A53M-3410:
Transboundary Contributions To Surface Ozone In California's Central Valley

Friday, 19 December 2014
Andrew Post1, Ian C Faloona2, Stephen A Conley1 and David Lighthall3, (1)University of California Davis, Davis, CA, United States, (2)Univ California, Davis, Davis, CA, United States, (3)San Joaquin Valley Air Pollution Control District, Fresno, CA, United States
Abstract:
Rising concern over the impacts of exogenous air pollution in California's Central Valley has prompted the establishment of a coastal, high altitude monitoring site at the Chews Ridge Observatory (1550 m) approximately 30 km east of Point Sur in Monterey County, under the auspices of the Monterey Institute for Research in Astronomy. Two and a half years of continuous ozone data are presented in the context of long-range transport and its potential impact on surface air quality in the San Joaquin Valley (SJV). Past attempts to quantify the impact of transboundary ozone on surface levels have relied on uncertain model estimates, or have been limited to weekly ozonesonde data. Here, we present an observationally derived quantification of the contribution of free tropospheric ozone to surface sites in the San Joaquin Valley throughout three ozone seasons (June through September, 2012-2014). The diurnal ozone patterns at Chews Ridge, and their correlations with ozone aloft over the Valley, have been presented previously. Furthermore, reanalysis data of geopotential heights indicate consistent flow from Chews Ridge to the East, directly over the SJV. In a related airborne project we quantify the vertical exchange, or entrainment, rate over the Southern SJV from a series of focused flights measuring ozone concentrations during peak photochemical hours in conjunction with local meteorological data to quantify an ozone budget for the area. By applying the entrainment rates observed in that study here we are able to quantify the seasonal contributions of free tropospheric ozone measured at Chews Ridge to surface sites in the San Joaquin Valley, and compare prior model estimates to our observationally derived values.