摘要 :
Limited time and resources usually characterize environmental decision making at policy organizations such as the U.S. Environmental Protection Agency. In these climates, addressing uncertainty, usually considered a flaw in scient...
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Limited time and resources usually characterize environmental decision making at policy organizations such as the U.S. Environmental Protection Agency. In these climates, addressing uncertainty, usually considered a flaw in scientific analyses, is often avoided. However, ignoring uncertainties can result in unpleasant policy surprises. Furthermore, it is important for decisionmakers to know how defensible a chosen policy option is over other options when the uncertainties of the data are considered. The purpose of this article is to suggest an approach that is unique from other approaches in that it considers uncertainty in two specific ways—the uncertainty of stakeholder values within a particular decision context and data uncertainty in the light of the decision-contextual data-values relationship. It is the premise of this article that the interaction between data and stakeholder values is critical to how the decision options are viewed and determines the effect of data uncertainty on the relative acceptability of the decision options, making the understanding of this interaction important to decisionmakers and other stakeholders. This approach utilizes the recently developed decision analysis framework and process, multi-criteria integrated resource assessment (MIRA). This article will specifically address how MIRA can be used to help decisionmakers better understand the importance of uncertainty on the specific (i.e., decision contextual) environmental policy options that they are deliberating.
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In this study, we introduce the prospect of using prognostic model-generated meteorological output as input to steady-state dispersion models by identifying possible advantages and disadvantages and by presenting a comparative ana...
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In this study, we introduce the prospect of using prognostic model-generated meteorological output as input to steady-state dispersion models by identifying possible advantages and disadvantages and by presenting a comparative analysis. Because output from prognostic meteorological models is now routinely available and is used for Eulerian and Lagrangian air quality modeling applications, we explore the possibility of using such data in lieu of traditional National Weather Service (NWS) data for dispersion models. We apply these data in an urban application where comparisons can be made between the two meteorological input data types. Using the U.S. Environment Protection Agency's American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model (AERMOD) air quality dispersion -model, hourly and annual average concentrations of benzene are estimated for the Philadelphia, PA, area using both hourly MM5 model-generated meteorological output and meteorological data taken from the NWS site at the Philadelphia International Airport. Our intent is to stimulate a discussion of the relevant issues and inspire future work that examines many of the questions raised in this paper.
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It is important to understand the effects of emission controls on concentrations of ozone, fine particulate matter (PM_(2.5)), and hazardous air pollutants (HAPs) simultaneously, to evaluate the full range of health, ecosystem, an...
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It is important to understand the effects of emission controls on concentrations of ozone, fine particulate matter (PM_(2.5)), and hazardous air pollutants (HAPs) simultaneously, to evaluate the full range of health, ecosystem, and economic effects. Until recently, the capability to simultaneously evaluate interrelated atmospheric pollutants ("one atmosphere" analysis) was unavailable to air quality managers. In this work, we use an air quality model to examine the potential effect of three emission reductions on concentrations of ozone, PM_(2.5), and four important HAPs (formaldehyde, acetaldehyde, acrolein, and benzene) over a domain centered on Philadelphia for 12-day episodes in July and January 2001. Although NO_x controls are predicted to benefit PM_(2.5) concentrations and sometimes benefit ozone, they have only a small effect on formaldehyde, slightly increase acetaldehyde and acrolein, and have no effect on benzene in the July episode. Concentrations of all pollutants except benzene increase slightly with NO_x controls in the January simulation. Volatile organic compound controls alone are found to have a small effect on ozone and PM_(2.5), a less than linear effect on decreasing aldehydes, and an approximately linear effect on acrolein and benzene in summer, but a slightly larger than linear effect on aldehydes and acrolein in winter. These simulations indicate the difficulty in assessing how toxic air pollutants might respond to emission reductions aimed at decreasing criteria pollutants such as ozone and PM_(2.5).
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Scientifically derived environmental indicators are central to environmental decision analysis. This article examines the interface between science (environmental indicators) and policy, and the dilemma of their integration. In th...
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Scientifically derived environmental indicators are central to environmental decision analysis. This article examines the interface between science (environmental indicators) and policy, and the dilemma of their integration. In the past, science has been shown to dominate many policy debates, usually with unfavorable results. The issue, therefore, is not whether science can determine policy but how science can be part of a more holistic analysis that incorporates other critical perspectives. This article discusses the importance of considering alternative views (as represented by different scientific indicators) within the policy debate. Six example ozone indicators, constructed from the same raw data, are used to illustrate this point. Two represent newly developed indicators that respond to present-day policy questions at the U.S. Environmental Protection Agency. The article concludes with a brief discussion of how such indicators can be used to better define a policy question, inform the policy debate, and evaluate policy alternatives.
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摘要 :
Scientifically derived environmental indicators are central to environmental decision analysis. This article examines the interface between science (environmental indicators) and policy, and the dilemma of their integration. In th...
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Scientifically derived environmental indicators are central to environmental decision analysis. This article examines the interface between science (environmental indicators) and policy, and the dilemma of their integration. In the past, science has been shown to dominate many policy debates, usually with unfavorable results. The issue, therefore, is not whether science can determine policy but how science can be part of a more holistic analysis that incorporates other critical perspectives. This article discusses the importance of considering alternative views (as represented by different scientific indicators) within the policy debate. Six example ozone indicators, constructed from the same raw data, are used to illustrate this point. Two represent newly developed indicators that respond to present-day policy questions at the U.S. Environmental Protection Agency. The article concludes with a brief discussion of how such indicators can be used to better define a policy question, inform the policy debate, and evaluate policy alternatives.
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