| Mitigation of severe urban haze pollution by a precision air pollution control approach | |
| Yu, Shaocai1,2,3; Li, Pengfei1,2; Wang, Liqiang1,2; Wu, Yujie1,2; Wang, Si1,2; Liu, Kai3; Zhu, Tong4; Zhang, Yuanhang4; Hu, Min4; Zeng, Liming4; Zhang, Xiaoye5; Cao, Junji6; Alapaty, Kiran7; Wong, David C.8; Pleim, Jon8; Mathur, Rohit8; Rosenfeld, Daniel9; Seinfeld, John H.3 | |
| 2018-05-25 | |
| Source Publication | SCIENTIFIC REPORTS
 |
| Volume | 8Issue:8151Pages:1-11 |
| Subtype | Article |
| Abstract | Severe and persistent haze pollution involving fine particulate matter (PM2.5) concentrations reaching unprecedentedly high levels across many cities in China poses a serious threat to human health. Although mandatory temporary cessation of most urban and surrounding emission sources is an effective, but costly, short-term measure to abate air pollution, development of long-term crisis response measures remains a challenge, especially for curbing severe urban haze events on a regular basis. Here we introduce and evaluate a novel precision air pollution control approach (PAPCA) to mitigate severe urban haze events. The approach involves combining predictions of high PM2.5 concentrations, with a hybrid trajectory-receptor model and a comprehensive 3-D atmospheric model, to pinpoint the origins of emissions leading to such events and to optimize emission controls. Results of the PAPCA application to five severe haze episodes in major urban areas in China suggest that this strategy has the potential to significantly mitigate severe urban haze by decreasing PM2.5 peak concentrations by more than 60% from above 300 mu g m(-3) to below 100 mu g m(-3), while requiring similar to 30% to 70% less emission controls as compared to complete emission reductions. The PAPCA strategy has the potential to tackle effectively severe urban haze pollution events with economic efficiency. |
| WOS Headings | Science & Technology |
| DOI | 10.1038/s41598-018-26344-1 |
| WOS Keyword | HYBRID RECEPTOR MODELS ; PARTICULATE MATTER ; SOURCE APPORTIONMENT ; EMISSION INVENTORY ; CHINA ; CMAQ ; POLLUTANTS ; TRANSPORT ; HANGZHOU ; AEROSOLS |
| Indexed By | SCI |
| Language | 英语 |
| WOS Research Area | Science & Technology - Other Topics |
| WOS Subject | Multidisciplinary Sciences |
| WOS ID | WOS:000433061300033 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ieecas.cn/handle/361006/5142 |
| Collection | 粉尘与环境研究室 |
| Affiliation | 1.Zhejiang Univ, Coll Environm & Resource Sci, Res Ctr Air Pollut & Hlth, Minist Educ, Hangzhou 310058, Zhejiang, Peoples R China 2.Zhejiang Univ, Coll Environm & Resource Sci, Key Lab Environm Remediat & Ecol Hlth, Minist Educ, Hangzhou 310058, Zhejiang, Peoples R China 3.CALTECH, Div Chem & Chem Engn, Pasadena, CA 91125 USA 4.Peking Univ, Coll Environm Sci & Engn, Beijing 100871, Peoples R China 5.Chinese Acad Meteorol Sci, Key Lab Atmospher Chem, CMA, 46 Zhong Guan Cun S Ave, Beijing 100081, Peoples R China 6.Chinese Acad Sci, Inst Earth Environm, Key Lab Aerosol Chem & Phys, SKLLQG, Xian, Shaanxi, Peoples R China 7.US Environm Protect Agcy EPA, Syst Exposure Div, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA 8.US Environm Protect Agcy EPA, Computat Exposure Div, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA 9.Hebrew Univ Jerusalem, Inst Earth Sci, Jerusalem, Israel |
| Recommended Citation GB/T 7714 | Yu, Shaocai,Li, Pengfei,Wang, Liqiang,et al. Mitigation of severe urban haze pollution by a precision air pollution control approach[J]. SCIENTIFIC REPORTS,2018,8(8151):1-11. |
| APA | Yu, Shaocai.,Li, Pengfei.,Wang, Liqiang.,Wu, Yujie.,Wang, Si.,...&Seinfeld, John H..(2018).Mitigation of severe urban haze pollution by a precision air pollution control approach.SCIENTIFIC REPORTS,8(8151),1-11. |
| MLA | Yu, Shaocai,et al."Mitigation of severe urban haze pollution by a precision air pollution control approach".SCIENTIFIC REPORTS 8.8151(2018):1-11. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Mitigation of severe（2735KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | Application Full Text | |
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