Monitoring Of Heavy Metal Pollution Research Articles

Development of Monitoring System for Heavy Metal Pollution in Sea Water of Mangrove Wetland in Leizhou Peninsula

Mangrove is a wetland ecosystem with high productivity in tropical and subtropical regions, which is of great significance for maintaining ecological diversity and protecting wetlands. With the rapid development of urbanization and industrialization, human activities such as the use of agricultural fertilizers and pollutant discharge have brought a series of problems. A large number of heavy metal pollutants enter rivers, lakes, seas and soils in different ways, bringing heavy pressure to the restoration of the ecological environment. Leizhou Peninsula Mangrove Nature Reserve, as one of the largest nature reserves in Chinese Mainland, is highly valued. Aiming at the study of heavy metal pollution in Leizhou Peninsula mangrove wetland, this paper proposes a monitoring system for heavy metal pollution in seawater of mangrove wetland. Wireless packet switching technology based on Global System for Mobile Communications (GSM) system, which provides end-to-end and wide area wireless IP connection. The main function modules of the system include: data input, real-time display of monitoring data, data query, data statistics and analysis, decision-making and early warning, early warning information release, etc. Through this technology, real-time monitoring of heavy metal pollution in sea water of mangroves in Leizhou Peninsula can be realized, which can effectively solve the problem of mangrove protection and maintain the ecological environment.

Health Risk Assessment of Some Selected Heavy Metals in Agricultural Soils from Katsina State, North-Western Nigeria

This work contributes to the monitoring of heavy metal pollution of Agricultural soils, Katsina State Nigeria, using Atomic Absorption Spectrophotometry. The heavy metal contamination of the soil samples were analyzed based on the Geoaccumulation index (Igeo), enrichment factor (EF), contamination factor (CF), pollution load index (PLI) and potential ecological risk index (PERI). The health risks of the evaluated heavy metals were estimated using the Hazard Quotient (HQ) and Hazard Index (HI)) to evaluate the possible non-carcinogenic effect and the Incremental Lifetime Cancer Risk (ILCR) for the cancer risk to the population. The results of the study had revealed that in the soil samples all the evaluated heavy metals lie within acceptable limits as set by the regulatory agencies. The evaluated soil samples pollution indices had revealed that the I-geo values for the soil samples were within the range of unpolluted to moderate pollution. Also, the heavy metal enrichment factor (EF) value for the soil samples have indicated that only the heavy metal Fe showed significant enrichment, with the soil samples being moderately contaminated with Fe. The pollution load index (PLI) also indicated unpolluted to moderate pollution. With the potential ecological risk index (PERI) values presenting low ecological risks. The calculated non-cancer risk indices in both the children and adults population for all the heavy metals were less than 1. With the exception of the ILCR for the heavy metal Pb in children from Daura zone that was in limits that environmental and regulatory agencies considered as unacceptable risk, risk values for all the heavy metals falls within the range of the threshold of the safe limit and limits regarded as safe by the regulatory agencies (10-7 to 10-4). The results of pollution indices have indicated that the Agricultural soil samples have low contamination and low health risks by the heavy metals evaluated.

Overview assessment of risk evaluation and treatment technologies for heavy metal pollution of water and soil

Heavy metals are highly toxic elements which are persistent in the natural environment, resulting in magnification throughout the food chain, adversely affecting both human and environmental health. Consequently, heavy metal pollution has received widespread research attention. This review assesses the current progress in heavy metal pollution monitoring, management and mitigations, which show a lack of systematic criteria for risk evaluation. Risk assessment and multivariate analysis methods are also discussed. Assessment of risk evaluation and multivariate statistical analysis are the basic step for the treatment technologies choosing. The technique used is always site-specific, and it often combines different strategies. Only by comprehensively considering the contaminated time, the concentration and nature of the contaminant, the soil/water and site characteristics, the contaminant's availability, and the existence of specific regulations can appropriate restoration and treatment plans be formulated. Combinations of GIS and modeling appear to be most effective for analysis of heavy metal pollution risk. In recent years, many physico, chemical and bio technologies have been used to remove heavy metal pollution from water and soil, each having inherent advantages and limitations. So far, no single method is universally effective for the removal of all heavy metals. Combining different technologies can lead to greater efficiency and may provide a reasonable method to conduct inter-governmental, cross-border heavy-metal prevention and monitoring, for the control of anthropogenic pollution sources. Efficient and commercially viable scaled-up heavy metal treatment technologies will yield large benefits to human and environmental health, as well as economic output. This review provides an overview of the currently available methods, to inform researchers and other stakeholders in the prevention of heavy metal pollution of water and soil.

Five‐wheel framework for system‐based monitoring of heavy metal pollution in rivers

AbstractSectorial approach for monitoring heavy metal pollution in rivers has failed to report realistic pollution status and associated ecological and human health risks. The increasing spread of heavy metals from different sources and emerging risks to human and environmental health call for reexamining heavy metal pollution monitoring frameworks. Also, the sources, spread, and load of heavy metals in the environment have changed significantly over time, requiring consequent modification in the monitoring frameworks. Therefore, studies on heavy metal monitoring in rivers conducted in the last decade were evaluated for experimental designs, research frameworks, and data presentations. Most studies (∼99%) (i) lacked inclusiveness of all environmental compartments; (ii) focused on “one pollutant – one/two compartment” or sometimes “one pollutant – one compartment – one effect” approach; and (iii) remained “data‐rich but information poor.” An ecological approach with integrative system thinking is proposed to develop a holistic approach for monitoring river pollution. It is visualized that heavy metal monitoring, risk analyses, and water management must incorporate tracking pollutants in different environmental compartments of a river (water, sediment, and floodplain/bank soil) and consider correlating it with riverbank land use. The systems‐based pollution monitoring and assessment studies will reveal the critical factors that drive heavy metals pollutant movement in ecosystems and associated potential risks to the environment, wildlife, and humans. Also, water quality and pollution indexing tools would help better communicate complex pollution data and associated risks among all stakeholders. Therefore, integrating systems approaches in scientific‐ and policy‐based tools would help sustainably manage the health of rivers, wildlife, and humans.

Discussion on the Status and Development of Heavy Metal Pollution Monitoring in Soil

Discussion on the Status and Development of Heavy Metal Pollution Monitoring in Soil

Measuring heavy metal ions in water using nature existed microalgae as medium based on terahertz technology

Heavy metal pollution in water seriously affects human health. The disadvantages of traditional metal ion detection methods involve long and cumbersome chemical pretreatment in the early stage, and large volume of samples. In this study, microalgae were used as the medium, and terahertz spectroscopy technology was employed to collect the changes of material components in it, so as to deduce the types and concentrations of heavy metal pollution in water. Through the partial least square(PLS), we establish the prediction model of heavy metal concentration, and the results show that the best detection time for Pb2+ is 6 h and Ni2+ is 18 h. The principal component analysis(PCA) shows that β-carotene is the most affected substance. Afterward we collect five real surface waters in East China and verify that the judgment accuracy of Pb2+ and Ni2+ are 100% and 93.2% respectively. The results indicate that the time is shorter than the traditional pretreatment time from more than 20–6 h, the sample volume is reduced from 50 mL to 10 mL, the detection accuracy is improved from 10 ng/mL to 1 ng/mL. In a word, we provide a new fast and real-time method for biological monitoring of heavy metal pollution in water.

An innovative autonomous robotic system for on-site detection of heavy metal pollution plumes in surface water

Smart monitoring has been studied and developed in recent years to create faster, cheaper, and more user-friendly on-site methods. The present study describes an innovative technology for investigative monitoring of heavy metal pollution (Cu and Pb) in surface water. It is composed of an autonomous surface vehicle capable of semiautonomous driving and equipped with a microfluidic device for detection of heavy metals. Detection is based on the method of square wave anodic stripping voltammetry using carbon-based screen-printed electrodes (SPEs). The focus of this work was to validate the ability of the integrated system to perform on-site detection of heavy metal pollution plumes in river catchments. This scenario was simulated in laboratory experiments. The main performance characteristics of the system, which was evaluated based on ISO 15839 were measurement bias (Pb 75%, Cu 65%), reproducibility (in terms of relative standard deviation: Pb 11–18%, Cu 6–10%) and the limit of detection (4 µg/L for Pb and 7 µg/L for Cu). The lowest detectable change (LDC), which is an important performance characteristic for this application, was estimated to be 4–5 µg/L for Pb and 6–7 µg/L for Cu. The life span of an SPE averaged 39 measurements per day, which is considered sufficient for intended monitoring campaigns. This work demonstrated the suitability of the integrated system for on-site detection of Pb and Cu emissions from large and medium urban areas discharging into small water bodies.

Bee pollens as biological indicators: An ecological assessment of pollution in Northern Turkey via ICP-MS and XPS analyses.

In this study, pollens were collected from 25 different locations of Northern Turkey to investigate pollution monitoring. Surface chemistry of pollen samples was characterized by X-ray photoelectron spectroscopy (XPS). Then the concentrations of certain elements (Li, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Cd, Ba, and Pb) in pollen samples were determined by inductively coupled plasma mass spectrometry (ICP-MS) for the evaluation of environmental pollution. The levels of elements were detected in the following ranges (minimum-maximum, mg/kg dry pollen): Li (0.18-0.39), Al (24.98-308.04), V (6.18-98.58), Cr (1.05-6.81), Mn (13.85-95.91), Fe (52.20-326.26), Co (0.15-0.34), Ni (1.66-10.79), Cu (8.61-19.01), Zn (20.47-70.02), As (1.22-2.65), Se (0.39-0.67), Cd (0.05-0.74), Ba (0.73-16.30), and Pb (0.00-0.26). It has been concluded that there is a correlation between the pollen samples with high heavy metal concentrations and traffic density as these regions are closer to the road in the northern region. It is exposed to pollution from various sources such as intensified urbanization and tourism activities carried out on land and sea; industrial activities are increasing rapidly due to the opportunities offered by the coastal areas, sea transportation, and agricultural, domestic, and industrial pollution coming from the inner regions through rivers and streams. In this sense, pollens can be used as potential bio-indicators for monitoring heavy metal pollution and gives an idea about how we can use them for future assessing purposes.

Study on the Hyperspectral Retrieval and Ecological Risk Assessment of Soil Cr, Ni, Zn Heavy Metals in Tailings Area.

The large-scale rapid monitoring of heavy metal pollution has become a hot topic due to increasing contamination of Tailings soil by heavy metal. In order to explore the possibility of using soil spectrum to estimate the content of heavy metals in soil and realize the rapid monitoring of soil heavy metals in the Yangshanchong tailings area in Tongling, China. The spectral reflectance of soil and the content of heavy metals (Cr, Ni, Zn) in soil were determined. The optimal bands of Cr, Ni and Zn elements in soil appeared at 467nm, 467nm and 468nm respectively, and the maximum correlation coefficients were - 0.716, - 0.685 and - 0.630. The inversion model of element Cr constructed under the Reciprocal Transformation Second Derivative has a better effect, and its determination coefficient R2 is 0.613; It is better to construct the model of elements Ni and Zn in the form of Reciprocal Transformation First Derivative, and their determination coefficients R2 are 0.724 and 0.603, respectively. The results of the single factor index method showed that the pollution degree of heavy metal elements in the soil in the study area is Ni > Zn > Cr; the Nemerow comprehensive pollution index method showed that the three elements in the study area were polluted to varying degrees, and the comprehensive pollution index was in order Ni > Zn > Cr; Comprehensive potential ecological hazard index evaluation, the pollution degree and ecological risk of the study area were low.

Monitoring of Heavy Metal Pollution in Water and Sediments at the Mid-Black Sea Region by Using Passive Sampling Method Diffusive Gradients in Thin Films

Determining the potential bioavailability of heavy metals, evaluating according to adapted regulations is essential to efficiently conserve our coastal and estuarine waters. In this study, it is aimed to determine the industrial pollution and various other pollution sources that the Black Sea Basin is exposed to by using DGT (Diffusive Gradients in Thin Films) method and grab (manuel) sampling method in water and sediment and to evaluate the existing pollution according to quality standards. In Samsun, seasonal samples were collected from five different sampling stations, namely Akkiraz Stream, Hıdırellez Stream, Organized Industrial Zone (OIZ) Channel, Şabanoğlu Stream and Selyeri Stream, which are selected from Tekkeköy region where industry is intensively active. In order to determine the heavy metal content in both water and sediment samples, the DGT method was chosen for passive sampling and the grab sampling method was used for active sampling, and the efficiency of the methods was evaluated. According to the results of the study, the heavy metal concentration in grab sampling for water samples in descending order Al> Fe> Zn> Pb> Ni> Cu; In the samples taken with DGT, they are listed as Al> Fe> Zn> Cu> Ni> Pb. There were significant relationships between the total metal concentrations of sediment (Csed) and water (Csu) in grab sampling and metal concentrations sediment (Csed-DGT) and water (Csu-DGT) measured by DGT. It was found that the sensitivity and performance of sampling with DGT was 2-10 times higher compared to grab sampling. The high resolution in situ DGT technique for the assessment and management of the potential release risk of heavy metals at the water-sediment interface is a complementary method that contributes to the standard grab sampling method.

Analysis and Determination of Polyphenol and Iron Concentrations in Some Selected Seaweed Species using UV-Vis

Seaweeds readily absorb heavy metals that are present in their environment, because of this; they are an effective way of monitoring heavy metal pollution in an area. The metal that is absorbed can be damaging to the seaweed cell walls. Seaweeds have evolved over time to have excellent antioxidant systems to combat this damage. One antioxidant they produce is polyphenol, a chemical molecule containing many phenol rings that bind to metals and keep them from the damaging the cell walls. They have been shown to be linked to the health benefits of red wine, fruit and vegetables. Samples of different species of seaweed from the Bangor area were collected, processed and analysed for their iron and polyphenol concentrations. Samples were collected from multiple points along the Bangor coastline, they were dried and processed into a fine, dry powder. The iron concentrations were analysed by Atomic Absorption Spectroscopy after digestion by HNO3. Different species were analysed for the iron and polyphenol content. The whole of the algae was analysed, as well as the nodules and the rest (stipe and blades). The polyphenol concentrations were analysed by a colourimetric assay using the Ragan and Glombitza method and quantified by UV/Vis spectroscopy. Different species were tested in order to see if the concentrations of iron and polyphenol change between species. Different parts of the seaweed were also tested to see where the higher concentrations of the metals were located. Iron concentration statistically significantly changed between all species with the concentrations ranging from 58.0 ± 3.5 mg/Kg to 796.0 ± 10.6 mg/Kg. The Polyphenol concentration changed statistically significantly between some species, but statistically not significant between others. Polyphenol concentration ranged from 63.7 ± 0.3 mg (g dw)-1 to 202.1 ± 6.7 mg (g dw)-1.

Generation of a novel transgenic marine medaka (Oryzias melastigma) for highly sensitive detection of heavy metals in the environment

As typic priority pollutants in the marine environment, heavy metals can be accumulated in the human body leading to serious environmental and health problems. The metal regulatory elements (MREs) have been identified to be the main functional parts for the response to heavy metals. To develop a convenient biological monitoring tool for the detection of heavy metals in the oceans, we generated a transgenic marine medaka line Tg(OmMT: eGFP) with a truncated metallothionein promoter, which was only 193 bp and drove the expression of eGFP. After Tg(OmMT:eGFP) embryos were treated with four different heavy metals and different concentrations, the results showed that the expression level of eGFP was consistent with that of the endogenous mt. The transgenic embryos are very sensitive to Hg2+, and the fluorescence could be induced in the 0.0002 μM concentration, which is far lower than the primary water standard. The expression level of eGFP and mt showed a dose-dependent manner to heavy metals concentration. Taken together, the newly established marine medaka is a sensitive, efficient, and convenient tool for monitoring heavy metal pollution in the environment, especially seawater.

Rapid diagnosis of heavy metal pollution in lake sediments based on environmental magnetism and machine learning

Environmental magnetism in combination with machine learning can be used to monitor heavy metal pollution in sediments. Magnetic parameters and heavy metal concentrations of sediments from Chaohu Lake (China) were analyzed. The magnetic measurements, high- and low-temperature curves, and hysteresis loops showed the primary magnetic minerals were ferrimagnetic minerals in sediments. For most metals, their concentrations were highest during the wet season and lowest during the medium-water period. Cd, Hg, and Zn were moderately enriched and Cd and Hg posed a considerable ecological risk. A redundancy analysis indicated a relationship between physicochemical indexes and magnetic parameters and heavy metal concentrations. An artificial neural network (ANN) and support vector machine (SVM) were used to construct six models to predict the heavy metal concentrations and ecological risk index. The inclusion of both the physicochemical indexes and magnetic parameters as input factors in the models were significantly ameliorated the simulation accuracy for the majority of heavy metals. The training and test R, for Be, Fe, Pb, Zn, As, Cu, and Cr were > 0.8. The SVM showed better performance and hence it has potential for the efficient and economical long-term tracking and monitoring of heavy metal pollution in lake sediments.

Rapid monitoring of heavy metal pollution in lake water using nitrogen and phosphorus nutrients and physicochemical indicators by support vector machine

A novel method of predicting heavy metal concentration in lake water by support vector machine (SVM) model was developed, combined with low-cost, easy to obtain nutrients and physicochemical indicators as input variables. 115 surface water samples were collected from 23 sites in Chaohu Lake, China, during different hydrological periods. The particulate concentrations of heavy metals in water were much higher than the dissolved concentrations. According to Nemerow pollution index (Pi), pollution degrees by Fe, V, Mn and As ranged from heavy (2 ≤ Pi < 4) to serious (Pi ≥ 4). The concentrations of most heavy metals were the highest during the medium-water period and the lowest during the dry season. Non-metric Multidimensional Scaling Analysis confirmed heavy metal concentrations had slight spatial difference but relatively large seasonal variation. Redundancy Analysis indicated the close associations of heavy metals with nutrient and physicochemical indicators. When both nutrient and physicochemical indicators were used as input variables, the simulation effects for most elements in total and particulate were relatively better than those obtained using only nutrient or only physicochemical indicators. The simulation effects for As, Ba, Fe, Ti, V and Zn were generally good, based on their training R values of 0.847, 0.828, 0.856, 0.867, 0.817 and 0.893, respectively, as well as their test R values of 0.811, 0.836, 0.843, 0.873, 0.829 and 0.826, respectively; and meanwhile, in both the training and test stages, these metals also had relatively lower errors. The spatial distribution of heavy metals in Chaohu Lake was then predicted using the fully trained SVM models.

Heavy metal levels in cattle egrets (Bubulcus ibis) foraging in some abattoirs in Lagos State metropolis

BackgroundHeavy metal accumulation in the ecosystem constitutes a potential toxic effect which is hazardous to human health. Increasing environmental pollution has necessitated the use of cattle egrets to evaluate the levels of heavy metal contamination, to establish their use in biomonitoring of heavy metals and to provide data for monitoring pollution in the environment.ResultsThe present study assessed the utilization of Bubulcus ibis in monitoring pollution in five abattoirs, namely Agege, Bariga, Kara, Itire and Idi-Araba, all situated in Lagos State. The concentration of five (5) heavy metals, cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) was determined in the liver, muscle and feather of Bubulcus ibis using the atomic absorption spectrophotometer. The trend of metal accumulation was in the order: Zn > Cu > Pb > Cd > Ni for all the sampled tissues. The mean tissue concentrations of the metals were significantly different (p < 0.05) among the sites. The highest levels of metal concentration were reported in the liver in all the locations. Mean concentration of Cd in Kara (0.003 ± 0.00058) was significantly (p < 0.05) higher than those found at Agege (0.0013 ± 0.00058) and Idi-Araba (0.001 ± 0.001). A significant difference (p < 0.05) was also observed between the mean concentrations of Cu in Bariga (0.01 ± 0.001) and Idi-Araba (0.003 ± 0.001).ConclusionAll the studied heavy metals were present in the liver, muscle and feathers of the cattle egrets. The contamination levels were ascertained from the study which indicated that cattle egrets are useful in biomonitoring studies and the generated data will serve as baseline data which could be compared with data from other locations for monitoring heavy metal pollution.

Monitoring of heavy metal pollution in urban and rural environments across Pakistan using House crows (Corvus splendens) as bioindicator.

A widely distributed urban bird, the house crow (Corvus splendens), was used to assess bioavailable heavy metals in urban and rural environments across Pakistan. Bioaccumulation of arsenic (As), zinc (Zn), lead (Pb), cadmium (Cd), nickel (Ni), iron (Fe), manganese (Mn), chromium (Cr), and copper (Cu) was investigated in wing feathers of 96 crows collected from eight locations and categorized into four groups pertaining to their geographical and environmental similarities. Results revealed that the concentrations of Pb, Ni, Mn, Cu, and Cr were positively correlated and varied significantly among the four groups. Zn, Fe, Cr, and Cu regarded as industrial outputs, were observed in birds both in industrialized cities and in adjoining rural agricultural areas irrigated through the Indus Basin Irrigation System. Birds in both urban regions accrued Pb more than the metal toxicity thresholds for birds. The house crow was ranked in the middle on the metal accumulation levels in feathers between highly accumulating raptor and piscivore and less contaminated insectivore and granivore species in the studied areas,. This study suggests that the house crow is an efficient bioindicator and supports the feasibility of using feathers to discriminate the local pollution differences among terrestrial environments having different levels and kinds of anthropogenic activities.

On-site low-power sensing nodes for distributed monitoring of heavy metal ions in water

Heavy metal pollution in water environments poses a great threat to public health and to the ecological environment due to its high toxicity and non-degradability. However, many existing detection methods require laboratory-based bulky instruments and time-consuming manual operations. Although some on-site systems exist, they are difficult to deploy on a large scale owing to their large size and high cost. Here, we report a sensing node featuring low power consumption and low cost, achieved by integrating microsensor, microfluidic, and electronic modules into a compact size for automatic and scalable heavy metal pollution monitoring. Digital microfluidic and electrochemical sensing modules are integrated on a chip, thereby combining the procedures of sample pretreatment, electrochemical sensing, and waste removal for automatic and continuous monitoring. The feasibility of the platform is demonstrated by Pb2+ detection in tap water. With a 3500 mA·h battery, the compact sensing node could work for several years in principle. There is scope for further improvements to the system in terms of wider functionality and reductions in size, power consumption, and cost. The sensing node presented here is a strong candidate for distributed monitoring of water quality as an Internet-of-Things application.

Assessment of heavy metal concentrations in the muscles of ten commercial fish species from Lagos lagoon, NigeriaAssessment of heavy metal concentrations in the muscles of ten commercial fish species from Lagos lagoon, Nigeria

The study was undertaken to assess the concentration of five heavy metals (zinc (Zn), lead (Pb), copper (Cu), iron (Fe) and manganese (Mn)) in the muscles of Tilapia zilli, Hydrocynus fiscalis, Parapristipoma humile, Caranx hippo, Cynoglossusa caudatus, Chrysichthys nigrodigitatus, Letjanus sp, Portunus validus, Sardinella maderensis, and Sphyreana sp. The concentrations of heavy metals were measured by atomic absorption spectrophotometry after digestion of the samples. There were significant differences (P&lt;0.05) in the concentration of heavy metals in fish muscles. There was no specific pattern in the levels of heavy metals among the fish species. P. validus had the highest concentration of Zinc in the fish sampled with a mean value of 14.45mg/g while T. zilli had the lowest concentrations of Zn and Mn. Sphyreana sp had the highest concentrations of Lead and Copper and Manganese in the muscles. Iron concentration was highest in the muscle of S. maderensis. In this study, the overall average concentrations of metals in fish muscles were in the order of Zn&gt; Fe &gt; Pb&gt; Cu&gt; Mn. The values of Zn and Cu were within or lower than the acceptable limits FAO/WHO (Food and Agriculture Organization Of the United Nations/World Health Organization) for concentration of heavy metals in fish while levels of Pb, Fe and Mn in the muscles of the various fishes were beyond the safe limit in foods. Close monitoring of heavy metal pollution of Lagos Lagoon is strongly advocated, in view of possible risks to the health of consumers.

Monitoring of heavy metal pollution by using populus nigra and cedrus libani

Monitoring of heavy metal pollution by using populus nigra and cedrus libani

Use of benthic foraminifera as a proxy for monitoring heavy metal pollution in the Swarnamukhi estuary, southeast coast of India

Benthic foraminiferal assemblages were surveyed as potential indicators of heavy metal pollution of sediments from Swarnamukhi estuary, southeast India. Grain size analysis indicated that the sediments were deposited under low energy conditions. Results of assessment by factor analysis and hierarchical cluster analysis showed relations among the heavy metals. The sediment pollution assessment was carried out using the Enrichment Factor (EF), and Pollution Load Index (PLI). The results showed significant seasonal variation in heavy metal concentrations, and several metals (e.g. Fe, Cr, Zn, Pb and Cd) had high abundance in the sediments. A total of 53 benthic foraminiferal species belonging to 20 genera and 3 suborders were recorded in the sediments. The effect of heavy metal pollution on foraminifera's species diversity was assessed. The assemblage changes and test abnormalities in foraminiferal species appeared to be proxies for evaluating environmental stresses. • Distribution and mobility of heavy metals in sediments collected from Swarnamukhi estuary were assessed. • A total of 53 species, 20 genera and 3 suborders according to their distribution was summarized. • Benthic foraminifera was used as a bio-indicator to evaluate the heavy metal pollution from the study area. • Benthic foraminiferal species and shell abnormalities were identified.