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An advection-diffusion equation-based approach to discern the meteorological factor effects on particle concentrations

  • Jiahao Ren
  • , Yizhen Chen
  • , Xi Zhang
  • , Yuxi Zhao
  • , Shuang Zhu
  • , Guanhua Zhou*
  • , Bowen Li
  • , Zhichun Cha
  • , Kai Zhang
  • *Corresponding author for this work
  • Chinese Research Academy of Environmental Sciences
  • The University of Kitakyushu

Research output: Contribution to journalArticlepeer-review

Abstract

The evaluation of the impact of meteorological conditions and anthropogenic emissions to PM2.5 concentrations is a subject of ongoing debetate, which holds significant importance in guiding the formulation and implementation of emission reduction policies. A new method, based on advection dispersion theory, has been developed to assess the impact of emission control measures and meteorological effects on the reduction of pollutant concentrations. This method involves classifying meteorological factors and utilizing the emission source intensity, which is characterized under various meteorological factors, to quantify the effects of meteorological factors and emission reduction on pollutant concentrations. Wind speed (WS), wind direction (WD), atmospheric stability (determined by cloud volume, solar radiation levels, surface wind speed) and mixed height are chosen as the key meteorological factors. Baoding City, situated within the Beijing-Tianjin-Hebei (BTH) region, is taken as an example in this study and is characterized by severe particle pollution. Due to the implementation of air pollution control measures from 2016 to 2020, the particulate pollution in this city has significantly reduced. The result of our method showed that despite the unfavorable conditions for pollutant dispersion during 2018 and 2021, the aggressive policies were estimated to have contributed to reductions in PM2.5 concentration. Specifically, there were reductions of 35.7, 19.6, 28.6, and 107.9 μg/m3 in spring, summer, autumn, and winter, respectively, from 2015 to 2018. Additionally, reductions of 8.2, 14.9, 30.0, and 50.7 μg/m3 were observed in the corresponding seasons from 2018 to 2021.

Original languageEnglish
Article number107213
JournalAtmospheric Research
Volume299
DOIs
StatePublished - 1 Apr 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Advection-diffusion equation
  • Emission reduction
  • Emission source intensity
  • Meteorological confounding
  • PM

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