A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Environmental Engineering and ManagementExamination Committee:Dr. Ekbordin Winijkul(Chairperson)Prof. Nguyen Thi Kim OanhDr. Sohee MinsunKimNationality:ThaiPrevious Degree:Bachelor of Public Health in Environmental Health ScienceMahidol University, ThailandScholarship Donor:Thailand (HM Queen)Asian Institute of TechnologySchool of Environment, Resources and DevelopmentThailandMay 2018

Thesis (M. Sc.) - Asian Institute of Technology, 2018

Bangkok has had a traffic congestion problem causing from high traffic volumes, complex roads route and unprofessional traffic management, etc. When vehicles stop at the signalized intersection, the drivers always keep their vehicle{u2019}s engines running whichalso emit high level of exhaust pollutants. This study aimed at estimating CO and PM10concentration from traffic at the Saladeang intersection in Bangkok, Thailand, by using the CAL3QHC model which has algorithm to estimate queue length for different signal timings. The required inputs were traffic volume, types of vehicles, vehicle composition, meteorological conditions and emission factors. These data were required inputs to the model to estimate pollutant concentrations from traffic at the intersection. Running and idling emission factors of different vehicle emission control technologies were estimated by using vehicle emission testing data from the Thailand Automotive Emission Laboratory and pre-developed emission factors from the EMission FACtor (EMFAC). Others data were collected from the survey and video camera at the intersections. Outputs of the model were the concentration of CO and PM10from 6am-10pm on 7 weekdays and 6 weekends during December 2017 and February 2018. These output concentrations were compared with the monitoring data, and found that the Fractional Bias and Index of Agreement were in the acceptable ranges. Thus, the CAL3QHCcan be used to predict traffic CO and PM10concentration at the Saladaeng intersection.The CAL3QHC model was, then, used to estimate pollutant concentration reduction based on three scenarios in Thailand{u2019}s Transportation System Development Strategies; changing red signal timing, converting all buses to electrical buses, and allowing only eco-cars at the intersection. The model outputs showed that decreasing the red light phase length by 30% could decrease both CO and PM10concentration at the intersection by 19% and 9%, respectively. Changing all buses to electrical buses could reduce 30% of PM10concentrationfrom baseline while the reduction in CO concentration was much smaller since diesel buses did not significantly contribute to CO emission in baseline. However, highest reduction was observed when allowing only the vehicles with the highest emission control technologies at the intersection which 32% and 35% reduction in concentration of CO and PM10were estimated, respectively.