Air quality in the San Joaquin Valley (SJV) was classified as extreme for the 1-hour standard and classified as serious for the new 8-hour standard—and thus will leave little opportunity for offsets. Today, SJV exploration and production is affected by emissions controls for improving air quality. Kern County, in the SJV, is the most oil productive county in California, generating two-thirds of all California petroleum. In 1999, oil wells in Kern County provided over 500,000 barrels of oil per day, ranking behind only Texas (1.4 million barrels per day), Louisiana (1.3 million barrels per day), and Alaska (on the order of 1 million barrels per day). In Kern County, the estimate of emissions for 1999 indicates that petroleum is responsible for 80 percent and 60 percent of all stationary source VOC (volatile organic compounds) and NOx emissions, respectively, which is about one-third of all emissions of each pollutant in the county. The threat of more-stringent air quality controls threatens to decrease present and future production in Kern and Fresno counties and thus threatens oil supply in the Western United States. This, in turn, will be of consequence for national energy security and the local, regional, and national economies.
Current practice for SIP planning involves modeling one or two high ozone episodes each of three or four days. There are over 100 days in exceedance of the new 8-hour standard and over 30 days in exceedance of the 1-hour standard in the SJV. Because of the diverse meteorology in the SJV and other regions, these exceedances will not be understood from modeling one or more episodes. Modeling a single or a small number of episodes as the basis for planning does not capture the diverse number of episodes and may not lead to an integrated strategy that will provide the most effective guidance to emissions reductions needed to meet that standard. A major impediment to modeling more episodes or even modeling a pollutant season is a lack of adequate data for model input and for evaluation of such models to ensure that they are predicting historic concentrations for the right reasons. Although a long-term, robust database is necessary to fully support seasonal modeling, the situation in Central California, with the SJV being designated as “extreme,” requires that researchers demonstrate the importance of seasonal modeling now and derive strategic information from it using the current, perhaps incomplete, database associated with summer 2000. Fortunately, many continuous monitoring stations throughout the region were put in place during that summer and have collected aerometric data continuously.
Current demands for longer-term modeling impact ozone in other parts of the country, as well as other aspects of air quality, since both visibility rules and particulate matter (PM) standards will require annual modeling. Furthermore, if we are to go to a multiple pollutant strategy, which is very much currently on the horizon of the Environmental Protection Agency, we must be able to achieve seasonal and even annual modeling for ozone. It is fortunate to have a robust seasonal data set to support such modeling, which will enable the project performer to evaluate not only performance and suggest potential strategies for control but will also enable the determination of what will actually be needed for seasonal and longer-term modeling. Because of the stochastic nature of atmospheric behavior, the project performer recognizes the need for an ensemble of events that can be analyzed to determine trends in air quality. Seasonal modeling results may begin to indicate that it is patterns that occur in space and time that need to be examined rather than what happens at a single point in time when CMAQ and other models are used to guide control decisions. Much of what researchers are learning is relevant to the application of other state-of-the-art air quality models. The sophisticated modeling tools that the researchers develop and refine are used to assess interactions among meteorology, emissions, and chemistry and to assess uncertainty. These have application to other air quality problems confronting oil and gas E&P operations as well.