广州地区典型多溴联苯醚迁移和归趋行为模拟

运用多介质逸度模型对典型PBDEs(BDE47、BDE99、BDE209)在广州地区大气、水体、土壤、沉积物中的浓度分布与多介质间的迁移、归趋进行了模拟研究并分析了3种化合物在研究区域环境多介质间的迁移通量,确定其在环境中的主要迁移过程;结合实际监测数据,对模型的可靠性进行验证;以BDE47和BDE209为例,对模型的输入参数进行灵敏度分析;并以BDE209为例,对模型进行不确定性分析.通过模拟浓度与实测浓度的对比,表明模型在该地区具有很好的适用性.结果表明,环境系统达到平衡时,BDE47、BDE99和BDE209在土壤和沉积物中的含量分别占其在环境系统总含量的17.73%和82.26%,14.65%和85.35%,4.81%和95.19%;PBDEs从环境系统中的消失途径主要为大气平流输出和土壤降解;logKow和大气平流输入是影响化合物在环境相中浓度分布的最主要因素;不确定性分析指出BDE209在土壤相中浓度的变异系数最大.     

基于不确定性的水资源优化配置模型及其实证研究

针对城市水资源系统中存在的不确定性,将可信性模糊机会约束规划模型与区间规划相结合,提出了不确定环境下的可信性模糊-区间线性规划(FILP)模型,将其应用于某城市水资源优化配置与科学管理中,构建了城市水资源优化配置FILP模型.该模型以城市的经济、社会与环境的可持续发展为目标,以供需水量等为不确定性约束,以各水源在各子区不同部门间的分配为决策变量,利用改进的风险显性区间规划算法进行求解得到一定置信度和意愿水平下的水资源优化配置风险-收益权衡方案.实证研究表明,该模型反映了不确定性因素对水资源系统收益的影响,能够为实际的优化决策提供方法支持.     

PnET-CN模型对东亚森林生态系统碳通量模拟的适用性和不确定性分析

东亚地区森林类型多样,开展区域生态系统碳循环模拟时应考虑森林类型的差异。论文利用基于叶氮浓度-最大净光合作用速率关系的PnET-CN模型,对东亚地区8 个森林生态系统通量观测站点的总生态系统碳交换（GEE）和生态系统呼吸（RE）进行模拟,以探讨模型的适用性并对不确定性来源进行分析。研究结果表明：①PnET-CN模型能较为准确地模拟东亚地区大部分森林生态系统站点的GEE和RE;②模型的适用性排序依次为温带、寒温带、亚热带、 热带,模型未能很好地模拟热带湿地森林GEE和RE 的季节与年际变异;③在同一气候区中,PnET-CN模型更加适用于针叶林碳交换的模拟;④PnET-CN模型比较准确地反映了东亚森林生态系统GEE、RE对气候因子（例如,温度或辐射）的响应,但在低温、较弱辐射条件下模型低估了GEE,在高温或较强辐射条件下高估了GEE;在低温条件下模型低估了RE,在高温条件下模型高估了RE。针对东亚多个森林通量站点的模拟情况,论文提出模型应在以下方面进行改进：①PnET-CN模型计算物候时除了考虑温度之外还应加入土壤湿度的影响,并对不同气候区森林生态系统赋予不同叶片凋落时长;②PnET-CN模型中温度对GEE的限制以及光合最适温度应该根据不同站点设置;③PnET-CN模型应该考虑森林生态系统对环境胁迫的适应性,加强对干旱等干扰的模拟;④同时对于拥有复杂水文条件的森林生态系统应该改进土壤含水量的算法,以准确反映该类型森林生态系统GEE和RE的季节变化。     

Minimax regret discounting

The paper considers an environmental policy decision in which the appropriate approach for discounting future costs and benefits is unknown. Uncertainty about the discount rate is formulated as a decision under Knightian uncertainty. To solve this, we employ minimax regret, a decision criterion that is much less conservative then the related criterion maximin—in particular, it can be shown to implement a “proportional response” in that it equally balances concern about the mistake of doing too little with that of doing too much. Despite the criterion's balanced nature, the minimax regret solution mimics a policy that maximizes the present discounted value of future net benefits with an effective (certainty-equivalent) discount rate that declines over time to the lowest possible rate. In addition to reinforcing Weitzman's (1998) original limiting result, the approach generates concrete policy advice when decision makers are unable to specify a prior over possible discount rates. We apply it to the Stern–Nordhaus discounting debate and find that the effective discount rate converges to the Stern rate in just under 200 years.     

基于前景理论突发水污染事件个体行为研究

前景理论(Prospect Theory,PT)能很好地描述个体在不确定条件下的行为决策模式和风险偏好。分析表明,利用前景理论研究突发水污染事件中的个体行为决策具有一定的适用性和可行性,因此,建立了突发水污染事件个体行为决策框架。以典型的镇江市水源苯酚污染事故为例,运用突发水污染事件个体行为决策框架,描述了突发水污染事件中的个体行为特征,研究了突发水污染事件中的个体主要决策偏差及其产生的主要原因,并对突发水污染事件中的个体决策偏差下的行为及行为表现进行了分析,提出了个体突发水污染事件应对模式。     

Fuzzy logic approach to calculation of thermal hazard distances in process industries

In this paper, a general procedure to deal with uncertainties in each stage of consequence modeling is presented. In the first part of the procedure, the sources of uncertainty are identified and confirmed by sensitivity analysis for the source term, dispersion, physical effects and consequence analysis. While the second part comprises an application of the fuzzy logic system to each step of the consequence modeling. The proposed procedure is verified by the case study for a pool fire liquefied natural gas (LNG) on water. The results in terms of thermal radiation distances are compared with calculations obtained using the Monte Carlo method and with experimental data. The consequence model based on fuzzy logic approach provides less uncertain and more precise results in comparison to the deterministic consequence model.     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.     

Scaling up of biomass simulation for Eucalyptus plantations based on landsenses ecology

ABSTRACT

Sustainable forest management on a regional scale requires accurate biomass estimation. At present, technologically comprehensive forecasting estimates are generated using process-based ecological models. However, isolation of the ecological factors that cause uncertainty in model behavior is difficult. To solve this problem, this study aimed to construct a meliorization model evaluation framework to explain uncertainty in model behavior with respect to both the mechanisms and algorithms involved in ecological forecasting based on the principle of landsenses ecology. We introduce a complicated ecological driving mechanism to the process-based ecological model using analytical software and algorithms. Subsequently, as a case study, we apply the meliorization model evaluation framework to detect Eucalyptus biomass forest patches at a regional scale (196,158 ha) using the 3PG2 (Physiological Principles in Predicting Growth) model. Our results show that this technique improves the accuracy of ecological simulation for ecological forecasting and prevents new uncertainties from being produced by adding a new driving mechanism to the original model structure. This result was supported by our Eucalyptus biomass simulation using the 3PG2 model, in which ecological factors caused 21.83% and 9.05% uncertainty in model behavior temporal and spatial forecasting, respectively. In conclusion, the systematic meliorization model evaluation framework reported here provides a new method that could be applied to research requiring comprehensive ecological forecasting. Sustainable forest management on regional scales contributes to accurate forest biomass simulation through the principle of landsenses ecology, in which mix-marching data and a meliorization model are combined.     

Modeling the impact of uncertainty in emissions trading markets with bankable permits

The various forms of uncertainty that firms may face in bankable emission permit trading markets will affect firms’ decision making as well as their market performance. This research explores the effect of increased uncertainty over future input costs and output prices on the temporal distribution of emission. In a dynamic programming setting, the permit price is a convex function of stochastic prices of coal and electricity. Increased uncertainty about future market conditions increases the expected permit price and causes a risk neutral firm to reduce ex ante emissions in order to smooth out marginal abatement costs over time. Finally, safety valves, both low-side and high-side, are suggested to reduce the impact of uncertainty in bankable emission trading markets.     

Climate change implications for disaster risk management in Japan: A case study on perceptions of risk management personnel and communities in Saijo city

This paper reviews climate change impacts and the existing disaster risk management system in Japan and offers the results of a structured questionnaire survey of the community leaders and disaster risk management personnel of Saijo city of Japan that assesses their perceptions about dealing with the extreme disasters by the existing disaster risk management systems. This study was inspired by the record number of typhoon landfall that has surprised the local government and communities in 2004. While unearthing the hidden vulnerabilities in cities like Saijo, this event has loosened the confidence of local communities on the disaster risk management systems. From the study, we conclude that the existing disaster risk management systems need further fillip and that the proactive community involvement in disaster risk management is still in nascent stages. Associating with the scientific community, involving the local communities (including the elderly), enhancing the redundancy in disaster risk management systems, inculcating strategic thinking and micro-level planning, conducting vulnerability assessments by considering the special circumstances including resource constraints of small cities and better policy coordination across the administrative hierarchy are some important considerations for dealing with the uncertainty brought by the extreme events.