The possibility of using Scots pine needles as biomonitor in determination of heavy metal accumulation

Detecting changes in industrial pollution by analyzing heavy metal concentrations in tree-ring wood from Romanian conifer forests

The impact of air pollution on forests, especially in urban areas, has been increasingly discussed recently. Many pollutants, including heavy metals, are released into the atmosphere from various sources, such as mining, non-ferrous metal processing plants, and fossil fuel combustion. These pollutants can adversely affect not only tree growth but also other species, including humans. This study compared the concentrations of several elements in tree-ring wood from two conifer species (Silver fir, Abies alba; Norway spruce, Picea abies) growing in polluted and unpolluted areas. Two regions in northern Romania (Bicaz and Tarnița) that were subjected to historical pollution changes were selected. Two chemical analyses were used: inductively coupled plasma mass spectrometry (ICP-MS) and X-ray fluorescence spectrometry (XRF). The silver fir trees from the intensively polluted area in the Tarnița region were negatively impacted by industrial pollution: the Mn concentrations were, on average, three times higher in polluted areas than in unpolluted areas (ca. 30 vs. 10 mg kg-1). This finding was consistent for both ICP-MS and XRF analyses. However, in Norway spruce, this difference was found only in the XRF data, which detected Mn concentrations seven times higher in trees from polluted areas than those from unpolluted areas (ca. 700 vs. 100 mg kg-1). In the Tarnița region, Norway spruce accumulated more heavy metals than silver fir, but the most pronounced differences between polluted and unpolluted areas were found in silver fir. The two analytical methods are commonly used to determine metal concentrations in wood, and they complement each other, with ICP-MS having a low detection limit for some elements and XRF having higher detection limits and better accuracy. Each method has its advantages and disadvantages, and the optimal method depends on many factors, such as the type of heavy metal analyzed, its concentration in wood, sample type, cost, analysis time, and sample preparation.

Evaluation of succulent plants Echeveria elegans as a biomonitor of heavy metals and radionuclides

This work evaluates the use of Echeveria elegans as a biomonitor of metals and radionuclides, using semi-urban soils as a study area. The study area is exposed to various trace elements of concern for various social groups in nearby localities. The quantification of metals and radionuclides was performed by X-ray fluorescence spectrometry and gamma spectrometry, respectively. Cumulative frequency distribution curves, descriptive statistics, and multivariate analysis were used to estimate the local geochemical baseline and identify geochemical and anthropogenic patterns of metals and radionuclides from topsoil and E. elegans. The evaluation of contaminants and the contribution of possible exposure routes (topsoil and atmospheric deposition) was performed with the enrichment factor (EF) and the relative concentration factor (CFR). The results suggest that the plant does not present significant physical stress due to the environmental conditions to which it was exposed. Likewise, it can bioaccumulate heavy metals from natural and anthropogenic sources. The quantification of radionuclides in the plant is below the detection limits, indicating a low bioavailability and transfer factor. The CFR and EF results showed that the plant accumulates metals from the topsoil and atmospheric deposition. The bioaccumulation mechanism would be related to the functioning of Crassulaceae Acid Metabolism (CAM). In topsoil, the organic acids of the plant would modify the solubility of the metals present in an insoluble form in the soil, acting as ligands and, subsequently, following the transport route of these metabolites. In atmospheric deposition, the metals deposited in the leaves would be incorporated into the plant through the opening of the stomata because of the capture of CO2 (at night, day, or during environmental stress) by the CAM. Overall, the evidence showed that the succulent can be used as a biomonitor of heavy metals. However, additional studies are required to determine its usefulness as a radionuclide biomonitor.

A case study of using artificial neural networks to predict heavy metal pollution in Lake Iznik

Artificial neural networks offer a viable route in assessing and understanding the presence and concentration of heavy metals that can cause dangerous complications in the wider context of water quality prediction for the sustainability of the ecosystem. In order to estimate the heavy metal concentrations in Iznik Lake, which is an important water source for the surrounding communities, characterization data were taken from five different water sources flowing into the lake between 2015 and 2021. These characterization results were evaluated with IBM SPSS Statistics 23 software, with the addition of the lake water quality system. For this purpose, seven distinct physicochemical parameters were measured and monitored in Karasu, Kırandere, Olukdere and Sölöz water sources flowing into the lake, to serve as input data. Concentration levels of 15 distinct heavy metals in Karsak Stream originating from the lake were as the output. Specifically, Sn for Karasu (0.999), Sb for Kırandere (1.000), Cr for Olukdere (1.000) and Pb and Se for Sölöz (0.995) indicate parameter estimation R2 coefficients close to 1.000. Sn stands out as the common heavy metal parameter with best estimation prospects. Given the importance of the independent variable in estimating heavy metal pollution, conductivity, COD, COD and temperature stood out as the most effective parameters for Karasu, Olukdere, Kırandere and Sölöz, respectively. The ANN model emerges as a good prediction tool that can be used effectively in determining the heavy metal pollution in the lake as part of the efforts to protect the water budget of Lake Iznik and to eliminate the existing pollution.

Research progress of the detection and analysis methods of heavy metals in plants

Heavy metal (HM)-induced stress can lead to the enrichment of HMs in plants thereby threatening people's lives and health via the food chain. For this reason, there is an urgent need for some reliable and practical techniques to detect and analyze the absorption, distribution, accumulation, chemical form, and transport of HMs in plants for reducing or regulating HM content. Not only does it help to explore the mechanism of plant HM response, but it also holds significant importance for cultivating plants with low levels of HMs. Even though this field has garnered significant attention recently, only minority researchers have systematically summarized the different methods of analysis. This paper outlines the detection and analysis techniques applied in recent years for determining HM concentration in plants, such as inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectrometry (AAS), atomic fluorescence spectrometry (AFS), X-ray absorption spectroscopy (XAS), X-ray fluorescence spectrometry (XRF), laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), non-invasive micro-test technology (NMT) and omics and molecular biology approaches. They can detect the chemical forms, spatial distribution, uptake and transport of HMs in plants. For this paper, the principles behind these techniques are clarified, their advantages and disadvantages are highlighted, their applications are explored, and guidance for selecting the appropriate methods to study HMs in plants is provided for later research. It is also expected to promote the innovation and development of HM-detection technologies and offer ideas for future research concerning HM accumulation in plants.

The spatial distribution of potentially toxic elements in the mountain forest topsoils (the Silesian Beskids, southern Poland)

Progressive industrialisation and urbanisation in recent decades have dramatically affected the soil cover and led to significant changes in its properties, which inevitably affect the functioning of other components of the forest ecosystems. The total content of Pb, Cd, Zn, Fe, Cr, Cu, Ni, As, and Hg was studied in twenty-five plots at different heights in the topsoil (organic and humus horizons) formed from the Carpathian flysch in the area of the Silesian Beskids (Western Carpathians). The aim of this article is to analyse the spatial distribution of potentially toxic elements in the mountain forest topsoil in different types of plant communities and to determine the relationship between altitude and potentially toxic elements contamination. The soils studied are acidic or very acidic, with an average range of 3.8 (H2O) and 2.9 (KCl). Concentrations of the metals Cd, Zn, Fe, Cr, Cu, Ni, and Hg on the plots that were analysed are within the range of permissible standards for forest ecosystems in Poland, while Pb and As exceed the permissible standards for this type of ecosystem. Spearman's rank correlation coefficient showed a high correlation between Fe-Cr (r(32) = 0.879, Pb-Hg r(32) = 0.772, Ni-Cr r(32) = 0.738, Zn-Cd r(32) = 0.734, and Cu-Hg r(32) = 0.743, and a moderate statistically significant positive correlation between Cu-Pb r(32) = 0.667 and As-Pb r(32) = 0.557. No correlation was found between altitude and the occurrence of potentially toxic elements. The geo-accumulation index (Igeo) index, on the other hand, indicates that Pb, As, and Cd have the highest impact on soil contamination in all study plots: it classifies soils from moderately to strongly polluted. The enrichment factor (EF) obtained for As and Hg indicates significant-to-very high enrichment in all areas studied. The potential ecological risk index (PLI) calculated for the sites indicates the existence of pollution in all areas examined. The highest risk categories (considerable to very high) are associated with cadmium and mercury.

Variation of Al concentrations depending on the growing environment in some indoor plants that used in architectural designs

Today, most of people's time is spent indoors. Air pollution indoors is much higher than outdoors. Therefore, the effect of indoor air on human health is much more than the outside air. One of the most effective methods of reducing indoor air pollution is the use of plants. However, in order for the plants to be used effectively for this purpose, it is first necessary to determine which plants are the most effective in reducing which pollutants. Within the scope of this study, the Al accumulation potential of seven ornamental plants, which are frequently used in interior architectural designs, was evaluated. Within the scope of the study, the variation of Al concentrations on the basis of species and environment was determined in plants grown in control, smoking environment, and traffic environment. As a result of the study, it was determined that Al concentrations changed statistically significantly both on the basis of environment and species, and the species with the highest Al accumulation potential was difenbahya.

The wild plant Gnaphalium lavandulifolium as a sentinel for biomonitoring the effects of environmental heavy metals in the metropolitan area of México Valley

Biomonitoring is a valuable tool for assessing the presence and effects of air pollutants such as heavy metals (HM); due to their toxicity and stability, these compounds can affect human health and the balance of ecosystems. To assess its potential as a sentinel organism of HM pollution, the wild plant Gnaphalium lavandulifolium was exposed to four sites in the metropolitan area of México Valley (MAMV): Altzomoni (ALT) Coyoacán (COY), Ecatepec (ECA), and Tlalnepantla (TLA) during 2, 4, and 8 weeks, between October and November 2019. Control plants remained under controlled conditions. The chemical analysis determined twelve HM (Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn) in the leaves. Macroscopic damage to the leaves, later determined in semi-thin sections under light microscopy, lead to a finer analysis. Transmission electron microscope (TEM) showed major structural changes: chromatin condensation, protoplast shrinkage, cytoplasm vacuolization, cell wall thinning, decreased number and size of starch grains, and plastoglobules in chloroplasts. All these characteristics of stress-induced programed cell death (sPCD) were related to the significant increase of toxic HM in the leaves of the exposed plants compared to the control (p < 0.05). Immunohistochemistry revealed a significant amount of proteases with caspase 3-like activity in ECA and TLA samples during long exposure times. Ultrastructural changes and sPCD features detected confirmed the usefulness of G. lavandulifolium as a good biomonitor of HM contamination. They supported the possibility of considering subcellular changes as markers of abiotic stress conditions in plants.

Bioremediation of hazardous pollutants from agricultural soils: A sustainable approach for waste management towards urban sustainability

Soil contamination is perhaps the most hazardous issue all over the world; these emerging pollutants ought to be treated to confirm the safety of our living environment. Fast industrialization and anthropogenic exercises have resulted in different ecological contamination and caused serious dangerous health effects to humans and animals. Agro wastes are exceptionally directed because of their high biodegradability. Effluents from the agro-industry are a possibly high environmental risk that requires suitable, low-cost, and extensive treatment. Soil treatment using a bioremediation method is considered an eco-accommodating and reasonable strategy for removing toxic pollutants from agricultural fields. The present review was led to survey bioremediation treatability of agro soil by microbes, decide functional consequences for microbial performance and assess potential systems to diminish over potentials. The presence of hazardous pollutants in agricultural soil and sources, and toxic health effects on humans has been addressed in this review. The present review emphasizes an outline of bioremediation for the effective removal of toxic contaminants in the agro field. In addition, factors influencing recent advancements in the bioremediation process have been discussed. The review further highlights the roles and mechanisms of micro-organisms in the bioremediation of agricultural fields.

Estimation of heavy metal concentrations (Cd and Pb) in plant leaves using optimal spectral indicators and artificial neural networks

The necessity of continuously monitoring the agricultural products in terms of their health has enforced the development of rapid, low-cost, and non-destructive monitoring solutions. Heavy metal contamination of the plants is known as a source of health threats that are made by their proximities with pollutant soil, water, and air. In this paper, a method was proposed to measure lead (Pb) and cadmium (Cd) contamination of plant leaves through field spectrometry as a low-cost solution for continuous monitoring. The study area was Mahneshan county of Zanjan province in Iran with rich heavy metal mines that have more potential for plant contamination. At first, we collected different plant samples throughout the study area and measured the Pb and Cd concentrations using ICP-AES, in which we observed that the concentrations of Pb and Cd are in the range of 1.4 ~ 282.6 and 0.3 ~ 66.7 μgg-1, respectively, and then we tried to find the optimum estimator model through a multi-objective version of genetic algorithm (GA) optimization that finds simultaneously the structure of an artificial neural network and its input features. The features extracted from the raw spectrums have been collimated to be compatible with the Sentinel-2 multispectral bands for the possibility of further developments. The results demonstrate the efficiency of the optimum estimator model in estimation of the leaves' Pb and Cd contamination, irrespective of the plant type, which has reached the R2 of 0.99 and 0.85 for Pb and Cd, respectively. Additionally, the results suggested that the 783-, 842-, and 865-nm spectral bands, which are similar to the 7, 8, and 8a sentinel-2 spectral bands, are more efficient for this purpose.

Pine needles as urban atmospheric pollution indicators: Heavy metal concentrations and Pb isotopic source identification

Pine needles are reliable passive bio-samplers that can be used to monitor atmospheric pollution levels. This study applied Pb isotope and multivariate statistical analyses to pine needles to examine the characteristics, sources, and ecological risks of atmospheric heavy metal pollution in the cities of the middle reaches of the Yangtze River, China. The heavy metal concentrations were higher than those measured in pine needles elsewhere in the world. They were higher in the metropolitan city (Wuhan) than in the medium-sized city (Yichang) and lowest in the natural setting (Shennongjia Forestry District), which is consistent with trends in urbanization and industrialization. Principal component analysis grouped the metals into three main sets associated with industrial activities and traffic sources. The Pb composition determined the main anthropogenic Pb sources were vehicle exhaust and industrial activities related to the lead-zinc ore, only a few of which were coal combustion. Three risk assessment indexes (pollution load index, ecological risk index, and bioconcentration factor) suggest that atmospheric heavy metals in the study area pose moderate environmental and health risks.

Heavy metal accumulation characteristics and physiological response of Sabina chinensis and Platycladus orientalis to atmospheric pollution

Heavy metal (Cu, Mn, Zn, Pb, and Cd) concentrations were measured in the leaves of Sabina chinensis and Platycladus orientalis collected from urban, suburban, and rural sites in Tianjin, China. Photosynthetic pigment contents, reactive oxygen species content, malondialdehyde (MDA) content and antioxidant enzyme activity were investigated, providing physiological response parameters. Our comparison of the sites revealed that urbanization significantly influenced the heavy metal concentrations in both plant leaves. At the rural site, both plant leaves exhibited the lowest heavy metal accumulation. The highest Cu, Mn, and Zn concentrations were found in S. chinensis leaves from the urban site; the highest Pb and Cd concentrations were found in P. orientalis leaves from the urban site. These results indicate that the urban site contained larger heavy metal concentrations in the plant leaves that may reflect the anthropogenic emission gradient. It is also found that S. chinensis may be used to monitor airborne heavy metal pollution because it is highly quick response to heavy metals, while P. orientalis may be used for mitigation due to its high resistance. The results of this study can contribute to the development of monitoring and environmental management plans by providing information on sensitive and resistant tree species for city greening in North China.

Periodical and regional change of particulate matter and CO2 concentration in Misurata

Today, environmental pollution, air pollution in particular, is among the most important problems in the world. Air pollution, which has become a global issue, is estimated to cause the death of around 1 in 8 people worldwide. Due to the significance of air pollution, all components of air pollution are of great importance for human health, and thus the studies on air pollution are highly important, especially in areas with high population density. In this study, it was aimed to determine the regional and periodic change of CO₂ and particulate matter pollution in the city of Misurata, one of the important cities of Libya. The study was conducted in the city centre of Misurata, and the measurements were made once in every three days between November and February at 7 different locations selected in the city centre. As a result of the measurements made, the changes in the pollution parameters were evaluated on the basis of zones and months. As a result of the study, the cleanest areas were found to be the industrial area (B3) located in the east of the city and the zone (B4), where the Al-Swehli farm was located, while the dirtiest areas were found to be the main street (B1 and B2) in the city centre and the city centre, in general. In terms of months, the lowest CO₂ values were obtained in January, and the highest value was in February, whereas the lowest particulate matter values were obtained in January and the highest values in December.

The potential of using Cedrus atlantica as a biomonitor in the concentrations of Cr and Mn

Air pollution is becoming increasingly dangerous which is quite a significant issue of today's world, especially air pollution from heavy metal, whose emission increases with industrial and traffic activities. This is of great importance in terms of environmental pollution and human health. Heavy metals do not deteriorate and disappear easily on earth. They are liable to bioaccumulate within cells in organisms. Most of them demonstrate harmful effects in addition as a result of advanced accumulation, and thus they emerge as toxic and carcinogenic. Therefore, it is of great importance to observe the changes in heavy metal concentrations in the air. One of the most effective techniques for monitoring the change of heavy metal concentrations in the atmosphere is the use of annual rings of trees as biomonitors. In this study, in the annual rings of the Cedrus atlantica Manetti tree cut at the Kastamonu province at the end of 2019, the variation of the concentrations of some of the heavy metals most associated with traffic density was tried to be determined. Within the scope of the study, Cr and Mn concentration in the outer bark and the inner bark was compared with the direction and wood for the variation of heavy metal concentrations. Also, variance analysis and Duncan test were applied and evaluated. As a result of the study, while the highest values in many heavy metals are generally obtained in the outer bark, the transfer of metals in the wood is limited, and some heavy metal concentrations change significantly depending on the direction, especially in the wood. This change is related to the traffic density, so Cedrus atlantica Manetti annual rings are very suitable as biomonitors for air pollution control.

The usability of Cupressus arizonica annual rings in monitoring the changes in heavy metal concentration in air

Air pollution, which has been increasing in recent years, has reached significant dimensions and has become one of the most important agenda topics of present day. Among air pollution components, heavy metals are of particular importance, since they are not easily decomposed, they tend to bioaccumulate, and some of them have toxic or carcinogenic effects even at low concentrations. Therefore, it is an extremely important subject to monitor the changes in heavy metal concentrations found in air. The most preferred method in determining the changes in heavy metal concentrations in the atmosphere is the use of biomonitors. From past to present, trees have been good biomonitors in determining the increase in heavy metal concentrations in the atmosphere. Particularly, with the help of the annual growth rings of trees, vital information can be obtained on the changes in heavy metal concentrations in air. In this study, after the annual rings were determined on the log taken from the main body of the cypress (Cupressus arizonica) tree cut from the Kisla park located in Kastamonu province, the concentrations of Bi, Cd, and Ni in the outer bark, inner bark, and wood were compared in the inward-facing and road-facing parts of these sections. Also, the changes in heavy metal concentrations in the annual rings were evaluated on a yearly basis. As a result of the study, it was found that the element concentrations in the outer bark of the road-facing part were generally at a higher level, and that the changes in the elements on a yearly basis generally followed a fluctuating course, but there had been a general increase in the Cd and Ni concentrations in recent years.

Assessment of heavy metal contamination in herbal medicinal products consumed in the Iranian market

Herbal medicines have been reported to contain many contaminants that are potential harmful to health. These include heavy metals, such as lead (Pb), cadmium (Cd), arsenic (As), and mercury (Hg). Therefore, this study aimed to measure the levels of Pb, Cd, As, and Hg in several orally administered herbal products available in the Iranian market. Fifteen products labeled (A-O) of different brands from three different production batches (n = 45) were purchased from traditional herbal medicine factories in Iran. Each sample was digested with nitric acid by the wet digestion method, and the resultant solutions were used to determine the concentrations of Pb, Cd, As, and Hg. These measurements were performed using flame atomic absorption spectrometry, graphite furnace atomic absorption, or cold vapor atomic absorption. The lead, cadmium, arsenic, and mercury contents in the investigated samples did not show significant levels that may be associated with toxicity. All four metals were present at concentrations below the limits recommended by the WHO (World Health Organization), American Herbal Products Association (AHPA), and Canadian standard, but in several herbal products, the concentrations of these trace elements exceeded the Agency for Toxic Substances and Disease Registry (ATSDR). The concentrations of Pb, Cd, As, and Hg in commercially available herbal remedies were well below the acceptable intake recommended by global recommendations. Our findings revealed that at present, the amount of heavy metals in medicinal herbs processed at the level of supply by pharmacies licensed is favorable.

Application of artificial neural networks to predict the heavy metal contamination in the Bartin River

In this study, copper (Cu), iron (Fe), zinc (Zn), manganese (Mn), nickel (Ni), and lead (Pb) analyses were performed, and the results were modelled by artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). Samples were taken from 3 stations selected on the Bartin River for 1 year between December 2012 and December 2013. Radial basis neural network (RBANN), multilayer perceptron (MLP) neural networks models, and adaptive neuro-fuzzy inference system (ANFIS) were applied to the data in order to predict the heavy metal concentrations. As a result of the study, the RMSE and MAE values of all the heavy metal models were found to have very low error values during the test phase, and it was found that the models created using MLP had R² values higher than 0.77 during the test phase; the test phase R² values of the models using RBN method were found to be ranging between 0.773 and 0.989, and the test phase R² value of the ANFIS model was higher than 0.80. If sorted from the best model to the worst by taking the MAE and RMSE values into consideration based on the test evaluation results, according to the heavy metal types, where all of the MLP, RBN, and ANFIS models were generally approximate to each other, RBN was successful for Cu, Zn, and Mn, while MLP model was successful for Ni and ANFIS model for Fe and Pb. According to the results, it can be inferred that the heavy metal contents can be estimated approximately with artificial intelligence models and relatively easy-to-measure parameters; it will be possible to detect heavy metals which are harmful to the viability of the rivers, both quickly and economically.