双火源条件下的XPS火蔓延速率研究

为研究挤塑聚苯乙烯泡沫板(XPS)双火源火焰迁移规律,在不同间距(0.5cm~8cm)的情况下,进行了竖直和水平方向的系列实验。研究发现:火蔓延速率和质量损失速率均随间距先上升后缓慢下降;在竖直方向实验中,火蔓延速率极值点右偏移于质量损失极值点。基于双火源条件下所得到的热解区传热系数,计算出火蔓延速率,进而分析火蔓延速率计算式中对流项和辐射项,得出火蔓延速率随间距的变化主要受控于传热系数。依据此结论解释了火蔓延速率和质量损失趋势相似但两者极值点偏移不同的原因。     

Emissions cap or emissions tax? A multi-sector business cycle analysis

We develop a multi-sector business cycle model to analyze stochastic implications of reducing CO₂ emissions with carbon permits or with carbon taxes in the presence of multiple sources of macroeconomic uncertainty. The model is calibrated to reflect the U.S. experience. As in previous studies, using a single-sector version of our model, we find that the cap regime generates lower volatility of real variables than the tax regime, but the latter may be preferable from the welfare perspective. Still, our multi-sector analysis points to the importance of the origin of the shocks in the ranking of the two instruments and to the desirability of going beyond a single-sector analysis in evaluating their merits. We find no significant difference between the cap and the tax regimes when shocks come from non-energy sectors. In contrast, the cap has lower volatility but higher welfare costs than the tax for the shocks to energy production.     

全球变暖环境下基于金属媒介的气候敏感性研究：对一种典型两栖动物的早期和潜在影响

尽管有很多复杂的模型预测了未来温度对变温动物的影响,广泛分布的亚致命性污染物对变温动物的热应激反应产生的影响却少有模型提及。由不断上升的温度所带来更高的代谢率可以让变温动物获利地加快代谢与发育,但在长期亚致命性污染物的存在下,因清除或解毒而导致的对生存资源的额外需求很可能使得生物难以跟上温度上升的步伐,即毒物诱导的气候敏感性假说。在以自然湖水为背景的室外生物鉴定中,我们调查了一种模式变温动物在6个不同浓度的镉、铜和铅混合物以及3个热动态下(环境温度,高于环境温度1.5摄氏度以及高于环境温度2.5摄氏度)的日周期性温度变化。金属浓度在大约10倍生物可利用性慢性标准单位 (BCCU,慢性标准浓度的生物可利用性比例总和)之下时,升温对于寇普氏树蛙(Hyla chrysoscelis)没有显著作用。在高于10倍BCCU以及高于环境温度1.5摄氏度的处理条件下,生长受到促进。相反地,在28倍BCCU以及升温2.5摄氏度的条件下,不仅生长情况收到抑制,变态后20 d未成年树蛙的身体状况指标相比于背景环境(环境温度下的湖水)中的未成年树蛙也要低34%。这些发现认为毒物诱导的气候敏感性是通过对青少年阶段的生物产生长期潜在的影响而实现的。在22世纪,即使在最保守的全球变暖预测模型下,亚致命性污染物依然会加剧变温动物所遭受的来自升温的影响。
精选自Tyler A. Hallman, Marjorie L. Brooks. Metals-mediated climate susceptibility in a warming world: larval and latent effects on a model amphibian. Environmental Toxicology and Chemistry: Volume 35, Issue 7, pages 1872–1882, July 2016. DOI: 10.1002/etc.3337
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3337/full
     

基于改进的多目标决策的水环境质量综合评价

在对水环境质量综合评价中,多目标决策-理想区间法解决了水环境质量评价标准是区间而非点的缺陷。但是在计算监测点到各理想区间向量的距离时,各水环境质量指标权重直接影响综合评价的结果,通常的确定方法是简单的假设各水环境质量指标的权重相等,这与实际情况相悖。为了解决这一问题,提出了将超标法用于多目标决策法中,利用超标法确定各水环境质量指标的权重,然后将其应用于多目标决策-理想区间法来分析水环境质量等级。并将改进后的多目标决策-理想区间法应用于珠江口及邻近海域的水环境中。基于超标法确定权重的多目标决策-理想区间法与聚类分析相比更有效,与等权重的多目标决策-理想区间法相比,更能体现水环境的污染状况,可应用于各种环境因子的综合评价中。     

A Combined MOIP–MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.     

Evaluation of Dairy Effluent Management Options Using Multiple Criteria Analysis

This article describes how options for managing dairy effluent on the Lower Murray River in South Australia were evaluated using multiple criteria analysis (MCA). Multiple criteria analysis is a framework for combining multiple environmental, social, and economic objectives in policy decisions. At the time of the study, dairy irrigation in the region was based on flood irrigation which involved returning effluent to the river. The returned water contained nutrients, salts, and microbial contaminants leading to environmental, human health, and tourism impacts. In this study MCA was used to evaluate 11 options against 6 criteria for managing dairy effluent problems. Of the 11 options, the MCA model selected partial rehabilitation of dairy paddocks with the conversion of remaining land to other agriculture. Soon after, the South Australian Government adopted this course of action and is now providing incentives for dairy farmers in the region to upgrade irrigation infrastructure and/or enter alternative industries.     

Cutting the cake: Supporting environmental fund allocation decisions

This paper describes a decision support model for allocating financial resources amongst multiple user groups in environmental management problems. The model is based on the multiple criteria analysis (MCA) method of compromise programming. It was used to inform the allocation of Natural Heritage Trust funds across 14 regions in Queensland, Australia. The model targets funding to those regions with greater natural resource management needs. Need is determined by 19 weighted criteria relating to natural resource assets and threats. The model was accepted by the Australian Government, Queensland Government and regional groups as an appropriate means for allocating program funds; first in 2005 and then again, with improvements, in 2007. This paper shows that an MCA model can improve the transparency, auditability and acceptance of allocation decisions which would otherwise be heavily politicised.     

Evaluating water quality investments using cost utility analysis

This study borrows concepts from healthcare economics and uses cost utility analysis (CUA) to select an optimum portfolio of water quality enhancement projects in Perth, Western Australia. In CUA, costs are handled via standard discounted cash flow analysis, but the benefits, being intangible, are measured with a utility score. Our novel methodology combines CUA with a binary combinatorial optimisation solver, known as a 'knapsack algorithm', to identify the optimum portfolio of projects. We show how water quality projects can be selected to maximise an aggregate utility score while not exceeding a budget constraint. Our CUA model applies compromise programming (CP) to measure utility over multiple attributes in different units. CUA is shown to provide a transparent and analytically robust method to maximise benefits from water quality remediation investments under a constrained budget.     

A nonlinear model for assessing multiple probabilistic risks: a case study in South five-island of Changdao National Nature Reserve in China

Several methods for estimating the potential impacts caused by multiple probabilistic risks have been suggested. These existing methods mostly rely on the weight sum algorithm to address the need for integrated risk assessment. This paper develops a nonlinear model to perform such an assessment. The joint probability algorithm has been applied to the model development. An application of the developed model in South five-island of Changdao National Nature Reserve, China, combining remote sensing data and a GIS technique, provides a reasonable risk assessment. Based on the case study, we discuss the feasibility of the model. We propose that the model has the potential for use in identifying the regional primary stressor, investigating the most vulnerable habitat, and assessing the integrated impact of multiple stressors.