Center for Embedded Network Sensing

The presence of arsenic in the groundwater has led to the largest environmental poisoning in history; tens of millions of people in the Ganges Delta continue to drink groundwater that is dangerously contaminated with arsenic (As). Rice fields receive large loads of arsenic with irrigation water and provide recharge to the underlying aquifer. It is currently not known whether rice fields are a sink or source of arsenic in the hydrologic system. In the dry season, as As(III)-containing minerals are oxidized, As(V) is released and will adhere to Fe hydr(oxide) minerals. When sediments are inundated with water, reducing conditions will then drive reduction of Fe hydr(oxides) and release of As. We have been intensively studying a field site in Munshiganj, Bangladesh with extremely high levels of arsenic in groundwater (up to 1.2 mg/L). To better understand geochemical and microbial processes leading to As mobilization in surface sediment, we deployed sensors to take temporally dense measurements across our experimental rice paddy. Data collected in both 2006 and 2007 showed trends in geochemical parameters indicating that diurnal, possibly plant-induced, processes may be important. Over a two month period, nitrate concentrations decrease consistently each day as ammonium levels increase, presumably through temperature driven reductive processes. Nitrate concentrations in the subsurface then increase while ammonium levels decrease, possibly due to root oxygen leakage or rapid infiltration of oxygen rich surface water. Using sediment from the rice paddy and artificial irrigation water, laboratory microcosms were constructed to simulate the diurnal cycles observed at the field site. In carbon-ammended treatments, Fe and As cycling can occur on the order of days. Oscillations in redox conditions on diurnal as well as seasonal time scales may be important in the mobilization of arsenic into aquifers. By elucidating As mobilization mechanisms at an experimental rice paddy, this work could ultimately lead to solutions that minimize As exposure in critical populations.