航空器场内失事应急演练评估指标体系与评估方法研究

针对目前我国民用运输机场航空器场内失事应急救援综合演练缺乏有效评估体系的现状，通过对演练过程进行系统分析，构建航空器场内失事应急救援演练评估指标体系，涵盖消防、医疗、公安、媒体应对、运行指挥中心、地服、飞行区7个组织部门的2级指标。结合航空器场内失事救援的业务特点以及指标体系内在逻辑，设计相应的评估方法，对开展的航空器场内失事应急演练进行评估；最后，以国内2个机场的相关应急演练过程为典型示例，进行应用分析。研究结果表明:构建的演练评估指标体系及评估方法能较好地应用于实际应急演练过程，进而在演练评估结果和建议的基础上，实现应急演练的持续改进。     

A product analysis-based study on the mechanism of inflammable gas explosion suppression

To study the mechanism of the suppressing effect of Expanded Aluminium (EA) on the premixed gas explosion, premixed methane-air and propane-air gases were undergone explosion reaction in the presence of EA in a self-designed closed pipeline with the overpressures and the compositions, rates and sensitivities of products analyzed. The results showed that the 9.5% methane-air and 5% propane-air explosions produced peak pressures decreased by 79.3% and 65.6%, and residual methane and propane contents increased by 270% and 560% respectively than without EA. In addition, the results revealed that the explosions of propane in the presence of EA produced less methane and carbon oxides contents, but more ethylene and propylene contents. The simulation showed that H, O, and OH are the key factors affecting the rate of products. The product compositions, together with other parameters, suggested that EA decreased temperature, inhibited chain initiation and propagation reaction, but facilitated chain termination reaction by advancing and accelerating the gas phase and wall destruction reaction of radicals, especially collisions and concentration of key free radicals. This new research method based on the analysis of explosion products can be used for in-depth research into gas explosion features and shed light on the suppressing mechanism of EA in flammable gas explosion.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

Computing sustainable manufacturing index with fuzzy analytic hierarchy process

The growing industrial interest in adopting sustainability programmes has ushered in studies regarding sustainability indicators which have continually flourished in current literature. However, limited attention is given to the development of priority ranking, which is an important input for any adopting firm. This paper presents a hybrid multi-criteria approach in determining priority areas in sustainable manufacturing (SM). Using fuzzy analytic hierarchy process to address uncertainty in hierarchical decision-making, this paper determines SM priority strategies and eventually identifies even lower level strategies. The computed sustainable manufacturing index is presented at both the organizational and operational levels for a real case study of an industrial plastic manufacturing firm. This work provides a detailed and transparent hierarchical decision-making approach based on SM framework, the use of which could be valuable to practicing managers across industries in their pursuit of greater sustainability.     

How certain are we about the certainty-equivalent long term social discount rate?

Theoretical arguments for using a term structure of social discount rates (SDR) that declines with the time horizon have influenced government guidelines in the US and Europe. The certainty equivalent discount rate that often underpins this guidance embodies uncertainty in the primitives of the SDR, such as growth. For distant time horizons the probability distributions of these primitives are ambiguous and the certainty equivalent itself is uncertain. Yet, if a limited set of characteristics of the unknown probability distributions can be agreed upon, ‘sharp’ upper and lower bounds can be defined for the certainty-equivalent SDR. Unfortunately, even with considerable agreement on these features, these bounds are widely spread for horizons beyond 75 years. So while estimates of the present value of intergenerational impacts, including the social cost of carbon, can be bounded in the presence of this ambiguity, they typically remain so imprecise as to provide little practical guidance.     

Co-treatment of fruit and vegetable waste in sludge digesters. An analysis of the relationship among bio-methane generation,process stability and digestate phytotoxicity

The co-digestion of a variable amount of fruit and vegetable waste in a waste mixed sludge digester was investigated using a pilot scale apparatus. The organic loading rate (OLR) was increased from 1.46 kg VS/m³ day to 2.8 kg VS/m³ day. The hydraulic retention time was reduced from 14 days to about 10 days. Specific bio-methane production increased from about 90 NL/kg VS to the maximum value of about 430 NL/kg VS when OLR was increased from 1.46 kg VS/m³ day to 2.1 kg VS/m³ day. A higher OLR caused an excessive reduction in the hydraulic retention time, enhancing microorganism wash out. Process stability evaluated by the total volatile fatty acids concentration (mg/l) to the alkalinity buffer capacity (eq. mg/l CaCO₃) ratio (i.e. FOS/TAC) criterion was <0.1 indicating high stability for OLR <2.46 kg VS/m³ day. For higher OLR, FOS/TAC increased rapidly. Residual phytotoxicty of the digestate evaluated by the germination index (GI) (%) was quite constant for OLR < 2.46 kg VS/m³ day, which is lower than the 60% limit, indicating an acceptable toxicity level for crops. For OLR > 2.46 kg VS/m³ day, GI decreased rapidly. This corresponding trend between FOS/TAC and GI was further investigated by the definition of the GI ratio (GIR) parameter. Comparison between GIR and FOS/TAC suggests that GI could be a suitable criterion for evaluating process stability.     

Hazard property classification of waste according to the recent propositions of the EC using different methods

Hazard classification of waste is a necessity, but the hazard properties (named “H” and soon “HP”) are still not all defined in a practical and operational manner at EU level. Following discussion of subsequent draft proposals from the Commission there is still no final decision. Methods to implement the proposals have recently been proposed: tests methods for physical risks, test batteries for aquatic and terrestrial ecotoxicity, an analytical package for exhaustive determination of organic substances and mineral elements, surrogate methods for the speciation of mineral elements in mineral substances in waste, and calculation methods for human toxicity and ecotoxicity with M factors.In this paper the different proposed methods have been applied to a large assortment of solid and liquid wastes (>1 0 0).Data for 45 wastes – documented with extensive chemical analysis and flammability test – were assessed in terms of the different HP criteria and results were compared to LoW for lack of an independent classification. For most waste streams the classification matches with the designation provided in the LoW. This indicates that the criteria used by LoW are similar to the HP limit values.This data set showed HP 14 ‘Ecotoxic chronic’ is the most discriminating HP. All wastes classified as acute ecotoxic are also chronic ecotoxic and the assessment of acute ecotoxicity separately is therefore not needed. The high number of HP 14 classified wastes is due to the very low limit values when stringent M factors are applied to total concentrations (worst case method). With M factor set to 1 the classification method is not sufficiently discriminating between hazardous and non-hazardous materials. The second most frequent hazard is HP 7 ‘Carcinogenic’. The third most frequent hazard is HP 10 ‘Toxic for reproduction’ and the fourth most frequent hazard is HP 4 “Irritant – skin irritation and eye damage”. In a stepwise approach, it seems relevant to assess HP 14 first, then, if the waste is not classified as hazardous, to assess subsequently HP 7, HP 10 and HP 4, and then if still not classified as hazardous, to assess the remaining properties.The elements triggering the HP 14 classification in order of importance are Zn, Cu, Pb, Cr, Cd and Hg. Progress in the speciation of Zn and Cu is essential for HP 14. Organics were quantified by the proposed method (AFNOR XP X30-489) and need no speciation. Organics can contribute significantly to intrinsic toxicity in many waste materials, but they are only of minor importance for the assessment of HP 14 as the metal concentrations are the main HP 14 classifiers. Organic compounds are however responsible for other toxicological characteristics (hormone disturbance, genotoxicity, reprotoxicity…) and shall be taken into account when the waste is not HP 14 classified.     

Plant blindness and the implications for plant conservation

Plant conservation initiatives lag behind and receive considerably less funding than animal conservation projects. We explored a potential reason for this bias: a tendency among humans to neither notice nor value plants in the environment. Experimental research and surveys have demonstrated higher preference for, superior recall of, and better visual detection of animals compared with plants. This bias has been attributed to perceptual factors such as lack of motion by plants and the tendency of plants to visually blend together but also to cultural factors such as a greater focus on animals in formal biological education. In contrast, ethnographic research reveals that many social groups have strong bonds with plants, including nonhierarchical kinship relationships. We argue that plant blindness is common, but not inevitable. If immersed in a plant‐affiliated culture, the individual will experience language and practices that enhance capacity to detect, recall, and value plants, something less likely to occur in zoocentric societies. Therefore, conservation programs can contribute to reducing this bias. We considered strategies that might reduce this bias and encourage plant conservation behavior. Psychological research demonstrates that people are more likely to support conservation of species that have human‐like characteristics and that support for conservation can be increased by encouraging people to practice empathy and anthropomorphism of nonhuman species. We argue that support for plant conservation may be garnered through strategies that promote identification and empathy with plants.     

Revisiting the national corporate social responsibility index

This paper relies on Gjølberg’s national corporate social responsibility (CSR) index while its purpose is twofold. First, it seeks to extend the methodological instrument for assessing national CSR and, second, it applies the new approach to a much larger pool of countries (n = 86) in an attempt to provide a global CSR outlook. The emergent picture from the study is one of deficient CSR penetration and wide variation among countries where most of the assessed countries are still lagging in the endorsement of international CSR initiatives and schemes. Findings offer fertile ground to theorists and researchers for a deeper investigation of the national specificity of CSR and to further identify institutional determinants that shape the social responsiveness and self-regulation of business entities. The study has also implications for managers and top executives to consider as it infers that the national background can be influential in the development of a CSR agenda and can condition the level of CSR penetration.     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.