IGSNRR OpenIR
Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information
Chen, Gongbo1; Knibbs, Luke D.2; Zhang, Wenyi3; Li, Shanshan1; Cao, Wei4; Guo, Jianping5; Ren, Hongyan4; Wang, Boguang6; Wang, Hao7; Williams, Gail2; Hamm, N. A. S.8; Guo, Yuming1
2018-02-01
Source PublicationENVIRONMENTAL POLLUTION
ISSN0269-7491
Volume233Pages:1086-1094
Corresponding AuthorGuo, Yuming(yuming.guo@monash.edu)
AbstractBackground: PM1 might be more hazardous than PM2.5 (particulate matter with an aerodynamic diameter <= 1 mu m and <= 2.5 mu m, respectively). However, studies on PM1 concentrations and its health effects are limited due to a lack of PM1 monitoring data. Objectives: To estimate spatial and temporal variations of PM1 concentrations in China during 2005-2014 using satellite remote sensing, meteorology, and land use information. Methods: Two types of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) data, Dark Target (DT) and Deep Blue (DB), were combined. Generalised additive model (GAM) was developed to link ground-monitored PM1 data with AOD data and other spatial and temporal predictors (e.g., urban cover, forest cover and calendar month). A 10-fold cross-validation was performed to assess the predictive ability. Results: The results of 10-fold cross-validation showed R-2 and Root Mean Squared Error (RMSE) for monthly prediction were 71% and 13.0 mu g/m(3), respectively. For seasonal prediction, the R-2 and RMSE were 77% and 11.4.Lg/m(3), respectively. The predicted annual mean concentration of PM1 across "China was 26.9 mu g/m(3). The PM1 level was highest in winter while lowest in summer. Generally, the PM1 levels in entire China did not substantially change during the past decade. Regarding local heavy polluted regions, PM1 levels increased substantially in the South-Western Hebei and Beijing-Tianjin region. Conclusions: GAM with satellite-retrieved AOD, meteorology, and land use information has high predictive ability to estimate ground-evel PM1. Ambient PM1 reached high levels in China during the past decade. The estimated results can be applied to evaluate the health effects of PM1. (C) 2017 Elsevier Ltd. All rights reserved.
KeywordPM1 Aerosol optical depth Meteorology Land use China
DOI10.1016/j.envpol.2017.10.011
WOS KeywordAEROSOL OPTICAL DEPTH ; PARTICULATE AIR-POLLUTION ; USE REGRESSION-MODEL ; GROUND-LEVEL PM2.5 ; TEMPORAL VARIATIONS ; SEASONAL-VARIATIONS ; HEALTH IMPACT ; MODIS ; CITY ; AOD
Indexed BySCI
Language英语
Funding ProjectCareer Development Fellowship of Australian National Health and Medical Research Council (NHMRC)[APP1107107] ; NHMRC Early Career Fellowship[APP1109193] ; NHMRC Centre of Research Excellence (CRE)-Centre for Air quality and health Research and evaluation[APP1030259] ; China Scholarship Council (CSC)
Funding OrganizationCareer Development Fellowship of Australian National Health and Medical Research Council (NHMRC) ; NHMRC Early Career Fellowship ; NHMRC Centre of Research Excellence (CRE)-Centre for Air quality and health Research and evaluation ; China Scholarship Council (CSC)
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences
WOS IDWOS:000424177000115
PublisherELSEVIER SCI LTD
Citation statistics
Cited Times:18[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/57115
Collection中国科学院地理科学与资源研究所
Corresponding AuthorGuo, Yuming
Affiliation1.Monash Univ, Sch Publ Hlth & Prevent Med, Dept Epidemiol & Prevent Med, Level 2,553 St Kilda Rd, Melbourne, Vic 3004, Australia
2.Univ Queensland, Sch Publ Hlth, Brisbane, Qld, Australia
3.Acad Mil Med Sci, Inst Dis Control & Prevent, Ctr Dis Surveillance & Res, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
5.Chinese Acad Meteorol Sci, Sate Key Lab Severe Weather, Beijing, Peoples R China
6.Jinan Univ, Inst Environm & Climate Res, Guangzhou, Guangdong, Peoples R China
7.Hong Kong Polytech Univ, Air Qual Studies, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R China
8.Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, Enschede, Netherlands
Recommended Citation
GB/T 7714
Chen, Gongbo,Knibbs, Luke D.,Zhang, Wenyi,et al. Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information[J]. ENVIRONMENTAL POLLUTION,2018,233:1086-1094.
APA Chen, Gongbo.,Knibbs, Luke D..,Zhang, Wenyi.,Li, Shanshan.,Cao, Wei.,...&Guo, Yuming.(2018).Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information.ENVIRONMENTAL POLLUTION,233,1086-1094.
MLA Chen, Gongbo,et al."Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information".ENVIRONMENTAL POLLUTION 233(2018):1086-1094.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chen, Gongbo]'s Articles
[Knibbs, Luke D.]'s Articles
[Zhang, Wenyi]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chen, Gongbo]'s Articles
[Knibbs, Luke D.]'s Articles
[Zhang, Wenyi]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chen, Gongbo]'s Articles
[Knibbs, Luke D.]'s Articles
[Zhang, Wenyi]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.