Geospatial modeling and ecological and human health risk assessments of heavy metals in contaminated mangrove soils

Prediction of heavy metals in polluted mangrove soils in Brazil with the highest reported levels of mercury using near-infrared spectroscopy

Infrared reflectance spectroscopy has demonstrated potential as a tool for monitoring and preventing contamination in different environments. The objective of this study was to evaluate the usage of near-infrared spectroscopy for predicting heavy-metal contamination in mangrove soils from the Botafogo River estuary located in Pernambuco State, Northeastern Brazil. These soils exhibit the highest mercury (Hg) levels ever reported for Brazilian mangrove soils. Sixty-one samples (obtained at depths ranging from 0 to 5 cm) were collected and measured using near-infrared (1000-2500 nm) reflectance spectroscopy. Preprocessing methods were applied, and partial least squares regression was used to build prediction models for attributes such as clay content, soil organic matter (SOM), pH, Eh, and concentrations of Cr, Cu, Hg, Ni, Pb, and Zn. The models were evaluated using root mean squared error (RMSE), the adjusted coefficient of determination (R2adj), bias, the ratio of performance to interquartile distance (RPIQ), and Lin's concordance correlation coefficient (CCC). The best outcomes were noted for concentrations of Cr, Cu, Hg, Ni, and Pb (RPIQ > 2.5 and R2adj > 0.80); second-best outcomes were found for Zn and SOM (RPIQ > 1.5 and R2adj > 0.70). Clay content, pH and Eh exhibited the poorest outcomes (RPIQ < 1.5). The importance of spectral preprocessing is highlighted, notably with Savitzky-Golay derivatives and Multiplicative Scatter Corrections, which boosted performance for most of the variables. Near-infrared spectroscopy can be efficiently used to predict Cr, Cu, Hg, Ni, Pb and SOM and represents a technique complementary to traditional analyses.

New Evidence of Semi-Mangrove Plant Barringtonia racemosa in Soil Clean-Up: Tolerance and Absorption of Lead and Cadmium

Mangrove plants play an important role in the remediation of heavy-metal-contaminated estuarine and coastal areas; Barringtonia racemosa is a typical semi-mangrove plant. However, the effect of heavy metal stress on this plant has not been explored. In this study, tolerance characteristics and the accumulation profile of cadmium (Cd) and lead (Pb) in B. racemosa were evaluated. The results indicated that B. racemosa exhibited a high tolerance in single Cd/Pb and Cd + Pb stress, with a significant increase in biomass yield in all treatment groups, a significant increase in plant height, leaf area, chlorophyll and carotenoid content in most treatment groups and without significant reduction of SOD, POD, MDA, proline content, Chl a, Chl b, Chl a + b, Car, ratio of Chl a:b and ratio of Car:Chl (a + b). Cd and Pb mainly accumulated in the root (≥93.43%) and the content of Cd and Pb in B. racemosa was root > stem > leaf. Pb showed antagonistic effects on the Cd accumulation in the roots and Cd showed antagonistic or synergistic effects on the Pb accumulation in the roots, which depended on the concentration of Cd and Pb. There was a significant synergistic effect of Cd and Pb enrichment under a low Cd and Pb concentration treatment. Thus, phytoremediation could potentially use B. racemosa for Cd and Pb.

Characteristics and Risk of Forest Soil Heavy Metal Pollution in Western Guangdong Province, China

West Guangdong is an important ecological barrier in Guangdong province, so understanding the spatial patterns and sources of heavy metal pollution of forest soil in this region is of great significance for ecological protection. In this study, the concentrations of heavy metals (Cd, Pb, Cu, Zn, and Ni) in forest soil were determined. Geostatistics, single-factor pollution index (PI), potential ecological risk index (RI), principal component analysis (PCA), and Pearson’s correlation analysis were used to evaluate and analyze the characteristics of heavy metal pollution of forest soil. The results showed that the average concentration did not exceed the critical value. Cd, Pb, and Cu were enriched in southwest Xinxing County, while Zn and Ni were enriched in most areas of the Yunan and Yuncheng districts. Two groups of heavy metals from different sources were identified by PCA and a correlation analysis. Cd, Pb, and Cu in their respective enrichment areas were mainly from marble and cement production, whereas Zn and Ni were primarily from transportation and chemical fertilizer. Most of the study area was safe or slightly polluted while the heavy metal-enriched areas were moderately to severely polluted. The potential ecological risk was at a lower level in the study area but moderate in southwest Xinxing County. In summary, human factors impact the spatial patterns and ecological risks of heavy metals in forest soil. This study provides a scientific basis for forest soil pollution control and ecological protection.