Mining activities in the Chini Lake catchment area have been extensive for several years, contributing to acid mine drainage (AMD) events with high concentrations of iron (Fe) and other heavy metals impacting the surface water. However, during the restriction period due to the COVID-19 outbreak, anthropogenic activities have been suspended, which clearly shows a good opportunity for a better environment. Therefore, we aimed to analyze the variation of AMD-associated water pollution in three main zones of the Chini Lake catchment area using Sentinel-2 data for the periods pre-movement control order (MCO), during MCO, and post-MCO from 2019 to 2021. These three zones were chosen due to their proximity to mining areas: zone 1 in the northeastern part, zone 2 in the southeastern part, and zone 3 in the southern part of the Chini Lake area. The acid mine water index (AMWI) was a specific index used to estimate acid mine water. The AMWI values from Sentinel-2 images exhibited that the mean AMWI values in all zones during the MCO period decreased by 14% compared with the pre-MCO period. The spatiotemporal analysis found that the highest polluted zones were recorded in zone 1, followed by zone 3 and zone 2. As compared with during the MCO period, the maximum percentage of increment during post-MCO in all zones was up to 25%. The loosened restriction policy has resulted in more AMD flowing into surface water and increased pollution in Chini Lake. As a whole, our outputs revealed that Sentinel-2 data had a major potential for assessing the AMD-associated pollution of water.
Recent increase in awareness of the extent of microplastic contamination in marine and freshwater systems has heightened concerns over the ecological and human health risks of this ubiquitous material. Assessing risks posed by microplastic in freshwater systems requires sampling to establish contamination levels, but standard sampling protocols have yet to be established. An important question is whether sampling and assessment should focus on microplastic concentrations in the water or the amount deposited on the bed. On three dates, five replicated water and bed sediment samples were collected from each of the eight sites along the upper reach of the Semenyih River, Malaysia. Microplastics were found in all 160 samples, with mean concentrations of 3.12 ± 2.49 particles/L in river water and 6027.39 ± 16,585.87 particles/m2 deposited on the surface of riverbed sediments. Fibres were the dominant type of microplastic in all samples, but fragments made up a greater proportion of the material on the bed than in the water. Within-site variability in microplastic abundance was high for both water and bed sediments, and very often greater than between-site variability. Patterns suggest that microplastic accumulation on the bed is spatially variable, and single samples are therefore inadequate for assessing bed contamination levels at a site. Sites with the highest mean concentrations in samples of water were not those with the highest concentrations on the bed, indicating that monitoring based only on water samples may not provide a good picture of either relative or absolute bed contamination levels, nor the risks posed to benthic organisms.
Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (Igeo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using Igeo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions.
Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.
Organic pollution continues to be an important worldwide obstacle for tackling health and environmental concerns that require ongoing and prompt response. To identify the LAB content levels as molecular indicators for sewage pollution, surface sediments had obtained from the South region of Malaysia. The origins of the LABs were identified using gas chromatography-mass spectrometry (GC-MS). ANOVA and a Pearson correlation coefficient at p
The humidity sensing characteristics of different sensing materials are important properties in order to monitor different products or events in a wide range of industrial sectors, research and development laboratories as well as daily life. The primary aim of this study is to compare the sensing characteristics, including impedance or resistance, capacitance, hysteresis, recovery and response times, and stability with respect to relative humidity, frequency, and temperature, of different materials. Various materials, including ceramics, semiconductors, and polymers, used for sensing relative humidity have been reviewed. Correlations of the different electrical characteristics of different doped sensor materials as the most unique feature of a material have been noted. The electrical properties of different sensor materials are found to change significantly with the morphological changes, doping concentration of different materials and film thickness of the substrate. Various applications and scopes are pointed out in the review article. We extensively reviewed almost all main kinds of relative humidity sensors and how their electrical characteristics vary with different doping concentrations, film thickness and basic sensing materials. Based on statistical tests, the zinc oxide-based sensing material is best for humidity sensor design since it shows extremely low hysteresis loss, minimum response and recovery times and excellent stability.
Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes.
Pristine tropical river systems are coming under increasing pressure from the development of economic resources such as forestry and mining for valuable elements. The Lebir catchment, north eastern Malaysia, is now under development as a result of unregulated tree felling and mining for essential and rare metals. Two sediment cores, one in the upstream reaches and the other from the downstream reaches, were taken from flood prone area of the Lebir River, Malaysia, and analysed for their elemental composition by XRF, specifically Al, Si, Fe, Ca, K, Mg, Mn, V, Cu, Ni, Pb, Cr, Zn, As, Th and U. Activities of fallout radionuclides, 137Cs and 210Pb were also determined to from a geochronological context. The elemental concentrations in the soils were assessed in terms of their enrichment factor and Si, Ca, K, Mg, Mn, V, Cu, Ni and Zn were found not to be enriched, whereas As, Th and U had elevated enrichment factors. The Th and U were particularly enriched in the downstream core indicating inputs from a tributary that drains a catchment with known deposits of Th and possibly U. The results suggest that the growth in economic development is fostering the transport of contaminants by the major rivers which, in turn, is contaminating the riverine floodplains. This points to the need for a more integrated and holistic approach to river basin management to maintain the environmental quality of these fragile aquatic systems.
Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
Airborne Microplastics (MPs), an emerging environmental issue, have gained recent attention due to their newfound presence in indoor environments. Utilizing the Web of Science database for literature collection, the paper presents a comprehensive review of airborne MPs including emission sources, assessment methods, exposure risks, and mitigation strategies. This review delves into the diverse sources and mechanisms influencing indoor airborne MP pollution, underscoring the complex interplay between human activities, ventilation systems, and the characteristics of indoor environments. Major sources include the abrasion of synthetic textiles and the deterioration of flooring materials, with factors like carpeting, airflow, and ventilation significantly impacting MP levels. Human activities, such as increased movement in indoor spaces and the intensive use of plastic-based personal protective equipment (PPE) post-pandemic, notably elevate indoor MP concentrations. The potential health impacts of airborne MPs are increasingly concerning, with evidence suggesting their role in respiratory, immune, and nervous system diseases. Despite this, there is a scarcity of information on MPs in diverse indoor environments and the inhalation risks associated with the frequent use of PPE. This review also stresses the importance of developing effective strategies to reduce MP emissions, such as employing HEPA-filtered vacuums, minimizing the use of synthetic textiles, and enhancing indoor ventilation. Several future research directions were proposed, including detailed temporal analyses of indoor MP levels, interactions of MP with other atmospheric pollutants, the transport dynamics of inhalable MPs (≤10 μm), and comprehensive human exposure risk assessments.
Owing to a wide range of advantages, such as stability, non-invasiveness, and ease of sampling, hair has been used progressively for comprehensive biomonitoring of organic pollutants for the last three decades. This has led to the development of new analytical and multi-class analysis methods for the assessment of a broad range of organic pollutants in various population groups, ranging from small-scale studies to advanced studies with a large number of participants based on different exposure settings. This meta-analysis summarizes the existing literature on the assessment of organic pollutants in hair in terms of residue levels, the correlation of hair residue levels with those of other biological matrices and socio-demographic factors, the reliability of hair versus other biomatrices for exposure assessment, the use of segmental hair analysis for chronic exposure evaluation and the effect of external contamination on hair residue levels. Significantly high concentrations of organic pollutants such as pesticides, flame retardants, polychlorinated biphenyls and polycyclic aromatic hydrocarbon were reported in human hair samples from different regions and under different exposure settings. Similarly, high concentrations of pesticides (from agricultural activities), flame retardants (E-waste dismantling activities), dioxins and furans were observed in various occupational settings. Moreover, significant correlations (p
The Jakarta Bay is the estuary for thirteen rivers that flow through densely populated and industrialized upstream regions. This condition has the potential to pollute the Jakarta Bay with microplastics that are transported from the upstream river. Meanwhile, people, particularly fishermen, continue to use Jakarta Bay for fishing and aquaculture. This study examined microplastics (MP) abundance in the whole tissues of green mussels (Perna viridis) grown in Jakarta Bay, Indonesia, and their health risks. MP was identified in all 120 green mussels, with fiber > film > fragment being the most common kinds. The abundance of fiber was 19 items/g of tissue, whereas the abundances of fragments and film were 14.5 items/g and 15 item/g, respectively. Fourier transform infrared spectroscopy tests on MP from the tissues of green mussels showed that there were 12 different types of MP polymers. The estimated amount of MP that humans consume each year varied from 29,120 MP items/year to 218,400 MP items/year for different age groups. Based on the total mean number of MP found in the tissues of green mussels and the amount of shellfish consumed per person in Indonesia, it was estimated that people ate 775,180 MP through shellfish each year.
The Damoh district, which is located in the central India and characterized by limestone, shales, and sandstone compact rock. The district has been facing groundwater development challenges and problems for several decades. To facilitate groundwater management, it is crucial to monitoring and planning based on geology, slope, relief, land use, geomorphology, and the types of the basaltic aquifer in the drought-groundwater deficit area. Moreover, the majority of farmers in the area are heavily dependent on groundwater for their crops. Therefore, delineation of groundwater potential zones (GPZ) is essential, which is defined based on various thematic layers, including geology, geomorphology, slope, aspect, drainage density, lineament density, topographic wetness index (TWI), topographic ruggedness index (TRI), and land use/land cover (LULC). The processing and analysis of this information were carried out using Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) methods. The validity of the results was trained and tested using Receiver Operating Characteristic (ROC) curves, which showed training and testing accuracies of 0.713 and 0.701, respectively. The GPZ map was classified into five classes such as very high, high, moderate, low, and very low. The study revealed that approximately 45% of the area falls under the moderate GPZ, while only 30% of the region is classified as having a high GPZ. The area receives high rainfall but has very high surface runoff due to no proper developed soil and lack of water conservation structures. Every summer season show a declined groundwater level. In this context, results of study area are useful to maintain the groundwater under climate change and summer season. The GPZ map plays an important role in implementing artificial recharge structures (ARS), such as percolation ponds, tube wells, bore wells, cement nala bunds (CNBs), continuous contour trenching (CCTs), and others for development of ground level. This study is significant for developing sustainable groundwater management policies in semi-arid regions, that are experiencing climate change. Proper groundwater potential mapping and watershed development policies can help mitigate the effects of drought, climate change, and water scarcity, while preserving the ecosystem in the Limestone, Shales, and Sandstone compact rock region. The results of this study are essential for farmers, regional planners, policy-makers, climate change experts, and local governments, enabling them to understand the groundwater development possibilities in the study area.
Microplastics (MPs) occurrence in farmed aquatic organisms has already been the prime priority of researchers due to the food security concerns for human consumption. A number of commercially important aquaculture systems have already been investigated for MPs pollution but the mud crab (Scylla sp.) aquaculture system has not been investigated yet even though it is a highly demanded commercial species globally. This study reported the MPs pollution in the mud crab (Scylla sp.) aquaculture system for the first time. Three different stations of the selected aquafarm were sampled for water and sediment samples and MPs particles in the samples were isolated by the gravimetric analysis (0.9% w/v NaCl solution). MP abundance was visualized under a microscope along with their size, shape, and color. A subset of the isolated MPs was analyzed by scanning electron microscope (SEM), and Fourier transform infrared spectroscopy (FTIR) for the surface and chemical characterization respectively. The average MPs concentration was 47.5 ± 11.875 particles/g in sediment and 127.92 ± 14.99 particles/100 L in the water sample. Fibrous-shaped (72.17%) and transparent-colored (59.37%) MPs were dominant in all the collected samples. However, smaller MPs (>0.05-0.5 mm) were more common in the water samples (47.69%) and the larger (>1-5 mm) MPs were in the sediment samples (47.83%). SEM analysis found cracks and roughness on the surface of the MPs and nylon, polyethylene, polypropylene, and polystyrene MPs were identified by FTIR analysis. PLI value showed hazard level I in water and level II in sediment. The existence of deleterious MPs particles in the mud crab aquaculture system was well evident. The other commercial mud crab aquafarms must therefore be thoroughly investigated in order to include farmed mud crabs as an environmentally vulnerable food security concern.
The aim of this study is to uncover the multifaceted environmental threats posed by Oil Spill Water Pollution (OSWP) originating from tanker terminals situated in the Qeshm and Hormozgan regions of Iran. In this region, water pollution arises from diverse sources, mostly from ruptured pipelines, corroded valves, unforeseen accidents, and aging facilities. The Qeshm Canal and Qeshm Tanker Terminal emerged as pivotal sites for investigation within this study. The focus is directed towards pinpointing vulnerable areas at risk of water contamination and delving into the intricate pathways and impacts associated with oil spills. Utilizing the sophisticated modeling capabilities of the National Oceanic and Atmospheric Administration's (NOAA) GNOME model, the research explores various scenarios extrapolated from seasonal atmospheric and oceanic data through 2022. The findings show the OSWP hazard zones located northeast of Qeshm. Notably, the wind and currents greatly affect how OSWPs are destined and dispersed. This underscores the intricate interplay between environmental factors and spill dynamics. In essence, this study not only sheds light on the imminent environmental threats posed by OSWP but also underscores the critical need for proactive measures and comprehensive strategies to mitigate the adverse impacts on marine ecosystems and coastal communities.
Cooling spaces have an optimistic influence on surface urban heat islands (SUHI). Blue spaces benefit from balancing the changing climate and heat variations. Because of the rapid deforestation and SUHI increase, the climate is gradually changing in Paschim Bardhhaman, West Bengal state, India. Paschim Bardhhaman has two sectors: specifically, Durgapur is the main industrial centre and Asansol has coal mines. This investigation aims to categorize spatiotemporal variations and seasonal differences in cooling spaces and their influence on SUHI, land use and land cover (LULC), and thermal differences using Landsat datasets for the years 1992, 2004, 2012, and 2022 in summer and winter. The coal mining and industrial range decreased from 10,391.92 (1992) to 3591.1 ha (2022), respectively. Open pit mining distresses fresh water by heavy water uses in ore processing, and mining water was applied to excerpt minerals. Among the two sub-divisions, the blue space amount was higher in Asansol because mining actions were higher in Asansol than in Durgapur. The open vegetation volume has reduced from 46,441.03 (1992) to 25,827.55 ha (2022) and dense vegetation has erased from 7368.02 (1992) to 15,608.56 ha (2022). Dense vegetation improved because of heavy precipitation in those regions. Mostly, Raghunathpur, Saraswatiganja, Bhagabanpur, Bistupur, Paschim Gangaram, Garkilla Kherobari, and Gourbazar have dense vegetation. The outcomes similarly demonstrate that the total built-up part has increased by 8412.82 ha in between 30 years. The built-up zone changes near the southeast and western Paschim Bardhhaman district. Those region needs appropriate attention and planning to survive soon.
In this study, the air quality index (AQI) of Indian cities of different tiers is predicted by using the vanilla recurrent neural network (RNN). AQI is used to measure the air quality of any region which is calculated on the basis of the concentration of ground-level ozone, particle pollution, carbon monoxide, and sulphur dioxide in air. Thus, the present air quality of an area is dependent on current weather conditions, vehicle traffic in that area, or anything that increases air pollution. Also, the current air quality is dependent on the climate conditions and industrialization in that area. Thus, the AQI is history-dependent. To capture this dependency, the memory property of fractional derivatives is exploited in this algorithm and the fractional gradient descent algorithm involving Caputo's derivative has been used in the backpropagation algorithm for training of the RNN. Due to the availability of a large amount of data and high computation support, deep neural networks are capable of giving state-of-the-art results in the time series prediction. But, in this study, the basic vanilla RNN has been chosen to check the effectiveness of fractional derivatives. The AQI and gases affecting AQI prediction results for different cities show that the proposed algorithm leads to higher accuracy. It has been observed that the results of the vanilla RNN with fractional derivatives are comparable to long short-term memory (LSTM).
The increasing occurrence of mismanaged plastic litter along India's coastline and the ominous challenges it poses to biodiversity and ecosystem health is a growing environmental concern. To address this issue, we comprehensively investigated the abundance, composition, and probable sources of marine litter on North Cinque Island, a remote uninhabited island in the Andaman and Nicobar archipelago, Bay of Bengal. This island is a designated wildlife sanctuary and serves as an important nesting site for Green, Hawksbill and Leatherback turtles. A total of 6227 litter items were enumerated, with an average concentration of 0.12 items/m2, representing 20 diverse litter types, with plastic dominating the litter composition (86 %). The cleanliness and environmental hazards of the coast due to the litter were assessed using different indices such as the Clean Coast Index (CCI), Plastic Accumulation Index (PAI), Hazardous Item Index (HII), and Clean Environment Index (CEI). CCI indicates the moderately clean-to-clean status of the surveyed sites. PAI points to low to moderate accumulation of plastic litter. HII of all five coasts fell in category II, suggesting a moderate abundance of hazardous items that can inflict injuries to the foraging turtle and their hatchlings. The CEI articulates the moderately clean to very clean status of the sites. Litter brand audit suggests a considerable amount of stranded litter on the coasts was transboundary and originated from six Indian Ocean Rim Countries (IORC), namely Thailand, Myanmar, Malaysia, Indonesia, Sri Lanka, and UAE. Joint solid waste management by the IORC is the need of the hour to avert litter accumulation on the pristine, remote islands.
This research focuses on examining the potential impact of charcoal briquettes and lumps on human health due to the emissions they release, and verifying their quality standards. Quality assessment was conducted using a device capable of measuring toxic gases to identify contaminants from various sources such as biomass, synthetic resins, coal, metals, and mineral matter. Toxicity assessments were carried out on five types of briquettes and two varieties of lump charcoal. All charcoal samples were subjected to elemental analysis (SEM/EDAX), including the examination of Ca, Al, Cr, V, Cu, Fe, S, Sr, Si, Ba, Pb, P, Mn, Rb, K, Ti, and Zn. The results showed that burning lump charcoal had toxicity indexes ranging from 2.5 to 5, primarily due to NOx emissions. Briquettes, on the other hand, exhibited higher toxicity indices between 3.5 and 6.0, with CO2 being the main contributor to toxicity. The average 24-h CO content of all charcoal samples exceeded the World Health Organization's 24-h Air Quality Guideline of 6.34 ppm, with a measurement of 37 ppm. The data indicates that most of the products tested did not meet the prevailing quality standard (EN 1860-2:2005 (E) in Appliances, solid fuels and firelighters for barbecuing-Part 2: Barbecue charcoal and barbecue charcoal briquettes-Requirements and test method, 2005), which specifies a maximum of 1% contaminants, with some products containing as much as 21% impurities. The SEM analysis revealed irregularly shaped grains with an uneven distribution of particles, and the average particle size distribution is quite broad at 5 μm. Malaysia Charcoal had the highest calorific value at 32.80 MJ/Kg, with the value being influenced by the fixed carbon content-higher carbon content resulting in a higher calorific value.
Riverine sediments are important reservoirs of heavy metals, representing both historical and contemporary anthropogenic activity within the watershed. This review has been conducted to examine the distribution of heavy metals in the surface sediment of 52 riverine systems from various Asian and European countries, as well as to determine their sources and environmental risks. The results revealed significant variability in heavy metal contamination in the world's riverine systems, with certain hotspots exhibiting concentrations that exceeded the permissible limits set by environmental quality standards. Among the studied countries, India has the highest levels of chromium (Cr), cobalt (Co), manganese (Mn), nickel (Ni), zinc (Zn), cadmium (Cd), copper (Cu), and lead (Pb) contamination in its riverine systems, followed by Iran > Turkey > Spain > Vietnam > Pakistan > Malaysia > Taiwan > China > Nigeria > Bangladesh > Japan. Heavy metal pollution in the world's riverine systems was quantified using pollution evaluation indices. The Contamination Factor (CF) revealed moderate contamination (1 ≤ CF Pakistan > Bangladesh > China > Taiwan > Japan and Iron, while the potential risks of ∑non-carcinogenic Pb, Cr, Ni, Cu, Cd, Co, Zn, and Mn for exposed human children and adults through ingestion and dermal contact were significantly influenced between acceptable to high risk, necessitating special attention from pollution control agencies.