Cancer Incidence and Community Exposure to Air Emissions from Petroleum and Chemical Plants in Contra Costa County, California: A Critical Epidemiological Assessment
Wong, Otto, Bailey, William J., Journal of Environmental Health
Contra Costa County covers an area of nearly 800 square miles in the northeastern portion of the San Francisco Bay area. It has a population of about 850,000. Its central and eastern sections are two of the fastest growing residential areas in the entire Bay area. In marked contrast, the "older" western and northern portions of the county are considerably more urban and industrial, with a total of five petroleum refineries and numerous chemical and other industrial plants concentrated along the rim of the bay.
Since the late 1970s, controversy has raged off and on as to whether emissions from these petrochemical operations are contributing to higher cancer rates -- particularly lung cancer -- in the so-called industrialized portions of the county. This was fueled initially by a National Cancer Institute (NCI) study in 1977 (1) which found Contra Costa, along with 38 other U.S. counties, with the heaviest concentrations of petroleum refining, to have significantly higher cancer mortality rates for a number of sites, including lung, nasal cavity and skin. However, a later study by researchers at the Kaiser-Permanente Medical Center in 1980 (2) did not find any association between cancer incidence and residence near petrochemical operations.
In 1984, two studies, by Kaldor et al. (3) and Austin et al. (4), both at the California Department of Health Services (DHS), came to different conclusions concerning the relationship between lung cancer and air pollution patterns throughout the county. Each employed different methods to measure and model specific air pollution contaminants for census tracts in the county, and to assess their correlation with cancer incidence. While Kaldor et al. included only industrial sources, Austin et al. also considered emissions from mobile sources, the highest single source of air toxics. A recent report published by the Bay Area Air Quality Management District (BAAQMD) (5) showed the central corridor along the Interstate Freeway 680 to have the highest concentration of benzene, and many other toxic compounds, in the county.
This paper will focus on the pitfalls of air pollution modeling from an epidemiologic perspective using these studies as examples. Vastly different conclusions can be reached, depending on how the data are derived and used. Furthermore, the models must be tested and validated with actual data. Finally, as with any epidemiological investigation, adequate control of confounding exposures is essential. For example, in studying the relationship between lung cancer and environmental exposures, smoking, occupational exposures and residential histories must be taken into consideration.
The Kaldor et al. (1984) study
Industrial air emissions -- In the Kaldor et al. (1984) study (3), the epidemiologists from the California DHS relied on a model developed by the BAAQMD to assess residential exposures to industrial air emissions. Since 1972, the BAAQMD has been estimating the amount of sulfur dioxide (S|O.sub.2~), hydrocarbons (HC) and nitrogen oxides (N|O.sub.x~) emitted from all major industries in Contra Costa County. These estimates were based on measurements taken at the point sources and the amount of chemicals used or produced by selected industrial sites. BAAQMD also estimates emissions by non-industrial sources such as automobiles, aircraft and small businesses.
In 1975, according to BAAQMD, 180 tons/day HC and 130 tons/day of S|O.sub.2~ were emitted by all sources in the county. Petroleum refineries and chemical plants accounted for 68 tons/day (38 percent) HC and 91 tons/day (70 percent) S|O.sub.2~. Power plants accounted for slightly less than 26 tons/day (20 percent) S|O.sub.2~, but less than 1 ton/day (1 percent) HC.
Air pollution model -- The BAAQMD developed an air pollution model based on the following information:
1) 1975 industrial emission estimates;
2) topographic data from U.S. geologic survey; and
3) 1973 meteorologic data. …