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Spatial/temporal variations and source apportionment of VOCs monitored at community scale in an urban area
Chang Ho Yu1, Xianlei Zhu2, Zhi-hua Fan1
1Division of Exposure Science, Environmental and Occupational Health Sciences Institute, Rutgers University, Piscataway, New Jersey, United States of America.
Abstract:
This study aimed to characterize spatial/temporal variations of ambient volatile organic compounds (VOCs) using a community-scale monitoring approach and identify the main sources of concern in Paterson, NJ, an urban area with mixed sources of VOCs. VOC samples were simultaneously collected from three local source-dominated (i.e., commercial, industrial, and mobile) sites in Paterson and one background site in Chester, NJ (located ∼58 km southwest of Paterson). Samples were collected using the EPA TO-15 method from midnight to midnight, one in every sixth day over one year. Among the 60 analyzed VOCs, ten VOCs (acetylene, benzene, dichloromethane, ethylbenzene, methyl ethyl ketone, styrene, toluene, m,p-xylene, o-xylene, and p-dichlorobenzene) were selected to examine their spatial/temporal variations. All of the 10 VOCs in Paterson were significantly higher than the background site (p<0.01). Ethylbenzene, m,p-xylene, o-xylene, and p-dichlorobenzene measured at the commercial site were significantly higher than the industrial/mobile sites (p<0.01). Seven VOCs (acetylene, benzene, dichloromethane, methyl ethyl ketone, styrene, toluene, and p-dichlorobenzene) were significantly different by season (p<0.05), that is, higher in cold seasons than in warm seasons. In addition, dichloromethane, methyl ethyl ketone, and toluene were significantly higher on weekdays than weekend days (p<0.05). These results are consistent with literature data, indicating the impact of anthropogenic VOC sources on air pollution in Paterson. Positive Matrix Factorization (PMF) analysis was applied for 24-hour integrated VOC measurements in Paterson over one year and identified six contributing factors, including motor vehicle exhausts (20%), solvents uses (19%), industrial emissions (16%), mobile+stationery sources (12%), small shop emissions (11%), and others (22%). Additional locational analysis confirmed the identified sources were well matched with point sources located upwind in Paterson. The study demonstrated the community-scale monitoring approach can capture spatial variation of VOCs in an urban community with mixed VOC sources. It also provided robust data to identify major sources of concern in the community.
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