This is the process of lining the digester by mortar or using sheets of foam as in Figure 17. This is one of the most important construction steps and should be carefully and accurately achieved. In case of lining, the process is performed using mortar containing 1 % silica. After the completion of the lining, the digester is painted using the petroleum Albumen. In other designs, the walls are heat insulated with a clad with non-corroding and weather-proof aluminum trapezoidal panels. On the other hand, the rural digesters are coated with layers of dry dirt and asbestos.

As indicated in Table 3, there are some digesters have been installed in a number of sub­Saharan Africa. These have mainly been pilot or demonstration projects aimed at testing the technical viability of small-scale biogas technology at a limited scale (Hivos, 2009a). These pilot projects have mostly been funded by non-governmental organizations and built for health clinics, schools, and small-scale farmers. While the small-scale biogas plants are located throughout Africa, only a few of them are operational (Parawira, 2009). There is also limited documentation on whether the existing biogas digesters have been successful in achieving the benefits highlighted in section 3.1. Some country specific examples is Tanzania, Ivory Cost and Burundi, which have produced biogas from animal and human waste using the Chinese fixed-dome digester and the Indian floating-cover digester (Omer and Fadalla, 2003). These have not been reliable and in many cases, poor performance has been reported (Omer and Fadalla, 2003). Thus, the plants have only operated for a short period due to poor technical quality (Mshandate and Parawira, 2009).

Currently, a number of different organizations are establishing biogas initiatives in Africa, particularly in rural areas, in order to supply cleaner burning energy solutions. These initiatives are at different stages of development such as: prefeasibility, feasibility, design and implementation to a limited extent. For instance, Burkard (2009) reports on five biogas case studies in Kenya which were to utilize agricultural leaves, residues from floriculture, and residues from vegetable production and canning. In 2010, it was reported that the Dutch government was to spend 200 million Kenyan Shilling to set up 8000 biogas digesters throughout the country. The initiative was targeting farmers practising zero grazing (Daily Nation, 2010). Similar projects are being implemented in Ethiopia, Uganda, Senegal, Burkina Faso, and Tanzania. There are also some other initiatives such as biogas for better life, which is at various stages of biogas development in Ethiopia, Kenya, Uganda, Sudan, Zambia, Malawi, South Africa, Lesotho, Swaziland, Mali, Senegal, and Ghana1. The Netherland Development Organization (SNV) has been supporting the development of National Biogas programmes in East Africa (Ethiopia, Kenya, Uganda, Tanzania, Rwanda) and West Africa (Senegal and Burkina Faso)[3] [4]. While there are few documented successful small-scale biogas plants in the rural areas of Africa, this section will present some selected country specific biogas projects.

1.1.2 Rwanda

Rwanda has a population of 10.2 million people of which 81% of this population reside in the rural areas in 2010 (United Nations, 2007). One of the famous biogas programmes is the Kigali Institute of Science and Technology (KIST) large-scale biogas plants developed and installed in prisons. The aim of these plants was to treat toilet wastes and generate biogas for cooking. The first plant prison which was operational in 2001, and by 2011, KIST has managed to build and operationalize biogas plants in 10 prisons. Each prison is supplied with a linked series of underground biogas digesters, in which the waste decomposes to produce biogas. After this treatment, the bio-effluent is safe to be used as fertiliser for production of crops and fuel wood. The project was funded by Red Cross and the plant consists of five interlocking chambers. KIST’s project saves 50% of wood for cooking and it won Ashden Award in 2006. The projects construction is managed by KIST, who also provides training to both civilians and prisoners.

Another biogas programme is the National Biogas Programme which is promoted by the Rwanda Ministry of Infrastructure, through the support by the Netherlands development organization. The programme aims at reducing firewood use by the households. The Ministry of Infrastructure estimates that 441 units have been installed to date, and approximately 15 000 households will be using biogas by end of 2011 for cooking and lighting[5]. The Ministry of Infrastructure of Rwanda is also collaborating with other ministries (e. g. Ministry of Education) in order to develop biogas plants in schools, clinics and community institutions.

(Fannin, 1987). In the natural environments, the optimum temperature for the growth of methane forming archaea is 5-25 °C for psychrophilic, 30-35 °C, for mesophilic, 50-60 °C, for thermophilic and >65 °C for hyprethermophilic (Tchobanoglous and Burton, 1996).

It is generally understood that higher temperature could produce higher rate of reaction and thus promoting higher application of organic loading rate (OLR) without affecting the organic removal efficiency (Chae et al., 2007; Choorit and Wisarnwan, 2007; Poh and Chong, 2009). Using palm oil mill effluent as the substrate, Choorit and Wisarnwan (2007) demonstrated that when the digester was operated at thermophilic temperature (55 °C), showed higher OLR application than the that of mesophilic (17.01 against 12.25 g COD/ m3-d) and the methane productivity was also higher (4.66 against 3.73 L/L/d) (Choorit and Wisarnwan, 2007). A similarly study by Chae et al (2007), indicated that the higher temperature of 35 °C led to the highest methane yield as compared to 30 °C and 25 °C although the methane contents only changed slightly.

Using cheese whey, poultry waste and cattle dung as substrates, Desai et al. (1994) showed that when the temperature was increased from 20, 40 and 60 °C, the biogas production and methane percentage increased as well. The digestion rate temperature dependence can be expressed using Arrhenius expression:

rt = r30(1.11)(£_30) (7)

where t is temperature in °C, and rt, r30 are digestion rates at temperature t and 30°C, respectively. Based in Eq. 7, the decrease in digestion rate for each 1 °C decreased in temperature below the optimum range is 11%. Similarly, the calculated rate at 25 °C y 5 °C are 59 and 7% respectively, relative to the rate at 30 °C (Dasai et al., 1994).

Although the thermophilic anaerobic process could increase the rate of reaction, the yield of methane that could be achieved over the specified organic amount is the same regardless of the mesophilic or thermophilic conditions. That value is 0.25 kg CH4/kg COD removed or 0.35 m3 CH4/kg COD removed (0 °C, 1 atm) which is derived by balancing the following equation (Eq. 8), taking into account the different operating conditions worked, can be explained that the values obtained for methane production is different in many scientific reports:

CH4+2O2 ^ CO2+2H2O (8)

Although thermophilic condition could result in higher application of organic loading rates and better destruction of pathogens, at the same time it is more sensitive to toxicants and temperature control is more difficult (Gerardi, 2003; Choorit and Wisarnwan, 2007). Furthermore, biomass washout that could lead to volatile fatty acids accumulation and methanogenesis inhibition could also occur if the thermophilic temperature could not be controlled (Poh and Chong, 2009). As a result, in tropical regions mesophilic temperatures are the preferred choice for anaerobic treatment (Yacob et al., 2005, Sulaiman et al., 2009).

Transport networks are designed to transport gas over longer distance. They are equipped with remote control which transmits all relevant data to the control centre. From the point of view of modeling these networks have an excellent information base for a moderate number of pipes and nodes (measurement points) making modeling straightforward and easy. The network structure of a transport system tends to be sparsely intermeshed.

2.4 Distribution networks

Distribution networks are designed to transport gas over shorter distance, e. g. within a city. They are equipped also with remote control, but only important data is transmitted to the control center. The amount of data handled may be subject to changes in the future when for each customer Smart Metering and on upper level Smart Grid will be introduced. From the point of view of modeling the distribution networks have an acceptable information base for all pipes but moderate number of measurement points making modeling an intensive work. The network structure of a distribution system tends to be strongly intermeshed. Distribution networks may have also a smaller trunk transportation system at a higher pressure level (e. g. 25, 16, 10 or 4 bar) while most of the pipes in the final distribution area are operated at 0.022 to 0.8 bar depending on the required flows.

Operating a 500 kWel CHP goes along with reduced feed-in tariffs of 20 €/MWh according to Austrian’s Eco-Electricity Act. The positive effect of lower investment and operating costs for larger capacities is therefore narrowed by less revenue for produced electricity. If is forbidden to use two CHPs with same capacity at one location in the maximum structure to gain higher feed-in tariffs the next larger CHP capacity has to be taken although this would

district heating

Fig. 5. PNS optimum structure with a central 500 kWel CHP

go along with shortened revenue. With this precondition the optimization of the maximum structure presented in Figure 2 but with only one central 500 kWel CHP unit whereas the rest of the optimum structure (Figure 3) stays the same.

The revenue is narrowed but not as much as it was in scenario 1. To use a 500 kWel central CHP would cause a revenue reduction of yearly 50,000 € within a payout period of 15 years.

Fig.3-5 showed the effect of grammage and rosin on dry tensile strength when other factors were held at 0 level. Adding the amount of bauxite at a low level, the dry tensile strength decreased with the increase of added rosin amount; adding the amount of bauxite at a high level, the added rosin amount almost had no effect on the dry tensile strength, maximum of the dry tensile strength occurred when bauxite was held at 4%, and rosin was held at 0.4%, because rosin adsorption has been saturated, there was no effect on the strength.

1.2.5 Effect of bauxite and wet strength agent on dry tensile strength

Fig.3-6 showed the effect of bauxite and wet strength agent on dry tensile strength when other factors held at 0 level. When bauxite was near 0 level, the dry tensile strength increased with the increase of wet strength agent, when bauxite was higher than the zero level, with the wet strength agent increased, the dry tensile strength first increased and then

decreased, the maximum occurred when wet strength agent was held at 2%, and bauxite was held at 3.5%. This is because with the adding of the wet strength agent, the adsorption of the fibre system to wet strength agent had already been saturated, and it no longer played a role in increasing strength, anionic trash in absorption system impacted the combination between the fibre, leading to strength decreased.

Findings show that one household plant could cost USD 550- 675 with wide standard deviation suggesting a high variation for the cost of installation depending on the expertise availability and the size of the biogas facility. The size for biogas plants ranged from 6­12m3.

poor (p<2%) categories. However, there was no significant difference of cost of installation between the less poor and the poor respondents. A major explanation to this is that a high proportion of the slightly well off respondents benefited from the pilot project in 1996 when the biogas facilities were installed at half cost by the Danish volunteers. This was a strategy used to sensitise and raise awareness and demand for the biogas facilities. Unfortunately, many people from the less poor and the poor categories could not take up this opportunity because of many reasons, one of them being risk averse. They wanted to learn from others how it worked and what the advantages were to be. However, by the time they were convinced by the technology and started adopting it, the price had gone back to the market price levels. Another reason for not adopting it during the promotion period was that they had other more pressing issues than biogas, such as a need for cash to carter farming activities and paying for education and health services. Various studies have shown that poor people are always risk averse and therefore it takes time for them to adopt a new technology. Many of the studies about technology adoption conclude that the pace of adopting a new technology in developing countries has been slow among the poor.[20] Feder et al., (1985) have identified factors such as aversion to risk and limited access to information as reasons that could partly explain why adoption is slow. Individual characteristics such as education, access to credit, the capacity to bear risk, availability of other inputs and access to information may play a big role in the adoption of the technology.

The determination of gas quantity, or volume is carried out under operating conditions (metering conditions). The result is an operational flow VB (TB, PB) as a function of temperature and pressure. This operational flow needs to be converted to standard conditions (TN = 0 ° C, pN = 1.01325 bar) in order to compare volumes and so that it can be used as an input for gas billing. Since the model for an ideal gas is only approximately valid for real gases at low pressures, a compressibility factor Z (T, p, xi) is introduced into the equation of state for ideal gases. The compressibility factor is mathematically approximated by a series expansion of the molar density (virial approach). The calculation of standard volume is thus given by equation 8. 3:

V(TN > Pn ) = TnPb Zn (3)

V(TB, Pb) TbPn Zb

The ratio of the compressibility factors is called the gas law deviation factor.

Two methods for calculating compressibility factors are given in G 486 including the supplementary sheets: The standard GERG-88 virial equation and the AGA8-DC92 equation of state. The former requires input parameters of p, T, HS, N, p, xCO2 and XH2, the latter the mole fractions. The AGA8 equation of state requires a full analysis by means of a process gas chromatograph.

Thixotropic fluids are generally dispersions, which when they are at rest construct an intermolecular system of forces and turn the fluid into a solid, thus, increasing the viscosity. In order to overcome these forces and make the fluid turn into a liquid and which may flow, an external energy strong enough to break the binding forces is needed. Thus, as above a yield stress is needed. Once the structures are broken, the viscosity is reduced when stirred until it receives its lowest possible value for a constant shear rate (Schramm, 2000). In opposite to pseudoplastic and dilatant fluids, the viscosity of thixotrpic fluids is time dependent: once the stirring has ended and the fluid is at rest, the structure will be rebuilt. This will inform about the fluid possibilities of being reconstructed. Wastewater and sewage sludge can be examples of fluids with thixotropic behaviour (Seyssieq & Ferasse, 2003) as well as paints and soap.

1.3 Rheological mathematical models

There are several rheological mathematical models applied on rheograms in order to transform them to information on fluid rheological behaviour. For non-Newtonian fluids the three models presented below are mostly applied (Seyssiecq & Ferasse, 2003).

Elvia Ines Garcia-Pena, Alberto Nakauma-Gonzalez and Paola Zarate-Segura

Bioprocesses Department, Unidad Profesional Interdisciplinaria de Biotecnologia,

IPN, Mexico City, Mexico

1. Introduction

As many countries have taken advantage of the richness of crude oil, fossil fuels have become the main energy source, and human activities have become entirely dependent on petroleum products. However, this is not sustainable because of the huge environmental cost of harvesting and utilizing vast amounts of fossil fuels (Fairley, 2011). Therefore, the need for alternative fuels has become critical, especially for a new generation of advanced biofuels that can maximize petroleum (crude oil) displacement and minimize the side effects of burning fossil fuels. The primary objective is then to produce biofuels from corn stalks or other ‘cellulosic plants’ (or even from municipal garbage) and jet fuels from dedicated energy crops such as the fast-growing Camelina sativa (Fairley, 2011). The challenges are then to develop the agriculture for these plants and improve their utilization at an industrial scale. In this way, net reductions in petroleum use and greenhouse-gas emissions will be long-lasting and ethical. Bridging this gap will require continued investment, research, government regulations and development of technology. The International Energy Agency (IEA) has recommend the maximized use of farm, forestry and municipal wastes as well as increased cultivation of dedicated energy crops away from lands that provide carbon sequestration and other critical environmental services. One way to develop biofuels along an environmental friendly path is to draft a set of standards and practices that biofuels producers must comply with, either voluntarily or by mandate (Fairley, 2011).

In large cities, such as Mexico City with a population of more than 20 million, concerns about waste disposal and the use of alternative energy sources has steadily increased. This population produces a tremendous amount of solid waste, more than 12,000 tons per day. On the other hand, to provide sufficient food for this population, many markets are distributed throughout the city. The central market for food distribution in Mexico City, Central de Abasto (CEDA), is the second largest market in the world, receiving 25,000 tons of food products and producing 895 tons of organic solid waste each day (84% of the total solid waste produced is organic waste, 50% of that is from fruits and vegetables).

Fruit and vegetable waste (FVW) is produced in large quantities in markets in many large cities (Mata-Alvarez et al., 1992; Misi and Forster, 2002; Bouallagui et al., 2003; Bouallagui et al., 2005). The application of an anaerobic digestion process for simultaneous waste treatment and renewable energy production from the organic fraction of these residues could therefore be of great interest (Bouallagui et al., 2005). The high biodegradability of FVW promotes the rapid production of volatile fatty acids (VFAs), resulting in a rapid decrease in pH, which in turn could inhibit methanogenic activity (Bouallagui et al., 2003; Bouallagui et al., 2009). A strategy to avoid the acidification of the system is the addition of cosubstrates. Data obtained during the codigestion of FVW and other substrates resulted in the design of an efficient digestion process, improving methane yields through the positive synergistic effects of the mixed materials exhibiting complementary characteristics and the supply of missing nutrients from the cosubstrate (Agdag and Sponza, 2005, Habiba et al. 2009, Bouallagui et al. 2009). In a recently published study (Garcia-Pena et al., 2011), a 30- Liter anaerobic digestion reactor operated with a mixture of FVW:MR (meat residues) (75:25) had a stable CH4 production percentage of 53 ± 2 % and a sustained pH of 6.9 ± 0.5 (naturally regulated) in a co-digestion process. The adequate and sustained performance and stable CH4 production were a result of an appropriate buffering capacity and highly stable operation of the experimental system. However, the biogas produced during this anaerobic process needs to be cleaned before use by eliminating a relatively high content of other compounds as CO2 and H2S.

Biogas consists of approximately 60-70% (v/v) methane (CH4), 30-40% (v/v) carbon dioxide (CO2), 1-2% (v/v) nitrogen (N2), 1000-3000 ppmv H2S, 20-30 ppmv of VFAs and 10­30 ppmv of ammonia (NH3), depending on the organic substrate used during the anaerobic process (Angelidaki et al., 2003). Hydrogen sulfide (H2S) is one of the most commonly reported reduced sulfur compounds, and represents up to 2% (v/ v) . However, this H2S concentration can be higher when a rich protein feedstock is used. H2S elimination is thus required because it reduces the life span of combustion engines by corrosion, forms SO2 upon combustion and is a malodorous and toxic compound (Angelidaki et al., 2003, Pride, 2002). Malodorous gases include mainly H2S (around 3000 ppmv) and some volatile fatty acids (VFAs).

Reducing CO2 and H2S content will significantly improve the quality of biogas. There have been many technologies developed for the separation of CO2 from gas streams, including absorption by chemical solvents, physical absorption, cryogenic separation, membrane separation and CO2 fixation by biological or chemical methods (Abatzoglou and Boivin, 2009, Granite and O’Brien, 2005). These techniques are of significant industrial importance and are generally applied during natural gas sweetening and in the removal of CO2 from flue gases of power plants.

H2S is currently removed using chemical, physical or biological methods. The most commonly used method is chemical absorption by selective amines, such as diglycolamine, monoethanolamine and methyldiethanolamine, but also by absorption into aqueous solutions, physical absorption on solid adsorbents or conversion to low-solubility metal sulfides (Horikawa et al., 2004, Osorio and Torres, 2009). Water scrubbing systems are also frequently used because of their simplicity and low cost (Kapdi et al., 2005, Rasi et al., 2008). Their use allows the production of high quality CH4 enriched gas from biogas by chemical absorption where a packed bed column and a bubble column are normally used to provide liquid/gas contact (Krumdieck et al., 2008). However, the main drawbacks of these chemical technologies are the high energy requirement, the stability and selectivity of the chemicals used, the high cost of the chemicals and their regeneration, the negative environmental impacts from liquid wastes, the large equipment size requirements and the high equipment corrosion rate (Tippayawong and Thanompngchart, 2010, Fortuny et al., 2008).

Biological treatments are cost effective and environmentally friendly processes (Shareenfdeen et al., 2003, Ng et al., 2004, Maestre et al., 2010). Biofiltration is one of the most promising clean technologies for reducing emissions of malodorous gases and other pollutants into the atmosphere (van Groenestijn and Hesselink, 1993, van Groenestijn and Kraakman, 2005). This technology has been proven to effectively control reduced sulfur compounds in diluted gas streams (Yang et al., 1994, Smet et al., 1998, Ergas et al., 1995, Chung et al., 1996, Devinny et al., 1999; Gabriel and Deshusses, 2003, Kim and Deshusses, 2005). However, the elimination of H2S from fuel gases requires systems that can handle high loads of pollutants for extended periods of time (Maestre et al., 2010). Surprisingly, there is still a limited number of reports on the removal of high concentrations of H2S (>1000 ppmv) using biofilters, biotrickling filters and bioscrubbers. On the other hand, two processes have been effectively applied for the removal of high concentrations of H2S from biogas or fuel gas in industrial processes: the Thiopaq process (Paques, The Netherlands) and the Biopuric process (Biothane, USA). The first one is a chemical process that uses a conventional caustic scrubber and an expanded bed bioreactor for the recovery of spent caustic and elemental sulfur generation. The Biopuric process combines a chemical scrubber with a subsequent biological treatment.

Although H2S treatment for industrial processes has already been applied through the above-mentioned commercial systems, there is a need for the development of alternative and sustainable biological processes. Regarding the development of biofiltration and/or biotrickling filter systems to eliminate high H2S concentrations, Rattanapan et al., 2009, compared the elimination of 200 to 4000 ppmv of H2S in two biofiltration systems. One of the biofilters was a sulfide oxidizing bacterium immobilized on Granular Activated Carbon (GAC) (biofilter A) and the other was GAC without cell immobilization (biofilter B). The results showed that in the GAC system, the H2S was autocatalytically oxidized when it absorbed into the CAG, reaching a removal percentage of 85%. The removal was enhanced to over 98% (even at a concentration as high as 4000 ppmv) through the biological activity in biofilter A. In this last system, the maximum elimination capacity was approximately 125 gH2S/m3GAC h. In addition, Fortuny et al., 2008, reported the performance of a biotrickling filter system for treating high concentrations of H2S in simulated biogas using a single reactor. Two laboratory-scale biotrickling filters filled with different packing materials were evaluated, the inlet H2S concentration ranged from 900 to 12000 ppmv. During long-term operation, a removal percentage of 90% was determined with an extremely high H2S concentration (6000 ppmv). Maximum elimination capacities of 280 and 250 g H2S/m3 h were obtained at empty-bed residence times of 167 and 180 s, respectively. During this study, the main end products of the biological oxidation of H2S were sulfate and elemental sulfur; the final percentage of these products varied as a function of the ratio of O2/H2S supplied (v/v). At a value of 5.3, corresponding to an inlet H2S concentration of 3000, the main product was sulfate (60-70%), whereas at the higher H2S concentration of 6000 ppmv, the sulfate recovery decreased to 20-30%. Elemental sulfur production varied inversely with the O2/H2S supplied (v/v), it was low at a ratio of 5.3 and increased up to 68-78% as the ratio decreased.

In a biofiltration system, a gas stream is passed through a packed bed on which pollutant­degrading organisms are immobilized as biofilms. Biotrickling filters use the same principle, but an additional liquid phase will flow through the reactor. In both systems, the microorganisms in the biofilms transform the absorbed H2S by metabolic activity into elemental sulfur or sulfate depending on the amount of available oxygen. Oxygen is thus the key parameter that controls the level of oxidation. Sulfur production (Eq. 1) results from the partial oxidation of sulfide instead of complete oxidation to sulfate (Eq. 2) when oxygen is limited, as is shown in Equations 1 and 2 (Kennes and Veiga, 2001).

H2S + 0.5O2 ^ S0 + H2O (1)

H2S + 2O2 • SO4-2 + 2H+ (2)

As the performance of a biofiltration system depends on the microbial community present in the reactor, the determination of the microorganism and the microbial activity responsible for the behavior of the process is very important. However, there is still a lack of understanding of the structure and dynamics of microbial communities and the physiological role of the main microbial population as well as the correlation between the global performance of the system with the metabolic activities of the microorganisms involved in the process. This knowledge could allow control of the reactor behavior and the design of enhanced processes to eliminate high concentrations of H2S in the gas phase because the performance of the process depends on the robustness of the microbial communities (Maestre et al., 2010).

Some authors have characterized microbial population diversity present in different gas phase reactors by analysis of biomarkers such as phospholipid fatty acids (Webster et al., 1997), molecular techniques such as fluorescent in situ hybridization (FISH) (Moller et al., 1996), cloning and sequencing of ribosomal RNA genes (Roy et al., 2003), terminal restriction fragment length polymorphism (Maestre et al., 2009) and denaturing gradient gel electrophoresis (Borin et al., 2006). There are only a few studies in the literature that focused on determining the microbial diversity of microorganisms capable of removing reduced sulfur compounds in biofilters or gas phase bioreactors using molecular biological approaches. Ding et al., 2006, reported the changes in the microbial diversity of a biofilter­treating methanol and H2S. In this study, the biofilter’s initial microbial community had a high diversity, but after the biofiltration system was fed with H2S, the microbial diversity decreased to adapt to the low pH and use H2S as an energy source. Maestre et al., 2010 studied and described the bacterial composition of a lab-scale biotrickling filter (BTF) treating high loads of H2S using 16S rRNA gene clone libraries. The authors reported the diversity, the community structure and the changes in the microbial population on days 42 and 189 of reactor operation. The main changes in microbial diversity were observed at the beginning of the process and again when steady state operation was reached (i. e., neutral pH and at an inlet H2S concentration of 2000 ppmv). At steady state, the major sequences associated with SOB included Thiothrix spp., Thiobacillus spp., and Sulfurimonas denitrificans. Additionally, FISH analysis was used to determine the spatial distribution of sulfur — oxidizing bacteria (SOB) along the length of the reactor under pseudo-steady state operation. The aerobic species were found to be predominantly along the system, but some facultative anaerobes were also found. The anaerobic microorganisms were associated with higher H2S concentrations (inlet) with lower oxygen availability. The distribution of a microbial community was associated with changes in the dissolved oxygen (DO) concentration, and the accumulation of elemental sulfur and the pH (Maestre et al., 2010). Recently, Omri et al., 2011 studied the microbial community structure of the three layers (bottom, middle and top) of a biofilter using the polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) analysis. The results obtained showed a high microbial diversity for bacteria, with the relative diversity of the bacterial community represented by the number of peaks in the profiles. Significant differences were observed between the microbial communities of the three layers of the biofilter. The Simpsons diversity index was used to determine the microbial diversity in the system, and the results indicated that the bottom and middle layers exhibited high diversity (1/D of 13.6 and 10.8, respectively). However, the microbial distribution in the top layer (1/D=8.75) was associated with the vertical gradient of the substrate, as higher H2S concentrations near the inlet allowed the growth of sulfur-oxidizing bacteria and low pH provided a favorable environment for the oxidation of H2S. The predominant bacteria in samples of the operation were found to be Pseudomonas sp, Moraxellacea, Acinetobacter and Exiguobacterium belonging to the phyla Pseudomonadaceae, gamma-Proteobacteria and Firmicutes.

In the present chapter, the data obtained for the potential use of FVW and meat residues for methane production will be presented. The results demonstrating how a codigestion process of FVW and MR enhanced methane production by increasing the C/N ratio and controlling the natural pH in a 30L reactor will also be analyzed and discussed. At different stages of the start up of the anaerobic digestion system, methane production increased from 14 to 50% as a result of the use of a protein rich feedstock (MR). However, the H2S concentration also increased in the biogas stream under these conditions. Due to the increased H2S content, and considering that this compound does not allow for the efficient use of methane as fuel, a biofiltration system was evaluated in the elimination of H2S. The results obtained for the elimination of H2S and VFAs (average concentrations of 1500 ppmv and less than 10 ppmv, respectively) in the gas stream from an anaerobic process by a biofiltration system will then be presented. The microbial population in the biofilter when operating at steady state conditions is also presented and discussed.