Effects of compost and technosol amendments on metal concentrations in a mine soil planted with Brassica juncea L

Hg and As pollution in the soil-plant system evaluated by combining multispectral UAV-RS, geochemical survey and machine learning

The combination of a low-density geochemical survey, multispectral data obtained with Unmanned Aerial Vehicle-Remote Sensing (UAV-RS), and a machine learning technique was tested in the search for a statistically robust prediction of contaminant distribution in soil and vegetation, for zones with a highly variable pollutant load. To this end, a novel methodology was devised by means of a limited geochemical study of topsoil and vegetation combined with multispectral data obtained by UAV-RS. The methodology was verified in an area affected by Hg and As contamination that typifies abandoned mining-metallurgy sites in recent decades. A broad selection of spectral indices were calculated to evaluate soil-plant system response, and four machine learning techniques (Multiple Linear Regression, Random Forest, Generalized Boosted Models, and Multivariate Adaptive Regression Spline) were tested to obtain robust statistical models. Random Forest (RF) provided the best non-biased models for As and Hg concentration in soil and vegetation, with R2 and rRMSE (%) ranging from 0.501 to 0.630 and from 180.72 to 46.31, respectively, and with acceptable values for RPD and RPIQ statistics. The prediction and mapping of contaminant content and distribution in the study area were well enough adjusted to the geochemical data and revealed superior accuracy for As than Hg, and for vegetation than topsoil. The results were more precise than those obtained in comparable studies that applied satellite or spectrometry data. In conclusion, the methodology presented emerges as a powerful tool for studies addressing soil and vegetation pollution and an alternative approach to classical geochemical studies, which are time-consuming and expensive.

Recovery of Degraded Areas through Technosols and Mineral Nanoparticles: A Review

Anthropogenic sources such as urban and agricultural runoff, fossil fuel combustion, domestic and industrial wastewater effluents, and atmospheric deposition generate large volumes of nutrient-rich organic and inorganic waste. In their original state under subsurface conditions, they can be inert and thermodynamically stable, although when some of their components are exposed to surface conditions, they undergo great physicochemical and mineralogical transformations, thereby mobilizing their constituents, which often end up contaminating the environment. These residues can be used in the production of technosols as agricultural inputs and the recovery of degraded areas. Technosol is defined as artificial soil made from organic and inorganic waste, capable of performing environmental and productive functions in a similar way to natural ones. This study presents results of international research on the use of technosol to increase soil fertility levels and recover degraded areas in some countries. The conclusions of the various studies served to expand the field of applicability of this line of research on technosols in contaminated spaces. The review indicated very promising results that support the sustainability of our ecosystem, and the improvement achieved with this procedure in soils is comparable to the hybridization and selection of plants that agriculture has performed for centuries to obtain better harvests. Thus, the use of a technosol presupposes a much faster recovery without the need for any other type of intervention.

Use of Brassica juncea and Dactylis glomerata for the phytostabilization of mine soils amended with compost or biochar

Phytostabilization of mine soils contaminated by potentially toxic elements (PTEs) requires plants tolerant to PTE toxicity and to the poor soil physico-chemical characteristics of these areas. A pot experiment was carried out to assess the phytostabilization potential of Brassica juncea and Dactylis glomerata in mine soils amended with compost and biochar. Furthermore, the Environmental Risk of the soils and the effects of the phytostabilization process on the microbiological population size and activity in the soils were also determined. According to the Ecological Risk Index (ERI) the soils studied presented "very high risk" and As, Cd and Pb were the target elements for phytostabilization. Both amendments improved soil conditions (e.g., increasing total-N and total organic-C concentrations) and contributed to PTE (Cd, Pb and Zn) immobilization in the soil. Compost showed a more marked effect on soil microbial biomass and nutrients release in soil, which led to higher B. juncea and D. glomerata biomass in compost treated soils. Biochar treatment showed a positive effect only on D. glomerata growth, despite it provoked strong PTE immobilization in both soils. The addition of both amendments resulted in an overall reduction of PTE concentration in the plants compared to the control treatment. In addition, both plant species showed higher accumulation of PTE in the roots than in the shoots (transfer factor<1) independently of the treatment received. Therefore, they can be considered as good candidates for the phytostabilization of PTE contaminated mine soils in combination with organic amendments like biochar and compost.

Phytoremediation of mine tailings by Brassica juncea inoculated with plant growth-promoting bacteria

Mine tailings represent a serious environmental pollution problem and techniques such as phytoremediation using plant growth-promoting bacteria become an important solution due to their environmentally friendly nature. The study performed using Brassica juncea L. (Indian mustard) and plant growth-promoting bacteria such as Serratia K120, Enterobacter K125, Serratia MC107, Serratia MC119 and Enterobacter MC156 showed that plant roots colonization favored the transfer of metals to the plant, mainly Al and Pb from the 8 analyzed metals with bioaccumulation factors >1 for Al, Pb, Cd and Fe obtained with Serratia K120, Enterobacter K125, Serratia MC107, Serratia MC119 and Enterobacter MC156. Based on these results, this system could be used in phytoextraction processes whereas Enterobacter MC156 reduced the bioaccumulation of metals, indicating the possible phytostabilization of metals present in mine tailings.