Abwasser

Biotransformation is the most important process removing manmade chemicals from the environment, yet mechanisms governing this essential ecosystem function are underexplored. To understand these mechanisms, we conducted experiments in flow-through systems, by colonizing stream biofilms under different conditions of mixing river water with treated (and ultrafiltered) wastewater. We performed biotransformation experiments with those biofilms, using a set of 75 micropollutants, and could disentangle potential mechanisms determining the biotransformation potential of stream biofilms. We showed that the increased biotransformation potential downstream of wastewater treatment plants that we observed for specific micropollutants contained in household wastewaters (downstream effect) is caused by microorganisms released with the treated effluent, rather than by the in-stream exposure to those micropollutants. Complementary data from 16S rRNA amplicon-sequencing revealed 146 amplicon sequence variants (ASVs) that followed the observed biotransformation patterns. Our results align with findings for community tolerance, and provide clear experimental evidence that microorganisms released with treated wastewater integrate into downstream biofilms and impact crucial ecosystem functions.

Bioaccumulation and trophic transfer of persistent legacy contaminants have been intensively characterized, but little is known on the contaminants of emerging concern (CECs) in freshwater food webs. Herein, we comprehensively screened CECs with a focus on polar substances and further evaluated their trophic transfer behavior in selected items from the food web of Lake Templin, Germany. Weselected one plankton, two mussel, and nine fish samples covering three trophic levels. With an effective multi-residue sample preparation method and high-resolution mass spectrometry-based target, suspect, and non-target screening, we characterized 477 targets and further screened unknown features in complex biota matrices. Of the 477 targets, 145 were detected and quantified in at least one species (0.02–3640 ng/g, dry weight). Additionally, the suspect and non-target analysis with experimental mass spectra libraries and in silico techniques (MetFrag and SIRIUS4/CSI:FingerID) enabled further identification of 27 unknown compounds with 19 confirmed by reference standards. Overall, the detected compounds belong to a diverse group of chemicals, including 71 pharmaceuticals, 27 metabolites, 26 pesticides, 16 per- and polyfluoroalkyl substances (PFASs), 4 plasticizers, 3 flame retardants, 11 other industrial chemicals and 14 others. Moreover, we determined the trophic magnification factor (TMF) of 34 polar CECs with >80% detection frequency, among which 6 PFASs including perfluorooctane sulfonic acid (PFOS), perfluorodecanoic acid (PFDA), perfluorohexane sulfonic acid (PFHxS), perfluorotridecanoic acid (PFTrA), perfluorotetradecanoic acid (PFTeA), and perfluoroundecanoic acid (PFUnA), exhibited biomagnification potential (TMF =1.8 - 4.2, p < 0.05), whereas 5 pharmaceuticals (phenazone, progesterone, venlafaxine, levamisole, and lidocaine) and 1 personal care product metabolite (galaxolidone) showed biodilution potential (TMF = 0.4 - 0.6, p < 0.05).

Oxidative treatment of seawater in coastal and shipboard installations is applied to control biofouling and/or minimize the input of noxious or invasive species into the marine environment. This treatment allows a safe and efficient operation of industrial installations and helps to protect human health from infectious diseases and to maintain the biodiversity in the marine environment. On the downside, the application of chemical oxidants generates undesired organic compounds, so-called disinfection by-products (DBPs), which are discharged into the marine environment. This article provides an overview on sources and quantities of DBP inputs, which could serve as basis for hazard analysis for the marine environment, human health and the atmosphere. During oxidation of marine water, mainly brominated DBPs are generated with bromoform (CHBr₃) being the major DBP. CHBr₃ has been used as an indicator to compare inputs from different sources. Total global annual volumes of treated seawater inputs resulting from cooling processes of coastal power stations, from desalination plants and from ballast water treatment in ships are estimated to be 470-800 × 10⁹ m³, 46 × 10⁹ m³ and 3.5 × 10⁹ m³, respectively. Overall, the total estimated anthropogenic bromoform production and discharge adds up to 13.5-21.8 × 10⁶ kg/a (kg per year) with contributions of 11.8-20.1 × 10⁶ kg/a from cooling water treatment, 0.89 × 10⁶ kg/a from desalination and 0.86 × 10⁶ kg/a from ballast water treatment. This equals approximately 2–6% of the natural bromoform emissions from marine water, which is estimated to be 385-870 × 10⁶ kg/a.

BACKGROUND: The effective reproductive number, R_e, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, R_e estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change.
OBJECTIVES: We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate R_e in near real time, independent of clinical data and without the associated biases.
METHODS: We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based R_e from this incidence.
RESULTS: The method to estimate R_e from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the R_e estimates from case report data as R_e estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer R_e.
DISCUSSION: To our knowledge, this is the first time R_e has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens.