Tradeoff between groundwater arsenite removal efficiency and current production in the self-powered air cathode
Yanxiao Si1, Guanghe Li1, Yue Wu1
1School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing, 100084, China; Key Laboratory of Solid Waste Management and Environment Safety (Tsinghua University), Ministry of Education, Beijing, 100084, China.
Abstract:
Naturally occurring arsenic enrichment in aquifers posts a huge threat to drinking water safety. To achieve energy-efficient arsenite [As(III)] removal, a self-powered iron electrocoagulation was developed that coupled iron corrosion anode with oxygen reduction air cathode for simultaneous As(III) oxidation and removal. Activated carbon (AC), which favored the four-electron oxygen reduction reaction (ORR, O2+4e-+4H+→2H2O, E0' = 0.816 V), and carbon black (CB), which favored two-electron ORR (O2+2e-+2H+→H2O2, E0' = 0.283 V), were evaluated for As(III) removal efficiency and current production performance. The comparison showed a tradeoff between higher current (i.e., higher iron corrosion rate) attributed to the higher reduction potential with four-electron ORR, and higher H2O2 production for improved As(III) oxidation with two-electron ORR yet the lower reduction potential The CB cathode that favored H2O2 production had the best As(III) removal of 99.2 ± 0.4% and the lowest maximum power density of 60 ± 0.3 mW m-2, while the AC cathode showed the opposite trend. These results suggested that cathode catalysts need to be carefully evaluated for the balance of As(III) removal and current production to provide a sustainable and effective solution for groundwater As(III) removal.
Related Concept Videos
Production Efficiency
C4 Pathway and CAM
C4 Pathway
The C4 pathway is used by plants such as...
Oxidation-Reduction Reactions
Nuclear Power
Nuclear Fuels
Nuclear fuel consists of a fissile isotope, such as uranium-235, which must be present in sufficient quantity to provide a...
Power
Air-entraining Agents


