Heavy Metal Pollution Research Articles

Usability of Robinia pseudoacacia in monitoring changes and reducing airborne palladium pollution

Palladium (Pd), whose use has been increasing in recent years, is one of the heavy metals that pose a danger to the environment and human health, and it is known that heavy metals can be extremely harmful when inhaled from the air and taken into the human body. Therefore, monitoring and reducing the change of Pd pollution in the air is very important. This study aimed to determine the usability of Robinia pseudoacacia, which is grown intensively in urban areas where heavy metal pollution may be high, to monitor and reduce the change in Pd pollution in the air. Within the scope of the study, changes in Pd concentration in Robinia pseudoacacia stem sections grown in Düzce, among the 5 most polluted cities in Europe, depending on organ, direction, and age range in the last 60 years, were evaluated. As a result, it was determined that Pd pollution in the region may have been released into nature through agricultural activities or transported from much more distant sources. It was also determined that the species is not a suitable biomonitor that can be used to monitor the change in Pd pollution. Still, it is an accumulator species that is extremely suitable for reducing Pd pollution.

Evaluation and risk assessment of heavy metals in wetland soil in the University of Lagos

A study was conducted to evaluate the concentration of heavy metals, and the physicochemical and microbiological properties of wetland soils at the University of Lagos. Soil samples were randomly collected from the Faculty of Science (FSC), Lagoon Front, and Distance Learning Institute areas at depths of 5 cm, 10 cm, 15 cm, and 20 cm using a soil auger. The samples were stored in sterile nylon bags, appropriately labelled, and transported to the University of Lagos Central Research Laboratory for chemical analysis. The physicochemical characteristics measured included soil pH, determined using a pH meter, and moisture content, assessed through the oven-drying method. Heavy metal concentrations were analyzed using an Atomic Absorption Spectrophotometer. Microbial population diversity was examined using the disc diffusion method. Statistical analysis was performed using SPSS version 20, and mean values were evaluated using Tukey’s multiple comparison test at a probability level of P < 0.05. The results revealed that soil pH ranged from 7.20 to 8.81, with the highest value (8.81) recorded near the Faculty of Science (FSC-3). Eight heavy metals, including Pb, Ni, Cr, Cd, Fe, Cu, Mn, and Zn, were analyzed. Lead concentrations ranged from 0.02 to 0.29 ppm, followed by nickel, which ranged from 0.01 to 0.13 ppm. Chromium ranged from 0.0 to 0.25 ppm, cadmium from 0.03 to 0.08 ppm, iron from 1.02 to 2.96 ppm, copper from 3.31 to 4.60 ppm, manganese from 3.31 to 5.16 ppm, and zinc from 1.67 to 9.17 ppm. Lead and zinc concentrations were found to be below the permissible limit at all locations, while chromium and cadmium were within permissible limits. However, Zn, Mn, Cu, Fe, and Ni exceeded the permissible limits. Correlation analysis revealed a significant correlation (P < 0.05) between Pb and Zn, likely due to effluents from human waste and seepage from nearby dumpsites into the lagoon, streams, or beaches. The isolated microbial flora included three bacterial genera, Bacillus megaterium, Bacillus spp, and Enterobacter spp, as well as four fungal genera, Aspergillus, Penicillium, Aspergillus flavus, and Fusarium. Bacterial counts were lower than fungal counts in polluted soils, likely due to the nutrient status of the soil. The isolates were found to be tolerant to slightly alkaline pH and heavy metal pollutants, with microbial variation attributed to the impact of pH and heavy metals on the microbial population.

Exploring Spatial Dynamics of Water Quality in a Tropical Lake Affected by Aquaculture

Lake Maninjau, like many surface water bodies worldwide, faces significant water pollution challenges due to extensive aquaculture activities, making it an ideal site to study the impact of fish farming on water quality, which has contributed to eutrophication and declining water quality. This study investigates the physicochemical parameters and pollution levels in the lake, aiming to provide insights into its environmental health. In August 2022, a comprehensive sampling campaign was undertaken at nine stations within the upper layers of open water and littoral zones of Lake Maninjau. In situ measurements, including temperature, dissolved oxygen, and pH, were conducted, accompanied by water sample collection for laboratory analysis of trace elements and heavy metals. Our study revealed notable variability in water parameters across different sites, with surface water layers exhibiting the greatest differences. While certain parameters such as temperature and conductivity remain relatively stable, pH levels show a decreasing trend with increasing water depth. Dissolved oxygen levels vary widely, while oxidation–reduction potential indicates water pollution, particularly in littoral zones. Potassium dominance within cations likely suggests anthropogenic influences, notably from aquaculture activities, that may also contribute to nutrient enrichment and heavy metal pollution. Elevated levels of total nitrogen and ammonia underscore the lake’s moderate pollution levels, with heavy metals such as mercury exceeding permissible limits, posing risks to aquatic life and human health.

Nymphaea lotus Distribution in Oguta Lake: Implications for Heavy Metal Pollution in Surface Water and Sediments

Water quality is increasingly deteriorating and has affected lakes, which are important sources of freshwater. Heavy metals are of great concern because they are mostly toxic and resistant to decomposition. Aquatic macrophytes serve as stable biological filters that purify water bodies by accumulating dissolved metals and toxins in their tissues. Given their ability to trap various toxic heavy metals, the macrophyte Nymphaea lotus, which is observed on the surface waters of Oguta Lake, was studied to estimate the concentrations of six heavy metals in the water, sediment, and macrophytes. This was achieved by studying the spatial and temporal distribution of Nymphaea lotus in the lake and analysing the concentrations of heavy metals in the surface water, macrophytes, and sediment samples. Descriptive statistics, exploratory data analysis, and correlation analysis were used to analyse data obtained. Results revealed that the population of Nymphaea lotus declines over time from June to November in all regions. Upstream had the highest concentration of macrophytes (64%), while the downstream area has the lowest (2%). The heavy metal concentrations in the three samples ranges from 0.16 mg/kg to 2.96 mg/kg in sediments and Nymphaea lotus, and from 0.16 mg/L to 2.16 mg/L in water, with lead showing the highest concentration across all sample type. This highlights heavy metal contamination in the lake. The sparsely populated Nymphaea lotus exhibits selective bioaccumulation of lead, mercury, and zinc, while it seems to exclude or inefficiently absorb arsenic and chromium. Correlation analysis suggests a close interdependence between the concentrations of metals in sediments, water, and macrophytes, with sediments playing a key role in both water contamination and macrophyte metal absorption. Corrective and preventive measures should be taken to restore the lake.

Heavy Metals Pollution Evaluation, Health Risk Assessment, and Source Identification in the Reservoirs, Northern Anhui Province, China

Heavy Metals Pollution Evaluation, Health Risk Assessment, and Source Identification in the Reservoirs, Northern Anhui Province, China

Enhancing the Phytoremediation of Heavy Metals by Plant Growth Promoting Rhizobacteria (PGPR) Consortium: A Narrative Review.

Heavy metal pollution has become a significant concern as the world continues to industrialize, urbanize, and modernize. Heavy metal pollutants impede the growth and metabolism of plants. The bioaccumulation of heavy metals in plants may create chlorophyll antagonism, oxidative stress, underdeveloped plant growth, and reduced photosynthetic system. Finding practical solutions to protect the environment and plants from the toxic effects of heavy metals is essential for long-term sustainable development. The direct use of suitable living plants for eliminating and degrading metal pollutants from ecosystems is known as phytoremediation. Phytoremediation is a novel and promising way to remove toxic heavy metals. Plant growth-promoting rhizobacteria (PGPR) can colonize plant roots and help promote their growth. Numerous variables, such as plant biomass yield, resistance to metal toxicity, and heavy metal solubility in the soil, affect the rate of phytoremediation. Phytoremediation using the PGPR consortium can speed up the process and increase the rate of heavy metal detoxification. The PGPR consortium has significantly increased the biological accumulation of various nutrients and heavy metals. This review sheds light on the mechanisms that allow plants to uptake and sequester toxic heavy metals to improve soil detoxification. The present review aids the understanding of eco-physiological mechanisms that drive plant-microbe interactions in the heavy metal-stressed environment.

Assessment of Heavy Metals in Tea Plantation Soil and Their Uptake by Tieguanyin Tea Leaves and Potential Health Risk Assessment in Anxi County in Southeast China

Evaluating heavy metal pollution in tea plantation soil and conducting potential health risk assessments are crucial for ensuring the safety of tea consumers. However, soil heavy metal pollution levels and dietary exposure risk remain poorly understood, and there is no consensus on how soil physicochemical properties affect heavy metal concentrations. In this study, seventy-three soil samples and corresponding tea leaves from main tea-producing regions in Anxi County were analyzed for arsenic (As), chromium (Cr), lead (Pb) and copper (Cu) concentrations. The results showed that mean concentrations of As, Cr, Cu and Pb in the soil did not exceed respective risk screening values in China (GB 15618-2018). The concentrations of As, Cr, Cu and Pb in the tea leaves were within limiting values of the Chinese National Food Safety Standard, and the bioaccumulation factor of heavy metals in descending order was Cu > Pb > As > Cr. The hazard index values of heavy metals indicated no potential human health risk. Soil pH, EAl, EA and AP were the main controlling factors for heavy metal in soil and tea leaves. Cu and Pb concentrations in tea leaves were positively correlated with soil Cu and Pb concentrations. These results provide a scientific basis for effective monitoring and management in tea plantations and for controlling potential risks in tea leaves.

Spatial analysis and soft computational modeling for hazard assessment of potential toxic elements in potable groundwater

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L−1) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

Spectral Variations of Reclamation Vegetation in Rare Earth Mining Areas Using Continuous–Discrete Wavelets and Their Impact on Chlorophyll Estimation

Ion-adsorption rare earth mining areas are primarily situated in the hilly regions of southern China. However, mining activities have led to extensive deforestation of the original vegetation. The reclamation vegetation planted for ecological restoration faces significant challenges in surviving under environmental stresses, including heavy metal pollution, ammonia nitrogen contamination, and soil drought. To rapidly and accurately monitor the growth of reclamation vegetation, this study investigates the spectral variations and their impact on the accuracy of chlorophyll estimation, utilizing hyperspectral data and relative chlorophyll content (SPAD). Specifically, continuous–discrete wavelet transforms were applied, along with the original spectra and first derivative spectra, to enhance spectral anomalies in the reclamation vegetation and identify chlorophyll-sensitive spectral features. Additionally, multiple linear stepwise regression and backpropagation neural network models were employed to estimate chlorophyll content. The results revealed the following: (1) the d5 and d6 scales of the discrete wavelet effectively highlighted spectral anomalies in the reclamation vegetation; (2) Salix japonica (Salix fragilis L.), among typical reclamation species, exhibited poor adaptability to the environmental conditions of the rare earth mining area; (3) the backpropagation neural network model demonstrated superior performance in chlorophyll estimation, with the spectral features Fir, Fir_d4, Fir_d5, and Fir_d6 significantly enhancing the accuracy of the model, achieving an R2 of 0.93 for Photinia glabra (Photinia glabra (Thunb.) Maxim.). The application of continuous–discrete wavelet transforms to hyperspectral data significantly improves the precision of chlorophyll estimation, underscoring the potential of this method for the rapid monitoring of reclamation vegetation growth.

Microbial remediation of heavy metal-polluted water

Heavy metal pollution in water has become a global environmental problem, threatening aquatic ecosystems and human health. Physical and chemical methods can effectively remove heavy metal pollutants, while their applications are limited due to the high costs, complex operation, and susceptibility to secondary pollution. Bioremediation is the most promising method for eliminating toxic pollutants. Microorganisms including bacteria, fungi, and algae can convert toxic heavy metals into less toxic forms, which has become an effective and environmentally friendly solution for the remediation of heavy metal pollution in water environments. This paper expounds the toxicity and mechanism of heavy metal pollution, microbial remediation mechanisms, and primary microbial remediation strategies, providing a reference for the removal or reduction of metal pollutants in water environments as well as the development of related technologies.

Surface display and application of cadmium-binding protein CADR on the cell wall of Chlamydomonas reinhardtii

Algae has been proven to have the potential to be efficient biosorbents in the detection and remediation of heavy metal pollution such as cadmium in the environment. This study aims to enhance the cadmium adsorption capacity of Chlamydomonas reinhardtii by expressing the cadmium-binding protein CADR on the cell wall by the surface display technology. Firstly, the golden gate technique was employed to construct the transformation vector PET-X-CADR, which anchored CADR to the cell wall with the cell wall protein GP1. The high-throughput screening with the fluorescence signal of the fusion tag YFP resulted in three engineered algal strains with high expression of CADR on the cell wall. Physiological experiments demonstrated that the CADR displayed on the cell wall did not affect the growth of the engineered algal strains exposed to cadmium with the concentration below 200 μmol/L. In the presence of 200 μmol/L cadmium, the growth rates of CADR-engineered algal strains were three times as that of the wild-type, indicating stronger tolerance of the CADR-engineered algae to cadmium. The protein lyase GLE released during the mating of Chlamydomonas was used to isolate the cell walls of wild-type and engineered strains, the cadmium content of which was compared. The results showed that the cell wall of the engineered strain exhibited an increase of 33% in cadmium adsorption capacity. This study gives insights into the application of algae in the management of cadmium pollution in the environment, especially in the recycling of heavy metals from the environment.

Endophytic Bacteria Improve Bio- and Phytoremediation of Heavy Metals

Currently, the problem of heavy metal pollution in China is becoming increasingly serious, which poses grave threats to the environment and human health. Owing to the non-biodegradability and toxicity of heavy metals, a more sustainable and ecological approach to remediate heavy metal pollution has always been a focus of attention for environmental researchers. In recent years, many scientists have found that phytoremediation aided by endophytes has high potential to remediate heavy metals owing to its low cost, effectiveness, environmental friendliness, and sustainability compared with physical and chemical methods. Indeed, the mechanism of interaction between endophytes, plants, and heavy metals in the soil is pivotal for plants to tolerate metal toxicity and thrive. In this review, we focus on the mechanism of how endophytic bacteria resist heavy metals, and the direct and indirect mechanisms employed by endophytic bacteria to promote the growth of plants and enhance phytoextraction and phytostabilization. Moreover, we also discuss the application of combinations of endophytic bacteria and plants that have been used to remediate heavy metal pollution. Finally, it is pointed out that although there have been many studies on phytoremediation systems that have been assisted by endophytes, large-scale field trials are important to deliver “real” results to evaluate and improve phytoremediation assisted with microorganisms in polluted natural environments.

Heavy metals in roadside soil along an expressway connecting two megacities in China: Accumulation characteristics, sources and influencing factors.

Transportation is widely recognized as a significant contributor to heavy metal (HM) pollution in roadside soils. A better understanding of HM pollution in soils near expressways is crucial, particularly given the rapid expansion of expressway transportation in China in recent years. In this study, 329 roadside topsoil samples were collected along the Beijing-Tianjin Expressway, which connects two megacities in China. Chemical analysis showed that HM concentrations in the soil samples were generally below national limits. The mean pollution index (Pi) values for As, Cr, Cu, Ni, Pb, and Zn ranged from 0.94 to 1.01, while Cd and Hg exhibited slightly higher mean Pi values of 1.19 and 1.13, respectively. The Nemerow integrated pollution index values for all samples ranged from 0.71 to 4.97, with a mean of 1.26. This suggests a slight enrichment of HM above natural background levels, especially for Cd and Hg. Source apportionment using positive matrix factorization revealed that natural sources contributed the most to soil HMs (64.51 %), followed by agricultural sources (19.15 %), traffic sources (9.77 %), and industrial sources (6.57 %). The Shapley additive explanation analysis, based on the random forest model, identified soil organic carbon, deep soil HM content, altitude, total soil K2O, urbanization composite impact index, and total soil P as primary influencing factors. This indicates that the impact of transportation on roadside soils along the Beijing-Tianjin Expressway is currently relatively limited. The prominent influence of soil properties and altitude underscored the importance of "transport" and "receptor" in the soil HMs accumulation process at the local scale. These findings provide critical data and a scientific basis for decision-makers to develop policies for expressway design and roadside soil protection.

The Impact of Heavy Metal Accumulation on Agricultural Soils and Its Mitigation

Heavy metal contamination in various fields such as agricultural soils create severe global challenges affecting crop health, productivity, and overall ecosystem stability. This review investigates the source effects of heavy metals, which initially accumulate due to industrial activities and chemicals used during farming. The excessive presence of these metals can disrupt normal plant metabolism and reduce their growth. Furthermore, these metals can penetrate the food chain, posing serious health risks to humans and animals. Recent advancements in mitigating heavy metal pollution have been found, such as phytoremediation and biotechnological innovations offering promising solutions. Also, sustainable approaches utilizing microbial enzymes, microalgae, and bio-char-based technologies have shown high efficiency in removing heavy metals from contaminated environments. Further biosensors for detecting metal contamination provide sensitive, portable, and cost-effective alternatives. Overall, this review emphasizes the urgent need for awareness and continued research.

Trends and risk assessment of heavy metals in the surface sediments of river-connected lakes: A case study of Dongting Lake

This study analyzed the spatiotemporal distribution characteristics, ecological risks, biological toxicity, and sources of Cu, Zn, Pb, Cd, Hg, and As in the surface sediments of Dongting Lake, as well as the response of benthic macroinvertebrates to these pollutants. Among the three lake regions, the concentration of Cu, Zn, Pb, Cd, and As fell in the order of South Dongting Lake (SD) > East Dongting Lake (ED) > West Dongting Lake (WD), whereas the concentration of Hg fell in the order of WD > SD > ED. The concentrations of Cu, Zn, Pb, and As were 1.69–2.02 times the background values recorded in 1986, whereas the concentrations of Cd and Hg were 8.97 and 5.32 times the background values, respectively. The ecological risk was low for Cu, Zn, Pb, As but high for Hg and Cd. For Dongting Lake in aggregate, the heavy metals caused considerable ecological risk and high biotoxicity, although the situation was improving in recent years. Cd, As, Cu, Pb, Hg were mainly from agricultural sources, mining sources, tire wear and agricultural sources, industrial smelting and mining sources, industrial processing and smelting sources, respectively, and Zn was from mixed sources. A total of 66 species of benthic macroinvertebrates were identified from the sediments. From 2018 to 2022, the dominant benthic macroinvertebrates gradually shifted from the pollution-resistant in Tubificidae to those in Gammarus, Bellamya, Valvatidae, etc. Oligochaetes and Stictochironomus spp. exhibited extremely high response to heavy metals and could serve as indicator organisms of heavy metal pollution.

Assessment of microplastic and heavy metal pollution in agricultural soils of Ernakulam District, Kerala, India.

Microplastics (MPs) and heavy metal pollution pose significant environmental threat, potentially leading to agroecosystem toxicity and jeopardizing food security. Therefore, this study aims to evaluate the abundance and risk assessment of these pollutants in five different farmlands of Ernakulam district, India. Results showed that MPs content in agricultural fields near commercialized areas such as Kakkanad Nedungapuzha, Nedumbassery, and Kadamakuddy was dominant compared to Nechoor, a rural area. The average microplastic abundance was found to be 45.6 ± 26.4 items kg⁻1 dw. Polypropylene (PP) and polyethylene (PE) were the dominant polymers found in the soil samples, constituting 45% and 25% of the microplastic content, respectively. The pollution load index of MPs indicates that the sampling sites are considered to be polluted as PLI > 1 with hazard level I. The heavy metal pollution status follows the order: Cu (80.3 to 724mg/kg) > Zn (77 to 543.5mg/kg) > Cr (171.65 to 334.65mg/kg) > As (10.25 to 79.5mg/kg) > Pb (2.05 to 30.3mg/kg) > Cd (0.3 to 14.35mg/kg). Calculated pollution load index (PLI) geo-accumulation index (Igeo), ecological risk assessment values indicate that commercialized regions exhibit high levels of trace metals, namely Cu, Zn, As, Cd, and Cr, posing a significant concern for the agricultural ecosystem. Our results indicate heightened microplastics and heavy metals prevalence in farmlands adjacent to commercial zones, necessitating immediate preventive action to mitigate increasing concentrations.

Nanoparticle-based Biosensors for Detection of Heavy Metal Ions

Heavy metal pollution is one of the most serious environmental problems in the world. Many efforts have been made to develop biosensors for monitoring heavy metals in the environment. Development of nanoparticle-based biosensors is the most effective way to solve this problem. This review presents the latest technology of nanoparticle-based biosensors for environment monitoring to detect heavy metal ions, which are magnetic chitosan biosensor, colorimetric biosensor, and electrochemical biosensor. Magnetic chitosan biosensor acts as a nanoabsorbent, which can easily detect and extract poisonous heavy metal ions such as lead ions and copper ions. There are several methods to prepare the chitosan based on the nanoparticle, which are cross-linking, co-precipitation, multi-cyanoguanidine, and covalent binding method. In colorimetric biosensor, gold and silver nanoparticles are commonly used to detect the lead and mercury ions. In addition, this biosensor is very sensitive, fast and selective to detect metal ions based on the color change of the solution mixture. Meanwhile, electrochemical biosensor is widely used to detect heavy metal ions due to a simple and rapid process, easy, convenient and inexpensive. This biosensor is focused on the surface area, which leads to significant improvement in the performance of devices in terms of sensitivity. The wide surface area can affect the performance of the biosensor due to a limited space for operation of electrode. Therefore, reduced graphene oxide is a suitable material for making the electrochemical biosensor due to a wide surface area, good conductivity and high mechanical strength. In conclusion, these three technologies have their own advantages in making a very useful biosensor in the detection of heavy metal ions.

Effects of nickel, lead, and copper stress on the growth and biochemical responses of Aegilops tauschii seedlings

Heavy metal pollution causes severe abiotic stress in cereal crops around the world. This study investigated the effects of different concentrations (0, 100, 200, and 300 mg·kg–1) of nickel, lead, and copper stress on the growth and biochemical responses of Aegilops tauschii seedlings, to provide a reference for research on the mechanism of invasion and screening potential sources of wheat tolerance genes. The results showed that nickel, lead, and copper stress caused a significant decrease in the contents of chlorophyll a, chlorophyll b, and chlorophyll (a + b) in A. tauschii, thereby inhibiting photosynthesis to different degrees and hindering seedling growth, which was reflected in significant reductions in plant height and root length, with the most notable effect observed under stress by 300 mg·kg–1 lead. As the concentration of heavy metals increased, the activities of antioxidant enzymes (SOD, POD, and APX), non-enzymatic antioxidants (GSH and AsA), and the contents of osmotic regulatory substances (proline and soluble proteins) in A. tauschii significantly increased. Additionally, heavy metal stress increased H2O2 and TBARS levels. However, when the nickel, lead, and copper concentrations reached 300 mg·kg–1, no significant differences were found in H2O2 or TBARS levels compared to those in the CK group. To summarize, A. tauschii can mitigate the accumulation of ROS and membrane lipid peroxidation caused by heavy metal stress through self-regulation, thus exhibiting a certain degree of tolerance to stress caused by different concentrations of nickel, lead, and copper. Finally, the evaluation using the membership function method revealed that among the three heavy metals, A. tauschii exhibited the strongest adaptation to Cu, followed by Ni and Pb.

Biological two-stage treatment technology for mitigating mining-related heavy metal pollution in Georgian rivers

ObjectivesThe study aimed to investigate heavy metal contamination (copper, arsenic, manganese) in Georgian rivers affected by mining and develop a two-stage water purification technology using Spirulina (Arthrospira platensis) and trehalose lipid (TRL). This technology offers a sustainable and efficient solution to mitigate environmental and health hazards from mining-related pollution, improving river ecosystems and public health.Data DescriptionThis study examines the current state of the Kvirila, Lukhuni, Kazretula, and Mashavera rivers in terms of heavy metal pollution. Data were collected from field application of a two-stage purification process. Initial assessments showed heavy metal concentrations exceeding local regulatory limits (საქართველოს საკანონმდებლო მაცნე. გარემოსდაცვითი ტექნიკური რეგლამენტების დამტკიცების თაობაზე. Environmental Technical Regulations Approval. www.matsne.gov.ge/en/document/view/2196792?publication=0&scroll=0. Accessed 22 Aug 2024.). The purification process involved a 72-h incubation in a primary tank, followed by membrane filtration and the addition of biomass with trehalose lipid (TRL) in a secondary tank. Post-treatment data revealed significant reductions in manganese and copper concentrations, bringing them below permissible thresholds. These data highlight the effectiveness of the two-stage purification technology in removing heavy metal contaminants from water sources impacted by industrial pollution. The findings demonstrate the potential of this technology to improve sustainable water management practices and provide scalable solutions for communities facing similar water quality challenges.

Accumulation of heavy metals (Cr, Cu, As, Cd, Pb, Zn, Fe, Ni, Co) in the water, soil, and plants collected from Edayar Region, Ernakulam, Kerala, India

The accumulation of heavy metals in the environment is a significant concern due to their potential toxicity and persistence. This study investigates the levels of heavy metal contamination in the water, soil, and plants of the Edayar region in Ernakulam, Kerala, India. The region has experienced industrialization and urbanization, leading to concerns about heavy metal pollution. The study aims to assess the concentrations of chromium (Cr), copper (Cu), arsenic (As), cadmium (Cd), lead (Pb), zinc (Zn), iron (Fe), nickel (Ni), and cobalt (Co) in water, soil, aquatic and terrestrial plants. Samples were collected from various locations within the Edayar region, and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was conducted to quantify heavy metal concentrations. The findings of this study will contribute to the assessment of heavy metal pollution in the Edayar region. Plants with a high diversity index were taken for analysis from both aquatic and terrestrial habitats. Scoparia dulcis L. seems to specialize in metal accumulation, possibly for protective purposes. Synedrella nodiflora Gaertn demonstrates adaptability to metal-rich environments through robust metal uptake and tolerance mechanisms. Alternanthera philoxeroides (Mart.) Griseb, on the other hand, appears to have developed mechanisms to manage heavy metal exposure. The results indicate significant levels of heavy metal contamination across all samples, with the highest concentrations detected in soil, followed by water and plants. Chromium and lead levels in soil exceeded the permissible limits set by international standards, posing potential risks to human health and the ecosystem. The accumulation patterns in plants varied, with higher bioaccumulation factors observed for zinc and copper, suggesting their preferential uptake. This study highlights the urgent need for remediation strategies and continuous monitoring to mitigate the impact of heavy metal pollution in the Edayar region. The results will help in understanding the environmental impact of human activities.