Air quality in China: Trends, drivers and mitigation

The size of the People’s Republic of China’s (henceforth ‘China’) economy has increased by 75-fold since economic reforms began in the late 1970s. Environmental policies were initially lax, especially during the 1980s and 1990s, which led to a substantial deterioration in China’s air quality. Megacity regions frequently experience episodes of smog, particularly during stagnant weather conditions. During these episodes, high concentrations of aerosols have been recorded. High concentrations of ambient fine aerosol (with an aerodynamic diameter of <2.5 µgm−3), known as PM2.5, has been identified as one of the most significant environmental risk factors that causes premature deaths by epidemiological research. Over 1 million deaths each year have been attributed to high ambient PM2.5 exposure in China.

Since the 2000s, air pollution control measures in China have become increasingly stringent. This has resulted in improvements in air quality, which have been observed by satellites, estimated in emission inventories, and since 2011 have been observed by a new national monitoring network consisting of over 1600 ground-based stations. The network records hourly concentrations of PM2.5, as well as nitrogen dioxide (NO2), ozone (O3) and sulphur dioxide (SO2). My analysis of the trends in this network found that during 2015-2017, the national median PM2.5 trend was −3.4 µgm−3 yr−1, SO2 −1.9 µgm−3 yr−1, NO2 had no overall trend, and the trend in ‘maximum daily 8-hour mean’ O3 was 4.7 µgm−3 yr−1. Negative PM2.5 and SO2 trends were significant at 53% and 59% of stations respectively. Positive O3 trends were significant at 50% of stations. There were negative trends in NO2 at 22% of stations, and positive at 26%.

Atmospheric air pollutant concentrations are determined not only by emissions, but by meteorological conditions, which influence their dispersion, chemical reaction rates and sinks. Therefore, inter-annual variability in meteorological conditions can be a confounding factor when evaluating the impact of China’s recent air quality control policies using observed trends. To untangle the competing drivers of meteorology and emissions, I used a regional atmospheric chemistry model, the ‘Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), to simulate air quality over China during 2015-2017. I simulated a scenario where emission changes were investigated, and compared this to a counterfactual where emissions were fixed. The model was able to reproduce the magnitude of observed PM2.5 trends in the variable emissions scenario (−3.5 µgm−3 yr−1), but not in the fixed emissions scenario −0.6 µgm−3 yr−1, demonstrating that changes were primarily driven by the emissions changes. Using an exposure-response function from recent a disease burden study, we estimated that during this period PM2.5-associated deaths reduced by 150000 yr-1. The observed positive trend in ozone was not reproduced by either scenario, suggesting that emissions change estimates were inaccurate or important processes are missing from WRF-Chem.

The COVID-19 outbreak and associated control measures gave a unique opportunity to analyse the effects of a sudden and irregular sectoral activity reduction, where emissions rates dropped in the industry and transport sectors, but were largely unchanged in electricity generation and residential sectors. I used measurement data from China’s monitoring network to estimate the impact on air quality of the ‘lockdown’ measures. I constructed an estimate from 2020 air quality based on 2015-2019 trends and seasonal cycles, along with the air quality impact of the Lunar New Year holiday. By comparing this with observed concentrations, I found that during the first ~2 months following the lockdown in Wuhan, NO2 concentrations were 27.0% lower on average across China. PM2.5 and PM10 concentrations were 10.5 and 21.4% lower respectively. O3 concentrations were increased during the first ~2 weeks of lockdown, but overall remained around expected concentrations during the entire period. After lockdown measures were relaxed in April, pollutant concentrations returned to expected levels.