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Heavy metal contamination in soils and vegetation poses a significant problem due to its toxicity and persistence. Toxic effects on vegetation include not only impaired growth, reduced yields, and even plant death but also biodiversity loss and ecosystem degradation. Addressing this issue requires comprehensive monitoring and remediation efforts to mitigate the environmental, human health, and ecological impacts. This review examines the state-of-the-art methodologies and advancements in remote sensing applications for detecting and monitoring heavy metal contamination in soil and its subsequent effects on vegetation. By synthesizing the current research findings and technological developments, this review offers insights into the efficacy and potential of remote sensing for monitoring heavy metal contamination in terrestrial ecosystems. However, current studies focus on regression and AI methods to link spectral reflectances and indices to heavy metal concentrations, which poses limited transferability to other areas, times, spectral discretizations, and heavy metal elements. We conclude that one important way forward is the more thorough understanding and simulation of the related physico-chemical processes in soils and plants and their effects on the spectral signatures. This would offer a profound basis for remote sensing applications for individual circumstances and would allow disentangling heavy metal effects from other stressors such as droughts or soil salinity. [ABSTRACT FROM AUTHOR]

Soil heavy metal pollution is one of the hottest topics in soil environmental research. There are a large number of small abandoned metal mines in China. Due to the lack of timely restoration and treatment, the heavy metal concentration in the soil within these mining areas often exceeds the local background levels, facilitating pollution spread to other natural factors such as precipitation, resulting in a wider extent of continuous contamination. This paper investigates the current status of heavy metal pollution in an abandoned small lead-zinc mine, particularly examining the concentrations of 10 specific heavy metals (V, Cr, Ni, Zn, As, Cd, Hg, Pb, Cu, Co) in soil samples. Additionally, it explores the extent of contamination caused by these heavy metals within the area. Besides, principal component analysis and positive matrix factorization model (PMF) were adopted to determine the sources of these heavy metals. The risk assessment of the pollution status was also carried out. The provision of a scientific basis for mining area management under similar conditions holds significant importance. The results indicate a significant positive correlation among the majority of these 10 heavy metals in soil. The presence of these heavy metals in the soil within the concentrator and tailings reservoir area primarily stems from mining operations, construction activities, and discharges from the power system. Hg, Pb, Zn, and As in the surrounding agricultural land mainly come from the heavy metal spillover from the mining area. Furthermore, the area is plagued by severe contamination from As and Pb. The Nemerow comprehensive index method has confirmed substantial pollution in both the concentrator and tailings reservoir. Additionally, there exists a substantial ecological risk ranging from moderate to high. [ABSTRACT FROM AUTHOR]

Traditionally, the assessment of heavy metal concentrations using remote sensing technology is sample-intensive, with expensive model development. Using a mining area case study of Daxigou, China, we propose a cross-time-domain transfer learning model to monitor heavy metal pollution using samples collected from different time domains. Specifically, spectral indices derived from Landsat 8 multispectral images, terrain, and other auxiliary data correlative to soil heavy metals were prepared. A cross time-domain sample transfer learning model proposed in the paper based on the TrAdaBoost algorithm was used for the Cu content mapping in the topsoil by selective use of soil samples acquired in 2017 and 2019. We found that the proposed model accurately estimated the concentration of Cu in the topsoil of the mining area in 2019 and performed better than the traditional TrAdaBoost algorithms. The goodness of fit (R2) of the test set increased from 0.55 to 0.66; the relative prediction deviation (RPD) increased from 1.37 to 1.76; and finally, the root-mean-square deviation (RMSE), decreased from 8.33 to 7.24 mg·kg−1. The proposed model is potentially applicable to more accurate and inexpensive monitoring of heavy metals, facilitating remediation-related efforts. [ABSTRACT FROM AUTHOR]

Over the last decade, a large number of studies have been conducted on heavy metals and magnetic susceptibility ( χ l f ) measurement in soils. Yet, a global understanding of soil contamination and magnetic responses remains elusive due to the limited scope or sampling sites of these studies. Hence, we attempted to explore a pollution proxy on a global scale. Through a meta-analysis of data from 102 published studies, our research aimed to provide a worldwide overview of heavy metal pollution and magnetic responses in agriculture soils. We mapped the geographic distribution of nine heavy metals (Cr, Cu, Zn, Pb, Ni, As, Cd, Mn, and Fe) in agricultural soils and explored their pollution sources and contributions. Since 2011, The accumulation of heavy metals has escalated, with industrial activities (31.5%) being the largest contributor, followed by agricultural inputs (27.1%), atmospheric deposition (22.66%), and natural sources (18.74%). The study reports χ l f ranging from 6.45 × 10−8 m3/kg to 319.23 × 10−8 m3/kg and χ f d from 0.59% and 12.85%, with the majority of the samples being below 6%, indicating heavy metal influence mainly from human activities. Pearson's correlation and redundancy analysis show significant positive correlations of Pb, Zn, and Cu with χ l f (r = 0.51–0.53) and Mn and Fe with χ f d (r = 0.50–0.53), while Pb, Zn, Cu, and As metals were shown to be key factors of variation in magnetic response. The average heavy metal pollution load index of 2.03 suggests moderate global agricultural soil pollution, with higher heavy metal contamination in areas of high χ l f . Regression analysis confirms soil is considered to be non-polluted below χ l f of 26 × 10 − 8   m 3 / k g and polluted above this threshold, with all contamination factors of metals showing a linear correlation with χ l f (R = 0.72), indicating that a significant relationship between χ l f and the geochemical properties of soils continues to exist on a global scale. This study provides new insights for large-scale agricultural soil quality assessment and magnetic response. [ABSTRACT FROM AUTHOR]

The pollution of agricultural soil by heavy metals is a significant environmental issue that has a serious impact on human health and food security. This study focused on investigating the presence of heavy metal pollution in sewage-irrigated soils in Taiyuan city. A total of 110 soil samples were analyzed for the presence of As, Hg, Cd, Pb, Cr, Cu and Zn. The results showed that the concentrations of these metals ranged from 0.06 to 26.74 mg/kg for As, 0.00 to 0.84 mg/kg for Hg, 0.03 to 0.69 mg/kg for Cd, 44.32 to 100.09 mg/kg for Pb, 9.85 to 42.19 mg/kg for Cr, 13.38 to 53.72 mg/kg for Cu, and 42.77 to 145.47 mg/kg for Zn. The average concentrations of these metals were found to be below the risk values specified in the "Soil environmental quality (GB15618-2018)", except for As and Cd in three sampling points in Xiaodian District. The heavy metal pollution in these areas can be attributed to various sources, such as industrial activities, the use of fertilizers and pesticides, and the irrigation process. According to the geo–accumulation index, the agricultural soil in the Taiyuan irrigation area was found to be uncontaminated by Zn, Cr, Cu, and As, and lightly contaminated by Cd, Hg, and Pb. The Nemerow Pollution Index indicated that the soil at all sampling points exhibited a slight level of pollution. Moreover, the ecological risk assessment indicated that all heavy metals posed a slight level of pollution. The findings of this study provide a scientific basis for the development of effective policies and measures for soil environmental protection and pollution control. [ABSTRACT FROM AUTHOR]

This study collected 1135 topsoil samples of cultivated land in Laiyang County, eastern China, to analyze the distribution, pollution and health risks of heavy metals (As, Cd, Cu, Cr, Hg, Ni, Pb and Zn). The results show that: (1) the levels of eight heavy metals at some sites were higher than the risk screening values in China, and there was heavy metal pollution. (2) An improved geoaccumulation index was used to evaluate soil pollution. The average value of Igeo before and after improvement was 0.32 (Iml, no pollution to medium pollution) and −0.04 (Iol, no pollution), respectively. (3) Hg and Cd were identified as the main contributors to ecological risk in this study, with a cumulative ecological risk contribution percentage > 65%. The results of the potential ecological risk index (PERI) show that 9.3% of the sampling sites were considered to have moderate ecological risk. (4) As, Pb, Ni and Cu made a contribution of >95% in terms of non-carcinogenic risk to adults and children through different exposure routes, and different soil intake routes posed no non-carcinogenic risk to adults; there was a sampling site with HQChildren > 1, which was consistent with the non-carcinogenic risk site, indicating that children in this location and surrounding areas are more likely to face dual health risks. Therefore, it is necessary to promote the risk management of heavy metals in the study area in order to safely use soil resources. [ABSTRACT FROM AUTHOR]

Environmental changes and heavy metal pollution are some of the consequences of anthropogenic activities. Many ecosystems, including edaphic ecosystems, suffer from the effects of pollution. The accurate assessment of soil heavy metal contamination leads to better approaches for remediating soils. The exploration of different ways, including biological methods, to conduct environmental monitoring is still ongoing. Here, we focus on reviewing the potential of ectomycorrhizal fungi as a natural indicator of soil heavy metal pollution. Mycorrhizal fungi fulfill basic criteria required as natural bio-indicators for heavy metal contamination. These fungi use different mechanisms such as avoidance and tolerance to survive in metalliferous soils. Thus, we promote ectomycorrhizal fungi as natural indicators. This review also synthesizes existing research on ectomycorrhizal mushrooms as natural bio-indicators for heavy metal pollution and the elaboration of mechanisms, by which ectomycorrhizal fungi meet the criteria required for a successful bio-indicator. [ABSTRACT FROM AUTHOR]

Contamination by heavy metals is a significant issue worldwide. In recent decades, soil heavy metals pollutants in China had adverse impacts on soil quality and threatened food security and human health. Anthropogenic inputs mainly generate heavy metal contamination in China. In this review, the approaches were used in these investigations, focusing on geochemical strategies and metal isotope methods, particularly useful for determining the pathway of mining and smelting derived pollution in the soil. Our findings indicate that heavy metal distribution substantially impacts topsoils around mining and smelting sites, which release massive amounts of heavy metals into the environment. Furthermore, heavy metal contamination and related hazards posed by Pb, Cd, As, and Hg are more severe to plants, soil organisms, and humans. It's worth observing that kids are particularly vulnerable to Pb toxicity. And this review also provides novel approaches to control and reduce the impacts of heavy metal pollution. Hydrometallurgy offers a potential method for extracting metals and removing potentially harmful heavy metals from waste to reduce pollution. However, environmentally friendly remediation of contaminated sites is a significant challenge. This paper also evaluates current technological advancements in the remediation of polluted soil, such as stabilization/solidification, natural attenuation, electrokinetic remediation, soil washing, and phytoremediation. The ability of biological approaches, especially phytoremediation, is cost-effective and favorable to the environment. [ABSTRACT FROM AUTHOR]

Simple Summary: Despite its high organic matter content, sewage sludge contains significant quantities of heavy metals, including those designated as hazardous, such as cadmium, nickel, chromium, mercury, copper, lead, and zinc, which, as a consequence, have a negative impact on living organisms. The current research sought to study the effect of dumping sludge, as one of the sources of pollution with heavy metals, on biodiversity and to assess the bioremediation and stress defense strategies of a tolerant plant species. The obtained results showed that soil pollution by heavy metals has a substantial influence on plant diversity. The selected species, Amaranthus retroflexus L., showed a high biological concentration factor (BCF) and low translocation factor (TF) for Cu, As and Ni. The stress defense strategies of A. retroflexus grown under complex heavy metals contamination are studied and discussed. Accumulation of heavy metals in soil is becoming an increasingly serious eco-environmental problem. Thus, investigating how plants mitigate heavy metal toxicity is necessary to reduce the associated risks. Here, we aimed to assess the bioremediation and stress defense strategies of tolerant plant species grown under complex heavy metals contamination. To this end, a field study was conducted on the vegetation cover of sites with different soil pollution levels. Forty-two plant species that belong to 38 genera and 21 families were identified. The pollution had a significant impact on plant richness in the polluted sites. Out of several screened plants, Amaranthus retroflexus L. was selected because of its high relative density (16.7) and a high frequency (100%) in the most polluted sites. The selected species showed a high biological concentration factor (BCF) and low translocation factor (TF) for Cu, As and Ni. To control the heavy metal-induced oxidative damage, A. retroflexus invested in detoxification (metallothionein and phytochelatins, glutathione and glutathione-S-transferase (GST). At the organ level, oxidase damage (H2O2, lipid and protein peroxidation) was observed, particularly in the roots. To mitigate heavy metal oxidative stress, antioxidant mechanisms (e.g., tocopherols, glutathione, peroxidases, catalase, peroxide dismutase and ASC-GSH cycle) were upregulated, mainly in the roots. Overall, our results suggested the potentiality of A. retroflexus as a promising bioremediatory and stress-tolerant plant at the same time; moreover, defense and detoxification mechanisms were uncovered. [ABSTRACT FROM AUTHOR]