Heavy metal spatial distribution, source analysis, and ecological risks in the central hilly area of Hainan Island, China: results from a high-density soil survey.

The presence of heavy metals in soil has gained considerable attention due to their potential risks to ecosystems and human health. In this study, a thorough soil investigation was performed in the hilly region of central Hainan, which was formerly regarded as an area with the highest ecological environmental quality. A total of 7094 soil samples were systematically collected with high density over a large area. Simultaneously, a detailed investigation was conducted on the surrounding environment of each sampling point, including environmental factors such as soil, land use and crop types. The soil samples were analysed for heavy metals, pH, organic matter, and other parameters. The soil heavy metal pollution level, ecological risk and health risk were evaluated using the geo-accumulation index and the potential ecological risk index. The findings showed that the average contents of the heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in the soil were 1.68, 0.042, 24.2, 6.49, 0.0319, 7.06, 29.6 and 49.8 mg·kg-1 respectively. Except for Hg, the mean values of the other heavy metals were either lower than or similar to the background values of Hainan. Also, only a few localised areas showed contamination by heavy metals. The primary sources of heavy metals, identified by a positive matrix factorisation model, could be categorised into four types: natural sources related to the soil formation process from acidic intrusive rocks (such as granite); natural sources primarily influenced by atmospheric deposition; anthropogenic sources associated with agricultural activities; and natural sources related to the soil formation process from middle-mafic intrusive rocks and black shales. The correlation analysis and variance analysis findings suggested that the content of heavy metals in the soil was primarily associated with the parent rock. The study area generally had low heavy metal levels and was not significantly polluted. However, agricultural activities still affected the enrichment of heavy metals. Therefore, it is imperative to remain vigilant about the ecological risks linked to soil heavy metals while continuing land development and expanding agricultural activities in the future. These findings indicate that conducting high-density soil surveys can enhance our understanding of regional soil heavy metals and enable reliable recommendations for agricultural planning. Whether in areas with low pollution risk or potential pollution risk, it is recommended that high-density soil surveys be conducted provide scientific guidance for further agricultural development.

Mapping soil trace metal distribution using remote sensing and multivariate analysis.

Trace metal soil contamination poses significant risks to human health and ecosystems, necessitating thorough investigation and management strategies. Researchers have increasingly utilized advanced techniques like remote sensing (RS), geographic information systems (GIS), geostatistical analysis, and multivariate analysis to address this issue. RS tools play a crucial role in collecting spectral data aiding in the analysis of trace metal distribution in soil. Spectroscopy offers an effective understanding of environmental contamination by analyzing trace metal distribution in soil. The spatial distribution of trace metals in soil has been a key focus of these studies, with factors influencing this distribution identified as soil type, pH levels, organic matter content, land use patterns, and concentrations of trace metals. While progress has been made, further research is needed to fully recognize the potential of integrated geospatial imaging spectroscopy and multivariate statistical analysis for assessing trace metal distribution in soils. Future directions include mapping multivariate results in GIS, identifying specific anthropogenic sources, analyzing temporal trends, and exploring alternative multivariate analysis tools. In conclusion, this review highlights the significance of integrated GIS and multivariate analysis in addressing trace metal contamination in soils, advocating for continued research to enhance assessment and management strategies.

Comparative assessment of soil quality dynamics using SQI modelling approach: a study in rice bowl of West Bengal, India.

The study attempted to evaluate the agricultural soil quality using the Soil Quality Index (SQI) model in two Community Development Blocks, Ausgram-II and Memari-II of Purba Bardhaman District. Total 104 soil samples were collected (0-20 cm depth) from each Block to analyse 13 parameters (bulk density, soil porosity, soil aggregate stability, water holding capacity, infiltration rate, available nitrogen, available phosphorous, available potassium, soil pH, soil organic carbon, electrical conductivity, soil respiration and microbial biomass carbon) in this study. The Integrated Quality Index (IQI) was applied using the weighted additive approach and non-linear scoring technique to retain the Minimum Data Set (MDS). Principal Component Analysis (PCA) identified that SAS, BD, available K, pH, available N, and available P were the key contributing parameters to SQI in Ausgram-II. In contrast, WHC, SR, available N, pH, and SAS contributed the most to SQI in Memari-II. Results revealed that Ausgram-II (0.97) is notably higher SQI than Memari-II (0.69). In Ausgram-II, 99.72% of agricultural lands showed very high SQI (Grade I), whereas, in Memari-II, 49.95% of lands exhibited a moderate SQI (Grade III) and 49.90% showed a high SQI (Grade II). Sustainable Yield Index (SYI), Sensitivity Index (SI) and Efficiency Ratio (ER) were used to validate the SQIs. A positive correlation was observed between SQI and paddy ( R2 = 0.82 & 0.72) and potato yield (R2 = 0.71 & 0.78) in Ausgram-II and Memari-II Block, respectively. This study could evaluate the agricultural soil quality and provide insights for decision-making in fertiliser management practices to promote agricultural sustainability.

Comparison of the Effects of LDPE and PBAT Film Residues on Soil Microbial Ecology.

The plastic film is extensively applied with limited recycling, leading to the long-run residue accumulation in soil, which offers a distinctive habitat for microorganisms, and creates a plastisphere. In this study, traditional low-density polyethylene (LDPE) plastic film and biodegradable polybutylene adipate terephthalate (PBAT) plastic film materials were selected to test their effects on soil microbial ecology. Based on high-throughput sequencing, compared to the soil environment, the alpha-diversity of bacterial communities in plastisphere was lower, and the abundance of Actinobacteria increased. Plastic film residues, as bacterial habitats, exhibited greater heterogeneity and harbor unique bacterial communities. The communities were distinguished between plastisphere and soil environment by means of a random-forest (RF) machine-learning model. Prominent distinctions emerged among bacterial functions between soil environment and plastisphere, especially regarding organics degradation. The neutral model and null model indicated that the constitution of bacterial communities was dominated by random processes except in LDPE plastisphere. The bacterial co-occurrence network of the plastisphere exhibited higher complexity and modularity. This study contributes to our comprehending of characteristics of plastisphere bacterial communities in soil environment and the associated ecological risks of plastic film residues accumulation.

Evaluating the efficacy of vermicomposted products in rain-fed wetland rice and predicting potential hazards from metal-contaminated tannery sludge using novel machine learning tactic.

The study assessed the ecotoxicity and bioavailability of potential metals (PMs) from tannery waste sludge, alongside addressing the environmental concerns of overuse of chemical fertilizers, by comparing the impacts of organic vermicomposted tannery waste, chemical fertilizers, and sole application of tannery waste on soil and rice (Oryza sativa L.) plants. The results revealed that T3, which received high-quality vermicomposted tannery waste as an amendment, exhibited superior enzymatic characteristics compared to tannery sludge amended (TWS) treatments (T8, T9). After harvesting, vermicomposted tannery waste treatment (T3) showed a more significant decrease in PMs bioavailability. Accumulation of PMs in rice was minimal across all treatments except T8 and T9, where toxic tannery waste was present, resulting in a high-risk classification (class 5 < 0.01) according to the SAMOE risk assessment. Results from Fuzzy-TOPSIS, ANN, and Sobol sensitivity analyses (SSA) further indicated that elevated concentrations of PMs (Ni, Pb, Cr, Cu) adversely impacted soil-plant health synergy, with T3 showing a minimal risk in comparison to T8 and T9. According to SSA, microbial biomass carbon and acid phosphatase activity were the most sensitive factors affected by PMs concentrations in TWS. The results from the ANN assay revealed that the primary contributing factor of toxicity on the TWS was the exchangeable fraction of Cr. Correlation statistics underscored the significant detrimental effect of PMs' bioavailability on microbial and enzymatic parameters. Overall, the findings suggest that vermicomposting of tannery sludge waste shows potential as a viable organic amendment option in the near future.

Determination of threshold values and heavy metal pollution assessment of soils in an industrial area in Ghana.

Industrial activities have the potential to pollute soils with a wide variety of heavy metals (HMs). In Ghana, however, assessment of HM pollution of soils in industrial areas remains limited. Accordingly, HM soil pollution in one of the industrial areas in Accra, Ghana was assessed. Soil samples were taken and analysed for HMs, including Fe, Zr, Zn, Ti, Sr, Rb, Mn, Pb, Cu, and Co, using X-Ray Fluorescence (XRF). HM geochemical threshold values (GTVs) were determined to establish soil HM pollution levels and identify areas needing remediation. Furthermore, risk assessments were conducted to evaluate the potential ecological and human health risks associated with these metals. The mean concentrations of Fe, Zn, Rb, Sr, Zr, Ti, Mn, Co, Cu, and Pb in the soils were: 27133.83, 147.72, 16.30, 95.95, 307.11, 4663.66, 289.85, 418.54, 44.97, and 112.88 mg/kg, respectively. Generally, the concentrations of HMs decreased with depth, although some lower layers exhibited elevated HM levels. Soil pollution levels were categorized as low for Fe, Rb, Zr, Ti, Mn, Co, and Cu; moderate for Sr and Zn; and considerable for Pb. Notably, the northwestern part of the study area displayed a considerable to very high degree of HM contamination. While HMs in the soils posed low ecological risk, the human health risk assessment indicated potential health effects from Co, particularly in children. The presence of HMs in the soils was noted to originate from both natural geological phenomena and human activities, including industrial operations, agricultural practices, landfill activities, and vehicular emissions.

Spatial variability and source analysis of soil heavy metals: A case study of the key planting area of special agricultural products in Cangxi County, China.

Heavy metal pollution in farmland soil represents a considerable risk to ecosystems and human health, constituting a global concern. Focusing on a key area for the cultivation of special agricultural products in Cangxi County, we collected 228 surface soil samples. We analyzed the concentration, spatial distribution, and pollution levels of six heavy metals (Cr, Cu, Pb, Ni, Zn, and Hg) in the soil. Moreover, we investigated the sources and contribution rates of these heavy metals using Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS) and Positive Matrix Factorization (PMF) models. Our findings indicate that none of the six metals exceeded the pollution thresholds for farmland soils. However, the mean concentrations of Cr and Ni surpassed the background levels of Sichuan Province. A moderate spatial correlation existed between Pb and Ni, attributable to both natural and anthropogenic factors, whereas Zn, Cu, Hg, and Cr displayed a strong spatial correlation, mainly due to natural factors. The spatial patterns of Cr, Cu, Zn, Pb, and Ni were similar, with higher concentrations in the northern and eastern regions and lower concentrations centrally. Hg's spatial distribution differed, exhibiting a broader range of lower values. The single pollution index evaluation showed that Cr and Ni were low pollution, and the other elements were no pollution. The average value of comprehensive pollution index is 0.994, and the degree of pollution is close to light pollution. Predominantly, higher pollution levels in the northern and eastern regions, lower around reservoirs. The PCA/APCS model identified two main pollution sources: agricultural traffic mixed source (65.2%) and natural parent source (17.2%). The PMF model delineated three sources: agricultural activities (32.59%), transportation (30.64%), and natural parent sources (36.77%). Comparatively, the PMF model proved more accurate and reliable, yielding findings more aligned with the study area's actual conditions.

The use of a portable X-ray fluorescence spectrometer for measuring nickel in plants: sample preparation and validation.

X-ray fluorescence is a fast, cost-effective, and eco-friendly method for elemental analyses. Portable X-ray fluorescence spectrometers (pXRF) have proven instrumental in detecting metals across diverse matrices, including plants. However, sample preparation and measurement procedures need to be standardized for each instrument. This study examined sample preparation methods and predictive capabilities for nickel (Ni) concentrations in various plants using pXRF, employing empirical calibration based on inductively coupled plasma optical emission spectroscopy (ICP-OES) Ni data. The evaluation involved 300 plant samples of 14 species with variable of Ni accumulation. Various dwell times (30, 60, 90, 120, 300 s) and sample masses (0.5, 1.0, 1.5, 2.0 g) were tested. Calibration models were developed through empirical and correction factor approaches. The results showed that the use of 1.0 g of sample (0.14 g cm-2) and a dwell time of 60 s for the study conditions were appropriate for detection by pXRF. Ni concentrations determined by ICP-OES were highly correlated (R2 = 0.94) with those measured by the pXRF instrument. Therefore, pXRF can provide reliable detection of Ni in plant samples, avoiding the digestion of samples and reducing the decision-making time in environmental management.

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.

Source identification and driving factor apportionment for soil potentially toxic elements via combining APCS-MLR, UNMIX, PMF and GDM.

The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil.

Mitigating microplastic stress on peanuts: The role of biochar-based synthetic community in the preservation of soil physicochemical properties and microbial diversity.

Tire-derived rubber crumbs (RC), as a new type of microplastics (MPs), harms both the environment and human health. Excessive use of plastic, the decomposition of which generates microplastic particles, in current agricultural practices poses a significant threat to the sustainability of agricultural ecosystems, worldwide food security and human health. In this study, the application of biochar, a carbon-rich material, to soil was explored, especially in the evaluation of synthetic biochar-based community (SynCom) to alleviate RC-MP-induced stress on plant growth and soil physicochemical properties and soil microbial communities in peanuts. The results revealed that RC-MPs significantly reduced peanut shoot dry weight, root vigor, nodule quantity, plant enzyme activity, soil urease and dehydrogenase activity, as well as soil available potassium, and bacterial abundance. Moreover, the study led to the identification highly effective plant growth-promoting rhizobacteria (PGPR) from the peanut rhizosphere, which were then integrated into a SynCom and immobilized within biochar. Application of biochar-based SynCom in RC-MPs contaminated soil significantly increased peanut biomass, root vigor, nodule number, and antioxidant enzyme activity, alongside enhancing soil enzyme activity and rhizosphere bacterial abundance. Interestingly, under high-dose RC-MPs treatment, the relative abundance of rhizosphere bacteria decreased significantly, but their diversity increased significantly and exhibited distinct clustering phenomenon. In summary, the investigated biochar-based SynCom proved to be a potential soil amendment to mitigate the deleterious effects of RC-MPs on peanuts and preserve soil microbial functionality. This presents a promising solution to the challenges posed by contaminated soil, offering new avenues for remediation.

Informal E-waste dismantling activities accelerated the releasing of liquid crystal monomers (LCMs) in Pakistan: Occurrence, distribution, and exposure assessment.

Liquid crystal monomers (LCMs) are emerging contaminants characterized by their persistence, bioaccumulation potential, and toxicity. They have been observed in several environmental matrices associated with electronic waste (e-waste) dismantling activities, particularly in China. However, there is currently no information on the pollution caused by LCMs in other developing countries, such as Pakistan. In this study, we collected soil samples (n = 59) from e-waste dismantling areas with different functions in Pakistan for quantification analysis of 52 target LCMs. Thirty out of 52 LCMs were detected in the soil samples, with the concentrations ranging from 2.14 to 191 ng/g (median: 16.3 ng/g), suggesting widespread contamination by these emerging contaminants. Fluorinated LCMs (median: 10.4 ng/g, range: 1.27-116 ng/g) were frequently detected and their levels were significantly (P < 0.05) higher than those of non-fluorinated LCMs (median: 6.11 ng/g, range: not detected (ND)-76.7 ng/g). The concentrations and profiles of the observed LCMs in the soil samples from the four functional areas varied. The informal dismantling of e-waste poses a potential exposure risk to adults and infants, with median estimated daily intake (EDI, ng/kg bw/day) values of 0.0420 and 0.1013, respectively. Calculation of the hazard quotient (HQ) suggested that some LCMs (e.g., ETFMBC (1.374) and EDFPB (1.257)) may pose potential health risks to occupational workers and their families. Considering the widespread contamination and risks associated with LCMs, we strongly recommend enhancing e-waste management and regulation in Pakistan.

Do Added Microplastics, Native Soil Properties, and Prevailing Climatic Conditions Have Consequences for Carbon and Nitrogen Contents in Soil? A Global Data Synthesis of Pot and Greenhouse Studies.

Microplastics threaten soil ecosystems, strongly influencing carbon (C) and nitrogen (N) contents. Interactions between microplastic properties and climatic and edaphic factors are poorly understood. We conducted a meta-analysis to assess the interactive effects of microplastic properties (type, shape, size, and content), native soil properties (texture, pH, and dissolved organic carbon (DOC)) and climatic factors (precipitation and temperature) on C and N contents in soil. We found that low-density polyethylene reduced total nitrogen (TN) content, whereas biodegradable polylactic acid led to a decrease in soil organic carbon (SOC). Microplastic fragments especially depleted TN, reducing aggregate stability, increasing N-mineralization and leaching, and consequently increasing the soil C/N ratio. Microplastic size affected outcomes; those <200 µm reduced both TN and SOC contents. Mineralization-induced nutrient losses were greatest at microplastic contents between 1 and 2.5% of soil weight. Sandy soils suffered the highest microplastic contamination-induced nutrient depletion. Alkaline soils showed the greatest SOC depletion, suggesting high SOC degradability. In low-DOC soils, microplastic contamination caused 2-fold greater TN depletion than in soils with high DOC. Sites with high precipitation and temperature had greatest decrease in TN and SOC contents. In conclusion, there are complex interactions determining microplastic impacts on soil health. Microplastic contamination always risks soil C and N depletion, but the severity depends on microplastic characteristics, native soil properties, and climatic conditions, with potential exacerbation by greenhouse emission-induced climate change.

Hazard estimation in urban home garden soils in an industrial area using microarthropods, soil properties and GIS modelling: an integrated approach.

The use of soil microarthropods as indicators of soil pollution in home gardens of an industrial area has been covered in this study. Soil samples were collected from 25 home gardens in three zones in Eloor during summer and North East monsoon from 2014 to 2018, for the study of soil microarthropods, soil properties, soil nutrients, and trace elements. The relationships among QBS-ar, microarthropod abundance, soil properties, and soil nutrients, were used to estimate the pollution hazard of the industrial area. The microarthropods present in the study area were Coleoptera, Hymenoptera, Diplopoda, and Araneae. A prominent study area feature was the absence of Collembola and Acari. The QBS-ar index score in these regions showed that the home gardens located adjacent to the industrial area showed low soil quality, with soil quality class values ranging from 1 to 2 throughout the study period. Discriminant analysis of soil nutrients with soil properties and microarthropod abundance showed that in Zone 1 and Zone 2, the data in 2018 was very well discriminated compared to other years. The hazard assessment in the Eloor region showed various levels of hazard zonation: Zone 1 with high-hazard and medium-hazard areas, Zone 2 with medium-hazard areas, and Zone 3 with low- and medium-hazard areas. The study is one of the first kinds that have used QBS-ar scores and soil properties along with soil nutrients and trace elements for estimating the level of hazard in home garden agroecosystems and thus points to an easy, simple, and practical approach in the monitoring and management of soil ecosystems.

Multivariate analysis applied to X-ray fluorescence to assess soil contamination pathways: case studies of mass magnetic susceptibility in soils near abandoned coal and W/Sn mines.

Determining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.

Manganese exposure from spring and well waters in the Shenandoah Valley: interplay of aquifer lithology, soil composition, and redox conditions.

Manganese (Mn) is of particular concern in groundwater, as low-level chronic exposure to aqueous Mn concentrations in drinking water can result in a variety of health and neurodevelopmental effects. Much of the global population relies on drinking water sourced from karst aquifers. Thus, we seek to assess the relative risk of Mn contamination in karst by investigating the Shenandoah Valley, VA region, as it is underlain by both karst and non-karst aquifers and much of the population relies on water wells and spring water. Water and soil samples were collected throughout the Shenandoah Valley, to supplement pre-existing well water and spring data from the National Water Information System and the Virginia Household Water Quality Program, totaling 1815 wells and 119 springs. Soils were analyzed using X-ray fluorescence and Mn K-Edge X-ray absorption near-edge structure spectroscopy. Factors such as soil type, soil geochemistry, and aquifer lithology were linked with each location to determine if correlations exist with aqueous Mn concentrations. Analyzing the distribution of Mn in drinking water sources suggests that water wells and springs within karst aquifers are preferable with respect to chronic Mn exposure, with < 4.9% of wells and springs in dolostone and limestone aquifers exceeding 100 ppb Mn, while sandstone and shale aquifers have a heightened risk, with > 20% of wells exceeding 100 ppb Mn. The geochemistry of associated soils and spatial relationships to various hydrologic and geologic features indicates that water interactions with aquifer lithology and soils contribute to aqueous Mn concentrations. Relationships between aqueous Mn in spring waters and Mn in soils indicate that increasing aqueous Mn is correlated with decreasing soil Mn(IV). These results point to redox conditions exerting a dominant control on Mn in this region.

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

BACKGROUND: Selenium (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. RESULTS: A 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. CONCLUSION: These 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.

Concentration of heavy metals in soil and leaves of Conocarpus Erectus Tree: A Biomonitoring Study, Ahvaz, Iran.

Heavy metals biomonitoring was performed using the Conocarpus erectus tree in Ahvaz city. Composite leaf and soil samples were collected from 23 selected stations. The concentrations of heavy metals (Pb, Zn, Cd, Cu, Fe and Mn) in leaf and soil samples, and bioavailability of metals in soil samples were determined. Examination of soil physicochemical parameters proved neutral to slightly alkaline nature, and low organic matter content in the soil samples. The mean concentration of heavy metals in soil was: Fe > Mn > Zn > Pb > Cu. Ecological risk assessment of heavy metals was in the range of safe to low risk (RI < 150). Although the concentration of metals in the more polluted areas was higher in both leaf and soil samples, there was no significant relationship between the concentrations of metals in the leaf and soil samples. This relationship is even lower between the bioavailable component of metals in the soil and the concentration of metals in the leaves. Transfer factor values based on total contents of metals in soil samples indicated that Conocarpus erectus is mostly contaminated with Zn and Cu. The results of Accumulation factor of plant revealed that Pb, Zn, and Fe were mostly enriched in the plant by anthropogenic activities. MAI values in heavy and light traffic, and industrial areas were 11.88, 8.01 and 8.15, respectively. In general, it is evident that the Conocarpus erectus leaves accumulate heavy metals in polluted areas, so it can be used as a bioindicator of air pollution with heavy metals in regions with similar conditions.

Pollution characteristics and quantitative source apportionment of heavy metals within a zinc smelting site by GIS-based PMF and APCS-MLR models.

The abandoned smelters present a substantial pollution threat to the nearby soil and groundwater. In this study, 63 surface soil samples were collected from a zinc smelter to quantitatively describe the pollution characteristics, ecological risks, and source apportionment of heavy metal(loid)s (HMs). The results revealed that the average contents of Zn, Cd, Pb, As, and Hg were 0.4, 12.2, 3.3, 5.3, and 12.7 times higher than the risk screening values of the construction sites, respectively. Notably, the smelter was accumulated heavily with Cd and Hg, and the contribution of Cd (0.38) and Hg (0.53) to ecological risk was 91.58%. ZZ3 and ZZ7 were the most polluted workshops, accounting for 25.7% and 35.0% of the pollution load and ecological risk, respectively. The influence of soil parent materials on pollution was minor compared to various workshops within the smelter. Combined with PMF, APCS-MLR and GIS analysis, four sources of HMs were identified: P1(25.5%) and A3(18.4%) were atmospheric deposition from the electric defogging workshop and surface runoff from the smelter; P2(32.7%) and A2(20.9%) were surface runoff of As-Pb foul acid; P3(14.5%) and A4(49.8%) were atmospheric deposition from the leach slag drying workshop; P4(27.3%) and A1(10.8%) were the smelting process of zinc products. This paper described the distribution characteristics and specific sources of HMs in different process workshops, providing a new perspective for the precise remediation of the smelter by determining the priority control factors.