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Source apportionment of PM10 in Delhi, India using PCA/APCS, UNMIX and PMF 被引量:8
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作者 srishti jain S.K. Sharma +1 位作者 T.K. Mandal Mohit Saxena 《Particuology》 SCIE EI CAS CSCD 2018年第2期107-118,共12页
Source apportionment of particulate matter (PM10) measurements taken in Delhi, India between January 2013 and June 2014 was carried out using two receptor models, principal component analysis with absolute principal... Source apportionment of particulate matter (PM10) measurements taken in Delhi, India between January 2013 and June 2014 was carried out using two receptor models, principal component analysis with absolute principal component scores (PCA/APCS) and UNMIX. The results were compared with previous estimates generated using the positive matrix factorization (PMF) receptor model to investigate each model's source-apportioning capability. All models used the PM10 chemical composition (organic carbon (OC), elemental carbon (EC), water soluble inorganic ions (WSIC), and trace elements) for source apportionment. The average PM10 concentration during the study period was 249.7±103.9 μg/m3 (range: 61.4-584.8 μg/m3). The UNMIX model resolved five sources (soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), a mixed source of biomass burning (BB) and sea salt (SS), and industrial emissions (IE)). The PCA/APCS model also resolved five sources, two of which also included mixed sources (SD, VE, SD+SS, (SA+BB+SS) and 1E). The PMF analysis differentiated seven individual sources (SD, VE, SA, BB, SS, IE, and fossil fuel combustion (FFC)). All models identified the main sources contributing to PM10 emissions and reconfirmed that VE, SA, BB, and SD were the dominant contributors in Delhi. 展开更多
关键词 Receptor model PCA/APCS UNMIX PMF Source apportionment
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