Quantitative source apportionment of heavy metal(loid)s in the agricultural soils of an industrializing region and associated model uncertainty

Ignoring the food route underestimated human health risk from potentially toxic elements in agricultural environments of Ziyang, Shaanxi, China

Staple food is a crucial exposure route for the human intake of potentially toxic elements (PTEs), but it has been neglected in previous human health risk (HHR) studies. Lack of attention to this issue will lead to an underestimation of HHR caused by PTEs. This study establishes a comprehensive regional identification method for health risk assessment (HRA), namely, soil-maize health risk assessment (SMHRA) and applies it to Ziyang, Shaanxi, which is a typical agricultural county. SMHRA considered the exposure pathway of staple food and utilized Monte Carlo simulation to enhance the accuracy of HRA for PTEs. Results indicated the PTE spatial heterogeneity in a soil-maize system. Introducing staple food exposure pathway would increase HHR values and probabilities 1.57-2.80 and 1.53-5.63 times than that when food route was not considered. Overall, the HHR caused by a single PTE was low, which relatively safe. The introduction of food pathway contributed to accurate estimate the HHR of As and Ni, and the risk probabilities ranged from 0.04% to 12.46%. Few areas had high levels of Ni, which pose health risks: approximately 1.8% for children and higher than 0.5% for adults. Both As and Ni had the highest contribution to HHR among all PTEs, with 33.84%-41.56% TNCR caused by As, and 54.73%-56.90% TCR created by Ni, respectively. For human health risk routes, the staple food exhibited the highest contribution to HHR among all exposure routes, with TNCR of 36.15%-56.73% and the TCR of 44.96%-64.28%. Our research imply that dietary intake of PETs must be considered in the human health risk assessment in agricultural environment, which offers the foundation for subsequent environmental risk prevention and control.

Characterization and source apportionment of heavy metal pollution in soil around red mud disposal sites using absolute principal component scores-multiple linear regression and positive matrix factorization models

In recent years, industrial waste and agrochemicals have reduced soil fertility and productivity, significantly impacting food security and ecosystems. In China, areas near red mud deposits from the aluminum industry show severe heavy metal contamination. This study examines agricultural soil near a red mud site in Shanxi Province, analyzing Cd, Cr, Hg, Ni, Pb, As, Cu, and Zn levels and distribution. Geostatistical methods and GIS are utilized to assess heavy metal pollution using the single factor index, the Nemerow integrated index, and the Hakanson potential ecological risk index. Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) and Positive Matrix Factorization (PMF) models are used for quantitative analysis of pollution sources. Research indicates that the average concentrations of eight heavy metals exceed the natural background values of Shanxi, placing them at a severe pollution level with moderate ecological risk. Specifically, indices for As, Pb, and Cr are 3.79, 3.38, and 3.26, indicating severe pollution; Cd, Cu, and Hg at 2.36, 2.62, and 3.00 suggest moderate pollution; Ni at 1.87 shows mild pollution, while Zn at 0.97 is not polluted. Hg presents the highest ecological risk with a coefficient of 120.00, followed by Cd (70.69) and As (37.92). Spatial analysis shows significant correlations among Pb, Zn, Cu, and Ni, while Cr, Cd, Hg, and As show greater variability and weaker correlations. Both models identify five main sources: industrial activities, agricultural fertilizers, red mud leachate, energy combustion, and natural geological backgrounds, with respective contribution rates in the APCS-MLR model at 27.7%, 24.6%, 18.1%, 15.2%, and 14.4%, and in the PMF model at 29.2%, 21.5%, 16.9%, 16.7%, and 15.7%. This study offers a scientific basis for controlling soil pollution in the region, filling a literature gap.

Significance of humic matters-soil mineral interactions for environmental remediation: A review

Industrial and human activities have led to serious soil and water pollution. Traditional remediation techniques have problems such as high treatment costs and the tendency to cause secondary pollution. Soil minerals and humic matters are common active components in soils. Both play vital roles and are frequently bound together to form humic matters-mineral complexes, which are considered sustainable and eco-friendly materials for environmental remediation and improvement. However, due to the complexity of humic matters-mineral interactions and the wide variation in the removal of different pollutants, there is a lack of research in this area. This paper provides a comprehensive introduction and summary of the interaction mechanisms between humic matters and typical soil minerals such as layered phosphate minerals and iron oxides, and their applications in environmental remediation, especially for the treatment of heavy metals (lead, mercury, chromium and cadmium) and organic pollutants (antibiotics, pesticides and polycyclic aromatic hydrocarbons) in water and soil. The humic matters-mineral complex can reduce the toxicity and migration rate of pollutants through adsorption, electrostatic attraction, together with H-bonding and hydrophobic interactions, reducing the harm of these pollutants to soil and water environments and realizing the efficient remediation of soil and water environments. And compared with the traditional treatment technology, this method is more green and environmental protection, and the treatment cost is greatly reduced. Finally, the deficiencies of using humic matters-mineral complex to achieve soil and water remediation were summarized and also proposed directions for future endeavors as well as concrete measures.

Source-risk and uncertainty assessment of trace metals in surface sediments of a human-dominated seaward catchment in eastern China

Current total concentration-based methods for source attribution and risk assessment often overestimate metal risks, thereby impeding the formulation of effective risk management strategies. This study aims to develop a framework for source-specific risk assessment based on metal bioavailability in surface river sediments from a human-dominated seaward catchment in eastern China. Metal bioavailability was quantified using chemical fractionation results, and source apportionment was conducted using the positive matrix factorization (PMF) model. Risk assessment integrated these findings using two indices: the Potential Ecological Risk Index (PERI) and the Mean Probable Effect Concentration Quotient (mPEC-Q), with uncertainty addressed via Monte Carlo simulations. Results indicated that average total concentrations of Cu, Pb, Zn, Cr, Hg, Cd, and As exceeded their respective background levels by 1.63 to 15.00 times. The residual fraction constituted the majority, accounting for 53.84 % to 77.79 % of total concentrations, suggesting significant natural origins. However, source apportionment revealed a predominant contribution from anthropogenic activities, including industrial smelting, agricultural practices, and atmospheric deposition. The contributions were found to vary between 5.35 % and 40.03 % when the total concentration was adjusted to bioavailable content. Total concentration-based PERI/mPEC-Q assessments indicated high/moderate risk levels, decreasing to considerable/low risk levels with bioavailability adjustment. Hg and Cd were identified as priority metals. Further incorporating source appointment parameters into the risk assessment, industrial smelting was identified as the primary contributor, accounting for 66.06 % of total risk by total concentration and 65.63 % by bioavailability. This underscores the role of bioavailability in mitigating risk overestimation. Monte Carlo simulations validated industrial smelting as a major risk contributor. This study emphasizes the importance of considering bioavailability in the source-risk assessment of sediment-metals, crucial for targeted risk management in urbanized catchment areas.

Source Apportionment and Risk Assessment of Potentially Toxic Elements Based on PCA and PMF Model in Black Soil Area of Hailun City, Northeast China

This study assessed the presence of potentially toxic elements (PTEs) in China's northeastern black soil belt, an area with limited prior research. We collected 304 soil samples (0-20 cm) from Gonghe Town, Hailun City, and analyzed the PTE contamination degree using the single-factor pollution index and Nemerow pollution index. The results demonstrated that the mean concentrations of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) were 11.16, 0.11, 65.29, 22.56, 0.03, 27.07, 26.09, and 66.01 mg/kg, respectively. Source apportionment was conducted via correlation analysis, principal component analysis, and positive matrix factorization, identifying four main sources: natural (33.2%), irrigation (29.5%), fuel (23.4%), and fertilizer (13.2%). The ecological risk index indicated a slight ecological risk, while the human health risk showed that non-carcinogenic risks were negligible and carcinogenic risks were acceptable. Our findings emphasize the need to prioritize controlling PTEs from fertilizer, particularly cadmium, and to a lesser extent, irrigation and fuel sources, focusing on As, Pband Hg. This research provides critical insights for policymakers aiming to manage PTE contamination in black soils.

Synchrotron induced X-ray fluorescence spectroscopy reveals heavy metal translocation in sludge amended soil-plant systems: assessment of ecological and health risks

The use of composted sludge from sewage treatment plants as a soil amendment is a common practice of recycling nutrients like organic carbon, nitrogen, and phosphorus. The sewage generated in larger cities of developing countries is often contaminated with various heavy metals (HMs) that ultimately end up in composted sludge. Thus, using such composted sludge is likely to pose ecological and human health risks. Hence, the knowledge of HM translocation in sludge-soil-plant systems is of vital importance. The present study was aimed at investigating the HM translocation in sludge-soil-plant system. The HM translocation was measured using synchrotron radiation-induced x-ray fluorescence spectrometry and atomic absorption spectroscopic techniques. The results indicated high HM mobility (up to 2628.5 mg kg-1) from sludge to spinach plant. The metal accumulation (mg kg-1) ranged in the order-Fe (950.55-2628.5) > Zn (20.11-172.13) > Cu (13.86-136.17) > Mn (2.13-34.67) > Cd (0.11-31.17) > Pb (1.50-30.16) > Co (0.18-9.85) As (0.02-7.80) > Cr (0.01-5.69). This observed accumulation depended on the volume of sewage being treated in the sewage treatment plant (STP) and varied in the order control < (8 MLD Bhagwanpur, STP 1) < (80 MLD Dinapur, STP2) < (140 MLD Dinapur, STP3) hence the HM load coming into STPs. The metal transfer factor, bioconcentration factor, and translocation factor values also correlated with the abundance of Fe, Cu, Pb, Cd, and Zn in spinach root and shoot compartments. The carcinogenic risk for heavy metal carcinogens like As, Cd, Cr, and Pb revealed children being more prone to cancer upon spinach consumption. Hence, it is necessary to assess the heavy metals present in the sludge prior to its application in agricultural fields.

The heterogeneous distribution of heavy metal(loid)s at a smelting site and its potential implication on groundwater

The downward migration of soil heavy metal(loid)s (HMs) at smelting sites poses a significant risk to groundwater. Therefore, it is requisite for pollution control to determine the pollution characteristics of soil HMs and their migration risks to groundwater. 198 soil samples collected from a Pb-Zn smelting site were classified into 6 clusters by self-organizing map (SOM) and K-means clustering. Cd, Zn, As, and Pb were identified as the characteristic contaminants of the site. The driving factors for the heterogeneous distribution of HMs have been validated through the implementation of K-means clustering and multiple-hits calculation. Using ultrafiltration extraction and microscopic analysis, the soil colloids were identified as crucial carriers facilitating the migration of HMs. Specifically, the colloidal fractions of Cd, Zn, and As, Pb in deep soil (3-4 m) accounted for 91 %, 78 %, 88 %, and 82 %, respectively, consistently surpassing those found in topsoil (0-0.5 m). It was primarily attributed to the strong affinity of HMs toward soil colloids (franklinite, PbS, and kaolinite) and dissolved organic matter (humic acids and protein). The research findings highlight the potential risk of colloidal HMs to groundwater contamination, providing valuable insights for the development of targeted management and remediation strategies.

Evaluation of ecological and health risks of trace elements in soils of olive orchards and apportionment of their sources using the APCS-MLR receptor model

İzmir, Turkey's third most populous city, is in an important position in terms of both agriculture and industry. The province, which contributes 9.3% to the country's industrial production, also has an important potential in terms of olive cultivation. However, until now, no research has been undertaken to analyze the content of trace elements (TEs) in the soil of olive orchards in İzmir. This study was carried out to determine the pollution level and ecological risks of TEs in the olive orchards soils of İzmir province, to reveal their potential sources and to evaluate their health risks. Among the TEs, the average content of only Ni (37.9 mg/kg) exceeded the world soil average content (29 mg/kg), while the average content of only Cd (0.176 mg/kg) exceeded the upper continental crust content (0.09 mg/kg). Enrichment factor revealed that there was significant enrichment for Cd in 73.6%, Ni in 11.6% and Cr in 5.4% of olive orchards, respectively, due to polluted irrigation water and agrochemicals. Similarly, ecological risk factor indicated that there were moderate and considerable ecological risks for Cd in 48.8% and 23.3% of olive orchards, respectively. Absolute principal component scores-multiple linear regression (APCS-MLR) model showed that Ni and Cr in the study area are affected by agricultural sources, Al, Co, Cu, Fe, Mn, Pb and Zn originate from lithogenic sources, and Cd originates from mixed sources. Based on health risk evaluation methods, non-carcinogenic and carcinogenic effects would not be expected for residents. This study provides significant knowledge for evaluating soil TE pollution in olive orchards and serves a model for source apportionment and human health risk evaluation of TEs in other agricultural regions.

Source apportionment of soil PTE in a northern industrial county using PMF model: Partitioning strategies and uncertainty analysis

Positive matrix factorization (PMF) has commonly been applied for source apportionment of potentially toxic elements (PTE) in agricultural soil, however, spatial heterogeneity of PTE significantly undermines the accuracy and reliability of PMF results. In this study, a representative industrial-agricultural hub in North China (Xuanhua district, Zhangjiakou City) was selected as the research subject, multiple partition processing (PP) strategies and uncertainty analyses were integrated to advance the PMF modeling and associated algorithm mechanisms were comparatively discussed. Specifically, we adopted three methods to split the research area into several subzones according to industrial density (PP-1), population density (PP-2), and the ecological risk index (PP-3) respectively, to rectify the spatial bias phenomenon of PTE concentrations and to achieve a more interpretable result. Our results indicated that the obvious enrichment of Cd, Pb, and Zn was found in the agricultural soil, with Hg and Cd accounted for 83.49% of the overall potential ecological risk. Combining proper PP with PMF can significantly improve the modelling accuracy. Uncertainty analysis showed that interval ratios of tracer species (Cd, Pb, Hg, and Zn) calculated by PP-3 were consistently lower than that of PP-1 and PP-2, indicating that PP-3 coupled PMF can afford the optimal modeling results. It suggested that natural sources, fertilizers and pesticides, atmosphere deposition, mining, and smelting were recognized as the major contributor for the soil PTE contamination. The contribution of anthropogenic activities, specifically fertilizers and pesticides, and atmosphere deposition, increased by 1.64% and 5.91% compared to PMF results. These findings demonstrate that integration of proper partitioning processing into PMF can effectively improve the accuracy of the model even at the case of soil PTE contamination with high heterogeneity, offering support to subsequently implement directional control strategies.

Homology and heterogeneity of soil trace elements of coal power production bases in arid and semi-arid areas of Northwest China

Coal power activities could cause regional fluctuations of trace elements, but the distribution information of these trace elements in arid and semi-arid areas is insufficient. In this study, the soil trace elements (As, B, Be, Cd, Co, Cr, Cu, Fe, Ga, Ge, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Ti, Tl, and Zn) of Ningdong Coal Power Production Base in China were monitored. Results showed that the concentrations of B, Tl, Mn, Pb, Cr, K, Cu, and Co exceeded background values. The maximum risk index reached 265.66, while the trace elements posed a cancer risk to children. Combining correlation analyses (CA), principal component analysis (PCA), and positive matrix factorization (PMF) techniques, it indicated that trace elements were mainly coming from coal combustion (34.15%), livestock farming (17.44%), traffic emissions (12.42%), and natural factors (35.99%). This study reveals the sources and potential ecological risks of soil trace elements in the Ningdong Coal and Power Production Base. It provides a scientific basis for developing targeted environmental management measures and reducing human health risks.

Pollution sources and risk assessment of potentially toxic elements in soils of multiple land use types in the arid zone of Northwest China based on Monte Carlo simulation

The concentration of potentially toxic elements (PTEs) in soils of different land-use types varies depending on climatic conditions and human. Topsoil samples were collected in Northwest China to investigate PTE pollution and risk in different land uses, and thereby estimate the risk of various pollution sources. The results showed that human activity had an impact on PTE concentrations in the study area across all land use types, with farmland, grassland, woodland, and the gobi at moderate pollution levels and the desert at light pollution levels. Different PTE sources pose different risks depending on the land-use type. Apart from deserts, children are exposed to carcinogenic risk from a variety of sources. A mixed natural and agricultural source was the main source of public health risk in the study area, contributing 38.7% and 39.0% of the non-carcinogenic and 40.7% and 35.5% of the carcinogenic risks, respectively. Monte Carlo simulations showed children were at a higher health risk from PTEs than adult s under all land uses, which ranked in severity as farmland > woodland > grassland > gobi > desert. As and Ni has a higher probability of posing both a non-carcinogenic and a carcinogenic risk to children. Sensitivity analysis showed that the contribution of parameters to the assessment model of PTEs exhibited the following contribution pattern: concentration > average body weight > ingestion rate > other parameters. The PTEs affecting the risk assessment model were not common among different land use types, where the importance distribution pattern of each parameter was basically the same in woodland, grassland, and farmland, and Ni contributed the most to carcinogenic risk. However, Cr contributed the most to the carcinogenic risk in the desert and gobi.

Assessing heavy metal and physiochemical pollution load of Danro River and its management using floating bed remediation

River Danro in Garhwa (India) plays a vital role as a significant source of surface water and a crucial tributary of the North Koel River, ultimately joining the Ganga River Basin. Serving both urban-industrial and rural areas, the region faces challenges, including sand mining near Belchampa Ghat. This study aimed to assess physicochemical and heavy metals pollution at nine sampling locations, utilizing the Overall Index of Pollution (OIP), Nemerow Pollution Index (NPI), and Heavy Metal Pollution Index (HPI). OIP values indicated excellent surface water quality (0.71) in non-monsoon and slight pollution (6.28) in monsoon. NPI ranged from 0.10 to 1.74 in non-monsoon and from 0.22 (clean) to 27.15 (heavily polluted) in monsoon. HPI results suggested groundwater contamination, particularly by lead. Principal component analysis (PCA) and geospatial mapping showed similar outcomes, highlighting the influence of adjacent land use on water quality. Recognizing the significance of the Danro River in sustaining life, livelihoods, and economic growth, the study recommends implementing measures like floating bed remediation and regulatory actions for effective river management. The study acknowledges weaknesses in the current practical assessment methods for water contamination. These weaknesses make it difficult to put plans for cleaning up and controlling contamination into action. Because of this, future research on developing new in-place remediation techniques should focus on creating better ways to measure how effective the cleanup is.

Source identification and exposure risk management for soil arsenic in urban reclamation areas with high background levels: A case study in a coastal reclamation site from the Pearl River Delta, China

Urbanization involving the excavation and reuse of arsenic-bearing geological materials may pose human health risks. We investigated the distribution and sources of soil arsenic at a coastal reclamation site in the Pearl River Delta, China, and proposed risk management strategies. Analysis of 899 soil samples revealed an average of 58.97 mg/kg arsenic, with a maximum of 1450 mg/kg, mainly in fill material obtained from a local island. Integrative analysis combining reclamation history, regional geology, and bedrock mineralogy conclusively identified hydrothermally altered arsenic-bearing sulfide minerals within extensively fractured bedrock as the primary source of arsenic. Physical weathering and anthropogenic rock blasting produced discrete arsenic-rich particles that were directly transported into soils during land reclamation and accumulated to potential hazardous levels. Oral, dermal, and inhalation pathways were identified as primary exposures for future populations. Integrated engineering and institutional controls, coupled with long-term monitoring, were recommended to mitigate risks. The results highlight the importance of identifying specific geogenic and anthropogenic sources that contribute to heavy metal enrichment of soils in reclaimed areas where native bedrock naturally contains elevated level of metals, supporting evidence-based best practices for risk management and future land use.

A study of environmental pollution and risk of heavy metals in the bottom water and sediment of the Chaohu Lake, China

Most of the existing research for heavy metals in water at present is focusing on surface water. However, potential environmental risk of heavy metals in the bottom water of lakes cannot be ignored. In this study, the content, distribution, and speciation of nine heavy metals (As, V, Cr, Co, Ni, Cu, Zn, Cd, and Pb) in the bottom water and sediment of Chaohu Lake were studied. Some pollution assessment methods were used to evaluate the environmental effect of heavy metals. Positive matrix factorization was conducted to investigate the potential sources of heavy metals in sediment. The contents of heavy metals in the bottom water of Chaohu Lake mean that its environmental pollution can be ignored. In sediment, Cd and Zn have showed stronger ecological risk. pH and redox potential are more likely to affect the stability of heavy metals in the bottom water of Chaohu Lake during the dry reason. Industrial sources (16%) are no longer the largest source of heavy metal pollution; traffic sources (33.6%) and agricultural sources (23.4%) have become the main sources of pollution at present. This study can provide some support and suggestions for the treatment of heavy metals in lakes.

Health risk assessment of heavy metals in wild fish and seasonal variation and source identification of heavy metals in sediments: a case study of typical urban river in Xi'an, China

In order to determine the status of heavy metal pollution in river sediments and wild fish in Xi'an, concentrations of heavy metals (Cr, Ni, Cu, Zn, As, and Pb) were collected and analyzed in sediments and wild fish during dry season (October-November 2020) and wet season (June-July 2021). This study aimed to investigate the spatial and temporal variations of heavy metals in urban rivers of Xi'an, China. Their distribution characteristics and sources as well their pollution levels and health risks were assessed. The findings revealed that influenced by human activities, the heavy metal content in sediments (mg·kg-1 dry weight) in wet season was ranked as follows: Cr (73.09) > Zn (63.73) > Pb (40.31) > Ni (31.52) > Cu (24.86) > As (6.83); in the dry season: Zn (94.07) > Cr (69.59) > Cu (34.24) > Ni (33.60) > Pb (32.87) > As (7.60). Moreover, 32 fish samples from six species indicated an average metal content trend (mg·kg-1 wet weight) of Zn (8.70) > Cr (0.57) > Pb (0.28) > Ni (0.27) > Cu (0.24) > As (0.05). The potential ecological risk indices for sediment heavy metal concentrations in both seasons were well below the thresholds, which indicates that the aquatic environment is in safe level. The analysis of the potential ecological risk of sediment heavy metal concentrations indicates that the aquatic environment is safe for the time being. Based on the estimated daily intake (EDI), target risk quotient (THQ), total target risk quotient (TTHQ), cancer risk (CR), total cancer risk (TCR), and the permissible safety limits set by the agencies, the consumption of the fish examined is safe for human health. However, the presence of Cr and As in wild fish should still be a concern for human health, especially for children. The cumulative effect of heavy metals and the bioconcentration factor (BCF) suggest that sediment and heavy metals in fish are closely related, with higher concentrations in fish living in the bottom layer of the water column than in other water layers, and increasing with increasing predator levels. Correlation analysis and PMF modeling identified and determined four comparable categories of potential sources, namely, (1) atmospheric deposition and traffic sources, (2) agricultural sources, (3) industrial sources, and (4) natural sources.

Risk assessment and source identification of soil heavy metals: a case study of farmland soil along a river in the southeast of a mining area in Southwest China

To investigate the heavy metals (HMs) contamination of surface farmland soil along the river in the southeast of a mining area in southwest China and identify the contamination sources, 54 topsoil samples were collected and the concentrations of seven elements (Zn, Ni, Pb, Cu, Hg, Cr, and Co) were determined by inductively coupled plasma optical emission spectrometry (ICP-OES) and atomic fluorescence spectrometry (AFS). The geo-accumulation index ([Formula: see text]) and comprehensive potential ecological risk index ([Formula: see text]) were used for analysis to determine the pollution degree of HMs and the risk level of the study area. Meanwhile, the Positive Matrix Factorization (PMF) model was combined with a variety of statistical methods to determine the sources of HMs. To explore the influence of the river flowing through the mining area on the concentrations of HMs in the farmland soil, 15 water samples were collected and the concentrations of the above seven elements were determined. The results showed that the concentrations of Pb, Cu, and Zn in soil all exceeded the risk screening value, and Pb in soil of some sampling sites exceeded control value of "Agricultural Land Soil Pollution Risk Control Standard".[Formula: see text] showed that Pb was heavily contaminated, while Cu and Zn were moderately contaminated. RI showed that the study area was at moderate risk. PMF and various statistical methods showed that the main source of HMs was the industrial source. In the short term, the river flowing through the mine has no significant influence on the concentration of HMs in the soil. The results provide a reference for the local government to control contamination and identify the sources of HMs.

A novel calibration method for continuous airborne metal measurements: Implications for aerosol source apportionment

Continuous metal monitors have been widely used in environmental monitoring due to the high temporal resolution, high detection limit, and necessity for near real-time source apportionment. However, the reliability of the conventional calibration method, the deviation caused by uncalibrated monitoring data, and the subsequent impact on source identification results are rarely discussed. In this study, a reliable multi-point calibration approach by Primary Standard Aerosol Mass Concentration Calibration System (PAMAS) for the Xact625i Ambient Metals Monitor was developed and applied. The measured data was almost meaningless in the low-concentration range with bias even exceeding 100 % by using the conventional single-point calibration method based on thin-film standards. PAMAS was utilized to generate aerosols with known concentrations of the 20 metal elements including Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Sr, Cd, Sn, Sb, Ba, Tl, Pb, and Bi, in two concentration ranges of 150-1200 ng m-3 and 2.5-30 ng m-3 to validate the Xact625i Monitor. The results showed that the elemental concentrations were underestimated, especially in the low-concentration range, only for Cr, As, and Sr with slopes close to unity (1.00 ± 0.03). After calibration by PAMAS, the slopes of the linear relationships between measured and standard concentrations were all unity for the 19 elements in the high-concentration range, and close to unity for the 15 elements in the low-concentration range, and the accuracy of the remaining elements was also improved. After considering the calibration of aerosol metal data, it was found the number of source factors and their contributions to metals and PM2.5 in Chongming Dongtan, China, based on the PMF model significantly changed. This study highlighted the need of developing reliable calibration methods for online aerosol monitoring instruments and implied that the source apportionment results could be biased without careful data calibration.

Effect of environmental factors on accumulation of trace metals in a typical shale gas exploitation area: A comprehensive investigation by machine learning and geodetector models

Whether a certain relationship is exist between shale gas exploitation and accumulation of trace metals in soil is a controversial issue in recent years. To date, few study clearly reveal the intrinsic contributions of natural and anthropogenic factors to accumulation of trace metals in soil. In this study, machine learning and geodetector models were integrated to investigate to contribution of environmental factors to variations of trace metals concentration. Before modeling, there are 10.33%-25.87% of soil considered as metal pollution, and the value of Pn further suggest that the Ba contribute the most to the comprehensive pollution index of trace metals in soil. The initial prediction of trace metals concentration by machine learning models is less effectively indicating the need for alternative approaches. To address this problem, post-constraints approach was used, and the post-constraint MSLR model demonstrates superior performance (R2 = 0.81) Additionally, through the utilization of geodetector model, the explanatory power (q) of CEC and SOM were identified as dominant natural factors with value of 0.055 and 0.089. respectively. Moreover, distance from working sites and working status were identified as the dominant anthropogenic factors associating to the spatial heterogeneity of trace metals in soil. The interaction between natural and anthropogenic factors showed a siginifacnt nonlinear enhancement effect on accumulation of Cr, Ba and Sr, and the highest value of q was 0.38 for SOM and distance. This study indicated that the potential metal contamination was related to shale gas exploitation and provide reference for controlling soil pollution in shale gas exploitation area and making management strategy.

Spatial and variety distributions, risk assessment, and prediction model for heavy metals in rice grains in China

In this study, 6229 brown rice grains from three major rice-producing regions were collected to investigate the spatial and variety distributions of heavy metals in rice grains in China. The potential sources of heavy metals in rice grains were identified using the Pearson correlation matrix and principal component analysis, and the health risks of dietary exposure to heavy metals via rice consumption were assessed using the hazard index (HI) and total carcinogenic risk (TCR) method, respectively. Moreover, 48 paired soil and rice samples from 11 cities were collected to construct a predicting model for Cd accumulation in rice grains using the multiple linear stepwise regression analysis. The results indicated that Cd and Ni were the main heavy metal pollutants in rice grains in China, with approximately 10% of samples exceeding their corresponding maximum allowable limits. The Yangtze River basin had heavier pollution of heavy metals than the Southeast Coastal Region and Northeast Plain, and the indica rice varieties had higher heavy metal accumulation abilities compared with the japonica rice. The Cu, Pb, and Cd mainly originated from anthropogenic sources, while As, Hg, Cr, and Ni originated from both natural and anthropogenic sources. The mean HI and TCR values of dietary exposure to heavy metals via rice consumption ranged from 2.92 to 4.31 and 9.74 × 10-3 to 1.44 × 10-2, respectively, much higher than the acceptable range, and As and Ni were the main contributor to the HI and TCR for Chinese adults and children, respectively. The available Si (ASi), total Cd (TCd), available Mo (AMo), and available S (AS) were the main soil factors determining grain Cd accumulation. A multiple linear stepwise regression model was constructed based on ASi, TCd, AMo, and AS in soils with good accuracy and precision, which could be applied to predict Cd accumulation in rice grains and guide safe rice production in contaminated paddy fields.

Ecological and contamination assessment of soil in the region of coal-fired thermal power plant

This study was carried out to determine the heavy metal pollution and possible sources of agricultural soils in Tavşanlı district, Which energy power plant is located. Total 83 soil samples were taken and 8 (Cu, Cr, Pb, Co, Fe, Mn, Ni, and Zn) heavy metals were analyzed in soil samples The mean concentration of heavy metals were determined as Cu (32.89 mg kg-1), Cr (285.69 mg kg-1), Co (36.37 mg kg-1), Mn (860.20 mg kg-1), Ni (457.59 mg kg-1), Pb (22.14 mg kg-1), Fe (30,250 mg kg-1) and Zn (65.05 mg kg-1), were determined. The mean concentrations of Cu, Cr Co, Mn and Ni found to be higher than both the upper continental crust values and the European soil mean values. Contamination factor Co (2.1), Cr (3.10) and Ni (9.73), enrichment factor Co (2.73), Cr (3.75) and Ni (11.42) and geoaccumulation index Co (0.18), Cr (0.50) and Ni (1.98) values showed that the soils were polluted by Co, Cr, and Ni. In addition, it was determined that Ni (48.65) poses a "moderate ecological risk" in the study area. Pearson correlation anaysis and principal component analysis determined that Cr, Co and Ni have both lithogenic and anthropogenic origin.

Machine learning combined with Geodetector quantifies the synergistic effect of environmental factors on soil heavy metal pollution

The critical prerequisite for the prevention and control of soil heavy metal (HM) pollution is the identification of factors that influence soil HM accumulation. The dominant factors have been individually identified and apportioned in existing studies. However, the accumulation of soil HMs results from a combination of multiple factors, and the influence of a single factor is less than the interaction of multiple parameters on soil HM pollution. In this study, we employed Geodetector to delve into the interaction effect of the influencing factors on the variations of soil HMs. We performed partial dependence plot to depict how these factors interact with each other to affect the HM content. We found that both individually and interactively, pH and agricultural activities significantly impact soil HM content. Except for Hg and Cu, the pairs with the most significant interaction effects all involve pH. For Pb, As and Zn, interaction with pH has the most significant driving force compared to the other factors. For Cu, Hg, and Ni, all environmental factor interactions increased their explanatory power, while for Cr, the single most significant driver decreased its driving power when interacting with other factors. Additionally, the study area exhibited a widespread prevalence of changes in HM concentration being governed by the synergistic effect of two factors. For the response of HMs to the interaction of pH and fertilizer, soil HM concentration was sensitive to pH, while fertilizer had less effect. These results provide a dependable method of investigating the interaction of environmental factors on soil HM content and put forth efficacious and potent tactical measures for soil HM pollution prevention and control based on the interaction type.

Ecological and health risk assessment associated with translocation of heavy metals in Lycopersicum esculentum from farmland soil treated with different composts

To meet the United Nations' Sustainable Development Goals, agricultural soil which is a non-renewable natural resource must be carefully managed. Heavy metals present in agricultural soil may imperil food security and instigate extreme risks to human health. Organic wastes have been long known for valuable amendments to soil thereby, improving overall soil health. In the present study, Echhornia crassipes, Hydrilla verticillata, and vegetable waste, was utilized to prepare compost amendments. Lycopersicum esculentum was used to metal uptake from compost amended soils. 5%, 10%, 15%, 25%, and 35% compost: soil (w/w) were studied to understand metal translocation in plants. Potential Ecological risk indices showed that while the degree of risk was medium for the natural soil, it reduced to slight for the soil amended with WHC and VWC for all compositions. The non-carcinogenic risks associated with the human health reduced on application of the composts, however, they still remained substantial for Fe, As, and Pb for WHC, HVC, and VWC composts at higher application ratios, especially among children. On the other hand, the carcinogenic health index values which were calculated to estimate the risk associated with ingestion of L. esculentum, showed a decrease in risk for all the metals studied, upon soil amendment. Soil amended with HVC compost showed an increase in carcinogenic risk for As, Pb, and Cr. Finally, we conclude that biological soil remediation is economical and a sustainable land management strategy that may lead to green and clean remediation solutions for metal contaminated soil.

Dynamic crosstalk between silicon nanomaterials and potentially toxic trace elements in plant-soil systems

Agricultural soil pollution with potentially toxic trace elements (PTEs) has emerged as a significant environmental concern, jeopardizing food safety and human health. Although, conventional remediation approaches have been used for PTEs-contaminated soils treatment; however, these techniques are toxic, expensive, harmful to human health, and can lead to environmental contamination. Nano-enabled agriculture has gained significant attention as a sustainable approach to improve crop production and food security. Silicon nanomaterials (SiNMs) have emerged as a promising alternative for PTEs-contaminated soils remediation. SiNMs have unique characteristics, such as higher chemical reactivity, higher stability, greater surface area to volume ratio and smaller size that make them effective in removing PTEs from the environment. The review discusses the recent advancements and developments in SiNMs for the sustainable remediation of PTEs in agricultural soils. The article covers various synthesis methods, characterization techniques, and the potential mechanisms of SiNMs to alleviate PTEs toxicity in plant-soil systems. Additionally, we highlight the potential benefits and limitations of SiNMs and discusses future directions for research and development. Overall, the use of SiNMs for PTEs remediation offers a sustainable platform for the protection of agricultural soils and the environment.

An integrated approach to identify the source apportionment of potentially toxic metals in shale gas exploitation area soil, and the associated ecological and human health risks

Public awareness of the potential environmental risks of shale gas extraction has increased in recent years. However, the status and environmental risks of potentially toxic metals (PTMs) in shale gas field soil remain unclear. A total of 96 topsoil samples were collected from the first shale gas exploitation area in China. The sources of nine PTMs in the soils were identified using positive matrix factorization and correlation analysis, and the ecological and human health risks of toxic metals from different sources under the two land use types were calculated. The results showed that mean pollution load index (PLI) values for farmland (1.18) and woodland (1.40) indicated moderate pollution, As, Cd and Ni were the most serious contaminants among all nine PTMs. The following four sources were identified: shale gas extraction activities (43.90%), nature sources (31.90%), agricultural and traffic activities (17.55%) and industrial activities (6.55%). For ecological risk, the mean ecological risk index (RI) values for farmlands (161.95) and woodlands (185.27) reaching considerable risk. The contribution ratio of shale gas extraction activities for farmlands and woodlands were 5.70% and 8.90%, respectively. Regarding human health risk, noncarcinogenic risks for adults in farmlands and woodlands were negligible. Industrial activities, agricultural and traffic activities were estimated to be the important sources of health risks. Overall, shale gas extraction activities had little impact on the ecological and human health risk. This study provides scientific evidence regarding the soil contamination potential of shale gas development activities.

Health risk assessment and bioaccumulation of potentially toxic metals from water, soil, and forages near coal mines of district Chakwal, Punjab, Pakistan

Water, forages, and soil contamination with potentially toxic metals (PTMs) through anthropogenic activities has become a significant environmental concern. It is crucial to find out the level of PTMs in water, soil, and forages near industrial areas. The PTMs enter the body of living organisms through these sources and have become a potential risk for humans and animals. Therefore, the present study aims at the health risk assessment of PTMs and their accumulation in soil, water, and forages of three tehsils (Kallar Kahar, Choa Saidan Shah, and Chakwal) in district Chakwal. Samples of wastewater, soil, and forages were collected from various sites of district Chakwal. PTMs detected in the present study were cadmium (Cd), chromium (Cr), lead (Pb), zinc (Zn), cobalt (Co), copper (Cu), and nickel (Ni), and their levels were measured through atomic absorption spectrophotometer (AAs GF95 graphite furnace auto sampler). Pollution load index (PLI), bio concentration factor (BCF), soil enrichment factors (EF), daily intake value (DIM), and health risk index (HRI) in sheep, cow, and buffalo were also analyzed. The results revealed that the mean concentration (mg/L) of Cd (0.72-0.91 mg/L), Cr (1.84-2.23 mg/L), Pb (0.95-3.22 mg/L), Co (0.74-2.93 mg/L), Cu (0.84-1.96 mg/L), and Ni (1.39-4.39 mg/L) in wastewater samples was higher than permissible limits set by WHO, NEQS, WWF, USEPA, and Pakistan in all three tehsils of district Chakwal. Similarly, in soil samples, concentrations of Cd (1.21-1.95 mg/kg), Cr (38.1-56.4 mg/kg), and Ni (28.3-55.9 mg/kg) were higher than their respective threshold values. The mean concentration of PTMs in forage samples (Parthenium hysterophorus, Mentha spicata, Justicia adhatoda, Calotropis procera, Xanthium strumarium, Amaranthaceae sp.) showed that maximum values of Cd (5.35-7.55 mg/kg), Cr (5.47-7.51 mg/kg), Pb (30-36 mg/kg), and Ni (12.6-57.5 mg/kg) were beyond their safe limit set for forages. PLI, BCF, and EF were > 1.0 for almost all the PTMs. The DIM and HRI for sheep were less than < 1.0 but for cows and buffalo were > 1.0. The current study showed that soil, water, and forages near coal mines area are contaminated with PTMs which enter the food chain and pose significant harm to humans and animals. In order to prevent their dangerous concentration in the food chain, regular assessment of PTMs present in soil, forages, irrigating water, and food is recommended.

Quantitative source apportionment and driver identification of soil heavy metals using advanced machine learning techniques

The accurate identification of pollution sources is essential for the prevention and control of possible pollution from soil heavy metals (SHMs). However, the positive matrix factorisation (PMF) model has been widely used as a conventional method for pollution source apportionment, and the classification of source apportionment results mainly relies on existing research and expert experience, which can result in high subjectivity in the source interpretation. To address this limitation, a comprehensive source apportionment framework was developed based on advanced machine learning techniques that combine self-organizing mapping and PMF with a gradient boosting decision tree (GBDT) model. Analysis of Cd, Pb, Zn, Cu, Cr, and Ni in 272 topsoils showed that the average contents of six heavy metals were 1.72-13.79 times greater than corresponding background values, among which Cd pollution was relatively serious, with 66.91 % of the sites having higher values than the specified soil risk screening values. The PMF results revealed that 79.43 % of Pb was related to vehicle emissions and atmospheric deposition, 79.32 % of Cd and 38.84 % of Zn were related to sewage irrigation, and 85.97 % of Cr and 85.50 % of Ni were from natural sources. Moreover, the GBDT detected that industrial network density, water network density, and Fe₂O₃ content were the major drivers influencing each pollution source. Overall, the novelty of this study lies in the development of an improved framework based on advanced machine learning techniques that led to the accurate identification of the sources of SHM pollution, which can provide more detailed support for environmental protection departments to propose targeted control measures for soil pollution.

Influencing factors identification and the nested structure analysis of heavy metals in soils in entire city and surrounding the multiple pollution sources

Identifying the sources of pollutants and analyzing the nested structure of heavy metals is vital for the prevention and control of soil pollution. However, there is a lack of research on comparison the main sources and the nested structure at different scales. In this study, two spatial extent scales were taken as the research objects, the results showed that, (1) the point exceeding standard rate of As, Cr, Ni, and Pb is higher at the entire city scale; (2) As and Pb, while Cr, Ni, and Zn, have weaker spatial variability at the entire scale and surrounding the pollution sources, respectively; (3) the contribution of the larger structure of Cr and Ni, while Cr, Ni, and Zn, at the entire scale and surrounding the pollution sources, respectively, is bigger to the total variability. The representation of semivariogram is better when the general spatial variability is weaker and the contribution of the smaller structure is lower; (4) various factors with different influencing distance could lead to nested structure even at a small extent spatial scale. The results provide a basis for the determination of remediation and prevention objectives at different spatial scales.

Spatial distribution, environmental risks, and sources of potentially toxic elements in soils from a typical abandoned antimony smelting site

The rapid development of the smelting industry increases the release of antimony (Sb) into the soil environment, which threatens human health and ecosystems. A total of 87 samples were collected from an abandoned Sb smelting site to evaluate pollution characteristics and environmental risks of the potentially toxic elements (PTEs). The contents of As, Cu, Ni, Pb, Sb, and Zn in the fresh soils determined by P-XRF were 131, 120, 60, 145, 240, and 154 mg/kg, respectively, whilst following drying, grinding, and sieving pretreatments, the corresponding contents increased to 367, 179, 145, 295, 479, and 276 mg/kg, respectively. There was a significant correlation between the data obtained by P-XRF and ICP-OES in the treated samples, which showed the application feasibility of P-XRF. The average contents of Sb and As were 440.6 and 411.6 mg/kg, respectively, which exceeded the control values of the development land in GB 36600-2018. The ecological risk levels of the six PTEs decreased in the following order: As > Sb > Pb > Zn > Ni > Cu. Non-carcinogenic risk revealed that As, Pb, and Sb posed health risks for children, whilst for carcinogenic risk, the risk values for As and Ni were higher than the limit values for both children and adults. Anthropogenic sources accounted for more than 70.0% of As, Pb, and Sb concentrations in soils, indicating a significant influence on PTEs accumulation. The findings provide a basis for quick determination of the contamination characteristics and risk control of PTEs at Sb smelting sites.

Combination of enrichment factor and positive matrix factorization in the estimation of potentially toxic element source distribution in agricultural soil

The study intended to assess the level of pollution of potential toxic elements (PTEs) at different soil depths and to evaluate the source contribution in agricultural soil. One hundred and two soil samples were collected for both topsoil (51), and the subsoil (51) and the content of PTEs (Cr, Cu, Cd, Mn, Ni, Pb, As and Zn) were determined using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The concentrations of Zn and Cd in both soil horizons indicated that the current study levels were higher than the upper continental crust (UCC), world average value (WAV), and European average values (EAV). Nonetheless, the concentration values of PTEs such as Mn and Cu for EAV, As, Cu, Mn, and Pb for UCC, and Pb for WAV were lower than the average values of the corresponding PTEs in this study. The single pollution index, enrichment factor, and ecological risk revealed that the pollution level ranged from low to high. The pollution load index, Nemerow pollution index, and risk index all revealed that pollution levels ranged from low to high. The spatial distribution confirmed that pollution levels varied between the horizons; that is, the subsoil was considered slightly more enriched than the topsoil. Principal component analysis identified the PTE source as geogenic (i.e. for Mn, Cu, Ni, Cr) and anthropogenic (i.e. for Pb, Zn, Cd, and As). PTEs were attributed to various sources using enrichment factor-positive matrix factorization (EF-PMF) and positive matrix factorization (PMF), including geogenic (e.g. rock weathering), fertilizer application, steel industry, industrial sewage irrigation, agrochemicals, and metal works. Both receptor models allotted consistent sources for the PTEs. Multiple linear regression analysis was applied to the receptor models (EF-PMF and PMF), and their efficiency was tested and assessed using root-mean-square error (RMSE), mean absolute error (MAE), and R² accuracy indicators. The validation and accuracy assessment of the receptor models revealed that the EF-PMF receptor model output significantly reduces errors compared with the parent model PMF. Based on the marginal error levels in RMSE and MAE, 7 of the 8 PTEs (As, Cd, Cr, Cu, Ni, Mn, Pb, and Zn) analysed performed better under the EF-PMF receptor model. The EF-PMF receptor model optimizes the efficiency level in source apportionment, reducing errors in determining the proportion contribution of PTEs in each factor. The purpose of building a model is to maximize efficiency while minimizing inaccuracy. The marginal error limitation encountered in the parent model PMF was circumvented by EF-PMF. As a result, EF-PMF is feasible and useful for apparently polluted environments, whether farmland, urban land, or peri-urban land.

Sensitive or tolerant functional microorganisms under cadmium stress: suggesting potential specific interaction network characteristics in the rhizosphere system of karst potato

The heavy metal cadmium (Cd) pollution in Chinese karst soils threatens food security, and microorganisms play an important role in regulating the migration and transformation of Cd in the soil-plant system. Nevertheless, the interaction characteristics between key microbial communities and environmental factors in response to Cd stress in specific crop environmental systems need to be explored. In this study, the soil (ferralsols)-microbe-crop (potato) system was taken as the object to explore the potato rhizosphere microbiome, using toxicology and molecular biology approaches, to explore the potato rhizosphere soil properties, microbial stress characteristics, and important microbial taxa under Cd stress. We hypothesized that different members of fungal and bacterial microbiome would regulate the resilience of potato rhizosphere and plants to Cd stress in the soil environment. Meanwhile, individual taxa will have different roles in the contaminated rhizosphere ecosystem. We found that soil pH was the main environmental factor affecting fungal community structure; urea-decomposing and nitrate-reducing functional bacteria as well as endosymbiotic and saprophytic functional fungi gradually decreased. In particular, Basidiomycota may play a key role in preventing the migration of Cd from the soil to plants (potato). These findings provide important candidates for screening the cascade of Cd inhibition (detoxification/regulation) from soil to microorganisms to plants. Our work provides an important foundation and research insights for the application of microbial remediation technology in the karst cadmium-contaminated farmland.

Assessment of sources, environmental, ecological, and health risks of potentially toxic elements in urban dust of Moscow megacity, Russia

Potentially toxic elements (PTEs) in urban dust of Moscow megacity and related risks have been studied. 78 samples were collected in the Moscow downtown in sites with different anthropogenic load, namely, major highways, residential area, and recreation zones. The concentrations of PTEs in urban dust were determined by ICP-MS and ICP-AES. Then, environmental, ecological and health risks of PTEs in urban dust were assessed. In addition, potential sources of PTEs in dust were identified. It is shown that Moscow dust is mainly contaminated by Sb, Zn, Pb, Cd, Cu, Sn, and Mo, which according to the data of principal component and correlation analyses can be attributed to anthropogenic sources (non-exhaust vehicle emissions). Potential ecological risk factor demonstrates that Cu, Mo, and Cd have moderate potential ecological risks in 13% of studied area, while Sb has this risk in 62% of area. Potential ecological risk indices indicate that 41% of studied territory is of moderate ecological risk. Concerning the human risks through ingestion, dermal contact, and inhalation pathways, PTEs in Moscow dust have no significant non-carcinogenic risks for adults. However, the value of total hazard index for children is 1.8 showing that non-carcinogenic risks may occur. Moreover, possible carcinogenic risks caused by Cr are evaluated. The finding of the present study can be used for ecological management in the megacity to reduce both ecological and human risks. A special attention should be given to periods of hot and dry weather and to traffic-related emissions.

Spatiotemporal patterns of soil heavy metal pollution risk and driving forces of increment in a typical industrialized region in central China

Excessive enrichment of soil heavy metals seriously damages human health and soil environment. Exploring the spatiotemporal patterns and detecting the influencing factors are conducive to developing targeted risk management and control. Based on the soil samples of Co, Cr, Cu, Mn, Ni, Pb, Zn, and Cd collected in one typical industrialized region in China from 2016 to 2019, this study analyzed the spatiotemporal pattern of geo-accumulation risk and potential ecological risk based on the spatiotemporal ordinary kriging (STOK) prediction, and probed the driving forces of heavy metal increments with the random forest (RF) regression model. The risk assessment revealed that soils were seriously contaminated by Pb, Cd, and Cu, moderately contaminated by Zn and Mn, and uncontaminated by Co, Cr, and Ni; more than 30% of areas had moderate to high potential ecological risks. From 2016 to 2019, soil heavy metal contents increased in more than 50% of regions and the growth rates of accumulations were ranked as Co (65%) > Ni (56%) > Mn (43%) > Pb (40%) > Cr (36%) > Zn (31%) > Cu (23%) > Cd (3%). High contents and increases of heavy metals in soils near industrial lands are higher. Smelter (24%), mine (20%), and factory (12%) were the major contributing factors for these heavy metal increments, followed by transportation (6%) and population (5%). The results indicated that the management of industrial discharge and contaminated soils should be strengthened to prevent the worsening soil heavy metal pollution in the study area.

Quantitative Source Apportionment of Potentially Toxic Elements in Baoshan Soils Employing Combined Receptor Models

Arable soils are crucial for national development and food security; therefore, contamination of agricultural soils from potentially toxic elements (PTEs) is a global concern. In this study, we collected 152 soil samples for evaluation. Considering the contamination factors and using the cumulative index and geostatistical methods, we investigated the contamination levels of PTEs in Baoshan City, China. Using principal component analysis, absolute principal component score-multivariate linear regression, positive matrix factorization, and UNMIX, we analyzed the sources and quantitatively estimated their contributions. The average Cd, As, Pb, Cu, and Zn concentrations were 0.28, 31.42, 47.59, 100.46, and 12.36 mg/kg, respectively. The Cd, Cu, and Zn concentrations exceeded the corresponding background values for Yunnan Province. The combined receptor models showed that natural and agricultural sources contributed primarily to Cd and Cu and As and Pb inputs, accounting for 35.23 and 7.67% pollution, respectively. Industrial and traffic sources contributed primarily to Pb and Zn inputs (47.12%). Anthropogenic activities and natural causes accounted for 64.76 and 35.23% of soil pollution, respectively. Industrial and traffic sources contributed 47.12% to pollution from anthropogenic activities. Accordingly, the control of industrial PTE pollution emissions should be strengthened, and awareness should be raised to protect arable land around roads.

Source-specific risk assessment for cadmium in wheat and maize: Towards an enrichment model for China

Cadmium (Cd) pollution of agricultural soil is of public concern due to its high potential toxicity and mobility. This study aimed to reveal the risk of Cd accumulation in soil and wheat/maize systems, with a specific focus on the source-specific ecological risk, human health risk and Cd enrichment model. For this we investigated more than 6100 paired soil and grain samples with 216 datasets including soil Cd contents, soil pH and grain Cd contents of 85 sites from China. The results showed that mining activities, sewage irrigation, industrial activities and agricultural practices were the critical factors causing Cd accumulation in wheat and maize cultivated sites. Thereinto, mining activities contributed to a higher Cd accumulation risk in the southwest China and Middle Yellow River regions; sewage irrigation influenced the Cd accumulation in the North China Plain. In addition, the investigated sites were classified into different categories by comparing their soil and grain Cd contents with the Chinese soil screening values and food safety values, respectively. Cd enrichment models were developed to predict the Cd levels in wheat and maize grains. The results showed that the models exhibited a good performance for predicting the grain Cd contents among safe and warning sites of wheat (R² = 0.61 and 0.72, respectively); while the well-fitted model for maize was prone to the overestimated sites (R² = 0.77). This study will provide national viewpoints for the risk assessments and prediction of Cd accumulation in soil and wheat/maize systems.

Source apportionment and source-specific risk evaluation of potential toxic elements in oasis agricultural soils of Tarim River Basin

As rapidly developing area of intensive agriculture during the past half century, the oases in the source region of the Tarim River have encountered serious environmental challenges. Therefore, a comparative analysis of soil pollution characteristics and source-specific risks in different oases is an important measure to prevent and control soil pollution and provide guidance for extensive resource management in this area. In this study, the concentration of potential toxic elements (PTEs) was analyzed by collecting soil samples from the four oases in the source region of the Tarim River. The cumulative frequency curve method, pollution index method, positive matrix factorization (PMF) model, geographical detector method and health risk assessment model were used to analyze the pollution status and source-specific risk of potential toxic elements in different oases. The results showed that Cd was the most prominent PTE in the oasis agricultural soil in the source region of the Tarim River. Especially in Hotan Oasis, where 81.25% of the soil samples were moderately contaminated and 18.75% were highly contaminated with Cd. The PTEs in the Hotan Oasis corresponded to a moderate level of risk to the ecological environment, and the noncarcinogenic risk of soil PTEs in the four oases to local children exceeded the threshold (TH > 1), while the carcinogenic risk to local residents was acceptable (1E-06 < TCR < 1E-04). The research results suggested that the Hotan Oasis should be the key area for soil pollution control in the source region of the Tarim River, and agricultural activities and natural sources, industrial sources, and atmospheric dust fall are the priority sources that should be controlled in the Aksu Oasis, Kashgar Oasis and Yarkant River Oasis, respectively. The results of this study provide important decision-making support for the protection and management of regional agricultural soil and the environment.

Source apportionment and risk assessment of soil heavy metals around a key drinking water source area in northern China: multivariate statistical analysis approach

With the intensive urbanization and industrialization in recent years, lots of products containing heavy metals (HMs) have brought in severe environment problems. Yuqiao Reservoir (YQR) is an important drinking water source area in Tianjin of China, and the soil environmental quality of YQR is vital for human health. The goal of this study was to identify the priority control pollutants and hotspots of HMs contamination of YQR catchment. Thus, an integrated field investigation was conducted to analyze the major elements such as As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in soils around YQR. Geoaccumulation index (Igeo), enrichment factor (EF) and potential ecological risk index (PERI) were employed to assess the contamination status of HMs. The average contents of these elements were given as follows: As 7.97 mg/kg, Cd 0.31 mg/kg, Cr 86.1 mg/kg, Cu 24.7 mg/kg, Hg 0.044 mg/kg, Ni 30.7 mg/kg, Pb 27.3 mg/kg and Zn 76.7 mg/kg. According to geoaccumulation index (I_geo) and enrichment factor (EF) values, Cd, Cr, Pb and As showed a prominent enrichment. The result of multivariate statistics showed that Cd, Cr, Cu, As, Ni, Pb and Zn concentrations were mainly affected by human activities, whereas Hg was mainly from natural release. The anthropogenic activities were the major sources with a contribution of 91.46%, while natural origins only contributed 8.54%. And agricultural fertilization, mining and traffic activities are the most probable sources of these heavy metals in the soil. The PERI values indicated that 65.7% of total HMs were at low risk, 22.5% in moderate risk and 11.8% in considerable risk. To ensure soil environmental quality and human health, cadmium should be listed as a priority control pollutant. Spatial maps of HMs and their integrated PERI provided clear hotspots that indicated lower risk in the region close to YQR but higher risk in the region far from YQR.

A Monte Carlo simulation-based health risk assessment of heavy metals in soils of an oasis agricultural region in northwest China

In recent years, heavy metal contamination of soils has been increasing, posing a major threat to food security, human health, and soil ecosystems. This study analyzed the spatial characteristics, contamination sources, risks of heavy metals by collecting topsoil samples from farmland in an oasis agricultural region in northwest China. The results found that soil heavy metals in farmland were at a moderate contamination level. The PMF model classifies soil heavy metals as fertilizer and pesticide sources dominated by As and Mn with 27.8 %, mixed sources of transport and agricultural sources dominated by Cu, Zn, Cd and Pb with 26.9 %, metal processing sources dominated by Cr and Ni with 22.6 %, and the combined pollution sources of Ti, V, Cr, Mn, Fe, As, Pb dominated by natural sources and fuel combustion. The noncarcinogenic and carcinogenic risks values from the ingestion route were higher for children than for adults. The non-carcinogenic risk of heavy metals to adults in the southwestern and central regions of the study area was >1 × 10^-4. The carcinogenic risk was >1 in all adults, but >1 in children in the central and southwestern study areas. Monte Carlo simulation takes into account the parameters and their distributions that affect the health risk assessment model by combining the uncertainty assessment with the health risk, which will reduce the uncertainty of the health risk assessment. The results showed that conventional deterministic risk assessment may overestimate health risk outcomes. In addition, As has a 1.85 % probability of non-carcinogenic risk to children, and an 85.3 % probability of total non-carcinogenic risk for children for all heavy metals. 69.5 % and 11.4 % probability of carcinogenic risk for children and adults respectively for Ni, and 96.4 % and 52.1 % probability of total carcinogenic risk, suggesting that Ni is a priority control heavy metal.

Spatial patterns in water quality and source apportionment in a typical cascade development river southwestern China using PMF modeling and multivariate statistical techniques

River cascade development is one of the human activities that have the most significant impact on the water environment. However, the mechanism of cascade development affecting river hydrochemical components still needs to be further studied. In this study, water quality index(WQI), positive matrix factorization(PMF) model and multivariate statistical techniques were used to identify the mechanism of cascade development affecting river hydrochemical components in an typical cascade development Rivers, Lancang River, China. The results showed that the water quality of Lancang River is relatively good due to less affected by human activity. The spatial variation of river hydrochemistry is affected by the development of cascade reservoirs, and shows three patterns: irregular variation (pH and DO), fluctuating decreasing (Na+, Cl-, SO42- and HCO3-) and multi-peak variation (TN, TDN, NO3--N and NH4+-N). It's worth noting that the concentration of the most hydrochemical parameters is higher in the upper reaches (less human activities) than that in the middle and lower reaches of river due to the retention effect of the reservoir on the chemical composition. The PMF model outputs revealed that the rock weathering and internal source, sewage and soil nitrogen, and chemical fertilizer were primary material sources of Lancang River. Compared with the natural channel zone (41.0%), the interaction of water-rock has more influence on chemical component in the reservoir area (56.3%), while the contribution of fertilizer (11.2%) to the river hydrochemistry is less. The sites of downstream of the reservoir dam were affected by the retention of the reservoir and the disturbance of the bottom drainage, which leads to the weakening of the influence of the sewage (44.7%) on the river material and the increase of the contribution of fertilizer (25.0%). These results could provide valuable information in controlling the eutrophication of cascade reservoirs and the scientific construction of river cascade reservoirs.

Spatial distribution, source apportionment, and ecological risk assessment of elements (PTEs, REEs, and ENs) in the surface soil of shiraz city (Iran) under different land-use types

In this study, 100 samples were collected from the topsoil of different land-use types (urban, industrial and agricultural) in Shiraz. The content of 26 elements was analyzed. CF, EF, Igeo, NPI, and PLI indices were used to evaluate soil pollution. Ecological risk assessment of metals was calculated by using Er and RI indexes. PCA analysis and the PMF model were used to determine the source of metals in soil. Also, the spatial distribution of metals and risk index were plotted using inverse distance weighting (IDW) with ArcGIS software (10.3). The metal concentrations in the soil ranged from 0.2067 ± 0.0946 (Ag) to 85,673.50 ± 4689.27 (Ca) mg kg^-1. The results show that all elements' Concentration in soils was lower than the DOE level. The mean concentration of All rare earth elements (REEs) was lower than WSA and ECM values. Hotspot points pollution of some metals such as Pb, Cd, and Ni are located in high-traffic parts of the urban area. Otherwise, hot spot points of As pollution are located in industrial sample points. Results of indexes show that Sb in urban and agricultural soils have highe mean values of CF (6.75 and 6.85) and Iegeo (2.17 and 2.13), respectively. In industrial soils, S has highe mean values of CF (14.95), EF (100.26), and Igeo (2.95). The PLI index shows that REEs (PLI <1) have no pollution, but PTEs and ENs have pollution (PLI >1). The mean Er, value shows that Sb (127.33) and Cd (104) have significant risk among metals. PCA and PMF models show that The main sources of elements in shiraz soil are vehicularly emitted, fertilizer use, sewage irrigation, atmospheric deposition, and parent material. Generally, results show that Most of the study area has considerable risk, especially concerning PTEs. So, it is recommended to pay more attention to the issue of traffic in the urban environment in to improve the state of the urban area.

Systematic Evaluation of Two Classical Receptor Models in Source Apportionment of Soil Heavy Metal(loid) Pollution Using Synthetic and Real-World Datasets

Due to the lack of a priori knowledge on true source makeup and contributions, whether the source apportionment results of Unmix and positive matrix factorization (PMF) are accurate cannot be easily assessed, despite the availability of built-in indicators for their goodness of fit and robustness. This study systematically evaluated, for the first time, the applicability and reliability of these models in source apportionment of soil heavy metal(loid)s with synthetic datasets generated using known source profiles and contributions and a real-world dataset as well. For eight synthetic datasets with different pollution source characteristics, feasible Unmix solutions were close to the true source component compositions (R² > 0.936; total mean squared errors (MSEs) < 0.04), while those of PMF had significant deviations (R² of 0.484-0.998; total MSEs of 0.04-0.16). Nonetheless, both models failed to accurately apportion the sources with collinearity or non-normal distribution. Unmix generally outperformed PMF, and its solutions showed much less dependence on sample size than those of PMF. While the built-in indicators provided little hint on the reliability of both models for the real-world dataset, their sample-size dependence indicated that Unmix probably yielded more accurate solutions. These insights could help avoid the potential misuse of Unmix and PMF in source apportionment of soil heavy metal(loid) pollution.

Accumulation of potentially toxic elements in Chinese tea (Camellia sinensis): Towards source apportionment and health risk assessment

Tea (Camellia sinensis) is a popular beverage that is consumed globally. However, a better understanding of potentially toxic elements (PTEs) content in tea leaves and infusion is necessary to minimize risk on human health. Therefore, 249 tea samples (grown in different areas) covering six types of tea were collected in China to investigate the PTEs contents, identify their potential source and assess the health risk associated with drinking tea. PTE contents in tea leaves across six tea types were ND-0.900 (Cd), 0.005-2.133 (As), ND-5.679 (Pb), ND-13.86 (Cr), 1.601-22.93 (Ni), ND-2.048 (Se), 0.109-622.4 (F), 13.02-269.9 (Rb), 1.845-50.88 (Sr), and 2.796-53.23 (Ba) mg/kg. The result of tea infusion showed that 14.3 %-44.1 % (green tea), 14.5 %-46.7 % (black tea), 10.5 %-25.3 % (dark tea), 13.6 %-34.2 % (oolong tea), 16.9 %-40.7 % (yellow tea), and 19.9 %-35.1 % (white tea) of F were released. All tea types, except green tea, exhibited comparatively low leachability of Cd, As, Pb and Cr in tea infusion. The source apportionment revealed that PTEs in tea leaves mainly originated from soil parental materials, while industrial activities, fertilizer application, and manufacturing processes may contribute to exogenous Se, Cd, As, and Cr accumulation. Health risk assessment indicated that F in tea infusion dominated the health risk. Humans may be exposed to a higher health risk by drinking green tea compared to that of other tea types. Nevertheless, the long-term tea consumption is less likely to contribute to pronounced non-carcinogenic and carcinogenic risks. This study confirmed that tea consumption is an important and direct pathway of PTEs uptake in humans. The health risk associated with drinking tea should be of concern.

Simultaneous Adsorption of Cu2+ and Cd2+ by a Simple Synthesis of Environmentally Friendly Bamboo Pulp Aerogels: Adsorption Properties and Mechanisms

The highly efficient, pollution-free and degradable biomass-based adsorbents used for the purification of wastewater are currently being highlighted in the research. Bamboo is an excellent raw material for pulp production due to its characteristics of fast growth, wide distribution and high cellulose content. In this study, a tannin/chitosan/bamboo pulp aerogel (TCPA), an environmentally friendly, renewable and low-density adsorbent, was synthesized using a simple freeze-drying method and analyzed by FTIR, XPS, SEM, TEM, TGA and surface area and porosity methods. TCPA has a large specific surface area (137.33 m2/g) and 3D porous structure, and its surface has multiple functional groups including amino, carboxyl and hydroxyl groups, which lead to a simultaneous absorption effect with Me2+ (Cu2+ and Cd2+). The maximum adsorption capacity for Cu2+ and Cd2+ of the TCPA was 72.73 mg/g and 52.52 mg/g, respectively. The adsorption processes of Me2+ by TCPA follow the pseudo-second-order model and Langmuir isotherm mode, and the adsorption processes are spontaneous and endothermic. The study provides a promising candidate for the treatment of wastewater containing heavy metal mixtures.

Heavy metals and their sources, potential pollution situations and health risks for residents in Adıyaman province agricultural lands, Türkiye

In this study, the contents of heavy metals (HMs) such as Al, Cd, Co, Cr, Cu Fe, Mn, Ni, Pb and Zn in soil samples collected from 403 sampling locations of the agricultural lands of Adıyaman Province (Türkiye) were determined by Inductively Coupled Plasma‒Optical Emission Spectrometry (ICP‒OES). The mean concentrations of Al, Cd, Co Cr, Cu Fe, Mn, Ni, Pb and Zn HMs were detected 28,986, 3.60, 15, 127, 52.67, 45,830, 817, 62.40, 10.75 and 66.25 mg kg^-1, respectively. These results showed that the average concentrations of Cd, Cr, Cu, Fe, Mn and Ni exceeded the Upper continental crust average. To determine and to evaluate the contamination status and distribution of HMs in agricultural soils, metal pollution parameters such as enrichment factor (EF), geoaccumulation index (I_geo), contamination factor (Cf), pollution load index, potential ecological risk factor (Er), and potential ecological risk index (RI) were used. Factor analyses (FA) and principal component analyses (PCA) indicated that Cd, Cr and Ni levels were influenced by anthropogenic sources, Fe by both lithological and anthropogenic sources, and other HMs by lithogenic origins. For both children and adults, the hazard index (HI) and total hazard index (THI) values of HMs were < 1, suggesting that non-carcinogenic health risks to residents through ingestion, inhalation pathways, and dermal contact were currently absent. In addition, the cumulative carcinogenic risk (CCR) results were within the acceptable risk range (10^-4 to 10^-6). The results showed that children were more sensitive to the non-carcinogenic and carcinogenic effects of HMs.

Nano-WSe2 Is Absorbable and Transformable by Rice Plants

As typical transition metal dichalcogenides (TMDC), tungsten selenide (WSe₂) nanosheets (nano-WSe₂) are widely used in various fields due to their layered structures and highly tunable electronic and magnetic properties, which results in the unwanted release of tungsten (W) and selenium (Se) into the environment. However, the environmental effects of nano-WSe₂ in plants are still unclear. Herein, we evaluated the impacts and fate of nano-WSe₂ and micro-WSe₂ in rice plants (Oryza sativa L.). It was found that both nano-WSe₂ and micro-WSe₂ did not affect the germination of rice seeds up to 5000 mg/L but nano-WSe₂ affected the growth of rice seedlings with shortened root lengths. The uptake and transportation of WSe₂ was found to be size-dependent. Moreover, W in WSe₂ was oxidized to tungstate while Se was transformed to selenocysteine, selenomethionine, Se^IV and Se^VI in the roots of rice when exposed to nano-WSe₂, suggesting the transformation of nano-WSe₂ in rice plants. The exposure to nano-WSe₂ brought lipid peroxidative damage to rice seedlings. However, Se in nano-WSe₂ did not contribute to the synthesis of glutathione peroxidase (GSH-Px) since the latter did not change when exposed to nano-WSe₂. This is the first report on the impacts and fate of nano-WSe₂ in rice plants, which has raised environmental safety concerns about the wide application of TMDCs, such as WSe₂ nanosheets.

Source apportionment of soil heavy metals with PMF model and Pb isotopes in an intermountain basin of Tianshan Mountains, China

A boom in tourism may lead to the enrichment in heavy metals (HMs) in soils. Contamination with HMs poses a significant threat to the security of the soil environment. In this study, topsoil samples were collected from a tourist area of Sayram Lake, and the concentrations of HMs (Cr, Cu, Ni, Pb, Zn and Cd) were determined. With contamination and eco-risk assessment models, correlation analysis, Pb isotope ratios, redundancy analysis and positive matrix factorization (PMF) model, the risks and sources of HMs in the soil were studied. The I_geo results suggested that Cd was the primary pollutant in the tourist area of Sayram Lake. The potential ecological risk index (PERI) showed that the study area was at low risk, and the pollution load index (PLI) indicated that the study area had a moderate contamination level. Qualitative and quantitative analyses apportioned three sources of HMs, namely, natural sources (38.5%), traffic sources (27.2%) and mixed sources (tourist waste and atmospheric deposition) (34.3%). Redundancy analysis results showed that the HMs content was related to SiO₂, Al₂O₃, TiO₂, P₂O₅, MnO, K₂O, Fe₂O₃ and SOC, and heavy metals tended to be stored in soil particles of grain sizes < 32 µm. These findings are expected to provide useful insights into the source identification of HMs in the soils of mountain tourism areas and provide a scientific decision-making basis for sustainable tourism development and for the assessment of ecological service values in the Tianshan Mountains.

Spatial distribution of heavy metals in rice grains and human health risk assessment in Hunan Province, China

Rice is the main food in China, and its pollution by heavy metals has attracted widespread attention. In this study, rice grain samples were collected from 14 prefecture-level cities in Hunan Province, China. The contents of 9 heavy metals (i.e., As, Cr, Co, Ni, Cu, Zn, Cd, Pb, and Sb) were measured using graphite digestion-inductively coupled plasma mass spectrometry (ICP-MS). Pearson correlation analysis and principal component analysis were performed to evaluate the correlation among these heavy metals. In addition, ordinary kriging interpolation were applied to investigate the spatial distribution pattern of the heavy metals. Results showed that the average concentrations of these heavy metals were 0.48 (As), 1.28 (Cr), 0.03 (Co), 0.84 (Ni), 2.39 (Cu), 15.73 (Zn), 0.28 (Cd), 0.66 (Pb), and 0.0043 (Sb) mg/kg, respectively. The single-factor pollution index (SFPI) contamination assessment showed that As, Pb, Cr, Ni, and Cd accumulated significantly in the rice grain, with over-standard rates of 100%, 100%, 64.70%, 47.05%, and 44.12%, respectively. The Sb concentrations at the sampling sites were low, and there was no obvious pollution. Health risk assessment showed that the target hazard quotient followed the order of As> Cr> Cd> Pb> 1.0> Co> Cu> Zn> Ni> Sb, and the carcinogenic risk value was in the order of Cd> Ni> As> Cr> 1.0×10^-4> Pb. In particular, quick actions should be taken to regulate As, Cr, and Cd contents in rice because they posed greater non-carcinogenic and carcinogenic health risks than the others to the local residents.

The Predominant Sources of Heavy Metals in Different Types of Fugitive Dust Determined by Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) Modeling in Southeast Hubei: A Typical Mining and Metallurgy Area in Central China

To develop accurate air pollution control policies, it is necessary to determine the sources of different types of fugitive dust in mining and metallurgy areas. A method integrating principal component analysis and a positive matrix factorization model was used to identify the potential sources of heavy metals (HMs) in five different types of fugitive dust. The results showed accumulation of Mn, Fe, and Cu can be caused by natural geological processes, which contributed 38.55% of HMs. The Ni and Co can be released from multiple transport pathways and accumulated through local deposition, which contributed 29.27%. Mining-related activities contributed 20.11% of the HMs and showed a relatively high accumulation of As, Sn, Zn, and Cr, while traffic-related emissions contributed the rest of the HMs and were responsible for the enrichment in Pb and Cd. The co-applied source-identification models improved the precision of the identification of sources, which revealed that the local geological background and mining-related activities were mainly responsible for the accumulation of HMs in the area. The findings can help the government develop targeted control strategies for HM dispersion efficiency.

Identifying contamination of heavy metals in soils of Peruvian Amazon plain: use of multivariate statistical techniques

The Peruvian Amazon plain has abundant natural resources and is home to great biodiversity, which makes it an area with high economic potential. However, the use of its resources through various activities has contributed to the release of heavy metals (HMs) into its soils, generating severe pollution problems which have mainly affected the health of local populations and their ecosystems. Currently, there are no comprehensive studies that have identified the specific sources of contamination by HMs in the soils of this part of the Peruvian territory. In this sense, this research aims to identify the possible sources of contamination by HMs in the soils of the Peruvian Amazon plain to focus efforts on the establishment of adequate measures for the protection of the health of people and the ecosystem. In the present study, samples of topsoils (0-20 cm depth) and subsoils (100-150 cm depth) were collected for the analysis of 11 HMs (Co, Cr, Cu, Fe, Mn, Ni, Pb, V, Zn, Be, and Hg) in 48 sites located in four regions of the Peruvian Amazon plain (Loreto, Amazonas, San Martín, and Ucayali), over the year 2019. The enrichment factor and geoaccumulation index were applied to assess contamination levels of HMs. The results indicated that topsoils and subsoils presented a greater enrichment by the elements Be and Pb, and were classified as moderately contaminated. Likewise, the integral analysis of these indexes together with principal component analysis, hierarchical cluster analysis, correlation analysis, and coefficient of variation allowed the identification of potential sources of contamination by HMs. As a result, Fe, Co, Zn, Ni, V, and Cr were associated with natural or lithogenic sources (parent material, crude oil deposits, and organic matter decomposition). Hg was attributed to anthropogenic sources (illegal gold mining, atmospheric deposition, and vehicle emissions). Be, Pb, Cu, and Mn originated from natural sources (parent material, crude oil deposits, decomposition of organic matter, and forest fires) and anthropogenic (areas degraded by solid waste, illegal gold mining, agriculture, and hydrocarbons). These findings provide essential information to establish regulations and prevent and control HM contamination in soils of the Peruvian Amazon plain.

Heavy Metal Contamination in Soils from a Major Planting Base of Winter Jujube in the Yellow River Delta, China

Surface soils form a major planting base of winter jujube in China were collected and detected for six heavy metals including Co, Ni, Cu, Zn, Cd, and Pb. The concentrations of Co, Ni, Cu, Zn, Cd, and Pb were 27.6 ± 6.0, 57.9 ± 12.8, 67.1 ± 10.3, 102.6 ± 23.4, 0.24 ± 0.07, and 25.1 ±5.9 mg/kg, respectively, showing an order of Zn > Cu > Ni > Co > Pb > Cd. The contents of the investigated metals were frequently observed higher than their related background values, suggesting that extra metal inputs occurred. Levels of all elements were below the associated risk screening values of agricultural soil in China, indicating healthy planting conditions for the winter jujube cultivation. Nemerow comprehensive pollution indexes of the metals in all the sampling stations were lower than 0.7, revealing a non-pollution status of the soils. Geo-accumulation indexes suggested that Zn and Pb caused no pollution, and Co, Ni, Cu, and Cd seemed to result in slight pollution. Co, Ni, Zn, Cd, and Pb had similar sources, which might be related to some natural processes and the use of fertilizers. Extra Cu might be mainly from the use of copper-containing pesticides. Based on our observations, the soils from the planting base of winter jujube in the Yellow River Delta were safe for the cultivation of winter jujube, and the rational utilization of pesticide and fertilizer were proposed to control the new inputs of heavy metals.

Long-term trend in surface ozone in Houston-Galveston-Brazoria: Sectoral contributions based on changes in volatile organic compounds

This study investigated the long-term variations in ambient levels of surface ozone, volatile organic compounds (VOCs), and nitrogen oxides (NO_x) within the Houston-Galveston-Brazoria (HGB) region. Analysis of ozone levels revealed an overall reduction in the maximum daily 8-h average ozone (MDA8 O₃) from 2000 to 2019 (April-October) with an average rate of ∼ -0.48 ppb/yr across HGB. With a few exceptions, the MDA8 O₃ reduction rates were more pronounced for the monitoring sites closer to the Houston Ship Channel (HSC). Meanwhile, ambient levels of NO_x and most VOC species (across the three representative sites as Houston Bayland Park, Haden Road, and Lynchburg Ferry) decreased significantly within the same investigation period, reflecting the impact of emission reductions. The positive matrix factorization (PMF) model applied to the mentioned sites identified regional background ozone, petrochemical emissions, engine combustion, natural gas/fuel evaporation, and solvent/painting/rubber industries as the major sources of MDA8 O₃. The regional background ozone was the predominant source, accounting for 59-70% of MDA8 O₃ across the three sites. Regarding the local anthropogenic emissions, natural gas/fuel evaporation was the largest contributor (19.5 ± 6.1%) to MDA8 O₃ at Houston Bayland Park, whereas petrochemical facilities (10.9 ± 4.9%) and solvent/painting/rubber industries (18.1 ± 9.5%) were the largest factor at Haden Road and Lynchburg Ferry, respectively. Notable reductions were found in the contributions of petrochemical emissions, engine combustion, and natural gas/fuel evaporation to MDA8 O₃ within 2000-2019, but an increasing trend was revealed in the role of solvent/painting/rubber industries on MDA8 O₃ most probably due to the enhanced demand for their products. Results of this study corroborated the success of emission control policies in limiting ozone precursors and provided useful details for prioritizing emission reduction policies to further reduce ozone pollution in the HGB.