guest ::
| Home > Publications database > Severe Surface Ozone Pollution in China: A Global Perspective > print |
| Home > Publications database > Severe Surface Ozone Pollution in China: A Global Perspective > print |
| 001 | 858702 | ||
| 005 | 20230127125335.0 | ||
| 024 | 7 | _ | |a 10.1021/acs.estlett.8b00366 |2 doi |
| 024 | 7 | _ | |a WOS:000442184100004 |2 WOS |
| 024 | 7 | _ | |a altmetric:45781370 |2 altmetric |
| 037 | _ | _ | |a FZJ-2018-07547 |
| 082 | _ | _ | |a 333.7 |
| 100 | 1 | _ | |a Lu, Xiao |0 0000-0002-5989-0912 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Severe Surface Ozone Pollution in China: A Global Perspective |
| 260 | _ | _ | |a Columbus, Ohio |c 2018 |b ACS |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1545210245_10680 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a The nationwide extent of surface ozone pollution in China and its comparison to the global ozone distribution have not been recognized because of the scarcity of Chinese monitoring sites before 2012. Here we address this issue by using the latest 5 year (2013-2017) surface ozone measurements from the Chinese monitoring network, combined with the recent Tropospheric Ozone Assessment Report (TOAR) database for other industrialized regions such as Japan, South Korea, Europe, and the United States (JKEU). We use various human health and vegetation exposure metrics. We find that although the median ozone values are comparable between Chinese and JKEU cities, the magnitude and frequency of high-ozone events are much larger in China. The national warm-season (April September) fourth highest daily maximum 8 h average (4MDA8) ozone level (86.0 ppb) and the number of days with MDA8 values of >70 ppb (NDGT70, 29.7 days) in China are 6.3-30% (range of regional mean differences) and 93-575% higher, respectively, than the JKEU regional averages. Health exposure metrics such as warm-season mean MDA8 and annual SOMO35 (sum of ozone means over 35 ppb) are 6.3-16 and 25-95% higher in China, respectively. We also find an increase in the surface ozone level over China in 2016 and 2017 relative to 2013 and 2014. Our results show that on the regional scale the exposure of humans and vegetation to ozone is greater in China than in other developed regions of the world with comprehensive ozone monitoring. |
| 536 | _ | _ | |a 512 - Data-Intensive Science and Federated Computing (POF3-512) |0 G:(DE-HGF)POF3-512 |c POF3-512 |f POF III |x 0 |
| 536 | _ | _ | |0 G:(DE-Juel-1)ESDE |a Earth System Data Exploration (ESDE) |c ESDE |x 1 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Hong, Jiayun |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Zhang, Lin |0 0000-0003-2383-8431 |b 2 |
| 700 | 1 | _ | |a Cooper, Owen R. |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Schultz, Martin |0 P:(DE-Juel1)6952 |b 4 |
| 700 | 1 | _ | |a Xu, Xiaobin |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Wang, Tao |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a Gao, Meng |0 0000-0002-8657-3541 |b 7 |
| 700 | 1 | _ | |a Zhao, Yuanhong |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Zhang, Yuanhang |0 P:(DE-HGF)0 |b 9 |
| 773 | _ | _ | |a 10.1021/acs.estlett.8b00366 |g Vol. 5, no. 8, p. 487 - 494 |0 PERI:(DE-600)2745499-X |n 8 |p 487 - 494 |t Environmental science & technology letters |v 5 |y 2018 |x 2328-8930 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/858702/files/acs.estlett.8b00366-1.pdf |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/858702/files/acs.estlett.8b00366-1.pdf?subformat=pdfa |x pdfa |y Restricted |
| 909 | C | O | |o oai:juser.fz-juelich.de:858702 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)6952 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-512 |2 G:(DE-HGF)POF3-500 |v Data-Intensive Science and Federated Computing |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |l Supercomputing & Big Data |
| 914 | 1 | _ | |y 2018 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b ENVIRON SCI TECH LET : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1060 |2 StatID |b Current Contents - Agriculture, Biology and Environmental Sciences |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b ENVIRON SCI TECH LET : 2017 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|