How does PM_2.5 affect forest phenology? Integrating PM_2.5 into phenology models for warm-temperate forests in China

Vegetation can regulate particulate matter (PM) through various mechanisms, such as facilitating the deposition of gases and particulates and purifying the air via photosynthesis. Conversely, PM directly damages leaves through dry deposition, while it also indirectly affects plant growth by altering weather conditions. However, the ways in which PM influence vegetation growth patterns, and the driving factors behind these impacts, remain unclear. In this study, we primarily focused on the start of the growing season (SOS) of warm-temperate zone forests in China with severe PM. SOS exhibited a trend of advancing at a rate of 0.15 days/yr during the study period from 2004 to 2022. We assessed the impact of satellite-derived fine PM (PM_2.5) and coarser PM (PM₁₀) on forest SOS across warm temperate forest regions in China using partial correlation analysis methods. After removing the effects of PM, we found that the correlation between temperature and SOS weakened. Additionally, PM exhibited a positive correlation with SOS in most pixels. Linear regression analysis revealed a significant negative correlation between relative humidity (RH) and the relationship between PM_2.5 and SOS. However, in areas where RH exceeds 60.38%, this effect becomes unstable, presumably due to increased aerosol hygroscopicity or the saturation of aerosol particles. We also found that as road network density increased, the relationship between PM_2.5 and SOS strengthened, whereas the impact of nightlight on this relationship was relatively weak. It is important to note that while the observed correlations reveal mechanisms by which PM_2.5 affects SOS, they do not directly imply causation, as the complex interactions between environmental factors may influence these relationships. Finally, we incorporated PM_2.5 into the phenology model and optimized its parameters using the least squares method, which improved the accuracy of SOS simulations and provided insights for predicting vegetation phenology in areas with severe PM pollution.