Source apportionment of PM2.5 at a regional background site in North China using PMF linked with radiocarbon analysis: insight into the contribution of biomass burning
- 1Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China
- 2State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
- 3Key Laboratory of Cities' Mitigation and Adaptation to Climate Change in Shanghai (CMA), College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China
- 4Yantai Oceanic Environmental Monitoring Central Station, SOA, Yantai, 264006, China
- 5Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- 6University of Chinese Academy of Sciences, Beijing, 100049, China
Abstract. Source apportionment of fine particles (PM2.5) at a background site in North China in the winter of 2014 was done using statistical analysis, radiocarbon (14C) measurement and positive matrix factorization (PMF) modeling. Results showed that the concentration of PM2.5 was 77.6 ± 59.3 µg m−3, of which sulfate (SO42−) concentration was the highest, followed by nitrate (NO3−), organic carbon (OC), elemental carbon (EC) and ammonium (NH4+). As demonstrated by backward trajectory, more than half of the air masses during the sampling period were from the Beijing–Tianjin–Hebei (BTH) region, followed by Mongolia and the Shandong Peninsula. Cluster analysis of chemical species suggested an obvious signal of biomass burning in the PM2.5 from the Shandong Peninsula, while the PM2.5 from the BTH region showed a vehicle emission pattern. This finding was further confirmed by the 14C measurement of OC and EC in two merged samples. The 14C result indicated that biogenic and biomass burning emission contributed 59 ± 4 and 52 ± 2 % to OC and EC concentrations, respectively, when air masses originated from the Shandong Peninsula, while the contributions fell to 46 ± 4 and 38 ± 1 %, respectively, when the prevailing wind changed and came from the BTH region. The minimum deviation between source apportionment results from PMF and 14C measurement was adopted as the optimal choice of the model exercises. Here, two minor overestimates with the same range (3 %) implied that the PMF result provided a reasonable source apportionment of the regional PM2.5 in this study. Based on the PMF modeling, eight sources were identified; of these, coal combustion, biomass burning and vehicle emission were the main contributors of PM2.5, accounting for 29.6, 19.3 and 15.9 %, respectively. Compared with overall source apportionment, the contributions of vehicle emission, mineral dust, coal combustion and biomass burning increased when air masses came from the BTH region, Mongolia and the Shandong Peninsula, respectively. Since coal combustion and vehicle emission have been considered as the leading emission sources to be controlled for improving air quality, biomass burning was highlighted in the present study.