Displaying publications 1 - 20 of 291 in total

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  1. Environmental DNA metabarcoding of freshwater fish in Malaysian tropical rivers using short-read nanopore sequencing as a potential biomonitoring tool
    Munian K, Ramli FF, Othman N, Mahyudin NAA, Sariyati NH, Abdullah-Fauzi NAF, et al.
    Mol Ecol Resour, 2024 May;24(4):e13936.
    PMID: 38419264 DOI: 10.1111/1755-0998.13936
    The approach of combining cost-effective nanopore sequencing and emerging environmental DNA (eDNA) metabarcoding could prove to be a promising tool for biodiversity documentation, especially in Malaysia. Given the substantial funding constraints in recent years, especially in relation to the country's biodiversity, many researchers have been limited to conduct restricted research without extended monitoring periods, potentially hindering comprehensive surveys and could compromise the conservation efforts. Therefore, the present study aimed to evaluate the application of eDNA metabarcoding on freshwater fish using short reads generated through nanopore sequencing. This assessment focused on species detection in three selected rivers within the Endau Rompin Landscape in Malaysia. Additionally, the study compared levels of species detection between eDNA metabarcoding and conventional sampling methods, examined the effectiveness of primer choice, and applied both metabarcoding and shotgun sequencing to the eDNA approach. We successfully identified a total of 22 and 71 species with an identification threshold of >97% and >90%, respectively, through the MinION platform. The eDNA metabarcoding approach detected over 13% more freshwater fish species than when the conventional method was used. Notably, the distinction in freshwater fish detection between eDNA primers for 12S rRNA and cytochrome oxidase I was insignificant. The cost for eDNA metabarcoding proved to be more effective compared to conventional sampling with cost reduction at 33.4%. With favourable cost-effectiveness and increased species detection, eDNA metabarcoding could complement existing methods, enhance holistic diversity documentation for targeted habitats and facilitate effective conservation planning.
    Matched MeSH terms: Environmental Monitoring/methods
  2. A meta-analysis highlighting the increasing relevance of the hair matrix in exposure assessment to organic pollutants
    Junaid M, Sultan M, Liu S, Hamid N, Yue Q, Pei DS, et al.
    Sci Total Environ, 2024 Mar 20;917:170535.
    PMID: 38307287 DOI: 10.1016/j.scitotenv.2024.170535
    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 
    Matched MeSH terms: Environmental Monitoring/methods
  3. Critical review on airborne microplastics: An indoor air contaminant of emerging concern
    Kek HY, Tan H, Othman MHD, Nyakuma BB, Ho WS, Sheng DDCV, et al.
    Environ Res, 2024 Mar 15;245:118055.
    PMID: 38154562 DOI: 10.1016/j.envres.2023.118055
    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.
    Matched MeSH terms: Environmental Monitoring/methods
  4. Environmental occurrence and assessment of organic pollutants in surface sediments of South Peninsular Malaysia
    Alkhadher SAA, Sidek LM, Zakaria MP, A Al-Garadi M, Suratman S
    Environ Geochem Health, 2024 Mar 15;46(4):140.
    PMID: 38488953 DOI: 10.1007/s10653-024-01916-5
    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 
    Matched MeSH terms: Environmental Monitoring/methods
  5. Environmental impact and human health effects of polycyclic aromatic hydrocarbons and remedial strategies: A detailed review
    Venkatraman G, Giribabu N, Mohan PS, Muttiah B, Govindarajan VK, Alagiri M, et al.
    Chemosphere, 2024 Mar;351:141227.
    PMID: 38253087 DOI: 10.1016/j.chemosphere.2024.141227
    Polycyclic Aromatic Hydrocarbons (PAHs) profoundly impact public and environmental health. Gaining a comprehensive understanding of their intricate functions, exposure pathways, and potential health implications is imperative to implement remedial strategies and legislation effectively. This review seeks to explore PAH mobility, direct exposure pathways, and cutting-edge bioremediation technologies essential for combating the pervasive contamination of environments by PAHs, thereby expanding our foundational knowledge. PAHs, characterised by their toxicity and possession of two or more aromatic rings, exhibit diverse configurations. Their lipophilicity and remarkable persistence contribute to their widespread prevalence as hazardous environmental contaminants and byproducts. Primary sources of PAHs include contaminated food, water, and soil, which enter the human body through inhalation, ingestion, and dermal exposure. While short-term consequences encompass eye irritation, nausea, and vomiting, long-term exposure poses risks of kidney and liver damage, difficulty breathing, and asthma-like symptoms. Notably, cities with elevated PAH levels may witness exacerbation of bronchial asthma and chronic obstructive pulmonary disease (COPD). Bioremediation techniques utilising microorganisms emerge as a promising avenue to mitigate PAH-related health risks by facilitating the breakdown of these compounds in polluted environments. Furthermore, this review delves into the global concern of antimicrobial resistance associated with PAHs, highlighting its implications. The environmental effects and applications of genetically altered microbes in addressing this challenge warrant further exploration, emphasising the dynamic nature of ongoing research in this field.
    Matched MeSH terms: Environmental Monitoring/methods
  6. Hydrogeochemical assessment of aquifer salinization in north-eastern Morocco's Gueroaou coastal plain using statistical methods
    Chahban M, Akodad M, Skalli A, Gueddari H, El Yousfi Y, Ait Hmeid H, et al.
    Environ Res, 2024 Mar 01;244:117939.
    PMID: 38128604 DOI: 10.1016/j.envres.2023.117939
    The Guerouaou aquifer investigation spanning 280 km2 in Ain Zohra yields promising outcomes, instilling optimism for regional water quality. These analyses were applied to 45 sampling instances from 43 wells, enabling a comprehensive water quality assessment. Groundwater conductivity ranged from medium to high, peaking at 18360 ms/cm2. The conductivity reveals insights about the groundwater's mineralization. Key physiochemical parameters fell within desirable thresholds, bolstering the positive perspective. HCO3- levels spanned 82-420 mg/L, while chloride content ranged from 38 to 5316 mg/L, benefiting water quality. NO3- ions, vital for gauging pollution, ranged from 0 to 260 mg/L, indicating favorable results. Cation concentrations exhibited encouraging variations: Ca2+- 24 to 647 mg/L, Mg2+- 12 to 440 mg/L, Na+- 18 to 2722 mg/L, K+- 1.75 to 28.65 mg/L. These collectively favor water quality. Halite breakdown dominated mineralization, as evidenced by the prevalence of Na-Cl-Na-SO4 facies. Water resource management and local communities need effective management and mitigation strategies to prevent saltwater intrusion.
    Matched MeSH terms: Environmental Monitoring/methods
  7. Enhancing subsurface contamination assessment via ensemble prediction of ground electrical property: A Colorado AMD-impacted wetland case study
    Kumar A, Singh UK, Pradhan B
    J Environ Manage, 2024 Feb;351:119943.
    PMID: 38169263 DOI: 10.1016/j.jenvman.2023.119943
    Acid mine drainage (AMD) is recognized as a major environmental challenge in the Western United States, particularly in Colorado, leading to extreme subsurface contamination issue. Given Colorado's arid climate and dependence on groundwater, an accurate assessment of AMD-induced contamination is deemed crucial. While in past, machine learning (ML)-based inversion algorithms were used to reconstruct ground electrical properties (GEP) such as relative dielectric permittivity (RDP) from ground penetrating radar (GPR) data for contamination assessment, their inherent non-linear nature can introduce significant uncertainty and non-uniqueness into the reconstructed models. This is a challenge that traditional ML methods are not explicitly designed to address. In this study, a probabilistic hybrid technique has been introduced that combines the DeepLabv3+ architecture-based deep convolutional neural network (DCNN) with an ensemble prediction-based Monte Carlo (MC) dropout method. Different MC dropout rates (1%, 5%, and 10%) were initially evaluated using 1D and 2D synthetic GPR data for accurate and reliable RDP model prediction. The optimal rate was chosen based on minimal prediction uncertainty and the closest alignment of the mean or median model with the true RDP model. Notably, with the optimal MC dropout rate, prediction accuracy of over 95% for the 1D and 2D cases was achieved. Motivated by these results, the hybrid technique was applied to field GPR data collected over an AMD-impacted wetland near Silverton, Colorado. The field results underscored the hybrid technique's ability to predict an accurate subsurface RDP distribution for estimating the spatial extent of AMD-induced contamination. Notably, this technique not only provides a precise assessment of subsurface contamination but also ensures consistent interpretations of subsurface condition by different environmentalists examining the same GPR data. In conclusion, the hybrid technique presents a promising avenue for future environmental studies in regions affected by AMD or other contaminants that alter the natural distribution of GEP.
    Matched MeSH terms: Environmental Monitoring/methods
  8. Fulltext Factors influencing occupational exposure to pyrethroids and glyphosate: An analysis of urinary biomarkers in Malaysia, Uganda and the United Kingdom
    Mueller W, Jones K, Fuhrimann S, Ahmad ZNBS, Sams C, Harding AH, et al.
    Environ Res, 2024 Feb 01;242:117651.
    PMID: 37996007 DOI: 10.1016/j.envres.2023.117651
    BACKGROUND: Long-term exposure to pesticides is often assessed using semi-quantitative models. To improve these models, a better understanding of how occupational factors determine exposure (e.g., as estimated by biomonitoring) would be valuable.

    METHODS: Urine samples were collected from pesticide applicators in Malaysia, Uganda, and the UK during mixing/application days (and also during non-application days in Uganda). Samples were collected pre- and post-activity on the same day and analysed for biomarkers of active ingredients (AIs), including synthetic pyrethroids (via the metabolite 3-phenoxybenzoic acid [3-PBA]) and glyphosate, as well as creatinine. We performed multilevel Tobit regression models for each study to assess the relationship between exposure modifying factors (e.g., mixing/application of AI, duration of activity, personal protective equipment [PPE]) and urinary biomarkers of exposure.

    RESULTS: From the Malaysia, Uganda, and UK studies, 81, 84, and 106 study participants provided 162, 384 and 212 urine samples, respectively. Pyrethroid use on the sampling day was most common in Malaysia (n = 38; 47%), and glyphosate use was most prevalent in the UK (n = 93; 88%). Median pre- and post-activity 3-PBA concentrations were similar, with higher median concentrations post-compared to pre-activity for glyphosate samples in the UK (1.7 to 0.5 μg/L) and Uganda (7.6 to 0.8 μg/L) (glyphosate was not used in the Malaysia study). There was evidence from individual studies that higher urinary biomarker concentrations were associated with mixing/application of the AI on the day of urine sampling, longer duration of mixing/application, lower PPE protection, and less education/literacy, but no factor was consistently associated with exposure across biomarkers in the three studies.

    CONCLUSIONS: Our results suggest a need for AI-specific interpretation of exposure modifying factors as the relevance of exposure routes, levels of detection, and farming systems/practices may be very context and AI-specific.

    Matched MeSH terms: Environmental Monitoring/methods
  9. Exploring the microplastic pollution: Unveiling origins and varieties in coastal sediments and waters of the Bushehr Province, Persian Gulf, Iran
    Gholizadeh M, Shadi A, Abadi A, Nemati M, Senapathi V, Karthikeyan S, et al.
    Mar Pollut Bull, 2024 Jan;198:115939.
    PMID: 38128339 DOI: 10.1016/j.marpolbul.2023.115939
    In this study, microplastic (MP) pollution in the coastal sediments and tidal waters of Bushehr province in the Persian Gulf was comprehensively investigated. The sampling stations were selected based on their proximity to various human activities in January and February 2022, such as tourism, fishing, urban development and industry. The results showed that the abundance of MP associated with different human activities varied. The highest concentrations were observed near the petrochemical industry in Asaluyeh, followed by the densely populated Bushehr and the fishing port of Dayyer. Other areas such as Ganaveh, Deylam and Mand also showed varying levels of MP contamination. The average MP concentration was 1.67 × 104 particles/km2 in surface water and 1346.67 ± 601.69 particles/kg in dry sediment. Fiber particles were in the majority in both sediment and water samples, mainly black. The sediment samples had a size range of 100-500 μm (41.34 %), while the water samples were between 500 and 1000 μm (33.44 %). The main polymers found were polyethylene (PE) and polypropylene (PP). This assessment highlights the widespread problem of microplastic pollution in the coastal and intertidal zones of Bushehr province in the Persian Gulf.
    Matched MeSH terms: Environmental Monitoring/methods
  10. Fulltext Assessment of coastal river water quality in Bangladesh: Implications for drinking and irrigation purposes
    Uddin MR, Khandaker MU, Ahmed S, Abedin MJ, Hossain SMM, Al Mansur MA, et al.
    PLoS One, 2024;19(4):e0300878.
    PMID: 38635835 DOI: 10.1371/journal.pone.0300878
    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.
    Matched MeSH terms: Environmental Monitoring/methods
  11. A review of personal exposure studies in selected Asian countries' public transport microenvironments: lessons learned and future directions
    Otuyo MK, Nadzir MSM, Latif MT, Din SAM
    Environ Sci Pollut Res Int, 2023 Dec;30(58):121306-121337.
    PMID: 37993649 DOI: 10.1007/s11356-023-30923-9
    This comprehensive paper conducts an in-depth review of personal exposure and air pollutant levels within the microenvironments of Asian city transportation. Our methodology involved a systematic analysis of an extensive body of literature from diverse sources, encompassing a substantial quantity of studies conducted across multiple Asian cities. The investigation scrutinizes exposure to various pollutants, including particulate matters (PM10, PM2.5, and PM1), carbon dioxide (CO2), formaldehyde (CH2O), and total volatile organic compounds (TVOC), during transportation modes such as car travel, bus commuting, walking, and train rides. Notably, our review reveals a predominant focus on PM2.5, followed by PM10, PM1, CO2, and TVOC, with limited attention given to CH2O exposure. Across the spectrum of Asian cities and transportation modes, exposure concentrations exhibited considerable variability, a phenomenon attributed to a multitude of factors. Primary sources of exposure encompass motor vehicle emissions, traffic dynamics, road dust, and open bus doors. Furthermore, our findings illuminate the influence of external environments, particularly in proximity to train stations, on pollutant levels inside trains. Crucial factors affecting exposure encompass ventilation conditions, travel-specific variables, seat locations, vehicle types, and meteorological influences. The culmination of this rigorous review underscores the need for standardized measurements, enhanced ventilation systems, air filtration mechanisms, the adoption of clean energy sources, and comprehensive public education initiatives aimed at reducing pollutant exposure within city transportation microenvironments. Importantly, our study contributes to the growing body of knowledge surrounding this subject, offering valuable insights for policymakers and researchers dedicated to advancing air quality standards and safeguarding public health.
    Matched MeSH terms: Environmental Monitoring/methods
  12. Fulltext Improving PM2.5 prediction in New Delhi using a hybrid extreme learning machine coupled with snake optimization algorithm
    Masood A, Hameed MM, Srivastava A, Pham QB, Ahmad K, Razali SFM, et al.
    Sci Rep, 2023 Nov 29;13(1):21057.
    PMID: 38030733 DOI: 10.1038/s41598-023-47492-z
    Fine particulate matter (PM2.5) is a significant air pollutant that drives the most chronic health problems and premature mortality in big metropolitans such as Delhi. In such a context, accurate prediction of PM2.5 concentration is critical for raising public awareness, allowing sensitive populations to plan ahead, and providing governments with information for public health alerts. This study applies a novel hybridization of extreme learning machine (ELM) with a snake optimization algorithm called the ELM-SO model to forecast PM2.5 concentrations. The model has been developed on air quality inputs and meteorological parameters. Furthermore, the ELM-SO hybrid model is compared with individual machine learning models, such as Support Vector Regression (SVR), Random Forest (RF), Extreme Learning Machines (ELM), Gradient Boosting Regressor (GBR), XGBoost, and a deep learning model known as Long Short-Term Memory networks (LSTM), in forecasting PM2.5 concentrations. The study results suggested that ELM-SO exhibited the highest level of predictive performance among the five models, with a testing value of squared correlation coefficient (R2) of 0.928, and root mean square error of 30.325 µg/m3. The study's findings suggest that the ELM-SO technique is a valuable tool for accurately forecasting PM2.5 concentrations and could help advance the field of air quality forecasting. By developing state-of-the-art air pollution prediction models that incorporate ELM-SO, it may be possible to understand better and anticipate the effects of air pollution on human health and the environment.
    Matched MeSH terms: Environmental Monitoring/methods
  13. An evaluation of spatial and seasonal distributions of dissolved trace metals in the water of the natural wetlands
    Alkhadher SAA, Suratman S, Mohd Sallan MIB
    J Environ Manage, 2023 Nov 01;345:118464.
    PMID: 37454570 DOI: 10.1016/j.jenvman.2023.118464
    The spatial and temporal distributions of trace metals in dissolved forms mainly result from anthropogenic and lithogenic contributions. Surface water samples (∼0.5 m) were collected monthly at respective stations from Setiu Wetland. In this study, the behaviour of trace metals in the dissolved phases along the water column from sampling sites in the Setiu Wetland, Malaysia was investigated. In addition, dissolved organic carbon (DOC) and physical parameters such as salinity, temperature, pH and dissolved oxygen (DO) of the surface water were measured in order to evaluate the relationship between trace metals fractionation with different water quality parameters. Size fractionation study of dissolved trace metals using ultrafiltration technique were also carried out and analysed using inductively coupled plasma mass spectrometry (ICP-MS). Correlation of trace metals with other measured parameters was made to furthermore understand the dynamics of trace metals and its fractionated components in this area. The concentration of dissolved trace metals was in the range of 0.001-0.16 μg/L for Cd, 0.12-2.81 μg/L for Cu, 0.01-1.84 μg/L for Pb, 3-17 μg/L for Fe and 1-34 μg/L for Zn, suggesting the input of anthropogenic sources for trace metals such as municipal, industrial, agricultural and domestic discharge. The periodic monitoring and evaluation of trace metals in wetlands and protected tropical areas is highly recommended.
    Matched MeSH terms: Environmental Monitoring/methods
  14. Fulltext A novel report on the occurrence of microplastics in Pekalongan River Estuary, Java Island, Indonesia
    Ismanto A, Hadibarata T, Kristanti RA, Sugianto DN, Widada S, Atmodjo W, et al.
    Mar Pollut Bull, 2023 Nov;196:115563.
    PMID: 37797535 DOI: 10.1016/j.marpolbul.2023.115563
    This study aimed to address the pressing issue of plastic pollution in aquatic ecosystems by assessing the prevalence and distribution of microplastics (MPs) in water and riverbank sediments of the Pekalongan River, a vital water source in Indonesia. From the present findings, MP concentrations in water ranged from 45.2 to 99.1 particles/L, while sediment concentrations ranged from 0.77 to 1.01 particles/g. This study revealed that fragment and film MPs constituted 30.1 % and 25.4 % of the total, respectively, with MPs measuring <1 mm and constituting 51.4 % of the total. Colored MPs, particularly blue and black MPs, accounted for 34 % of the total. The primary polymer components, as determined via Fourier transform infrared spectroscopy, were identified as polystyrene, polyester, and polyamide. In response to the escalating plastic waste crisis caused by single-use plastics, Pekalongan's local government implemented refuse segregation and recycling programs as part of its efforts to transition toward zero-waste practices.
    Matched MeSH terms: Environmental Monitoring/methods
  15. An integrated investigation of hydrocarbon pollution in Ahoada area, Niger Delta Region, Nigeria
    Umar HA, Khanan MFA, Shiru MS, Ahmad A, Rahman MZA, Din AHM
    Environ Sci Pollut Res Int, 2023 Nov;30(55):116848-116859.
    PMID: 36633746 DOI: 10.1007/s11356-023-25144-z
    This study investigates hydrocarbon pollution in the Ahoada community of the Niger Delta region of Nigeria. The study uses a geographic information system (GIS) for mapping oil spill hotspots in the region. The resistivity method was used to delineate the extent of hydrocarbon pollution to a depth of 19.7 m in the Ahoada area of the region. Three categories of soil samples, impacted soil (IMS), remediated soil (RS), and control soil (CS), were collected and analyzed for the presence of BTEX, PAH, TPH, TOC, and TOG. The concentrations of the samples from the IMS and RS were compared to that of the CS to determine the extent of pollution. The GIS mapping shows that the most polluted areas in the Niger Delta Region are Rivers, Bayelsa, and Delta states. Results of the geophysical images revealed contaminants' presence to depths beyond 20 m at some locations in the study area. The highest depth of contaminant travel was at Ukperede. Soil samples' analysis showed that the range of concentrations of TPH in IMS at Oshie was 17.27-58.36 mg/kg; RS was 11.73-50.78 mg/kg which were higher than the concentrations of 0.68 mg/kg in the CS. PAHs are more prevalent in Ukperede, ranging from 54.56 to 77.54 mg/kg. BTEX concentrations ranged from 0.02 to 0.38 mg/kg for IMP and 0.01-2.7 mg/kg for RS against a CS value of 0.01 mg/kg. The study revealed that there are characteristically high resistivity values in the samples which were corroborated by the findings from the resistivity survey. TOC was found to be higher in the IMS and RS than in the CS, demonstrating that a significant quantity of the hydrocarbon has undergone appreciable decomposition.
    Matched MeSH terms: Environmental Monitoring/methods
  16. Abundance and characteristics of microplastic in some commercial species from the Persian Gulf, Iran
    Gholizadeh M, Shadi A, Abadi A, Nemati M, Senapathi V, Karthikeyan S
    J Environ Manage, 2023 Oct 15;344:118386.
    PMID: 37352628 DOI: 10.1016/j.jenvman.2023.118386
    Global production of plastics has increased dramatically in recent decades and is considered a major threat to marine life and human health due to their stability, persistence, and potential to move through food chains. The study was conducted to detect, identify and quantify microplastics (MP) in the gastrointestinal tract (GI) of some commercial fish species in the North Persian Gulf in Bushehr Province: Psettodes erumei, Sphyraena jello, Sillago sihama, Metapenaeus affinis and Portunus segnis. A total of 216 plastic particles were collected from 102 individuals (72.68% of all sampled individuals; MP prevalence of 85.1% for M. affinis, 80% for P. segnis, 70% for P.erumei, 60.3% for S.sihama, 45.2% for S.jello). The average number of microplastics per organism was 2.26 ± 0.38 MP/ind (considering only species that ingested plastic, n = 102) and 1.51 ± 0.40 pieces/ind (considering all species studied, n = 140). Microfibers accounted for 58.49% of the total microplastics, followed by fragments (33.02%) and pellets (8.49%). The most common color of microplastic was black (52.83%), followed by blue (22.64%) and transparent (15.09%). The length of microplastic ranged from 100 to 5000 μm with an average of 854 ± 312 μm. Microplastics were significantly (p 
    Matched MeSH terms: Environmental Monitoring/methods
  17. Seasonal influence on physicochemical properties of the sediments from Bay of Bengal coast with statistical approach
    Pandion K, Dowlath MJH, Arunachalam KD, Abd-Elkader OH, Yadav KK, Nazir N, et al.
    Environ Res, 2023 Oct 15;235:116611.
    PMID: 37437863 DOI: 10.1016/j.envres.2023.116611
    The current study aims to investigate the influence of seasonal changes on the pollution loads of the sediment of a coastal area in terms of its physicochemical features. The research will focus on analyzing the nutrients, organic carbon and particle size of the sediment samples collected from 12 different sampling stations in 3 different seasons along the coastal area. Additionally, the study discusses about the impact of anthropogenic activities such as agriculture and urbanization and natural activities such as monsoon on the sediment quality of the coastal area. The nutrient changes in the sediment were found to be: pH (7.96-9.45), EC (2.89-5.23 dS/m), nitrogen (23.98-57.23 mg/kg), phosphorus (7.75-11.36 mg/kg), potassium (217-398 mg/kg), overall organic carbon (0.35-0.99%), and sediment proportions (8.91-9.3%). Several statistical methods were used to investigate changes in sediment quality. According to the three-way ANOVA test, the mean value of the sediments differs significantly with each season. It correlates significantly with principal factor analysis and cluster analysis across seasons, implying contamination from both natural and man-made sources. This study will contribute to developing effective management strategies for the protection and restoration of degraded coastal ecosystem.
    Matched MeSH terms: Environmental Monitoring/methods
  18. Fulltext Air quality prediction by machine learning models: A predictive study on the indian coastal city of Visakhapatnam
    Ravindiran G, Hayder G, Kanagarathinam K, Alagumalai A, Sonne C
    Chemosphere, 2023 Oct;338:139518.
    PMID: 37454985 DOI: 10.1016/j.chemosphere.2023.139518
    Clean air is critical component for health and survival of human and wildlife, as atmospheric pollution is associated with a number of significant diseases including cancer. However, due to rapid industrialization and population growth, activities such as transportation, household, agricultural, and industrial processes contribute to air pollution. As a result, air pollution has become a significant problem in many cities, especially in emerging countries like India. To maintain ambient air quality, regular monitoring and forecasting of air pollution is necessary. For that purpose, machine learning has emerged as a promising technique for predicting the Air Quality Index (AQI) compared to conventional methods. Here we apply the AQI to the city of Visakhapatnam, Andhra Pradesh, India, focusing on 12 contaminants and 10 meteorological parameters from July 2017 to September 2022. For this purpose, we employed several machine learning models, including LightGBM, Random Forest, Catboost, Adaboost, and XGBoost. The results show that the Catboost model outperformed other models with an R2 correlation coefficient of 0.9998, a mean absolute error (MAE) of 0.60, a mean square error (MSE) of 0.58, and a root mean square error (RMSE) of 0.76. The Adaboost model had the least effective prediction with an R2 correlation coefficient of 0.9753. In summary, machine learning is a promising technique for predicting AQI with Catboost being the best-performing model for AQI prediction. Moreover, by leveraging historical data and machine learning algorithms enables accurate predictions of future urban air quality levels on a global scale.
    Matched MeSH terms: Environmental Monitoring/methods
  19. Impacts of industrial production and air quality by remote sensing on nitrogen dioxide concentration and related effects: An econometric approach
    Kurniawan R, Budi Alamsyah AR, Fudholi A, Purwanto A, Sumargo B, Gio PU, et al.
    Environ Pollut, 2023 Oct 01;334:122212.
    PMID: 37454714 DOI: 10.1016/j.envpol.2023.122212
    The high concentration of nitrogen dioxide (NO2) is to blame for West Java's poor Air Quality Index (AQI). So, this study aims to determine the influence of industrial activity as reflected by the value of its imports and exports, wind speed, and ozone (O3) on the high concentration of tropospheric NO2. The method used is the econometric Vector Error Correction Model (VECM) approach to capture the existence of a short-term and long-term relationship between tropospheric NO2 and its predictor variables. The data used in this study is in the form of monthly time series data for the 2018-2022 period sourced from satellite images (Sentinel-5P and ECMWF Climate Reanalysis) and publications of the Central Bureau of Statistics (BPS-Statistics Indonesia). The results explained that, in the short-term, tropospheric NO2 and O3 influence each other as they would in a photochemical reaction. In the long-term, exports from the industrial sector and wind speed have a significant effect on the concentration of tropospheric NO2. The short-term effect occurs directly in the first month after the shock, while the long-term effect occurs in the second month after the shock. Wind gusts originating from industrial areas cause air conditions to be even more alarming because tropospheric NO2 pollutants spread throughout the region in West Java. Based on the coefficient correlation result, the high number of pneumonia cases is one of the impacts caused by air pollution.
    Matched MeSH terms: Environmental Monitoring/methods
  20. Microplastics pollution in mud crab (Scylla sp.) aquaculture system: First investigation and evidence
    Hossain S, Ahmad Shukri ZN, Waiho K, Ibrahim YS, Minhaz TM, Kamaruzzan AS, et al.
    Environ Pollut, 2023 Jul 15;329:121697.
    PMID: 37088255 DOI: 10.1016/j.envpol.2023.121697
    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.
    Matched MeSH terms: Environmental Monitoring/methods
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