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Alexander J.,Karlsruhe Institute of Technology | Bollmann A.,Betriebs und Forschungslaboratorium | Seitz W.,Betriebs und Forschungslaboratorium | Schwartz T.,Karlsruhe Institute of Technology
Science of the Total Environment | Year: 2015

The dissemination of medically relevant antibiotic resistance genes (ARGs) (blaVIM-1, vanA, ampC, ermB, and mecA) and opportunistic bacteria (Enterococcus faecium/. faecalis, Pseudomonas aeruginosa, Enterobacteriaceae, Staphylococcus aureus, and CNS) was determined in different anthropogenically influenced aquatic habitats in a selected region of Germany. Over a period of two years, four differently sized wastewater treatment plants (WWTPs) with and without clinical influence, three surface waters, four rain overflow basins, and three groundwater sites were analyzed by quantitative Polymerase Chain Reaction (qPCR). Results were calculated in cell equivalents per 100. ng of total DNA extracted from water samples and per 100. mL sample volume, which seems to underestimate the abundance of antibiotic resistance and opportunistic bacteria. High abundances of opportunistic bacteria and ARG were quantified in clinical wastewaters and influents of the adjacent WWTP. The removal capacities of WWTP were up to 99% for some, but not all investigated bacteria. The abundances of most ARG targets were found to be increased in the bacterial population after conventional wastewater treatment. As a consequence, downstream surface water and also some groundwater compartments displayed high abundances of all four ARGs. It became obvious that the dynamics of the ARG differed from the fate of the opportunistic bacteria. This underlines the necessity of an advanced microbial characterization of anthropogenically influenced environments. © 2015 Elsevier B.V. Source


Jekel M.,TU Berlin | Ruhl A.S.,TU Berlin | Meinel F.,TU Berlin | Zietzschmann F.,TU Berlin | And 18 more authors.
Environmental Sciences Europe | Year: 2013

In urban areas, water often flows along a partially closed water cycle in which treated municipal wastewater is discharged into surface waters which are one source of raw waters used for drinking water supply. A number of organic micro-pollutants (OMP) can be found in different water compartments. In the near future, climatic and demographic changes will probably contribute to an increase of OMP and antibiotic-resistant pathogens in aquatic ecosystems. The occurrence of OMP, possible adverse effects on aquatic organisms and human health and the public perception must be carefully assessed to properly manage and communicate potentially associated risks and to implement appropriate advanced treatment options at the optimum location within the water cycle. Therefore, the interdisciplinary research project ASKURIS focuses on identification and quantification, toxicological assessment and removal of organic micro-pollutants and antibiotic-resistant pathogens in the Berlin water cycle, life cycle-based economic and environmental assessment, public perception and management of potential risks. © 2013 Jekel et al.; licensee Springer. Source


Schymanski E.L.,Eawag - Swiss Federal Institute of Aquatic Science and Technology | Singer H.P.,Eawag - Swiss Federal Institute of Aquatic Science and Technology | Slobodnik J.,R.O.S.A. | Ipolyi I.M.,R.O.S.A. | And 25 more authors.
Analytical and Bioanalytical Chemistry | Year: 2015

In this article, a dataset from a collaborative non-target screening trial organised by the NORMAN Association is used to review the state-of-the-art and discuss future perspectives of non-target screening using high-resolution mass spectrometry in water analysis. A total of 18 institutes from 12 European countries analysed an extract of the same water sample collected from the River Danube with either one or both of liquid and gas chromatography coupled with mass spectrometry detection. This article focuses mainly on the use of high resolution screening techniques with target, suspect, and non-target workflows to identify substances in environmental samples. Specific examples are given to emphasise major challenges including isobaric and co-eluting substances, dependence on target and suspect lists, formula assignment, the use of retention information, and the confidence of identification. Approaches and methods applicable to unit resolution data are also discussed. Although most substances were identified using high resolution data with target and suspect-screening approaches, some participants proposed tentative non-target identifications. This comprehensive dataset revealed that non-target analytical techniques are already substantially harmonised between the participants, but the data processing remains time-consuming. Although the objective of a “fully-automated identification workflow” remains elusive in the short term, important steps in this direction have been taken, exemplified by the growing popularity of suspect screening approaches. Major recommendations to improve non-target screening include better integration and connection of desired features into software packages, the exchange of target and suspect lists, and the contribution of more spectra from standard substances into (openly accessible) databases. [Figure not available: see fulltext.] © 2015 Springer-Verlag Berlin Heidelberg Source


Fleischer S.,Betriebs und Forschungslaboratorium | Fleischer S.,Aalen University of Applied Sciences | Weiss S.C.,Betriebs und Forschungslaboratorium | Lucke T.,Betriebs und Forschungslaboratorium | And 3 more authors.
Ozone: Science and Engineering | Year: 2015

Although oxamic acid has been identified as an ozone oxidation product from several precursor compounds, concentrations for drinking water have not been published previously. This study shows results from a full-scale drinking water treatment plant, noting that the mean concentrations for oxamic acid reached 21.3 μg/L after ozonation and prior to filtration. Subsequent multiple-layer filtration removed 85% of oxamic acid on average, and mean concentrations in drinking water were 2 μg/L. Up to 5.9% of the oxamic acid found in ozone-treated groundwater may be formed from Chloridazon metabolites. Copyright © 2015 International Ozone Association. Source


Muller A.,Betriebs und Forschungslaboratorium | Muller A.,Luneburg University | Schulz W.,Betriebs und Forschungslaboratorium | Ruck W.K.L.,Luneburg University | Weber W.H.,Betriebs und Forschungslaboratorium
Chemosphere | Year: 2011

Non-target screening via high performance liquid chromatography-mass spectrometry (HPLC-MS) has gained increasingly in importance for monitoring organic trace substances in water resources targeted for the production of drinking water. In this article a new approach for evaluating the data from non-target HPLC-MS screening in water is introduced and its advantages are demonstrated using the supply of drinking water as an example. The crucial difference between this and other approaches is the comparison of samples based on compounds (features) determined by their full scan data. In so doing, we take advantage of the temporal, spatial, or process-based relationships among the samples by applying the set operators, UNION, INTERSECT, and COMPLEMENT to the features of each sample. This approach regards all compounds, detectable by the used analytical method. That is the fundamental meaning of non-target screening, which includes all analytical information from the applied technique for further data evaluation. In the given example, in just one step, all detected features (1729) of a landfill leachate sample could be examined for their relevant influences on water purification respectively drinking water. This study shows that 1721 out of 1729 features were not relevant for the water purification. Only eight features could be determined in the untreated water and three of them were found in the final drinking water after ozonation. In so doing, it was possible to identify 1-adamantylamine as contamination of the landfill in the drinking water at a concentration in the range of 20ngL-1. To support the identification of relevant compounds and their transformation products, the DAIOS database (Database-Assisted Identification of Organic Substances) was used. This database concept includes some functions such as product ion search to increase the efficiency of the database query after the screening. To identify related transformation products the database function " transformation tree" was used. © 2011 Elsevier Ltd. Source

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