A41A-0007
In-situ Measurements of Ozone Production Rates and Comparisons to Model-derived Production Rates During the Houston, TX and Denver, CO DISCOVER-AQ Campaigns

Thursday, 17 December 2015
Poster Hall (Moscone South)
Bianca Chae Baier1, William H Brune1, David Owen Miller1 and Barry L Lefer2, (1)Pennsylvania State University Main Campus, University Park, PA, United States, (2)NASA Headquarters, Washington, DC, United States
Abstract:
Tropospheric ozone (O3) is a secondary pollutant that has harmful effects on human and plant life. The climate and urban emissions in Houston, TX and Denver, CO can be conducive for significant ozone production and thus, high ozone events. Tighter government strategies for ozone mitigation have been proposed, which involve reducing the current EPA eight-hour ozone standard from 75 ppb to 65-70 ppb. These strategies rely on the reduction of ozone precursors in order to decrease the ozone production rate, P(O3). The changes in the ozone concentration at a certain location are dependent upon P(O3), so decreasing P(O3) can decrease ozone levels provided that it has not been transported from other areas. Air quality models test reduction strategies before they are implemented, locate ozone sources, and predict ozone episodes.

Traditionally, P(O3) has been calculated by models. However, large uncertainties in model emissions inventories, chemical mechanisms, and meteorology can reduce confidence in this approach. A new instrument, the Measurement of Ozone Production Sensor (MOPS) directly measures P(O3) and can provide an alternate approach to determining P(O3). An updated version of the Penn State MOPS (MOPSv2.0) was deployed to Houston, TX and Denver, CO as a part of NASA’s DISCOVER-AQ field campaign in the summers of 2013 and 2014, respectively. We present MOPS directly-measured P(O3) rates from these areas, as well as comparisons to zero-dimensional and three-dimensional modeled P(O3) using the RACM2 and MCMv2.2 mechanisms. These comparisons demonstrate the potential of the MOPS to test and evaluate model-derived P(O3), to advance the understanding of model chemical mechanisms, and to improve predictions of high ozone events.