Refined source apportionment of residential and industrial fuel combustion in the Beijing based on real-world source
Min Cui1, Yingjun Chen2, Caiqing Yan3
1College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225009, PR China.
Abstract:
Residential and industrial emissions are considered as dominant contributors to ambient fine particulate matter (PM2.5) in China. However, the contributions of residential and industrial fuel combustion are difficult to distinguish because specific source indicators are lacking. In this study, real-world source testing was performed on residential coal, biomass and industrial combustion, industrial processes, and diesel and gasoline vehicle source emissions in the Beijing-Tianjin-Hebei region, China. PM2.5 emission factors and chemical profiles, including 97 compositions (e.g., carbonaceous matter, water-soluble ions, elements, EPA priority polycyclic aromatic hydrocarbons (EPAHs), methyl PAHs (MPAHs), and n-alkanes) were obtained for the aforementioned sources. The results showed high OC1, OC2, fluoranthene, methyl fluoranthene, and retene in emissions from residential coal combustion, high OC3, sulfate, Ca, and iron abundance in emissions from industrial combustion, and high Pb and Zn loadings in emissions from industrial processes. Furthermore, specific diagnostic ratios were determined to distinguish between residential and industrial fuel combustion. For example, the ratios of MPAHs/EPAHs (>1) and Mfluo/Fluo (>5) can be used as fingerprinting ratios to distinguish residential coal combustion from other sources. Finally, 1-h resolution refined source apportionments of PM2.5 were conducted in Beijing during two haze events (EP1 and EP2) with a chemical mass balance (CMB) model based on the localized real-world source profiles established in this study. Source apportionment results of CMB showed that the contributions of industrial and residential fuel combustion were 19.4% and 30.8% in EP1 and 26.8% and 18.1% in EP2, respectively, which were comparable to the results of the positive matrix factorization model (R2 = 0.82). This study provides valuable information for the successful and accurate determination of the contributions of residential and industrial fuel combustion to ambient PM2.5.
