This study provides a combined dataset on N loss pathways and fluxes from sloping cropland in the purple soil area, southwestern China. A lysimeter experiment was conducted to quantify nitrate leaching (May 2004–May 2010) and N₂O emission (May 2009–May 2010) losses. Nitrate leaching was the dominant N loss pathway and annual leaching fluxes ranged from 19.2 to 53.4 kg N ha⁻¹, with significant differences between individual observation years (P < 0.05). Direct N₂O emissions due to N fertilizer use were 1.72 ± 0.34 kg N ha⁻¹ yr⁻¹, which corresponds to an emission factor of 0.58 ± 0.12%. However, indirect N₂O emissions caused by nitrate leaching and surface runoff N losses, may contribute another 0.15–0.42 kg N ha⁻¹ yr⁻¹. Our study shows that nitrate leaching lowered direct N₂O emissions, highlighting the importance for a better understanding of the tradeoff between direct and indirect N₂O emissions for the development of meaningful N₂O emission strategies.

Polyethylene passive samplers (PE) were deployed in Narragansett Bay, RI, to examine freely dissolved concentrations of polybrominated diphenyl ethers (PBDEs) in surface, bottom, and sediment porewater. PBDE congeners in the water column and porewater were below 3 pg L⁻¹. In the surface water, only PBDE congeners containing up to 5 bromines were detected, while in the deeper water congeners 153 and 154 (6 bromines) were also detected. Activity ratios of surface-bottom water and porewater-bottom water suggested that lower brominated (di-tetra) congeners reached Narragansett Bay from surface waters and sediments. PBDEs in the surface water probably originated from a combination of air–water exchange, freshwater runoff, rivers, and wastewater treatment plants. It is suggested that deep water was the source of higher brominated PBDEs to the Bay implying that the more hydrophobic PBDEs reached depth on particles and/or that these congeners were degraded in sediments. On-going sources supply PBDEs to Narragansett Bay.

Water samples collected from upstream tributaries of the Pearl River Delta (PRD) and from locations within the PRD (South China) were analyzed for 27 polycyclic aromatic hydrocarbons (PAHs). Average concentrations (aqueous plus particulate) of total 27 PAHs (Σ₂₇PAH), 16 priority PAHs designated by the United States Environmental Protection Agency (USEPA) except naphthalene (Σ₁₅PAH), and the seven carcinogenic PAHs (Σ₇PAH) classified by the USEPA were 260 ± 410, 130 ± 310, and 15 ± 12 ng/L, respectively. Riverine PAHs were predominantly generated from coal and vegetation combustion, coke production, vehicle exhausts, and petroleum residues, accounting for 28%, 25%, 22% and 21%, respectively, on average. Upstream riverine fluxes of Σ₂₇PAH and Σ₁₅PAH amounted to 38.9 and 12.9 tons/year, respectively. The net contributions of Σ₂₇PAH and Σ₁₅PAH from sources within the PRD were estimated at 21.4 and 21.0 tons/year, respectively.

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.

Polycyclic Aromatic Hydrocarbons (PAHs) transported by surface runoff result in nonpoint source pollution and jeopardize aquatic ecosystems. The transport mechanism of PAHs during rainfall-runoff events has been rarely studied regarding pervious areas. An experimental system was setup to simulate the runoff pollution process on PAHs-contaminated soil. The enrichment behavior of soil-bound PAHs was investigated. The results show that soil organic matters (SOM), rather than clay particles, seem to be the main carrier of PAHs. The enrichment is highly conditioned on runoff and erosion processes, and its magnitude varies among PAH compounds. It is not feasible to build a simple and universal relationship between enrichment ratio and sediment discharge following the traditional enrichment theory. To estimate the flux of PAHs from pervious areas, soil erosion process has to be clearly understood, and both organic carbon content and composition of SOM should be factored into the calculation.

Salinization is a major and growing threat to freshwater ecosystems, yet its effects on aquatic invertebrates have been poorly described at a community-level. Here we use a controlled experimental setting to evaluate short-term stream community responses to salinization, under conditions designed to replicate the duration (72 h) and intensity (up to 5 mS cm⁻¹) of salinity pulses common to Mediterranean rivers subjected to mining pollution during runoff events. There was a significant overall effect, but differences between individual treatments and the control were only significant for the highest salinity treatment. The community response to salinization was characterized by a decline in total invertebrate density, taxon richness and diversity, an increase in invertebrate drift and loss of the most sensitive taxa. The findings indicate that short-term salinity increases have a significant impact on the stream invertebrate community, but concentrations of 5 mS cm⁻¹ are needed to produce a significant ecological response.

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.

Current-use insecticides including organophosphate (OPs) and synthetic pyrethroid (SPs) insecticides were analyzed in 35 sediment samples collected from Chaohu Lake in China, where a transition from a traditional agricultural to a modern urbanized society is ongoing. Total concentrations of five OPs and eight SPs ranged from 0.029 to 0.681 ng/g dry weight and 0.016–301 ng/g dry weight, respectively. Toxic unit analysis showed that 13% of the sediment samples likely produced over 50% of the mortality for benthic invertebrates. Analysis also showed that cypermethrin was the principal contributor to the toxicity. Spatial distribution evaluation implied that OPs were mainly from non-point sources associated with agricultural activities. Conversely, SPs may have been derived from runoff of inflowing rivers through urban regions, as their concentrations were well-correlated with concentrations of other urban-oriented contaminants.

Spatial distribution and source apportionment of polycyclic aromatic hydrocarbons (PAHs) in the surface sediments of the Yangtze Estuary, especially the North Branch, have been fully investigated. PAH concentrations increased with the descending distance from the inner estuary to the adjacent sea, and varied significantly in various estuarine regions. Water currents (e.g., river runoff and ocean current) greatly affected the distribution pattern. In addition, ambient sewage and traffic also contributed to the PAH pollution in the estuary. In the adjacent sea, PAH values along the −20m isobath were higher than those along the −10m isobath due to the “marginal filter” phenomenon formed by different water currents. In most sites, PAHs had poor correlations with sediment size, but had positive correlations with total organic carbon. Based on the qualitative and quantitative analysis results, PAH sources were proved to be mainly from a mixture of petroleum combustion, biomass, and coal combustion.

Land use (and land management) change is seen as the primary factor responsible for changes in sediment and nutrient delivery to water bodies. Understanding how sediment and nutrient (or constituent) concentrations vary with land use is critical to understanding the current and future impact of land use change on aquatic ecosystems. Access to appropriate land-use based water quality data is also important for calculating reliable load estimates using water quality models. This study collated published and unpublished runoff, constituent concentration and load data for Australian catchments. Water quality data for total suspended sediments (TSS), total nitrogen (TN) and total phosphorus (TP) were collated from runoff events with a focus on catchment areas that have a single or majority of the contributing area under one land use. Where possible, information on the dissolved forms of nutrients were also collated. For each data point, information was included on the site location, land use type and condition, contributing catchment area, runoff, laboratory analyses, the number of samples collected over the hydrograph and the mean constituent concentration calculation method. A total of ∼750 entries were recorded from 514 different geographical sites covering 13 different land uses. We found that the nutrient concentrations collected using “grab” sampling (without a well defined hydrograph) were lower than for sites with gauged auto-samplers although this data set was small and no statistical analysis could be undertaken. There was no statistically significant difference (p<0.05) between data collected at plot and catchment scales for the same land use. This is most likely due to differences in land condition over-shadowing the effects of spatial scale. There was, however, a significant difference in the concentration value for constituent samples collected from sites where >90% of the catchment was represented by a single land use, compared to sites with <90% of the upstream area represented by a single land use. This highlights the need for more single land use water quality data, preferably over a range of spatial scales. Overall, the land uses with the highest median TSS concentrations were mining (∼50,000mg/l), horticulture (∼3000mg/l), dryland cropping (∼2000mg/l), cotton (∼600mg/l) and grazing on native pastures (∼300mg/l). The highest median TN concentrations are from horticulture (∼32,000μg/l), cotton (∼6500μg/l), bananas (∼2700μg/l), grazing on modified pastures (∼2200μg/l) and sugar (∼1700μg/l). For TP it is forestry (∼5800μg/l), horticulture (∼1500μg/l), bananas (∼1400μg/l), dryland cropping (∼900mg/l) and grazing on modified pastures (∼400μg/l). For the dissolved nutrient fractions, the sugarcane land use had the highest concentrations of dissolved inorganic nitrogen (DIN), dissolved organic nitrogen (DON) and dissolved organic phosphorus (DOP). Urban land use had the highest concentrations of dissolved inorganic phosphorus (DIP). This study provides modellers and catchment managers with an increased understanding of the processes involved in estimating constituent concentrations, the data available for use in modelling projects, and the conditions under which they should be applied. Areas requiring more data are also discussed.