Ethanol fuels: Energy security,economics, and the environment

Problems of fuel ethanol production have been the subject of numerous reports, including this analysis. The conclusions are that ethanol: does not improve U.S. energy security; is uneconomical; is not a renewable energy source; and increases environmental degradation. Ethanol production is wasteful of energy resources and does not increase energy security. Considerably more energy, much of it high- grade fossil fuels, is required to produce ethanol than is available in the energy output. About 72% more energy is used to produce a gallon of ethanol than the energy in a gallon of ethanol. Ethanol production from corn is not renewable energy. Its production uses more non- renewable fossil energy resources in growing the corn and in the fermentation/distillation process than is produced as ethanol energy. Ethanol produced from corn and other food crops is also an unreliable and therefore a non-secure source of energy, because of the likelihood of uncontrollable climatic fluctuations, particularly droughts which reduce crop yields. The expected priority for corn and other food crops would be for food and feed. Increasing ethanol production would increase degradation of agricultural land and water and pollute the environment. In U.S. corn production, soil erodes some 18- times faster than soil is reformed, and, where irrigated, corn production mines water faster than recharge of aquifers. Increasing the cost of food and diverting human food resources to the costly and inefficient production of ethanol fuel raise major ethical questions. These occur at a time when more food is needed to meet the basic needs of a rapidly growing world population.     

Civilians under fire: evacuation behaviour in north Israel during the Second Lebanon War

This paper seeks to understand evacuation behaviour in a case of spontaneous evacuation. During the Second Lebanon War of 2006, more than one‐third of residents in north Israel spontaneously evacuated—the remainder stayed in situ. Using a telephone survey of 665 respondents residing in north Israel, we were able to characterise the behaviour of evacuees and non‐evacuees. The main reasons cited for evacuating were fear of injury to self or family, the effect on children, inability to remain in a protective space, and family pressure. The main reasons cited for remaining at home were no suitable alternative, did not perceive a high level of danger, had to go to work, and there is no place like home. There were no significant differences with regard to most socio‐demographic characteristics of the population. These findings should aid emergency managers in preparing the population for a future emergency and in engaging in effective dialogue with the population during an emergency on the evacuation option.     

Job embeddedness and voluntary turnover in the face of job insecurity

Two important contributions to the understanding of voluntary turnover are the ideas that employees become embedded in a net or web of restraining forces on- and off-the-job and that they experience varying degrees of control and desire that yield proximal withdrawal states explaining turnover motivations. We build on these ideas in two multi-wave studies to study job insecurity, one of the most common work stressors and top concerns among employees around the world. Study 1 demonstrates that job search mediates the positive relationship between job insecurity and voluntary turnover, and that employees higher in on-the-job embeddedness are less likely to search for jobs despite job insecurity. Study 2 demonstrates that turnover intention mediates the positive relationship between job insecurity and voluntary turnover, and that employees higher in on-the-job embeddedness are less likely to contemplate quitting despite job insecurity. However, off-the-job embeddedness had opposite interactive effects, exacerbating the relationship of job insecurity with turnover.     

The mediating role of job characteristics in job redesign interventions: A serendipitous quasi‐experiment

The aim of this paper is to examine the mediating role played by five key job characteristics in the relationship between employee participation in a job redesign intervention and employee well‐being. In studies of job redesign interventions, it has been assumed that any effects of employee participation in job redesign on well‐being are a result of changes in job characteristics rather than participation in change per se. It is therefore important to statistically test for mediation in job redesign intervention studies to help establish that the change in job characteristics is the mechanism through which job redesign interventions work. However, this has rarely been tested directly, either because data to allow tests of mediation have not been collected (e.g. assessments of job characteristics) or because data have been collected but mediation has not been tested using accepted procedures. This makes it unclear whether changes in job characteristics explain the effects. Results from multilevel analyses of a longitudinal 9‐month long serendipitous quasi‐experimental participative job redesign intervention showed that changes in job control, participation, skill utilization and feedback, but not task obstacles, were sufficient to account for the relationship between the intervention and employee well‐being. Copyright © 2009 John Wiley & Sons, Ltd.     

Prioritizing prevention opportunities in the Washington State construction industry, 2003-2007

Objective

This study compares construction industry groups in Washington State by injury severity and cost, and ranks industry groups according to potential for prevention.

Methods

All Washington State workers' compensation compensable claims with date of injury between 2003 and 2007 were classified into North American Industrial Classification System (NAICS) industry groups. Claims were then aggregated by injury type and industry groups were ranked according to a prevention index (PI). The PI is the average of the rank orders of the claim count and the claim incidence rate. A lower PI indicates a higher need for prevention activities. The severity rate was calculated as the number of days of time loss per 10,000 full-time equivalents (FTEs).

Results

For all injury types, construction industry groups occupy 7 of the top 15 PI ranks in Washington State. The severity rate among construction industry groups was twice that for non-construction groups for all injury types. Foundation, structure, and building exterior contractors (NAICS 2381) ranked highest in prevention potential and severity among construction industry groups for most common injury types including falls from elevation, fall on same level, struck by/against, and musculo-skeletal disorders of the neck, back, and upper extremity (WMSDs). Median claim costs by injury type were generally higher among construction industry groups.

Conclusions

The construction industry in Washington State has a high severity rate and potential for prevention. The methods used for characterizing these industry groups can be adapted for comparison within and between other industries and states.

Impact on Industry

These data can be used by industry groups and employers to identify higher cost and higher severity injury types. Knowledge about the relative frequencies and costs associated with different injury types will help employers and construction industry associations make better informed decisions about where prevention efforts are most needed and may have the greatest impact. The results of this study can also be used by industry stakeholders to cooperatively focus on high cost and high severity injuries and explore best practices, interventions, and solutions as demonstrated by efforts to prevent musculoskeletal disorders in masonry (Entzel, Albers, & Welch, 2007). Initiating construction industry groups to focus on high cost and high severity injuries may also help prevent other types of injuries.     

Differentiating antecedents of organizational commitment: a test of March and Simon's model

Recent theory regarding the nature of organizational commitment suggests that viewing it as comprised of two dimensions, value commitment and continuance commitment, is of theoretical and practical value. This field study found the differential antecedents of these two commitment dimensions to be consistent with the March and Simon (1958) framework using the two-dimensional organizational commitment questionnaire from Mayer and Schoorman (1992). Organizational tenure, retirement benefits, education, and age were more highly correlated with continuance commitment, while felt participation, perceived prestige, job involvement, and role ambiguity were more highly correlated with value commitment. Analysis using LISREL 7 supported the pattern of relationships between the antecedents and the two commitment dimensions. © 1998 John Wiley & Sons, Ltd.     

Amounts of pesticides reaching target pests: Environmental impacts and ethics

Less than 0.1% of pesticides applied for pest control reach their target pests. Thus, more than 99.9% of pesticides used move into the environment where they adversely affect public health and beneficial biota, and contaminate soil, water, and the atmosphere of the ecosystem. Improved pesticide application technologies can improve pesticide use efficiency and protect public health and the environment.     

Growth kinetics and competition between Methanosarcina and Methanosaeta in mesophilic anaerobic digestion.

Methanosarcina species with a high maximum specific growth rate (mumax) and high half-saturation coefficient (KS) and Methanosaeta species with a low mumax and low KS are the only known aceticlastic methanogens. Because of Methanosaeta's low KS, the low acetate concentrations in conventional, mesophilic anaerobic digestion yield Methanosaeta dominance. However, Methanosarcina absorbs increases in acetate more efficiently and thus promotes more stable digestion. This paper tests the hypothesis that decreasing digester feeding frequencies can increase Methanosarcina predominance. Two acetate-fed reactors were established at a 17-day solids retention time. One reactor was fed hourly, and one was fed once daily. Microscopic and molecular methods were used to verify that the hourly fed reactor enriched for Methanosaeta, while the daily fed reactor enriched for Methanosarcina. Growth and substrate-use kinetics were measured for each reactor. A digester overload condition was simulated, and the Methanosarcina-enriched reactor was found to perform better than the Methanosaeta-enriched reactor. These findings indicate that Methanosarcina dominance can be achieved with infrequent feedings, leading to more stable digestion.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.