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Environmental Monitoring

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Machine learning-based evolution of water quality prediction model: An integrated robust framework for comparative application on periodic return and jitter data.

Environmental pollution (Barking, Essex : 1987)
Accurate water quality prediction is paramount for the sustainable management of surface water resources. Current deep learning models face challenges in reliably forecasting water quality due to the non-stationarity of environmental conditions and t...

A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.

Sensors (Basel, Switzerland)
Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollution on human health and ecosystems. Due to the limited number and geographical coverage of advanced, highly accurate sensors monitoring air pollutants, ...

An investigation of microbial groundwater contamination seasonality and extreme weather event interruptions using "big data", time-series analyses, and unsupervised machine learning.

Environmental pollution (Barking, Essex : 1987)
Temporal studies of groundwater potability have historically focused on E. coli detection rates, with non-E. coli coliforms (NEC) and microbial concentrations remaining understudied by comparison. Additionally, "big data" (i.e., large, diverse datase...

Combining deep learning and machine learning techniques to track air pollution in relation to vegetation cover utilizing remotely sensed data.

Journal of environmental management
The rapid urban expansion in Dhaka, the capital of Bangladesh, has escalated air pollution levels and led to a significant decrease in green spaces. This study employed machine learning (ML) and deep learning (DL) techniques to examine the relationsh...

Development of a method for detecting and classifying hydrocarbon-contaminated soils via laser-induced breakdown spectroscopy and machine learning algorithms.

Environmental science and pollution research international
In recent years, there has been a significant increase in oil exploration and exploitation activities, resulting in spills that pose a severe threat to the environment and public health. The present work aims to develop a method to detect and classif...

Advancing Source Apportionment of Atmospheric Particles: Integrating Morphology, Size, and Chemistry Using Electron Microscopy Technology and Machine Learning.

Environmental science & technology
To further reduce atmospheric particulate matter concentrations, there is a need for a more precise identification of their sources. The SEM-EDS technology (scanning electron microscopy and energy-dispersive X-ray spectroscopy) can provide high-resol...

Integration of remote sensing and machine learning algorithm for agricultural drought early warning over Genale Dawa river basin, Ethiopia.

Environmental monitoring and assessment
Drought remains a menace in the Horn of Africa; as a result, the Ethiopia's Genale Dawa River Basin is one of the most vulnerable to agricultural drought. Hence, this study integrates remote sensing and machine learning algorithm for early warning id...

Integrated machine learning-based optimization framework for surface water quality index comparing coastal and non-coastal cases of Guangxi, China.

Marine pollution bulletin
In this study, an optimized comprehensive water quality index (WQI) model framework is developed, which combines advanced machine learning technology to compare different types of surface water quality assessment. The proposed framework enhancement e...

Detecting living microalgae in ship ballast water based on stained microscopic images and deep learning.

Marine pollution bulletin
Motivated by the need of rapid detection of living microalgae cells in ship ballast water, this study is intended to determine the activities of microalgae using stained microscopic images and detect the living cells with image processing algorithms....

Assessing the impact of rainfall, topography, and human disturbances on nutrient levels using integrated machine learning and GAMs models in the Choctawhatchee River Watershed.

Journal of environmental management
Nutrient pollution caused by excessive total nitrogen (TN) and total phosphorus (TP) is a significant environmental challenge globally, threatening water quality and ecosystem health. This study investigates the interplay between rainfall, topography...