Validation of spectrophotometric method for Se(IV) determination: analytical applications

As selenium is an important part of the antioxidant enzymes and also because there are several studies suggesting a possible link between cancer and selenium deficiency, this paper presents a spectrophotometric method for the assay of Se(IV), using N,N-diethyl-p-phenylenediamine monohydrochloride as reagent. The proposed method is based on the reaction between the selenium and potassium iodide in low acidic medium, when iodine is released. This last product will further oxidise the new reagent. The final obtained product is strongly coloured in red and has an absorption maximum at 552 nm and molar extinction coefficient (ε) of 6.1?×?10⁴ L mol^?1 cm^?1. The optimum working conditions were established, and the developed method was validated, being characterised by a good linearity (in the range of 0.5–3.0 μg/mL), a limit of detection (0.0573 μg/mL) and a limit of quantification (0.1737 μg/mL). At the same time, the repeatability, the precision of the method and the accuracy were established. The proposed and validated method was applied with good results for the determination of Se(IV) in spring and bottled water from Iasi and also in pharmaceutical and cosmetic products.     

Air pollution, precipitation chemistry and forest health in the Retezat Mountains, Southern Carpathians, Romania

In the Retezat Mountains concentrations of O3, NO2 and SO2 in summer season 2000-2002 were low and below toxicity levels for forest trees. While NH3 concentrations were low in 2000, the 2001 and 2002 concentrations were elevated indicating possibility for increased N deposition to forest stands. More than 90% of the rain events were acidic with pH values <5.5, contributing to increased acidity of soils. Crown condition of Norway spruce (Picea abies) and European beech (Fagus sylvatica) was good, however, defoliation described as >25% of foliage injured increased from 9.1% in 2000 to 16.1% in 2002. Drought that occurred in the southern Carpathians between fall 2000 and summer 2002 and frequent acidic rainfalls could cause the observed decline of forest condition. Both Norway spruce and European beech with higher defoliation had lower annual radial increments compared to the trees with low defoliation. Ambient O3 levels found in the Retezat did not affect crown condition of Norway spruce or European beech.     

Spatially valid data of atmospheric deposition of heavy metals and nitrogen derived by moss surveys for pollution risk assessments of ecosystems

For analysing element input into ecosystems and associated risks due to atmospheric deposition, element concentrations in moss provide complementary and time-integrated data at high spatial resolution every 5 years since 1990. The paper reviews (1) minimum sample sizes needed for reliable, statistical estimation of mean values at four different spatial scales (European and national level as well as landscape-specific level covering Europe and single countries); (2) trends of heavy metal (HM) and nitrogen (N) concentrations in moss in Europe (1990–2010); (3) correlations between concentrations of HM in moss and soil specimens collected across Norway (1990–2010); and (4) canopy drip-induced site-specific variation of N concentration in moss sampled in seven European countries (1990–2013). While the minimum sample sizes on the European and national level were achieved without exception, for some ecological land classes and elements, the coverage with sampling sites should be improved. The decline in emission and subsequent atmospheric deposition of HM across Europe has resulted in decreasing HM concentrations in moss between 1990 and 2010. In contrast, hardly any changes were observed for N in moss between 2005, when N was included into the survey for the first time, and 2010. In Norway, both, the moss and the soil survey data sets, were correlated, indicating a decrease of HM concentrations in moss and soil. At the site level, the average N deposition inside of forests was almost three times higher than the average N deposition outside of forests.     

A regional flux-based risk assessment approach for multiple contaminated sites on groundwater bodies

In the context of the Water Framework Directive (EP and CEU, 2000), management plans have to be set up to monitor and to maintain water quality in groundwater bodies in the EU. In heavily industrialized and urbanized areas, the cumulative effect of multiple contaminant sources is likely and has to be evaluated. In order to propose adequate measures, the calculated risk should be based on criteria reflecting the risk of groundwater quality deterioration, in a cumulative manner and at the scale of the entire groundwater body. An integrated GIS- and flux-based risk assessment approach for groundwater bodies is described, with a regional scale indicator for evaluating the quality status of the groundwater body. It is based on the SEQ-ESO currently used in the Walloon Region of Belgium which defines, for different water uses and for a detailed list of groundwater contaminants, a set of threshold values reflecting the levels of water quality and degradation with respect to each contaminant. The methodology is illustrated with first results at a regional scale on a groundwater body-scale application to a contaminated alluvial aquifer which has been classified to be at risk of not reaching a good quality status by 2015. These first results show that contaminants resulting from old industrial activities in that area are likely to contribute significantly to the degradation of groundwater quality. However, further investigations are required on the evaluation of the actual polluting pressures before any definitive conclusion be established.     

Estimating population impacts via dynamic occupancy analysis of Before-After Control-Impact studies

Estimating environmental impacts on populations is one of the main goals of wildlife monitoring programs, which are often conducted in conjunction with management actions or following natural disturbances. In this study we investigate the statistical power of dynamic occupancy models to detect changes in local survival and colonization from detection-nondetection data, while accounting for imperfect detection probability, in a Before-After Control-Impact (BACI) framework. We simulated impacts on local survival and/or detection probabilities, and asked questions related to: (1) costs and benefits of different analysis models, (2) confounding changes in detection with changes in local survival, (3) sampling design trade-offs, and (4) species with low vs. high rates of turnover. Estimating seasonal effects on local survival and colonization, as opposed to estimating Before-After effects, had little effect on the power to detect changes in local survival. Estimating a parameter that accounted for pretreatment differences in local survival between Control and Impact sites decreased power by 50%, but it was critical to include when such differences existed. When the experimental treatment had a negative impact on species detectability but analysis assumed constant detection, the Type I error rates were dramatically inflated (0.20 0.33). In general, there was low power (< 0.5) to detect a 50% decrease in local survival for all combinations of sites (N = 50 vs. 100), seasons sampled (8 vs. 12), and visits per site per season (4 vs. 6). Unbalanced designs performed worse than balanced designs, with the exception of the case of treatments being implemented in different seasons at different sites. Adding more control sites improved the ability to detect changes in local survival. Surveying more seasons after impact resulted in modest power gains, but at least three seasons before impact were required to successfully implement BACI occupancy studies. Turnover rates had a low impact on power. Occupancy studies conducted in a BACI design offer the opportunity to detect environmental impacts on wildlife populations without the costs of intensive studies. However, given the low power to detect small changes (20%) in local survival, these studies should be used when researchers are confident that major treatment impacts will occur or very large sample sizes are obtainable.