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TU Berlin

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Forschung

Towards a Predictive Understanding of Surface Water Quality

Societal background: Surface water quality and the need for a predictive understanding

Poor surface water quality is one of the most urgent environmental problems worldwide. In Germany, 54% of streams and 37% of lakes are polluted (schlecht & unbefriedigend, Umweltbundesamt, 2015). In the U.S., the numbers are equally bad, with 54% of streams and 68% of lakes polluted (EPA, 305(b) list, 2015). Globally, the drinking water supply of 1.8 billion people is contaminated (WHO, 2015). Effective management of these problems requires a predictive understanding of these systems. How will the water quality of this river change if we upgrade that treatment plant? What changes to our agricultural practices are required to clean up this lake? How will climate change affect the health of this estuary? Unfortunately, we presently do not understand our surface water systems enough to answer these questions with confidence. As an example, consider Lake Erie in the U.S. In the 1970s the lake was highly eutrophic, prompting billions of dollars in management actions (i.e., building and upgrading treatment plants). Although the lake initially responded with significant improvements in eutrophic symptoms (e.g., hypoxia, algal biomass), it is now is experiencing a resurgence of eutrophy, including frequent toxic cyanobacteria blooms, that threaten the ecological health and water supply of millions of people. The water quality is now worse than before the management actions were implemented! There is a need to develop a predictive understanding of surface water systems, in other words models and modelers, to support their effective and sustainable management.

 

Problem statement: Models with old chemistry and biology

The main problem with our existing models is that they are based on old science. They were developed in the 1980s and have not been updated with current chemistry and biology knowledge. For example, for nutrient-limited phytoplankton growth, existing operational models still use a simple equation developed in 1942 (Monod). This stands in stark contrast to the tremendous progress made in the basic sciences. There is an opportunity to substantially improve our water quality models by incorporating modern understanding from chemistry and biology.

 

Scientific focus: Water quality at the intersection of chemistry and biology

The general scientific focus of the specialty area Water Quality Engineering is on water quality with a focus on biogeochemistry and microbial ecology. In other words, water quality affected by microbes and vice versa. Presently, we are focusing on two specific problems: Cyanotoxins and emergent contaminants. Cyanotoxins are a group of chemicals produced by various species of cyanobacteria, probably as a way for them to mitigate damage from oxidative stress. Many of them are acutely toxic to dogs, cows and people. Emerging contaminants includes a long list of pharmaceuticals and personal care products, like hormone active chemicals responsible for the feminization of fish and antibiotics.

 

Structure of the Specialty Area: An integrated, cross-disciplinary approach

The specialty area Water Quality Engineering is thematically organized into three laboratories focusing on chemistry, biology and modeling. Each lab is active in research and teaching, and they are connected by a common focus on two large and important societal problems: Emergent contaminants (pharmaceuticals and personal care products) and cyanotoxins. They interact with the common goal to advance and produce an important societal output: A predictive understanding of surface water systems for management. This understanding comes in the form of technology (i.e. models) and people (i.e. modelers).

Lupe

 

Chemistry lab

Models need to be supported by field measurements of chemical concentrations. Model processes, like degradation of sorption of contaminants, need to be investigated and parameterized in the lab. The following activities are performed in the chemistry lab:

·         Sampling and Analysis. A major task of the chemistry lab is to perform sample collection and analysis for cyanotoxins and emergent contaminants. Measuring these compounds is challenging from an analytical perspective, because we are concerned with very low concentrations.

·         Experimentation. Another task is to perform experiments to investigate chemical transformation processes. Often times we are concerned with breakdown products of chemicals, which sometimes are more toxic than the parent compound. Trace contaminants are subject to a number of transformation processes, including hydrolysis, direct and indirect photolysis and biotransformation. One area that is especially important to the two research foci identified above is redox chemistry. This is one (hypothesized) reason why cyanobacteria produce toxins. Also, it is a major part of the indirect photolysis transformation process.

·         Removal of trace organics (i.e. water treatment). Beyond understanding the production and transformation of trace chemicals, practical solutions need to be developed to remove them from the water.

 

Biology lab

Microbes are major players in the water quality of surface water systems. Cyanobacteria produce toxic chemicals that are lethal to dogs, cows and people. Antibiotics select for resistant bacteria that may promote the spread of antibiotic resistance. Bacteria methylate mercury, which magnifies up the food chain and poses a threat to human health. Many substances, including pharmaceuticals and personal care products (PPCPs), are degraded by microbes. The following activities are performed in the biology lab:

·         Sampling and Analysis. Models of microbes in surface waters and their activities need to be supported by biological measurements. This includes traditional measurements, like Chlorophyll a and nutrient concentrations and species cell counts, as well as more modern and specialized observations, like gene, transcript, protein and metabolite levels.

·         Experiments. Understanding the interaction of microbes with chemicals requires performing controlled experiments. Maintaining and culturing microbial systems is a major part of the work in the biology laboratory.

 

Modeling lab

Modeling of environmental fate and transport. Models that address these problems include processes from several disciplines (chemistry, microbiology, limnology, hydrology), so they do not uniquely fit into any one area. An important distinguishing feature of the microbe models we develop and use is that they use an agent-based modeling (ABM) approach. This is different from the traditional environmental modeling approach where microbes are simulated as chemical concentrations (e.g. µg Chlorophyll a / L). In ABM, individual microbes are simulated explicitly. Given that there are large numbers of microbes in natural surface water systems, this naturally results in large computing requirements.

·         Model development. Existing models of surface water systems were developed in the 1970s and 80s and they are based on old biology. A major task of the modeling lab is to update these models with modern chemistry and biology.

·         Model application. Models are applied to surface water systems to test them and demonstrate their utility in making predictions.

The research group tightly integrates modern chemistry and biology with modeling. This is a novel concept and precisely what is lacking in our existing surface water quality management approach and why we presently cannot predict the outcome of our management actions.

aktuelle Projekte

Überblick und Informationen zu aktuellen Projekten des Fachgebiets Wasserreinhaltung. mehr zu: aktuelle Projekte

abgeschlossene Projekte

Überblick und Informationen zu abgeschlossenen Projekten des Fachgebiets Wasserreinhaltung. mehr zu: abgeschlossene Projekte

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