A large and overlooked Cd source in karst areas: The migration and origin of Cd during soil formation and erosion

Pollution area identification, receptor model-oriented sources and probabilistic health hazards to prioritize control measures for heavy metal management in soil

Identifying the primary source of heavy metals (HMs) pollution and the key pollutants is crucial for safeguarding eco-health and managing risks in industrial vicinity. For this purpose, this investigation was carried out to investigate the pollution area identification with soil static environmental capacity (QI), receptor model-oriented critical sources, and Monte Carlo simulation (MCS) based probabilistic environmental and human health hazards associated with HMs in agricultural soils of Narayanganj, Bangladesh. The average concentration of Cr, Ni, Cu, Cd, Pb, Co, Zn, and Mn were 98.67, 63.41, 37.39, 1.28, 23.93, 14.48, 125.08, and 467.45 mg/kg, respectively. The geoaccumulation index identified Cd as the dominant metal, indicating heavy to extreme contamination in soils. The QI revealed that over 99% of the areas were polluted for Ni and Cd with less uncertain regions whereas Cr showed a significant portion of areas with uncertain pollution status. The positive matrix factorization (PMF) model identified three major sources: agricultural (29%), vehicular emissions (25%), and industrial (46%). The probabilistic assessment of health hazards indicated that both carcinogenic and non-carcinogenic risks for adult male, adult female, and children were deemed unacceptable. Moreover, children faced a higher health hazard compared to adults. For adult male, adult female, and children, industrial operations contributed 48.4%, 42.7%, and 71.2% of the carcinogenic risks, respectively and these risks were associated with Ni and Cr as the main pollutants of concern. The study emphasizes valuable scientific insights for environmental managers to tackle soil pollution from HMs by effectively managing anthropogenic sources. It could aid in devising strategies for environmental remediation engineering and refining industry standards.

Combining chemical analysis and toxicological methods to access the ecological risk of complex contamination in Daye Lake

As one of the nine primary non-ferrous metal smelting bases in China, Daye Lake basin was polluted due to diverse human activities. But so far the pollution status and related ecological risks of this region have not been detailly investigated. In current study, pollutants including heavy metals, polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) in eight sediment samples from Daye Lake were quantified. 18S rRNA gene sequencing was employed to profile the nematode community structure within these sediments. Model organism Caenorhabditis elegans (C. elegans) were further applied for a comprehensive ecological risk assessment of Daye Lake. Notably, Cadmium (Cd) was identified as a key driver of ecological risk, reaching an index of 1287.35. At sample point S4, OCPs particularly p,p'-DDT, displayed an extreme ecological risk with a value of 23.19. Cephalobidae and Mononchida showed strong sensitivity to pollutant levels, reinforcing their suitability as robust bioindicators. The composite pollutants in sampled sediments caused oxidative stress in C. elegans, with gene Vit-2 and Mtl-1 as sensitive biomarkers. By employing the multiple analysis methods, our data can offer valuable contributions to environmental monitoring and health risk assessment for composite polluted areas.

Study on Plant-blanket to reduce heavy metal migration caused by precipitation and to improve the soil environment of pyritic tailings

The increasing demand for mineral resources due to industrial development has led to significant tailings pollution during the mineral extraction process. In the southwestern region of China, a large amount of pyritic tailings containing pyrite cinder easily leaches heavy metals and other pollutants when exposed to precipitation, resulting in widespread soil contamination. Effective remediation methods are urgently needed to address this issue. This study utilized naturally occurring Plant-blanket formed by the symbiosis of moss and herbaceous plants on pyritic tailings as restoration material. Through leaching experiments and staining tracer techniques, the study investigated the ability of Plant-blanket to reduce the migration of heavy metals from pyrite cinder to soil under the influence of precipitation and its role in improving the soil environment. The results showed that within 12 h, the Plant-blanket could absorb water equivalent to 206.9 % of its own weight and had good water retention ability. It reduced the stained area ratio of soil horizontal and vertical profiles after precipitation leaching by a maximum of 76.08 % and 46.41 %, respectively, and improved the pH, cation exchange capacity (CEC), bulk density, and water content of soil at different depths. In addition, after being covered by Plant-blanket, the migration of Cd and Cu was reduced by a maximum of 44.35 % and 55.77 % respectively, and it increased the diversity and abundance of bacterial communities, promoting the recovery of soil microbial ecological functions. These findings indicate that Plant-blanket can regulate water and improve soil environment, and has certain control ability on the migration of Cd and Cu produced by pyritic tailings. Meanwhile, Plant-blanket plays an important role in improving the soil environment in mining areas and promoting ecosystem restoration, providing valuable reference for further exploration of ecological restoration of tailings.

Grassland degradation affected vegetation carbon density but not soil carbon density

BACKGROUND

With the profound changes in the global climate, the issue of grassland degradation is becoming increasingly prominent. Grassland degradation poses a severe threat to the carbon cycle and carbon storage within grassland ecosystems. Additionally, it will adversely affect the sustainability of food production. The grassland ecosystem in the northwest region of Liaoning Province, China, is particularly vulnerable due to factors such as erosion from the northern Horqin Sandy Land, persistent arid climate, and issues related to overgrazing and mismanagement of grassland. The degradation issue is especially pronounced in this ecological environment. However, previous research on the carbon density of degraded grasslands in Northeast China has predominantly focused on Inner Mongolia, neglecting the impact on the grasslands in the northwest of Liaoning Province. Therefore, this experiment aims to assess the influence of grassland degradation intensity on the vegetation and soil carbon density in the northwest of Liaoning Province. The objective is to investigate the changes in grassland vegetation and soil carbon density resulting from different degrees of grassland degradation.

METHODOLOGY

This study focuses on the carbon density of grasslands at different degrees of degradation in the northwest of Liaoning Province, exploring the variations in vegetation and soil carbon density under different levels of degradation. This experiment employed field sampling techniques to establish 100 × 100 m plots in grasslands exhibiting varying degrees of degradation. Six replications of 100 × 100 m plots per degradation intensity were sampled. Vegetation and soil samples were collected for analysis of carbon density.

RESULTS

The results indicate that in the context of grassland degradation, there is a significant reduction in vegetation carbon density. Furthermore, it was found that root carbon density is the primary contributor to vegetation carbon density. In comparison to mildly degraded grasslands, moderately and severely degraded grasslands experience a reduction in vegetation carbon density by 25.6% and 52.6%, respectively. However, with regard to the impact of grassland degradation on soil carbon density, it was observed that while grassland degradation leads to a slight decrease in soil carbon density, there is no significant change in soil carbon density in the short term under the influence of grassland degradation.

CONCLUSIONS

Therefore, grassland degradation has exerted a negative impact on aboveground vegetation carbon density, reducing the carbon storage of above-ground vegetation in grasslands. However, there was no significant effect on grassland soil carbon density.

Comparing the Effects of Lime Soil and Yellow Soil on Cadmium Accumulation in Rice during Grain-Filling and Maturation Periods

The karst area has become a high-risk area for Cadmium (Cd) exposure. Interestingly, the high levels of Cd in soils do not result in an excessive bioaccumulation of Cd in rice. Carbonate rock dissolution ions (CRIs) could limit the accumulation and translocation of Cd in rice. CRIs can become a major bottleneck in the remediation and management of farmlands in karst areas. However, there is limited research on the effects of CRIs in soils on Cd accumulation in rice. The karst area of lime soil (LS) and the non-karst areas of yellow soil (YS) were collected, and an external Cd was added to conduct rice cultivation experiments. Cd and CRIs (Ca2+, Mg2+, CO32-/HCO3-, and OH-) in the rice-soil system were investigated from the grain-filling to maturity periods. The results showed that CRIs of LS were significantly higher than that of YS in different treatments. CRIs of LS were 2.05 mg·kg-1 for Ca2+, 0.90 mg·kg-1 for Mg2+, and 42.29 mg·kg-1 for CO32- in LS. CRIs could influence DTPA Cd, resulting in DTPA Cd of LS being lower than that of YS. DTPA Cd of YS was one to three times larger than that of YS. Cd content in different parts of rice in YS was higher than that of LS. Cd in rice grains of YS was one to six times larger than that of LS. The uptake of Cd from the soil during Filling III was critical in determining rice Cd accumulation. CRIs in the soil could affect Cd accumulation in rice. Ca2+ and Mg2+ had significant negative effects on Cd accumulation of rice at maturity and filling, respectively. CO32-/HCO3- and OH- had significant negative effects on DTPA Cd in soil.

Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area

Mining activities have resulted in a substantial accumulation of cadmium (Cd) in agricultural soils, particularly in southern China. Long-term Cd exposure can cause plant growth inhibition and various diseases. Rapid identification of the extent of soil Cd pollution and its driving factors are essential for soil management and risk assessment. However, traditional geostatistical methods are difficult to simulate the complex nonlinear relationships between soil Cd and potential features. In this study, sequential extraction and hotspot analyses indicated that Cd accumulation increased significantly near mining sites and exhibited high mobility. The concentration of Cd was estimated using three machine learning models based on 3169 topsoil samples, seven quantitative variables (soil pH, Fe, Ca, Mn, TOC, Al/Si and ba value) and three quantitative variables (soil parent rock, terrain and soil type). The random forest model achieved marginally better performance than the other models, with an R2 of 0.78. Importance analysis revealed that soil pH and Ca and Mn contents were the most significant factors affecting Cd accumulation and migration. Conversely, due to the essence of controlling Cd migration being soil property, soil type, terrain, and soil parent materials had little impact on the spatial distribution of soil Cd under the influence of mining activities. Our results provide a better understanding of the geochemical behavior of soil Cd in mining areas, which could be helpful for environmental management departments in controlling the diffusion of Cd pollution and capturing key targets for soil remediation.

Stable isotopic signature of cadmium in tracing the source, fate, and translocation of cadmium in soil: A review

Cadmium (Cd), one of the most severe environmental pollutants in soil, poses a great threat to food safety and human health. Understanding the potential sources, fate, and translocation of Cd in soil-plant systems can provide valuable information on Cd contamination and its environmental impacts. Stable Cd isotopic ratios (δ114/110Cd) can provide "fingerprint" information on the sources and fate of Cd in the soil environment. Here, we review the application of Cd isotopes in soil, including (i) the Cd isotopic signature of soil and anthropogenic sources, (ii) the interactions of Cd with soil constituents and associated Cd isotopic fractionation, and (iii) the translocation of Cd at soil-plant interfaces and inside plant bodies, which aims to provide an in-depth understanding of Cd transport and migration in soil and soil-plant systems. This review would help to improve the understanding and application of Cd isotopic techniques for tracing the potential sources and (bio-)geochemical cycling of Cd in soil environment.

Phthalate esters pollution in the leachate, soil, and water around a landfill near the sea, Iran

This investigation aimed to scrutinize the level of phthalate esters (PEs) in the landfill leachate of a coastal city in the north of the Persian Gulf and the sensitive ecosystem (soil and water) around it. Soil (two depths) and water samples were prepared from 5 stations in wet and dry seasons. The studied landfill leachate contained 114-303 μg/L of phthalates. The highest concentration of phthalates was related to bis (2-ethylhexyl) phthalate (3257 ng/g) in the wet season at surface soil (0-5 cm) in the landfill site, while the lowest one (6 ng/g) belonged to dimethyl phthalate at sub-surface soil at 700 m from the landfill in the dry season. A significant change in the level of Σ6PEs in the dry (303 μg/L) and wet (114 μg/L) seasons (P ≤ 0.05) was observed for water samples. The PE concentrations in wet times were higher in all soil depths than in dry times. With increasing depth, the content of phthalates decreased in all studied environments. A direct relationship was observed between the phthalates concentration and the pH value of leachate/water and soil. The PEs concentration was linked to electrical conductivity (leachate: R2 = 0.65, P < 0.01 and surface soil: R2 = 0.77, P < 0.05) and the soil organic content. The ecological risk of di-n-butyl phthalate, benzyl butyl phthalate, bis (2-ethylhexyl) phthalate, and di-n-octyl phthalate in the wet season was greater than one. The results showed that significant levels of phthalate esters are released from landfills to the surrounding environment, which requires adequate measures to maintain the health of the ecosystem and nearby residents.

Geochemical evaluation, ecological and human health risk assessment of potentially toxic elements in urban soil, Southern India

Roadside soil contamination is mostly caused by human-caused pollutant deposition. PTEs are among the many substances that are harmful for both humans and the environment. PTE concentrations in roadside soil in Chennai, southern India, have been determined in this study. To evaluate the seriousness of the threats, more environmental and geochemical indices have been applied. 83 soil samples have been obtained from the study regions and focusing on important roads. Elemental analysis has been analyzed with ED-XRF and sieve-filtered samples focused on PTEs such as arsenic, barium, cobalt, chromium, copper, iron, potassium, nickel, lead, thorium, titanium, zinc, and uranium. Significant metallic variations have been found in soil samples around roads by the investigation. The elements this study examined section ascending in the following sequence: Fe > Ti > Zn > Cr > Pb > Cu > Ni > Th > As > U > K. In the research area, the CD classification denotes high contamination, whereas the CF indices show mild to significant pollution. PLI indicates moderate to high pollution, whereas EF suggests excessive enrichment. Igeo demonstrates a range from uncontaminated to highly contaminated. PERI showed high levels in the northern study region, whereas GUFI shows several hot spots indicating moderate to severe pollution. The Hazard Index (HI) values for all metals were less than one, demonstrating the absence of non-carcinogenic risks for both adults and children. Multivariate data show natural and anthropogenic PTEs in roadside soil. In addition, a soil quality monitoring system is needed to mitigate continual contamination risks.

Evaluation of soil texture classification from orthodox interpolation and machine learning techniques

The current investigation examines the effectiveness of various approaches in predicting the soil texture class (clay, silt, and sand contents) of the Rawalpindi district, Punjab province, Pakistan. The employed techniques included artificial neural networks (ANNs), kriging, co-kriging, and inverse distance weighting (IDW). A total of 44 soil specimens from depths of 10-15 cm were gathered, and then the hydrometer method was adopted to measure their texture. The map of soil grain sets was formulated in the ArcGIS environment, utilizing distinct interpolation approaches. The MATLAB software was used to evaluate soil texture. The gradient fraction, latitude and longitude, elevation, and soil texture fragments of points were proposed to an ANN. Several statistical values, such as correlation coefficient (R), geometric mean error ratios (GMER), and root mean square error (RMSE), were utilized to evaluate the precision of the intended techniques. In assessing grain size and spatial dissemination of clay, silt, and sand, the effectiveness and precision of ANN were superior compared to kriging, co-kriging, and inverse distance weighting. Still, less than a 50% correlation was observed using the ANN. In this examination, the IDW had inferior precision compared to the other approaches. The results demonstrated that the practices produced acceptable results and can be used for future research. Soil texture is among the most central variables that can manipulate agriculture plans. The prepared maps exhibiting the soil texture groups are imperative for crop yield and pastoral scheduling.

WITHDRAWN: Trace metals translocation from soil to plants: Health risk assessment via consumption of vegetables in the urban sprawl of a developing country

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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.

Exposure to arsenic and other potentially toxic elements: health risk assessment and source analysis in the Wuming Basin, Guangxi Province, China

Guangxi, China, is one of the world's largest karst regions where potential toxic elements tend to accumulate, resulting in high soil background values. This study explores the ecological risk, elemental baseline values, and sources of potential toxic elements in karst regions, expanding the research to include 21 common elements. The significance of this research lies in its implications for the management of potential toxic element pollution, the formulation of environmental quality standards, and soil remediation in karst areas. In this study, 12,547 topsoil samples (0-20 cm) were collected in the study area. Pollution assessment and ecological risk evaluation of eight potential toxic elements (Zn, Ni, Cu, Pb, Cd, Hg, Cr, and As) were conducted using the geo-accumulation index method and potential ecological risk index method. Multivariate statistical analysis was applied to analyze the total content of 21 common elements (Zn, Ni, Cu, Pb, P, Cd, Hg, Co, Mn, Cr, V, I, S, As, pH, Se, N, CaO, Corg, Mo, and F). Additionally, the potential sources of 21 soil elements were preliminarily quantitatively analyzed using the principal component analysis-absolute principal component scores-multiple linear regression receptor model. The results showed that (1) Zn, Ni, Cu, Pb, Cd, Cr, V, and As were enriched in the research area and Ca, Cd, Mn, Mo, Hg, As, and Cu might have been influenced by human activities; (2) Cr, Pb, As, and Zn were generally lightly polluted, with Hg having a moderate potential ecological risk level; and (3) Ni and Zn have contributions of 37.99% and 35.07% from geological sources, agricultural fertilization, and pesticides. Mo, V, Cr, Se, Hg, and As exhibit contributions ranging from 39.44 to 59.22% originating from geological backgrounds and human activities. Corg, S, N, and P show contributions of 45.39% to 80.33% from surface vegetation. F, Co, Mn, and Pb have contributions ranging from 31.63 to 47.93% from acidic rocks in the soil parent material, mining activities, and transportation. Cd and CaO derive 31.67% and 40.23%, respectively, from soil parent material and industrial sources. I has 31.94% from geological background and human activities, and 31.95% from soil parent material and atmospheric sources. Cu has 30.56% from geological sources. The study results can serve as a scientific basis for element research in karst areas domestically and internationally.

Field application of hydroxyapatite and humic acid for remediation of metal-contaminated alkaline soil

The quality of soil is essential for ensuring the safety and quality of agricultural products. However, soils contaminated with toxic metals pose a significant threat to agricultural production and human health. Therefore, remediation of contaminated soils is an urgent task, and humic acid (HA) with hydroxyapatite (HAP) materials was applied for this study in contaminated alkaline soils to remediate Cd, Pb, Cu, and Zn. Physiochemical properties, improved BCR sequential extraction, microbial community composition in soils with superoxide dismutase (SOD), peroxidase (POD), and chlorophyll content in plants were determined. Among the studied treatments, application of HAP-HA (2:1) (T7) had the most significant impact on reducing the active forms of toxic metals from soil such as Cd, Pb, Cu, and Zn decreased by 18.59%, 9.12%, 11.83%, and 3.33%, respectively, but HAP and HA had a minor impact on metal accumulation in Juncao. HAP (T2) had a beneficial impact on reducing the TCleaf/root of Cd, Cu, and Zn, whereas HAP-HA (T5) showed the best performance for reducing Cd and Cu in EFleaf/soil. HAP-HA (T5 and T7) showed higher biomass (57.3%) and chlorophyll (17.9%), whereas HAP (T4) showed better performance in POD (25.8%) than T0 in Juncao. The bacterial diversity in soil was increased after applying amendments of various treatments and enhancing metal remediation. The combined application of HAP and HA effectively reduced active toxic metals in alkaline soil. HAP-HA mixtures notably improved soil health, plant growth, and microbial diversity, advocating for their use in remediating contaminated soils.

Fractionation and Characterization of Metallic Elements in Soils in Land Use Systems

Land use has a great impact on soil dynamics. The soils of various land use systems in Central Karakoram have been under immense pressure in the recent past due to certain anthropogenic activities such as land use practices and land use cover changes. These influences have an impact on the spatial distribution of metallic elements (MEs) in the soils of various land uses. Herein, we investigated the occurrence of the MEs, copper (Cu), zinc (Zn), and nickel (Ni), in soils of various land uses such as the permafrost, pasture, forest, and agricultural lands of the Central Karakorum region. The MEs were extracted in exchangeable, adsorbed, organically bound, carbonated, precipitated, and residual forms. The concentrations of MEs showed a significant dependence on the extraction method used, and the extraction trend followed the order of EDTA > HNO3 > KNO3 > NaOH > H2O. Zn showed the highest concentration compared to Ni and Cu in all extractions, whereas the land uses' ME concentration followed the order of agricultural land > permafrost > forest > pasturelands. The highest values of total Zn, Ni, and Cu were 712 ± 01 mg/kg, 656 ± 02 mg/kg, and 163 ± 02 mg/kg, respectively, in agricultural soil. The ME concentration showed significant variations between different land uses, and the highest concentration was noted in agricultural soil. Zn was found to be a dominant ME compared to Ni and Cu. We believe this effort will provide opportunities for scholars to investigate MEs around the globe.

Distribution and transport of contaminants in soil through mining processes and its environmental impact and health hazard assessment: A review of the prospective solutions

Environmental regulations were concerned with support in reaction to the enormous ecological harm caused by mining in the past. Because mining, dumping, and tailings can generate waste and radioactive consequences, society must develop methods for successfully treating mining waste from mine dumps, tailings, and abandoned mines. Strict policies associated with environmental regulations to avoid the possible dangers caused by garbage and radioactivity. Several characteristics, including background contamination from natural sources related to mineral deposits, contamination from industrial activities in three-dimensional subsurface space, a problem with long-term remediation following mine closure, a problem with secondary contaminated areas near mine sites, land use conflicts, and abandoned mines, distinguish it. Reusing and recycling mine waste occasionally results in cost-effective advantages in the mining sector by offsetting natural resource requirements and reducing the volume of garbage materials. These benefits stem from recycling and reusing mining waste, which can lower the amount of garbage that must be managed. This review focuses on realistic strategies for anticipating mining exploration control and attempts to examine those methods in-depth. Management strategies for limiting the environmental impact of mining dumps, stockpiles, and tailings were discussed. The environmental assessment was also mentioned to carry out specific control and take preventive actions.

Effects of agricultural land use on soil nutrients and its variation along altitude gradients in the downstream of the Yarlung Zangbo River Basin, Tibetan Plateau

Agricultural development in alpine ecosystems can cause significant changes in soil nutrients. With large altitude spans, the combined effect of the two is still unclear in existing research. To answer this problem, this study took the downstream of the Yarlung Zangbo River Basin (YZRB) as the study area, and designed a comparative soil sampling scheme along the altitude gradient. We compared soil nutrient characteristics facility agricultural land (FA) and field cultivated land (FC), using grassland (GL), the main source of agriculture expansion, as a reference. A total of 44 sampling areas were designed within an altitude range of 800-3500 m to reveal the effects of agricultural land development along the altitude gradient on soil nutrients. Research found that the FA significantly improved soil nutrient levels, with most nutrient indicators higher than those of FC and GL (P < 0.05), while the above indicators of FC were only slightly higher than GL. Moreover, the effects of agricultural development decreased with soil depth, and mainly occurred within the 0-30 cm soil layer (P < 0.05). With increasing altitude, most of soil nutrients first decreased and then increased and differences in soil nutrients among different land use modes first expanded and then shrank. This may be related to differences in farmland management methods, vegetation coverage, and temperature under different altitude gradient constraints. Especially in middle-altitude areas, the FA not only breaks through the low-temperature limitations of the plateau, but also has the advantage of large-scale development, which is suggested for future agricultural intensification in the plateau.

Potentially toxic metals in irrigation water, soil, and vegetables and their health risks using Monte Carlo models

Food safety has become a serious global concern because of the accumulation of potentially toxic metals (PTMs) in crops cultivated on contaminated agricultural soils. Amongst these toxic elements, arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb) receive worldwide attention because of their ability to cause deleterious health effects. Thus, an assessment of these toxic metals in the soils, irrigation waters, and the most widely consumed vegetables in Nigeria; Spinach (Amaranthushybridus), and Cabbage (Brassica oleracea) was evaluated using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The mean concentration (measured in mg kg-1) of the PTMs in the soils was in the sequence Cr (81.77) > Pb(19.91) > As(13.23) > Cd(3.25), exceeding the WHO recommended values in all cases. This contamination was corroborated by the pollution evaluation indices. The concentrations (measured in mg l-1) of the PTMs in the irrigation water followed a similar pattern i.e. Cr(1.87) > Pb(1.65) > As(0.85) > Cd(0.20). All the PTMs being studied, were found in the vegetables with Cr (5.37 and 5.88) having the highest concentration, followed by Pb (3.57 and 4.33), and As (1.09 and 1.67), while Cd (0.48 and 1.04) had the lowest concentration (all measured in mg kg-1) for cabbage and spinach, respectively. The concentration of the toxic metals was higher in spinach than in cabbage, which may be due to the redistribution of the greater proportion of the metals above the ground tissue, caused by the bioavailability of metals in the aqueous phase. Expectedly, the hazard index (HI),and carcinogenic risk values of spinach were higher than that of cabbage. This implies that spinach poses potentially higher health risks. Similarly, the Monte Carlo simulation results reveal that the 5th percentile, 95th percentile, and 50th percentile of the cumulative probability of cancer risks due to the consumption of these vegetables exceeds the acceptable range of 1.00E-6 and 1.00E-4. Thus, the probable risk of a cancerous effect is high, and necessary remedial actions are recommended.

Exploring the Impact of Salicylic Acid and Farmyard Manure on Soil Rhizospheric Properties and Cadmium Stress Alleviation in Maize (Zea mays L.)

Cadmium (Cd) pollution is a growing environmental problem that negatively impacts plant growth and development, particularly in maize. In this research, the impact of farmyard manure (FYM) and salicylic acid (SA) on rhizospheric characteristics and the reduction of Cd stress in maize was examined at Government College (GC) University, Lahore, in 2022. The experiment was arranged with a randomized design, including three replications of 12 treatments (T1 = Control; T2 = Farmyard manure; T3 = Salicylic Acid; T4 = 100 mg/kg of soil Cd; T5 = 200 mg/kg of soil Cd; T6 = Farmyard manure + Salicylic acid; T7 = FYM + 100 mg/kg soil Cd; T8 = FYM + 200 mg/kg soil Cd; T9 = SA + 100 mg/kg soil Cd; T10 = SA + 200 mg/kg soil Cd; T11 = FYM + SA + 100 mg/kg soil Cd; T12 = FYM + SA + 200 mg/kg soil Cd). Results demonstrated that Cd stress negatively affected the maize plant and soil properties, but the application of SA and FYM was effective to mitigate the Cd stress up to a certain level. A reduction of 41.52%, 39.14%, and 39.94% in root length, length of the leaf, and crop growth rate was noticed, due to the Cd stress at 200 mg/kg soil, but this reduction was reduced to 18.83%, 10.35%, and 12.26%, respectively, when FYM and salicylic acid were applied as a combined application under the same stress level of Cd. The root biomass, leaf surface area, and length were all improved by SA and FYM, which enhanced the plant's capacity to absorb nutrients and improve growth under Cd stress. In conclusion, the use of salicylic acid together with farm manure can be an effective approach to mitigate Cd stress in maize crops.