Exploring the role of emotional intelligence in behavior-based safety coaching

INTRODUCTION: Safety coaching is an applied behavior analysis technique that involves interpersonal interaction to understand and manipulate environmental conditions that are directing (i.e., antecedent to) and motivating (i.e., consequences of) safety-related behavior. A safety coach must be skilled in interacting with others so as to understand their perspectives, communicate a point clearly, and be persuasive with behavior-based feedback. METHOD: This article discusses the evidence-based "ability model" of emotional intelligence and its relevance to the interpersonal aspect of the safety coaching process. RESULTS: Emotional intelligence has potential for improving safety-related efforts and other aspects of individuals' work and personal lives. Safety researchers and practitioners are therefore encouraged to gain an understanding of emotional intelligence and conduct and support research applying this construct toward injury prevention.     

A safety self-management intervention for mining operations

PROBLEM: This quasi-experimental field study examined the efficacy of a safety self-management process to increase safety-related work practices in mining operations. METHODS: After a 7-week baseline, 15 miners participated in a safety self-management training and education presentation. The participants in a prebehavior condition (n=8) recorded their intentions to engage in specific percentages of safety-related work behaviors before starting their shift for the day. In contrast, participants in a postbehavior condition (n=7) recorded their percentages of safety-related work behaviors after their shift for the day. RESULTS: During withdrawal (4 weeks), the miners did not complete any self-monitoring forms. Based on 10,905 behavioral observations, safety self-management was effective at increasing the frequency of safety-related behavior (p<.05). For the prebehavior condition, the mean percent safe score across three target behaviors increased 34.8% during intervention. Similarly, in the postbehavior condition, the mean percent safe score across three target behaviors increased 40.1% during intervention. IMPACT ON INDUSTRY: The results suggest that employees who work in relative isolation or have little oversight, compared to traditional industrial workers, may benefit from a process by which they can systematically observe themselves.     

SMART-SREC: A stochastic model of the New Jersey solar renewable energy certificate market

Markets for solar renewable energy certificates (SRECs) are gaining in prominence in many states, stimulating growth of the US solar industry. However, SREC market prices have been extremely volatile, causing high risk to participants and potentially less investment in solar power generation. Such concerns necessitate the development of realistic, flexible and tractable models of SREC prices that capture the behavior of participants given the rules that govern the market. We propose an original stochastic model called SMART-SREC to fill this role, building on established ideas from the carbon pricing literature, and including a feedback mechanism for generation response to prices. We calibrate the model to the New Jersey market and backtest it, analyzing parameter sensitivity and demonstrating its ability to reproduce historical dynamics. Finally, we run simulations to investigate the role and impact of regulatory parameters, thus providing insight into the crucial role played by market design.     

Non-cooperative and cooperative climate policies with anticipated breakthrough technology

Global warming can be curbed by pricing carbon emissions and thus substituting fossil fuel with renewable energy consumption. Breakthrough technologies (e.g., fusion energy) can reduce the cost of such policies. However, the chance of such a technology coming to market depends on investment. We model breakthroughs as an irreversible tipping point in a multi-country world, with different degrees of international cooperation. We show that international spill-over effects of R&D in carbon-free technologies lead to double free-riding, strategic over-pollution and underinvestment in green R&D, thus making climate change mitigation more difficult. We also show how the demand structure determines whether carbon pricing and R&D policies are substitutes or complements.     

A heuristic for setting effective standards to ensure global environmental sustainability

Most environmental professionals and decision-makers, and certainly the public at large, hold the view that the integrity of earth’s natural environment will be conserved for posterity and sustainable development achieved if all the nations rigorously enforced their environmental and emission standards. It is argued in this paper that this view, sincerely held by many as an “axiomatic truth,” is mistaken and misplaced. This is because as a biogeochemical entity the Earth has limited self-regenerative capacity (SRC) to cope with anthropogenic pollution, and all kinds of environmental problems ensue when that limit is exceeded. Indeed, mounting environmental problems now occurring on all fronts amply testify to the fact that the limit has already been exceeded. They also provide necessary and sufficient proof that environmental and emission standards have been woefully inadequate for protecting earth’s natural environment and life-support systems. It is argued that true global environmental sustainability will be achieved, paving the way to true global sustainable development, if and only if global environmental and emission standards are set so that global anthropogenic pollution does not exceed the limit of earth’s natural SRC to cope with such pollution. These and related issues are discussed in this paper. A simple mathematical model using basic mathematics is also presented to explain how the phenomenon of “positive feedback” works in some of the environmental problems to exacerbate environmental degradation and progressively to erode nature’s SRC.

硫磺回收装置酸性气配风控制方案探讨

主要介绍采用克劳斯制硫工艺的硫磺回收装置制硫转化炉配风调节的几种控制方案以及气体分析仪对稳定操作。提高硫回收率所起的重要作用。     

Exploring alternative states in ecological systems with a qualitative analysis of community feedback

Demonstrating and predicting the existence of alternative states in natural communities remains a challenge for ecologists and is essential for resource managers. Positive feedback is often presented as central in maintaining alternative ecosystem states, but no formal approach relates this part of theory to real world applications. Through qualitative modelling of community response to long-term perturbations, we define generic mechanistic links between positive feedback and the occurrence of alternative states. Positive feedback diminishes a system's overall resistance to change, and can create and maintain correlations in the relative abundance of variables that coincide with alternative states.Through specific models of the dynamics of Tasmanian rocky-reef communities, which are affected by climate and fishing and persist within alternative states, we demonstrate the ability of our theoretical framework to predict alternative states in ecosystems and inform management intervention. A qualitative knowledge of community structure permits a thorough analysis of system feedback and an assessment of the potential for an ecosystem to exhibit alternative states. We illustrate the usefulness of the approach to inform management priorities, and to focus monitoring and field research on the key drivers of ecosystem dynamics.     

Adaptive Management on Public Lands in the United States: Commitment or Rhetoric?

Adaptive management (AM) is the process of implementing land management activities in incremental steps and evaluating whether desired outcomes are being achieved at each step. If conditions deviate substantially from predictions, management activities are adjusted to achieve the desired outcomes. Thus, AM is a kind of monitoring, an activity that land management agencies have done poorly for the most part, at least with respect to ground-based monitoring. Will they do better in the future? We doubt it unless costs, personnel, and future commitment are seriously addressed. Because ecosystem responses to management impacts can ripple into the distant future, monitoring programs that address only the near future (e.g., 10–20 years), are probably unreliable for making statements about resource conditions in the distant future. We give examples of this. Feedback loops between ecosystem response and adjustment of management actions are often broken, and therefore AM again fails. Successful ground-based monitoring must address these and other points that agencies commonly ignore. As part of the solution, publics distrustful of agency activities should be included in any monitoring program.     

Grass feedbacks on fire stabilize savannas

Savannas commonly consist of a discontinuous cover of overstory trees and a groundcover of grasses. Savanna models have previously demonstrated that vegetation feedbacks on fire frequency can limit the density of overstory trees, thereby maintaining savannas. Positive feedbacks of either savanna trees alone or trees and grasses together on fire frequency have been shown to result in a stable savanna equilibrium. Grass feedbacks on fire frequency, in contrast, have resulted in stable equilibria in either a grassland or forest state, but not in a savanna. These results, however, were derived from a system of differential equations that assumes that fire occurrence is strictly deterministic and that vegetation losses due to fire are continuous in time. We develop an alternative formulation of the grass-fire feedback model that assumes that fires are discrete and occur stochastically in time to examine the influence of these assumptions on the predicted state of the system. We show that incorporating fire as a discrete event can produce a recurring temporal refuge in which both grass and trees co-occur in a stable, bounded savanna. In our model, tree abundance is limited without invoking demographic bottlenecks in the transition from fire-sensitive to fire-resistant life history stages. An increasing strength of grass feedback on fire results in regular, predictable fires, which suggests that the system can also be modeled using a set of difference equations. We implement this discrete system using modified Leslie/Gower difference equations and demonstrate the existence of a bounded savanna state in this model framework. Our results confirm the potential for grass feedbacks to result in stable savannas, and indicate the importance of modeling fire as a discrete event rather than as a loss rate that is continuous in time.     

Emergy and emergy algebra explained by means of ingenuous set theory

Emergy is an important concept that has originated several effects in ecology, systems ecology and sustainability science. Its communication, however, has always presented several problems, since it does not follow the same rules of conservation as other energy-based approaches. Attempts have been made to clarify emergy by means of more formal/mathematical approaches, but the problem persists. In this paper, we have introduced a view of emergy and of its algebra based on ingenuous set theory. By means of this simple tool, emergy can be defined as the set of solar exergy that is directly and indirectly necessary to make a product. The operation that correctly sums the emergy “carried” by the inputs to a process is the union. This definition and the operation of union are able to account for all the rules of emergy algebra.