Arsenic Release Metabolically Limited to Permanently Water-Saturated Soil in Mekong Delta

Microbial reduction of arsenic-bearing iron oxides in the deltas of South and Southeast Asia produces widespread arsenic-contaminated groundwater. Organic carbon is abundant both at the surface and within aquifers, but the source of organic carbon used by microbes in the reduction and release of arsenic has been debated, as has the wetland type and sedimentary depth where release occurs. Here we present data from fresh-sediment incubations, in situ model sediment incubations and a controlled field experiment with manipulated wetland hydrology and organic carbon inputs. We find that in the minimally disturbed Mekong Delta, arsenic release is limited to near-surface sediments of permanently saturated wetlands where both organic carbon and arsenic-bearing solids are sufficiently reactive for microbial oxidation of organic carbon and reduction of arsenic-bearing iron oxides. In contrast, within the deeper aquifer or seasonally saturated sediments, reductive dissolution of iron oxides is observed only when either more reactive exogenous forms of iron oxides or organic carbon are added, revealing a potential thermodynamic restriction to microbial metabolism. We conclude that microbial arsenic release is limited by the reactivity of arsenic-bearing iron oxides with respect to native organic carbon, but equally limited by organic carbon reactivity with respect to the native arsenic-bearing iron oxides

Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments

The use of low-cost air quality sensors for air pollution research has outpaced our understanding of their capabilities and limitations under real-world conditions, and there is thus a critical need for understanding and optimizing the performance of such sensors in the field. Here we describe the deployment, calibration, and evaluation of electrochemical sensors on the island of Hawai`i, which is an ideal test bed for characterizing such sensors due to its large and variable sulfur dioxide (SO2) levels and lack of other co-pollutants. Nine custom-built SO2 sensors were co-located with two Hawaii Department of Health Air Quality stations over the course of 5 months, enabling comparison of sensor output with regulatory-grade instruments under a range of realistic environmental conditions. Calibration using a nonparametric algorithm (k nearest neighbors) was found to have excellent performance (RMSE < 7 ppb, MAE < 4 ppb, r2 > 0.997) across a wide dynamic range in SO2 (< 1 ppb, > 2 ppm). However, since nonparametric algorithms generally cannot extrapolate to conditions beyond those outside the training set, we introduce a new hybrid linear–nonparametric algorithm, enabling accurate measurements even when pollutant levels are higher than encountered during calibration. We find no significant change in instrument sensitivity toward SO2 after 18 weeks and demonstrate that calibration accuracy remains high when a sensor is calibrated at one location and then moved to another. The performance of electrochemical SO2 sensors is also strong at lower SO2 mixing ratios (< 25 ppb), for which they exhibit an error of less than 2.5 ppb. While some specific results of this study (calibration accuracy, performance of the various algorithms, etc.) may differ for measurements of other pollutant species in other areas (e.g., polluted urban regions), the calibration and validation approaches described here should be widely applicable to a range of pollutants, sensors, and environments