The fabrics, either in the form of natural or chemical fibres, have reached millions of tonnes of production and have provided huge advantages to world economic values (Aizenshtein, 2004). In social terms it has provided benefits to more than 2.2 million workers through 114,000 textile-related companies. In 2001, the European textile and clothing industries contributed to about 3.4% of the EU manufacturing industrial revenue and granted 6.9% of

© 2013 Muda et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

the work opportunities to the citizens (IPPC, 2003). According to recent statistics, the global textile market is worth more than US$400 billions (Directory of Textile Manufacturers and Suppliers — http://www. teonline. com/industry-overview. html). It is predicted that the global textile production will grow up to 50% by 2014 as compared to the fabrication in 2005.

Globally, Malaysia is also known for its high quality textile and apparels. Since the early 1970s, when the country started to embark on being an export-oriented country, the growth of Malaysian’s textile and apparel industry has increased tremendously and now provides an export value of 3.5 billion USD. This has listed the textile industry as the ninth largest contributor to total earnings of the manufactured exports in 2007. The industry has provided more than 67,000 work opportunities through 637 licensed textile production companies with investments of 2.6 billion USD (MIDA, 2007).

In Malaysia and many other developing countries, most of the textile mills are of small and medium scale. For these mills, the full installation of a wastewater treatment plant is quite difficult due to economic reasons. Hence, the mills have been discharging significant quantities of pollutants into the streams with fiber manufacturing and dyeing sectors being the predominant ones (Haroun and Azni, 2009).

1.1. Ni/BCC catalyst

The procedure of ion exchange is shown in Figure 5 and Figure 6. Yallourn (YL) coal char was used as catalyst support. YL coal (Australian brown coal) received in the form of briquettes. The coal was crushed, sieved to a particle size range of 1 — 2 mm in diameter, and then dried at 380 K for 12 h. The nickel addition to the coal matrix was achieved by ion — exchange with a solution of basic hexa ammine nickel carbonate (NH3)6NiCO3 (Figure 5, 6). The coal was mixed with the (NH3)6NiCO3 solution for 24 h and then recovered by filtration. The recovered solid was washed with distilled water and filtered again. Then, the washed solid was dried under N2 flow at 380 K for 24 h. Last, raw catalysts were produced.

Catalysts was characterized by powder X-ray diffraction on XRD; M03XHF22, Mac Science Co., Ltd, using CuKa radiation(40 kV, 30 mA) in order to identify the potential evolution of the crystalline phases during catalyst pyrolysis tests. The diffractograms were recorded a step time of 10 sec. SEM analysis was applied to study the surface structure of Ni/BCC catalyst (FE-SEM; JSM-6700F, JEOL Datum Ltd.). An atomic absorption flame emission spectrophotometer (AA-6400F, Shimadzu Corp.) was used to examine the amount of Ni on raw Ni/BCC (Ni 9 + 1%-dry). After pyrolyzing with nitrogen gas at 923 K for 90, its weigh loss is approximately 54 %, and therefore, nickel loaded in coal char could be estimated 19.6 + 2%-char base. The intimacy of the contact between coal char and catalyst was so effective that the reactivity was considerably higher than those prepared by a conventional impregnation method [21-24]. Nitrogen adsorption characterization of catalysts was performed on equipment for automatic gas and vapor adsorption measurement (BELSORP-max, BEL Japan Co. Ltd.). Prior to adsorption measurement, the catalysts were degassed at 573 K for 3 h under a dynamic vacuum. The surface areas of fresh catalysts (Ni/BCC), which were obtained after pyrolysis of raw Ni/BCC at 923 K for 90 min is 350 m2/g [28,29].

1.2. Ni/АЬОз catalyst

A conventional nickel catalyst (No. C13-4, Ni 20±2 wt % SUD-CHEMIE CATALYSTS JAPAN, Inc.) that was supported with alumina was also used to compare with Ni/BCC catalyst. It was crushed and sieved to the fraction of 0.5 — 1 mm.

The cost of biethanol per litre presented here mainly calculated from the cost of raw materials used; i. e. lignocellulosic biomass and sulfuric acid and processing cost. Fixed operating costs are excluded from this calculation. Fixed operating costs including labour and various overhead items are fully incurred regardless of the operating production capacity and their contribution to the total cost of bioethanol is estimated at 15 to 18%. [37] stated that cost of biomass contribute almost 60% to the total production cost which is the highest contributor to the cost of bioethanol. Therefore, the main focus here is to estimate the effect of raw materials price on the cost of bioethanol.

1.1.3. Cost of lignocellulosic biomass

Assessing the various costs of mobilising lignocellulosic biomass today which include harvesting, collection, pre-processing, substitution and transportation to a downstream hub, the order of biomass can be mobilised at globally competitive costs, i. e., at a cost of less than RM 250 per dry-weight tonne. The distance of transportation should be less than 100km in radius from the collection area.

1.1.4. Cost of sulfuric acid and recovery charge

The sulfuric acid is sells at RM 264 per tonne. By far, sulfuric acid is the largest expenditure of raw materials in the process of making bioethanol from lignocellulosic biomass. Nonetheless, the current technology enable the acid-sugar solution from hydrolysis separated into acid and sugar components by means of chromatographic separation using commercial available ion exchange resins to separate the components without diluting the sugar. The separated sulfuric acid is recirculated and reconcentrated to the level required by the decrystallization and hydrolysis steps. Using this technology almost up to 100% of the sulfuric acid can be recovered from the process.

Supercritical fluid extraction (SFE) is one of the relatively new efficient separation method for the extraction of essential oils from different plant materials. The new products, extracts, can be used as

a good base for the production of pharmaceutical drugs and additives in the perfume, cosmetic, and food industries. Use of SFE under different conditions can allow selecting the extraction of different constituents. The main reason for the interest in SFE was the possibility of carrying out extractions at

temperature near to ambient, thus preventing the substance of interest from incurring in thermal denaturation.

Supercritical fluid extraction has proved effective in the separation of essential oils and its derivatives for use in the food, cosmetics, pharmaceutical and other related industries, producing high-quality essential oils with commercially more satisfactory compositions (lower monoterpenes) than obtained with conventional hydro-distillation (Ehlers et al., 2001; Diaz-Maroto et al., 2002; Ozer et al., 1996). Also, extraction with supercritical fluids requires higher investment but can be highly selective and more suitable for food products. This plays a mechanistic role in supercritical fluid chromatography (SFC), where it contributes to the separation of the solutes that are injected into the chromatographic system.

Supercritical fluid extraction is an interesting technique for the extraction of flavouring compounds from vegetable material. It can constitute an industrial alternative to solvent extraction and steam distillation processes (Stahl, E. and Gerard, D. 1985). SFE allows a continuous modification of solvent power and selectivity by changing the solvent density (Nykanen, I. et al., 1991). Nevertheless, the simple SFE process, consisting of supercritical CO2 extraction and a one-stage subcritical separation, in many cases does not allow a selective extraction because of the simultaneous extraction of many unwanted compounds.

1.1. Anaerobic processes

Opposite to the aerobic are anaerobic processes, which are performed in the absence of oxygen by groups of heterotrophic bacteria, which in a process of liquefaction/gasification in two stages, becomes a 90% organic matter present at first in intermediate (partially finished products stabilized that include organic acids and alcohols) and then to methane and gaseous carbon dioxide:

organic mater —— ——"c——— > intermediaries + CO2 + H2S + H2O (1)

organic acids———— —— ——— >CH4 + CO2 (2)

The process is applied universally in hot anaerobic digesters, where in the primary and biological sludge is maintained for about 30 days at 35 °C to reduce its volume (about 30%) and their ability to putrefaction, there by simplifies the removal of sludge. The advantage of this type of digestion is that generates energy in the form of methane and the production of sludge is only 10% [5, 25].

One of the large advantages of most willows is that they can be propagated vegetatively by means of cuttings. Traditionally, cuttings of about 20 cm in length were produced manually from 1-year old long rods. These cuttings were taken during the winter period, when willow is dormant, and could be stored in a fridge until planting in spring. During commercialization of the growing system in Sweden in the late 1980s, manual planting was replaced by machine planting. Establishment costs for short rotation willow coppice decreased substantially during the initial phase of commercialization in Sweden [45]. This was mainly achieved by mechanisation of planting, employing equipment which, in one process, cuts willow rods (1.8 — 2.4 m. long) into cuttings and then plants them (Figure 1). These cuttings are around 18 to 20 cm long, and the cutting is pressed down into the prepared soil so that only 1-2 cm protrudes above soil surface. This is believed to provide the cutting with good soil contact, thereby minimizing the risk of drying out [46]. Field storage of cuttings can result in water loss and reduce shoot survival and biomass production. This problem has partly been overcome by the use of entire shoots, which are considered to be more resistant to desiccation than cuttings [47]. Volk et al. [48] also pointed to risks of desiccation and showed that a prolonged time of field storage after cold storage may lead to a decrease in survival and growth rate.

Cutting size (length and diameter) has positive effects on subsequent willow growth. The positive effects of cutting size on growth and survival decline with increasing sizes ([49, 50, 51], and Rossi [52] found that the differences in cutting length with relevance for establishment in practice are to be found between lengths of 10 and 20 cm. Positive effects of cutting size generally are attributed to the size of the carbohydrate pool available for allocation to roots and shoots [53]. The effect of cutting length may also be associated to the ability of longer cuttings to withstand soil desiccation [54]. The phenological development of buds and shoots is affected by cutting size and also by the height above ground from where the cuttings were taken [51]. Using the simple assessment criteria for bud development as described in Table 1, bud development, a few weeks after planting, is a function of the diameter size of the planted cutting (Figure 3). However, cuttings derived from apical positions along shoots display for a given diameter a higher shoot biomass production than cuttings derived from the more basal parts (Figure 4). As willow rods display a taper, the question arises which of the two factors (cutting size or position) is the strongest determinant of shoot biomass production during early establishment.

A further evaluation of produced shoot biomass on the cuttings showed that cutting size by far is the single most important determinant of early biomass production, which led to the recommendation to employ thicker cuttings and to discard the thinner apical parts from long rods. While the introduction of planting machines has increased the speed of planting

and reduced planting costs, ongoing research indicates that planting machines may cause damage to cuttings, especially when planted in compacted soils. Preliminary results by Verwijst et al. [32] and by Edelfeldt et al. [55], suggest that that undamaged cuttings had a better growth performance than visibly damaged cuttings. Planting by machine on hard soil resulted in a relatively large number of cuttings landing on the soils surface. Soil compaction and machine planting interacted with cutting dimensions, the poorer performance of thinner cuttings being more pronounced in compacted soil (Figure 5).

Furthermore, machine planting also increased the relative variation of shoot height (Figure 6) compared to hand prepared and planted cuttings. Consequently, to obtain a faster and more even establishment of willows, Edelfeldt et al. [55] recommend thorough soil cultivation prior to planting, further development of planting machines to minimise damage to cuttings at planting, and the use of cuttings with a diameter of at least 10-11 mm.

Treatment

Figure 6. Relative variation (%) and its standard error in plant height for manually planted cuttings (Treatment 0) versus machine planted cuttings in Soft and Hard soil (Treatments 1 and 2, respectively).

The research objective of this case study was to develop an appropriate control method for a bioprocess and to implement it on a laboratory plant, namely the control of the fed batch cultivation of Hansenula polymorpha yeast for alcoholoxydase-containing biomass. At first, the process is described and a mathematical model is proposed and then the control strategy is defined and the intelligent control structure is designed. Finally, the control performances are tested through real data.

A discontinuous fed-batch bioprocess for alcoholoxydase-containing biomass with the methylotrophic yeast Hansenula polymorpha CBS — 4732 was operated in an airlift lab — bioreactor The intracellular enzyme, to be separated further on, is used for obtaining a high — specialized kit for methanol/ethanol determination. The yeast was cultivated on a complex medium with (NHi)2SO4, KH2PO4, Na2HPO4, MgSO4*7H2O, CaCh, yeast extract or autolysed residual beer yeast as organic N source and microelements (Fe, B, Cu, I,

)

where: Es and Em are the substrate and medium loss by evaporation [g/h]; ps and рм are the substrate and medium densities [g/L]; Yx/s is the substrate conversion yield referred to the biomass [g dry matter/ g substrate]; q is the specific growth rate [1/h]; V is the volume of the cultivation medium in the bioreactor [L]; x and S are the biomass and substrate concentrations [g/L] and t is the time [h], qmax represents the maximum specific growth rate [1/h] and Ks is the saturation constant [g/g]. The main process parameters were: continuous temperature control 37oC; a minimal level of pO2 — 10% from the saturation concentration was maintained during the exponential growth; continuous pH control between 4.5 — 5.0 by addition of NH4OH (12.5%); no foam control, if the main parameters are optimally controlled. The unique C source, the methanol was introduced function of the yeast growth rate in connection with the substrate consumption rate for avoiding the growth inhibition by substrate concentration. The developed model (1) is based on the mass-balance principle and on the hypothesis of a non-inhibitive substrate effect (i. e. the specific growth rate is defined by
the Monod equation). In line with the operation mode (fed-batch with discontinuous substrate feeding), there are discontinuous variations of the main variables due to: substrate feeding, medium feeding (to overcome the loss by evaporation or sample collection) or samples withdraws. That is why the following mass-balance equations are to be added to express each discontinuous modification for volume, and substrate or biomass concentrations:

Vk + ASk + AMk = PMk + Vk +1

SkpMVk + ASkpS = PMkpMSk + Sk+1pMVk +1 (32)

XkVk = PMkXk + Xk+1Vk+1

where: Vk, Vk+1=volume before / after modification [L]; ASk, AMk=substrate volume and respectively medium volume adding [L]; PMk=sample withdraw [L]. The same notations are used for Sk, Sk+1 and Xk, Xk+1. We use: ps = 800[g/L]., respectively qm = 1000[g/L]. The identification of the model parameters was carried out based on measured values in order to minimize the modeling error. The identification procedure (i. e. Nelder-Mead algorithm) determines the optimum values for the following process parameters: Es, Em, pmax, Ks and Yx/s.

For this bioprocess, the overall control objective is to obtain large biomass quantities, based on the assumption that high biomass concentration will assure the obtaining of important alcoholoxydase-active biomass. In this paper a control system based on fuzzy logic is proposed. It is well known that Fuzzy Control Systems (FCS) can manipulate incomplete and uncertain information about the process assuring high control performances [6-8]. The proposed FCS receives information about the state of the bioprocess expressed by the biomass and substrate concentrations. Based on this information, FCS computes the quantity of substrate to be added into the reactor. According to these observations the inputs of FCS are the biomass (X) and substrate (S) concentrations, and the output is the correction to be applied on the substrate addition. The rules of FCS are presented in Table 1.

Rules evaluation by the inference engine is made according to the min-max inference rule and the output defuzzyfication is made based on the centroid defuzzyfication method.

Table 6. The rule base

4. Results & discussions

The control loop was implemented in MATLAB, version 7.5. For control loop simulation the proposed mathematical model was used and the simulation results were compared with the experimental data.

The simulation results show that the proposed fuzzy control system is capable of computing the substrate feedings needed for cell growth according to the biomass concentration increase. The evolution of the substrate concentration marks the substrate consumption and additions, as well as the increase of the additions along with cell growth. The biomass concentration obtained by simulation follow closely the experimental data. As a conclusion of this case-study, it can be accepted that the success of such a control implementation is critically dependent upon the technical operating conditions of the process.

5. Conclusions

The overview on the current status of bioprocess modeling and control focuses on three main topics: (i) unstructured versus structured and metabolic modeling; (ii) control based on common technique (model based control and adaptive control); (iii) control based on artificial intelligence.

It is finally to underline that the framework of bioprocess modeling & control still offers interesting perspectives to obtain robust control solutions for the aerobic bioprocess. Moreover the future of bioprocesses’ optimal control will rely on applying the same concept: the use of different modeling methods in conjunction with intelligent control techniques. If a simplified representation of the bioprocess exists (i. e. an a priori model), this optimal profile can serve as an initial trajectory for intelligent control algorithms when the complexity of the process representation is described in a subjective mode (by human expert).

Changes in the HRT of the reactor system caused variation of the anaerobic and aerobic react times. It also may affect the loading rate imposed to the system if the substrate concentration is maintained. These conditions will affect the microbial activity within the biogranules and may influence the performance of the reactor system. The details of the experimental conditions of the reactor system are shown in Table 5.

The microbial activity was measured based on the OUR of a complete one cycle operation.

The OUR was measured several times before each of the stages ended and showed that most of the external substrate was consumed more or less within the first 30 minutes of each aerobic reaction phase. Figures 12 and 13 show the profiles of the OUR throughout the experiment from Stage I to Stage VI.

The OUR profile (Figure 12) shows that the initial measurement of the OUR was reduced as the HRT increased (Stage I to Stage III). This is due to the reduction in the OLR as the HRT increased. Less oxygen is required as the organic load concentration is reduced. After a sharp increase of OUR at the beginning of each cycle in all stages, the OUR measurement was consistently low until the end of the cycle. The low value of the OUR indicates that most of the external substrates have been consumed. It also means that the microorganisms in the reactor system are under starvation phase. At this phase, no further degradation was observed even though the HRT was extended. During the starvation phase, endogenous respiration will take place, except at the beginning of the second phase of aerobic reaction where there was a short increase in the OUR. This increase is caused by the mineralization of

amines, the byproduct of dye degradation during the second anaerobic reaction phase. As the duration of anaerobic reaction phase increased, the short pulse increased as shown in Figure 13 (a and b) of Stage IV and V, respectively. Stage IV and Stage V were operated with the same HRT and organic loading but were different in the anaerobic and aerobic reaction phase ratio.

500 400 300 200 100 0

0 0.5 1 1.5 2 2.5 3

The changes in the HRT will also affect the biomass accumulated within the reactor system. The HRT was increased from 6 hours in Stage I to 24 hours in Stage Ш, without the addition of any substrate. This resulted in the reduction of OLR supplemented into the reactor system from 2.5 to 0.6 kg COD/m3 day. The HRT for Stage Ш to VI was kept constant i. e. 24 hours, but the duration of anaerobic and aerobic react phases was varied. From Stage III onwards, the OLR was increased to 0.8 kg COD/m3 day by increasing the concentration of the carbon sources in the synthetic textile dyeing wastewater.

250

250

200

150

100

50

0

140

120

100

80

60

40

20

0

6 8 10 Time (hours)

Figure 13. OUR profile of (a) Stage IV (Aerobic phase 11.84 hours), (b) Stage V (Aerobic phase 5.84 hours), (c) Stage VI (Aerobic phase 17.84 hours)

Table 6 shows the oxidation-reduction potential (ORP) values measured during the second phase of the anaerobic and aerobic reactions during the experiments. The ORP profile of all the stage corresponded very well with the dissolved oxygen. As the anaerobic react phase increased, more of negative values of the ORP were recorded. During the aerobic phase the ORP varies between +98 to +177 mV.

The biomass profile at steady state with stepwise increment of HRT (Stage I to Ш) and variation of react phases (Stage IV to VI) are shown in Table 8. As shown in Table 7, it is apparent that the biomass concentration (MLSS) in the reactor decreased and the VSS in the effluent were also reduced with the increase in the HRT (Stage I to III). The reduction of the biomass concentration in the reactor may be due to the lower value of OLR applied in the reactor system as the HRT increased.

When the OLR was increased to 0.8 kg COD/m3-day, there was an improvement in the biomass concentration where the biomass concentration have increased to 30.5 ± 3.4 g/L and 31.6 ± 3.7 g/L in Stage IV and Stage V as compared to 25.2 ± 1.8 g/L of biomass concentration in Stage III which run at the same HRT (24 hours) but with OLR 0.6 kg COD/m3-day. The increase in OLR has caused an increment in the biomass concentration in the reactor. A

slight increase in the biomass concentration was also observed along with the longer period of the anaerobic phase (Stage V), i. e. 18 hours.

The ratio of the volatile biomass (MLVSS) to total biomass (MLSS) reduced from Stage I to Stage III mainly due to decrease in the OLR as the HRT increased from 6 to 24 hours, whereas the MLVSS/MLSS ratio of the Stage III and Stage IV with 12 hours aerobic reaction phase was observed higher with the ratio of 0.73 and 0.85, respectively. The increment may be due to the increase of the OLR from 0.6 to 0.8 kg COD/m3 day (Stage III to Stage IV). Increase in the OLR means more carbon sources were supplied to the microorganisms in the reactor. When more food is available, more growth will take place and this is indicated by the increase in the MLVSS/MLSS ratio.

However, when the anaerobic period of the HRT is extended, the MLVSS/MLSS ratio decreased (0.71). Decrease in MLVSS/MLSS ratio may indicate an increase of inorganic accumulation within the granulation biomass. When the duration of aeration phase was increased up to 18 hours, the biomass started to reduce again (Stage VI) and increase of VSS in the effluent was once again observed. This may give an indication that too long of aerobic reaction phase is not suitable for granular biomass system. Prolong of aeration time may result in instability of the reactor performance. The profile of biomass concentration of the reactor system is given in Figure 14.

The SRT of the reactor system increased from 27.6 ± 13.4 to 78.9 ± 30.8 d when the length of the HRT increased from 6 to 24 hours (Stage I to Stage III). With HRT of 24 hours, increase of anaerobic reaction phase up to 18 hours (Stage IV to Stage V) has slightly increased the SRT from 70.1 ± 23.9 to 72.5 ± 23.3 d. The SRT value changes in each stage of the experiment. According to Wijffels and Tramper (1995), the favorable sludge age for high removal efficiency for COD and nitrification process is more than 4 days. Based on the SRT obtained, this biogranular system is capable of the simultaneous degradation of nitrification process and COD removal. Since the treatment goal is to remove recalcitrant dyeing compound, the SRT value of all stages evaluated in this experiment was in the acceptable range from degradation of xenobiotic compounds (Grady et al. 1999).

The SVI value of the biogranules was used to evaluate the biogranules settling ability. It is anticipated that bigger biogranules will have higher settling velocity and hence, reduce the SVI value, indicating good settling ability. The SVI value improved when the anaerobic react phase was prolonged in Stage V indicating such reaction pattern will help to develop granules with better settling profile. According to Panswad et al. (2001a), inert biomass increased as the anoxic/anaerobic condition was prolonged. It is possible that the accumulation of inert particles within the biogranules increased and resulted in improved SVI properties. Table 8 showed the physical properties of the biogranules at different stages of the react phase.

Figure 15 shows the profile of SVI of the reactor system. The SVI value in Stage V was reduced from 16.8 ± 1.3 mL/g (in Stage IV) to 15.5 ± 1.3 mL/g. This is expected to be due to the accumulation of more inert solids within the biogranules as shown with low levels of MLVSS/MLSS ratio in Stage V (0.71). Despite changes in HRT that caused decrease in the size of biogranules, the SVI values of the whole experiments were good except for Stage VI. During Stage VI, the prolonged of the aerobic phase (i. e. 17.8 hours), which was operated at high superficial air velocity (2.5 cm/s), cause the biogranules to rupture. At this stage, the size of biogranules becomes smaller causing the settleability of the particles to reduce and was demonstrated with increase in SVI value.

Hydraulic retention time is an important parameter that control the contact time between the biomass and the wastewater in a reactor system. The HRT of a system must be long enough for the degradation process to take place. However, in the application of biogranules in the treatment system, the HRT should not be too long as it may cause the disintegration of the granules. According to Tay et al. (2002) and Wang et al. (2005), a short

HRT is favorable for rapid granulation process, while too long HRTs may lead to granulation system failure due to high biomass lost (Pan et al., 2004). An optimum HRT of biogranulation systems will be able to stabilize the reactor performance with good biomass retention and high removal performance. According to Pan et al. (2004), the optimum HRT for aerobic granulation systems ranging from 2 to 12 hours where stable aerobic granules with good settleability and microbial activities. However, the optimum HRT for treating different types of wastewater may vary depending on the type of wastewater and the targeted degradation compound.

Utilization of the energy from methane emitted by animal manure is of current ongoing interest. Biogas production is the technology that converts animal manure and other biomasses into viable fuel, recycling the carbon resource of animal slurry. Biogas production is known to be the most suitable technology to produce renewable fuels from wet biomass such as animal slurry.

Biogas can be produced from nearly all kinds of biomass, nevertheless, the largest resource represented is animal slurry. In an effort to obtain higher methane yields, co-digestion of livestock manure with industrial organic waste has been implemented successfully in large scale biogas plants in Denmark. Nevertheless, only a few biogas plants have generated economic profit in Denmark. Facing a 10-fold dramatic increase of Danish biogas production, the economic point of view should be integrated by ensuring the price of biogas being competitive in the energy market. This could be done either by increasing biogas yield or reducing operating costs per feedstock unit. The low profitability of biogas produced from animal slurry is due to the fact that quality and quantity of organic pools are critical. Low biodegradability (BD) of animal slurry is often caused by large amounts of indigestible fractions which are concentrated during animal digestion. The quantity of organic pools in slurry is often too small to perform economically viable operations [10,11]. Biogas productivity per unit of feedstock volume is inevitably related to its biochemical and physical composition. Hence, energy crop has been widely used as co-substrate to enhance biogas productivity particularly in Germany and Austria, using mostly maize, sunflower, grass and Sudan grass [16]. Meanwhile, in Denmark industrial organic waste is co-digested in most large scale biogas plants to increase methane yield. This results in limited availability of organic industrial waste, creating a setback of extending the biogas industry [11,17].

Anaerobic digestion (AD) has been used to treat biodegradable solid waste such as MSW, industrial waste and sewage sludge over decades. Biogas containing methane and carbon dioxide is the main product form AD digester. Generally, biogas is collected in the gas tank and they can be directly exported to national gas grid or sent to combustion in the CHP system to generate electricity (with a yield in the range of 0.7 — 2.0 kwh/m3 biogas) and heat.

AD process is a dynamic complex system involving microbiological, biochemical, and physical-chemical processes though which the biodegradable waste are turned into biogas. Among biological waste treatment methods, AD has been identified as the most environmentally sustainable option for treating biowaste since it offers a unique technology which enables not only diverting biodegradable from landfill but also producing bio-energy and potential by-products such as a beneficial soil conditioner [80].

AD systems generally have four classifications [80]:

• Mesophilic (30 — 40 °C) or thermophilic (50 — 65 °C) according to temperature

• Wet digestion (< 15% dry solid) or dry digestion ( between 20% — 40% dry solid) according to the solid content in feedstock

• Single step (one vessel) or multiple step digestions (normally two-step digestion i. e. hydrolysis and methanogenesis)

• Batch digestion (loading feedstock in the beginning and remove products at the end of process) or continuous digestion (loading feedstock and withdraw products continuously)

Generally, five trophic groups are considered to be relevant to the process such as hydrolysing bacteria, acidogenic bacteria, acetogenic bacteria, aceticlastic and hydrogentrophic methanogens. They are involved in a series of digestion steps which are described as following and in Figure 7 [81] :

1. Carbohydrates, lipids, proteins etc. are broken down through hydrolysis to sugars, long — chain fatty acids and amino acids by extracellular enzymes released by hydrolytic bacteria;

2. Then these molecules are converted into volatile fatty acids, alcohols, CO2 and H2 in acidogenesis step;

3. These molecules are then further converted by acetogenic bacteria mainly into acetic acid, H2 and CO2;

4. Finally, all these intermediate products are turned into CH4, CO2 and water in the last step where methanogenic bacteria are involved. Three biochemical pathways are used by methanogens to produce methane gas:

a. Acetotrophic methanogenesis: 4 CH3COOH ->4 CO2 + 4 CH4

b. Hydrogenotrophic methanogenesis: CO2 + 4 H2-> CH4 + 2 H2O

c. Methylotrophic methanogenesis: 4 CH3OH + 6 H2 -> 3 CH4 + 2 H2O

Due to for different substances, biological consortia and digestion conditions, the overall biogas yield and methane content will vary. Typically, the methane content of biogas is in the range of 40-70 % (v/v) [82].

Several key factors influence the Ad performance. They include pH, temperature, organic loading rate (OLR), the ratio of inoculum to substance (I/S) and the presence of inhibitory substances. Generally, mesophilic AD (35 — 37 °C) is more preferred than thermophilic AD (50 — 60°C) since the latter one offers less methane yield and it is more sensitive to environment change [81]. The pH range suggested for AD process is in the range of 6.8 -7.2 [80]. In addition, anaerobic digestion requires attention to the loading of nutrients for bacteria including carbon and nitrogen. The proper ratio of these two components (C/N) depends on the digestibility of the carbon and nitrogen sources between 20: 1 and 30:1. Other nutrients such as S, Mg, K, P, Ca, Fe, Zn, Al, Ni, Co, Cu and vitamin B12 are necessary [80]. However, these components are generally contained in the Organic Fraction of MSW (OFMSW) while they are added in the laboratory scale AD systems.

Organic matters
Hydrolysis

Soluble organic molecules
Acidogenesis (fermentation)

Regarding the AD process operation, I/S ratio is considered as one the most important parameter. It is suggested to be approx 1 by Raposo et al.[83] who found that biogas production was inversely proportional to the I/S ratio in the range of 1 to 3. two stage AD is more preferred because it provides optimum environmental conditions for each bacteria group, offers accelerated digestion rates, better stability and thus increased methane yield [80]. Another process parameter is retention time which includes hydraulic retention time and solid retention time. The former refers to the mean time that any portion of liquid feed remains in a digestion system; the latter is defined as the mean time for any portion of solid feed or microbal biomass remains in the digester. These two retention times are the same in a single stage digester; while in a two stage digestion system the longer solid retention time is, the higher degradation rates and biogas yields are obtained [80]. In addition to the above process parameters discussed, the organics loading rate (OLR) is also critical which is measured as volatile solid (VS) or chemical oxygen demand (COD) of feed to a unit volume of digester per unit time [80]. The range for OLR is suggested in the range of 6 — 9.7 kg VS/day/m3 which is varied with the biodegradability of feedstock and AD systems [81].

Furthermore, the quality of OFMSW treated in biogas plants is also crucial for balanced performance of the biogas process, the technical feasibility of process and the use of residual/effluent as agricultural soil conditioner. Therefore, the costs associated with waste collection, sorting and pre-treatment should be considered [84].

Currently, most of MSW in the U. S. are sent to composting as an alternative to landfill. This is because it is more difficult to treat OFMSW than treating wastewater or manure. In addition, the AD of OFMSW requires a large amount of investment and technological experience as well as a higher capital and operating cost than compositing and landfilling [82]. The relatively low gate fees for landfill in the U. S. and relatively low energy prices make AD difficult to be commercialized in the U. S compared to those in Europe [82]. However, in the UK, there is currently very little waste treatment using AD apart from the use of AD to treat sewage sludge and wastewaters [85].

However, LCA studies have shown that AD of MSW reduces environmental impacts and is more cost — effective (in Europe) on a whole system basis than composting or landfilling options [86, 87].