Perceptions toward stewardship among residents living near U.S. Department of Energy Nuclear Facilities

Although stewardship has been widely defined and used in environmental management and planning, there is a dearth of studies that describe how the lay public perceives this concept. A national sample of residents in 14 states who live near DOE nuclear facilities were interviewed to delineate public understanding and awareness of the stewardship program of the U.S. Department of Energy (DOE). This study discusses the findings of the survey and discusses how institutional trust influences public participation and resident’s choices of potential stewards. Almost 40% of the respondents could not define stewardship; those who did, believed that ‘responsibility,’ ‘management,’ and ‘accountability’ are key elements of stewardship. In addition, about a third of the respondents identified Federal groups and the DOE as potential stewards. Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue     

Selectivity in the complexation of actinides by humic substances

The interactions of a range of actinide elements (Th, U, Np, Pu, Am) with humic substances from the Needle's Eye natural analogue site were studied by gel permeation chromatography. Bulk humic substances were isolated by ammonia extraction, followed by dialysis against distilled water and freeze-drying. The gel permeation results suggest that Needle's Eye humic substances can be fractionated into three incompletely resolved fractions with average molecular weights determined by analytical ultracentrifugation around 49 000 for Fraction 1, around 14 700 for Fraction 2 and around 8000 for Fraction 3. Although there are significant differences between the organic matter elution patterns in individual gel permeation experiments, presumably due to differences in column packing, these are much smaller than the differences between metal ions. The uranium that is naturally present in these humic substances is largely bound in the late-eluting fraction. Spikes of the early actinides, including Np and Pu in controlled valency states, have been added to the humic substances, and gel permeation of the spiked humic substances shows that the three humic fractions vary greatly in their effectiveness and selectivity as ligands for early actinides.     

Science in the public process of ecosystem management: lessons from Hawaii, Southeast Asia, Africa and the US Mainland

Partnerships and co-operative environmental management are increasing worldwide as is the call for scientific input in the public process of ecosystem management. In Hawaii, private landowners, non-governmental organizations, and state and federal agencies have formed watershed partnerships to conserve and better manage upland forested watersheds. In this paper, findings of an international workshop convened in Hawaii to explore the strengths of approaches used to assess stakeholder values of environmental resources and foster consensus in the public process of ecosystem management are presented. Authors draw upon field experience in projects throughout Hawaii, Southeast Asia, Africa and the US mainland to derive a set of lessons learned that can be applied to Hawaiian and other watershed partnerships in an effort to promote consensus and sustainable ecosystem management. Interdisciplinary science-based models can serve as effective tools to identify areas of potential consensus in the process of ecosystem management. Effective integration of scientific input in co-operative ecosystem management depends on the role of science, the stakeholders and decision-makers involved, and the common language utilized to compare tradeoffs. Trust is essential to consensus building and the integration of scientific input must be transparent and inclusive of public feedback. Consideration of all relevant stakeholders and the actual benefits and costs of management activities to each stakeholder is essential. Perceptions and intuitive responses of people can be as influential as analytical processes in decision-making and must be addressed. Deliberative, dynamic and iterative decision-making processes all influence the level of stakeholder achievement of consensus. In Hawaii, application of lessons learned can promote more informed and democratic decision processes, quality scientific analysis that is relevant, and legitimacy and public acceptance of ecosystem management.     

Genetic differentiation in a pelagic crustacean (Meganyctiphanes norvegica: Euphausiacea) from the North East Atlantic and the Mediterranean Sea

Meganyctiphanes norvegica (M. Sars)is a pelagic crustacean that plays a key role in marine food webs of North Atlantic Ocean and marginal seas. We studied eight population samples collected in the European Atlantic and Mediterranean Sea. By means of single strand conformation polymorphism analysis (SSCP) and direct sequencing, we investigated a segment of 158 base pairs of the mitochondrial gene coding for the subunit 1 of NADH dehydrogenase. We found 12 sequence variants among the 385 individuals studied. Analysis of molecular variance (AMOVA) showed that 14.75% of the total genetic variability was explained by differences between populations, thus indicating absence of panmixia for these populations. Pairwise comparisons revealed three distinct genetic pools: the first one represented by Cadiz Bay, the second one by the Ligurian Sea, and the third one included all the NE Atlantic samples. We also investigated one population from the Alboran Sea (within the Mediterranean basin, east of the Strait of Gibraltar). This population was found to be genetically intermediate between the NE Atlantic samples and the Ligurian sample, suggesting that the restriction to the gene flow is not associated with the Strait of Gibraltar, but possibly with the Oran–Almeria oceanographic front. The present work indicates that M. norvegica, although endowed with a high dispersal capacity because of its pelagic habit, can develop separate breeding units inside the same oceanic basin (the Atlantic). Furthermore, the Ligurian sample should be considered as a distinct evolutionary entity, separated from the Atlantic population. Received: 2 May 1999 / Accepted: 26 November 1999     

Zinc removal from synthetic waters using magnetite/graphene oxide composites

The removal of heavy metals from wastewater has become a global challenge, which demands the continuous study of efficient and low-cost treatment alternatives such as adsorption. In this research, the removal of zinc was evaluated using batch adsorption processes with nonconventional materials such as graphene oxide (GO), magnetite (MG), and their composites (GO:MG), formulated with three weight ratios (2:1, 1:1, and 1:2). Graphene was synthesized by the modified Marcano method, using pencil lead graphite as a precursor. MG and the composites were synthesized by chemical coprecipitation of ferrous sulfate and ferric chloride. The materials were characterized by Raman and Fourier transform infrared spectroscopies, scanning electron microscopy, X-ray diffraction, and the Brunauer–Emmett–Teller method to determine the functional groups, microstructural and morphological characteristics, and specific surface area. Batch adsorption tests were carried out to optimize the adsorbent dose and contact time with zinc solutions of 10 ppm. Zinc adsorption reached equilibrium at 2 h, with an optimal dose between 0.25 and 1.0 g/L. The maximum zinc removal efficiencies/adsorption capacities were 98.6%/165.6, 83.4%/47.6, 83.5%/21.9, 72.8%/19.9, and 82.2%/9.25 mg/g using GO, 2GO:1MG, 1GO:1MG, 1GO:2MG, and MG, respectively. Furthermore, the analysis of the isotherm and adsorption kinetics models determined that the adsorption processes using MG and the composites fit the Sips and pseudo-second-order models.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

Air pollution characteristics associated with mesoscale atmospheric patterns in northwest continental Europe

An impact related daily air quality index (DAQx), calculated for 15 air quality monitoring stations (traffic, background, and industry) in Belgium, France, Germany and Luxembourg, was compared to mesoscale atmospheric patterns between 2001 and 2007. Meteorological conditions were described by the Hess and Brezowsky synoptic weather classification system and gridded data of the EU FP6 ENSEMBLES project of total precipitation and mean surface temperature. DAQx values indicate sufficient to poor air quality in the urban area of Brussels and at urban traffic stations, as well as satisfactory air quality at the background stations. The air quality index refers to more than 90% to the presence of high PM₁₀, O₃ and NO₂ concentrations. SO₂ and CO play only a minor role. The investigation of weather regimes indicates that zonal and mixed cyclonic circulation regimes are associated with better air quality than meridional and anticyclonic weather regimes. In general, weather regimes with high daily precipitation lead to better air quality than dryer air masses because of lower contribution of PM₁₀ to the air quality index. A trend analysis of weather regimes from 1978 to 2007 shows significant (α = 0.05) positive trends for weather classes associated with lower PM₁₀ concentrations. The results of a case study at a German station examining the relationship between PM₁₀ concentrations and local meteorological quantities (wind speed and precipitation) confirm the results of the regional analysis.     

Tracer Study In an Urban Valley

Results of a series of nighttime tracer experiments conducted during the Autumn of 1966 in the industrialized valley of Johnstown, Pa., are discussed. Quite atypical meteorology and dispersion occur within a classical drainage flow framework. An urban heat island effect is observed creating uniform temperature and wind structures within a layer of air flowing through the valley. Dispersion in the valley at night is comparable to that of neutral conditions over open country.     

Assessing the long-term supply risks for mineral raw materials—a combined evaluation of past and future trends

This paper develops a method for identifying and assessing long-term supply risks for mineral raw materials. The method is based on a combined evaluation of past and future supply and demand trends. By analysing raw material boom and bust cycles over the past 50 years, we have quantified indicators and defined benchmarks for identifying critical market situations. By applying the method, risks for supply shortage may be identified at an early stage. In addition, a numerical evaluation model has been developed for better comparison between various mineral raw materials. Compared to other assessment methods this method uses specific benchmarks for each raw material to better assess supply risks. The method is embedded within a systematic and comprehensive analytical approach.