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    <subfield code="a">AIT Diss. no.ET-17-01</subfield>
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    <subfield code="a">Rotchana Intharathirat</subfield>
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    <subfield code="a">Sustainable municipal solid waste management systems for small and medium sized cities in Thailand</subfield>
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    <subfield code="a">Pathum Thani, Thailand :</subfield>
    <subfield code="b">Asian Institute of Technology,</subfield>
    <subfield code="c">2017</subfield>
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    <subfield code="a">Dissertation ;</subfield>
    <subfield code="v">no. ET-17-01</subfield>
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    <subfield code="a">A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Energy, School of Environment, Resources and Development</subfield>
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    <subfield code="a">Thesis (Ph.D.) - Asian Institute of Technology, 2017</subfield>
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    <subfield code="a">Municipal solid waste management (MSWM) has become a crucial issue worldwide, not only because  of  the  increase  of  waste  generation,  but also  due  to  its  improper disposal.  Improper management  of  MSW,  typically  through landfills  and  open  dumping,  hascaused  serious environmental  impacts.To  evaluate  the  most  appropriate  MSWM  system, several  models have  been  developed  to  support  a  decision  making  process. These  models  were  mostly practiced for large cities, while only a few were found for medium and small cities. There is no single optimal MSWM system that can be applied to both large and small cities since they have  different  characteristics. It  is,  therefore,  vital  to  evaluate  the  most  suitable  MSWM system for medium and small cities, as decisions made at an early stage can have significant impacts  to  MSWM  in  laterphases  as  cities  grow. Selecting  the  most effective  MSWM requires  consideration  of  various  parameters.  For  instance,  it  is  complicated  for  developing countries, such as Thailand, due to the lack of reliable data, including thestatus of MSWM, characteristics of technologies used and applied, and present and future MSW generation and composition.Firstly, this study aims to assess the status of MSWM systems in Thailandto clarify existing decision  making  processes  and  to  propose  appropriate  alternatives. The implementationof waste-to-energy  (WTE)  and  other  treatment  systems  invested  and  operated  by  the  private sector  were  also  comprehensively  assessed. Due  to  the  lack  of  data  on  MSW  treatment systems in medium and small cities, this assessment was carriedout at the country level and was  used  to  represent  alternative  treatment  systems  for  medium  and  small  cities. Secondly, this  study  attempts  to  fill  a  gap  where traditional  forecasting  models  of  MSW  quantity  (i.e., regression   analysis,   time-series   analysis,   and   econometric   models)   are   challenging   to implement  given  their  data  requirements.  The  innovative  models,  grey  models  (GM),  are developed  by  using  limited  data  and  consider  influencing  factors  to  achieve   greatest accuracy. In  most  developing  countries, it  is  difficult  to  collect  reliable  data  on  MSW quantities in large, medium and small cities. Therefore, this study utilized time-series data of MSW  collected  countrywide  for  developing  alternative  models. Despite  sources  of  MSW generation  identified  in  various  sectors  (residential,  commercial,  institution,  and  municipal services), a fewstudies investigated factors affecting MSW generated from only two sectors (residential  and  commercial).  Hence,  this  study  considers  these  factors  in  developing  MSW forecasting  models  to  address  the  lack  of  data.  Thirdly, based  on  the  outcomes  obtained above,  the  MSWM  systems  for  medium  and  small  cities  were  evaluated  involving  relevant participatory  stakeholders.  Given  the  lack  of  data, this  study  focuses  on  front-end  and  end-pipe  treatment  systems,excluding separation  at  source  and  collection  systems.  Group meetings  or  workshops  were  not  conducted  in  this  study  due  to  the  unavailability  of stakeholders at the top of each organizationThe assessment of MSWM systems was carried out based on a review of available literature, interviews,andsitevisits focusing on existinggeneral MSW management systems and WTE treatment systems, including consideration of pre-treatment, treatment and disposal systems. This studyassessedthe details of WTE systems:anaerobic digestion (AD), incineration (IC), gasification (GF), landfill gas (LFG) and refuse derived fuel (MBT-RDF). Results show that the  current  annual  amount  of  MSW  generatedtreated  is2.54  Mt  (9.5%  of  total  26.8  Mt generatedin 2013), which generates66 MW of electricity,as well as 78.26 ktoe of heat. It is estimated  that  about  8.17  Mt  of  MSW  (30.5%)  will  be  treated,319  MW  of  electricitygenerated,as  well  as  78.26  ktoe  of  heat,when  the  plants  presently  under  construction and planning   start   operation.   Eight   systems   consisting   of   three general MSWM   systems  iv(composting  (MBT-CP), recycling  (MT-Re)  and  landfill  (LF))  and  five  WTE treatment systems (AD, IC, GF, MT-RDF and LFG) were proposed as MSWM alternatives for further decision making process.A  methodological  framework  for  MSW  forecasting  was  developed  considering  traditional and  innovative  grey  models.  The  forecasting  framework  could  be  distinguished  as  having four  main  steps: i)  identifying  and  selecting  influencing  factors,  ii)  developing  alternative models,  iii)  verifying  models,  and  iv)  forecasting  the  amount  of  MSW  quantity  at  country level with prediction intervals. Fifteenmodels were developed by using time series data from 2000  to  2012. Results  show  that GMwith  convolution  integral,GMC  (1,  5),  is  the  best  fitmodel and used to forecast MSW collectedwith the least error of 1.16% MAPE. This model indicates  that  the  amount  of  MSW  collected  would  increase  by  1.40%  per  year,which  is  in the range from 43,435{u2013}44,994 t/d in 2013 to 47,735{u2013}49,293 t/d in 2020, and 55,177{u2013}56,735 t/d  in  2030.  The  increase  of  MSW  collected  may reflect representative  factors  of the commercial sector (population density, urbanization and proportion employment) rather than that of the residential sector (household size). It was also observed that demographic factors are more important than socio-economic factors.The evaluation of MSWM systems was conducted by using the Analytical Hierarchy Process (AHP)   method   through   assigning   weights   in   pair-wise   comparison   matrices   by   11 stakeholders  from  five  groups  of  organization  such  as governmental,  academic,  technical, local  authority  and  NGOs.  This  study  identified four  main  criteria(environmental,  social, economic  and  technical),  and  12  sub-criteria(diversion  from  landfill,  GHG  emissions, environmental  impacts, capital  cost,  O&amp;M  cost, revenue  &amp; benefit, public  acceptance, creation  of  jobs, simplicity, maturity, and  local  equipment)to  be  simultaneously  considered for  selecting  the  most  suitable  MSWMsystems  among  eight  alternatives  mentioned  above. Results  indicate  that stakeholderspreferenced  the environmental  aspect  as being the  most important,  followed  by  social  consideration,whereaseconomic  and  technical  aspects wereconsidered equal for both medium and small cities. It can be concluded that in the context of Thailand,  stakeholders  focus more on  strong  sustainability.  The  preferences  of  stakeholders on sub-criteria show that public acceptance is the most important, followed by environmental impacts and diversion from landfill. As per this study, the most suitable MSWM system is the mechanical biological treatment combined with composting (MBT-CP) for medium city and mechanical  treatment  combined  with  RDF  (MT-RDF)  for  small  city,  while  both  landfilling and  landfill  gas were identified  as  the  worst  options. Stakeholders  prefer the waste-to-resource   (WTR)   scheme   than   waste-to-energy   (WTE)   to   achieve   sustainable   MSW management in Thailand.This studypresentsa systematic methodology for MSW forecasting that addresses the limited availability   of data   in   a   developing   country.   It also   offerswider   application and encouragement  toresearchers  in  other  developing  countries   and  fields  of  study.  The evaluation  of  MSWM  systemsthat  engage relevant  stakeholders  and thus  reflecttheir preferences,can assist decision makers and local authorities in tacklingthe issue of MSWM in other regions of the study area.</subfield>
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