The high wastewater volumes produced during citrus production at pre- and post-harvest level presents serious pesticide point-source pollution for groundwater bodies. Biobeds are used for preventing such point-source pollution occurring at farm level. We explored the potential of biobeds for the depuration of wastewaters produced through the citrus production chain following a lab-to-field experimentation. The dissipation of pesticides used pre- or post-harvest was studied in compost-based biomixtures, soil, and a straw-soil mixture. A biomixture of composted grape seeds and skins (GSS-1) showed the highest dissipation capacity. In subsequent column studies, GSS-1 restricted pesticides leaching even at the highest water load (462Lm⁻³). Ortho-phenylphenol was the most mobile compound. Studies in an on-farm biobed filled with GSS-1 showed that pesticides were fully retained and partially or fully dissipated. Overall biobeds could be a valuable solution for the depuration of wastewaters produced at pre- and post-harvest level by citrus fruit industries.

On-road emissions are a major contributor to rising concentrations of atmospheric greenhouse gases. In this study, we applied a downscaling methodology based on commonly available spatial parameters to model on-road CO₂ emissions at the 1 × 1 km scale for the Boston, MA region and tested our approach with surface-level CO₂ observations. Using two previously constructed emissions inventories with differing spatial patterns and underlying data sources, we developed regression models based on impervious surface area and volume-weighted road density that could be scaled to any resolution. We found that the models accurately reflected the inventories at their original scales (R² = 0.63 for both models) and exhibited a strong relationship with observed CO₂ mixing ratios when downscaled across the region. Moreover, the improved spatial agreement of the models over the original inventories confirmed that either product represents a viable basis for downscaling in other metropolitan regions, even with limited data.

Growing attention is devoted to understand the influence of the short-term variations in air concentrations on the environmental fate of semivolatile organic compounds (SVOCs) such as polycyclic aromatic hydrocarbons (PAHs). These variations are ascribable to factors such as temperature-mediated air-surface exchange and variability of planetary boundary layer (PBL) height and structure. But when investigating the fate of SVOCs at a local scale, further variability can derive from specific point source contributions. In this context, a new modeling approach (AirPlus) which integrates a previously developed model (AirFug) with an air dispersion model (AERMOD) is presented. The integrated model is illustrated for two PAHs in a Northern Italy scenario. Results show how chemical contributions deriving from background advective inflows, local emissions and a point source interact in an hourly-varying meteorological scenario to determine air concentration rapid changes and the consequent response of the soil compartment.

Air, soils and sediments surrounding an abandoned pentachlorophenol (PCP) factory were sampled to determine the levels of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), unintentionally formed during PCP production. The mean concentration of PCDD/Fs in ambient air was one order of magnitude higher than that of the reference site. A trend of decreasing concentrations with increasing distance from the factory was observed, suggesting this site has a significant influence on the regional ambient air. As for soil samples collected within 3 km from the factory and sediment samples from the adjacent rivers, high levels of contamination were found with WHO-TEQ concentrations of 193 ± 211 pg/g and 667 ± 978 pg/g, respectively. The PCDD/F homologue profiles of all samples were consistent with those found in the technical product of PCP, with OCDD as the dominant congener. These results indicate PCDD/Fs in the historical contaminated site pose a long-term impact on surrounding environment.

China represents a significant market for the sale of personal care products (PCPs). Given the continuous emission of hundreds of chemicals used in PCPs to waste water and the aquatic environment after regular use, methods for prioritising the environmental risk assessment for China are needed. In an effort to assess the prioritisation of chemicals used in PCPs in China, we have identified the chemical ingredients used in 2500 PCPs released to the Chinese market in 2009, and estimated the annual emission of these chemicals. The physical-chemical property data for these substances have been estimated and used as model inputs in the RAIDAR model. In general, the RAIDAR model provides an overall assessment of the multimedia fate of chemicals, and provides a holistic approach for prioritising chemical ingredients. The prioritisation exercise conducted in this study is shown to be strongly influenced by loss processes, such as the removal efficiencies of WWT plants and biotransformation.

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.

Mercury (Hg) in autumn litterfall from predominately deciduous forests was measured in 3 years of samples from 23 Mercury Deposition Network sites in 15 states across the eastern USA. Annual litterfall Hg dry deposition was significantly higher (median 12.3 micrograms per square meter (μg/m²), range 3.5–23.4 μg/m²) than annual Hg wet deposition (median 9.6 μg/m², range 4.4–19.7 μg/m²). The mean ratio of dry to wet Hg deposition was 1.3–1. The sum of dry and wet Hg deposition averaged 21 μg/m² per year and 55% was litterfall dry deposition. Methylmercury was a median 0.8% of Hg in litterfall and ranged from 0.6 to 1.5%. Annual litterfall Hg and wet Hg deposition rates differed significantly and were weakly correlated. Litterfall Hg dry deposition differed among forest-cover types. This study demonstrated how annual litterfall Hg dry deposition rates approximate the lower bound of annual Hg dry fluxes.

It has been proposed that bioaccumulated concentrations of toxic metals in tolerant biomonitors be used as indicators of metal bioavailability that could be calibrated against the ecological response to metals of sensitive biotic assemblages. Our hypothesis was that metal concentrations in caddisfly larvae Hydropsyche siltalai and Plectrocnemia conspersa, as tolerant biomonitors, indicate metal bioavailability in contaminated streams, and can be calibrated against metal-specific ecological responses of mayflies. Bioaccumulated concentrations of Cu, As, Zn and Pb in H. siltalai from SW English streams were related to the mayfly assemblage. Mayflies were always sparse where bioavailabilities were high and were abundant and diverse where bioavailabilities of all metals were low, a pattern particularly evident when the combined abundance of heptageniid and ephemerellid mayflies was the response variable. The results offer promise that bioaccumulated concentrations of metals in tolerant biomonitors can be used to diagnose ecological impacts on stream benthos from metal stressors.

To identify different NO₃ ⁻ sources in surface water and to estimate their proportional contribution to the nitrate mixture in surface water, a dual isotope and a Bayesian isotope mixing model have been applied for six different surface waters affected by agriculture, greenhouses in an agricultural area, and households. Annual mean δ¹⁵N–NO₃ ⁻ were between 8.0 and 19.4‰, while annual mean δ¹⁸O–NO₃ ⁻ were given by 4.5–30.7‰. SIAR was used to estimate the proportional contribution of five potential NO₃ ⁻ sources (NO₃ ⁻ in precipitation, NO₃ ⁻ fertilizer, NH₄ ⁺ in fertilizer and rain, soil N, and manure and sewage). SIAR showed that “manure and sewage” contributed highest, “soil N”, “NO₃ ⁻ fertilizer” and “NH₄ ⁺ in fertilizer and rain” contributed middle, and “NO₃ ⁻ in precipitation” contributed least. The SIAR output can be considered as a “fingerprint” for the NO₃ ⁻ source contributions. However, the wide range of isotope values observed in surface water and of the NO₃ ⁻ sources limit its applicability.

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.