AIMC Topic: Environmental Pollution

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Machine learning in ecotoxicology: Pollutant exposure levels and detection, biotoxicity and environmental behavior prediction.

The Science of the total environment
In recent years, the worsening problem of environmental pollution and the limitations of traditional toxicological assays have accelerated the adoption of machine learning (ML) in ecotoxicology. ML enables rapid and accurate prediction of pollutant e...

Using XGBoost and memetic programming to identify hotspots of sediment plastic pollution.

Environmental pollution (Barking, Essex : 1987)
Despite growing global initiatives on sustainable plastic management, less than 10 % of plastic waste is effectively recycled, resulting in widespread environmental dispersion and pollution. This study examines the relative influence of topographic, ...

Quantitative inversion of soil heavy metal pollution using a GA-BP neural network model.

Environmental monitoring and assessment
With the rapid development of industrialization in China, significant economic benefits have been accompanied by varying degrees of threat to the soil environment, particularly from heavy metal pollution. The rapid quantitative inversion of heavy met...

Integrating pollution indices, spatial interpolation, and machine learning for soil contamination analysis along the Zarqa River, Jordan.

Environmental monitoring and assessment
This study assesses soil contamination along the Zarqa River (ZR) in Jordan by integrating pollution indices, geostatistical interpolation, and machine learning models. We collected 34 soil samples from agricultural lands within the study area. Sampl...

Unlocking urban soil secrets: machine learning and spectrometry in Berlin's heavy metal pollution study considering spatial data.

Environmental monitoring and assessment
Berlin has historically been impacted by heavy metal (HM) emissions, raising concerns about soil pollution. In this study, machine learning (ML) techniques were applied to predict HM concentrations across the Berlin metropolitan area. A dataset of 66...

Uncovering soil heavy metal pollution hotspots and influencing mechanisms through machine learning and spatial analysis.

Environmental pollution (Barking, Essex : 1987)
Soil heavy metal (HM) pollution is a significant and widespread environmental issue in China, highlighting the need to quantify influencing factors and identify priority concern areas for effective prevention and management. Based on published litera...

A novel graph convolutional neural network model for predicting soil Cd and As pollution: Identification of influencing factors and interpretability.

Ecotoxicology and environmental safety
Soil pollution caused by toxic metals poses serious threats to the ecological environment and human well-being. Accurately predicting toxic metal concentrations is critical for safeguarding soil environmental security. However, the distribution of so...

Managerial myopia and its barrier to green innovation in high-pollution enterprises: A machine learning approach.

Journal of environmental management
Green technology innovation has become a vital remedy in response to the world's growing ecological problems and the urgent need for sustainable development. However, businesses are sometimes discouraged from undertaking such efforts due to the signi...

Pollution risk assessment in sub-basins of an open dump using drones and geographic information systems.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
The sustainable management of municipal solid waste (MSW) presents a pressing global challenge. This study introduces an innovative methodology for analysing open dumps in Tucumán, Argentina, using unmanned aerial vehicles (UAVs) and DroneDeploy soft...

MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting.

Journal of exposure science & environmental epidemiology
BACKGROUND: Many chemical releases are first noticed by community members, but reporting these concerns often involves considerable hurdles. Artificial Intelligence (AI)-enabled technologies, especially large language models (LLMs), can potentially r...