Pollution Index Research Articles

Assessment of the Quality of Borehole Water Collected Around Unlined Solid Waste Dumpsites within Awka Metropolis

Groundwater is an important natural resource that is essential to man and other living things. However, it can become polluted resulting from natural and anthropogenic conditions. The quality of selected groundwater samples collected from boreholes around abandoned and active dumpsites in Awka metropolis, Nigeria between January and March 2023, was assessed using water quality index (WQI) method. The samples were analyzed for their physico-chemical properties and some selected heavy metals using atomic absorption spectroscopy. The results of the physico-chemical analysis showed that the mean pH ranged from 5.75 – 6.71 in January as compared to 5.92 – 6.98 in February and 5.94 – 6.84 in March indicating slight acidity. Calcium and magnesium content ranged from 8 – 20mg/l of Ca2+ and 96 – 314 mg/l of Mg2+ ion. The concentration of heavy metals in the samples were all seen to be within the standard limits for potable water (Fe (0.057 – 2.384 ppm), Cu(0.00 – 0.185 ppm) except for mercury, lead and cadmium(Hg (0.00 – 0.248 ppm), Pb (0.00 – 0.051 ppm), Cd (0.006 – 0.39 ppm) for the month of February whereas heavy metal concentration for the month of March ranged from Fe (1.432 – 2.908 ppm), Cu (0.00 – 0.008 ppm), Hg (0.00 – 0.016 ppm), Pb (0.00 – 0.003 ppm), Cd (0.00 – 0.01ppm). Pollution Index of the sampled borehole water from the different locations shows that some were potable and can be consumed without treatment. The study shows that solid wastes contribute to the level of contamination caused by Heavy metals and some physico-chemical parameters in groundwater matrix.

Hydro-chemical characterization of groundwater using multivariate statistics in Hawassa City, Southern Ethiopia

ABSTRACT This study characterized the hydro-chemical characteristics of groundwater for assessing the possibility of managed aquifer recharge in Hawassa City. A total of 48 water samples were taken from hand-dug wells and boreholes and examined to determine the water type, critical metrics, and key determinants of water quality. Multivariate statistical techniques such as hierarchical cluster, principal component, and linear discriminant analysis were used. The samples were divided into four variable groups and four case cluster groups. The results depicted the water hardness group (C1), soil salinity group (C2), weak and strong acids forming group (C3), and pollution indicator group (C4). Four water types were identified, Na–HCO3 and Ca–Na–HCO3 (87.5%), Ca–HCO3, and Na–Cl. Na–HCO3 was the dominant in hand-dug wells than in deep boreholes, which may account for evaporation or contaminations. Seven principal components with a cumulative variance of 78.58% were also formed. The first two, hardness and salinity, contributed 25.4 and 11.4% variance, respectively. In linear discriminate analysis, three discriminate functions with eight variables were generated, namely pH, K+, Na+, Ca2+, HCO3−, Cl−, BOD5, and COD. Thus, it is revealed that the decline in water quality attributed to natural and anthropogenic causes that require regulation enforcement and higher recharge to reverse the situation.

The synergy of renewable energy consumption, green technology, and environmental quality: Designing sustainable development goals policies

AbstractGreen technology (GT) and the utilization of renewable energy (RE) are widely acknowledged as a catalyst for energy efficiency, economic growth, and a tool for combating environmental degradation. Although various studies have examined the ecological repercussions of these two improvements, they have primarily used traditional pollution indicators (namely, carbon emissions and ecological footprint) and ignored nations with the highest cleaner energy adoption. To bridge this gap, the present research seeks to analyze the relationship between GT, RE consumption, economic growth, trade, and load capacity factor in the top‐10 renewable economies. In addition to environmental pollution indicators, the study utilizes the load capacity factor as a novel proxy for environmental quality and investigates the load capacity curve hypothesis using the Cross‐sectional‐autoregressive distributed lag model from 1990 to 2021. According to the empirical findings, all explanatory variables have a significant long‐term effect on the load capacity. More precisely, GT and RE consumption contribute to the sustainability of the ecosystem, while trade increases the ecological deficit. Furthermore, the findings do not support the validity of the load capacity curve hypothesis, implying that the environmental restorative benefits of economic well‐being may not manifest in the latter stages of economic growth. Given these findings, policymakers in the top‐10 renewable economies should seize the environmental prospects offered by GT and RE and update trade and growth policies in a way that promotes biocapacity while simultaneously reducing the ecological footprint to reach the long‐term sustainable development goals (SDGs), particularly SDGs 7 and 13.

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.

Assessment of Water Status, Bottom Sediments, Macrophytes in the Light of Index Analysis and Geochemical Parameters of Selected Dam Reservoirs of Kielce Upland (Poland)

Concentrations of trace elements such as Cr, Zn, Cd, Co, Mn, Cu, Ni, Pb, and Fe were investigated in water, bottom sediments, and macrophytes (Phragmites australis and Typha latifolia L.) collected from the Borków, Wilków, and Rejów water reservoirs in the Kielce Upland (Poland). The main objective of this study was to investigate the condition of water, bottom sediments, and macrophytes in selected three sedimentary basins of the Kielce Upland and to identify natural and anthropogenic factors influencing this condition. The secondary objectives were (i) to determine the contents of trace metals in water, bottom sediments, and macrophytes, (ii) to assess the quality of abiotic and biotic elements of the ecosystem based on selected criteria, (iii) to compare reservoirs in terms of pollution, and (iv) to determine the ability of macrophytes to be used as a bioindicator of water/sediment pollution. Field tests were conducted in 2021. The trace metals in water were determined by ETAAS (Cr, Cd, Mn, Cu, Ni, Pb) and FAAS (Zn), and spectrophotometry method (Fe). The trace metals in sediments and macrophytes, including Cr, Zn, Cd, Co, Mn, Cu, Ni, Pb, and Fe, were detected using ICP-OES method. Contamination of bottom sediments with potentially toxic metals was determined based on the geo-accumulation index (Igeo), contamination factor (CF), and pollutant load index (PLI). Statistical analyses were performed using the Statistica PL 13.1. The analyses showed that the accumulation of trace elements in the surface layer of the reservoir sediments increases as follows: in Borków, Cd < Co < Ni < Cu < Pb < Cr < Zn < Mn < Fe; in Wilków, Cd < Co < Cu < Ni < Pb < Cr < Zn < Mn < Fe; and in Rejow, Cd < Co = Cu = Ni = Pb < Zn < Cr < Mn < Fe. It was shown that the average distribution of metals in the bottom sediments of the studied reservoirs was as follows: Borków > Wilków > Rejów. Research has shown that the degree of trace metal accumulation increases as follows: water < sediments < macrophytes (except Pb from the reservoir in Borków).

Analisis Kualitas dan Indeks Pencemaran Air pada Usaha Budidaya Perikanan di Desa Kota Karang Kecamatan Kumpeh Ulu Kabupaten Muaro Jambi

This research aims to analyze the quality of freshwater cultivation and analyze the pollution index for freshwater cultivation in Desa Kota Karang, Kec. Kumpeh Ulu, Kabupaten Muaro Jambi. This research uses quantitative analysis techniques. The results of analysis and water quality tests concluded that the cultivation ponds in Desa Kota Karang were in the lightly polluted category. Based on research conducted on 10 ponds, there were 3 ponds that met quality standards, the rest were in the lightly polluted category. This is based on tests and analysis of physical, chemical and biological parameters. Meanwhile, the results of the pollution index analysis obtained IP values ranging from 0.88 to 2.91. According to PP Number 22 of 2021, if 1 < IP ≤ 5 then the cultivation pond in Desa Kota Karang is in the lightly polluted category. Based on the results of the air quality analysis and pollution index, the air quality in the cultivation ponds in Kota Karang Village is still suitable for use for fish cultivation. Therefore, it is necessary to carry out further monitoring and recovery efforts for BOD and COD parameters that have exceeded class III quality standards of PP Number 22 of 2021 concerning Freshwater Fisheries Cultivation, so that ponds in Desa Kota Karang remain safe for carrying out cultivation activities.

Residual Assessment of Emerging Pesticides in Aquatic Sinks of Lahore, Pakistan

In recent decades, the use of pesticides has become fundamental to agricultural growth. However, the persistent and toxic nature of pesticides has led to significant concerns regarding their ecological and human health consequences. Therefore, for a better understanding of pesticide contamination and its potential risks, here we assessed the levels of five emerging pesticides—acetochlor, imidacloprid, MCPA, atrazine, and allethrin—in soil samples from ponds used for irrigation and in drinking water samples from nearby areas in Lahore, Pakistan. Our findings revealed that 100% of the samples were contaminated, posing substantial ecological and human health risks. Based on the toxic units (TUsum), all the soil samples showed higher toxic pressure, exceeding acute and chronic toxicity thresholds for earthworms, while 100% of water samples posed chronic toxicity risks to crustaceans and 10% to algae. Pollution index (PI) analysis further classified 100% of the soil samples and 10% of the water samples as highly polluted. These findings show high-pesticide residues in both soil and water and highlight immediate risk assessment and mitigation measures to protect non-target organisms. This preliminary information can be used to adopt risk assessment monitoring programmes and help higher authorities in making policies and guidelines to mitigate the escalating risk for ecology and humans.

Spatial Distribution, Leaching Characteristics, and Ecological and Health Risk Assessment of Potential Toxic Elements in a Typical Open-Pit Iron Mine Along the Yangzi River

Potential toxic elements (PTEs) pollution in the soil of abandoned open-pit mines can lead to great ecological risk to the areas around the mining districts. This study selected a typical abandoned open-pit iron mine along the Yangzi River in southeast China to investigate the spatial distribution, leaching characteristics, and ecological and health risk of the soil PTEs (As, Pb, Cd, Ni, Cr, Cu, and Zn). Leaching tests and sequential extraction were applied to study the migration of PTEs under the condition of rainfall. Different risk assessment methods were used to analyze the pollution and ecological risk of PTEs. The contents of As and Cu exceeded the background value of the Chinese soil guideline, with average contents of 50.71 ± 1.59 and 197.47 ± 16.09, respectively. The leaching test and sequential extraction indicated that sites 8 and 9 posed the greatest risk of PTE migration. According to the map of the Nemerow integrated pollution index (NIPI), the pollution level of the middle bare area of the study area was the highest, and Cu possessed the highest pollution index (PI) of 3.92. The average geo-accumulation index (Igeo) of As and Cu was between 1 and 2, reaching the pollution level of moderately contaminated. The average potential ecological risk coefficient (Ei) of As was the highest, and the contributions of As, Cu, and Cd to the potential ecological risk of the whole study area were 46.7%, 29.7%, and 14.3%, respectively. The range of the hazard index (HI) and the range of the As carcinogenic risk (CRAs) of all the sampling sites for children were 1.30–3.94 and 2.19 × 10−4–7.20 × 10−4, and As accounted for more than 85% of the total noncarcinogenic risk, indicating that the comprehensive pollution of PTEs in the study area posed great carcinogenic and noncarcinogenic risks to children. This study can be a proper reference for the subsequent recovery methods and environmental management of the whole mining area.

Evaluation of Urbanization Influences on Beach Sediment Contamination with Heavy Metals Along the Littoral Zone of Alexandria City, Egypt

The western coastal area of Alexandria City, Egypt, faces significant environmental challenges due to heavy metal (HM) contamination in beach sediments, driven by intensive urbanization, tourism, commercial harbors, and industrial activities. Therefore, this study focuses on geochemically assessing HM levels in sediment samples from 28 sites and employed various descriptive and multivariate statistical approaches, pollution indices, and sediment quality guidelines (SQGs) to identify pollution hotspots, define contamination grades, and assess the quality of beach sediments. The average concentrations of Cd, Co, Cr, Cu, Pb, and Zn were 25.7, 30, 2.2, 7.5, 2.9, and 8.0 times, respectively, compared to the geochemical background (carbonate sedimentary rocks). et al.-Hanuvil Beach, relatively elevated contents of these metals were recorded. In addition, samples showed Zn levels higher than the corresponding probable effect concentration (PEC) and effect range medium (ERM) values, suggesting adverse impacts on biota. The principal component (PC) analysis revealed the anthropogenic origin of Cd, Co, and Pb in PC1, the mixed origin of Cr, Cu, Mn, and Zn in PC2, and the natural source of Fe in PC3. According to the applied single pollution indices, HM contamination grades were ranked in ascending order of Mn < Fe < Cr < Cd < Cu < Pb < Zn < Co. In conclusion, the HMs (Cu, Zn, Cd, Co, Pb, and Cr) in the study area are anthropogenic, attributed mainly to untreated discharge of municipal and industrial wastewater and solid wastes, atmospheric deposition of air pollutants, and tourism activities.

Pollution and health risk assessments related to heavy metals on three prominent beaches in Makkah Province, Kingdom of Saudi Arabia: Concerning levels of cadmium pollution.

Beach pollution can impact the health of people living in or visiting coastal areas. The primary goal of this research was to investigate the presence of heavy metal pollutants and associated health risks in three distinct coastal cities, Jeddah, Al-Lith, and Al-Qunfudhah, located along Saudi Arabia's Red Sea coast. Forty-three soil samples were collected from different locations, heavy metals including Fe, Zn, Mn, Cu, Cd, and Pb were isolated, and analyzed using inductively coupled plasma optical emission spectroscopy. Various metrics such as pollution indices (PI), integrated pollution indices (IPI), enrichment factors (EF), daily dose averages (ADD), hazard quotients (HQ), and hazard indices (HI), as well as principal component analysis (PCA) and cluster analysis were employed to evaluate the environmental impacts and health risks posed by these heavy metals. The results revealed that Fe, Pb, Cu, Mn, and Zn concentrations in beach zones were below their respective background levels, while concentrations of Cd exceeded corresponding background levels. PCA revealed the highest levels of Pb, Fe, and Mn on Al-Qundudah beach, while Cd and Cu were highest on Al-Lith beach, and Zn was highest on Jeddah beach. PI values highlighted extremely high levels of Cd pollution on all designated beaches. The findings provide a foundational basis for further investigations into health problems potentially related to Cd contamination, such as chronic kidney disease (CKD), osteomalacia, and osteoporosis.

Spatial distribution, ecological and human health risks of potentially toxic elements (PTEs) in river Ravi, Pakistan: A comprehensive study

Significant quantities of potentially toxic elements have been and are still being discharged into Pakistan's rivers through natural sources and anthropogenic activities. The present study provides a comprehensive study of potentially toxic element contamination in the water and sediment of the Ravi River, Pakistan. The research aims to examine the extent of pollution, its ecological risks, and the potential human health impacts through detailed geospatial analysis and statistical correlation. Water and sediment representative samples were taken and analyzed for potentially toxic elements, including Cobalt (Co), Cadmium (Cd), Zinc (Zn), Nickel (Ni), Arsenic (As), Chromium (Cr), Lead (Pb), Copper (Cu), and Manganese (Mn). Various pollution indices, such as the “Geo-accumulation Index (Igeo), Modified degree of Contamination (mCd), Nemerow comprehensive pollution index (Pt), Contamination factor (CF), Enrichment factor (EF), Pollution Load Index (PLI), and Potential Ecological Risk Index (PERI),” were calculated to determine the contamination levels and ecological risks. The results indicated significant spatial variability in metal concentrations, with higher levels observed in industrial and urban areas (near Lahore). Cd and As were identified as the most critical pollutants, exhibiting high Igeo, CF, EF, and PERI values. The PLI revealed that several regions along the river are heavily polluted. Pt shows high comprehensive pollution near Lahore and moderate to high pollution in surrounding areas. According to mCd, most of the study area, especially sampling points near Lahore, ranges between 8 and 16, indicating a high degree of pollution. The Human Health Risk (HHR) assessment, considering ingestion, inhalation, and dermal contact pathways, highlighted that children are particularly vulnerable, showing higher Hazard Quotient (HQ) and Hazard Index (HI) values for several metals. Correlation analysis revealed significant relationships between certain metals, suggesting common sources of contamination, likely from industrial discharges and urban runoff. The comprehensive mapping and statistical analysis underscore the urgent need for implementing effective pollution control measures to mitigate the risks posed by potentially toxic element contamination in the Ravi River. This study provides critical insights for policymakers and environmental managers to prioritize areas for remediation and to develop strategies to protect both ecological and human health in the region.

Application of Heavy Metal Pollution Index (HPI) of Water Quality Assessment in Tengi River

Application of Heavy Metal Pollution Index (HPI) of Water Quality Assessment in Tengi River

Air Quality Prediction in Urban Environment Using IoT Sensor Data

The increasing concern for environmental health has led to a heightened need for accurate air quality monitoring and prediction. This study presents a framework for predicting the Air Quality Index (AQI) using existing datasets rather than relying on real-time data from IoT sensors. The proposed system incorporates various machine learning algorithms, including Linear Regression, Neural Networks, and XGBoost, to analyze the relationships between air pollution indicators and AQI values. The methodology encompasses essential steps such as data preprocessing, normalization, and dividing the dataset into training and testing sets. Although the system has not yet been implemented, preliminary analyses indicate that the use of these models has the potential to yield reliable AQI predictions, which can significantly assist policymakers and public health officials in implementing effective air quality management strategies.

Arsenic and Heavy Metals in Soils and Plants near Sulfide Mines: Implications for Phytoremediation and Phytomanagement.

The accumulation of heavy metals (i.e., As, Cu, Ni, Pb, and Zn) in soils and native plant species near copper, nickel, and pyrite mines in Vietnam was assessed. The highest soil As, Cu, Ni, Pb, and Zn concentrations recorded in mine soils were 42.3, 1570, 9870, 128, and 462 mg/kg, and those in agricultural soils were 11.4, 453, 94.9, 34.4, and 147 mg/kg, respectively. Pollution index (PI) values indicated heavy pollution (PI = 3.99-13.0) for mine soils, and unpolluted to severely polluted (PI = 0.65-2.84) for agricultural soils. Soil enrichment factors had a wide range, from minimal to extreme enrichment of heavy metals (EF = 0.03-91.4). Arsenic minerals may be the main source of high As concentrations in sulfide mines. The As, Cu, Ni, Pb, and Zn concentrations of 20 native plant species near three mines were in the ranges of 0.05-1150, 3.17-123, 0.47-291, 0.08-6.34, and 6.87-168 mg/kg (dry weight, DW), respectively. Based on the recorded hyperaccumulation levels (1150 mg/kg, DW), bioaccumulation factors (BAF = 2.4-90.0), biomass, and rapid growth, Pteris vittata L. is considered a promising plant for phytoextraction of As in soils. Bidens pilosa L. has potential for phytostabilization of sulfide-bearing soils, given its low concentrations of heavy metals in plant shoots, BAF values of <1, high biomass, and wide distribution. Integrated phytoremediation and phytomanagement are applicable to metal-contaminated soils. Phytomining, energy crops, and vegetation cover should be investigated for the phytomanagement of metal-contaminated soils in mining areas.

Occupational exposure assessment of heavy metals in human scalp hair among tannery workers in Bahir Dar, Ethiopia: Indication of pollution

Ethiopia, is one of the African countries, has immense potential for skins and hides for the leather industries, which will play a crucial role in converting nations into manufacturing-driven economies through industrialization. The chemicals applied in the tanning process are a serious concern for employees and the community if proper safety measures are not taken. The pollution status of employees working in Anbessa and Bahir Dar tannery factories was evaluated by collecting hair samples. After the hair samples washed with acetone, and deionized water, the hair samples were digested with 4 mL of HNO3 and 2 mL of HClO4 for 1:30 h at 250 °C. The levels of metals (Cr, Pb, Zn, Cu, Ni, and Cd) were subsequently analyzed using a Flame Atomic Absorption Spectrophotometer (FAAS). The mean concentrations of Cu, Ni, Zn, Pb, and Cr in the Anbessa tannery factory workers were 17.34–22.75, 16.38–35.03, 235.4–369.2, 30.46–67.31, and 97.56–189.18, respectively, in the various working departments of the factory. Similarly, the concentrations of Cu, Ni, Zn, Cd, Pb, and Cr in the hair of Bahir Dar tannery workers were 30.1–105.9, 17.88–62.20, 216.9–762.1, 0.35–5.21, 33.42–91.42, and 118.5–305.7, respectively. Chromium was found to be the most accumulated metal next to Zn with in both tannery workers that highlighted significant occupational health risks. The principal component analysis (PCA) analysis provide an insights into the interactions between occupational factors and metal exposure. In conclusion, the results of hair analysis from the employees of tannery factories indicates alarming levels of metal exposure, especially for zinc and chromium, which might pose health problems in long time exposure. Thus, it's critical to monitor occupational activities that can harm human health and the environment.

Green bond premium diagnosis: An interplay of repayment obligation structure

This paper examines at-issuance yield (price) differential between green and non-green bonds. The paper also checks the sensitiveness of the differentials to the repayment obligation structure of the bonds. For this, we test for differentials in the standard and revenue segments separately. From Bloomberg®, we extract US municipal green bonds from 2014 to 2023 and apply propensity score matching to generate sample sets comprising 26440, 23848, and 11702 bonds. Through univariate tests and OLS linear regression, we document lower yield for green bonds compared to non-greens (i.e., negative yield differential implying the existence of green premium) ranging from 2.7 to 6.9 basis points, implying cost savings to green issuers. The results are robust to alternate measuring variable and surrogate matched samples—the premiums decline in a non-pro-environmental regime and the pandemic. Green investors perceive higher risk in counties with higher pollution index. The premiums enlarge in the standard segment compared to revenue because of greater trust in the recourse feature than revenue stream collaterals. Citing the lack of tangible municipal revenue streams in emerging economies, our findings endorse the standard (general obligation) green bonds to raise finance at initial stages and create revenue-generating infrastructures.

Novel nanoliter spray enhanced microwave plasma ionization mass spectrometry for the simultaneous detection of heavy metals and organic plasticizers in soil: A case study in a lead-acid battery industrial park

Soil pollution is predominantly attributed to the presence of heavy metal elements and organic compounds; However, current detection methodologies are restricted to the identification of only one of these two sources at a time. A novel analytical approach, known as nanoliter spray enhanced microwave plasma ionization mass spectrometry (Nano-Spray-EMPI-MS), has been developed to facilitate the simultaneous detection of both heavy metals and organic pollutants in soil samples. This technique is characterized by its requirement for minimal sample volumes, thereby allowing for efficient and rapid analysis. The research concentrated on the simultaneous analysis of five heavy metals (Pb, Zn, Cu, Cr, and Ni) and three major phthalates (PAEs), specifically DEHP, DBP, and DMP. The detection and quantification limits for the heavy metals were established to be between 0.16-0.57 and 0.53–1.88 μg L−1, respectively, while the limits for the PAEs ranged from 0.02 to 0.05 and 0.07–0.16 μg L−1. Validation of the method's efficacy in soil detection demonstrated recovery rates of 90.9 %–105.7 % for heavy metals and 89.4 %–97.2 % for PAEs. The application of this method analyzing soil samples collected from an area adjacent to a lead-acid battery industrial park in China revealed varying levels of contamination by both heavy metals and PAEs. Notably, Lead contamination was found to be the most pronounced, with a peak concentration of 862.5 mg kg−1 and a correspondingly high pollution index. These findings are significant for evaluating local ecological risks, pinpointing sources of pollution, and formulating effective pollution management strategies in the region.

Концентрация химических элементов в хвое Larix gmelinii и листьях Betula pendula

In the Trans-Baikal Territory, mining enterprises significantly pollute the environment with chemical elements. In these conditions, monitoring the state of the environment, including with the help of indicator plants, is of great importance. Among the woody plants, Gmelin larch (Larix gmelinii (Rupr.) Kuzen.) and silver birch (Betula pendula Roth.) are the most common in the region. Using the example of the Bystrinskoe Cu–Au–Fe skarnporphyry deposit, the concentrarion of 46 chemical elements in the needles of Gmelin larch and the leaves of silver birch, as well as the content of these elements in the soil, has been studied. The aim of the study is to identify plant species differences in the accumulation of elements and the prospect for using plants as indicators of environmental pollution. Scientific work has been carried out on 11 sample plots in natural plant communities near the enterprise’s facilities in August 2022. Soil and plant samples have been collected at the same time, at the same sites. The chemical analysis of the samples has been carried out using the “Methodology for measuring the metal content in solid objects by inductively coupled spectrometry” (FER 16.1:2.3:3.11–98). Differences in the concentration of elements in plants in relation to the clarke of terrestrial plants have been established. A statictically significant higher concentration of K, Ca, P, Mg, Fe, Ba, Zn, Na, Rb, Ni, Co, Ga, Sn, Y, Zr, Cd and Nb has been found in birch leaves compared to larch needles, and, conversely, a higher concentration of Sc, W and Hg – in larch needles than in birch leaves. Significant differences between plants have been established in the biological absorption coefficient of Se, P, Sn, Ca, Mn, Sr, Cd, Mg, K, W, Ni, Zn, Sc, Rb, Na and Nb. Knowledge about the peculiarities of accumulation of chemical elements in plant organs can be used for biomonitoring environmental pollution and, possibly, for phytoremediation of contaminated soils.

Impact of physical activity levels on the association between air pollution exposures and glycemic indicators in older individuals

BackgroundAir pollution may exacerbate diabetes-related indicators; however, the longitudinal associations between air pollutant concentrations and glycemic markers remain unclear. In this prospective cohort study, we examined the longitudinal associations between air pollution and glycemic indicators among older individuals with normoglycemia at baseline and determined whether these associations differed according to changes in physical activity levels.MethodsOverall, 1,856 participants (mean age, 70.9 years) underwent baseline and 4-year follow-up surveys. We used linear mixed-effect models to examine the associations between previous 1-year exposures to air pollutants and glycemic indicators. We further investigated associations between previous 5-year exposures to air pollutants and glycemic indicators after the inverse probability of treatment weighting (IPTW). We explored effect modifications by the level of physical activity maintenance and changes in metabolic equivalent of task (METs) for physical activity.ResultsLevels of particulate matter with aerodynamic diameters ≤ 10 μm (PM10) and ≤ 2.5 μm, and nitrogen dioxide (NO2) were significantly associated with increased fasting blood glucose, Hemoglobin A1c, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR) values. After IPTW, the associations remained significant for PM10 and NO2. The positive associations of NO2 with insulin and HOMA-IR remained significant in the maintained inactive group, but not in the maintained moderate-to-vigorous active group. The positive associations of PM10 or NO2 with insulin and HOMA-IR remained significant in the group with increased METs, but not in those with decreased METs. In the post-hoc analysis of non-linear relationships between an increase in METs and glycemic indicators, insulin and HOMA-IR remarkably increased in the higher PM10 and NO2 exposure group from the point of 12,000 and 13,500 METs-min/week increase, respectively.ConclusionsWe demonstrated longitudinal associations between air pollution exposures and increased insulin resistance in older individuals. Maintaining moderate-to-vigorous physical activity may mitigate the adverse effects of air pollution on insulin resistance. In older individuals dwelling in highly polluted areas, an increase of less than 12,000 METs-min/week may be beneficial for insulin resistance.

Source apportionment and influencing factors of surface water pollution through a combination of multiple receptor models and geodetector

In line with sustainable development goals (SDGs), precise quantification of water pollution and analysis of environmental interactions are crucial for effectively safeguarding water resources. In this study, Nemerow's pollution index was used to evaluate water quality, three receptor models were used to identify pollution sources, and Geodetector analysis was applied to explore environmental interactions in the North Shangyu Plain, Southeast China. Using 5207 surface water samples from September 2023 with 11 physicochemical parameters, the results showed that surface rivers in the North Shangyu Plain exhibited varying degrees of pollution: slight pollution upstream, moderate pollution in midstream and downstream, and concentrated high pollution in certain areas, with TN, CODCr, and TP as the primary pollutants. Multimethod source apportionment significantly improved the accuracy of pollution source attribution and identified five main sources: domestic sewage (1.42%–3.54%) characterized by NO3-N, phytoplankton source (38.43%–50.05%) indicated by chl and PC, agricultural cultivation (16.1%–17.63%) marked by TP and CODMn, industrial wastewater (17.64%–25.1%) primarily associated with TN, and natural source (10.32%–13.26%) characterized by DO, NH3-N, and CODCr. Influencing factor analysis validated the source identification. Natural factors had minor impacts on water parameters, while pollution control from agricultural activities was suggested to diversify fertilizer types rather than merely reduce quantities. The combined effects of industrial and aquaculture activities intensified pollution from TN, chl, and PC, underscoring the need for targeted management practices. This study showed the objectivity and reliability of using a combined approach of multiple receptor models and Geodetector to evaluate the river water quality status, which helps assist decision-makers in formulating more effective water resource protection strategies.