An integrated approach to municipal solid waste management

Resources, Conservation and Recycling 24 (1998) 33–50

An integrated approach to municipal solid waste management E. Daskalopoulos *, O. Badr, S.D. Probert Department of Applied Energy, School of Mechanical Engineering, Cranfield Uni6ersity, Cranfield, Bedfordshire, MK43 OAL UK Accepted 5 May 1998

Abstract A theoretical model has been developed for the management of municipal solid waste streams (MSW), taking into account their rates and compositions, as well as their adverse environmental impacts. The model identifies the optimal combination of technologies for the handling, treatment and disposal of MSW in a better economic and more environmentally sustainable way. © 1998 Elsevier Science B.V. All rights reserved. Keywords: Municipal waste; Management; Computer model; Economics; Environmental impact

1. Model design The developed model considers the environmental and economic impacts that an integrated municipal solid waste (MSW) management approach (for a region or a country) will have. It uses the estimated quantity and composition of the MSW [1], as inputs and predicts the likely impacts, if this waste is to be treated by one or a combination of the following main waste-treatment and disposal technologies: * Corresponding author. Present address: c/o A. Daskalopulu, Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, UK. Tel.: +44 1895 274000, ext. 2831; fax: + 44 1895 251686; e-mail: [email protected] 0921-3449/98/$ - see front matter © 1998 Elsevier Science B.V. All rights reserved. PII S0921-3449(98)00031-7

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landfilling; mass-burn incineration with energy recovery; waste recycling; and waste composting. Other waste management and treatment methods, such as gasification, pyrolysis, the production of refuse-derived fuels or fluidised-bed combustion will not be considered in the present evaluation procedure, because they are still only employed either in small-scale pilot programmes or their economic viability has not, as yet, been fully established. The evaluation process is based on an audit and the obtained results are compared with best-practice benchmarks. The criteria used to identify the optimal option for the waste management sector, are: “ The rates of energy consumption (EC), as electricity or primary fuels, during the processes adopted. “ The rates of emissions of greenhouse gases to the atmosphere, expressed in terms of an equivalent global warming potential (GWP) that each method or a combination of them will result in. “ The net economic cost (NEC) of the operations involved. This is defined as the total cost, for designing, building and commissioning of the necessary equipment; operation and maintenance; and aftercare for the selected facilities minus the likely revenues from the individual processes. These revenues arise as a result of: “ (a) the sale of the electricity generated using landfill gas (LFG) and from an MSW incineration plant; “ (b) the additional revenue from the sale of the recovered ferrous metal; “ (c) the combined sales of the recovered materials in a materials recovery facility (MRF) and “ (d) the sale of the earth conditioner produced in waste-composting facilities. The collection and transportation costs associated with each of the waste-management alternatives have not been taken into account because the available information did not provide an adequately documented basis for further comparisons. Also they would be comparable for each of the alternatives. These performance criteria can be simply translated into corresponding associated costs and the final comparison will be made on a ‘total cost basis’. Therefore the model user should know: “ the local tariffs paid for the consumption of electricity, diesel fuel and natural gas; “ the market prices for the recovered materials and the electricity generated; “ the development costs for the individual waste management (WM) processes in the considered region or country. However, because no clear-cut opinions exist regarding the importance of each of these evaluation criteria, preliminary weighting factors are assumed in the model (Table 1). It is up to the model user to modify the values of these weighting factors in order to comply with the particular objectives of the waste management policy adopted. “ “ “

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Table 1 Assumed weighting factors in the theoretical model Evaluation criterion

Weighting factors

Rate of energy consumption (EC) Global warming potential (GWP) Net economic cost (NEC) Total

0.50 0.35 0.15 1.00

The MSW amount for the considered period along with its estimated composition are used directly as inputs to the model to calculate the environmental and economic impacts involved in the selected WM approach. Having the tonnage of each of the individual waste fractions, the economically feasible upper limits for recycling, composting or incineration can be set [2]. These are only indicative of the technical constraints that each waste material imposes (Table 2). These figures will be used in the model as the maximum potential rates that can be achieved within the different waste management scenarios. The different waste management (WM) scenarios will involve one of the following available alternatives: “ Landfilling the waste in several sites, each with a maximum annual acceptance capability of 200000 t/year (i.e. scenario L) “ Incinerating the waste in mass-burn facilities, each with a nominal input of 200000 t/year, prior to landfilling the residual solid output in the landfill sites specified (i.e. scenario I-L) “ Operating materials recovery facilities (MRFs), each with an annual handling capability of 130000 t/year, to separate the recyclable materials, prior to mass incinerating the rest and finally disposing the residual solids in landfill sites (i.e. scenario R-I-L) “ Recovering the compostable fraction of the waste in sites, with an annual acceptance capacity of 100000 t/year, and land filling the remaining fractions (i.e. scenario C-L) “ Recovering the recyclable fractions and landfilling the remaining part (i.e. scenario R-L) Table 2 Waste material limitations Waste material

Recyclable (%)

Combustible (%)

Compostable (%)

Landfill only (%)

Paper Plastic Metal Glass Organic Other

60 65 81 90 0 9

20 35 0 0 0 11

20 0 0 0 100 80

0 0 19 10 0 0

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“

Recovery of the compostable fractions of the waste prior to mass incinerating the rest and finally disposing the residual solids in landfill sites (i.e. scenario C-I-L) “ Recovery of as much as possible of the recyclable and compostable fractions of the waste before finally disposing the solid residuals in landfill sites (i.e. scenario R-C-L) “ Recovering the recyclable and compostable fractions prior to mass incinerating the rest and finally disposing the solid residual in landfill sites (i.e. scenario R-C-I-L) The final step of the analysis is the identification of the optimal combination between the individual waste treatment methods in these scenarios. For this, the Simplex technique will be used via an already developed computer program [3]. The general form of the ‘total cost’ that should be minimised is: Total cost = C*X L L +C*X I I +C* RXR + C*X C C

(1)

subject to the following relevant boundary conditions and constraints: XL 5ULL, XI 5ULI, XR 5ULR, XC 5 ULC XL \0, XI \0, XR \0, XC \0 XL +XI +XR +XC =MSW where XL, XI, XR and XC are the tonnages of the waste stream that will be treated by the individual waste management technology; CL, CI, CR and CC are the total cost coefficients related to the individual waste management technologies (i.e. the total cost per tonne of waste material treated); and ULL, ULI, ULR and ULC are the upper limits for the individual waste management processes. Choosing between different waste management systems on the basis of environmental considerations is facilitated if the number of categories to be considered are reduced by aggregation. The method that has been widely accepted is the aggregation of inventory categories that contribute to the same environmental effect. Methane and carbon dioxide emissions, for example, both contribute to the enhanced greenhouse effect and so will lead to global warming [4–6]. By using weighting factors, which depend on their relative contribution to global warming, it is possible to aggregate emissions of these gases together into a ‘global warming impact’ category. The release of 1 kg of methane will cause an equivalent contribution to global warming as does 35 kg of carbon dioxide, taken over a 20-year time span [7], so giving a global warming potential (GWP) for methane of 35. The cost related to the emission of greenhouse gases due to each WM option can be evaluated by attempting to cost all possible environmental damage that is associated with it, such as: “ potential crop yield reductions; “ forest damage; “ sea level rise; and “ damage to human health.

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Table 3 Estimated costs of greenhouse gas emissions Reference

[4] [8] [10] [6]

US$/tonne of carbon equivalent emitted in the stated period 1991–2000

2001 – 2010

2011 – 2020

2021 – 2030

0.3–65.9 (7.3) 5.3 10.0–12.0 6.3–47.7 (20.4)

6.8 12.0 – 14.0 7.2 – 53.8 (22.9)

8.6 14.0 – 18.0 8.1 – 60.3 (25.4)

10.0 3.4 – 57.6 8.8 – 66.2 (27.8)

The figures in brackets denote the statistical means.

Several studies have been carried out on this issue. The procedure followed is generally based on the so-called dose-response approach in order to evaluate the environmental impacts and then associate economic values with each of these impacts. Typically, these studies used a doubling of CO2 atmospheric concentration as a benchmark. Nordhaus [8] (as pointed out in [1] also) mainly focused on the costs arising from the impacts on agriculture and from the sea-level rise, and suggested a value of 1% of the gross national product (GNP) of a country, but it could be anywhere in the range of 0.25–2%. Cline [9] and Fankhauser [6] provided improvements to the Nordhaus estimates, by distinguishing between different world regions. Fankhauser suggested that the impacts will be more severe in developing countries rather than in the developed world. However, despite differences in the individual damage categories, these three studies roughly agreed on the overall result, with the cost of damage, resulting from CO2 doubling, being in the order of 1–2% of GNP. The corresponding estimates for the cost of the environmental damage per tonne of atmospheric loading are shown in Table 3. A mean value of $14/t of carbon equivalent (i.e. £8.4/t) is assumed for the present model.

2. Energy, environmental and financial aspects for the different waste management processes

2.1. Landfilling Landfilling stands alone as the only waste disposal method that can deal with all materials in a solid-waste stream. All the developed scenarios involve the landfill option as the disposal route for at least the remaining residuals of the other WM processes used. The environmental impacts of landfilling the waste depend on the design of the landfill, method of operation and the nature of the waste deposited. The by-products of a landfill site are LFG and the leachate generated within the site. For the purposes of the present analysis, the LFG will be the only output of the site that will be examined. Because both the production rate and the LFG collection efficiency varies from one landfill site to another [11–14], an average value of 40% gas collection efficiency will be used for the present analysis. Table 4

1.05 250

0.51 0

Glass 0.32 0

Metal 1.04 0

Plastic

1.43 250

Textiles

Nm3 indicates one cubic meter of LFG at 15°C and one standard atmosphere absolute pressure.

Landfill volume of waste (m3/t) LFG generation (Nm3/t)

Paper

Type of waste

Table 4 Data regarding LFG generation rates for a landfill site used in the model [15]

1.11 250

Organic

0.2002 35

Other

0.77 100

Compost

0.67 0

Ash

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presents the LFG generation rates for the different waste fractions of the MSW stream, while the composition of it is presented in Table 5. Assuming an average volumetric concentration of 55% for CH4 which has a calorific value of 37.75 MJ/Nm3 [16] in the LFG, the LFG might have, as an upper average energy content of 20.8 MJ/Nm3. The UK Department of the Environment estimated figures [17] within the range of 15–21 MJ/Nm3. In the present analysis, an average value of 18 MJ/Nm3 is assumed. If the LFG produced is used to drive a gas-fired engine, with a conversion efficiency of 30%, to generate electricity, then an electrical output of 1.5 kWh/Nm3 can be exported to the grid. However, to operate all the necessary equipment on site the average fuel consumption is around 0.6 l of diesel fuel per m3 of void space filled, while the electricity consumption is around 22 kWh/t [15].

2.2. Incineration Combustion can be regarded either as a pre-treatment method for the wastes prior to the residuals’ final disposal or as a means for valorising part of the waste by energy recovery. The actual emissions to air will depend on the type of pollution-abatement equipment installed and the efficiency of their operation. It will be assumed that the recovered energy is used to generate electricity, which is then exported from the system. It will also be assumed that all the emissions are within the limits of the recently imposed emission limits in the UK, which seem to be currently the most stringent in Europe (Table 6). The amount of the carbon dioxide produced is not included in the emission data, because there is no legal limit for it. However, the amount emitted could be calculated from the carbon content of the fractions in the MSW, assuming that all the carbon content is given off as CO2; all the other emissions are attributed equally to all the fractions entering the mass-burn process. Table 5 Composition of the LFG generated in a landfill site, as presumed in the model [15] Components

LFG composition (g/Nm3)

CO CO2 CH4 HCl HF H2S HC Chlorinated HC Cadmium Chromium Lead Mercury Zinc

0.0125 883.93 392.86 0.065 0.013 0.2 2 0.035 5.6E-06 6.6E-07 5.1E-06 4.1E-08 7.5E-05

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Table 6 Air emissions from the combustion of MSWBTB6\ Emission rate (g/tonne of waste burned) based on the cited references EC directive 89/369/EEC, 1989a Particulates CO NOx SOx HCl HF Total HC Chlorinated HC Dioxins/furans Arsenic Cadmium Chromium Copper Lead Mercury Nickel Zinc

Ref. [18]b

Ref. [19]c

500 125 25 2.5 0.0384 0.0836 0.000005 0.008 0.0135 0.013 0.055 0.245 0.00285 0.002 0.85

150 100 350 300 30 2 2 2 0.5*10−6 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

150 500 1500 250 100

2.5 0.5 6.25 6.25 6.25 6.25 0.5

a

Calculated for plant meeting the EC Directive for a new incineration plant and producing 5000 Nm3 of stack gas per tonne of waste burned. b Based on a plant meeting the German 17th Emission Regulation and assuming a production of 5000 Nm3 of stack gas per tonne of waste burned [18,20]. c Based on the latest standards imposed in the UK [19].

The thermal-treatment approach, as well as liberating energy from the feedstock, also consumes energy, which is required for operating the cranes, moving grates, fans for air injectors, emission-control equipment and general heating and lighting purposes. An assessment of a 200000-t/year incineration plant for refuse with a net calorific value of 8.01 MJ/kg produced a corresponding gross electrical output of 520 kWh/t of waste, with an average efficiency of 23% and a net power export of 450 kWh/t [21,12]. As a solid residue 20 kg of filter dust will be assumed to be produced per tonne of waste. Additional natural gas is burnt at a rate of  0.23 Nm3/t of waste to heat up the incinerator during the start-up period. Table 7 provides a summary of the emission data used for the incineration option in the model.

2.3. Composting Biological treatment, either in the form of composting or biogasification, can be used to treat both the organic fraction and the paper fraction of an MSW stream. The energy consumption of the process will depend on the level of the technology employed. According to the data reported for German plants [22], a typical energy consumption of 35 (9 15) kWh/input tonne can be assumed, for a site treating

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10000 t/year (Table 8). A value of 30 kWh/input tonne will be used for the present model. The final output of the process will be 50% of the initial input volume of the total organic material (i.e. organic waste and paper fraction) [23]. The remaining 50% is lost due to evaporation and respiration. The main gaseous emission to air is that of carbon dioxide, with an average rate of 320 kg/t of wet organic material feedstock.

2.4. Recycling

“ “

Recycling of post-consumer materials found in the MSW involves: the recovery of the materials from the waste stream; an intermediate processing (such as sorting and compaction) of the residual materials;

Table 7 Air emissions and solid waste residues during the incineration option [15] Outputs

Solid waste (t/ t) Bottom ash Filter dust

Type of waste Paper

Glass

Metal

Plastic

Organic

Other

Compost

0.084 0.032

0.9 0.032

0.85 0.032

0.06 0.032

0.077 0.032

0.42 0.032

0.154 0.032

150 0 0 350 300 30 2 2 2

150 0 0 350 300 30 2 2 2

150 100 2 492 500 350 300 30 2 2 2

150 100 563 900 350 300 30 2 2 2

150 100 1 025 900 350 300 30 2 2 2

150 100 1 127 800 350 300 30 2 2 2

5

5

5

5

5

5

× 10−6 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

×

×

×

×

×

Air emissions (g/t) Particulates 150 CO 100 CO2 1 128 500 NOx 350 SOx 300 HCl 30 HF 2 HC 2 Chlorinated 2 hydrocarbons Dioxins/ 5 furans × 10−6 As 0.1 Cd 0.1 Cr 0.1 Cu 0.1 Pb 0.1 Hg 0.1 Ni 0.1 Zn 0.1

10−6 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

10−6

10−6 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

10−6 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

10−6 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Capacity (t/year) Feedstock Energy consumption (kWh/t)

10 000 Biowaste 35 (9 15)

German range

Plant type

13 700 Biowaste-greenwaste 18

Windrow composting

Table 8 Energy consumption of various composting plants [22]

6800 Biowaste-greenwaste 18

Box composting

18 000 Wet waste 50

Tunnel reactor

35 000 Biowaste-greenwaste 40

Drum composting

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Table 9 Air emissions savings and solid waste residues due to recycling [24,25,30] Paper Solid waste (kg/t) Air emissions (g/t) Particulates CO CO2 NOx N2O SOx HCl HF H2S HC NH3 Pb Hg Savings in energy consumption

0.0653 3270 2280 2310 53 3947 3.3 0.005 12 1692 04 0.003 6.8

Glass −0.0245

Metal 0.255

16831 47

24004 −486

663 91 946 67 −22

352 176 2855 0.46

1151 1.9 −15.5

10364 66.1

3.7

12.4

Plastic −0.1564 1566 272 498674 7660 3398 0.8 16414

21.79

“ “

transportation of the recovered materials; and final processing to provide either an end product or a raw material for manufacturers. Several reports have been produced concerning the energy consumption and emissions resulting due to waste recycling [24–29]. In many of these studies, the main objective was to compare the environmental impacts of producing recycled versus virgin materials [25]. These analyses have been based on a cradle-to-produced-material basis. For the virgin materials, this included the extraction of the raw materials, whereas for the recycled ones, the cradle stage began as they were discarded as waste materials. The savings in energy requirements and emission levels when using recycled materials will be utilised in order to produce a positive attitude towards recycling (Table 9). In this model it is assumed that an average diesel fuel consumption of 1.0 l/t is required for an MRF site with a nominal handling capacity of 130000 t of MSW/year. 3. Model results and discussion In order to demonstrate the use of the model, the management of the MSW in the UK is considered as an example. The model involves eight steps, which provide the generated results, in response to the input data required.

3.1. Step 1 The user introduces the projected gross domestic product (GDP) and the population of the country or the region, for the current or the future year

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Table 10 Prediction of the waste amount and composition for the given country Name of the country Gross domestic product Population Estimated MSW amount Total consumer expenditure (TCE) Related fraction of TCE

UK 975.0 (billion US$) 57.411 (million inhabitants) 19.258 (million tonnes) 575.51 (billion US$) 114.99 (billion US$)

considered. These two initial values will be used to calculate the corresponding amount of the generated MSW, the total consumer expenditure (TCE) and that part of it (RTCE) related to the MSW generation. This information is utilised to provide an estimate of the waste composition on a tonnage basis (Table 10).

3.2. Step 2 The derived composition is presented in terms of the adjusted tonnage of the individual waste fractions (Table 11).

3.3. Step 3 During this step, the user has to define certain characteristics of the waste treatment/disposal facilities which are available or already installed. These include: “ The existence of and LFG collection system in the landfill site, along with the gas recovery efficiency. “ The electricity generation efficiency in incineration plants, the agreed electricity tariff for the sale of the electricity generated, the efficiency of the ferrous metal recovery facility and the market prices of the recovered metals. “ The recovery efficiency of the MRF facility, along with the market prices for the recovered materials. “ The market price for the final compost product. Table 11 Prediction ofthe waste composition Component

Amount (t)

Paper Plastic Glass Metal Organic Other Total

4 477 270.70 4 569 595.60 824 852.49 1 197 886.30 6 304 021.50 1 883 934.20 19 257 561.00

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Table 12 Characteristics of the waste management systems LFG collection LFG collection efficiency Electricity generating efficiency Electricity tariff for recovered energy Ferrous metal recovery efficiency Price/tonne of ferrous metal recovered MRF efficiency Price for recovered paper Price for recovered plastic Price for recovered glass Price for recovered metal Price for produced compost product Consumption price for diesel Consumption price for electricity Consumption price for LFG Total developing cost for a landfill site Total developing cost for an incineration Plant Total developing cost for an MRF facility Total developing cost for a composting site

Yes 40% 20% 0.026 (£/kWh) 80% 20 (£/t) 70% 8.48 (£/t) 58.91 (£/t) 19.86 (£/t) 15.72 (£/t) 20 (£/t) 0.6 (£/l) 0.0434 (£/kWh) 0.0791 (£/Nm3) 8 (£/t) 37 (£/t) 35 (£/t) 45 (£/t)

The unit prices for different energy forms used for the operations on the site, along with the total development costs involved in each operation.The above questions have to be answered before proceeding to the following steps. The user should enter a zero value for those parameters that are not appropriate for the desired policy plans or objectives (Table 12).

3.4. Step 4 The user will be provided with the maximum technically feasible limits for the individual WM processes (i.e. waste materials limitations), as these are derived from the waste amount and composition of the given waste stream (Table 13). Table 13 Waste material limitations Waste fraction

Recyclable (%)

Combustible (%)

Compostible (%)

Landfill (%)

Total

Paper Plastic Metal Glass Organic Other Total (t) % (by mass)

60 65 81 90 0 9 7.57×106 39.30997

20 35 0 0 0 11 2.71×106 14.06631

20 0 0 0 100 80 8.70×106 45.166452

0 0 20 10 0 0 2.81×105 1.457271

19 257 561 100

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Table 14 Selection of the initial percentages for the individual waste management scenarios

Intial values (fractions of one) Landfill Incineration MRF Composting Total Adjusted values (fractions of one) Landfill Incineration Recycling Composting Total

L

I-L

R-L

C-L

R-C-L

R-I-L

C-I-L

R-C-I-L

1.00

0.10 0.90

0.65

0.55

0.30

0.45 0.10

0.30 0.40 1.00

0.55 0.10 0.35

0.10 0.10 0.35 0.45 1.00

0.35 1.00

1.00

1.00

0.45 1.00

1.00

0.27 0.73

0.65

0.67

0.40

0.33 1.00

0.30 0.29 1.00

0.35 1.00

1.00

1.00

1.00

0.57 0.08 0.35 1.00

0.45 1.00

0.59 0.08 0.33 1.00

0.24 0.08 0.35 0.33 1.00

3.5. Step 5 The user has to specify the desired percentages of the waste stream that should be entering the individual waste treatment/disposal routes, bearing in mind the maximum permissible limits. These initial values will automatically be adjusted, so that the solid residues from the incineration, recycling and composting processes are taken into account in the following calculation steps (Table 14).

3.6. Step 6 The user is able to see, in a series of tables, the performance characteristics of the different WM scenarios adopted. These characteristics involve (Table 15): “ The electricity, diesel fuel and natural gas consumption in terms of cost. “ The GWP and the associated environmental costs. “ Development, revenues and the net economic costs (NEC).

3.7. Step 7 The evaluation criteria for the analysis are given weighting factors in order to reflect the objectives of the MSW management policy (Table 1), according to which the total costs of the WM scenarios are calculated (Table 16).

3.8. Step 8 This provides the necessary coefficients CI for the ‘total cost’ equation, Eq. (1), employed to determine the optimal amounts XI of the MSW to be treated/disposed

Net economic costs (NEC) involved in the different WM scenarios (£) Landfill Incineration Recycling Composting Total

Environmental cost (£) Landfill Incineration Recycling Composting Total

−2.19×106 4.63×108

4.61×108

8.94×107

1.94×108

2.21×108

8.94×107

6.03×107 1.34×108

4.97×107

6.90×106 4.28×107

I-L

2.21×108

Costs for the energy consumption for the different WM scenarios (£) Landfill 2.53×107 Incineration Recycling Composting Total 2.53×107

L

Table 15 Performance characteristics for the different waste management scenarios

2.10×108

1.51×108

5.83×107

1.51×108

7.14×106

1.43×108

1.16×107

4.81×106

1.64×107

R-L

3.69×10 4.11×108

8

4.15×107

9.07×106 1.58×108

1.48×108

8.28×106 2.52×107

1.70×107

C-L

1.30×108 3.28×108 4.78×108

2.01×107

6.13×106 8.08×106 1.04×108

8.98×107

4.13×106 7.36×106 1.35×107

1.02×107

R-C-L

2.51×108

4.81×107 5.15×107

1.47×108

1.26×108 1.48×107 7.14×106

1.43×107

1.43×107 4.76×106 4.81×106

R-I-L

3.13×107 5.15×107 1.51×108 3.69×108 4.52×108

1.31×108 1.48×107 7.14×106 9.07×106 1.55×108

8.28×106 2.79×107

1.49×107 4.76×106

C-I-L

1.36×105 5.15×107 1.51×108 3.69×108 5.72×108

9.07×106 8.34×107

5.24×107 1.48×107

5.98×106 4.76×106 4.81×106 8.28×106 1.42×107

R-C-I-L

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Table 16 Total performance of the selected scenarios Total cost of the WM scenarios (£)

EC GWP NEC Total

L

I-L

R-L

C-L

R-C-L

R-I-L

C-I-L

R-C-I-L

1.27×107 2.72×107 1.34×107 5.33×107

2.49×107 2.38×107 6.45×107 1.13×108

5.79×106 1.67×107 3.15×107 5.40×107

1.26×107 1.93×107 6.16×107 9.36×107

6.74×106 1.12×107 7.18×107 8.97×107

7.15×106 1.64×107 3.72×107 6.07×107

1.40×107 1.89×107 6.73×107 1.00×108

7.11×106 8.49×106 8.54×107 1.01×108

of by the technologies considered, in a given WM scenario, with the minimum total cost (Table 17).

4. Conclusions and recommendations The current costs still favour the landfill option of managing the MSW. However, the impact of a potential levy on the waste land filled, could reduce the gap between the costs of landfilling and the other alternative waste-treatment technologies. Thus changes in public perception and the attitude of the waste management industry will probably occur. Recycling rates can be increased by the introduction of the necessary financial incentives to stimulate the development of markets for recovered materials from the materials recovery facilities and therefore provide a more stable market price for them. The relative cost of composting could be reduced if appropriate legislation measures could be implemented (on a regional or a national scale), banning the deposition of organic wastes in landfill sites. This would reduce the rates of LFG production and the corresponding revenues from the sale of the electricity generated. Incentives that would favour the use of organic-derived earth conditioners could provide a bigger market for the compost product. Neither the collection nor the transportation costs are included in the presented model. It is our belief that the introduction of these figures would create a more complete representation of the current situation in the waste management sector, and provide more realistic figures for future planning.

Table 17 Simplex coefficients for the selected waste management systems Simplex coefficients

CL

CI

Value (£/t)

4.64

24.30

CR 22.55

CC 41.72

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