Optimization-based source apportionment of PM_2.5 incorporating gas-to-particle ratios

A modified approach to PM_2.5 source apportionment is developed, using source indicative SO₂/PM_2.5, CO/PM_2.5, and NO_x/PM_2.5 ratios as constraints, in addition to the commonly used particulate-phase source profiles. Additional information from using gas-to-particle ratios assists in reducing collinearity between source profiles, a problem that often limits the source-identification capabilities and accuracy of traditional receptor models. This is especially true in the absence of speciated organic carbon measurements. In the approach presented here, the solution is based on a global optimization mechanism, minimizing the weighted error between apportioned and ambient levels of PM_2.5 components, while introducing constraints on calculated source contributions that ensure that the ambient gas-phase pollutants (SO₂, CO, and NO_y) are reasonable. This technique was applied to a 25-month dataset of daily PM_2.5 measurements (total mass and composition) at the Atlanta Jefferson Street SEARCH site. Results indicate that this technique was able to split the contributions of mobile sources (gasoline and diesel vehicles) more accurately than particulate-phase source apportionment methods. Furthermore, this technique was able to better quantify the direct contribution (primary PM_2.5) of coal-fired power plants to ambient PM_2.5 levels.