(494c) Global Source Apportionment of Atmospheric Particulate Matter

As our society continues to develop and grow, it is necessary to expand our understanding of the impacts of atmospheric pollutant emissions on global scales. Researchers and regulatory agencies alike have used source apportionment as a powerful tool for quantifying and estimating these impacts on the regional scale. Towards expanding these capabilities from regional to global models, we have developed a new source apportionment scheme for the GEOS-Chem global atmospheric chemical transport model. The Global Particulate Matter Source Apportionment Technology (GPSAT) module represents the first incorporation into a global model. We have developed GPSAT within GEOS-Chem so that it will be available to all users in future versions of GEOS-Chem.

GPSAT can estimate contributions from different source classes (including locations and source types) without multiple model iterations or the need to create customized tracers. GPSAT is both computationally efficient and flexible. GPSAT allows us to develop a more complete picture of the impacts of intercontinental transport on global air pollutant concentrations. We will share estimates of the contributions from nine large, continent-scale, regions. We will also share further spatially refined estimates of contributions for the regions with the highest contributions globally. Finally we quantify the contributions of the 20 largest megacities to global air pollution concentrations using the average transport distance. We will specifically discuss the regions of the globe that most disproportionately impact global pollutant concentrations.

Through this project we have demonstrated an enhanced research tool (GEOS-chem with GPSAT) that will allow researchers throughout the globe to address a variety of scientific questions related to our understanding of long-range transport and the climate forcing contributions of different processes throughout the atmospheric component of the Earth System. Our goal in the analysis described here using GPSAT is to demonstrate the power and flexibility of the tool and thereby increase adoption by other researchers. The results from the analysis also provide necessary estimates for international discussions around air pollution. In addition, this analysis identifies areas most in need of focused attention in model improvement to potentially decrease model uncertainties. Finally, we provide a base-framework that other researchers can extend in the future to address the contributions from different processes throughout the entire Earth System and to identifying relative contributions to aerosol-climate feedbacks.