Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory
This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near-real-time traffic data on road segments to develop a vehicle emission invent...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-03-01
|
| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/16/3161/2016/acp-16-3161-2016.pdf |
| _version_ | 1811193363193397248 |
|---|---|
| author | B. Jing L. Wu H. Mao S. Gong J. He C. Zou G. Song X. Li Z. Wu |
| author_facet | B. Jing L. Wu H. Mao S. Gong J. He C. Zou G. Song X. Li Z. Wu |
| author_sort | B. Jing |
| collection | DOAJ |
| description | This paper presents a bottom-up methodology based on the local emission
factors, complemented with the widely used emission factors of Computer
Programme to Calculate Emissions from Road Transport (COPERT) model and near-real-time traffic data on road segments to develop a vehicle emission
inventory with high temporal–spatial resolution (HTSVE) for the Beijing
urban area. To simulate real-world vehicle emissions accurately, the road
has been divided into segments according to the driving cycle (traffic
speed) on this road segment. The results show that the vehicle emissions of
NO<sub><i>x</i></sub>, CO, HC and PM were 10.54 × 10<sup>4</sup>, 42.51 × 10<sup>4</sup>
and 2.13 × 10<sup>4</sup> and 0.41 × 10<sup>4</sup> Mg respectively.
The vehicle emissions and fuel consumption estimated by the model were
compared with the China Vehicle Emission Control Annual Report and fuel
sales thereafter. The grid-based emissions were also compared with the
vehicular emission inventory developed by the macro-scale approach. This
method indicates that the bottom-up approach better estimates the levels and
spatial distribution of vehicle emissions than the macro-scale method, which
relies on more information. Based on the results of this study, improved air
quality simulation and the contribution of vehicle emissions to ambient
pollutant concentration in Beijing have been investigated in a companion
paper (He et al., 2016). |
| first_indexed | 2024-04-12T00:08:11Z |
| format | Article |
| id | doaj.art-589905de964d415d907bb1b004f59098 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-12T00:08:11Z |
| publishDate | 2016-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-589905de964d415d907bb1b004f590982022-12-22T03:56:03ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242016-03-01163161317010.5194/acp-16-3161-2016Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventoryB. Jing0L. Wu1H. Mao2S. Gong3J. He4C. Zou5G. Song6X. Li7Z. Wu8The College of Environmental Science & Engineering, Nankai University, Tianjin, ChinaThe College of Environmental Science & Engineering, Nankai University, Tianjin, ChinaThe College of Environmental Science & Engineering, Nankai University, Tianjin, ChinaChinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, ChinaThe College of Environmental Science & Engineering, Nankai University, Tianjin, ChinaThe College of Environmental Science & Engineering, Nankai University, Tianjin, ChinaMOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing, ChinaThe College of Environmental Science & Engineering, Nankai University, Tianjin, ChinaCollege of Civil and Transportation Engineering, Hohai University, Suzhou, ChinaThis paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near-real-time traffic data on road segments to develop a vehicle emission inventory with high temporal–spatial resolution (HTSVE) for the Beijing urban area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NO<sub><i>x</i></sub>, CO, HC and PM were 10.54 × 10<sup>4</sup>, 42.51 × 10<sup>4</sup> and 2.13 × 10<sup>4</sup> and 0.41 × 10<sup>4</sup> Mg respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The grid-based emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Based on the results of this study, improved air quality simulation and the contribution of vehicle emissions to ambient pollutant concentration in Beijing have been investigated in a companion paper (He et al., 2016).https://www.atmos-chem-phys.net/16/3161/2016/acp-16-3161-2016.pdf |
| spellingShingle | B. Jing L. Wu H. Mao S. Gong J. He C. Zou G. Song X. Li Z. Wu Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory Atmospheric Chemistry and Physics |
| title | Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory |
| title_full | Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory |
| title_fullStr | Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory |
| title_full_unstemmed | Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory |
| title_short | Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 1: Development and evaluation of vehicle emission inventory |
| title_sort | development of a vehicle emission inventory with high temporal spatial resolution based on nrt traffic data and its impact on air pollution in beijing part 1 development and evaluation of vehicle emission inventory |
| url | https://www.atmos-chem-phys.net/16/3161/2016/acp-16-3161-2016.pdf |
| work_keys_str_mv | AT bjing developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT lwu developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT hmao developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT sgong developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT jhe developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT czou developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT gsong developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT xli developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory AT zwu developmentofavehicleemissioninventorywithhightemporalspatialresolutionbasedonnrttrafficdataanditsimpactonairpollutioninbeijingpart1developmentandevaluationofvehicleemissioninventory |