Bioremediation of mine-affected water

地球化学、基因组学和信息科学技术的快速新进展正在改变工程师设计、监测、控制和操作复杂的基于生物的污染水修复过程的方式，这是世界上大多数地区非常关注的问题。采矿业是加拿大一个重要的经济产业，其可持续性取决于满足越来越严格的水质准则。与传统化学方法相比，利用自然地球化学和生物过程的水处理技术正在获得支持，成为从受地雷影响的水中去除化学化合物以保护水生生态系统的更具成本效益和可靠的方法。由于对影响其有效性的无数相互关联的因素缺乏了解，这些天然水处理方法的广泛接受和采用受到阻碍。我们将重点关注那些因其对环境的紧迫影响而需要紧急关注的高度优先的关切事项。这些包括硒、氮化合物如硝酸盐和铵以及硫酸盐。目前去除这些的方法需要几个步骤，是能源密集型的，并产生大量的污泥。我们将开发的新工艺利用了来自矿场的富集微生物菌群的代谢潜力，这些菌群有能力同时去除一种以上的化合物。这有可能大大简化MIW处理，降低成本并提高效率。然而，由于微生物-微生物相互作用的复杂性以及环境变量对微生物种群组成和代谢动力学的影响，保持可靠的生物反应器性能和成功的处理是具有挑战性的。在我们的工作中，我们建议更好地理解这些复杂性，并构建动态模型，用于开发新的生物增强和生物刺激策略，使MIW治疗更可靠，更具成本效益，对环境的影响更小。* * 为了实现这些目标，我们将使用高分辨率表征和监控使能技术。我们建议使用色谱法和矿物学方法来解决污染物去除到化学物种水平的机制。基因生物标志物和整个DNA的测序将用于识别微生物并组装其基因组，以便随着时间的推移和在不同条件下跟踪微生物种群结构和功能。来自实验室和现场生物反应器的化学和遗传数据将使用新兴的机器学习方法进行特征选择和建模，这将为我们将测试的新过程控制理念提供信息，以提高MIW处理的有效性和可靠性。

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.