• We investigate pollutants and nutrients in the environment.

  • We elucidate processes and mechanisms in the field and laboratory.

  • We explore biochemical reactions that shape the environment.

  • We study DNA preservation in rocks to investigate environmental biomes.

  • We explore the nanoscale to understand processes of global relevance.

  • We use models to quantify processes and mechanisms.


Latest publications

Remediation of fluoride contaminated water using encapsulated active growing blue-green algae, Phormidium sp.

Elevated fluoride concentration in drinking water is a global concern that impacts health of millions. Developing low cost remediation methods empower communities with fewer resources available to protect their health.

Together with colleagues from CSIR India, and University of Tasmania in Australia, we have demonstrated that fluoride can be removed by using common blue-green algae, Phormidium sp. Using Response Surface Methodology (RSM) we were able to optimize parameters for the highest fluoride removal in our system. Further work is currently ongoing on process optimization to develop a household level pilot scale experimental reactor in a small village in eastern India.

Yamini Mittal, Pratiksha Srivastav, Naresh Kumar, Asheesh KumarYadav
2020 - Environmental Technology and Innovation, in press

Wood-based activated biochar to eliminate organic micropollutants from biologically treated wastewater

Implementing advanced wastewater treatment (WWT) to eliminate organic micropollutants (OMPs) is a necessary step to protect vulnerable freshwater ecosystems and water resources. To this end, sorption of OMP by activated carbon (AC) is one viable technology among others. However, conventional AC production based on fossil precursor materials causes environmental pollution, including considerable emissions of greenhouse gases. In this study, we produced activated biochar (AB) from wood and woody residues by physical activation and evaluated their capability to eliminate OMPs in treated wastewater. Activated biochar produced under optimized conditions sorbed 15 model OMPs, of which most were dissociated at circumneutral pH, to the same or higher extent than commercial AC used as a reference. While wood quality played a minor role, the dosage of the activation agent was the main parameter controlling the capacity of ABs to eliminate OMP. Our results highlight the possibility for local production of AB from local wood or woody residues as a strategy to improve WWT avoiding negative side effects of conventional AC production.

Nikolas Hagemann, Hans-Peter Schmidt, Ralf Kaegi, Mark Boehler, Gabriel Sigmund, Andreas Maccagnan, Christa S. McArdell, Thomas D. Bucheli
2020 - Science of The Total Environment, in press

Deep Learning Neural Network Approach for Predicting the Sorption of Ionizable and Polar Organic Pollutants to a Wide Range of Carbonaceous Materials

Most contaminants of emerging concern are polar and/or ionizable organic compounds, whose removal from engineered and environmental systems is difficult. Carbonaceous sorbents include activated carbon, biochar, fullerenes, and carbon nanotubes, with applications such as drinking water filtration, wastewater treatment, and contaminant remediation. Tools for predicting sorption of many emerging contaminants to these sorbents are lacking because existing models were developed for neutral compounds. A method to select the appropriate sorbent for a given contaminant based on the ability to predict sorption is required by researchers and practitioners alike. Here, we present a widely applicable deep learning neural network approach that excellently predicted the conventionally used Freundlich isotherm fitting parameters log KF and n (R2 > 0.98 for log KF, and R2 > 0.91 for n). The neural network models are based on parameters generally available for carbonaceous sorbents and/or parameters freely available from online databases. A freely accessible graphical user interface is provided.

Gabriel Sigmund, Mehdi Gharasoo, Thorsten Hüffer, Thilo Hofmann
2020 - Environmental Science & Technology, 54: 4583-4591