Assessment of source-receptor relationships of aerosols: an integrated forward and backward modeling approach Sarika Kulkarni , University of Iowa Follow http://www.lib.uiowa.edu/sc/contact/

[摘要] This dissertation presents a scientific framework that facilitates enhanced understanding of aerosol source - receptor (S/R) relationships and their impact on the local, regional and global air quality by employing a complementary suite of modeling methods. The receptor - oriented Positive Matrix Factorization (PMF) technique is combined with Potential Source Contribution Function (PSCF), a trajectory ensemble model, to characterize sources influencing the aerosols measured at Gosan, Korea during spring 2001. It is found that the episodic dust events originating from desert regions in East Asia (EA) that mix with pollution along the transit path, have a significant and pervasive impact on the air quality of Gosan. The intercontinental and hemispheric transport of aerosols is analyzed by a series of emission perturbation simulations with the Sulfur Transport and dEposition Model (STEM), a regional scale Chemical Transport Model (CTM), evaluated with observations from the 2008 NASA ARCTAS field campaign. This modeling study shows that pollution transport from regions outside North America (NA) contributed ∼ 30 and 20% to NA sulfate and BC surface concentration. This study also identifies aerosols transported from Europe, NA and EA regions as significant contributors to springtime Arctic sulfate and BC. Trajectory ensemble models are combined with source region tagged tracer model output to identify the source regions and possible instances of quasi-lagrangian sampled air masses during the 2006 NASA INTEX-B field campaign. The impact of specific emission sectors from Asia during the INTEX-B period is studied with the STEM model, identifying residential sector as potential target for emission reduction to combat global warming. The output from the STEM model constrained with satellite derived aerosol optical depth and ground based measurements of single scattering albedo via an optimal interpolation assimilation scheme is combined with the PMF technique to characterize the seasonality and regional distribution of aerosols in Asia. This innovative analysis framework that combines the output from source - oriented chemical transport models with receptor models is shown to reduce the uncertainty in aerosol distributions, which in turn leads to better estimates of source - receptor relationships and impact assessments of aerosol radiative forcing and health effects due to air pollution.