Bioresource Technology 100 (2009) 2355–2360
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A multi-criteria ranking of different technologies for the anaerobic digestion for energy recovery of the organic fraction of municipal solid wastes A. Karagiannidis *, G. Perkoulidis Department of Mechanical Engineering, Aristotle University of Thessaloniki, Box 483, GR 54124, Thessaloniki, Greece
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Article history: Received 14 August 2008 Received in revised form 14 November 2008 Accepted 18 November 2008 Available online 31 December 2008 Keywords: Anaerobic digestion Municipal solid waste Organic fraction Multi-criteria ranking Electre III
a b s t r a c t This paper describes a conceptual framework and methodological tool developed for the evaluation of different anaerobic digestion technologies suitable for treating the organic fraction of municipal solid waste, by introducing the multi-criteria decision support method Electre III and demonstrating its related applicability via a test application. Several anaerobic digestion technologies have been proposed over the last years; when compared to biogas recovery from landfills, their advantage is the stability in biogas production and the stabilization of waste prior to final disposal. Anaerobic digestion technologies also show great adaptability to a broad spectrum of different input material beside the organic fraction of municipal solid waste (e.g. agricultural and animal wastes, sewage sludge) and can also be used in remote and isolated communities, either stand-alone or in conjunction to other renewable energy sources. Main driver for this work was the preliminary screening of such methods for potential application in Hellenic islands in the municipal solid waste management sector. Anaerobic digestion technologies follow different approaches to the anaerobic digestion process and also can include production of compost. In the presented multi-criteria analysis exercise, Electre III is implemented for comparing and ranking 5 selected alternative anaerobic digestion technologies. The results of a performed sensitivity analysis are then discussed. In conclusion, the performed multi-criteria approach was found to be a practical and feasible method for the integrated assessment and ranking of anaerobic digestion technologies by also considering different viewpoints and other uncertainties of the decision-making process. Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction Anaerobic digestion (AD) is a complex process in which anaerobic bacteria decompose organic matter under lack of oxygen. Many calculations and exercises in the EU and elsewhere have shown that the capture of and energy recovery from bio-methane may considerably contribute to Greenhouse Gases (GHG) emission reductions, in particular if used as a biofuel (e.g. Tilche and Galatola, 2008). Considering also energy crops that will become available in the next few years as a result of Common Agricultural Policy (CAP) reform, the potential for biogas production from the agricultural sector seems truly promising, whereas after considering the achievable GHG reductions, a very large carbon emission trading ‘‘value” could support the investment needs. There are a number of different techniques, which are usually distinguished on the basis of the operating temperature (i.e. thermophilic plants operate at around 55 °C (50–65 °C) and mesophilic ones at around 35 °C (20–45 °C)) and the percentage of dry matter in the feedstock (i.e. dry systems with 30–40% dry matter, wet systems with 10–25% dry matter). The higher the temperature, the faster the * Corresponding author. Tel.: +30 2310 996011; fax: +30 2310 996012. E-mail address:
[email protected] (A. Karagiannidis). 0960-8524/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2008.11.033
process, but the thermophilic process may be harder to control and will need more biogas for heating to keep them at the required temperature (EC, 2006, p. 48). AD of the Organic Fraction of Municipal Solid Waste (OFMSW) has received increased attention since the early 1990s, with the introduction of both commercial and pilot AD plant designs. Hessami et al. (1996) designed a low-cost reactor for the OFMSW based on traditional Indian and Chinese rural home-reactors, while Iglesias-Rodriguez et al. (1997) studied the pilot-scale AD of OFMSW, achieving a maximum concentration of 66% CH4 in the produced biogas. Callaghan et al. (1999) suggested co-digestion of OFMSW with animal manure, achieving mixed results, whereas Chugh et al. (1999) studied the AD of commingled MSW and showed that very fast digestion rates can be achieved with proper leachate circulation. Burtscher et al. (1998) proposed a methodology for tracing and eliminating pathogens during AD, with both mesophilic and thermophilic reactors showing positive results. Furthermore, Sawayama et al. (1998) studied the AD of OFMSW in an Upflow Anaerobic Sludge Blanket (UASB) reactor, showing better-than-combustion energy recovery. Rao et al. (2000) developed a mathematical model in order to predict the maximum biogas recovery from the OFMSW. Dalheimer et al. (1999) presented a multi-chamber anaerobic dry fermentation process for the
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biological pre-treatment of MSW, whereas Sharma et al. (2000) designed and constructed a reactor for the AD of semi-solid organic waste co-digested with sewage sludge. Schmit and Ellis (2001) made a comparison between temperature-phased and other state of the art processes for the AD of the OFMSW. Vandevivere et al. (2002) compared the most common types of anaerobic digesters and made a first distinction among one-stage, two-stage and batch systems. Giannopoulos et al. (2005) evaluated AD of the OFMSW as an alternative treatment method and presented a case study for a mesophilic, low-solids concentration AD plant for the Prefecture of Xanthi, Greece. Forster-Carneiro et al. (2007) studied the dry-thermophilic AD of the OFMSW focusing on inoculum sources. Finally, Fernandez et al. (2008) studied the influence of Total Solid (TS) contents during anaerobic mesophilic treatment of the OFMSW. Out of these papers and many others, the need for precise classification of AD processes and their operating limits and characteristics is evident, whereas a profound lack of validated financial data on the operation of commercial AD processes has also been often observed. The system of the Hellenic islands used here as background is such a profound case. In this context, a gap in standard and commonly accepted conceptual frameworks and methodological tools for the evaluation of different AD processes has also been determined. The present paper presents the initial application of such a newly developed conceptual framework and methodological tool for providing decision support in this field via evaluating and ranking selected AD technologies to treat the OFMSW of Hellenic islands, according to a set of suitable criteria through multi-criteria analysis. This tool was implemented as a software platform in a spreadsheet environment; it was used in this work as a preliminary technology screening and assessment tool for the subsequent analysis and has ever since been proven easily expandable to additional criteria and candidate alternative technologies; both these experiences will be reported separately in the near future.
2.
3.
4.
2. Methods AD encompasses a broad family of processes which can be classified according to (cf. i.a. Buekens, 2005; Giannopoulos et al., 2005): (a) their feedstock input mode into: batch and continuous processes; the later can be further classified into single-step and double- or (for certain feedstock) multiple step; (b) the geometry of the main treatment unit into: vertical and horizontal units. Various flow arrangements and mixing methods can be implemented in each case. All these categories can work under either mesophilic or thermophilic conditions; they can be further categorized (as already mentioned) according to the digester’s Dry Solids (DSs) w/w content into ‘‘wet” and ‘‘dry” fermentation technologies. Digesters are furthermore characterized as single and multi staged in accordance with the continual or daily feed of solids and liquids. If two tanks are used, the first tank features hydrolysis, acidogenesis and acetogenesis, while the second optimises methane forming conditions from volatile fatty acids. (Buekens, 2005; Verma, 2002). Several commercial AD plant designs have been developed over the years (cf. i.a. Deublein and Steinhauser, 2008). Five of these were selected for evaluation in the frame of this work following some related literature survey on relatively contemporary technologies. These processes are shortly presented below: 1. Waasa: a vertical digester, internally separated for the predigestion of the input material, is used in order to digest waste with 10–15% VS-content. Both temperature phases may be used, a biogas production of 100–150 m3/Mg (input material)
5.
may be achieved in two parallel reactors, whereas Hydraulic Retention Times (HRT) of 10–20 days have been reported (Williams et al., 2003). The process has been tested on a number of waste as mechanically or source-separated MSW, sewage sludge, slaughterhouse waste, fish waste and animal manure (Ahring, 2003). One characteristic of this process is its main reactor, which is divided into various zones in a simple way. The first zone is made up of a pre-chamber inside the main reactor. The mixing in the reactor is by pneumatic stirring, where biogas is performed pumped through the base of the reactor. A small part of the digestate is mixed into the newly fed bio waste to speed up the process by inoculation. Valorga: this process uses a vertical digester with biogas recirculation (internally, within the digester) and typically operates with a 25–32% VS-content and a HRT of 18–25 days. Produced biogas ranges between 80 and 160 m3/Mg (input material). This process was initially designed to treat OFMSW and was later adapted to treating mixed MSW (Verma, 2002; de Laclos et al., 1997). It was developed in France and is a semi-dry mesophilic process, which takes place in the following way: after pre-treatment, the waste is mixed with recycled process water (Ahring, 2003). Dranco: the Dry Anaerobic Composting (Dranco) process is a thermophilic (reported in the range of 50–58 °C), high-solids, single-stage technology with no biogas recirculation and a 15–40% VS-content. HRT in the vertical digester is typically 20 days, biogas production is between 100 and 200 m3/Mg (input material) and plant capacities 10,000–35,000 Mg/year have been reported (Verma, 2002). It is a pure dry-process for treatment of the OFMSW. Indeed, this process requires high TS content in the reactor in order to have optimal performance. Kompogas: this high VS-content digester with no gas recirculation is operated at a 15–20 days HRT; whereas a typical biogas rate of 100 m3/Mg of input material is reported (Wellinger et al., 1993). The Kompogas process is a dry-process developed in Switzerland and operates in the thermophilic range (Ahring, 2003). The reactor is a horizontal cylinder and the flow through the reactor is a plug flow. In the reactor, a stirrer provides some mixing of the waste. Recirculation of a part of the effluent to the incoming substrate ensures inoculation. BTA: this is a multi-stage, low-solids system for treating either mixed MSW or source-separated OFMSW. BTA combines waste pre-treatment and separation stages in a fully enclosed and reportedly highly automated facility, whose capacity may be between 2000 and 150,000 Mg/year (Verma, 2002; Rahn and Gandolfi, 2007). It is a wet AD process, which was conceived in 1984 and consists of wet-mechanical pre-treatment and biological conversion of organics by use of AD (Blischke, 2004).
For the ranking of the above examined processes, four criteria were used: (a) GHG emissions, (b) energy recovered, (c) material recovered and (d) operating cost (Fig. 1). It was decided to use multiple criteria in an attempt to encompass different points of view explicitly and quantitatively into the decision-making process especially for the particular case study area for the results of the presented analysis, namely the Hellenic islands where very controversial interests, conflicting view points and particular constraints exist in their MSW management (as well as energy) sector and the challenges that it currently faces (Papadopoulos and Karagiannidis, 2008). AD was recognised as a favourable solution for such insular systems, as also confirmed by other studies in both developed and developing countries (Karagiannidis et al., 2008) and this paper presents next the results of the preliminary technology screening and ranking. It was evident to the analysts that different or additional criteria could also have been used, but the above were
A. Karagiannidis, G. Perkoulidis / Bioresource Technology 100 (2009) 2355–2360
Fig. 1. Operating cost of each process, where the collection cost of MSW is not included.
retained in this work in an attempt to encompass different aspects of recovery, economics and environment resource. The performances of the above five AD processes for the OFMSW on each of the above criteria were calculated for a standard plant capacity of 20,000 Mg (input material)/year, by means of a pre-compiled validated knowledge base (Karidas and Karpenisioti, 2002; Blischke, 2004; Fernandez et al., 2008), which was incorporated in the developed spreadsheet; they are given in Table 1. The MSW collection cost was not included in the operating cost at this stage. The amount of produced compost referred to the recovered material. The energy recovery was calculated by the total energy content (kWh/Mg) of each processes calculated produced biogas assuming its conversion to electricity and thermal energy in internal combustion engines coupled to combined heat and power units (Nichols, 2004). The Electre III method used next belongs to the Electre class of multi-criteria methods, which compare possible actions (in the present case: the 5 selected processes) according to their performance in different criteria (Roy, 1996; Dias and Climaco, 2002; EEA, 2003). The here presented decision model was therefore formulated as a discrete problem, since the possible alternatives are a priori set and not to be determined via the optimization of some objective function. The several possibilities to resolve inconsistency by Electre method have also been reviewed (Mousseau et al., 2003). Electre is used by researches in methods and appli-
Table 1 Performances of the 5 processes for each of the four criteria. Process
Waasa Valorga Dranco Kompogas BTA
Criteria GHG emited (kg CO2-eq/Mg)
Recovered energy (kWh/ Mg)
Recovered materials (kg/ Mg)
Operating cost (€/Mg)
216 228 226 208 212
730 700 760 585 700
300 320 260 250 280
90 68 62 63 95
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cations in engineering and infrastructure investment, in environmental assessment, to option choice-problems within environmental appraisal and for choosing the best alternative MSW management system (Rogers and Bruen, 2000; Hokkanen and Salminen, 1997). As far as the integrated management of MSW is concerned, Electre was used for the final election of various scenarios for transferring, treating and final disposing the MSW (Karagiannidis and Moussiopoulos, 1997; Perkoulidis et al., 1999; Perkoulidis et al., 2000; Karagiannidis et al., 2003). Karagiannidis and Moussiopoulos (1997) present an application of multi-criterial aid for decisions in the area of MSW management in Greece, in the context of a case study for household wastes in the Greater Athens Area. It should be noted that the importance of multicriteria analysis and especially the implementation of Electre for solving problems concerning cleaner products and processes and life cycle assessment towards sustainability are taken into account by many researches (Petrie et al., 2000; Aeolos, 2002). Finally, as a non trade-off method (cf. 4.2) Electre III has been very often used in strategic, decision-making problems (Roy, 1996; Norese, 2006; Mroz, 2008; Papadopoulos and Karagiannidis, 2008). As far as the mathematical settings are concerned, any discrete multiple criteria decision-making problem is usually formulated by a set of alternatives A = (x1, x2,..., xn) and a set (f1, f2,..., fk) of criteria. The criteria are real-valued functions defined on the set A so that fl(xj) represents the performance of the alternative xj on the criterion fl. From the point of view of a decision maker, uncertainty of the data can also be dealt with in an easy and practical way by applying the so-called pseudo-criterion, which is a preference model including two different thresholds: a preference threshold pl(fl(xj)) and an indifference threshold ql(fl(xj)) for each criterion fl (l = 1,..., k). These thresholds may be constants, linear or affine functions of fl(xj) in the form
pl ðfl ðxj ÞÞ ¼ ap;l þ bp;l fl ðxj Þ and ql ðfl ðxj ÞÞ ¼ aq;l þ bq;l fl ðxj Þ For every criterion fl, the double threshold model is the following: It is valid that xi is preferred to xj if fl(xi) > fl(xi) + pl(fl(xj)) xi is weakly preferred to xj if fl(xj) + ql(fl(xj)) < fl(xj) 6 j fl(x ) + pl(fl(xj)), and xi is indifferent to xj if fl(xj) + ql(fl(xj)) P fl(xi) and fl(xj) + ql(fl(xj)) P fl(xj) where pl(fl(xj)) and ql(fl(xj)) are preference and indifference thresholds, respectively and pl(fl(xj)) > ql(fl(xj)) > 0. Weak preference is supposed to describe the hesitation between indifference and preference. Electre III is a typical and sophisticated method using pseudocriteria and taking the risk to a certain extent to establish outranking relations which can incorporate both criteria error and uncertainties, as well as risk aspects attitudes or sensitivities of decisionmakers; the later were assessed by the authors to be especially important in the field of MSW management in Hellenic islands and this was an additional important reason for the selection of this particular MCDA method. In Electre III, an outranking degree S(xi, xj) is used which describes the outranking credibility of xi over xj taking its values between 0 and 1 (Miettinen and Salminen, 1999). The value of S(xi, xj) is defined based on the so-called concordance and discordance indices. A concordance index C(xi, xj) is computed for each pair of alternatives (xi, xj) by
Cðxi ; xj Þ ¼
k X
wl cl ðxi ; xj Þ
l¼1
where the weighting coefficients wl sum up to one, and
ð1Þ
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A. Karagiannidis, G. Perkoulidis / Bioresource Technology 100 (2009) 2355–2360 Table 4 Concordance matrix in the case of giving 50% weight to the criterion ‘GHG emitted’ and 50% weight to the ‘Recovered energy’ and 0% weight to the ‘Recovered materials’ and 0% weight to the ‘Operating cost’.
Waasa Valorga Dranco Kompogas BTA
Fig. 2. Frequency distribution of each process’ ranking (position 1: best; position 5: worst) for the 10 weight combinations used in the sensitivity analysis.
Table 2 Frequency distribution of each process’ ranking (position 1: best; position 5: worst) for the 10 weight combinations used in the sensitivity analysis. The sums of 1st and 2nd position ranking are given in the 3rd column. Process
1st (%)
2nd (%)
1st and 2nd (%)
3rd (%)
4th (%)
5th (%)
Waasa Valorga Dranco Kompogas BTA
23 23 31 8 15
27 18 27 27 0
50 41 58 35 15
18 27 9 9 36
14 14 14 43 14
0 0 0 33 67
8 > 1 if f l ðxj Þ þ ql ðfl ðxj ÞÞ P fl ðxj Þ; > < i i j cl ðxi ; xj Þ ¼ 0 if f l ðx Þ þ pl ðfl ðx ÞÞ 6 fl ðx Þ; > j i > l ðx Þfl ðx ÞÞ : pl ðfl ðxi Þðf ; otherwise p ðf ðxi Þq ðf ðxi ÞÞ l l
l
ð2Þ
l
3. Results and discussion A conceptual framework and methodological tool for the evaluation of different AD technologies was presented at this paper for 5 selected commercial processes. The final ranking of processes was performed by means of selected criteria, which addressed both targets of current waste management trends (energy and material recovery) as well as global environmental indicators (CO2 emissions).
Waasa
Valorga
Dranco
Kompogas
BTA
1 2 105 0.5 0.5 0.5
1 1 1 0.5 1
0.5 1 105 1 0.5 0.5
0.5 0.5 0.5 1 0.5
0.5 0.5 0.5 0.5 1
Due to the recently declared attitudes from private sector concerning the construction of an AD facility, aim of the paper was to implement the Electre III Multi-Criteria Decision-Making (MCDA) method for performing then the sensitivity analysis, which gave the ranking results, in order to consider different preferences of various possible decision makers towards the four used criteria. These were operationalised by using different combinations of criteria weights, aiming to illustrate sensitivity of the ranking results towards potentially different priorities as expressed by different decision makers. For this particular test case, Dranco process was ranked in the best position at 31% of all cases, whereas the method most frequently ranked in the 2nd best position were, Dranco, Kompogas and Waasa (27%). In the 1st best position, Dranco was followed by Valorga and Waasa, which achieved the same percentiles of 1st position ranking (cf. Fig. 2 and Tables 2 and 3). After looking back at Table 1, Dranco combines the relative advantages of lowcost and high energy recovery, which seem to have contributed at 58% of all its rankings being either in the best (1st-cf. above) or 2nd best position, followed by (cf. Tables 2 and 3) Wassa (50%), Valorga (41%), Kompogas (35%), and BTA (15%). BTA’s high cost seems to be critical in limiting its ranking at the worst position in this analysis. It was observed that in the case of giving 50% weight to the criteria ‘GHG emitted’ and ‘Recovered energy’ and 0% weight to the ‘Recovered materials’ and ‘Operating cost’, Dranco, Waasa and BTA were ranked in the 1st best position (Table 3). In this case, the descending distillation ranking of Electre III was used. Descending distillation selected at first the best process to end to worst one, i.e. Waasa, Dranco and BTA to Valorga and Kompogas. Furthermore, the calculated concordance matrix of Electre III displayed all the comprehensive concordance indices for every pair of 5 processes (Table 4). It was also observed that Dranco’s performance was greater or equal to Valorga’s performance [=1, Eqs. (1) and (2)], while Dranco was weakly preferred to Waasa [=0.5, Eqs. (1) and (2)]. The concordance index showed that Dranco was not strictly preferred to any other process cl (xi, xj) – 0. Finally, the 5 processes were incomparable to each other as it was given by the ranking matrix with the above-mentioned criteria’s weights (Table 5).
Table 3 Calculated rankings of processes in accordance with the 50%-step applied on all 4-criteria weights (B: BTA, D: Dranco, K: Kompogas, V: Valorga, and W: Waasa). Criterion weight GHG emitted (%)
Recovered energy (%)
Recovered materials (%)
Operating cost (%)
100 0 0 0 50 0 0 50 50 0
0 100 0 0 50 50 0 0 0 50
0 0 100 0 0 50 50 0 50 0
0 0 0 100 0 0 50 50 0 50
Sum (%)
1st
2nd
3rd
4th
5th
100 100 100 100 100 100 100 100 100 100
K D V D B, D, W V, W V K B, W D
B W W K K D D D K, V V, W
W B, V B V V B W B, W D K
D K D W – K K V – B
V – K B – B – –
A. Karagiannidis, G. Perkoulidis / Bioresource Technology 100 (2009) 2355–2360 Table 5 Ranking matrix of processes (P: if process xi is better than process xj, I: if process xi is equivalent to process xj, P: if process xi is as good as to process xj, R: if process xi is incomparable to process xj).
Waasa Valorga Dranco Kompogas BTA
Waasa
Valorga
Dranco
Kompogas
BTA
I P I P I
P I P P P
I P I P I
P P P I P
I P I P I
The developed information from the sensitivity analysis could be used to help decision-making about private sector investment in an AD typology selection. Of course, the sensitivity of the results depends heavily on the input data from Table 1 and any further developments in the characteristics of these (or other competitive) methods could significantly affect future ranking. Despite that, the interest private or (or even public/social) sector may apply the proposed MCDA and sensitivity analysis methodology to help assess the selection of an AD technology. 4. Conclusions A conceptual framework and methodological tool for the evaluation of different AD technologies was presented for 5 selected commercial processes, where the final ranking of processes was performed by means of energy and material recovery, as well as global environmental indicators. Current energy prices and targeted reduction of fossil fuel combustion will draw increasingly more attention towards anaerobic digestion, together with the ever increasing pressure to landfill less organic materials. Future research should take into account non-linear functions for the calculation of criteria performances, as well as more direct interaction with decision-makers. References AEOLOS, 2002. An End-of-Life of Product Systems. EVEN – European Virtual Engineering Network. Project funded by the European Community under the Competitive and Sustainable Growth Programme (1998–2002). Project No. GTC2-2001-33012. Ahring, B.K., 2003. Biomethanation II. In: Scheper, T. (Ed.), Advances in Biochemical Engineering/Biotechnology, vol. 82. Springer, Berlin, p. 220. Blischke, J., 2004. Combining anaerobic digestion with enclosed tunnel composting. BioCycle 45 (4), 49. Buekens, A., 2005. Energy Recovery from Residual Waste by means of Anaerobic Digestion Technologies. Conference ‘‘The Future of Residual Waste Management in Europe”, 17–18 November, Luxemburg. Burtscher, C., Fall, P.A., Wilderer, P.A., Christ, O., Wuertz, S., 1998. Detection and survival of pathogens during two-stage thermophilic/mesophilic anaerobic digestion of suspended organic waste. Water Science Technology 38 (12), 123– 126. Callaghan, F.J., Wase, D.A.J., Thayanithy, K., Forster, C.F., 1999. Co-digestion of waste organic solids: batch studies. Bioresource Technology 67 (2), 117–122. Chugh, S., Chynoweth, D.P., Clarke, W., 1999. Degradation of unsorted municipal solid waste by a leach-bed process. Bioresource Technology 69 (2), 103–115. Dalheimer, F., Heerenklage, J., Stegmann, R., 1999. A multichamber anaerobic dry fermentation plant for the pretreatment of RMSW. In: Cossu, Christensen, Stegmann (Hrsg.): Proceedings of Sardinia ‘99, International Symposium on Sardinia, Cagliari, I, 1999, 443–446. Deublein, D., Steinhauser, A., 2008. Biogas from Waste and Renewable Sources – An Introduction, Wiley-VCH, p. 443. Dias, L., Climaco, J., 2002. Exploring the consequences of imprecise information in choice problems using Electre. In: Bouyssou, D., Jacquet-Lagreze, E., Perny, P., Slowinski, R., Vanderpooten, D., Vincke, Ph. (Eds.), Aiding Decisions with Multiple Criteria (essays in honor of Bernard Roy). Kluwer, pp. 175–193. EC, 2006. Reference Document on Best Available Techniques for the Waste Treatments Industries. Integrated Pollution Prevention and Control, August. EEA, 2003. Assessment of information related to waste and material flows, a catalogue of methods and tools. Technical Report 96, European Environment Agency, Project Manager, Dimitrios Tsotsos, European Topic Centre on Waste and Material Flows, Copenhagen, Denmark.
2359
Fernandez, J., Perez, M., Romero, L.I., 2008. Effect of substrate concentration on dry mesophilic anaerobic digestion of organic fraction of municipal solid waste (OFMSW). Bioresource Technology 99, 6075–6080. Forster-Carneiro, T., Perez, M., Romero, L.I., Sales, D., 2007. Dry-thermophilic anaerobic digestion of organic fraction of the municipal solid waste: focusing on the inoculum sources. Bioresource Technology 98, 3195–3203. Giannopoulos, D., Voudrias, E., Aivazidis, A., 2005. Anaerobic treatment of municipal solid waste: evolution and perspectives. In: Technical Chamber of Greece (Eds.), Electronic Proceedings in CD-ROM. Paper Nr O-C 250 (in Greek). HELECO 2005, 3–6 February, Athens/Greece. Hessami, M.A., Christensen, S., Gani, R., 1996. Anaerobic digestion of household organic waste to produce biogas. Renewable Energy 9 (1–4), 954– 957. Hokkanen, J., Salminen, P., 1997. Choosing a solid waste management system using multi criteria decision analysis. European Journal of Operational Research 98, 19–36. Iglesias-Rodriguez, J., Castrillon, L., Maranon, E., Sastre, H., 1997. Solid-state Anaerobic Digestion of Unsorted Municipal Solid Waste in a Pilot-plant Scale Digester. University of Oviedo, Spain. Karagiannidis, F., Moussiopoulos, N., 1997. Application of Electre III for the integrated management of municipal solid wastes in the greater Athens area. European Journal of Operational Research, 439–449. Karagiannidis, A., Perkoulidis, G., Moussiopoulos, N., Chrysochoou, M., 2003. Facility location for solid waste management through compilation and multicriterial ranking of optimal decentralised scenarios: a case study for the region of Peloponesse in southern Greece. Engineering Research 1, 7–18. Karagiannidis, A., Wittmaier, M., Langer, S., Bilitewski, B., Malamakis, A., 2008. Thermal processing of waste organic substrates: developing and applying an integrated framework for feasibility assessment in developing countries. In: Proceedings Venice 2008 Biomass and Waste to Energy Symposium, November 17–20, Venice, Italy. Karidas, A., Karpenisioti, K., 2002. System development for energy recovery perspectives evolution from organic waste. Diploma Thesis. Laboratory of Heat Transfer and Environmental Engineering. Department of Mechanical Engineering. Aristotle University of Thessaloniki (in Greek). de Laclos, H.F., Desbois, S., Saint-Joly, C., 1997. Anaerobic digestion of municipal solid organic waste: valorga full-scale plant in Tilburg, The Netherlands. Water Science and Technology 36 (6–7), 457–462. Miettinen, K., Salminen, P., 1999. Decision-aid for discrete multiple criteria decision making problems with imprecise data. European Journal of Operational Research 119, 50–60. Mousseau, V., Figueira, J., Dias, L., Gomes da Silva, C., Climaco, J., 2003. Resolving inconsistencies among constraints on the parameters of an MCDA model. European Journal of Operational Research 147, 72–93. Mroz, T., 2008. Planning of community heating systems modernization and development. Applied Thermal Engineering 28, 1844–1852. Nichols, C.E., 2004. Overview of anaerobic digestion technologies in Europe. BioCycle 45 (1), 47. Norese, M.F., 2006. Electre III as a support for participatory decision-making on the localisation of waste-treatment plants. Land Use Policy 23, 76–85. Papadopoulos, A., Karagiannidis, A., 2008. Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems. Omega 36, 766–776. Perkoulidis, G., Karagiannidis, A., Moussiopoulos, N., 1999. Investigation of the prospects of thermal treatment of urban solid waste by a location-allocation model and multicriteria analysis in the region of Eastern Macedonia and Thrace. In: Tsiligiridis, G. (Ed.), Proceedings of the 6th National Conference on Renewable Energy Sources (IST 99). Institute of Solar Technology Thessaloniki, Greece, 3–5 November, vol. 1, Volos, Greece, pp. 539–547 (in Greek). Perkoulidis, G., Karagiannidis, A., Moussiopoulos, N., 2000. Investigation of interprefectural collaboration schemes for municipal solid waste management. In: Tsihrintzis, V.A., et al. (Eds.), Proceedings of the 5th Conference on Protection and Restoration of the Environment, 3–6 July, vol. 2, Thassos, Greece, pp. 827– 834. Petrie, J., Stewart, M., Basson, L., Notten, P., Brett, A., 2000. Structured Approaches to Decision Making for Cleaner Products and Processes, Use of Life Cycle Assessment in Effective Environmental Decision Making, CRESTA–Centre for Risk, Environment and Systems Technology and Analysis, Department of Chemical Engineering. University of Sydney, Sydney, NSW. Rahn, T., Gandolfi, P.B., 2007. Modification and Optimisation of Existing MBT Plants using BTA Technology. 2nd International Symposium MBT, Hanover, Germany, May, 177–186. Rao, M.S., Singh, S.P., Singh, A.K., Sodha, M.S., 2000. Bioenergy conversion studies of the organic fraction of MSW: assessment of ultimate bioenergy production potential of municipal garbage. Applied Energy 66 (1), 75–87. Rogers, M., Bruen, M., 2000. Using Electre III to choose the best route option for the Dublin Port Motorway, proceedings of the ASCE. Journal of Transportation Engineering 126 (4), 313–323. Roy, B., 1996. Multicriteria Methodology for Decision Aiding. Kluwer, Dordrecht. Sawayama, S., Inoue, S., Tsukahara, K., Minowa, T., Ogi, T., 1998. Anaerobic treatment of liquidized organic wastes. Renewable Energy 16, 1094– 1097. Schmit, K.H., Ellis, T.G., 2001. Comparison of temperature-phased and 2-phase anaerobic co-digestion of primary sludge and MSW. Water Environment Research 73, 314–321.
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A. Karagiannidis, G. Perkoulidis / Bioresource Technology 100 (2009) 2355–2360
Sharma, V.K., Testa, C., Lastella, G., Cornacchia, G., Comparato, M.P., 2000. Inclinedplug-flow type reactor for anaerobic digestion of semi-solid waste. Applied Energy 65 (1–4), 173–185. Tilche, A., Galatola, M., 2008. The potential of bio-methane as bio-fuel/bio-energy for reducing greenhouse gas emissions: a qualitative assessment for Europe in a life cycle perspective. Water Science and Technology 57, 1683–1692. Vandevivere, P., de Baere, L., Verstraete, W., 2002. Types of anaerobic digester for solid wastes. In: Mata-Alvarez (Ed.), Biomethanization of the Organic Fraction of Municipal Solid Wastes. IWA Publishing Company, pp. 111–140.
Verma, Sh., 2002. Anaerobic Digestion of Biodegradable Organics in Municipal Solid Wastes, Department of Earth and Environmental Engineering, Fu Foundation School of Engineering and Applied Science, Columbia University. Wellinger, A., Wyder, K., Metzler, A.E., 1993. Kompogas - a new system for the anaerobic treatment of source separated waste. Water Science and Technology 27 (2), 153–158. Williams, R.B., Jenkins, B.M., Nguyen, D., 2003. Solid Waste Conversion: A Review and Database of Current and Emerging Technologies. Final Report. Department of Biological and Agricultural Engineering. University of California, Davis.
