Characterization and Source Apportionment of PM2.5 Based on the Online Observation in Tianjin

Abstract

To study the characterization and source apportionment of PM2.5 in Tianjin, based on high-resolution online monitoring data from 2017 to 2019, the concentrations and its chemical compositions and sources of PM2.5 were analyzed. The results showed that the average concentration of PM2.5 was 61 μg ·m-3. The primary chemical compositions of PM2.5 were nitrate, organic carbon (OC), ammonium, sulfate, elemental carbon (EC), and Cl- and their corresponding mass percentages to PM2.5 were 17.7%, 12.6%, 11.5%, 10.7%, 3.4%, and 3.1%, respectively. From 2017 to 2019, the concentrations of PM2.5 and its main chemical compositions exhibited a decreasing trend; the mass ratios of NO3- and NH4+ to PM2.5 exhibited an increasing trend, while the mass ratios of SO42-, OC, and EC to PM2.5 exhibited a decreasing trend; further, the mass ratio of Cl- exhibited a slight increasing trend. The concentrations of K+, Ca2+, and Na+ and their mass percentages to PM2.5 increased. The concentrations of PM2.5 and its primary components were relatively higher during heating season, and relatively lower during non-heating season. High values of SOR and NOR indicated that the secondary transformation of nitrate and sulfate played an important role during summer and autumn, which resulted in higher mass percentages of secondary inorganic ions (NO3-, SO42-, and NH4+) to PM2.5 during summer and autumn. When the PM2.5 concentrations were at excellent levels, the mass ratios of the secondary inorganic ions to PM2.5 were relatively lower, the mass ratios of OC, Ca2+, and Na+ to PM2.5 were relatively higher, and secondary organic carbon (SOC) was high. When the PM2.5 concentrations were between light pollution to heavy pollution levels, as the pollution levels increased, the mass percentages of secondary inorganic ions, OC, EC, and Cl-, and other components (K+, Ca2+, and Na+) showed a significant increasing trend, relatively stable level, slightly increasing trend, and decreasing trend, respectively. When PM2.5 concentrations were between moderate pollution to heavy pollution levels, the influence of vehicle emission increased significantly. The source apportionment of PM2.5 were analyzed using the positive matrix factorization model. The major sources of PM2.5 in Tianjin were secondary source, vehicle exhaust, industrial and coal combustion emissions, and crustal dust. From 2017 to 2019, the contribution of vehicle exhaust increased, and the contribution of secondary source and crustal dust showed a slight increasing trend, while the contribution of industrial and coal combustion emissions decreased. For Tianjin, vehicle exhaust and industrial and coal combustion emissions were the primary sources of PM2.5. The adjustment of industrial and energy structure and management and control of vehicle exhaust are the main directions for air pollution control in Tianjin.