Humidity and PM2.5 composition determine atmospheric light extinction in the arid region of northwest China


Suwubinuer Rekefu , Xiaoxiao Zhang , Xiang Ding , Dilinuer Talifu , Xinming Wang , Abulikemu Abulizi , Mailikezhati Maihemuti

DOI:10.1016/j.jes.2020.07.007

Received February 12, 2020,Revised , Accepted July 06, 2020, Available online August 14, 2020

Volume 100,2021,Pages 279-286

Atmospheric visibility can directly reflect the air quality. In this study, we measured water-soluble ions (WSIs), organic and element carbon (OC and EC) in PM2.5 from September 2017 to August 2018 in Urumqi, NW China. The results show that SO42−, NO3 and NH4+ were the major WSIs, together accounting for 7.32%–84.12% of PM2.5 mass. Total carbon (TC=OC+EC) accounted for 12.12% of PM2.5 mass on average. And OC/EC > 2 indicated the formation of secondary organic carbon (SOC). The levels of SO42−, NO3 and NH4+ in low visibility days were much higher than those in high visibility days. Relative humidity (RH) played a key role in affecting visibility. The extinction coefficient (bext) that estimated via Koschmieder formula with visibility was the highest in winter (1441.05 ± 739.95 Mm−1), and the lowest in summer (128.58 ± 58.00 Mm−1). The bext that estimated via IMPROVE formula with PM2.5 chemical component was mainly contributed by (NH4)2SO4 and NH4NO3. The bext values calculated by both approaches presented a good correlation with each other (R2 = 0.87). Multiple linear regression (MLR) method was further employed to reconstruct the empirical regression model of visibility as a function of PM2.5 chemical components, NO2 and RH. The results of source apportionment by Positive Matrix Factorization (PMF) model showed that residential coal combustion and vehicle emissions were the major sources of bext.

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