陇中黄土丘陵地区农村生活能源消费的环境经济成本分析

陇中黄土丘陵地区经济贫困、环境脆弱、生活能源短缺,生物质过量消费成为生态环境退化的重要驱动因素。论文通过问卷调查获取相关数据,并建立计量模型,基于替代性分析估算了不同用能结构情景下的环境经济成本。结果表明,现状户均生活能源消费2 112.44kgce/a,人均428.59kgce/a,用能水平较低。目前农户消费能源选择的主要依据是能源的现金支出和可获得性。与农户现状用能结构相比较,4种替代结构的能源消费总成本、环境成本、经济成本及现金支出差异较大。利用沼气和太阳能的结构各项成本低,应是今后农村能源建设的方向。     

Inorganic nitrogen removal of toilet wastewater with an airlift external circulation membrane bioreactor

Removal of inorganic nitrogen (inorganic-N) from toilet wastewater, using a pilot-scale airlift external circulation membrane bioreactor (AEC-MBR) was studied. The results showed that the use of AEC-MBR with limited addition of alkaline reagents and volumetric loading rates of inorganic-N of 0.19-0.40 kg inorganic-N/(m3·d) helped achieve the desired nitrification and denitrification. Furthermore, the effects of pH and dissolved oxygen (DO) on inorganic-N removal were examined. Under the condition of MLSS at 1.56-2.35 g/L, BOD5/ammonia nitrogen (NH/-N) at 1.0, pH at 7.0-7.5, and DO at 1.0-2.0 mg/L, the removal efficiencies of NH4 -N and inorganic-N were 91.5% and 70.0%, respectively, in the AEC-MBR. The cost of addition of alkaline reagent was approximately 0.5-1.5 RMB yuan/m3, and the energy consumption was approximately 0.72 kWh/m3 at the flux of 8 L/(m2·h).     

层次化健康风险评估方法在苯污染场地的应用及效益评估

以北京某大型苯污染场地为例,详细介绍了如何开展层次化健康风险评估.同时,结合场地污染调查结果,比较了不同层次风险评价确定的土壤苯修复目标、修复量及修复成本的差异.结果表明,在1×10-6可接受致癌风险水平下,该场地第二层次风险评价确定的0～1.5 m深度范围内土壤苯修复目标为0.26 mg·kg-1、1.5～10 m范围内土壤苯修复目标为0.15mg·kg-1,相应的土壤修复量约为292 759 m3,修复成本约2.06亿元.但是,基于该场地苯污染区域土壤气中苯浓度进行的第三层次风险评价确定的0～1.5 m深度范围内土壤苯修复目标为2.6 mg·kg-1、1.5～10 m范围内土壤苯修复目标为1.5mg·kg-1,相应的土壤修复量约为153 222 m3,减少139 537 m3,修复成本为1.49亿元,减少了5 700万元,修复成本的降低远多于因开展第三层次风险评价所付出的约10万元的成本.因此,对于类似大型VOCs污染场地,开采第三层次健康风险评价能够节省大量修复成本、带来巨大的经济效益.     

西安市PM2.5健康损害价值评估

选取2014、2015、2016年冬季PM_(2.5)(24 h)浓度平均值,采用泊松回归模型评价全市居民连续3 a冬季PM_(2.5)暴露的急性健康损害效应,修正的人力资本法评估过早死亡经济损失,疾病成本法评估住院、患病与门诊经济损失.结果表明,研究时段内(2014、2015、2016年冬季)由PM_(2.5)造成的经济损失约为335.23亿元(95%CI:249.61~369.75)、211.05亿元(95%CI:135.60~268.80)、371.32亿元(95%CI:272.46~411.64),分别约占当年GDP的6.10%(4.54%~6.73%)、3.64%(2.34%~4.63%)、5.91%(4.34%~6.55%);健康经济损失与当年冬季PM_(2.5)浓度均值呈正相关关系;PM_(2.5)污染物对西安市常住人口健康影响显著,影响的病例(2014、2015、2016年)分别约为1 071 338例(95%CI:646 432~1 385 847)、438 273例(95%CI:246 842~599 989)、1 019 503例(95%CI:611 407~1 324 547);对哮喘儿童患者的影响比成人显著,而慢性支气管炎的影响成人比儿童显著.该研究可为西安市实施PM_(2.5)空气质量标准的成本效益分析提供科学的依据,为环境质量的管理提供参考.     

中国应对气候变化的碳减排研究进展

全球气候变化日益引起各国和公众的关注,我国也针对气候变化和二氧化碳减排进行了大量研究以应对挑战。文章在全面总结中国碳减排的研究文献基础上,从碳排放量估算及其影响因素、二氧化碳减排的情景分析、政策技术措施的潜力和成本分析、区域碳减排等4个方面系统归纳分析了我国主要的碳减排研究现状,提出了碳减排研究前景与展望,并建议开发适用于我国的碳减排研究模型,加强我国不同行业不同区域的碳减排研究,提出客观可行的减排措施。     

深圳市综合水质指数研究及其在水资源资产评估上的应用

自然资源资产评估技术是开展自然资源资产负债表实践和实行环境责任离任审计的重要技术支撑。水资源作为一项重要自然资源,如何有效评估水资源资产是不可回避的问题。论文以深圳市为研究区域,一是采用综合污染指数法和主成分分析法,以总氮、氨氮、总磷、化学需氧量、生化需氧量、固体悬浮物为指标参数构建了深圳市综合水质指数以评价水资源综合水质。二是以该综合水质评估模型为基础,通过采用治污成本法分析综合水质与治污成本间的关系,从而构建深圳市景观水和饮用水资源的价值量评估模型。论文还以深圳市大鹏新区为试点开展了水资源价值量评估,评估结果显示,2015年大鹏新区景观水和饮用水资源的价值量分别为3.60亿、0.35亿元。     

以经济学实验研究处罚机制对排污收费政策执行的影响

为研究处罚机制对排污收费政策执行效果的影响,建立了排污收费政策下风险中性企业的最优决策模型,设计了经济学实验.采用数据统计、线性随机效应模型、单因素不等重复实验方差分析等方法分析实验数据,验证了该模型得出的假设.结果表明,边际处罚期望对于企业的违法量和排放量决策均有显著负影响;企业边际减排成本对于企业的排放量决策有显著正影响,对于违法量决策没有显著影响;相同边际处罚期望下,监测频率越高,企业的服从率越高,且在边际处罚期望较高时,更为明显.因此,提高边际处罚期望可同时改善企业违法行为与促进企业减排.同时,为降低执行成本,在边际处罚期望较低时,可首先将线性罚款向梯级罚款转变.当边际处罚期望上升到较高水平时,则应注重监测频率的提高,并应重点监控那些排污量大而不是边际减排成本高的企业.     

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.