form NH3, which is harmful and toxic [85]. So, mesophilic digestion is desirable in the
case of dairy wastewater degradation. Also, dairy wastewater as a substrate holds the
potential to enrich the digestate with nitrogen released from proteins and fats and produce
a nutritious biofertilizer [255].
3.5Effects of RGO-NZVI composite on Microorganisms
The most abundant and representative populations of microbes present in R3 and control
digesters are given in Figure 3.10. The species-wise classification showed that
Methanosaeta, Methanosarcinales and Methanobrevibacter were the most frequent
groups in R3 and the major CH4 contributors belonging to archaea. The control showed
the presence of more hydrogenotrophic methanogens, Methanobrevibacter,
Methanoculleus and Methanocorpusculum. The relative abundance of Methanosaeta and
Methanosarcinales demonstrates the possibility of their participation in DIET for CH4
production in R3 rather than being produced from the hydrogenotrophic pathway. The
high volume of CH4 made from R3 is relatable to this phenomenon with heavy-duty
methanogens such as Methanosaeta and Methanosarcinales. The enrichment of hydrogen
consumer, Methanobrevibacter in R3 could be attributed to the amendment of NZVI,
which is in agreement with the previous reports [122,256]. It is reported that certain
species belonging to Methanobacter could also participate in DIET, which is usually
considered hydrogenotrophs [106]. So, species such as Methanobrevibacter millerae
would have also contributed to CH4 via DIET. R3 was also rich in sulfate and iron-
reducing bacteria such as Desulfovibrio, Desulfotomaculum, Desulfitobacterium and
Desulfofundulus, which are active in DIET. For example, abundant Desulfotomaculum-
ferrireducens participate in DIET with high gene expression for c-type cytochromes
[257,258].
75

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Control
R
e
la
t
iv
e
a
b
u
n
d
a
n
c
e
Methanobrevibacter-sp.-
YE315
Methanoculleus-bourgensis
Methanocorpusculum-
labreanum
Methanosphaerula-palustris
Methanosarcinales-archaeon-
ANME-2c-ERB4
Methanoculleus-chikugoensis
Clostridium-sp.-SY8519
Thermoclostridium-
stercorarium
Clostridium-sp.-JN-9
Clostridium-taeniosporum
Clostridium-carboxidivorans
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
R3
R
e
la
t
iv
e
a
b
u
n
d
a
n
c
e
Methanosaeta-harundinacea
Methanosarcinales-archaeon-
ANME-2c-ERB4-
Methanobrevibacter-smithii
Methanobrevibacter-sp.-
YE315
Megasphaera-elsdenii
Clostridium-
saccharobutylicum
Clostridium-sp.-C1
Clostridium-sp.-CT4
Clostridium-sporogenes
Clostridium-gasigenes
Methanocorpusculum-
labreanum
a) b)
Figure 3.21 Relative abundance of main archaeal and bacterial species in R3 (a) and
control digesters (b)
The existence of an interspecies electron channel by attracting the conductive composite
is confirmed by the expression of iron complex receptor protein, as shown separately for
R3 and Control in Figure 3.11a. The dominance in the expression of peptide binding
protein in R3 shows that the amyloid protein on the cell surface binds to the RGO-NZVI
composite with the binding protein and facilitates the direct electron transfer for
Methanosaeta [87]. The presence of ferrous ion transport protein indicates the active role
of iron in microbial activities. A longer band in R3 hints about the enrichment in genes
for ferrous ion transport protein. So, the addition of RGO-NZVI has influenced the
expression of these genes positively to enhance the electrical properties. In addition to
assisting in methanogenesis, ferrous ions could also have engaged in gene regulation and
nucleic acid synthesis [259]. Further, the frequency of genes for the expression of
pyruvate-ferredoxin oxidoreductase (PFOR), a chief enzyme in anaerobic metabolism,
was highest in R3. The formation of low-potential ferredoxins helps with electron
transport and hydrogen evolution. Also, Desulfovibrio has been a dynamic organism in
ferredoxin activity [260]. Another organism, Magnetospirillum, appeared in R3, which
hints about the alteration of microbial population upon adding iron [261]. Future studies
would be necessary to understand the effect of magnetic field in the proliferation of
species in an anaerobic digester supplemented with RGO-NZVI.
76

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
DNA primase [EC:2.7.7.101]
Preprotein translocase subunit SecA [EC:7.4.2.8]
Cell division protease FtsH [EC:3.4.24.-]
Diguanylate cyclase [EC:2.7.7.65]
Pyruvate-ferredoxin/flavodoxin oxidoreductase [EC:1.2.7.1 1.2.7.-]
Putative ABC transport system permease
Beta-galactosidase [EC:3.2.1.23]
Peptide/nickel transport system substrate-binding protein
Ferrous iron transport protein B
Ribonucleoside-triphosphate reductase (formate) [EC:1.1.98.6]
Elongation factor G
Type I restriction enzyme, R[EC:3.1.21.3]
Excinuclease ABC subunit A
Site-specific DNA recombinase
Iron complex outermembrane recepter protein
Beta-glucosidase [EC:3.2.1.21]
ATP-binding cassette, subfamily B, multidrugpump
TonB-dependent starch-binding outer membrane protein
Uncharacterized protein
Starch-binding outer membrane protein, SusD/RagB
0 50 100 150 200
21.8%
20.4%
18.4%
3.6%
1.9%1.8%
31.4%
Lentisphaerae
Phixviricota
Chloroflexi
Fusobacteria
Verrucomicrobia
Streptophyta
Tenericutes
Fibrobacteres
Spirochaetes
Others
Actinobacteria
Bacteroidetes
Firmicutes
Proteobacteria
Euryarchaeota
24.2%
23.5%
10.4%
4.6%
3%
1%
2.1%
30.2%
Others
Tenericutes
Verrucomicrobia
Fibrobacteres
Spirochaetes
Actinobacteria
Uroviricota
Bacteroidetes
Euryarchaeota
Proteobacteria
Firmicutes
0%
Number of genes
R3
Control
a)a)a)
b) c)
Figure 3.22 The abundance of genes for major functionalities observed (a), phylum-level
classification of microbes observed in control digester (b) and R3 (c)
Figures 3.11b and c show the phylum-level classification of the microbes identified. The
introduction of RGO-NZVI additive to the anaerobic digester diversified the microbial
population compared to the control, with a 63.3% more count of microbial species in R3.
The phylum euryarchaeota was the highest in R3, whereas firmicutes dominated in the
control digester. The dominance of firmicutes refers to efficient hydrolysis followed by
hindered methanogenesis. The rise of VFAs in control could be due to this suppression of
methanogens [262]. In total, 234 genera of microbes were identified in R3 and 156 in
control. Clostridium, followed by Acidaminococcus, hydrolytic bacteriae, appeared as the
significant genera of bacteria in R3, accounting for 16.47% and 3.59%, respectively.
Also, the control digester favored Clostridium and Prevotella as dominant genera with
13.58% and 3.54%, respectively. The abundance of firmicutes was reduced in R3
compared to the control, probably due to the iron spike in the media [263]. Another
bacterial species, Escherichia, an indicator organism, appeared in both reactors. The
77

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
numbers were lesser in R3 than in the control, inferring the inactivation of indicator
organisms in the presence of NZVI [264]. However, a report by Kim et al., 2018 says that
the presence of Escherichia could have assisted in the fermentation of organic pollutants
during digestion and produced intermediates for CH4 generation [265].
These results suggest that the amendment of conductive additives into the digester helped
improve the spatial diversity of microbial species' positively affecting organic waste
degradation. Furthermore, the DIET was aided and enhanced by adding RGO-NZVI
composite into the media.
3.6Demonstration of the effect of additive in EGSB continuous reactor
Figure 3.12 shows the
laboratory-scale setup of the
EGSB reactor. The
performance of the reactor
while treating dairy wastewater
for 180 days is shown in
Figure 3.13. During Phase I,
the removal of organics steadily
increased until the start of
Phase II. There was a slight
decrease in SCOD removal
efficiency at the beginning of
Phase II and later improved to
reach the steady efficiency shown in Phase I. This is an indication of low performance
due to shock load. The system could not retain the efficiency when a higher OLR was
given. After acclimatization, the tolerant microbial population adapted to the organics
present in the dairy wastewater. So, there was not much fluctuation in SCOD removal
during Phase I. Similar results were observed while measuring the product gas. After 30
days, the CH4 and biogas volume decreased. But, when the system reached equilibrium,
the gas production resumed. The reactors’s performance improved when RGO-NZVI
composite was added. From day 81 onwards % SCOD removal was improved sharply to
78
Figure 3.23 Laboratory set-up of EGSB reactor

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
reach a stable removal performance. Similarly, biogas production and CH4 volume
increased considerably. While, the residual VFA concentration declined from the day of
the commencement of Phase III, fluctuations in pH were stabilized since Phase III. A
substantial decrement in NH4
+
could also be observed during this period. The effect of
shock load is visible in the pattern of NH4
+
formation also. The stable operation during
Phase I brought NH4
+
formation to a plateau. But, after increasing the OLR, NH4
+
formation started. Here, the most important fact is that an increase of OLR at the end of
Phase III has not lowered the performance of the reactor. This might be achieved due to
the assistance of RGO-NZVI mediated electron transfer and microbial enrichment. As
explained in the batch studies, the community was enriched with more electroactive and
methanogenic species in the presence of RGO-NZVI additive. So, VFA consumption was
improved and thus the accumulation decreased. But, when the OLR was increased at the
start of Phase IV, VFA concentration slightly increased, yet, stayed below the level that
was exhibited during Phase III. Likewise, the trend of NH4
+
concentration was slightly
upwards from day 130 till day 140 and after attaining a peak concentration of 295.08 mg
L
-1
, it reduced to the level that was shown at the steady state of Phase III. After the
addition of RGO-NZVI, the fluctuation in the pH was minimal and stayed within a
favorable range.
By observing all the results, it could be concluded that the addition of composites in the
continuous system has good prospects for improving the system performance. Gas
formation and removal of organics were enhanced. Moreover, the additives helped in
maintaining favorable environmental conditions for the further operation of the reactor.
But, here the behavior of the reactor with and without further addition of the composites
needs to be studied. Similarly, the effect of conductive materials in the long-term
operation also needs to be observed.
79

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
0 30 60 90 120 150 180
0
10
20
30
40
50
60
70
80
%
S
C
O
D
r
e
m
o
v
a
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Phase IPhase II Phase IIIPhase IV
0 30 60 90 120 150 180
0
200
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600
800
1000
Biogas
CH
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a
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m
e
(
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L
)
0
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H
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(
m
L
)
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i
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a
l
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F
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(
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-
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)

Time (day)
0 30 60 90 120 150 180
6
6.2
6.4
6.6
6.8
7
7.2
7.4
7.6
p
H
Time (day)
a) b)
c)
a)
d)
e)
c)
0 30 60 90 120 150 180
0
100
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400
N
H
4
+
c
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n
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e
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t
r
a
t
i
o
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(
m
g
L
-
1
)
Time (day)
0 30 60 90 120 150 180
0
5
10
15
20
25
30
F
e
2
+
C
o
n
c
e
n
t
r
a
t
i
o
n

(
m
g
L
-
1
)
Time (day)
Figure 3.24 Performance of EGSB reactor and properties of the effluent.
80

Chapter 3: RGO-NZVI assisted dairy wastewater degradation
3.7Conclusions
In the present study, a demonstration of enhanced CH4 production from dairy wastewater
by adding RGO-NZVI composite was conducted. The results implied that the conductive
additives helped improve biogas production and reduce the organic load in dairy
wastewater by mediating the electron transport between functional microbial species.
Here, the attached growth of microbial biomass onto the conductive supplement ensured
the optimum utilization of available substrates. The simultaneous digestion in the
presence of various ratios of the conductive materials showed that the outcomes of the
RGO-NZVI composite addition into anaerobic digestion are dose-dependent and may
cause inhibitory effects in the system at higher NZVI dosages. Further, the NH4
+
concentration played an essential part in the reactor, which exhibited inhibition in low-
efficiency reactors. The analysis of the microbial community revealed that the abundance
and diversity of methanogenic species could be altered by the conductive composites
added. Further, continuous anaerobic digestion in the EGSB reactor showed remarkable
performance after reaching equilibrium. The SCOD removal and CH4 production has
reached a steady rate during Phase IV. So, the addition of RGO-NZVI composite is
beneficial for degradation, when incorporated into an anaerobic system handling high-fat
waste.
81

Chapter 4
Photocatalytic pretreatment of dairy wastewater
and benefits of the photocatalyst as an enhancer of
anaerobic digestion
VB
CB
e-
e-
e-
e-
e-
e-
+++++
Dairy wastewater
LED Light Source
RGO-NZVI
nanocatalyst
e-
e-
e-
e-
e-
e-
e-
e-
CH
4+CO
2Pretreated
wastewater
Spent catalyst Electroactive
microbes
Treated
wastewater

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
4.1Preface
As observed in the previous chapter, RGO-NZVI has positive impacts on anaerobic
digestion. Also, RGO and NZVI have photocatalytic properties, which may be employed
for pretreating dairy wastewater to facilitate faster solubilization of substrates. This study
evaluated the practicability of RGO-NZVI catalyst to mediate both photocatalytic
pretreatment and biological process. For this, the composite catalyst was employed
initially for the photodegradation of dairy wastewater. After attaining partial
solubilization of organic substrates in dairy wastewater, the pretreated dairy wastewater
containing RGO-NZVI was anaerobically digested. This integrated process incorporating
photocatalysis and anaerobic degradation for dairy wastewater treatment was expected to
reduce the lag time of acetogenesis. The system was assessed for its efficiency in
enhancing biogas production and methane enrichment from pretreated dairy wastewater.
The efficiency of the spent catalyst after pretreatment on biodegradation and waste
valorization was evaluated. Further, the kinetics of the anaerobic digestion of pretreated
wastewater were monitored to see the significance of pretreatment in wastewater
degradation.
4.2Characteristics of spent RGO-NZVI catalyst
The pattern of XRD analysis and Raman spectra of the spent catalyst are provided in
Figure 4.1a and Figure 4.1b, respectively. The characteristic peaks observed at 45.72°
and 65.28° in the XRD pattern of the fresh catalyst disappeared after photocatalytic
degradation. This might be attributed to the leaching of NZVI into the liquid phase and
the oxidation of NZVI during photocatalysis. However, the peaks at 30.73°, 35.32°and
55.03° were preserved, which indicates the oxidized form of iron on the catalyst surface
[53]. The observations showed that the photodegradation of dairy wastewater caused the
catalyst to modify its surface. The Raman spectra exhibited two dominant peaks at 1350
and 1584 cm
-1
which represent D and G peaks of RGO, respectively. The 2D and G+D
peaks were also observed at 2700 and 2932 cm
-1
, respectively. The pattern of spent
catalyst has shown lesser intensity at every peak. Low-intensity curves at 220 and 285
cm
-1
stand for the NZVI molecules, which was not prominent in the case of spent catalyst
[228].
83

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
Further, the variations in the FTIR pattern (Figure 4.1c) were not significant for the spent
catalyst compared to the intact one. Other notable bands at 679 and 825 cm
-1
represented
typical oxides of iron with Fe–O, Fe–O–H bending vibration [53]. Peaks at 2152 and
2983 cm
-1
indicate the alkynes and alkane stretch in the RGO, respectively [53,224].
Moreover, a few minor peaks at 3610 and 3622 cm
-1
stand for the free alcohol stretching
and vibrations [30]. Similarly, the presence of primary and secondary amine, amide
functional groups and isocyanates are shown by the peaks at 1540 cm
-1
and

2270 cm
-1
[239,240]. However, the peak at 1695 cm
-1
, which appeared in

the pattern of fresh
catalyst, has been split into two less intense peaks at 1640 and 1718 cm
-1
. Also, a new
broad peak at 1010 cm
-1
was introduced, representing more C-O groups.
10 20 30 40 50 60 70 80
0 5001000150020002500300035004000
I
n
t
e
n
s
i
t
y

(
a
.
u
.
)
Raman Shift (cm
-1
)
4000350030002500200015001000
T
r
a
n
s
m
i
t
t
a
n
c
e

(
%
)
Wavenumber (cm
-1
)

2q Degrees
I
n
t
e
n
s
i
t
y

(
a
.
u
)
EDC NH S-3.tif
a) b)
c) d) e)
Figure 4.25 The pattern obtained from XRD analysis (a), Raman spectra (b), FTIR image of
the spent catalyst (c), SEM images of RGO-NZVI composite before (d) and after (e)
photocatalysis.
Morphology of RGO-NZVI composite through SEM analysis before and after
photocatalytic degradation has been given in Figures 4.1d and 4.1e. The images implied
that photocatalysis of wastewater using RGO-NZVI catalyst had caused slight
dissociation of carbon layers in RGO. The initial catalytic surface was compact and
84

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
compressed, which after the degradation became a loose pack of carbon layers linked
with weak van-der Waal’s force of interaction. Yet, these loose layers may be beneficial
in biological degradation, giving a more exposed surface area for the attached growth of
microbes and intensifying electron transport.
4.3Optimization of operational conditions of photodegradation
The synthetic dairy wastewater was treated by photocatalysis incorporating an RGO-
NZVI catalyst. The preliminary batch studies showed that the photo-degradative
mineralization increased the SCOD of wastewater for a certain duration. The highest
solubilization was observed after 4 h of photocatalysis, with an increment of 23.51 ±
0.8% SCOD at an initial SCOD of 4850 mg L
-1
. Similarly, DOC increased by 29.97 ±
0.9% at this time. Beyond 4 h, no further solubilization was exhibited because the SCOD
and DOC started to decrease. The pretreatment ceased at this point of maximum SCOD
concentration to gain an economically feasible combination of the two processes. Figure
4.2a shows a slight drop in SCOD concentration until 30 min, possibly due to the rapid
conversion of easily accessible soluble organics.
Generally, the low valence transition metals such as iron help to disrupt O-O bondage in
the peroxy disulfate anions (S2O8
-
) to produce sulfate radicals (SO4·) as per Eqn. 4.1. In
the absence of a catalyst, this breakage requires high energy input because the activation
energy for the reaction is 140.25 kJ [266]. Here, Eqn. 4.1 represents the generation of
highly reactive sulfate radicals from APS, mediated by NZVI catalyst. Similarly, photon-
induced electrons from excited RGO-NZVI catalyst can decompose disulfate ions into
reactive radicals (Eqn 4.2) [15].
Fe
0
+S
2
O
8
2−¿→SO
4
·−¿+Fe
3+¿+SO
4
2−¿¿
¿
¿
¿
4.6
e
−¿+S
2O
8
2−¿→SO
4
·−¿+SO
4
2−¿¿
¿
¿
¿
4.7
Fe
0
+S
2
O
8
2−¿→SO
4
·−¿+Fe
2+¿+SO
4
2−¿¿
¿
¿
¿
4.8
85

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
There is a possibility that air-induced surface corrosion of ZVI produces Fe
2+
and H2O2.
But, studies showed that oxidative degradation of organic compounds by H2O2 in the
presence of ZVI is an inefficient and slow process [266].
0 100 200 300 400 500
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
4 5 6 7 8 9
2000
2500
3000
3500
4000
S
C
O
D
(
m
g

L
-
1
)
pH
SCOD
Initial SCOD
1200
1400
1600
1800
DOC
Initial DOC
D
O
C
(
m
g

L
-
1
)
0 100 200 300 400 500
4000
4500
5000
5500
6000
6500
S
C
O
D
(
m
g

L
-
1
)
Time (min)
SCOD
DOC
1800
2000
2200
2400
2600
2800
3000
D
O
C
(
m
g

L
-
1
)
C
e ( mg/ L)
a) b)
Figure 4.26 Changes in SCOD and DOC with respect to time (pH= 4, dosage= 1 g L
-1
) (a)
and influence of initial pH of the solution (dosage= 1 g L
-1
, time= 4 h) (b)
The effect of initial pH (4-9) on photocatalytic pretreatment was investigated and shown
in Figure 4.2b. It was found that the RGO-NZVI catalyst showed maximum efficiency in
the acidic range. An increase of 38.77±0.85% SCOD and 39.05±1.3% DOC was
measured at an initial pH of 5. However, the solubilization significantly decreased as the
initial pH increased to alkaline. Activation of APS in the acidic region (≤6) favors the
exclusive formation of sulfate radicals; an increase in pH results in the formation of
hydroxyl radicals. But, the abundant OH
-
ions reacted with these active radicals (sulfate
and hydroxyl), reducing the overall degradation kinetics and causing a decline in
solubility [15]. Scavenging of active radicals may also occur with excess metal catalyst
(Eqn 4.3) [15]. In this study, the major part of the iron in the catalyst is zerovalent, which
eventually gets oxidized in the presence of oxygen. So, the scavenging effect could be
neglected during the initial phase of photodegradation. But, as the catalysis progresses,
the generated ferrous ions may start making the radicals unreactive. And thus, a longer
duration of pretreatment may be undesirable due to this effect of ferrous ions.
86

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
Further, as shown in Figure 4.3a, at higher catalyst dosages, viz., above 0.3 g, the
variation in the maximum SCOD concentration was insignificant. Despite having more
free electrons released and facilitation of more conducting channels by a large quantity of
RGO, the lower efficiency of the photodegradation might be due to the reduction of
transmitted light through the solution by scattering the light and blocking the photons.
The deactivation of reactive moieties due to the collision with the ground state molecules
also should have contributed to the lower efficiency of mineralization [267].
Figure 4.3b represents the effect of initial organic loading (as SCOD) on photocatalytic
performance. It was found that an increase in initial organic loading resulted in a decrease
in solubilization efficiency. When the initial SCOD varied from 2200 to 17460 mg L
-1
,
the solubilization efficiency declined from 40.45±1.69% to 6.64±0.2% in terms of
maximum SCOD and 35.5±1.2% to 11.77±0.5% in terms of DOC. At high substrate
concentrations, the number of reactive radicals produced to degrade the organic
compounds might be insufficient [268]. Also, high concentrations of organic compounds
imparted more turbidity and reduced the uniform distribution of light [269]. Reactive
radical scavenging could also occur by the organic radicals formed by the degradation of
complex molecules [266].
0.1 0.2 0.3 0.4 0.5
0
5
10
15
20
25
30
24681012141618
0
10
20
30
40
50
S
C
O
D

i
n
c
r
e
a
s
e

(
%
)
Dosage of RGO-NZVI (g)
a)

S
C
O
D

i
n
c
r
e
a
s
e

(
%
)
Initial sCOD (x 10
3
mg L
-1
)
b)
Figure 4.27 Effect of different catalyst dosage (a) and initial organic loading (b) on
solubilization
4.4Effect of pretreatment on anaerobic digestion
87

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
The pretreated dairy wastewater was digested for 28 days to observe the biogas
production. Figure 4.4a represents the cumulative biogas production on each sampling
day. The highest daily biogas production in D1 and D2 were 335±13.73 and 285±9.97
mL, respectively, on day 4, which was 55.81±2.3% and 32.55±0.8% higher than CD on
the day of most biogas production (day 6 with 215±9.24 mL). The cumulative yields of
biogas from D1 and D2 were 1870±65.45 mL and 1520±59.28 mL, respectively, which
were 31.69±1.05% and 7.14±0.15% more than that obtained from CD (1420±58.22 mL).
Figure 4.4b shows the composition of CH4 in the biogas. Comparing both plots, the daily
CH4 production in D1 and D2 was the highest on day 4, with 90.37±3.8% and
47.05±1.8%, more than the maximum daily yield of CH4 in CD (day 6), respectively.
These results also infer that active methanogenesis began earlier in D1 and D2 than in
CD [111].
0 5 10 1 5 20 25 3 0 35
0
25 0
50 0
75 0
1 000
1234567101316192428
0
20
40
60
80
D1
D2
CD
Time (days)
C
H
4

c
o
m
p
o
s
i
t
i
o
n
(
%
)
0 5 10 15 20 25 30
0
500
1000
1500
2000
D1
D2
CD
C
u
m
u
l
a
t
i
v
e

b
i
o
g
a
s
p
r
o
d
u
c
t
i
o
n

(
m
L
)
Time (days)
a) b)
Figure 4.28 Cumulative volume of biogas produced from each digester (a) and daily CH4
composition of biogas (b)
The high-fat content of dairy wastewater hinders the permeability of cell walls and thus
causes slow hydrolysis and consumption of these compounds in CD [172]. Since
microbial growth and metabolism largely depend upon the soluble substrate
concentration, improved solubility in D1 and D2 showed better performance than CD.
The partial solubilization of organic pollutants helped to reduce the load on the hydrolytic
microbes. Thus, the usual lag time of methanogenesis has been reduced in D1 and D2.
So, it can be further deduced that photocatalytic pretreatment positively influenced biogas
88

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
production. The superior performance of D1 indicates the tremendous advantage of the
amendment of biocatalysts after pretreatment. As explained earlier, during photocatalysis,
the RGO-NZVI catalyst undergoes physicochemical changes and may have affected the
electrical and conductive properties. A slight amendment with fresh catalyst imparted the
advantages of intact conductive additives in D1.
Figure 4.5a shows the performance of digester D1 in removing SCOD. D1 exhibited a
better reduction of SCOD with 72.99±2.84% efficiency until day 28, whereas D2 and CD
showed 67.72±2.91% and 61.08±1.89% of SCOD removal, respectively. Studies reported
the efficient anaerobic digestion of organic substrates with carbonaceous and magnetic
additives [131]. The DIET boost by the presence of conductive moieties in the digestion
system improved CH4 production [132]. In this study, partial solubilization of organic
compounds by photocatalytic pretreatment and the spent catalyst for increased DIET
caused good digestion efficiency regarding SCOD removal and CH4 enrichment. Apart
from this, the influence of the spent catalyst was evaluated through an exclusive digestion
experiment. The total CH4 from this digester was 19.65±0.7% more compared to the
control reactor. Similarly, SCOD removal was superior by 9.5±0.4%.
0 5 10 15 20 25 30 35
0
250
500
750
1000
0 5 10 15 20 25 30
0
20
40
60
80
D1
D2
CD
S
C
O
D
r
e
m
o
v
a
l
(
%
)
Time (days)
1234567101316192428
0
20
40
60
80
F
e
2
+
c
o
n
c
e
n
t
r
a
t
i
o
n
(
m
g
L
-
1
)
Time (days)
D1
D2
CD
a) b)
Figure 4.29 Efficiency in removing SCOD (a) and dissolution of Fe
2+
during the
digestion period (b)
The trend of iron dissolution into the liquid phase during anaerobic digestion is given in
Figure 4.5b. D1 showed a slow increase of Fe
2+
throughout the digestion period.
89

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
However, the variation of Fe
2+
in D2 was insignificant. The decomposition of solids in
cow dung released some Fe
2+
ions due to microbial activity, which caused an increasing
trend in CD. At the start of anaerobic digestion, fresh RGO-NZVI was added to D1, so
the iron dissolution showed an upward trend. However, D2 was not amended with the
catalyst and thus, the existing Fe
2+
concentration did not change significantly.
The concentration of VFA plays a significant role in predicting the efficiency of
anaerobic degradation. High VFA concentrations indicate a slow rate of acetogenesis and
methanogenesis. Also, the downfall in media pH may hamper the growth of microbes.
Figure 4.6a represents the changes in VFA concentration during the digestion of
pretreated dairy wastewater. The larger values indicate a higher rate of hydrolysis and
acidogenesis than aceto- and methanogenesis. The initial phase of acclimatization and
activation of methanogenic microbes causes a delay in converting these acids into acetic
acid, CO2 and CH4. As seen in Figure 4.4b, the high composition of CH4 (71.28±3.06%
and 64.72±2.78% in D1 and D2, respectively) was found on day 4. From this period of
active methanation onwards, the concentration of organic acids started declining. The
depleting substrate concentration caused the total VFA to fall to as low as 51.11±0.66 and
50.82±1.98 mg L
-1
in D1 and D2, respectively. However, due to the delayed
methanogenesis, CD exhibited an increasing pattern of VFA concentration for longer.
From day 6, CD has started showing an eventual decrease in VFA concentration.
90

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
0 5 10 15 20 25 30 35
0
250
500
750
1000
0 5 10 15 20 25 30
0
250
500
750
1000
D1 Exp
D2 Exp
CD Exp
C
u
m
u
la
tiv
e
C
H
4
(m
L
)
Time (days)
D1 model
D2 model
CDmodel
1234567101316192428
0
100
200
300
0
100
200
300
0
100
200
300
T
o
t
a
l
V
F
A

(
m
g
L
-
1
)
Time (days)
CD
D2
D1

a) b)
Figure 4.30 Concentration of VFA (as acetic acid) during the digestion period (a) and
non-linear fitting of experimental data against modified Gompertz model derived data (b)
4.5Modified Gompertz model fitting
Figure 4.6b gives insights into the kinetics of biogas production according to the
modified Gompertz model. The model parameters and correlation coefficient values for
each digester are shown in Table 4.1. Similar to the experimental observations, CH4
produced from D1 was the highest, with 81.01±3.24% more than CD. The CH4
generation from D2 was 38.93±1.1% higher than CD. Further, the daily CH4 production
in D1 and D2 were approximately 1.65 and 0.69 times more than CD, respectively. The
significance of pretreatment could also be explained by examining each reactor's lag
time. Here, CD had much higher values of λ, with an order of λCD> λD2> λD1. Thus, the
solubilization of organic substances by photocatalytic pretreatment caused faster
methanogenesis. Further, the amendment of the biocatalyst aided in reducing λ in D1.
Table 4.14 Comparison of modified Gompertz model parameters obtained from non-
linear fitting of experimental data
91

Chapter 4: Photocatalytic pretreatment and effect of spent catalyst
Digeste
r
M0,exp (mL)M0, model (mL)Rmax (mL/day) λ (day) R
2
D1 971.85±34.01931.25 181.61 1.73 0.998
D2 710.07±15.62714.74 115.56 1.44 0.992
CD 499.86±20.49514.46 68.28 2.22 0.967
4.6Conclusions
This research analyzed the significance of the pretreatment of dairy wastewater through
photocatalysis before biological degradation. The results indicated that photocatalysis
facilitated partial solubilization of organic compounds. After the pretreatment, the spent
photocatalyst has shown efficiency in mediating electron transport during the anaerobic
digestion of dairy wastewater. Also, a slight amendment of the RGO-NZVI composite
before anaerobic digestion caused a significant increase in biogas volume and CH4
composition. Kinetics of biogas production showed that the digester amended with
biocatalyst had 1.65 times more potential for CH4 production than the control digester.
Similarly, the reduction of SCOD from the wastewater was higher in the digester loaded
with pretreated wastewater and catalyst amendment. However, the pretreatment duration
might improve by incorporating high-intensity light. So, from the study, it can be inferred
that photocatalysis is an efficient pretreatment method to improve the biogas production
potential of wastewater. A combined photocatalytic anaerobic digester train in the dairy
wastewater treatment plant would be promising to convert the recalcitrant, fat-rich
organic waste in the wastewater to energy.
92

Chapter 5
A ternary NZVI-polypyrrole composite facilitated
improved anaerobic digestion performance

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
5.1Preface
Previous chapters discussed the conducting environment encouraging microbes to shift
the electron transfer to DIET. DIET influences the physiochemical behavior in the
anaerobic media. Here, the scope of conductive polymer additive such as PPy associated
with NZVI in anaerobic digestion is under-explored. Polymers can assist the anaerobic
process by upgrading reactor performance in terms of SCOD removal and CH4
enrichment. This study evaluated the performance of a ternary conductive composite,
developed from NZVI, polypyrrole and carbon black (Ppy-CB-NZVI) on batch anaerobic
digestion of dairy wastewater at different dosages. Also, the kinetic model fitting was
carried out with the modified Gompertz model to quantify the biomethane production
potential of the projected digester system. This chapter attempted to predict the general
mechanism of Ppy-CB-NZVI action from the kinetic parameter analysis.
5.2Physico-chemical characteristics of the composite
Figure 5.1a represents the XRD pattern of the as-synthesized Ppy-CB-NZVI ternary
composite. The characteristic peak at 2θ = 45.3° and 65.3° represents NZVI. The peak at
24.5° shows the presence of carbon black [270,271]. From this peak, the turbostratic
structure of carbon is shown. The broad curve starting from 22.4° is a characteristic of
amorphous polypyrrole in the sample. This is contributed by the scattering occurring at
the interplanar domain of the Ppy chain [272].
The pattern obtained from Raman analysis is shown in Figure 5.1b. The bands observed
at 1333 cm
-1
and 1596 cm
-1
may be assigned for the D and G bands of Ppy-CB. The band
of disorder could be due to the vibrational aromatic rings, random arrangement of edge
structures and asymmetry in CB structure. A minor peak at 1522 cm
-1
could have been
contributed by Ppy [273,274]. The pair of peaks at 220 and 281 cm
-1
is attributed to the
presence of NZVI in the composite [228].
The important inferences from FTIR spectra of the ternary composite (Figure 5.1c) are as
follows. The peaks at 1587 and 1465 cm
-1
could be assigned to the C-C and C-N
94

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
stretching vibrations, respectively [270]. The broad peak observed between 3000 to 3500
cm
-1
could be ascribed to Fe-O bonding and phenolics, which supports the reduction of
iron oxides to form NZVI. The aromatic C=C stretch and −CH3 group were characterized
by peaks at 2785 and 2848cm
-1
. A narrow peak at 787cm
-1
is due to the oxides of Fe [44].
4000350030002500200015001000
0 500100015002000250030003500
Wavenumber (cm
-1
)
Intensity (a.u
.)
1020304050607080
Ñ
Ñ
ª
In
ten
sity (a.u
)
2q (Degrees)
T
ransm
ittance (%
)
Wavenumber (cm
-1
)
a)
f)
e)
d)
c)
b)
Figure 5.31 Physico-chemical characterization of PPy-CB-NZVI a) XRD pattern, b)
Raman Spectra, c) FTIR spectra, d), e) FESEM images at resolutions 30 µ and 3 µ
respectively and f) images of surface elemental mapping
The morphology of the PPy-CB-NZVI composite was examined from FESEM images
(Figure 5.1d and 5.1e). A thick layer of NZVI deposited on the PPy-CB surface during
95

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
coprecipitation is exhibited in Figure 5.1d. Although the exposed surface area of PPy-CB
is not predominant, the NZVI layer allows the diffusion of liquid media towards the PPy-
CB surface. So, NZVI and PPy-CB together catalyze the transformation of organic
compounds to generate CH4. Figure 5.1f shows the distribution of major elements on the
NZVI-PPy-CB layer. The composite surface is enriched with Fe due to the NZVI
deposition on PPY-CB. Despite the presence of carbon-rich polypyrrole and carbon black
in the composite, the surface elemental mapping showed low carbon and it could be due
to the coverage of the PPy-CB surface by no-carbon NZVI.
5.3Effect of different PPy-CB-NZVI dosages on degradation and
methanogenesis
The effect of the PPy-CB-NZVI composite on the anaerobic digestion of dairy
wastewater is presented in Figure 5.2. Figures 5.2a and b indicates that PPy-CB-NZVI
had a positive influence on the biogas generation and reduction of organic load in the
media. The gas production kept rising and the highest volume recorded was on day 5 in
all the digesters except D1 and D5. The highest volume of biogas was obtained from D3
with a composite dosage of 0.4 g L
-1
, which was 43.27% more than D1 (control digester).
Additionally, D3 showed better CH4 composition throughout the process, with a
maximum CH4 content on day 4 (Figure 5.2c). All the digesters except D1 followed the
same trend, whereas D1 produced maximum CH4 on day 6 and a total volume of 605±21
mL of CH4 until the completion of the process. The highest observed CH4 composition
was 70.23% in D3 and the total CH4 production was about 1085.18 mL which was 1.79
times higher than the control reactor. A cumulative 2185 ± 76 mL of biogas was obtained
from D3, while 1525±64 mL was obtained from D1 during the entire digestion period.
Though D3 exhibited superior performance, the distinction between D3 and D4 was
insignificant. A total of 1004.02±32 mL CH4 was obtained from D4 and the highest CH4
concentration was 68.05±1.4% on day 4. These results show that PPy-CB-NZVI dosage
higher than 0.4 g L
-1
had negligible impact on anaerobic digestion. Higher dosage caused
a slight decline in biogas volume and quality, as seen for D4.
The cumulative volume (739.67±33.6 mL) and composition of CH4 (62.86±2.7% of CH4
on day 4) from D5 was predominant compared to D2, possibly due to the benefits of PPy
96

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
and CB added at high dosage. Whereas D2 produced a total of 1520±65 mL of biogas and
608±21 mL of CH4 until the completion of the digestion period. Qian et al. (2022) have
elaborated on the mechanism of PPy in upgrading anaerobic digestion by adding PPy.
Diversification of microbial community, promoting methylotrophic metabolism,
enhancing acetyl coenzyme and enhanced DIET were proposed to be the possible causes
for CH4 enrichment [95]. Another study showed that PPy could support relatively high
EPS production and better biofilm formation in anaerobic digestion [147]. The lower
dosage of ternary composite in D2 was insufficient to impart its conductive properties
throughout the liquid media, so D2 did not show any significant performance compared
to D1.
The dominant performance of ternary composite-added digesters could be ascribed to the
conductive property of the components. A negatively charged microbial cell surface is
likely to get attracted to the positively charged surface of PPy due to the presence of NH
functional groups [95]. Studies reported the benefits of conductive polymers on the
proliferation of microbial communities, which actively contribute to direct interspecies
electron transport. Zhou et al. (2021) studied polyaniline's effect and found that it can
enrich the DIET microbes effectively [107]. Further, PPy is an excellent adsorbent of
hydrophobic proteins [275]. Notably, acetogens and methanogens are hydrophobic [139].
In this scenario, the proteins adsorbed by NZVI-PPy-CB composite could be easily
accessed and experience direct electron transfer to the microbes. PPy is a conductive
polymer with an ordered macropore structure with high electron affinity [276]. So, the
protein-mediated cell addition facilitates the faster charge transfer between electron-
transferring species. The conductive polymers are also said to stimulate cell responses
with active and favorable surface chemistry towards biological cells. The affinity of the
ternary additive may also improve by this property. As a conjugated polymer, PPy
exhibits unique intrinsic properties and micro-mechanics [275]. Here, the biochemical
electron transfer occurring on the surface of the conjugated polymer partially delocalizes
and creates surface polarons. These surface polarons try to stabilize themselves by
polarizing the surrounding media. This deformation phenomenon of polymer structure
and polarization could benefit digestion [277].
97

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
0 5 10 15 20 25 30 35
0
25 0
50 0
75 0
10 00
0 5 10 15 20 25 30
0
20
40
60
80
S
C
O
D

r
e
m
o
v
a
l

(
%
)
Time (days)
1 2 3 4 5 6 7 10 13 16 19 23 27 31
0
20
40
60
80
D1
D2
D3
D4
D5
Time (days)
C
H
4
c
o
m
p
o
s
i
t
i
o
n
(
%
)
0 5 10 15 20 25 30
0
500
1000
1500
2000
D1
D2
D3
D4
D5
C
u
m
u
l
a
t
i
v
e

b
i
o
g
a
s

p
r
o
d
u
c
t
i
o
n

(
m
L
)
Time (days)
D
a
il
y
b
io
g
a
s
p
r
o
d
u
c
ti
o
n

(L
)
a) b)
c)
Figure 5.32 Performance of anaerobic digesters during 31-day digestion a) cumulative
volume of biogas produced, b) efficiency in removing SCOD, c) CH4 composition in
biogas
PPy-CB-NZVI in D2, D3 and D4 assisted in early methanogenesis compared to the
control digester. Reactor D4 slightly outperformed D3 in SCOD removal from the
wastewater with 74.69±3.2% and 73.79±2.2% efficiency, respectively. Until a digestion
period of 13 days, the degradation of organic substrates was on a steady increase. Later,
the active SCOD removal did not improve much due to the possible deficiency of easily
degradable compounds and reached a plateau. A similar trend of SCOD removal was also
observed, with the highest in D4 and the lowest in D1, which was 22.3% less efficient
than D4. A removal of 58.04±2.2 % was observed in D1. D5 had a better performance of
SCOD removal than D2 and D1, but less than D3 and D4. By the exhaustion of substrates
and limited nutrients, microbial metabolism decreases, thereby, gas production.
98

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
5.4Trend of pH, Fe
2+
, VFA and NH4
+
concentration during the process
When acidic pH prevails in the anaerobic system, H
+
partial pressure increases and
inhibits homotropic metabolism; thereby, CH4 production decreases. But, NZVI, CB and
PPy support DIET, where H
+
is utilized faster than MIET. This phenomenon raises the
media pH. When hydrolysis and acidogenesis are paced up, acid accumulates during the
initial digestion period. The addition of composite improves the acid utilization to
produce acetic acid and acetoclastic pathways to magnify methanogenesis. The system
pH is buffered by adding the ternary composite [95]. At the start of the process, pH
decreased in all the reactors due to the acidification of the organic substrates in the media
(Figure 5.3). This pH decline continued until the active methanogenesis started while the
consumption of VFA increased. More fluctuation in pH was found in D1 compared to
other digestors in the experiment. Similarly, D3 and D4 have shown resistance to pH
fluctuations to a greater extent. This could be due to the buffering effect of PPy-CB-
NZVI in the media.
123456710131619232731
6
6.5
7
6
6.5
7
6
6.5
7
6
6.5
7
6
6.5
7
R1
p
H
Time (days)
R2

R3

R4

R5

c)
D5
D4
D3
D2
D1
Figure 5.33 Trend of pH in the anaerobic digesters during the digestion period
99

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
As shown in Figure 5.4a, Fe
2+
concentration in the liquid media has increased throughout
the digestion process. Higher concentrations were observed in D3 and D4, which implied
the slight leaching of Fe from the PPy-CB-NZVI surface to the slurry. The release of any
oxygen from the carbohydrates in the substrate might react with the Fe
0
to produce higher
valence ions. However, these higher valent iron molecules help form aggregates of
extracellular polymeric substances. EPS aggregates are expected to possess some redox
properties, which could further aid DIET [278]. But, the formation of EPS aggregate has
not been measured in this study. Though the amount of the composite added was more in
D4, the final leached iron concentration in R4 did not significantly differ from that
observed in D3. This specifies that a high degree of media redox reactions caused the
leaching at a high composite dosage [57]. A higher concentration of Fe
2+
found in D5 than
in D1 implies that the PPy-CB could also enhance the degradation of substrates and
release some innate Fe2+ ions in the biomass material.
0 5 10 15 20 25 30 35
0
250
500
750
100 0
123456710131619232731
0
20
40
60
80
100
R1
R2
R3
R4
R5
Time (days)
R
esidual V
F
A

(
m
g L
-1
)
123456710131619232731
0
20
40
60
80
100
F
e
2+
con
cen
tration

(
m
g L
-1
)
Time (days)
R1
R2
R3
R4
R5
D
aily bioga
s p
rod
uc
tio
n (L)
a) a)
b)
D1
D2
D3
D4
D5
D1
D2
D3
D4
D5
Figure 5.34 Leaching of Fe
2+
into the liquid media (a) and VFA accumulation in the
digestors (b)
100

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
Total residual VFA values in the reactors during the digestion period are presented in
Figure 5.4b. The formation of VFA started from the beginning of the process due to the
disintegration of organic substrates by the hydrolytic bacteria. Elevated hydrolysis and
acidogenesis during the initial phase caused higher residual VFA and declined later when
VFA’s were actively utilized for CH4 generation. A comparison of VFA residue reveals
the significance of the PPy-CB-NZVI composite added in D2, D3 and D4. The variation
was in a similar trend in these digestors with the highest accumulation on day 3.
Enhanced hydrolysis accompanied by faster and boosted methanogenesis since day 3 has
caused a decline in VFA concentration thereafter [127]. However, D1’s acid accumulation
continued till day 5 and the peak declined later. This could be attributed to the delayed
methanogenesis compared to the other digesters [134]. Though CH4 was produced during
this initial period in D1, the VFA consumption rate was insufficient compared to the VFA
generation rate. Nevertheless, when the methanogenesis was slowed down, the VFA
started to accumulate in all the digesters. The hydrolysis stage also would have almost
stopped so that some of this accumulated VFA was transformed to CH4, which caused a
downward trend in the VFA concentration. Similarly, the degradable fraction in the media
exhausts after a period, and the cells reach the decline phase unless there is feed addition.
Since no intermittent feed was added, microbial metabolism was reduced, hence CH4
generation [140].
The trend of NH4
+
is given in Figure 5.5a. The concentration in the control digestor kept
increasing until the digestion period ended. This shows the slow ammonification of
nitrogen in the substrates under normal conditions of digestion of dairy wastewater.
However, external enhancing agents caused varied NH4
+
production in the media [279].
The concentrations in D3, D4 and D5 initially increased to reach a peak and then
dropped. However, D2 followed the trend shown by D1 until day 16 and then slightly
reduced. These NH4
+
concentrations indicate that the composite affected the
disintegration of the substrates and controlled the NH4
+
evolution. Dairy waste is a rich
source of nitrogen embedded in the form of proteins. The decomposition of such
compounds liberates nitrogen and is consumed by microbes to form ammonia. In
addition, co-digestion with cow dung facilitates the release of nitrogen and supplements
microbial metabolism. Ultimately, higher nitrogen content in the substrate causes high
101

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
NH4
+
generation. Excess NH4
+
release causes inhibition and subsequent reduction in
process performance and deterioration of biogas quality [280].
123456710131619232731
100
150
200
D1
D2
D3
D4
D5
N
H
4
+

c
o
n
c
e
n
t
r
a
t
i
o
n

(
m
g

L
-
1
)
Time (days)
0 5 10 15 20 25 30
0
250
500
750
1000
D1
D2
D3
D4
D5
C
H
4

p
r
o
d
u
c
e
d

(
m
L
)
Time (days)
a) b)
Figure 5.35 NH4
+
concentration during the digestion (a) non-linear fitting curve for
experimental and model data for methanogenesis (b) and cyclic voltammetry curve of
sludge with and without PPy-CB-NZVI (c)
5.5Kinetics of digestion
The modified Gompertz model suited well for the experimental data of anaerobic
digestion of dairy wastewater with good regression parameters. The calculated model
parameters are given in Table 5.3. According to the model, the cumulative CH4 found in
D3 was 79.16% more than in the control reactor. As observed through experiments, D1
and D2 exhibited almost similar performance. Similarly, here, the effect of PPy-CB-
102

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
NZVI is visible while analyzing the lag phase time found for each digester. By adding the
ternary composite, the delay phase was reduced. However, after examining the values of
λ, it is clear that the composite dosage did not have much significance.
The better performance of ternary composite-laden digestors could be due to the boost-up
in the electrochemical behavior of the sludge in the presence of highly conductive
material. Also, polypyrrole’s ability to alter gene expression would have contributed to
better oxidation of compounds. It was proposed that butyrate oxidation can be enhanced
in the presence of PPy [95]. Also, CB is another carbon-conductive material that can
mediate the electron transfer phenomena. The extracellular electron shift process highly
depends on the conductivity of the media. The cyclic voltammetry curve, as shown in
Figure 5.5c, depicts the superior electrochemical property of sludge containing the
polymer composite. During digestion, electrons are released while the conversion of
energy molecules, NAD+ to NADH and FAD to FADH2, occurs. PPy has been proven to
assist and pace up the gene expressions corresponding to these enzymatic reactions.
Hence, the charge transfer mediates the higher production of CH4 through microbial
metabolism [95].
Table 5.15 Modified Gompertz model fitting parameters for digesters
Model
paramete
r
M0, exp (mL) M0 (mL)
Rmax
(mL/day)
λ (day)R
2
D1 605.7±21 589.95±17 86.62±2 2.07±0.040.99
D2 608.5±21 592.7±17 86.68±3 1.85±0.040.99
D3 1085.18±38 1031.26±34 149.84±5 2.01±0.040.99
D4 1004.02±32 950.59±39 138.15±6 2±0.07 0.98
D5 739.67±33 695.46±21 104.54±3 1.87±0.040.99
5.6Conclusions
103

Chapter 5: NZVI-polypyrrole enhanced anaerobic digestion
In this study, a ternary conductive composite made of PPy, CB and NZVI was
synthesized and experimented for intensified anaerobic digestion of dairy wastewater.
Analysis of biogas during the 31-day digestion period showed that the cumulative biogas
production was 60.66% higher in the presence of the PPy-CB-NZVI. Similarly,
74.69±3.2% SCOD removal was observed in the digester containing the composite. The
results of residual VFA analysis and corresponding CH4 generation illustrated that the
ternary additive significantly influenced hydrolysis, fatty acid metabolism and
acetogenesis, leading to higher gas production. The addition of PPy-CB-NZVI to the
digester improved the conductivity of the media and thereby elevating the rate of electron
transport between the methanogenic species.
104

Chapter 6
Magnetic adsorbent developed with alkali-thermal
pretreated biogas slurry solids for the removal of heavy
metals: optimization, kinetic and equilibrium study

Chapter 6: Biogas slurry solids based heavy metal adsorption
6.1Preface
Earlier chapters discussed about the anaerobic wastewater treatment systems. However,
this research would be complete only when there is a mention of handling post treatment
biogas digestate. This chapter discusses an application of biogas slurry solids combined
with INP for physico-chemical wastewater treatment. A low-cost adsorbent was prepared
by magnetic modification of pretreated biogas slurry solids (BSS) to remove heavy
metals such as Cu
2+
, Cd
2+
and Pb
2+
. Given the significant advantages of modification, an
adsorbent (MMPSS) was developed from alkali-thermal pretreated BSS and
magnetization for the adsorption of heavy metal ions such as Cu
2+
, Cd
2+
and Pb
2+
. The
process conditions were optimized for the pretreatment of BSS and magnetization to get
MMPSS adsorbent. Further, the optimization of heavy metal adsorption using the
developed MMPSS adsorbent was conducted by RSM. The parameters of kinetics and
isotherm mathematical models were estimated and analyzed.
6.2Physicochemical Characterization of Adsorbent
Table 6.1 represents the initial characteristics of BSS. The bulk density of an adsorbent
affects the adsorption capacity [281]. Here, a comparatively low bulk density value of
BSS denotes a good porous structure of the material. More than 50% weight loss after
thermal treatment of BSS could be attributed to the digestion of certain complexes, such
as silica, in an alkaline environment [37].
Table 6.16 Physicochemical characteristics of BSS
BSS Properties Measured values
Moisture (%) 9.95
Ash (%) 54.14
Gross Calorific Value (GCV) (KJ kg
-1
) 1771.23
Bulk Density (g mL
-1
) 0.5103
Conductivity (mS) 2.71
Yield after Thermal treatment (wt %)47.25
Cu
2+
(mg kg
-1
)* 5.31
Cd
2+
(mg kg
-1
)* -
Pb
2+
(mg kg
-1
)* 1.15
*mg of heavy metal per kg of BSS
106

Chapter 6: Biogas slurry solids based heavy metal adsorption
Figure 6.1b shows the clear porous surface of PSS with varying dimensions, compared
to BSS (Figure 6.1a), due to the disappearance of complex bulk molecules during
pretreatment. From Figure 6.1c, the particle size of synthesized MIN was observed to be
in a range of 26-80 nm. The surface image of MMPSS contained nano-sized particles in
abundant quantity, which affirms the magnetization of PSS (Figure 6.1d). The irregular
porous morphology of PSS and nano-porous surface structure favors the long path for
heavy metal diffusion [276]. Figure A.1a shows the morphology of MMPSS after
binding to heavy metals. The EDX analysis of PSS and MMPSS is shown in Figures 6.1e
and 6.1f. This revealed that the elements O, S and Ca contributed 67.91%, 15.10% and
8.16% toward the weight of MMPSS, respectively. Yet, the presence of Iron (12.69%)
and Oxygen (55.26%) elements in the case of MMPSS proves that magnetic modification
of the material has been sufficient. As per Figure A.1b, the surface of the spent MMPSS
is characterized by the presence of respective heavy metal ions adsorbed.
Figure 6.36 FE-SEM images of (a) BSS, (b) PSS, (c) MIN and (d) MMPSS and EDX
analysis spectrum of (e) BSS and (f) MMPSS
Figure 6.2a shows the PZC of MMPSS. The influence of PZC in adsorption has been
discussed in detail in section 6.6. According to porosity characteristics given by BET
surface analysis (Table 6.2), BSS had the lowest surface area, thereby limiting the uptake
of metal ions [282]. Visibly, MMPSS had ample surface area concerning BSS, which
107

Chapter 6: Biogas slurry solids based heavy metal adsorption
implied that pretreatment and magnetic modification incremented the adsorption area.
Consequently, adsorption capacity and efficiency got accelerated [198]. The improved
surface area and pore volume could be ascribed to the expansion of pores and
expungement of certain complexes like silica [37]. It can be noted that MIN has the
highest attributes of porosity features which is evident because of its particle size in the
nano-range. But, when it comes to MIN-modified adsorbent, there is a reduction in pore
characteristics. During cross-linking, some of the MIN particles get suspended
(unattached) and washed away; therefore, the quantity of MIN on the surface of MMPSS
would be less than stoichiometry (1:2 ratio). However, MMPSS had an improved total
surface area by 87% compared to BSS. Figure 6.2b represents the adsorption-desorption
isotherm plot for MMPSS.
Table 6.17 BET Characteristics of different materials involved throughout the
development of adsorbent
Adsorbent
Surface area
(m
2
/g)
Pore volume
(cc/g)
BJH Pore
Diameter (nm)
BSS 4.668 0.07 2.993
PSS 29.478 0.52 2.985
MIN 42.7 0.108 4.746
MMPSS 35.881 0.56 3.318
The magnetic property of MIN and MMPSS was studied at room temperature in a field
strength of ±15,000G. The S-shaped symmetrical curve showed no significant remanence
or coercivity retained (Figure 6.2c and d). Therefore, the adsorbent developed has
superparamagnetic behavior [204]. The separation of solids was visibly fast when the
aqueous solution containing the adsorbent was brought into an external magnetic field.
This shows that MMPSS adsorbent can be effectively conserved with less material loss
when used for the continuous adsorption process.
108

Chapter 6: Biogas slurry solids based heavy metal adsorption
-20000 -10000 0 10000 20000
-1.2
-0.6
0
0.6
1.2
-1.2
-0.6
0
0.6
1.2

M
a
g
n
e
t
ic
F
lu
x
D
e
n
s
it
y
, B
(
e
m
u
)
Magnetic Field Intensity, H c
(Oe)
MMPSS

MIN
01234567891011
-3
-2
-1
0
1
2
3
D
p
H
pH
pHpzc= 3.5
0.0 0.2 0.4 0.6 0.8 1.0
0
5
10
15
20
25
30
35
40

Adsorption
Desorption
V
o
l
u
m
e

@

S
T
P

(
c
c
/
g
)
Relative Pressure (P/P
o
)
a)
d)
c)
b)
Figure 6.37 Characteristics of MMPSS: PZC (a), BET adsorption-desorption (b), VSM
plot of MIN (c) and MMPSS (d)
Figure 6.3 shows the XRD pattern of BSS, PSS, MIN, intact and spent MMPSS. The
pattern for BSS showed less intense peaks, which indicated the amorphous or anisotropic
nature of sludge [283]. The single narrow peak at a 2θ value of 30.98
o
could be attributed
to the presence of silicon dioxide, which was confirmed by EDX analysis. After alkali-
thermal treatment, a narrower peak at 57.59
o
was introduced. Moreover, this amorphous
nature of the adsorbent caused enhanced adsorption efficiency [284]. Pattern for MIN
shows the typical crystal structure of magnetite nanoparticles with characteristic
diffraction peaks at 30.14
o
, 36.51
o
, 45.54
o
, 58.06
o
, 62.50
o
and 69.35
o
[285]. The plot of
MMPSS showed peaks corresponding to PSS and MIN. The peaks at 31.08° and 61.43°
represent the base material PSS. But, there was a shift in peaks observed with reduced
intensity. The cross-linking and weak chemical transformation could be the probable
reason for this shift [286]. However, the highest peaks at 35.67° and 41.68° disappeared
109

Chapter 6: Biogas slurry solids based heavy metal adsorption
from the pattern of spent adsorbent. This proves that structural changes were predominant
during the adsorption process. It was revealed that the crystal structure of MIN in
MMPSS was not altered after adsorption; thus, the role of nanoparticles in the process
was insignificant. The pattern of MMPSS after adsorption showed peaks at 12.37°,
25.42° representing the formation of copper complex and 25.47 and 27.03° for lead-based
complex formation [287].
Figure 6.38 XRD and FTIR spectra of BSS, PSS, MIN and MMPSS adsorbent (intact
and spent)
To verify the functionalization and magnetic modification, FTIR analysis was conducted
and the spectra obtained are shown in Figure 6.3b for BSS, MIN, PSS and MMPSS. For
BSS, the peak at 1036 cm
-1
stands for primary alcohol that occurred during anaerobic
fermentation. The peak that appeared in the range 1634-1645 cm
-1
is ascribed to simple
non-cyclic, monosubstituted alkene (C=H) along with amides. Whereas the less intensity
peak at 787 cm
-1
represented out-of-plane bending of alkene [288,289]. The spectrum of
PSS contained the peak 785 cm
-1
with reduced intensity and showed a slight shift of peak
110

Chapter 6: Biogas slurry solids based heavy metal adsorption
at 1003 cm
-1
. An additional peak was introduced at 3630 cm
-1
, representing free alcohol
due to alkali treatment. The broad peaks observed at 1450 cm
-1
and 1638 cm
-1
could be
due to the transformation of alkene and amide to show the –CH3 bend and amine (-NH)
bend. In the case of MIN, there was a strong peak at 575 cm
-1
,

which indicates Fe-O
vibrations of Fe3O4.
Additionally, the peak at 1400 cm
-1
and 3400 cm
-1
could be attributed to OH bending and
OH stretching, respectively, which probably occurred from oxidation [285]. The peak at
1630 cm
-1
in the spectra denotes -NH bending, possibly due to the amino groups adsorbed
during synthesis. The spectra of MMPSS showed similar peaks compared to PSS at 1004
cm
-1
. Similarly, it also had characteristic peaks at 1532 cm
-1
for the nitro (R-NO2) group,
1700 cm
-1
denoting carboxylic acid (-COOH) and amide (-N-H). A weak intensity peak at
2180 cm
-1
may be due to the alkyne group. Modification of BSS aided in the addition of
the alcohol group, which was further confirmed by a peak at 3700 cm
-1
. The spectra of
MMPSS confirmed the crosslinking of MIN onto PSS. Introduction of new peaks was
observed in the case of spent adsorbent in ranges 2780-3010 cm
-1
showing saturated
alkane stretch, 3340-3400 cm
-1
for H bonds formed while complexing and 2280 cm
-1
for
cyanates.
6.3Optimization of the conditions of pretreatment
A molecule's kinetic energy depends on the system's temperature [290]. Also, as reported
in the literature, the swelling power of bio-sorbents increases with the temperature rise,
further enhancing the penetration ability [291]. In the batch experiments, the adsorption
capacity improved with an increase in the temperature of pretreatment and declined
beyond 423 K (Figure 6.4a). The adsorption capacity of MMPSS varied as
Cu
2+
>Cd
2+
>Pb
2+
with values of 13.18±0.4 mg g
-1
, 12.28±0.3 mg g
-1
and 11.55±0.3 mg g
-1
,
respectively. Adsorbents developed in the presence of KOH showed better adsorption
capacity than the control. This could be attributed to the functionalization of the
adsorbent surface with the hydroxyl (OH
-
) group, which enhanced affinity towards metal
ions [292]. Higher temperature facilitates better diffusion of hydroxyl ions into the bulk
matrix and produces functionalized adsorbent [293].
111

Chapter 6: Biogas slurry solids based heavy metal adsorption
The time dependence of adsorption capacity has been reported in Figure 6.4b. When the
heating time increased, there was a significant increase in the adsorption capacity. Longer
contact time facilitated more diffusion of KOH molecules into the micropores present on
BSS [294]. The increment in adsorption capacity existed till the heating time of 1.5 h.
Beyond a particular heating time, pores get shrunk and pore volume reduces, decreasing
the capacity and increasing the pretreatment cost [295].
Figure 6.4c represents the variation in the surface property of PSS with a change in the
volume of KOH. The interaction of KOH caused surface functionalization of adsorbent
[296], for which the optimum ratio was found to be 1:10 with adsorption capacities of
16.36±0.5, 15.83±0.5 and 14.64±0.4 mg g
-1
for Cu
2+
, Cd
2+
and Pb
2+
respectively. When
the ratio was decreased from 1:2.5 to 1:10, there was an almost linear increment in
adsorption capacity. The addition of a larger reagent volume caused more KOH
molecules in contact with BSS; heating at a high temperature caused water evaporation
and thereby concentrated KOH. A high concentration of KOH results in the
reconstruction of micropores by hydrolysis, causing the degradation of impurities that
play the least role in adsorption [297]. When the ratio was further decreased to 1:25, the
number of metals adsorbed was reduced. More nucleophilic interactions result in the
disappearance of certain porous materials that were prominent in adsorption [294].
The potential of MIN crosslinked to PSS for heavy metal adsorption has been given in
Figure 6.4d. There was an increment in adsorption capacity when the ratio of MIN to
PSS varied from 1:10 to 1:1. Magnetite efficiently adsorbs metal ions to its surface with
its high surface area and magnetic property. The surface area of the adsorbent is
proportional to the quantity of nanoparticles added [43]. But, the difference in adsorption
capacities of adsorbents prepared at a ratio of 1:2 and 1:1 was not significant. The
maximum adsorption capacity obtained was 18.26±0.6 mg g
-1
, 19.86±0.8 mg g
-1
and
19.66±0.7 mg g
-1
for Pb
2+
, Cu
2+
and Cd
2+,
respectively.
112

Chapter 6: Biogas slurry solids based heavy metal adsorption
300325350375400425450475500
6.4
8
9.6
11.2
6.9
9.2
11.5
13.8
1:11:21:31:41:51:61:71:81:91:10
14
15
16
17
18
19
20

A
d
s
o
r
p
t
i
o
n
C
a
p
a
c
i
t
y
(
m
g
/
g
)
MIN to PSS ratio (w/w)
Pb
Cu
Cd
1:2.51:51:7.51:101:12.51:151:17.51:201:22.51:25
10
11
12
13
14
15
16
17

A
d
s
o
r
p
t
i
o
n

C
a
p
a
c
i
t
y

(
m
g
/
g
)
BSS to KOH ratio (w/v)
Pb
Cu
Cd

A
d
s
o
r
p
t
i
o
n

C
a
p
a
c
i
t
y

(
m
g
/
g
)
Temperature (K)
0.5 1 1.5 2 2.5 3 3.5
6
8
10
12
14
16

A
d
s
o
r
p
t
i
o
n

C
a
p
a
c
i
t
y

(
m
g
/
g
)
Time (hr)
Pb
Cd
Cu
Control

Pb
Cd
Cu
MMPSSa) b)
c) d)
Figure 6.39 Variation in adsorption capacity of adsorbent with respect to pretreatment
temperatures (a), time (b), BSS to KOH ratios (c) and different MIN to PSS ratios (d)
6.4Optimization of adsorption using RSM
Numerical values assigned in design corresponding to each Influencing parameter (A, B,
C and D) and responses for adsorption of three different heavy metal ions are presented in
Table 6.3. ANOVA for all the regressions was carried out to see the significance under a
confidence interval of 95% (Table 6.4). The relevance of each variable was marked out
after analyzing the p-value and F-value. Statistical models corresponding to the responses
for all heavy metals Cu
2+
, Pb
2+
and Cd
2+
were significant, with all sequential p values
<0.05 and lack of fit p value >0.05. The insignificant lack of fit values indicates that the
model is valid for the given experimental parameters and the correlation between process
113

Chapter 6: Biogas slurry solids based heavy metal adsorption
variables and adsorption capacity is significant [298,299]. Considering all the other
regression variables, the quadratic model can fit the response data for the adsorption of
Cu
2+
, Pb
2+
and Cd
2+
ions. The regression equations for each metal are mentioned as
Equations 6.1-6.3.
Table 6.18 Design values of influencing parameters and responses of adsorption study
Run
Coded Variables Pb
2+
Cu
2+
Cd
2+
AB C D qe, calqe, preqe, calqe, preqe, calqe, pre
1 615 0.510013.112.413.613.012.912.4
2 790 0.612522.321.922.822.622.221.9
3 465 0.510013.114.414.115.313.414.7
4 740 0.675 13.912.914.013.313.312.7
5 540 0.675 12.912.113.913.013.112.1
6 665 0.550 9.8 10.510.311.19.8 10.6
7 740 0.612517.018.217.918.917.118.2
8 790 0.475 15.215.316.016.015.315.4
9 740 0.475 11.513.012.013.211.612.7
10 790 0.675 14.214.315.215.114.614.6
11 665 0.510018.718.921.119.720.519.0
12 665 0.510018.418.919.319.718.619.0
13 665 0.510018.318.919.319.718.619.0
14 540 0.412518.018.318.919.118.318.5
15 665 0.510019.318.919.219.718.419.0
16 740 0.412519.820.220.821.120.020.3
17 665 0.310021.820.122.120.821.320.0
18 590 0.675 14.513.915.415.014.814.4
19 61150.510018.318.819.219.818.619.1
20 665 0.710016.418.017.418.716.717.9
21 790 0.412523.624.724.725.723.724.8
22 865 0.510018.116.718.517.318.116.7
23 590 0.475 14.914.115.915.015.114.2
24 590 0.412522.623.323.524.122.823.3
25 665 0.515025.925.026.725.826.125.2
26 590 0.612522.521.323.021.922.321.4
27 540 0.612517.517.118.017.917.417.3
28 665 0.510018.818.919.219.718.619.0
29 540 0.475 11.311.411.811.911.111.3
30 665 0.510020.118.920.319.719.519.0
114

Chapter 6: Biogas slurry solids based heavy metal adsorption
Table 6.19 Results of the ANOVA test for the experimental design data
Metal
ion
SourceSum of squares
Degrees of
freedom
Mean
Square
F valuep-value
Cu
2+
Model 451.41 14 32.24 25.43< 0.0001
A 5.85 1 5.85 4.61 0.0485
B 68.25 1 68.25 53.83< 0.0001
C 6.84 1 6.84 5.40 0.0346
D 323.44 1 323.44 255.07< 0.0001
A² 20.13 1 20.13 15.87 0.0012
B² 19.01 1 19.01 14.99 0.0015
Residual 19.02 15 1.27 - -
Lack of Fit15.81 10 1.58 2.46 0.1657
Pure Error 3.21 5 0.6417 - -
Cd
2+
Model 443.19 14 31.66 24.08< 0.0001
A 6.24 1 6.24 4.74 0.0458
B 68.04 1 68.04 51.75< 0.0001
C 6.27 1 6.27 4.77 0.0452
D 318.93 1 318.93 242.60< 0.0001
A² 18.97 1 18.97 14.43 0.0017
B² 18.73 1 18.73 14.25 0.0018
Residual 19.72 15 1.31 - -
Lack of Fit16.34 10 1.63 2.42 0.1709
Pure Error 3.38 5 0.6758 - -
Pb
2+
Model 437.18 14 31.23 20.40< 0.0001
A 7.59 1 7.59 4.96 0.0418
B 61.07 1 61.07 39.89< 0.0001
C 7.05 1 7.05 4.60 0.0487
D 315.76 1 315.76 206.26< 0.0001
A² 19.55 1 19.55 12.77 0.0028
B² 18.57 1 18.57 12.13 0.0033
Residual 22.96 15 1.53 - -
Lack of Fit20.73 10 2.07 4.64 0.0520
Pure Error 2.23 5 0.4466 - -
115

Chapter 6: Biogas slurry solids based heavy metal adsorption
q
eCu
2+¿
¿= 19.74 + 0.49A + 1.69B -0.53C + 3.67D -0.08AB -0.23AC +
0.17AD -0.25 BC + 0.47BD -0.56CD -0.86 A
2
-0.83B
2
+ 0.005C
2
-
0.31D
2
6.9
q
eCd
2+¿
¿= 19.04 + 0.51 A + 1.68B -0.51C + 3.64D -0.08AB -0.23AC +
0.09AD -0.18BC + 0.47BD -0.52CD -0.83A
2
-0.83 B
2
-0.02C
2
-0.29
D
2
6.10
q
ePb
2+¿
¿=18.93 + 0.56 A + 1.59B + -0.54C + 3.63D -0.11AB -0.19AC +
0.06AD -0.21BC + 0.59BD -0.46 CD -0.84A
2
-0.82B
2
+ 0.027C
2
-
0.29 D
2
6.11
These polynomials are the best-fit equations provided by the model for each ion. Here, A,
B, C, D, A
2
, and B
2
are the major influencing factors as per the quadratic model for all the
metal ions adsorbed. The model F values of 25.43, 20.4 and 24.08 for Cu
2+
, Pb
2+
and Cd
2+,
respectively, indicate that model is adequate and there is only a 0.01% chance that noise
causes this large F value to occur [299]. The observed signal-to-noise ratio (adequate
precision) of 18.44, 16.58 and 17.99 for Cu
2+
, Pb
2+
and Cd
2+
were above the desirability
value. Also, no transformation was required for the data as per the Box-Cox Plot obtained
for each metal ion.
Design-Expert® Software
Cu
Color points by value of
Cu:
10.312 26.667
Ac t u al
P
red
icted
Predic ted vs. Ac tual
10
15
20
25
30
10 15 20 25 30
P
r
e
d
i
c
t
e
d
Actual
15
25
10
20
30
15 2510 20 30
Cu
2+
Design-Expert® Software
Cd
Color points by value of
Cd:
9.812 26.057
Actu al
P
re
d
ic
te
d
Predicted vs. Actu al
5
10
15
20
25
30
5 10 15 20 25 30
P
r
e
d
i
c
t
e
d
Actual
5
15
25
10
20
30
5 15 2510 20 30
Cd
2+ Design-Expert® Software
Pb
Color points by va lue of
Pb:
9.792 25.857
A ctua l
P
red
icte
d
Predicted vs. Actual
5
1 0
1 5
2 0
2 5
3 0
5 1 0 1 5 2 0 2 5 3 0
P
r
e
d
i
c
t
e
d
Actual
5
15
25
10
20
30
5 15 2510 20 30
Pb
2+
Figure 6.40 Graphical comparison of predicted responses by design and experimental
responses of adsorption capacity for heavy metals, a) Cu
2+
, b) Cd
2+
and c) Pb
2+
The goodness of fit was investigated for the adsorption responses to see the validity of
the mathematical model compared to actual experimental data. The predicted and
observed values were plotted and related for all the adsorbates in Figure 6.5. The
regression coefficients from the comparison obtained were 0.959, 0.957 and 0.95 for
116

Chapter 6: Biogas slurry solids based heavy metal adsorption
Cu
2+
, Cd
2+
and Pb
2+
respectively. The closer to unity values of these coefficients indicate
that the model complies with acceptance criteria.
6.4.1 Effect of pH, time, dosage and initial concentration on adsorption
The mutual influence of pH and time is given in Figure 6.6, while the dosage and initial
concentration were 0.5 g and 100 mg L
-1
(values at center points), respectively. An
increasing trend in qe value was observed with progress in adsorption time from 15 to 100
min; from there, it decreased slightly. Adsorption of all ions exhibited a similar pattern
concerning the independent variables, A and B.
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
C
u
2
+
)

(
m
g
/
g
)
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
P
b
2
+
)

(
m
g
/
g
)
A: pH
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
C
d
2
+
)

(
m
g
/
g
)
Figure 6.41 3D-interaction effect plots of pH and time for adsorption
The contour plot in Figure 6.7 presents the mutual interaction of pH and dosage of
adsorbent. According to this bell-shaped trend observed, at extreme acidic and basic
levels, qe stayed below the equilibrium values. The reduction in adsorption capacity at
acidic pH could be due to the competition of heavy metal ions and other potential
electron-sharing ions for surface ligands [208]. The removal efficiency depends on the
electro-negativity of the species present [300]. Also, it was observed that MMPSS
adsorbents exhibit maximum adsorption capacity near neutral pH. At pH below PZC
117

Chapter 6: Biogas slurry solids based heavy metal adsorption
(Figure 6.2a), the number of binding sites gets distributed between metal ions and H
+
ions and thus, the desired complex formation is reduced [301]. But, as the pH increased
beyond the PZC value (pH 3.5), the removal rate improved drastically till pH 6, where
the highest removal rate was observed due to the reduction in cations in the solution.
When heavy metal ions acted as priority entities, complex formation between the
functional groups of MMPSS and metal ions

dominated. The high concentration of Na
+
in
the solution (due to NaOH addition) competes with the Cu2+, Pb2+ and Cd2+ for the
binding site; thus, the adsorption rate is reduced [302]. Also, the possible desorption of
ions from the surface in an alkaline environment (shown in the regeneration experiment)
brings more competing molecules into the media as the process continues. Here, there is
also a possibility of metal ions combining with aqueous phase OH
-
and resulting removal
by precipitation [301].
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
C
u
2
+
)

(
m
g
/
g
)
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
C
d
2
+
)

(
m
g
/
g
)
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
P
b
2
+
)

(
m
g
/
g
)
Figure 6.42 3D-interaction effect plots of initial concentration and time for adsorption
After attaining equilibrium, the uptake of metal ions occurs while desorbing an equal
amount of adsorbate [39]. Regarding the combined effect of time and initial
concentration, as shown in Figure 6.7, a sharp rise in qe value with growing initial
concentration values from 50 mg l
-1
to 150 mg l
-1
was observed. This is due to the
118

Chapter 6: Biogas slurry solids based heavy metal adsorption
occupancy of more functional sites on the adsorbent surface by metal ions until saturation
is attained. This can be ascribed to the fact that the adsorbent surface could accommodate
more ions when functional groups available have not participated in adsorption. The rise
of removal capacity ceased at 150 mg l
-1
as the active adsorption site gets saturated. The
limited availability of these complex-forming sites restricts the further addition of metal
ions onto the matrix [303]. Similarly, qe decreased upon increasing the ratio of the
quantity of adsorbent to the initial concentration. This could be explained clearly when
the initial concentration of metal ions is constant (100 mg L
-1
). As qe is calculated in
terms of concentration and weight of adsorbent, it varies linearly with variation in
parameter when the other one is constant [184]. When the varied initial concentration
exceeds the equilibrium concentration, qe becomes constant (at a constant dosage value).
Figure 4a shows the effect of independent variables C and D. So, when one could directly
impact qe, the other is inversely affecting qe until a dynamic equilibrium is reached [304].
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
C
d
2
+
)

(
m
g
/
g
)
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
C
u
2
+
)

(
m
g
/
g
)
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
C
d
2
+
)

(
m
g
/
g
)
A
d
s
o
r
p
t
i
o
n
c
a
p
a
c
i
t
y
(
P
b
2
+
)

(
m
g
/
g
)
Figure 6.43 3D-interaction plots of time and dosage for adsorption
119

Chapter 6: Biogas slurry solids based heavy metal adsorption
6.4.2 Validation of model variables
According to the quadratic model, the optimum values of process variables predicted and
experimental data of validation of predicted points are detailed in Table 6.4. The
prediction of validation points is based on the criteria of dosage of adsorbent to be
minimum and initial ion concentration to be the maximum value. The experimental
results were not highly distinguishable from predicted qe values, with percentage errors
of 3.33%, 2.24% and 0.74% for Cu
2+
, Cd
2+
and Pb
2+
. Adsorption of Cu
2+
onto MADS was
more effective than the other two metal ions. The percentage difference between the
highest (Cu
2+
) and lowest (Pb
2+
) adsorption capacities is 3.13%.
Table 6.20 Predicted values of individual parameters and results of validation experiment
for three different metal ions Cu
2+
, Cd
2+
and Pb
2+
.
Parameter Units
Metal ions adsorbed
Cu
2+
Cd
2+
Pb
2+
pH - 6.480 6.692 6.924
Time minutes 107.658 106.421 106.08
Dosage g 0.4 0.4 0.4
Initial Concentrationmg/L 150 150 150
Desirability - 1 1 1
qe, predicted mg/L 30.216 29.208 29.117
qe, experimental mg/L 29.721 28.551 28.601
6.5Kinetic Study
A suitable kinetic model could be applied to evaluate the performance of the adsorbent
and theoretically predict the efficiency at any point of time [305]. Experimentally, a
tremendous increase in adsorption capacity was observed with an increase in the
adsorption time up to 60 min and all metal ions followed a similar trend (Figure A). After
the equilibrium point, the plot reached a plateau since uptake equals the release of metal
ions [306].
Three different kinetic models were chosen according to the possibility of fitting the
experimental data with a maximum regression coefficient value. As shown in Table 6.5,
the Pseudo second-order model fits the data with a coefficient of 0.986, 0.985 and 0.988
for Cu
2+
, Cd
2+
and Pb
2+,
respectively. The adsorption capacities were comparable with the
120

Chapter 6: Biogas slurry solids based heavy metal adsorption
measured values. The initial sorption rates calculated considering the intercept value of
the linear plot are 0.112 mg (g min)
-1
, 0.055 mg (g min)
-1
and 0.07 mg (g min)
-1
for Cu
2+
,
Cd
2+
and Pb
2+
, respectively. It was noted that the adsorption process falls to zone II as the
calculated approaching equilibrium factor (Rw) (Equation 6.4) is in a range of
0.01<Rw<0.1. Thereafter, it was concluded that the adsorption of heavy metals to
MMPSS follows a well-approaching equilibrium pattern. Reportedly, a significant error
appears in predicting adsorption time (t) using Rw values [307]. To avoid this error, the
time of adsorption was calculated from the relation given in Equation 6.5.
R
w=
1
1+k
2
q
e
t
ref
6.12
tref is the longest operation time, qe is the amount of adsorption and k2 is the second-order
rate constant (g mg
-1
min
-1
).
t
x=
W
k
2
q
e
6.13
Where, t
x is at particular Fractional adsorption (X). The values of X were calculated and
plotted against the second-rate index (W) (Equations 6.6 and 6.7 ).
W=
X
1−X
6.14
X=
q
t
q
e
6.15

The adsorption time was found to be 51.53 min, 43.97 min and 96.19 min when X=0.95.
From the calculated values of kinetic parameters, Intraparticle diffusion theory is the least
fit for the adsorption of Cu
2+
, Cd
2+,
and Pb
2+
onto MMPSS.
6.6Equilibrium study
Adsorption isotherms are used to explain the association of adsorbate to the adsorbent.
Table 6.5 includes the model parameters for calculated experimental data, applying
121

Chapter 6: Biogas slurry solids based heavy metal adsorption
different isotherm models. Among the four isotherm theories compared, the observed data
more fitted to the Langmuir isotherm model with an R
2
value of more than 0.9 for the
adsorption of all three heavy metals. Assuming that qm does not change with temperature,
the mechanism of adsorption of heavy metal ions onto MMPSS could be explained by the
Langmuir model. Although the difference between correlation coefficients for different
heavy metals was minimal, Cu
2+
had the highest fit, followed by Pb
2+
.

In the case of the
Temkin isotherm model, the calculated adsorption capacity values were fitted with good
correlation, but R
2
was slightly below that for the Langmuir model. Observing the non-
linear fit among three metal ions, a similar trend as that of the Langmuir model was seen
with the Temkin model.
When an adsorption system follows Langmuir isotherm theory, the adsorbate is supposed
to attach to the surface with a single type of chemical bondage. So, in this study, the
attachment of heavy metals onto MMPSS could be attributed to interaction with the
hydroxyl anion functional group. It was postulated in a study that Pb cations form
complexes with two adjacent anions (OH
-
) by electrostatic force [308]. The native
functional groups and those generated during pretreatment facilitate the formation of
surface complexes with metal ions. At higher equilibrium concentrations, the surface
monolayer tends to be saturated. Also, the interaction is within this monolayer where the
transmigration of metal ionic species is restricted [309]. Considering the thermodynamic
behavior of the adsorption system, when the adsorption is homogeneous, ∆H° of
adsorption tends to be constant throughout the process. From the model parameter values,
it is conclusive that physisorption took a remarkable role in the adsorption of heavy metal
ions.
In addition to the above characteristics, the Separation factor, RL can decide the shape of
the isotherm. When 0<RL < 1, the isotherm is favorable, along with a concave isotherm
shape [310]. Because when the values of RL are unity, attaining equilibrium is impossible.
In this study, RL values show that it is near zero (but greater), indicating that adsorption is
strong enough but not irreversible.
122

Chapter 6: Biogas slurry solids based heavy metal adsorption
T
a
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6
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2
+
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f
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(
×
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ln(q
e
−q
t)=lnq
e
−k
1
t
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q
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1
(k
2.q
e
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)
+
1
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e
.tq
t=K
ipdt
1/2
+C
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e
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e
=
1
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+
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m
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L=
1
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lnq
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f
+(
1
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.lnC
e
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t
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d
y
123

Chapter 6: Biogas slurry solids based heavy metal adsorption
qe- equilibrium adsorption capacity (mg g
-1
), qt- adsorption capacity (mg g
-1
) at time (min)
‘t’, k1, k2- rate constants (min
-1
, g (mg min)
-1
respectively) of adsorption corresponding to
pseudo first and second order, R
2
- correlation coefficient, kipd - Intraparticle Diffusion
rate constant (g (mg min)
-1
), C- intercept, qm- maximum adsorption capacity (mg g
-1
),
KL- Langmuir constant (L mg
-1
), RL- Separation factor, Kf, n- Freundlich constants (L mg
-
1
), BT- surface heterogeneity constants (mg g
-1
), KT- Temkin equilibrium binding constant
(L mg
-1
), KD- constant related to the mean free energy (mol
2
kJ
-1
), E- mean adsorption
energy (KJ mol
-1
).
6.7Thermodynamic Study
Thermodynamic parameters are analyzed to understand the process's sorption mechanism
and temperature dependency. An adsorption study was conducted in a temperature range
of 293 K to 333 K to calculate thermodynamic parameters onto MMPSS. The parameters
were evaluated based on the Van’t Hoff equation (Equation 6.8).
∆H°−T∆S°=−RTlnK
c
6.16
∆G°=∆H°−T∆S°
6.17
Where ∆H° - change of enthalpy, ∆S° - change of entropy. T - temperature (K), Kc-
distribution coefficient and R - gas constant (8.314J mol
-1
K
-1
).
Gibb’s free energy change (∆G°) was obtained from Equation 6.9. Here the adsorbate to
adsorbent value is kept constant (30 mg g
-1
) to maintain the standard condition and avoid
the error of ∆S° calculations [311]. The investigation of temperature effects involved a
linear plot of 1/T against log Kc. The calculated values of parameters from the plot are
presented in Table 6.7.
Table 6.22 Attributes of adsorption thermodynamics for heavy metal adsorption
Metal Ion
Adsorbed
∆G° (KJ/mol) ∆H°
(KJ/
mol)
∆S°
(J/mol)293(K)303(K)313(K)323(K)333(K)
Cu
2+
-1.604-1.635-1.666-1.697-1.728-0.6953.101
Pb
2+
-0.447-0.452-0.458-0.463-0.469-0.2860.548
Cd
2+
-1.394-1.425-1.455-1.486-1.516-0.5033.042
124

Chapter 6: Biogas slurry solids based heavy metal adsorption
Positive values of ∆S° indicate that the adsorption process is favored due to increased
randomness at the junction of metal ions and adsorbent. According to Langmuir Isotherm,
each adsorbate molecule possesses constant enthalpy [309]. Also, it could be deduced
from the values of ∆H°<0, that heat release occurs during adsorption [312]. Negative
values of ∆G° can be accounted for the spontaneous process. The importance of
thermodynamic parameters indicates the minimal effect of temperature on the adsorption
of heavy metal ions onto MMPSS adsorbent. Also, the adsorption process of Cu
2+
and
Cd
2+
relates to the values of ∆H°, ∆S° and ∆G°.
6.8Mechanism of Adsorption
The complexity of adsorption depends on the mechanism of the process. In this study, the
raw material, BSS, has native hydroxyl ion group on its surface, which was confirmed by
FTIR spectra analysis (peak at 1036 cm
-1
). The additional peak at 3630 cm
-1
implied that
PSS was enriched with OH
-
ions, thereby improving functionality. Darezereshki et al.
(2018) mentioned the role of magnetite in the adsorption of heavy metals from an
aqueous solution at a pH of 5.5 [201]. Here, MMPSS showed optimum efficiency near
neutral pH and decreased at acidic pH. Below PZC, the competition of protons with
heavy metals prevails. The negative charge density rises when the pH increases and
positively charged metal ions are taken to the surface [39]. Heavy metal ions get reduced
by anion-cation electrostatic interaction with hydroxyl

groups and subsequent complex
formation [308]. Here, all the metals adsorbed were divalent; each heavy metal ion
occupied two adjacent hydroxyl ions on the surface of the MMPSS adsorbent.
Thermodynamic analysis implied physisorption dominated adsorption. But, FTIR
analysis revealed the hydrogen bond formed while adsorption. Also, the presence of
cyanate groups shows that amide groups would have participated in the complex
formation. The appearance of a few peaks in the XRD pattern confirmed complexes
formed by heavy metals. Further, the monolayer formation of the hydroxyl-metal ion
complex was confirmed by the fit observed for the adsorption data towards Langmuir
adsorption. So, the adsorption by MMPSS involved multiple phenomena of electrostatic
interaction and complex formation in a monolayer. The presence of adsorbed heavy
metals in the EDX spectra of spent MMPSS further strengthens these conclusions.
125

Chapter 6: Biogas slurry solids based heavy metal adsorption
During desorption, it was clear that metal ions tending to chloride formation desorbed
more in HCl eluent than with NaOH. Generally, ionic species having higher valence tend
to be adsorbed more than lower valence ions [300]. But, all three metals adsorbed were
divalent. So, adsorption efficiency did not vary greatly among the ionic species adsorbed.
The efficiency of simultaneous adsorption was also evaluated based on a three-metal
system, where 50 mg L
-1
of

each of the three metal ions was subjected to adsorption by
MMPSS. With a 68.77 % overall removal efficiency, the system revealed that the
presence of more than a metal ion could decelerate the rate of adsorption and the
efficiency of removal.
6.9Regeneration of adsorbent
The reusability of MMPSS adsorbent was studied in five consecutive cycles of
adsorption. The MMPSS adsorbent was filtered out from the solution and regenerated
with eluents 0.1 M HCl or 0.1 M NaOH by keeping for 12 h. The strength of eluents was
chosen not to disturb the chemical structure of the adsorbent surface [313]. After eluting,
the solids were washed repeatedly, and the material loss after each cycle was less than
1%. The adsorption experiments with regenerated MMPSS were performed at optimized
conditions. Figure 6.9 shows that HCl is a better eluent to desorb heavy metals [314]. The
adsorption capacity was reduced by 16.99 %, 15.34% and 18.17% for Cu
2+
, Cd
2+
and Pb
2+
,
respectively, from cycles 1 to 5. But, when NaOH was used as a regenerating agent,
27.35%, 25.66% and 26.4% for Cu
2+
, Cd
2+
and Pb
2+
,

respectively, were the reduction in
adsorption capacity compared to the virgin adsorbent. It was concluded that effective
regeneration is possible for the developed adsorbent, i.e., MMPSS, at experimented
strength of eluents. According to Table 6.8, MMPSS adsorbent had better adsorption
capacity than other novel adsorbents developed.
126

Chapter 6: Biogas slurry solids based heavy metal adsorption
1 2 3 4 5
0
5
10
15
20
25
30
q
e
(
m
g
g
-
1
)
Cu
Cd
Pb
(a) (b)
q
e

(
m
g
g
-
1
)
1 2 3 4 5
0
5
10
15
20
25
30
No. of cycles
Cu
Cd
Pb
No. of cycles
Figure 6.44 Adsorption capacity of regenerated adsorbent; (a) 0.1 M HCl as eluent and
(b) 0.1 M NaOH as eluent
Table 6.23 Comparison of heavy metal adsorption onto various adsorbents studied
Adsorbent
Heavy metal
removed
Adsorption
capacity
(mg/g)
Reference
Egyptian Na-activated bentonite
Pb
2+
Cd
2+
5.435
3.145
[315]
-SH enriched bentonite (BSH)
Pb
2+
Cu
2+
22.06
21.94
[205]
Banana peel powder
Pb
2+
Cu
2+
12.846
12.645
[190]
Freshwater microalgal isolates
Pb
2+
Cd
2+
4.49
5.48
[182]
KOH-activated carbon
Cu
2+
Pb
2+
14.3
35.5
[194]
Chlorella colonials (Freshwater
Algae)
Cd
2+
9.65 [208]
MMPSS
Cu
2+
Cd
2+
Pb
2+
26.84
24.79
23.86
This study
6.10Conclusions
In this study, a magnetic adsorbent MMPSS was developed by crosslinking alkali-thermal
pretreated biogas slurry solids and magnetic iron nanoparticles. From the characterization
of materials, it was concluded that MMPSS adsorbent had improved surface properties,
127

Chapter 6: Biogas slurry solids based heavy metal adsorption
thereby good adsorption capacity for heavy metal ions Cu
2+
, Cd
2+,
and Pb
2+
compared to
the parent material. The interaction of the adsorbent with the heavy metal ions in the
aqueous phase followed pseudo-second-order kinetics. The Langmuir isotherm showed
the best fit for single-metal adsorption systems and implied that physisorption played a
major mechanism for adsorption. This was confirmed by a thermodynamic study. It was
proved that the MMPSS adsorbent retained its adsorption capacity after five repeated
adsorption cycles. So, it can be concluded from this study that the magnetic adsorbent
developed from biogas slurry solids could be used as an alternative low-cost adsorbent
for reducing the concentration of heavy metals Cu
2+
, Cd
2+
and Pb
2+
in the aqueous phase
to below permissible limits. There are geographical areas where the available water needs
to be adequately treated for domestic use. An immobilized column of MMPSS adsorbent
could be effectively used to remediate contaminated water with heavy metal
concentrations below 150 mg L
-1
and make it potable. A treatment system framed in such
a way may be feasible for the community where the cost of treatment has sustained as a
limiting factor. Likewise, biogas slurry solids can be valorized to use as a medium for
pollutant recovery.
128

Chapter 7
Conclusions and Future Perspectives

Chapter 7: Conclusions and Future Perspectives
7.1Summary
This research considered the tremendous advantages of INPs in wastewater treatment and
addressed a few of the current research gaps. The main aim of this study was to
investigate the efficiency of INP-based composites in biological (anaerobic digestion)
and chemical processes (adsorption). After conducting a comprehensive literature review,
the existing research gap was understood and the objectives of this research were framed.
The literature analyzed were related to the properties and applications of INP-based
composites, anaerobic digestion of fat-rich substrates and modification of the process by
altering the operational conditions, the influence of DIET in CH4 enrichment, methods of
pretreatment of wastewater and sludge-based magnetic adsorbents. The role of DIET and
allied microbial populations in a composite-based system must be explored in detail.
Also, the literature lacks knowledge about RGO-NZVI composite system and its
mechanistic investigation. Also, the possibility of diverse applications of highly
functional biogas slurry solids could be explored.
The specific objectives of this study were,
To synthesize NZVI conductive composite with RGO as a carrier and study its
effect on anaerobic digestion of dairy wastewater through batch and continuous
study and optimize the operational parameters.
To illustrate the ability of RGO-NZVI composite to catalyze photocatalytic
pretreatment followed by anaerobic digestion of dairy wastewater.
To synthesize a ternary composite from PPy, CB and NZVI and observe the
effects in anaerobic digestion of dairy wastewater through a batch process.
To develop an INP composite adsorbent from pretreated biogas slurry solids to
sequester heavy metals and the optimization of adsorption conditions by response
surface methodology.
Based on the set goals for this research, several trials of batch anaerobic studies were
conducted with one variable at a time approach for each parameter for 35 days each and
reported the optimum parameter values to obtain maximum efficiency. The effect of two
different conductive composites, RGO-NZVI and PPy-CB-NZVI, were evaluated through
130

Chapter 7: Conclusions and Future Perspectives
batch experiments. The mechanistic investigation would be incomplete with deep
molecular-level analysis based on the metagenomic study of the existing microbial
population. A genomic level comparison of biomass collected from digesters with and
without modification revealed the difference in protein expressions and population
diversity. Later, a continuous reactor was fabricated and run for 180 days to observe the
effect of adding RGO-NZVI at varying OLRs. Also, the dual application of conductive
composite was tested by employing RGO-NZVI in a consecutive photocatalytic-
biological process. This study compared and reported digestion with and without
pretreatment, with and without the amendment of the fresh catalyst after pretreatment
(before anaerobic digestion). Another polypyrrole-based polymer composite was
supplemented in the digestion process to observe its effects. Finally, the fate of biogas
sludge solids was demonstrated by developing a magnetic adsorbent for heavy metal
removal.
7.2Conclusions
This study explored the features of INPs to assist in environmental remediation by
biological and physicochemical processes. Considering the low retainability and tendency
for aggregate formation of INPs, this research has focused on INP-based composites. The
major conclusions from this research are given below.
A conductive composite made of NZVI and RGO boosted the CH4 composition,
biogas volume and removal of organic compounds. The additive enriched the
microbial population with more methanogenic species and increased species
diversity. DIET-based redox mechanism prevailed in the system with ferrous ion
transport proteins and pyruvate-ferredoxin oxidoreductase metabolism.
The pretreatment of the substrate before anaerobic digestion improved the
digestion performance by enriching CH4 in biogas and reducing the lag phase
time for methanogenesis. This phenomenon was facilitated due to the partial
solubilization of organic constitution by photodegradation and activation by the
spent photocatalyst. Further, a fresh amendment of the catalyst exhibited superior
performance compared to the control reactors. This study demonstrated the
131

Chapter 7: Conclusions and Future Perspectives
feasibility of an integrated photocatalytic-biological degradation system using
RGO-NZVI as a catalyst.
The ternary composite prepared out of PPy, CB and NZVI influenced the primary
stages of digestion positively to increase the transformation of complex molecules
to short-chain fatty acids. In addition, acetogenesis was enhanced, which led to
the acceleration of CH4 generation.
The magnetic adsorbent developed from biogas sludge formed complexes from
hydroxyl groups on the surface with the heavy metal ions by electrostatic
interactions over the monolayer. The adsorption process followed second-order
kinetics and the Langmuir isotherm model, inferring the possibility of
physisorption as a dominant mechanism. Magnetic separability is the most
relevant advantage of the developed adsorbent. The adsorbent is efficient even
after multiple adsorption cycles, implying that the material recyclability is good
enough. The geographical area with a low economic index, where the cost of
wastewater treatment is a prominent factor and the requirement of selective heavy
metal removal at moderate concentrations may depend on the MMPSS adsorbent
developed in this study.
7.3Future scope of the study
Iron leaching was observed while using NZVI composites, possibly due to the
direct exposure to the aqueous phase. This may be reduced by immobilizing the
composite in a polymer matrix. By this, the recyclability can be improved.
Anaerobic digestion is a source of biofuels such as bioethanol, biobutanol etc. The
effect of the studied composites to boost solubilization may be utilized further to
enhance the yield of such biofuels.
The effect of magnetic and electric field might cause changes in redox and
material distribution in the system in the presence of conductive additives. Studies
reported the positive effects of magnetic field in anaerobic digestion tests.
Similarly, the development of a fuel cell incorporating the anaerobic system
mentioned in the study may be subjected to extensive research in the future.
132

Chapter 7: Conclusions and Future Perspectives
RGO and NZVI could be employed in other AOPs as catalysts. Studies on the
applicability of other pretreatment methods may be conducted.
133

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Chapter 7: Conclusions and Future Perspectives
Dissemination
Research articles
S Tundup, P S Roshini, A Kumar, A Sahoo, B Paramasivan (2021). Evaluating the
scientific contributions of biogas technology on rural development through
scientometric analysis. Environmental Technology & Innovation 24, 101879
R Sasidharan, A Kumar (2022). Response surface methodology for optimization
of heavy metal removal by magnetic biosorbent made from anaerobic sludge.
Journal of the Indian Chemical Society 99 (9), 100638
R Sasidharan, A Kumar (2022). Magnetic adsorbent developed with alkali-
thermal pretreated biogas slurry solids for the removal of heavy metals:
optimization, kinetic, and equilibrium study. Environmental Science and Pollution
Research 29 (20), 30217-30232
R Sasidharan, A Kumar, B Paramasivan, A Sahoo (2023). Reduced graphene
oxide-nano zerovalent iron assisted anaerobic digestion of dairy wastewater: a
potential strategy for CH4 enrichment. Journal of Environmental Chemical
Engineering, 110035
R Sasidharan, A Kumar, B Paramasivan, A Sahoo (2023). Photocatalytic
pretreatment of dairy wastewater and benefits of the photocatalyst as an enhancer
of anaerobic digestion. Journal of Water Process Engineering 52, 103511
R Sasidharan, A Kumar, B Paramasivan, A Sahoo. A ternary NZVI-polypyrrole
composite for anaerobic digestion of dairy wastewater. (to be communicated)
Conferences
R Sasidharan, A Kumar (2022) International Conference ChemTSF – 2022. IIT
Roorkee.
R Sasidharan, A Kumar (2021) Advances in Chemical, Biological and
Environmental Engineering" ICACBEE-2021, MNIT Jaipur.
R Sasidharan, A Kumar (2021) Advanced sustainable research for environment
and management ASREEM 2021, SVNIT.

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