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Environmental Monitoring

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Predicting surface soil pH spatial distribution based on three machine learning methods: a case study of Heilongjiang Province.

Environmental monitoring and assessment
Comprehensive and accurate acquisition of surface soil pH spatial distribution information is essential for monitoring soil degradation and providing scientific guidance for agricultural practices. This study focused on Heilongjiang Province in China...

Explainable AI analysis for smog rating prediction.

Scientific reports
Smog poses a direct threat to human health and the environment. Addressing this issue requires understanding how smog is formed. While major contributors include industries, fossil fuels, crop burning, and ammonia from fertilizers, vehicles play a si...

AI-driven approaches for air pollution modelling: A comprehensive systematic review.

Environmental pollution (Barking, Essex : 1987)
In recent years, air quality levels have become a global issue with the rise of harmful pollutants and their effects on climate change. Urban areas are especially affected by air pollution, resulting in a deterioration of the environment and a surge ...

Forecasting deforestation and carbon loss across New Guinea using machine learning and cellular automata.

The Science of the total environment
The island of New Guinea harbors some of the world's most biologically diverse and highly endemic tropical ecosystems. Nevertheless, progressing land-use change in the region threatens their integrity, which will adversely affect their biodiversity a...

Uncovering key sources of regional ozone simulation biases using machine learning and SHAP analysis.

Environmental pollution (Barking, Essex : 1987)
Atmospheric chemical transport models (CTMs) are widely used in air quality management, but still have large biases in simulations. Accurately and efficiently identifying key sources of simulation biases is crucial for model improvement. However, tra...

Advanced deep learning models for predicting elemental concentrations in iron ore mine using XRF data: a cost-effective alternative to ICP-MS methods.

Environmental geochemistry and health
Accurate elemental analysis is a critical requirement for mineral exploration, particularly in regions like Iran, where the mining sector has experienced a substantial increase in exploration activities over the past decade. Inductively Coupled Plasm...

Prediction of chlorination degradation rate of emerging contaminants based on machine learning models.

Environmental pollution (Barking, Essex : 1987)
Assessing the degradation of emerging contaminants in water through chlorination is crucial for regulatory monitoring of these contaminants. In this study, we developed a machine learning model to predict the apparent second-order reaction rate const...

Prediction of landfill gases concentration based on Grey Wolf Optimization - Support Vector Regression during landfill excavation process.

Waste management (New York, N.Y.)
In some areas, there is a phenomenon that the landfill is full or even over-capacity with the extension of the service period. With the aging and damage of the protective facilities, this phenomenon may have a more serious impact on the surrounding e...

Prediction of surface water pollution using wavelet transform and 1D-CNN.

Water science and technology : a journal of the International Association on Water Pollution Research
Permanganate index (COD), total nitrogen, and ammonia nitrogen are important indicators that represent the degree of pollution of surface water. This study combined ultraviolet-visible (UV-vis) spectroscopy with a one-dimensional convolutional neural...

Prediction of river dissolved oxygen (DO) based on multi-source data and various machine learning coupling models.

PloS one
Too low a concentration of dissolved oxygen (DO) in a river can disrupt the ecological balance, while too high a concentration may lead to eutrophication of the water body and threaten the health of the aquatic environment. Therefore, accurate predic...