The ends of uncertainty: Air quality science and planning in Central California
- Univ. of California, San Francisco, CA (United States)
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 documents 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 to identify significant nodes of interaction. Dominant policy coalitions are described through narratives distinguished by their uses of and responses to uncertainty, their exposures to risks, and their responses to the principles of conservatism, civil duty, and caution. Policy narratives are delineated using aggregated respondent statements to describe and understand advocacy coalitions. I found that models impacted the planning process significantly, but were used not purely for their scientific capabilities. Modeling results provided justification for decisions based on other constraints and political considerations. Uncertainties were utilized opportunistically by stakeholders instead of managed explicitly. Ultimately, the process supported the partisan views of those in control of the modeling. Based on these findings, as well as a review of model uncertainty analysis capabilities, I recommend modifying the planning process to allow for the development and incorporation of uncertainty information, while addressing the need for inclusive and meaningful public participation. 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.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 822267
- Report Number(s):
- LBNL-54222; R&D Project: 672401; TRN: US200412%%577
- Resource Relation:
- Other Information: TH: Thesis (Ph.D.); Submitted to the University of California, Berkeley, CA (US); PBD: 1 Sep 2003
- Country of Publication:
- United States
- Language:
- English
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