Environmental Risk Assessment of Trace Metal Pollution: A Statistical Perspective

Environmental Geochemistry and Health, Journal Year: 2025, Volume and Issue: 47(4)

Published: Feb. 28, 2025

Abstract Trace metal pollution is primarily driven by industrial, agricultural, and mining activities presents complex environmental challenges with significant implications for ecological human health. Traditional methods of risk assessment (ERA) often fall short in addressing the intricate dynamics trace metals, necessitating adoption advanced statistical techniques. This review focuses on integrating contemporary methods, such as Bayesian modeling, machine learning, geostatistics, into ERA frameworks to improve precision, reliability, interpretability. Using these innovative approaches, either alone or preferably combination, provides a better understanding mechanisms transport, bioavailability, their impacts can be achieved while also predicting future contamination patterns. The use spatial temporal analysis, coupled uncertainty quantification, enhances hotspots associated risks. Integrating models ecotoxicology further strengthens ability evaluate health risks, providing broad framework managing pollution. As new contaminants emerge existing pollutants evolve behavior, need adaptable, data-driven methodologies becomes ever more pressing. advancement tools interdisciplinary collaboration will essential developing effective management strategies informing policy decisions. Ultimately, lies diverse data sources, analytical techniques, stakeholder engagement, ensuring resilient approach mitigating protecting public

Language: Английский

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Effects of urban sprawl due to migration on spatiotemporal land use-land cover change: a case study of Bartın in Türkiye

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 4, 2025

Rapid urban growth is a subject of worldwide interest due to environmental problems. Population growth, especially migration from rural areas, leads land use and cover (LULCC) changes in centres. Therefore, LULCC analyses are among the studies that will help decision-makers achieve better sustainable management planning. The objective this study was ascertain impact urbanization, which resulted migration, on alterations LULCC, with particular focus forest areas surrounding Bartın city centre between 2000 2020. Spatial databases for two periods were used determine growth. spatial temporal patterns quantified by interpreting data. Remote sensing (RS) geographical information systems (GIS) have been data collection, analysis, presentation. assessed under nine classes using optical remote methods stand-type maps created aerial photos. To how affects status transition matrices each five sprawl zones around city. annual change determined "annual rate". results indicate urbanization 2020 increased approximately 19% (2510645.82 m2). However, did not harm forests; 10.32% (174729.65 m²) over same period. process particularly evident open agricultural zones. During period, there 37% reduction (2943229.85 59% (1265457.76 m²). can be attributed its demographic structure, mainly includes population emergence new job opportunities. Factors such as challenging living conditions, insecure environments because increase temporary foreign asylum seekers, retirees returning their hometowns believed contributed

Language: Английский

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Combatting toxic chemical elements pollution for sub-Saharan Africa's ecological health

Environmental Pollution and Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Hydrological low flow and overlapped trend analysis for drought assessment in Western Black Sea Basin

Natural Hazards, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 22, 2024

Language: Английский

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Spider Webs as Biomonitoring Tool for Heavy Metal Pollution in Diverse Environments: A Study in Kochi City

Environmental Quality Management, Journal Year: 2025, Volume and Issue: 34(4)

Published: March 20, 2025

ABSTRACT This study evaluates the use of webs from two species spiders, Cyrtophora cicatrosa and Pholcus phalangioides , as biomonitoring tools for heavy metal pollution across diverse environments in Kochi city, Kerala, India. Web samples Thevara, Eloor, Kizhakkambalam, representing urban, industrial, semi‐urban/agricultural areas, respectively, were analyzed Cr, Cu, Mn, Mo, Ni, Pb, Sn, Zn concentrations using ICP‐OES spectroscopy. Results showed site‐specific variation, with reaching its highest concentration Eloor (7558 ppm) Kizhakkambalam (4947.50 ppm). Relative distribution results revealed that Sn dominant metals accumulated most sites. The principal component analysis (PCA) highlight capture a broad range agricultural sources, while show specific affinities industrial urban pollutants, suggesting stronger sensitivity to urban‐industrial pollution. These findings demonstrate spider offer cost‐effective, species‐specific, non‐invasive approach environmental monitoring, enabling targeted assessment informing effective mitigation strategies settings.

Language: Английский

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Comparative Analysis of Data Visualization and Deep Learning Models in Air Quality Forecasting

Sakarya University Journal of Computer and Information Sciences, Journal Year: 2025, Volume and Issue: 8(1), P. 89 - 111

Published: March 27, 2025

This study utilizes air pollution data from the Continuous Monitoring Center of Ministry Environment, Urbanization, and Climate Change in Turkey to predict various pollutants using three advanced deep learning approaches: LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), RNN (Recurrent Network). Missing dataset were imputed K-Nearest Neighbor (K-NN) algorithm ensure completeness. Furthermore, a fusion technique was applied integrate multiple pollutant enhancing richness reliability input features for modeling. The increasing issue, driven by factors such as population growth, urbanization, industrial development, is major environmental concern. evaluates these models estimate concentrations selects most accurate, RNN, forecasting over next years. Each prediction assessed performance metrics MAE, RMSE, R² robust model evaluation. Visualization forecast results achieved through methods like Box Plots, Violin Point Scatter Graphs, making quality information more accessible general audiences. In terms performance, an 0.88 PM10 0.93 SO2, while demonstrated 0.94 0.95 SO2. However, emerged accurate model, achieving 0.97 both SO2 forecasts. allows forecasts levels three-year period. findings indicate that predictive modeling, combined with visualization techniques, could significantly contribute mitigating future uncertainties enhance comprehension patterns non-expert

Language: Английский

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The Effect of Compost and Moringa Leaf Extract Biostimulant on the Phytoremediation of Gold Mine Tailing Storage Facilities in South Africa Using Chrysopogon Zizanioides (L.) Roberty

Published: Jan. 1, 2025

Language: Английский

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Assessing heavy metal pollution in urban children's playgrounds: comparative analysis of soil, dust, and moss bioaccumulation

Journal of Environmental Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

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Source profiling, pollution and health risk assessment of heavy metals in agricultural soils around an industrial cluster using PCA and GIS-assisted PMF

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(7)

Published: June 2, 2025

Language: Английский

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Toxic metal accumulation, health risk, and distribution in road dust from the urban traffic-intensive environment

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(51), P. 60792 - 60803

Published: Oct. 11, 2024

Language: Английский

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