Proposal of new distribution coefficients (Kd) of potentially toxic elements in soils for improving environmental risk assessment in the State of São Paulo, southeastern Brazil

Spatial distribution, sources, and risk assessment of potentially toxic elements in cultivated soils using isotopic tracing techniques and Monte Carlo simulation

Potentially toxic elements (PTEs) in cultivated lands pose serious threats to the environment and human health. Therefore, improving the understanding of their distinct sources and environmental risks by integrating various methods is necessary. This study investigated the distribution, sources, and environmental risks of eight PTEs in cultivated soils in Lishui City, eastern China, using digital soil mapping, positive matrix factorisation (PMF), isotopic tracing, and Monte Carlo simulation. The results showed that Pb and Cd are the main pollutants, which posed higher ecological risks in the study area than the other PTEs. Natural, mining, traffic, and agricultural sources were identified as the four determinants of PTE accumulation via a PMF model combined with Pearson correlation analysis, showing that their contribution rates were 22.6 %, 45.7 %, 15.2 %, and 16.5 %, respectively. Stable isotope analysis further confirmed that local mining activities affected the HM accumulation. Additionally, non-carcinogenic and carcinogenic risk values for children were 3.18 % and 3.75 %, respectively, exceeding their acceptable levels. We also identified that mining activities were the most important sources of human health risks (55.7 % for adults and 58.6 % for children) via Monte Carlo simulations coupled with the PMF model. Overall, this study provides insights into the PTE pollution management and health risk control in cultivated soils.

A machine learning based approach for estimating site-specific partition coefficient Kd of organic compounds: Application to nonionic pesticides

The partitioning coefficient K_d for a specific compound and location is not only a key input parameter of fate and transport models, but also critical in estimating the safety environmental concentration threshold. In order to reduce the uncertainty caused by non-linear interactions among environmental factors, machine learning based models for predicting K_d were developed in this work based on literature datasets of nonionic pesticides including molecular descriptors, soil properties, and experimental settings. The equilibrium concentration (C_e) values were specifically included for the reason that a varied range of K_d corresponding to a given C_e occurred in a real environment. By transforming 466 isotherms reported in the literature, 2618 paired equilibrium concentrations of liquid-solid (C_e-Q_e) data points were obtained. Results of SHapley Additive exPlanations revealed that soil organic carbon, C_e, and cavity formation were the most important. The distance-based applicability domain analysis was conducted for the 27 most frequently used pesticides with 15952 pieces of soil information from the HWSD-China dataset by setting three C_e scenarios (i.e., 10, 100, and 1000 μg L^-1). It was revealed the groups of compounds showing log K_d < 0.06 and log K_d > 1.19 were composed mostly of those with log K_ow of -0.800 and 5.50, respectively. When log K_d varied between 0.100 and 1.00, it was impacted by interactions among soil types, molecular descriptors, and C_e comprehensively, which accounted for 55% of the total 2618 calculations. It could be concluded that site-specific models developed in this work are necessary and practicable for the environmental risk assessment and management of nonionic organic compounds.

Influence of soil properties on the development of bacterial community tolerance to Cu, Ni, Pb and Zn

Pollution-Induced Community Tolerance (PICT) is a helpful and sensitive methodology to evaluate the effect of metal pollution in soils using microorganisms as indicators. PICT was used to determine the increase of bacterial community tolerance to Cu, Ni, Pb and Zn (Δlog IC₅₀), and to assess the influence of soil properties on the development of bacterial community tolerance to Cu, Ni, Pb, and Zn. Soil samples showed a wide range of properties, such as pH (3.96-7.47), texture (13.8-31.7% clay) or organic matter (9.7-30.7%). Bacterial growth measured by the [³H]-leucine incorporation method was used as the PICT endpoint. Bacterial communities generally developed tolerance in response to Cu, Ni and Zn additions to soils. However, bacterial communities showed no tolerance to Pb, probably due to high Pb sorption in studied soils. Soil properties influenced the development of bacterial community tolerance to Cu, Ni and Zn. Effective cation exchange and a soil sorption parameter (Freundlich's linearity index) were the selected variables to estimate Δlog IC₅₀ to Cu (R² = 0.65). Clay content and Ni-soluble are the main factors to estimate Δlog IC₅₀ to Ni (R² = 0.63). Organic matter content and a sorption parameter (maximum sorption capacity of the soil from Langmuir equation) are the soil properties to estimate Δlog IC₅₀ to Zn (R² = 0.45). Most of the variables exerted their effect in soil, i.e. PICT selection phase. However, clay content affected bacterial community tolerance determination (PICT detection phase), leading to overestimated measurements of bacterial community tolerance.

Soils of the Ribeira Valley (Brazil) as Environmental Protection Barriers: Characterization and Adsorption of Lead and Cadmium

In waste disposal areas, soils can be used as environmental protection barriers to retain potentially toxic metals. Although most studies focus on lateritic soils, it is still of interest to evaluate other soil types, aiming to select the best materials among those available near the contamination area, reducing costs and construction efforts. This paper characterizes and evaluates the behavior of 13 soil materials collected in a region (Ribeira Valley, Brazil) with a history of improper mining waste disposal for the retention of lead (Pb) and cadmium (Cd) and their possible use as environmental protection barriers. All soils were acidic, kaolinitic, with negatively charged particles. Soils were grouped into three classes according to soil properties, such as particle size distribution, cation exchange capacity (CEC), and specific surface area (SSA), using cluster and principal component analysis. The Pb and Cd adsorption capacities ranged from 288 to 479 µg g−1 and 207 to 326 µg g−1, respectively, obtained from batch equilibrium tests. In general, all soils presented suitable characteristics for the retention of Pb and Cd, but four of them (1 to 4) showed the highest adsorption capacities, probably due to their larger SSA, CEC and percentage of fines (clay + silt).

Towards a Soil Remediation Strategy Using Biochar: Effects on Soil Chemical Properties and Bioavailability of Potentially Toxic Elements

Soil contamination with potentially toxic elements (PTEs) is considered one of the most severe environmental threats, while among remediation strategies, research on the application of soil amendments has received important consideration. This review highlights the effects of biochar application on soil properties and the bioavailability of potentially toxic elements describing research areas of intense current and emerging activity. Using a visual scientometric analysis, our study shows that between 2019 and 2020, research sub-fields like earthworm activities and responses, greenhouse gass emissions, and low molecular weight organic acids have gained most of the attention when biochar was investigated for soil remediation purposes. Moreover, biomasses like rice straw, sewage sludge, and sawdust were found to be the most commonly used feedstocks for biochar production. The effect of biochar on soil chemistry and different mechanisms responsible for PTEs' immobilization with biochar, are also briefly reported. Special attention is also given to specific PTEs most commonly found at contaminated soils, including Cu, Zn, Ni, Cr, Pb, Cd, and As, and therefore are more extensively revised in this paper. This review also addresses some of the issues in developing innovative methodologies for engineered biochars, introduced alongside some suggestions which intend to form a more focused soil remediation strategy.