While terrestrial moss and other plants are frequently used for environmental mapping and monitoring projects, data on the regional geochemistry of humus are scarce. Humus, however, has a much larger life span than any plant material. It can be seen as the “environmental memory” of an area for at least the last 60–100 years. Here concentrations of 39 elements determined by ICP-MS and ICP AES, pH and ash content are presented for 259 samples of forest floor humus collected at an average sample density of 1 site/300km² in the Czech Republic. The scale of anomalies linked to known contamination sources (e.g., lignite mining and burning, metallurgical industry, coal fired power plants, metal smelters) is documented and discussed versus natural processes influencing humus quality. Most maps indicate a local impact from individual contamination sources: often more detailed sampling than used here would be needed to differentiate between likely sources.

Modelling complex systems such as farms often requires quantification of a large number of input factors. Sensitivity analyses are useful to reduce the number of input factors that are required to be measured or estimated accurately. Three methods of sensitivity analysis (the Morris method, the rank regression and correlation method and the Extended Fourier Amplitude Sensitivity Test method) were compared in the case of the CERES-EGC model applied to crops of a dairy farm. The qualitative Morris method provided a screening of the input factors. The two other quantitative methods were used to investigate more thoroughly the effects of input factors on output variables. Despite differences in terms of concepts and assumptions, the three methods provided similar results. Among the 44 factors under study, N₂O emissions were mainly sensitive to the fraction of N₂O emitted during denitrification, the maximum rate of nitrification, the soil bulk density and the cropland area.

The aim of this study is to illustrate the importance of farm scale heterogeneity on nitrogen (N) losses in agricultural landscapes. Results are exemplified with a chain of N models calculating farm-N balances and distributing the N-surplus to N-losses (volatilisation, denitrification, leaching) and soil-N accumulation/release in a Danish landscape. Possible non-linearities in upscaling are assessed by comparing average model results based on (i) individual farm level calculations and (ii) averaged inputs at landscape level. Effects of the non-linearities that appear when scaling up from farm to landscape are demonstrated. Especially in relation to ammonia losses the non-linearity between livestock density and N-loss is significant (p > 0.999), with around 20–30% difference compared to a scaling procedure not taking this non-linearity into account. A significant effect of farm type on soil N accumulation (p > 0.95) was also identified and needs to be included when modelling landscape level N-fluxes and greenhouse gas emissions.

This paper describes results of chemical and isotopic analysis of inorganic carbon species in the atmosphere and precipitation for the calendar year 2008 in Wrocław (SW Poland). Atmospheric air samples (collected weekly) and rainwater samples (collected after rain episodes) were analysed for CO₂ and dissolved inorganic carbon (DIC) concentrations and for δ¹³C composition. The values obtained varied in the ranges: atmospheric CO₂: 337–448ppm; δ¹³CCO₂ from −14.4 to −8.4‰; DIC in precipitation: 0.6–5.5mgdm⁻³; δ¹³CDIC from −22.2 to +0.2‰. No statistical correlation was observed between the concentration and δ¹³C value of atmospheric CO₂ and DIC in precipitation. These observations contradict the commonly held assumption that atmospheric CO₂ controls the DIC in precipitation. We infer that DIC is generated in ambient air temperatures, but from other sources than the measured atmospheric CO₂. The calculated isotopic composition of a hypothetical CO₂ source for DIC forming ranges from −31.4 to −11.0‰, showing significant seasonal variations accordingly to changing anthropogenic impact and atmospheric mixing processes.

Perfluorinated compounds (PFCs) measured in surface running waters indicated the existence of different emission sources in eight main city basins. The tap water reflected the contamination pattern and levels in their corresponding source water basins. The daily intakes through tap water consumption ranged from <0.01 to 0.73 ng kg⁻¹ d⁻¹ for perfluorooctanoate (PFOA) and <0.01 to 0.08 ng kg⁻¹ d⁻¹ for perfluorooctanesulfonate (PFOS). Tap water intake-derived exposure accounted for 8.6%–101% (for PFOA) and while <10% (for PFOS) of total daily exposure, which was estimated from Korean serum concentrations using a pharmacokinetic model. Our findings indicate that tap water intake could be an important contributor to PFOA exposure in Korean populations; accordingly, additional efforts are necessary to improve the removal efficiency of perfluorinated compounds (PFCs) in the water purification process. However, more fundamentally the aim would be to reduce the discharge of PFCs from potential sources within the basin.

By comparing five ecosystem types in the Czech Republic over several years, we recorded the highest carbon sequestration potential in an evergreen Norway spruce forest (100%) and an agroecosystem (65%), followed by European beech forest (25%) and a wetland ecosystem (20%). Because of a massive ecosystem respiration, the final carbon gain of the grassland was negative. Climate was shown to be an important factor of carbon uptake by ecosystems: by varying the growing season length (a 22-d longer season in 2005 than in 2007 increased carbon sink by 13%) or by the effect of short- term synoptic situations (e.g. summer hot and dry days reduced net carbon storage by 58% relative to hot and wet days). Carbon uptake is strongly affected by the ontogeny and a production strategy which is demonstrated by the comparison of seasonal course of carbon uptake between coniferous (Norway spruce) and deciduous (European beech) stands.

This study investigated changes in diversity of shrub-tree layer, leaf decomposition rates, nutrient release and soil NO fluxes of a Brazilian savanna (cerrado sensu stricto) under N, P and N plus P additions. Simultaneous addition of N and P affected density, dominance, richness and diversity patterns more significantly than addition of N or P separately. Leaf litter decomposition rates increased in P and NP plots but did not differ in N plots in comparison to control plots. N addition increased N mass loss, while the combined addition of N and P resulted in an immobilization of N in leaf litter. Soil NO emissions were also higher when N was applied without P. The results indicate that if the availability of P is not increased proportionally to the availability of N, the losses of N are intensified.

The diffusive gradients in thin films (DGT) technique was evaluated in modelling wheat (Triticum aestivum) arsenic toxicity using a dataset of As-contaminated soil samples (n=28) collected from former sheep dip sites. Above ground wheat biomass from a 21-day early growth bioassay was adopted as the response variable and the dose–response relationships were modelled using the three-parameter sigmoid equation. The DGT-derived effective soil solution As to P concentration ratios corresponded strongly to the differences in the response variable. With a single sample identified as an outlier, the 95% confidence interval for the effective soil solution As/P molar concentration ratio which resulted in a 50% reduction in the response (EC50) was 0.168–0.360. While the DGT-derived soil measure of As/P ratio was shown as a promising phytotoxicity predictor, the influence of P nutrition on the dose–response relationship deserves further consideration.

Few studies have quantified the accuracy of soil metal bioavailability assays using large datasets. A meta-analysis from experiments spanning 6 months to 13 years on 12 soil types, compared bioavailability estimate efficiencies for wheat and ryegrass. Treatments included biosolids ± metals, comparing total metal, Ca(NO₃)₂, EDTA, soil solution, DGT and free ion activity. The best correlations between soil metal bioavailability and shoot concentrations were for Ni using Ca(NO₃)₂ (r² = 0.72) which also provided the best estimate of Zn bioavailability (r² = 0.64). DGT provided the best estimate of Cd bioavailability, accounting for 49% of shoot Cd concentrations. There was no reliable descriptor of Cu bioavailability, with less than 35% of shoot Cu concentrations defined. Thus interpretation of data obtained from many soil metal bioavailability assays is unreliable and probably flawed, and there is little justification to look beyond Ca(NO₃)₂ for Ni and Zn, and DGT for Cd.

We examined the accumulation, subcellular distribution, and toxicity of Hg(II) and MeHg in three marine phytoplankton (the diatom Thalassiosira pseudonana, the green alga Chlorella autotrophica, and the flagellate Isochrysis galbana). For MeHg, the inter-species toxic difference could be best interpreted by the total cellular or intracellular accumulation. For Hg(II), both I. galbana and T. pseudonana exhibited similar sensitivity, but they each accumulated a different level of Hg(II). A higher percentage of Hg(II) was bound to the cellular debris fraction in T. pseudonana than in I. galbana, implying that the cellular debris may play an important role in Hg(II) detoxification. Furthermore, heat-stable proteins were a major binding pool for MeHg, while the cellular debris was an important binding pool for Hg(II). Elucidating the different subcellular fates of Hg(II) and MeHg may help us understand their toxicity in marine phytoplankton at the bottom of aquatic food chains.