Jörg Klasmeier

Occurrence and spatial distribution of microplastics in sediments from Norderney.

The spatial distribution of small potential microplastics (SPM) (<1 mm) in beach sediments was studied on a 500 m stretch of the North Sea island of Norderney. Their correlation with visible plastic debris (VPD) (>1 mm) was also examined. Small microparticles were extracted from 36 one kg sediment samples and analysed by visual microscopic inspection and partly by thermal desorption pyrolysis gas chromatography/mass spectrometry. The smallest particle size that could be analysed with this method was estimated to be 100 μm. The mean number of SPM at the three sampling sites (n = 12) was 1.7, 1.3 and 2.3 particles per kg dry sediment, respectively. SPM were identified as polypropylene, polyethylene, polyethylene terephthalate, polyvinylchloride, polystyrene and polyamide. The organic plastic additives found were benzophenone, 1,2-benzenedicarboxylic acid, dimethyl phthalate, diethylhexyl phthalate, dibutyl phthalate, diethyl phthalate, phenol and 2,4-di-tert-butylphenol. Particles were distributed rather homogenously and the occurrence of SPM did not correlate with that of VPD.

Fate of β-blocker human pharmaceuticals in surface water: comparison of measured and simulated concentrations in the Glatt Valley Watershed, Switzerland.

This study focused on the occurrence and fate of four beta-blockers (atenolol, sotalol, metoprolol, propranolol) in wastewater and surface water. Measured concentrations were compared with predicted concentrations using an implementation of the geo-referenced model GREAT-ER for the Glatt Valley Watershed (Switzerland). Particularly, the question was addressed how measured and simulated data could complement each other for the exposure assessment of human pharmaceuticals and other micropollutants entering surface water through wastewater treatment plants (WWTP). Concentrations in the Glatt River ranged from <LOQ to 83 ng L(-1) with the highest concentrations found for atenolol. Higher loads were measured on days with combined sewer overflow events during high flow conditions. GREAT-ER was able to predict spatially resolved river concentrations based on average consumption and excretion data, removal in wastewater treatment plants (WWTPs) and dissipation and degradation processes in surface water within a factor of 2. These results indicate that modelling might be sufficient to estimate daily average exposure concentrations for compounds that are either recalcitrant or whose degradation and sorption behaviour can be predicted with confidence based on laboratory experiments. Chemical measurements, in contrast, should be reserved for assessing point sources, investigating mechanisms which lead to short-term temporal fluctuations in compound loads, and determining in-situ degradation rates in conjunction with modelling.

A conceptual model describing the fate of sulfadiazine and its metabolites observed in manure-amended soils.

Sulfadiazine (SDZ) belongs to the chemical class of sulfonamides, one of the most important groups of antibiotics applied in animal husbandry in Europe. These antibiotics end up in the soil after manure from treated animals is applied as fertilizer. They can inhibit soil microbial functions and enhance the spread of resistance genes among soil microorganisms. In order to assess the exposure of soil microorganisms to SDZ, a conceptual kinetic model for the prediction of temporally resolved antibiotic concentrations in soil was developed. The model includes transformation reactions, reversible sequestration and the formation of non-extractable residues (NER) from SDZ and its main metabolites N(4)-acetyl-sulfadiazine (N-ac-SDZ) and 4-hydroxy-sulfadiazine (OH-SDZ). The optimum model structure and rate constants of SDZ kinetics and its metabolites were determined by fitting different model alternatives to sequential extraction data of a manure-amended Cambisol soil. N-ac-SDZ is degraded to SDZ with a half-life of 4d, whereas OH-SDZ is not. Though, based on the available data, the hydroxylation of SDZ seems to be negligible, it is still included in the model structure since this process has been observed in recent studies. Sequestration into a residual fraction has similar kinetics for SDZ, N-ac-SDZ and OH-SDZ and is one order of magnitude faster than the reverse translocation. The irreversible formation of NER is restricted to SDZ and OH-SDZ. The model shows good agreement when applied to extraction data measured independently for a Luvisol soil. The combination of sequential extraction data and the conceptual kinetic model enables us to gain further insight into the long-term fate and exposure of sulfonamides in soil.

Determination of soil biodegradation half-lives from simulation testing under aerobic laboratory conditions: a kinetic model approach.

A kinetic model approach for determination of biodegradation half-lives from soil simulation testing is presented. The model describes transformation of the parent compound to metabolites and formation of bound (non-extractable) residues as well as mineralization in soil under aerobic laboratory conditions. Experimental data for several pesticide compounds from various soil simulation tests are used for fitting kinetic rate constants. Formation of bound residues, either from parent or metabolites or from both, can be described by first-order kinetics for all examined compounds. Correlation of kinetic rate constants of primary degradation and formation of bound residues from parent compound suggests a common mechanism, presumably co-metabolic microbial activity, for both processes. Inverse modelling allows for estimation of primary degradation half-life DegT50 instead of disappearance time DT50. Application of the DegT50 approach in PBT assessment might result in a different persistent classification for which the developed model delivers an appropriate evaluation tool.

Emissions of OTNE (Iso-E-super) – Mass flows in sewage treatment plants

The fate and mass flows of OTNE ([1,2,3,4,5,6,7,8-octahydro-2,3,8,8-tetramethylnaphthalen-2yl]ethan-1-one) which is commercialized as Iso-E-Super were studied in three large scale sewage treatment plants (STPs) in detail. The results are compared to 14 smaller ones located in Germany and Switzerland. OTNE inflow concentrations ranged from 4000 to 13,000 ngl(-1) while the effluent concentrations ranged from 500 to 6,900 ngl(-1). It is eliminated from the waste water with 56-64% during waste water treatment. High OTNE concentrations in sewage sludge showed that the elimination was mainly driven by sorption to sludge. This complies with major elimination in the first settling basins (primary settling tanks) while it was removed to a lesser extent in the aeration basin of the activated sludge treatment or in successive biofilters. The mass flows of OTNE in the influent of the German STPs were between 0.9 and 1.9 g per inhabitant and year. In the annual effluents mass flows of OTNE ranged between 0.2 and 0.8 g per inhabitant which complies with data measured in 13 smaller STPs from Switzerland. The similarity of data suggests that the observed mass flow data might be extrapolated to other European regions.

Surface water concentrations of the fragrance compound OTNE in Germany : A comparison between data from measurements and models

Emissions of the fragrance compound OTNE (Iso-E-Super) to surface waters have been investigated by means of a combined analytical (measurements) and modeling approach. The compound is an ingredient in many household products and is emitted into surface waters almost exclusively via the wastewater pathway. Measured concentrations of OTNE in surface waters of the Ruhr river catchment basin ranged from 30 to 100 ng L(-1), and were thus in the same order of magnitude as the polycyclic musks AHTN and HHCB. The geo-referenced exposure model GREAT-ER (Geo-referenced Regional Exposure Assessment Tool for European Rivers) was used to simulate OTNE concentrations in the Ruhr river basin. Model results could plausibly explain monitoring data at all sampling sites when considering the discharge conditions during the sampling period and specific local characteristics. According to the model, approximately half of the total OTNE emissions into the Ruhr river basin are transferred from surface water into the atmosphere and the sediment. Volatilization from lakes was identified as the major removal process of the fragrance compound OTNE. To identify possible regional differences, samples from the Danube in Hungary were also analysed. The OTNE concentrations were in the same order of magnitude (29-810 ng L(-1)) as in the Ruhr catchment, but exhibited higher spatial variability.

Geo-referenced modeling of zinc concentrations in the Ruhr river basin (Germany) using the model GREAT-ER.

Zinc enters surface waters from a variety of different emission sources. The geo-referenced model GREAT-ER (Geo-referenced Regional Exposure Assessment Tool for European Rivers) was applied to simulate spatially resolved zinc concentrations in the Ruhr river basin. The model links geo-referenced emissions (loads) to concentrations at local and regional scales and allows for evaluating the relative importance of emission sources. For each emission from point sources (household, industry, urban runoff) and non-point sources (agriculture, natural background), zinc loads were independently estimated using appropriate reference parameters (number of inhabitants, surface area drained, agricultural area, zinc ore regions). For point emissions from industry and mine drainage loads were taken directly from available data compilations. Simulated total zinc concentrations agree well with monitoring data. The strength of the modeling tool became evident from the unequivocal link that could be established between observed surface water concentrations and the large zinc input from geogenic sources and abandoned mines. These emission sources are regional characteristics of the Ruhr river basin and due to the fact that some regions are relatively rich in zinc ore, which was extracted over a long period of time. Although most of these emissions occur in the upper part of the catchment, they contribute to approximately one-third to the zinc load at the confluence with the Rhine River. Urban emissions from household, traffic (road) and buildings (roof) were shown to be responsible for approximately half of the concentration in the Ruhr at the confluence with the Rhine River.

Influence of Distributional Shape of Substance Parameters on Exposure Model Output

Uncertainty of environmental concentrations is calculated with the regional multimedia exposure model of EUSES 1.0 by considering probability input distributions for aqueous solubility, vapor pressure, and octanol-water partition coefficient, K(ow). Only reliable experimentally determined data are selected from available literature for eight reference chemicals representing a wide substance property spectrum. Monte Carlo simulations are performed with uniform, triangular, and log-normal input distributions to assess the influence of the choice of input distribution type on the predicted concentration distributions. The impact of input distribution shapes on output variance exceeds the effect on the output mean by one order of magnitude. Both are affected by influence and uncertainty (i.e., variance) of the input variable as well. Distributional shape has no influence when the sensitivity function of the respective parameter is perfectly linear. For nonlinear relationships, overlap of probability mass of input distribution with influential ranges of the parameter space is important. Differences in computed output distribution are greatest when input distributions differ in the most influential parameter range.

Analysis of potassium formate in airport storm water runoff by headspace solid-phase microextraction and gas chromatography–mass spectrometry

Potassium formate was extracted from airport storm water runoff by headspace solid-phase microextraction (HS-SPME) and analyzed by GC-MS. Formate was transformed to formic acid by adding phosphoric acid. Subsequently, formic acid was derivatized to methyl formate by adding methanol. Using sodium [(2)H]formate (formate-d) as an internal standard, the relative standard deviation of the peak area ratio of formate (m/z 60) and formate-d (m/z 61) was 0.6% at a concentration of 208.5 mg L(-1). Calibration was linear in the range of 0.5-208.5 mg L(-1). The detection limit calculated considering the blank value was 0.176 mg L(-1). The mean concentration of potassium formate in airport storm water runoff collected after surface de-icing operations was 86.9 mg L(-1) (n=11) with concentrations ranging from 15.1 mg L(-1) to 228.6 mg L(-1).

Mechanistic link between uptake of sulfonamides and bacteriostatic effect: model development and application to experimental data from two soil microorganisms.

Sulfonamides (SA) are antibiotic compounds that are widely used as human and veterinary pharmaceuticals. They are not rapidly biodegradable and have been detected in various environmental compartments. Effects of sulfonamides on microbial endpoints in soil have been reported from laboratory incubation studies. Sulfonamides inhibit the growth of sensitive microorganisms by competitive binding to the dihydropteroate-synthase (DHPS) enzyme of folic acid production. A mathematical model was developed that relates the extracellular SA concentration to the inhibition of the relative bacterial growth rate. Two factors--the anionic accumulation factor (AAF) and the cellular affinity factor (CAF)--determine the effective concentration of an SA. The AAF describes the SA uptake into bacterial cells and varies with both the extra- and intracellular pH values and with the acidic pKa value of an SA. The CAF subsumes relevant cellular and enzyme properties, and is directly proportional to the DHPS affinity constant for an SA. Based on the model, a mechanistic dose-response relationship is developed and evaluated against previously published data, where differences in the responses of Pseudomonas aeruginosa and Panthoea agglomerans toward changing medium pH values were found, most likely as a result of their diverse pH regulation. The derived dose-response relationship explains the pH and pKa dependency of mean effective concentration values (EC50) of eight SA and two soil bacteria based on AAF and CAF values. The mathematical model can be used to extrapolate sulfonamide effects to other pH values and to calculate the CAF as a pH-independent measure for the SA effects on microbial growth.