Insights into the chemical characterization and sources of PM2.5 in Beijing at a 1-h time resolution

As the widespread application of online instruments penetrates the environmental fields, it is interesting to investigate the sources of fine particulate matter (PM2.5) based on the data monitored by online instruments. In this study, online analyzers with 1-h time resolution were employed to observe PM2.5 composition data, including carbon components, inorganic ions, heavy metals and gas pollutants, during a summer in Beijing. Chemical characteristics, temporal patterns and sources of PM2.5 are discussed. On the basis of hourly data, the mean concentration value of PM2.5 was 62.16±39.37μgm−3 (ranging from 6.69 to 183.67μgm−3). The average concentrations of NO3−, SO42−, NH4+, OC and EC, the major chemical species, were 15.18±13.12, 14.80±14.53, 8.90±9.51, 9.32±4.16 and 3.08±1.43μgm−3, respectively. The concentration of PM2.5 varied during the online-sampling period, initially increasing and then subsequently decreasing. Three factor analysis models, including principal component analysis (PCA), positive matrix factorization (PMF) and Multilinear Engine 2 (ME2), were applied to apportion the PM2.5 sources. Source apportionment results obtained by the three different models were in agreement. Four sources were identified in Beijing during the sampling campaign, including secondary sources (38–39%), crustal dust (17–22%), vehicle exhaust (25–28%) and coal combustion (15–16%). Similar source profiles and contributions of PM2.5 were derived from ME2 and PMF, indicating the results of the two models are reasonable. The finding provides information that could be exploited for regular air control strategies. [Display omitted] •PM2.5 was measured by online instruments with 1-h time resolution in Beijing.•Chemical characteristic and temporal patterns of PM2.5 and components were discussed.•PCA, PMF and ME2, were applied to apportion the sources based on the online dataset.