Emissions, meteorological and climate impacts on PM2.5 levels in Southern California using a generalized additive model: Historic trends and future estimates

Annual fine particulate matter (PM2.5) mass concentrations in the South Coast Air Basin (SoCAB) of California decreased from around 30 mu g/m3 to 11 mu g/m3 between 2000 and 2013 but rose from 11 mu g/m3 to 13 mu g/m3 between 2014 and 2018, raising important questions about the effectiveness of ongoing emission control pol-icies. A two-step generalized additive model (GAM)-least squares approach was developed to explore the effects of emissions, large-scale climate events and meteorological factors on daily PM2.5 mass concentrations from 2000 to 2019 to quantitatively link impacts of emissions and meteorological on PM2.5 and to assess factors leading to the increase. The GAM had an R2 = 0.99 and root mean square error (RMSE) = 0.7 mu g/m3 for the annual average PM2.5 concentrations. The two-step method had an R2 = 0.93 and RMSE = 4.07 mu g/m3 for the 98th percentile 24-hr average PM2.5 concentrations. Variations in both emissions and relative humidity were of high importance compared with other included factors. Interactions of NH3 emissions with NOx and SO2 emissions, which lead to ammonium nitrate and sulfate aerosol formation, were the most important factors. Meteorological effects on PM2.5 explained the majority of the daily PM2.5 fluctuations. Emission changes (increases in SO2 and PM2.5) led to increases in predicted PM2.5 between 2014 and 2018. Predicted future PM2.5, using projected emissions and meteorological data from model simulations of representative concentration pathway (RCP) scenarios, are around 12 mu g/m3 (annual) and 30 mu g/m3 (98th percentile daily), which are both close to the current National Ambient Air Quality Standards (NAAQS) for PM2.5. Meteorological impacts on the predicted PM2.5 in future years lead to variations of +/- 2 mu g/m3 for the annual average and +/- 5 mu g/m3 for the 98th percentile daily level. Future climate changes lead to a probable year-to-year variation that will let PM2.5 levels in some years exceed the standard.