mathematical modelling of reverse sulfur reduction in
TRANSCRIPT
DEGREE PROJECT IN CHEMICAL ENGINEERING AND TECHNOLOGY, FIRST LEVEL PRAGUE, CZECH REPUBLIC 2020
KTH ROYAL INSTITUTE OF TECHNOLOGY KTH ENGINEERING SCIENCES IN CHEMISTRY, BIOTECHNOLOGY AND HEALTH
Mathematical Modelling of
Reverse Sulfur Reduction in
Microaerobic Biofilm
Laura Raud Pettersson
DEGREE PROJECT Bachelor of Science in
Chemical Engineering and Technology
Title: Mathematical Modelling of Reversed Sulfur Reduction in Microaerobic Biofilm Swedish title: Matematisk modellering av den omvända svavelreduktionen i en mikroaerob biofilm Keywords: Microaeration, Mathematical Model, ADM1 Reversed Sulfur Reduction, Microaerobic Biofilm Work place: UCT Prague Supervisors at the workplace: Markéta Andreides & Jan Bartáček Supervisor at KTH: Sara Thyberg Naumann Student: Laura Raud Pettersson
Date: 2020-06-18 Examiner: Sara Thyberg Naumann
i
Sammanfattning
Anaerob rötning av slam från avloppsreningsverk i huvudsyfte att producera biogas, består av ett
flertal olika biologiska processer som involverar olika typer av bakterier. En introduktion av små
mängder syre till rötningskammaren möjliggör en kultivering av sulfidoxiderande bakterier (SOB).
Dessa bakterier kan oxidera och omvandla vätesulfid (H2S) till elementärt svavel och sulfater. H2S
är en biprodukt under rötningsprocessen, dock är det av en stor betydelse att avlägsna gasen på
grund av dess korrosiva och toxiska egenskaper. Sulfatreducerande bakterier (SRB) tar upp det
elementära svavlet samt sulfaterna för att sedan reducera dessa tillbaka till H2S. Denna biologiska
återbildning av H2S kallas inom engelskan för reversed reduction. Då det är essentiellt att avlägsna
H2S från rötgas innan uppgradering, är det intressant att studera huruvida den omvända reduktionen
av SRB har en signifikant inverkan på den totala avlägsningsgraden av H2S i rötkammaren.
Baserat på den litteraturstudie som har utförts kring den omvända reduktionen, har en matematisk
modell ännu inte tagits fram för att beskriva denna typ av biologiska process. Därför är syftet med
detta examensarbete att ta fram en matematisk modell för den ovannämnda processen. Resultaten
från simuleringarna i den framtagna matematiska modellen visar att den omvända reduktionen inte
har en påverkan på det totala avlägsnandet av H2S i rötkammarens gasfas.
ii
Abstract
Anaerobic treatment of waste-water sludge as a goal to produce biogas include various microbial
processes. By introducing small amount of oxygen (microaeration) to the digester, enables a
cultivation of sulfide oxidizing bacteria (SOB). SOB are able to oxidize harmful hydrogen sulfide
gas to elemental sulfur and sulfate. H2S is a by-product formed naturally by fermentative bacteria
present in the digester, however it is known to obtain highly corrosive and toxic properties. Sulfate
reducing bacteria (SRB) are able to utilize elemental sulfur and sulfates in order to produce
hydrogen sulfide gas (H2S). This specific process performed by SRB is abbreviated as reversed
reduction. Since it is highly undesirable to have H2S in raw produced biogas, it is therefore of a
great interest to study whether reversed reduction by SRB have a significant impact on the overall
H2S removal efficiency.
According to the extent of the literature study done on reversed reduction, a mathematical model
has not yet been created for this particular type of biological process. A mathematical model was
therefore designed for the purpose of describing reversed reduction, a biochemical process
performed by SRB. The simulation results based on the developed mathematical model conclude
that reverse reduction has no observed impact on the overall hydrogen sulfide removal process in
the headspace compartment.
iii
Content
1 Introduction ............................................................................................................................ 1
2 Anaerobic Digestion ............................................................................................................... 3
2.1 Principles of Anaerobic Digestion ................................................................................... 3
2.2 Factors Affecting AD ....................................................................................................... 4
2.2.1 Temperature.............................................................................................................. 4
2.2.2 VFA’s and pH .......................................................................................................... 5
2.2.3 Ammonia .................................................................................................................. 5
2.3 Biogas ............................................................................................................................... 6
3 Hydrogen Sulfide .................................................................................................................... 7
3.1 Acid Base Equilibrium ..................................................................................................... 7
3.2 Desulfurization Methods .................................................................................................. 8
3.2.1 Physico-Chemical Desulfurization ........................................................................... 9
3.2.2 Biological Desulfurization ..................................................................................... 10
4 Principles of Microaeration ................................................................................................. 12
4.1 Air Dosing Point ............................................................................................................. 12
4.2 Positive and Negative Aspects of Microaeration ........................................................... 13
4.3 Process Control............................................................................................................... 14
4.3.1 Oxidation Reduction Potential (ORP) .................................................................... 14
5 Microbiology ......................................................................................................................... 16
5.1 Organisms Involved in AD............................................................................................. 16
5.2 Sulfate Reducing Bacteria (SRB) ................................................................................... 16
5.3 Sulfide Oxidizing Bacteria (SOB) .................................................................................. 17
5.3.1 Photoautotrophic SOB ............................................................................................ 17
5.3.2 Chemolithotrophic SOB ......................................................................................... 18
5.4 Biofilm............................................................................................................................ 18
5.4.1 Biofilm in Sewer Systems ...................................................................................... 19
5.5 Reverse Reduction .......................................................................................................... 19
6 Mathematical Modelling ...................................................................................................... 21
6.1 Anaerobic Digestion Model No. 1 (ADM1) .................................................................. 21
6.2 Mathematical Equations in ADM1................................................................................. 22
6.2.1 Mass Balance .......................................................................................................... 22
6.2.2 Kinetics ................................................................................................................... 22
6.3 ADM1-S/O ..................................................................................................................... 24
iv
7 Mathematical Modelling of Reverse Reduction ................................................................ 25
7.1 Definition of Compartments ........................................................................................... 25
7.2 Kinetic Expressions Involved in Reverse Reduction ..................................................... 27
7.3 Testing of the Mathematical Model ............................................................................... 28
8 Results and Discussion ........................................................................................................... 1
8.1 Sulfur Species in Biofilm Compartment Including and Excluding SRB ......................... 1
8.2 H2S Concentration in Headspace Including and Excluding SRB .................................... 2
8.3 Variation of Initial H2S Concentration in Headspace ...................................................... 3
9 Conclusion ............................................................................................................................... 4
10 References ............................................................................................................................... 5
11 Appendix ................................................................................................................................. I
11.1 Calculation of Stochiometric Coefficients ....................................................................... I
11.1.1 Conversion of H2S to elemental sulfur ..................................................................... I
11.1.2 Conversion of Elemental Sulfur to Sulfate.............................................................. II
11.1.3 Conversion of Thiosulfate to Sulfate and Elemental Sulfur.................................... II
11.1.4 Conversion of Hydrogen Sulfide to Thiosulfate .................................................... III
1
1 Introduction
Opting for renewable and alternative energy resources has become important as ever
considering the trends of increased urbanization and industrialization around the world. In order to
tackle the climate changes and protect our environment, it is therefore of great importance to seek
for alternative energy resources and try to optimize and enhance current production processes
(Mathiesen et al., 2011; Hosseini and Wahid, 2014). Biogas production from biological waste from
WWTP (wastewater treatment plants) have gained a lot of attention lately, because of the efficient
possibility of taking care of biological waste and at the same time have the possibility to produce
energy-rich gas also known as biogas (Nguyen and Khanal, 2018).
However, the biogas that is produced in an anaerobic digester contains a lot of impurities such
as hydrogen sulfide. H2S is mainly known for its toxicity and corrosive properties (Park et al.,
2014). Desulfurization can be performed with various adsorption and scrubbing techniques. These
methods usually require unit extensions within the existing system, additional chemicals and
operations in high pressures- resulting in higher expenses (Krayzelova et al., 2015; Nguyen, 2018).
An alternative economically attractive desulfurization method can be performed in-situ within
the anaerobic digester (AD). Microaeration (introduction of small amount of oxygen to the
digester) is imposed in order to enable a microaerobic environment (Ramos et al., 2014). This type
of environment favors specific bacteria cultures known as sulfide oxidizing bacteria (SOB) that are
able to convert hydrogen sulfide to elemental sulfur and/or sulfates (Nguyen and Khanal, 2018).
Other bacteria present in the biofilm are sulfate reducing bacteria (SRB) which are able to convert
sulfate back to H2S (Fdz.-Polanco et al., 2009).
The aim of this thesis is to study the kinetics of sulfide formation (SRB) in the biofilm of an
AD by creating a mathematical model based on a widely accepted mathematical model of anaerobic
wastewater treatment created by International Water Association, ADM1 (Batstone et al., 2002).
In this model, different parameters such as biofilm area, biofilm thickness and O2/H2S ratio in the
headspace were varied to study the reverse reduction performed by SRB to form H2S.
2
Why reverse reduction is studied is to see if the produced H2S by the SRB has a significant
impact of the overall H2S removal efficiency in an anaerobic digester.
The goals of this thesis are:
- To describe anaerobic and microaerobic fermentation in detail
- To overview classical desulfurization methods with main focus on aeration
- In theory, describe reverse reduction of oxidized sulfur forms in biofilm
- Based on the theoretical knowledge, develop simple mathematical model of reversed
reduction in a simulation programme called Aquasim
- Discuss and compare obtained results with literature
3
2 Anaerobic Digestion
2.1 Principles of Anaerobic Digestion
Anaerobic digestion (AD) is considered to be an efficient method for combating the
atmosphere pollution and recovering energy by biologically treating industrial as well as
agricultural organic waste (Ariunbaatar et al., 2014) . Lately, AD has become an essential part in
modern large-scale wastewater treatment plants (WWTP) because of the possibility to use primary
and secondary sludge as a substrate for anaerobic bacteria and produce energy rich biogas. The
main problem of WWTP is the disposal of waste sludge (Edelmann et al., 2005). The disposal can
be done in many various ways, but the most common methods usually involve composting,
incineration and landfilling. Before the sludge disposal, one must also perform various pre-
treatments to be able to qualify for the End-of-waste criteria of existing disposal legislations
(Kacprzak et al., 2017). These treatment processes therefore often result in high economical
expenses and are considered to account for up to 50% of the entire operating costs in a WWTP
(Appels et al., 2008; Kacprzak et al., 2017). Not only is AD an efficient way to minimize the waste
volumes from WWTP, AD can also reduce landfilling gases that emit to the atmosphere.
Landfilling gas contains mostly of carbon dioxide (47%) and methane (47%). The remaining 6%
add up with trace gases such as hydrogen gas, carbon monoxide, oxygen and nitrogen gas (James
G. Speight, 2019). Another positive aspect of AD is the fact that the nutrient-rich solids that are
left after the digestion process can be used as crop fertilizers (Pozniak et al., 2019).
Anaerobic digestion includes series of processes, where biodegradable material is broken down by
various organisms in absence of oxygen. AD involves four main steps; hydrolysis, acidogenesis,
acetogenesis and methanogenesis. Hydrolysis is the first step in AD process, where large organic
molecules with high molecular weight such as; nucleic acids, proteins, fats, lipids and
polysaccharides are hydrolyzed to smaller molecular components (e.g. amino acids, fatty acids and
simple sugars) by extracellular enzymes (Myint et al., 2007; Appels et al., 2008).. In general,
hydrolysis is considered to be the rate-determining in the entire AD process. This reaction stage
can be catalyzed by extracellular enzymes excerpted by microorganisms present in the acidogenesis
step (Eze et al., 2012).
4
The monomers that are formed in hydrolysis are then broken down by fermentative bacteria
(acidogenes) forming hydrogen sulfide, ammonia, carbon dioxide, volatile fatty acids (VFA’s),
hydrogen gas and alcohols (Nayono, 2010). This process is called acidogenesis. The most
important VFA formed is acetate, since it can directly be utilized as a substrate by methanogens
(Nayono, 2010). The factors affecting AD will be discussed furthermore below in chapter 2.2.
The formed intermediate products from acidogenesis are furthermore broken down by acetogens
to form mainly acetic acid and also carbon dioxide and hydrogen. This process goes by the name
acetogenesis (Pozniak et al., 2019).
Finally, the terminal process in AD is methanogenesis. Methanogens convert the formed
intermediates from previous process steps to methane, carbon dioxide and water. These products
also add up to the main constituents of biogas (Pozniak et al., 2019).
2.2 Factors Affecting AD
2.2.1 Temperature
Anaerobic digestion can either take place under mesophilic conditions (35-37°C) or
thermophilic conditions (55 °C) (Vindis et al., 2009; Awe et al., 2017).
An increased temperature has many positive impacts on AD. The performance of AD and
degradation of biomaterials are enhanced with increased temperatures. Higher temperatures in
thermophilic operations result in higher pathogen destruction along with greater biogas production,
higher specific growth rates and overall higher metabolic rates (El-Mashad et al., 2004; Chen et
al., 2017).
According to Gallert (1998), a temperature increase within thermophilic operations showed that
the microflora had a higher tolerance against accumulated ammonia compared to mesophilic
operations. However, in an environmental aspect it is not optimal to run a reactor in thermophilic
conditions due to the additional energy demand. For instance, during the wintertime in Italy when
mesophilic operational temperature was not reached, supplementary fossil fuel was necessary to
obtain the required temperatures in the reactors (Bolzonella et al., 2005).
5
2.2.2 VFA’s and pH
It is important to acknowledge the toxicity when high concentrations of VFA’s and
ammonia are present in AD, since it could potentially wipe out the entire microflora (Nguyen et
al., 2018). As mentioned above, VFA’s are intermediate products that naturally form in the second
step of AD, acidogenesis. VFA’s have one to maximum six carbons in their molecule structure.
The most common VFA’s that are present in AD include acetic acid, propionic acid, butyric acid
and valeric acid and caproic acid (Chen et al., 2017). However, the VFA’s that are most dominant
in AD are acetic acid and propionic acid (Buyukkamaci et al., 2004). The ratio between acetic acid
and propionic acid can be used as an indicator of the digester performance. It is important to denote
that propionic acid is a dissociation product of caproic acid. If the system is overloaded, acetogenic
organisms reverse their metabolic pathway to produce propionic acid from hydrogen and acetic
acid (Marchaim and Krause, 1993). Acetic acid and propionic acid will therefore result in a pH
decrease, which can potentially lead to digestor failure. Thus, it is important to constantly measure
the concentration of VFAs present in the system in order to avoid microbial stress (Nguyen and
Khanal, 2018). High concentrations of propionic acid is also toxic to methanogens. According to
Wang et al., (2009), concentrations at 900mg/L caused a significant decrease of methanogenic
bacteria concentrations in their AD: 6×107 to 0.6–1×107 bacteria/ml, resulting in an overall
decreased methane yield. The most favorable pH interval for methanogens is considered to be
between 6.5-7.2 (Appels et al., 2008).
2.2.3 Ammonia
Ammonia is present in AD when the raw material consists of nitrogen- or protein-rich organic
substrates mainly in forms (𝑁𝐻4+) (ammomium) and free ammonia (𝑁𝐻3). Ammonia is used as a
nutrition for the growth of the microflora. However, high concentration of ammonia can on the
contrary be toxic to the bacteria present in AD (Yenigün et al., 2013; Chen et al., 2017). Free
ammonia (𝑁𝐻3) can diffuse into the cell membrane of an organism and disrupt the proton and
potassium balance inside the cell (Kayhanian, 1999). Ammonia inhibition for un-adapted
methanogenic bacteria has been observed at concentrations 1.5-2.5 g-N/L (Hansen et al., 1998).
The higher the pH in the anaerobic digester, the higher concentration of free ammonia is present.
According to Koster (2007), an increase from pH 7 to 8 will lead to an eight-fold increase of free
ammonia concentration.
6
2.3 Biogas
Raw biogas produced with anaerobic digestion consist approximately 60 vol% CH4 and 40
vol% CO2 (Dinel et al., 1988; Vindis et al., 2009; Okoro et al., 2019). Besides CH4 and CO2, the
raw biogas may contain other contaminants such as N2 (0.2 vol%); ammonia (<100ppm); chloride
compounds (0-5ppm) and hydrogen sulfide (0-10 000ppm) (Persson et al., 2006). The average
calorific value of biogas is considered to be ~21.5 MJ/m3 while the value for natural gas is around
36 MJ/m3 (Hosseini and Wahid, 2014).
The lower heating value of biogas produced in AD varies between 13,720-27,440 kJ/m3 at NTP
(normal temperature and pressure) (Hosseini et al., 2014). The heating value is a standard unit used
to describe how much energy is released when one normal cubic meter of fuel is combusted.
Eventual water vapor that is formed should also be completely condensed before the heating value
can be estimated. However, the lower heating value represents the energy formed in which the
water has not been condensed. Despite the lower calorific value of biogas (compared to natural
gas), it is important to denote that biogas is an excellent substitution for fossil fuels since its
production is entirely made out of renewable raw materials. Although combustion of biogas and
natural gas generate the same amount of CO2, biogas is still considered to be carbon neutral since
no fossil carbon is added to the raw material from which biogas is latter derived (Shiratori et al.,
2010; Eriksson, 2014). Raw biogas can be used for electricity and heat production in cogeneration
unit (Persson et al., 2006).
7
3 Hydrogen Sulfide
Hydrogen sulfide (H2S) is a very toxic colorless and flammable gas that is mostly recognized
for its strong odor of rotten eggs (Reiff et al., 1992). Since H2S is considered to be one of the main
participants in the biogeochemical sulfur cycle on earth, it would therefore not be a surprise to find
its presence in natural gas, volcanic gases and swamps (Reiff et al., 1992). Aquatic environment in
which anaerobic digestion takes place, will result in formation of H2S due to an organic matter
break down performed by various bacteria (Reiff et al., 1992). Other bacteria can use energy from
the oxidation process of H2S to sulfates or elemental sulfur by using nitrate or oxygen as an electron
acceptor (Clarke, 1953).
The amount of hydrogen sulfide present in biogas depends on the sulfate concentration present in
the introduced wastewater to the anaerobic digester. Sulfate rich wastewaters originate mostly from
industries (e.g. paper-, pharmaceutical and textile production) that utilize sulfur enriched raw
material for various processes (Hulshoff et al., 1998; Krayzelova et al., 2017). High concentrations
of H2S in biogas may result in a risk of release, which already at concentrations ~140mg/m3 causes
olfactory paralysis in humans (Chou, 2003; Okoro et al., 2019). Hydrogen sulfide formed in AD
may result in damages within the cogeneration unit due to H2S high ability to corrode steel and
concrete (Jeníček et al., 2017). Furthermore, the combustion of biogas containing H2S generate the
production of sulfur dioxide (SO2), which causes acid rain when released to the atmosphere
(Chaiprapat et al., 2015). With respect to the negative aspects mentioned above, pre-treatment of
the impurities in biogas is crucial when biogas is to be sustainably reused.
3.1 Acid Base Equilibrium
In liquid, H2S can also be dissociated with respect to pH, since the gas is considered to be
a weak acid (Li et al., 2013). The gas-liquid equilibrium of H2S can be described by Henry’s law.
In other words, the solubility of H2S is highly dependent on temperature and pressure (De Bruyn
et al., 1995). However, the equilibrium between H2S in liquid phase and the gas phase is dependent
on the amount of H2S present in the aquatic environment (Yongsiri et al., 2004). The concentration
of aqueous H2S is directly correlated to pH, it can thus be concluded that the concentration of
aqueous hydrogen sulfide is favored by lower pH. The lower the pH, the higher concentration of
8
dissolved H2S, resulting consequently a faster emission of H2S(aq) to the gas phase (Yongsiri et
al., 2004). The dissociation of H2S is described in equation 1-2 below (Yongsiri et al., 2004).
H2S(aq) + H2O(aq) → HS(aq)− + H3O(aq)
+ Eq. 1
HS(aq)− + H2O(aq) → S(aq)
2− + H3O(aq)+ Eq. 2
The pKa (adic dissociation constant) values at T=25°C for equations 1-2 are stated approximately
as 6.98 and 19±2 respectively (Hughes et al., 2009). Since the pH within anaerobic digestion is
around 7, the most dominating species of sulfur in the liquid phase are HS(aq)− and H2S(aq).
Figure 1: Illustrates the two main species of Hydrogen Sulfide present in anaerobic digester with respect to pH.
Source: (Okoro et al., 2019)
3.2 Desulfurization Methods
Desulfurization methods of hydrogen sulfide is are mainly classified into two different
categories; physico-chemical desulfurization and biological desulfurization.
If methanization or biomethanization (i.e. physico-chemical or biological upgrading of biogas to
nature gas quality) is to be performed, the concentration of hydrogen sulfide within raw biogas
must constantly be below <100ppm (Phelps et al., 2017).
9
3.2.1 Physico-Chemical Desulfurization
Physico-chemical desulfurization involve modifications in chemical and physical
phenomena in order to inhibit the formation of hydrogen sulfide in anaerobic digestion processes
(Okoro et al., 2019).
Precipitation strategy prevents dissolved sulfides to form hydrogen sulfide directly in the digester.
Here, additional chemicals are added that have a tendency to bind the solved sulfides to form
insoluble complexes or convert sulfides to elemental sulfur. The most common chemical additives
that are used to form metallic sulfur complexes are salts containing ferrous (Fe2+) and/or ferric iron
(Fe3+). This desulfurization method requires a pump to enable a continuous inflow of iron salts to
the digester, which results in an increased energy demand within the unit operation (Okoro et al.,
2019). Precipitation takes place directly in the anaerobic digester. A regeneration of sulfide is not
possible because of the high insolubility of the formed salts (Persson et al., 2006).
Absorption treatment involves direct contact between the contaminated biogas and water/or organic
solvents. Here, the binding properties of the constituents present in biogas are utilized in order to
enable a separation between the more polar H2S and CO2 and non-polar methane (Persson et al.,
2006). Absorption of H2S can either be carried out with water (physical absorption) or other organic
solvents (chemical absorption)- which enable a chemical conversion to metal sulfide or elemental
sulfur depending of the solvent used. Physical absorption involving water can be executed in spray
towers or packed beds. This method goes commonly by the name scrubbing. The disadvantage
with physical absorption methods is the requirement of large volumes of water in order to achieve
a full removal of H2S (if no recirculation of water is implemented) as well as the high pressure
demand for the scrubbing systems (Kapdi et al., 2005; Okoro and Sun, 2019). Scrubbing can also
be done with a water solution of sodium hydroxide. Here, NaOH reacts with H2S to form insoluble
salts as sodium sulfide and sodium hydrogen sulfide. Due to the insolubility of the salts, a
regeneration of sulfur is therefore not possible (Persson et al., 2006).
Adsorption over activated carbon (AC) is another desulfurization method that can be applied. Due
to AC’s large specific area and high adsorption capacity, H2S can directly be oxidized to elemental
sulfur and water. In order to furthermore increase the reaction rate of the oxidation reaction, AC
can be impregnated with sulfuric acid (H2SO4) or potassium iodide (KI). The negative aspects of
10
using impregnated AC rather than virgin AC lies within the regeneration of the adsorbent. When
virgin AC has been saturated with sulfur, regeneration of AC can be done in an oven. However,
since impregnated AC has been treated with various chemicals, regeneration cannot thus be
performed, and the AC must therefore be disposed (Persson et al., 2006; Awe et al., 2017).
3.2.2 Biological Desulfurization
Biological desulfurization utilizes various microorganisms in order to oxidize H2S to
mainly sulfates and elemental sulfur. The technical configuration of this desulfurization method
can be performed in-situ, where oxygen is introduced to the anaerobic digestor or with various
biofiltration technologies (Persson et al., 2006; Awe et al., 2017). The in-situ biotechnological
desulfurization will be discussed furthermore in chapter 4.
Bioscrubbing (BS) consists of two unit operations. In the first operation, microorganisms are
dispersed in liquid media and latter sprayed over the gas that is to be treated. The second unit
involves a biological treatment of the liquid containing the absorbed pollutants. The targeted gas
is treated in a gas-liquid contractor containing a packed bed, where a counter-current process
between the gas and the liquid media takes place (Van Groenestijn, 2001). The limitations that may
occur with bioscrubbers are the mass transfer limitations between the gas and the liquid. As
observed in some cases, the biodegradation can be the rate limiting step. However, if the system
retains high biomass concentration, the diffusion itself is considered to be the rate-limiting step.
Overall, this method has been liberally applied in purpose of removing H2S and volatile organic
compounds (VOC’s). In the terms of VOC, bioscrubbing has a higher removal efficiency of the
VOC’s than biotrickling filters (Koutinas et al., 2005).
Biofiltration (BF) as a desulfurization method is performed in a bioreactor, where biogas is
transferred through a packed filter material or beds of granular material. The filter or granular
material is infused with bacteria strains of Genera Thiobacillus, which are responsible of the
oxidation of H2S to its unharmful components (Sparks and Chase, 2016). Biogas is introduced in
the bottom of the bioreactor, whilst the water solution containing nutrients has its inflow on the
top. Biofiltration is thus defined as a counter-current system. Besides raw biogas, air is
simultaneously embedded in the gas inflow in order to maintain an optimal moisture balance in the
11
biofilm (Toledo-Cervantes et al., 2017). The nutrients in this desulfurization method are usually
added batch-wise to the bioreactor (Pathak et al., 2017). The main drawback with biofilters is the
poor microbial density in the biofilm, resulting in an overall decrease of bioreactor performance.
Another drawback with biofilters is the clogging tendency of the biofilm, which derives a higher
pressure drop and increased operation costs. (Schiavon et al., 2016; Toledo-Cervantes et al., 2017).
Biotrickling filters (BTF’s) is almost identical to BF’s in terms of operational set-up and function.
However, unlike in biofilters, the flow of the nutrient solution through the filter bed is continuous
(Pathak et al., 2017) Also, bedding in BTF’s consist of conventional instead of compost (Liu et al,
1999). The nutrient solution is either continuously trickled or circulated over the bed (Pathak et al.,
2017). Not only does the continuous flow provide enough nutrients to the biofilm, but it also
transports away microbial decomposition products and excess biomass. Parameters such as pH and
nutrient content is easier to control with a continuous flow over the reactor. The packed media has
therefore a lower clogging tendency, which drastically reduces the pressure drop within the
bioreactor (Schiavon et al., 2016). The biggest advantage with BTF’s are their high ability to
remove VOC’s, ammonia and other odor-causing compounds. The suggested reason behind this
high impurity removal efficiency could be the high internal biomass density within the fixed bed
(Liu et al., 1999).
As a conclusion, higher temperatures, pressures and requirement of additional chemicals are
needed in ability to perform physical-chemical desulfurization methods. Compared to
biotechnological desulfurization, chemical desulfurization therefore result in increased expenses in
the economical point of view as well as in a higher energy demand (Krayzelova et al., 2015). This
report will examine another biodesulfurization method that have gained a lot of attention these past
couple of years, microaeration (Nguyen and Khanal, 2018).
12
4 Principles of Microaeration
Microaeration is when a small amount of oxygen is introduced to an anaerobic digester to
enable both anaerobic and aerobic biological activities. It may seem contradictory of adding oxygen
to an anaerobic environment, considering methanogens and acetogens intolerance towards oxygen.
However, microaeration has on the contrary proven to be an effective way of removing hydrogen
sulfide from produced biogas as well as enhancing the overall process of AD (Botheju et al., 2011).
Microaeration enables a microbial respiration for one important culture of bacteria, sulfur oxidizing
bacteria (SOB). SOB are responsible for oxidizing hydrogen sulfide to elemental sulfur (Namgung
et al., 2014; Krayzelova et al., 2015). The main oxidation reactions of hydrogen sulfide taking
place in the reactor headspace of an AD are as follow (Buisman et al., 1990; Janssen et al., 1995;
Botheju and Bakke, 2011; Díaz et al., 2011; Chen et al., 2020).
2HS− + O2(g) → 2S0 + 2OH− Eq. 3
2HS− + 4O2(g) → 2SO42− + 2H+ Eq. 4
2HS− + 2O2(g) → 2S2O32− + H2O Eq. 5
Bioreactors come in many different configurations, i.e. continuous stirred tank reactor (CSTR); up-
flow anaerobic sludge blanket (UASB); fluidized bed reactor and anaerobic fixed film reactor.
Nonetheless, the two most widely used configurations are considered to be CSTR and UASB
(Wilkie et al., 2004; Kaparaju et al., 2009). Microaeration has successfully been implemented in
seven full-scale WWTP in central Europe between the year span of 2003-2015 as a goal to remove
hydrogen sulfide biochemically within biogas production. Successful H2S removal efficiencies
were obtained in full-scale WWTP (above 97%) even at high initial concentrations above 4000
mg/m3 (Fdz.-Polanco et al., 2009; Díaz et al., 2011; Jeníček et al., 2017).
4.1 Air Dosing Point
It has been researched upon whether it is better to have the air dosing point in the liquid phase
or in the gas phase in order to obtain the highest H2S removal efficiency. Air that was directly
dosed to the headspace (gas phase) resulted in a higher H2S removal efficiencies compared to the
13
air dosage performed in the aqueous phase (Díaz et al., 2011; Krayzelova et al., 2015; Sousa et al.,
2019). It was shown that air in headspace resulted in a cultivation of SOB, which are responsible
for sulfide oxidation (Díaz et al., 2011). According to Krayzelova, air dosage to the liquid phase
resulted in higher oxygen demand in the system. The reason behind this phenomenon is the
occurring oxidation of degradable organic compounds. The consequence of higher air dosage
increases therefore the impurity content of produced biogas due to the presence of nitrogen
(Krayzelova et al., 2015). It is important to take into account that mixing oxygen with biogas may
result in an explosion if the methane/air ratio is between 5-15% (Appels et al., 2008). Luckily, an
explosion in the reactor headspace is highly unlike to happen because of the low concentrations of
oxygen present in AD. Thus, oxygen is almost directly consumed by SOB when introduced to the
headspace. However, it is still important to take the explosion risk under consideration and make
sure that the AD system has no leakage (Jeníček et al., 2017; Sousa et al., 2019).
4.2 Positive and Negative Aspects of Microaeration
Not only does microaeration provide great removal of hydrogen sulfide, but microaeration
have also been observed to enhance the removal of volatile suspended solids (VSS) due to oxidation
of organic matter in AD (Jenicek et al., 2008). As mentioned above, hydrolysis is considered to be
the rate-determing step of the overall AD system. Botheju and Bakke (2011) suggest that the
enhanced hydrolysis depends on the amount of acidogenic biomass present in AD. Hydrolysis is
carried out by extracellular enzymes which are utilized by acidogens. Acidogens will obtain a
higher yield in the presence of O2, thus increasing its population and resulting in more hydrolysis
(Botheju and Bakke, 2011).
According to Botheju (2010), microaeration reduces the amount of volatile fatty acids (VFA’s)
present in AD. Botheju suggests that microaeration can therefore stabilize AD systems in the start-
up period, where the presence of VFA’s usually is higher. Lower presence of VFA’s prevent pH
drops in anaerobic digestors (Botheju and Bakke, 2011).
A research carried out by Wang et al. (2014) observed that microaeration had a positive impact on
a system recovery when the AD system was exposed to shock loading. It was suggested that
14
microaeration might be valuable in terms of restoring the metabolic activity of methanogens and
overall helping to reduce microbial inhibition caused by toxic pollutants (Wang et al., 2014).
One of the negative aspects of microaeration is the partial oxidation of organic matter in the liquid
phase of AD. Addition of oxygen may result in unnecessary oxidation processes within the sludge,
resulting in a higher chemical oxygen demand (COD). However, according to Krayzelova (2015),
oxygen that is added through microaeration gets consumed quickly by facultative bacteria when
introduced to the digester. The amount of COD did not change significantly and can thus be
neglected (Krayzelova et al., 2015).
Accumulation of elemental sulfur is considered to be a common problem in microaerated AD’s. If
not removed properly, the accumulation can lead to pipeline clogging or hindered mixing. Due to
sulfurs high molecular weight, a digester damage to overweight may occur in extreme cases if
sulfur is not continuously removed from the digester (Donoso-Bravo et al., 2018). However,
studies carried out by Díaz (2011) and Ramos (2014) showed little or no sulfur accumulation at all
respectively. Krayzelova (2014) observed that most of the elemental sulfur had fallen to the bottom
of the liquid phase and was latter removed alongside with the liquid effluent.
4.3 Process Control
4.3.1 Oxidation Reduction Potential (ORP)
Oxidation reduction potential ORP is a measurement method that measures electron activity in
aqueous solutions. Each biological system obtains a different ORP value (Khanal and Huang,
2006). ORP within biological desulfurization has proven to be an effective method to control the
oxygen dosage during microaeration, since ORP measures the tendency of an aqueous solution to
accept or donate electrons. ORP is a very sensitive method to measure even the slightest of changes
within the aqueous solution. This is because ORP expresses a linear relationship between
logarithmic concentration of oxygen and redox potential (Lipták and Venczel, 2016; Nguyen and
Khanal, 2018; Nguyen et al., 2019). The optimum ORP value for microaerobic systems varies from
a range 0mV to -300mV with respect to standard hydrogen electrode (SHE). All ORP values above
0mV represent aerobic conditions. Optimal ORP values as a target for a high sulfide removal
15
efficiency lies within the interval of -275mV to -265mV (Khanal and Huang, 2006). Other
frequently occurring redox pairs within AD such as SO42−/HS− (sulfidogenesis) and
CO2/CH4 (methanogenesis) obtain ORP values between -200mV and -300mV (Nguyen and
Khanal, 2018). With these specified values amongst many more within AD, ORP is therefore a
good control strategy when air is introduced to the liquid phase in an AD.
Another process control which can be applied within AD systems is proportional integral
derivative (PID), which is defined as a fixed-gain control system. PID is expressed by a
proportional, integral and a derivative algorithm. The proportional algorithm describes the present
error, integral algorithm the past error and derivative algorithm the future error. An anaerobic
process is defined as a non-linear system since the optimal state and conditions adjust over time.
Therefore, PID is considered not to be a suitable process controller if the circumstances change
within the AD system (such as substrate feed) (Åström and Hägglund, 2001; Bernard et al., 2001;
Nguyen et al., 2015). However, PID control has successfully been applied in a full-scale pilot plant
by Ramos (2014), which minimized the issue of excess substrate oxidation due to a more controlled
oxygen dosing (Ramos et al., 2014; Nguyen and Khanal, 2018).
16
5 Microbiology
5.1 Organisms Involved in AD
The organisms that are presented in AD are: hydrolytic bacteria (hydrolysis), fermentative
bacteria (acidogenesis & acetogenesis) and methanogens (methanogenesis). Bacteria that involve
the conversion of sulfur are called sulfate reducing bacteria (SRB) and sulfide oxidizing bacteria
(SOB). As described before, organic matter that is introduced to the anaerobic digester gets broken
down through series of processes. Here, products formed in a previous step could be used as a
substrate for the after following process i.e. formed intermediate products from acidogenesis are
used as substrate for the following acetogenesis-step. This type of symbiosis between bacteria is
abbreviated as a syntrophic relationship. It is important to maintain a balance between all factors
affecting the syntrophic relationship in order to maintain a steady system operation (Nguyen and
Khanal, 2018).
5.2 Sulfate Reducing Bacteria (SRB)
Sulfate reducing bacteria use organic carbon as an electron donor and sulfate as an electron
acceptor, where sulfate is latter reduced to sulfide (Hilton and Oleszkiewicz, 1988; Chen et al.,
2008). SRB can be divided into two different groups- incomplete and complete oxidizers. The
incomplete oxidizers oxidize i.e. acetate and lactate to CO2. The complete oxidizers transform
acetate to CO2 and HCO3− (Chen et al., 2008). SRB can metabolize long chain fatty acids (LCFA),
organic acids, aromatic compounds and alcohols. SRB can inhibit the overall AD process in two
different ways- directly or indirectly. Direct inhibition involves a competition of substrates (i.e.
acetate, hydrogen, propionate & butyrate) with other bacteria present in the system. Indirect
inhibition is defined as the poisoning of other bacteria in the system by producing excess amount
of sulfides ((Appels et al., 2008; Chen et al., 2008). SRB are the most important bacteria in matter
of degrading of propionate (Appels et al., 2008). However, SRB compete the most with
methanogens over H2, which affects the methane yield negatively (Appels et al., 2008). The general
reaction mechanism carried out by SRB is described below in equation 6.
SO42− + organic matter → HS− + H2O + HCO3
− Eq. 6
17
Furthermore, the SRB can also utilize elemental sulfur to form sulfates and H2S. This process is
described in equation 7 below (Finster 2008).
4S0 + 4H2O → SO42− + 2HS− + 5H+ Eq. 7
5.3 Sulfide Oxidizing Bacteria (SOB)
Sulfide oxidizing bacteria use electrons from oxygen (aerobic microbial species) or nitrates
(anoxic microbial species) (Janssen et al., 1998). SOB are divided into photoautotrophic bacteria
which use light as their energy resource, and chemolithotrophic bacteria where the energy is
obtained directly from oxidation reactions (Janssen et al., 1998). The electrons produced in the
oxidation process of sulfur compounds are taken up by dissolved oxygen, allowing the formation
of H2S. The most essential biological oxidation reactions of H2S done by the SOB in a microaerated
environment are described in equation 8-11 below (Tang et al., 2009).
H2S +1
2O2 → S0 + H2O, ΔG0 = −209.4kJ/reaction Eq. 8
S0 +3
2O2 + H2O → SO4
2− + 2H+, ΔG0 = −587.1kJ/reaction Eq. 9
H2S + 2O2 → SO42− + 2H+, ΔG0 = −798.2kJ/reaction Eq. 10
S2O32− + 2O2 + H2O → 2SO4
2− + 2H+, ΔG0 = −818.3kJ/reaction Eq. 11
5.3.1 Photoautotrophic SOB
Photoautotrophic convert H2S to elemental sulfur. The CO2 that is used by SOB as a carbon
source, is reduced and integrated to other organic components. Photoautotrophic bacteria have a
very slow cultivating rate, which demands a system optimization in order to provide the bacteria a
necessary amount of light. As a consequence, operational costs will increase. However, the growth
of photoautotrophic bacteria doesn’t have to depend on litotrophy. If there is a sufficient amount
of suitable organic matter, the bacteria growth can be stimulated by the presence of a carbon source
(Pokorna-Zabranska 2015).
18
5.3.2 Chemolithotrophic SOB
Chemolithotrophic SOB use energy that is released from oxidation of various sulfur species
occurring in AD as their primary metabolic energy resource. (Pokorna and Zabranska, 2015) These
SOB can be divided into four different subgroups of species; obligate chemolithotrophs, facultative
chemolithotrophs, chemolithoheterotrophs and chemoorganoheterotrophs (Tang et al., 2009).
- Obligate chemolithotrophs (i.e. Thiobacillus, Thiomicrospira) use CO2 as carbon source (Tang
et al., 2009; Pokorna and Zabranska, 2015).
- Facultative chemolithotrophs (i.e. some Thiobacillus, Thermotrix and Paracoccus
denitrificans) can cultivate chemolithoautotrophically with CO2 and other inorganic
components as energy resource. They can also cultivate heterotrophically with complex
organic components or mixotrophically where the bacteria can use both CO2 and complex
organic components as energy resources (Tang et al., 2009; Pokorna and Zabranska, 2015).
- Chemolithoheterotrophs (i.e. Thiobacillus & Beggiatoa) generate energy from oxidation of
reduced sulfur compounds. These bacteria are not able to utilize carbon dioxide as an energy
resource (Tang et al., 2009; Pokorna and Zabranska, 2015).
- Chemoorganoheterotrophs (i.e. Thiobacterium & Thiotrix) are able to utilize the energy of the
oxidizing process of reduced sulfur (Tang et al., 2009; Pokorna and Zabranska, 2015).
The most common SOB bacteria observed in the headspace of a microaerated AD are various forms
of Proteobacteria. (Díaz et al., 2011; Ramos et al., 2014; Pokorna and Zabranska, 2015).
5.4 Biofilm
The biofilm compartment in a microaerobic digester consists of an aerobic zone, anoxic zone
and an anaerobic zone. The outermost layer exposed to the headspace is assumed to mostly contain
SOB. Continuing deeper into the biofilm layer where anoxic conditions prevail, SRB will be
assumed to be the most dominating species. The deeper most layer of the biofilm favors the
metabolism of methanogens because of the anaerobic environment (Li et al., 2019). The
characteristics of the biofilm in an AD will in this report be assumed to be of the same character as
the biofilms present in well-ventilated sewer systems, which were described more detailed than
19
microaerobic biofilms in the digestors. The biofilm in sewer systems is described in chapter 5.4.1
below.
5.4.1 Biofilm in Sewer Systems
In general, the commercial operation of sewage systems can be divided into gravity sewers
and pressure sewers. Different operation methods result therefore in different biofilms. The main
difference between sewer biofilms lies in the concentration of dissolved oxygen (DO). Sewer
systems operated with gravitational forces tend to have higher concentrations of DO (Li et al.,
2019). The reason behind this is that the pipes are only partially filled with sewage, allowing
enough space for a gas-phase to co-exist in the pipe (Li et al., 2017). The most dominant
microorganisms in a well-ventilated sewer biofilm are aerobic and anoxic bacteria, such as SOB
and denitrifying bacteria. These two bacteria lead to an oxidation of H2S and a reduction of nitrate
respectively (Chen and Leung, 2000; Li et al., 2019). The concentration of dissolved oxygen
decreases with an increase of the biofilm depth. These conditions favor therefore the metabolisms
of SRB and methanogens, which perform the sulfate reduction and methane production
respectively (Marjaka et al., 2003; Li et al., 2019).
5.5 Reverse Reduction
By a brief observation of equations 7-10 in chapter 5 above, one can see that the presence of
oxygen is a crucial parameter for the overall microbial metabolism of the SOB. Oxygen limiting
conditions are known to inhibit the sulfide oxidation capability. Furthermore, the oxygen limitation
can also result in a poor microbial growth of the SOB, resulting in a decreased sulfide removal
degree in a reactor (Tang et al., 2009). The dominating bacteria in anoxic – anaerobic environment
will therefore be SRB and other anaerobes, which will thrive more in oxygen limiting conditions.
Since the SRB are responsible for the H2S formation, the overall uptake of H2S by SOB won’t be
as effective due to a shortage of the SOB in the outermost layer of the biofilm and a potential
reverse reduction of the created sulfates by SRB. This result thus in an accumulation of H2S in the
gas phase, which can potentially either cause a microbial collapse in an AD or corrosion damages
in the equipment. The symbiosis between SRB and SOB are therefore of a great importance when
20
it comes to an efficient biological removal of hydrogen sulfide. The reverse reduction consists of
the following 4 steps:
1. Uptake of H2S by SOB and conversion to elemental sulfur in microaerobic conditions.
2. Uptake of elemental sulfur by SOB and oxidation to sulfate ions in microaerobic conditions.
3. The sulfate ions are then utilized by the SRB, which reduce the sulfate ion back to hydrogen
sulfide. Elemental sulfur can also be utilized by SRB to form elemental sulfur.
4. Hydrogen sulfide will again be oxidized by the SOB to sulfates, closing the reverse
reduction cycle.
21
6 Mathematical Modelling
Mathematical models are a crucial aspect within the development and optimization of WWTP.
A simulation allows a scientist to evaluate multiple operating conditions and predict different
treatment scenarios. A mathematical model enables a deeper understanding when optimizing,
evaluating, planning, designing and problem solving work of currently existing WWTPs (Boltz et
al., 2010). As a result of immense studies, existing WWTP simulators have expanded to include a
biofilm reactor model. This biofilm reactor model can for instance describe one-, two- or even three
dimensional numerical description of a biofilm (Boltz et al., 2010). A general biofilm model is
based on Fick’s Law, Monod-type kinetics, Navier-Stokes law and other mass balance equations
which are important for the description on the ongoing chemical reactions and conversions
(Wanner and Reichert, 1996).
6.1 Anaerobic Digestion Model No. 1 (ADM1)
ADM1 is a mathematical model which was stablished at the 8th World Congress on
Anaerobic Digestion on the year of 1997 in Japan. The aim with the developed mathematical model
was to define a universal mathematical description of an anaerobic digester, including the ongoing
chemical reactions and processes that take place within the digester itself. ADM1 describes both
the physical and biochemical conversion processes present in an AD. The model has been widely
accepted and therefore frequently used for the purpose of optimization and designing of a full-scale
WWTP, as mentioned above (Wanner and Reichert, 1996; Batstone et al., 2002).
The biochemical processes in ADM1 consist of the essential anaerobic processes such as
disintegration; hydrolysis; acidogenesis; acetogenesis and methanogenesis. Besides the
biochemical processes, physico-chemical processes, which are not affected by micro-organisms,
are also a part of the ADM1 model. Liquid-liquid reactions (rapid ion association/dissociation),
gas-liquid exchanges (gas transfer) and liquid-solid transformations (precipitation and
solubilization of ions) are the building constituents of physico-chemical processes within the
model. It is of great importance to include the physico-chemical processes, since inhibitions factors
(i.e. pH, free acids/bases and dissolved gas concentrations) can thus be expressed (Batstone et al.,
2002).
22
Although ADM1 has been widely used in order to mathematically model the anaerobic treatment
of wastewater, it does however lack a description of the ongoing processes of sulfate reduction
within the AD (Batstone et al., 2002). Therefore, an extended version of ADM1 (ADM1-S/O) has
been developed by Pokorna-Krayzelova (2017), in which sulfate reduction and sulfide oxidation
(microaeration) has been incorporated to the original ADM1 model.
6.2 Mathematical Equations in ADM1
6.2.1 Mass Balance
A mass balance is required for a proper description of the mass transfer across the system
boundaries. The mathematical equation of a mass transfer can be described as:
dMsys
dt= min − mout + r Eq. 12
Where min and mout is the mass flow rates to and from the system respectively in units (mass/time).
Msys is the total mass in the system as a function over time. The overall generation rate is expressed
as r and is defined as a sum of all the different rates influencing a specific compound. The overall
generation rate is obtained from equation 13 below (Batstone, 2006) .
𝑟 = ∑ 𝜌𝑖𝑛 , where 𝜌𝑖…𝑛 are different conversion rates. Eq. 13
6.2.2 Kinetics
Any type of disintegration of a substrate or a decay of a specific microorganism can be
mathematically described as a first order kinetic equation (Batstone et al., 2002):
𝑑𝑆
𝑑𝑡= 𝐾𝑆,𝑚𝑎𝑥 ∙ 𝑆 Eq. 14
Where KS,max is the constant for maximum decay rate of a specific substrate of amount S.
23
Biological activity (growth rate) can be described kinetically by Monod (Michaelis-Menton)
mathematical relationship. The equation of Monod-type kinetics is expressed as equation 15 below
(Chezeau and Vial, 2019).
𝜇 = 𝜇𝑚𝑎𝑥 ∙𝑆
𝐾𝑠+𝑆 Eq. 15
Where 𝜇 is the specific growth rate (h-1), 𝜇𝑚𝑎𝑥 the maximum specific growth rate, KS the Monod
half-saturation constant (g/L) and S the limiting substrate concentration (g/L).
The Monod type kinetics can be modified to include several substrates. Furthermore, the kinetic
expression can be generalized to express substrate inhibition on the bacterial growth rate. This
variation of kinetic equation is expressed below in equation 16 (Chezeau and Vial, 2019).
𝜇 = 𝜇𝑚𝑎𝑥 ∙𝑆
(𝐾𝑠+𝑆)+(𝑆2
𝐾𝐼) Eq. 16
Where KI is the substrate inhibition constant in (g/L).
A linearized version of equation 15, is presented below in equation 17. This version is preferable
when describing more complex mechanisms- such as consecutive and parallel reaction pathways,
where biomass is assumed to change over time. Here, 𝜇𝑚𝑎𝑥 and 𝐾𝑠 can be deducted by linear
regression analysis (Chezeau and Vial, 2019).
𝑑𝑋
𝑑𝑡= 𝑟𝑥 = 𝜇𝑚𝑎𝑥
𝑆
𝐾𝑠+𝑆∙ 𝑋 Eq. 17
Here, X is variable for the biomass (g/L) and S for the substrate (g/L).
24
6.3 ADM1-S/O
ADM1-S/O is an extended version of ADM1 done by Pokorna-Krayzelova in 2017. In this
extension, four processes of sulfate reduction (by SRB) (Fedorovich et al., 2003; Batstone, 2006)
and one additional process of sulfide oxidation (by SOB) was added to the ADM1 matrix.
The four biochemical reduction reactions which are performed by SRB are (Pokorna-Krayzelova
et al., 2017; Ahmed et al., 2018) :
The conversion of butyrate and sulfate to acetate and hydrogen sulfide by bSRB (Eq. 18):
C3H7COOH +1
2SO4
2− + H+ → 2CH3COOH +1
2H2S Eq. 18
Conversion of propionate and sulfate to acetate and hydrogen sulfide by pSRB (Eq. 19):
C2H5COOH +3
4SO4
2− +3
2H+ → CH3COOH + CO2 +
3
4H2S + H2O Eq. 19
Conversion of acetate and sulfate to carbon dioxide and hydrogen sulfide by aSRB (Eq. 20):
CH3COOH + SO42− + 2H+ → 2CO2 + H2S + 2H2S Eq. 20
Conversion of hydrogen- and sulfuric acid to hydrogen sulfide by hSRB (Eq. 21):
H2 +1
4SO4
2− +1
2H+ →
1
4H2S + H2O Eq. 21
The additional oxidation process that has been added to the ADM1-S/O model is the biochemical
oxidation of H2S to elemental sulfur by SOB (Jensen et al., 2011). The chemical reaction for this
process is described below in (Eq. 22):
H2S +1
2O2 → S0 + H2O Eq. 22
The biochemical processes for the uptake of substrate and decay of the bacteria can be described
in the form of Monod-type kinetics and first order kinetics respectively. It is also important to
consider the various inhibition factors present in the reduction processes performed by the SRB.
Additional details and information regarding the extended ADM1-S/O model can be found in
Pokorna-Krayzelova’s publication ‘’Model based optimization of microaeration for biogas
desulfurization in UASB reactors’’ (2007).
25
7 Mathematical Modelling of Reverse Reduction
According to the extent of the literature study done on reversed reduction of sulfur and sulfates, an
extended mathematical model has not yet been created for this particular type of biological process.
As mentioned above, an extended version of ADM1 (ADM1-S/O) was developed by Pokorna-
Krayzelova (2107) which included four processes of sulfate reduction performed by the SRB and
one additional sulfide oxidation process performed by the SOB. The mathematical model created
to describe reverse reduction included furthermore the reduction process of elemental sulfur to
form H2S done by SRB.
7.1 Definition of Compartments
A mathematical model was established around two involved compartments; the biofilm and
the headspace in order to describe the reversed reduction of oxidized sulfur forms (elemental sulfur
and sulfates). An illustration of the compartments including the ongoing chemical processes is
presented below in figure 2. The equilibrium between the biofilm compartment and the headspace
compartment is described with Henry’s Law [Eq. 23](Payne, 2017).
𝐶𝐴,𝑙𝑖𝑞 = 𝐾𝐻 ∙ 𝑃𝐴,𝑔𝑎𝑠 [Eq. 23]
Where CA,liq is the concentration of a gas in the liquid phase, KH Henry’s law constant
(characterized for every individual gas), PA,gas the partial pressure of a gas in the gas phase.
Hydrogen sulfide present in the headspace (before the start of microaeration), will be taken up by
the SOB and oxidized to elemental sulfur [Eq. 24]. Elemental sulfur will then be taken up by both
SOB and SRB. The SOB will oxidize elemental to sulfate [Eq. 25] and the SRB will reduce
elemental sulfur back to H2S [Eq. 26]. The sulfate ions will be utilized by SRB as an electron donor
and be reduced back to H2S [Eq. 27]. The decay rate for both SOB and SRB are also incorporated
to the mathematical model [Eq.28-29]. Organic matter from decayed bacteria were used as a
substrate for the SRB, which was calculated by multiplying bacteria concentration with decay rate
of both defined type of bacteria. For the calculations involving stochiometric coefficients, organic
matter was simplified and expressed as C6H12O6. The pH decreases in the direction of the deeper
most layer to the outermost (Li et al., 2017). Diffusivity of the gases O2 and H2S was also
incorporated to the mathematical model. The matrix for the mathematical model including the
26
process rates and stochiometric coefficients can be found in table 1. Calculation of stochiometric
coefficients is presented in chapter 12 under appendix. The kinetic parameters for the process rates
are listed in table 2. The chemical oxidation of H2S in the headspace is described by chemical
oxidation rate (Pokorna-Krayzelova et al., 2018) [Eq. 30].
The mathematical model was implemented in Aquasim 2.0 (Reichert, 1998). Since this model only
is defined around the biofilm and headspace compartment, pH inhibition was neglected. pH
inhibition is important to consider when creating a model around a liquid-phase compartment
containing granular sludge (Pokorna-Krayzelova et al., 2017). pH is also assumed to be constant,
meaning that acid-base equilibrium is not included in the model. Decayed bacteria are assumed to
be utilized as a carbon source for the SRB and CO2 for the SOB. The oxygen introduced to the
headspace is assumed to be utilized only by SOB and not the organic substrate. The biological
oxidation of H2S is assumed to be faster than the chemical oxidation.
Figure 2: Illustrates the biofilm- and headspace compartments in which reversed reduction takes place.
27
7.2 Kinetic Expressions Involved in Reverse Reduction
The five kinetic expressions that will be utilized for the mathematical modelling will be the
ones used in an extended version of ADM1 (ADM1-S/O), developed by Pokorna-Krayzelova
(2017). As described in chapter 6.3, four processes of sulfate reduction and one process for
sulfide oxidation was included in the mathematical model.
The uptake and reduction of H2S to elemental sulfur (by SOB) is described in equation 24.
ρ = km,SOBSH2S
Ks,H2S+SH2SXSOB
SO2
Ks,O2+SO2
[Eq. 24]
Where ρ is the overall process rate (g/L,h) X is the concentration of SOB biomass (g/L), S the
substrate concentration (g/L), km the maximum uptake rate (mmol S/mg CODX, h).
Uptake of elemental sulfur and oxidation to sulfate (by SOB) is described below in equation 25:
ρ = km,SOBSS
Ks,S+SSXSOB
SO2
Ks,O2+SO2
[Eq. 25]
Uptake of sulfate and elemental sulfur (by SRB) are expressed as equation 26 and 27
respectively. The maximum uptake rate km is assumed to be same for both uptake processes.
ρ = km,S,SRBSorg
Korg+SorgXSRB
S𝑆0
Ks,𝑆0+S𝑆0 [Eq. 26]
ρ = km,SO42−,SRB
Sorg
Korg+SorgXSRB
S𝑆𝑂4
2−
Ks,S𝑂4
2−+SS𝑂4
2− [Eq. 27]
The decay of the SOB and SRB in the biofilm compartment are described by first order kinetic
equations (equation 28-29):
28
𝜌 = 𝑘𝑑𝑒𝑐,𝑋𝑆𝑂𝐵 ∙ 𝑋𝑆𝑂𝐵 [Eq. 28]
𝜌 = 𝑘𝑑𝑒𝑐,𝑋𝑆𝑅𝐵 ∙ 𝑋𝑆𝑅𝐵 [Eq. 29]
Where kdec is the decay rate of a specific bacteria (1/h).
The chemical oxidation rate of H2S in headspace compartment is described in equation 30. Here,
concentrations of both oxygen and hydrogen sulfide was taken under consideration and
implemented in the equation.
𝑅𝑐ℎ𝑒𝑚.𝑜𝑥 = 𝑘𝑚,𝑐ℎ𝑒𝑚.𝑜𝑥 ∙ (𝑆𝐻2𝑆)𝛼 ∙ (𝑆𝑂2)𝛽 [Eq. 30]
Where 𝛼 and 𝛽 are the reaction orders, 𝑘𝑚,𝑐ℎ𝑒𝑚.𝑜𝑥 the rate constant for chemical oxidation of H2S.
SH2S and SO2 are the concentrations in (g/L).
7.3 Testing of the Mathematical Model
To assure that the mathematical model works and that the microaeration is properly
functioning in the model, H2S concentration was observed in both headspace compartment and
biofilm compartment. In this simulation, the oxidation processes performed by the SOB and the
reduction processes for SRB were activated. The concentration profiles for H2S in both
compartments were plotted with different initial concentrations of O2 in headspace. Two different
scenarios were observed; the first scenario was simulated under microaerobic conditions (0.5 mmol
O2/L) whilst the other scenario was simulated under oxygen limiting conditions (0.0005 mmol
O2/L). Initial H2S concentration was held constant at 0.05 mmol/L as well as the biofilm thickness
LFSS at 0.015m.
29
The simulation indicates a fully functioning mathematical model. Results in Graph 1 show that
under O2-limiting conditions, H2S consumption by the SOB in the headspace is much slower
compared with a micro-aerated system. Kinetics of H2S removal are observed to be greater for a
micro-aerated process, indicating a good overall H2S removal efficiency. After 0.2 hours, H2S was
completely consumed by the SOB in the micro-aerated environment. In contrast, H2S was reduced
to a concentration of 0.01675 mmol/L after 0.2 hours. Graph 2 shows an increase and accumulation
of produced H2S by the SOB in the biofilm. After 0.123 h, H2S concentration peaks at a maximum
of 0.03282 mmol/L which is followed by a slow decrease of H2S concentration. This decrease is
due the equilibrium (Henry’s Law) shift towards the headspace compartment. This because the
concentration of H2S in headspace after 0.123 hours is 0.01687 mmol/L compared with the higher
H2S concentration in biofilm of 0.03282 mmol/L.
0
0,01
0,02
0,03
0,04
0,05
0,06
0 0,1 0,2 0,3 0,4
Co
nce
ntr
atio
n [
mm
ol/
]
Time [h]
H2S Concentration in Headspace Compartment
Microaeration (0.5 mmolO2/L)
Oxygen limiting (0.0005mmol O2/L)
Graph 1: Illustrates H2S concentration in the headspace
compartment with varied initial concentrations of O2.
Graph 2: Illustrates H2S concentration in the biofilm compartment
with varied initial concentrations of O2.
0
0,005
0,01
0,015
0,02
0,025
0,03
0,035
0 0,1 0,2 0,3 0,4
Co
nce
ntr
ati
on
[m
mo
l/L]
Time [h]
H2S Concentration in Biofilm Compartment
Micraeration (0.5 mmolO2/L)
Oxygen limiting (0.0005mmol O2/L)
29
Table 1: Matrix Used for the Mathematical Modelling of Reverse Reduction
Components
→ S𝐇𝟐𝐒 SHS- 𝐒𝐬 S𝐎𝟐
S𝐒𝐎𝟒𝟐- S𝐒𝟐𝐎𝟑
𝟐- 𝐒𝐨𝐫𝐠 𝐗𝐂 𝑿𝐒𝐎𝐁 𝑿𝐒𝐑𝐁
Processes ↓ Process rate ρ, [𝐠/𝐋 ∙ 𝐡] ↓ Eq.
Uptake of H2S by SOB
−1 +1 − (16 − YSOB
32)
YSOB ρ = km,SOB
SH2S
Ks,H2S + SH2S
XSOB
SO2
Ks,O2+ SO2
𝟐𝟒
Uptake of S0 by SOB
−1 − (48 − YSOB2
32) +1 YSOB2 ρ = km,SOB
SS
Ks,S + SS
XSOB
SO2
Ks,O2+ SO2
𝟐𝟓
Uptake of
SO42- by SRB
(1 − YSRB
64) − (
1 − YSRB
64) −1 YSRB ρ = km,SRB,SO4
2−
Sorg
Korg + Sorg
XSRB
S𝑆𝑂42−
Ks,S𝑂42− + SS𝑂4
2− 𝟐𝟔
Uptake of S0
by SRB (
YSRB − 1
112)
− (YSRB − 1
112) −1 YSRB ρ = km,SRB,𝑆0
Sorg
Korg + Sorg
XSRB
S𝑆0
Ks,𝑆0 + S𝑆0 𝟐𝟕
Decay of SOB +1 −1 𝜌 = 𝑘𝑑𝑒𝑐,𝑋𝑆𝑂𝐵 ∙ 𝑋𝑆𝑂𝐵 𝟐𝟖
Decay of SRB +1 −1 𝜌 = 𝑘𝑑𝑒𝑐,𝑋𝑆𝑅𝐵 ∙ 𝑋𝑆𝑅𝐵 𝟐𝟗
Chemical oxidation of H2S
−1 −1 +
1
2
𝑅𝑐ℎ𝑒𝑚.𝑜𝑥 = 𝑘𝑚,𝑐ℎ𝑒𝑚.𝑜𝑥 ∙ (𝑆𝐻2𝑆)𝛼 ∙ (𝑆𝑂2)𝛽 𝟑𝟎
Composition
matrix
G per COD
per unit
64 64 48 −32 0 64 1 1 1 1
Mole S per unit
1 1 1 0 1 2 0 0 0 0
Hyd
rog
en
su
lfid
e
(mm
ol
S/
L)
Hyd
rog
en
su
lfid
e
ion
(m
mo
l S/
L)
Ele
men
tal
sulf
ur
(m
mo
l S/
L)
Oxyg
en
(m
mo
l O
2/
L)
To
tal
sulf
ate
(m
mo
l S/
L)
Th
iosu
lfate
(m
mo
l S/
L)
Org
an
ic s
ub
stra
te
(mm
ol/
L)
Co
mp
osi
tes
(g
CO
D/
L)
SO
B d
eg
rad
ers
(g
CO
D/
L)
SR
B d
eg
rad
ers
(g
CO
D/
L)
30
Table 2: Kinetic Parameters and Coefficients
Parameter Value Unit Reference
Reaction order
𝜶 1.1 − Pokorna-Krayzelova et al., (2018b)
𝜷 0.9 − Pokorna-Krayzelova et al., (2018b)
Gas Diffusivity
𝑫𝑯𝟐𝑺 0.294 m2/h (Laby, 1986; Stewart, 2003)
𝑫𝑶𝟐 0.3 m2/h (Laby, 1986; Stewart, 2003)
𝑫𝑺 0.294 m2/h (Laby, 1986; Stewart, 2003)
Decay rate
𝒌𝒅𝒆𝒄,𝑿𝑺𝑶𝑩 0.0024 1/h (Wanner and Gujer, 1986)
𝒌𝒅𝒆𝒄,𝑿𝑺𝑹𝑩 0.00038 1/h (Batstone et al., 2002)
Henry’s law constants with T-terms
𝑲𝑯,𝑯𝟐𝑺 0.10000 ∙ 𝑅𝑇 ∙ exp (
−17459
100𝑅∙ (
1
𝑇𝑆𝑇𝐷
−1
𝑇))
− (Sander, 2015)
𝑲𝑯,𝑶𝟐
0.00130 ∙ 𝑅𝑇 ∙ exp (−12471
100𝑅∙ (
1
𝑇𝑆𝑇𝐷
−1
𝑇))
− (Sander, 2015)
Mass flux coefficient
𝒌𝑳𝒂 𝑩𝑭 10 L/h Adjusted in Aquasim
Maximum uptake rates
𝒌𝒎,𝑯𝟐𝑺,𝑺𝑶𝑩 482 mmol S/mg CODX, h Pokorna-Krayzelova et al., (2018b)
𝒌𝒎,𝑺,𝑺𝑶𝑩 0.001 mmol S/mg CODX, h Pokorna-Krayzelova et al., (2018b)
𝒌𝒎,𝑺𝑶𝟒𝟐−,𝑺𝑹𝑩 0.015 mmol S/mg CODX, h (Batstone, 2006)
𝒌𝒎,𝑺,𝑺𝑹𝑩 0.015 mmol S/mg CODX, h Adjusted in Aquasim
Half saturation constants
𝑲𝒔,𝑯𝟐𝑺,𝑺𝑶𝑩 0.001 mmol S/L Pokorna-Krayzelova et al., (2018b)
𝑲𝒔,𝑶𝟐,𝑺𝑶𝑩 0.1 mmol 𝑂2/L Pokorna-Krayzelova et al., (2018b)
𝑲𝒔,𝑺,𝑺𝑶𝑩 0.001 mmol S/L Pokorna-Krayzelova et al., (2018b)
𝑲𝒔,𝑺𝑶𝟒𝟐−,𝑺𝑹𝑩 0.1 mmol S/L (Batstone, 2006)
𝑲𝒔,𝑺,𝑺𝑹𝑩 0.001 mmol S/L Adjusted in Aquasim
𝑲𝒔,𝒐𝒓𝒈,𝑺𝑹𝑩 4 ∙ 10−6 mmol COD/L Adjusted in Aquasim
Rate constant for chemical ox. of H2S
𝒌𝒎,𝒄𝒉𝒆𝒎𝒐𝒙 0.001 1/h Pokorna-Krayzelova et al., (2018b)
Biomass yield
𝒀𝑺𝑶𝑩 10.37 mg COD/mmol S Pokorna-Krayzelova et al., (2018b)
𝒀𝑺𝑹𝑩 0.8 mg COD/mmol S (Batstone, 2006)
30
8 Results and Discussion
8.1 Sulfur Species in Biofilm Compartment Including and Excluding SRB
The purpose for this specific simulation was to observe whether the reverse reduction
performed by SRB had a significant impact on the H2S concentration in the biofilm compartment.
The initial conditions of H2S and O2 concentrations were both set to 0.5 mmol/L. The concentration
profiles of elemental sulfur, sulfates and H2S were studied in presence and absence of the SRB
reduction reactions. The involved chemical processes for the SOB were activated in both scenarios.
The results are presented below in graphs 3-4.
Comparing the two scenarios above, H2S concentration for the simulation including SRB has a
visibly higher value compared to the simulation without SRB. A concentration maximum is
obtained for both scenarios after 0.006 hours. For the scenario excluding the SRB, the maximum
H2S concentration was 0.0477 mmol/L whilst for the scenario without the SRB, the concentration
obtained a higher value of 0.0615 mmol/L. These results indicate that with the presence of SRB,
the processes for reversed reduction of sulfur and sulfates take place in the biofilm.
0
0,01
0,02
0,03
0,04
0,05
0,06
0,07
0,08
0 0,1 0,2 0,3 0,4
Co
nce
ntr
atio
n [
mm
ol/
L]
Time [h]
Sulfur Species in Biofilm CompartmentWithout SRB's
Initial conditions: O2: 0.5 mmol/L, H2S: 0.5 mmol/L
Elemental Sulfur
H2S
Sulfate
0
0,01
0,02
0,03
0,04
0,05
0,06
0,07
0,08
0 0,1 0,2 0,3 0,4
Co
nce
ntr
atio
n [
mm
ol/
L]
Time [h]
Sulfur Species in Biofilm CompartmentWith SRB's
Initial conditions: O2: 0.5 mmol/L, H2S: 0.5 mmol/L
Elemental Sulfur
H2S
Sulfate
Graph 3: Illustrates concentration profiles for sulfur species
present in the biofilm without the biochemical processes for SRB’s.
Graph 4: Illustrates concentration profiles for sulfur species
present in the biofilm with the biochemical processes for SRB’s.
30
8.2 H2S Concentration in Headspace Including and Excluding SRB
Since the reverse reduction had an impact of the total amount of produced H2S in biofilm,
it is therefore of interest to see if this supplementary H2S has an impact on the total H2S
concentration in the headspace. Two scenarios were one again observed, one in which the SRB
processes included and in the second where SRB reduction processes were muted. The initial
concentrations of H2S and O2 were both set to 0.5 mmol/L. The results for both simulations were
plotted in the same graph, which is presented below as graph 5.
Graph 5: Illustrates H2S concentration profiles in headspace for the simulations performed with and without SRB.
An interpretation of the results demonstrates a very small difference between the obtained H2S
concentration profiles in headspace. This small concentration difference does not inhibit the
removal rate of the H2S in the headspace. For both scenarios, the approximate amount of time
that it takes for the H2S concentration to be consumed by the SOB is 0.2 hours. After 0.2 hours
the concentration for the scenario including SRB was decreased to 4,54 ∙ 10−4 mmol/L, while
for the scenario without the H2S concentration was decreased to 4,49 ∙ 10−4 mmol/L. It can be
concluded that the kinetics for the H2S removal are greater than the kinetics of the reversed
reduction, in which H2S formed. Thus, when there is enough oxygen provided to SOB, the
reverse reduction will not affect the concentration of H2S in headspace.
0
0,1
0,2
0,3
0,4
0,5
0,6
0 0,1 0,2 0,3 0,4
Co
nce
ntr
atio
n [
mm
ol/
L]
Time [h]
H2S in Headspace CompartmentWith and Without SRB's
Initial conditions: O2: 0.5 mmol/L, H2S: 0.5 mmol/L
With SRB's
Without SRB's
30
8.3 Variation of Initial H2S Concentration in Headspace
Here, the initial H2S concentration in headspace was varied between: 0.05 mmol/L, 0.5
mmol/L, 1.0 mmol/L and 2.0 mmol/L respectively. O2 concentration was kept constant in this
simulation at a stochiometric value of 0.5 mmol/L. The biofilm thickness (LSSS) was held at
0.015m. The oxidation processes for SOB were constantly activated in the simulation. Two
simulation scenarios were carried out similarly the ones above- one including the biochemical
reactions performed by the SRB and the other without. The purpose with this simulation was to
observe how the presence and absence of SRB affected the H2S in the headspace compartment
with different initial H2S concentrations stated above. The results are presented below in graphs
6-7.
Results from both simulations suggest that reverse reduction did have almost no influence on the
overall H2S removal rate in the headspace compartment for all of the different initial H2S
concentrations. The different H2S concentrations are due to the tabulated maximum uptake rate of
SOB, which was defined as a constant in the model.
0
0,2
0,4
0,6
0,8
1
0 0,05 0,1 0,15
Co
nce
ntr
atio
n [
mm
ol/
L]
Time [h]
H2S Concentration in Headspace Without SRB's(With diffirent initial H2S concentrations)
Initial conditions: O2: 0.5 mmol/L, LFss: 0.015 m
0.05 mmol/L
0.5 mmol/L
1 mmol/L
0
0,2
0,4
0,6
0,8
1
0 0,05 0,1 0,15
Co
nce
ntr
atio
n [
mm
ol/
L]
Time [h]
H2S Concentration in Headspace With SRB'S(With different initial H2S concentrations)
Initial conditions: O2: 0.5 mmol/L, LFss: 0.015 m
0.05 mmol/L
0.5 mmol/L
1 mmol/L
Graph 6: Illustrates H2S concentration profiles with different
initial start concentrations. SRB’s were excluded in this simulation.
Graph 7: Illustrates H2S concentration profiles with different
initial start concentrations. SRB’s were included in this simulation.
30
9 Conclusions
The conclusions that can be drawn from this thesis are as follow:
- A mathematical model was successfully developed to describe the reverse reduction.
- Based on the results, is can be concluded that the reverse reduction has no observed impact
on the overall hydrogen sulfide removal process in the headspace compartment.
- Based on the developed model, sulfur is assumed to be the main substrate for the SRB, since
sulfate production was negligible.
- Considering the fact that concentration of H2S increased in the biofilm, it would be assumed
that more O2 is required within the microaeration to ensure a good H2S removal. However,
the observed simulation results in headspace compartment indicate a barely perceptible
difference.
30
10 References Ahmed, W. and Rodríguez, J. (2018) ‘Modelling sulfate reduction in anaerobic digestion: Complexity evaluation and parameter
calibration’, Water Research. Elsevier Ltd, 130, pp. 255–262. doi:
10.1016/j.watres.2017.11.064.
Appels, L. et al. (2008) ‘Principles and potential of the anaerobic digestion of waste-activated sludge’, Progress in Energy and
Combustion Science. Pergamon, pp. 755–781. doi:
10.1016/j.pecs.2008.06.002.
Ariunbaatar, J. et al. (2014) ‘Pretreatment methods to enhance anaerobic digestion of organic solid waste’, Applied Energy.
Elsevier Ltd, pp. 143–156. doi: 10.1016/j.apenergy.2014.02.035.
Åström, K. J. and Hägglund, T. (2001) ‘The future of PID control’,
Control Engineering Practice. Pergamon, 9(11), pp. 1163–1175. doi: 10.1016/S0967-0661(01)00062-4.
Awe, O. W. et al. (2017) ‘A Review of Biogas Utilisation,
Purification and Upgrading Technologies’, Waste and Biomass
Valorization. Springer Netherlands, pp. 267–283. doi: 10.1007/s12649-016-9826-4.
Batstone, D. J. et al. (2002) ‘The IWA Anaerobic Digestion Model
No 1 (ADM1).’, Water science and technology : a journal of the
International Association on Water Pollution Research. IWA Publishing, 45(10), pp. 65–73. doi: 10.2166/wst.2002.0292.
Batstone, D. J. (2006) ‘Mathematical modelling of anaerobic
reactors treating domestic wastewater: Rational criteria for model use’, Reviews in Environmental Science and Biotechnology, pp.
57–71. doi: 10.1007/s11157-005-7191-z.
Bernard, O. et al. (2001) Advanced monitoring and control of
anaerobic wastewater treatment plants: software sensors and controllers for an anaerobic digester. Available at:
https://iwaponline.com/wst/article-pdf/43/7/175/429874/175.pdf
(Accessed: 5 May 2020).
Boltz, J. P. et al. (2010) ‘Mathematical modelling of biofilms and biofilm reactors for engineering design’. doi:
10.2166/wst.2010.076.
Bolzonella, D. et al. (2005) ‘Mesophilic anaerobic digestion of
waste activated sludge: Influence of the solid retention time in the wastewater treatment process’, Process Biochemistry. Elsevier,
40(3–4), pp. 1453–1460. doi: 10.1016/j.procbio.2004.06.036.
Botheju, D. and Bakke, R. (2011) Oxygen Effects in Anaerobic
Digestion-A Review, The Open Waste Management Journal.
De Bruyn, W. J. et al. (1995) ‘Henry’s law solubilities and
Śetchenow coefficients for biogenic reduced sulfur species
obtained from gas-liquid uptake measurements’, Journal of
Geophysical Research. John Wiley & Sons, Ltd, 100(D4), pp. 7245–7251. doi: 10.1029/95JD00217.
Buisman, C. et al. (1990) ‘Kinetics of chemical and biological
sulphide oxidation in aqueous solutions’, Water Research.
Pergamon, 24(5), pp. 667–671. doi: 10.1016/0043-1354(90)90201-G.
Buyukkamaci, N. and Filibeli, A. (2004) ‘Volatile fatty acid
formation in an anaerobic hybrid reactor’, Process Biochemistry.
Elsevier, 39(11), pp. 1491–1494. doi: 10.1016/S0032-9592(03)00295-4.
Chaiprapat, S. et al. (2015) ‘Bio-desulfurization of biogas using acidic biotrickling filter with dissolved oxygen in step feed
recirculation’, Bioresource Technology. Elsevier Ltd, 179, pp.
429–435. doi: 10.1016/j.biortech.2014.12.068.
Chen, C. et al. (2017) ‘Enhanced performance of denitrifying sulfide removal process at high carbon to nitrogen ratios under
micro-aerobic condition’, Bioresource Technology. Elsevier Ltd,
232, pp. 417–422. doi: 10.1016/j.biortech.2017.02.031.
Chen, G. H. and Leung, D. H. W. (2000) ‘Utilization of oxygen in a sanitary gravity sewer’, Water Research. Elsevier Science Ltd,
34(15), pp. 3813–3821. doi: 10.1016/S0043-1354(00)00143-3.
Chen, Q. et al. (2020) ‘Review on microaeration-based anaerobic
digestion: State of the art, challenges, and prospectives’, Science of the Total Environment. Elsevier B.V., p. 136388. doi:
10.1016/j.scitotenv.2019.136388.
Chen, Y., Cheng, J. J. and Creamer, K. S. (2008) ‘Inhibition of
anaerobic digestion process: A review’, Bioresource Technology. Elsevier, pp. 4044–4064. doi: 10.1016/j.biortech.2007.01.057.
Chezeau, B. and Vial, C. (2019) ‘Modeling and Simulation of the
Biohydrogen Production Processes’, in Biohydrogen. Elsevier, pp.
445–483. doi: 10.1016/b978-0-444-64203-5.00019-8.
Chou, D. C.-H. S. J. (World H. O. (2003) HYDROGEN SULFIDE:
HUMAN HEALTH ASPECTS. Geneva. Available at:
https://www.who.int/ipcs/publications/cicad/en/cicad53.pdf (Accessed: 24 April 2020).
CLARKE, P. H. (1953) ‘Hydrogen sulphide production by
bacteria.’, Journal of general microbiology. Microbiology Society,
8(3), pp. 397–407. doi: 10.1099/00221287-8-3-397.
Díaz, I. et al. (2011) ‘Effect of oxygen dosing point and mixing on
the microaerobic removal of hydrogen sulphide in sludge
digesters’, Bioresource Technology. Elsevier, 102(4), pp. 3768–
3775. doi: 10.1016/j.biortech.2010.12.016.
Dinel, H. et al. (1988) ‘A field study of the effect of depth on
methane production in peatland waters: equipment and preliminary
results’, Journal of Ecology, 76(4), pp. 1083–1091. doi:
10.2307/2260635.
Donoso-Bravo, A. et al. (2018) ‘Mathematical modelling of in-situ
microaerobic desulfurization of biogas from sewage sludge
digestion’, Biotechnology Reports. Elsevier B.V., 20, p. e00293.
doi: 10.1016/j.btre.2018.e00293.
Edelmann, W., Baier, U. and Engeli, H. (2005) ‘Environmental
aspects of the anaerobic digestion of the organic fraction of
municipal solid wastes and of solid agricultural wastes’, Water
Science and Technology. IWA Publishing, 52(1–2), pp. 203–208. doi: 10.2166/wst.2005.0518.
El-Mashad, H. M. et al. (2004) ‘Effect of temperature and
temperature fluctuation on thermophilic anaerobic digestion of
cattle manure’, Bioresource Technology. Elsevier, 95(2), pp. 191–201. doi: 10.1016/j.biortech.2003.07.013.
Eriksson, O. N. (2014) ‘Biogas and natural gas’, ResearchGate,
(August), pp. 10–12. doi: 10.13140/2.1.5190.1128.
Eze, J. I. and Ezeudu, C. C. (2012) ‘Evaluation of biogas
30
generating potentials of animal and food wastes International
Journal of Biosciences (IJB)’, International Journal of Biosciences (IJB). INNSPUB, 2(10(1)), pp. 73–81. Available at:
https://www.researchgate.net/publication/311577080_Evaluation_
of_biogas_generating_potentials_of_animal_and_food_wastes_Int
ernational_Journal_of_Biosciences_IJB (Accessed: 21 March
2020).
Fdz.-Polanco, M. et al. (2009) ‘Hydrogen sulphide removal in the
anaerobic digestion of sludge by micro-aerobic processes: Pilot
plant experience’, Water Science and Technology. IWA
Publishing, 60(12), pp. 3045–3050. doi: 10.2166/wst.2009.738.
Fedorovich, V., Lens, P. and Kalyuzhnyi, S. (2003) ‘Extension of
anaerobic digestion model no. 1 with processes of sulfate
reduction’, in Applied Biochemistry and Biotechnology - Part A
Enzyme Engineering and Biotechnology. Springer, pp. 33–45. doi: 10.1385/ABAB:109:1-3:33.
Van Groenestijn, J. W. (2001) ‘Bioscrubbers’, in. Springer,
Dordrecht, pp. 133–162. doi: 10.1007/978-94-017-0930-9_5.
Hansen, K. H., Angelidaki, I. and Ahring, B. K. (1998) ‘Anaerobic
digestion of swine manure: Inhibition by ammonia’, Water
Research. Elsevier Sci Ltd, 32(1), pp. 5–12. doi: 10.1016/S0043-
1354(97)00201-7.
Hilton, B. L. and Oleszkiewicz, J. A. (1988) ‘Sulfide‐Induced
Inhibition of Anaerobic Digestion’, Journal of Environmental
Engineering. American Society of Civil Engineers, 114(6), pp.
1377–1391. doi: 10.1061/(ASCE)0733-9372(1988)114:6(1377).
Hosseini, S. E. and Wahid, M. A. (2014) ‘Development of biogas
combustion in combined heat and power generation’, Renewable
and Sustainable Energy Reviews. Elsevier Ltd, pp. 868–875. doi:
10.1016/j.rser.2014.07.204.
Hughes, M. N., Centelles, M. N. and Moore, K. P. (2009) ‘Making
and working with hydrogen sulfide. The chemistry and generation
of hydrogen sulfide in vitro and its measurement in vivo: A
review’, Free Radical Biology and Medicine. Pergamon, pp. 1346–1353. doi: 10.1016/j.freeradbiomed.2009.09.018.
Hulshoff Pol, L. W. et al. (1998) Anaerobic treatment of sulphate-
rich wastewaters.
James G. Speight (2019) ‘Unconventional Gas Production’, in
Natural gas. Gulf Professional Publishing, p. 462. doi:
10.1016/B978-0-12-809570-6.00003-5.
Janssen, A. J. H. et al. (1995) ‘Biological sulphide oxidation in a fed-batch reactor’, Biotechnology and Bioengineering, 47(3), pp.
327–333. doi: 10.1002/bit.260470307.
Janssen, A. J. H. et al. (1998) ‘Application of the redox potential
for controling a sulfide oxidizing bioreactor’, Biotechnology and Bioengineering. John Wiley & Sons, Ltd, 60(2), pp. 147–155. doi:
10.1002/(SICI)1097-0290(19981020)60:2<147::AID-
BIT2>3.0.CO;2-N.
Jenicek, P. et al. (2008) ‘Use of microaerobic conditions for the improvement of anaerobic digestion of solid wastes’. doi:
10.2166/wst.2008.493.
Jeníček, P. et al. (2017) ‘Simple biogas desulfurization by
microaeration – Full scale experience’, Anaerobe. Academic Press, 46, pp. 41–45. doi: 10.1016/j.anaerobe.2017.01.002.
Jensen, H. S. et al. (2011) ‘Growth kinetics of hydrogen sulfide
oxidizing bacteria in corroded concrete from sewers’, Journal of
Hazardous Materials. Elsevier, 189(3), pp. 685–691. doi:
10.1016/j.jhazmat.2011.03.005.
Kacprzak, M. et al. (2017) ‘Sewage sludge disposal strategies for
sustainable development’, Environmental Research. Academic
Press Inc., 156, pp. 39–46. doi: 10.1016/j.envres.2017.03.010.
Kaparaju, P., Serrano, M. and Angelidaki, I. (2009) ‘Effect of
reactor configuration on biogas production from wheat straw
hydrolysate’, Bioresource Technology. Elsevier, 100(24), pp.
6317–6323. doi: 10.1016/j.biortech.2009.06.101.
Kapdi, S. S. et al. (2005) ‘Biogas scrubbing, compression and
storage: Perspective and prospectus in Indian context’, Renewable
Energy. Pergamon, 30(8), pp. 1195–1202. doi:
10.1016/j.renene.2004.09.012.
Kaye, G. W. C. and Laby, T. H. (1986) Tables of Physical and
Chemical Constants and Some Mathematical Constants. Available
at: https://archive.org/details/tablesofphysical004093mbp
(Accessed: 2 June 2020).
Kayhanian, M. (1999) ‘Ammonia inhibition in high-solids
biogasification: An overview and practical solutions’,
Environmental Technology (United Kingdom). Taylor & Francis
Group , 20(4), pp. 355–365. doi: 10.1080/09593332008616828.
Khanal, S. K. and Huang, J.-C. (2006) ‘Online Oxygen Control for
Sulfide Oxidation in Anaerobic Treatment of High-Sulfate
Wastewater’, Water Environment Research. Wiley, 78(4), pp. 397–
408. doi: 10.2175/106143006x98804.
Koster, I. W. (2007) ‘Characteristics of the pH-influenced
adaptation of methanogenic sludge to ammonium toxicity’,
Journal of Chemical Technology & Biotechnology. John Wiley &
Sons, Ltd, 36(10), pp. 445–455. doi: 10.1002/jctb.280361003.
Koutinas, M., Peeva, L. G. and Livingston, A. G. (2005) ‘An
attempt to compare the performance of bioscrubbers and
biotrickling filters for degradation of ethyl acetate in gas streams’,
Journal of Chemical Technology & Biotechnology, 80(11), pp. 1252–1260. doi: 10.1002/jctb.1319.
Krayzelova, L. et al. (2014) ‘Microaeration for hydrogen sulfide
removal in UASB reactor’, Bioresource Technology. Elsevier Ltd,
172, pp. 297–302. doi: 10.1016/j.biortech.2014.09.056.
Krayzelova, L. et al. (2015) ‘Microaeration for hydrogen sulfide
removal during anaerobic treatment: a review’, Reviews in
Environmental Science and Biotechnology, 14(4), pp. 703–725.
doi: 10.1007/s11157-015-9386-2.
Li, Q. and Lancaster, J. R. (2013) ‘Chemical foundations of
hydrogen sulfide biology’, Nitric Oxide - Biology and Chemistry.
NIH Public Access, pp. 21–34. doi: 10.1016/j.niox.2013.07.001.
Li, W. et al. (2019) ‘Current status and future prospects of sewer
biofilms: Their structure, influencing factors, and substance
transformations’, Science of the Total Environment. Elsevier B.V.,
p. 133815. doi: 10.1016/j.scitotenv.2019.133815.
Li, X. et al. (2017) ‘The ecology of acidophilic microorganisms in
the corroding concrete sewer environment’, Frontiers in
Microbiology. Frontiers Research Foundation. doi:
10.3389/fmicb.2017.00683.
Lipták, B. G. and Venczel, K. (2016) Analysis and Analyzers,
Volume 2. 5th edn. Edited by B. G. Lipták and K. Venczel. Boca
Raton: Taylor and Francis Ltd. doi:
https://doi.org/10.4324/9781315370330.
30
Liu, D. H. . and Liptak, B. G. (1999) Environmental Engineers’
Handbook. 2nd edn. Edited by B. G. Liptak. Lewis Publishers, CRC Press. Available at:
https://books.google.cz/books?hl=sv&lr=&id=nAZskcJQCHIC&oi
=fnd&pg=PT9&ots=a9OtZ4JtcP&sig=oHHiM8b2vD79XTzwGYt
FYLdECsU&redir_esc=y#v=onepage&q=biotrickling&f=false
(Accessed: 1 May 2020).
Marchaim, U. and Krause, C. (1993) ‘Propionic to acetic acid
ratios in overloaded anaerobic digestion’, Bioresource Technology.
Elsevier, 43(3), pp. 195–203. doi: 10.1016/0960-8524(93)90031-6.
Marjaka, I. W. et al. (2003) ‘Augmentation of self-purification
capacity of sewer pipe by immobilizing microbes on the pipe
surface’, Biochemical Engineering Journal. Elsevier, 15(1), pp.
69–75. doi: 10.1016/S1369-703X(02)00182-1.
Mathiesen, B. V., Lund, H. and Karlsson, K. (2011) ‘100%
Renewable energy systems, climate mitigation and economic
growth’, Applied Energy. Elsevier Ltd, 88(2), pp. 488–501. doi:
10.1016/j.apenergy.2010.03.001.
Myint, M., Nirmalakhandan, N. and Speece, R. E. (2007)
‘Anaerobic fermentation of cattle manure: Modeling of hydrolysis
and acidogenesis’, Water Research. Elsevier Ltd, 41(2), pp. 323–
332. doi: 10.1016/j.watres.2006.10.026.
Namgung Kyu, H., Ahn, H. and Song, J. (2014) ‘Development of a
two-phase bioreactor for the biological removal of hydrogen
sulfide from biogas - ScienceDirect’, Energy Procedia. Seoul:
Elsevier Inc., pp. 1143–148. doi:
https://doi.org/10.1016/j.egypro.2011.12.1067.
Nayono, S. E. (2010) ‘Anaerobic digestion of organic solid waste
for energy production’. doi: 10.5445/ksp/1000015038.
Nguyen, D. et al. (2015) ‘Automatic process control in anaerobic
digestion technology: A critical review’, Bioresource Technology.
Elsevier Ltd, pp. 513–522. doi: 10.1016/j.biortech.2015.06.080.
Nguyen, D. et al. (2019) ‘Intermittent micro-aeration: New strategy to control volatile fatty acid accumulation in high organic
loading anaerobic digestion’, Water Research. Elsevier Ltd, 166, p.
115080. doi: 10.1016/j.watres.2019.115080.
Nguyen, D. and Khanal, S. K. (2018) ‘A little breath of fresh air into an anaerobic system: How microaeration facilitates anaerobic
digestion process’, Biotechnology Advances. Elsevier Inc., pp.
1971–1983. doi: 10.1016/j.biotechadv.2018.08.007.
Okoro, O. V. and Sun, Z. (2019) ‘Desulphurisation of Biogas: A Systematic Qualitative and Economic-Based Quantitative Review
of Alternative Strategies’, ChemEngineering. MDPI AG, 3(3), p.
76. doi: 10.3390/chemengineering3030076.
Park, K. et al. (2014) ‘Mitigation strategies of hydrogen sulphide emission in sewer networks - A review’, International
Biodeterioration and Biodegradation. Elsevier Ltd, 95(PA), pp.
251–261. doi: 10.1016/j.ibiod.2014.02.013.
Pathak, N. and Mahajan, P. V. (2017) ‘Ethylene Removal From Fresh Produce Storage: Current Methods and Emerging
Technologies’, in Reference Module in Food Science. Elsevier.
doi: 10.1016/b978-0-08-100596-5.22330-5.
Payne, B. (2017) ‘Henry’s Law and Monitoring Methane in Groundwater Wells’, in. Elsevier, pp. 275–319. doi:
10.1016/bs.apmp.2017.08.010.
PERSSON Owe JÖNSSON Arthur WELLINGER, M. et al. (2006)
Biogas Upgrading to Vehicle Fuel Standards and Grid Injection
Biogas Upgrading IEA Bioenergy Content Biogas Upgrading Task 37-Energy from Biogas and Landfill Gas BY THE END OF 2006
THE FOLLOWING NATIONS WERE MEMBERS OF TASK 37.
Available at: www.eia.doe.gov (Accessed: 28 April 2020).
Phelps, T., David Wrightsman, S. and Development Manager, B. (2017) INTERNAL COMBUSTION ENGINES Combined Heat and
Power, Business Development Manager.
Pokorna-Krayzelova, L. et al. (2017) ‘Model-based optimization of
microaeration for biogas desulfurization in UASB reactors’, Biochemical Engineering Journal. Elsevier B.V., 125, pp. 171–
179. doi: 10.1016/j.bej.2017.06.009.
Pokorna-Krayzelova, L. et al. (2018) ‘Final products and kinetics
of biochemical and chemical sulfide oxidation under microaerobic conditions’, Water Science and Technology. IWA Publishing,
78(9), pp. 1916–1924. doi: 10.2166/wst.2018.485.
Pokorna, D. and Zabranska, J. (2015) ‘Sulfur-oxidizing bacteria in
environmental technology’, Biotechnology Advances. Elsevier Inc., pp. 1246–1259. doi: 10.1016/j.biotechadv.2015.02.007.
Pozniak, T. I., Chairez Oria, I. and Pozniak, A. S. (2019) ‘Chapter
11 - Biodegradation’, in Marinakis, K., Lawrence, L., and
Mukthar, O. (eds) Ozonation and Biodegradation in Environmental Engineering. Jonathan Simpson, pp. 353–388. doi:
10.1016/B978-0-12-812847-3.00023-8.
Ramos, I., Pérez, R. and Fdz-Polanco, M. (2014) ‘The headspace
of microaerobic reactors: Sulphide-oxidising population and the impact of cleaning on the efficiency of biogas desulphurisation’,
Bioresource Technology. Elsevier Ltd, 158, pp. 63–73. doi:
10.1016/j.biortech.2014.02.001.
Reichert, P. (1998) AQUASIM 2.0 - User Manual. Computer
Program for the Identification and Simulation of Aquatic Systems.
Dubendorf. Available at:
https://www.eawag.ch/en/department/siam/software/ (Accessed: 7
June 2020).
Reiff, R. 1, Hulbert, W. C. and Roth, S. H. (1992) TOXICOLOGY
OF HYDROGEN SULFIDE, Annu. Rev. Pharmacol. Toxicol.
Available at: www.annualreviews.org (Accessed: 23 April 2020).
Sander, R. (2015) ‘Compilation of Henry’s law constants (version
4.0) for water as solvent’, Atmos. Chem. Phys, 15, pp. 4399–4981.
doi: 10.5194/acp-15-4399-2015.
Schiavon, M. et al. (2016) ‘Comparison between conventional biofilters and biotrickling filters applied to waste bio-drying in
terms of atmospheric dispersion and air quality’, Environmental
Technology. Taylor and Francis Ltd., 37(8), pp. 975–982. doi:
10.1080/09593330.2015.1095246.
Shiratori, Y. et al. (2010) ‘Internal reforming SOFC running on
biogas’, International Journal of Hydrogen Energy. Pergamon,
35(15), pp. 7905–7912. doi: 10.1016/j.ijhydene.2010.05.064.
Sousa, M. R. et al. (2019) ‘Evaluation of different air dosing strategies to enhance H 2 S removal in microaerobic systems
treating low-strength wastewaters’, Environmental Technology.
Taylor and Francis Ltd., 40(28), pp. 3724–3734. doi:
10.1080/09593330.2018.1487470.
Sparks, T. and Chase, G. (2016) ‘Air and Gas Filtration’, in Filters
and Filtration Handbook. Elsevier, pp. 117–198. doi:
10.1016/b978-0-08-099396-6.00003-4.
30
Stewart, P. S. (2003) ‘Diffusion in biofilms’, Journal of
Bacteriology. American Society for Microbiology Journals, pp. 1485–1491. doi: 10.1128/JB.185.5.1485-1491.2003.
Tang, K., Baskaran, V. and Nemati, M. (2009) ‘Bacteria of the
sulphur cycle: An overview of microbiology, biokinetics and their
role in petroleum and mining industries’, Biochemical Engineering Journal. Elsevier, pp. 73–94. doi: 10.1016/j.bej.2008.12.011.
Toledo-Cervantes, A. et al. (2017) ‘Biogas upgrading using algal-
bacterial processes’, in Microalgae-Based Biofuels and
Bioproducts: From Feedstock Cultivation to End-Products. Elsevier Inc., pp. 283–304. doi: 10.1016/B978-0-08-101023-
5.00012-1.
Vindis, Peter et al. (2009) The impact of mesophilic and
thermophilic anaerobic digestion on biogas production The impact of mesophilic and thermophilic anaerobic digestion on biogas
production Manufacturing and processing Manufacturing and
processing. Available at: www.journalamme.org (Accessed: 28
April 2020).
Wang, W. et al. (2014) ‘Oxygen-limited aeration for relieving the
impact of phenolic compounds in anaerobic treatment of coal
gasification wastewater’, International Biodeterioration and
Biodegradation. Elsevier Ltd, 95(PA), pp. 110–116. doi:
10.1016/j.ibiod.2014.06.009.
Wang, Y. et al. (2009) ‘Effects of volatile fatty acid concentrations
on methane yield and methanogenic bacteria’, Biomass and Bioenergy. Pergamon, 33(5), pp. 848–853. doi:
10.1016/j.biombioe.2009.01.007.
Wanner, O. and Gujer, W. (1986) ‘A multispecies biofilm model’,
Biotechnology and Bioengineering. John Wiley & Sons, Ltd, 28(3), pp. 314–328. doi: 10.1002/bit.260280304.
Wanner, O. and Reichert, P. (1996) ‘Mathematical modeling of
mixed‐culture biofilms’, Biotechnology and Bioengineering. John
Wiley & Sons, Ltd, 49(2), pp. 172–184. doi: 10.1002/(SICI)1097-0290(19960120)49:2<172::AID-BIT6>3.0.CO;2-N.
Wilkie, A. C. et al. (2004) ‘Fixed-film anaerobic digestion of
flushed dairy manure after primary treatment: Wastewater
production and characterisation’, Biosystems Engineering. Academic Press, 89(4), pp. 457–471. doi:
10.1016/j.biosystemseng.2004.09.002.
Yenigün, O. and Demirel, B. (2013) ‘Ammonia inhibition in
anaerobic digestion: A review’, Process Biochemistry. Elsevier, pp. 901–911. doi: 10.1016/j.procbio.2013.04.012.
Yongsiri, C., Vollertsen, J. and Hvitved-Jacobsen, T. (2004)
‘Effect of temperature on air-water transfer of hydrogen sulfide’,
Journal of Environmental Engineering, 130(1), pp. 104–109. doi: 10.1061/(ASCE)0733-9372(2004)130:1(104).
32
11 Appendix
11.1 Calculation of Stochiometric Coefficients
The stochiometric coefficients were calculated in the same way as Krayzelova-Pokorna (2017).
11.1.1 Conversion of H2S to elemental sulfur
H2S + aO2 → bS0 + H2O + y ∙ xSOB1
COD balance calculation with implementing molecular weights of atoms:
CODBalance = 1(64) + a(−32) → 1(48) + YSOB1
Solving for a:
64 − 32a → 48 + YSOB1
a =16 − YSOB1
32
Sulfur balance and solving for b:
1 + 0 → 𝑏 ∙ 1 + 0
𝑏 = 1
Obtaining stochiometric coefficients for H2S, O2, S0 and SOB degradation term XSOB. The
negative (-) and positive (+) signs before the stochiometric coefficients represent consumption
and formation respectively.
SO2= − (
16 − YSOB1
32)
SS0= +1
SH2S = −1
YSOB1 = XSOB
32
11.1.2 Conversion of Elemental Sulfur to Sulfate
𝑆0 + 𝑎𝑂2 → 𝑐𝐻2𝑆𝑂4 + 𝑦 ∙ 𝑥𝑆𝑂𝐵2
COD balance:
CODBalance = 1(48) + a(−32) → c(0) + YSOB2
Solving for a:
𝑎 =48 − 𝑌𝑆𝑂𝐵2
32
Sulfur balance and solving for c:
1 + 0 → 𝑏 ∙ 1 + 0
𝑐 = 1
Obtaining stochiometric coefficients for SO42-, O2, S0 and SOB degradation term XSOB. The
number 2 in the 𝑌𝑆𝑂𝐵2 variable stands for the other SOB species which are specifically
responsible for the uptake of elemental sulfur and converting it so sulfates.
SO2= − (
48 − YSOB2
32)
SS0= −1
SS𝑂42− = +1
YSOB2 = XSOB
11.1.3 Conversion of Thiosulfate to Sulfate and Elemental Sulfur
𝐻2𝑆2𝑂3 + 𝑎𝑂2 → 𝑐𝐻2𝑆𝑂4 + 𝑏𝑆0 + 𝑌𝑆𝑂𝐵3
COD balance:
CODBalance = 1(64) + a(−32) → c(0) + b(48) + YSOB2
Solving for a:
32
𝑎 =48𝑏 − 64 + 𝑌𝑆𝑂𝐵3
−32
The term b was calculated to 1 above in chapter 12.1.1, the stochiometric coefficient a is equal
to:
a =16 − YSOB3
32
Sulfur balance:
1 ∙ 2 + 0 → c ∙ 1 + b ∙ 1 ∙ +0
2 → C + B, where b=1 & c=1
Obtaining stochiometric coefficients for SO42-, O2, S0, thiosulfate and XSOB. The number 3 in the
𝑌𝑆𝑂𝐵2 variable stands for the other SOB species which are specifically responsible for the
conversion of thiosulfates to sulfates and elemental sulfur.
SO2= − (
16 − YSOB3
32)
SS0= +1
SS𝑂42− = +1
𝑆𝑆2𝑂32− = −1
YSOB3 = XSOB
11.1.4 Conversion of Hydrogen Sulfide to Thiosulfate
𝐻2𝑆 + 𝑎𝑂2 → 𝑑𝐻2𝑆2𝑂3 (+𝐻2𝑂)
COD balance:
CODBalance = 1(64) + a(−32) → d(64)
Solving for a:
32
𝑎 =64 − 64𝑑
32
𝑎 = 2 − 2𝑑
Sulfur balance:
1 + 0 → d ∙ 2
𝑑 =1
2
Obtaining stochiometric coefficients for H2S, O2, S0 and thiosulfate:
Inserting the calculated stochiometric coefficient d and solving for a gives us a=1.
SO2= −1
𝑆𝑆2𝑂32− = +
1
2
S𝐻2𝑆 = −1