Changes in nitrogen oxides emissions in California during 2005–2010 indicated from top‐down and bottom‐up emission estimates

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.

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