How polluted are cities in central Europe? - Heavy metal contamination in Taraxacum officinale and soils collected from different land use areas of three representative cities

Predictive analysis and risk assessment of potentially toxic elements in Beijing gas station soils using machine learning and two-dimensional Monte Carlo simulations

Gas stations not only serve as sites for oil storage and refueling but also as locations where vehicles frequently brake, significantly enriching the surrounding soil with potentially toxic elements (PTEs). Herein, 117 topsoil samples from gas stations were collected in Beijing to explore the impact of gas stations on PTE accumulation. The analysis revealed that the average Pollution Index (PI) values for Cd, Hg, Pb, Cu, and Zn in the soil samples all exceeded 1. The random forest (RF) model, achieving an AUC score of 0.95, was employed to predict PTE pollution at 372 unsampled gas stations. Additionally, a Positive Matrix Factorization (PMF) model indicated that gas station operations and vehicle emissions were responsible for 70 % of the lead (Pb) enrichment. Probabilistic health risk assessments showed that the carcinogenic risk (CR) and noncarcinogenic risk (NCR) for PTE pollution to adult females were the highest, at 0.451 and 1.61E-05 respectively, but still within acceptable levels. For adult males at contaminated sites, the Pb-associated CR and NCR were approximately twice as high as those at uncontaminated sites, with increases of 107 % and 81 %, respectively. This study provides new insights for managing pollution caused by gas stations.

Plants as effective bioindicators for heavy metal pollution monitoring

This study investigated the bioindicator potential of Amaranthus retroflexus L., Plantago lanceolata L., Rumex acetosa L., and Trifolium pratense L. including the use of Lolium multiflorum L. as a reference species, for heavy metal pollution monitoring, in particular Zinc (Zn), Cadmium (Cd), Nickel (Ni), and Lead (Pb). Controlled heavy metal contamination was applied through irrigation with metal nitrate solutions two levels of contamination (low and high). The study also focused on analyzing heavy metals concentration in plant tissues and related physiological responses. Distinct physiological responses to heavy metal stress were observed among the investigated species, highlighting unique variations in their reactions. Hydrogen peroxide, malondialdehyde content, and enzymatic activities emerged as reliable indicators of plant stress induced by heavy metal solutions. P. lanceolata displayed elevated Zn concentrations in both roots and leaves (3271 ± 337 and 4956 ± 82 mg kg-1). For Pb, L. multiflorum and P. lanceolata showed highest root concentrations (2964 ± 937 and 1605 ± 289 mg kg-1), while R. acetosa had higher leaf concentration (1957 ± 147 mg kg-1). For Ni, L. multiflorum had the highest root concentration (1148 ± 93 mg kg-1), and P. lanceolata exhibited the highest leaf concentration (2492 ± 28 mg kg-1). P. lanceolata consistently demonstrated the highest Cd concentrations in both roots (126 ± 21 mg kg-1) and leaves (163 ± 12 mg kg-1). These results provide valuable insights for selecting effective bioindicator species to establish control strategies for heavy metal pollution.

Biomonitoring with the Use of the Herbal Plant Taraxacum officinale as a Source of Information on Environmental Contamination

The aim of this study was to assess the level of contamination of the common dandelion-Taraxacum officinale-with selected metals (Mn, Fe, Ni, Cu, Zn, Cd, and Pb) and to demonstrate that this plant can be used in passive biomonitoring of industrial sites. Two sample transects (the first was near a forest, an area potentially uncontaminated by analytes [A], while the second ran near a steel mill, a contaminated area [B]), each about 1.5 km long, located in Ozimek, Opole Province, Poland, were used in this study. Metals in plant and soil samples were determined by atomic absorption spectroscopy (AAS). Based on the analysis of the obtained results to determine the concentration of metals, plants at site A were more contaminated with Mn (240 mg/kg d.m.) and those at site B with Fe (635 mg/kg d.m.). Mean Pb values (8.39 mg/kg d.m.) were higher at the industrial site (B) and statistically significant at the forest site (A), together with Mn and Fe at the p < 0.001 level. The BCF values for T. officinale showed that Cu (0.473) and Zn (0.785) accumulated to an average degree on both transects. This shows that dandelion is heavily loaded with these metals. Both dandelion and soil samples showed the highest concentrations of Mn, Fe, and Zn, especially in the polluted area B, which is the result of pollution not only from the smelter (dust from electric arc furnaces in steel smelting, extraction installations in production halls transmitting pollutants into the air from molding sand, or waste from molding and core masses dumped on the heap and blown by the wind from the landfill) but also from the high anthropopressure caused by human activity-for example, heating processes or road transport. Our results confirmed that Taraxacum officinale can be successfully used as a herbal plant in passive biomonitoring to assess the quality of the environment, but it must be collected from uncontaminated areas if we want to use it like a medicinal plant.

Integrated assessment of the pollution and risk of heavy metals in soils near chemical industry parks along the middle Yangtze River

Industrialization in riparian areas of critical rivers has caused significant environmental and health impacts. Taking eight industrial parks along the middle Yangtze River as examples, this study proposes a multiple-criteria approach to investigate soil heavy metal pollution and associated ecological and health risks posed by industrial activities. Aiming at seven heavy metals, the results show that nickel (Ni), cadmium (Cd), and copper (Cu) exhibited the most significant accumulation above background levels. The comprehensive findings from Pearson correlation analysis, cluster analysis, principal component analysis, and industrial investigation uncover the primary sources of Cd, arsenic (As), mercury (Hg), and lead (Pb) to be chemical processing, while Ni and chromium (Cr) are predominantly derived from mechanical and electrical equipment manufacturing. In contrast, Cu exhibits a broad range of origins across various industrial processes. Soil heavy metals can cause serious ecological and carcinogenic health risks, of which Cd and Hg contribute to >70 % of the total ecological risk, and As contributes over 80 % of the total health risk. This study highlights the importance of employing multiple mathematical and statistical models in determining and evaluating environmental hazards, and may aid in planning the environmental remediation engineering and optimizing the industry standards.

Predictions of heavy metal concentrations by physiochemical water quality parameters in coastal areas of Yangtze river estuary

Due to the degradation-resistant and strong toxicity, heavy metals pose a serious threat to the safety of water environment and aquatic ecology. Rapid acquisition and prediction of heavy metal concentrations are of paramount importance for water resource management and environmental preservation. In this study, heavy metal concentrations (Cr, Ni, Cu, Pb, Zn, Cd) and physicochemical parameters of water quality including Temperature (Temp), pH, Oxygen redox potential (ORP), Dissolved oxygen (DO), Electrical conductivity (EC), Electrical resistivity (RES), Total dissolved solids (TDS), Salinity (SAL), Cyanobacteria (BGA-PE), and turbidity (NTU) were measured at seven stations in the Yangtze river estuary. Principal Component Analysis (PCA) and Spearman correlation analysis were employed to analyze the main factors and sources of heavy metals. Results of PCA revealed that the main sources of Cr, Ni, Zn, and Cd were steel industry wastewater, domestic and industrial sewage, whereas shipping and vessel emissions were typically considered sources of Pb and Cu. Spearman correlation analysis identified Temp, pH, ORP, EC, RES, TDS, and SAL as the key physicochemical parameters of water quality, exhibiting the strongest correlation with heavy metal concentrations in sediment and water samples. Based on these results, multiple linear regression as well as non-linear models (SVM and RF) were constructed for predicting heavy metal concentrations. The results showed that the results of the nonlinear model were more suitable for predicting the concentrations of most heavy metals than the linear model, with average R values of the SVM test set and RF test set being 0.83 and 0.90. The RF model showed better applicability for simulating the concentration of heavy metals along the Yangtze river estuary. It was demonstrated that non-linear research methods provided efficient and accurate predictions of heavy metal concentrations in a simple and rapid manner, thereby offering decision-making support for watershed managers.

Common weeds as heavy metal bioindicators: a new approach in biomonitoring

Environmental pollution by heavy metals affects both urban and non-urban areas of Europe and the world. The use of bioindicator plants for the detection of these pollutants is a common practice. An important property of potential bioindicators is their easy availability and wide distribution range, which means that they can be practically used over a wide area. Therefore, common and widely distributed weeds: Trifolium pratense L., Rumex acetosa L., Amaranthus retroflexus L., Plantago lanceolata L., ornamental species Alcea rosea L., and Lolium multiflorum L. var. Ponto were selected as a potential bioindicators of heavy metals (Cd, Pb, Cu, Zn). Plants were exposed in the same soil conditions in three sample sites in the Poznań city. It was found that all species had heavy metal accumulation potential, especially A. rosea, P. lanceolata and L. multiflorum for Zn (BCF = 6.62; 5.17; 4.70) and A. rosea, P. lanceolata for Cd (BCF = 8.51; 6.94). Translocation of Cu and Zn was the most effective in T. pratense (TF_Cu = 2.55; TF_Zn = 2.67) and in A. retroflexus (TF_Cu = 1.50; TF_Zn = 2.23). Cd translocation was the most efficient in T. pratense (TF_Cd = 1.97), but PB was the most effective translocated in A. retroflexus (TF_Pb = 3.09).. Based on physiological response to stress, it was detected an increasing level of hydrogen peroxide (H₂O₂) in roots and leaves of all samples, with the highest in all organs of A. rosea. Enzymatic activity levels of CAT, APOX, and also the marker of polyunsaturated fatty acid peroxidation MDA, were higher after 6 weeks of exposure in comparison to control samples and varied in time of exposure and between species and exposure. After the experiment, in almost all samples we detected a reduction of chlorophyll content and relative water content, but in efficiency of photosynthesis parameters: net photosynthesis rate, intercellular CO₂ concentration and stomatal conductance, we noted increased values, which proved the relatively good condition of the plants. The examined weeds are good bioindicators of heavy metal contamination, and their combined use makes it possible to comprehensively detection of environmental threats.

A spatial distribution - Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil

With the rapid development of urbanization, heavy metal pollution of soil has received great attention. Over-enrichment of heavy metals in soil may endanger human health. Assessing soil pollution and identifying potential sources of heavy metals are crucial for prevention and control of soil heavy metal pollution. This study introduced a spatial distribution - principal component analysis (SD-PCA) model that couples the spatial attributes of soil pollution with linear data transformation by the eigenvector-based principal component analysis. By evaluating soil pollution in the spatial dimension it identifies the potential sources of heavy metals more easily. In this study, soil contamination by eight heavy metals was investigated in the Lintong District, a typical multi-source urban area in Northwest China. In general, the soils in the study area were lightly contaminated by Cr and Pb. Pearson correlation analysis showed that Cr was negatively correlated with other heavy metals, whereas the spatial autocorrelation analysis revealed that there was strong association in the spatial distribution of eight heavy metals. The aggregation forms were more varied and the correlation between Cr contamination and other heavy metals was lower. The aggregation forms of Mn and Cu, Zn and Pb, on the other hand, were remarkably comparable. Agriculture was the largest pollution source, contributing 65.5 % to soil pollution, which was caused by the superposition of multiple heavy metals. Additionally, traffic and natural pollution sources contributed 17.9 % and 11.1 %, respectively. The ability of this model to track pollution of heavy metals has important practical significance for the assessment and control of multi-source soil pollution.

Soil potentially toxic element pollution at different urbanization intensities: Quantitative source apportionment and source-oriented health risk assessment

Potentially toxic element (PTE) pollution of urban soils has become the focus of social concern, but the differences of the sources, pollution levels and source-oriented human health risks (HHR) of PTE in urban soils among different urban intensity areas is rarely known. This study explored a comprehensive scheme that combined positive matrix factorization model and source-oriented assessment to quantitatively assess the priority pollution sources and HHR in urban soils from areas with different urbanization intensities. All the average values for PTE concentrations, except for Cr, were higher than their corresponding background values. The contributions made by the four sources (atmospheric deposition, agricultural activities, traffic activities, and natural sources) were relatively similar (22.29-29.89%) in the low urbanization intensity (LUI) area, whereas traffic activities and atmospheric deposition made the greatest contributions in the medium urbanization intensity (MUI) (29.12%) and the high urbanization intensity (HUI) (38.97%) areas, respectively. The geo-accumulation index results revealed that Cd was the most polluting element and the HUI area had the highest pollution levels. The content-oriented assessment of HHR demonstrated that the non-carcinogenic risks were acceptable, but the carcinogenic risks were unacceptable. According to the source-oriented HHR assessment, among the anthropogenic activities, atmospheric deposition contributed the most to carcinogenic risk of children in all areas, and atmospheric deposition, traffic activities and agricultural activities contributed the most to the carcinogenic risk of adults in HUI, MUI and LUI, respectively. This suggest that control measures need to be tailored to the appropriate urbanization intensity to effectively curb PTE pollution caused by anthropogenic activities.

Contamination of food crops by unintentionally released PCB 47, PCB 51 and PCB 68 in the vicinity of silicone production sites and their relevance for human health assessment

Since it was shown that silicone rubber production can unintentionally release PCBs, these production sites have become a focus of investigation. The use of the cross-linking agent bis(2,4)-dichlorobenzoylperoxide (2,4-DCBP) can lead to emissions of the PCB congeners PCB 47, PCB 51 and PCB 68 into the environment and cause their accumulation e. g. in food crops. To determine the presence and extent of this uptake, we used the newly developed method dandelion screening. Samples were taken from wild dandelion plants near nine production sites in North Rhine-Westphalia, Germany, and analysed for PCBs. In some cases, the regional orientation values for the maximum background level (OMB) were exceeded by up to nine times. Overall, background levels were exceeded at seven of the nine sites investigated and mitigation measures were initiated at the production sites. In order to validate the dandelion screening results, kale was exposed, which allowed for a health assessment. A wide-ranging consumption recommendation was then issued in four out of nine study areas. At this point in the investigations, risk reduction measures had already been implemented at all production sites investigated, so it can be assumed that the exposures at sites not yet in focus are significantly greater. This is a globally relevant problem, as 2,4-DCBP is used in many countries.

Novel metallomic profiling and non-carcinogenic risk assessment of botanical ingredients for use in herbal, phytopharmaceutical and dietary products using HR-ICP-SFMS

Knowledge of element concentrations in botanical extracts is relevant to assure consumer protection given the increased interest in plant-based ingredients. This study demonstrates successful multi-element investigations in order to address the lack of comprehensive profiling data for botanical extracts, while reporting for the first time the metallomic profile(s) of arnica, bush vetch, sweet cicely, yellow rattle, bogbean, rock-tea and tufted catchfly. Key element compositions were quantified using a validated HR-ICP-SFMS method (µg kg-1) and were found highly variable between the different plants: Lithium (18-3964); Beryllium (3-121); Molybdenum (75-4505); Cadmium (5-325); Tin (6-165); Barium (747-4646); Platinum (2-33); Mercury (5-30); Thallium (3-91); Lead (12-4248); Bismuth (2-30); Titanium (131-5827); Vanadium (15-1758); Chromium (100-4534); Cobalt (21-652); Nickel (230-6060) and Copper (1910-6340). Compendial permissible limits were not exceeded. Overall, no evidence of a health risk to consumers could be determined from consumption of the investigated plants at reasonable intake rates. Mathematical risk modelling (EDI, CDI, HQ, HI) estimated levels above safe oral thresholds only for Cd (16%) and Pb (8%) from higher intakes of the respective plant-derived material. Following high consumption of certain plants, 42% of the samples were categorised as potentially unsafe due to cumulative exposure to Cu, Cd, Hg and Pb. PCA suggested a potential influence of post-harvest processing on Cr, Ti and V levels in commercially-acquired plant material compared to wild-collected and farm-grown plants. Moreover, a strong correlation was observed between Pb-Bi, Be-V, Bi-Sn, and Tl-Mo occurrence. This study may support future research by providing both robust methodology and accompanying reference profile(s) suitable for the quality evaluation of essential elements and/or metal contaminants in botanical ingredients.

Ranking of Basin-Scale Factors Affecting Metal Concentrations in River Sediment

River sediments often contain potentially harmful pollutants such as metals. Much research has been conducted to identify factors involved in sediment concentrations of metals. While most metal pollution studies focus on smaller scales, it has been shown that basin-scale parameters are powerful predictors of river water quality. The present study focused on basin-scale factors of metal concentrations in river sediments. The study was performed on the contiguous USA using Random Forest (R.F.) to analyze the importance of different factors of the metal pollution potential of river sediments and evaluate the possibility of assessing this potential from basin characteristics. Results indicated that the most important factors belonged to the groups Geology, Dams, and Land cover. Rock characteristics (contents of K2O, CaO, and SiO2) and reservoir drainage area were strong factors. Vegetation indices were more important than land cover types. The response of different metals to basin-scale factors varied greatly. The R.F. models performed well with prediction errors of 16.5% to 28.1%, showing that basin-scale parameters hold sufficient information for predicting potential metal concentrations. The results contribute to research and policymaking dependent on understanding large-scale factors of metal pollution.

Spatiotemporal variation and sources of soil heavy metals along the lower reaches of Yangtze River, China

Excessive accumulation of soil heavy metals (HMs) result in the deterioration of soil quality and reduction of agricultural productivity and safety. The accumulation status, temporal change, and sources of soil HMs were determined by large-scale field surveys in 2014 and 2019 in rapid urbanization and industrialization area along the lower reaches of the Yangtze River, China. Eighty-two surface soil samples were collected in 2014 and ninety-five surface soil samples and seven soil profiles (0-100 cm) were collected in 2019. The mean concentrations (in, mg kg^-1) of As (10.17), Cd (0.33), Cr (86.38), Cu (38.22), Hg (0.11), Ni (37.67), Pb (43.95), and Zn (113.15) were greater than the corresponding background values. The concentrations of these 8 HMs significantly varied with site-specific distributions depending on nearby landscape patterns with decreasing order: agricultural soil around industrial > agricultural soil > fallow soil. Cd and Hg were found to be priority pollutants due to their greater accumulations in this study area. Combined analyses of principal component analysis and positive matrix factorization model addressed source apportionment of soil HMs. Industrial activities, parent materials, and agricultural and traffic activities were three major sources and their contributions were 35.56%, 35.20%, and 29.23%, respectively. The concentrations of soil As, Cd, Cr and Pb increased with time. This study elucidates how changes in land uses and time affect soil HMs and provides reasonable suggestions for the effective reduction of HM contamination in economically and industrially developed areas of China, and elsewhere.

Significant release of unintentionally produced non-Aroclor polychlorinated biphenyl (PCB) congeners PCB 47, PCB 51 and PCB 68 from a silicone rubber production site in North Rhine-Westphalia, Germany

Silicone rubber production using bis(2,4)-dichlorobenzoylperoxide (2,4-DCBP) as cross-linking agent was recently found to emit significant amounts of the non-Aroclor PCB congeners PCB 47, PCB 51 and PCB 68 into ambient air. Emissions were reported initially to be associated with flue gas condensate flakes deposited in the direct vicinity of the production site. These flakes were mainly composed of 2,4-dichlorobenzoic acid and were contaminated with PCBs in the range of 150-300 mg/kg. Analysis of ambient air proved that also substantial gaseous emissions of the specific PCB congeners occur. The PCB congeners PCB 47, PCB 51 and PCB 68 were also found in bulk deposition samples, bio-indicators (dandelion, kale) and soil samples in the vicinity of the production site. Substitution of 2,4-DCBP by other cross-linking agents and mitigation measures led to a significant decrease of environmental impact.

The fate and contamination of trace metals in soils exposed to a railroad used by Diesel Multiple Units: Assessment of the railroad contribution with multi-tool source tracking

Soil samples from cut slopes from lightly loaded railway lines used by Diesel Multiple Units for 5 years in Gdansk (Poland) were collected and analyzed for trace metals (TMs): Zn, Pb, Cd, Ni, Cr, Cu, and Fe. The main aim was to assess soil enrichment, contamination status, and distribution of TMs relative to the distance from the railway track. Extensive source tracking analyses were performed using cluster analysis (CA) and the Pb isotope ratios approach (²⁰⁶Pb, ²⁰⁷Pb, and ²⁰⁸Pb). Soil samples were affected by Cr, Cu, Pb, and Zn (max values in mg/kg d.w.: 31.1, 145, 80.5, and 115, respectively). The Enrichment Factor showed moderate (Cr, Zn, Pb) to very severe (Cu) enrichment. CA allowed TMs to be divided into two general groups: a) containing Zn, Pb, Cd with slight interaction with Cu; and b) containing Fe and Ni with slight interaction with Cr. Correlation analyses indicated Cr as an outlying TM delivered from a separate source associated with the specificity of the construction of railroad 248, where alloys containing Cr were used to counteract increasing wear-and-tear of the rails. Pb isotopic ratios in the ranges of 1.16-1.20 (²⁰⁶Pb/²⁰⁷Pb) and 2.05-2.10 (²⁰⁸Pb/²⁰⁶Pb) corresponded to anthropogenic supplementation (coal combustion, road vehicles, and railroad transport) of Pb and Pb-correlated TMs (Zn, Cd, and partly Cu). Despite the research focus on the impact of the railroad contribution, a comparison with other forms of transport indicated that road transport appeared to have a higher contributing factor to TM pollution at the investigated site. This general conclusion again emphasizes the lower environmental footprint exhibited by railway transport in comparison to road transport.

Contamination, sources and health risk of heavy metals in soil and dust from different functional areas in an industrial city of Panzhihua City, Southwest China

The contamination of heavy metals in urban soil and dust is closely related to anthropogenic emissions, while to what extent the metal contamination varies among different functional areas in industrial cities remains unclear. In this study, the contamination and health risk of seven heavy metals in the soil and dust were assessed at different functional areas of Panzhihua City, Southwest China, and their sources were identified by the spatial divisions and Pb isotopes. The results showed that the contamination of V and Cr in the vanadium/steel plant (VsA) and the contamination of Cd, Pb and Zn in the iron-ore smelting (IsA) were significantly higher relative to other functional areas. The sources of the contaminated heavy metals in the soil and dust were mainly from smelting and manufacturing vanadium/steel products, coal combustion and traffic. Vanadium and Cr were the major metals primarily contributing to the noncarcinogenic and carcinogenic risks, despite the low contamination level of Cr. The results indicate that the VsA is the priority control area in the Panzhihua City, and besides V, more attention should be paid in the future to monitor Cr risk in the soil and dust because of its high contribution to the health risk.