Search

Abstract Geogenic enrichment of arsenic (As) in groundwater has been a topic of worldwide concern over the past several decades due to the severe health threat to an estimated over one hundred million people. Despite the genetic diversity and the spatial variability of As concentrations, the most common geogenic As-enriched groundwater occurs in flat, low-lying river floodplains and fluvial-lacustrine plains. Within river systems draining the Himalaya, tectonic movement, sedimentological processes and palaeoclimatic optima after the Last Glacial Maximum have created favorable conditions for the formation of high-As aquifer systems mainly within the Late Pleistocene-Holocene deposits. The co-deposition of As-bearing Fe oxides and reactive organic matter within sediments of deltas/floodplains or fluvial-lacustrine plains forms the premise for As release under reducing geochemical environments. However, depending on the reactivity of organic matter and As-bearing Fe oxides, as well as the availability of aqueous sulfate, geochemical mechanisms controlling As enrichment in the groundwater differ between the coastal floodplains of South and Southeast Asia and the fluvial-lacustrine plains of North and Central China. The indigenous geomicrobes thriving to adapt to specific aquifer environments may mediate Fe-S-As biogeochemical cycling responsible for As speciation transformation, dissolution/desorption, and hence mobilization. Hydrologic processes regulated by the local and regional groundwater flow regimes control As transport as well as its spatial distribution. Special attention must be paid to anthropogenic perturbation from intensive groundwater pumping and land use changes that affect the aquifer hydrological conditions and the biogeochemical processes, thus altering groundwater As levels. To decipher the patterns of As variation within the aquifers, an integrated approach characterizing the major sedimentological, hydrobiogeochemical and anthropogenic processes influencing As release and transport needs to be applied to ensure sustainable water supply for domestic and agricultural needs. Highlights • Sedimentogenesis explains high-As groundwater in Late Pleistocene-Holocene aquifers. • As mobilization processes differ between floodplains and fluvial-lacustrine basins. • Anthropogenic influences on As fate must be carefully discerned and managed. • Predicting As needs integrated knowledge of sedimentology and hydrobiogeochemistry. [ABSTRACT FROM AUTHOR]

Biogeochemical hotspots are pervasive at terrestrial-aquatic interfaces, particularly within groundwater-surface water mixing zones (hyporheic zones), and they are critical to understanding spatiotemporal variation in biogeochemical cycling. Here, we use multi 'omic comparisons of hotspots to low-activity sediments to gain mechanistic insight into hyporheic zone organic matter processing. We hypothesized that microbiome structure and function, as described by metagenomics and metaproteomics, would distinguish hotspots from low-activity sediments by shifting metabolism towards carbohydrate-utilizing pathways and elucidate discrete mechanisms governing organic matter processing in each location. We also expected these differences to be reflected in the metabolome, whereby hotspot carbon (C) pools and metabolite transformations therein would be enriched in sugar-associated compounds. In contrast to expectations, we found pronounced phenotypic plasticity in the hyporheic zone microbiome that was denoted by similar microbiome structure, functional potential, and expression across sediments with dissimilar metabolic rates. Instead, diverse nitrogenous metabolites and biochemical transformations characterized hotspots. Metabolomes also corresponded more strongly to aerobic metabolism than bulk C or N content only (explaining 67% vs. 42% and 37% of variation respectively), and bulk C and N did not improve statistical models based on metabolome composition alone. These results point to organic nitrogen as a significant regulatory factor influencing hyporheic zone organic matter processing. Based on our findings, we propose incorporating knowledge of metabolic pathways associated with different chemical fractions of C pools into ecosystem models will enhance prediction accuracy. [ABSTRACT FROM AUTHOR]