Health and economic benefits of heavy-duty diesel truck emission control policies in Beijing
文献类型：期刊论文
| 作者 | Cheng, Shifen3,4; Zhang, Beibei3,4; Peng, Peng3,4; Lu, Feng1,2,3,4 |
| 刊名 | ENVIRONMENT INTERNATIONAL
 |
| 出版日期 | 2023-09-01 |
| 卷号 | 179页码:9 |
| 关键词 | Heavy-duty diesel trucks Traffic emissions Dispersion model Health impact assessment Scenario analysis |
| ISSN号 | 0160-4120 |
| DOI | 10.1016/j.envint.2023.108152 |
| 通讯作者 | Lu, Feng(luf@lreis.ac.cn) |
| 英文摘要 | PM2.5 emissions from heavy-duty diesel trucks (HDDTs) have a significant impact on air quality, human health, and climate change, and seriously threaten the UN Sustainable Development Goals. Globally, a series of emission control measures have been implemented to reduce pollution emissions from HDDTs. Current studies assessing the impact of these measures on air quality and human health have mainly used coarse-grained emission data as input to dispersion model, resulting in the inability to capture the spatiotemporal variability of pollutant concentrations and tending to increase the uncertainty of health impact assessment results. In this study, we quantified the impact of pollution control policies for HDDTs in Beijing on PM2.5 concentrations, human health, and economic losses by integrating policy scenario analysis, pollution dispersion simulation, public health impact and economic benefit assessment models, supported by high spatiotemporal resolution emission data from HDDTs. The results show that PM2.5 concentrations from HDDTs exhibit significant spatial aggregation characteristics, with the intensity of aggregation at night being about twice as high as that during the day. The emission hotspots are mainly concentrated in the sixth, fifth and fourth rings and major highways. Compared to the "business as usual" scenario in 2018, the current policy of updating the fuel standard to China VI and the emission standard to China 6 can reduce PM2.5 concentrations by 96.72%, thereby avoiding 612 premature deaths, which is equivalent to obtaining economic benefits of 1.65 billion CNY. This study further emphasizes the importance of high spatiotemporal resolution emission data during traffic dispersion modeling. The results can help improve the understanding of the effectiveness of emission reduction measures for HDDTs from a health benefit perspective. |
| WOS关键词 | DISPERSION MODEL ; VEHICLE EMISSIONS ; AIR-POLLUTION ; UNITED-STATES ; SAO-PAULO ; IMPACTS ; PM2.5 ; RLINE ; CHINA ; EXPOSURE |
| 资助项目 | National Natural Science Foundation of China[42101423] ; Innovation Project of LREIS[KPI003] ; Innovation Project of LREIS[YPI002] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23010202] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001060113700001 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | National Natural Science Foundation of China ; Innovation Project of LREIS ; Strategic Priority Research Program of the Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/196895]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Lu, Feng |
| 作者单位 | 1.Fuzhou Univ, Acad Digital China, Fuzhou, Peoples R China 2.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cheng, Shifen,Zhang, Beibei,Peng, Peng,et al. Health and economic benefits of heavy-duty diesel truck emission control policies in Beijing[J]. ENVIRONMENT INTERNATIONAL,2023,179:9. |
| APA | Cheng, Shifen,Zhang, Beibei,Peng, Peng,&Lu, Feng.(2023).Health and economic benefits of heavy-duty diesel truck emission control policies in Beijing.ENVIRONMENT INTERNATIONAL,179,9. |
| MLA | Cheng, Shifen,et al."Health and economic benefits of heavy-duty diesel truck emission control policies in Beijing".ENVIRONMENT INTERNATIONAL 179(2023):9. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。