Multi-layered physical factors govern mercury release from soil: Implications for predicting the environmental fate of mercury.

Despite the recognised risks of human exposure to mercury (Hg), the drivers of gaseous elemental mercury (GEM) emissions from the soil remain understudied. In this study, we aimed to identify the environmental parameters that affect the GEM flux from soil and derive the correlations between environmental parameters and GEM flux. Principal component analysis (PCA), factor analysis (FA), and structural equation modelling (SEM) were performed on samples from forest and non-forest sites. The associated results revealed the impact of each environmental parameter on GEM flux, either due to the interaction between the parameters or as a coherent set of parameters. An introductory correlation matrix examining the relationship between two components showed a negative correlation between GEM flux and atmospheric pressure at the two sites, as well as strong correlations between atmospheric pressure and soil temperature. In cases of non-forest open sites with no trees, the PCA and FA results were consistent, indicating that atmospheric pressure, solar irradiance, and soil moisture-defined as primary causality-are largely independent drivers of GEM flux. In contrast, the PCA and FA results for the forest areas with high humidity, tree coverage, and shade were inconsistent, confirming the hypothesis that primary causality affects GEM flux rather than consequent parameters driven by primary causality, such as air and soil temperature and atmospheric humidity. The SEM results provided further evidence for primary and consequent causality as crucial drivers of the GEM flux. This study demonstrates the importance of key primary parameters, such as atmospheric pressure, solar irradiance, and soil moisture content, that can be used to predict mercury release from soils, as well as the importance of consequent parameters, such as air and soil temperature and atmospheric humidity. Monitoring the magnitude of these environmental parameters alone may facilitate the estimation of mercury release from soils and be useful for detailed modelling of soil-air Hg exchange.

Temporal assessment of copper speciation, bioavailability and toxicity in UK freshwaters using chemical equilibrium and biotic ligand models: Implications for compliance with copper environmental quality standards.

Although significant progress has been made in understanding how environmental factors modify the speciation, bioavailability and toxicity of metals such as copper in aquatic environments, the current methods used to establish water quality standards do not necessarily consider the different geological and geochemical characteristics of a given site and the factors that affect copper fate, bioavailability potential and toxicity. In addition, the temporal variation in the concentration and bioavailable metal fraction is also important in freshwater systems. The work presented in this paper illustrates the temporal and seasonal variability of a range of water quality parameters, and Cu speciation, bioavailability and toxicity at four freshwaters sites in the UK. Rivers Coquet, Cree, Lower Clyde and Eden (Kent) were selected to cover a broad range of different geochemical environments and site characteristics. The monitoring data used covered a period of around six years at almost monthly intervals. Chemical equilibrium modelling was used to study temporal variations in Cu speciation and was combined with acute toxicity modelling to assess Cu bioavailability for two aquatic species, Daphnia magna and Daphnia pulex. The estimated copper bioavailability, toxicity levels and the corresponding ecosystem risks were analysed in relation to key water quality parameters (alkalinity, pH and DOC). Although copper concentrations did not vary much during the sampling period or between the seasons at the different sites; copper bioavailability varied markedly. In addition, through the chronic-Cu BLM-based on the voluntary risk assessment approach, the potential environmental risk in terms of the chronic toxicity was assessed. A much higher likelihood of toxicity effects was found during the cold period at all sites. It is suggested that besides the metal (copper) concentration in the surface water environment, the variability and seasonality of other important water quality parameters should be considered in setting appropriately protective environmental quality standards for metals.

Accounting for pH heterogeneity and variability in modelling human health risks from cadmium in contaminated land.

The authors have previously published a methodology which combines quantitative probabilistic human health risk assessment and spatial statistical methods (geostatistics) to produce an assessment, incorporating uncertainty, of risks to human health from exposure to contaminated land. The model assumes a constant soil to plant concentration factor (CF(veg)) when calculating intake of contaminants. This model is modified here to enhance its use in a situation where CF(veg) varies according to soil pH, as is the case for cadmium. The original methodology uses sequential indicator simulation (SIS) to map soil concentration estimates for one contaminant across a site. A real, age-stratified population is mapped across the contaminated area, and intake of soil contaminants by individuals is calculated probabilistically using an adaptation of the Contaminated Land Exposure Assessment (CLEA) model. The proposed improvement involves not only the geostatistical estimation of the contaminant concentration, but also that of soil pH, which in turn leads to a variable CF(veg) estimate which influences the human intake results. The results presented demonstrate that taking pH into account can influence the outcome of the risk assessment greatly. It is proposed that a similar adaptation could be used for other combinations of soil variables which influence CF(veg).

Application of factorial kriging analysis to the FOREGS European topsoil geochemistry database.

Concern about increasing levels of trace elements in the environment has led to the development and implementation of a global programme to determine the current baseline levels of these chemicals in the Earth's surface. The FORum of European Geological Surveys (FOREGS) has recently published a geochemical database for Europe, while progress on similar databases is continuing in other major regions of the world. The FOREGS database comprises multimedia samples collected at a resolution of approximately 72x72 km from 26 European countries. This enables the investigation of the factors governing geochemical variation on a continental scale, potentially allowing contributions of natural processes to be appreciated prior to setting environmental quality standards. This paper investigates the variation in European topsoil geochemistry using factorial kriging analysis, which performs principal components analysis at different spatial scales. The results are interpreted with the aid of a GIS database. Four spatial scales were identified: a nugget component representing variation over a range less than the sampling density; a 'short' scale component with a range of 296 km; an 'intermediate' scale component (875 km); and a 'long' scale component (1750 km). The first three principal components (PCs) of the nugget covariance matrix explained 22.2% of the overall variance, representing local variation in geology, land use, weathering and organic matter content. The first two PCs of the short range structure explained 12.6% of the variance, representing variation according to the major structural divisions of Europe, and to carbonate content. The first PC of the intermediate structure explained 7.2% of the variance and was found to relate to glacial history and Quaternary deposition. Finally, the first three PCs of the long range structure explained 29.6% of the variance and represented variation due to mineralisation, soil texture, climate and possibly anthropogenic contamination.

A spatially-evaluated methodology for assessing risk to a population from contaminated land.

A methodology is proposed which combines quantitative probabilistic human health risk assessment and spatial statistical methods (geostatistics) to produce an assessment of risks to human health from exposure to contaminated land, in a manner which preserves the spatial distribution of risks and provides a measure of uncertainty in the assessment. Maps of soil contaminant levels, which incorporate uncertainty, are produced from sparse sample data using sequential indicator simulation. A real, age-stratified population is mapped across the contaminated area, and intake of soil contaminants by individuals is calculated probabilistically using an adaptation of the Contaminated Land Exposure Assessment (CLEA) model. An abundance of information is contained in results which can be interrogated at the population and individual level, and mapped to provide a powerful visual tool for risk managers, enabling efficient targeting of risk reduction measures to different locations.