Wednesday, 10 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Rebecca Paulsen Edwards, Southwestern Univ., Georgetown, TX; and M. Engle and G. A. Morris
Tropospheric ozone is a respiratory irritant which forms in the presence of nitrogen oxides and hydrocarbon precursors in sunlight. Concentrations of ozone at the surface depend on a number of factors, including local production and long-range transportation, and natural and anthropogenic sources. Meteorological conditions also play a key role in ozone production. Over the last 30 years, air quality has significantly improved, especially in areas with large local sources of industrial and automotive emissions. The economy of the Gulf Coast of the United States is strongly tied to the oil and gas industry, which is situated both on and offshore. Houston, Texas, the largest city along the Gulf Coast, has historically been known for poor air quality largely due to this embedded source of anthropogenic hydrocarbons. Although Houston and other cities have benefitted from improving air quality due to enhanced emissions standards, many locations along the Gulf Coast still exceed the National Ambient Air Quality Standards (NAAQS) for ozone a few times each year. Understanding the anthropogenic and natural causes of high ozone events benefits future air quality management efforts.
Surface ozone concentration data from five Gulf Coast states (Texas, Louisiana, Mississippi, Alabama, and Florida) from the period 1980-2010 were used to create a database of 8-hour peak ozone concentrations for the United States Gulf Coast. The database was then leveraged to perform an analysis of climate-scale influences on tropospheric ozone in the region. In particular, the influence of the El Nino-Southern Oscillation (ENSO) was evaluated. To extract an ENSO signal from a dataset with a long-term decreasing temporal trend in surface ozone, a detrending algorithm was applied to each site. Using the detrended data, we evaluate the dependence of surface ozone concentration on ENSO phase along the Gulf Coast datasets.
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