Model simulation of carbonaceous fine particulate matter using SAFAR emission inventory and comparison with EDGAR-HTAP simulations

In this study, the evaluation of carbonaceous fine particulate matter (C-PM) was conducted using the SAFAR-India regional model. Two emission inventories were utilized: the newly developed SAFAR inventory and the global EDGAR-HTAP inventory, both for the year 2018. The simulation aimed to capture the seasonal and spatial patterns of black carbon (BC) and organic carbon (OC) concentrations. To validate model results, surface meteorological parameters, and C-PM concentrations were compared with the MERRA reanalysis data for the Indian region. Model simulated surface C-PM concentration with SAFAR emission inventory is found to be slightly overestimated (1.10), whereas simulated results with EDGAR emission inventory is significantly underestimated as compared to MERRA data. Model-simulated meteorological parameters showed a better correlation with MERRA reanalysis. Simulated geographical patterns of seasonal mean C-PM with SAFAR emission inventory exhibit quite a better comparison with MERRA reanalysis as against EDGAR simulated results. However, some differences in the present results are visible, particularly over the IGP region, as compared to MERRA data, but they are mainly attributed to a significant difference in the special resolution of present results (much finer) as compared to coarser MERRA data. In the Indo-Gangetic Plain (IGP) region, the concentration of BCSF and OCSF (BC and OC with SAFAR emission, respectively) show the peak during the winter, followed by the post-monsoon season. Although the correlation coefficients of hourly time series of surface BCSF and OCSF concentrations with MERRA over India are high (0.92 and 0.88), the poor RMSE, is attributed mainly to different scales of resolution. The model simulated BC, and OC concentrations with SAFAR emission input capture the pattern of spatial distribution reasonably well. The present evolution of BC and OC will help to better quantify their impact on climate and atmospheric conditions over the Indian region.