Increasing levels of dissolved organic matter (DOM) in watercourses in the northern hemisphere are mainly due to reduced acid rain, climate change, and changes in agricultural practices. However, their impacts vary in time and space. To predict how DOM responds to changes in environmental pressures, we need to differentiate between allochthonous and autochthonous sources as well as identify anthropogenic DOM. In this study we distinguish between allochthonous, autochthonous, and anthropogenic sources of DOM in a diverse watercourse network by assessing effects of land cover on water quality and using DOM characterization tools. The main sources of DOM at the studied site are forests discharging allochthonous humic DOM, autochthonous fulvic DOM, and runoff from urban sites and fish farms with high levels of anthropogenic DOM rich in protein-like material. Specific UV absorbency (sUVa) distinguishes allochthonous DOM from autochthonous and anthropogenic DOM. Anthropogenic DOM differs from autochthonous fulvic DOM by containing elevated levels of protein-like material. DOM from fishponds is distinguished from autochthonous and sewage DOM by having high sUVa. DOM characteristics are thus valuable tools for deconvoluting the various sources of DOM, enabling water resource managers to identify anthropogenic sources of DOM and predict future trends in DOM.

Increasing levels of dissolved organic matter (DOM) in watercourses in the Northern hemisphere is mainly due to reduced acid rain, climate change, and changes in agricultural practices. However, their impacts vary in time and space. To predict how DOM respond to changes in environmental pressures we need to differentiate between allochthonous and autochthonous sources, as well as identify anthropogenic DOM. In this study we distinguish between allochthonous, autochthonous, and anthropogenic sources of DOM in a diverse watercourse network using DOM characterization tools and by assessing effects of land cover on water quality. Main sources of DOM are forests discharging allochthonous humic DOM, autochthonous fulvic DOM, and runoff from urban sites and fish farms with high levels of anthropogenic DOM rich in protein like material. Specific UV absorbency (sUVa) distinguish allochthonous DOM from autochthonous and anthropogenic DOM. Anthropogenic DOM differ from autochthonous fulvic DOM by containing elevated levels of protein like material. DOM from fishponds is distinguished from autochthonous and sewage DOM by having high sUVa. DOM characteristics thus provide valuable tools for deconvoluting the various sources of DOM allowing water resource managers to predict future trends in DOM and detect anthropogenic sources of DOM.

There are several process design options for enhanced coagulation-filtration in drinking water treatment plants (DWTPs). This study compares the carbon footprint and economic impact of two common process designs based on enhanced coagulation-filtration with pH, Ca, and alkalinity adjustment for corrosion control. The process designs are direct filtration (DF) using Al coagulant with limewater (DF-Al) and contact filtration (CF) using Fe coagulant with alkaline filter layers (CF-Fe). The operational data are retrieved from full-scale DWTPs. The results show that the carbon footprint from operations is five times larger for the DF-Al compared to the CF-Fe. Operational costs covering chemicals and energy are almost 30% higher for the DF-Al. Simplified material intensity estimations for the construction phase show that the carbon footprint and investment cost increase with increasing process area, which are larger for the DF-Al. Therefore, to reduce environmental impacts and costs, the design of drinking water treatment processes should be carefully considered even for very similar processes. The results should motivate both water professionals and decision-makers to include a carbon footprint evaluation as a routine step in the DWTP selection and design phases.

Several actors have an impact on the quality of drinking water, but ultimately drinking water treatment plants (DWTPs) play a decisive role in ensuring that water quality complies with public regulations. Several developing technologies are combined in water treatment processes. In this paper, we are analysing the technological development of DWTPs in the South Bohemian region of the Czech Republic. The empirical basis is five DWTPs of varying size, and data are gathered through semi-structured interviews with relevant staff inside and outside of the five DWTPs. This study identifies the interplay of factors driving technological development: public regulations, the economic capacity of local DWTP owners together with subsidies from the European Union and national authorities, political priorities by local authorities, and the knowledge network. The paper addressess learning–knowledge–change processes of DWTPs, thereby contributing to our understanding of developing competence in producing drinking water. Generally, large DWTPs are front-runners in introducing new technologies while the smaller ones are lagging. Still, private companies operating small plants on behalf of municipal owners ensure that those DWTPs are part of a wider knowledge network, aiding to introduce a necessary and cost-effective upgrade to treatment steps

Levels of dissolved natural organic matter (DNOM) are increasing in our boreal watercourses. This is manifested by an apparent increase in its yellow to brown colour of the water, i.e., browning. Sound predictions of future changes in colour of our freshwaters is a prerequisite for predicting effects on aquatic fauna and a sustainable operation of drinking water facilities using surface waters as raw water sources. A model for the effect of climate on colour (mg Pt L^-1) has been developed for two surface raw water sources in Scotland, i.e., at Bracadale and Port Charlotte. Both sites are situated far out on the Scottish west coast, without major impact of acid rain, with limited amounts of frost, and with limited recent land-use changes. The model was fitted to 15 years long data-series on colour measurements, provided by Scottish Water, at the two sites. Meteorological data were provided by UK Met. The models perform well for both sites in simulating the variation in monthly measured colour, explaining 89 and 90% of the variation at Bracadale and Port Charlotte, respectively. These well fitted models were used to predict future changes in colour due to changes in temperature and precipitation based on median climate data from a high emission climate RCP8.5 scenario from the HadCM3 climate model (UKCP18). The model predicted an increase in monthly average colour during growing season at both sites from about 150 mg Pt L^-1 to about 200 mg Pt L^-1 in 2050–2079. Temperature is found to be the most important positively driver for colour development at both sites.