The dynamic multi-box algorithm of atmospheric environmental capacity

Sci Total Environ. 2022 Feb 1;806(Pt 4):150951. doi: 10.1016/j.scitotenv.2021.150951. Epub 2021 Oct 14.

Abstract

It is very important for air pollution prevention and control to accurately quantify atmospheric environment capacity (AEC) in the planetary boundary layer (PBL). This study developed a high temporal-resolution dynamic multi-box algorithm to estimate PM2.5 AEC with a PBL ceilometer and Doppler wind profile lidar in Beijing City. Compared with the traditional A-value method, two primary improvements are introducing the time coefficient and vertical multi-box assumption into the original box model. The algorithm can accurately calculate the PM2.5 AEC under different circulation patterns and predict the short-time dynamic change of AEC. The results show that the time coefficient effectively reduced the estimation errors when the initial PM2.5 concentration, horizontal wind speed and PBL heights change greatly with time, such situation is consistent with most circulation patterns. And the improvement of multi-box model is much more remarkable when the PM2.5 concentration and horizontal wind change greatly in the vertical direction, such as A, NE and W type circulations. The ideal AEC under polluted circulation patterns won't increase infinitely with wind speed and PBL height, generally less than 30 t/h. The horizontal advection has a much greater effect on expanding the capacity of PM2.5 than the vertical diffusion under clean circulation patterns, and the maximum value of ideal AEC can reach 50 t/h. The positive residual AEC under clean circulations indicates surplus capacity for PM2.5 because of vigorous turbulences, while weak diffusion and ventilation conditions under polluted circulations lead to negative residual AEC and insufficient capacity of atmosphere.

Keywords: Atmospheric environmental capacity; Dynamic multi-box model; Regional pollution control; Synoptic circulation types.

MeSH terms

  • Air Pollutants* / analysis
  • Air Pollution* / analysis
  • Algorithms
  • China
  • Environmental Monitoring
  • Particulate Matter / analysis
  • Seasons

Substances

  • Air Pollutants
  • Particulate Matter