The impacts of COVID-19, meteorology, and emission control policies on PM_2.5 drops in Northeast Asia

Northeast Asia, particularly China and South Korea, experiences frequent high PM_2.5 pollution events during winter and early spring. Since January 2020, the COVID-19 pandemic led to significant reductions in anthropogenic emissions due to lockdowns and restrictions on public activity. Previous studies have observed decreases in air pollutant concentrations, including PM_2.5, during this period. However, disentangling the effects of reduced emissions from meteorological variability and pre-existing emission control policies remains a challenge. This study addresses this challenge by employing air quality modeling and observational data to quantitatively separate the contributions of these factors to changes in PM_2.5 concentration in China and South Korea between 2016 and 2020, a period encompassing both the pre-COVID-19 period and the pandemic itself. The study's importance lies in providing a quantitative understanding of the relative influences of these factors, offering valuable insights for policymakers seeking to improve air quality in the region.

Existing literature documents the frequent occurrences of high PM_2.5 pollution in Northeast Asia, particularly in China and South Korea, during winter and early spring. Studies have examined the role of meteorological conditions, such as wind speed and relative humidity, in influencing air pollution levels. The impact of emission control policies implemented in the region to mitigate air pollution has also been investigated. Several studies reported reductions in air pollutant concentrations following the COVID-19 outbreak, but often lacked the ability to quantitatively isolate the specific contributions of reduced emissions, meteorological conditions, and pre-existing policies. This research bridges the gap by providing a quantitative assessment of these factors using a comprehensive modeling approach.

The study employed a combined approach using observational data and air quality modeling. Observational PM_2.5 concentration data were obtained from the China National Environmental Monitoring Center (CNEMC) and Air Korea for the period of 2016-2020. Meteorological data were sourced from the Meteorological Assimilation Data Ingest System (MADIS) stations in China and South Korea. The Community Multiscale Air Quality (CMAQ) model (ver. 4.7.1) was used to simulate PM_2.5 concentrations in Northeast Asia, with meteorological input data generated by the Weather Research Forecast (WRF) model (ver. 3.9.1). The CREATE 2015 Emission Inventory, processed through the SMOKE modeling system, provided anthropogenic emission data. Biogenic emissions were estimated using the MEGAN model. The study divided the analysis into a pre-COVID-19 period (December 2016-March 2019) and a COVID-19 period (December 2019-March 2020), further subdividing the COVID-19 period into a first half (December 2019-January 2020) and a second half (February-March 2020) to capture the time-dependent impact of the pandemic's control measures. A key aspect of the methodology was the use of fixed anthropogenic emissions in the CMAQ model for both the pre-COVID-19 and COVID-19 periods to isolate the impact of meteorological conditions. The difference between simulated and observed PM_2.5 concentrations was then attributed to the combined effect of emission control policies and COVID-19-induced emission reductions. A further analysis separated these two effects by comparing pre-COVID-19 trends in simulated and observed PM_2.5 concentrations. The study employed a regression analysis to quantify the impacts of meteorology, emission control policies, and COVID-19 on PM_2.5 concentration changes in different regions of Northeast Asia, including Northern, Central and Southern China, and the Seoul Metropolitan Area (SMA) in South Korea.

The study found significant reductions in PM_2.5 concentrations in both China and South Korea during the COVID-19 period compared to the pre-COVID-19 period. Specifically, PM_2.5 concentrations decreased by -16.8 µg/m³ in China and -9.9 µg/m³ in South Korea in February and March 2020. Air quality modeling allowed the researchers to isolate the impact of different factors. The influence of anthropogenic emission reductions due to COVID-19 was estimated at approximately -16% in China and -21% in South Korea. Meteorological conditions contributed to a decrease in PM_2.5 concentration in the second half (-7% in China, -5% in South Korea), but increased concentration in the first half (2% in China, 5% in South Korea). Emission control policies independently contributed to reductions in PM_2.5 concentrations in both halves of the COVID-19 period. In China, the impacts were -10.5 µg/m³ (-15%) and -4.2 µg/m³ (-8%) in the first and second halves, respectively. In South Korea, reductions were -2.9 µg/m³ (-9%) and -1.3 µg/m³ (-4%). Notably, the impact of COVID-19-induced anthropogenic emission reductions was significantly larger than the impact of meteorological changes or pre-existing emission control policies during February-March 2020. The study further revealed regional variations in the impacts of different factors, with Northern China showing a more pronounced response to COVID-19-related emission reductions compared to Central and Southern China.

The findings highlight the significant role of reduced anthropogenic emissions due to COVID-19 lockdowns in improving air quality in Northeast Asia, particularly during the second half of the COVID-19 period. The quantitative separation of the impacts of various factors offers valuable information for policy development. The substantial contribution of COVID-19-induced emission reductions underscores the need for sustained efforts to decrease emissions in the long term. While meteorological conditions and existing emission control policies play a role, the findings show that larger emission reductions are necessary to achieve substantial and consistent improvement in air quality in the region. The study's results emphasize the potential benefits of comprehensive emission control measures and regional collaboration to address air pollution in Northeast Asia.

This study demonstrated the significant contribution of COVID-19-induced emission reductions to the observed decrease in PM_2.5 concentrations in Northeast Asia. The quantitative analysis of the influence of meteorology, pre-existing emission control policies, and the pandemic provides critical insights for designing more effective air quality management strategies. Future research could focus on refining emission inventories and exploring the long-term implications of COVID-19-related emission reductions on air quality and climate change in the region. Further studies could explore the synergistic effects of various factors and develop more sophisticated models to predict the impact of future emission scenarios.

The study assumes independence between meteorological conditions and emissions in the simplified quantitative estimations of their respective impacts. The accuracy of the results depends on the reliability of the emission inventories and air quality models used. Regional variations and complexities in air pollution dynamics may not be fully captured by the chosen modeling approach. The study focuses on a specific period during the COVID-19 pandemic and may not be fully generalizable to other time periods or events.