Use of native mosses as biomonitors of heavy metals and nitrogen deposition in the surroundings of two steel works

A biomonitoring survey using the moss species Hypnum cupressiforme Hedw. was conducted in the surroundings of two steel plants located in the North of Spain. Levels of V, Cr, Ni, Cu, Zn, As, Cd, Hg, Pb and N were determined. Very high concentrations in the areas of study were detected when compared to nearby unaffected regions. Similar trends were observed for all the elements in the differently orientated transects, showing an appreciable influence of the NW prevailing winds of the region in the dispersion of pollutants, as well as a clear decreasing gradient in the concentrations of metals in mosses within a distance of 1500 meters from the facilities. A differentiation between the elements emitted by the chimney as result of the industrial activity (V, Cr, Ni, Cu and As) and those with a high presence in steel slag deposits (Zn, Cd, Hg and Pb) was observed. The range of contamination was also established by means of the Contamination Factor, indicating a category 4 out of 6 categories, which shows the high levels reported in the areas of study. A different dynamic was registered for nitrogen regarding the rest of the heavy metals analysed except for Hg, probably due to the elevated volatility and mobility of both elements, as well as their high persistence in the atmosphere.     

Determination of cobalt,nickel and iron at trace level in natural water samples by in-column chelation-reversed phase high-performance liquid chromatography

This paper reports the utilization of 4-(2-pyridylazo) resorcinol (PAR) as a chelating reagent for in-column derivatization and the determination of trace Co, Fe, and Ni ions by reversed-phase high-performance liquid chromatography with photodiode array detector. A good separation of Co, Fe, and Ni chelates were achieved by using an Inertsil ODS-3 column and a mobile phase, consisted of methanol–THF–water mixture (50:5:45) containing ammonium acetate buffer (pH 5.0) and PAR. After full optimization, good repeatability of retention times (relative standard deviation (RSD) < 0.05%) and peak areas (RSD < 1.7%) was achieved as well as a good linearity (r ² > 0.9991). The detection limits (S/N = 3), expressed as micrograms per liter, were 0.50 (Co), 9.07 (Fe), and 2.00 (Ni). The applicability and the accuracy of the developed method were estimated by the analysis of spiked water samples and certified reference material BCR 715 wastewater-SRM.     

Forty years of atmospheric radiocarbon monitoring around Bohunice nuclear power plant, Slovakia

Radiocarbon variations in the atmospheric CO(2) with attenuating amplitudes and decreasing mean values with typical maxima in summer and minima in winter have been observed since 1967 in two localities of Slovakia, in Bratislava and Zlkovce, situated about 60 km NE from Bratislava, only 5 km from the Bohunice Nuclear Power Plant (NPP). The (14)C record in Bratislava has been influenced mainly by fossil CO(2) emissions, in contrast to the Zlkovce record which has been more variable, as it has clearly been affected by operation of the Bohunice NPP. However, during specific meteorological conditions with NE transport of air masses to Bratislava, the effect of the Bohunice NPP has been visible in Bratislava as well. Maximum (14)C concentrations (up to 120% above a natural background) were observed around A1 NPP which used CO(2) with admixture of air as a cooling agent. The (14)C concentrations around four pressurized light water reactors were up to 30% above the background. The Delta(14)C values in the heavily polluted atmosphere of Bratislava were up to 10% and at Zlkovce up to 5% lower than the European clean air represented by the Jungfraujoch Delta(14)C data. Later the Delta(14)C values were similar at both sites, and from 2003 they were close to the European clean air levels. The observed Delta(14)C behaviour in the atmosphere provides a unique evidence of decreased fossil fuel CO(2) emissions in the region, as well as the long-term effect of the Bohunice NPP on the Bratislava and Zlkovce stations. The estimated annual radiation doses to the local public due to digestion of radiocarbon contaminated food have been estimated to be around 3 microSv.     

The development and application of remote sensing to monitor sand dune habitats

Sand dunes are complex systems that contain several habitats, often as mosaics or transitions between types. Several of these habitats are afforded protection under European Legislation and in the UK nationally within Special Areas of Conservation (SAC) and Sites of Special Scientific Interest (SSSI). Natural England has a statutory duty to report to Europe on the conservation status and condition of sand dunes; and is required to report to the UK Government on designated sites. To achieve this we have sought ways of capturing, analysing and interpreting data on the extent and location of sand dune habitats. This requires an ability to be able to obtain data over large areas of coastline in an efficient way. Natural England and Environment Agency Geomatics have worked collaboratively for over 16 years, sharing data and ecological knowledge. In 2012 work started to evaluate the use of remote sensing to map UK BAP and Annex I sand dune habitats. A methodology has now been developed and tested to map sand dune habitats. The key objective was to provide an operational tool that will help to map these habitats and understand change on sites around England. This has been achieved through analysis of LIDAR and Compact Airborne Spectrographic Imager (CASI) data using Object Orientated Image Analysis. Quality Control (QC) and accuracy assessments have shown this approach to be successful and 11 sites have been mapped to date. These techniques are providing a new approach to monitoring change in coastal vegetation communities and informing management of protected sites.     

A whole-farm strategy to reduce environmental impacts of nitrogen

Dutch regulations for ammonia emission require farmers to inject slurry into the soil (shallow) or to apply it in narrow bands at the surface. For one commercial dairy farm in the Netherlands it was hypothesized that its alternative farming strategy, including low-protein feeding and surface spreading, could be an equally effective tool for ammonia emission abatement. The overall objective of the research was to investigate how management at this farm is related to nitrogen (N) losses to the environment, including groundwater and surface water. Gaseous emission of ammonia and greenhouse gasses from the naturally ventilated stables were 8.1 and 3.1 kg yr(-1) AU(-1) on average using the internal tracer (SF(6))-ratio method. Measurements on volatilization of ammonia from slurry application to the field using an integrated horizontal flux method and the micrometeorological mass balance method yielded relatively low values of ammonia emissions per ha (3.5-10.9 kg NH(3)-N ha(-1)). The mean nitrate concentration in the upper ground water was 6.7 mg L(-1) for 2004 and 3.0 mg L(-1) for 2005, and the half-year summer means of N in surface water were 2.3 mg N L(-1) and 3.4 mg N L(-1) for 2004 and 2005, respectively. Using a nutrient budget model for this farm, partly based on these findings, it was found that the calculated ammonia loss per ton milk (range 5.3-7.5 kg N Mg(-1)) is comparable with the estimated ammonia loss of a conventional farm that applies animal slurry using prescribed technologies.     

The power of simulating experiments

Addressing complex ecological research questions often requires complex empirical experiments. However, due to the logistic constraints of empirical studies there is a trade-off between the complexity of experimental designs and sample size. Here, we explore if the simulation of complex ecological experiments including stochasticity-induced variation can aid in alleviating the sample size limitation of empirical studies. One area where sample size limitations constrain empirical approaches is in studies of the above- and belowground controls of trophic structure. Based on a rule- and individual-based simulation model on the effect of above- and belowground herbivores and their enemies on plant biomass, we evaluate the reliability of biomass estimates, the probability of experimental failure in terms of missing values, and the statistical power of biomass comparisons for a range of sample sizes. As expected, we observed superior performance of setups with sample sizes typical of simulations (n = 1000) as compared to empirical experiments (n = 10). At low sample sizes, simulated standard errors were smaller than expected from statistical theory, indicating that stochastic simulation models may be required in those cases where it is not possible to perform pilot studies for determining sample sizes. To avoid experimental failure, a sample size of n = 30 was required. In conclusion, we propose that the standard tool box of any ecologist should comprise a combination of simulation and empirical approaches to benefit from the realism of empirical experiments as well as the statistical power of simulations.