Arable soils are a significant source of nitric oxide (NO), a precursor of tropospheric ozone, and thereby contribute to ozone pollution. However, their actual impact on ozone formation is strongly related to their spatial and temporal emission patterns, which warrant high-resolution estimates. Here, we combined an agro-ecosystem model and geo-referenced databases to map these sources over the 12 000 km2 administrative region surrounding Paris, France, with a kilometric level resolution. The six most frequent arable crop species were simulated, with emission rates ranging from 1.4 kg N–NO ha−1 yr−1 to 11.1 kg N–NO ha−1 yr−1. The overall emission factor for fertilizer-derived NO emissions was 1.7%, while background emissions contributed half of the total NO efflux. Emissions were strongly seasonal, being highest in spring due to fertilizer inputs. They were mostly sensitive to soil type, crops' growing season and fertilizer N rates. The use of an agro-ecosystem model at regional scale makes it possible to map the emissions of nitric oxide from arable soils at a resolution compatible with tropospheric ozone models.

Vegetable production in China is associated with high inputs of nitrogen, posing a risk of losses to the environment. Organic matter mineralisation is a considerable source of nitrogen (N) which is hard to quantify. In a two-year greenhouse cucumber experiment with different N treatments in North China, non-observed pathways of the N cycle were estimated using the EU-Rotate_N simulation model. EU-Rotate_N was calibrated against crop dry matter and soil moisture data to predict crop N uptake, soil mineral N contents, N mineralisation and N loss. Crop N uptake (Modelling Efficiencies (ME) between 0.80 and 0.92) and soil mineral N contents in different soil layers (ME between 0.24 and 0.74) were satisfactorily simulated by the model for all N treatments except for the traditional N management. The model predicted high N mineralisation rates and N leaching losses, suggesting that previously published estimates of N leaching for these production systems strongly underestimated the mineralisation of N from organic matter.

The purpose of this paper was to use quantitative systems-level approach employing biotic ligand model based threshold damage model to examine physiological responses of tilapia and freshwater clam to sequential pulsed and fluctuating arsenic concentrations. We tested present model and triggering mechanisms by carrying out a series of modeling experiments where we used periodic pulses and sine-wave as featured exposures. Our results indicate that changes in the dominant frequencies and pulse timing can shift the safe rate distributions for tilapia, but not for that of freshwater clam. We found that tilapia increase bioenergetic costs to maintain the acclimation during pulsed and sine-wave exposures. Our ability to predict the consequences of physiological variation under time-varying exposure patterns has also implications for optimizing species growing, cultivation strategies, and risk assessment in realistic situations.

An agricultural ammonia (NH3) emission inventory in the North China Plain (NCP) on a prefecture level for the year 2004, and a 5 × 5 km2 resolution spatial distribution map, has been calculated for the first time. The census database from China's statistics datasets, and emission factors re-calculated by the RAINS model supported total emissions of 3071 kt NH3–N yr−1 for the NCP, accounting for 27% of the total emissions in China. NH3 emission from mineral fertilizer application contributed 1620 kt NH3–N yr−1, 54% of the total emission, while livestock emissions accounted for the remaining 46% of the total emissions, including 7%, 27%, 7% and 5% from cattle, pigs, sheep and goats, and poultry, respectively. A high-resolution spatial NH3 emissions map was developed based on 1 × 1 km land use database and aggregated to a 5 × 5 km grid resolution. The highest emission density value was 198 kg N ha−1 yr−1. The first high-resolution spatial distribution of ammonia emissions for the North China Plain showed rates up to 200 kg NH3–N ha−1 yr−1.

Estimates of non-point source (NPS) contribution to total water pollution in China range up to 81% for nitrogen and to 93% for phosphorus. We believe these values are too high, reflecting (a) misuse of estimation techniques that were developed in America under very different conditions and (b) lack of specificity on what is included as NPS. We compare primary methods used for NPS estimation in China with their use in America. Two observations are especially notable: empirical research is limited and does not provide an adequate basis for calibrating models nor for deriving export coefficients; the Chinese agricultural situation is so different than that of the United States that empirical data produced in America, as a basis for applying estimation techniques to rural NPS in China, often do not apply. We propose a set of national research and policy initiatives for future NPS research in China.

This paper describes a method of estimating emission fluxes of biogenic volatile organic compounds (BVOCs) based on the approach proposed by Guenther et al. (1995) and the high-resolution Corine land-cover 2000 database (1 × 1 km resolution). The computed emission fluxes for the Czech Republic (selected for analysis as being representative of a heavily cultivated, central European country) are compared with anthropogenic emissions, both for the entire country and for individual administrative regions. In some regions, BVOC emissions are as high as anthropogenic emissions; however, in most regions the BVOC emissions are approximately 50% of the anthropogenic emissions. The yearly course of BVOC emissions (represented by monoterpenes and isoprene) is presented, along with the spatial distribution of annual mean values. Differences in emission distributions during winter (January) and summer (June) are also considered. The amount of the biogenic VOCs emitted over the central Europe is comparable with the anthropogenic VOC emissions from this region.

Linear Alkylbenzene Sulfonates (LAS) effects (mortality, egestion rate, behaviour) on the marine deposit feeder Hydrobia ulvae were assessed in whole-sediment and water-only systems. The results were combined with a bioenergetic-based kinetic model of exposure pathways to account for the observed toxicity. The 10-d LC50 value based on the freely dissolved fraction was 9.3 times lower in spiked sediment (0.152 ± 0.001 (95% CI) mg/L) than in water-only (1.390 ± 0.020 (95% CI) mg/L). Consequently, the actual 10-d LC50 value (208 mg/kg) was overestimated by the Equilibrium Partitioning calculation (1629 mg/kg). This suggests that the sediment associated LAS fraction was bioavailable to the snails. It could also be due to modifications in physiological parameters in absence of sediment, the organism natural substrate. Lethality of the marine gastropod deposit feeder Hydrobia ulvae exposed to LAS in water-only system was inappropriate to predict LAS toxicity in sediment system.

Simulation modelling with CHUM-AM was carried out to investigate the accumulation and release of atmospherically-deposited heavy metals (Ni, Cu, Zn, Cd and Pb) in six moorland catchments, five with organic-rich soils, one with calcareous brown earths, in the Pennine chain of northern England. The model considers two soil layers and a third layer of weathering mineral matter, and operates on a yearly timestep, driven by deposition scenarios covering the period 1400-2010. The principal processes controlling heavy metals are competitive solid-solution partitioning of solutes, chemical interactions in solution, and chemical weathering. Agreement between observed and simulated soil metal pools and surface water concentrations for recent years was generally satisfactory, the results confirming that most contemporary soil metal is from atmospheric pollution. Metals in catchments with organic-rich soils show some mobility, especially under more acid conditions, but the calcareous mineral soils have retained nearly all anthropogenic metal inputs. Complexation by dissolved organic matter and co-transport accounts for up to 80% of the Cu in surface waters.

Accumulation of cadmium in periphyton was investigated under field conditions while Cd concentration and speciation were dynamically varying in a small stream during rain events. Speciation in water was determined in situ by diffusion gradient in thin-films (DGT) and by modeling of complexation with fulvic acids. During the rain events, dissolved Cd concentrations increased from 0.17 nM to 0.27–0.36 nM, and 70–97% were DGT-labile. Cd content in periphyton closely followed Cd concentrations in water, despite higher concentrations of Zn and Mn, and may be controlled by either free or DGT-labile Cd concentrations. Decrease of Cd content in periphyton after the rain events was slower than the decrease of Cd concentration in water. Concentrations of Zn, Mn, Cu, Pb and Fe in periphyton also followed the dynamic variations of metal concentrations in water. Repeated exposure of periphyton to elevated dissolved Cd may lead to Cd accumulation. Cadmium accumulation in periphyton was examined in a small stream during rain events in relation to Cd speciation.

There is strong interest in developing tools to link chemical concentrations of contaminants to the potential for observing sediment toxicity that can be used in initial screening-level sediment quality assessments. This paper presents new approaches for predicting toxicity in sediments, based on 10-day survival tests with marine amphipods, from sediment chemistry, by means of the application of Partial Least Squares-Discriminant Analysis (PLS-DA) and Counter-propagation Artificial Neural Networks (CP-ANNs) to large historical databases of chemical and toxicity data. The exploration of the internal structure of the developed models revealed inherent limitations of predicting toxicity from common chemical analyses of bulk contaminant concentrations. However, the results obtained in the validation of these models combined relevant values of non-error classification rate, sensitivity and specificity of, respectively, 76, 87 and 73% with PLS-DA and 92, 75 and 97% with CP-ANNs, outperforming the results reported for previous approaches. Models for predicting toxicity based on amphipod tests, derived using PLS-DA and CP-ANN, can be useful aids for screening-level sediment quality assessment.