It is difficult to identify inorganic aerosol (IA) (primary and secondary), the main component of PM2.5, without the significant tracers for sources. We are not aware of any studies specifically related to the IA's local contribution to PM2.5. To effectively reduce the IA load, however, the contribution of local IA sources needs to be identified. In this work, we developed a hybrid methodology and applied online measurement of PM2.5 and the associated compounds to (1) classify local and long-range transport PM2.5, (2) identify sources of local PM2.5 using PMF model, and (3) quantify local source contribution to IA in PM2.5 using regression analysis. Coal combustion and iron ore and steel industry contributed the most amount of IA (~42.7%) in the study area (City of Taichung), followed by 32.9% contribution from oil combustion, 8.9% from traffic-related emission, 4.6% from the interactions between agrochemical applications and combustion sources (traffic-related emissions and biomass burning), and 2.3% from biomass burning. The methodology developed in this study is an important preliminary step for setting up future control policies and regulations, which can also be applied to any other places with serious local air pollution.
Keywords: Fine particles; IA source contribution; Regression analysis; Source apportionment; Trace metal.
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