锅炉除尘脱硫及其废水回用系统的经济损益分析

以燃煤锅炉掺烧固硫除尘脱硫及其废水回用系统为研究对象，利用环境系统费用效益分析方法，分析了该系统的环保投入和取得的环境效益。结果表明：对燃烧高硫煤的８０ｔ／ｈ规模的锅炉房，环保费用的现值为３１２６万元，环保效益的现值为９７２９万元，费用与效益之比为１∶３１１。结果说明锅炉掺烧固硫除尘脱硫及其废水循环技术具有很好的经济效益。该分析方法和结果为燃煤锅炉除尘脱硫工艺方案的选择和系统的优化研究提供了基础。     

Game theory approach to optimal capital cost allocation in pollution control

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关于大型社会经营活动安全问题的探讨

笔者列举了相关事例,指出了大型社会经营活动的主要特点;从制度、操作、技术研究、教育4方面分析了目前大型社会经营活动存在的现实突出问题;重点从公共场所安全、应急、疏散、人群、活动容量、旅游安全、安全管理、工作实践这几个方面综述了大型社会经营活动安全相关研究的进展并指出不足之处;在上述研讨的基础上结合风险评价理论等,提出了一个较为完善的保障大型社会经营活动安全的构想,并详细论述其内容、方法及技术路线。该构想对开展大型社会经营活动的事故预防、风险管理、应急处理和控制具有重要参考价值。     

对财务经济分析体系发展的初探

随着我国社会主义市场经济体制的建立和发展,企业将面临着一个日益完善的市场经济体系,这就要求企业的行为要更加规范。于是能够评价、分析企业盈利能力、生存能力、发展能力等各项指标的财务分析体系,就显得尤为重要了。本文主要从现行条件下财务分析体系入手,从财务分析体系的内容和发展前景两个方面,阐述了对财务分析体系发展的几点初步认识。     

基于安全投入产出模型的城市安全资源优化策略

城市安全投入与安全经济效益是制约城市安全产出的两个关键因素。为了揭示两者间的关系及其在提高城市安全度方面的作用，笔者借鉴安全经济学理论和方法，在研讨安全投入产出概论的基础上，在安全经济效益不变和安全投入量已知的情况下，提出了建立安全投入产出模型的方法。并以企业为例，从微观上验证了模型的有效性。不仅为城市安全管理决策者提供了制定安全投入目标、确定安全投入效用水平的量化工具，而且更加突出了提高安全经济效益的重要性。同时，提出了建立“资源共享”的城市重大危险源安全应急网络策略，为进一步优化城市安全资源配置和提高资源利用率奠定了基础。     

Estimating the Recreational-Use Value for Hiking in Bellenden Ker National Park, Australia

The recreational-use value of hiking in the Bellenden Ker National Park, Australia has been estimated using a zonal travel cost model. Multiple destination visitors have been accounted for by converting visitors’ own ordinal ranking of the various sites visited to numerical weights, using an expected-value approach. The value of hiking and camping in this national park was found to be $AUS 250,825 per year, or $AUS 144,45 per visitor per year, which is similar to findings from other studies valuing recreational benefits. The management of the park can use these estimates when considering the introduction of a system of user pays fees. In addition, they might be important when decisions need to be made about the allocation of resources for maintenance or upgrade of tracks and facilities.     

A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

Environmental cost of using poor decision metrics to prioritize environmental projects

Conservation decision makers commonly use project‐scoring metrics that are inconsistent with theory on optimal ranking of projects. As a result, there may often be a loss of environmental benefits. We estimated the magnitudes of these losses for various metrics that deviate from theory in ways that are common in practice. These metrics included cases where relevant variables were omitted from the benefits metric, project costs were omitted, and benefits were calculated using a faulty functional form. We estimated distributions of parameters from 129 environmental projects from Australia, New Zealand, and Italy for which detailed analyses had been completed previously. The cost of using poor prioritization metrics (in terms of lost environmental values) was often high—up to 80% in the scenarios we examined. The cost in percentage terms was greater when the budget was smaller. The most costly errors were omitting information about environmental values (up to 31% loss of environmental values), omitting project costs (up to 35% loss), omitting the effectiveness of management actions (up to 9% loss), and using a weighted‐additive decision metric for variables that should be multiplied (up to 23% loss). The latter 3 are errors that occur commonly in real‐world decision metrics, in combination often reducing potential benefits from conservation investments by 30–50%. Uncertainty about parameter values also reduced the benefits from investments in conservation projects but often not by as much as faulty prioritization metrics.