Distributed or centralised energy-from-waste policy? Implications of technology and scale at municipal level

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Energy Policy 35 (2007) 2622–2634 www.elsevier.com/locate/enpol

Distributed or centralised energy-from-waste policy? Implications of technology and scale at municipal level David Longdena,, John Brammera, Lucy Bastina, Nic Cooperb a

School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham, West Midlands B4 7ET, UK b Compact Power Ltd., Yara House, St. Andrews Road, Avonmouth, Bristol BS11 9HZ, UK Received 30 June 2006; accepted 19 September 2006 Available online 16 November 2006

Abstract Energy-from-waste (EfW) policies can provide an essential part of landfill diversion and climate change strategies. Many UK waste disposal authorities (WDAs) are currently deciding which energy-from-waste policies are most suitable for their respective municipal areas. Such decisions are challenging since the environmental, economic and social implications of any EfW policy must be fully considered, now that planning guidelines require a full Sustainability Assessment. More specifically, WDAs must identify suitable site locations for facilities, and the optimal scale and number of facilities. This paper reports the results from a study that has developed and appraised EfW policy options using Geographical Information Systems and Multi Criteria Analysis modelling. These methods were used to evaluate and compare the impacts of several EfW strategies in the UK administrative areas of Cornwall and Warwickshire. Different strategies have been defined by the size and number of the EfW facilities, as well as the technology chosen, which includes conventional incineration and advanced thermal treatment. The overall conclusion of this work is that distributed small-scale EfW facilities score most highly overall on the chosen decision criteria and that scale is more important than technology design in determining overall EfW policy impact. r 2006 Elsevier Ltd. All rights reserved. Keywords: Energy-from-waste; Distributed generation; Multi-criteria analysis

1. Introduction This paper presents the policy appraisal results of an energy from waste (EfW) planning project applied to the UK county areas of Warwickshire and Cornwall. Both areas have similar populations of over half a million and waste arising of approximately 290,000 tonnes (2003/2004). In contrast, they are very different in geography with Cornwall being a mostly sea-bordered peninsula in an isolated UK position, while Warwickshire is situated in the Midlands with excellent transport links to the surrounding conurbations. Specifically, the paper compares several geographically distinct EfW scenarios that feature traditional incineration or ATT facilities at large, medium and local scale. This has been achieved using a multi-criteria decision analysis (MCDA) modelling approach. Before Corresponding author. Tel.: +44 121 204 3417.

E-mail address: [email protected] (D. Longden). 0301-4215/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2006.09.013

discussing in EfW policies in local contexts, however, it is necessary to consider the expanse of existing UK policy that influences the formulation and appraisal of EfW solutions. 1.1. UK Energy, waste, CO2 reduction and planning policy contexts At a time when North Sea reserves of gas and oil are in decline and security of energy supply is of great concern (DTI, 2003), the EU Landfill Directive is promoting a major change in waste management and is driving new EfW capacity for the non-recyclable, residual waste fraction (DEFRA, 2006) Failure to meet the 75% of biodegradable municipal waste of 1995 levels diversion targets may mean that UK waste disposal authorites (WDAs) could face up to £180 million of fines (Eminton, 2005). There is also great concern that the UK Government’s targets of achieving a 60% reduction in carbon emissions

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by 2050 and 10% of UK electricity from renewable sources by 2010 will not be achieved (PIU, 2002; RCEP, 2000). EfW is regarded as a means for producing renewable energy, since approximately 70% of municipal solid waste (MSW) is defined as being carbon neutral (Aeat, 2005). Stretching across all waste, energy and climate change issues are the requirements of sustainable development (WCED, 1987), which in the UK context are described by the government’s sustainability strategy (DEFRA, 2005). Recovering energy from waste is regarded as a way of displacing fossil fuel in energy generation as well as providing a sustainable alternative to landfill (Consonni et al., 2005a; Corti and Lombardi, 2004; DEFRA, 2006; Murphy and McKeogh, 2004; Porteous, 2005; Tyson et al., 1996), although this can be a controversial view (Boyle et al., 2003). A recent report concluded that potential energy recovery from residual waste could account for as much as 17% of total UK electrical energy demand by 2020 (Lee et al., 2005). Electricity generation is a primary concern of EfW developers, due to its favourable effect on project economics of capital intensive schemes (Williams, 2005), but in the opinion of the authors, does not represent sound resource management when generation efficiencies of between 13% and 24% (Malkow, 2004) result in a great amount of potentially useful energy being lost in the form of waste heat (Pepermans et al., 2005). In order to make maximum savings in CO2 emissions, it is clearly necessary to deploy EfW plant in a combined heat and power (CHP) role, where heat and power generation efficiencies can reach up to 80% (Beggs, 2002). For further explanation of CHP and its climate change implications refer to Boyle et al. (2003). Planning permission is particularly difficult for EfW plants at the local level in the UK (Ares and Bolton, 2002). Sixty-three percent of operating UK plants have been built on the sites of former incinerators and are located in urban areas with significant potential heat demand (ILEX Energy, 2005). More recent plants however, built since the introduction of the landfill directive, are increasingly being built on industrial sites in more sensitive rural/ suburban environments, often more remote from potential heat consumers (Carey, 2006). This trend may further inhibit the potential for large EfW plants being able to operate in CHP mode and exploit the energy efficiency gains. Against a background of conflicts in planning (BBC, 2004; Faulkner, 2006a, b; FoE, 2002), the Government detailed its vision for a 2020 UK energy system in the Energy White Paper (DTI, 2003). ‘‘There will be much more local generation, in part from medium/small community power plant, fuelled by locally grown biomass and locally generated waste y Plant will also increasingly generate heat for local use.’’ This vision presents great challenges for the UK planning system. In order to successfully achieve planning permission for any EfW policy, WDAs must prove that their EfW policies meets the requirements of the decision-making tools and

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principles outlined in the EU Waste Framework, notably, the waste hierarchy and proximity principle. Failure to meet these guidelines may result in planning failure at a public enquiry (FoE, 2002). The waste hierarchy is of consequence to the correct sizing of EfW facilities, since energy recovery is of relatively low position in the hierarchy, being inferior to minimisation, re-use and recycling (DEFRA, 2006; DETR, 2000). The Proximity Principle states that waste should be disposed of as geographically near as possible to its source. Policies detailing planned recycling and composting rates, as well as other factors such as varying waste growth rates and composition have significant implications for EfW planning in terms of the effect on the calorific value of the remaining residual waste, as well as the respective size and site locations of the facilities (Brereton, 1996; Subramanian, 2000; Tyson et al., 1996; Wenisch et al., 2004). 1.2. The current UK EfW situation EfW is extensively used in Europe, but less in the UK (Porteous, 2005). Table 1 however, shows that significant differences in chosen EfW policies exist between countries, with varying numbers of plants in operation and average capacities. The table shows that there is by no means any given rule for choosing sizes of EfW plant, with the Netherlands preferring large capacity plants of greater than 480 ktpa, while Norway with the same number of plants preferring the much smaller 60 ktpa capacity. The UK average of 246 ktpa is mid-way between the large centralised plants of the Netherlands and the small plants of Norway. There are currently 19 EfW plants of varying capacity in the UK, only 4 of which are producing heat and electricity in a CHP configuration. Of the remaining 15, one plant generates heat only, with the remainder producing electricity only. Other European countries have far greater experience of EfW and CHP (Duncan, 2006). Germany, for example, operates 67 EfW CHP plants in municipal heating schemes (ILEX Energy, 2005). In technology terms, nearly all UK plants use thermal combustion processes, but one small pyrolysis/gasification plant has been operating on clinical waste for more than 3

Table 1 Number of MSW incinerators and average plant capacities adapted from Williams (2005) Country

Number of incinerators

Average plant capacity (1000 tonnes/year)

Italy Norway Sweden France The Netherlands UK

32 11 30 210 11 17

91 60 136 132 488 246

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years (Compact Power, 2006). The building of two more pyrolysis/gasification plants, intending to use MSW feedstock, is due to commence later this year (Compact Power, 2006; Dauber, 2006). If alternative routes to landfill are made using ‘‘new’’ technologies capable of electricity generation such as anaerobic digestion and pyrolysis/gasification plant, WDAs will be in receipt of Renewable Obligation Certificates (ROCs). ROCs essentially add a 3 pence/kWh premium for generators (Hartnell, 2006). It is currently unclear how ROCs will impact the economics of the ‘‘new’’ technologies, but it is clear that they could be significantly advantaged over conventional incineration (Livingston, 2002), which until recently did not qualify for ROCs. In April 2006, the UK DTI decided to allow conventional technology to qualify, subject to the inclusion of quality CHP (ILEX Energy, 2005). The deployment of such technology configurations can result in meeting both the Renewables Obligation and Landfill Directive targets. 1.3. Current local EfW policy development WDAs have previously used best practicable environmental option (BPEO) (Williams, 2005) as the basis on which to select waste management options and policies. BPEO has now been replaced by the Planning and Policy Statement 10 (PPS 10) requirement to use more inclusive sustainability assessment (SA) in evaluating waste policy options (ODPM, 2005). To assist in identifying the BPEO, life cycle assessment (White et al., 1995) has often been used in the form of software tools such as WISARD (Ecobilan, 2006) to inform waste policy makers on the performance of various waste management scenarios. It has been highlighted that WISARD does not include alternative EfW options that involve the emerging and arguably cleaner ATT technologies based on pyrolysis/ gasification or anaerobic digestion (Purser, 2003). WISARD is now being replaced by the new WRATE life-cycle assessment software (Environment Agency, 2006a) later this year to ensure that new and emerging technologies are included within the Sustainability Assessment of EfW options, now that this measure has replaced BPEO (Eunomia and ERM, 2005). Planners in both Warwickshire and Cornwall have employed WISARD to determine which overall waste management strategy is the BPEO, and what EfW policy should be adopted (Higham, 1999; Jainter and Poll, 2005; Wheeler and Jainter, 2006). In the case of both counties, the preferred EfW policy is one large centralised combustion facility of between 180 and 230 ktpa. In order to manage transport impact, further use of waste transfer stations (WTS) is anticipated (Biffa, 2002; US-EPA, 2002). 1.4. Policy and conflict The preference for large centralised provision in both Warwickshire and Cornwall is attracting criticism because

it has evolved from decision processes which have not fully considered the merits of using new technology, combined heat and power, and local community-sized facilities. Decentralised facilities have the potential to reduce waste transport miles and the associated impacts (Unpublished data, Bastin and Longden). Opposition groups are concerned that the WDAs preferred centralised approach does not properly address the obligations of climate change and sustainable development (Taylor, 2006). The transport of waste is a particularly sensitive issue in choosing waste management policies (Gershman et al., 1986). The WDAs considered in these case studies have used consultants’ in-house spreadsheet models to estimate the associated transport impacts of any waste management strategy and its constituent EfW policy (Higham, 1999; Jainter and Poll, 2005; Wheeler and Jainter, 2006). Unfortunately, it is often unclear how these models work and what their underlying assumptions are? There are many actors, each with their own interests that need to be considered in EfW decision making (Nilsson et al., 2005; Norese, 2003; Shmelev and Powell, 2006). The most important of these in a local context are the WDAs (Maniezzo et al., 1998) who have a statutory duty to manage waste with their officers and publicly elected councillors, advised by consultants. In the commercial arena are large waste management and technology companies, interested in winning lucrative contracts in an arguably oligopolistic market, reportedly worth between £2 and £7 billion (OFT, 2006; Pfeifer, 2006). Other parties include non-governmental organisations and the public who may form effective opposition groups. Pursuing any one route to EfW within a municipal area without thorough investigation of the merits of alternative routes can lead to effective criticism. There is a need for an approach which measures the merits and impacts of different scales of EfW technology within the local context (Nilsson et al., 2005; Shmelev and Powell, 2006; Wey, 2005). A framework (such as that reported here) that develops and evaluates several alternative scenarios on a consistent basis has the potential to be more inclusive of actors and experts views and could reduce the problem of effective opposition in the planning and approval process.

2. Related studies Many recent EfW appraisal studies are technology related and engage in the comparison of conventional incineration and ‘‘novel’’ or ‘‘emerging’’ EfW systems often based on pyrolysis or gasification (Azapagic and Camana, 2005; Murphy and McKeogh, 2004; Porteous, 2005). Further studies have been commissioned for the purpose of informing local authorities (Enviros, 2004; Fichtner, 2004; Livingston, 2002; Mc Lanaghan, 2002). The economic and environmental effects of centralised vs. distributed EfW have been examined at the regional level (Bergsdal et al., 2005; Consonni et al., 2005a, b) and recently at the

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local county administration level (Wheeler and Jainter, 2006). Waste management policy appraisal, often integrating EfW solutions have made extensive use of life cycle analysis (Ayres et al., 1998; Azapagic and Camana, 2005; Bergsdal et al., 2005; Consonni et al., 2005b; Corti and Lombardi, 2004; Nilsson et al., 2005; Wenisch et al., 2004). The need to include the qualitative views and opinions of conflicting actors and experts has ensured that multi-criteria analysis methods has remained a useful appraisal tool (Barda et al., 1990; Cheng et al., 2003; Dai et al., 2001; Dujim and Markert, 2002; Khelifi et al., 2006; Norese, 2003). The need to account for local conditions has led to an increasing use of spatial decision tools based on geographical information systems (GIS) to model base line waste conditions, identify potential facility locations and estimate transport impacts (Cheng et al., 2003; Maniezzo et al., 1998; Matejicek et al., 2006; Nilsson et al., 2005; Shmelev and Powell, 2006). The results from studies regarding what is the best technology and scale are ambiguous. In some cases, authors argue that large-scale incineration using wellproven combustion technology is superior to small scale (Consonni et al., 2005b; Higham, 1999; Jainter and Poll, 2005), while others argue that small scale is superior or the effects are marginal. This is principally where the use of heat is concerned (Bergsdal et al., 2005; Kristiansen, 2006) or where facilities have been designed to be economic at small scale by reducing the need for expensive air emissions abatement systems (Dawber, 2006). Transport is regarded as a key issue (Harbottle et al., 2006), that is significantly reduced in the results of small-scale, multiple facility modelling (Bergsdal et al., 2005), but has also been argued as insignificant (Wheeler and Jainter, 2006). 3. Methodology 3.1. Defining the scenarios This paper considers five scenarios with different EfW technologies and scales. Scenarios 1–3 utilise conventional combustion facilities with unit capacities of 180, 60 and 60/ 30 ktpa, respectively, corresponding to large, medium and

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local. Scenarios 4 and 5 utilise the emerging advanced thermal treatment (ATT) facilities, based on pyrolysis and gasification processes, with unit capacities of 60 and 30 ktpa, respectively (medium and local). A large-scale ATT scenario has not been included as many suppliers are not presently offering this option in the UK (Cooper, 2003; Dawber, 2006). Table 2 summarises the above, and also shows that scenarios are characterised by different numbers of facilities and the use of waste transfer stations (WTS). Considering WTS is important when assessing transport impact, particularly in the case of the large scenarios. Local facilities have capacities of either 60 or 30 ktpa determined by the size of the locally collectable waste resource. In the case of the local scenarios, the term ‘‘local’’ is defined to be equivalent to the UK district level of local government. In relating the choice of unit capacities to real operating plant, it should be noted that 2 of the 19 UK EfW plants have capacities of 30 and 60 ktpa, respectively (ILEX Energy, 2005) and can be regarded as being consistent with the medium and local scenarios, whereas 8 of the 19 have capacities greater than 180 ktpa and therefore conform to the concept of large, or centralised provision. The locations of EfW facilities within the scenarios have significant implications for determining transport impact. The locations of the large scenarios in both counties are pre-determined and have been taken from the local WDA waste management or BPEO strategies (Cornwall County Council, 2001; Jainter and Poll, 2005). These are on large areas of derelict post-industrial land. In the case of hypothetical local and medium-scale facilities, however, a more sophisticated approach is required. These facilities have been located using a Geographical Information System (GIS), on the basis of the availability of waste within a specific radius combined with a range of other siting criteria (Longden et al., 2005). The GIS has also been used to calculate the associated road transport impact of supplying the facilities with waste fuel from their respective catchments. These results became the basis for the transport impacts scores in the MCDA model. Quantified impacts have been aggregated for all facilities in each scenario and include journeys, lorry miles, economic and

Table 2 EfW scenarios modelled for Cornwall and Warwickshire Description

Technology Notation Scale capacity (ktpa) Number of plants Use of waste transfer stations a

Cornwall. Warwickshire.

b

Scenarios 1

2

3

4

5

Large

Medium

Local

Medium

Local

Combustion L SC 180 1 Yes

Combustion M SC 60 3 Yes

Combustion Loc SC 60/30 4a, 5b No

Pyrolysis/gasification M S ATT 60 3 Yes

Pyrolysis/gasification Loc S ATT 60/30 4a, 5b No

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external costs. GIS has been widely used in academic energy planning studies (Dagnall et al., 2000; Freppaz et al., 2004; Graham et al., 2000; Krukanont and Prasertsan, 2004; Noon and Daly, 1996; Tyson et al., 1996; Voivontas et al., 2001), but far less by WDAs or their consultants to support real EfW decision-making processes. 3.2. Developing the MCDA model This project has used a commercially available MCDA software tool HIVIEW (Phillips, 2004), developed by the London School of Economics, to identify the preferred EfW scenario option. In HIVIEW, the user constructs a tree hierarchy model using criteria agreed to be important in making the decision. Each criterion is then assigned a weight, according to its perceived importance in the overall decision. Scores for each criterion and scenario option are then researched and derived. HIVIEW expects the criteria to be ‘‘swing-weighted’’; that is, the weightings should reflect not only the perceived importance of the criteria, but also the absolute range of scores obtained (an important criteria with a very narrow range of scores should receive less weighting than one with a very broad range). However, it was felt that this might add confusion to the process of obtaining weights, so the score range effect was instead accounted for by adding a mock scenario, in which the criteria scores are either zero (if a high score is desirable) or the sum of the lowest and highest scenario scores (if a low score is desirable). The scenario scores are then normalised to a scale of 0–100 for each criteria, with 100 corresponding to the most desirable score. The normalised scores are then multiplied by the cumulative weights. The results for each criterion are finally added to produce an overall result for each scenario. The choice of criteria in the model was arrived at by a literature review and consultation with council officers and local experts. The majority of criteria from previous studies respected environmental impact. This is justified since ‘‘In 1984, 60.1% of Americans prioritised environmental protection over economic growth. In April 2000, the proportion was 67%’’ (Greenberg et al., 2002). Environmental criteria generally includes air emissions (Shmelev and Powell, 2006), displaced CO2 emissions from fossil fuels (Consonni et al., 2005b; Corti and Lombardi, 2004), water discharges (Bergsdal et al., 2005), discharges to ground, (fly and bottom ash) (Azapagic and Camana, 2005; Dujim and Markert, 2002), dioxins and risks to human health (Harbottle et al., 2006; Porteous, 2005), transport (Maniezzo et al., 1998; Wey, 2005) and land take (Dujim and Markert, 2002; Jainter and Poll, 2005). Financial or cost criteria included labour and capitalrelated expenditure (Greenberg et al., 2002), gate fee (Murphy and McKeogh, 2004), net present value (Nilsson et al., 2005), and transport costs (Cheng et al., 2003). With these criteria in mind, group discussions were then held to determine which criteria were of most interest to the officers and local experts involved in the case study

decision-making process (Norese, 2003). A result of this was the decision to include the additional criteria of strategy flexibility and technology maturity. The same model structure was ultimately used for both councils, and is shown in Fig. 1. The model did not initially include social criteria, but these were added due to concerns about the impact of such issues on the planning system and the need for eventual public acceptance of any EfW policy. Application of the MCDA model took place in early 2006. Table 3 shows the scores that have been allocated to these criteria for all Cornwall and Warwickshire scenarios. To derive technology scores for the combustion scenarios, data describing the performance of various real and modelled facilities has been collected from a variety of sources including the Environment Agency’s Waste Technology Data Centre (Environment Agency, 2006b), consultant reports (Enviros, 2004, 2005; Fichtner, 2004) and academic journals (Brereton, 1996; Consonni et al., 2005a; Gershman et al., 1986; Murphy and McKeogh, 2004). To arrive at the input measurements for the MCDA model for 30, 60 and 180 ktpa facilities, the sourced data was plotted between the scales of 30 and 250 ktpa and interpolated to produce best-fit curves with r2 values ranging between 0.75 and 0.99. Some MCDA input measurements were normalised, but others were aggregated to describe the overall impact as determined by the number of plants in the scenario. The MCDA input measurements for the ATT scenarios are based primarily on the Compact Power technology—a staged pyrolysis and gasification process (Cooper, 2003). Data provided by Compact Power has been validated against independent sources where possible (Enviros, 2005; Fichtner, 2004). The underlying scenario scores in Table 3 are regarded as sufficiently accurate at the strategic county planning level. Every effort has been made to ensure that data sources have been derived by the same method, such as that detailed in the WID directive for air emissions, for example (DEFRA, 2004). Comparisons between scenarios have been kept valid by using the same interpolated relationship curves to derive scores for 180, 60 and 30 ktpa scale facilities. Many indicator scores are not technology dependant, but geography dependant and have been consistently derived for all scenarios by the same GIS techniques. Such criteria include those related to transport, potential for community ownership and flexibility. Criteria dependant on technical issues such as net cost per tonne and air emissions are very similar if not exactly the same for both areas. 4. Results The scores presented in Table 3, highlight differences that result from the geographic characteristics of the two case study areas. The greatest dissimilarity is shown in the transport related scores, where the large scale Warwickshire scenario has a 42% less impact than the correspond-

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Fig. 1. Decision tree structure for EfW options for Warwickshire and Cornwall.

ing Cornwall scenario. This can be explained by the fact that Cornwall has a weaker road network, lower waste arising density and larger transport distances (Unpublished data, Bastin and Longden). There are further differences derived from the GIS site identification technique, which produced the result of 4 or 5 plants for the local scenarios in Cornwall and Warwickshire, respectively. The potential for community ownership and flexibility criteria derive their scores as a function of the number of plant per scenario and hence, Warwickshire, is more favourable on these criteria. Apart from geographically derived differences, the data in Table 3 shows that the technically based scores differ significantly between ATT and Combustion scenarios. ATT shows more favourable environmental performance with lower emissions to air, land and water. In addition, ATT has lower building and average stack heights, indicating that this technology (represented by the Compact Power design) has a lower visual impact over combustion. The data also suggests that ATT is also less expensive on a net cost per tonne basis and use of land. Combustion seems only to be superior to ATT at all scales on its displaced fossil fuel CO2 emissions and its technical maturity. The trade-off that ATT designers face between achieving high environmental performance, but at the cost of low energy efficiencies is discussed by Malkow, 2004.

The MCDA model weightings were supplied by individual WDA officers representing the fields of waste policy, sustainability, energy management, environmental management and planning in their respective councils. The cumulative weightings obtained for each criterion are shown in Table 4, together with the mean and standard deviations across officers. In the case of both counties, the highest mean cumulative weightings were 14.6% (Cornwall) and 12.2% (Warwickshire) and were allocated to the ‘‘net carbon dioxide savings’’ from electricity generation. This criterion also showed the greatest inconsistency in weighting with s ¼ 9.2 and 4.8, suggesting differing concerns about the effects of climate change. The second most heavily weighted criterion in both counties was ‘‘health of the local community’’ (measured by dioxins produced) with cumulative weights of 11%. Community perceptions of risk, especially regarding health, can have a major effect on the extent of local opposition (Loosemore et al., 2006) despite attempts of several studies to reassure the public that modern incineration poses very little risk (Enviros et al., 2004). The next most heavily weighted criteria were ‘‘Net cost per tonne’’ (of MSW processed), ‘‘Flexibility’’ and ‘‘Technical maturity’’. These reveal a high level of monetary awareness and officers’ regard for the need to carry forward cost-effective solutions that have a good track record. The least weighted criteria in both counties

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Table 3 Individual criteria scores for each scenario used in MCDA model Criteria

Indicator

Scenarios Warwickshire

Lorry traffic impact on local communities Jobs created Health of local community Community ownership Plant emissions to air Plant emissions to land Plant water discharges to sewer Scenario site footprint Individual plant site visual impact

Displaced fossil fuel carbon dioxide emissions Total external costs of waste road transportb Net cost per tonne processed Cost of WTS and road transport of wastec Technical maturity Flexibility and strategic value

Cornwall

L SC

M SC

Loc SC

MS ATT

Loc S ATT

L SC

M SC

Loc SC

MS ATT

Loc S ATT

Deliveries per site per day

62

27

19

27

19

49

28

21

28

21

Full time Dioxins ITEQ ng/Nm3 District allocated

47 0.03

69 0.03

91 0.03

66 0.003

90 0.003

47 0.03

69 0.03

80 0.03

66 0.003

78 0.003

20

60

100

60

100

17

50

67

50

67

233

233

233

44

44

233

233

233

44

44

46.2

44.5

44

25.9

21.5

46.2

44.5

44.3

25.9

23.7

40.5

40.5

40.5

18.8

18.8

40.5

40.5

40.5

18.8

18.8

2.73

4.13

5.89

2.9a

3.0a

2.73

4.13

5.0

2.9a

3.0a

33

20

20

10

10

33

20

20

10

10

89

60

60

25

21

89

60

60

25

23

23.7

20.2

18.9

12.8

12.8

23.7

20.2

19.5

12.8

12.8

£k/annum

312

178

122

178

122

506

372

332

372

332

£/tonne

51

79

84

59a

67a

51

79

85

54a

59a

£ million/annum

1.097

0.526

0.208

0.526

0.208

2.546

1.489

1.353

1.489

1.353

No of operational plant in UK No of plants in scenario

19

19

19

0

0

19

19

19

0

0

1

3

5

3

5

1

3

4

3

4

Monitored emissions (mg/ Nm3) Bottom ash and fly ash (ktpa) ktpa

All sites total (ha) Building height average (m) Chimney stack average (m) CO2 (ktpa) elec gen only

a

Data available solely from commercial source. Based on £0.51 per mile traveled from the (Strategic Rail Authority, 2003). c Does not include collection costs, solely transit. Costs of owning and operating WTS at £6.35/t. Cost of road transport at £1.91 ton/mile from the (USEPA, 2002) (inflated to 2006 prices). b

include ‘‘Individual plant site footprint’’, ‘‘Plant emissions to land’’ and ‘‘Plant water discharges’’ indicating that officers are generally satisfied with these aspects of modern EfW technology performance. ‘‘Community ownership’’ also was given a low weighting which may reflect a generally low level of understanding of the concept (CSE, 1997) and how this may apply to EfW facilities. To the authors’ knowledge, the latter has not been attempted in the UK to date, but has been applied in Denmark (Kristiansen, 2006). The term ‘‘Community scale’’ has

been used to describe a 60 ktpa plant in Lincolnshire, UK (Club recycle, 2005). The ‘‘emissions to air’’ criteria represented a medium weighting and reflects that this criteria is still of considerable importance despite the use of modern air pollution control (APC) technologies and regulation by the Waste Incineration Directive (WID) (DEFRA, 2004). Other medium range weights were given to ‘‘Costs of WTS and road transport’’ and ‘‘External costs of road transport’’. This indicates that officers understand the importance of

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Table 4 Individual officers’ cumulative weightings Criteria

Cornwall

Warwickshire

Officer 1 Social Health of local community Jobs created Lorry traffic impact on local communities Community ownership

s 2

Mean

3

Officer 1

2

3

4

5

s

Mean

9.6 5.8 7.7 1.9

8.3 1.7 8.3 1.7

15.1 4.5 11.3 7.5

2.9 1.7 1.6 2.7

11.0 4.0 9.1 3.7

5 3.3 7.4 8.3

13.7 8.2 11 4.1

11.5 6.9 8 5.7

11.9 8.4 4.8 11.9

11.8 4.7 7.1 7.1

3.0 2.0 2.0 2.6

10.8 6.3 7.7 7.4

Economic Technical maturity Flexibility and strategic value Net cost per tonne processed Cost of WTS and road transport

7.4 10.7 9.3 7.4

17.9 5.1 6.3 5.1

5.1 9.3 5.7 7.1

5.6 2.4 1.6 1.0

10.1 8.4 7.1 6.5

11.8 8.2 10.5 9.5

8.8 5.3 12 3.6

8 8 9.5 6.6

5.8 5.8 7.2 7.2

6.5 7.2 9.5 7.6

2.1 1.2 1.6 1.9

8.2 6.9 9.7 6.9

Environmental Individual plant site visual impact Individual plant site footprint Plant emissions to land Plant emissions to air Plant water discharges to sewer Net carbon dioxide savings External costs of road transport

7.8 5.2 2.6 12.9 1.3 4.5 7.4

5.7 4.6 4 4 4 12.7 5.1

3.2 1.3 0.6 0.6 0.6 26.7 5.3

1.9 1.7 1.4 5.2 1.5 9.2 1.0

5.6 3.7 2.4 5.8 2.0 14.6 5.9

3.9 7.8 3.9 3.9 1.6 6.1 8.7

1.3 2.1 4.3 4.3 4.3 9.5 7.6

3.2 2.8 2.8 4 4 9.9 8.9

2 1.7 3.4 3.4 3.4 19.3 3.9

2.7 1.1 2.7 5.3 2.7 16 8

0.9 2.4 0.6 0.6 1.0 4.8 1.8

2.6 3.1 3.4 4.2 3.2 12.2 7.4

Table 5 Final overall weighted MCDA scores WDA

Weighting

Scenario L SC

M SC

Loc SC

M S ATT

Loc S ATT

Cornwall

Officer 1 Officer 2 Officer 3 Mean score

22 37 39 33

34 46 50 40

38 49 55 47

53 44 55 51

58 48 60 55

Warwickshire

Officer 1 Officer 2 Officer 3 Officer 4 Officer 5 Mean score

29 28 27 35 30 30

43 40 41 47 43 43

54 48 52 58 53 53

45 51 51 54 52 51

59 61 63 67 64 63

minimising waste transport impacts and related costs in any waste management strategy (Gershman et al., 1986). Table 5 shows the final overall weighted scores for each scenario. For Cornwall, the mean results ranked local ATT best, followed by medium ATT and then local combustion in third place. At the individual level, Officers 1 and 3 followed a similar pattern, but Officer 2’s results presented an alternative set of scores ranking local combustion first, followed by local ATT, and medium ATT, respectively. For Warwickshire, the mean results ranked local ATT first, followed by local combustion and lastly medium ATT. This pattern of results was the same for individual officers, except one officer who ranked medium ATT second, after local ATT, with local combustion ranked third.

All officers from both counties ranked medium and large combustion scenarios in 4th and 5th rank, respectively. The large combustion scenario is the typically followed, EfW policy in the UK to date. It is interesting to note that the geographically based scores such as those of transport, where Cornwall showed a significantly higher road impact than Warwickshire did not influence the overall results, both areas indicating that small-scale EfW options are preferred. This can be explained by the relatively low weightings officers placed on these criteria. However, as transport impact is relatively low in local and medium scenarios, a higher weighting would only have increased their preference score over the large centralised scenario.

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5. Discussion It is interesting to note that ATT outperforms combustion at the same scale in all but one officer’s final score. It is perhaps unfortunate, that at present there are no existing examples of a fully commissioned facility at the relevant scales in the UK, but this is expected not to be the case by 2007 (Club recycle, 2006c). The model suggests, however, that this technology has great potential for the near future. Fig. 2 shows a typical example of how each criterion contributes to the final score for each scenario (Warwickshire, Officer 3). The ATT scenarios outperform combustion scenarios overall and attract merit against a larger number of criteria, notably in the environmental categories. The largest factor in their superior final score, however, is the contribution of the criterion—‘‘Health of local community’’, measured by dioxin emissions (see Table 3). This result might reasonably be challenged on the grounds that the dioxin emission values for both technologies, while different, are both significantly below the already strict emission limit of 0.1 ng/Nm3 set by WID, therefore, the scores could be regarded as the same. On this basis the overall scores for the two technologies illustrated in Fig. 2 would end up almost identical. Regarding scale, (but not technology), local and medium-scale plants, spread the social and environmental

impact in a more equitable manner, and attract score contributions from these criteria. Smaller-scale facilities show advantages in road transport, cost of operating waste transfer stations (WTS), potential for community ownership, and of a more flexible strategy, in the sense that capacity can be increased in smaller increments over time if necessary. In contrast the large combustion scenario receives contributions from just six criteria. It should be noted, however, that the highest scores appear in four of these, namely ‘‘Technical maturity’’, ‘‘Net cost per tonne’’ (deriving from economies of scale), ‘‘Displacement of fossil fuel-derived CO2 emissions’’ (again from superior electrical efficiency) and ‘‘Individual plant site footprint’’ (indicating the lowest amount of land area required). The latter three points derive from the effects of scale. At larger scale, it becomes more cost-effective to invest in plant features designed to raise efficiency, and major plant items such as steam turbines are inherently more efficient as scale increases (Cole, 1991; Porteous, 2005). A limited contribution comes from job creation. The criterion ‘‘displaced fossil fuel CO2 emissions’’ considers only electricity generation and not the supply of heat in CHP mode. This is at present, a deficiency in the model, but it is expected that smaller-scale facilities are more likely to be successfully deployed in a CHP role. This is illustrated in a recent survey, from which the authors identify that 72% of all 1 MWe and above UK CHP plants

Fig. 2. Criteria contribution to MCDA overall scores.

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were between 1 and 10 MWe output (23% were greater than 10 MWe). The rates of the increase in numbers of 1–10 MWe plant commissioned between 1996 and 2004, has also been higher than their larger counterparts (DTI, 2005). Large-scale CHP is especially difficult in non-urban areas, where sufficient demand for the heat must be found. Indeed in CHP schemes it is usually the heat demand that defines the parameters of the project. Generally, smaller heat loads with a suitable profile are more easily found than large ones, and require proportionately less investment (Beggs, 2002). In light of the results in Table 5 (which apply only to the counties considered), it is at first sight surprising that the majority of WDAs have rejected small-scale distributed facilities in favour of large-scale centralised ones. This appears to be because in real decisions, decision makers place far higher weights on the investment cost of the facility and on technical risk than the officers have done in this academic exercise. Interestingly, these factors are strongly linked to political risk (Paynter, 2006). This riskaverse attitude to new and emerging technology is understandable when WDAs can be fined at £150 per tonne if they exceed their landfill allowances (Eminton, 2005). Another reason might be that planners have not considered in their decision-making process the cost savings that can accrue from reducing waste transport distances and closing waste transfer stations or revenues from the sale of heat and steam. The advantages of the large-scale combustion EfW option may, therefore, have been overstated by some

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authors, who only present their argument in terms of displaced CO2 emissions from electricity generation and net cost per tonne processed or similar monetary indicator (Patel, 2005). It is clear that on these criteria, large facilities will nearly always be superior to small ones due to scale economies, although some authors state this superiority is often over-perceived and marginal by net present value calculations across project lifetimes (Kristiansen, 2006). Fig. 3 shows the model result for Warwickshire Officer 3 when the effect of social criteria along with ‘‘Flexibility and strategic value’’ and ‘‘Cost of WTS and road transport’’ criteria have been removed, by assigning them a zero weighting (note that the weighting for external costs of transport has been retained). This may more closely match decision-making processes in real situations. The new system of weights provides a large cumulative weight for ‘‘Net cost per tonne’’ (29%) and ‘‘Technical maturity’’ (26%). The overall scores in Fig. 3 now show that the large combustion scenario is superior to scenarios involving smaller scales of plant. The important point to note is that the overweighting of just two criteria (over 55% of all weighting in the model) and the omission of other possibly important criteria could change the selected policy. This could be criticised as a narrow basis for decision-making. It is clear, however, as is often found in MCDA, that the result is vulnerable to error in that the specified weightings may not accurately reflect the real situation. However the essential value of MCDA is in demonstrating that an

Fig. 3. MCDA results with bias towards economic and technical risk criteria.

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auditable and transparent method has been followed in decision-making. Weightings and scores can be independently reviewed and subjected to sensitivity analysis (Nilsson et al., 2005). The standard deviations of the weightings in Table 4 show that the planning officers are far from agreement on the importance of individual criteria in the process of formulating EfW policy. The attractiveness of local-scale scenarios revealed here may not be universal—it is possible that large-scale systems, regardless of technology, may make the largest contribution in terms of social, environmental and economic criteria in urban conurbations, for example, where waste arising is dense, transport distances are short and there are significant local opportunities for heat demand. More research is required to investigate this. Relating these observations to the real world of UK EfW decision-making and other non-case study WDAs, it is interesting to note that while Cheshire County Council are considering a regional large-scale EfW policy for reasons of efficiency and financial cost, (Club recycle, 2006a), Surrey have already had to abandon such a policy because of planning failure for a large-scale combustion facility, and are currently carrying out a consultation on the number and type of small or medium scale plants required to replace the large-scale proposal (Club recycle, 2006b). Other cancelled or delayed UK large-scale EfW projects at the time of writing include Norfolk (Faulkner, 2006b), Belvedere (Faulkner, 2006a) and Aberdeen (Club recycle, 2004). A multi-criteria analysis such as that presented here might have saved much time, effort and money. 6. Conclusions 6.1. Model results For the counties considered, this study concludes that the local-scale distributed EfW scenarios are the most attractive overall, followed by the medium-scale options and lastly the large-scale centralised option. The local-scale scenarios have the lowest transport costs, and are superior in terms of the social criteria and some environmental criteria. They also provide greater flexibility in managing changes in residual waste availability and demand for recycling, since they can be commissioned in a more stepwise manner, gradually releasing capital expenditure. The large-scale centralised scenarios however, have superior net cost per tonne of waste and superior CO2 emission displacement if electricity generation only is considered. This may not be the case if CHP is considered in the local scenarios, since heat demands can be more easily met. In terms of technology, the ATT facilities (based on the Compact Power design in this study) are superior overall to combustion ones of similar scale. However, these technologies are not yet established in the market. Furthermore this conclusion is influenced to a large extent by dioxin emission performance, the weighting of which is controversial. Choice of technology is in any case, less important

than issues of scale and site locations in determining overall EfW policy impact. 6.2. Policy implications To increase chances of success in EfW development, UK WDAs should adopt a flexible decision-making approach that can take into account the full cost and benefits of several EfW solutions tailored specifically for the WDA area. The latter should include a full assessment of distributed local and medium-scale scenarios, considering issues including the operation of WTS, lorry road transport, potential for local heat use and electrical grid connections. Assessment should not focus purely on the project economics and the technical maturity of EfW technology, but should take full account of overall sustainability. EfW planning should be backed up by decision-assistance tools, which are transparent and can be easily updated as new technologies (and options) become available. With such an approach, EfW projects may begin to experience fewer failures and delays in the planning process. EfW can then start to make a significant contribution to sustainable development in the UK, meeting landfill diversion, renewable energy and energy efficiency targets. Acknowledgements The authors wish to thank the officers of Warwickshire and Cornwall County Council who participated in this project—particularly Jonathan Horsfield, Anthony Weight, and to Tony Holmes for the supply of GIS data and feedback. Also to David Sweeting and Jon Beswick for their data inputs and advice regarding the Compact Power ATT systems. GIS electrical grid data for Warwickshire were contributed by Central Networks plc. References Aeat, 2005. Renewable Heat and Heat from Combined Heat and Power Plants—Study and Analysis. DTI & DEFRA, London. Ares, E., Bolton, P., 2002. Waste Incineration, House of Commons Library. House of Commons, London. Ayres, R.U., Ayres, L., Martinas, K., 1998. Exergy, waste accounting, and life-cycle analysis. Energy 23, 355–363. Azapagic, A., Camana, D., 2005. Municipal solid waste as an energy resource: mass-burn incineration of small-scale pyrolysis. In: Proceedings of the Seventh World Congress of Chemical Engineering, Glasgow, UK. Barda, O., Dupuis, J., Lencioni, P., 1990. Multicriteria location of thermal power plants. European Journal of Operational Research 45, 332–346. BBC, 2004. Changing Places: BAN Waste, London. Beggs, C., 2002. Energy: Management, Supply and Conservation. Butterworth-Heinemann, Oxford. Bergsdal, H., Stromman, A., Hertwich, E., 2005. Environmental assessment of two waste incineration strategies for central Norway. International Journal of LCA 10, 263–272. Biffa, 2002. Future Perfect—Available tools logistics technologies.

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