Bioremediation of mine-affected water

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Rapid new advances in geochemical, genomic and informatic science and technology are transforming the way that engineers design, monitor, control and operate complex biologically-based processes for remediation of contaminated water, a cause for great concern in most parts of the world. Mining is an example of one economically important Canadian industry where its sustainability depends on meeting increasingly more stringent water quality guidelines. Water treatment technologies that leverage natural geochemical and biological processes versus conventional chemical methods are gaining support as more cost-effective and reliable approaches to remove chemical compounds from mine-influenced water (MIW) so as to protect aquatic ecosystems. Widespread acceptance and adoption of these naturally based water treatment approaches are hindered by lack of knowledge on the myriad of interrelated factors that influence their effectiveness. We will focus on high-priority constituents of concern that require urgent attention due to their imminent impact on the environment. These include selenium, nitrogen compounds such as nitrate and ammonium and sulphate. Current methods to remove these require several steps, are energy intensive and produce large volumes of sludge. The new processes that we will develop leverage the metabolic potential of enriched microbial consortia from mine sites that have the capacity to simultaneously remove more than one compound at a time. This has the potential to greatly simplify MIW treatment reducing costs and increasing effectiveness. However, due to the complexity of microbe-microbe interactions and the effect of environmental variables on the dynamics of microbial population composition and metabolism, it is challenging to maintain reliable bioreactor performance and successful treatment. In our work, we propose to better understand these complexities and construct dynamic models that will be used to develop novel bioaugmentation and biostimulation strategies to make MIW treatment more reliable, cost-effective and less impactful on the environment. To achieve these goals we will use high-resolution characterization and monitoring enabling technologies. We propose to resolve mechanisms of contaminant removal to the chemical species level using chromatography and mineralogical methods. Sequencing of genetic biomarkers and whole DNA will be used to identify microorganisms and assemble their genomes so that microbial population structure and function can be tracked over time and under different conditions. Chemistry and genetic data from laboratory and field bioreactors will be combined using emerging machine-learning approaches for feature selection and modeling that will inform new process control philosophies that we will test to improve the effectiveness and reliability of MIW treatment.