摘要:

To clarify the aerosol optical properties under different pollution levels and their impacting factors, hourly organic carbon (OC), elemental carbon (EC), and water-soluble ion (WSI) concentrations in PM2.5 were observed by using monitoring for aerosols and gases (MARGA) and a semicontinuous OC/EC analyzer (Model RT-4) in Wuhan from 9 to 26 January 2018. The aerosol extinction coefficient (bext) was reconstructed using the original Interagency Monitoring of Protected Visual Environment (IMPROVE) formula with a modification to include sea salt aerosols. A good correlation was obtained between the reconstructed bext and measured bext converted from visibility. bext presented a unimodal distribution on polluted days (PM2.5 mass concentrations > 75 μg•m-3), peaking at 19:00. bext on clean days (PM2.5 mass concentrations < 75 μg•m-3) did not change much during the day, while on polluted days, it increased rapidly starting at 12:00 due to the decrease of wind speed and increase of relative humidity (RH). PM2.5 mass concentrations, the aerosol scattering coefficient (bscat), and the aerosol extinction coefficient increased with pollution levels. The value of bext was 854.72 Mm-1 on bad days, which was 4.86, 3.1, 2.29, and 1.28 times of that obtained on excellent, good, acceptable, and poor days, respectively. When RH < 95%, bext exhibited an increasing trend with RH under all pollution levels, and the higher the pollution level, the bigger the growth rate was. However, when RH > 95%, bext on acceptable, poor and bad days decreased, while bext on excellent and good days still increased. The overall bext inWuhan in January was mainly contributed by NH4NO3 (25.2%) and organic matter (20.1%). The contributions of NH4NO3 and (NH4)2SO4 to bext increased significantly with pollution levels. On bad days, NH4NO3 and (NH4)2SO4 contributed the most to bext, accounting for 38.2% and 27.0%, respectively. © 2019 by the authors.

附注:

Export Date: 20 August 2020通讯地址: Wang, H.; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and TechnologyChina; 电子邮件: hongleiwang@nuist.edu.cn基金资助详情: State Key Joint Laboratory of Environmental Simulation and Pollution Control, 19K03ESPCP基金资助详情: Natural Science Foundation of Jiangsu Province, BK20180801基金资助详情: National Natural Science Foundation of China, NSFC, 41905026, 41805096, 91644224基金资助详情: 18KJB170011基金资助文本 1: Funding: This study was supported by the National Natural Science Foundation of China (91644224, 41805096 and 41905026), the special fund of State Key Joint Laboratory of Environment Simulation and Pollution Control (19K03ESPCP), the Natural Science Foundation of Jiangsu Province (BK20180801) and the Natural Science Research Project for Universities of Jiangsu Province, China (18KJB170011).