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1.
Water Res ; 257: 121689, 2024 Jun 15.
Artículo en Inglés | MEDLINE | ID: mdl-38723350

RESUMEN

With the global concerns on antibiotic resistance (AR) as a public health issue, it is pivotal to have data exchange platforms for studies on antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the environment. For this purpose, the NORMAN Association is hosting the NORMAN ARB&ARG database, which was developed within the European project ANSWER. The present article provides an overview on the database functionalities, the extraction and the contribution of data to the database. In this study, AR data from three studies from China and Nepal were extracted and imported into the NORMAN ARB&ARG in addition to the existing AR data from 11 studies (mainly European studies) on the database. This feasibility study demonstrates how the scientific community can share their data on AR to generate an international evidence base to inform AR mitigation strategies. The open and FAIR data are of high potential relevance for regulatory applications, including the development of emission limit values / environmental quality standards in relation to AR. The growth in sharing of data and analytical methods will foster collaboration on risk management of AR worldwide, and facilitate the harmonization in the effort for identification and surveillance of critical hotspots of AR. The NORMAN ARB&ARG database is publicly available at: https://www.norman-network.com/nds/bacteria/.


Asunto(s)
Farmacorresistencia Microbiana , Farmacorresistencia Microbiana/genética , Farmacorresistencia Bacteriana/genética , Antibacterianos/farmacología , Bacterias/genética , Bacterias/efectos de los fármacos , China , Genes Bacterianos
2.
Water Res ; 230: 119539, 2023 Feb 15.
Artículo en Inglés | MEDLINE | ID: mdl-36610182

RESUMEN

A state-of-the-art wide-scope target screening of 2,362 chemicals and their transformation products (TPs) was performed in samples collected within the Joint Danube Survey 4 (JDS4) performed in 2019. The analysed contaminants of emerging concern (CECs) included three major categories: plant protection products (PPPs), industrial chemicals and pharmaceuticals and personal care products (PPCPs). In total, 586 CECs were detected in the samples including 158 PPPs, 71 industrial chemicals, 348 PPCPs, and 9 other chemicals. A wide-variety of sample matrices were collected including influent and effluent wastewater, groundwater, river water, sediment and biota. Forty-five CECs (19 PPPs, 8 industrial chemicals, 18 PPCPs) were detected at levels above their ecotoxicological thresholds (lowest predicted no-effect concentration (PNEC) values) in one or more of the investigated environmental compartments, indicating potential adverse effects on the impacted ecosystems. Among them 12 are legacy substances; 33 are emerging and qualify as potential Danube River Basin Specific Pollutants (RBSPs). Moreover, the efficiency of the wastewater treatment plants (WWTPs) was evaluated using 20 selected performance indicator chemicals. WWTPs showed effective removal (removal rate ≥80%) and medium removal (removal rate 25-80%) for 6 and 8 of the indicator chemicals, respectively. However, numerous contaminants passed the WWTPs with a lower removal rate. Further investigation on performance of WWTPs is suggested at catchment level to improve their removal efficiency. WWTP effluents are proven to be one of the major sources of contaminants in the Danube River Basin (DRB). Other sources include sewage discharges, industrial and agricultural activities. Continuous monitoring of the detected CECs is suggested to ensure water quality of the studied area.


Asunto(s)
Monitoreo del Ambiente , Contaminantes Químicos del Agua , Ríos/química , Ecosistema , Contaminantes Químicos del Agua/análisis , Espectrometría de Masas , Cromatografía de Gases , Preparaciones Farmacéuticas
3.
Environ Sci Eur ; 34(1): 104, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36284750

RESUMEN

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/). Supplementary Information: The online version contains supplementary material available at 10.1186/s12302-022-00680-6.

4.
Water Res ; 199: 117167, 2021 Jul 01.
Artículo en Inglés | MEDLINE | ID: mdl-34015748

RESUMEN

The presence of SARS-CoV-2 RNA in wastewater was first reported in March 2020. Over the subsequent months, the potential for wastewater surveillance to contribute to COVID-19 mitigation programmes has been the focus of intense national and international research activities, gaining the attention of policy makers and the public. As a new application of an established methodology, focused collaboration between public health practitioners and wastewater researchers is essential to developing a common understanding on how, when and where the outputs of this non-invasive community-level approach can deliver actionable outcomes for public health authorities. Within this context, the NORMAN SCORE "SARS-CoV-2 in sewage" database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date. Through offering direct access to underpinning meta-data sets (and describing its use in data interpretation), the NORMAN SCORE database is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance. It is also a tool to engage public health practitioners in discussions on use of the approach, providing an opportunity to build mutual understanding of the demand and supply for data and facilitate the translation of this promising research application into public health practice.


Asunto(s)
COVID-19 , SARS-CoV-2 , Humanos , Salud Pública , ARN Viral , Aguas Residuales
6.
Sci Total Environ ; 681: 475-487, 2019 Sep 01.
Artículo en Inglés | MEDLINE | ID: mdl-31121398

RESUMEN

Seven-day composite effluent samples from a German monitoring campaign including 33 conventional wastewater treatment plants (WWTP) were analyzed for linear alkylbenzene sulfonates (LAS) and alkyl ethoxysulfates (AES) and were screened by wide-scope suspect screening for 1564 surfactants and their transformation products (TPs) by UHPLC-ESI-QTOF-MS. Corresponding seven-day composite influent samples of selected WWTPs showed high influent concentrations as well as very high removal rates for LAS and AES. However, average total LAS and AES effluent concentrations were still 14.4 µg/L and 0.57 µg/L, respectively. The LAS-byproducts di-alkyl tetralin sulfonates (DATSs), the TPs sulfophenyl alkyl carboxylic acids (SPACs) and sulfo-tetralin alkyl carboxylic acids (STACs) reached maximum effluent concentrations of 19 µg/L, 17 µg/L and 5.3 µg/L, respectively. In many cases the sum of the concentration of all LAS-related byproducts and TPs surpassed the concentration of the precursors. High concentrations of up to 7.4 µg/L were found for 41 polyethylenoglycol homologs. Quantified surfactants and their TPs and by-products together accounted for concentrations up to 82 µg/L in WWTP effluents. To determine the risk of individual surfactants and their mixtures, single homologs were grouped by a "weighted carbon number approach" to derive normalized Predicted No-Effect Concentrations (PNEC), based on experimental ecotoxicity data from existing risk assessments, complemented by suitable Quantitative Structure-Activity Relationships (QSAR) predictions. Predicted Environmental Concentrations (PEC) were derived by dividing effluent concentrations of surfactants by local dilution factors. Risks for all analyzed surfactants were below the commonly accepted PEC/PNEC ratio of 1 for single compounds, while contributions to mixture toxicity effects from background levels of LAS and DATS cannot be excluded. Maximum LAS concentrations exceeded half of its PNEC, which may trigger country-wide screening to investigate potential environmental risks.

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