East Asia and Pacific Region: MARINE PLASTICS SERIES Plastic Waste Material Flow Analysis for Thailand SUMMARY REPORT © 2022 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpre- tations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy, completeness, or currency of the data included in this work and does not assume responsibility for any errors, omissions, or discrepancies in the information, or liability with respect to the use of or failure to use the information, methods, processes, or conclusions set forth. 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Plastic Waste Material Flow Analysis for Thailand SUMMARY REPORT CONTENTS ACKNOWLEDGEMENTS.....................................................................................................................................8 ABBREVIATIONS & DEFINITIONS....................................................................................................................9 EXECUTIVE SUMMARY.......................................................................................10 KEY FINDINGS: HIGH-PRIORITY CATCHMENTS....................................................................................... 11 KEY FINDINGS: TOURIST HOTSPOTS.......................................................................................................... 11 RECOMMENDATIONS....................................................................................................................................... 13 SECTION 1. INTRODUCTION..............................................................................14 1.1 Background.................................................................................................................................................... 14 1.2 About the Study........................................................................................................................................... 14 1.2.1 Scope of the Study.............................................................................................................................................15 1.2.2 Outline of the Report........................................................................................................................................15 SECTION 2. MODELING APPROACH AND METHODOLOGY....................18 2.1 General Approach and Definitions.......................................................................................................... 18 2.2 Modeling Leakages of Mismanaged Plastic Waste from Land-based Sources......................22 2.2.1 Overview of the SWM Model......................................................................................................................... 22 2.2.2 Determining MPW Available for Wash-off............................................................................................... 23 2.3 Modeling Wash-off and Transport of Plastic Waste to the Sea.................................................. 29 2.3.1 Rainfall-runoff Modeling................................................................................................................................. 29 2.3.2 Fate and Transport Modeling of Plastics.................................................................................................. 34 SECTION 3. STUDY RESULTS..........................................................................40 3.1 Assessment of MPW from Land-based Sources.............................................................................. 40 3.1.1 High-priority Catchments...............................................................................................................................40 3.1.2 Tourist Hotspots................................................................................................................................................49 3.2 Estimated Plastic Discharges from Rivers and Coastal Areas................................................... 53 3.2.1 Estimated MPW Discharges from High-priority Catchments............................................................ 53 3.2.2 Estimation of MPW Discharges from Tourist Hotspots.......................................................................60 3.3. Confidence and Validation of Results................................................................................................. 60 3.3.1 SWM Model..........................................................................................................................................................61 3.3.2 Hydrological Models........................................................................................................................................62 3.3.3 Fate and Transport Models...........................................................................................................................62 3.4 Comparison with Previous Complementary Estimates................................................................. 63 4 | Plastic Waste Material Flow Analysis for Thailand: Summary Report SECTION 4. CONCLUSIONS AND RECOMMENDATIONS........................66 4.1 Key Results and Conclusions of the Assessment..............................................................................67 4.1.1 How much plastic waste is being discharged into the marine environment?................................. 67 4.1.2 Where does the discharged plastic waste come from?........................................................................ 67 4.2 Recommendations for Policy and Investments................................................................................ 69 4.2.1 Measures to Reduce Transport of Leaked MPW (Downstream in Waste Chain).......................... 70 4.2.2 Measures to Reduce MPW (Mid-stream in Waste Chain).................................................................... 71 4.3 Recommendations to Improve the Data and Underlying Models................................................74 REFERENCES........................................................................................................ 75 FIGURES Figure 1. Geographic scope of this study .....................................................................................................................16 Figure 2. Schematic representation of the modeling approach............................................................................19 Figure 3. Conceptual framework for modeling material flow (green/light brown), leakages (red) and wash-off/transport of plastic waste from land-based sources via rivers (blue) ....................................19 Figure 4. Sankey diagram providing insight in the physical flow of waste down the waste chain from source to sea......................................................................................................................................................................... 20 Figure 5. SWM model flow schematic constructed from PCD and NSO adapted schematics.................. 23 Figure B3.1. Waste exposed to rainfall and potentially mobilized........................................................................ 25 Figure 6. Overview of the wflow_sbm processes ...................................................................................................... 30 Figure 7. Example of Ko Samui showing the principles of land and river runoff .............................................. 31 Figure 8. Outlet points of the model to the ocean with different resolutions. In blue, the rivers on Ko Samui................................................................................................................................................................................. 31 Figure 9. Overview of the reservoirs which are included in the hydrological model. In black, the catchment delineation from the Department of Water Resources (DWR) is shown ................................... 32 Figure 10. Schematized diagram of the approach to fate and transport modeling of plastics ................ 34 Figure 11. Conceptual framework of the fate and transport of MPW from emission (direct disposal in water, leakages from fly-tipping and dumpsites) to surface waters including the retention processes applied on land and in rivers ...................................................................................................................... 35 Figure 12. Schematic of fate and transport modeling based on wflow_sbm grid. Plastic is washed off of the land surface into the surface water, which is then carried downstream to the nearest downstream neighbor ....................................................................................................................................................... 36 Figure 13. Main sources and pathways for mismanaged plastic waste for each of the catchments....... 41 Figure 14. Destination of uncollected plastic waste (based on NSO’s survey percentage) ........................ 42 Figure 15. Critical districts contributing most to exposed MPW are indicated with red boundary ......... 43 Figure 16a. Spatial distribution of exposed MPW from dumping/fly-tipping in top 10 critical districts.................................................................................................................................................................................. 45 Figure 16b. Spatial distribution of exposed MPW from direct disposal to water in top 10 critical districts.................................................................................................................................................................................. 45 Contents | 5 Figure 16c. Spatial distribution of exposed MPW from unsanitary landfills (controlled dumps and open dumpsites) in top 10 critical districts ............................................................................................................... 45 Figure 16d. LAO types across top 10 critical districts............................................................................................. 46 Figure 17. Main sources and pathways for MPW for each of the catchments................................................. 50 Figure 18a. Spatial distribution of exposed MPW from dumping/fly-tipping in tourist hotspots.............. 51 Figure 18b. Spatial distribution of exposed MPW from unsanitary landfills (controlled dumps and open dumpsites) in tourist hotspots ............................................................................................................................. 51 Figure 18c. LAO types across tourist hotspots.......................................................................................................... 52 Figure 19. Fate of exposed MPW from land-based sources for the high-priority catchments in Thailand.................................................................................................................................................................................. 54 Figure 20. Fate of MPW transported in the main rivers of the five high-priority catchments ................. 54 Figure 21. Spatial distribution of exposed MPW (grey shades) and the resulting mid-point estimates of MPW discharged into the marine environment (blue circles) from river mouths and coastal areas ....................................................................................................................................................................... 55 Figure 22. Modeled time series of MPW discharge at river mouth of the Tha Chin River (red line) for the mid-point scenario and the River discharge (blue line, reverse right axis) ......................................... 56 Figure 23. Modeled time series of MPW discharge at river mouth of the Chao Phraya River (red line) for the mid-point scenario and the River discharge (blue line, reverse right axis) .................................57 Figure 24. Relative changes in priority ranking for districts when hydrology is considered ......................60 Figure 25. Spatial distribution of exposed MPW (grey shades) and the resulting mid-point estimates of MPW discharged into the marine environment (blue circles) from river mouths and coastal areas ........................................................................................................................................................................61 Figure 26. Confidence levels for the various study areas, based on the validation of the SWM model....................................................................................................................................................................................... 62 Figure 27. Confidence levels for the various study areas, based on the validation of the Hydrological model............................................................................................................................................................. 63 Figure 28. Confidence levels for the various study areas, based on the validation of the Fate and Transport model.................................................................................................................................................................. 63 Figure 29. Sankey diagram for the four high-priority catchments showing an approximation of the plastic waste material flow from generation to discharge to the marine environment............................... 68 Figure 30. Origin of exposed MPW (labels in kton/year) in four catchments with confident results only (based on NSO’s survey percentage)................................................................................................................... 69 6 | Plastic Waste Material Flow Analysis for Thailand: Summary Report TABLES Table 1. Summary of SWM model data sources, limitations and assumptions.............................................. 26 Table 2. Summary of the assumptions and limitation in the hydrological models and the impact on the results........................................................................................................................................................................ 33 Table 3. Summary of the assumptions and limitation in the fate and transport models and the impact on the results..........................................................................................................................................................37 Table 4. Critical areas that contribute most to exposed MPW ................................................................ 44 Table 5. Top 10 critical districts according to exposed MPW generated in the Phetchaburi River catchment ............................................................................................................................................................................ 46 Table 6. Top 10 critical districts according to exposed MPW generated in the Mae Klong catchment .............................................................................................................................................................................47 Table 7. Top 10 critical districts according to exposed MPW generated in the Tha Chin catchment........47 Table 8. Top 10 critical districts according to exposed MPW generated in the Chao Phraya catchment............................................................................................................................................................................. 48 Table 9. Top 10 critical districts according to exposed MPW generated in the Bang Pakong catchment............................................................................................................................................................................. 49 Table 10. Relative contribution of districts to exposed MPW in the three tourist hotspots....................... 52 Table 11. Top 10 districts based on exposed MPW from land-based sources................................................... 58 Table 12. Top 10 districts based on discharge of MPW into the marine environment................................... 59 Table 13.Comparing modeled results with (inter)national literature................................................................... 64 Table 14. Top 10 critical districts according to exposed MPW washed off from diffuse sources............... 70 Table 15. Top 10 critical districts according to exposed MPW generated in urban subdistricts................. 71 Table 16. Top 10 critical districts according to exposed MPW generated in rural subdistricts ..................72 Table 17. Top 10 critical districts according to exposed MPW from point sources..........................................73 BOXES Box 1. Definitions.................................................................................................................................................................. 21 Box 2. NSO Socioeconomic Household Survey.......................................................................................................... 24 Box 3. MPW and Exposed MPW..................................................................................................................................... 25 Box 4. Definitions of Environmental Processes.......................................................................................................... 34 Box 5. Health and Environmental Hazards from Burning (Plastic) Waste.........................................................72 Tables | 7 ACKNOWLEDGEMENTS Plastic Waste Material Flow Analysis for Thailand is the first large scale assessment that integrates waste generation and waste management performance data with hydrological condition data, given the importance of surface water in carrying plastic waste into the marine environment. The study was conducted by a core team from Deltares, Panya Consultants Co., Ltd. and HII: Bastien van Veen, Dr. Napat Jakrawattana, Dr Piyamarn Sisomphon, Mark Hegnauer, Lora Buckman, Bancha Oonta-on, Sutinee Lowattanatakul, Theerapol Charoensuk, Kachapond Chettanawanit, and Kay Khaing Kyaw. Additional support was provided by a wider team from Deltares – Ira Wardani, Rizka Akmalia, Christian Ligouri, and Hélène Boisgontier; Panya Consultants Co., Ltd. – Monluk Nontakaew; and HII – Narongrit Luangdilok, Watin Thanathanphon, Apimook Mooktaree, and Ticha Lolupiman. The work was managed by a World Bank team comprised of Waraporn Hirunwatsiri, Piyarat Kittiwat, Kate Philp, Rattanyu Dechjejaruwat, and Anjali Acharya, under the leadership and guidance of Birgit Hansl and Mona Sur. Solvita Klapare, Klaus Sattler, and Chucheep Wongsupap also provided valuable inputs to improve the report. Kate Philp compiled this Summary Report, and cover and report design were prepared by Sarah Hollis. The study team would like to thank all the stakeholders who participated during the study for their support, including Bangkok Metropolitan Administration (BMA), National Statistical Office (NSO), Regional Environmental Offices (REO.4-15), Department of Local Administration (DLA), Marine and Coastal Resources Research and Development Institute, Marine and Coastal Resources Research Center, Royal Irrigation Department, Kasetsart University, Chulalongkorn University, Thammasart University, Asian Institute of Technology, Electricity Generating Authority of Thailand, Plastics Institute of Thailand, Plastic Industry Club (The Federation of Thai Industries), and Thailand Institute of Packaging and Recycling Management for Sustainable Environment. Special acknowledgement is due to the Ministry of Natural Resources and Environment, Thailand, for enabling and supporting the study. In particular, the study team gratefully acknowledges the dialogue and inputs provided by the Department of Marine and Coastal Resources and the Pollution Control Department. Funding for this report and the webinar series was provided by PROBLUE, an umbrella multi-donor trust fund, administered by the World Bank, that supports the sustainable and integrated development of marine and coastal resources in healthy oceans. 8 | Plastic Waste Material Flow Analysis for Thailand: Summary Report ABBREVIATIONS & DEFINITIONS BMA Bangkok Metropolitan Administration DELWAQ Fate and transport modeling software D-Emissions Plugin to DELWAQ to calculate the fate and transport of plastic DEM Digital elevation model DMCR Department of Marine and Coastal Resources LAO Local administrative organization MFA Material flow analysis MNRE Ministry of Natural Resources and Environment MPW Mismanaged plastic waste MS Excel Microsoft Excel MSW Municipal solid waste NSO National Statistical Office PCD Pollution Control Department RTSD Royal Thai Survey Department SAO Subdistrict administrative organization SDG Sustainable Development Goal SWG Solid waste generated SWM Solid waste management wflow_sbm Hydrological rainfall runoff model Abbreviations & Definitions | 9 EXECUTIVE SUMMARY T hailand, like many countries around the world, is in the midst of a significant plastic waste crisis. In 2019, the Government of Thailand released the Roadmap for Plastic Waste Management 2018-2030 and is developing the National Action Plan on Marine Plastic Debris to alleviate the current impacts and avert future damage caused by marine plastic debris. While these efforts are critical steps toward reining in the country’s plastic pollution problem, further insight is needed into where the plastic waste comes from and how it moves in the environment. This study aims to better understand how plastic waste travels from land-based sources to marine environments by analyzing the material flow of plastic waste in five high-priority catchments (Phetchaburi, Mae Klong, Tha Chin, Chao Phraya and Bang Pakong) and three tourist hotspots (Krabi, Phuket and Ko Samui). The analysis produced reliable results for the generation of plastic waste from land-based sources for all eight locations. The results for waste transport to the marine environment were found to be reliable in only four catchments (Phetchaburi, Tha Chin, Chao Phraya and Bang Pakong) whereas the results for the remaining catchment (Mae Klong) were unreliable due to limited hydrological data. This study presents the first large-scale assessment in Thailand to integrate national waste generation and waste management performance data with actual hydrological conditions to estimate how mismanaged plastic waste is carried and discharged into the marine environment. The study uses the best available data from national sources including from the Pollution Control Department (PCD), the National Statistical Office (NSO), the Bangkok Metropolitan Administration (BMA) and other sources. Consultation on the methodological approach and available data was undertaken with relevant government agencies, academia and private sector representing plastics and recycling industries. By mapping the relationship between waste sources, leakage pathways and plastic discharges to the marine environment, this study identifies the most significant hotspots contributing to marine plastic debris and the specific associated waste handling practices (e.g., open dumpsites, household disposal behavior, etc.). Building on previous analysis on the material flow of plastics in Thailand, this study helps inform policy interventions and investments from the Government of Thailand and local administrative organizations to effectively reduce marine debris. The models developed can also help monitor progress relative to environmental factors, such as seasonal rainfall variations. 10 | Plastic Waste Material Flow Analysis for Thailand: Summary Report KEY FINDINGS: generated, and therefore the large HIGH-PRIORITY CATCHMENTS absolute volumes of uncollected plastic waste. A large amount of uncollected • Despite a high collection and recycling rate, waste in Chao Phraya is disposed a large volume of uncollected plastic waste directly into waterways. as well as many unsanitary disposal facilities result in a significant amount of mismanaged • 10 districts (of 247 in total) account for 51.7 plastic waste (MPW): percent of the total exposed MPW in the high-priority catchments. ö Approximately 11,070 kton of municipal solid waste (MSW) is generated ö Most of the solid and plastic waste is annually—17.4 percent of which is plastic generated in the Bangkok Metropolitan waste. Administration (BMA) area, but most ö Formal collection and recycling rates disposal facilities are situated in the are high with a combined rate of 88.8 surrounding smaller cities and subdistricts. percent. ö The top 10 MPW contributing districts ö While most collected plastic waste is are all situated near Bangkok and are either recycled or disposed of at a sanitary relatively close to the marine environment. disposal facility, nearly a quarter of • Across four high-priority catchments (excluding collected plastic waste is disposed in Mae Klong), on average, 47.6 percent of formal open dumpsites or controlled MPW that ends up in the rivers is discharged dumps, or is openly burned/buried. into the marine environment. ö An additional 214.7 kton/year of plastic waste remains uncollected. ö This represents only about 0.55 percent of the total amount of plastic waste ö Collected but poorly managed plastic that is generated in these areas. waste and uncollected plastic waste result in an estimated 428 kton/year of MPW. ö Higher rates of plastic discharges are associated with the rainy season and lower • Most MPW available for wash-off to rivers averages with the dry season. and the marine environment (exposed MPW) is generated in rural areas (70.1 percent). • An annual average total of 9.3 kton/year of plastic waste is discharged into the marine ö Collection rates are generally much lower environment from four high priority catchments in rural areas and this is also where most (excluding Mae Klong). disposal facilities and open dumpsites are found. ö This is equivalent to a marine plastic footprint of 0.4 kg/capita/year. ö Despite high collection rates, Bangkok is also a significant contributor (18.4 ö During particularly rainy years this may percent) to exposed MPW due to increase to 14.3 kton/year, while it may the large absolute volumes of waste be as low as 4.9 kton/year in drier years. Executive Summary | 11 KEY FINDINGS: is a result of the limited district-specific TOURIST HOTSPOTS data available. • A total of 16.8 kton/year of MPW is • There is an estimated 0.7 kton/year of exposed generated, with the source varying across MPW. the tourist hotspots. ö Exposed MPW is leaked into the ö Approximately 381.9 kton of MSW is environment primarily as point source generated annually—17.2 percent of in the cities (from unsanitary disposal which is plastic waste. facilities) and as mostly diffuse sources ö In Phuket, the MPW is derived from (from uncollected waste) in the more uncollected waste but in Krabi, MPW rural areas. is evenly divided between uncollected • The lack of reliable hydrological data in the waste and disposal at open dumpsites. tourist hotspots led to unreliable results ö The model results indicate that in for the transport of exposed MPW to the Ko Samui, no (plastic) waste remains marine environment. uncollected. This is likely unrealistic but Photo: Shutterstock / NavyBank. 12 | Plastic Waste Material Flow Analysis for Thailand: Summary Report RECOMMENDATIONS • Overall: Consider introducing city-wide clean-up sweeps just before the start of the rainy season. Goal 1: Reduce transport of leaked MPW (downstream in waste chain) • Overall: Improve laws and regulations to support the implementation of measures, including Initially, focus on areas at a close distance from the enforcing separation at source, monitoring and coast that have been identified as key contributing controlling the operation of waste disposal districts (see Table 14 in section 4.4.1): and capacity building of local authority staff • In urban areas: Install trash racks in urban in waste management. drainage systems just before the outlet to a main river or waterway, and clean them daily. Goal 3: Improve the data and underlying models • In rural areas: Install trash racks in irrigation • Increase systematic sampling of the solid canals just downstream from villages. waste generated and waste composition at the Local Administrative Organization (LAO) • In rivers: Promote and expand river clean-up or subdistrict levels. initiatives such as the one managed by the BMA in the Chao Phraya River. • Undertake field studies to assess the material recovery factor for residential waste pickers. • Overall: Analyze possible constraints to installing recommended equipment. These measures • Include a specific solid waste management do not require large financial investments and (SWM) question in the National Statistical Office there may be additional constraints, such as (NSO) annual survey module—for example, one operational costs, preventing progress. that targets the frequency of waste handling practices. • Overall: Monitor plastic waste in the riverine environment as it is intercepted by trash racks. • Require recycling shops to provide a detailed overview of the amounts of the various types Goal 2: Reduce MPW generation (mid-stream in waste of waste that arrive at the locations and their chain) individual recycling rate. • In urban areas: Further improve waste collection, • Require a daily log to be kept at disposal particularly in the Chao Phraya catchment. facilities of how much solid waste arrives at • In rural areas: Develop an efficient and the facility and where each truck comes from. coordinated waste collection system in rural • Monitor the area around controlled dumps and Thailand. open dumpsites to detect leakage of (plastic) • Overall: Invest in well-managed final disposal waste. facilities and upgrade unsanitary disposal • In the future: Once better SWM data is available, facilities (open dumpsites and controlled the modeling can be further improved by dumps), giving priority to the facilities near collecting hydrological data in the tourist waterways, at close distance to the coast and hotspots and small catchments as well as data in key districts. on the water taken out of rivers for irrigation and water levels in reservoirs. Executive Summary | 13 SECTION 1. INTRODUCTION 1.1 BACKGROUND L ike the rest of the world, Thailand is facing the challenge of increasing waste generation, especially plastic waste. Although waste management in Thailand has rapidly improved in recent years (Master Plan of Solid Waste Management 2016–2021), residual waste and plastic waste are still major concerns that could have negative effects, including significant inputs to marine debris. In April 2019, to systematically address the plastic waste challenge, the Government of Thailand released the Roadmap for Plastic Waste Management 2018–2030 and announced the development of a National Action Plan on Marine Plastic Debris to prevent and mitigate plastic waste issues, in line with the Sustainable Development Goal (SDG) 14: “Conserve and sustainably use the oceans, seas and marine resources.” An important step in supporting the Action Plan is to analyze the flow of plastic waste from land-based sources to the marine environment. This report aims to build capacity for material flow analysis (MFA) of plastics in Thailand and to help strengthen the knowledge base of plastic waste with a focus on waste that enters the marine environment. This project in Thailand builds on methodology developed for a similar project conducted in Indonesia (World Bank 2021). In Thailand, a significant amount of solid and plastic waste leaks into the environment and a large amount of plastic is observed in the rivers and in the marine environment. However, little is known about the quantities that are discharged into the marine environment and where the waste comes from. Insight into the physical flow of mismanaged plastic waste is crucial for guiding effective policymaking decisions. 1.2 ABOUT THE STUDY The main questions asked by this study include: • How much plastic waste is being discharged into the marine environment annually? • Where does this leaked plastic waste come from? • What can be done to reduce the discharge of plastic waste into the marine environment? This study is the first large-scale assessment in Thailand where national data of waste generation and waste management performance are integrated with actual hydrological conditions of the rivers—which carry plastic waste from land-based sources into the marine environment. The study applies a methodology and modeling approach (like the one applied elsewhere in the region [World Bank 2021]) to produce estimates of mismanaged plastic waste carried in and discharged by freshwater systems, with high spatial resolution and using the best available data from national sources. Results help establish a baseline of plastic waste discharges into the marine environment in Thailand and help inform the structure, target 14 | Plastic Waste Material Flow Analysis for Thailand: Summary Report activities and monitoring and evaluation framework While acknowledging that smaller plastic particles of the Action Plan. (including microplastics) are of high interest and concern, By incorporating the interdependency between sources, this study considers only the larger fraction of plastics as leakage pathways and riverine plastic discharges, this a starting point. It excludes sources—such as weathering integrated approach pinpoints the most critical hotspots of textiles, paints and tires—that generate microplastics of plastic leakages and the specific waste handling and can reach the marine environment through sewers practices that generate them (e.g., open dumpsites and atmospheric deposition in addition to waterways. or households disposing of waste in waterways). This Although the modeling accounts for processes of approach also quantifies their relative contribution to fragmentation as plastic is carried from land into the the plastic discharge into the marine environment. sea, the results do not make a distinction between Additionally, leakages and hotspots can be linked plastic sizes or plastic types. Only the total plastic to geographical areas (e.g., administrative areas or mass that is discharged into the marine environment (sub) districts) to better differentiate between regions is considered in this study. that need special attention. Most importantly, these The study focuses specifically on five high-priority results can help set local priorities, define interventions catchments that discharge into the upper Gulf of and prioritize investments, and can effectively reduce Thailand (Phetchaburi, Mae Klong, Tha Chin, Chao marine debris while monitoring progress relative to Phraya and Bang Pakong) and three tourist hotspots environmental factors (e.g., rainfall, discharge and (Krabi, Phuket and Ko Samui). The geographic scope annual/seasonal variations), which are quantitatively is shown in Figure 1 and some basic administrative accounted for. information of the focus areas is provided in Appendix B. This report will discuss issues related to data availability, 1.2.2 Outline of the Report knowledge gaps, assumptions and validation, and will provide recommendations for future improvements This report is designed to assess how much mismanaged that can lead to better estimates and more useful plastic waste (MPW) is flowing into the Gulf of Thailand. results. Applying a similar approach in the future will In Chapter 2, the approach and methodology are help to monitor progress toward the implementation presented and explained, and the various definitions of the Action Plan and observe the effectiveness of used in the report are discussed. The different steps in national and local measures in preventing new inputs the models and the data used to develop the models of plastic waste into the sea. and databases are also described. The data gaps and the impact assumptions may have on the final results This report builds on previous studies on MFA of are also identified. plastic in Thailand. Further details on these studies are provided in Appendix A. The results of the models are presented in Chapter 3. The solid waste management model results are 1.2.1 Scope of the Study provided first, followed by the results from the fate and Marine plastic debris originates from many different transport models. Section 3.3 describes the validation sources, including both land- and sea-based activities, of the model results and situates the results among and is often related to the mishandling of municipal, other relevant studies. industrial and agricultural solid waste, as well as loss Chapter 4 provides the final conclusions and recom- of materials such as cargo or fishing gear. mendations, which offer priority lists and examples This study focuses on land-based sources of marine of recommended measures to reduce marine debris. plastic debris resulting from municipal solid waste. Specific recommendations are also provided to address Plastic waste that originates from maritime activities identified data and knowledge gaps. such as fishing and shipping (sea-based sources) as Additional background information and more detailed well as any other industries that are not accounted results, validation and recommendations are available for in the municipal solid waste data used as input in the Appendices. for the study’s estimates is excluded. Section 1.Introduction | 15 Figure 1. GEOGRAPHIC SCOPE OF THIS STUDY Source: Original figure for this publication. 16 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Photo: Shutterstock / YJ.K. Section 1.Introduction | 17 SECTION 2. MODELING APPROACH AND METHODOLOGY I n this chapter, the general approach for the modeling of the material flow of plastic waste in Thailand is described. The relevant processes, tools and modeling methodologies are briefly described in sections 2.1, 2.2 and 2.3. Further description of the underlying approach can be found in World Bank (2021). 2.1 GENERAL APPROACH AND DEFINITIONS A schematic of the data and models that make up the modeling approach is shown in Figure 2. A Solid Waste Management (SWM) model was developed to quantify the amount of plastic emitted to the environment by human activity and demonstrate the various sources and pathways of plastics from origin to disposal. This model provides an estimate of the MPW leaked into terrestrial and riverine environments, as well as the locations of these leakages—which are inputs for the fate and transport models. Wash-off is the driving factor for transport of plastics to surface water, so a hydrological rainfall runoff model (wflow_sbm) is used with a fate and transport model (D-Emissions) to calculate the amount of plastic leakage to the environment that is washed off the land and into rivers. The transport of plastic through the river network is then modeled with a combination of wflow_sbm and DELWAQ to determine the final amount of plastic debris that reaches the marine environment. The general approach for this study involves integrating Thai data on SWM with hydrology to model the flow of plastic waste generated on land, leakages from different land-based sources into waterways and transport through rivers into the marine environment (Figure 3). Clear definitions of the different fractions of plastic waste are essential for proper mass balance computation. See Box 1 for the key definitions used in this study. The material flow diagram in Figure 4 provides insight into the physical flow of plastic waste and the fractions of waste that are transferred down the waste chain or reach a specific site or domain as a final destination. The individual rates and figures are determined in the various steps of the modeling train. 18 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 2. SCHEMATIC REPRESENTATION OF THE MODELING APPROACH Source: Original figure for this publication. Figure 3. CONCEPTUAL FRAMEWORK FOR MODELING MATERIAL FLOW (GREEN/LIGHT BROWN), LEAKAGES (RED) AND WASH-OFF/TRANSPORT OF PLASTIC WASTE FROM LAND-BASED SOURCES VIA RIVERS (BLUE) Solid waste management From mismanaged plastic waste in environment Main Sources of MPW Wash-o and riverine 1 Households transport of plastic 2 Markets, business, other activities waste 3 Consumers 4 Unsanitary/controlled land lls Main Leakages of MPW into environment 5 Direct disposal in water 6 Illegal dumping 7 Fly-tipping 8 Leakages from unsanitary land lls Source: World Bank, 2020. Section 2.Modeling Approach and Methodology | 19 Figure 4. SANKEY DIAGRAM PROVIDING INSIGHT IN THE PHYSICAL FLOW OF WASTE DOWN THE WASTE CHAIN FROM SOURCE TO SEA Plastic Waste Generation Formally Collected Uncollected Disposed to Unsanitary Facilities Other Openly Recycled Burned Disposed Disposed to on Land Sanitary Facilities Exposed to Disposed Not Exposed Environment in Rivers to Environment Dry Environment Washed-off to Rivers Washed-off to and Retained Directly Disposed in Soils in Rivers Retained in Rivers/ Discharged into Captured by Dams Marine Environment Possible pathways for plastic waste material flow from generation to the marine environment Source: Original figure for this publication. 20 | Plastic Waste Material Flow Analysis for Thailand: Summary Report BOX 1. DEFINITIONS Recycled, managed No leakage Sanitary disposal, managed (In)formal No leakage collection MANAGED WASTE Controlled disposal, partly managed Most is managed, but 2-5% leaks into the environment 100% available for wash-o Permanently stored in the Open dumping, mismanged 5-20% available for wash-o , terrestrial environment 100% leaks into the environment rest stored Open burning, mismanged Actual wash-o in waterways Permanently stored in the 100% leaks into the environment 0% available for wash-o , all burned depends on rainfall, rest stored riverine environment UNSANITARY DISPOSAL FAC. SANITARY D. FAC. Fly-tipping, mismanaged 100% leaks into the environment 100% is available for wash-o MISMANAGED WASTE Disposed in water, mismanaged Discharge into marine environment 100% directly disposed in water 100% into waterways 100% leaks into the environment depends on hydrology Open burning, mismanged 0% available for wash-o , all burned 100% leaks into the environment Uncollected waste Other, mismanged 0% available for wash-o , all stored 100% leaks into the environment SOURCES: Economic sector, human activity or infrastructure from which waste is released waste that leaks from controlled dumps (which have some level of containment but into the environment. The means of release (leakage) are specified to indicate the are not as rigorous as sanitary landfills, a rate is attributed). mechanism or the way the waste item leaves the intended cycle (as in Veiga et al. 2016). MPW has a likelihood of ending up in the terrestrial environment and/or in waterways Examples: direct disposal in water (leakage) from households (source) depending on the conditions in which it is handled, contained and how much is exposed UNCOLLECTED WASTE: All waste that is left uncollected (by both formal and informal to rainfall (see Exposed MPW). collection). EXPOSED MPW (AVAILABLE FOR WASH-OFF): The fraction of MPW that is exposed (UN)SANITARY TREATMENT FACILITIES: Sanitary treatment facilities are facilities to rainfall and can be transported by rain (i.e., that can leak from terrestrial environment where solid waste is handled and treated in such a way that it does not result in leakage into waterways). (Burned and buried MPW are not considered exposed to rainfall.) into the environment. At unsanitary treatment facilities, leakages are expected. Whether this will end up in waterways will depend on the permeability of the soil, the inclination of the terrain and the distance to waterways. From point sources of MPW LEAKAGES: Flow of plastic waste into the environment (or from one environmental (e.g., controlled dumps or open dumpsites) a wash-off availability rate is attributed compartment into another), from a particular source, either by accidental (e.g., loss) to determine the potential maximum leakage into waterways. or purposeful release (e.g., littering, direct disposal in water) or by action of physical factors such as rain and wind. The pathway should be further specified as “leakages MARINE DEBRIS: Also referred to as marine litter, is any processed or synthetic into waterways” to indicate the fraction that ends up in rivers through direct disposal material or item that ends up in the marine environment, directly discarded or lost or as a result of wash-off. All leaked plastic results from MPW, but not all MPW leaks from maritime activities (sea-based for example, fishing and shipping), direct littering at into waterways (e.g., it can be burned). the coast or carried from land-based activities via runoff, river outflows, etc. (GESAMP 2019). Plastic marine debris constitutes the plastic fraction of marine debris, which MPW: The fraction of plastic waste that is not adequately collected, treated or contained, tends to be the predominant material. Note that this study focuses only on plastic and can or will end up in the environment. Specifically, MPW accounts for all the marine debris that originates from land-based sources. uncollected plastic waste; all losses from collection and recycling; all plastic waste that ends up in open dumpsites and is openly burned or buried, as well as the plastic Section 2.Modeling Approach and Methodology | 21 The study includes a sequential set of analyses and transported downstream toward the marine uses different types of data and tools (described in environment unless it is retained in the river— more detail in 2.2 and 2.3). The overall approach can either by settling to the riverbed or getting be summarized as follows: captured by natural or artificial obstacles such 1. Leakages of MPW: Population and solid as vegetation or dams. This is simulated by waste handling and management data (e.g., modeling the wash-off (D-Emissions) and plastic waste generated, collected, treated riverine transport of plastic waste with a fate and handling practices) are used to assess and transportation model (DELWAQ). the plastic waste flow and estimate amounts As a result, a spatially and temporally (based on of mismanaged plastic generated within a hydrological variations during the nine-year period) local administrative organization (LAO) and/ variable representation of the transport and fate of or (sub)district. Any plastic waste that is not plastic waste from land-based sources to the marine properly collected and treated can be directly environment can be constructed as a reflection of disposed of in waterways or disposed of certain waste generation (three scenarios: low, mid, and leaked into waterways via the terrestrial and high) and waste management characteristics from environment. A static database is created the communities that live within the catchment. which is considered representative for the 2018 situation based on available data obtained from 2.2 MODELING LEAKAGES OF the Pollution Control Department (PCD), the MISMANAGED PLASTIC WASTE FROM LAOs, the Bangkok Metropolitan Administration LAND-BASED SOURCES (BMA), and the National Statistical Office (NSO). Based on the available data, three scenario This section describes the approach to assess and datasets are constructed to represent low, quantify potential leakages of MPW from land-based mid and high estimates for exposed MPW. sources. 2. Hydrological factors: Runoff as a result of The primary data source for this model is data from rainfall and river flow are the driving forces the PCD, followed by data from the NSO, BMA and that can wash off plastic waste from land other sources. The PCD holds the essential data to into waterways and transport it downstream assess the waste flow through the formal collection and through rivers. Runoff from rainfall and recycling part of the waste chain while NSO holds key river flow is simulated using a hydrological information on the treatment of uncollected waste. There model (wflow_sbm). The process is simulated is no information on the contribution of the informal considering the local topographical conditions, sector on the flow of waste in Thailand. A summary soil-type, land-use and spatially and temporally overview of the data sources, the data limitations and variable meteorological data. A spatially and the assumptions are provided in Table 1. temporally variable representation (time series) 2.2.1 Overview of the SWM Model of runoff and discharge is created based on a historical rainfall time series obtained for The SWM model for this project is developed specifically January 2010 to December 2018 and includes for Thailand. It builds on the unique Thai context, both dry years (2014 and 2015) and wet years the organization of the Thai administration and the (2011, 2013 and 2017). SWM structure. The model is based on the complex solid waste material flow diagrams of the PCD and 3. Plastic fate and transport: Any MPW that three leading Thai universities. Including the insights is leaked into the terrestrial environment gained from the national surveys, the model shows how is exposed to degradation (weathering, mismanaged and uncollected plastic waste may end fragmentation into smaller particles), burial in up in the environment. The SWM model specifically soils and physical barriers that obstruct plastic focuses on potential leakages of mismanaged waste, from washing off. The excess plastic waste is beginning at the point of solid waste generation in the exposed to rainfall and may wash off through material flow diagram. It does not specify or quantify runoff, where it is then transported to a river, the upstream processes. stream or lake. MPW that is washed off to and disposed of directly in waterways will be 22 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 5. SWM MODEL FLOW SCHEMATIC CONSTRUCTED FROM PCD AND NSO ADAPTED SCHEMATICS Source: Original figure for this publication. Thailand produces a large amount of solid waste tationally processed with an MS Excel-based SWM (estimated by Kojima (2019) at 26,850 kton in 2016), but model1 developed as part of this project. not all waste is collected (PCD 2019; Kaza et al. 2018) and a significant amount ends up in the environment 2.2.2 Determining MPW Available for Wash-off (NSO 2020). As illustrated in Figure 3, the two driving The first step in determining the MPW available for forces behind MPW in Thailand are inadequate SWM wash-off (exposed MPW) is to estimate solid waste practices (with final disposal in unsanitary facilities) generation and formal collection rates. Solid waste and inadequate treatment and disposal behavior (i.e., generated per capita is estimated by interpreting how individuals and households handle their waste, in and filtering solid waste generation figures at the particular the uncollected portion). Mismanaged solid LAO level obtained from LAOs and the PCD, along waste and MPW leaks into the environment through with population figures from the Royal Thai Survey these pathways. MPW consists of all uncollected waste, Department (RTSD). There is no data available to all waste that is disposed of in open dumpsites and the differentiate the solid waste generated (SWG) between fraction that is available for wash-off from controlled various sources, including differentiating between waste dumps. Through the specific locations of the formal from residents and tourists. The plastic fraction is (unsanitary) treatment facilities (point sources), the estimated based on waste composition figures from spatial distribution of mismanaged collected waste is the PCD and BMA. Formal collection figures, including captured. The spatial distribution of uncollected waste for recycling, are directly obtained from the PCD and and the inadequate handling thereof (diffuse sources) BMA. is captured through the spread of the population The final destination of collected solid waste and over subdistricts. plastic waste is then determined based on data from A schematic of the SWM model flow diagram is presented in Figure 5. All the SWM data is compu- 1 Microsoft Excel (MS Excel) was chosen as the spreadsheet pro- cessor due to the familiarity of many people with MS Excel for data processing. This familiarity is important for smooth adop- tion and knowledge transfer of the SWM model to the Ministry of Natural Resources and Environment (MNRE) for extension and regular updating of the model. Section 2.Modeling Approach and Methodology | 23 the PCD. This may include sanitary disposal facilities To account for uncertainties, three figures (low, mid (e.g., sanitary landfills) without any leakage to the and high) are estimated for the SWG per capita and environment but may also include unsanitary disposal the plastic content. At the subdistrict and disposal facilities (e.g., controlled landfills or open dumpsites) facility levels, this results in specific low, mid and high which may leak into the environment. estimates of mismanaged waste, feeding into three Next, the amount of uncollected waste is estimated scenarios for leakage patterns in the focus areas. These through the difference between the total amount of SWG three scenarios are considered representative for a and the total amount formally collected (through formal best estimate (midestimate) and a likely range (low collection and recycling). Waste handling practices for and high estimates). uncollected waste are based on an interpretation of the As the SWM data are analyzed on a spatial scale of national survey2 (see Box 2) and are used to estimate subdistrict, this is also the spatial scale of the derived diffuse leakages from the uncollected waste fraction leakage estimates. For catchment-scale modeling directly into waterways and into the environment. this has been shown to be adequate in resolution Lastly, while some MPW that is leaked into the for understanding leakage patterns and analysis of environment is exposed to natural forces that may possible mitigation scenarios. The tourist hotspot mobilize this waste and move it to a waterway, not all locations chosen for this study are much smaller in MPW is exposed to these forces (e.g., waste that is buried area and therefore much more sensitive to localized or burned). In locations where high concentrations of waste handling practices and small-scale hydrological MPW can be found (e.g., open dumpsites) only a small events. To account for lack of resolution in the SWM fraction of the total amount of the waste disposed is data, the calculated leakage rates are mapped to a exposed to the forces that could cause wash-off. In the high-resolution population dataset.3 This raster dataset model this is captured by an “available for wash-off” is composed from satellite imagery to approximate the parameter. The type of formal disposal facility is used locations of buildings as a proxy for population density. to estimate the amount of waste that may be exposed In this way, the exact location of SWM leakage can to wash-off at point sources (exposed MPW), with the be better approximated for these small catchments. fractions based on expert judgement due to a lack of scientific data. See Box 3 for more details. BOX 2. NSO SOCIOECONOMIC HOUSEHOLD SURVEY The socioeconomic household survey was conducted by 7. Dispose in public space the NSO in 2018. This household survey provides key 8. Others information to validate collection data and to quantify handling practices for uncollected waste. The NSO summarized the responses and reported the results as a percentage for each province. The survey asked people in the household how they handle their municipal solid waste (MSW). This multiple-choice Choices number (1) and (3) are considered as formal question included the following potential responses: collection for formal treatment and recycling. The rest are considered uncollected and are managed by the 1. Officially collected by government people in the household. The options for animal feed 2. Openly burning (4) and composting (5) were omitted since because they are not relevant to plastic waste. The remaining options 3. Brought to landfill are recalculated to find the relative percentage of each 4. Feed the animals at home for the handling of uncollected waste. These percentages 5. Composting/use as fertilizer at home are used to estimate the fraction of uncollected waste that is available for wash-off. 6. Dispose into river/canal 3 https://data.humdata.org/dataset/thailand-high-resolution-pop- 2 Household Socio-Economic Survey Project 2018, the National ulation-density-maps-demographic-estimates (accessed July 2, Statistical Office (NSO). 2020). 24 | Plastic Waste Material Flow Analysis for Thailand: Summary Report BOX 3. MPW AND EXPOSED MPW At locations where high concentrations of waste can be at open dumpsites this accounts for 5–20 percent (with found, it is assumed that at any point in time only a fraction a mid-point estimate of 10 percent) of (plastic) waste of the amount of waste is exposed to the natural forces that is at any one point in time exposed to rainfall. Only that may lead MPW to wash-off. As a result, not all waste this amount is then available for wash-off. For the three that is disposed on a controlled dump or open dumpsite scenarios (low, mid and high) the following exposure ends up exposed and available for wash-off. rates are used in the SWM model: 5 percent for the low scenario, 10 percent for the mid scenario and 20 percent At controlled dumps it is assumed that only the lighter for the high scenario. fractions of (plastic) waste are leaked into the environment (through various means) and therefore considered From sites where (plastic) waste is openly burned, it is “mismanaged.” It is estimated that from controlled dumps, assumed that all waste leaks into the environment and 2–5 percent (with a mid-point estimate of 3 percent) of is therefore mismanaged. However, it is also assumed (plastic) waste may leak into the environment (through that no (macro) plastics are present after burning and mobilization by wind, rain, animals, etc.). This percentage that 0 percent of (plastic) waste is available for wash-off is considered exposed to rainfall and available for wash-off. from locations where waste is openly burned. Similarly, For the three scenarios (low, mid and high) the following for buried (plastic) waste, it is assumed that 0 percent of leakage rates are used in the SWM model: 2 percent for (plastic) waste is available for wash-off. the low scenario, 3 percent for the mid scenario and 5 Whether exposed MPW will wash off depends on actual percent for the high scenario. rainfall and is calculated by the fate and transport model At open dumps, all waste is considered to have leaked into (D-Emissions). The exposed MPW amounts are simulated the environment and is therefore considered mismanaged. as point sources which are then modeled as an amount However, only waste on the top layer and at the foot of in one grid cell of the fate and transport model. This is the dumpsite is considered exposed to rainfall and could further explained in section 2.3. be mobilized (see Figure B3.1 below). It is estimated that Figure B3.1. WASTE EXPOSED TO RAINFALL AND POTENTIALLY MOBILIZED Section 2.Modeling Approach and Methodology | 25 Table 1. SUMMARY OF SWM MODEL DATA SOURCES, LIMITATIONS AND ASSUMPTIONS Indicator/ Data source Data limitations Assumptions made Expected impact of subindicators assumptions (1) Total SWG (population × solid waste generated per capita) Population RTSD None Population dataset from 2018 used — SWG per capita PCD guideline No detailed One estimate is based on LAO High uncertainty (2019) SWG per capita reported SWG figures4 with outliers translates into a wide available at LAO/ (10% smallest and 10% highest) range of estimated LAO (2020) subdistrict level replaced with the average SWG per SWG and very high NSO survey capita figure for the province. uncertainty on (2019) uncollected waste. One estimate is based on LAO Further downstream in reported formal collection figures the material flow model and NSO collection rates. SWG per this will result in a wide capita figures were multiplied with range for (exposed) a factor to obtain collection rates uncollected waste. more in line with NSO results at provincial level. Three scenarios are generated for SWG and One estimate is based on the PCD represent low, mid, and guideline. high estimates. Subdistrict results are arranged to get low, mid, and high estimates. (2) Total plastic waste generated (SWG x plastic content) Plastic content PCD (2004) There is no Mid estimate is based on PCD This results in a wide underlying estimates. range for plastic content BMA data from PCD and subsequently leads (2007–2019) Low estimate is based on the estimates. to a wide range for average for non-recyclable plastic (exposed) MPW (from PCD estimates over the period 2017–2019 (BMA both collected and differentiate data). uncollected waste). according to High estimate is based on the Therefore a wide range region and LAO average for non-recyclable plastic for plastic discharge type. over the period 2010–2014 (BMA estimates is expected. BMA differentiates data). between non-recyclable and recyclable plastics. (3) Total plastic waste collected (formally collected + recycled) Total (plastic) PCD database5 No data available Solid waste collected is May lead to net waste formally (2019) on origin of waste proportionally distributed over the “import/export” collected disposed at formal various formal treatment facilities of waste in the BMA database disposal sites. according to the formal capacity. model because of (2019) discrepancies between BMA dataset Solid waste is collected and Both estimated total SWG is aggregated disposed within the same province representing and installed capacity in data at Bangkok (except for Bangkok province). 2018 collected an LAO/subdistrict. provincial level waste and does not Potential over/under- provide insight at estimation of MPW at district level. LAO/(sub)district level because all waste 4 Although reported as SWG, the figures are derived from the collected waste figures directly. 5 Thailand Municipal Solid Waste Management Database. URL: https://thaimsw.pcd.go.th/report1.php. 26 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Indicator/ Data source Data limitations Assumptions made Expected impact of subindicators assumptions with final destination of the specific LAO/ (sub)district is used to estimate MPW and MPW per capita for that LAO/(sub)district. There is little to no effect on discharges from catchments as “import/export” differences are mainly in the upstream boundaries of the catchment. Limited uncertainty on MPW from point sources. Results for Bangkok are not representative at (sub)district level and should only be interpreted with caution at provincial level. Collected by No data No data available Not considered Collection by waste waste pickers available pickers is generally very small. It is expected that the impact on the results is negligible. (4) Total plastic waste uncollected Handling Household Data is only Provincial value is representative at Discharges of practices for Socio-Economic available at subdistrict level. catchments are uncollected Survey Project provincial level. representative, but waste 2018, NSO, de-aggregated results Only multiple as the most to LAO level are choice where recent data unreliable. respondents for household can choose solid waste multiple options is practices available. Survey is based on a small sampling size. (5) Total recycled plastic waste (recycled from waste dealer and recycle plant) Recovery from PCD database No data is It is assumed that all waste collected There is potential over/ recycling shops available on origin at recycling shops is recycled and underestimation of BMA database of waste recycled. that there are no recycling losses MPW. However, this from the shops. leakage source is small No data is and it should not have a available on significant influence on effective recycling the discharge results. fraction. No validation dataset is available. Section 2.Modeling Approach and Methodology | 27 Indicator/ Data source Data limitations Assumptions made Expected impact of subindicators assumptions (6) Total plastic waste disposed to final destination (disposal to sanitary landfills + controlled dumps + official dumpsites + total recycled plastic waste) Disposal to PCD gate data No data is All waste is formally collected and is There is no effect on the sanitary disposal available on evenly distributed over the available estimated discharges, PCD facility facilities origin of waste treatment facilities according to but there is uncertainty classification (sanitary disposed at formal installed capacity. surrounding the actual landfills, treatment facility. flow of (plastic) waste. incinerators, integrated facilities, etc.) Disposal to PCD controlled Same as above. Same as above. Same as above. unsanitary dump data disposal facilities (controlled dumps) Disposal to PCD open Same as above. Same as above. Same as above. unsanitary dumpsites data disposal facilities (open dumpsites) Disposal to PCD open Same as above. Same as above. Same as above. unsanitary burning data disposal facilities (open burning) (7) Total MPW ([total uncollected plastic waste + losses from collection] + total plastic disposed of to open dumpsites + leakages from controlled dumps) Disposal to Same data as No information on It is assumed there is 0% leakage of If there is a small sanitary disposal numbers (4) actual leakages is waste. amount of plastics facilities and (6) available. leaked at these (sanitary facilities, it may result in landfills, a slight underestimate incinerators, of MPW. integrated facilities, etc.) Disposal to Same data as No information on There are three ranges of leakage The range is considered unsanitary numbers (4) actual leakages is of plastic waste going to controlled realistic to capture the disposal and (6) available. dump: low (2%), mid (3%) and high uncertainties and the facilities (5%). Rationale: Waste is mostly light resulting MPW range is Expert opinion6 is (controlled used upon initial plastic bags and other waste that wide. dumps) consultation with may be blown away and leak into the environment. relevant agency. Disposal to Same data as No information on It is assumed that 100% leaks into There is no effect. unsanitary numbers (4) actual leakages is the environment. disposal and (6) available. facilities (open dumpsites) 6 There are no scientific studies available to estimate potential leakage rates from various disposal facilities. Therefore, similar values have been considered as were used in a similar material flow study for Indonesia (World Bank 2021). Although it was not possible to compare the conditions at disposal facilities on the ground, due to the absence of verified local Thai estimates and the fact that the estimates used in the study for Indonesia were provided by solid waste management experts, also based on global experience (including personal observations at disposal facilities in Thailand), it is believed these are best estimates that can be used until better (local) estimates based on scientific research become available. 28 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Indicator/ Data source Data limitations Assumptions made Expected impact of subindicators assumptions Disposal to Same data as No information on It is assumed that 100% leaks into There is no effect. unsanitary numbers (4) actual leakages is the environment. disposal and (6) available. facilities (open burning) (8) Total exposed MPW (available for wash-off) (from sanitary landfills + controlled dumps + formal dumpsites + uncollected plastic waste) From unsanitary Calculation: Expert opinion6 is It is assumed that 100% of MPW There is no effect. disposal Total plastic used upon initial (leaked plastic waste) exposed is facilities— waste disposed consultation with available for wash-off. controlled relevant agency. Landfill When landfill coordinates are dumps (leakage) coordinates available they are considered as from PCD point source. From unsanitary Calculation: Expert opinion7 is There are three ranges for exposed The wide range for disposal Total plastic used upon initial MPW (available for wash-off) going exposed MPW from facilities—open waste disposed consultation with to open dumpsites: low (5%), mid open dumpsites is dumpsites Open dumpsite relevant agency. (10%) and high (20%). Rationale: considered realistic Only the top layer and the foot are to capture the coordinates exposed to the elements (rain and uncertainties and the from PCD wind) and may be transported. resulting discharge range is wide. When open dumpsite coordinates are available they are considered as point source. From unsanitary Calculation: Expert opinion is Complete burning is assumed with There are a limited disposal Total plastic used upon initial 0% of MPW exposed (available for number of locations, facilities—open waste disposed consultation with wash-off). which may result in burning relevant agency. underestimation of Open burn-site discharge range. coordinates from PCD 2.3 MODELING WASH-OFF AND • Relate these land cover types to different soil TRANSPORT OF PLASTIC WASTE infiltration capacity rates TO THE SEA • Simulate the surfaces runoff toward the (small) rivers 2.3.1 Rainfall-runoff Modeling To simulate the rainfall-runoff process for the catchments The rainfall-runoff process is the main driver of the in Thailand, wflow_sbm models are setup. Wflow_sbm wash-off of plastic waste. The main hydrological is a fully distributed, physically-based hydrological component is the direct surface runoff. This process model. happens when the rainfall cannot infiltrate the ground. The main relevant processes included in the wflow_sbm This is often the case in high-density paved areas model are: (e.g., urban areas with dense road network) that have reduced infiltration capacity of the soil and during • Rainfall interception high-intensity rainfall that exceeds the infiltration • Soil-related processes (infiltration, evaporation) capacity of the soil. • Routing of the sub-surface flows Direct surface runoff transports the plastic waste over • Routing of the surface flows the surface toward the (small) rivers. To accurately • Simple reservoir and lake routing processes simulate this process, a detailed catchment model is needed. It should be able to: An overview of the relevant processes in the wflow_sbm • Distinguish between different land cover and model is shown in Figure 6. soil types Section 2.Modeling Approach and Methodology | 29 Figure 6. OVERVIEW OF THE WFLOW_SBM PROCESSES Source: https://deltares.github.io/Wflow.jl/dev/. Since the wflow_sbm model is fully distributed, all downstream direction to other land cells, river cells input parameters can be provided as spatially varying or directly to the marine environment. For the tourist parameters. Parameters can be directly linked to land hotspots, the latter process (direct runoff to the marine cover types and/or soil types. In this way, models are environment) is very relevant because there are no, or derived with a strong link to observed features of the a limited number of, (big) rivers to transport the water landscape and processes are simulated based on and plastic to the marine environment. An example the best available knowledge of the physical system. for Ko Samui is presented in Figure 7. The hydrological models are set up for the five mainland Since the process depends also on the resolution of basins (Chao Phraya, Tha Chin, Bang Pakong, Mae the model, an analysis is done to find the optimal Klong and Phetchaburi) as well as for the three tourist resolution of the model. It was found that to represent hotspots (Krabi province, Phuket and Ko Samui). The the important processes that can be modelled with basics of the modeling approach are the same for all the wflow_sbm model, a resolution of 300×300 m2 basins. For the tourist hotspots, the model resolution would suffice for the island models. For the mainland is higher to better account for the smaller-scale catchments, which are much larger in size, a spatial hydrological features of the landscape. For the five resolution of 1×1 km2 is found to be optimal. To show the mainland basins, models have been developed with a difference in detail between different model resolutions, resolution of 1×1 km2. For the three tourist hotspots, the outlet points of the model to the ocean are shown the model resolution was increased to 300×300 m2. for three different resolutions in Figure 8. This figure The wflow_sbm model calculates both land and river shows that water is not only discharged via the rivers runoff. In the model, a distinction is made between (blue lines), but also directly as surface runoff from land cells and river cells based on the upstream area the land to the ocean. of the cell. Water can move from the land cells in a 30 | Plastic Waste Material Flow Analysis for Thailand: Summary Report The hydrological model also includes a lake and reservoir For the other reservoirs, assumptions—partly based on module, to simulate the effect of reservoir management global data—are made to simulate reservoir outflow on the downstream flows. This is highly relevant for accurately. the five mainland basins where a total of 16 reservoirs Assumptions and Limitations are included in the model schematization. These reservoirs have a large impact on the hydrology and Before applying the wflow_sbm model for a material can also trap solid waste. An overview of the reservoirs flow analysis or when applying the wflow_sbm model included in the hydrological model is presented in for any other purpose, it is important to understand Figure 9. Only the most important reservoirs had data the main assumptions and limitations of the model. available to set up, calibrate and validate the model. See Table 2 for details. Figure 7. EXAMPLE OF KO SAMUI SHOWING THE PRINCIPLES OF LAND AND RIVER RUNOFF Source: Original figure for this publication. Section 2.Modeling Approach and Methodology | 31 Figure 8. OUTLET POINTS OF THE MODEL TO THE OCEAN WITH DIFFERENT RESOLUTIONS. IN BLUE, THE RIVERS ON KO SAMUI Source: Original figure for this publication. Figure 9. OVERVIEW OF THE RESERVOIRS WHICH ARE INCLUDED IN THE HYDROLOGICAL MODEL.7 IN BLACK, THE CATCHMENT DELINEATION FROM THE DEPARTMENT OF WATER RESOURCES (DWR) IS SHOWN Source: Original figure for this publication. 7 The stream order is a positive integer value used to indicate the level of branching in a river system. According to the “top down” system de- vised by Strahler, rivers of the first order are the uppermost tributaries. If two streams of the same order merge, the resulting stream is given a number that is one higher. If two rivers with different stream orders merge, the resulting stream is given the higher of the two numbers. 32 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Table 2. SUMMARY OF THE ASSUMPTIONS AND LIMITATION IN THE HYDROLOGICAL MODELS AND THE IMPACT ON THE RESULTS Assumptions made Expected impact of assumptions Use of global data sets Digital elevation model (DEM): The use of a global DEM results in less accurate stream for model setup network, especially in the downstream regions of the catchments. The impact on the total After a quick catchment area and plastic wash-off is probably low. assessment of available Land/soil data: The land cover data and soil data are coarse. The global data provides less local datasets, it detail, resulting in lower model performance. This can be (partly) fixed by calibration of the was concluded that model, so the overall impact of this assumption is probably low for the mainland areas. For only datasets for the coastal zones and small island, the impact is higher as the land cover data for these rainfall and reservoirs regions is very inaccurate. In fact, in Ko Samui no urban build-up is seen in the land cover could be used in the data, resulting in unrealistically low wash-off rates. Improved land cover data could fix this. hydrological model. The other underlying Dam/reservoir data: This information is crucial for correct simulation of the flows in the datasets were obtained rivers. Relying on global data alone will heavily affect the results of the hydrological from global datasets models. A validated local dataset is required to improve the models. This dataset can then specifically established be used to change the model parameters such as the target levels (both minimum and for hydrological maximum) and the release discharge rates for each reservoir. assessments of It is assumed that 100% of incoming MPW remains trapped at the dams/reservoirs. catchments in the Therefore, if certain dams/reservoirs are not included in the model then the discharge may absence of local data. be overestimated. Considering that most dams are located in the upstream catchments and only a small fraction of total MPW is trapped, the effect is likely small. Limited calibration of Calibration of the models is the way to improve model performance. The limited the hydrological models calibration results in low performance of the hydrological models in Mae Klong and Phetchaburi catchments (see section 3.3) and for the smaller catchments and islands. Under/overestimation of runoff and/or discharge will result in under/overestimation of MPW wash-off and transport. Diversions and canals The current model is built on top of the global MERIT Hydro dataset. This dataset is used not included in the to derive the (natural) stream network. For the upstream part of the catchments, this works model very well, but for the downstream, flat part of the catchments, the derived river network is not accurate and contains errors. This is especially true of the many man-made irrigation and drainage canals that are excluded from the dataset, causing incorrect drainage patterns in this part of the catchment. The wflow_sbm model also works with a one-directional flow that causes some errors in the downstream part of the catchment where many diversions of the flow exist. Large diversion can potentially be added to the model by assuming fixed abstraction rates from the main rivers. This has only been done for the Mae Klong catchment in a very simple manner by adding one abstraction just upstream of the Mae Klong dam. In some catchments, the diverted volumes are normally small. Therefore, on the total plastic wash-off that may reach the marine environment, the impact of this limitation is expected to be low. For specifically Mae Klong and Phetchaburi, the total volume of diverted water is relatively large compared to the total discharge volume of these rivers. In these catchments, the impact of these diversions is potentially large, resulting in under or overestimation of the total runoff and plastic discharge in the model. Urban drainage not Small-scale (urban) drainage structures (canals, pumps, tunnels) are not included in explicitly included in the the model. A detailed analysis of the urban hydrology is therefore not possible using model8 the current models. However, the urban areas are included in the models as areas with reduced infiltration. The general effect of urban areas generating more plastic discharge can therefore be simulated with the current models. 8 To correctly model the hydrology in the urban environment, a more complex hydrological model should be used. This model is very different from a catchment model like wflow. Such a model should, for example, be able to incorporate two-directional and energy-gradient driven flow (i.e., water can flow in two or more directions) and the model should be able to include typical urban hydrological processes like con- trolled flow (pumps, gates) and flow via sewer pipes. The urban environment also requires a model to be set up on a (much) higher resolution to account for these small details that strongly determine how water moves through an urban area. As a simpler workaround, the effect of plastic removal due to urban drainage structures in the current model could potentially be included by adding one or more artificial dams in the wflow model at the locations where the water from the Bangkok areas enter the main rivers. However, this was not included in the model since this requires a thorough analysis on where these fictive barriers would have to be placed, based on the real situation in the Bangkok drainage system. This obviously also needs significant observation data. Section 2.Modeling Approach and Methodology | 33 2.3.2 Fate and Transport Modeling of Plastics mass is washed off to the surface water, it is picked up As shown in Figure 10, the fate and transport modeling by the river transport model. This models the fate and comprises two models that apply a spatially and transport of plastic as it moves downstream through temporally variable numerical modeling approach. the surface water network from its source to the final The emission model shows the fate and transport endpoint where it is discharged from the river mouth of plastics on land from the source of leakage to to the open sea. While on land or in the surface water, wash-off into surface water. These calculations are plastic is subjected to a number of environmental performed on each cell of the model grid and subjected processes (that is, degradation, burial, retention, etc.) to the time-varying rainfall runoff as calculated by the See Box 4 for details. Each of these is described in hydrology model. There is no transport of plastics on further detail in the following sections. land between the model cells. Instead, once plastic Figure 10. SCHEMATIZED DIAGRAM OF THE APPROACH TO FATE AND TRANSPORT MODELING OF PLASTICS Source: Original figure for this publication. BOX 4. DEFINITIONS OF ENVIRONMENTAL PROCESSES Wash-off: The rate of plastic that is moved from paved available to wash-off (i.e., burial in the ground, trapping and unpaved surfaces to the surface water as a function by vegetation and/or infrastructure) of the rainfall runoff rate Retention in rivers: All processes which, when combined, Degradation: All processes which, when combined, describe describe the capture and retention of plastic within the the physical breakdown of plastic into smaller fragments surface water and is approximated using a standard and particles that are not modeled (i.e. physical weathering, sedimentation process exposure to UV radiation, mechanical breakdown by road Capture behind dams: At dams and reservoir locations, traffic, humans and/or animals) it is assumed that 100 percent of plastics are retained and Burial: All processes which, when combined, describe properly disposed. the capture and retention of plastic so that it is no longer 34 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Wash-off, Fate and Transport Modeling of Plastic D-Emissions calculates the rate of wash-off for each Waste from Land: D-Emissions computational cell based on the infiltration excess D-Emissions is a plugin of the fate and transport calculated by the wflow_sbm model and the source of modeling software DELWAQ which calculates the emission. Wash-off is calculated as a first-order process transport of plastic from the terrestrial environment with a homogenous rate so the rate of plastic wash-off to surface waters and the various processes which is directly proportional to the rainfall runoff within an the plastic is subjected to along the way. upper and lower bound. During dry periods, plastic mass accumulates on the land surface, which is then There are three main pathways through which MPW available to wash-off during the next rainfall event. can be released into the environment (Figure 11): Fate and Transport Modeling of Plastic Waste in • Direct disposal in water Rivers: DELWAQ • Leakage from dumping/fly-tipping The routing of surface water is provided by the • Leakage from unsanitary landfills (controlled dumps wflow_sbm model as described in section 2.3.1. This and dumpsites) approach applies a DEM to show the water and plastic mass are transported from each cell to its nearest Any plastic waste that is not (properly) collected, downstream neighbor. Figure 12 shows an example contained and treated (MPW) can leak into the of how this is schematized. The mass flux of plastic environment ([1], [2] and [3] from Figure 11). Some that is transported in the surface water is directly MPW is exposed to rainfall and may at some point wash proportional to the mass transport flux of water as off to a waterway or river [4] or be disposed directly calculated by the hydrology model. in water [1]. In the environment, MPW is exposed to forces that degrade [6] or bury [7] it. D-Emissions is In a waterway, plastic is subsequently exposed to used to simulate these two processes as first-order forces that can further degenerate or trap it (see [8] removal functions. Plastic waste that is degraded or and [9] in Figure 11), such as settling to the river buried remains in the terrestrial environment and is not bottom or becoming caught in vegetation. Plastic remobilized. The remaining fraction of plastic waste waste can be trapped or retained by natural (lakes is then available to wash-off and can be transported and vegetation) or artificial (dams, waste traps, etc.) to a waterway, river or lake. Figure 11. CONCEPTUAL FRAMEWORK OF THE FATE AND TRANSPORT OF MPW FROM EMISSION (DIRECT DISPOSAL IN WATER, LEAKAGES FROM FLY-TIPPING AND DUMPSITES) TO SURFACE WATERS INCLUDING THE RETENTION PROCESSES APPLIED ON LAND AND IN RIVERS Source: Deltares. Section 2.Modeling Approach and Methodology | 35 Figure 12. SCHEMATIC OF FATE AND TRANSPORT MODELING BASED ON WFLOW_SBM GRID. PLASTIC IS WASHED OFF OF THE LAND SURFACE INTO THE SURFACE WATER, WHICH IS THEN CARRIED DOWNSTREAM TO THE NEAREST DOWNSTREAM NEIGHBOR Source: Original figure for this publication. barriers that may prevent it from reaching the marine environment. Any other fraction of plastic waste is discharged into the marine environment and becomes plastic marine debris. Although dams and reservoirs have been included in the models as retention points, trash racks have not been incorporated in the models. Trash racks are present in some cities in the urban drainage systems and sometimes in smaller rivers and canals. These structures may capture floating MPW before it reaches the marine environment. However, observations have shown that their retention efficiency varies between different racks and with the season (e.g., during wet season, grid can be lifted to prevent flooding upstream). Assumptions and Limitations The MFA methodology used in this study considers all plastic mass as one entity. Therefore, environmental processes based on the size, shape, density and/or polymer type are not modeled explicitly. To avoid overparameterization of the model where these parameters cannot be quantified, the model includes three processes: degradation of material on land, burial in soils and retention within the surface water network. Each of these processes are described as first-order removal processes with a constant rate and have been estimated based on literature and expert judgement, while ensuring a complete mass balance. Photo: Shutterstock / MaeManee. Further details are provided in Table 3. 36 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Table 3. SUMMARY OF THE ASSUMPTIONS AND LIMITATION IN THE FATE AND TRANSPORT MODELS AND THE IMPACT ON THE RESULTS Process/ Data Assumptions made Expected impact of assumptions process limitations parameter Degradation No data Includes all processes which, when, Calibration of rate constant could available for combined describe the physical only be performed for the five priority degradation breakdown of plastic waste into smaller catchments. Therefore, we expect of total plastic particles that are not modeled (i.e., the degradation process to be well mass on a physical weathering, exposure to UV representative of large catchments in catchment radiation, mechanical breakdown by road Thailand, but may be overestimated in scale traffic, humans and/or animals). smaller coastal catchments Microplastics resulting from degradation The MFA approach means that are assumed to be retained on land and microplastics are not modeled explicitly are not modeled in the environment. in the environment. Therefore, we cannot quantify the extent of influence First-order process with rate constant [-d]. of microplastics on the total discharge This rate constant is determined through of plastics from rivers to sea, but we a combination of model calibration and assume this to be small relative to expert judgement. larger plastic items. Degradation is assumed to be homogenous over area; different rate constants are applied for paved and unpaved area. Single rate constant is determined through calibration of model to measurements of plastic discharge at river mouths of five priority catchments and is applied to all catchments. Burial No data Includes all processes which, when Calibration of rate constant could available for combined, describe the capture and only be performed for the five priority burial of total retention of plastic so that it is no longer catchments. Therefore, we expect the plastic mass on available to wash-off (i.e., burial in the burial process to be well representative a catchment ground, trapping by vegetation and/or of large catchments in Thailand, but scale infrastructure). may be overestimated in smaller First-order process with rate constant [-d]. coastal catchments. This rate constant is determined through The global datasets used to define land a combination of model calibration and cover are too coarse to adequately expert judgement. represent smaller catchments in Burial only occurs over unpaved area. Thailand. This can result in an overestimation of burial if built-up areas Single rate constant is determined through in a catchment are smaller than the calibration of model to measurements of dataset resolution. plastic discharge at river mouths of five priority catchments and applied to all catchments. Section 2.Modeling Approach and Methodology | 37 Process/ Data Assumptions made Expected impact of assumptions process limitations parameter Wash-off No data Wash-off of plastic from land is directly Results for individual catchments were available for proportional to rainfall runoff. shown to be sensitive to the ratio of wash-off of paved to unpaved areas, as the runoff All land surface can be categorized as macroplastics rate for paved areas tends to be paved or unpaved. Differing rate constants from land much greater than for unpaved areas, are applied for both categories. surface on a resulting in a higher wash-off rate. The catchment Plastic will begin to wash off after a certain global datasets used to define land scale lower threshold of rainfall runoff is reached cover are too coarse to adequately [mm/d]. represent smaller catchments in There is an upper threshold runoff rate at Thailand. For example, no built-up which all plastic is washed-off [mm/d]. areas in Ko Samui exist in the land cover dataset and the entire island Both the lower threshold and maximum is considered unpaved. This results wash-off rates are determined through in very little runoff generated and a combination of model calibration and consequently little wash-off of plastics. expert judgement. Single rate constant for both is determined through calibration of model to measurements of plastic discharge at river mouths of five priority catchments and applied to all catchments. Observations were not available to calibrate the threshold values for paved and unpaved areas independently. Both are based on expert judgement. Retention in Insufficient Includes all processes which, when There is significant uncertainty in the rivers data available combined, describe the capture and actual retention of plastic in rivers to quantify retention of plastic within the surface because channel features could not retention rate water. be modeled at the large spatial scale constant at of this study, and due to the unknown Modeling does not take into account a catchment nature of the behavior of plastics in the specific river channel features (i.e., bed scale natural environment. The only way to shape, roughness, vegetation, etc.) reduce this uncertainty is to perform Approximated using a standard detailed measurements in the field to sedimentation process dependent on flow quantify this behavior. rate and constant settling velocity applied for inorganic matter [m/d]. Capture by Estimates of 100% of plastic mass is retained at the The presence and location of dams dams retention at dam. are derived from global datasets and dams at other may not be representative of the All plastic retained at the dam is removed locations or of and disposed of in a sanitary landfill facility. actual water management practices in other types not Thailand. Only large infrastructure with available All dams are treated equally regardless of reservoirs at the spatial resolution of size, type or location. the input dataset are included. In the Chao Phraya dam lies case that 100% of plastic is not actually upstream of removed at infrastructure the model the model may underestimate plastic transport boundary, and through the rivers. In the case that therefore could critical infrastructure is not included, not be used the model may overestimate plastic directly in this transport through rivers. study for model It is not yet known how water collection calibration and diversion through urban canals affects plastic transport due to limitations to the spatial refinement of the hydrology model used in this study. 38 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Photo: Shutterstock / Iurii Stepanov. Section 2.Modeling Approach and Methodology | 39 SECTION 3. STUDY RESULTS I n this section, the key results from the MPW assessment and the plastic discharge estimates are presented and discussed. Each section is divided into two parts where respectively the results for the high-priority catchments and the tourist hotspots are presented. 3.1 ASSESSMENT OF MPW FROM LAND-BASED SOURCES In this section, the key results from the MPW assessment in the terrestrial environment are presented and discussed. The assessment is separated into two parts, the first part presents and discusses the results for the high-priority catchments and the second part provides the results for the tourist hotspots. Detailed results segregated by high-priority catchments and tourist hotspots are presented in Appendix C. 3.1.1 High-priority Catchments This section presents an overview of the SWM and MPW assessment results for the five high-priority catchments that discharge into the upper Gulf of Thailand (Phetchaburi, Mae Klong, Tha Chin, Chao Phraya and Bang Pakong). Solid Waste and Plastic Waste Generated The SWM model results indicate that in the high-priority catchments approximately 11,070 kton of municipal waste is generated annually (mid-point estimate). The range for these high-priority catchments is between 9,040 and 14,610 kton of solid waste per year. This is largely correlated with population—the Chao Phraya catchment, with a population of nearly 16 million (four times that of the next largest catchment) generates the highest amount. Based on data from the PCD, plastic content makes up an average of 17.4 percent of solid waste. The PCD data differentiates plastic content relative to LAO classification and defines plastic content as higher in more densely populated areas (cities and towns) compared to more rural areas. However, on average, each high-priority catchment has a similar plastic content estimate. It is projected that a total of 1,923.3 kton of plastic waste is generated each year in the high-priority catchments. Final Destination of SWG Most collected solid waste in the high-priority catchments is either recycled or ends up at sanitary disposal facilities and is well contained. However, 4.4 percent is disposed in controlled dumps, 18.9 percent ends up in formal (open) dumpsites and 0.4 percent is openly burned at formal open burn facilities. Part of the amount disposed in controlled dumps or open dumpsites is assumed available for wash-off and may wash off during rainfall events, flowing into waterways. Most plastic is formally collected or recycled as part of solid waste, but a significant amount of plastic remains uncollected (mid-range estimate of 11.2 percent, 214.7 kton per year) in high-priority catchments. With the addition of the estimated plastic waste that is disposed of in formal open dumpsites and formal open burning locations and the potential leakages from controlled dumps, a total of 428 kton/ 40 | Plastic Waste Material Flow Analysis for Thailand: Summary Report year of MPW is obtained (with a range of 242.9–1,087.0 Exposed MPW (Plastic Waste Available for Wash-off) kton/year). Total MPW exposed—the amount of plastic that is The source of MPW varies across the catchments (Figure available for wash-off—is derived from uncollected 13). The populous Chao Phraya catchment shows a plastic waste (directly disposed in water or dumped/ much higher proportion of MPW from uncollected fly-tipped), combined with the fraction of collected plastic waste compared to the other catchments that but mismanaged plastic waste available for wash-off show a higher proportion from open dumping. This from controlled dumps and formal open dumpsites. It is due to a relatively large portion of solid waste that excludes plastic waste that is burned or buried because is collected and sent to sanitary disposal facilities this is assumed not to be unexposed to rainfall and or to (un)sanitary disposal facilities outside of the unavailable for wash-off. catchment. Although the Chao Phraya catchment The SWM model estimates that 58.7 percent of MPW has the lowest MPW per capita (mid-range estimate that is exposed for wash-off is attributed to handling of 10.0 kg/capita/year), a large population means practices of uncollected waste that may lead to wash-off that a significant amount of (plastic) waste remains of leaked plastics into waterways (e.g., fly-tipping and uncollected (mid-range estimate 96.5 kton/year, nearly disposal to water). In most catchments, the practice twice that of the next highest catchment). of disposing of uncollected waste on land accounts Uncollected plastic waste is handled in different ways— for the vast majority of this, but in the Chao Phraya disposal on land, disposal in water, openly burned or catchment, a large portion of exposed MPW originates buried (Figure 14). It is most commonly disposed of via from disposal directly in water. Most plastic waste open burning, accounting for 80.7 percent (mid-range available for wash-off from formal disposal facilities estimate) of all uncollected waste in the high-priority originates from open dumpsites (accounting for 38.6 catchments. Open burning is practiced by households percent of overall MPW available for wash-off). as it is an easy and relatively cheap way to reduce the volume of uncollected waste. Figure 13. MAIN SOURCES AND PATHWAYS FOR MISMANAGED PLASTIC WASTE FOR EACH OF THE CATCHMENTS 100.0 90.0 80.0 70.0 60.0 kton/year 50.0 40.0 30.0 20.0 10.0 0.0 Phetchaburi Mae Klong Tha Chin Chao Phraya Bang Pakong from uncollected plas�c waste from open dumping from open burn loca�ons from controlled dumps Source: Original calculations for this publication. Section 3. Study Results | 41 Figure 14. DESTINATION OF UNCOLLECTED PLASTIC WASTE (BASED ON NSO’S SURVEY PERCENTAGE) 90.0 80.0 70.0 60.0 kton/year 50.0 40.0 30.0 20.0 10.0 0.0 Phetchaburi Mae Klong Tha Chin Chao Phraya Bang Pakong plas�c waste disposed on land (fly-�pping or terrestrial dumping) plas�c waste disposed into water plas�c waste openly burned plas�c waste other methods Source: Original calculations for this publication. There is considerable uncertainty in the results of waste remains uncollected. For uncollected waste, exposed MPW due to uncertainty in estimating exposed open burning is the most common waste handling MPW at disposal sites, as well as uncertainty in the practice, but it is much more prevalent in the smaller amounts of uncollected plastic waste. This uncertainty LAOs than it is in larger towns and cities. The study is highest in the Chao Phraya catchment because of results indicate that within cities (except for the BMA) the large population, which is reflected in the large disposal of (plastic) waste directly into water is more volumes of MPW. common than in rural areas (assuming subdistrict municipalities and SAOs are mostly rural municipalities). Results Based on LAO Level Detailed Analysis of Critical Areas Contributing In Thailand, SWM is organized through LAOs. To inform to Exposed MPW policy decisions moving forward, it is important to understand aggregated results at LAO type level. The study results indicate that most MPW is generated in Detailed results and figures at various LAO levels the more rural areas (subdistrict municipality and SAO). can be found in Appendix D. It is in these areas that large amounts of (plastic) waste remain uncollected and where most open dumpsites Most solid and plastic waste is generated in the BMA. can be found. From these sources, plastic waste may However, despite Bangkok and other cities generating leak into the environment. Figure 15 provides insight a large amount of waste, most disposal facilities are into the spatial distribution of exposed MPW in the situated outside cities in smaller subdistricts. This is high-priority catchments. reflected in the high amounts of solid waste processed Table 4 presents the top 10 districts that contribute and disposed in the subdistrict municipalities and most to exposed MPW generation in the five subdistrict administrative organizations (SAOs). It is high-priority catchments. Together these districts also here that most unsanitary disposal facilities— contribute 51.7 percent to the total exposed MPW that may cause leakages of plastic waste—can be in the high-priority catchments available from 247 found. The data and model results suggest that a districts. This is a significant contribution and is caused large amount of solid waste is exported from larger by the fact that these districts contain the largest urban areas to the rural (sub)districts. open dumpsites9 and, with only a few exceptions, The source of most MPW is in the smaller more rural subdistricts, where the MPW per capita is much higher. 9 In the 10 biggest open dumpsites (out of 471 active open dump- sites), 35 percent of solid waste that ends up in open dumpsites But even in the cities, a significant amount of plastic is disposed. 42 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 15. CRITICAL DISTRICTS CONTRIBUTING MOST TO EXPOSED MPW ARE INDICATED WITH RED BOUNDARY Source: Original calculations for this publication. collection rates (from formal collection and recycling) The high relative contribution of Mueang Nonthaburi are relatively high (around 90.0 percent). This results (#4) to MPW available for wash-off is a result of the large in high concentrations of MPW in certain districts and population and hence the large total volume of MPW specific locations. In other districts the lower collection generated. The collection rate is approximately 75 rates in combination with large populations lead to percent on average, with about 25 percent uncollected. large amounts of uncollected waste . While most uncollected waste is openly burned (80 Interestingly, the critical districts are all at relatively percent) in Nonthaburi province, a large share of close distance to the sea. This is partly a reflection uncollected waste is disposed directly in open water of the population distribution but is also a result of (13 percent) and the remaining part is disposed in the the prevailing SWM conditions in the districts; the public environment (7 percent). largest open dumpsites are found at a relatively close In Ban Bueng (#2), Mueang Samut Sakhon (#3) and distance to Bangkok. Mueang Chachoengsao (#7), unsanitary disposal The districts that contribute most to exposed MPW facilities are the main source of exposed MPW. The are all situated near Bangkok (Figure 16a-d). In these largest open dumpsites can be found in these three districts the main source for MPW available for wash-off districts. These open dumpsites account for just over is uncollected waste. 25 percent of waste disposed in open dumpsites in the five catchments. Only a small fraction of the plastic In Phanat Nikhom (#1) and Mueang Chon Buri (#5), that is disposed in these open dumpsites is exposed collection rates are low at around 34.8 percent and and available for wash-off. It is suspected that a large 51.5 percent respectively, leaving a large portion of amount of solid waste is “imported” from adjacent SWG uncollected in these districts. districts, which would explain the very high rates of MPW per capita. Section 3. Study Results | 43 Table 4. CRITICAL AREAS THAT CONTRIBUTE MOST TO EXPOSED MPW Exposed MPW Primary Sources of Relative Contribution (kton/year) Exposed MPW High Mid Low Direct to Water Collection Rate Open Dump (kton/year) (kton/year) (kton/year) Fly-tipping Population ID District TH2006 Phanat Nikhom 7.11 5.18 0.12 9.7% 203,656 34.8% 3.17 - 4.87 TH2002 Ban Bueng 8.93 3.41 1.14 6.4% 155,297 95.4% 31.38 - 0.27 TH7401 Mueang Samut 8.65 3.23 1.19 6.0% 559,730 95.8% 30.94 - - Sakhon TH1201 Mueang 6.28 2.48 0.24 4.6% 656,021 75.0% - 1.65 0.83 Nonthaburi TH2001 Mueang Chon 4.56 2.25 0.09 4.2% 129,241 51.5% 2.42 - 2.01 Buri TH1003 Nong Chok 4.17 2.23 - 4.1% 195,069 63.8% - 0.09 2.14 TH2401 Mueang 5.78 2.14 0.78 4.0% 165,316 74.5% 21.43 - - Chachoengsao TH1022 Phasi Charoen 4.20 2.12 - 4.0% 215,153 68.7% - 0.08 2.04 TH1019 Taling Chan 3.63 1.80 - 3.3% 192,590 70.4% - 0.07 1.73 TH1206 Pak Kret 2.14 1.53 0.06 2.8% 363,905 76.9% - 1.02 0.51 Three districts (#6, #8 and #9) fall within the BMA collection within the BMA and to collect detailed data area. The available SWM data for the BMA area is at (sub)district level to improve the SWM database too coarse (only available at provincial level) to draw and model, and to better inform improvement efforts. specific conclusions about districts. These three districts Looking at the most critical districts in each priority showing up in the top 10 should be considered more catchment, a wide range of measures are required as an indication of a general need to further increase to address the marine debris problem. Figure 16a. SPATIAL DISTRIBUTION OF EXPOSED MPW FROM DUMPING/FLY-TIPPING IN TOP 10 CRITICAL DISTRICTS 44 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 16b. SPATIAL DISTRIBUTION OF EXPOSED MPW FROM DIRECT DISPOSAL TO WATER IN TOP 10 CRITICAL DISTRICTS Figure 16c. SPATIAL DISTRIBUTION OF EXPOSED MPW FROM UNSANITARY LANDFILLS (CONTROLLED DUMPS AND OPEN DUMPSITES) IN TOP 10 CRITICAL DISTRICTS Figure 16d. LAO TYPES ACROSS TOP 10 CRITICAL DISTRICTS Source: Original calculations for this publication. Section 3. Study Results | 45 Phetchaburi River Catchment to provide proper SWM services in combination with In the top 10 districts that contribute most to exposed investments to upgrade existing unsanitary disposal MPW in the Phetchaburi River catchment (Table 5), facilities and to build new sanitary disposal facilities. almost all exposed MPW is generated in the more rural Chao Phraya River Catchment districts. Most exposed MPW (84.3 percent) is generated In the top 10 districts that contribute most to exposed from point sources (unsanitary disposal facilities) and MPW in the Chao Phraya River catchment (Table 8), only 15.7 percent from uncollected waste through about 20.9 percent of exposed MPW is generated fly-tipping. To reduce exposed MPW, investments from point sources (unsanitary disposal facilities in are required to upgrade existing unsanitary disposal the more rural districts) and the rest from uncollected facilities and to build new sanitary disposal facilities. waste in the more urban areas (21.2 percent through Mae Klong River Catchment direct disposal to water and 57.9 percent through In the top 10 districts that contribute most to exposed fly-tipping). Investments in the predominantly urban MPW in the Mae Klong River catchment (Table 6), almost districts should focus on increasing collection rates all exposed MPW is generated in the more rural districts. while investments in more rural districts are required About 51.4 percent of exposed MPW is generated from to reduce leakages from unsanitary disposal facilities. point sources (unsanitary disposal facilities) and 48.6 Bang Pakong River Catchment percent from uncollected waste through fly-tipping. In the top 10 districts that contribute most to exposed To reduce exposed MPW, investments are required MPW in the Bang Pakong River catchment (Table to provide proper SWM services in combination with 9), about 34.2 percent is generated at unsanitary investments to upgrade existing unsanitary disposal disposal facilities (point sources). Disposal directly facilities and build new sanitary disposal facilities. into water only accounts for less than 1 percent; the Tha Chin River Catchment remaining 64.8 percent leaks through fly-tipping. In the top 10 districts that contribute most to exposed To address the solid waste management issues in MPW in the Tha Chin river catchment (Table 7), almost this catchment, investments are required in the rural all exposed MPW is generated in the more rural districts. areas to provide proper SWM services and to reduce About 45.8 percent of exposed MPW is generated from leakages from unsanitary disposal facilities. In the point sources (unsanitary disposal facilities) and 54.2 urban areas collection rates need to be increased and percent from uncollected waste through fly-tipping. awareness-raising campaigns are required to reduce To reduce exposed MPW, investments are required direct disposal into waterways. Table 5. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW GENERATED IN THE PHETCHABURI RIVER CATCHMENT Exposed MPW (kton/year) Population Point Diffuse Relative ID District Dry Dry Wet Total Contribution Urban Rural TH7601 Mueang - 0.06 - 0.06 3.5% 12.8% 87.2% Phetchaburi TH7605 Tha Yang 0.65 0.05 - 0.69 39.3% 0.0% 100.0% TH7606 Ban Lat 0.02 0.04 - 0.07 3.8% 0.0% 100.0% TH7604 Cha-Am 0.03 0.04 - 0.07 4.0% 48.5% 51.5% TH7607 Ban Laem 0.10 0.03 - 0.13 7.1% 0.0% 100.0% TH7608 Kaeng Krachan 0.08 0.02 - 0.11 6.1% 0.0% 100.0% TH7602 Khao Yoi 0.06 0.02 - 0.08 4.7% 0.0% 100.0% TH7603 Nong Ya Plong 0.02 0.01 - 0.03 1.8% 0.0% 100.0% TH7008 Pak Tho 0.52 0.00 - 0.52 29.7% 0.0% 100.0% TH7010 Ban Kha - 0.00 - 0.00 0.0% 0.0% 100.0% 46 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Table 6. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW GENERATED IN THE MAE KLONG CATCHMENT Exposed MPW (kton/year) Population Point Diffuse Relative ID District Dry Dry Wet Total Contribution Urban Rural TH7301 Mueang 0.09 0.95 - 1.05 28.2% 32.6% 67.4% Nakhon Pathom TH7103 Bo Phloi 0.06 0.10 - 0.16 4.2% 0.0% 100.0% TH7101 Mueang 0.68 0.09 - 0.77 20.7% 33.3% 66.7% Kanchanaburi TH7108 Sangkhla Buri 0.08 0.07 - 0.15 4.0% 0.0% 100.0% TH7112 Nong Prue 0.02 0.06 - 0.08 2.3% 0.0% 100.0% TH7105 Tha Maka 0.16 0.06 - 0.22 5.9% 2.6% 97.4% TH7102 Sai Yok 0.10 0.04 - 0.14 3.8% 0.0% 100.0% TH7106 Tha Muang 0.19 0.04 - 0.23 6.3% 9.3% 90.7% TH7107 Thong Pha 0.11 0.04 - 0.15 4.0% 0.0% 100.0% Phum TH7111 Dan Makham 0.05 0.02 - 0.07 1.8% 0.0% 100.0% Tia Table 7. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW GENERATED IN THE THA CHIN CATCHMENT Exposed MPW (kton/year) Population Point Diffuse Relative ID District Dry Dry Wet Total Contribution Urban Rural TH7401 Mueang Samut 3.23 - - 3.23 28.6% 5.3% 94.7% Sakhon TH7305 Bang Len 0.01 1.38 - 1.39 10.6% 0.0% 100.0% TH7301 Mueang 0.45 0.71 - 1.16 10.3% 32.6% 67.4% Nakhon Pathom TH7302 Kamphaeng - 1.13 - 1.13 10.0% 0.0% 100.0% Saen TH7304 Don Tum 0.10 0.85 - 0.95 8.4% 0.0% 100.0% TH7303 Nakhon Chai Si 0.21 0.72 - 0.93 8.2% 0.0% 100.0% TH7307 Phutthamonthon - 0.80 - 0.80 7.1% 0.0% 100.0% TH7209 U Thong 0.55 - - 0.55 4.8% 0.0% 100.0% TH7306 Sam Phran - 0.22 - 0.22 1.9% 24.5% 75.5% TH7202 Doem Bang 0.19 - - 0.19 1.7% 0.0% 100.0% Nang Buat Section 3. Study Results | 47 Table 8. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW GENERATED IN THE CHAO PHRAYA CATCHMENT Exposed MPW (kton/year) Population Point Diffuse Relative ID District Dry Dry Wet Total Contribution Urban Rural TH1201 Mueang - 0.83 1.65 2.48 14.8% 79.7% 20.3% Nonthaburi TH1022 Phasi Charoen - 2.04 0.08 2.12 12.7% 100.0% 0.0% TH1019 Taling Chan - 1.73 0.07 1.80 10.7% 100.0% 0.0% TH1046 Khlong Sam - 1.46 0.06 1.52 9.1% 100.0% 0.0% Wa TH1206 Pak Kret - 0.41 0.83 1.24 7.4% 64.1% 35.9% TH1016 Bangkok Yai - 0.96 0.04 1.00 6.0% 100.0% 0.0% TH1414 Uthai 0.87 - - 0.87 5.2% 0.0% 100.0% TH1104 Phra Pradaeng 0.72 - - 0.72 4.3% 79.3% 20.7% TH1601 Mueang Lop 0.63 0.03 - 0.66 3.9% 21.6% 78.4% Buri TH1406 Bang Pa-In 0.46 - - 0.46 2.8% 7.5% 92.5% Table 9. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW GENERATED IN THE BANG PAKONG CATCHMENT Exposed MPW (kton/year) Population Point Diffuse Relative ID District Dry Dry Wet Total Contribution Urban Rural TH2006 Phanat Nikhom 0.32 4.63 - 4.95 25.5% 3.2% 96.8% TH2002 Ban Bueng 3.14 0.27 - 3.41 17.6% 18.8% 81.2% TH2001 Mueang Chon 0.24 2.01 - 2.25 11.6% 15.4% 84.6% Buri TH1003 Nong Chok - 2.14 0.09 2.23 11.5% 100.0% 0.0% TH2401 Mueang 2.14 - - 2.14 11.0% 15.3% 84.7% Chachoengsao TH2011 Ko Chan - 1.33 - 1.33 6.9% 45.4% 54.6% TH1046 Khlong Sam - 1.03 0.04 1.07 5.5% 100.0% 0.0% Wa TH2010 Bo Thong 0.12 0.36 - 0.48 2.5% 0.0% 100.0% TH2406 Phanom 0.37 - - 0.37 1.9% 0.0% 100.0% Sarakham TH2005 Phan Thong 0.00 0.28 - 0.28 1.5% 0.0% 100.0% 48 | Plastic Waste Material Flow Analysis for Thailand: Summary Report 3.1.2 Tourist Hotspots remains uncollected. The model results indicate that This section presents an overview of the SWM and in Ko Samui, no (plastic) waste remains uncollected. MPW assessment results for three tourist hotspots This is likely unrealistic but is a result of the limited (Phuket, Krabi and Ko Samui). district-specific data available. Solid Waste and Plastic Waste Generated According to the 2018 data, all formally collected waste in Phuket flows to the sanitary disposal facility The generation of solid and plastic waste in tourist areas on the island, compared to 85.2 percent in Krabi and varies between the resident and tourist populations. a negligible amount in Ko Samui where most waste However, there is no data available in the tourist ends up in an open dumpsite. However, there are hotspots to differentiate the origin of solid waste or ongoing developments that are not yet reflected in the the plastic content of solid waste. available data. It is known that in Phuket, the landfill The SWM model results indicate that in the tourist capacity is almost reached and the city government is hotspots, approximately 381.9 kton of MSW is actively looking for alternatives. Similarly, in Ko Samui, generated annually (mid-point estimate). Based on alternatives are under development and currently (2021) data from the PCD, which does not differentiate for all waste is wrapped in the island and transported to tourist areas, plastic content in solid waste is similar to the mainland for final disposal with no waste disposed the high-priority catchments with an average of 17.2 at the old open dumpsite. percent. It is estimated that in the tourist hotspots, a Adding the estimated amount of plastic waste that total of 65.8 kton of plastic waste is generated annually. is disposed of in formal open dumpsites (11.1 kton/ Final Destination of SWG year) to the estimated 6.9 kton plastic (10.5 percent) An estimated 86.2 kton of plastic waste finds its final that remains uncollected in the tourist hotspots, a destination in the tourist hotspots and the additional total mid-range estimate of 16.8 kton/year of MPW is 19.8 kton likely originates from adjacent (sub)districts. obtained. However, as noted above, the Ko Samui open Most plastic is formally collected or recycled and only dumpsite is not currently operational. Removing this 10.5 percent of plastic waste that arrives in the area dumpsite from the estimates, the total is approximately Photo: Shutterstock / AfriframPOE. Section 3. Study Results | 49 Figure 17. MAIN SOURCES AND PATHWAYS FOR MPW FOR EACH OF THE CATCHMENTS 9.0 8.0 7.0 6.0 kton/year 5.0 4.0 3.0 2.0 1.0 0.0 Krabi Phuket Ko Samui* from uncollected plas�c waste from open dumping from open burn loca�ons from controlled dumps * Note that currently in Ko Samui, all collected waste is wrapped and transported to the mainland for final disposal and is no longer disposed at the open dumpsite. Source: Original calculations for this publication. 10 kton/year of MPW. In Phuket, this amount is derived a mid-point estimate of exposed MPW for the tourist from uncollected waste but in Krabi, MPW is evenly hotspots as 0.7 kton/year, with 0.5 kton/year attributed divided between uncollected waste and disposal at to handling practices of uncollected waste and 0.2 open dumpsites. Figure 17 shows the source distribution kton/year from open dumpsites in Krabi province. of MPW in the three tourist hotspots.10 As with the high-priority catchment areas, there is Uncollected plastic waste in the tourist hotspots is considerable uncertainty in the amount of exposed primarily either handled via disposal on land or open MPW in the tourist hotspots. This uncertainty is partly a burning. It is estimated that about 9.7 percent of the result of the uncertainty in exposed MPW at unsanitary total amount of plastic waste generated and 91.9 disposal facilities (only in Krabi and Ko Samui), but percent of uncollected plastic waste is openly burned. is also caused by the uncertainty in the amount of Households continue to practice open burning because uncollected (plastic) waste. it is an easy and relatively cheap way to reduce the Detailed Analysis of Critical Areas Contributing volume of uncollected waste. to Exposed MPW Exposed MPW (Plastic Waste Available for Wash-off) The study results indicate that exposed MPW is leaked Total MPW exposed—the amount of plastic waste into the environment primarily as point source in the that is available for wash-off—is derived from city and as mostly diffuse sources (from uncollected uncollected waste (disposed in the environment/ waste) in the more rural LAOs. Figures 18a-c provide fly-tipping) combined with the fraction of collected, insight into the spatial distribution of exposed MPW but mismanaged, plastic waste available for wash-off in the tourist hotspots. from formal open dumpsites. Considering the data In Table 10, the contribution of the districts to exposed limitations for Ko Samui11, the SWM model provides MPW generation in the tourist hotspots are presented. Three districts—Ko Samui, Mueang Phuket, and Khao 10 Note that currently in Ko Samui, all collected waste is wrapped and transported to the mainland for final disposal and is no Phanom—contribute nearly 90 percent to exposed longer disposed at the open dumpsite. MPW. 11 Note that currently in Ko Samui, all collected waste is wrapped and transported to the mainland for final disposal. Based on the available data (which include the presence of an open dumpsite on the island), the model indicates that no waste remains uncol- lected. 50 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 18a. SPATIAL DISTRIBUTION OF EXPOSED MPW FROM DUMPING/FLY-TIPPING IN TOURIST HOTSPOTS Figure 18b. SPATIAL DISTRIBUTION OF EXPOSED MPW FROM UNSANITARY LANDFILLS (CONTROLLED DUMPS AND OPEN DUMPSITES) IN TOURIST HOTSPOTS Section 3. Study Results | 51 Figure 18c. LAO TYPES ACROSS TOURIST HOTSPOTS Source: Original calculations for this publication. Table 10. RELATIVE CONTRIBUTION OF DISTRICTS TO EXPOSED MPW IN THE THREE TOURIST HOTSPOTS12 Exposed MPW Primary Sources of Exposed (kton/year) MPW Relative Population SWG/cap Direct to Water Collection Rate Contribution to Total Open Dump (kton/year) (kton/year) (kton/year) Fly-tipping Exposed MPW Rank ID District High Med Low 3 TH8105 Ao Luek 0.36 0.11 0.04 7.5% 39,648 1.06 87.8% 1.07 - 0.01 4 TH8108 Nuea Khlong 0.20 0.05 0.02 3.5% 48,674 1.12 88.0% 0.45 - 0.01 5 TH8101 Mueang 0.22 0.01 0.00 0.3% 82,795 1.52 97.2% - - 0.01 Krabi 6 TH8102 Khao 0.02 0.00 0.00 0.1% 7,650 1.23 92.4% - - 0.00 Phanom 7 TH8303 Thalang 0.23 0.00 - 0.0% 178,668 0.80 100.0% - - 0.00 2 TH8301 Mueang 0.84 0.52 0.00 34.1% 413,375 1.14 80.0% - - 0.52 Phuket 8 TH8302 Kathu 0.05 0.00 0.00 0.0% 111,575 1.09 100.0% - - 0.00 1 TH8404 Ko Samui 3.23 0.84 0.30 54.5% 42,023 1.89 100.0% 8.35 - - 12 Note that currently in Ko Samui, all collected waste is wrapped and transported to the mainland for final disposal. Based on the available data (which include the presence of an open dumpsite on the island), the model indicates that no waste remains uncollected. 52 | Plastic Waste Material Flow Analysis for Thailand: Summary Report 3.2 ESTIMATED PLASTIC DISCHARGES Incorporating MPW that is directly disposed in water FROM RIVERS AND COASTAL AREAS and does not remain in the terrestrial environment, increases the average percentage of plastic waste that MPW that is disposed of improperly in the dry terrestrial ends up in a waterway to 41.3 percent (19.5 kton/year) environment can be exposed to wash-off. However, of the total MPW that is both available for wash-off it may take some time to be mobilized by rainfall and directly disposed in water. runoff into streams, rivers or lakes. During this time, MPW is exposed to natural processes that may bury As seen in Figure 19, most MPW is from the highly populated catchments of the Tha Chin, Chao Phraya, or fragment plastics and prevent a fraction of MPW and Bang Pakong Rivers. In the Phetchaburi Bang from being washed off. MPW that ends up in a stream, Pakong catchments, a large fraction of exposed MPW river or lake is transported downstream and may end remains in the terrestrial environment (about 80–90 up in the marine environment, unless prevented from percent). In these catchments, most exposed MPW doing so by natural processes or anthropogenic in- leaks into the environment as diffuse source and in the frastructures. The longer MPW remains in a river, with upstream reaches of the catchment where subdistricts long travel times in general associated with larger tend to be large and more rural. catchments and inland communities, the more MPW is weathered and fragmented by natural processes Transport and Fate of MPW in Rivers and the more these fragments will be retained (e.g., Overall, across the four high-priority catchments in river sediments). Fate and transport modeling is (excluding Mae Klong), 46.9 percent of MPW that ends used to approximate these processes. up in a river is discharged into the marine environment. This section presents the results from the fate and The remaining MPW is retained in the riverine system transportation modeling of exposed MPW for the (51.9 percent across the four catchments) or captured high-priority catchments and the tourist hotspots. First, behind dams (1.2 percent across the catchments) (Figure the results of actual wash-off of exposed MPW in the 20). The Tha Chin River has the highest plastic discharge dry terrestrial environment are presented. Second, the (mid-range estimate of 4.01 kton/year) following by results of the transport and fate modeling of MPW in the Chao Phraya River (3.45 kton/year) and the Bang the rivers are presented, followed by a presentation of Pakong River (1.80 kton/year) (Figure 21). estimated MPW discharges into the marine environment The modeled MPW discharge estimates for the and a brief discussion on the seasonality of MPW rivers (most importantly the Chao Phraya River, which discharges into the marine environment. runs through Bangkok) have not been corrected for There is low confidence in the hydrological modeling plastic waste that is retained and removed through for the Mae Klong catchment and the tourist hotspot waste racks and (in)formal removal activities (mostly areas. Therefore, the fate and transport results for limited to working hours). In Bangkok, for example, a significant amount of debris is removed from the these should be interpreted with caution. See further river through regular cleaning operations and a large detail in section 3.3. Please note, the results for the amount of waste accumulates in the urban drainage Mae Klong are not considered when presenting system and retention ponds (where it may increase totals or averages for the high-priority catchments urban flood hazards) and may, from time-to-time, be in this section. retrieved. However, the activities are not sufficiently 3.2.1 Estimated MPW Discharges from High- continuous and predictable to account for in the models. priority Catchments In addition, during certain periods and events, the cleaning activities may be suspended and waste racks/ Wash-off of MPW from Land into Waterways gates may be opened to prevent upstream flooding. The fate and transport model indicates that a mid-range Therefore, all waste that is carried in the upstream estimate of 63 percent (27.7 kton/year) of exposed system runs through. Although a significant amount of MPW remains in the terrestrial environment (e.g., waste may be retrieved from the system via cleaning buried by natural processes), while the rest (37 percent) activities and waste racks, this may only be the tip of washes off to streams, rivers or lakes (16.3 kton/year). the ‘waste-berg’. Section 3. Study Results | 53 Figure 19. FATE OF EXPOSED MPW FROM LAND-BASED SOURCES FOR THE HIGH-PRIORITY CATCHMENTS IN THAILAND 20.0 0.4 15.0 0.0 6.6 2.7 4.8 kton/year 10.0 4.9 5.0 9.9 10.0 6.6 0.0 0.0 0.1 0.1 1.5 0.0 1.2 Phetchaburi Mae Klong* Tha Chin Chao Phraya Bang Pakong weathered and/or retained in soils washed-off to rivers direct disposed in water *Results for Mae Klong River have low confidence and are not included in the presented figures in the text. Source: Original calculations for this publication. Figure 20. FATE OF MPW TRANSPORTED IN THE MAIN RIVERS OF THE FIVE HIGH-PRIORITY CATCHMENTS 8.0 7.0 3.45 6.0 5.0 4.01 kton/year 4.0 1.80 3.0 4.20 2.0 3.04 3.00 1.0 0.06 0.04 0.04 0.08 0.0 0.24 Phetchaburi Mae Klong* Tha Chin Chao Phraya Bang Pakong captured behind dams retained in rivers total discharged into marine environment *Results for Mae Klong River have low confidence and are not included in the presented figures in the text. Source: Original calculations for this publication. 54 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 21. SPATIAL DISTRIBUTION OF EXPOSED MPW (GREY SHADES) AND THE RESULTING MID-POINT ESTIMATES OF MPW DISCHARGED INTO THE MARINE ENVIRONMENT (BLUE CIRCLES) FROM RIVER MOUTHS AND COASTAL AREAS Source: Original calculations for this publication. Section 3. Study Results | 55 Seasonal and Daily Variations of Plastic Discharges after implementation of policy measures which could from Rivers suggest that measures are not working, while the To assess seasonal variations of plastic discharges, the increase may, in reality, be caused by hydrological complete time series of the fate and transport model variations. as well as the complete time series of the hydrological Model results show strong seasonal variations with model are analyzed. The simulated period for the higher discharges associated with the rainy season hydrological model covers the period from January and lower average discharges with the dry season 2010 to December 2018 and is based on observed (e.g., the Tha Chin River in Figure 22). In Thailand, (through remote sensing) daily rainfall distribution. This the rainy season starts around June and lasts until provides an accurate representation of hydrological October, and this is also clearly visible in the modeled conditions for every day in the simulated period. The MPW discharges. SWM model is based on reported data considered However, even during the dry season, modeled high representative for the year 2018 only and does not discharges of MPW may be expected after brief rainfall contain information on any variability during the year. events (e.g., the early 2012 rainfall event in the Chao The model also does not include population growth, Phraya River, Figure 23). This behavior has also been economic development and changing behaviors. observed in other catchments where a short rainfall While this is a limitation of the model, the study event after a dry spell can mobilize a large amount of does not aim to construct a historical time series accumulated exposed MPW in the catchment. This to estimate historical discharges of plastics into the will then be washed off, transported downstream and marine environment. Rather, by using a static flux of discharged into the marine environment. exposed MPW, it is possible to assess the effect of hydrology on the expected discharge of MPW into the Overall, the model results indicate large daily marine environment. This makes evaluation of policy variations in MPW discharge. This should be taken into options and verification of the actual effects through consideration when monitoring rivers and elsewhere. observations easier. For example, field observations These large daily variations have been observed in may show no change or an increase in plastic discharges field measurements elsewhere (World  Bank  2021); Figure 22. MODELED TIME SERIES OF MPW DISCHARGE AT RIVER MOUTH OF THE THA CHIN RIVER (RED LINE) FOR THE MID-POINT SCENARIO AND Tha THE Chin RIVER DISCHARGE (timeseries (BLUE MPW discharge into LINE, marineREVERSE ) RIGHT AXIS) environment 150.0 0 140.0 200 130.0 400 120.0 600 110.0 800 [ton/ day] MPW discharge into marine environment 100.0 1000 [m3/s] 90.0 1200 average river discharge 80.0 1400 70.0 1600 60.0 1800 50.0 2000 40.0 2200 30.0 2400 20.0 2600 10.0 2800 0.0 3000 03-01-10 04-04-10 04-07-10 03-10-10 01-01-12 01-04-12 01-07-12 30-09-12 30-12-12 31-03-13 30-06-13 29-09-13 29-12-13 30-03-14 29-06-14 28-09-14 28-12-14 29-03-15 28-06-15 27-09-15 27-12-15 27-03-16 26-06-16 25-09-16 25-12-16 26-03-17 25-06-17 24-09-17 24-12-17 25-03-18 24-06-18 23-09-18 23-12-18 02-01-11 03-04-11 03-07-11 02-10-11 Source: Original calculations for this publication. 56 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 23. MODELED TIME SERIES OF MPW DISCHARGE AT RIVER MOUTH OF THE CHAO PHRAYA RIVER (RED LINE) FOR THE MID-POINT SCENARIO AND Chao Phraya THE RIVER (timeseries DISCHARGE MPW discharge (BLUE LINE,environment) REVERSE RIGHT AXIS) into marine 200.0 0 180.0 1,000 160.0 2,000 [ton/ day] 140.0 3,000 MPW discharged into marine environment [m3/ s] 120.0 4,000 Average river discharge 100.0 5,000 80.0 6,000 60.0 7,000 40.0 8,000 20.0 9,000 0.0 10,000 03-01-10 04-04-10 04-07-10 03-10-10 01-01-12 01-04-12 01-07-12 30-09-12 30-12-12 31-03-13 30-06-13 29-09-13 29-12-13 30-03-14 29-06-14 28-09-14 28-12-14 29-03-15 28-06-15 27-09-15 27-12-15 27-03-16 26-06-16 25-09-16 25-12-16 26-03-17 25-06-17 24-09-17 24-12-17 25-03-18 24-06-18 23-09-18 23-12-18 02-01-11 03-04-11 03-07-11 02-10-11 Source: Original calculations for this publication. although longer-term observations are rare and more in reducing the discharge of MPW into the marine long-term continuous field observations are needed environment. Mueang Nonthaburi becomes the district in Thailand to further confirm these trends. that contributes most to discharged MPW. Plastic Discharges from Rivers to the Marine The top 10 critical districts relative to importance Environment in the Top 10 Critical Districts regarding discharge of MPW into the marine The fate of the exposed MPW that leaks into the environment (Table 12), account for about 59.7 percent of terrestrial and riverine environment in the top 10 critical exposed MPW discharged into the marine environment. districts (Table 11) shows that the amount of MPW that However, these districts account for just 45.1 percent remains in the terrestrial and riverine environments of the total amount of exposed MPW generated in varies significantly between different districts. In the high-priority catchments. Bangkok (and elsewhere), multiple dams and weirs In a spatial representation (Figure 24), it is also clear are constructed that are assumed to capture all MPW that districts closer to the sea and/or closer to the that enters a waterway upstream of these structures. bigger rivers have a higher relative contribution to This is reflected by the high percentage of MPW that the amount of MPW discharged into the marine remains in the riverine system in the districts Klong environment. This is in line with expectations. Sam Wa, Nong Chok, and Phasi Charoen and even Figure 24 also shows that the districts close to the in Mueang Chon Buri. main barrage in the Chao Phraya—which forms the The relative importance of the critical districts changes border between the lower and upper Chao Phraya significantly when hydrology is considered. For instance, catchments—become more important when addressing it becomes clear that although the collection rate in marine debris. Therefore, it is crucial to validate the Mueang Chon Buri is very low, it is likely that investing assumptions made in this assessment (e.g., that all to improve collection rates in the much bigger district waste is trapped behind the main barrage). of Mueang Nonthaburi has a much greater effect Section 3. Study Results | 57 Table 11. TOP 10 DISTRICTS BASED ON EXPOSED MPW FROM LAND-BASED SOURCES Exposed MPW Final Destination of to Total MPW Contribution Contribution (kton/year) Exposed MPW Discharge Relative Relative Point Diffuse Terrestrial Riverine Marine ID District Dry Dry Wet Total TH2006 Phanat 0.32 4.63 - 4.95 9.4% 3.53 0.69 0.73 7.4% Nikhom TH2002 Ban Bueng 3.14 0.27 - 3.41 6.4% 2.88 0.33 0.21 2.1% TH7401 Mueang 3.23 - - 3.23 6.1% 2.24 0.30 0.69 7.0% Samut Sakhon TH1046 Khlong Sam - 2.49 0.10 2.59 4.9% 1.58 0.63 0.39 4.2% Wa TH1201 Mueang - 0.83 1.65 2.48 4.7% 1.23 0.58 0.67 11.3% Nonthaburi TH2001 Mueang Chon 0.24 2.01 - 2.25 4.3% 1.76 0.11 0.39 4.0% Buri TH1003 Nong Chok - 2.14 0.09 2.23 4.2% 1.35 0.57 0.31 3.3% TH7301 Mueang 0.55 1.66 - 2.21 4.2% 1.29 0.34 0.57 5.9% Nakhon Pathom TH2401 Mueang 2.14 - - 2.14 4.0% 1.22 0.54 0.38 3.9% Chachoengsao TH1022 Phasi Charoen - 2.04 0.08 2.12 4.0% 0.93 0.69 0.51 5.3% 58 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Table 12. TOP 10 DISTRICTS BASED ON DISCHARGE OF MPW INTO THE MARINE ENVIRONMENT Exposed MPW Final Primary Sources of Relative Contribution to (kton/year) Destination of Exposed MPW Relative Contribution Total MPW Discharge Exposed MPW Open Dump (kton/ Direct to Water Collection Rate Urban Rural (kton.year) Terrestrial SWG/Cap Riverine Marine year) ID District Dry Dry Wet Total TH1201 Mueang - 0.83 1.65 2.48 4.7% 0.41 0.96 1.11 11.3% 79.7% 20.3% 1.24 75.1% - 1.65 Nonthaburi TH2006 Phanat 0.32 4.63 - 4.95 9.4% 3.53 0.69 0.73 7.4% 3.2% 96.8% 0.91 34.8% 3.17 - Nikhom TH7401 Mueang 3.23 - - 3.23 6.1% 2.24 0.30 0.69 7.0% 5.3% 94.7% 0.85 94.2% 30.94 - Samut Sakhon TH7301 Mueang 0.55 1.66 - 2.21 4.2% 1.29 0.34 0.57 5.9% 32.6% 67.4% 1.17 89.6% 1.56 - Nakhon Pathom TH1206 Pak Kret - 0.41 0.83 1.24 2.3% 0.22 0.47 0.56 5.7% 64.1% 35.9% 1.49 77.0% - 0.83 TH1022 Phasi - 2.04 0.08 2.12 4.0% 0.89 0.71 0.52 5.3% 100.0% 0.0% 1.58 68.7% - 0.08 Charoen TH1019 Taling - 1.73 0.07 1.80 3.4% 0.89 0.45 0.46 4.7% 100.0% 0.0% 1.58 70.4% - 0.07 Chan TH1046 Khlong - 2.49 0.10 2.59 4.9% 1.52 0.66 0.41 4.2% 100.0% 0.0% 1.58 68.7% - 0.10 Sam Wa TH1016 Bangkok - 0.96 0.04 1.00 1.9% 0.32 0.28 0.40 4.1% 100.0% 0.0% 1.58 69.2% - 0.04 Yai TH2001 Mueang 0.24 2.01 - 2.25 4.3% 1.76 0.11 0.39 4.0% 15.4% 84.6% 0.79 51.5% 2.42 - Chon Buri Section 3. Study Results | 59 Figure 24. RELATIVE CHANGES IN PRIORITY RANKING FOR DISTRICTS WHEN HYDROLOGY IS CONSIDERED Source: Original calculations for this publication. 3.2.2 Estimation of MPW Discharges from Time series of plastic discharges into the marine Tourist Hotspots environment were generated for the different outlet The fate and transport model indicates that from points (rivers and coasts) of the tourist hotspots. As the tourist hotspots, about 88.6 percent of exposed with the high-priority catchments, analyzing these MPW available for wash-off (i.e., resulting from illegal results shows that climatic variabilities are high and dumping/fly-tipping and exposed MPW leaked from indicate that during wet years, expected annual MPW controlled dumps and open dumpsites) remains in discharges are much higher compared to dry years. the terrestrial environment (e.g., buried by natural The spatial representation of Phuket and Krabi (Figure processes). Only 10.2 percent of exposed MPW washes 25) also indicates that in Phuket most MPW enters off directly or is transported via waterways into the the marine environment around Phuket town (the marine environment. In the waterways, only 1.3 percent calculation is based on the NSO’s survey percentage). of the total exposed MPW gets buried or stored. This is much less compared to the large catchments and 3.3. CONFIDENCE AND VALIDATION OF is mostly a direct result from the limited length of RESULTS the waterways on the islands. The model results for the islands are considered uncertain as the models Modeling results have been validated against a number could not be validated directly due to unavailable of available datasets to indicate the ability of the various observation data. models to represent the actual conditions. In general, only limited data are available to accurately validate 60 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 25. SPATIAL DISTRIBUTION OF EXPOSED MPW (GREY SHADES) AND THE RESULTING MID-POINT ESTIMATES OF MPW DISCHARGED INTO THE MARINE ENVIRONMENT (BLUE CIRCLES) FROM RIVER MOUTHS AND COASTAL AREAS Source: Original calculations for this publication. the models. Further details on the validation for the significantly increases the uncertainty of the results, different components are provided in Appendix E. especially at the lowest levels (subdistrict and LAO level). At catchment level, this translates into a very wide 3.3.1 SWM Model range (difference between the low and high scenarios) Confidence of Input Data and Results for MPW discharged into the marine environment. The available data did not allow for a detailed statistical There is some uncertainty associated with the input analysis (such as a Monte Carlo analysis13) over the data for the SWM model. Three scenarios (low, mid entire waste flow model, which should be considered and high estimates) were produced for SWG per capita when more detailed SWM data are available. and plastic content as a result. In Thailand, no detailed Hydrological variability due to daily, seasonal and data is available on SWG per capita at (sub)district annual rainfall was also accounted for. The datasets or LAO level. SWG per capita rates were estimated used to construct the SWM database are mostly based on the available downstream data (reported based on data obtained for 2018 and the SWM formally collected waste from PCD and LAOs and model results are therefore considered to represent reported collection rates from NSO with low, mid the 2018 situation. The hydrological effects on MPW and high estimates developed in line with the (inter) wash-off and transport were estimated using a historical national literature). The three scenarios of input data (spatially representative) rainfall dataset for the period were then used to establish estimates for exposed January 2010 to December 2018, with daily rainfall MPW which are used to simulate actual wash-off and transport of MPW from land-based sources to the 13 Computational simulation of repeated sampling to generate a marine environment as described in section 2.3. This range of possible values. Section 3. Study Results | 61 estimates at a high spatial (1 km2) and temporal 3.3.2 Hydrological Models (daily) resolution. The results account for the wide The model results for the Phetchaburi and Mae Klong variability of precipitation in Thailand and the results catchments are slightly uncertain (reasonably confident reflect the daily variability and seasonality of MPW to confident) because in these catchments, irrigation loads in the riverine environment in the high-priority schemes are present. These irrigation schemes extract catchments. The simulations result in time series for water from the river. No data was available to account MPW discharged into the marine environment. For for these abstractions in the model. each of the three scenarios the minimum, average The number of irrigation schemes in the Phetchaburi and maximum annual (for a moving 365-day period) is limited and therefore the results of this catchment discharges of MPW into the marine environment are still considered sufficient for the purposes of this were determined. These estimates are considered study. The model results of other catchments are representative for dry, average and wet years. considered good to very good. As such the results provide insight in both uncertainty No validation datasets were available for the tourist of SWM data and the range due to climatological hotspots and therefore the hydrological models for variations. The study results indicate that the these domains could not be calibrated. The results climatological variations result in expected discharges for these areas are considered highly uncertain and during a wet year to be about twice the discharges require further validation/calibration. See Figure 27 expected during a dry year. The uncertainty in SWM for a depiction of confidence levels for the various data is much wider and the difference between the study areas. low-end estimate and high-end estimate is roughly a factor of 4.5. 3.3.3 Fate and Transport Models Validation of Input Data and Results Based on the validation of the model results with Overall, based on the available local SWM data, it was observation datasets from the BMA and the Department possible to generate a realistic spatial distribution of of Marine and Coastal Resources (DMCR) (see Appendix managed and mismanaged (plastic) waste. However, E), it is concluded that the models for the Tha Chin, because there is uncertainty with regard to the amount Chao Phraya and Bang Pakong Rivers perform very of (plastic) waste that is exposed and therefore available well and the model for the Phetchaburi River performs for wash-off at the various unsanitary disposal facilities, well during the wet season, but less otherwise. the results for the catchments with a significant number Of the well-performing models, the model results from of unsanitary disposal facilities are considered to be the mid-point (Tha Chin) and high-end (Phetchaburi, less certain. See Figure 26 for a depiction of confidence Chao Phraya and Bang Pakong) scenarios are in line levels for the various study areas. with the field observations (data obtained from DMCR), and are in line with the estimated monthly average plastic loads retrieved from riverine debris Figure 26. CONFIDENCE LEVELS FOR THE VARIOUS STUDY AREAS, BASED ON THE VALIDATION OF THE SWM MODEL Bang Pakong Chao Phraya Phetchaburi Mae Klong Ko Samui Tha Chin Phuket Krabi Confidence Model Level Confident SWM Reasonably Confident Uncertain Note: Details on the validation for each of the data inputs to the SWM model are provided in Appendix E. 62 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 27. CONFIDENCE LEVELS FOR THE VARIOUS STUDY AREAS, BASED ON THE VALIDATION OF THE HYDROLOGICAL MODEL Bang Pakong Chao Phraya Phetchaburi Mae Klong Ko Samui Tha Chin Phuket Krabi Confidence Model Level Confident HYDROLOGY Reasonably Confident Uncertain Note: Details on the hydrological model validation are provided in Appendix E. (data obtained from the BMA). We conclude that the with the models of the main catchments. The model results of the Tha Chin are very good and the models for the small islands likely underperform results of the Phetchaburi, Chao Phraya and Bang (caused by the underperforming hydrological Pakong catchments are somewhat uncertain. See models) and the estimated MPW discharges are Figure 28 for a depiction of confidence levels for likely underestimated. the various study areas. The model results of the Mae Klong and the small 3.4 COMPARISON WITH PREVIOUS islands are considered uncertain: COMPLEMENTARY ESTIMATES • The model for the Mae Klong does not perform It is difficult to compare the modeled estimates for well throughout the year. This is likely because MPW in the high-priority catchments with (inter) the wflow_sbm model is not representative for national studies because the (inter)national studies low runoff and low discharge conditions and is have a different geographical (mostly national) focus. further reduced because of the uncertainty of the Benchmarking to these studies is required to be able operational conditions of the irrigation schemes to put the results of this study in perspective. When and the dam in the downstream reach of the river. we consider that the high-priority catchments with • The models for the small islands could not be confident results covering approximately 34.1 percent validated directly because no observation data is of the population, the results of the (inter)national available. To get an indication of performance, the studies can be downscaled relative to the covered model results are compared to the results obtained population. By doing this, no justice is done to the Figure 28. CONFIDENCE LEVELS FOR THE VARIOUS STUDY AREAS, BASED ON THE VALIDATION OF THE FATE AND TRANSPORT MODEL Bang Pakong Chao Phraya Phetchaburi Mae Klong Ko Samui Tha Chin Phuket Krabi Confidence Model Level Confident FATE AND Reasonably TRANSPORT Confident Uncertain Note: Details on the fate and transport model validation are provided in Appendix E. Section 3. Study Results | 63 actual conditions nor the intentions of the individual So far, existing (inter)national studies have not included studies. However, since the intention of this exercise hydrology as a driver for wash-off and transport, and is only to compare results of this study with results do not use local SWM data and handling practices, from available peer-reviewed international studies, relying on national averages instead. this method provides an opportunity to do so. Downscaling the results of available (inter)national The confident results are presented in Table 13 alongside studies to the covered population in this study allows results from existing (inter)national studies. The results for comparison with previous peer reviewed (inter) of this study are on the lower end of previous studies. national studies. This shows that the estimated SWG The existing studies have their own caveats, which and PWG figures are in the same order as reported are further discussed in this section. and presented in the (inter)national literature. This In general, most previous global studies (for example, indicates that the results of the SWM model are realistic Jambeck et al. 2015) tend to be biased toward European and gives confidence to MPW and discharge results and North American rivers and the available studies (for the catchments with confident results). on riverine plastic debris focus mainly on plastic in This study puts a mid-point estimate for MPW at 388.6 rivers with large basins, although such basins are not kton/year (range 178.7–1,002.2 kton/year). The mid-point necessarily the largest contributors to the ocean plastic estimate is slightly higher than the downscaled Jambeck pollution. In addition, plastic transport and composition et al. (2015) figure. It must be noted that Jambeck et are often not measured consistently over time and al. (2015) based their assessment only on plastic waste geographic areas, with numbers averaged instead. generated by the population living within 50 km of the Table 13. COMPARING MODELED RESULTS WITH (INTER)NATIONAL LITERATURE Research/ Year Population Coverage SWG Plastic PWG MPW MPW per Exposed Exposed Discharged Study (People) (%) (kton/ Content (kton/ (kton/ Capita MPW MPW per MPW year) (%) year) year) (kton/ (kton/ Capita (kton/year) year) year) (kg/yr/ cap) This (mid) 23,146,449 34.1% 10358.3 17.4% 1799.7 385.9 16.79 49.9 2.13 9.3 study confident range 8,503.5 1,221.0 - 178.5 - 7.72 - 8.9 - 0.38 - 1.9 - results14 - 13,715.8 2,878.2 998.1 43.30 189.1 8.17 32.3 PCD 2018 67,936,438 100.0% 27,800.0 4,730.015 17.0% N/A N/A N/A N/A N/A downscaled 23,146,44916 34.1% 9,471.7 1,611.5 Bureecan 2017 100.0% 3,560.0 1,070.0 et al N/A3 N/A N/A N/A N/A N/A N/A downscaled 34.1% 1,212.9 364.6 Chula- 2017 100.0%17 15,800.018 1,930.0 30.0 10 - 30 10 - 30 longkorn N/A3 20.0% N/A downscaled 34.1% 5,383.2 657.6 10.2 3.4 - 10.2 3.4 - 10.2 Jambeck 2015 26,000,00019 41.9%20 31,200.0 3,740.0 1,030.0 150 - 470 et al 12% 39.62% N/A downscaled 3,714,810 3 14.3% 4,457.8 534.4 147.2 51.1 - 160.3 14 Covers the Bang Taboon, Tha Chin, Chao Phraya and Bang Pakong catchments only 15 Not in the PCD report, estimates prepared by Deltares et al using 17.0% plastic content 16 Reported figures downscaled to the coverage of the 4 catchments with confident model results 17 Only based on 11 target products 18 Only accounted for formal collection 19 Only coastal population, within 50km from coast 20 Total population in Thailand in 2010 was approximately 62 million 64 | Plastic Waste Material Flow Analysis for Thailand: Summary Report coast (using the population of 2010) while this study (2017) (downscaled 3.4–10.2 kton/year). However, the calculated MPW generated by the entire population estimated range is considerably lower than Jambeck in the high-priority catchments only (representative et al. (2015). This is because this study: for 2018 and including the BMA). • Uses actual local SWM data (2018). Total exposed MPW in the catchments with confident • Accounts for different handling practices of results is estimated at 51.5 kton/year (range 8.9–189.1 uncollected waste (open burning, fly-tipping, kton/year). This is considerably higher than the results disposal in water and others). from Chulalongkorn University (2017), which puts a • Uses actual locations for point sources (controlled national figure at 10–30 kton/year. The models indicate dumps and open dumpsites). that a large amount of exposed MPW remains in the terrestrial and riverine environments, and for the four • Only considers a part of MPW available for wash-off catchments with reliable results, discharged MPW (exposed MPW). is estimated at 9.3 kton/year (range 1.9–32.3 kton/ Jambeck et al. (2015) do not consider these and build year). The range is in the same order but wider than on national reported SWM data from 2010. the estimated range by Chulalongkorn University Photo: Shutterstock / Wachiwit. Section 3. Study Results | 65 SECTION 4. CONCLUSIONS AND RECOMMENDATIONS T his study has built material flow models for the five high-priority catchments around Bangkok that discharge into the Upper Gulf of Thailand and for three tourist hotspots (Phuket, Krabi and Ko Samui). These models provide insight into plastic waste generation and handling practices in these areas and show how these translate into plastic waste leakages and discharges into the marine environment. The high spatial resolution resulting from the SWM model built on local data has provided important insights that can direct policies, measures and investments, and can inform the National Marine Debris Action Plan to reduce marine debris in the most effective way. The results show that a more ambitious target to reduce marine debris could even be possible when measures are focused on the most critical districts. By integrating the best available local data and incorporating realistic hydrological processes and state-of-the-art transport modeling, this approach makes considerable progress in assessing plastic pollution from land-based sources in Thailand. Similar to its application elsewhere in the region (World Bank 2021), the value of this methodology to inform policy includes: • Establishing realistic baselines of plastic waste discharges for four of the catchments against which progress can be measured. • Helping to set differentiated priorities between catchments and districts by providing local insight into the (relative) contribution of those districts and specific waste handling practices to the plastic waste pollution. • Exploring different scenarios of investment and policy interventions through assessing potential impact of measures on the reduction of plastic discharges. • Helping to determine optimal observation sampling intervals to reliably draw conclusions on the effectiveness of implemented policy measures and investments. There are, nevertheless, scope and opportunities for further improvement. The production of better solid waste dataflows and accurate hydrological models, long time series of field observations, as well as new emerging knowledge on plastic waste leakages (especially from unsanitary disposal facilities) and riverine transport processes will enable this approach to be further refined and validated, while reducing the range of uncertainty. Comparison with field observations (obtained from DMCR for the period December 2016 to August 2019) shows good correlation of model results with discrete observations. Also, noting the limitations of the scarce field observation data in representativeness for annual trends (if at all), the study’s conclusion that MPW discharges from individual rivers during wet years may be double of what they may be during a dry year seems to be confirmed by the field observations. It is therefore cautiously concluded that the trend (that MPW discharges are reducing) that may be observed in the observation data from DMCR is, at least partly, a result of climatic variations. Ongoing observation data may be able to confirm this. 66 | Plastic Waste Material Flow Analysis for Thailand: Summary Report While the SWM model performs well for all assessed When hydrology is considered, it was found that areas, it was concluded that the hydrological and fate across the four catchments about 81.0 percent of and transport models for the tourist hotspots and the exposed MPW remains in the environment and only Mae Klong catchment underperform. Therefore, results 19.0 percent (9.3 kton/year) is discharged into the of the fate and transport model of the tourist hotspots marine environment. This represents only about 0.55 and the Mae Klong catchment are not presented in percent of the total amount of plastic waste that is this chapter. generated in these areas. Across the four catchments This chapter presents the key conclusions of the an average 37.0 percent of exposed MPW in the assessment that can help inform decision-making and terrestrial environment is estimated to wash off to a provides recommendations on how this approach can waterway and 63.0 percent remains in the dry terrestrial be improved for future assessments and use in the environment. Of the exposed MPW that enters the Thai context. The key conclusions are presented as riverine environment (through actual wash-off or from answers to the first two research questions: direct disposal in waterways), an average of 47 percent is being discharged into the marine environment and 1. How much plastic waste is being discharged 53 percent remains trapped in the riverine environment. into the marine environment? The study results indicate that, following the mid 2. Where does this plastic waste come from? scenario, from the four high-priority catchments with The recommendations provide the answers to the reliable results, an annual average total of 9.3 kton/ last question: year of plastic waste is discharged into the marine 3. What can Thailand do to reduce the discharge environment. This is equivalent to a marine plastic of plastic waste into the marine environment? footprint of 0.4  kg/capita/year. During particularly rainy years this may increase to 14.3 kton/year and The final part of this chapter concludes with recom- during drier years it may be as low as 4.9 kton/year. mendations to improve the data and models that are Although the total amount of MPW generated is a essential for monitoring and evaluating the effectiveness significant amount, most (exposed) MPW remains in of policy options and progress. the terrestrial and riverine environments. 4.1 KEY RESULTS AND CONCLUSIONS OF It was shown that most plastic waste is discharged THE ASSESSMENT during the rainy season: over the simulated period, in the four catchments combined an average of 79.6 Figure 29 presents the Sankey diagram for the percent of the total MPW discharged into the marine four high-priority catchments with reliable results environment was modeled as discharged during the (Phetchaburi, Tha Chin, Chao Phraya and Bang Pakong) rainy season. It was also shown that exposed MPW — from top to bottom showing the flow of plastic from that has accumulated on land during an extended generation, collection, disposal and then pathways drier period can wash off during a rainfall event in through the environment. the dry season, resulting in a brief but high load of plastic waste discharged into the marine environment. 4.1.1 How much plastic waste is being discharged into the marine environment? 4.1.2 Where does the discharged plastic waste The mid to high-end scenarios from the SWM model come from? are considered the scenarios that resemble the actual It was found that formal collection (60.3 percent) and SWM situation closest. The mid scenario shows that recycling (28.5 percent) rates across the studied areas the volume of MPW generated in the study areas is are high with a combined rate of 88.8 percent. However, estimated to total about 444.8 kton/year (428.0 kton/ across the studied areas a significant amount of waste year in the high-priority catchments and 16.8 kton/year remains uncollected and there is a large number of in the tourist hotspots). It is estimated that only 2.8 formal unsanitary disposal facilities where (plastic) percent of plastic waste generated and 12.4 percent waste may leak into the environment. In Thailand, of MPW generated may be available for wash-off and the population has a general preference to burn is considered exposed MPW (49.9 kton/year in the uncollected waste (80.7 percent of uncollected waste four catchments). Section 4.Conclusions and Recommendations | 67 Figure 29. SANKEY DIAGRAM FOR THE FOUR HIGH-PRIORITY CATCHMENTS SHOWING AN APPROXIMATION OF THE PLASTIC WASTE MATERIAL FLOW FROM GENERATION TO DISCHARGE TO THE MARINE ENVIRONMENT Plastic Waste Generation 100% Formally Collected 89.0% Uncollected 11.0% Disposed to Unsanitary Facilities 15.0% Other Openly Recycled 0.6% Burned Disposed to 21.4% 8.7% Disposed Sanitary on Land Facilities 1.5% 52.6% Exposed to Disposed Not Exposed Environment to Environment in Rivers 1.1% 0.2% 13.9% Dry Environment Washed-off to Rivers 0.9% Retained Washed-off to and in Soils Directly Disposed 1.7% in Rivers 1.1% Retained in Rivers/ Discharged into Captured by Dams Marine Environment 0.6% Possible pathways for 0.5% plastic waste material flow from generation to the marine environment Source: Original figure for this publication. 68 | Plastic Waste Material Flow Analysis for Thailand: Summary Report Figure 30. ORIGIN OF EXPOSED MPW (LABELS IN KTON/YEAR) IN FOUR CATCHMENTS WITH CONFIDENT RESULTS ONLY (BASED ON NSO’S SURVEY PERCENTAGE) 9.74 20.78 2.37 3.67 BMA City Municipality 19.39 Town Municipality Subdistrict Municipality SAO Source: Original calculations for this publication. is burned) although this is less common in the urban 37.1 percent), and Bang Pakong (1.8 kton/year, 19.3 areas. Burned (plastic) waste is assumed to not wash-off percent) rivers. and is therefore not considered exposed MPW. Although there is considerable uncertainty with Across all studied catchments and districts, 58.1 regard to the results for the tourist hotspots and the percent of exposed MPW comes from uncollected Mae Klong River catchment, it is not expected that waste (32 kton/year) and 41.9 percent comes from these areas combined will contribute significantly to unsanitary disposal facilities (23.1 kton/year) (mainly marine debris. These areas combined generate only open dumping). 9.2 percent of total exposed MPW while the four Most exposed MPW is generated in the rural districts other catchments combined generate 90.8 percent. (37.4 kton/year or 70.1 percent) (smaller subdistrict municipalities and SAOs) where collection rates are 4.2 RECOMMENDATIONS FOR POLICY generally much lower than in cities and where in general AND INVESTMENTS most disposal facilities (including in some cases for The following recommendations have been formulated urban areas) and open dumping locations can be based on the results of the assessment and can be found. In addition, also in the Bangkok Metropolitan considered in view of reducing the flow of plastic region a significant amount of exposed MPW is waste from land-based sources into the marine generated. Although the collection rate in Bangkok environment. Concrete recommendations for short- is high, the large volumes of waste generated result and medium-term actions for the districts that most in a still significant overall volume of exposed MPW contribute to exposed MPW and MPW discharged of 9.7 kton/year (18.4 percent of total exposed MPW into the marine environment are provided. generated). See Figure 30 for a breakdown by origin. Recommendations to reduce discharge of plastic In general, it was found that with increasing distance waste to marine environment are identified at to the sea, the relative amount of plastic waste that different locations in the waste flow diagram. While enters the marine environment becomes smaller, due it is generally agreed that measures to reduce plastic to retention and removal processes. This underscores waste generation are most effective and sustainable in that priority should be given to addressing solid waste the long term, there are multiple useful measures that problems in districts closer to the sea and downstream can prevent plastic leakages and may be effective and/ of the dams. or cost-effective in the short term. From the waste flow Looking at the individual catchments, it was found that diagrams it becomes clear that measures downstream 9.3 kton/year enters the marine environment from the in the waste chain are expected to be more efficient Phetchaburi (0.04 kton/year, 0.5 percent), Tha Chin (4.0 in reducing marine debris. For example, reducing kton/year, 43.2 percent), Chao Phraya (3.5 kton/year, direct disposal to water by 1 kton/year is expected Section 4.Conclusions and Recommendations | 69 to result in an average reduction of 0.4 kton/year in to prevent plastic waste from reaching the marine plastic discharge, while to obtain the same reduction environment. in discharged plastic waste through reducing plastic Initially, focus on areas at close distance from the waste generation in total, plastic waste generation coast (but also consider installing them elsewhere), needs to be reduced by almost 175 kton/year. However, including those districts listed in Table 14. measures upstream in the waste chain have many • In urban areas: Install trash racks in urban drainage other benefits and may still be preferable. systems, just before the outlet to a main river or In this section, based on the study results, concrete waterway and clean them daily. measures and policy recommendations are provided to: • In rural areas: Install trash racks in irrigation canals 1. Reduce transport of leaked MPW (downstream just downstream from villages. in waste chain). • In rivers: Promote and expand river clean-up 2. Reduce MPW generation (mid-stream in waste initiatives such as the one managed by the BMA chain). in the Chao Phraya River. 4.2.1 Measures to Reduce Transport of Leaked It is recommended, as a first next step, to analyze MPW (Downstream in Waste Chain) possible existing constraints to the required investments Measures to capture MPW leaked or about to leak into to install such equipment. It is noted that these measures waterways can be most effective in reducing marine do not require large financial investments and there debris in the short term. For example, these can be may be existing constraints that prevent this from particularly advantageous if they make use of existing happening, such as operational costs. infrastructure and therefore can be implemented at In addition, intercepting waste as it is carried short notice. It is recommended to optimize the use of downstream provides an excellent opportunity to existing structures in waterways and drainage systems monitor plastic waste in the riverine environment. Table 14. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW WASHED OFF FROM DIFFUSE SOURCES Exposed MPW Primary Source of Relative Contribution (kton/year) Population Exposed MPW Direct to Water Collection Rate (kton/year) (kton/year) Total Urban Rural Fly-tipping ID District High Med Low TH2006 Phanat Nikhom 7.11 5.18 0.12 11.6% 203,656 3.2% 96.8% 34.8% - 4.87 TH1201 Mueang 6.28 2.48 0.24 10.4% 656,021 79.7% 20.3% 75.0% 1.65 0.83 Nonthaburi TH1022 Phasi Charoen 4.20 2.12 - 9.9% 215,153 100.0% 0.0% 68.7% 0.08 2.04 TH1046 Khlong Sam Wa 3.01 1.52 - 8.4% 263,088 100.0% 0.0% 68.7% 0.06 1.46 TH1003 Nong Chok 4.17 2.23 - 7.3% 195,069 100.0% 0.0% 63.8% 0.09 2.14 TH1019 Taling Chan 3.63 1.80 - 7.2% 192,590 100.0% 0.0% 70.4% 0.07 1.73 TH1206 Pak Kret 2.14 1.53 0.06 6.0% 363,905 64.1% 35.9% 76.9% 1.02 0.51 TH1016 Bangkok Yai 2.00 1.00 - 5.5% 103,306 100.0% 0.0% 69.2% 0.04 0.96 TH7305 Bang Len 2.52 1.39 0.76 4.3% 106,318 0.0% 100.0% 59.4% - 1.38 TH2001 Mueang Chon Buri 4.56 2.25 0.09 3.7% 129,214 15.4% 84.6% 51.5% - 2.01 70 | Plastic Waste Material Flow Analysis for Thailand: Summary Report This data is currently largely lacking and it is urgently Investments to improve collection rates in the urban required to validate and improve the other datasets and areas should start with the districts that contribute models and evaluate the effects of policy interventions. most to the exposed MPW from uncollected waste in the Chao Phraya and Bang Pakong Rver catchments 4.2.2 Measures to Reduce MPW (Mid-stream in (Table 15). Waste Chain) 2. Develop an efficient waste collection system Measures to reduce MPW focus on improving solid in rural Thailand waste management practices, services to collect more Uncollected plastic waste accounts for about 50–70 solid waste and improve final disposal to prevent percent of marine debris. It is mostly in rural areas leakages into the environment. Following the identified where a significant part of solid waste remains main sources of MPW (unsanitary disposal facilities uncollected (across the study area approximately 21 and uncollected waste), the following measures are percent). In these areas most uncollected waste is identified (the high-priority districts based on their burned by people (almost 90 percent) and only a relative contribution to marine debris are indicated fraction is expected to reach the marine environment. with an *): Because of the diffuse nature of this problem, it is 1. Further improve waste collection in urban areas recommended to invest in the development of an Collection rates in the urban areas are fairly high (in efficient waste collection system for rural Thailand. Bangkok about 85 percent of waste is formally collected). In Thailand, SWM is the responsibility of the LAOs. However, considering the large urban population, a Contrary to the larger LAOs (mostly in affluent urban significant volume of waste remains uncollected in areas), the small LAOs and especially the SAOs in the urban areas. Some of this waste finds its way to the rural areas have budget constraints and limited waterways and the marine environment. expertise to organize proper waste collection and management. Table 15. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW GENERATED IN URBAN SUBDISTRICTS Exposed MPW to Total MPW Contribution Contribution Uncollected Urban Area MPW from Collection Discharge (kton/year) Waste in Exposed Relative Relative Priority Point Diffuse Rate ID District Catchment Dry Dry Wet Total TH1046 * Khlong Sam Chao Phraya/ - 2.49 0.10 2.59 4.7% 1.6% 68.7% 2.59 Wa Bang Pakong TH1003 Nong Chok Chao Phraya - 2.14 0.09 2.23 4.0% 1.3% 63.8% 2.23 TH1022 * Phasi Charoen Chao Phraya - 2.04 0.08 2.12 3.8% 2.0% 68.7% 2.12 TH1019 * Taling Chan Chao Phraya - 1.73 0.07 1.80 3.3% 1.8% 70.4% 1.80 TH1201 * Mueang Chao Phraya - 0.83 1.65 2.48 4.5% 4.3% 75.0% 1.72 Nonthaburi TH1016 * Bangkok Yai Chao Phraya - 0.96 0.04 1.00 1.8% 1.6% 69.2% 1.00 TH1206 * Pak Kret Chao Phraya - 0.51 1.02 1.53 2.8% 2.7% 76.9% 0.94 TH2011 Ko Chan Bang Pakong - 1.33 - 1.33 2.4% 0.3% 39.0% 0.49 TH2001 * Mueang Chon Bang Pakong 0.24 2.01 - 2.25 4.1% 1.5% 51.5% 0.49 Buri Section 4.Conclusions and Recommendations | 71 BOX 5. HEALTH AND ENVIRONMENTAL HAZARDS FROM BURNING (PLASTIC) WASTE It is generally known that burning plastic is a major source of air pollution. Openly burning plastics releases large amounts of toxic gases that are harmful to humans, vegetation, and animals, and are a source of environmental pollution in general (Verma et al. 2016). The released toxics can cause a wide variety of serious health issues in humans including aggravating respiratory illnesses such as COVID-19 (Zhu et al. 2020). The top 10 critical districts with regard to exposed • Development of a sorting system and collection MPW from uncollected plastic waste (Table 16), show of waste by classification. that addressing this problem is not an easy task. Apart • Training to implement best practices on sorting and from Phanat Nikhom, the relative contributions of each collecting, such as separate collection schedules of the districts is only about 2–4 percent. Therefore, for different types of waste. reducing uncollected waste requires a coordinated • Finding sanitary disposal sites for small LAOs effort and is likely going to take some time before that could join with a close larger LAO based it really starts to show in reduced MPW discharged on the cluster. into the marine environment. • In some cases where the disposal site is far away The central government, through the environmental from the collection area, providing a transfer station fund, should promote and support the organization for waste from remote locations. of solid waste management in these LAOs through: • Evaluation of the collection and transport of solid waste capacity and provide sufficient and suitable machinery, equipment and vehicles. Table 16. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW GENERATED IN RURAL SUBDISTRICTS Exposed MPW Contribution to Total (kton/year) Population MPW Discharge Contribution Relative Relative Point Diffuse Total Urban Rural Priority ID District Catchment Dry Dry Wet Total TH2006 * Phanat Nikhom Bang Pakong 0.32 4.87 - 5.18 9.4% 3.0% 203,656 3.2% 1.0% TH2001 * Mueang Chon Buri Bang Pakong 0.20 2.01 - 2.25 4.1% 1.5% 129,241 15.4% 84.6% TH7305 Bang Len Tha Chin 0.01 1.38 - 1.39 2.5% 1.3% 106,318 0.0% 100.0% TH7302 Kam Phaeng Saen Tha Chin - 1.13 - 1.13 2.0% 0.9% 150,776 0.0% 100.0% TH7301 * Mueang Nakhom Tha Chin 0.55 1.66 - 2.21 4.0% 2.2% 326,448 32.6% 67.4% Pathom TH7304 Don Tum Tha Chin 0.10 0.85 - 0.95 1.7% 1.0% 56,942 0.0% 100.0% TH2011 Ko Chan Bang Pakong - 1.33 - 1.33 2.4% 0.3% 59,682 45.4% 54.6% TH7303 Phutthamonthon Chao Phraya - 0.87 - 0.87 1.6% 0.7% 23,866 0.0% 100.0% TH1201 * Mueang Chao Phraya - 0.83 1.65 2.48 4.5% 4.3% 656,021 79.7% 20.3% Nonthaburi TH7303 Nakhon Chai Si Tha Chin 0.21 0.72 - 0.93 1.7% 1.0% 118,971 0.0% 100.0% 72 | Plastic Waste Material Flow Analysis for Thailand: Summary Report 3. Invest in well-managed final disposal facilities Therefore, similar to the clean-up activities of the and upgrade unsanitary disposal facilities (open urban drainage systems and the trimming of trees dumpsites and controlled dumps), giving priority prior to the onset of the rainy season, the LAO should to the facilities nearby waterways consider increasing the frequency of waste collection Although Thailand has invested significantly in solid prior to and during the rainy season to help reduce the waste management and has constructed many sanitary amount of washed-off plastic waste. The government disposal facilities over the past 10 years, there are may even consider actively looking for accumulated still many unsanitary disposal sites (especially in the plastic waste in the area and removing it before it can more rural areas). The PCD already has a list of priority be washed off, using the weather forecast to plan and facilities that require attention. This study provides coordinate efforts. additional information to determine the top priority 5. Improve laws and regulations to support the facilities that are expected to contribute most to marine implementation of measures debris. The top 10 critical districts that accommodate Develop a law to enforce MSW separation/sorting the priority facilities contribute to about 25 percent at source, separate collection and clustering of local of total exposed MPW (Table 17). authorities for the management of solid waste, including The top three cover the biggest open dumpsites in the regulations on the system for monitoring, control, the studied area, each with an annual absorption establishment and operation of waste disposal, and capacity between 100–200 kton/year. These open capacity building of the local authority’s staff in waste dumpsites deserve urgent attention and measures management. The laws to be improved include: should be taken to properly contain waste disposed • Act on the maintenance of cleanliness and at these locations. orderliness of the country 2017 4. Consider introducing city-wide clean-up sweeps • Announcement of the Ministry of Interior on Waste just before the start of the rainy season Management 2017 The study results indicate that the plastic waste discharge peaks mostly occur during the rainy season. Table 17. TOP 10 CRITICAL DISTRICTS ACCORDING TO EXPOSED MPW FROM POINT SOURCES Exposed MPW Relative (kton/year) Relative Contribution Priority Point Diffuse Contribution to Total MPW ID District Catchment Dry Dry Wet Total Discharge TH7401 * Mueang Samut Tha Chin 3.23 - - 3.23 5.8% 2.7% Sakhon TH2002 Ban Bueng Bang Pakong 3.14 0.27 - 3.41 6.2% 0.8% TH2401 Mueang Bang Pakong 2.14 - - 2.14 3.9% 1.5% Chachoengsao TH1414 Uthai Chao Phraya 0.87 - - 0.87 1.6% 0.4% TH8404 Ko Samui Ko Samui 0.84 - - 0.84 1.5% 0.1% TH1104 Phra Pradaeng Chao Phraya 0.72 - - 0.72 1.3% 1.1% TH7101 Mueang Mae Klong 0.68 0.09 - 0.77 1.4% 0.1% Kanchanaburi TH7605 Tha Yang Bang Taboon 0.65 0.05 - 0.69 1.3% 0.0% TH1601 Mueang Lop Buri Chao Phraya 0.63 0.03 - 0.66 1.2% 0.2% TH7209 U Thong Tha Chin 0.55 - - 0.55 1.0% 0.3% Section 4.Conclusions and Recommendations | 73 In addition, each LAO should strictly enforce regulations Once better SWM data and an improved SWM model is that require households, markets, businesses and all available, evaluate whether improving the hydrological other organizations in their area to separate their models to the described level of detail is required and waste at source. will provide the necessary additional information to Establish a process of participation by local residents inform policy. The available hydrological information in giving recommendations, making decisions and was incomplete for some catchments and all the tourist cooperating in the implementation of management hotspots (the islands and Krabi province). These data projects. Manage solid waste and hazardous waste are used to estimate the runoff and discharge and from the beginning. This will reduce conflicts and provide estimates to calculate wash-off of exposed opposition from the people. MPW. If it is needed, recommendations to improve the hydrological data include (see Appendix F for The study results indicate that by eliminating the more details): exposed MPW from the top 10 most critical districts from the priority catchments, the amount of MPW • Start collecting hydrological data at the small discharged into the marine environment from the islands and in the small catchments. priority catchments will reduce significantly, potentially • Collect datasets that describe the water taken by about 50 percent. Prioritizing the top three most out of the rivers for irrigation and water levels in, critical districts may reduce the discharge of MPW and management schemes of, reservoirs. into the marine environment by about 25 percent. Lastly, modeling of fate and transport of plastics in 4.3 RECOMMENDATIONS TO IMPROVE rivers is still in its infancy and presents a great number of challenges. Investigating plastic waste distribution THE DATA AND UNDERLYING MODELS along riverbanks, in the water column, in riverine The results of the assessment are based on limited sediment and so on could help to better understand data and developing knowledge. In this section, rec- how different riverine features (e.g, size, meandering, ommendations are provided to improve the data and vegetation, soil) can affect the transport and retention knowledge. Further details are provided in Appendix F. of plastic waste. More realistic parameters of retention As the SWM data provides the basis to estimate could be defined. These are, nevertheless, research exposed MPW, it is recommended to first improve questions that need to be addressed through scientific SWM data before considering improving the other investigation and the larger scientific community. As models. Recommendations to improve this data could new knowledge on riverine transport and fate becomes include (see Appendix F for more details): available, it can then be incorporated in the calibration of the transport modeling parameters. 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