How the speciation of arsenic affects its interaction with reactive iron minerals, Dr Jeffrey Paulo H. Perez

INVITATION
#ESRFscience Live Online Seminars
"How the speciation of arsenic affects its interaction with reactive iron minerals"
Monday, July 18th, 10:30 - online -
Presented by Dr. Jeffrey Paulo H. Perez, GFZ German Research Centre for Geosciences
Please click HERE for the replay of the webinar
Webinar ID: 956 1276 7176
Passcode: 843542
ABSTRACT
Green rust is a mixed valence layered iron mineral that often forms in Fe2+-rich and oxygen-poor environments. Its presence controls nutrient availability and the mobility of many contaminant (e.g., As, Cr).1 Among these, arsenic is one toxic element for which green rust is the Fe(II)-bearing mineral with one of the highest arsenic uptake capacity in circum-neutral conditions.2 However, the mechanism and interdependencies between green rust and arsenic species, and their role in formation and transformation reactions in the subsurface, are still poorly understood. Combining high-resolution electron microscopy (S/TEM) and synchrotron-based X-ray spectroscopy and scattering techniques (XAS/PDF), I will show how the oxidation state of arsenic highly affects its interaction with iron minerals, and green rust in particular. I will discuss the effect on (i) As removal efficiency and its corresponding (ii) binding mechanism, and discuss how these interactions change (iii) mineral formation and transformation kinetics and (iv) the long-term stability of As-bearing green rusts.3,4 I will also present how these results provide new insights on mineral-contaminant interactions in anoxic environments, as well as its potential for mineral-based technologies for groundwater remediation
References
(1) Usman et al., Chem. Rev. 2018, 118 (7), 3251-3304. (2) Perez et al., Sci. Total Environ. 2019, 648, 1161-1170. (3) Perez et al., Environ. Sci. Technol. 2020, 54 (6), 3297-3305. (4) Perez et al., Environ. Sci.: Nano 2021, 8, 2950-2963.
Funding: The organisation of this online seminar series is supported by STREAMLINE, a European project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870313.