An assessment of emission from vehicle fleets in the Bangkok metropolitan region under various scenarios. | |
| Author | Rungtiwa Buadee |
| Call Number | AIT Thesis no.EV-17-18 |
| Subject(s) | Air quality management--Thailand--Bangkok Climatic changes--Thailand--Bangkok Motor vehicle fleets |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Environmental Engineering and Management |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. EV-17-18 |
| Abstract | Annually, the number of vehicle population and fuel technologies in Bangkok Metropolitan Region (BMR) has been rapidly changing. Updating the emission factors (EFs) for mobile sources is a crucial implementation to reduce uncertainty in emission estimation of on-road mobile source for urban air quality management in BMR. This study comprehend the current status of vehicle fleets and fleet technologies in BMR and used an International Vehicle Emission (IVE) model to develop EFs for current vehicle fleets of personal car (PC), motorcycle (MC), taxi, van, public passenger pick-up (Song Thaew) and public motorized tricycle (Tuk-Tuk) in BMR for the base case of 2015. The developed EFs were accordingly used to estimate the traffic emissions and characterized the potential emission reduction scenarios to quantify their impacts on traffic emission in BMR. Questionnaires, GPS surveys, and video recordings were used to collect vehicle fleets activity data which covered highways, arterial roads and residential roads in urban, sub-urban, and outskirts areas of BMR. The distribution of vehicle technologies of the vehicle fleet in BMR was surveyed. The average vehicle kilometer travelled (VKT) for each type of vehicles was calculated by relationship between vehicle age and odometer reading obtained from survey. The result of questionnaire surveys found that the average ages (year) of PC, MC, taxi, van, Song Thaew, and Tuk-Tuk were 5.7, 4.2, 4.2, 6.1,11.8, and 7.7, respectively. The composite EFs were obtained from IVE model simulation while gasohol fueled EFs were obtained from Pollution Control Department. The developed EFs were then used together with previous developed bus and truck EFs to estimate traffic emission for base case 2015 and three optimistic scenarios; (S1) Euro III technology implementation, (S2) Euro IV technology implementation for the entire fleet, and (S3) eco-driving scenario for the active fleets. The estimated traffic emissions of major pollutants for the base case 2015, in Gg/year, were 57,857, 1,193, 229, and 172 for CO₂, CO, NOx, and VOCs, respectively. The estimated emission of S1 showed the reductions of emitted CO, PM, VOCs, and NOx by 50%, 32%, 26% and 11%, respectively as compared to the base case. Accordingly, the global warming potential (GWP) in 20-year CO₂ equivalent of S1 was reduced by 12.95%. More reduction was obtained from S2 for CO, PM, VOCs, and NOx of 58%, 33%, 28% and 15%, respectively while that of GWP was 12.77%. However, eco-driving scenario can reduce CO, PM, VOCs, and NOx emissions by 24%, 13%, 8%, and 8%, respectively. The global warming potential (GWP) in 20-year CO₂ equivalent of S3 was reduced by 12.84%. Thus, the application of Euro IV standard for the vehicle fleets in BMR, as in S2, would gain the most benefits to air quality and climate forcing mitigation as compared to other scenarios. Beneficially, the findings of this study can bring the suggestion on possible emission control measures to policy makers for future policy implementation. |
| Year | 2017 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Environmental Engineering (EV) |
| Chairperson(s) | Nguyen, Thi Kim Oanh; |
| Examination Committee(s) | Thammarat Koottatep;Permadi, Didin Agustian;Ekbordin Winijkul;Narita, Daiju; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Thesis (M.Sc.) - Asian Institute of Technology, 2017 |