Seasonal variations in the mass characteristics and optical properties of carbonaceous constituents of PM2.5 in six cities of North China

Carbonaceous constituents have various adverse impacts on human health, visibility, and climate change. Although comprehensive studies on the characteristics of carbonaceous constituents have been conducted recently, systematic studies covering both the mass characteristics and light-absorption properties of carbonaceous constituents on a regional scale in China are quite limited. In this study, current seasonal measurements of organic carbon (OC) and elemental carbon (EC) in PM2.5 were investigated during autumn and winter (1-30 October 2017 and December 18, 2017 to January 17, 2018) in six selected cities located at the eastern foot of the Taihang Mountains: Beijing, Baoding, Shijiazhuang, Handan, Xinxiang, and Zhengzhou. Seasonal variations were similar when Beijing was excluded. The lowest concentrations of OC (18.33 +/- 9.39 mg/m(3)) and EC (7.66 +/- 5.64 mg/m(3)) were observed in Xinxiang (autumn) and Beijing (winter), respectively, while the highest concentrations of OC (38.43 +/- 62.10 mg/m(3)) and EC (12.24 +/- 24.67 mg/m(3)) occurred in Baoding during winter mainly due to elevated fuel combustion for space heating. The results of the potential source contribution function (PSCF) analysis suggested that border zones between several provinces in North China should be highlighted in order to strengthen pollution control. Moreover, by separating the optical properties of brown carbon from those of black carbon, we were able to estimate the contributions of brown carbon to the PM2.5 total light-absorption coefficient. The results show that the brown carbon absorption coefficient (at 405 nm) in winter at six sites accounted for 21.2%, 33.3%, 34.7%, 39.1%, 48.6%, and 23.3% of the PM2.5 light absorption, which are values that are comparable to the contribution of black carbon in Xinxiang. These results provide a more comprehensive understanding of carbonaceous constituents on a regional scale. (C) 2020 Elsevier Ltd. All rights reserved.