E3S Web of Conferences (Jan 2021)

Analysis on the Characteristics and Cause of a Compound Pollution Process in Changsha in 2017

  • Yan Hu,
  • Hongwu Liu,
  • Huanqian Liu,
  • Zhonghai Yin

DOI
https://doi.org/10.1051/e3sconf/202125901001
Journal volume & issue
Vol. 259
p. 01001

Abstract

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Using the conventional meteorological observations, the air Air quality monitoring data, the L-band wind-profiling radar data, the NECP reanalysis data, and the simulation results of the HYSPLIT4 model, the compound pollution process from November 2 to 5, 2017 in Changsha is comprehensively analyzed in this study, including the sources and transport paths of pollutions, the Meteorological conditions and atmospheric boundary layer characteristics. The results showed that the process of air pollution in Changsha is a compound pollution process with high concentration of O3 and fine PM2.5 coexisting. It reached serious pollution from 08:00 to 11 : 00 on 4, PM2.5 was 269.3 ug·m−3 at 09:00 on 4 November. The characteristics of the two phases of this pollution process were clearly different. The first phase was mainly result of accumulation of local pollutants, and the second one was mainly result of outside resource. The maximum wind were light breezein on this pollution process, gentle breeze mainly occurred in the second stage of pollution, and the maximum wind velocity was 4.4m/s. It appearred multi-layer inversion usually, temperature stratification was stabled, and the inversion layer thickness reached the maximum value 909m at 20:00 on 3 November. The boundary layer convergenced and ascented movement, horizontal transport, vertical wind field distribution and atmospheric layer provided the favorable conditions for the air pollution process. The results showed that short-range transport of pollutants is the maily reason based on the HYSPLIT4 model, the northeast airflow was dominant at 100-1000m height. The vary of wind profile data and CO and SO2 emission ratio showed that the different pollution characteristics of two phases, the maximum ratio was more than 100. It has an important indicator for weather forecast in Changsha.