Characteristics and oxidative potential of atmospheric PM_(2.5) in Beijing: Source apportionment and seasonal variation

摘要

PM2.5 (particulate matter with the aerodynamic diameter D-p 2.5 mu m) was hypothesized to generate reactive oxygen species (ROS) and induce oxidative stress associated with inflammation and cardiovascular diseases. In the current study, PM2.5 concentrations, water-soluble ions and elements, carbonaceous components and ROS activity characterized by the dithiothreitol (DTT) assay were determined for the PM2.5 samples collected in Beijing, China, over a whole year. Source apportionments of PM2.5 and DTT activity were also performed. The mean +/- standard deviation of PM2.5, DTTm (mass-normalized DTT activity) and DTTv (volume-normalized DTT activity) were 113.8 +/- 62.7 mu g.m(-3), 0.13 +/- 0.10 nmol.mu g(-1).min(-1) and 12.26 +/- 6.82 nmol.m(-3).min(-1), respectively. The seasonal averages of DTTm and DTTv exhibited peak values during the local summer. Organic carbon (OC), NO3-, SO42-, NH4+ and elemental carbon (EC) were the dominant components in the constituents tested. Higher concentrations of carbonaceous components occurred in autumn and winter compared with spring and summer. Based on the positive matrix factorization model (PMF), the simulation results of source apportionment for PM2.5 in Beijing, obtained using the annual data, identified the main categories as follows: dust, coal combustion, secondary sulfate and industrial emissions, vehicle emissions and secondary nitrates. Most detected constituents exhibited significantly positive correlations with DTTv (p 0.01). The results corresponding to multiple linear regression (MLR) between DTTv activity and source contribution to PM2.5 manifested the sensitivity sequence of DTTv activity for the resolved sources as vehicle emissions secondary sulfate and industrial emissions coal combustion dust.Capsule: Based on a descending sequence of relative contribution, the diagnostic sources of DTTv activity in PM2.5 from Beijing included primarily vehicle emissions, secondary sulfates and industrial emissions, coal combustion, and dust. (c) 2018 Elsevier B.V. All rights reserved.