Metal Concentrations In Soils Research Articles

Quarry soil and quarry stream water baseline level parameters around Chestedi Quarry, F.A.U.C. Golden Ltd Quarry, Fakunle Quarry and River Oyanmi in Igarra, Akoko Edo

The primary objective of this research was to investigate the initial levels of chemical parameters surrounding quarry operations in Igarra, Akoko-Edo, Edo State. Specifically, three prominent quarries (Chestedi, F.A.U.C. Golden Ltd, and Fakunle) were examined, along with the water of River Onyami flowing through these quarries from the Ojirami dam. Each quarry site yielded four soil samples collected at a various depth (between 0 – 15 cm) and different geographical coordinates, while four water samples were obtained from River Onyami. These samples underwent analysis for their physicochemical properties and the chemical speciation of Fe, Zn, Cu, Pb, Cr, and Mn. As Tessier et al. (1978) described, a sequential extraction method was employed to partition the heavy metals into five different fractions. Total concentrations of heavy metals in both soil and water samples were determined. The distribution of heavy metals in the soil exhibited the following order of accumulation: Fe > Zn > Mn > Cu > Pb > Cr, whereas in water samples, the order was Fe > Zn > Cu > Mn > Pb > Cr. Iron and zinc emerged as the predominant heavy metals in the soil, with iron within permissible limits but zinc, copper, manganese, lead, and chromium exceeding their respective limits. In the stream water, iron and lead surpassed their permissible limits, while Zn, Cu, Cr, and Mn remained below theirs. Comparative analysis against WHO, NIS DPR, and CCME maximum contamination/permissible limits was conducted for heavy metal concentrations and physicochemical properties in both soil and water samples. Mobility Factors (MF), Environmental Risk Factors (ERF), Contamination Factors (CF), Pollution Load Index (PLI), and Geoaccumulation Index (GI) were computed. Results from this study indicate that the soil is conducive to supporting growth and is nutrient-rich for various applications, while the water is suitable for irrigation and other domestic purposes.

Metallomic mapping of gut and brain in heavy metal exposed earthworms: A novel paradigm in ecotoxicology

This study explored the uptake of lead in the epigeic earthworm Dendrobaena veneta exposed to 0, 1000, and 2500 μg Pb/g soil. The soil metal content was extracted using strong acid digestion and water leaching, and analysed by means of Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to estimate absolute and bioavailable concentrations of metals in the soil. The guts and heads of lead-exposed earthworms were processed into formalin-fixed and paraffin embedded sections for high-resolution multi-element metallomic imaging via Laser Ablation ICP-MS (LA-ICP-MS). Metallomic maps of phosphorus, zinc, and lead were produced at 15-μm resolution in the head and gut of D. veneta. Additional 4-μm resolution metallomic maps of the earthworm brains were taken, revealing the detailed localisation of metals in the brain. The Pb bioaccumulated in the chloragogenous tissues of the earthworm in a dose-dependent manner, making it possible to track the extent of soil contamination. The bioaccumulation of P and Zn in earthworm tissues was independent of Pb exposure concentration. This approach demonstrates the utility of LA-ICP-MS as a powerful approach for ecotoxicology and environmental risk assessments.

Bioaccumulation, transfer characteristics of metals in six vascular plants, and soil pollution assessment from Wachangping karst bauxite residue areas

Bauxite residue (BR) is a large volume by-product generated during bauxite smelting process and metal pollution problem is becoming increasingly prominent in residue areas. Accumulation and transfer of metals in six vascular plants were analyzed and soil environment was evaluated. Results found levels of Al (2,110–26,280 mg kg−1), Fe (990 to 9,880 mg kg−1), Ca (8,020 to 49,250 mg kg−1), Mg (2,060 to 17,190 mg kg−1), K (16,840 to 39,670 mg kg−1), and Ti (80 to 1,240 mg kg−1) in plants. Metal concentrations in soils exceeded background levels. Bioconcentration factor (BCF) found that Al, Fe, and Ti in plants (roots, stems, and leaves) were relatively depleted (BCF <1). Transfer factor (TF) of Al, Fe, Ca, K, and Ti in plants was distinctly higher than 1 and mainly concentrated in stems and leaves. Pollution indices revealed that soil environment was at moderated to serious contaminated risk. Principal components analysis (PCA) showed that Artemisia caruifolia Buch. and Siegesbeckia orientalis L. plants had a good ability to absorb Al and Fe, which can be used as biological indicators and restoration materials.

Human and Ecological Risk Assessment of Soil and Plants Metal Contamination in a Tropical Municipal Solid Waste Dumping Site

ABSTRACT The growing open waste dumpsite contributes to heavy metal leaching, harming public health and ecosystem services. Hence, the study’s novelty lies in its integrated assessment of heavy metal concentration (Cd, Cr, Cu, Fe, Ni, Pb, and Zn) in soil and plants, incorporating risk assessment using both single and combined indexes in the largest active waste dumpsite in Kelantan, Malaysia. Heavy metal in soil samples Cu (164.896 ± 205.096), Pb (122.177 ± 93.309), and Cr (32.74 ± 26.569) were recorded to exceed the standards, while in the studied plants (castor bean, papaya, pea eggplant, and water spinach), Pb concentrations in all plant parts have surpassed the Malaysia Food Regulation (1985) and FAO/WHO guidelines (2016). Translocation factor (TF) in Cu, Cr, and Pb in water spinach and Cr, Cu, and Cd in pea eggplant have TF > 1. Bioconcentration factor (BCF) was < 1 in pea eggplant and water spinach except for Pb in pea eggplant. Correlation analysis revealed a strong correlation between heavy metals in the soil while contrasts in the plants. The potential ecological risk index (PERI) reveals that the soil waste dumpsite is contaminated with heavy metals. The hazard index (HI) and lifetime cancer risk (LCR) values of heavy metals on the soil surface had negligible non-cancer risks posed to adults and indicate that soil ingestion and dermal absorption were the two primary carcinogenic risk exposure routes. These findings implied that Beris Lalang waste dumpsite is a potential source of toxic pollutants to the environment and the local population. It is recommended to conduct a comprehensive feasibility study and design an implementation plan for leachate treatment plant. Additionally, a comprehensive assessment of the specific contaminants present in the leachate and their potential impacts on the environment should be conducted to inform targeted and effective treatment strategies.

Towards interpretable machine learning for observational quantification of soil heavy metal concentrations under environmental constraints

Monitoring heavy metal concentrations in soils is central to assessing agricultural production safety. Satellite observations permit inferring concentrations from spectrum, thereby contributing to the prevention and control of soil heavy metal pollution. However, heavy metals exhibit weak spectral responses, particularly at low and medium concentrations, and are predominantly influenced by other soil components. Machine learning (ML)-driven modelling can produce predictions but lacks interpretability. Here, we present an interpretable ML framework for concentration quantification modelling and investigated the contributions of spectral and environmental factors—pH and organic carbon—to the estimation of metals with multiple concentration gradients, as analysed through SHAP (SHapley Additive exPlanations) data derived from four learning-based scenarios. The results indicated that scenarios SHC (spectral, pH, and organic carbon) and SH (spectral and pH) were the most optimal for chromium (Cr) [RPD = 1.42, Adj R2 = 0.62], and cadmium (Cd) [RPD = 1.80, Adj R2 = 0.80]. Under environmental constraints, the spectral predictability for Cr and Cd was improved by 67 % and 87 %, respectively. We concluded that interpretable modelling, utilising both spectral and soil environmental factors, holds significant potential for estimating heavy metals across concentration gradients. It is recommended that samples with higher organic carbon content and lower pH be selected to enhance Cr and Cd predictions. An advanced grasp of interpretable predictions facilitates earlier warning of heavy metal contamination and guides the formulation of robust sampling strategies.

Elevated Uptake and Translocation Patterns of Heavy Metals in Different Food Plants Parts and Their Impacts on Human Health.

Irrigation with contaminated wastewater is a common practice in cultivation of crops and vegetables in many developing countries due to the scarcity of available fresh water. The present study has investigated the transfer and mobilization trends of heavy metals in different crops and vegetables plants grown in contaminated soil and waterbody. The translocation patterns of metals from polluted sources into different organs of plants bodies such as roots and edible parts and associated health risks have been evaluated simultaneously. Total of 180 different environmental samples including food plants, agricultural soil, and irrigation water were collected and analyzed. Heavy metal concentrations (Fe, Ni, Mn, Pb, Cu, Cd, As) in water, soil, and different parts of crops and vegetable plants were compared with the permissible levels reported by FAO/WHO, EU, and USEPA. Different metals contents within the food plants were found to be in the order of Fe > Mn > Ni > Cu > Pb > Cd > As. Pollution load index (PLI) data indicate that soil is highly polluted with Cd as well as moderately contaminated by As and Cu. Bioconcentration factor (BCF) analysis showed excessive accumulation of some heavy metals in crops and vegetables. Target hazard quotient (THQ) and target carcinogenic risk (TCR) analysis data showed higher carcinogenic and non-carcinogenic risks for both adult and children from the consumption of metal-contaminated food items. The results of metal pollution index (MPI), estimated daily intake (EDI), and hazard index (HI) analyses demonstrated the patterns of metals pollution in different food plants.

Assessment of heavy metals and human health risk associated with the consumption of crops cultivated in industrial areas of Maputo, Mozambique

This study aimed to evaluate heavy metals concentrations in soils and vegetables (cabbage, lettuce, and cassava) cultivated at Matola and Beluluane Industrial Parks, and to assess health risks linked to their consumption through estimated daily intake, hazard index (HI), and incremental lifetime cancer risk. Concentrations of Al, As, Co, Cd, Cr, Ni, Pb, and Zn were determined in the two sites. Soil concentrations of As at Beluluane site and As, Cd, and Cr at Matola site exceeded reference limits of the Food and Agriculture Organization/World Health Organization, showing heavy metal contamination. At Beluluane site, all studied vegetables presented As and Pb levels higher than reference limits, Cd concentrations were higher than the reference limit in cabbage, lettuce, and cassava leaves. At Matola site crops concentrations of As, Cd, Cr, and Pb exceeded the reference limits. Zinc exceeded the reference limit in all crops except in cabbage. HIs for vegetables from Beluluane exceeded 1.0 in cabbage (2.66), lettuce (2.27), and cassava leaves (2.37). Likewise, at Matola, HIs exceeded 1.0 in lettuce (1.67), cassava leaves (1.65), and root tubers (13). We found that vegetables cultivated in industrial parks present high carcinogenic risk due to heavy metal contamination, rendering them unsuitable for human consumption.

Fertility and heavy metal pollution in silage maize soil irrigated with different levels of recycled wastewater under conventional and no-tillage practices

AbstractIrrigation with recycled domestic wastewater has been known to obtain positive effects on improving soil fertility, but it may also become a risk factor in case of causing an increase in soil salinity and/or heavy metal concentration of soil. No-tillage can retain soil moisture, helping to reduce irrigation water necessity, and thus lower amounts of heavy metals and salts are added to soil under wastewater irrigation conditions. The objective of this study was to analyze the effects of wastewater irrigation at different levels of on silage maize cultivation under conventional tillage and no-tillage conditions by comparing to full irrigation with fresh water. The two-year experiment was planned according to the split-plots design in the random blocks with three replications. The results indicated that full irrigation with wastewater increased soil salinity, organic matter content, total nitrogen, plant available phosphous, exchangeable cations, exchangeable sodium percentage and soil essential and non-essential heavy metal contents, but decreased soil pH and lime content. Increasing rates in organic matter content, total nitrogen, plant available phosphorus and exchangeable potassium were higher, but in electrical conductivity, and heavy metal accumulation were lower in soil under no-tillage as compared to conventional tillage. Contamination and enrichment factors and geographic accumulation index showed that non-essential heavy metal contamination due to cadmium and nickel, increased in full irrigation with wastewater. Irrigation with wastewater also increased heavy metal accumulation in silage maize. No-tillage can be a recommendable water management practice considering that the risks of soil salinity and heavy metal accumulation can be reduced and that soil fertility can be increased. Also, in reducing the risk of accumulation of cadmium and nickel in soil, 33% deficit irrigation with wastewater can make no-tillage more available.

Re-Interpretation of Metal(Loid) Concentrations in Urban Soils of Two Different Land Uses by Positive Matrix Factorisation

Positive matrix factorisation (PMF) is a receptor model, which is frequently used in environmental geochemistry for metal(loid)s’ source apportionment in various matrices. In this study, concentration data for As, Cu, Co, Cr, Fe, Mn, Ni, Pb, Sb, V and Zn in urban soils of two land uses (playground and roadside soils) from the city of Bratislava (Slovak Republic) were reinterpreted using the PMF model to quantify the contributions of individual sources of metal(loid)s in soils. Brake and tyre abrasion (27.0%), mixed traffic/industrial sources (14.3%), and natural origin (58.7%) were identified for roadside soils, while mixed traffic sources (28.4%), Cu-specific source (24.6%), and natural origin (47.0%) contributed to the metal(loid) concentrations in playground soils. Factor contributions revealed prevailing non-exhaust sources dominated by Cu, Sb and Zn over mixed traffic/industrial sources in roadside soils, following the world trend. Strong negative correlations of the 206Pb/207Pb isotopic ratio with Factor 1 in both groups of soils, representing traffic and industrial sources, are an evidence of the correct assignment of the obtained factor profiles to the actual sources of metal(loid)s in soils. There were significant differences in the proportion of mixed traffic sources in playground soils among the five urban districts, while the largest proportion of this source was identified in the city centre with the longest urbanisation and industrial history. Error estimation methods (displacement, bootstrap, displacement with bootstrap) proved that the data fit the model well and there was a minimal rotational ambiguity and random errors in the base model run.

Plant colonizers of a mercury contaminated site: trace metals and associated rhizosphere bacteria

Background and aimsMercury (Hg) contamination poses severe human and environmental health risks. We aimed to evaluate the colonization of Hg-contaminated sites by native plants and the prokaryotic composition of rhizosphere soil communities of the dominant plant species.MethodsA field study was conducted at a Hg-contaminated site in Romania. Metal concentrations in soil and plant samples were analyzed using portable X-ray fluorescence spectrometry. The prokaryotic composition of rhizosphere soil communities was determined through 16S rRNA amplicon sequencing and community functionality was predicted through PICRUSt2.ResultsSite-specific trace metal distribution across the site drove plant species distribution in the highly contaminated soil, with Lotus tenuis and Diplotaxis muralis associated with higher Hg concentrations. In addition, for the bacterial communities in the rhizosphere soil of D. muralis, there was no observable decrease in alpha diversity with increasing soil Hg levels. Notably, Actinomycetota had an average of 24% relative abundance in the rhizosphere communities that also tested positive for the presence of merA, whereas in the absence of merA the phylum’s relative abundance was approximately 2%. merA positive rhizosphere communities also displayed an inferred increase in ABC transporters.ConclusionsThe results suggest a dependence of species-wise plant survival on local trace metal levels in soil, as well as an intricate interplay of the latter with rhizosphere bacterial diversity. Knowledge of these interdependencies could have implications for phytoremediation stakeholders, as it may allow for the selection of plant species and appropriate soil microbial inoculates with elevated Hg tolerance.

Human health risk assessment of metal-contaminated soils in Sydney estuary catchment (Australia)

Sydney estuary catchment supports the largest city in Australia and provides essential eco-social and environmental services; however, the region has been influenced by extensive anthropogenic modification. Soil metal concentrations in the catchment had been studied previously; however, the current investigation was designed to determine the risk posed by these contaminants to human health. Soil metal concentrations were higher than observed in most global capitals and increased substantially in the south and south-east of the catchment and close to the central business district. Road-side soils and road dust contained the highest concentration of metals in the catchment. Lead in catchment soils was closely related to traffic density and sourced from the historic use of Pb in petrol. A human health assessment indicated that soil Cd, Ni and Zn posed no non-carcinogenic risk (NCR), or carcinogenic risk (CR) for children, or adults in Sydney estuary catchment and that Cu and Cr may pose minor NCR for children. Vehicle-related Pb raised the greatest human health risk in catchment soils and may pose NCR at 32% and 4.3% of sites for children and adults, respectively. Inconsistent analytical techniques used in CR and NCR evaluations produce incomparable assessments and a consistent` methodology is suggested to improve interpretation. Human health risk may well be higher than commonly calculated due to pollutants present in urban soil not being included in assessments.

Health risk assessment of heavy metals in soil and vegetables from major agricultural sites of Ohio and West Virginia

Contamination of soil and crops with heavy metals (HMs) poses a significant environmental challenge in the United States, while the status of metal contamination and associated health risks have been merely studied. Hence, this study aimed to assess metal contamination in major agricultural sites of Ohio and West Virginia, and evaluate the potential health risks associated with consuming metal-contaminated vegetables. Among the agricultural sites studied, Fe was the most predominant contaminant in all the sampling sites, ranging from 28,410 to 67,306 mg/kg of soil, exceeding the permissible limit of the US-EPA. Whereas Cd was the least contaminant, exceeding the permissible limit only in three sampling sites (ME1, ME3, and ME6), ranging from 0.13 to 2.91 mg/kg of soil. Interestingly, range of metals in vegetable samples were within the permissible limits. Principal component and hierarchical cluster analysis indicated the different natural and anthropogenic sources of metals in soil. In noncarcinogenic health risk assessment, the values of EDI, TEDI, THQ and HI levels for all the metals were lower than their daily uptake. However, CR and TCR assessment reveal significant risks associated with Ni exposure for both adults and children, with values of 3.487E-4 and 1.172E-3, and 5.362E-4 and 1.286E-3, respectively, within these agricultural sites. Therefore, regular monitoring of metal concentrations in soil and vegetables, as well as associated health risks, is strongly recommended to prevent potential health hazards in the future.

Different “nongrain” activities affect the accumulation of heavy metals and their source-oriented health risks on cultivated lands

“Nongrain” production on cultivated land is one of the primary environmental issues in China. Different “nongrain” activities may introduce different pollution sources to the local environment, leading to variations in heavy metal contents in soil, which can profoundly impact national food security. In this study, three typical “nongrain” regions (Nanxun (NX), Xiaoshan (XS) and Lin'an (LA)) with intensive aquaculture, tea planting and flower (seedling) growth on cultivated land around the Hangzhou metropolitan area were selected to address the spatial heterogeneity of accumulation levels, sources and source-oriented health risks of heavy metals in soil. The results showed that Hg was the main pollutant in NX and XS, while Cd and As were the major contaminants in LA. Aquiculture and sericultural industries (37.43%), natural sources (23.59%) and industrial activities (38.99%) were the major sources in NX; atmospheric deposition (37.73%), flower and seedling planting (23.49%) and metal-related industries (35.16%) were the major sources in XS; and atmospheric deposition (28.06%), excessive application of fertilizers and pesticides during tea planting (43.47%) and natural sources (28.47%) were the major sources in LA. The major risk population, area, exposure route and hazardous elements were children, LA, ingestion and As and Cr, respectively. From the perspective of source-based health risk assessment, in addition to natural sources that are difficult to intervene in, industrial activities, especially leather and wood process industries, metal-related industries and excessive fertilizer and pesticide application during tea planting contributed the most to the total health risk, which explained 67%, 41% and 42%, respectively, of the total risk in NX, XS and LA. High health risks are present in sources with heavy loadings of hazardous heavy metals (As and Cr); thus, to protect human health, the corresponding high-risk anthropogenic pollution sources in different “nongrain” areas need to be controlled.

Phytoremediation by trees as a nature-based solution for mitigating metal contamination in urban soils.

Trace metals in the environment are important pollutants affecting human health, particularly in urban areas worldwide. Phytoremediation as a nature-based solution (NBS) and environmentally friendly technology may decrease high concentrations of trace metals in urban soils, protecting public health (especially children) and contributing to urban sustainability. This study examined trace metal contamination of urban soils and trees in six cities in the Republic of Srpska (RS), Bosnia and Herzegovina (BiH) and investigated the potential of selected tree species for phytoremediation as a NBS for metal-polluted urban soils. Contamination of urban soils was assessed by quantifying the concentrations of 11 trace metals (B, Ba, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, and Zn). To estimate phytoremediation potential of urban tree species, concentration and bioconcentration factor of the 11 metals were quantified in leaves of three common and abundant tree species: Aesculus hippocastanum L. (horse chestnut), Platanus acerifolia Willd. (plane), and Tilia sp. (lime). The results showed that trace metal concentrations in leaf samples did not exceed toxicity threshold guideline values. Further assessments are needed to establish the true potential of the three species as NBS for urban soils.

Characteristics and Identification Priority Source of Heavy Metals Pollution in Farmland Soils in the Yellow River Basin

Assessments of the soil environmental quality of farmland and pollution source apportionment are the foundation for ensuring national food security and agricultural sustainable development, as well as an important prerequisite for the pursuit to keep our lands clean. This study evaluated the characteristics of heavy metal pollution in farmland soils in the Yellow River Basin from 2000 to 2023, based on the data of heavy metal contents including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, using the geo-accumulation index method. Source apportionment was conducted by employing a positive matrix factorization (PMF) model. The probabilistic health risks were evaluated by coupling Monte Carlo simulation with a human health risk assessment model, and priority pollution sources and elements were identified. The results showed that:① the average content of all heavy metals in farmland soils within the study area was lower than the screening values specified in the soil environment quality risk control standard for soil contamination of agriculture land (GB 15618-2018) (pH>7.5). However, the contents of Cd, As, and Zn in the samples exceeded their screening values, with percentages of 21.69%, 5.56%, and 1.23%, respectively, with Cd having the highest rate of exceedance. ② Hg and Cd were moderately polluted, Cu and Pb were slightly polluted, and the other elements were not polluted. ③ The main sources of heavy metals in farmland soil were traffic-industrial sources, natural-agricultural sources, industrial-natural sources, and agricultural-industrial sources, with contribution rates of 37.04%, 26.69%, 21.72%, and 14.55%, respectively. ④ Heavy metals in farmland soil posed carcinogenic health risks to adults and children but did not have non-carcinogenic risks; As and Cd were priority control elements for human health risks, and industrial-natural sources and agricultural-industrial sources were priority control sources in the study area.

SOLID-PHASE FRACTIONATION OF HEAVY METAL IONS IN SOILS FROM MUNICIPAL WASTE DUMPSITE IN PORT HARCOURT, NIGERIA

In many cities across the developing countries solid wastes are disposed indiscriminately without recourse to the human health risk. Heavy metals found in solid wastes may likely be released into the environment via flood runoff. To assess whether the contaminants can affect the groundwater, soil samples were collected for analysis in two seasons – dry and wet seasons. To determine level of the metals in the soil matrix, the samples were subjected to acid digestion followed by atomic absorption spectroscopy analysis. The different solid-phases associated with heavy metals were evaluated from the soil samples by using sequential extraction method. The geo-accumulation index and mobility factor were considered to assess the level of contamination and migration of the metals present in the soil. The soil metal contents strongly correlated with the soil pH and organic matter. The exchangeable fraction has Cr &gt; Pb &gt; Co in the order of its mobility in the soil, whilst in the residual fraction suggesting the most immobile species with Pb &gt; Co &gt; Cr &gt; Ni present in the soil. The geo-accumulation index showed that the degree of pollution of the dumpsite during the dry and wet seasons was mostly unpolluted. The study indicates that the metals of interest may not likely pose environmental risk due to their relatively low concentrations and the chemical species in which they exist in soil.

Urbanization-driven forest soil greenhouse gas emissions: Insights from the role of soil bacteria in carbon and nitrogen cycling using a metagenomic approach

Increasing population densities and urban sprawl have induced greenhouse gas (GHG) emissions from the soil, and the soil microbiota of urban forests play a critical role in the production and consumption of GHGs, supporting green development. However, the function and potential mechanism of soil bacteria in GHG emissions from forests during urbanization processes need to be better understood. Here, we measured the fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in Cinnamomum camphora forest soils along an urbanization gradient. 16S amplicon and metagenomic sequencing approaches were employed to examine the structure and potential functions of the soil bacterial community involved in carbon (C) and nitrogen (N) cycling. In this study, the CH4 and CO2 emissions from urban forest soils (sites U and G) were significantly greater than those from suburban soils (sites S and M). The N2O emissions in the urban center (site U) were 24.0 % (G), 13.8 % (S), and 13.5 % (M) greater than those at the other three sites. These results were related to the increasing bacterial alpha diversity, interactions, and C and N cycling gene abundances (especially those involved in denitrification) in urban forest soils. Additionally, the soil pH and metal contents (K, Ca, Mg) affected key bacterial populations (such as Methylomirabilota, Acidobacteriota, and Proteobacteria) and indicators (napA, nosZ, nrfA, nifH) involved in reducing N2O emissions. The soil heavy metal contents (Fe, Cr, Pb) were the main contributors to CH4 emissions, possibly by affecting methanogens (Desulfobacterota) and methanotrophic bacteria (Proteobacteria, Actinobacteriota, and Patescibacteria). Our study provides new insights into the benefits of conservation-minded urban planning and close-to-nature urban forest management and construction, which are conducive to mitigating GHG emissions and supporting urban sustainable development by mediating the core bacterial population.

Inversion of heavy metal content in soil using hyperspectral characteristic bands-based machine learning method

The global concern regarding the adverse effects of heavy metal pollution in soil has grown significantly. Accurate prediction of heavy metal content in soil is crucial for environmental protection. This study proposes an inversion analysis method for heavy metals (As, Cd, Cr, Cu, Ni, Pb) in soil based on hyperspectral and machine learning algorithms for 21 soil reference materials from multiple provinces in China. On this basis, an integrated learning model called Stacked RF (the base model is XGBoost, LightGBM, CatBoost, and the meta-model is RF) was established to perform soil heavy metal inversion. Specifically, three popular algorithms were initially employed to preprocess the spectral data, then Random Forest (RF) was used to select the best feature bands to reduce the impact of noise, finally Stacking and four basic machine learning algorithms were used to establish comparisons and analysis of inversion model. Compared with traditional machine learning methods, the stacking model showcases enhanced stability and superior accuracy. Research results indicate that machine learning algorithms, especially ensemble learning models, have better inversion effects on heavy metals in soil. Overall, the MF-RF-Stacking model performed best in the inversion of the six heavy metals. The research results will provide a new perspective on the ensemble learning model method for soil heavy metal content inversion using data of hyperspectral characteristic bands collected from soil reference materials.

Accumulation of Heavy Metals and Determination of Natural Radioactivity in the Soil-Thyme System in Omerli, Istanbul: Assessment of Ecological and Health Risk

A significant pathway for human exposure to environmental pollutants is the metal transfer from soil to plants. In this study accumulation of different metals was investigated and natural radioactivity levels were measured in the soil–thyme system. It was found that the soil had higher concentrations of Br, Cr, Mn, Ni, and Pb than the world average and P, Ca, and Zn had higher transfer factors. The natural radioactivity level in the soils is similar to the World average. For thyme samples the average values for 226Ra, 232Th and 40K were found as 22.7 ± 10.9 Bqkg-1, 61.3 ± 19.9 Bqkg-1 and 722 ± 391 Bqkg-1, respectively. The health and ecological risks of soil were evaluated. The total hazard index of the child was 1.453 on average, greater than that of the adult (0.175), primarily due to the contribution of Cr. Ecological risk assessed based on various indices indicated that Pb and Ni show environmental contamination risk. Our findings confirm that metal concentrations in plants are influenced by metal concentrations in soil, and that metal interactions are important for pollution risk management.

Contamination of urban soils in a historical mining town of northern Chile

In northern Chile, economic activities related to mining and thermoelectric energy have existed in the city of Tocopilla since the early 1900s and metal concentrations in soils have likely been altered by historic anthropogenic activities. To assess the concentrations of Cu, Zn, Pb, Ni, Co, and Cr in urban soils of Tocopilla, a total of 70 superficial (2 cm) and 70 deep (20 cm) soil samples were collected in 2014. Furthermore, to analyze concentration changes in soils over time, 18 superficial (5 cm) samples were collected in 2020–2021. A numerical evaluation (geoaccumulation index, and enrichment factor), principal component analysis, and spatial distribution approach were applied to infer geogenic and anthropogenic influence on the concentrations of these elements. The main conclusions of this research indicate that urban soils of Tocopilla contain geogenic Cu, Zn, Pb, Ni, Co and Cr. However, elevated concentrations of Cu, Zn, and Pb cannot be attributed to a geogenic origin alone, as a proportion of their enrichment is considered to be anthropogenically sourced. The contamination of anthropogenic elements has been found to be related to historic copper mining and thermoelectric energy production. Furthermore, when compared to other sites globally, median concentrations of Cu (945 mg/kg in 2014 and 823 mg/kg in 2020) and Zn (305 mg/kg in 2014 and 196 mg/kg in 2020) in superficial urban soils are among the highest worldwide. Regarding 2020–2021 sampling, Zn and Pb concentrations have increased, while Cu, Cr, Co, and Ni have remained similar to the 2014 samples.