A Measurement-Model Fusion Approach for Improved Wet Deposition Maps and Trends

Air quality models provide spatial fields of wet deposition (WD) and dry deposition that explicitly account for the transport and transformation of emissions from thousands of sources. However, many sources of uncertainty in the air quality model including errors in emissions and meteorological inputs (particularly precipitation) and incomplete descriptions of the chemical and physical processes governing deposition can lead to bias and error in the simulation of WD. We present an approach to bias correct Community Multiscale Air Quality model output over the contiguous United States using observation-based gridded precipitation data generated by the Parameter-elevation Regressions on Independent Slopes Model and WD observations at the National Atmospheric Deposition Program National Trends Network sites. A cross-validation analysis shows that the adjusted annual accumulated WD for NO₃ ^-, NH₄ ⁺, and SO₄ ^2- from 2002 to 2012 has less bias and higher correlation with observed values than the base model output without adjustment. Temporal trends in observed WD are captured well by the adjusted model simulations across the entire contiguous United States. Consistent with previous trend analyses, WD NO₃ ^- and SO₄ ^2- are shown to decrease during this period in the eastern half of the United States, particularly in the Northeast, while remaining nearly constant in the West. Trends in WD of NH₄ ⁺ are more spatially and temporally heterogeneous, with some positive trends in the Great Plains and Central Valley of CA and slightly negative trends in the south.