Selection of an appropriate waste-to-energy conversion technology for Dhaka City, Bangladesh

Abstract

Solid waste disposal poses a significant problem, as it leads to land pollution if openly dumped, water pollution if dumped in low lands and air pollution if burnt. Moreover, the scarcity of land and increase in land prices especially in Dhaka, the capital city of Bangladesh create the problems of developing new landfill sites. Realising the existing and future impacts of waste disposal issues, the analytic hierarchy process model was applied to select an appropriate Waste-to-Energy (WTE) conversion technology for household waste of Dhaka-Mirpur Cantonment area. Three alternatives, namely, anaerobic digestion, pyrolysis and plasma gasification (PG) technologies and nine criteria under three aspects (technological, environmental and financial) were chosen for comparison. The analysis revealed that PG is the most appropriate WTE conversion technology in the study area. The selected PG technology has a relatively small footprint; it can treat unsorted waste and can produce good-quality synthetic gas without generating extremely toxic by-products.

Keywords:

• Solid waste
• waste to energy
• analytic hierarchy process
• plasma gasification

1. Introduction

Waste Management is one of the challenging tasks for city authorities in many developing countries including Bangladesh due to increase in the generation of waste and the high costs associated for its management (Guerrero, Maas, and Hogland 2013). According to Burntley (2007), the municipal authority in developing countries faces several problems including lack of organisation, financial resources, complexity and system multi-dimensionality for waste management. Several factors including urbanisation, inequality, economic growth, cultural and socio-economic aspects, policy, governance, institutional issue and international influences usually effect the performances of solid waste management in developing countries (Marshall and Farahbakhsh 2013). Based on research outcomes of UNFPA, Dhaka, the capital city of Bangladesh is one of the most polluted cities in the world and management of municipal waste is one of the major concerned issues for the city (Bhuiya 2007). The average waste generation per person per day in Dhaka City is about 0.56 kg which has an average calorific value of 550–850 kcal/kg (JICA 2005). This quantity is expected to increase due to rapid economic and population growth, especially in urban areas. On the other hand, only about 42% of generated waste is collected and dumped at landfill sites in Dhaka City and the rest are left uncollected. As a result, this improperly disposed waste poses serious health implications to the people where it may have the potential of transmitting diseases (Ahmed and Zerin 2009). In parallel, the demand for electricity in Bangladesh far exceeds the domestic supply. The ‘vision 21’ by the Government of Bangladesh has a mission to provide electricity to all by the year 2021 (Ahammed and Azeem 2013). But, only 42% of the population has access to national grid electricity (Ahammed and Azeem 2013) and per capita electricity consumption is around 150 KW (as of 2008), which is one of the lowest in Asian Region (Ahamad and Islam 2011). The electricity generation of the country has been overly dependent on natural gas. Wastes became one of the renewable resources that could play a major role in renewable energy (Nzihou 2010). Various thermal processes such as combustion, pyrolysis or gasification have been developed for treating these wastes in the aim to recover energy from the organic fraction (Zhang, Xu, and Champagne 2010).

Different categories of waste conversion technologies are designed to handle different types of waste feedstock. In general, pyrolysis technologies utilise only plastics, gasification technologies utilise municipal solid waste (MSW) and anaerobic digestion (AD) utilises food, yard and paper waste (Manaf, Basri, and Basri 2008). Selection of an appropriate waste conversion technology can be complicated due to the intrinsic trade-off between socio-political, environmental, ecological and economic factors. Substantial research in the area of Multi Criteria Decision Analysis (MCDA) brought attainable practical methods for applying scientific approaches to handle complex multi-criteria problems. Analytic hierarchy process (AHP) is one of the MCDA techniques which is widely used in environmental decision-making issues (Ahammed and Azeem 2013).

The leading advantage of AHP method is that it can manage a complex problem by preparing a hierarchy of choices explaining the reasons of such choices through decomposing and synthesis (Kangas 1993; Triantaphyllou and Mann 1995). It compares different alternatives and attributes using a scale of relative importance (Belton and Gear 1983). Existing literature suggests several applications of AHP model for waste management. Aragones-Beltran, Pastor-Ferrando, and Garcia-garcia (2010) applied AHP to select the optimal location of municipal waste plant among six alternative plant sites using twenty-one criteria in Valencia, Spain. Parekh et al. (2015) demonstrated the applications of AHP to assign weightage for 44 indicators of solid waste management in Gujarat, India. Shahabi et al. (2014) mentioned that AHP is a better decision-making tool for locating land fill sites of solid waste management in Iran. However, the existing literature suggests that the application of AHP model for selecting Waste-to-Energy (WTE) conversion technology in Bangladesh is very rare (possibly, unavailable) and the authors believe that this is probably the first work of its kind.

This study area covers the jurisdiction of the Cantonment Board of Dhaka (CBD), which totals about 20 km² and includes Baridhara DOHS, Banani DOHS, Mohakhali DOHS, Dhaka Cantonment, Mirpur DOHS and Mirpur Cantonment. The area also covers Kachukhet Bazar and all other private residential areas within CBD. This study covers two types of solid wastes generated in the jurisdiction of the CBD: namely, domestic and medical waste. Liquid and gaseous wastes are not included within the scope of this study. We considered three alternatives and nine criteria to select the most appropriate WTE technology for the study area. We provided weights and prepared priority matrix for three alternatives using the AHP model.

2. Materials and methods

2.1. Selection of technologies

We performed Energy System Analysis (ESA) and Life Cycle Analysis (LCA) and selected the following three technologies to produce electricity from waste:

(i)	Anaerobic Digestion,
(ii)	Pyrolysis and,
(iii)	Plasma Gasification.

The key features of the selected WTE technologies are given below (Malkow 2004; Appels, Baeyens, and Dewil 2008; Hlina et al. 2014):

2.1.1. Anaerobic digestion

•	Well-known technology for domestic sewage and organic wastes treatment, but not for unsorted MSW.
•	Biological conversion of biodegradable organic materials in the absence of oxygen at temperatures 55–75 °C (thermophilic digestion – most effective temperature range).
•	Residue is stabilised organic matter that can be used as soil amendment after proper dewatering.
•	Digestion is used primarily to reduce quantity of sludge for disposal / reuse.
•	Methane gas generated is used for electricity – energy production.

2.1.2. Pyrolysis

•	Thermal degradation of organic materials is occurred through the uses of indirect, external sources of heat.
•	Temperatures between 300 and 850 °C are maintained for several seconds in the absence of oxygen.
•	Products are char, oil and syngas composed primarily of O2, CO, CO2, CH4 and complex hydrocarbons.
•	Syngas can be utilised for energy production or proportions can be condensed to produce oils and waxes.
•	Syngas typically has net calorific value (NCV) of 10–20 MJ/Nm.

2.1.3. Plasma Gasification

•	Use of electricity passed through graphite or carbon electrodes, with steam and/or oxygen – air injection to produce electrically conducting gas (plasma).
•	Temperature is above 3000 °C.
•	Organic materials are converted to syngas composed of H2 and CO.
•	Inorganic materials are converted to solid slag.
•	Syngas can be utilised for energy production or proportions can be condensed to produce oils and waxes.

2.2. Decision criteria

We considered three decision criteria (technology, environment and financial) and nine sub-criteria (technological maturity, reliability, energy potential, land area requirement, air-water pollution, requirement of waste separation, plant establishment cost, operation and maintenance cost and revenue earn) to select the most appropriate WTE conversion technology. The description of the selected sub-criteria is shown in Table 1.

Table 1. Description of sub-criteria.

Criteria	Sub-criteria	Description
Technology	Technological maturity	It means the development status of the technology i.e. whether the technology is in the research state or in commercial use state. More mature technology is preferred
	Reliability	It refers to success rate and the frequency of using the technology. More reliable technology is preferred
	Energy potential	Maximum possible generation of energy from waste is preferred
Environment	Land area requirement	Scarcity of land is one of the prime concerns. Minimum land requirement is preferred
	Air and water pollution	The selected WTE technology should provide minimum potential hazard to the environment. Minimum air and water pollution is preferred
	Requirement of waste separation	Separation of waste at source is one of the challenging tasks; hence, minimum requirement of waste separation is preferred
Financial	Plant establishment cost	Minimum plant establishment cost is preferred
	Operation and maintenance cost	Minimum operation and maintenance cost is preferred
	Revenue earn	Maximum possibility of revenue earn is preferred

2.3. Applying AHP model

Several multi-criteria decision analysis techniques have been proposed in the existing literature, such as, AHP, fuzzy AHP, Weighted Product Model, Additive Weighting Model, Computational Neural Network, Artificial Neural Network and the AHP model is the most popular one. The papers published by Ahammed and Azeem (2013) and Ahammed, Hewa, and Argue (2012) describe the workout procedures of the AHP model. The summary of applying AHP model is shown in Figure 1, while Figure 2 shows the hierarchy structure of WTE technologies. It starts with setting the goal followed by selection of alternatives. Practical judgement is necessary for criteria selection. Pairwise comparisons are required in two stages: (i) among criteria and (ii) among alternatives using each criterion.

Figure 1. Steps for applying AHP model.

Figure 2. Hierarchy structure of WTE technologies.

2.4. Pair-wise comparisons of alternatives

In AHP, preferences between two alternatives were determined by making pair-wise comparisons using each criterion. These comparisons were made using Saaty’s discrete 9 value scale (Table 2). Comparisons of alternatives were evaluated by four experts in Bangladesh.

Table 2. Saaty’s discrete 9 value scale of relative importance.

Numerical value (i)	Definition
1	Equal importance
3	Moderate importance
5	Strong importance
7	Very strong importance
9	Absolute importance
2,4,6,8	Intermediate values between two adjoining judgements
1/i	Inverse importance

A hypothetical comparison of three alternatives A₁, A₂ and A₃ using single criterion C₁ is shown in Table 3.

Table 3. A hypothetical comparison table.

	A1	A2	A3
A1	1	p	q
A2	1/p	1	r
A3	1/q	1/r	1

Table 3 can be transferred into n × n pair-wise comparison matrix, A_w.

The relative weights of A₁, A₂ and A₃ can be determined from matrix A by normalising it into a new matrix (say, N_w). This process requires dividing the elements of each column by the sum of the elements of the same column. The desired relative weights of three alternatives are then computed as row average of the new matrix.

2.5. Consistency check

The columns of A are identical, means the decision-maker exhibits perfect consistency in specifying the entries of the comparison matrix A. Mathematically, the matrix A is consistence if

It is logical that all comparisons may not be consistence. A reasonable level of inconsistency is expected and tolerated due to the nature of human judgement. To determine whether or not, the level of inconsistency is ‘reasonable’, Saaty (1980) developed a methodology as:

•	Estimate the Consistency Index (CI) using Equation 1(1) .

(1)

Here, n is the size of matrix (n × n) and λ_max can be defined as the product of A_w and N_w.

•	Consistency Ratio (CR) can be estimated using Equation 2(2) . As a rule of thumb, if CR value is equal or less than 0.10, the pair-wise comparison results are accepted; otherwise, these should be rejected and revised.

(2)

The Random Consistency (RC) of the Matrix A can be estimated using Table 4.

Table 4. The Random Consistency (RC) for various matrix size (n).

n	1	2	3	4	5	6	7	8	9
RC	0.00	0.00	0.58	0.90	1.12	1.24	1.32	1.41	1.45

2.6. Ranking of alternatives

The final step of the AHP application starts giving the weights of alternatives. It can be executed by multiplying the alternative decision matrix with criteria judgement matrix as:

where A, B, C are the three possible alternatives and x, y, z are three selection criteria.

3. Results and discussions

Table 5 shows the relative weights of criteria and ranks of WTE technologies using different criteria. It was noticed from Table 5 that technical feature (percentage priority 52%) was the most important attribute followed by the financial aspect (32%). The least important attribute was environmental aspect (16%). Reliability (55%), requirement of waste separation (51%) and plant establishment cost (54%) were the most important criteria for technical, environmental and financial attributes, respectively.

Table 5. Relative weights of criteria and ranks of WTE alternatives.

		Weight of criteria		Ranks of WTE technologies
Attribute	Criteria	Level one	Level two	Anaerobic digestion (AD)	Pyrolysis	Plasma gasification (PG)
Technical aspect		0.52		0.25	0.26	0.49
	Technological maturity		0.17	0.77	0.13	0.10
	Reliability		0.55	0.16	0.28	0.56
	Energy potential		0.28	0.10	0.31	0.59
Environmental aspect		0.16		0.21	0.31	0.47
	Land area requirement		0.32	0.11	0.31	0.57
	Air and water pollution		0.17	0.57	0.28	0.15
	Requirement of waste separation		0.51	0.16	0.32	0.52
Financial aspect		0.32		0.45	0.24	0.34
	Plant establishment cost		0.54	0.73	0.19	0.12
	Operation and maintenance cost		0.17	0.15	0.28	0.57
	Revenue earn		0.29	0.10	0.30	0.6

The final WTE decision matrix D and final criteria judgement matrix J were identified from Table 5 and overall ranking of WTE technologies was determined as a product of D and J.

It was noticed from Table 5 that, considering technical and environmental criteria, PG technology is the most preferred option (percentage priorities were 49 and 47% respectively); financial criteria indicated that anaerobic digestion was the most preferred option (45% percentage priority). Considering all criteria at a time, PG (47%) followed by AD (29%) was the most preferred WTE technology for Dhaka City. Figure 3 shows the ranking of WTE technologies for the production of electricity in Bangladesh.

Figure 3. (a) Rankings of WTE technologies using different criteria, (b) Overall ranking of WTE technologies.

3. Conclusions

The municipal solid waste is a never lasting source. It is increasing day by day in developing countries including Bangladesh and hence, it is considered as a source of renewable energy. WTE has been worldwide accepted and its popularity as renewable energy is increasing at a very first rate. No such WTE plant has yet been established in Bangladesh. PG is one of the promising WTE technologies with potentiality to solve many complex energy and environmental challenges that many developing countries including Bangladesh face.

A detailed techno-economic and environmental assessment of three types of WTE technologies for Bangladesh including AD, Pyrolysis and PG were executed using the AHP model. Relative priorities of alternatives for WTE technologies were performed using nine criteria including technological maturity, reliability, energy potentiality, land area requirement, air-water pollution, requirement of waste separation, plant establishment cost, operation and maintenance cost and potentiality of revenue earn. Pair-wise comparisons of alternatives were performed against each criterion and ranked using a scale from 0 to 9. During the process of applying the AHP model, consistency of ranking was thoroughly checked and a reasonable level of inconsistency was accepted due to the nature of human judgement. After the analysis, it was found that PG (percentage priority 47%) followed by AD (29%) is the most appropriate WTE technology for Dhaka City, Bangladesh.

The model used in this study can also be applied for the selection of WTE technologies in other developing countries. Potential WTE technologies could be site specific and criteria can be selected based on geo-environmental and socio-economic conditions. Hence, this paper has provided a new dimension of decision support system to select WTE technologies for developing countries.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on Contributors

S. M. Sayedur Rahman completed Master of Engineering degree from the Department of Industrial and Production Engineering of Bangladesh University of Engineering and Technology.

Abdullahil Azeem, PhD, works as a professor at the Department of Industrial and Production Engineering of Bangladesh University of Engineering and Technology.

Faisal Ahammed, PhD, works as a lecturer at the School of Natural and Built Environments of the University of South Australia.