Improved CMAQ predictions of particulate matter utilizing the satellite-derived aerosol optical depth

Regional air quality models such as the Community Multiscale Air Quality (CMAQ) model have been widely used to study and simulate multi-scale air quality issues. Although they are capable of providing high quality atmospheric chemistry profiles through the utilization of high resolution inputs relating meteorology and emissions with chemical reactions, they cannot simulate air quality accurately if other input data are not appropriate and reliable. There have been few studies on the importance of chemical initial conditions (ICs) as it is considered that the impact of concentration fields specified at the beginning of simulation wears off quickly. This paper demonstrates that the significant errors during the early part of the simulation can damage model predictions and conversely if the ICs are prescribed appropriately with available observations, they can compensate for the shortcomings of the air quality prediction system especially when the episode-based emissions inputs representing real-life emission variations such as forest fires as well as the effects of long-range transport events that are not reflected in the basic model inputs. The key hypothesis of the present study is that prediction of aerosols can be improved by the initialization of the aerosol fields with the satellite-derived Aerosol Optical Depth (AOD). We compare the effects of using fine mode and total AOD for the initialization in terms of regional bias characteristics. We found that the impacts of two-step initial conditions adjustments could be substantial in the case of aerosol events such as wildfires, which the present modeling system does not consider during simulation due to the deficiency in the emission inputs. The total AOD case helped to refine PM 2.5 predictions over the northwestern area, where wildfire events occurred, for the fire event days improving the correlation coefficient significantly from 0.12 to 0.67. CMAQ predicted PM 2.5 concentrations in the fine mode case decreased by 10–50 μg/m 3 in large areas of the northwestern region, resulting in more realistic PM 2.5 predictions with reduced unusual high peak cells. This study suggest that the use of initial conditions adjusted by total or fine mode AOD can help to improve PM 2.5 simulations, even though further refinements of the vertical distribution of aerosols are critically needed. ► Satellite derived AOD can be used to adjust initial conditions of the model. ► New method developed to adjust CMAQ PM 2.5 initia