Optimisation of arsenic-rich MIne wastes phytostabilisation strategies: prediction of impacts on water and pollutants bioavailability to plants linked with MicrObial activities – oMIMo

This objective is addressed by the oMIMo consortium (BRGM, ISTO, Li2D-DRF/CEA and LEB/ADERA) through an interdisciplinary approach combining geochemistry, digital modeling, plant physiology, microbiology and omics approaches with a good operational knowledge of the management of old mining sites. The oMIMo methodology is based on a controlled scenario of assisted phytostabilisation. oMIMo proposes to integrate into the MTR data indicative of active microbial processes linked to the metabolisms of As, Fe and S. A mesocosm was filled with 1200 kg of tailings from a tin (Sn) mine in March 2023. This pilot experiment reproduces on a metric scale the different compartments of the deposit: phytostabilised surface, underlying unsaturated zone, then saturated zone. In parallel, sub-metric experiments in 20 L pots started at the beginning of May 2023 with 2 types of residues containing As, that of the Ag-Pb mine and those of the Sn mine. The plant species chosen for these tests is Festuca rubra, and the mine tailings were amended in the plant colonisation zone with a mixture of limestone and compost. These experiments will be continued for 2 years and will make it possible to acquire precise data on the evolution of geochemistry, microbial processes, and the bioavailability/toxicity of As and metals for plants. The RTM will be based on a mass balance and thermodynamic laws. A network of stoichiometric metabolic reactions will represent the redox sequence suspected of occurring in the residues, feeding a first version of the model with the state of the art and the first geochemical data from metric and submetric experiments. In the second version of the model, this formalism will be enriched in order to simulate controlled thermokinetic reactions and to couple microbial metabolisms with abiotic geochemical processes. The reaction network will be corrected by the identification of active bacteria by 16S rRNA sequencing from sub-metric experiments, then by omics data (metagenomics and metaproteomics) from the metric experiment. For each metabolism detected, the thermodynamic term will be coupled to a Monod equation whose “biomass” component will be linked to a growth function for each metabolic group. The parameters of these functions will first be estimated by determining the abundance (by MPN, Most Probable Number) of bacteria from the metabolic groups of interest. The omics data will provide a more precise picture of active metabolisms and their distribution from the surface to the water-saturated zone. A third version of the model will integrate transport parameters. The calculated data will be compared to measured water geochemistry data and plant bioindicators (stress level and pollutant concentrations) for the surface compartment.

Experimental results are being acquired on metric pilot tests as well as sub-metric pot tests: pH, redox potential, conductivity and chemistry of pore water, including speciation (AsIII and AsV) of As. The solids are being characterised (inorganic and organic chemistry, mineralogy, particle size). The first samples from the pot experiments were taken to carry out the following microbiological analyses: most probable number of microorganisms oxidizing or reducing As, Fe and S, and active bacterial diversity via 16S rRNA sequencing. At the same time, optimisations are carried out on the methods for extracting proteins and nucleic acids from these mining wastes, in order to ensure optimal yield, in terms of quantity and quality, for the omics analyses to be carried out on the samples from experiments.

The sub-metric experiments in pots and on the metric pilot scale will be continued for 2 years. At the same time, a pilot phytostabilisation experiment on the Sn mine site has been underway for 3 years. Monitoring, in particular of pore water at different depths, was set up near the phytostabilised plot and outside it. These data will be compared to those collected during the oMIMo project experiments in order to refine the different versions of the model. A PhD thesis will also be carried out in parallel with the oMIMo project, entitled “Integration of omics data for the digital modeling of bioenergetic couplings. Application to the prediction of the fate of mining waste contaminants.” This PhD thesis will start in October 2023. It will make it possible to carry out experiments complementary to those of oMIMo, in microcosms, and will contribute to the realisation of the first stages of the development of the RTM.

The oMIMo project has not yet been the subject of scientific production after 6 months of completion.

Securing mining residues represents a major environmental challenge. Most metal mines produced waste containing iron (Fe) and sulfur (S), with the toxic element arsenic (As) being present at more than 50% of sites. Phytostabilisation often appears as an appropriate option to minimize the risks linked to the dispersion of particles by erosion, at a moderate cost. However, its integration into rehabilitation projects by site managers must be supported by a quantitative assessment of its effect on the fate of As and metals in the waste masses. oMIMo aims to develop a tool for predicting the mobility of As and metals and their availability to plants in a phytostabilised arsenic mining waste, based on a reactive transport modeling methodology (RTM) integrating microbial parameters. This objective will be addressed by the oMIMo consortium (BRGM, ISTO, Li2D-DRF/CEA and LEB/ADERA) through an interdisciplinary approach combining geochemistry, numerical modeling, plant physiology, microbiology (classical and molecular) and omics approaches coupled with a good knowledge of the former mining sites operational management. The oMIMo methodology is based on a controlled scenario of assisted phytostabilisation, developed up to the metric pilot and for which a first version of RTM has been developed for the residues of an Ag-Pb mine. oMIMo proposes to integrate into the RTM data indicative of active microbial processes related to As, Fe and S metabolisms. Sub-metric experiments will be carried out on 2 types of residue, that (well known) of the Ag-Pb mine and those, also arsenic, of a tin (Sn) mine. These tests, coupled with a metric pilot carried out with the residue of the Sn mine, will make it possible to acquire information on the evolution of the geochemistry, the microbial processes, and the bioavailability/toxicity of As and metals for plants. The RTM will be based on a mass balance and thermodynamic laws. A network of stoichiometric metabolic reactions will represent the redox sequence suspected to occur in the tailings, feeding a first version of the model with state-of-the-art and geochemical data. In the second version of the model, this formalism will be enriched in order to simulate controlled thermokinetic reactions and to couple microbial metabolisms with abiotic geochemical processes. The reaction network will be corrected via the identification of active bacteria by 16SrRNA sequencing, then by omics data (metagenomics and metaproteomics) from the metric experiment. For each detected metabolism, the thermodynamic term will be coupled with a Monod equation whose “biomass” component will be linked to a growth function for each metabolic group. The parameters of these functions will first be estimated using the “Most Probable Number” of bacteria from metabolic groups. Omics data will provide a more accurate picture of active metabolisms and their distribution from the surface to the water-saturated zone. A third version of the model will integrate transport parameters. The calculated data will be compared with measured water geochemistry data and plant bio-indicators (stress level and pollutant concentrations) for the surface compartment. In terms of impacts, oMIMo will address the need to predict impacts, including arsenic and metal fluxes toward groundwater, when developing phytostabilisation as an operational option for As-rich mining sites management. oMIMo will provide a modeling methodology accompanied by recommendations, including the type of relevant analyses (geochemical, mineralogical and biological) to be carried out for the numerical determination of the medium and long-term evolution of As and metal fluxes.