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Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model
Gao, S (Gao, Shuang)1; Yang, W (Yang, Wen)2; Zhang, H (Zhang, Hui)1; Sun, YL (Sun, Yanling)1; Mao, J (Mao, Jian)1; Ma, ZX (Ma, Zhenxing)1; Cong, ZY (Cong, Zhiyuan)3; Zhang, X (Zhang, Xian)1; Tian, SS (Tian, Shasha)1; Azzi, M (Azzi, Merched)4; Chen, L (Chen, Li)1; Bai, ZP (Bai, Zhipeng)1,2
Source PublicationATMOSPHERIC ENVIRONMENT
2018-02-01
Volume174Issue:0Pages:180-187
DOI10.1016/j.atmosenv.2017.11.045
AbstractThe determination of background concentration of PM2.5 is important to understand the contribution of local emission sources to total PM2.5 concentration. The purpose of this study was to exam the performance of baseline separation techniques to estimate PM2.5 background concentration. Five separation methods, which included recursive digital filters (Lyne-Hollick, one-parameter algorithm, and Boughton two-parameter algorithm), sliding interval and smoothed minima, were applied to one-year PM2.5 time-series data in two heavily polluted cities, Tianjin and Jinan. To obtain the proper filter parameters and recession constants for the separation techniques, we conducted regression analysis at a background site during the emission reduction period enforced by the Government for the 2014 Asia-Pacific Economic Cooperation (APEC) meeting in Beijing. Background concentrations in Tianjin and Jinan were then estimated by applying the determined filter parameters and recession constants. The chemical mass balance (CMB) model was also applied to ascertain the effectiveness of the new approach. Our results showed that the contribution of background PM concentration to ambient pollution was at a comparable level to the contribution obtained from the previous study. The best performance was achieved using the Boughton two-parameter algorithm. The background concentrations were estimated at (27 +/- 2) mu g/m(3) for the whole year, (34 +/- 4) mu g/m(3) for the heating period (winter), (21 +/- 2) mu g/m(3) for the non-heating period (summer), and (25 +/- 2) mu g/m(3) for the sandstorm period in Tianjin. The corresponding values in Jinan were (30 +/- 3) mu g/m3, (40 +/- 4) mu g/m(3), (24 +/- 5) mu g/m(3), and (26 +/- 2) mu g/m(3), respectively. The study revealed that these baseline separation techniques are valid for estimating levels of PM2.5 air pollution, and that our proposed method has great potential for estimating the background level of other air pollutants.
WOS IDWOS:000423888400017
Language英语
Indexed BySCIE
KeywordAIR-POLLUTION SOURCE APPORTIONMENT SITE EXPOSURE STATION HAIKOU GASES CHINA PM10
WOS Research AreaEnvironmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS SubjectEnvironmental Sciences ; Meteorology & Atmospheric Sciences
Cooperation Status国际
ISSN1352-2310
Department环境变化与地表过程重点实验室
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itpcas.ac.cn/handle/131C11/8747
Collection图书馆
Affiliation1.Tianjin Normal Univ, Sch Geog & Environm Sci, Tianjin, Peoples R China;
2.Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing, Peoples R China;
3.Chinese Acad Sci, Inst Tibetan Plateau Res, Beijing, Peoples R China;
4.Commonwealth Sci & Ind Res Org CSIRO Energy, N Ryde, NSW, Australia.
Recommended Citation
GB/T 7714
Gao, S ,Yang, W ,Zhang, H ,et al. Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model[J]. ATMOSPHERIC ENVIRONMENT,2018,174(0):180-187.
APA Gao, S .,Yang, W .,Zhang, H .,Sun, YL .,Mao, J .,...&Bai, ZP .(2018).Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model.ATMOSPHERIC ENVIRONMENT,174(0),180-187.
MLA Gao, S ,et al."Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model".ATMOSPHERIC ENVIRONMENT 174.0(2018):180-187.
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