Comprehensive analyses linking PM2.5 to its precursors and meteorological conditions across regions and time scale in China

Abstract

This study conducts a comprehensive analysis of the intricate relationships between PM_2.5 concentrations, their chemical precursors and meteorological factors across nine distinct regions in China from 2015 to 2022. Employing sophisticated wavelet-based methodologies—wavelet coherence (WTC), partial wavelet coherence (PWC), and multiple wavelet coherence (MWC)—the research delves into the scale-specific, temporal, and spatial interactions between these variables. Our findings reveal that CO and NO₂ are the predominant precursors affecting PM_2.5 concentrations across most regions, whereas SO₂ holds greater influence in the South and Southwest. Key meteorological drivers include boundary layer height (BLH), wind speed (WU/WV), temperature (TM), precipitation (TP), and relative humidity (RHU), each exhibiting region- and time-scale-dependent impacts. Notably, BLH and wind speed play critical roles in PM_2.5 dispersion in northern regions, whereas RHU and TP are particularly influential in the South and Southwest, especially during wet seasons. Temperature's influence is dual-faceted, showing positive correlations with PM_2.5 on short time scales and negative correlations on longer scales. The study highlights the synergistic effects of meteorological factors and precursors, demonstrating that optimal combinations provide superior explanatory power for PM_2.5 variability compared to individual factors. The East, South, and Southwest regions display the strongest coherence between PM_2.5 and these combined influences, underscoring the need for region-specific and integrated air quality management strategies. These insights suggest targeted reduction of NO₂ and CO emissions in the North and Northeast, and SO₂ in the South and Southwest, while adapting to seasonal meteorological conditions, could significantly enhance PM_2.5 mitigation efforts.