Selective recovery of rare earth elements and value-added chemicals from the Dicranopteris linearis bio-ore produced by agromining using green fractionation.

The increasing demand for Rare Earth Elements (REEs) and the depletion of mineral resources motivate sustainable strategies for REE recovery from alternative unconventional sources, such as REE hyperaccumulator. The greatest impediment to REE agromining is the difficulty in the separation of REEs and other elements from the harvested biomass (bio-ore). Here, we develop a sulfuric acid assisted ethanol fractionation method for processing D. linearis bio-ore to produce the pure REE compounds and value-added chemicals. The results show that 94.5% of REEs and 87.4% of Ca remained in the solid phase, and most of the impurities (Al, Fe, Mg, and Mn) transferred to the liquid phase. Density functional theory calculations show that the water-cation bonds of REEs and Ca cations were broken more easily than the bonds of the cations of key impurities, causing lower solubility of REEs and Ca compounds. Subsequent separation and purification led to a REE-oxide (REO) product with a purity of 97.1% and a final recovery of 88.9%. In addition, lignin and phenols were obtained during organosolv fractionation coupled with a fast pyrolysis process. This new approach opens up the possibility for simultaneous selective recovery of REEs and to produce value-added chemicals from REE bio-ore refining.

Discrimination and Quantification of Soil Nanoparticles by Dual-Analyte Single Particle ICP-QMS.

This study presents the new application of dual-analyte single particle inductively coupled plasma quadrupole mass spectrometry (spICP-QMS) to the discrimination and quantification of two typical soil nanoparticles (kaolinite and goethite nanoparticles, abbr. KNPs and GNPs) in three samples (SA, SB, and SC) with three detection events (Al unpaired event, Fe unpaired event, and paired event). SA was mainly composed of KNPs with a concentration of 28 443 ± 817 particle mL-1 and a mean particle size of 140.7 ± 0.2 nm. SB was mainly composed of GNPs with a concentration of 39 283 ± 702 particle mL-1 and a mean particle size of 141.8 ± 2.9. In SC, the concentrations of KNPs and GNPs were 22 4541 ± 1401 and 70 604 ± 1623 particle mL-1, respectively, and the mean particle sizes of KNPs and GNPs were 140.7 ± 0.2 and 60.2 ± 0.3 nm, respectively. The accuracy of dual-analyte spICP-QMS was determined by spiking experiments, comparing these results with the measurements of other techniques, analyzing the samples in different SA and SB proportions and in different SC concentrations. Our results demonstrated that the dual-analyte spICP-QMS is a promising approach to distinguishing different kinds of natural NPs in soils.

Effects of in situ leaching on the origin and migration of rare earth elements in aqueous systems of South China: Insights based on REE patterns, and Ce and Eu anomalies.

In situ leaching of ion-adsorption rare earth element (REE) deposits has released large amounts of REE-containing wastewater. However, the origin, speciation, distribution and migration of REEs in aqueous systems of the mining catchment are poorly understood. Groundwater, surface water, in situ leachates and weathered granite soil samples were collected from a catchment affected by mining activities in South China. The REE concentrations in groundwater (6.18 × 10-3-0.49 µmol L-1) and surface water (2.54-44.05 µmol L-1) decreased from upstream to downstream. REEs in groundwater were detected in organic matter associated (FA-REE) colloids, while the REE3+ and REE(SO4)+ were converted to REE(CO3)+ and FA-REE colloids from leachates and upstream surface water to downstream. The REE patterns of leachates and upstream groundwater (light and middle REE enrichment) resembled those of soil, but showed heavy REE enrichment due to FA-REE colloids in the downstream. REE in surface water were derived from middle REE enriched leachate. The Ce and Eu anomalies in the water samples indicated the REE origin (i.e., mining activities) and the hydrological variations (e.g., oxidation environment and water-rock interaction). Our results reveal the origin and fate of REE in aqueous systems of ion-adsorption REE mining catchments.

Optimizing environmental pollution controls in response to textile dyeing sludge, incineration temperature, CaO conditioner, and ash minerals.

The dynamics of heavy metal speciation and flue gas emissions during the incineration of textile dyeing sludge (TDS) were quantified as a function of four addition levels of CaO, incineration temperature, and ash minerals using thermogravimetric analysis and experimental tube furnace. The TDS incineration was most improved with the addition of 10% CaO. The increased fractions of CaO coupled with the ash minerals changed the retention behaviors of eight heavy metals. The CaO addition increased the Cu, Zn, As, and Pb retentions, did not significantly change Cr, Mn, and Cd, but decreased the Ni retention. The CaO addition enhanced the speciation stability of Cu and transferred the Cr, Cd, and As speciations to the mobile fractions. The increased temperature weakened the Zn and Pb retentions and the speciation stabilities of As and Pb and turned the Cr, Mn, Ni, Cu, Zn, and Cd speciations into the stable fractions. The CaO addition inhibited HCN, NO, NO2, COS, SO2, CS2, and SO3 emissions from the TDS incineration. Neural network-based multi-response optimization was implemented to determine the optimal operational temperature for the TDS incineration and the reduction of the 12 gas emissions. The range of 640-755 °C with(out) 5% CaO appeared to be most beneficial in terms of both environmental quality and economic efficiency.

Transformation behaviors and environmental risk assessment of heavy metals during resource recovery from Sedum plumbizincicola via hydrothermal liquefaction.

Environmentally sound disposal of hyperaccumulator harvests is of critical importance to industrialization of phytoremediation. Herein, transformation behaviors and environmental risk of heavy metals were comprehensively examined during subcritical hydrothermal liquefaction of Sedum plumbizincicola. It is concluded that low temperature liquefaction favored resource recovery of heavy oil and hydrochars in terms of higher energy density, improved carbon sequestration and less energy consumption. Heavy metals were mainly distributed into hydrochars and water soluble phase with less than 10% in heavy oil. All metal elements except As could be accumulated in hydrochars by extending reaction time, whereas more than 96% of As was redistributed into water soluble phase. Prolonged liquefaction time facilitated immobilization of Cd, Cr and As in hydrochars, but fast liquefaction favored Pb stabilization. Liquefaction significantly reduced environmental risk level of Cd, Zn and As, but may mobilize Pb and Mn, especially for Mn to very high risk level at 240 ºC. High temperature with long reaction time tended to inhibit leaching rate of Mn, whereas low liquefaction temperature with short reaction time prevented the leaching of Zn and As from hydrochars. Overall, these findings are essential for downstream upgrading of heavy oil and metals recovery from hydrochars.

Parametric assessment of stochastic variability in co-combustion of textile dyeing sludge and shaddock peel.

This study aimed at quantification of co-combustion behaviors and kinetic parameters of textile dyeing sludge (TDS) and shaddock peel (SP) in response to blend ratio, heating rate, and temperature. The experimental responses of mass loss (ML) and mass loss rate (MLR) measured using a thermogravimetric analyzer were also estimated using the best-fit multiple non-linear regression (MNLR) models. The independent validations of the models led to high coefficients of determination of 99.8% for ML and 83.8% for MLR. Stochastic uncertainty associated with the model predictors was assessed using Monte Carlo simulations. Our results indicated that the overall cumulative uncertainty was greater in the model predictions of MLR than ML.

Influence of catalysts on co-combustion of sewage sludge and water hyacinth blends as determined by TG-MS analysis.

Effects of the three metal carbonates (K2CO3, Na2CO3, and MgCO3) were quantified on catalytic co-combustion of the sewage sludge and water hyacinth (SW) blend using a thermogravimetric-mass spectrometric (TG-MS) analysis and kinetics modeling. The main dominating steps of the catalysts were the organic volatile matter release and combustion stage. Weighted mean values of activation energy (Em) were estimated at 181.18KJ·mol-1, 199.76KJ·mol-1, 138.76KJ·mol-1, and 177.88KJ·mol-1 for SW, SW+5% K2CO3, SW+5% Na2CO3, and SW+5% MgCO3, respectively. The lowest Em occurred with SW+5% Na2CO3. Overall, catalyst effect on co-combustion appeared to be negligible as indicated by Gibbs free energy (ΔG). The normalized intensities of SW+MgCO3 were strongest. The addition of Na2CO3 and MgCO3 to SW increased flue gases emissions (CO2, NO2, SO2, HCN, and NH3) of SW, whereas the addition of K2CO3 to SW reduced flue gases emissions from the entire combustion process.

Co-combustion of sewage sludge and coffee grounds under increased O2/CO2 atmospheres: Thermodynamic characteristics, kinetics and artificial neural network modeling.

(Co-)combustion characteristics of sewage sludge (SS), coffee grounds (CG) and their blends were quantified under increased O2/CO2 atmosphere (21, 30, 40 and 60%) using a thermogravimetric analysis. Observed percentages of CG mass loss and its maximum were higher than those of SS. Under the same atmospheric O2 concentration, both higher ignition and lower burnout temperatures occurred with the increased CG content. Results showed that ignition temperature and comprehensive combustion index for the blend of 60%SS-40%CG increased, whereas burnout temperature and co-combustion time decreased with the increased O2 concentration. Artificial neural network was applied to predict mass loss percent as a function of gas mixing ratio, heating rate, and temperature, with a good agreement between the experimental and ANN-predicted values. Activation energy in response to the increased O2 concentration was found to increase from 218.91 to 347.32 kJ·mol-1 and from 218.34 to 340.08 kJ·mol-1 according to the Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa methods, respectively.