Subsurface environments are complicated systems, and are subject to overlapping physical, chemical, and biological controls. Although a snapshot, the chemistry at any specific time, can provide valuable information regarding the quality of groundwater and geochemical status of the environment, a time series account, that is how the chemistry evolves over time, can help pinpoint how diverse controlling factors collectively shape the evolutionary path of the environment.
Our research questions range from theoretical to practical. For example, how groundwater chemistry influences, and in turn is influenced by, natural microbial populations? What is the fate of arsenic and other contaminants in aquifers? How can numerical simulation integrate our understanding of transport, chemistry, and biology to better understand the environment?
We combine laboratory and field experiments with numerical modeling to address questions of groundwater chemistry.
Our experiments test natural environments directly in the field or indirectly in laboratory reactors. As the experiments progress, we collect a suite of chemical parameters, including those of gasses, aqueous solutions, and solid minerals. Our routine analyses include gas chromatography (GC), ion chromatography (IC), high-performance liquid chromatography (HPLC), and spectrophotometer. Our goal is to monitor closely and comprehensively how the chemistry evolves with time.
Our modeling efforts cover a wide range of scales, from pore fluids to field-scale reactive transport. The goal is to summarize the current understanding of geochemical and biogeochemical processes in the environment, to explore numerically the gap between our current understanding and the complexity of natural systems, and to identify critical processes that control reaction paths of geochemical and biogeochemical systems.
A paper coauthored by Jin, Roden, and Giska is in press in Geomicrobiology Journal; the title is Geomicrobial kinetics: Extrapolating laboratory studies to natural environments. In this paper, we proposed a best-choice approach for simulating microbial reactions in geochemical systems.