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231.
Erin L. Murphy Miranda Bernard Gwenllian Iacona Stephanie B. Borrelle Megan Barnes Alexis McGivern Jorge Emmanuel Leah R. Gerber 《Conservation biology》2022,36(2):e13827
Marine plastic pollution has emerged as one of the most pressing environmental challenges of our time. Although there has been a surge in global investment for implementing interventions to mitigate plastic pollution, there has been little attention given to the cost of these interventions. We developed a decision support framework to identify the economic, social, and ecological costs and benefits of plastic pollution interventions for different sectors and stakeholders. We calculated net cost as a function of six cost and benefit categories with the following equation: cost of implementing an intervention (direct, indirect, and nonmonetary costs) minus recovered costs and benefits (monetary and nonmonetary) produced by the interventions. We applied our framework to two quantitative case studies (a solid waste management plan and a trash interceptor) and four comparative case studies, evaluating the costs of beach cleanups and waste-to-energy plants in various contexts, to identify factors that influence the costs of plastic pollution interventions. The socioeconomic context of implementation, the spatial scale of implementation, and the time scale of evaluation all influence costs and the distribution of costs across stakeholders. Our framework provides an approach to estimate and compare the costs of a range of interventions across sociopolitical and economic contexts. 相似文献
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Julian W. Jones Thomas E. Emmel Bernard A. Laseke 《Journal of the Air & Waste Management Association (1995)》2013,63(6):852-856
The U.S. EPA’s Air and Energy Engineering Research Laboratory is responsible for assessing control technology performance and costs under the National Acid Precipitation Assessment Program. A major part of this assessment involves developing site-specific estimates of the performance and costs of retrofitting SO2 and NOx control technologies for the top 200 SO2- emitting (1980) coal-fired power plants in the 31-state eastern region. This effort includes detailed evaluation of a small number of plants (30 or less) representing a cross-section of the top 200 population. In cooperation with the states of Ohio and Kentucky (in conjunction with the U.S. EPA’s State Acid Rain Grant Program), efforts were undertaken to visit and conduct detailed evaluation of 12 coal-fired plants—five in Ohio, seven in Kentucky and the Tennessee Valley Authority System. A variety of commercial and advanced SO2 and NOx control technologies—including precombustion, combustion (in-furnace), and postcombustion (flue gas cleanup) technologies—were applied to each plant through conceptual designs. Retrofit factors (applied to the capital cost of a new pollution control system), cost “adders” (e.g., movement of existing equipment), and costs were developed for applying the control technologies to the boilers of each plant. Results of these and subsequent efforts will be valuable in evaluations of acid deposition control strategies by federal and state agencies and by electric utilities. 相似文献
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The link between individual habitat selection decisions (i.e., mechanism) and the resulting population distributions of dispersing organisms (i.e., outcome) has been little-studied in behavioural ecology. Here we consider density-dependent habitat (i.e., host) selection for an energy- and time-limited forager: the mountain pine beetle (Dendroctonus ponderosae Hopkins). We present a dynamic state variable model of individual beetle host selection behaviour, based on an individual’s energy state. Field data are incorporated into model parameterization which allows us to determine the effects of host availability (with respect to host size, quality, and vigour) on individuals’ decisions. Beetles choose larger trees with thicker phloem across a larger proportion of the state-space than smaller trees with thinner phloem, but accept lower quality trees more readily at low energy- and time-states. In addition, beetles make habitat selection decisions based on host availability, conspecific attack densities, and beetle distributions within a forest stand. This model provides a framework for the development of a spatial game model to examine the implications of these results for attack dynamics of beetle populations. 相似文献
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