[Comparison of Three Receptor Models for Source Apportionment of PM_2.5 in Shanghai: Using Hourly Resolved PM_2.5...

Continuous measurements of PM_2.5 and its chemical composition, including inorganic ions, carbon components, and inorganic elements, were conducted in the urban area of Shanghai from November 2 to 24, 2014. The chemical characteristics and sources of PM_2.5 were discussed. The average mass concentration of PM_2.5 was (64±33) μg·m^-3 (ranging from 12 to 181 μg·m^-3). Organic matter contributed the most to the PM_2.5 chemical components, accounting for about 28.1% of total PM_2.5, followed by NO₃^-, SO₄^2-, and NH₄⁺, which accounted for 17.4%, 12.4%, and 10.7%, respectively. Meanwhile, three receptor models, including positive matrix factorization (PMF), chemical mass balance (CMB), and multilinear engine 2 (ME2), were applied to apportion the PM_2.5 sources based on these online data. The results showed that eight sources were identified, including secondary nitrate, secondary sulfate, secondary organic carbon, heavy fuel oil burning, industry, mobile vehicle exhaust, dust, and power plants. The secondary sources (44.9%-64.8%), including secondary nitrate, secondary sulfate, and secondary organic carbon, were found to be the important contributors to PM_2.5. The other two main sources were mobile vehicle exhaust (16.8%-24.8%) and power plants (5.6%-14.9%), whereas other sources were slightly lower contributors. To better verify the accuracy of the PMF, CMB, and ME2 models, the profiles, temporal patterns, and concentrations of different sources obtained by the three models were discussed. Similar source profiles and contributions of secondary nitrate, secondary sulfate, secondary organic carbon, and mobile vehicle exhaust were derived from the PMF, CMB, and ME2, indicating that the results of the three models were reasonable. The ME2 and PMF models simulate better results for power plants and dust sources than CMB, whereas CMB obtained better results for industrial sources.