Muskox status,recent variation,and uncertain future

Ambio - Muskoxen (Ovibos moschatus) are an integral component of Arctic biodiversity. Given low genetic diversity, their ability to respond to future and rapid Arctic change is unknown, although...     

A quantitative integrated assessment of pollution prevention achieved by Integrated Pollution Prevention Control licensing

This paper presents an innovative, quantitative assessment of pollution avoidance attributable to environmental regulation enforced through integrated licensing, using Ireland's pharmaceutical-manufacturing sector as a case study. Emissions data reported by pharmaceutical installations were aggregated into a pollution trend using an Environmental Emissions Index (EEI) based on Lifecycle Assessment methodologies. Complete sectoral emissions data from 2001 to 2007 were extrapolated back to 1995, based on available data. Production volume data were used to derive a sectoral production index, and determine ‘no-improvement’ emission trends, whilst questionnaire responses from 20 industry representatives were used to quantify the contribution of integrated licensing to emission avoidance relative to these trends. Between 2001 and 2007, there was a 40% absolute reduction in direct pollution from 27 core installations, and 45% pollution avoidance relative to hypothetical ‘no-improvement’ pollution. It was estimated that environmental regulation avoided 20% of ‘no-improvement’ pollution, in addition to 25% avoidance under business-as-usual. For specific emissions, avoidance ranged from 14% and 30 kt a^− 1 for CO₂ to 88% and 598 t a^− 1 for SO_x. Between 1995 and 2007, there was a 59% absolute reduction in direct pollution, and 76% pollution avoidance. Pollution avoidance was dominated by reductions in emissions of VOCs, SO_x and NO_x to air, and emissions of heavy metals to water. Pollution avoidance of 35% was attributed to integrated licensing, ranging from between 8% and 2.9 t a^− 1 for phosphorus emissions to water to 49% and 3143 t a^− 1 for SO_x emissions to air. Environmental regulation enforced through integrated licensing has been the major driver of substantial pollution avoidance achieved by Ireland's pharmaceutical sector — through emission limit values associated with Best Available Techniques, emissions monitoring and reporting requirements, and performance targets specified in environmental management plans. This compliant sector offers a positive, but not necessarily typical, case study of IPPC effectiveness.     

Evaluating the role of environmental quality in the sustainable rural economic development of England

The issue of the sustainable development of rural economies in England has recently received considerable attention. This is because many of the poorest areas in the country are rural, often of high environmental quality, but suffering from high unemployment and a lack of services and facilities. The rapid decline in agricultural incomes and in-migration of affluent urban workers since 1990 has exacerbated economic inequality in such areas. A number of factors have the potential to drive rural development and this paper applies, and considers, the feasibility of a method from the USA for combining economic and environmental variables in a regional growth model to examine the hypothesis that environmental quality is an important determinant of sustainable rural development in England. The model output suggests that, although environmental quality does play a role in sustainable rural development in England there are other, more important, factors driving development. These include business and communications infra-structure, the degree and opportunities for commuting and underlying employment prospects. The robustness and limitations of the method for combining economic and environmental variables is discussed in relation to the spatial interrelatedness of Local Authority Districts in England, and conclusions are drawn about areas for refinement and improvement of the method.

Compositional changes of crude oil SARA fractions due to biodegradation and adsorption on colloidal support such as clays using Iatroscan

The compositional changes of saturates, aromatics, resins and asphaltenes (SARA) fractions in aqueous clay/oil microcosm experiments with a hydrocarbon-degrading microorganism community were analysed using Iatroscan. The clay mineral samples used in this study were organomontmorillonite, acid-activated montmorillonite and K, Ca, Zn and Cr montmorillonites produced by modifying the original montmorillonite sample. The evaluation and quantification of biodegradation and adsorption were carried out using a combination of the Iatroscan and gravimetric analysis. The SARA compositions in the presence of organomontmorillonite and acid-activated montmorillonite after incubation follow the same pattern in which the aromatic fraction is higher than the other fractions unlike in the presence of unmodified, K, Ca and Zn montmorillonites, where the saturates fraction is higher than the other fractions. Changes in SARA fractions due to biodegradation seemed to occur most in the presence of unmodified and calcium montmorillonites; hence, the removal of SARA fractions due to biodegradation was significant and enhanced in the presence of these two clay samples. However, biodegradation in the presence of organomontmorillonite and acid-activated and Cr montmorillonites was hindered. The study indicated that Cr montmorillonite adsorbed resins most, whereas Zn and K montmorillonites adsorbed aromatics most after incubation.     

Meta‐analytic tests of relationships between organizational justice and citizenship behavior: testing agent‐system and shared‐variance models

Research on the unique effects of different types of perceived fairness on citizenship behavior that benefits individuals (organizational citizenship behavior (OCB‐I) and organizations (OCB‐O) has produced mixed results. We assert that how OCB‐O and OCB‐I are conceptualized affects the patterns of results, and we hypothesize that, when OCB is conceptualized appropriately, an agent‐system model is supported (interactional and procedural justice are the strongest unique predictors of OCB‐I and OCB‐O, respectively). We also hypothesize that shared variance among the justice types explains additional variance in OCB. Analyses of semi‐ partial correlations conducted on meta‐analytic coefficients supported our hypotheses. Theoretical and practical implications are discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Industrial pollution,spatial stigma and economic decline: the case of Asopos river basin through the lens of local small business owners

This paper explores the notion of environmentally induced spatial stigma through an analysis of data from interviews across public attitudes to pollution within the Asopos river basin in central Greece. The area has a 40 year plus history of legal and illicit industrial waste disposal and public debate on the associated environmental degradation. The study focuses on the perceptions and beliefs of a sector of the community likely to be directly and negatively affected by stigma, that is small business owners in the tourism and hospitality sector. The qualitative analysis explores awareness and viewpoints on environmental degradation and water quality within the local context, implications for the local economy and the individual's own enterprise, views on industrial environmental management as well as corporate responsibility and future prospects for the environmental problems of Asopos. Findings reveal a noticeable variation in views on industrial pollution and ecosystem deterioration among the respondents, but overall a strong environmentally induced stigmatization of the area. They also uncover an information asymmetry and lack of credible commitment by government bodies and industry members in disclosing accurate information, a situation likely to increase speculation and uncertainty within the community. The paper concludes by addressing implications of the findings to policy-making and managerial considerations, along with future research perspectives which aim to increase considerations of sustainability aspects for local development.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

Inexpensive substrate sampler for macroinvertebrates

Assessment of aquatic macroinvertebrates is a critical component of many watershed monitoring programs and passive samplers are often used to collect long-term site data, especially in environments where active sampling is not possible. However, standard passive samplers can be expensive and lost in extreme conditions. We developed a sampler using plastic soda bottles (PSB) filled with river rock and compared its effectiveness with standard Hester-Dendy samplers in both lotic and lentic environments. Abundance, taxa richness, and macroinvertebrate composition showed no significant differences between sampler types in either habitat type. PSB samplers, which can be constructed for less than one dollar each, collected the same number of organisms and represented the same diversity as Hester-Dendy devices that cost around $38 each. In studies where funds are limited, PSB samplers appear to be suitable for passive monitoring.