Exploring the trend, prediction and driving forces of aerosols using satellite and ground data, and implications for climate change mitigation

Human activities-related aerosol emissions and CO ₂ emissions originate from many of the common sources. Identifying the aerosol variations and the underling determinates can provide insights into united mitigation policy controls targeting on both aerosol pollution and climate change. Long-term trend analysis and modeling offers an effective way to fully appreciate how aerosols interlink with carbon cycle and climate change. This study analyzes the current trends, models the future predictions, and investigates potential driving forces of aerosol loading at six sites across North America and East Asia during 2003–2015. Satellite-retrieved MODIS Collection 6 retrievals and ground measurements derived from AERONET are used. Results show that there is a persistent decreasing trend in AOD for both MODIS data and AERONET data at three sites. Monthly and seasonal AOD variations reveal consistent aerosol patterns at sites along mid-latitudes. Regional differences caused by impacts of climatology and land cover types are observed for the selected sites. Statistical validation of time series ARIMA models indicates that the non-seasonal ARIMA model performs better for AERONET AOD data than for MODIS AOD data at most sites, suggesting the method works better for data with higher quality. The seasonal ARIMA model reproduces time series with distinct seasonal variations much more precisely. The reasonably predicted AOD values could provide reliable estimates to better inform the decision-making for sustainable environmental management. Drawn from aerosol pollution control strategies, it is suggested that the enforcement of regulations on emission sources and the initiative of reforestation on emission sinks could have potential implications for climate change mitigation. © 2019