| Air quality planning in Central California is complicated and controversial despite millions of dollars invested to improve scientific understanding. This research describes and critiques the use of photochemical air quality simulation modeling studies in planning to attain standards for ground-level ozone in the San Francisco Bay Area and the San Joaquin Valley during the 1990's. Data are gathered through archival research and interviews with planners, modelers, and policy-makers at public agencies and with representatives from the regulated and environmental communities. Interactions amongst organizations are diagramed and policy narratives are delineated.; Planning agencies are found to pursue a strategy of controlling all emissions feasible regardless of available modeling evidence, whereas the regulated community emphasizes the limits of scientific understanding. All participants invoke uncertainty concerns opportunistically. Predetermined policy positions and other constraints, such as deadlines and political will, obviate modeling results. Consequently, models are often used selectively to justify predetermined decisions.; By documenting an actual air quality planning process these findings provide insights about the potential for using new scientific information and understanding to achieve environmental goals, most notably the analysis of uncertainties in modeling applications. Concurrently, needed uncertainty information is identified and capabilities to produce it are assessed. Practices to facilitate incorporation of uncertainty information are suggested based on research findings, as well as theory from the literatures of the policy sciences, decision sciences, science and technology studies, consensus-based and communicative planning, and modeling. |
