Simulation and analysis of causes of a haze episode by combining CMAQ-IPR and brute force source sensitivity method

Abstract

In other studies the Integrated Process Rate (IPR) method was widely used to analyze the impact of various physical and chemical processes and their relative significance on PM2.5 in pollution episodes for specific sites; however, sources of pollution and their effect in planning emission control strategies were not considered. Using results of a brute force source sensitivity (BFSS) method may complement IPR. This paper integrates CMAQ-IPR and BFSS to examine the causes of a PM2.5 episode on Jan 15, 2010 across two air quality monitoring stations in Taichung, Taiwan (Shalu, a rural station and Situn, an urban station). Two pollution deterioration events (time intervals) were observed and simulated. When only CMAQ-IPR was used for simulation, the results revealed most pollution (>60%) was from local sources at the Situn Station. The two deterioration intervals differed however, as interval 1 showed a contribution from local emissions (49%), vertical advection (41%) and aerosols processes (10%). Interval 2 at Shalu Station was categorized as a downwind monitoring station, where emission from the grid constituted only 37%, and the majority of pollutants travelling by horizontal advection (56%), and to some extent, aerosols process (6%). Simulation by integrating IPR and BFSS (including diesel vehicles, gasoline vehicles/motorcycles, construction/road dust, iron/steel industries, and power plants around Taiwan) rendered to the type of physical or chemical process in which pollutants went through and its impact on the concentration of PM2.5 in the air quality monitoring station, which helped planning of emission control measures. Simulation results indicated improvement of PM2.5 concentrations in Situn and Shalu would be limited (only 0.2–4.2% contribution to deteriorating PM2.5 levels at the stations) even the emissions of the power plants and iron/steel industries in whole Taiwan were under control. However, by controlling the emissions of diesel vehicles, gasoline vehicles/motorcycles, and construction/road dust in whole Taiwan, the improvent is much enhanced (49–79% contribution to deteriorating PM2.5 levels at the stations), but it cost a lot. Nonethless, the improvement was quite significant by controlling the local emissions (around the monitoring station) of diesel vehicles, gasoline vehicles/motorcycles, and construction/road dust for Situn Station as they accounted for 72–85% of these three sources contribution to deteriorating PM2.5 levels at the station. For Shalu Station, it required a wide area of controlling the emissions from diesel vehicles, gasoline vehicles/motorcycles, and construction/road dust because there was 22–53% of these three sources contribution to deteriorating PM2.5 levels at the station from horizontal or vertical advection.