Seasonal variations in spatial distribution, mobilization kinetic and toxicity risk of arsenic in sediments of Lake Taihu, China

Numerical sediment quality guidelines (SQGs) for freshwater ecosystems have previously been developed using a variety of approaches. Each approach has certain advantages and limitations which influence their application in the sediment quality assessment process. In an effort to focus on the agreement among these various published SQGs, consensus-based SQGs were developed for 28 chemicals of concern in freshwater sediments (i.e., metals, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and pesticides). For each contaminant of concern, two SQGs were developed from the published SQGs, including a threshold effect concentration (TEC) and a probable effect concentration (PEC). The resultant SQGs for each chemical were evaluated for reliability using matching sediment chemistry and toxicity data from field studies conducted throughout the United States. The results of this evaluation indicated that most of the TECs (i.e., 21 of 28) provide an accurate basis for predicting the absence of sediment toxicity. Similarly, most of the PECs (i.e., 16 of 28) provide an accurate basis for predicting sediment toxicity. Mean PEC quotients were calculated to evaluate the combined effects of multiple contaminants in sediment. Results of the evaluation indicate that the incidence of toxicity is highly correlated to the mean PEC quotient (R(2) = 0.98 for 347 samples). It was concluded that the consensus-based SQGs provide a reliable basis for assessing sediment quality conditions in freshwater ecosystems.

Arsenic poisoning affects millions of people worldwide. Human arsenic intake from rice consumption can be substantial because rice is particularly efficient in assimilating arsenic from paddy soils, although the mechanism has not been elucidated. Here we report that two different types of transporters mediate transport of arsenite, the predominant form of arsenic in paddy soil, from the external medium to the xylem. Transporters belonging to the NIP subfamily of aquaporins in rice are permeable to arsenite but not to arsenate. Mutation in OsNIP2;1 (Lsi1, a silicon influx transporter) significantly decreases arsenite uptake. Furthermore, in the rice mutants defective in the silicon efflux transporter Lsi2, arsenite transport to the xylem and accumulation in shoots and grain decreased greatly. Mutation in Lsi2 had a much greater impact on arsenic accumulation in shoots and grain in field-grown rice than Lsi1. Arsenite transport in rice roots therefore shares the same highly efficient pathway as silicon, which explains why rice is efficient in arsenic accumulation. Our results provide insight into the uptake mechanism of arsenite in rice and strategies for reducing arsenic accumulation in grain for enhanced food safety.

Naturally occurring arsenic in groundwater affects millions of people worldwide. We created a global prediction map of groundwater arsenic exceeding 10 micrograms per liter using a random forest machine-learning model based on 11 geospatial environmental parameters and more than 50,000 aggregated data points of measured groundwater arsenic concentration. Our global prediction map includes known arsenic-affected areas and previously undocumented areas of concern. By combining the global arsenic prediction model with household groundwater-usage statistics, we estimate that 94 million to 220 million people are potentially exposed to high arsenic concentrations in groundwater, the vast majority (94%) being in Asia. Because groundwater is increasingly used to support growing populations and buffer against water scarcity due to changing climate, this work is important to raise awareness, identify areas for safe wells, and help prioritize testing.