In California, emission control strategies have been implemented to reduce air pollutants. Here we estimate the changes in nitrogen oxides (NOx = NO + NO2) emissions in 2005-2010 using a state-of-the-art four-dimensional variational approach. We separately and jointly assimilate surface NO2 concentrations and tropospheric NO2 columns observed by Ozone Monitoring Instrument (OMI) into the regional-scale Sulfur Transport and dEposition Model (STEM) chemical transport model on a 12 × 12 km2 horizontal resolution grid in May 2010. The assimilation generates grid-scale top-down emission estimates, and the updated chemistry fields are evaluated with independent aircraft measurements during the NOAA California Nexus (CalNex) field experiment. The emission estimates constrained only by NO2 columns, only by surface NO2, and by both indicate statewide reductions of 26%, 29%, and 30% from ~0.3 Tg N/yr in the base year of 2005, respectively. The spatial distributions of the emission changes differ in these cases, which can be attributed to many factors including the differences in the observation sampling strategies and their uncertainties, as well as those in the sensitivities of column and surface NO2 with respect to NOx emissions. The updates in California's NOx emissions reduced the mean error in modeled surface ozone in the Western U.S., even though the uncertainties in some urban areas increased due to their NOx-saturated chemical regime. The statewide reductions in NOx emissions indicated from our observationally constrained emission estimates are also reflected in several independently developed inventories: ~30% in the California Air Resources Board bottom-up inventory, ~4% in the 2008 National Emission Inventory, and ~20% in the annual mean top-down estimates by Lamsal et al. using the global Goddard Earth Observing System (GEOS)-Chem model and OMI NO2 columns. Despite the grid-scale differences among all top-down and bottom-up inventories, they all indicate stronger emission reductions in the urban regions. This study shows the potential of using space-/ground-based monitoring data and advanced data assimilation approach to timely and independently update NOx emission estimates on a monthly scale and at a fine grid resolution. The well-evaluated results here suggest that these approaches can be applied more broadly.

During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to -0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz, NOy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 Were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx, emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx, emissions, followed by VOCs and CO. PAN as a reservoir of NOx, can contribute to a significant amount of surface ozone through thermal decomposition. Copyright 2007 by the American Geophysical Union.