Factors influencing voting by the united states congress on the national energy act

A myriad of factors, both economic and political, influenced the voting by members of the United States Congress on the 1978 National Energy Act. Determinant factors considered in our analysis included the percentage of residents in the Congressman's district residing in the central city or on farms; the percentage of residents who belong to labor unions; the average level of education of the residents; oil, coal, and natural gas production in the state relative to total domestic production. The results, determined by means of logit analysis, indicate that the impact on low-income energy consumers, the effect on overall employment, the impact on farmers, and the benefits to energy interests, as well as ideology and the subjective perception that the need exists to do something about the energy situation in the United States, were all important explanatory factors.The author is an economist with the United States Department of Energy. The views expressed are those of the author and do not necessarily represent the policies of the Department of Energy or the views of other Department of Energy staff members.     

Public reaction to the risks of energy technology

Implicit in every government decision on energy technology is a trade-off of a certain amount of risk in return for societal benefits. As a result of growing public concern over such risks, environmental analysts are increasingly being requested not only to describe potential adverse consequences but also to quantify their probability. However, this task is frustrated not only by inadequate experience with, and incomplete knowledge of, the causality of environmental impacts, but also by a disparity between individual and societal views of risk. While the societal view is based on objective risk functions andnet societal benefit, individuals tend to rely on subjective judgment, and consider the distribution as well as the amount of benefit. Thus, environmental risk assessments, produced by analysts on behalf of society as a whole, are likely to be quite speculative, and are unlikely to be reliable indicators of the acceptability of risk to the public.     

A CODED ALGORITHM FOR CAPACITY EXPANSION OF A WATER QUALITY MANAGEMENT SYSTEM1

ABSTRACT: This paper describes a mathematical model, an algorithm and a computer program that were specially developed to study the problem of a water quality management system undergoing a rapidly increasing environmental stress. The model output will determine the locations, sizes and the timing of construction of new treatment plants plus an overall treatment plant operating policy so that environmental standards are maintained at a minimum cost. The model, as formulated, is a 0-1 mixed integer programming problem which is solved by decomposing it into a capital budgeting problem (solved by Little's branch and bound algorithm) and an operational policy problem (solved by linear programming). The coded algorithm (in FORTRAN 10) has been tested with a semi-realistic example.     

DETERMINATION OF SEDIMENT YIELD BY TRANSFERRING RAINFALL DATA1

ABSTRACT: A methodology for obtaining the optimal design value to allow for sediment storage in a reservoir is presented for the situation where no data on sediment loads in the incoming streams are available. Information concerning the amount of sediment delivered to the reservoir over its life-time is obtained by a sediment yield model which uses data on rainfall amount and duration obtained from a nearby experimental watershed. Bayesian Decision Theory is used to obtain the optimal storage requirements in order to consider the natural variation of rainfall and the sampling error due to the short rainfall record available. The normally difficult calculations involved were made tractable by the use of simplifications and approximations valid in the context of the problem. Results show that sediment storage requirements can be calculated in this manner and that consideration of the uncertainties involved leads to a storage requirement substantially larger than that calculated without such consideration.     

Slash fire hazard analysis on the Siskiyou National Forest

Potential increase in fire hazard as a result of timber harvesting is a concern of forest managers throughout the United States. Treating fuels can help reduce unacceptable fire hazards. To evaluate alternative fuel treatments, managers need to know their effects on fire hazard. A decision analysis approach to estimating fire hazard in terms of expected burned area was applied to a watershed in the Siskiyou National Forest (Oregon). Three treatment alternatives (do nothing and two levels of yarding unmerchantable material) were evaluated, and the effects of the treatments were projected over a 90-yr period. Initially, the effects of applying a treatment are small. After 50 years of treatment, the most intense alternative can be expected to show almost a 50% reduction in burned area compared to no treatment. The procedure also estimates burned are by fire size and fire intensity classes. Managers may find this useful for estimating expected fire effects associated with a particular fuel treatment regime.     

Use of hydrodynamic models for the management of the Danube Delta wetlands: The case study of Sontea-Fortuna ecosystem

Due to its high biodiversity the Danube Delta, in Romania, is recognized as a UNESCO World Heritage Natural Site and it is listed as a RAMSAR wetland. The Danube River variable discharges have a great impact on the habitats and the overall ecological status of the delta. One of its most vulnerable parts, from both hydrodynamic and morphological point of view is the Sontea-Fortuna wetland located in the upstream of the Danube Delta. Sontea-Fortuna wetland is susceptible to both floods and droughts. On a long term, decision makers in the area need to know which measures to implement and how these will impact/improve the environment.This article presents how a 3D hydrodynamic model can be used as support for making sound decisions regarding the management of deltaic ecosystems. In particular, the methodology is applied on the Sontea-Fortuna wetland. The case study is part of a wider research in the area, which was developed within the EnviroGRIDS EU FP7 research project. EnviroGRIDS aimed at building capacity for scientists, decision-makers and the general public in the Black Sea Catchment, through collection and sharing of environmental data and models at the basin scale.     

Green defaults: Information presentation and pro-environmental behaviour

There is inconsistency in many people's choice of electricity. When asked, they say they prefer a ‘green’ (i.e., environmentally friendly) source for this energy. Yet, although green electricity is available in many markets, people do not generally buy it. Why not? Motivated by behavioural decision research, we argue that the format of information presentation drastically affects the choice of electricity. Specifically, we hypothesise that people use the kind of electricity that is offered to them as the default. We present two natural studies and two experiments in the laboratory that support this hypothesis. In the two real-world situations, there was a green default, and most people used it. In the first laboratory experiment, more participants chose the green utility when it was the default than when ‘grey’ electricity was the default. In the second laboratory experiment, participants asked for more money to give up green electricity than they were willing to pay for it. We argue that changing defaults can be used to promote pro-environmental behaviour. Potential policy-making applications of this work are discussed.     

Land-use forecasting and hydrologic model integration for improved land-use decision support

This paper develops a methodology for integrating a land-use forecasting model with an event scale, rainfall-runoff model in support of improving land-use policy formulation at the watershed scale. The models selected for integration are loosely coupled, structured upon a common GIS platform that facilitates data exchange. The hydrologic model HEC-HMS is calibrated for a specific storm event that occurred within central Washington State. The land-use forecasting model, What If? is implemented to forecast future spatial distributions of low-density residential land-uses under low and high population growth estimates. Forecasted land-use distribution patterns for the years 2015, 2025, and 2050 are then used as land-use data input for the calibrated hydrologic model, keeping all other parameters constant. Impacts to the stream discharge hydrograph are predicted as the study area becomes increasingly developed as forecasted by What If?. The initial results of this integration process demonstrate the synergy that can be generated through the linkage of the selected models. The ability to quantifiably forecast the potential hydrologic implications of proposed land-use policies before their implementation offers land-use decision-makers a valuable tool for discerning which proposed land-use alternatives will be effective at minimizing storm water runoff.     

任务驱动下的建筑施工现场危险源关联规则挖掘

大数据时代的建筑施工现场会产生海量数据信息,如何利用这些数据并从中找出建筑施工现场内外环境中危险源之间的关联关系,对于施工安全尤为重要。利用Apriori算法挖掘施工隐患数据集,生成危险源关联规则;然后依据任务驱动思想令计算机将施工任务映射到相应施工情境下的危险源关联规则中,管理者便可根据具体施工任务搜索到更想要关注的安全规则信息;从这些规则信息的搜索结果发现,隐患的发生常常是由于危险源在时间上的连续或在空间上的交互所致,因此利用这些挖掘出的关联规则可以帮助施工管理人员对施工现场进行有效安全管理。