RESUMO
Accurate identification and rapid analysis of PM2.5 sources and formation mechanisms are essential to mitigate PM2.5 pollution. However, studies were limited in developing a method to apportion sources to the total PM2.5 mass in real-time. In this study, we developed a real-time source apportionment method based on chemical mass balance (CMB) modeling and a mass-closure PM2.5 composition online monitoring system in Shenzhen, China. Results showed that secondary sulfate, secondary organic aerosol (SOA), vehicle emissions and secondary nitrate were the four major PM2.5 sources during autumn 2019 in Shenzhen, together contributed 76 % of PM2.5 mass. The novel method was verified by comparing with other source apportionment methods, including offline filter analysis, aerosol mass spectrometry, and carbon isotopic analysis. The comparison of these methods showed that the new real-time method obtained results generally consistent with the others, and the differences were interpretable and implicative. SOA and vehicle emissions were the major PM2.5 and OA contributors by all methods. Further investigation on the OA sources indicated that vehicle emissions were not only the main source of primary organic aerosol (POA), but also the main contributor to SOA by rapid aging of the exhaust in the atmosphere. Our results demonstrated the great potential of the new real-time source apportionment method for aerosol pollution control and deep understandings on emission sources.