Abstract

Fine particulate matter (PM2.5) poses a risk to human health. In January 2017, the PM2.5 pollution in China was severe, and the average PM2.5 concentration had increased by 14.7% compared to that in January 2016. Meteorological conditions greatly influence PM2.5 pollution. The relationship between PM2.5 and meteorological factors was assessed using monitoring data and the Community Multiscale Air Quality modeling system (CMAQ) was used to quantitatively evaluate the impacts of variations of meteorological conditions on PM2.5 pollution. The results indicate that variations of meteorological conditions between January 2017 and January 2016 caused an increase of 13.6% in the national mean concentration of PM2.5. Unlike the Yangtze River Delta (YRD), where meteorological conditions were favorable, unfavorable meteorological conditions (such as low wind speed, high humidity, low boundary layer height and low rainfall) contributed to PM2.5 concentration worsening by 29.7%, 42.6% and 7.9% in the Beijing-Tianjin-Hebei (JJJ) region, the Pearl River Delta (PRD) region and the Chengdu-Chongqing (CYB) region, respectively. Given the significant influence of local meteorology on PM2.5 concentration, more emphasis should be placed on employing meteorological means to improve local air quality.

Highlights

  • China’s rapid economic development over the past two decades has caused an increase in PM2.5 concentrations [1,2]

  • The PM2.5 pollution in January 2017 was severe and the average concentration of PM2.5 nationwide was 78 μg m−3, which represents an increase of 14.7% over the level in January 2016

  • Compared with January 2016, the national mean PM2.5 concentration increased by 14.7%

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Summary

Introduction

China’s rapid economic development over the past two decades has caused an increase in PM2.5 concentrations [1,2]. The major factors affecting ambient PM2.5 concentration are emissions of air pollutants and meteorological conditions [9,10]. Weather Research and Forecasting (WRF) Model and Community Multiscale Air Quality (CMAQ) were widely adopted to simulate variations of PM2.5 concentration and regional pollution transport [18]. Compared with January 2016, the mean PM2.5 increased by 43.8% and 62.5% in the JJJ region and the PRD regions (http://datacenter.mep.gov.cn), respectively This abnormal phenomenon has not yet been explained and we report here on the influence of meteorology on the PM2.5 concentration in these regions. January 2017 was selected as the target investigation period and characteristics of PM2.5 pollution and their relationships with meteorological conditions were analyzed in different regions. The impact of meteorological conditions on PM2.5 pollution was quantitatively analyzed both nationwide and in specific regions where high PM2.5 concentrations and precursor emissions were of this study help us to deepen our understanding of the impact of meteorological conditions on PM2.5 pollution and provide insights into possible air pollution control strategies

Study Area
Data and
Meteorological Data
Ambient Air Quality Data
Sampling Program
Emission Inventory
Modeling System
Results and Discussion
Monitoring
Conclusions
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