Lifetime exposure to arsenic in residential drinking water in Central Europe.

OBJECTIVE: Methods and results are presented for an arsenic exposure assessment integral to an epidemiological case-control study of arsenic and cancer-the European Commission funded ASHRAM (Arsenic Health Risk Assessment and Molecular Epidemiology) study carried out in some counties of Hungary, Romania and Slovakia. METHODS: The exposure history of each participant (N = 1,392) was constructed by taking into account how much water they consumed (as water, in drinks and in food), sources of drinking water in their various residences over their lifetime, and the concentrations of arsenic in their various water supplies measured by Hydride Generation-Atomic Absorption Spectrometry (HG-AAS). Concentrations of arsenic in previous water supplies were either derived from contemporary analyses of the same source, or from routine historical data from measurements performed by the authorities in each country. Using this approach, 80% of the recorded lifetime residential history was matched to an arsenic concentration. Seven indices of current, life time, and peak exposure were calculated. RESULTS: The exposure indices were all log-normally distributed and the mean and median lifetime average concentrations were in Hungary 14.7 and 13.3 microg l(-1), Romania 3.8 and 0.7 microg l(-1) and in Slovakia 1.9 and 0.8 microg l(-1), respectively. Overall 25% of the population had average concentrations over 10 microg l(-1) and 8% with exposure over 50 microg l(-1). CONCLUSIONS: Careful assessment of arsenic in drinking water supplies (both current and previous) enabled the majority of study participants' cumulative lifetime of potential exposure to arsenic in residential water to be characterised

Predictive modeling of plant uptake of Pb and Cd : Implications of aerial deposition and the origin of parameterisation data

We developed ordinary least squares regression models to predict uptake of cadmium and lead, two metals that are of public health significance because of their toxicity, in the edible tissues of lettuce. Models were parameterised using data on soil metal concentration, pH, and organic carbon. To assess the impact of physical contamination in form of aerial deposition and soil-splash on the metal concentration in lettuce, separate linear regression models were parameterised for indoor- and outdoor-grown lettuce, assuming the physical contamination to be negligible for indoor conditions. Both Cd models showed high model fit and strong predictive performance, when tested on an independent dataset, suggesting uptake via roots to be dominant. For Pb, the indoor model performed better than the outdoor model, indicating that physical contamination, contributes significantly to metal concentration in lettuce leaves. Our results highlight the importance of the parameterisation data when developing uptake models for predictions and risk assessment. Regression models for predicting Pb concentration in lettuce based on indoor data should not be used for predicting lettuce concentrations cultivated in outdoor conditions unless the contribution of physical contamination is explicitly accounted for

Using spatial-stream-network models and long-term data to understand and predict dynamics of faecal contamination in a mixed land-use catchment

Thanks to the Scottish Government's Hydro Nation Scholars Programme for funding AJN to do this research. Thanks to the Drinking Water Quality Regulator (DWQR) for Scotland for providing information about private water supplies and septic tanks in the Tarland.Peer reviewedPostprin

Students' participation in collaborative research should be recognised

Letter to the editor