Rapid sand filters (RSF) are an established and widely applied technology for groundwater treatment. Yet, the underlying interwoven biological and physical-chemical reactions controlling the sequential removal of iron, ammonia and manganese remain poorly understood. To resolve the contribution and interactions between the individual reactions, we studied two full-scale drinking water treatment plant configurations, namely (i) one dual-media (anthracite and quartz sand) filter and (ii) two single-media (quartz sand) filters in series. In situ and ex situ activity tests were combined with mineral coating characterization and metagenome-guided metaproteomics along the depth of each filter. Both plants exhibited comparable performances and process compartmentalization, with most of ammonium and manganese removal occurring only after complete iron depletion. The homogeneity of the media coating and genome-based microbial composition within each compartment highlighted the effect of backwashing, namely the complete vertical mixing of the filter media. In stark contrast to this homogeneity, the removal of the contaminants was strongly stratified within each compartment, and decreased along the filter height. This apparent and longstanding conflict was resolved by quantifying the expressed proteome at different filter heights, revealing a consistent stratification of proteins catalysing ammonia oxidation and protein-based relative abundances of nitrifying genera (up to 2 orders of magnitude difference between top and bottom samples). This implies that microorganisms adapt their protein pool to the available nutrient load at a faster rate than the backwash mixing frequency. Ultimately, these results show the unique and complementary potential of metaproteomics to understand metabolic adaptations and interactions in highly dynamic ecosystems.@en

Arsenic is mainly removed from groundwater by adsorption onto, or co-precipitation with iron flocs and -deposits. The efficiency of this process depends on various factors, amongst which the oxidation state of arsenic, adsorption competition or poor iron floc removal. The aim of this study was to assess the adsorption efficiency of arsenic in full-scale groundwater treatment plants in the Netherlands. Adsorption efficiency is dependent on the concentration of adsorbent (Fe) and adsorbate (As), both of which vary considerably at the various treatment plants. To allow comparing treatment plants at these different Fe and As concentrations, the framework of a linearized isotherm graph was used. As a reference, jar tests were executed to derive adsorption isotherms of As(III) and As(V) based on co-removal with Fe2+ precipitation. All treatment plants have a higher adsorption efficiency than the As(III) reference, and lower adsorption efficiency than the As(V) reference. Treatment plants with an efficiency close to the As(III) reference may suffer from incomplete arsenic oxidation, although other causes cannot be ruled out. Classifying removal efficiency can be used in an initial research phase to identify treatment plants with relatively poor performance as candidates for improvement. Furthermore, treatment plants can be grouped into categories with similar adsorption efficiency, aiding in identification of common factors responsible for As removal.@en

Een deel van het Nederlandse drinkwater wordt geproduceerd uit oeverfiltraat. De vraag is in hoeverre oeverfiltratie organische microverontreinigingen kan verwijderen. In deze studie is een voorspellend model ontwikkeld op basis van functionele groepen in de molecuulstructuur van deze stoffen. Het model bleek in staat de biodegradeerbaarheid van minstens 70 procent van de organische microverontreinigingen goed te kunnen voorspellen. Het model was minder betrouwbaar voor stoffen waarvan de voorspelde biodegradatiesnelheid zeer laag was en voor stoffen die amide- of aminegroepen bevatten. De bredere praktische toepasbaarheid van het model werd onderzocht met behulp van pyrazool en dimethoaat.@en

Een deel van het Nederlandse drinkwater wordt geproduceerd uit oeverfiltraat. De vraag is in hoeverre oeverfiltratie organische microverontreinigingen kan verwijderen. In deze studie is een voorspellend model ontwikkeld op basis van functionele groepen in de molecuulstructuur van deze stoffen. Het model bleek in staat de biodegradeerbaarheid van minstens 70 procent van de organische microverontreinigingen goed te kunnen voorspellen. Het model was minder betrouwbaar voor stoffen waarvan de voorspelde biodegradatiesnelheid zeer laag was en voor stoffen die amide- of aminegroepen bevatten. De bredere praktische toepasbaarheid van het model werd onderzocht met behulp van pyrazool en dimethoaat.@en