A hybrid methodology to quantitatively identify inorganic aerosol of PM_2.5 source contribution

It is difficult to identify inorganic aerosol (IA) (primary and secondary), the main component of PM_2.5, without the significant tracers for sources. We are not aware of any studies specifically related to the IA's local contribution to PM_2.5. 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 PM_2.5 and the associated compounds to (1) classify local and long-range transport PM_2.5, (2) identify sources of local PM_2.5 using PMF model, and (3) quantify local source contribution to IA in PM_2.5 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.