The COD removal efficiency, TP removal efficiency, biogas production and composition were markedly influenced by using steel elements as an additional medium in the UASB reaction chamber.

During Stage 1, both UASB reactors reached the steady-state after 25 days of operation. No statistically significant differences (p>0.05) were observed between UASB reactor with steel elements (RFe) and UASB reactor without steel elements (R0) in term of the average COD removal efficiency and biogas production rate (Fig. 2; 3). Nevertheless, RFe indicated higher (p<0.05) removal efficiency in phosphate (86.2%) and TP (81.2%) than R0 in which the analyzed values were 1.8% and 22.8%, respectively (Fig. 3). CH4 content in biogas produced in RFe was as high as 67.1% which was higher by 11.9% than in R0 (p<0.05). In Stage 2 and 3 both UASB reactors demonstrated a stable work, but statistically significant differences in the values of all the monitoring parameters between R0 and RFe were noticed (p<0.05). The duration of each stage were 36 and 48 days, respectively. The average TP removal efficiency and phosphate removal efficiency in RFe were higher by 77.7% and 83.7%, respectively than in R0 during Stage 2, and 68.1% and 73.9%, respectively during Stage 3 (Fig. 3). During Stage 2 and 3 high COD removal efficiencies (95.6%, 94.8%, respectively) were remained in RFe, in contrast to that of 84.2% in Stage 2 and 80.1% in Stage 3 in Ro (Fig. 3). The average CH4 content in biogas of 78.0% and biogas production of 2.59 m3m-3d-1 in RFe, in contrast to that of 60.8% and 0.92 m3m-3d-1, respectively in R0 (p<0.05), were observed during Stage 2. In Stage 3, biogas production increased by 1.12 m3m-3d-1 in R0 and 1.2 m3m-3d-1 in RFe, but it was still significantly higher in RFe (3.79 m3m-3d-1) than in R0 (2.04 m3m-3d-1), p<0.05 (Fig. 2). Moreover in that stage, the highest methane content in biogas of 79.8% in RFe and 68.1% in R0 were achieved (Fig. 2). During the last stage it was found the highest biogas production rate in RFe of 4.01 m3m-3d-1, while 1.86 m3m-3d-1 in R0 was observed (p<0.05). The average

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CH4 content in biogas decreased to 72.3% in RFe, in contrast to that of 64% in Ro, and the differences between R0 and RFe were statistically significant (p<0.05) (Fig. 2). It was found decrease in TP removal efficiency in RFe and R0 to 72.2 and 10.1%(p<0.05), respectively. According to this, the phosphate removal efficiencies decreased, too (Fig. 3). COD removal efficiency was lower than in Stage 3 and achieved 88.8% in RFe and 71.8% in R0, p<0.05 (Fig. 3).

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The study demonstrated that the COD removal efficiency was markedly influenced by using steel elements as an additional medium of the UASB reactor. Iron ions generated from the steel elements must have acted as coagulants and were involved in the removal of suspended organic matter. After the operation time of 219 days, sludge samples from both UASB reactors were collected for the determination of TSS, which was higher by 52.1% in RFe than in R0. Moreover, ferrous ions in wastewater could react to form hydroxides which were the sorption areas for suspended organic matter. Additional sorption areas were made by steel elements surface. Enhancement of COD removal efficiency by zero-valent iron processes were reported by Jeon et al. (2003) and Lai et al. (2007). Vlyssides et al. (2009) showed that the addition of ferrous ions in the form of ferrous chloride solution (2% w/v) induced a stable and excellent COD removal efficiency from synthetic milk wastewater, regardless of the increasing in OLR. When the OLR was as high as 10 g COD L-1 d-1, the COD removal efficiency of 98% was achieved.

reacted with ferrous iron to probably form insoluble vivianite precipitated in the reaction chamber. It can be confirmed by significant increasing of TSS (by 52.1% in RFe) and the accumulative iron ions and phosphorus content detected in the anaerobic granular sludge in RFe at the end of the experimental period. The TP and total iron percentage in the dry matter was 0.314 and 0.0981, respectively, in RFe and 0.019 and 0.0129, respectively, in R0. This results confirmed the anaerobic microbial corrosion occurred in RFe. Choung & Jeon (2000) and Jeon et al. (2003) obtained similar trends for domestic wastewater treatment under anaerobic conditions. Moreover, the colour of anaerobic sludge granules from RFe was black, while from R0 was grey with white conglomerates (Fig. 4). It indicates that the presence of iron determine the colour of granules. The black colour of granules is due to the formation of large amounts of iron sulphide precipitate (Vlyssides et al., 2009). It was seen that the granule diameter in the sludge bed in RFe was smaller than in R0. It was different from the data reported by Vlyssides et al. (2009), who observed a considerable increase of 40% in the mean granule diameter resulted in iron accumulation in granules.

During the experimental period high iron concentrations in the RFe effluent were observed. During Stage 1, the highest content of iron was noticed (20.1 mg L-1) and it was consequently decreased to 19.2, 15.8, 14.2 mg L-1 in Stage 2, 3, 4, respectively. The decrease of the total iron in the effluent from the UASB reactor packed with steel elements can indicate the formation of a protective layer on the steel surface. According to Volkland et al. (2001) under certain conditions the vivianite could act as a corrosion-inhibiting layer. Moreover, biofilm-forming bacteria can protect steel from corrosion. With a dense suspension of microorganisms (> 109 cells mL-1) they can protect the steel surface by forming a corrosion-inhibiting layer in consequence of bacterial adsorption and adhesion (Volkland et al., 2001; Yu et al., 2000). Microbial corrosion and the formation of iron precipitates deteriorate the reactive media of steel elements (Karri et al., 2005). It could explain the gradual decrease in phosphorus and TP removal with the duration of the experiment.

Biogas production rate and CH4 content in biogas were higher in RFe than in R0 in all stages (except Stage 1 where the differences in biogas production between RFe and R0 were not statistically significant). According to Karri et al. (2005) zero valent iron was an electron donor for methanogenesis. It suggested that microbial corrosion of steel elements supported methanogenesis which contributed to the more CH4 and biogas production in RFe. Iron may play an important role in granulation phenomena and was found to be a component of essential enzymes that carry out numerous anaerobic reactions (Vlyssides et al., 2009; Yu et al., 2000). The conversion of COD to biogas components and bacterial growth may be limited at iron deficient concentrations. However, the accumulation of iron ions may decrease the specific activity of the bacterial groups, including methanogens (Yu et al., 2000). It was reported that high Fe2+ concentration in the anaerobic sludge granules led to decrease of the specific activity of biomass due to the presence of a large amount of minerals deposited within the granules, a significant decrease in the water content in granules, and the possible toxicity of high-concentration Fe2+ accumulated inside the granules (Yu et al., 2000). During the experiment, biogas production rate was not decreased from Stage 1 to 4, which could indicate that the activity of methanogenic bacteria was not inhibited by anaerobic steel corrosion process. The maximum value for biogas rate was 8.22 L d-1 in RFe and 4.2 L d-1 in R0. Najafpour et al. (2008) achieved the biogas production of 3.6 L d-1 for HRT of 48 h with the methane content of 76% from UF whey permeate. Venetsaneas et al. (2009) achieved about 1 L CH4 d-1 and 68% v/v methane content in biogas in the two-stage process for cheese whey fermentation.

Fig.2-2 showed the quality percentage of cellulose, hemi-cellulose, and lignin in biogas residue.

According to research results (Gao Zhenghua, 2008; Chen Hongzhang, 2008), the cellulose, hemi-cellulose, lignin of straw, wheat and corn stalks compared with these of biogas residue fibre were shown in table 2-4.

The comparative analysis results showed that, cellulose quality percentage of biogas residue fibre after anaerobic fermentation was 5% higher than straw, wheat stalk, corn stalk; while hemi-cellulose quality percentage was 5%lower than straw, wheat stalk, corn stalk; lignin quality percentage did not change. The result showed that anaerobic fermentation to lignin content was not influence, hemi-cellulose relatively reduced, cellulose relatively increased, it is positive to the resources utilization of biogas residue.

Biogas technology utilizing animal waste is not new in Tanzania; it was introduced in the country as early as the 1950s by private stakeholders. In 1975, the government through the Small Industries Development Organisation (SIDO) introduced the Indian design (floating gasholder digester) in primary and secondary schools, rural health centres and a number of other institutions. In 1982, the Parastatal Organization Centre for Agricultural Mechanization and Rural Technology (CAMARTEC) increased the dissemination of this technology in the northern regions. About 1 year later, that is around 1983, technical cooperation between Tanzania and the Federal Republic of Germany led to the introduction of the Biogas Extension Services (BES). CAM ARTEC and the Deutsche Gesellschaft fur Technische Zusammenarbeit (GTZ) were in-charge of implementing this project and the latter seconded an interdisciplinary team of social scientists, mechanical engineers and agriculturists to Tanzania (Sasse et al., 1991). Between 1984-1985 more strategies were developed to boost biogas adoption. Household plants were offered with a digester volume of 8, 12 and 16m3, and in 1990 the programme comprised standardized plants of sizes 12, 16, 30 and 50m3 for households and institutions (Mwakaje, 2008). The development work towards sustainable reliability and user friendliness resulted in extensive integration of biogas plants into the work routines of farmers. Over the period, CAMARTEC were involved in building capacity by training technicians in biogas plant construction. A »biogas unit» scheme was introduced and this integrated biogas plants, livestock housing with a concrete floor (Mwakaje, 2008). CAMARTEC was also providing advice on the utilization of slurry, gas pipeline systems, burners and lamps; and women were specifically instructed on how to use and manage the plants. The Ministry of Energy and Minerals in collaboration with donors was also promoting biogas use in the Dar es Salaam region. Its main activity was to support the dissemination of biogas technology in the region through facilitating training for private craftsmen, built demonstration plants and undertaking monitoring and evaluation. Up to 1989, only 200 units of biogas had been installed all over the country (Sasse et al., 1991) but in 1992 this had increased to 600 plants national-wide. Nevertheless, as Mwakaje (2008) noted despite all the efforts, the biogas technology did not diffuse much to the rural poor communities in many parts of the country where indoor fed dairy cattle are kept. Reasons for this poor diffusion of the biogas technology included high installation and maintenance costs and inadequate awareness about the technology. The conventional units being built in the country were large and expensive, costing approximately US$ 1400 for one unit (Rutamu, 1991) to USD 2200 depending on the size of digester (IRA, 2005). Furthermore, repair and maintenance required highly skilled labour and most component parts, constructed mainly from concrete and steel, were far out of the financial reach of smallholder farmers (Mwakaje, 2008). This slow pace of biogas technology development by CAMARTEC raised a number of criticisms among stakeholders. For example, the Evangelical Lutheran Church of Tanzania (ELCT) blamed CAMARTEC its commercially oriented and strictly standardized dissemination programme. The ELCT claimed that the programme had not been adapted to Tanzanian conditions as it only served the rich farmers (Sasse et al., 1991). But also most of the CAMATERC activities were concentrated mainly in the two regions of Kilimanjaro and Arusha in a country with more than 20 regions. On the other hand, the Ministry of energy and minerals’ activities were concentrated in the Dar es Salaam region where unfortunately indoor fed dairy cattle are limited to a few households.

Reacting to some of these criticisms, the government of Tanzania changed the biogas technology dissemination strategy in the country. In the years starting 2000 polythene tubular digesters were promoted to reduce production cost through using local materials and simplified installation and operation costs (Mwakaje, 2008). The type of plastic needed for polythene was locally manufactured in Tanzania, maintenance and repair were simple, cheap, and did not require skilled labour and the cost of construction was low. A model promoted by the Sustainable Rural Development (SURUDE) was a low-cost design suitable for poor farmers (CEBITEC, 2003) in rural areas. The material cost was about US$ 100. However, this type of biodigester had one major disadvantage in that it could be easily sabotaged (torn out). This is because the plastic materials of the biodigestor are normally placed on the surface outside the house and therefore could easily be destroyed (Mwakaje 2008).

The cover membrane consists of a weather protection foil, gasholder membrane or gas collector, clamp hose, level indicator for the gas collector, excess and low-pressure safeguard, and a supporting structure (Fig. 24). A desulphurization unit is integrated into the inner membrane (gasholder) to reduce the hydrogen sulfide (H2S). The collector is sealed gas-tight with two cone-shaped foils and a clamp rail.

There are three structure types for supporting the cover, which are: (1) a steel post supports directly the cover, (2) a wood structure (incl. a wood post) supports the cover, and (3) a steel post supports a wood structure which in turn supports the cover.

Fig. 24. Air supported double membrane cover (MT-ENERGIE GmbH & Co. KG)

6.2 Monitoring and controlling

The individual facility components are monitored by computer technology even from afar. At the same time technical procedures, as well as input and output quantities are neatly documented. The computer system consists of an on-site control system installed on a computer and sometimes another remote access system on another computer located far away from the site, e. g. in the company’s headquarter. The remote computer is connected to the site through routers (ISDN or DSL), allowing a remote control of the site. Any of the aforementioned computers is able control the biogas plant through controlling the central plant control system which is connected to the digester running components (agitator, pump, feeding system…etc.), the cogeneration unit, and the biogas analyzer. A control system allows for real-time local and remote operation and monitoring as well as data gathering (Fig. 25).

Also, the Herchel-Bulkley model indicated that reactor fluid A performed as a pseudo­Newtonian fluid called Bingham plastic, since the yield stress-value was > 0 (0.24 Pa) and a flow behaviour index of 1.06 (Table 4). Results obtained by the Ostwald and Bingham models confirmed a Bingham plastic behaviour of reactor A. However, since the X0-value was almost 0 and the n-value 1 it was also closely performing as a Newtonian fluid which is consistent with the flow curve appearance (Fig. 2). However, when studying the viscosity curve (Fig. 4) the results showed an initial viscosity decrease and then a constant viscosity indicating a pseudo-Newtonian fluid behaviour.

The Herschel-Bulkley and Ostwald models both indicated a pseudoplastic behaviour of reactor D, since the X0-value was 0 and n < 1 (Table 4). The Bingham model gave a yield stress of 0.33 Pa which did not indicate Newtonian or Bingham plastic behaviour. Thus, the common results for reactor D strongest indicate a pseudoplastic fluid behaviour.

Reactor B was hard to define also when modelling the rheogram data values of figure 4. The regression values were low for all three mathematical models (Table 4). However, the Herschel-Bulkely model had a flow behaviour index n>1 indicating that the fluid acted as a shear thickening (dilatant) fluid, but the Ostwald and Bingham models indicated pseudoplastic and Bingham plastic behaviours, respectively. When the static yield stress appeared in the reactor B rheogram (Figures 2 and 4), the flow behaviour index showed shear thickening fluid behaviour (n=3.4) and a limit viscosity of 8 mPa*s. This also corresponded to a low consistency value (5*1010). At the static yield stress of 24 Pa (Fig. 5), the flow behaviour index showed shear thickening fluid behaviour (n=1.41) and a limit viscosity of 22 mPa*s. This also corresponded to a low consistency value (5*10-4). As soon as the fluid was measured again, n decreased (0.70) showing a pseduoplastic behaviour and K increased (0.11) indicating that the consistency of the reactor material was higher. The limit viscosity was 17 mPa*s. These results showing a time dependency and structure recovery strengthen the arguments for a thixotropic fluid behaviour of reactor B. Once the stirring has ended and the fluid was at rest, the fluid structure starts to rebuild. Therefore, the viscosity become time dependent. This information is important to consider for biogas reactor performance, e. g. when applying semi-continuous mixing.

Also, fluids from reactor C and E were hard to define from modelling of the rheogram data because they gave indications for fluids being between pseudoplastic and Bingham plastic behaviours, i. e. the t0-values were >0 (2.89 and 2.38) and n <1 (Table 4).

2. Conclusion

The biogas reactor fluids investigated were behaving viscoplasticly, since they had yield stress and one of them was also thixotropic, due to its partial structure recovering. However, the reactor treating slaughterhouse waste was very close to act as a Newtonian fluid. Also, there was a difference in dynamic — and limit viscosities depending on the substrates used. The results demonstrated that similar TS values did not necessarily correspond to similar flow and viscosity behaviours. Nor, did biosludge from two different Swedish paper mill industries with similar TS show similar viscosity values.

To encounter problems related to involvement of new substrates and/or co-digestions in existing facilities, investigations for possible viscosity changes are needed. Ongoing research will hopefully provide an important basis for predictions of changes in rheology linked to the composition of the organic materials, which are translated in the process. This is important in order to achieve proper designs in relation to possible variation in substrate mixes in conjunction with new constructions, but also to better control material flows in the existing facilities to avoid disturbances in the reactor performance.

The data obtained for the microbial population by DGGE were further analyzed by Jaccard’s (3) and Sorensen-Dice’s (4) indexes. Similarity indices are frequently used to study the coexistence of species or the similarity of sampling sites. A matrix of similarity coefficients, between either species or locations, may be used to analyze changes in microbial populations over time or at different locations (Real and Vargas, 1996). Jaccard’s index is one of the most useful and widely used indices to determine similarity between binary samples. Jaccard’s index may be expressed as follows:

] =—— ^—— (3)

nA+nB-nAB

where nAB is the number of bands in both samples A and B, nA is the number of bands present in sample A, and nB is the number of bands present in sample B.

Sorensen-Dice’s index, also known as Sorensen’s similarity coefficient, is also used to compare the similarity of two samples. It can also be applied to the presence/absence of data. The index is described by the expression, the terms of the equations are the same as describe above:

г 2пав

Jn —

nA+nB

2. Results

The pH is relatively easy to measure, and is often the only parameter of the liquid phase which is measured on line. The change of the pH can be an indicator, for the stability of anerobic digestion process. Since the micro-organisms can grow at only one specific pH range. The effluent pH can also affect the pH in the digester. The use of the pH as an indicator is normally based on the fact that a decrease of the pH corresponds to the accumulation of VFA. Some anaerobic systems apply the control of the pH where an acid or a base is added to ensure the suitable pH for the microbial growth.

2.4 Alkalinity

Alkalinity is a better alternative than the pH to indicate the accumulation of VFA, because the increase in VFA will directly consume alkalinity before the great change of pH. However, it is proved that the total alkalinity (TA) measured by the titration of the sample with pH 4.3 is not very sensitive because of the combination of result of VFA and bicarbonate to the TA (Hill & Bolte, 1989). Partial Alkalinity (PA) or bicarbonate alkalinity measured by titration of sample in pH 5.75 has an empirical correlation to the VFA accumulation (Wang & al., 2005). However, one does not observe this during the VFA accumulation at the time of the ammonia overload, because this latter increases the alkalinity of the system (Wang & al., 2005).

A 5 L UASB reactor with 4.5 L working volume (R1) was made of stainless steel and cylindrical in shape (Fig. 12). The reactor was constantly stirred at 50 rpm. The pH of mixed liquid in R1 was controlled automatically with 6 M NaOH. The temperature in R1 was maintained at 37°C by inserting the reactor in the thermostatic chamber. For start-up, the reactor was filled with undiluted UF whey permeate and was operated anaerobically at a batch mode. When hydrogen production reached its peak value, the bioreactor feeding mode was turned to a continuous one at a HRT of 24 h (OLR of 10 g COD L-1 d-1) or at a HRT of 12 h (OLR of 20 g COD L-1 d-1). The R1 performance (biogas production and composition in H2 and CH4, COD, Total Volatile Fatty Acids — TVFA concentration, pH) was monitored twice a week throughout the experimental period (84 days).

A 5 L UASB reactor with 4.5 L working volume (R2) was made of stainless steel and cylindrical in shape (Fig. 12). The reactor was constantly stirred at 50 rpm. The pH of mixed liquid in R2 was controlled automatically at pH 7.2 (±0.05) with 6 M NaOH. The temperature in R2 was maintained at 37°C by inserting the reactor in the thermostatic chamber. The R2 was fed with the effluent from R1, which was collected in a 3 L container used as a storage tank which was constantly stirred at 50 rpm (Fig. 12). The temperature in the tank was maintained at 37°C by placing it in the thermostatic chamber. Overflow effluent flowed out in the top part of the storage tank and was collected in a separate container. The R2 was operated at an HRT of 3 d. The R2 performance (biogas production and composition in CH4, COD, TVFA concentration, pH) was monitored twice a week throughout the experimental period, from day 51 to 84. Before R2 was fed with R1 effluent, the diluted UF whey permeate had been used as a feedstock to reach the OLR of 2 g COD L-1 d-1 and HRT of 3 d.

The rule of optimization based on film performance meeting the agronomic requirement to reduce energy consumption and save raw materials as much as possible was applied to determine the optimum combination of the factors. The result was that when rosin was held at 0.8%, bauxite was held at 4%, wet strength agent was held at 1.8%, beating degree was held at 35 SR°, grammage was held at 80 g/m2, the performance that was dry tensile strength was greater than 30N, wet tensile strength was greater than 12N, the degradation period was 35 days to 60 days could be obtained, seeing in Fig 3-13.

3.5 Manufacturing technology

Based on the above research results, manufacturing technology of the biogas residue fibre film was obtained, seeing Fig 3-14.

The flocculation efficiency of chitosan is sensitive to its characteristics. The most important characteristics of chitosan for flocculation efficiency are the degree of deacetylation and molecular weight since these are the main factors that affect particle size, particle formation and aggregation in the flocculation process. However, environmental conditions, i. e. pH and ionic strength, are also important in the dissolution and the charge of chitosan for flocculation process.