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Selecting sustainable waste-to-energy technologies for municipal

solid waste treatment a game theory approach for group

decision-making

Atousa Soltani Rehan Sadiq Kasun Hewagea School of Engineering University of British Columbia 1137 Alumni Avenue Kelowna BC V1V 1V7 Canada

a r t i c l e i n f o

Article history

Received 14 April 2015

Received in revised form

30 November 2015

Accepted 1 December 2015

Available online 23 December 2015

Keywords

Sustainability

Municipal Solid Waste Management

(MSWM)

Game theory

Analytical hierarchy process (AHP)

Group decision-making

a b s t r a c t

An ef 1047297cient waste treatment strategy should be cost-effective and minimize potential impacts on various

stakeholders and the environment This study proposes a decision framework that can model the

stakeholders con1047298icting priorities over the sustainability criteria when selecting a municipal solid waste

treatment option The proposed framework compares life cycle sustainability impacts of selected options

and develops a weighing scheme for combining impacts based on stakeholders preferences It then uses

game theory to help the stakeholders fairly share the costs and bene1047297ts and guides the stakeholders to

reach an agreement on a mutually sustainable and pragmatic solution In this study the application of

the framework to select a waste-to-energy technology for Vancouver Canada is demonstrated The case

study discusses the prospect of producing refuse-derived fuel by cement industry and the municipality

Results show that the cement industry and the municipality may mutually bene1047297t from the refuse-

derived fuel if the industry pays a tipping fee of $0077e096 per kg waste to access the required

amount of solid waste from the municipality The outcome of the framework can help in the approval

and application of an overall sustainable option by both stakeholders and in making the negotiation

more ef 1047297cient and timely

copy 2015 Elsevier Ltd All rights reserved

1 Introduction

Municipal Solid Waste (MSW) is de1047297ned as ldquorefuse that origi-

nates from residential commercial institutional demolition land

clearing or construction sourcesrdquo in the Environmental Management

Act (The Government of British Columbia 2015) The generation of

MSW has doubled globally in the past decade and it is anticipated

to triple in the next decade (The World Bank 2012) In 2012 one in

eight deaths worldwide were linked to air pollution a consequence

of unsustainable policies in transport energy and waste manage-ment sectors (WHO 2014) In 2008 Canada disposed1 of 777 kg of

MSW per capita the third highest amount in the world and the

highest amount among the developed countries (Hoornweg and

Bhada-Tata 2012) (Fig 1) Canadians disposed of about 25 million

tonnes of MSW (720 kg per capita) in 2012 with the province of

British Columbia (BC) making up to 10 of that share ( Statistics

Canada 2015)

Municipal Solid Waste Management (MSWM) is a complex

process that requires group decision-making on selecting waste

collection routes transfer stations and treatment locations and

strategies from various available options (Dewi et al 2010 Soltani

et al 2015) The selection of a treatment strategy is one of the most

debated issues in the literature and is the core of MSWM ( Achillas

et al 2013) Waste treatment strategies often comprise land1047297lling

and waste-to-energy (WTE) technologies An optimal waste treat-ment strategy is a result of prudent and scienti1047297cally justi1047297able

decision-making that minimizes the risks to the environment and

human health and maximizes cost ef 1047297ciency (Sadiq 2001) A

sustainability paradigm looks for a waste treatment strategy that

ldquomeets the needs of the present without compromising the ability

of future generations to meet their own needsrdquo (Brundtland 1987)

In the context of MSWM sustainability refers to the assessment of

environmental economic and social impacts of available waste

treatment options Sustainable waste management aims to reduce

waste generation re-use and recycle waste materials and recover

energy to ultimately preserve resources for the future Recovering

Corresponding author

E-mail address Atousasoltanialumniubcca (A Soltani)1 The disposed waste refers to the amount of generated waste after diversion and

recycling

Contents lists available at ScienceDirect

Journal of Cleaner Production

j o u r n a l h o m e p a g e w w w e l s e v i e r c o m l o c a t e j c l e p r o

httpdxdoiorg101016jjclepro201512041

0959-6526copy

2015 Elsevier Ltd All rights reserved

Journal of Cleaner Production 113 (2016) 388e399



energy from disposed waste can generate power for municipalities

offer fossil fuel substitutes to industries and reduce greenhouse

gases and other hazardous pollutants (Metro Vancouver 2014a)

There are various sustainability assessment frameworks and

tools available for calculating environmental impacts (eg life cycle

assessment (LCA) (the International Organization for

Standardization (ISO) 2006a) environmental risk analysis

(SETAC 2004) environmental impact assessment (Canter 1977))

and net economic costs (eg life cycle costing (LCC) (Blanchard

et al 1990)) In addition there are numerous frameworks for

comparing the performances in one criterion to another and

1047297nding a balance A multi-criteria decision analysis (MCDA)

framework provides different methods that can help decision-

makers to 1047297nd a suitable trade-off amongst these criteria andchoose an option with the lowest overall impacts (Soltani et al

2015) While LCA and LCC are effective in accounting for the im-

pacts of waste treatment options throughout their life cycle MCDA

methods are required to aggregate their outcomes

Meanwhile waste treatment for achieving sustainability goals is

even more complex when multiple stakeholders with con1047298icting

interests are involved In Canada collection diversion (ie reuse

recycling and composting) and disposal of waste are generally

handled by the municipal governments (Environment Canada

2012) In addition to the municipal government multiple stake-

holders such as NGOs environmental experts general public and

industries affect policies and decisions related to MSWM Soltani

et al (2015) provided a state-of-the-art review with respect to

multiple stakeholders involvement in MSWM in which munici-palities and experts were found to be involved in decision-making

more than other stakeholders

Waste treatment often creates a situation where the munici-

pality bears all the costs of waste treatment while other stake-

holders bene1047297t from it without contributing to the costs this

situation is known as the lsquofree-riderrsquo problem The municipality is

responsible for providing the public goods and services such as

waste treatment and ends up paying the associated costs The free-

rider problem can discourage the municipality from choosing the

more advanced and more expensive technologies or can result in

the over-using of the provided service A solution to this problem is

to involve other stakeholders in the decision-making and execution

process Other stakeholders will be encouraged to contribute to-

wards the relevant costs of sustainable waste treatments if

municipalities combine these services with other in-demand ser-

vices (Carraro and Marchiori 2003) Using WTE technologies for

waste treatment mitigates the free-rider problem by offering

cleaner energy solutions to industries and encouraging them to pay

for the recovered energy and materials but to make this feasible

the municipality and industry should 1047297rst negotiate their fair share

of costs and bene1047297ts to mutually agree on a WTE technology

Hence effective waste management should evaluate stakeholders

dialogues in addition to technical assessments (Achillas et al

2013)

This study proposes a decision framework to help multiple

stakeholders reach an agreement on a ldquosustainablerdquo waste treat-

ment option and share the associated costs and bene1047297ts in a fair

and mutually acceptable way This framework is especially helpfulfor using WTE technology where often various stakeholders get

involved This research aims to 1047297ll the gap in the literature on

choosing the most sustainable and pragmatic waste treatment

option when stakeholders have con1047298icting priorities

2 Background information

In this section components of the proposed framework

including sustainability assessment tools waste treatment options

and decision analysis methods are discussed in more detail

21 Sustainability assessment tools

A sustainability paradigm helps in choosing building or offer-

ing products and services that conserve resources such as money

water soil air and humans in an acceptable balance Sustainability

assessment tools such as LCA and LCC can evaluate the environ-

mental impacts and economic costs and bene1047297ts of selected MSWM

options

211 Life cycle assessment

LCA is a popular method that helps experts estimate environ-

mental burdens of products processes and services throughout

their life (USEPA 2006) LCA identi1047297es and quanti1047297es inputs and

outputs to a system including materials energy waste and

pollution (SETAC 1993) According to the ISO 14040 and 14044

standards LCA consists of four general steps (ISO 2006a 2006b)

Fig 1 Ten countries with the highest disposal of MSW per capita in 2008 (derived from D-waste (2015))

A Soltani et al Journal of Cleaner Production 113 (2016) 388e 399 389



1 Goal and scope encompass system boundary functional unit

criteria under study available options and involved stake-

holders The system boundary is the section of the life of a

product or service that is considered in the LCA Waste

treatment is often the end-of-life process for products but in

waste management studies the life of a disposed waste is

often from the collection point to the waste treatment plant

land1047297ll and even the re-using destination The functional

unit is the homogenous unit of waste for which all impacts

are estimated The criteria are directly connected to the goal

of the study In sustainable waste management these

criteria include environmental economic and e when

available e social criteria The available options are the al-

ternatives that are being compared based on the selected

criteria and the stakeholders are the agents or individuals

that are impacting or being impacted by the outcomes of

these assessment

2 Life Cycle Inventory (LCI) is a collection of all materials energy

and discharges entering a system boundary or released to land

water and air To develop the LCI a 1047298ow chart of input and

output materials and discharges from and to the system

boundary is initially displayed SimaPro is a comprehensive tool

for collecting data and analyzing the impacts of various productsand services with access to various databases (eg ecoinvent

Agri-Footprint European reference Life Cycle Database and US

Life Cycle Inventory Database)

3 Life cycle Impact Assessment (LCIA) groups the inputs and

outputs collected in LCI under environmental impact categories

based on their potential hazards to human health and the

environment LCIA usually includes the following steps selec-

tion of impact categories classi1047297cation characterization

normalization grouping weighting and reporting the results

(USEPA 2006) Based on the ISO standards 14040 and 14044 for

Life Cycle Impact Assessment and their technical report ISOTR

14047 the most common environmental impact categories are

abiotic depletion (depletion of resources) stratospheric ozone

depletion summer smog (photochemical oxidation or photooxidant formation) acidi1047297cation human toxicity and ecotox-

icity (terrestrial and aquatic) (ISO 2006a 2006b 2012) SimaPro

can present both mid-point and end-point impacts using

different impact assessment methods (eg CML-IA EDIP ILCD

ReCiPe BEES and TRACI) SimaPro also follows different studies

to develop the default characterization factors (eg Intergov-

ernmental Panel on Climate Change for climate change impact

category) A list of all characterization models can be found in

PRe (2015)

4 Interpretation of results is the last step which includes expla-

nation of the outcomes by experts

Since LCA does not consider economic or social impacts of a

product or process LCC is often suggested to be used in parallelwith LCA in a sustainability assessment (Gluch and Baumann

2004)

212 Life cycle costing

LCC sums up the monetary values of costs and bene1047297ts from all

stages of the life of a product or service in a system boundary

(Gluch and Baumann 2004) Common costs include investment

operation and borrowing costs while bene1047297ts include sale reve-

nues (Carlsson Reich 2005) Various methods are used to perform

LCC in waste management studies including Net Present Value

(NPV) (Carlsson Reich 2005) equivalent annual cost (Tsilemou and

Panagiotakopoulos 2006) and internal rate of return (Caputo et al

2003)

In this paper NPV method is proposed to consider the time

value of money Future costs and bene1047297ts (recurrent or one-time)

are discounted to present values using equation (1)

NPV frac14Xn

t frac140

NFV eth1 thorn r THORNt (1)

where NPV is the present value of net economic cost NFV is the netfuture costs r is the real interest rate t is time and n is the total

number of periods

It should be noted that decision-making solely based on the

outcomes of LCC will end in subjective decisions that overlook the

environmental dimension (Gluch and Baumann 2004) Many social

impacts can also be considered through economic assessment (eg

employment neighbourhood land prices etc) There are various

quantitative and qualitative methods for evaluating social impacts

(Refer to a review by Chhipi-Shrestha et al 2014) Although these

methods are not further discussed in this study the following sub-

criteria can be considered for social assessment of waste treatment

options

- Proximity to residential area (eg Noise Odour (Den Boer et al

2007))

- Workers and neighbourhoods safety (Sheppard and Meitner

2005)

- Employment (Den Boer et al 2007)

- Affordability

- Public acceptability

- Land use (Den Boer et al 2007)

22 Waste-to-energy technologies

Among all MSWM stages waste treatment is often the main

path toward the protection of the environment and human health

and growth of the economy (Soltani et al 2015) In recent years

waste treatment is facing new constraints as a result of limitedspace for land1047297lls increasing opportunity cost of disposed waste

and strict environmental regulations (Reza et al 2013) The

objective of sustainable assessment in the waste context is to

reduce environmental impacts and economic costs of waste treat-

ments while being aware of their social effects and eventually

create a balance between these outcomes Recovering energy from

waste is a more advanced strategy that conceives of waste as an

opportunity rather than a liability

WTE technologies recover energy in the form of heat electricity

or steam and retrieve bottom ash and metal from disposed waste

Various WTE technologies areas follows (Metro Vancouver 2014a)

1 Mass-burn incinerations are the most commonly used WTE

technology In mass-burn incineration waste is directly com-busted after mild or moderate pre-processing to produce elec-

tricity In this study WTE options refers to mass-burn

incineration

2 Gasi1047297cation and pyrolysis convert waste to syngas or vapour to

generate electricity and heat

3 Co-combustion of Refuse-derived fuel (RDF) in a cement kiln is

another use of WTE technology in MSW treatment that sub-

stitutes fossil fuels with RDF in the production process of

cement RDF is a solid fuel recovered from high-calori1047297c value

fraction of MSW (Genon and Brizio 2008 Reza et al 2013) To

produce RDF MSW undergoes some or all of the following

stages sorting or mechanical separation shredding screening

blending and pelletizing (Gendebien et al 2003) The extent of

environmental impacts and economic net costs of RDF depends

A Soltani et al J ournal of Cleaner Production 113 (2016) 388e 399390



on MSW composition in the region and recovery rate but

substitution of fossil fuels in an energy-intensive industry such

as cement with RDF will de1047297nitely reduce greenhouse gas

emissions and mitigate many environmental concerns (Reza

et al 2013)

23 Decision analysis

The 1047297rst step in selecting a sustainable waste treatment strategy

is to calculate the total impact of all options on the stakeholders

Many frameworks and methods have been developed to combine

the results of environmental and economic assessments (eg en-

ergy and material intensity metrics (Schwarz et al 2002) sus-

tainability accounting (Bebbington et al 2007) MCDA (Contreras

et al 2008) and monetized ecological footprints (Sutton et al

2012)) MCDA the most popular among these frameworks is a

collection of various methods that analyzes multiple criteria and

helps decision-makers to rank or select acceptable options or to

choose one optimal option Finding a balance among the criteria is

an important part of sustainable development (Neugebauer et al

2015) Since impact assessments are presented in different units

and the value of impacts in one criterion is different from the otherones using MCDA is necessary to present a uni1047297ed sustainability

index In addition for deciding on investment opportunities in

waste treatment the concept of MCDM is more helpful than relying

solely on life cycle assessments (Spengler et al 1998)

However to use MCDA methods stakeholders should 1047297rst agree

on the criteria of interest and the importance of each criterion in

comparing the available options (Van den Hove 2006) If stake-

holders have con1047298icting priorities over criteria reaching an

agreement is likely to be challenging (De Feo and De Gisi 2010)

MCDA techniques aggregate the impacts on stakeholders but fall

short on considering stakeholders con1047298icts and their in1047298uences on

each other in reaching a mutual decision Game theory on the other

hand is a natural choice for analyzing the trade-offs between

environment and economy and considering stakeholders con1047298ictsand dialogues (Moretti 2004)

231 Analytical hierarchy process (AHP)

AHP is a common MCDA technique that offers a mathematical

solution for presenting preferences by using a pairwise comparison

of criteria (Hossaini et al 2014 Sadiq 2001) AHP can help experts

assign weights to various criteria aggregate impacts from those

criteria and compare MSWM options accordingly There are 1047297ve

steps in AHP (Saaty 1980)

- Present the problem in a hierarchy of goals criteria and

alternatives

- Collect data on available options and criteria of interest

- Generate a weighting system for criteria through pair-wisecomparison

- Rank alternatives by aggregating scores and weights

- Perform a sensitivity analysis to validate the data and mitigate

uncertainty

In AHP the outcomes of pairwise comparisons are presented in

a priority matrix and developed into a set of ldquopriority ratio scalerdquo

(Hossaini et al 2014 Sadiq et al 2003) In Matrix A [Eq (2)] each

entry aij shows on what scale criterion i is preferred to criterion j

(Hossaini et al 2014) The advantages of the pairwise comparison

technique in AHP include its ease of use and understandability for

non-expert users AHP is also the most common method in waste

treatment studies with multiple stakeholders Saatys 9-scale is

often used to compare the criteria verbally (Table 1) (Saaty 1988)It

is important to be consistent with the scale in pairwise

comparisons

A frac14

24

1 hellip a1n

hellip 1 hellip

an1 hellip 1

35 (2)

Weights are often developed from a priority matrix using

various mathematical approaches such as eigenvector geometric

mean and arithmetic mean which are believed to present similar

results and not be signi1047297cantly different (Hossaini et al 2014)

Assuming that matrix A shows the relevant importance of each

criterion against the other ones the multiplication of A and W(weight matrix) results in a scalar multiple of W (Saaty 1994) The

scalar value (Eigenvalue) and W (Eigenvector) are calculated using

equation (3) Once weights are developed their consistency should

be examined The values in a matrix are consistent where each

entry aij frac14 wi=w j (wi is the weight of criterion or sub-criterion i

ethPn

ifrac141wi frac14 1)) (Tesfamariam and Sadiq 2006)

AW frac14 lW (3)

Although AHP is more convenient and effective it suffers from

the same shortcoming as other MCDA techniques in considering

con1047298icts in priorities in a group decision-making process (Tseng

et al 2009) A few studies in the literature have offered solutions

for con1047298icts among stakeholders (eg Munda 2002 van den Hove

2006) but lsquogame theoryrsquo is more suitable in choosing among waste

treatment options Game theory can model different types of in-

teractions among stakeholders and predict the outcomes of

negotiations

232 Game theory

Game theory studies self-interested2 stakeholders when they

interact in a series of games (Leyton-Brown and Shoham 2008)

What makes game theory versatile is its use of mathematical

modelling to understand human interactions Game theory is based

on the fact that satisfaction of each stakeholder can change in

response to other stakeholders actions as well as their own Games

are portrayals of actions that players are interested in and can do

while solutions present the actions they do take (Osborne and

Rubinstein 1994)In a two-player game game theory 1047297rst gathers the information

on stakeholders utilities (or net bene1047297ts) from each pair of actions

(eg how much will each stakeholder bene1047297t if stakeholder 1

chooses action a and stakeholder 2 chooses action b) Based on the

type of decision-making problem this information is then por-

trayed in a decision tree or a table Although each stakeholder

might choose an optimal option when deciding individually game

theory looks for solutions that are stable in a mutual setting In this

setting stakeholders answer a series of ldquowhat if helliprdquo questions

Table 1

Saatys 9-scale (Saaty 1988)

Scale Verbal de1047297nition

1 Equal importance

3 Moderate importance

5 Strong importance

7 Very strong or demonstrated dominance

9 Extreme importance or strongest af 1047297rmation

2 4 6 8 Intermediate values

2 Self-interested here means that stakeholders prefer some situations to other

situations (or states) and they will act toward making those situations happen

(Leyton-Brown and Shoham 2008)




before 1047297nalizing their decision These questions are often asking

whether they would change their decision if the other stakeholder

chooses any of the possible options

When WTE technologies are proposed for a region municipal-

ities and industry need to share costs and bene1047297ts in a way that

satis1047297es both of them In many studies (eg McGinty et al 2012

Weikard and Dellink 2008 Finus 2000 Kaitala and Pohjola

1995) game theory offers solutions for fair distribution of costs

and bene1047297ts among stakeholders to stabilize environmental de-

cisions Game theory is also an effective method for decisions that

require stakeholders collaboration (Nagarajan and Sosic 2008)

There have been only a few studies that used game theory for

waste management decision-making Cheng et al (2002 2003)

applied a cooperative game theory approach to select a new land-

1047297ll site Moretti (2004) proposed a cooperative game theory

method to divide costs of waste collection between municipalities

Joslashrgensen (2010) used game theory for a regional waste disposal

problem Karmperis et al (2013) proposed a framework called the

waste management bargaining game to help players negotiate over

the surplus pro1047297t of various MSWM options More details on

studies with game theory solutions are presented in Table 2 These

studies do not consider stakeholders impacts on each others de-

cisions when interactions are unavoidable These studies also fail toguide stakeholders to reach a mutual agreement by changing their

share of costs and bene1047297ts

3 Proposed framework

This study proposes a decision framework to address the chal-

lenges of choosing a mutually sustainable waste treatment strategy

when the stakeholders have con1047298icting preferences This decision

framework aims to help the main stakeholders the municipality

and industry to reach a mutual agreement on a sustainable and

pragmatic waste treatment option In this framework game theory

complements AHP LCA and LCC to model the dialogues among

stakeholders and guide them to reach a sustainable solution Fig 2

presents a schematic of the proposed framework for waste treat-ment options Production and co-combustion of RDF in cement

kilns in Metro Vancouver Canada is chosen as a case study to

demonstrate the proposed framework

31 Scope de 1047297nition

The 1047297rst step in the proposed framework is to de1047297ne the scope

of the study namely the objectives and scenarios The objective of

this study is to compare the available waste treatment options in

municipalities and then guide the interested stakeholders to

mutually agree on a sustainable and pragmatic option The sce-

narios are often built according to available and proposed waste

treatment options composition of disposed waste and involved

stakeholders

32 Sustainability assessment

Life cycle assessment and life cycle costing are used as sus-

tainability assessment methods to evaluate the impacts of selected

waste treatment options on each stakeholder The social impacts

are not separately assessed through social life cycle assessment in

this study but if available laboursafety neighborhood land pricing

and political stability due to the decision are among the factors that

can be considered (De la Fuente et al 2015) Other factors such as

pollution changes in employment and impacts on welfare and

market of natural resources can be considered through environ-

mental and economic impacts Although in many investment de-

cisions social factors are often ignored by industry including the

municipality as the main stakeholder with veto power on the 1047297nal

decision helps include social impacts as part of the decision This

study will focus on the environmental and economic impacts but

the framework has the ability to take the outcomes of social impact

assessments (grey area in Fig 2) into the consideration

In the LCA the system boundary is de1047297ned to include all activ-

ities in the life of disposed waste from the disposal of waste at

treatment plants or land1047297ll to mechanical treatment incineration

and recovery of materials (a cradle to gate approach) In the cradle

to gate approach all activities from the extraction of materials

(disposal of waste) to the execution of the project (recovery of

material and energy or land1047297lling of the waste) are considered The

transportation of recovered material and energy to the destination

point is not considered The functional unit is 1 kg of MSW

The in1047298ows and out1047298ows of energy mass emissions and dis-

charges to and from the system boundary are derived using the

European Life Cycle Database (ELCD) in SimaPro 80 software ELCDgathers data on average waste treatment plants and land1047297lls with

leachate control in Europe The inventories are derived for incin-

eration and land1047297lling of 1 kg of waste components such as paper

and plastic in an average treatment plant or land1047297ll in Europe In-

ventories are then adapted to waste composition of the region

under study To perform an impact assessment inventories are

grouped for each impact category RECIPE method for mid-point

impacts is used as a default in SimaPro 80 to aggregate the

Table 2

MSWM studies with game theory solutions

Game

theory

model

PaperAuthors Topic Method Stakeholders Criteria

Location Disposalcollection

Cost-bene1047297t

Municipality Experts Public Wasteindustry

Environment Economy Agriculture Social

Cooperative Cheng et al

(2002)

Cooperative game theory e

MCDA

Cheng et al

(2003)

Inexact linear

programming e MCDA

Joslashrgensen

(2010)

Dynamic cooperative game

theory

Moretti (2004) Cooperative game theory e

Shapley value

Erkut et al

(2008)

Lexicographic miniemax

approach

Karmperis

et al (2013)a Waste management

bargaining game

Competitive Davila et al

(2005)

Grey integer programming

e Zero-sum game

a

Partially competitive and cooperative




impacts under each mid-point impact category These values are

then uni1047297ed and presented for each treatment option

In the LCC it is important to de1047297

ne a scope coherent with thescope of LCA A scheme of all costs and bene1047297ts within the scope of

study is formed and values per functional unit are estimated in

dollars For this study previous data on similar waste treatment

plants experts knowledge and published literature are used to

generate these estimates Costs and bene1047297ts considered in this

framework are presented in Table 3 Opportunity cost is in fact the

bene1047297t that is not achieved as a result of a decision Carbon tax is

the tax that some governments assign to productions and services

with high levels of greenhouse gas emission Operation and

maintenance costs are the values that businesses pay monthly or

annually to achieve a desired level of productivity and these

include salaries rent and maintenance of buildings and equip-

ment Depending on the project under study the transportation

cost can include the costs of trucks and gas from the disposal sta-

tion to the treatment plant Building equipment and land costs are

paid at the beginning of the production process as an investment

Stakeholders earn revenue by selling the recovered material and

energy (as electricity gas etc) If the recovered energy substitutes

fossil fuels the price of the substituted fossil fuels can be consid-

eredas a bene1047297t Sunk costs orcosts that have already beenpaidare

not considered Net economic cost of each treatment option iscalculated for each stakeholder and then presented in dollar value

33 Decision-making for sustainable waste treatment

Once the magnitude of impacts is calculated the AHP method is

used to develop weights and then assign them to environmental

and economic criteria in a two-step hierarchy The 1047297rst priority

matrix is developed from pairwise comparison of environmental

impact categories This matrix shows the signi1047297cance of different

environmental impacts on humans and the environment Although

stakeholders can perform these comparisons on their own the

framework suggests a more consistent and transparent approach

with scienti1047297c proof Tool for the Reduction and Assessment of

Chemical and other environmental impacts (TRACI) The US EPAgathered a well-mixed group of experts industry and municipal-

ities to develop TRACI create the priority matrices and evaluate

weights (Bare 2002) TRACI provides three weighting systems of

Environmentally Preferable Purchasing (EPP) US EPA Science

Advisory Board and Harvard Kennedy School of Government

(Table 4) (Gloria et al 2007) The suggested weighting system in

the framework is EPP as it asks experts to compare the impacts in

short medium and long term and then uses AHP to develop the

weights

In the next level of hierarchy stakeholders are asked to compare

environmental burdens with economic costs to create a priority

matrix (Fig 3) This matrix is designed to show each stakeholders

priority when making a sustainable decision AHP uses this priority

matrix and the eigenvalue method to calculate weights for the

Fig 2 Decision framework

Table 3

Costs and bene1047297ts considered in proposed framework

Costs Bene1047297ts

Opportunity cost Fossil fuel saving

Carbon tax Recovered materials revenue

Operation and maintenance cost Energy revenue (eg Electricity sale)

Transportation cost

Land costs

Building and equipment costs




criteria The overall weights of the impact categories are now

calculated from the weights developed for the environmental cri-

terion and the TRACI weights To estimate the utility of the stake-

holders or sustainability Indices the overall weights (signi1047297canceof criteria andsub-criteria) aremultiplied by impacts (magnitude of

burdens or costs) (5) In this framework a higher sustainability

index means that the waste treatment option is less sustainable for

the stakeholder

Final weight of environmental impact categoryiethweiTHORN frac14 wi we

(4)

Sustainability index ethSITHORN frac14 The weight of criterionethwm or weiTHORN

relevant impact

(5)

Finally the proposed framework uses game theory to model the

dialogues and predict the best option for each stakeholder Thenormal model in the game theory is used for this framework as it

represents simultaneous decision-making when stakeholders have

full information about each other The game is portrayed in a matrix

form with stakeholder 1 in rows and stakeholder 2 in columns

Values in the matrix are sustainability indexes for available and

proposed waste treatment options (Table 5) If equilibrium exists

the outcome of the game will be a pure strategy Pure strategy

selects the most sustainable waste treatment option for each

stakeholder Decisions are stable in the equilibrium point therefore

stakeholders do not bene1047297t from changing their choices

34 Mutual agreement

At this point if the framework predicts land1047297ll for the munici-pality and a WTE technology for the selected industry it will

provide no waste for the industry to recover energy from the waste

Hence the proposed framework takes it further to estimate fair

shares of costs and bene1047297ts (ie a tipping fee that one stakeholder

shouldpay to the other one) to make the WTE technology attractive

to the municipality and assure mutual agreement on a sustainable

option

Independent variables such as waste composition have uncer-

tain values which can change sustainability indexes and ultimately

stakeholders decisions To take this into account a general

regression equation is presented in equation (6) to estimate the

relation between these variables and sustainability indexes

SIij frac14 a1 X 1 thorn a2 X 2 thornthorn an X n i frac14 1hellip n j frac14 1hellip n (6)

where SIij is sustainability index of alternative i for stakeholder j ak

is the coef 1047297cient of X k and X k is the kth independent variable (eg

cost estimates weights etc)

The higher the ak the moredependent is the 1047297nal decision to X k

This regression equation will show how changes in X k will affect SI

4 Case study

The goal of this case study is to implement the developed

framework for WTE decision-making to help Metro Vancouver and

the cement industry in the region by estimating their fair shares of

costs and bene1047297ts as well as reaching a mutual agreement on RDFMetro Vancouver is a regional district in the province of BC Canada

that consists of 21 municipalities In this study Metro Vancouver is

referred to as a municipality

41 Scope de 1047297nition for MSWM in Metro Vancouver

In 2008 Canadas local governments spent $26 billion while

earning $18 billion on waste management Nova Scotia and BC

spent the highest per person ($30) on waste treatment and oper-

ation about twice the national average value (Statistics Canada

2011) Metro Vancouver aims to reduce waste management costs

and environmental impacts to generate earnings for the munici-

pality In addition they are aware of social impacts such as

employment material and energy markets and pollution and noisein the neighbourhood of waste treatment plants Therefore

Table 4

Weighting systems for environmental impact categories (Gloria et al 2007)

Impact category Weights

EPP Science advisory Harvard

Global warming 293 16 11

Fossil fuel depletion 97 5 7

Criteria air pollutants 89 6 10

Water intake 78 3 9

Human health cancerous 76 11 6

Human health noncancerous 53

Ecological toxicity 75 11 6

Eutrophication 62 5 9

Habitat alteration 61 16 6

Smog 35 6 9

Indoor air quality 33 11 7

Acidi1047297cation 30 5 9

Ozone depletion 21 5 11

Total 100 100 100

Level 1 of the hierarchy Level 2 of the hierarchy

Environmental impact categories CriteriaCosts Environmental Economic

Sub-criteria s1 s2 hellip sn Environmental 1

TRACI - EPP w1 w2 hellip wn Economic 1

Final weightswe

w1

we

w2hellip

we

wnWeights we wm

Fig 3 Weights for each stakeholder in a two-level hierarchy

Table 5

Example of a two-player normal game theory model

Stakeholder 2

Option a Option b Option c

Stakeholder 1 Option 1 SI11 SI2aa SI11 SI2b SI11 SI2c

Option 2 SI12 SI2b SI12 SI2b SI12 SI2c

Option 3 SI13 SI2c SI13 SI2b SI13 SI2c

a SIij is the sustainability index of option j for stakeholder i i frac14 12 and j frac14 123abc




additional steps are always taken to make sure these impacts are

minimized For example waste treatment plants are built in in-

dustrial neighbourhoods and it is considered that new waste

treatment plants follow increased employment in the waste

section

Metro Vancouvers MSWM plan includes recycling and re-using

of waste materials producing energy from waste and disposing of

the rest in land1047297lls In 2010 around 14 million tonnes of solid

waste equivalent to about 45 of the generated waste were

disposed of in land1047297lls or burned in the WTE plant (Metro

Vancouver 2010) Delta and Cache Creek land1047297lls receive waste

from the Metro Vancouver area The WTE facility in Burnaby

currently carries out mass burn thermal treatment3 Metro Van-

couver plans to build a new WTE plant and RDF is one of the

proposed options for this upcoming plant (Reza et al 2013 Metro

Vancouver 2014b) About 58 of waste is recycled now while the

target is to recycle 80 by 2020 For the 700000 tonnes of waste

remaining after 80 diversion the planned distribution is as fol-

lows (Metro Vancouver 2013)

- 50000 tonnes to Delta land1047297ll

- 280000 tonnes to Burnaby WTE plant

- 370000 tonnes to new WTE plant

In this case study the two stakeholders of Metro Vancouver and

the cement industry are proposing the new waste treatment option

of combusting RDF in cement kilns Besides RDF other scenarios in

this case study are land1047297lling and WTE (mass-burn) To fully un-

derstand the scope of these scenarios waste composition in Metro

Vancouver is presented in Table 6


Sustainability assessment in this case study is mainly built on

the results from a study conducted by Reza et al (2013) where

environmental and economic impacts of RDF were compared with

existing waste treatment options in Metro Vancouver In 2013around 34 million tonnes of MSW were disposed of in Metro

Vancouver Three different scenarios were considered for treatment

of the disposed waste in this study

- Land1047297lling of the disposed waste The composition of mixed

MSW in Vancouver is used for estimation of land1047297lling impacts

- Mass-combustion of the disposed waste The composition of

mixed MSW in 2013 is used for the calculation of impacts

- Co-combustion of RDF in cement kilns in Vancouver Cement

kilns areassumed to be close to potential cement manufacturers

In previous studies RDF production recovered 20e50 of the

disposed MSW (Nithikul 2007 Rotter et al 2004 Gendebien

et al 2003) In this study 40 of the disposed MSW (eg pa-

per plastic wood textile rubber and leather) is recovered for

RDF production and co-combustion in cement kilns

For LCA inputs and outputs (eg materials energy and emis-

sions) from land1047297lling and incineration of each component of waste

were collected from SimaPro 80 and then adapted to Vancouvers

waste composition (Table 7) The values in Table 7 show the mid-

point impacts of 1 kg MSW in each impact category For RDF co-

combustion in cement kilns the required technological changes

in the production line additional indoor air emissions in the plant

and the impacts on the quality of cement are not considered or

discussed Since RDF has not yet been used in cement kilns in

Canada some additional impacts may exist that are not considered

in this studyTo perform LCC for this case study land1047297lling costs were based

on the current tippingfee of $0108 per kg waste (City of Vancouver

2013) Cost of land1047297lling for the industry is the opportunity cost of

not choosing WTE or RDF which is the cost of fossil fuels in their

current practice Price of coal was considered as $007 per kg coal

(78$ per ton) The energy of 1 kg coal is 245 MJ (Reza et al 2013)

equivalent to 680 kWh whilethe output energy for 1 kg of MSW in

the WTE plant in Burnaby was 15 MJ or 42 kWh in 2007 (TRI

Environmental Consulting Inc 2008) In addition when land-

1047297lling is chosen as the waste treatment option industry should pay

carbon tax at the rate of $30 per tonne of CO 2 equivalent emissions

(BC Ministry of Finance 2014)

WTE pro1047297ts for municipality include metal recovery and elec-

tricity sale If WTE is chosen industries save on fossil fuel and

carbon tax Metro Vancouver earns on average about $6 million per

year from electricity produced in the WTE facility (120000 MWh)

and $14 million per year from recovered metal (Metro Vancouver

2014a) One (1) kg of waste generates $0005 revenue from 003 kg

scrap metal and $0022 revenue from electricity Construction

operation and land costs of the existing WTE facility were

considered as sunk costs

Land1047297ll reduction of 60 (derived from Reza et al 2013) was

considered as a bene1047297t for the municipality and tax saving fuel

saving and metal recovery were considered as bene1047297ts for in-

dustry Since stakeholders impact each other LCC is presented to

show the result of these impacts (Table 8) Metro Vancouver is

considering 10 potential treatment plans for the future among

which two options are planning to use RDF (Metro Vancouver

2014d) Therefore it is assumed that Metro Vancouver can stillproduce RDF without the cement industry but the cost will be

slightly higher In addition the cement industry would follow its

current practice if Metro Vancouver chooses land1047297ll or WTE

Table 8 shows the LCC results of stakeholders selecting a pair of

actions at the same time For example when stakeholder 2 (Metro

Vancouver) decides to land1047297ll waste and stakeholder 1 (cement

industry) prefers RDF the economic impacts on stakeholder 2 and 1

are $063 and $0108 per kg MSW respectively

43 Decision-making for multiple stakeholders

The developed framework creates two levels of weights for

environmental and economic criteria and their sub-criteria TRACI

Table 6

Metro Vancouver MSW composition in 2013 (Metro Vancouver 2014c)

MSW components Vancouver in 2013 ()

Paper 136

Plastic 144

Compostable organics 362

Wooda 27

Textile 27

Rubber 27Leathermultiple composite 27

Metals 32

Glass 16

Building material 84

Electronic waste 11

Household hazardous 09

Household hygiene 50

Bulky objects 41

Fines 06

Total 100

a Wood textile rubber and leather are reported in total under non-compostable

organics

3 In this case study WTE option refers to mass burn treatment used in the

Burnaby plant




provides the weights of the environmental impact categories

These weights are similar for both stakeholders According to the

speci1047297cs of each case study and the availability of impact data the

collection of impact categories can vary Once the impact categories

are selected their weights can be calculated (out of 100) from the

original EPP weights (Table 9)

In addition the authors have made reasonable assumptions

based on their expert judgements for stakeholders priorities in

comparing environmental and economic criteria They have made

assumptions about the stakeholders priorities (ie whether theyprefer environmental or economic criterion) and the degree of

those priorities (ie how much they prefer one criterion over

another) These judgements arrive from the authors involvement

in many individual and group discussions with Metro Vancouver

and the cement industry and participation in relevant conferences

by Metro Vancouver Metro Vancouver has continuously explored

sustainable waste management plans to prioritize the environ-

ment and human health while it is a safe assumption that the

cement industry would only invest in an option when it is

1047297nancially sound Table 10 presents the subsequent priority ma-

trix The stakeholders express their preferences through pairwise

comparisons of criteria using Saatys 9-scale Weights of envi-

ronmental impacts and net economic costs are estimated for each

stakeholder using AHPTable 10 shows that the economic net cost is a much greater

concern for industry as opposed to the municipality Final weights

are calculated by multiplying the weights of the environmental

impact categories and the weight of environmental criterion itself

Since economic criterion is notbranched out into other sub-criteria

its initial and 1047297nal weights are the same

In the next step the sustainability index of each waste treat-

ment option is calculated from the impacts and 1047297nal weights of

the criteria Game theory presents these sustainability indices in a

table format with stakeholder 1 (the cement industry) in the

rows and stakeholder 2 (Metro Vancouver) in the columns In this

study game theory searches for pure strategy solutions (a

de1047297nitive solution rather than a mixture of solutions) The solu-

tion shows that RDF is a dominant strategy for the cement in-

dustry as RDF always has a lower or equal sustainability index in

spite of Metro Vancouver choosing any other option WTE is also

a strict dominant strategy for Metro Vancouver As a result game

theory analysis suggests that WTE and RDF are the best optionsfor Metro Vancouver and for the cement industry respectively

considering the current assumptions (Table 11) The industry

should pay a tipping fee to convince the municipality to select the

RDF option

Table 7

Environmental impact assessment for Metro Vancouver case study

Impact category Unit Land1047297ll WTE (Mass-combustion) Co-combustion of RDF in cement kilns

Ozone depletion kg CFC-11 eq 226E-09 377E-08 449E-08

Global warming kg CO2 eq 223E-01 211E-02 255E-02

Smog kg O3 eq 560E-03 864E-03 144E-02

Acidi1047297cation mol Hthorn eq 138E-02 997E-02 121E-01

Eutrophication kg N eq 509E-04 197E-05 301E-05

Carcinogenics CTUh 288E-10 170E-10 223E-10Non carcinogenics CTUh 524E-10 623E-09 870E-09

Respiratory effects kg PM10 eq 290E-04 405E-04 446E-04

Ecotoxicity CTUe 226E-09 152E-02 146E-02

Table 8

Economic net costs for case study in Metro Vancouver

Stakeholder 1s choiceeStakeholder 2s choice Stakeholder 1 e Industry ($ per kg MSW) Stakeholder 2 e Municipality ($ per kg MSW)

Land1047297lleLand1047297ll 063 0108

Land1047297lleWTE 063 0026a

Land1047297lleRDF 063 005

WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043

a Negative value indicates earnings

Table 9

The 1047297rst-level weights for Metro Vancouver case study

Weights of the selected environmental sub-criteria () Sum

C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100

S i Stakeholders C i Sub-criteria

Table 10

The second priority matrix and weighting system for Metro Vancouver case study

Criteria Stakeholder 1 e Industry Stakeholder 2 e

Municipality

Environmental Economic Environmental Economic

Environmental 100 025 100 700

Economic 400 100 014 100

Weights () 20 80 87 13




44 Mutual agreement on RDF option

The tipping fee should be an amount that will convince the

municipality to prefer RDF to WTE while keeping the industry

interested in RDF The developed framework suggests that if the

cement industry pays a tipping fee of $0077e096 per kg waste to

Metro Vancouver both stakeholders will bene1047297t from a proposed

newRDF plant in Vancouver BC (7 8) This value is calculated basedon previous assumptions

$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)

where x is a positive tipping fee per kg MSW

For Metro Vancouver to ef 1047297ciently plan future MSWM strate-

gies the relationship between RDFs sustainability index and in-

dependent variables was presented in a regression equation This

regression will show how important the impact of uncertainties is

on the outcome of the framework More detailed uncertainty

assessment is required in the future to include more sources of

uncertainty Waste composition and economic net cost carryparameter uncertainty due to unavailability of complete and pre-

cise data Therefore waste composition components and economic

net cost versus 1047297nal sustainability index for RDF was graphed Fig 4

shows that in producing RDF economic net cost has the highest

impact on the sustainability index of the cement industry while

plastic has the highest positive impact on sustainability index of

Metro Vancouver At all times the sustainability index of the

cement industry from RDF is higher than that of Metro Vancouver

5 Summary and conclusions

MSWM is complex and can have high costs Waste treatment

strategy is the core of MSWM due to the signi1047297cance of its envi-

ronmental and economic impacts To choose and apply a sustain-

able waste treatment option municipalities generally develop

partnerships with other stakeholders such as industries In case of

selecting a WTE treatment technology this partnership has a side

of competition as the valuable product of energy enters the system

Therefore reaching a mutual agreement among multiple stake-

holders with con1047298icting priorities is often a complicated affair If a

mutual agreement is not reached the disposed waste is not

directed into the most mutually sustainable path

This study proposes a decision framework to assist two stake-

holders with con1047298icting priorities in evaluating environmental and

economic e and whenever available social e impacts of selected

waste treatment options and choosing the most mutually sustain-

able one Sustainable options are different from each stakeholders

point of view which results in sustainable options to often not get

selected by both stakeholders This will result in a perfectly

reasonable treatment option to never get approved This frame-

work estimates stakeholders fair shares of costs and bene1047297ts and

helps them reach a mutual agreement on a single optimal option

that is environmentally superior and economically feasible The

developed framework uses LCA LCC and AHP to help stakeholders

to compare various optionsand then appliesgame theory to model

stakeholders actions con1047298icts and dialogues The results of this

framework will help municipalities to explore more advanced and

sustainable treatment options such as WTE technologies and avoid

the free-rider problem

The application of the developed framework was demonstratedwith a case study of RDF in Metro Vancouver Two stakeholders of

Metro Vancouver and the cement industry compared sustainability

impacts of land1047297lling using mass-burn WTE and co-combusting

Table 11

Game theory results for Metro Vancouver case study

-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5

S u s t a i n a b i l i t y

I n

d e x

Changes in the variable

PlasticCompostable organics

Econ 1

Plastic

Compostable organics

Econ 2


Metals

Glass

Paper

Economic net cost

RDF for cement industry

RDF for Metro Vancouver

Fig 4 Parameter uncertainty of RDF in Metro Vancouver case study




RDF in cement kilns to investigate the possibility of collaborating

on a new RDF treatment plant As a result mass-burn WTE and RDF

were selected as the most sustainable options for Metro Vancouver

and the cement industry respectively The developed framework

estimated that a tipping fee of $077e$096 per kg MSW should be

paid by the cement industry to MetroVancouver so that RDFcan be

applied as Metro Vancouvers new waste treatment option and the

cement industrys solution to high-intensity fossil fuel consump-

tion This value is only based on assumptions and factors consid-

ered in this paper Without the proposed framework the

collaboration might not take place or negotiations might be

inef 1047297cient

There are various types of uncertainties (parameter model and

scenario) in this framework that will affect the robustness of the

results Parameter uncertainty refers to vague incorrect and

imprecise values such as composition of MSW in Metro Vancouver

input and output emission data derived from other databases and

tools as well as assumptions made for costs and bene1047297ts Model

uncertainty discusses inaccurate hypotheses about the general

model or relationship of variables such as impact assessment out-

comes and the game theory model Scenario uncertainty is con-

cerned with the environment of assessments such as differences in

the regions of collected data and case study These uncertaintiesshould be explored in more detail in a future study To show the

sensitivity of the outcomes of the framework to the uncertainties a

sensitivity analysis is performed The assessment of the un-

certainties in waste composition and economic net cost shows that

RDF is preferred by industry at all timesAlso sustainability indexes

of industry and the municipality are more impacted by economic

net cost and share of plastic in waste composition respectively

Social impacts are dif 1047297cult to assess quantitatively and carry the

subjectivity of decision-makers into the decision-making process

The developed framework has the ability to combine the outcomes

of social life cycle assessment methodologies with environmental

and economic assessment results according to the stakeholders

priorities but it does not discuss methodologies for quantifying

these impacts In addition there is no other case of co-combustionof RDF in cement kilns in Canada which makes the evaluation of

social impacts prone to subjectivity hard to evaluate and out of the

scope of the case study While social impacts are not quanti1047297ed for

the discussed case study they are still believed to impact munici-

palitys actions and priorities

The most challenging part of this framework was providing

accurate data and real scenarios that represented the waste treat-

ment in a region and interactions among stakeholders Other lim-

itations of this framework and potentials for future studies include

consideration of interest rate in LCC consideration of additional

costs of RDF in LCC using other software packages for LCA using

real stakeholders for pair-wise comparisons expansion of two-

player game into n-player game and consideration of other game

theory models (eg uncertainty about other stakeholders actions)in the framework

Acknowledgements

We would like to thank NSERC for the 1047297nancial support from

second and third authors NSERC-DG grants We also appreciate the

help of Ms Sarah Wellman at Metro Vancouver Ms Yihting Lim at

TRI Environmental Consulting and Mr Navid Hossaini and Mr

Fasihur Rahman at UBC

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Rotter VS Kost T Winkler J Bilitewski B 2004 Material 1047298ow analysis of RDF-production processes Waste Manag (New York NY) 24 (10) 1005e1021httpdxdoiorg101016jwasman200407015

Saaty T 1980 The Analytic Hierarchy Process Planning Priority Setting ResourceAllocation (Decision Making Series) McGraw Hill New York

Saaty TL 1988 What is the analytic hierarchy process In Mitra G (Ed) Math-ematical Models for Decision Support Proceedings of the NATO AdvancedStudy Institute on Mathematical Models for Decision Support vol 4 8 Springer-Verlag Berlin Heidelberg Berlin Heidelberg

Saaty TL 1994 How to make a decision the analytic hierarchy process Interfaces24 (6) 19e43

Sadiq R 2001 Drilling Waste Discharges in the Marine Environment a Risk BasedDecision Methodology Memorial University of Newfoundland Retrieved from

httpresearchlibrarymunca1250 Sadiq Rehan Husain T Veitch B Bose N 2003 Evaluation of generic types of

drilling 1047298uid using a risk-based analytic hierarchy process Environ Manag 32(6) 778e787

Schwarz J Beloff B Beaver E 2002 Use sustainability metric to guide decisionmaking Chem Eng (July) 58e63 Retrieved from httppeopleclarksonedu~wwilcoxDesignsustainpdf

Society of Environmental Toxicology and Chemistry (SETAC) 1993 Guidelines forlife-cycle assessment a code of practice Portugal doi First edition

Society of Environmental Toxicology and Chemistry (SETAC) 2004 EnvironmentalRisk Assessment SETAC Technical Issue Paper Pensacola FL doiThirdPrinting

Sheppard SRJ Meitner M 2005 Using multi-criteria analysis and visualisationfor sustainable forest management planning with stakeholder groups ForEcol Manag 207 (1e2) 171e187 httpdxdoiorg101016jforeco200410032

Soltani A Hewage K Reza B Sadiq R 2015 Multiple stakeholders in multi-criteria decision-making in the context of municipal solid waste manage-ment a review Waste Manag (New York NY) 35 318e328 httpdxdoiorg101016jwasman201409010

Spengler T Geldermann J Heuroahre S Sieverdingbeck A Rentz O 1998 Devel-opment of a multiple criteria based decision support system for environmentalassessment of recycling measures in the iron and steel making industry

J Clean Prod 6 (1) 37e52 httpdxdoiorg101016S0959-6526(97)00048-6Statistics Canada 2011 Spending on Waste Management Retrieved November 19

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Statistics Canada 2015 Disposal and Diversion of Waste by Province and Territory(Total Waste Disposal)

Sutton PC Anderson SJ Tuttle BT Morse L 2012 The real wealth of nationsmapping and monetizing the human ecological footprint Ecol Indic 16 11e22httpdxdoiorg101016jecolind201103008

Tesfamariam S Sadiq R 2006 Risk-based environmental decision-making usingfuzzy analytic hierarchy process (F-AHP) Stoch Environ Res Risk AssessSpringer 21 (1) 35e50

The Government of British Columbia 2015 Part 3 d municipal waste managementEnviron Manag Act Retrieved July 08 2015 from httpwwwbclawscacivix

documentLOCcompletestatreg-E-EnvironmentalManagementAct[SBC2003]c5300_Act03053_03xmlThe World Bank 2012 What a Waste a Global Review of Solid Waste Management

Retrieved from httpgoworldbankorgBCQEP0TMO0TRI Environmental Consulting Inc 2008 Solid Waste Composition Study for Metro

Vancouver Retrieved from httpwwwmetrovancouverorgaboutpublicationsPublicationsSolidWasteCompositionStudyFinal-2007pdf

Tseng M-L Lin Y-H Chiu ASF 2009 Fuzzy AHP-based study of cleaner pro-duction implementation in Taiwan PWB manufacturer J Clean Prod 171249e1256

Tsilemou K Panagiotakopoulos D 2006 Approximate cost functions for solidwaste treatment facilities Waste Manag Res 24 (4) 310e322

United States Environmental Protection Agency (USEPA) 2006 Life cycle assess-ment principles and practice Cincinnati OH doiEPA600R-06060

Van den Hove S 2006 Between consensus and compromise acknowledging thenegotiation dimension in participatory approaches Land Use Policy 23 (1)10e17 httpdxdoiorg101016jlandusepol200409001

Weikard H-P Dellink RB 2008 Sticks and carrots for the design of internationalclimate agreements with renegotiations Ann Oper Res 1e20

World Health Organization (WHO) 2014 7 million Premature Deaths AnnuallyLinked to Air Pollution Retrieved January 27 2015 from httpwwwwhointmediacentrenewsreleases2014air-pollutionen




energy from disposed waste can generate power for municipalities

offer fossil fuel substitutes to industries and reduce greenhouse

gases and other hazardous pollutants (Metro Vancouver 2014a)

There are various sustainability assessment frameworks and

tools available for calculating environmental impacts (eg life cycle

assessment (LCA) (the International Organization for

Standardization (ISO) 2006a) environmental risk analysis

(SETAC 2004) environmental impact assessment (Canter 1977))

and net economic costs (eg life cycle costing (LCC) (Blanchard

et al 1990)) In addition there are numerous frameworks for

comparing the performances in one criterion to another and

1047297nding a balance A multi-criteria decision analysis (MCDA)

framework provides different methods that can help decision-

makers to 1047297nd a suitable trade-off amongst these criteria andchoose an option with the lowest overall impacts (Soltani et al

2015) While LCA and LCC are effective in accounting for the im-

pacts of waste treatment options throughout their life cycle MCDA

methods are required to aggregate their outcomes

Meanwhile waste treatment for achieving sustainability goals is

even more complex when multiple stakeholders with con1047298icting

interests are involved In Canada collection diversion (ie reuse

recycling and composting) and disposal of waste are generally

handled by the municipal governments (Environment Canada

2012) In addition to the municipal government multiple stake-

holders such as NGOs environmental experts general public and

industries affect policies and decisions related to MSWM Soltani

et al (2015) provided a state-of-the-art review with respect to

multiple stakeholders involvement in MSWM in which munici-palities and experts were found to be involved in decision-making

more than other stakeholders

Waste treatment often creates a situation where the munici-

pality bears all the costs of waste treatment while other stake-

holders bene1047297t from it without contributing to the costs this

situation is known as the lsquofree-riderrsquo problem The municipality is

responsible for providing the public goods and services such as

waste treatment and ends up paying the associated costs The free-

rider problem can discourage the municipality from choosing the

more advanced and more expensive technologies or can result in

the over-using of the provided service A solution to this problem is

to involve other stakeholders in the decision-making and execution

process Other stakeholders will be encouraged to contribute to-

wards the relevant costs of sustainable waste treatments if

municipalities combine these services with other in-demand ser-

vices (Carraro and Marchiori 2003) Using WTE technologies for

waste treatment mitigates the free-rider problem by offering

cleaner energy solutions to industries and encouraging them to pay

for the recovered energy and materials but to make this feasible

the municipality and industry should 1047297rst negotiate their fair share

of costs and bene1047297ts to mutually agree on a WTE technology

Hence effective waste management should evaluate stakeholders

dialogues in addition to technical assessments (Achillas et al

2013)

This study proposes a decision framework to help multiple

stakeholders reach an agreement on a ldquosustainablerdquo waste treat-

ment option and share the associated costs and bene1047297ts in a fair

and mutually acceptable way This framework is especially helpfulfor using WTE technology where often various stakeholders get

involved This research aims to 1047297ll the gap in the literature on

choosing the most sustainable and pragmatic waste treatment

option when stakeholders have con1047298icting priorities

2 Background information

In this section components of the proposed framework

including sustainability assessment tools waste treatment options

and decision analysis methods are discussed in more detail

21 Sustainability assessment tools

A sustainability paradigm helps in choosing building or offer-

ing products and services that conserve resources such as money

water soil air and humans in an acceptable balance Sustainability

assessment tools such as LCA and LCC can evaluate the environ-

mental impacts and economic costs and bene1047297ts of selected MSWM

options

211 Life cycle assessment

LCA is a popular method that helps experts estimate environ-

mental burdens of products processes and services throughout

their life (USEPA 2006) LCA identi1047297es and quanti1047297es inputs and

outputs to a system including materials energy waste and

pollution (SETAC 1993) According to the ISO 14040 and 14044

standards LCA consists of four general steps (ISO 2006a 2006b)

Fig 1 Ten countries with the highest disposal of MSW per capita in 2008 (derived from D-waste (2015))




















these assessment



























PRe (2015)





2004)










2003)




NPV frac14Xn

t frac140



number of periods










options


2007))


2005)


- Affordability





















incineration



















et al 2013)





































alternatives





uncertainty











comparisons

A frac14

24

1 hellip a1n

hellip 1 hellip

an1 hellip 1

35 (2)











ethPn


AW frac14 lW (3)









negotiations

232 Game theory


















Table 1



1 Equal importance


5 Strong importance






















































stakeholders





































Table 2


Game

theory

model



Cost-bene1047297t




(2002)


MCDA

Cheng et al

(2003)

Inexact linear

programming e MCDA

Joslashrgensen

(2010)


theory


Shapley value

Erkut et al

(2008)


approach

Karmperis


bargaining game


(2005)


e Zero-sum game

a















































weights







Table 3


Costs Bene1047297ts




Transportation cost

Land costs











the stakeholder


(4)


relevant impact

(5)












34 Mutual agreement







option












4 Case study
















Table 4







Water intake 78 3 9






Smog 35 6 9




Total 100 100 100





Final weightswe

w1

we

w2hellip

we

wnWeights we wm


Table 5


Stakeholder 2













section



























































































Table 6



Paper 136

Plastic 144


Wooda 27

Textile 27


Metals 32

Glass 16


Electronic waste 11



Bulky objects 41

Fines 06

Total 100


organics


Burnaby plant














































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345































































these assessment



























PRe (2015)





2004)










2003)




NPV frac14Xn

t frac140



number of periods










options


2007))


2005)


- Affordability





















incineration



















et al 2013)





































alternatives





uncertainty











comparisons

A frac14

24

1 hellip a1n

hellip 1 hellip

an1 hellip 1

35 (2)











ethPn


AW frac14 lW (3)









negotiations

232 Game theory


















Table 1



1 Equal importance


5 Strong importance






















































stakeholders





































Table 2


Game

theory

model



Cost-bene1047297t




(2002)


MCDA

Cheng et al

(2003)

Inexact linear

programming e MCDA

Joslashrgensen

(2010)


theory


Shapley value

Erkut et al

(2008)


approach

Karmperis


bargaining game


(2005)


e Zero-sum game

a















































weights







Table 3


Costs Bene1047297ts




Transportation cost

Land costs











the stakeholder


(4)


relevant impact

(5)












34 Mutual agreement







option












4 Case study
















Table 4







Water intake 78 3 9






Smog 35 6 9




Total 100 100 100





Final weightswe

w1

we

w2hellip

we

wnWeights we wm


Table 5


Stakeholder 2













section



























































































Table 6



Paper 136

Plastic 144


Wooda 27

Textile 27


Metals 32

Glass 16


Electronic waste 11



Bulky objects 41

Fines 06

Total 100


organics


Burnaby plant














































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345



















































et al 2013)





































alternatives





uncertainty











comparisons

A frac14

24

1 hellip a1n

hellip 1 hellip

an1 hellip 1

35 (2)











ethPn


AW frac14 lW (3)









negotiations

232 Game theory


















Table 1



1 Equal importance


5 Strong importance






















































stakeholders





































Table 2


Game

theory

model



Cost-bene1047297t




(2002)


MCDA

Cheng et al

(2003)

Inexact linear

programming e MCDA

Joslashrgensen

(2010)


theory


Shapley value

Erkut et al

(2008)


approach

Karmperis


bargaining game


(2005)


e Zero-sum game

a















































weights







Table 3


Costs Bene1047297ts




Transportation cost

Land costs











the stakeholder


(4)


relevant impact

(5)












34 Mutual agreement







option












4 Case study
















Table 4







Water intake 78 3 9






Smog 35 6 9




Total 100 100 100





Final weightswe

w1

we

w2hellip

we

wnWeights we wm


Table 5


Stakeholder 2













section



























































































Table 6



Paper 136

Plastic 144


Wooda 27

Textile 27


Metals 32

Glass 16


Electronic waste 11



Bulky objects 41

Fines 06

Total 100


organics


Burnaby plant














































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345



























































































stakeholders





































Table 2


Game

theory

model



Cost-bene1047297t




(2002)


MCDA

Cheng et al

(2003)

Inexact linear

programming e MCDA

Joslashrgensen

(2010)


theory


Shapley value

Erkut et al

(2008)


approach

Karmperis


bargaining game


(2005)


e Zero-sum game

a















































weights







Table 3


Costs Bene1047297ts




Transportation cost

Land costs











the stakeholder


(4)


relevant impact

(5)












34 Mutual agreement







option












4 Case study
















Table 4







Water intake 78 3 9






Smog 35 6 9




Total 100 100 100





Final weightswe

w1

we

w2hellip

we

wnWeights we wm


Table 5


Stakeholder 2













section



























































































Table 6



Paper 136

Plastic 144


Wooda 27

Textile 27


Metals 32

Glass 16


Electronic waste 11



Bulky objects 41

Fines 06

Total 100


organics


Burnaby plant














































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345

























































































weights







Table 3


Costs Bene1047297ts




Transportation cost

Land costs











the stakeholder


(4)


relevant impact

(5)












34 Mutual agreement







option












4 Case study
















Table 4







Water intake 78 3 9






Smog 35 6 9




Total 100 100 100





Final weightswe

w1

we

w2hellip

we

wnWeights we wm


Table 5


Stakeholder 2













section



























































































Table 6



Paper 136

Plastic 144


Wooda 27

Textile 27


Metals 32

Glass 16


Electronic waste 11



Bulky objects 41

Fines 06

Total 100


organics


Burnaby plant














































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345





















































the stakeholder


(4)


relevant impact

(5)












34 Mutual agreement







option












4 Case study
















Table 4







Water intake 78 3 9






Smog 35 6 9




Total 100 100 100





Final weightswe

w1

we

w2hellip

we

wnWeights we wm


Table 5


Stakeholder 2













section



























































































Table 6



Paper 136

Plastic 144


Wooda 27

Textile 27


Metals 32

Glass 16


Electronic waste 11



Bulky objects 41

Fines 06

Total 100


organics


Burnaby plant














































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345



















































section



























































































Table 6



Paper 136

Plastic 144


Wooda 27

Textile 27


Metals 32

Glass 16


Electronic waste 11



Bulky objects 41

Fines 06

Total 100


organics


Burnaby plant














































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345

























































































RDF option

Table 7





Smog kg O3 eq 560E-03 864E-03 144E-02






Table 8



Land1047297lleLand1047297ll 063 0108



WTEeLand1047297ll 063 0108

WTEeWTE 063 0026

WTEeRDF 063 005

RDFeLand1047297ll 063 0108

RDFeWTE 063 0026

RDFeRDF 031 0043


Table 9



C1 Abiotic

depletion

C2

Acidi1047297cation

C3

Eutrophication

C4 Global

warming 100

C5 Ozone

depletion

C6 Human

toxicity

C7 Fresh aquatic

ecotoxicity

C8 Terrestrial

ecotoxicity

C9 Photochemical

oxidation

8 4 9 40 3 10 11 10 5 100


Table 10



Municipality



Economic 400 100 014 100

Weights () 20 80 87 13











$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345






















































$024 thorn 075 xlt $047 xlt $096 (7)

$001 013 xlt $002 xgt$0077 (8)
















































Table 11


-006

-005

-004

-003

-002

-001

0

- 5

- 4

- 3

- 2

- 1

C u r r e n t

d a t a 1 2 3 4 5


I n

d e x



Econ 1

Plastic


Econ 2


Metals

Glass

Paper

Economic net cost


















inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345


























































inef 1047297cient






































Acknowledgements






References







jecolecon200610021












































e345


























































e345













































selecting sustainable waste-to-energy technologies for municipal solid waste treatment a game theory...

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