气候变化领域集成服务门户(CCPortal): Source apportionment of airborne particulate matters over the Athabasca oil sands region: Inter-comparison between PMF modeling and ground-based remote sensing

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DOI	10.1016/j.atmosenv.2019.117103
	Source apportionment of airborne particulate matters over the Athabasca oil sands region: Inter-comparison between PMF modeling and ground-based remote sensing
	Xing Z.; Xiong Y.; Du K.
发表日期	2020
ISSN	1352-2310
卷号	221
英文摘要	The airborne particulate matters (PM) emissions associated with oil sands mining and processing operations in Athabasca oil sands regions (AOSR) could impact ambient air quality. But to what scales the effects could geographically reach remains unclear. The study was conducted to investigate the geographical influence of PM emissions within the AOSR at three sampling sites. The first site is sandwiched by oil sands mining and processing facilities. The second site is an urban site and close to the oil sands mining and processing areas. The third site is a remote rural site. Over the 2-year period (2015 and 2016), the observed geometric mean PM2.5 concentrations at Fort McKay (in AOSR), Fort McMurray (near AOSR), and Anzac (far away from AOSR) were 4.81, 5.89, and 3.30 μg/m3, respectively. The temporal variations of PM2.5 showed more elevated concentrations in spring and summer than winter and fall, which was consistent with the aerosol optical depth (AOD) observation. The Positive Matrix Factorization (PMF) modeling results at the above three sites suggest that anthropogenic sources were the dominant contributors of ambient aerosol concentrations within AOSR. According to the depleted vanadium (V) content in the surface dust factor from near AOSR site to remote site, the influence of petroleum coke dust as the primary source on aerosol emissions is geographically limited. The result also revealed the considerably long lasting influence of bitumen spill on the local aerosol source contributions. From the ground-based remote sensing observations of aerosol optical properties, petroleum coke could influence the atmospheric aerosol levels over AOSR with highly light-absorbing coarse-mode aerosols under warm and dry weather conditions. © 2019 Elsevier Ltd
关键词	Fine particulate matter Oil sands Petroleum coke dust PMF Source apportionment
语种	英语
scopus关键词	Air quality; Atmospheric aerosols; Dust; Factorization; Gasoline; Oil sands; Optical properties; Particulate emissions; Petroleum coke; Remote sensing; Sand; Urban growth; Vanadium compounds; Aerosol optical depths; Aerosol optical property; Airborne particulate matters; Elevated concentrations; Fine particulate matter; Ground-based remote sensing; Positive matrix factorization models; Source apportionment; Particles (particulate matter); asphalt; coke; petroleum; vanadium; aerosol; ambient air; anthropogenic source; climate conditions; dust; ground-based measurement; modeling; oil sand; particulate matter; remote sensing; source apportionment; temporal variation; urban site; aerosol; airborne particle; Article; autumn; concentration (parameter); dust; geographic distribution; optical depth; particulate matter; priority journal; remote sensing; seasonal variation; spring; summer; tar sand; winter; Alberta; Athabasca Oil Sands; Canada; Fort McKay; Fort McMurray
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/249483
作者单位	Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Canada
推荐引用方式 GB/T 7714	Xing Z.,Xiong Y.,Du K.. Source apportionment of airborne particulate matters over the Athabasca oil sands region: Inter-comparison between PMF modeling and ground-based remote sensing[J],2020,221.
APA	Xing Z.,Xiong Y.,&Du K..(2020).Source apportionment of airborne particulate matters over the Athabasca oil sands region: Inter-comparison between PMF modeling and ground-based remote sensing.ATMOSPHERIC ENVIRONMENT,221.
MLA	Xing Z.,et al."Source apportionment of airborne particulate matters over the Athabasca oil sands region: Inter-comparison between PMF modeling and ground-based remote sensing".ATMOSPHERIC ENVIRONMENT 221(2020).