Investigating sensitivity of ozone to emission reductions in the New York City (NYC) metropolitan and downwind areas

Ozone sensitivity to emission changes in urban environments were examined using WRF and CAMx simulations for the New York City metropolitan area (NYC) with data from the 2018 Long Island Sound Tropospheric Ozone Study measurements. The WRF simulation showed large positive biases of windspeed over entire domain, but those were significantly reduced with observational nudging. The base CAMx simulation showed large positive bias for NO2 concentrations in NYC, which was corrected after NOx emission adjustment (22% reduction) based on previous work. The improved modeling platform demonstrated reliable performance skills for regulatory applications. Pollution transport from NYC to the downwind region were well captured by the model. Simulated ozone concentration increases in response to NOx emission reductions within NYC proximity suggested this area to be a VOC-limited ozone formation regime. Reducing anthropogenic emissions by 50% for all pollutants reduced the number of simulated ozone exceedances from 18 to 9 days for NYC. Emission reductions were even more effective for air quality improvements in the downwind region with ozone exceedances decreasing from 20 to 7 days. Source apportionment showed mobile and industrial solvent emission sectors to be contributing more to ozone exceedances than the electrical generating units (EGU) sector in both NYC and the downwind region. The largest air quality improvement appeared to be associated with VOC emission reductions from the industrial solvent sector. All source sectors yielded higher ozone production efficiency when emissions were reduced by 50%, suggesting remaining emissions can be more potent in producing ozone per molecule of NOx.

Automated summary

The sensitivity of ozone to emission changes in urban environments was investigated using WRF and CAMx simulations for the NYC metropolitan area based on data from the Long Island Sound Tropospheric Ozone Study in 2018. The simulations showed that observational nudging significantly reduced the positive biases in wind speed. Adjusting NOx emissions based on previous work corrected the large positive biases in NO2 concentrations in NYC. The improved modeling platform demonstrated reliable performance for regulatory applications.