Chemical feedback effects on the spatial patterns of the NO<sub>x</sub> weekend effect: a sensitivity analysis

Abstract

Abstract. We examine spatial variations in the weekdayweekend pattern of NO 2 over the Los Angeles metropolitan area using the Ozone Monitoring Instrument (OMI) and then compare the observations to calculations using the WRFChem model. We find that the spatial pattern of the weekdayweekend variations of the NO 2 column in the model is significantly different than observed. A sensitivity study shows that the contrasting spatial pattern of NO 2 on weekdays and weekends is a useful diagnostic of emissions and chemistry. These improvements suggest that constraints from spacebased observations of the processes affecting urban photochemistry (e.g., spatial patterns of emissions, ratios of VOC to NO x emissions, rate constants) are possible at a level of detail not previously described.

The Dawn of Geostationary Air Quality Monitoring: Case Studies From Seoul and Los Angeles

“…By providing the means to distinguish sources, long-term trends can be used to evaluate the changes of emissions driven by regulatory programs (Kim et al, 2006), technological controls (e.g., Russell et al, 2012), and economic activity (e.g., Russell et al, 2012;de Foy et al, 2016;Duncan et al, 2016). Whether considering daily measurements or analysis of long term monthly averages, instruments like OMPS NM provide a well-characterized, quantitatively stable measurement reflecting a balance of NO 2 emissions and removal at spatial scales of ∼25 km, with some limited information on pollutant transport (e.g., Beirle et al, 2011;Valin et al, 2013Valin et al, , 2014de Foy et al, 2016). As such, the measurements available from the past have not been sufficient to address the more pressing air quality management needs: the ability to distinguish sources within urban airsheds, characterization of local mesoscale flow patterns on pollutant transport, quantification of NO 2 removal mechanisms (e.g., Valin et al, 2013), or better characterization of photochemical ozone production to NO x (NO + NO 2 ) or VOC control strategies (e.g., Martin et al, 2004;Duncan et al, 2010;Jin et al, 2017;Schroeder et al, 2017).…”

“…NO 2 columns are smaller at all sites on the weekend (Saturday-Sunday) than during the week (Monday-Friday) in both regions. These weekdayweekend differences are a fingerprint that can help identify the contribution of various anthropogenic NO 2 sources based on our understanding of their day-of-week variation (e.g., heavy duty diesel trucking; Harley et al, 2005) and important non-linear chemical feedbacks (e.g, Valin et al, 2014).…”

“…At all sites, the weekend column densities are lower than those during the weekdays, highlighting the influence of anthropogenic activity on air quality. The longerterm averages of the NO 2 column reveal important information on chemical transport, but primarily reveal important lessons for understanding the chemical mass balance of NO 2 emissions and loss, or insights on the importance of sources of pollutant emissions that are known to have a day-of-week variation (e.g., Beirle et al, 2003;Harley et al, 2005;Valin et al, 2014).…”

“…These data have been useful for understanding global (e.g., Martin et al, 2003;Jaegl et al, 2005), regional (e.g., Duncan et al, 2016;Travis et al, 2016) and local air quality (e.g., Zhu et al, 2017) over daily (e.g., Valin et al, 2014;de Foy et al, 2016), seasonal (e.g., Russell et al, 2010), interannual, and decadal time periods (van der et al, 2008;De Smedt et al, 2015). However, the relatively coarse spatial resolutions and single daily observation times have substantially limited these applications, particularly within the air quality management community which needs to be able to distinguish temporal profiles of emissions from different source sectors and identify specific physical processes to justify regulatory decisions.…”

Distributions of ice supersaturation and ice crystals from airborne observations in relation to upper tropospheric dynamical boundaries

“…The formation and evolution from clear-sky ISS to cirrus clouds involves multiscale dynamical processes, which not only influence their macroscopic structure such as horizontal and vertical extent but also influence their microphysical properties. On the microscale, in situ aircraft observations (~200 m horizontal scale) have demonstrated that the characteristics of ice-supersaturated regions (ISSRs, where ISS is spatially continuously observed), such as location and RHi magnitude, are dominated by water vapor horizontal variability as opposed to temperature variability [Diao et al, 2014a]. In addition, cloud model studies have shown that the formation of ISS and ice crystals is influenced by small-scale dynamics, such as vertical velocity perturbations [Spichtinger and Gierens, 2009a], eddies and turbulence [Fusina and Spichtinger, 2010], and gravity waves [Spichtinger and Krämer, 2013].…”