直读光谱仪碳元素检出限不确定度分析

依据JJG1059-1999对直读光谱仪碳元素检出限的不确定度进行了评估,分析了影响测量不确定度的各个因素,计算得出直读光谱仪碳元素检出限的扩展不确定度为:U=0.11%,k=2。     

Life cycle assessment of coated white board: a case study in China

Life cycle assessment was carried out using IMPACT2002+ to estimate the environmental impact of coated white board production, which is common in China. Normalized results showed that the potential impacts of respiratory inorganics, terrestrial ecotoxicity, global warming, and non-renewable energy had a dominant contributions to overall environmental impact. Specifically, emissions from chemical and energy production processes exhibited higher potential impact (more than 80% of the total contribution) on the environment than that of emissions generated from transport, landfill, wastewater treatment, and paper plants infrastructure. Energy recovery from black liquor and energy generation based on natural gas are key factors in reducing overall environmental potential impact. The current paper presents improvements on the environmental performance of a coated white board production site in China.     

More is not always better: coping with ambiguity in natural resources management

Coping with ambiguities in natural resources management has become unavoidable. Ambiguity is a distinct type of uncertainty that results from the simultaneous presence of multiple valid, and sometimes conflicting, ways of framing a problem. As such, it reflects discrepancies in meanings and interpretations. Under the presence of ambiguity it is not clear what problem is to be solved, who should be involved in the decision processes or what is an appropriate course of action. Despite the extensive literature about methodologies and tools to deal with uncertainty, not much has been said about how to handle ambiguities. In this paper, we discuss the notions of framing and ambiguity, and we identify five broad strategies to handle it: rational problem solving, persuasion, dialogical learning, negotiation and opposition. We compare these approaches in terms of their assumptions, mechanisms and outcomes and illustrate each approach with a number of concrete methods.     

Multimodel inference and adaptive management

Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study's inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.     

A two-stage inexact joint-probabilistic programming method for air quality management under uncertainty

A two-stage inexact joint-probabilistic programming (TIJP) method is developed for planning a regional air quality management system with multiple pollutants and multiple sources. The TIJP method incorporates the techniques of two-stage stochastic programming, joint-probabilistic constraint programming and interval mathematical programming, where uncertainties expressed as probability distributions and interval values can be addressed. Moreover, it can not only examine the risk of violating joint-probability constraints, but also account for economic penalties as corrective measures against any infeasibility. The developed TIJP method is applied to a case study of a regional air pollution control problem, where the air quality index (AQI) is introduced for evaluation of the integrated air quality management system associated with multiple pollutants. The joint-probability exists in the environmental constraints for AQI, such that individual probabilistic constraints for each pollutant can be efficiently incorporated within the TIJP model. The results indicate that useful solutions for air quality management practices have been generated; they can help decision makers to identify desired pollution abatement strategies with minimized system cost and maximized environmental efficiency.     

Application of fuzzy logic to explosion risk assessment

Safety and health of workers potentially being at risk from explosive atmospheres are regulated by separate regulations (ANSI/AIHA in USA and ATEX in the European Union). The ANSI/AIHA does not require risk assessment whereas it is compulsory for ATEX. There is no standard method to do that assessment. For that purpose we have applied the explosion Layer of Protection Analysis (ExLOPA), which enables semi-quantitative risk assessment for process plants where explosive atmospheres occur. The ExLOPA is based on the original work of CCPS for LOPA taking into account an explosion accident scenario at workplace. That includes typical variables appropriate for workplace explosion like occurrence of the explosive atmosphere, the presence of effective ignition sources, activity of the explosion prevention and mitigation independent protection layers as well as the severity of consequences. All those variables are expressed in the form of qualitative linguistic categories and relations between them are presented using expert based engineering knowledge, expressed in the form of appropriate set of rules. In this way the category of explosion risk may be estimated by the semi-quantitative analysis. However, this simplified method is connected with essential uncertainties providing over or under estimation of the explosion risk and may not provide real output data.In order to overcome this problem and receive more detailed quantitative results, the fuzzy logic system was applied. In the first stage called fuzzification, all linguistic categories of the variables are mapped by fuzzy sets. In the second stage, the number of relation between all variables of analysis are determined by the enumerative combinatorics and the set of the 810 fuzzy rules “IF-THEN” is received. Each rule enables determination of the fuzzy risk level for a particular accident scenario. In the last stage, called defuzzification, the crisp value of final risk is obtained using a centroid method. The final result of the risk presents a contribution of each risk category represented by the fuzzy sets (A, TA, TNA and NA) and is therefore more precise and readable than the traditional approach producing one category of risk only. Fuzzy logic gives a possibility of better insights into hazards and safety phenomena for each explosion risk scenario. It is not possible to receive such conclusions from the traditional ExLOPA calculation results. However it requires the application of computer-aided analyses which may be partially in conflict with a simplicity of ExLOPA.The practical example provides a comparison between the traditional results obtained by ExLOPA and by fuzzy ExLOPA methods.     

Massachusetts v. Environmental Protection Agency: Constructing “Certainty” as Rebuttal

Massachusetts v. Environmental Protection Agency was the first Supreme Court opinion generated specifically as a response to the issue of anthropogenic CO₂ emissions, alleging that Environmental Protection Agency's (EPA) failure to regulate is leading to environmental harms for plaintiffs. This essay examines the majority opinion of Justice Stevens and his use of presumption and burden of proof, within a logic of problematic integration, to construct “certainty” as a rebuttal to and rejection of the “uncertainty” offered by EPA. I examine how this strategically constructed rebuttal to “uncertainty” functions as a declarative act of “certainty,” advancing a proposition whose scientific, legal, or political acceptance could function as a tipping point away from the claims of “uncertainty” used by opponents on this contentious issue. Because of the court's influence, the implications of their “certainty” extend beyond the case and into the broader discussion of climate change science and environmental communication.     

IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty

In this study, an interval-parameter fuzzy-robust programming (IFRP) model is developed and applied to the planning of solid waste management systems under uncertainty. As an extension of the existing fuzzy-robust programming and interval-parameter linear programming methods, the IFRP can explicitly address system uncertainties with complex presentations. Parameters in the IFRP model can be represented as interval numbers and/or fuzzy membership functions, such that the uncertainties can be directly communicated into the optimization process and resulting solution. Furthermore, highly uncertain information for the lower and upper bounds of interval parameters that exist due to the complexity of the real world can be effectively handled through introducing the concept of fuzzy boundary interval. Consequently, robustness of the optimization process and solution can be enhanced. Results of the case study indicate that useful solutions for planning municipal solid waste management practices can be generated. They reflect a compromise between optimality and stability of the study system. Willingness to pay higher costs will guarantee the system stability; however, a desire to reduce the costs will run the risk of potential instability of the system. The results also suggest that the proposed hybrid methodology is applicable to practical problems that are associated with highly complex and uncertain information.     

Dealing with uncertainty in the assessment of human exposure to radioactivity in food and the environment

This paper presents an overview of the approach used to assess radiation dose and risk to members of the public from radioactivity in food and the environment. It describes uncertainties in the process and suggests ways of dealing with them to improve the risk assessment process. It also explains how uncertainty in the assessed dose/risk can be communicated to non-expert audiences such as members of the public. The issues covered in this paper apply to risk assessment of any contaminant and not only radioactivity.     

Info-Gap Decision Theory for Assessing the Management of Catchments for Timber Production and Urban Water Supply

While previous studies have examined how forest management is influenced by the risk of fire, they rely on probabilistic estimates of the occurrence and impacts of fire. However, nonprobabilistic approaches are required for assessing the importance of fire risk when data are poor but risks are appreciable. We explore impacts of fire risk on forest management using as a case study a water catchment in the Australian Capital Territory (ACT) (southeastern Australia). In this forested area, urban water supply and timber yields from exotic plantations are potential joint but also competing land uses. Our analyses were stimulated by extensive wildfires in early 2003 that burned much of the existing exotic pine plantation estate in the water catchment and the resulting need to explore the relative economic benefits of revegetating the catchment with exotic plantations or native vegetation. The current mean fire interval in the ACT is approximately 40 years, making the establishment of a pine plantation economically marginal at a 4% discount rate. However, the relative impact on water yield of revegetation with native species and pines is very uncertain, as is the risk of fire under climate change. We use info-gap decision theory to account for these nonprobabilistic sources of uncertainty, demonstrating that the decision that is most robust to uncertainty is highly sensitive to the cost of native revegetation. If costs of native revegetation are sufficiently small, this option is more robust to uncertainty than revegetation with a commercial pine plantation.