Concentration and chemical speciation for the determination of Cu,Zn, Ni,Pb and Cd from refuse dump soils using the optimized BCR sequential extraction procedure

The optimized BCR sequential extraction procedure (proposed by the Standards, Measurements and Testing Programme (SM&T) of the European Union) was applied to seven topsoil samples from refuse dump sites for the determination of Cu, Zn, Ni, Pb and Cd. The metals were partitioned into four operationally defined chemical fractions: acid extractable, reducible, oxidizable and residual, and analysed using flame atomic absorption spectrophotometry, FAAS. The results were compared with total metal concentrations obtained using HNO₃, HClO₄ and HF digestion procedures. Results for total metal analysis ranged from - 15.55 to 43.45 for Cu, 37.15 to 222.35 for Zn, 5.15 to 12.10 for Ni, 10.30 to 93.05 for Pb and 0.35 to 3.75 for Cd in μgg⁻¹ dry weight. The results of the partitioning study showed that zinc prevailed in the more soluble fractions and was distributed between the acid-extractable (32.4%) and the reducible (40.3%) fractions, whereas Pb was distributed mainly in the reducible fraction. Copper and nickel were predominantly associated with the reducible and residual fractions - 53.4, 33.3 and 51.1, 24.1% respectively. The ranking of the four fractions for the partitioning of cadmium was: reducible > residual > oxidizable > acid extractable. The percentage recovery for all metals when comparing total metal concentration with the fractional sum of the optimized BCR procedure, were of the order: Zn(93%) > Pb(83%) > Cu(78) > Cd > (68%) > Ni(63%).     

EFFECTS OF MUNICIPAL WASTEWATER DISCHARGES ON AQUATIC COMMUNITIES,BOISE RWER,IDAHO1

ABSTRACT: Aquatic communities in the Boise River were examined from October 1987 to March 1988 to determine whether they were adversely affected by trace elements in effluents from two Boise wastewater treatment facilities. Trace-element concentrations in the Boise River were less than or near analytical-detection levels and were less than chronic toxicity criteria when detectable. Insect communities colonizing artificial substrates upstream and downstream from the wastewater treatment facilities were strongly associated, and coefficients of community loss indicated that effluents had benign enriching effects. The distributions of trace-element-intolerant mayflies indicated that trace-element concentrations in effluents did not adversely affect intolerant organisms in the Boise River. Condition factor of whitefish was significantly increased downstream from the Lander Street wastewater treatment facility and was significantly decreased downstream from the West Boise wastewater treatment facility.     

Prioritizing Wetland Restoration for Sediment Yield Reduction: A Conceptual Model

In a climate of limited resources, it is often necessary to prioritize restoration efforts geographically. The synoptic approach is an ecologically based tool for geographic prioritization of wetland protection and restoration efforts. The approach was specifically designed to incorporate best professional judgment in cases where information and resources are otherwise limited. Synoptic assessments calculate indices for functional criteria in subunits (watersheds, counties, etc.) of a region and then rank the subunits. Ranks can be visualized in region-scale maps which enable managers to identify areas where efforts optimize functional performance on a regional scale. In this paper, we develop a conceptual model for prioritizing watersheds whose wetlands can be restored to reduce total sediment yield at the watershed outlet. The conceptual model is designed to rank watersheds but not individual wetlands within a watershed. The synoptic approach is valid for applying the sediment yield reduction model because there is high demand for prioritizing disturbed wetlands for restoration, but there is limited, quantitative, accurate information available with which to make decisions. Furthermore, the cost of creating a comprehensive database is prohibitively high. Finally, because the model will be used for planning purposes, and, specifically, for prioritizing based on multiple decisions rather than optimizing a single decision, the consequence of prioritization errors is low. Model results cannot be treated as scientific findings. The conclusions of an assessment are based on judgement, but this judgement is guided by scientific principles and a general understanding of relevant ecological processes. The conceptual model was developed as the first step towards prioritizing of wetland restoration for sediment yield reduction in US EPA Region 4.     

A factor analytic study of attitudinal structure and its impact on rural landowners' access policies

Previous research has shown that rural landowners' hunter access policies are determined in large part by their attitudes towards hunters, legal liability, conservation, and economic incentives. The results of this study support this research and indicate that East Texas, USA, landowners' decisions to allow or restrict access are based, in part, on attitudes toward hunter behavior, hunting as a social activity, leasing as a management practice, and a perceived obligation toward wildlife stewardship. Attitude-based profiles of landowners who adopted one of four access policies are compared.     

DYNAMICS OF SIMULATED EFFECTS OF IRRIGATION OVER DRYLAND FARMING IN SASKATCHEWAN1

ABSTRACT: Irrigation development in Saskatchewan was initiated as an instrument to bring forth regional stability through drought proofing and diversification in the agricultural sector. This development has been surrounded by controversies. Particularly, some critics questioning its economic value to the farmer. In this study, irrigation on a farm is compared as a growth alternative to the expansion of dryland farming. Under relatively conservative machine replacement policies, modest family withdrawals, government subsidized irrigation loans, and relatively favorable gross operating margins, irrigation can be a profitable undertaking in the South Saskatchewan River Basin.     

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.