Impacts of Soil NOx Emission on O3 Air Quality in Rural California.

Nitrogen oxides (NOx) are a key precursor in O3 formation. Although stringent anthropogenic NOx emission controls have been implemented since the early 2000s in the United States, several rural regions of California still suffer from O3 pollution. Previous findings suggest that soils are a dominant source of NOx emissions in California; however, a statewide assessment of the impacts of soil NOx emission (SNOx) on air quality is still lacking. Here we quantified the contribution of SNOx to the NOx budget and the effects of SNOx on surface O3 in California during summer by using WRF-Chem with an updated SNOx scheme, the Berkeley Dalhousie Iowa Soil NO Parameterization (BDISNP). The model with BDISNP shows a better agreement with TROPOMI NO2 columns, giving confidence in the SNOx estimates. We estimate that 40.1% of the state's total NOx emissions in July 2018 are from soils, and SNOx could exceed anthropogenic sources over croplands, which accounts for 50.7% of NOx emissions. Such considerable amounts of SNOx enhance the monthly mean NO2 columns by 34.7% (53.3%) and surface NO2 concentrations by 176.5% (114.0%), leading to an additional 23.0% (23.2%) of surface O3 concentration in California (cropland). Our results highlight the cobenefits of limiting SNOx to help improve air quality and human health in rural California.

Resolving and Predicting Neighborhood Vulnerability to Urban Heat and Air Pollution: Insights From a Pilot Project of Community Science.

Urban heat and air pollution, two environmental threats to urban residents, are studied via a community science project in Los Angeles, CA, USA. The data collected, for the first time, by community members, reveal the significance of both the large spatiotemporal variations of and the covariations between 2 m air temperature (2mT) and ozone (O3) concentration within the (4 km) neighborhood scale. This neighborhood variation was not exhibited in either daily satellite observations or operational model predictions, which makes the assessment of community health risks a challenge. Overall, the 2mT is much better predicted than O3 by the weather and research forecast model with atmospheric chemistry (WRF-Chem). For O3, diurnal variation is better predicted by WRF-Chem than spatial variation (i.e., underestimated by 50%). However, both WRF-chem and the surface observation show the overall consistency in describing statistically significant covariations between O3 and 2mT. In contrast, satellite-based land surface temperature at 1 km resolution is insufficient to capture air temperature variations at the neighborhood scale. Community engagement is augmented with interactive maps and apps that show the predictions in near real time and reveals the potential of green canopy to reduce air temperature and ozone; but different tree types and sizes may lead to different impacts on air temperature, which is not resolved by the WRF-Chem. These findings highlight the need for community science engagement to reveal otherwise impossible insights for models, observations, and real-time dissemination to understand, predict, and ultimately mitigate, urban neighborhood vulnerability to heat and air pollution.