安全降变原理及C-S-R事故致因新模型

为发展安全科学原理和给事故防控与调查提供新的方法,根据变化对系统安全的影响机制,开展安全降变原理及事故致因新模型研究。首先,提出安全降变原理并解析其内涵及研究意义。其次,基于安全降变原理,给出不同层级安全系统变化的分类实例,并对作业场所事故及其致因重新定义和分类。再次,构建基于安全降变原理的C-S-R事故致因新模型。最后,基于事故案例分析,验证所提出的C-S-R事故致因新模型与安全降变原理的有效性。结果表明,各级安全系统中自发或是受联动的变化超出系统的变化承受水平时,将导致事故的发生。经事故案例分析验证可知,安全降变原理及C-S-R事故致因新模型具有充分的实用性。     

基于24Model的矿工怠工行为 管理模式架构及策略研究

为减少矿工怠工行为,基于24Model研究矿工怠工行为的管理模式架构及策略。首先,基于冰山模型理论分析矿工怠工行为的影响因素;其次,基于24Model和行为修正理论提出集怠工行为识别、行为原因分析、行为管理策略选择和行为修正评估于一体的矿工怠工行为管理模式架构;最后,提出了针对性的管理策略。对于提高煤矿企业矿工的工作绩效具有重要的理论意义和实践价值。     

Material flow analysis of lubricating oil use in California

Petroleum lubricating oils, used throughout the economy, are distinct among petroleum products in their capacity to be recovered and recycled at the end of their useful life. Used lubricating oil is regulated at the state and federal level because of concerns about environmental impacts arising from improper disposal, although rates of recovery are not known. We present a material flow analysis of lubricants through California's economy in the years 2007–2012. We introduce a novel technique for computing aggregate waste generation from a collection of hazardous waste manifest records, and apply it in order to determine a recovery rate for used oil and to estimate the quantity of oil managed informally in the state. The records also offer a detailed view of the fate of used oils after they are recovered. We find that around 62% of lubricants are recoverable at end of life, of which 70–80% is being recovered. This rate shows a slight downward trend. If the trend is accurate, measures should be taken to improve the performance of the used oil management system. Policy opportunities exist to reduce the quantity of oil managed informally through improving access to responsible used oil management methods. These include increasing the collection of used oil from industrial sources as well as “do it yourself” oil changes, expanding in-state reprocessing capacity, and promoting increased out-of-state reprocessing of used oil. Our methods introduce new possibilities to make use of direct observation in material flow analysis, potentially improving data availability and quality and increasing the relevance of material flow methods in policy applications.     

A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

The difficulties of systematic reviews

The need for robust evidence to support conservation actions has driven the adoption of systematic approaches to research synthesis in ecology. However, applying systematic review to complex or open questions remains challenging, and this task is becoming more difficult as the quantity of scientific literature increases. We drew on the science of linguistics for guidance as to why the process of identifying and sorting information during systematic review remains so labor intensive, and to provide potential solutions. Several linguistic properties of peer‐reviewed corpora—including nonrandom selection of review topics, small‐world properties of semantic networks, and spatiotemporal variation in word meaning—greatly increase the effort needed to complete the systematic review process. Conversely, the resolution of these semantic complexities is a common motivation for narrative reviews, but this process is rarely enacted with the rigor applied during linguistic analysis. Therefore, linguistics provides a unifying framework for understanding some key challenges of systematic review and highlights 2 useful directions for future research. First, in cases where semantic complexity generates barriers to synthesis, ecologists should consider drawing on existing methods—such as natural language processing or the construction of research thesauri and ontologies—that provide tools for mapping and resolving that complexity. These tools could help individual researchers classify research material in a more robust manner and provide valuable guidance for future researchers on that topic. Second, a linguistic perspective highlights that scientific writing is a rich resource worthy of detailed study, an observation that can sometimes be lost during the search for data during systematic review or meta‐analysis. For example, mapping semantic networks can reveal redundancy and complementarity among scientific concepts, leading to new insights and research questions. Consequently, wider adoption of linguistic approaches may facilitate improved rigor and richness in research synthesis.     

Study of lignocellulosic biomass ignition properties estimation from thermogravimetric analysis

In the last decade, the use of renewable resources has increased significantly in order to reduce the energetic dependence on fossil fuels, as they have an important contribution to the global warning and greenhouse gasses effect. Because of that, research on biofuels has been increased in the last years as its characteristics of use match those of the conventional fuel's: solid biomass can be used instead of coals, and biodiesel could replace diesel. Research on solid biomass ignition properties has been considerably developed because of the amount of industrial accidents related to the treatment and use of solid biomass (self-ignition, dust explosions, etc.). On the other hand, thermogravimetric analysis (TGA) is becoming and important characterization technique as it can be used to determine a wide spectrum of properties, such as kinetics, composition, proximate analysis, etc. This research aims to combine thermal analysis and ignition properties, by using the TGA to obtain the elemental composition of lignocellulosic biomass and compare those results to Minimum Ignition Energy (MIE) values test output, so a relation between composition and MIE can be found.To achieve this aim, biomass samples from different origins have been used: oil palm wastes (empty fruit bunches, mesocarp fiber and palm kernel shell), agricultural wastes (straw chops) and forestry wastes (wood chips and wood powder). Also, raw materials and torrefied biomass were compared. The hemicellulose/cellulose ratio was calculated and compared to different flammability properties, finding out that the greater the ratio and the lower the onset temperature (temperature at which the pyrolysis reaction accelerates), the lower was the minimum ignition energy. From this basis it was possible to define “tendency areas” that grouped the samples whose MIE values were similar. Three tendency areas were found: high minimum ignition energy, medium minimum ignition energy, and low ignition energy.     

Tracking a half century of media reporting on gray wolves

Natural resource and wildlife managers must balance the disparate priorities of a diversity of stakeholders. To manage these priorities, a firm understanding of topics salient to the public is needed. The media often report on issues of importance to the public; therefore, these reports may be a useful measure of public interest. However, efficient methods for distinguishing diverse topics related to a wildlife management issue reported in the media and changes in the salience of those topics have been lacking. We used latent Dirichlet allocation, a Bayesian mixture model, to quantitatively assess the salience of topics surrounding the gray wolf (Canis lupus), which was reintroduced to Idaho (U.S.A.) in 1995. We analyzed articles published from 1960 to 2015 in an Idaho newspaper. We identified 6 distinct topics associated with gray wolves: policy, hunting, biological status, implementation of management, recovery, and human-wolf conflict. The salience of topics pre- and postreintroduction of wolves (1995) and pre- and postdelisting of wolves from the U.S. Endangered Species Act (2009) differed significantly, underscoring that these events were turning points in how issues were being publicly discussed and framed. Articles written by the local reporters were more likely to report on topics regarding conflict between humans and wolves, whereas articles sourced from a national outlet reported more on topics pertaining to wolf policy and biological status. In the context of managing a contentious, far-ranging, and long-lived wildlife species, our methods can help guide the location and timing of a suite of management strategies (e.g., media relation plans and stakeholder engagement) that promote human-wildlife coexistence across different landscapes.     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

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.