Soil Concentrations Research Articles

Globally-significant arsenic release by wildfires in a mining-impacted boreal landscape

Metal mining and smelting activities are one of the largest anthropogenic sources of arsenic pollution to the environment, with pervasive consequences to human and environmental health. Several decades of metal processing activities near Yellowknife, NT, Canada have resulted in widespread accumulation of arsenic in biomass, soils, and sediments, exceeding environmental and human health limits. The landscape surrounding Yellowknife is frequently disturbed by wildfire, most recently in 2023, when 2500 km2 burned. While wildfire-mediated release of stored arsenic around Yellowknife likely represents an incipient threat to human and ecosystem health, a quantification of the potential magnitude of arsenic remobilization from wildfires is absent. Here we combine publicly available soil and biomass arsenic concentrations and land cover datasets with the current best estimates of pyrogenic arsenic speciation and release in upland and wetland ecosystems to estimate the potential range of arsenic remobilization due to wildfires in the region surrounding Yellowknife from 1972 to 2023. Since 1972, wildfires have potentially led to the release of 141–562 Mg of arsenic, with 61–381 Mg emitted to the atmosphere and 39–109 Mg mobilized as water-soluble species. The large range in potential atmospheric emissions was due to the range in peat emission efficiency (5%–84%) that resulted in more arsenic being released from wetlands than the uplands. In 2023 alone, our estimated atmospheric release from just four wildfires was between 15%–59% of global annual arsenic wildfire emissions and likely represented between 2 and 9% of total global arsenic emissions from all natural sources. Given that climate change has and will continue to increase both annual area burned and soil burn severity, we emphasize that future increased wildfire activity closer to Yellowknife will place legacy soil arsenic stores at risk of an even larger catastrophic and unprecedented release, especially as wetlands become drier.

Gross alpha/beta and radionuclide activity concentrations in soil, plant and some fruits around the Tehran Research Reactor

Human activities usually have some contamination as effluents from chemical industries and radionuclides from nuclear reactors. For assessing the probable radioactive contamination in vicinity of Tehran Research Reactor, The gross alpha and beta radioactivity concentrations in soil, pine and cedar leaves and some selected fruits (fig, apple, berry and pomegranate) were investigated using an alpha/beta spectrometer during 2021–2022. Also, the concentrations of artificial and natural radionuclides in samples were investigated by the method of gamma spectroscopy. The gross alpha activity concentrations in soil, pine and cedar leaves and some selected fruits samples are from 0.05 to 0.35 Bq/gr and 0.07–0.31 Bq/gr and 0.04–0.18 Bq/gr, respectively. The gross beta activity concentrations in soil, pine and cedar leaves and some selected fruit samples are from 0.73 to 4.25 Bq/gr and 0.21–3.97 Bq/gr and 1.01–2.71 Bq/gr, respectively. Average activities concentration of natural radionuclide 232Th, 238U and 40K in soil, pine and cedar leaves and some selected fruits are 31.89–16.23–582.73 Bq/kg and 1.84–0.99–84.60 Bq/kg and 1.98–1.09–72.08 Bq/kg respectively. From artificial radionuclides, just 137Cs is recognized in soil sample and the range of 137Cs concentration in surface soils was observed to vary in the range 0.85–2.21 (Bq/kg). The result showed that the Tehran Research Reactor activities not have increased the environmental radioactivity and radiation level in the area.

Impact of Fertilizers Application on Leaf Litter Decomposition and Nutrient Cycling in White Poplar (Populus alba L.) Forest Ecosystem

Fertilizer application plays a crucial role in the decomposition of white poplar leaf litter and cycling of nutrients within forest ecosystems. The impact of various fertilizer additions on white poplar leaf litter and nutrient cycling is poorly understood. In this study, seven treatments were conducted at the following levels: Control (CK), no adding mineral fertilizers, N fertilization (+N), N and P fertilization (+NP), N, P, K fertilization (+NPK), P, K (+PK), manure fertilizer (+MF), and bird fertilizers (+BF) in a white poplar plantation in Qadis district, and used the litterbag techniques to measure litter mass remaining. The main objectives of our study were: (1) to explore the response of white poplar leaf litter decomposition to various fertilizers and accelerate the decomposition process; (2) to examine the relationship between C, N, and P concentration and their stoichiometric characteristic in leaf litter and soil. In this investigation, our results showed that white poplar leaf litter was significantly affected by fertilizers, and the decomposition process was greatly accelerated with + MF, +NPK, and + BF. The decay rate constant k (year −1) shows the decomposition rate of white poplar leaf litter as follows: +MF > +NPK > +BF > +PK > +NP > +N > CK (0.56, 0.53, 0.52, 0.51,0.51,0.5, and 0.46). Soil nutrients N, P and K increased significantly during the decomposition time with + MF, +NPK, and + BF, respectively, while C:N, C:P, and N:P ratios were highest in the white poplar leaf litter, and lowest in soil, we observed significant association between nutrients concentrations in soil and white poplar leaf and their stoichiometric. This current study concluded that adding + MF, +NPK and + BF fertilizers might be the preferred management option as they provided potentially beneficial changes in leaf litter decomposition and increased nutrient concentration. The data obtained will be a valuable reference for fertilization management strategies in forest ecosystems.

Implications of current soil phosphorus levels for manureshed analysis in North Carolina

AbstractManure relocation strategies are needed to mitigate excessive phosphorus (P) application to agricultural land in areas of intensive animal agricultural production. This requires conceptual frameworks such as the manureshed, which categorizes agricultural areas according to the potential to export or receive manure for P fertilization. To further understand how the manureshed concept could be utilized, assessments of the potential implementation and necessity of the manureshed model are needed. With North Carolina at the center of the largest manureshed in the United States, North Carolina is an ideal test case to identify areas of concern for manure relocation under the manureshed framework. Swine and poultry dominate North Carolina's agricultural production, and because the vast majority of North Carolina producers are not required to limit manure applications to a P‐based rate, P accumulates. Therefore, soil test data from samples submitted to the North Carolina Department of Agriculture and Consumer Services (NCDA&CS) from 2017 to 2019 were used to determine how manureshed classes defined by Spiegal et al. correspond to current soil test P levels. It was determined that 36% of counties experience very high (>100 mg P kg−1; N = 36) median P concentrations in soil. Furthermore, fields cultivated with warm‐season forages had the highest mean P concentration (188 mg kg−1) and high median P trended toward counties with high animal production. Lastly, while mean soil P for all manureshed classifications fell into the very high category, manure source counties had the highest mean soil P concentrations (188 mg kg−1), which was 39%–52% higher than the other classifications. This suggests that, in addition to manuresheds classification, soil test data are needed to design and promote manure redistribution strategies.

Bayesian risk prediction model: An accessible strategy to predict cadmium contamination risk in wheat grain grown in alkaline soils

Excessive cadmium (Cd) concentration in wheat grain is becoming a widespread concern in China. Considering the complexity of Cd transfer in the soil-wheat system, how the Cd risk in wheat grain be accurately predicted from the limited details available is of great significance for the risk management of Cd. Bayes' theory could leverage existing data by combining prior information and observational data, providing a promising strategy with which to calculate a more robust posterior probability of a grain sample exceeding the food safety standard (FSS) for Cd (0.1 mg kg−1). In the current study, a risk prediction model, based on Bayes’ theory, was established to achieve a more accurate prediction of the wheat grain Cd risk from a limited number of soil parameters. The risk prediction model could predict the risk probability of wheat grain with a Cd concentration exceeding the FSS under a given soil concentration of either total Cd or diethylenetriaminepentaacetic acid (DTPA)-extractable Cd. Soil total Cd concentration proved to be a better variable for the model with greater predictive accuracy. The model predicted that fewer than 5% of the wheat grain would have a Cd concentration exceeding the FSS when grown in soil with a total Cd concentration of less than 0.299 mg kg−1. The risk probability rose significantly to 50% when the soil total Cd reached 0.778 mg kg−1. The accuracy of the model was greater than the widely applied multiple linear regression model, whereas previously published data from similar soil conditions also confirmed that the Bayesian model could predict wheat Cd risk with minimal error. The proposed model provides an accurate, accessible and cost-effective methodology for predicting Cd risk in wheat grown in alkaline soils before harvest. The wider application to other soil conditions, crops or contaminants using the Bayesian model is also promising for risk management authorities.

Tradescantia response to air and soil pollution, stamen hair cells dataset and ANN color classification.

Tradescantia plant is a complex system that is sensible to environmental factors such as water supply, pH, temperature, light, radiation, impurities, and nutrient availability. It can be used as a biomonitor for environmental changes; however, the bioassays are time-consuming and have a strong human interference factor that might change the result depending on who is performing the analysis. We have developed computer vision models to study color variations from Tradescantia clone 4430 plant stamen hair cells, which can be stressed due to air pollution and soil contamination. The study introduces a novel dataset, Trad-204, comprising single-cell images from Tradescantia clone 4430, captured during the Tradescantia stamen-hair mutation bioassay (Trad-SHM). The dataset contain images from two experiments, one focusing on air pollution by particulate matter and another based on soil contaminated by diesel oil. Both experiments were carried out in Curitiba, Brazil, between 2020 and 2023. The images represent single cells with different shapes, sizes, and colors, reflecting the plant's responses to environmental stressors. An automatic classification task was developed to distinguishing between blue and pink cells, and the study explores both a baseline model and three artificial neural network (ANN) architectures, namely, TinyVGG, VGG-16, and ResNet34. Tradescantia revealed sensibility to both air particulate matter concentration and diesel oil in soil. The results indicate that Residual Network architecture outperforms the other models in terms of accuracy on both training and testing sets. The dataset and findings contribute to the understanding of plant cell responses to environmental stress and provide valuable resources for further research in automated image analysis of plant cells. Discussion highlights the impact of turgor pressure on cell shape and the potential implications for plant physiology. The comparison between ANN architectures aligns with previous research, emphasizing the superior performance of ResNet models in image classification tasks. Artificial intelligence identification of pink cells improves the counting accuracy, thus avoiding human errors due to different color perceptions, fatigue, or inattention, in addition to facilitating and speeding up the analysis process. Overall, the study offers insights into plant cell dynamics and provides a foundation for future investigations like cells morphology change. This research corroborates that biomonitoring should be considered as an important tool for political actions, being a relevant issue in risk assessment and the development of new public policies relating to the environment.

Effects of Chinese “double carbon strategy” on soil polycyclic aromatic hydrocarbons pollution

Polycyclic aromatic hydrocarbons (PAHs) and carbon dioxide primarily originate from the combustion of fossil fuels and biomass. The implementation of the Chinese “double carbon strategy” is expected to impact the distribution of PAH emissions, consequently influencing the spatial distribution trend of PAHs in surface soil. Therefore, it is crucial to quantitatively evaluate the effectiveness of the Chinese “double carbon strategy” on soil PAH pollution for the purpose of “the reduction of pollution and carbon emissions”. This study utilized 15,088 individual PAH concentration data from 943 soil samples collected between 2003 and 2020 in China, in conjunction with PAH emissions at a 10 km resolution, for meta-analysis. The calculated PAH emissions in this study are in line with the global PAH emission inventory (PKU-PAH-2007), with a relative standard deviation at the provincial level of less than 25 %. Subsequently, a novel method was developed using emission density and Kow of PAHs to predict PAH concentrations in surface soil based on a least-squares regression model. Compared to other environmental models, the method established in this study significantly reduced the percent sample deviation to less than 70 %. Furthermore, energy consumption data for China were simulated based on the implementation plan of the “double carbon strategy” to project PAH emissions and soil PAH levels for the years 2030 and 2060. The predicted PAH emissions in China were estimated to decrease to 41,300 t in 2030 and 10,406.5 t in 2060 from 78,815 t in 2020. Moreover, the heavily contaminated areas of soil PAHs (i.e., total PAH concentrations in soil exceeding 1000 μg kg−1) were projected to decrease by 45 % and 82 % in 2030 and 2060, respectively, compared to levels in 2020. These findings suggest that the implementation of the “double carbon strategy” can fundamentally reduce the pollution of PAHs in surface soil of China.

Evaluating the Potential of Carbon Black for Safening of Herbicides in Soil

ABSTRACT Finely divided carbon char products offer a cost-effective method for the safening of herbicides in soil. In this investigation, two contrasting carbon char sources: Virgin Activated Charcoal (VAC) and Recovered Carbon Black (RCB) products were evaluated for safening of metsulfuron, sulfentrazone and pyroxasulfone herbicides in soil using sugar beet bioassay, and of rimsulfuron using perennial ryegrass bioassay. Plants were grown for seven days in WhirlPack® bags in soil with added carbon char product and added herbicide, and the root or shoot lengths were measured. The VAC was more efficacious in herbicide safening than the RCB. For the VAC, concentrations in soil (wt/wt) as low as 0.375% fully deactivated metsulfuron, sulfentrazone and pyroxasulfone, while for the RCB product a gradual degree of safening was observed, except for pyroxasulfone that was completely deactivated by both VAC and RCB. The VAC at concentrations of 3% and above fully deactivated rimsulfuron, while RCB did not. The two carbon char products examined in this study had different physical properties, of which the specific surface area (91 and 515 m2 g−1 for the RCB and VAC, respectively) and specific surface area of pores (75 and 247 m2 g−1 for RCB and VAC, respectively) showed the greatest difference. Higher surface area promoting greater sorption may explain more effective deactivation of herbicides by the VAC. To obtain the same degree of herbicide safening, more RCB would be required.

Phytoremediation potential of Brassica oleracea varieties through cadmium tolerance gene expression analysis

BackgroundBrassica oleracea var. acephala, commonly referred to as kale, is a well-documented plant species, a food crop but well recognized for its capacity to endure and manage the accumulation of heavy metals. In this research, the phytoremediation potential of kale was evaluated based on cadmium intake, utilizing three distinct kale varieties originating from Bosnia and Herzegovina. All kales were grown in controlled conditions, with different concentrations of cadmium (Cd), a known strong pollutant found in small concentrations in soil under normal environmental conditions. After the root length analysis and cadmium atomic spectrometry, we utilized quantitative PCR (qPCR) and cycle threshold (Ct) values to calculate the expression levels of five genes associated with Cd heavy metal response: Mitogen-activated protein kinase 2 (MAPK2), Farnesylated protein 26 and 27 (HIPP26, HIPP27), Natural resistance-associated macrophage protein 6 (RAMP6), and Heavy metal accumulator 2 (HMA2). ResultsThe atomic reader's analysis of rising cadmium concentrations revealed a proportional decline in the length of kale roots. The gene expression levels corresponded to cadmium stress differently among varieties, but mostly showing notable up-regulations under Cd stress, indicating the strong Cd presence within the plant. ConclusionsThis study demonstrated differences in gene expression behavior among three B. oleracea varieties from Bosnia and Herzegovina, indicating and filtering the Cd-resistant kale, and kale varieties suitable for phytoremediation. For the first time, such a study was conducted on kale varieties from Bosnia and Herzegovina, analyzing the impact of cadmium on the growth and resilience of these species.

Impact on sulfadiazine bio-accessibility in soils through organic diffusive gradients in thin films (o-DGT): Differentiation based on microplastic polymers, aging, and soil properties

Due to the similar sources of swage irrigation, organic fertilizer, and sludge application, microplastics (MPs) and antibiotics coexist inevitably in the agriculture soils. However, the impacts of MPs with different polymer types and aging status on the bio-accessibility of co-existing antibiotics in soils remained unclear. Therefore, we using the diffusive gradients films for organic compounds devices (o-DGT) to evaluated the distribution of sulfadiazine (SDZ) in both paddy soil and saline soil amended with 0.5 % (w/w) MPs. Four polymer types (polyethylene: PE, polypropylene: PP, polyamide: PA, and polyethylene terephthalate: PET) and two aging statuses (aged PE and aged PP) of MPs were used in this study. Results showed that soil properties significantly influence the partition of SDZ in soil and soil solution, and SDZ gained a lower degradation rate but higher mobility in saline soil. MPs pose different impacts on partition of SDZ between paddy soil and saline soil. Notably, PP reduced the labile solid phase-solution phase partition coefficient (Kdl) by 17.7 % in paddy soil, while PE, PP, and aPE increased the Kdl value by 2.00, 1.62, and 2.81 times in saline soil. Besides, in saline soil, all the MPs reduced the SDZ concentration in the soil solution, while significantly increased the SDZ in o-DGT phase. Conversely, MPs did not impact the SDZ's o-DGT concentration in paddy soil. Additionally, MPs increased the R value of SDZ in two soils, especially in saline soil. It suggested that MPs could potentially enhance the resupply of SDZ from soil to plants, particularly under saline conditions. Furthermore, aged MPs had a more pronounced effect on these indicators compared to virgin MPs in saline soil. Therefore, MPs in soil poses a potential risk for biota's uptake of SDZ, particularly in fragile environment. Moreover, the risk intensifies with aged MPs.

Modeling risk assessment of soil heavy metal pollution using partial least squares and fuzzy logic: A case study of a gully type coal-based solid waste dumpsite

Continuous release and migration of heavy metals from coal-based solid waste (CSW) dumpsites often results in significant encroachment on ecological lands and pollution of natural environments. As a result, there is an urgent need for long-term and rapid monitoring, analysis, and assessment to control environmental risks associated with large CSW dumpsites. We constructed a new composite model (PLS-FL) that uses partial least squares regression (PLSR) and fuzzy logic inference (FLI) to accurately predict heavy metal concentrations in soils and assess pollution risk levels. The potential application of the PLS-FL was tested through a gully type CSW case study. We compared 20 modeling strategies using the PLS-FL: five types heavy metals (Cd, Zn, Pb, Cr and As) * four spectral transformation methods (first derivative (FD), second derivative (SD), reverse logarithm (RL), and continuum removal (CR)) * one variable selection method (competitive adaptive reweighted sampling (CARS)). The results showed that the combination of derivative transformation and CARS was recommended for estimation, with R2C > 0.80 and R2P > 0.50. When comparing the PLSR model with four traditional machine learning methods (Support Vector Machines (SVM), Random Forests (RF), Extreme Learning Machines (ELM), and KNN), the PLSR model demonstrated the highest average prediction accuracy. Additionally, the FLI process no longer relies on human perception and expert opinion, enhancing the model's objectivity and reliability. The evaluation results revealed that the heavy metal contamination areas of the CSW dumpsite are concentrated at the bottom of the gully, with more severe contamination in the north. Furthermore, a high-risk zone exists in the interim storage area for CSW to the east of the dump. These findings align with the initial detections at the sampling sites and highlight the need for targeted monitoring and control in these areas. The application of the model will empower regulators to quickly assess the overall situation of large-scale heavy metal pollution and provide scientific program and data support for continuous large-scale pollution risk monitoring and sustainable risk management.

The Influence of the Soil Profile on the Formation of the Elemental Image of Grapes and Wine of the Cabernet Sauvignon Variety.

The features for assessing the authenticity of wines by region of origin are studied, based on the relationship between the mineral composition of the wine, the grapes, and the soil profile (0 to 160 cm) from the place of growth of Cabernet Sauvignon grapes. Soil, grape, and wine samples were taken from the territories of six vineyards in the Anapa district of Krasnodar Territory, Russia. Using the methods of ICP-OES, thermal, and X-ray phase analysis, the soils were differentiated into three groups, differing in mineralogical and mineral compositions. The soil samples of the first group contained up to 31% quartz, the second group up to 25% quartz and 19% mixed calcite, and the third group up to 32% calcite and 15% quartz. The formation of the elemental image of the grapes was studied, taking into account the total content and mobile forms of metals in the soil. The territorial proximity of the vineyards did not affect the extraction of elements from the soil into the grape berry, and the migration of metals for each territory was selective. According to the values of the biological absorption coefficient, the degree of transition of metals from the soil to a berry was estimated. For K, Ti, Zn, Rb, Cu, and Fe in all berries, the coefficient was higher than 1.00, which means that the berry extracts contained not only mobile-form, but also difficult-to-dissolve metal compounds. The migration of macro-components from the soil to the berry was low, and amounted to 6-7% for Ca, 0.8-3.0% for Na, and 25-70% for Mg of the concentration of their mobile forms. For all territories, the maximum correlation between metal concentrations in grapes and soil was observed for samples from a depth of 0-40 cm. The discriminant model based on concentrations of Rb, Al, K, Sr, Co, Na, Pb, Ca, and Ni showed the formation of clusters in the territories of vineyard cultivation. The developed model allow the problems of identifying wines by region to be solved with high accuracy, using their elemental image.

Degradation of petroleum hydrocarbon contaminants by Rhodococcus erythropolis KB1 synergistic with alfalfa (Medicago sativa L.).

Petroleum hydrocarbons are a stubborn pollutant that is difficult to degrade globally, and plant-microbial degradation is the main way to solve this type of pollutant. In this study, the physiological and ecological responses of alfalfa to petroleum hydrocarbons in different concentrations of petroleum hydrocarbon-contaminated soil with KB1 (Rhodococcus erythropolis) were analyzed and determined by laboratory potting techniques. The growth of alfalfa (CK) and alfalfa with KB1 (JZ) in different concentrations of petroleum hydrocarbons contaminated soil was compared and analyzed. The results of the CK group showed that petroleum hydrocarbons could significantly affect the activity of alfalfa antioxidant enzyme system, inhibit the development of alfalfa roots and the normal growth of plants, especially in the high-concentration group. KB1 strain had the ability to produce IAA, form biofilm, fix nitrogen, produce betaine and ACC deaminase, and the addition of KB1 could improve the growth traits of alfalfa in the soil contaminated with different concentrations of petroleum hydrocarbons, the content of soluble sugars in roots, and the stress resistance and antioxidant enzyme activities of alfalfa. In addition, the degradation kinetics of the strain showed that the degradation rate of petroleum could reach 75.2% after soaking with KB1. Furthermore, KB1 can efficiently degrade petroleum hydrocarbons in advance and significantly alleviate the damage of high concentration of petroleum hydrocarbons to plant roots. The results showed that KB1 strains and alfalfa plants could effectively enhance the degradation of petroleum hydrocarbons, which provided new ideas for improving bioremediation strategies.

Can the concentration of elements in wild-growing mushrooms be deduced from the taxonomic rank?

The mineral composition of wild-growing mushroom species is influenced by various environmental factors, particularly the chemical properties of the soil/substrate. We hypothesised that element uptake might also correlate with taxonomic classification, potentially allowing us to predict contamination levels based on mushrooms within the same taxonomic rank. This study compared the mineral composition (Ag, As, Ba, Ca, Cd, Co, Cu, Fe, Hg, K, Mg, Mn, Mo, Na, Ni, Pb, Se, and Zn) of 16 saprotrophic mushroom species from 11 genera across 4 families and 2 orders. Among these were 13 edible and 3 inedible mushrooms, all collected from natural, wild stands in a forest in central-western Poland between 2017 and 2020.Phallus impudicus exhibited the highest mean content of Ba (together with Phallus hadriani) (6.63 and 8.61 mg kg−1, respectively), Ca (with Paralepista gilva and Stropharia rugosoannulata) (803, 735 and 768 mg kg−1, respectively), Cd (with Lycoperdon perlatum) (3.59 and 3.12 mg kg−1, respectively), Co (0.635 mg kg−1), and Fe (with P. hadriani and S. rugosoannulata) (476, 427 and 477 mg kg−1, respectively), while Macrolepiota mastoidea showed the highest content of Ag (1.96 mg kg−1), As (with Coprinus comatus) (1.56 and 1.62 mg kg−1, respectively) and Cu (with Macrolepiota procera and Chlorophyllum rhacodes) (192, 175 and 180 mg kg−1, respectively). Comparing the content of the analysed elements in the genera represented by at least two species, a similarity was observed, the same as the mean concentration in soil under these species.Soil characteristics could be a superior factor that overshadows the impact of the mushroom genus on the elements accumulation, obscuring its role as a determinant in this process. The results are not definitive evidence that belonging to a particular taxonomic rank is a prerequisite condition affecting the accumulation of all elements. A closer focus on this issue is needed.

Health Risk Assessment of Heavy Metals in Soils of a City in Guangdong Province Based on Source Oriented and Monte Carlo Models

Taking a city in Guangdong Province as the research area, the concentration and spatial distribution characteristics of heavy metals in the surface soil were studied to clarify the situation of soil heavy metal pollution and priority control factors, providing basic data for the prevention and control of soil heavy metal pollution in the city. The content characteristics of heavy metals in 221 soil samples in the city were analyzed, and the potential health risk assessment and source analysis were carried out through the Monte Carlo model, the potential health risk assessment (HRA) model, and the PMF receptor model. It was found that heavy metals ω(As), ω(Hg), ω(Cd), ω(Pb), ω(Cr), ω(Cu), ω(Ni), and ω(Zn) in the soil of the city were 18.16, 0.43, 1.46, 68.57, 98.34, 64.19, 26.53, and 257.32 mg·kg-1, respectively, with a moderate to high degree of variation. Except for Ni concentration, the soil concentrations of other heavy metal elements exceeded the background values of soil in Guangdong Province to a certain extent, and the concentrations of Cd and Zn exceeded the national secondary standards, resulting in severe heavy metal pollution; the main sources of heavy metals were industrial sources, and natural parent materials, lead battery manufacturing, transportation, artificial cultivation, and pesticide and fertilizer inputs also had an undeniable impact on the accumulation of heavy metals in the soil. Heavy metals in the soil had a certain degree of tolerable carcinogenic health risk for both children and adults, whereas non-carcinogenic risks could be ignored. The potential health risk of children was greater than that of adults, and the main exposure route was through oral intake. The input sources of pesticides and fertilizers and As should be the main controlling factors for the health risks of heavy metals in the city's soil, followed by mixed sources and Cr. There were differences in the spatial distribution characteristics and relative pollution levels of heavy metals, and it is necessary to deepen zoning monitoring and control, strengthen soil pollution prevention and control, and reduce human input of heavy metals in soil.

Mineral composition and heavy metal risk assesment of selected geophagic soils from Tanzania

Geophagy or Pica is the unintentional traditional behavior of eating soil by indigenous people in different countries. practiced in many countries due to nausea among pregnant women and mineral deficiencies without knowing the associated health risks. In this study the mineral composition of geophagic soil and its associated health risk among consumers was determined. Dry soil sticks consumed by women were obtained from open markets in Morogoro, Njombe and Mwanza regions in Tanzania. The elemental concentration of geophagic soil was analyzed using Flame Atomic Absorption spectrophotometer. Health risk assessment methods were used to obtain health information after chronic exposure to geophagic soils. The tests used were Target Hazard Quotients (THQ), Total Target Hazard Quotients (TTHQ) and Cancer Risks (CR). The concentration range of metals in samples obtained from three different regions were 16,335.7–47,773.7 mg/kg for Fe, 46.2–1073.5 mg/kg for Ca, 155.3–514.9 mg/kg for K, 44.5–112.4 mg/kg for Zn, 40.7–95.1 mg/kg for Na, 2.4–66.7 mg/kg for Cu, 109.5–572.6 mg/kg for Mn, 3.8–6.85 mg/kg for Pb, 3.1–93 mg/kg for Ni, 62.7–638.6 mg/kg for Cr and 0.4 mg/kg for Cd. The Provisional Daily Intake (PDI), THQ, TTHQ and CR ranged between 3.0 × 10−3 –34.12 mg/kg/day bw, 0.043–48.75, 34.52–77.36 and 2.55×10−5- 0.23 respectively. The TTHQ>1 was evident for metals in all sampling sites which is indicative of non-carcinogenic health effects. Prolonged exposure to Pb at low concentrations in samples from all the sites can cause pathological effects. The cancer risk values for Pb, Ni, Cr and Cd were <1 in which the consumer is likely not to develop cancer in a life time. Essential minerals – Fe, Ca, Zn, Na, K and toxic metals Pb, Cr, Ni and Cu were detected in all the samples. Cd occurred only in samples from Mwanza region that was below the tolerable daily intake. According to WHO/FAO expert’s joint committee any amount of Pb consumption is not permitted. Given the presence of essential minerals in the geophagic soils which are however accompanied by toxic minerals in some cases which might have carcinogenic effects, prolonged consumption should be discouraged to avoid risks of serious adverse effects to the health of the general population.

Patterns and determinants of calcium concentrations in forest litter and different soil horizons in warm-temperate China

Calcium is an essential nutrition for the integrity and structure of plant cells, and is generally neglected because of its high abundance in temperate forest soil. To date, little is known about the changes in soil Ca and the main natural drivers in the conserved forests. Here, the concentrations of Ca in forest litter and different soil horizons (0–10, 10–20, 20–30, and 30–50 cm) from 234 forest plots were measured. Spatial variations in litter and soil Ca concentrations beneath different forest types were determined, and a structural equation model (SEM) was constructed to evaluate the causal pathways of the biotic and abiotic drivers. The results showed that litter Ca concentration beneath broadleaved forests and mixed broadleaf-conifer forests (22.62 and 19.76 mg/g, respectively) were significantly greater than that beneath the coniferous forest (15.35 mg/g). The Ca concentrations in the soil significantly increased with latitude (soil depth < 30 cm) and longitude. However, litter and soil Ca concentrations significantly declined with elevation. The basal area of the forest and soil C/N were the dominant factors regulating the concentration of Ca in litter and soil profiles, respectively. The SEM highlighted the important effects of Ca concentration in deep soil (soil depth > 20 cm) on litter Ca concentration. The basal area and soil C/N had negative and positive direct effects on Ca concentration in topsoil (soil depth < 20 cm), respectively. The precipitation and temperature in the growing season had indirect effects by affecting the soil C/N and basal area. These results collectively suggest that different forest types influence the redistribution of Ca belowground, and the process is mainly mediated by the basal area and soil C/N. The afforestation in the study area with admixture of conifers and broadleaved trees is a desirable management for the improvement of forest productivity and soil fertility.

Combined application of arbuscular mycorrhizal fungi and selenium fertilizer increased wheat biomass under cadmium stress and shapes rhizosphere soil microbial communities

BackgroundSelenium (Se) fertilizer and arbuscular mycorrhizal fungi (AMF) are known to modulate cadmium (Cd) toxicity in plants. However, the effects of their co-application on wheat growth and soil microbial communities in Cd-contaminated soil are unclear.ResultsA pot experiment inoculation with two types of AMF and the application of Se fertilizer under Cd stress in wheat showed that inoculation AMF alone or combined with Se fertilizer significantly increased wheat biomass. Se and AMF alone or in combination significantly reduced available Cd concentration in wheat and soil, especially in the Se combined with Ri treatment. High throughput sequencing of soil samples indicated that Se and AMF application had stronger influence on bacterial community compared to fungal community and the bacterial network seemed to have more complex interconnections than the fungal network, and finally shaped the formation of specific microflora to affect Cd availability.ConclusionThese results indicate that the application of Se and AMF, particularly in combination, could successfully decrease soil Cd availability and relieve the harm of Cd in wheat by modifying rhizosphere soil microbial communities.

Elevated CO2 exacerbates the risk of methylmercury exposure in consuming aquatic products: Evidence from a complex paddy wetland ecosystem

Elevated CO2 levels and methylmercury (MeHg) pollution are important environmental issues faced across the globe. However, the impact of elevated CO2 on MeHg production and its biological utilization remains to be fully understood, particularly in realistic complex systems with biotic interactions. Here, a complete paddy wetland microcosm, namely, the rice-fish-snail co-culture system, was constructed to investigate the impacts of elevated CO2 (600 ppm) on MeHg formation, bioaccumulation, and possible health risks, in multiple environmental and biological media. The results revealed that elevated CO2 significantly increased MeHg concentrations in the overlying water, periphyton, snails and fish, by 135.5%, 66.9%, 45.5%, and 52.1%, respectively. A high MeHg concentration in periphyton, the main diet of snails and fish, was the key factor influencing the enhanced MeHg in aquatic products. Furthermore, elevated CO2 alleviated the carbon limitation in the overlying water and proliferated green algae, with subsequent changes in physico-chemical properties and nutrient concentrations in the overlying water. More algal-derived organic matter promoted an enriched abundance of Archaea-hgcA and Deltaproteobacteria-hgcA genes. This consequently increased the MeHg in the overlying water and food chain. However, MeHg concentrations in rice and soil did not increase under elevated CO2, nor did hgcA gene abundance in soil. The results reveal that elevated CO2 exacerbated the risk of MeHg intake from aquatic products in paddy wetland, indicating an intensified MeHg threat under future elevated CO2 levels.

Review of soil environment quality in India near coal mining regions: current and future predictions.

Production and utilization of coal are one of the primary routes of accumulation of Toxic Elements (TEs) in the soil. The exploration of trends in the accumulation of TEs is essential to establishing a soil pollution strategy, implementing cost-effective remediation, and early warnings of ecological risks. This study provides a comprehensive review of soil concentrations and future accumulation trends of various TEs (Cr, Ni, Pb, Co, Cu, Cd, Zn, Fe, Mn, and As) in Indian coal mines. The findings revealed that average concentrations of Cr, Mn, Ni, Cu, Zn, Pb, and Co surpass India's natural background soil levels by factors of 2, 4.05, 5.32, 1.77, 9.6, and 6.15, respectively. Geo-accumulation index values revealed that 27.3%, 14.3%, and 7.7% of coal mines are heavily polluted by Ni, Co, and Cu, respectively. Also, the Potential Ecological Risk Index indicates that Cd and Ni are primary contaminants in coal mines. Besides, the health risk assessment reveals oral ingestion as the main exposure route for soil TMs. Children exhibit a higher hazard index than adults, with Pb and Cr being major contributors to their non-carcinogenic risk. In addition, carcinogenic risks exist for females and children, with Cr and Cu as primary contributors. Multivariate statistical analysis revealed that TEs (except Cd) accumulated in the soil from anthropogenic sources. The assessment of future accumulation trends in soil TE concentrations reveals dynamic increases that significantly impact both the ecology and humans at elevated levels. This study signifies a substantial improvement in soil quality and risk management in mining regions.