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1.
Environ Manage ; 50(6): 1204-18, 2012 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-23052473

RESUMEN

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.


Asunto(s)
Toma de Decisiones , Ecosistema , Monitoreo del Ambiente
2.
Environ Sci Technol ; 44(6): 2131-7, 2010 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-20170160

RESUMEN

We present a model that integrates the economic input-output approach of life cycle assessment with environmental fate, exposure, and risk assessment to estimate the spatial distribution of air toxic health risks due to sector-specific economic activity in the U.S. The model is used to relate the economic activity and exposure potential (population density and meteorology) associated with point source emissions of the heavy metal and carcinogen, hexavalent chromium, or Cr(VI), on a county basis. Total direct annual airborne emissions of Cr(VI) in the U.S. were 44 tonnes in 2002, with 97% from facilities in four major sectors: power generation, wood, plastics, and chemicals, metals, and scientific services. These include 6 tonnes of Cr(VI) emitted in the supply chains of these sectors. A highly variable national distribution of lifetime cancer risk is predicted, with a population-weighted mean of 2.7 x 10(-7), but with hot-spot counties with lifetime risks as high as 6 x 10(-6). Furthermore, high exposures and risks tend to occur in more highly populated counties. In particular, the population of Los Angeles County is exposed to the highest level of risk in the country and almost three-quarters of the total predicted cancer incidence due to inhalation of airborne Cr(VI) emissions. This finding can be attributed largely to the use of Cr(VI) as a corrosion inhibitor by the scientific services sector facilities in the county, the use of shorter facility stacks, and their sitting within a highly populated area. These results indicate that linking economic activity, emission estimates, and fate and transport models for air toxics can inform both life cycle impact and comparative health risk assessments, allowing us to better target emission reductions to minimize hot-spots of risk.


Asunto(s)
Contaminantes Atmosféricos/análisis , Contaminación del Aire/estadística & datos numéricos , Cromo/análisis , Conservación de los Recursos Naturales/métodos , Contaminación del Aire/economía , Monitoreo del Ambiente , Industrias/estadística & datos numéricos , Modelos Químicos , Modelos Económicos , Medición de Riesgo , Estados Unidos
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