Urban road transport emissions and potential for reducing emissions by electric vehicles
Road transport is one of the fastest-growing sectors contributing significantly to air pollution and greenhouse gas (GHG) emissions, especially in urban areas where exceedances of nitrogen oxides (NOx) and particulate matters (PM) values are frequent. These pollutants have clear health implications...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/169224 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-169224 |
---|---|
record_format |
dspace |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering::Civil engineering::Transportation |
spellingShingle |
Engineering::Civil engineering::Transportation Dwiyanti Arimbi Jinca Urban road transport emissions and potential for reducing emissions by electric vehicles |
description |
Road transport is one of the fastest-growing sectors contributing significantly to air pollution and greenhouse gas (GHG) emissions, especially in urban areas where exceedances of nitrogen oxides (NOx) and particulate matters (PM) values are frequent. These pollutants have clear health implications and indicate the need to plan and implement effective measures (such as introducing electric vehicles) to reduce road vehicles’ emissions. Emissions estimation from road transport could be applied using an emissions model. However, the emissions model reflecting Singapore’s local conditions is not yet available, and there are only limited emissions quantification efforts over the last few decades in Singapore.
This research aims to analyse how and to what extent the existing emissions models apply to Singapore’s urban area emissions estimation. This aim is accompanied by vehicle fleet development and emissions inventory estimation for 2004-2019, the identification of aggregated emission factors (EFs) from air quality measurements at the Kallang Paya-Lebar (KPE) tunnel expressway and estimation of potential emissions reduction of electric vehicles (EV) scenario (up to 2050).
The emissions loads for all pollutants showed a decreasing trend from 2004-2019. This result comes from the series of transportation policies such as vehicle growth control by way of vehicle quota system (VQS) and vehicle ownership in terms of the certificate of entitlement (COE) (which results in a high turnover rate of vehicles) and a combination of fiscal measures (e.g., vehicle taxes). A clear reduction trend was found for pollutants of carbon monoxide (CO) and volatile organic compounds (VOC), with passenger cars (PCs) and motorcycles (MCs) being the primary sources. Meanwhile, NOx, PM10 and PM2.5 emissions, which are mainly released by diesel vehicles, gradually decreased despite increasing the vehicle population using diesel and its transport activities. A comparison of bottom-up and top-down carbon dioxide (CO2) estimations showed less agreement, with a difference of 20% due to some limitations. The methodology, results and conclusions may apply to neighbouring cities in South-East Asia.
The aggregated EF was derived from the Kallang-Paya Lebar (KPE) tunnel measurement in 2015 showed CO=1.46 g/veh-km and NOx=0.28 g/veh-km. These values are compared to previous studies performed in other tunnels globally. It was evident that both CO and NOx EFs are at a low-level range. Still, some parts need to be improved in future EFs development in a tunnel and other real-world measurements.
Potential air pollutants and emissions reduction by penetration of electric vehicles (EVs) are estimated using COPERT emissions model under four scenarios; baseline, the basic scenario (S1), the medium scenario (S2) and the most ambitious scenarios (S3). Significant emissions reduction potential for 2050 is identified in scenario 3, with a reduction of 83%, 96%, and 85% in CO, VOC and CO2. NOx reduction is estimated at 66%, while for PM, the reduction is predicted to have less reduction (<50%) due to the still high share of non-exhaust emissions. The results provide a basis and support for additional policies to promote and manage EVs. Besides, insights into improving air quality are offered to support the global climate change issue. |
author2 |
Wong Yiik Diew |
author_facet |
Wong Yiik Diew Dwiyanti Arimbi Jinca |
format |
Thesis-Doctor of Philosophy |
author |
Dwiyanti Arimbi Jinca |
author_sort |
Dwiyanti Arimbi Jinca |
title |
Urban road transport emissions and potential for reducing emissions by electric vehicles |
title_short |
Urban road transport emissions and potential for reducing emissions by electric vehicles |
title_full |
Urban road transport emissions and potential for reducing emissions by electric vehicles |
title_fullStr |
Urban road transport emissions and potential for reducing emissions by electric vehicles |
title_full_unstemmed |
Urban road transport emissions and potential for reducing emissions by electric vehicles |
title_sort |
urban road transport emissions and potential for reducing emissions by electric vehicles |
publisher |
Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/169224 |
_version_ |
1773551341265747968 |
spelling |
sg-ntu-dr.10356-1692242023-08-01T07:08:34Z Urban road transport emissions and potential for reducing emissions by electric vehicles Dwiyanti Arimbi Jinca Wong Yiik Diew Interdisciplinary Graduate School (IGS) Gebhard Wulfhorst CYDWONG@ntu.edu.sg; gebhard.wulfhorst@tum.de Engineering::Civil engineering::Transportation Road transport is one of the fastest-growing sectors contributing significantly to air pollution and greenhouse gas (GHG) emissions, especially in urban areas where exceedances of nitrogen oxides (NOx) and particulate matters (PM) values are frequent. These pollutants have clear health implications and indicate the need to plan and implement effective measures (such as introducing electric vehicles) to reduce road vehicles’ emissions. Emissions estimation from road transport could be applied using an emissions model. However, the emissions model reflecting Singapore’s local conditions is not yet available, and there are only limited emissions quantification efforts over the last few decades in Singapore. This research aims to analyse how and to what extent the existing emissions models apply to Singapore’s urban area emissions estimation. This aim is accompanied by vehicle fleet development and emissions inventory estimation for 2004-2019, the identification of aggregated emission factors (EFs) from air quality measurements at the Kallang Paya-Lebar (KPE) tunnel expressway and estimation of potential emissions reduction of electric vehicles (EV) scenario (up to 2050). The emissions loads for all pollutants showed a decreasing trend from 2004-2019. This result comes from the series of transportation policies such as vehicle growth control by way of vehicle quota system (VQS) and vehicle ownership in terms of the certificate of entitlement (COE) (which results in a high turnover rate of vehicles) and a combination of fiscal measures (e.g., vehicle taxes). A clear reduction trend was found for pollutants of carbon monoxide (CO) and volatile organic compounds (VOC), with passenger cars (PCs) and motorcycles (MCs) being the primary sources. Meanwhile, NOx, PM10 and PM2.5 emissions, which are mainly released by diesel vehicles, gradually decreased despite increasing the vehicle population using diesel and its transport activities. A comparison of bottom-up and top-down carbon dioxide (CO2) estimations showed less agreement, with a difference of 20% due to some limitations. The methodology, results and conclusions may apply to neighbouring cities in South-East Asia. The aggregated EF was derived from the Kallang-Paya Lebar (KPE) tunnel measurement in 2015 showed CO=1.46 g/veh-km and NOx=0.28 g/veh-km. These values are compared to previous studies performed in other tunnels globally. It was evident that both CO and NOx EFs are at a low-level range. Still, some parts need to be improved in future EFs development in a tunnel and other real-world measurements. Potential air pollutants and emissions reduction by penetration of electric vehicles (EVs) are estimated using COPERT emissions model under four scenarios; baseline, the basic scenario (S1), the medium scenario (S2) and the most ambitious scenarios (S3). Significant emissions reduction potential for 2050 is identified in scenario 3, with a reduction of 83%, 96%, and 85% in CO, VOC and CO2. NOx reduction is estimated at 66%, while for PM, the reduction is predicted to have less reduction (<50%) due to the still high share of non-exhaust emissions. The results provide a basis and support for additional policies to promote and manage EVs. Besides, insights into improving air quality are offered to support the global climate change issue. Doctor of Philosophy 2023-07-10T01:21:28Z 2023-07-10T01:21:28Z 2021 Thesis-Doctor of Philosophy Dwiyanti Arimbi Jinca (2021). Urban road transport emissions and potential for reducing emissions by electric vehicles. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/169224 https://hdl.handle.net/10356/169224 10.32657/10356/169224 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |