Development of a robust chromatographic method for the detection of chlorophenols in cork oak forest soils

A major concern for the cork and wine industry is ‘cork taint’ which is associated with chloroanisoles, the microbial degradation metabolites of chlorophenols. The use of chlorophenolic compounds as pesticides within cork forests was prohibited in 1993 in the European Union (EU) following the introduction of industry guidance. However, cork produced outside the EU is still thought to be affected and simple, robust methods for chlorophenol analysis are required for wider environmental assessment by industry and local environmental regulators. Soil samples were collected from three common-use forests in Tunisia and from one privately owned forest in Sardinia, providing examples of varied management practice and degree of human intervention. These provided challenge samples for the optimisation of a HPLC-UV detection method. It produced recoveries consistently >75 % against a soil CRM (ERM-CC008) for pentachlorophenol. The optimised method, with ultraviolet (diode array) detection is able to separate and quantify 16 different chlorophenols at field concentrations greater than the limits of detection ranging from 6.5 to 191.3 μg/kg (dry weight). Application to a range of field samples demonstrated the absence of widespread contamination in forest soils at sites sampled in Sardinia and Tunisia.     

Impact of growth conditions on transport behavior of E. coli

The aim of this investigation is to determine the effect that growth solution has on the cell surface properties and transport behavior of eleven Escherichia coli isolates through saturated porous media. The two growth solutions used were a standard laboratory growth medium (LB) and a dairy manure extract solution. In general, cells grown in manure extract were more hydrophobic, had a more negative zeta potential, had lower amounts of surface macromolecules, and had lower attachment efficiencies than isolates grown in LB. An inverse relationship between the natural log of zeta potential and the attachment efficiency of the isolates for the cells grown in LB media was the only statistically significant correlation observed between transport behavior and cell characteristics of the isolates. This study shows the need to consider growth conditions when studying bacteria to better mimic the environmental stresses that bacteria undergo in the natural environment. This approach could lead to a better understanding of the behavior of manure-derived bacteria in aquatic and terrestrial environments.     

Predicting estuarine sediment metal concentrations and inferred ecological conditions: an information theoretic approach

Empirically derived relationships associating sediment metal concentrations with degraded ecological conditions provide important information to assess estuarine condition. Resources limit the number, magnitude, and frequency of monitoring activities to acquire these data. Models that use available information and simple statistical relationships to predict sediment metal concentrations could provide an important tool for environmental assessment. We developed 45 predictive models for the total concentrations of copper, lead, mercury, and cadmium in estuarine sediments along the Southern New England and Mid-Atlantic regions of the United States. Using information theoretic model-averaging approaches, we found total developed land and percent silt/clay of estuarine sediment were the most important variables for predicting the presence of all four metals. Estuary area, river flow, tidal range, and total agricultural land varied in their importance. The model-averaged predictions explained 78.4, 70.5, 56.4, and 50.3% of the variation for copper, lead, mercury, and cadmium, respectively. Overall prediction accuracies of selected sediment benchmark values (i.e., effects ranges) were 83.9, 84.8, 78.6, and 92.0% for copper, lead, mercury, and cadmium, respectively. Our results further support the generally accepted conclusion that sediment metal concentrations are best described by the physical characteristics of the estuarine sediment and the total amount of urban land in the contributing watershed. We demonstrated that broad-scale predictive models built from existing monitoring data with information theoretic model-averaging approaches provide valuable predictions of estuarine sediment metal concentrations and show promise for future environmental modeling efforts in other regions.     

The development and application of water management sustainability indicators in Brazil and Scotland

This paper reports the formulation and application of a framework of catchment-level water resource management indicators designed to integrate environmental, economic and social aspects of sustainability. The framework of nine indicators was applied to the River Dee and River Sinos catchments in Scotland and Brazil, respectively, following an indicator selection process that involved inputs from water management professionals in both countries, and a pilot exercise in Scotland. The framework was found to capture a number of key sustainability concerns, and was broadly welcomed by water resource managers and experts as a means of better understanding sustainable water resource management. Issues relating to poor water quality and public water supply were particularly prominent in the findings for the Sinos, while findings for the Dee suggested that more attention might be focused on building institutional capacity and public participation in catchment management. The use of some proxy indicators was required in both catchments due to poor data availability, and this problem may hinder the further development of indicator frameworks that attempt to better integrate environmental, economic and social dimensions of sustainability.