A Multi‐Dimensional Decomposition Method of the Meteorology‐Driven and Emission‐Driven Effects on Year‐to‐Year Air Quality Variations

Abstract

Abstract The annual assessment of emission control effects on air quality is essential for policy adjustments. However, this assessment is difficult as the inter‐annual changes in pollution are impacted by complex meteorological conditions. In this study, based on our wind‐pollution decomposition (WPD) method, which decomposes wind effects (wind‐driven) and nonwind effects, we established the meteorology‐pollution decomposition (MPD) method, which separates meteorological effects (met‐driven) and nonmeteorological effects by importing other meteorological parameters, to approximate the emission change effects (emission‐driven) by the nonmeteorological effects. The performance of the MPD method was assessed by comparing the results of the WPD and MPD methods at multiple representative stations in Hong Kong with the longest continuous data available in China from 2000 to 2018. The decomposed emission‐driven impact is also validated by using the gross domestic product growth rates data. The emission‐driven contributions determined by the WPD and MPD methods generally show agreement in trend, while the met‐driven effects are generally larger than the wind‐driven effects with the same or opposite trend. The results showed that the met‐driven effect from the MPD method is more reasonable than the wind‐driven effect from the WPD method in representing complex meteorological influences, which indicates a better representation of emission‐driven impacts by the nonmeteorological effects during the unusual meteorological years, such as El Niño‐Southern Oscillation events. The MPD method represents an independent approach, which is based only on regular observations, to quantify the long‐term trend in emission‐driven impacts as well as the integrated meteorological impacts on the atmospheric environment under the background of climate change.