Assessing Model Characterization of Single Source Secondary Pollutant Impacts Using 2013 SENEX Field Study Measurements

Abstract

Aircraft measurements made downwind from specific coal fired power plants during the 2013 Southeast Nexus field campaign provide a unique opportunity to evaluate single source photochemical model predictions of both O and secondary PM species. The model did well at predicting downwind plume placement. The model shows similar patterns of an increasing fraction of PM sulfate ion to the sum of SO and PM sulfate ion by distance from the source compared with ambient based estimates. The model was less consistent in capturing downwind ambient based trends in conversion of NO to NO from these sources. Source sensitivity approaches capture near-source O titration by fresh NO emissions, in particular subgrid plume treatment. However, capturing this near-source chemical feature did not translate into better downwind peak estimates of single source O impacts. The model estimated O production from these sources but often was lower than ambient based source production. The downwind transect ambient measurements, in particular secondary PM and O, have some level of contribution from other sources which makes direct comparison with model source contribution challenging. Model source attribution results suggest contribution to secondary pollutants from multiple sources even where primary pollutants indicate the presence of a single source.

Decadal changes in summertime reactive oxidized nitrogen and surface ozone over the Southeast United States

“…Aircraft campaigns during the summers of 2004 and 2013, including the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT; Singh et al, 2006), the Southeast Nexus (SENEX; Warneke et al, 2016), and the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC 4 RS; Toon et al, 2016), provide detailed characterization of tropospheric composition in this region separated by nearly a decade. These data have been widely used to evaluate model estimates of RON and ozone Pierce et al, 2007;Perring et al, 2009;Fischer et al, 2014;Hudman et al, 2007;Henderson et al, 2011;Hudman et al, 2009;Edwards et al, 2017;Baker and Woody, 2017;Travis et al, 2016;Mao et al, 2013b;Fisher et al, 2016;Yu et al, 2016;Liu et al, 2016). Together with measurements from surface networks, including the National Atmospheric Deposition Program (NADP) and EPA Air Quality System (AQS), these datasets enable a close examination of responses of RON and surface ozone to NO x emission reductions in this region.…”

Characterizing CO and NOy Sources and Relative Ambient Ratios in the Baltimore Area Using Ambient Measurements and Source Attribution Modeling

“…Source apportionment approaches implemented in photochemical transport models track pollutants emitted from specific sources through the transport and chemistry calculations within the model and provide information on estimated source contributions to pollutant mixing ratios at every time step and at each grid location within the modeling domain. Source apportionment implementations in photochemical grid models have been used to differentiate modeled contribution to primary and secondary pollutants from broad source sectors ( Baker et al, 2016 ; Fann et al, 2013 ; Goldberg et al, 2016 ), specific facilities ( Baker & Kelly, 2014 ; Baker & Woody, 2017 ), and lateral boundary chemical inflow using reactive tracers ( Baker et al, 2015 ; Dolwick et al, 2015 ).…”

Response

“…For example, the model study of Mascioli et al (2016) reported little sensitivity in southeast surface temperatures to external forcings such as anthropogenic aerosols or even greenhouse gases. In contrast, Banerjee et al (2017) found that as much of 50 % of the observed 1950-1975 summertime cooling trend in the southeast could be explained by increasing aerosols. Examining multi-model output, Mascioli et al (2017) concluded that aerosols accounted for just 17 % of this cooling trend in summer.…”