Abstract
Abstract. A framework was developed to quantitatively assess the contribution of meteorology variations to the trend of fine particular matter (PM2.5) concentrations and to separate the impacts of meteorology from the control measures in the trend, based upon the Environmental Meteorology Index (EMI). The model-based EMI realistically reflects the role of meteorology in the trend of PM2.5 and is explicitly attributed to three major factors: deposition, vertical accumulation and horizontal transports. Based on the 2013–2019 PM2.5 observation data and re-analysis meteorological data in China, the contributions of meteorology and control measures in nine regions of China were assessed separately by the EMI-based framework. Monitoring network observations show that the PM2.5 concentrations have declined by about 50 % on the national average and by about 35 % to 53 % for various regions. It is found that the nationwide emission control measures were the dominant factor in the declining trend of China PM2.5 concentrations, contributing about 47 % of the PM2.5 decrease from 2013 to 2019 on the national average and 32 % to 52 % for various regions. The meteorology has a variable and sometimes critical contribution to the year-by-year variations of PM2.5 concentrations, 5 % on the annual average and 10 %–20 % for the fall–winter heavy pollution seasons.
Highlights
Recent observation data from the Ministry of Ecology and Environment of China (MEE) have shown a steady improvement of air quality across the country, especially in particular matter (PM) concentrations (Hou et al, 2019)
This paper presents a methodology to assess the individual impacts of meteorology and emission changes, based on a modelderived index EMI, i.e., Environmental Meteorology Index, and observational data, providing a comprehensive analysis of the air quality trends in various regions of China, with mechanistic and quantitative attributions of various factors
The EMI2.5 can realistically reflect the contribution of meteorological factors to the PM2.5 variations in the time series with impact mechanisms and can be used as an index to judge whether the meteorological conditions are favored or not for the PM2.5 pollutions in a region or time period
Summary
Recent observation data from the Ministry of Ecology and Environment of China (MEE) have shown a steady improvement of air quality across the country, especially in particular matter (PM) concentrations (Hou et al, 2019). In the Beijing–Tianjin–Hebei (BTH) region, a correlation analysis and principal component regression method (Zhou et al, 2014) was used to identify the major meteorological factors that influenced the API (Air Pollution Index) time series in China from 2001 to 2010, indicating that air pressure, air temperature, precipitation and relative humidity were closely related to air quality with a series of regression formulas. This paper presents a methodology to assess the individual impacts of meteorology and emission changes, based on a modelderived index EMI, i.e., Environmental Meteorology Index, and observational data, providing a comprehensive analysis of the air quality trends in various regions of China, with mechanistic and quantitative attributions of various factors. Research has shown that after the change in reporting standard, the PM2.5 concentration in most cities decreased, and the number of good days to meet the standard increased (Zhang and Rao, 2019)
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