Combining Active and Passive Airborne Remote Sensing to Quantify NO2 and Ox Production near Bakersfield, CA

Aims: The objective of this study is to demonstrate the integrated use of passive and active remote sensing instruments to quantify the rate of NOx emissions, and investigate the Ox production rates from an urban area.
Place and Duration of Study: A research flight on June 15, 2010 was conducted over Bakersfield, CA and nearby areas with oil and natural gas production.
Methodology: Three remote sensing instruments, namely the University of Colorado AMAX-DOAS, NOAA TOPAZ lidar, and NCAS Doppler lidar were deployed aboard the NOAA Twin Otter during summer 2010. Production rates of nitrogen dioxide (NO2) and Ox‘(background corrected O3 + NO2) were quantified using the horizontal flux divergence approach by flying closed loops near Bakersfield, CA. By making concurrent measurements of the trace gases as well as the wind fields, we have reduced the uncertainty due to wind field in production rates.
Results: We find that the entire region is a source for both NO2 and Ox’. NO2 production is highest over the city (1.35 kg hr-1 km-2 NO2), and about 30 times lower at background sites (0.04 kg hr-1 km-2 NO2). NOx emissions as represented in the CARB 2010 emission inventory agreewell with our measurements over Bakersfield city (within 30%). However, emissions upwind of the city are significantly underestimated. The Ox’ production is less variable, found ubiquitous, and accounts for 7.4 kg hr-1 km-2 Ox’ at background sites. Interestingly, the maximum of 17.1 kg hr-1 km-2 Ox’production was observed upwind of the city. A plausible explanation for the efficient Ox’ production upwind of Bakersfield, CA are favorable volatile organic compound (VOC) to NOx ratios for Ox’ production, that are affected by emissions from large oil and natural gas operations in that area.
Conclusion: The NO2 and O3 source fluxes vary significantly, and allow us to separate and map NOx emissions and Ox production rates in the Central Valley. The data is probed over spatial scales that link closely with those predicted by atmospheric models, and provide innovative means to test and improve atmospheric models that are used to manage air resources. Emissions from oil and natural gas operations are a source for O3 air pollution, and deserve further study to better characterize effects on public health.