Occurrence and behaviour of 4-nonylphenol in river water of Germany

An analytical method composed of solid-phase-extraction (SPE) followed by gas chromatography-mass spectrometry (GC-MS) has been developed to investigate the occurrence and the behaviour of the endocrine disruptor 4-nonylphenol (4-NP) in river water of Germany. 16 Para-isomers of the complex mixture of 4-NP isomers have been resolved in the SPE-extracts of river water samples. The mass spectra indicate the presence of four distinct groups of isomers. The different groups are characterised by different base peaks of the mass spectra dependent on the substitution of the alpha-carbon on the alkyl chain. The different isomers show (i) alpha-methyl, alpha-ethyl (base peak 149), (ii) alpha-dimethyl (base peak 135), (iii) alpha-methyl, alpha-propyl, alpha-butyl (base peak 121) and (iv) alpha-methyl, alpha-propyl, alpha-butyl (base peak 107) configuration of the alkyl chain. The recovery of the unbranched compound 4-n-NP was > or = 90%. Detection limit and determination limit of the whole analytical procedure were 6 ng L(-1) and 25 ng L(-1), respectively with a relative standard deviation of 11.7%. The concentration of the sum of the 4-NP isomers in all samples of river water ranged from 28 ng L(-1) (Elbe River) to 1220 ng L(-1)(Oder River). In a period of a higher river water level, a higher amount of 4-NP was detected in the Oder River than in a period of a lower water level. Therefore dilution was not the determinant factor of the 4-NP concentration in river water. The diurnal dynamics of the sewage treatment works (STWs) have to be considered as an influencing factor for the presence of 4-NP in river water.     

Multi-scale scenarios of spatial-temporal dynamics in the European livestock sector

The European livestock sector has changed rapidly in the recent past and further changes are expected in the near future due to reforms in the European Common Agricultural Policy (CAP), increasing environmental concerns and changing consumer awareness. We developed a multi-scale modeling approach for exploring spatial and temporal dynamics of livestock distribution by accounting for drivers at different spatial scales. Such approach can provide a basis for environmental impact assessments of livestock farming at broad spatial scales. Assessment of change in both quantity and location was made for six livestock types. Four contrasting scenarios were applied ranging from globalization to regionalization, as well as from low regulation levels and dominance of market forces towards a higher degree of governmental regulation. National level livestock numbers as calculated by a macro-economic model were spatially distributed at the landscape scale according to the scenario assumptions considering biophysical, socio-economic, and political forces. Results indicate for most of the old European Union (EU) member countries a decrease in livestock numbers. In the new EU member countries sheep, goats and pigs are expected to decline while beef cattle and poultry are expected to grow. Livestock densities are expected to increase both within and outside current livestock hotspot regions in absence of environmental legislations. Environmental pressure as result of high livestock densities may, however, also remain in regulated scenarios where environmental policies are implemented and income support remains stable over time due to path dependencies in the livestock sector. But contrary to the non-regulated scenario it is less likely that new areas with high risk of negative environmental impacts due to livestock farming will develop.     

Occurrence and distribution of benzothiazole in the Schwarzbach watershed (Germany)

This study quantifies the regional distribution of the micropollutant benzothiazole (BT) in river water by sampling 15 river sites in the Schwarzbach watershed (about 400 km(2)) from November 2008 to February 2010. Additionally, wastewater samples from three municipal wastewater treatment plants (WWTPs) in Germany were analyzed. BT was detected in all wastewater influent and effluent samples as well as in all river water samples collected downstream of wastewater discharge. This corroborates the ubiquitous occurrence of BT in the aqueous environment. Concentrations were between 58 and 856 ng L(-1) in the river water. The observed mean concentration at the outlet of the investigated catchment was 109 ng L(-1). With only a few exceptions, temporal and spatial variations of BT concentrations in river water were low. Rather similar BT concentrations over a wide range of river discharge indicate that dilution along the mainstream is negligible and, thus, supports the hypothesis that paved surface runoff during rain events is an important BT source not only for wastewater influent but also for river water. This was supported by detecting the highest BT concentrations at sampling locations close to the dense highway network around the city of Frankfurt. Since BT was also detected in river water collected from locations that were clearly unaffected by wastewater effluent discharge, surface runoff must be considered as a diffuse source of BT in river water.     

Multiple environmental burdens and neighborhood-related health of city residents

Urban living environments are known to influence human well-being and health; however, little is known about the multidimensionality of different environmental burdens. The aim of this study is to examine the relations between multiple burdens and self-rated health of city residents in Berlin. A spatial analysis was conducted to determine neighborhood street blocks with high versus low levels of three environmental burdens (traffic noise, air pollution, lack of public green space) as study sites for a cross-sectional household questionnaire. Burden level served as a dichotomous predictor to compare residents' self-reports of neighborhood satisfaction, life satisfaction, health behavior, and psychological and physical health symptoms. Residents from high-burden blocks appraised the environmental conditions more stressful, reported poorer health behavior and were less satisfied with their neighborhood than residents from low-burden blocks. However, they did not differ in regard to more general health symptoms. Three other burdens (behavior-related noise, litter and dirt in public space, lack of urban vegetation), which could not be varied objectively, were assessed by their perceived intensity. Regression analyses of the relations between the perceived levels of all six burdens and outcomes in the total sample revealed the following: Neighborhood satisfaction could be predicted from multiple stressors and resources that co-occur independently, while more general health symptoms were related only to perceived air pollution. The results have implications for both urban planning and public health.     

Correction to: Effect of biosolid hydrochar on toxicity to earthworms and brine shrimp

Environmental Geochemistry and Health - Unfortunately, in the original publication of the article, Prof. Yong Sik Ok’s affiliation was incorrectly published. The author’s affiliation is...     

Hierarchical linear mixed models in multi-stage sampling soil studies

The issue of variances of different soil variables prevailing at different sampling scales is addressed. This topic is relevant for soil science, agronomy and landscape ecology. In multi-stage sampling there are randomness components in each stage of sampling which can be taken into account by introducing random effects in analysis through the use of hierarchical linear mixed models (HLMM). Due to the nested sampling scheme, there are several hierarchical sub-models. The selection of the best model can be carried out through likelihood ratio tests (LRTs) or Wald tests, which are asymptotically equivalent under standard conditions. However, when the comparison leads to a restricted hypothesis of variance components, standard conditions are not maintained, which leads to more elaborated versions of LRTs. These versions are not disseminated among environmental scientists. The present study shows the modeling of soil data from a sampling where sites, fields within sites, transects within fields, and sampling points within transects were selected in order to take samples from different vegetation types (open and shade). For soil data, several sub-models were compared using Wald tests, classic LRTs and adjusted LRTs where the distribution of the test statistic under the null hypothesis is the Chi-square mixture of Chi-square distributions. The inclusion of random effects via HLMM and suggested by the latest version of LRT allowed us to detect effects of vegetation type on soil properties that were not detected under a classical ANOVA.