分光光度法测定地下水中六价铬的不确定度评定

对二苯碳酰二肼分光光度法测地下水中六价铬的不确定度来源进行分析、计算和合成,标准曲线的不确定度采用线性双误差拟合。地下水样品测定结果表明,影响测定结果的不确定度因素主要来源于六价铬标准系列溶液配制和样品的重复测定,对地下水样品中六价铬测定的不确定度作了评估。     

A chemical plant protection game incorporating bounded rational attackers and distribution-free uncertainties

The chemical industry has an important role in our modern society. Due to the existence of hazardous materials and possible extreme producing conditions, chemical facilities are also considered dangerous. Research has pointed out that a successful attack on chemical plants may cause mass casualties, in the United States. Game theory has been employed to improve the protection of chemical plants, and current literature on chemical plant protection games assume a ‘rational’ attacker. The present paper studies a game-theoretic model, which is played by a rational defender and a ‘bounded rational’ attacker, for improving chemical plant protection. The attacker modeled in this paper is assumed to play higher payoff strategies with higher probabilities, which is innovative from the current chemical security literature. Attackers in the current chemical plant protection games would always play the strategy with the highest payoff (probability of 100%). Distribution-free uncertainties on attacker's parameters are also integrated into the model. An algorithm for solving the game presented in this paper is also proposed. A case study reveals that although a bounded rational attacker would reduce the defender's expected payoff, the defender's equilibrium strategy from the present model is robust to different attacker behaviors.     

Resolving structural uncertainty in natural resources management using POMDP approaches

In recent years there has been a growing focus on the uncertainties of natural resources management, and the importance of accounting for uncertainty in assessing management effectiveness. This paper focuses on uncertainty in resource management in terms of discrete-state Markov decision processes (MDP) under structural uncertainty and partial observability. It describes the treatment of structural uncertainty with approaches developed for partially observable resource systems. In particular, I show how value iteration for partially observable MDPs (POMDP) can be extended to structurally uncertain MDPs. A key difference between these process classes is that structurally uncertain MDPs require the tracking of system state as well as a probability structure for the structure uncertainty, whereas with POMDPs require only a probability structure for the observation uncertainty. The added complexity of the optimization problem under structural uncertainty is compensated by reduced dimensionality in the search for optimal strategy. A solution algorithm for structurally uncertain processes is outlined for a simple example in conservation biology. By building on the conceptual framework developed for POMDPs, natural resource analysts and decision makers who confront structural uncertainties in natural resources can take advantage of the rapid growth in POMDP methods and approaches, and thereby produce better conservation strategies over a larger class of resource problems.     

Uncertainty characterization approaches for risk assessment of DBPs in drinking water: A review

The management of risk from disinfection by-products (DBPs) in drinking water has become a critical issue over the last three decades. The areas of concern for risk management studies include (i) human health risk from DBPs, (ii) disinfection performance, (iii) technical feasibility (maintenance, management and operation) of treatment and disinfection approaches, and (iv) cost. Human health risk assessment is typically considered to be the most important phase of the risk-based decision-making or risk management studies. The factors associated with health risk assessment and other attributes are generally prone to considerable uncertainty. Probabilistic and non-probabilistic approaches have both been employed to characterize uncertainties associated with risk assessment. The probabilistic approaches include sampling-based methods (typically Monte Carlo simulation and stratified sampling) and asymptotic (approximate) reliability analysis (first- and second-order reliability methods). Non-probabilistic approaches include interval analysis, fuzzy set theory and possibility theory. However, it is generally accepted that no single method is suitable for the entire spectrum of problems encountered in uncertainty analyses for risk assessment. Each method has its own set of advantages and limitations. In this paper, the feasibility and limitations of different uncertainty analysis approaches are outlined for risk management studies of drinking water supply systems. The findings assist in the selection of suitable approaches for uncertainty analysis in risk management studies associated with DBPs and human health risk.     

Ranking Canadian universities: a quantitative approach for sustainability assessment using uD-SiM

This paper introduces a model that enables a comparison between universities based on sustainability indicators related to environmental, economic, social and educational aspects. The proposed model is based on a driving force-pressure-state-exposure-effect-action (DPSEEA) framework and is called uncertainty-based DPSEEA-Sustainability index Model (uD-SiM). The uD-SiM applies the concept of causality and develops sustainability index (SI), which is an outcome of nonlinear relationships of sustainability indicators in different stages of DPSEEA. In this paper, this fuzzy-based multi-criteria decision-making model is used to evaluate the sustainability of five Canadian universities, namely the University of British Columbia, the University of Toronto, the University of Alberta, the McGill University and the Memorial University. The final ranking results are compared with the Green report card ranking for 2010 through SI. The application of various actions and strategies that can be applied to different stages of the framework to improve sustainability in higher education institutions is also discussed.     

Pragmatic Approaches for Water Management Under Climate Change Uncertainty1

Stakhiv, Eugene Z., 2011. Pragmatic Approaches for Water Management Under Climate Change Uncertainty. Journal of the American Water Resources Association (JAWRA) 47(6):1183–1196. DOI: 10.1111/j.1752‐1688.2011.00589.x Abstract: Water resources management is in a difficult transition phase, trying to accommodate large uncertainties associated with climate change while struggling to implement a difficult set of principles and institutional changes associated with integrated water resources management. Water management is the principal medium through which projected impacts of global warming will be felt and ameliorated. Many standard hydrological practices, based on assumptions of a stationary climate, can be extended to accommodate numerous aspects of climate uncertainty. Classical engineering risk and reliability strategies developed by the water management profession to cope with contemporary climate uncertainties can also be effectively employed during this transition period, while a new family of hydrological tools and better climate change models are developed. An expansion of the concept of “robust decision making,” coupled with existing analytical tools and techniques, is the basis for a new approach advocated for planning and designing water resources infrastructure under climate uncertainty. Ultimately, it is not the tools and methods that need to be revamped as much as the suite of decision rules and evaluation principles used for project justification. They need to be aligned to be more compatible with the implications of a highly uncertain future climate trajectory, so that the hydrologic effects of that uncertainty are correctly reflected in the design of water infrastructure.     

A multi-approach strategy in climate attribution studies: Is it possible to apply a robustness framework?

Attribution studies investigate the causes of recent global warming. For a few decades the scientific community generally adopted dynamical models – the so-called Global Climate Models (GCMs) – for such an investigation. These models show the essential role of anthropogenic forcings in driving the temperature behaviour of the last half century. In the last period even other (data-driven) methodological approaches were adopted for attribution studies. This allows the scientific community to compare the results coming from these different approaches and to possibly increase their robustness. For such a purpose, the paper explores the possibility of applying a robustness framework, so far used only in the case of multi-model GCM ensembles, to a strategy including models from different methodological orientations, assessing such an application especially in the light of the independence issue.     

再生水补给型水体中病原微生物的来源、归宿及其风险评估

我国北方地区,以污水处理厂出水等非常规水源补给为主的河/湖逐渐成为城市群下游河流的主导类型;以污水处理厂尾水为补给水源的湿地公园近年来亦大量涌现.在节约城市用水、改善生态环境的同时,污水所携带的病原体对环境安全和人类健康带来潜在的威胁.为评估水环境病原微生物污染的健康风险,深入了解水体中病毒的类型以及病毒污染与环境因素之间的关系,认识病原微生物在水环境系统中的迁移轨迹、人暴露风险点及暴露途径具有重要的意义.针对典型再生水补给型水体存在的公共卫生安全问题,借鉴同时探索污水流行病学方法,并结合微生物定量风险评估（QMRA）分析,通过“污染-风险评价-风险预警”的流程,可以实现病原微生物污染全过程风险管理,为城市水环境的管理和良性运行提供理论支撑.     

考虑参数和边界条件不确定性的地下水污染随机模拟

为了分析模型参数的随机变化和边界条件的随机变化对地下水溶质运移模型输出结果的不确定性影响,采用蒙特卡洛模拟对一假想算例展开研究,并结合风险评估阐述不确定性分析结果.首先,建立研究区地下水溶质运移数值模拟模型,并综合利用局部灵敏度分析和全局灵敏度分析方法筛选出对模型输出结果影响较大的参数,连同模型的边界条件(第一类边界条件-水头值)一起作为随机变量.然后,利用优化超参数的高斯过程回归(GPR)方法建立模拟模型的替代模型,代替模拟模型完成蒙特卡洛随机模拟.最后,对随机模拟的结果进行统计分析和区间估计,并利用污染物浓度的概率分布函数对1、2、3号观测井进行地下水污染风险评价.结果表明:置信水平>80%时,1,2,3号观测井污染物浓度值的置信区间分别为34.77~35.03,57.74~58.04,100.07~100.69mg/L.此外,1,2,3号观测井为轻度污染的风险分别为6%,100%,100%;为中度污染的风险分别为0%,0%,99.6%;为重度污染的风险分别为0%,0%,0.5%,藉此为地下水污染修复防治和地下水的合理利用提供可靠参考依据.     

不确定性条件下地下水污染监测井网优化设计——基于XGBoost替代模型

在地下水污染监测井网优化设计中,应用模拟优化方法时客观存在的模型参数不确定性往往会影响到设计监测井网的可靠性.针对该问题,重点考虑了渗透系数和污染源释放强度的不确定性,应用模拟优化方法和蒙特卡罗方法求解上述不确定性参数影响下的最优监测井布设方案.为缓解蒙特卡罗方法多次调用模拟模型所产生的巨大计算负荷,本研究建立了XGBoost替代模型,代替模拟模型与优化模型进行耦合.为提高监测井网对实际污染羽的监测精度,污染监测井网优化模型以监测空间矩误差极小化为优化目标.此外,本次研究还考虑了监测井网设计中污染源释放强度的动态变化过程.最后,以抚顺市某煤矸石堆放场地为基础建立假想例子,验证所提方法的有效性.结果表明:1.XGBoost能够有效近似模拟模型的输入输出关系,显著降低了计算负荷.2.空间矩能够有效评估监测井网插值污染羽和实际污染羽的逼近程度,优化设计后的监测井网能够较为准确地捕捉到实际污染羽的状态.3.模拟优化方法结合蒙特卡罗方法能有效求解不确定性条件下最优监测井网的设计问题.本文为地下水污染监测井网设计提供了一种稳定可靠的方法.