Environment Canada recently developed a clean method suitable for sampling trace levels of metals in surface waters. The results of sampling for total mercury in the Laurentian Great Lakes between 2003 and 2009 give a unique basin-wide perspective of concentrations of this important contaminant and represent improved knowledge of mercury in the region. Results indicate that concentrations of total mercury in the offshore regions of the lakes were within a relatively narrow range from about 0.3 to 0.8 ng/L. The highest concentrations were observed in the western basin of Lake Erie and concentrations then declined towards the east. Compared to the offshore, higher levels were observed at some nearshore locations, particularly in lakes Erie and Ontario. The longer-term temporal record of mercury in Niagara River suspended sediments indicates an approximate 30% decrease in equivalent water concentrations since 1986.

Predictions of surface water exposure to “down-the-drain” chemicals are presented which employ grid-based spatially-referenced data on average monthly runoff, population density, country-specific per capita domestic water and substance use rates and sewage treatment provision. Water and chemical load are routed through the landscape using flow directions derived from digital elevation data, accounting for in-stream chemical losses using simple first order kinetics. Although the spatial and temporal resolution of the model are relatively coarse, the model still has advantages over spatially inexplicit “unit-world” approaches, which apply arbitrary dilution factors, in terms of predicting the location of exposure hotspots and the statistical distribution of concentrations. The latter can be employed in probabilistic risk assessments. Here the model was applied to predict surface water exposure to “down-the-drain” chemicals in China for different levels of sewage treatment provision. Predicted spatial patterns of concentration were consistent with observed water quality classes for China.

Annual and weekly mercury (Hg) concentrations, precipitation depths, and Hg wet deposition in the Great Lakes region were analyzed by using data from 5 monitoring networks in the USA and Canada for a 2002–2008 study period. High-resolution maps of calculated annual data, 7-year mean data, and net interannual change for the study period were prepared to assess spatial patterns. Areas with 7-year mean annual Hg concentrations higher than the 12 ng per liter water-quality criterion were mapped in 4 states. Temporal trends in measured weekly data were determined statistically. Monitoring sites with significant 7-year trends in weekly Hg wet deposition were spatially separated and were not sites with trends in weekly Hg concentration. During 2002–2008, Hg wet deposition was found to be unchanged in the Great Lakes region and its subregions. Any small decreases in Hg concentration apparently were offset by increases in precipitation.

Llobregat River (North-East Spain) is the most important drinking water source for Barcelona and its surrounding area. As one of the only water sources in the area the river water have been overexploited and effluents from more than 30 urban wastewater treatment plants, industries and agriculture runoffs have been discharged into the river. This article reviews the presence of emerging contaminants published during the last decades, emphasizing on the observed effects on ecosystems caused by the contamination. Pesticides, surfactants, estrogens, pharmaceuticals and personal care products and even abuse drugs are the main groups detected in different studies, reporting alterations in species composition, abundance or biomass and endocrine disruption measured by alterations in enzymatic activity or specific protein production. The information available provides an overview of the river status according to the Water Framework Directive.

The paper presents an analysis of measured riverine concentrations of 16 common organic water contaminants. From observed concentrations we back-calculate emissions and chemical half lives through a simple inverse model. The analysis does not allow identifying a single half life/emission factor combination, but a set of combinations which are Pareto-optimal (or “non-dominated”). The approach is shown to provide a rational basis for the screening of chemicals in rivers: with reference to the 16 chemicals considered here, estimated emission factors and half lives are consistent with the ones reported in other studies. For more precise estimates, prior knowledge about either emission factors or half lives is necessary. For the considered chemicals, loads to European seas can be subsequently estimated with an uncertainty usually within a factor of 2. The approach can be proposed for the inventorying of catchment-specific chemical pollutant emissions required for European environmental policies.

Groundwater contamination by leachate is the most damaging environmental impact over the entire life of a hazardous waste landfill (HWL). With the number of HWL facilities in China rapidly increasing, and considering the poor status of environmental risk management, it is imperative that effective environmental risk management methods be implemented. A risk assessment indices system for HWL groundwater contamination is here proposed, which can simplify the risk assessment procedure and make it more user-friendly. The assessment framework and indices were drawn from five aspects: source term, underground media, leachate properties, risk receptors and landfill management quality, and a risk assessment indices system consisting of 38 cardinal indicators was established. Comparison with multimedia models revealed that the proposed indices system was integrated and quantitative, that input data for it could be easily collected, and that it could be widely used for environmental risk assessment (ERA) in China.

Shanxi Province is one of the regions in northern China where endemic arsenicosis occurs. In this study, stepwise logistic regression was applied to analyze the statistical relationships of a dataset of arsenic (As) concentrations in groundwaters with some environmental explanatory parameters. Finally, a 2D spatial model showing the potential As-affected areas in this province was created. We identified topography, gravity, hydrologic parameters and remote sensing information as explanatory variables with high potential to predict high As risk areas. The model identifies correctly the already known endemic areas of arsenism. We estimate that the area at risk exceeding 10μgL⁻¹ As occupies approximately 8100km² in 30 counties in the province.

Total mercury concentrations are presented for 19 Swedish watercourses 2000–2010, together with an analysis of factors affecting these concentrations in space and time. Organic matter (OM) measured as absorbance at 420nm (Abs₄₂₀) and total organic carbon (TOC) were the variables most strongly correlated with THg concentrations in the pooled dataset from all 19 watercourses, explaining 66% and 61% of the variance respectively. The correlation between THg and OM indicates that OM is the main controlling factor independent of geographical variation in Hg deposition, geology, or any other factor evaluated in this study. Despite an increase in TOC concentrations at most sites during the study period, THg increased in only one of the watercourses, and the THg/TOC ratio decreased significantly at six sites. The Abs₄₂₀ did not increase like TOC. We suggest that OM-fractions absorbing at 420nm are more important for Hg mobilization than other OM-fractions.

Mercury loads in tropical estuaries are largely controlled by the rainfall regime that may cause biodilution due to increased amounts of organic matter (both live and non-living) in the system. Top predators, as Trichiurus lepturus, reflect the changing mercury bioavailability situations in their muscle tissues. In this work two variables [fish weight (g) and monthly total rainfall (mm)] are presented as being important predictors of total mercury concentration (T-Hg) in fish muscle. These important explanatory variables were identified by a Weibull Regression model, which best fit the dataset. A predictive model using readily available variables as rainfall is important, and can be applied for human and ecological health assessments and decisions. The main contribution will be to further protect vulnerable groups as pregnant women and children. Nature conservation directives could also improve by considering monitoring sample designs that include this hypothesis, helping to establish complete and detailed mercury contamination scenarios.