This study demonstrates the use of positive matrix factorization (PMF) in a region with a major Petrochemical Complex, a prominent source of volatile organic compounds (VOCs), as a showcase of PMF applications. The PMF analysis fully exploited the quality and quantity of the observation data, sufficed by a cluster of 9 monitoring sites within a 20 km radius of the petro-complex. Each site provided continuous data of 54 speciated VOCs and meteorological variables. Wind characteristics were highly seasonal and played a decisive role in the source-receptor relationship, hence the dataset was divided into three sub-sets in accordance with the prevailing wind flows. A full year of real-time data were analyzed by PMF to resolve into various distinct source types including petrochemical, urban, evaporative, long-range air parcels, etc., with some sites receiving more petro-influence than others. To minimize subjectivity in the assignment of the PMF source factors, as commonly seen in some PMF works, this study attempted to solidify PMF results by supporting with two tools of spatially/temporally resolved air-quality model simulations and observation data. By exploiting the two supporting tools, the dynamic process of individual sources to a receptor were rationalized. Percent contributions from these sources to the receptor sites were calculated by summing over the occurrence of different source types. Interestingly, although the Petro-complex is the single largest local VOC source in the 20 km radius study domain, all monitoring sites in the region received far less influence from the Petro-complex than from other emission types within or outside the region, which together add up to more than 70% of the total VOC abundance.
Keywords: Petrochemical complex; Photochemical assessment measurement stations (PAMS); Source-receptor.
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