Assessing air pollution risks from electric vehicles in Bangkok : towards mitigation strategies and policy recommendations | |
| Author | Nawapat Choosuwan |
| Call Number | AIT RSPR no.UI-24-01 |
| Subject(s) | Air--Pollution--Government policy--Thailand--Bangkok Urban pollution--Thailand--Bangkok |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Urban Innovation and Sustainability |
| Publisher | Asian Institute of Technology |
| Abstract | Air pollution remains a critical concern in densely populated urban areas, particularly in cities like Bangkok where transportation emissions are a predominant contributor. This study aims to comprehensively understand the current situation and explore the relationship between electric vehicle (EV) adoption and air pollution risk in Bangkok, ultimately proposing effective policy recommendations for promoting EV adoption and improving air quality. The research utilized advanced machine learning models, including XGBoost, Naive Bayes, K-Nearest Neighbors (KNN), and Random Forest to assess air pollutant emission risks. The air pollutant emission risk assessment employs various air pollutants and environmental factors considered, such as CO, SO2, NO2, O3, PM2.5, PM10, wind speed (WS), wind direction (WD), relative humidity (RH), temperature, building density, road density, distance from roads, and the Normalized Difference Vegetation Index (NDVI). Pearson’s correlation was employed in the study to examine the relationship between EV charging density and air pollutant emission risk in Bangkok CBD. The findings for the current situation reveal a significant increase in Battery Electric Vehicle (BEV) registrations from 2018 to 2023, driven by technological advancements, government incentives, and rising environmental awareness. However, the study also highlights persistently high levels of particulate matter (PM2.5 and PM10) in densely populated and high-traffic areas, indicating the need for more aggressive measures to improve air quality. Key findings indicate that all models consistently identified high and very high-risk zones, particularly in the Central Business District (CBD) and along major roads, underscoring the significant impact of vehicular traffic and dense urbanization on air quality. A notable achievement of this study is the identification of a significant inverse correlation between EV charging capacity and air pollution risk, with areas of high charging capacity showing lower pollution levels. The insights and recommendations provided in this study offer a comprehensive roadmap for policymakers and stakeholders. By addressing infrastructure gaps, enhancing capacity, leveraging successful models, and fostering public-private collaboration, Bangkok can significantly reduce its environmental footprint and promote a healthier urban environment. |
| Year | 2024 |
| Type | Research Study Project Report (RSPR) |
| School | School of Environment, Resources, and Development |
| Department | Department of Development and Sustainability (DDS) |
| Academic Program/FoS | Urban Innovation and Sustainability (UIS) |
| Chairperson(s) | Pramanik, Malay; |
| Examination Committee(s) | Vilas Nitivattananon;Ekbordin Winijkul; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Research Studies Project Report (M. Sc.) - Asian Institute of Technology, 2024 |