TY  - SER
AU  - Nawapat Choosuwan
AU  - Pramanik,Malay
AU  - Vilas Nitivattananon,
AU  - Ekbordin Winijkul,
ED  - Royal Thai Government Fellowship,
TI  - Assessing air pollution risks from electric vehicles in Bangkok: towards mitigation strategies and policy recommendations
T2  - Research studies project report
PY  - 2024///
CY  - Pathum Thani
PB  - Asian Institute of Technology
KW  - Air
KW  - Pollution
KW  - Government policy
KW  - Thailand
KW  - Bangkok
KW  - Urban pollution
N1  - A research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Urban Innovation and Sustainability; Research Studies Project Report (M. Sc.) -  Asian Institute of Technology, 2024
N2  - 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{u2019}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.
UR  - http://203.159.5.9/ait-thesis/detail.php?q=B22689
ER  -