Development of vehicle population model using system dynamic approach for vehicle emission estimation | |
| Author | Kalyarat Rueangrat |
| Call Number | AIT Thesis no.EV-21-06 |
| Subject(s) | Vehicles--Environmental aspects--Thailand--Bangkok Air--Pollution--Thailand--Bangkok Particles--Environmental aspects--Thailand--Bangkok |
| 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 |
| Abstract | This study focuses on estimating emission from on-road transport sector in Bangkok Metropolis Region (BMR) during 2020-2030 which includes Bangkok, Nakhon Pathom, Pathum Thani, Nonthaburi, Samut Prakan, and Samut Sakhon. The on-road vehicle fleet is categorized into eight vehicle types including sedan, microbus, pick-up & van, motortricycle, bus, and truck. The system dynamic approach is used to establish relationships between various parameters that influence vehicle fleet behavior and emissions. Using Stella software, a clear relationship between emission factors, vehicle age, vehicle technology, retired vehicles, fuel consumption, fuel efficiency, and new engine emission were established, ensuring model transparency. The system dynamic model for vehicle emission estimated was developed for BMR during 2020-2030. For the next 10 years, the PM2.5 emission projection showed a decreasing trend under the BAU fuel consumption scenarios because of the cleaner EURO standard implementation in the futue. Emissions were reduced by 78% in 2030. For the year 2030, total PM2.5 emission under the business-as-usual scenario was 5.6 kt. There were large contributions of PM2.5 emission from truck, pick-up and van with the share combination of 83% of the total emission. However, if there was a delayed in emission standard implementation, cumulative PM2.5 emission in BMR during 2020-2030 would increase 22- 100% according to our estimation. The development of system dynamics for vehicle emission estimation in this study can be used to estimate PM2.5 emission from on-road transportation in BMR. It gives a clear picture of emission estimation. It can classify major polluters based on vehicle types and technologies, providing for the most cost-effective emission reduction measures to be prioritized. Furthermore, the model can be used to analyze and evaluate a variety of possible policy and control scenario simulations. |
| Year | 2021 |
| 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 and Management (EV) |
| Chairperson(s) | Ekbordin Winijkul; |
| Examination Committee(s) | Shipin, Oleg;Xue, Wenchao; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2021 |