AIMC Topic: Environmental Monitoring

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Estimating the spatial distribution and exploring the factors influencing cultivated land quality through a hybrid random forest and Bayesian maximum entropy model.

Environmental research
Cultivated land is one of the most valuable agricultural resources; its quality is not only the foundation of national food security but also a crucial issue for global sustainable development. However, owing to data limitations and spatial heterogen...

Deep learning-based screening approach for priority pollutants: a case study on retired power battery recycling.

Environmental pollution (Barking, Essex : 1987)
With the rapid increase in the production of retired power batteries, the potential environmental risks during recycling must urgently be identified and assessed. This study presented a novel screening framework for pollutant prioritization utilizing...

Artificial intelligence tools to assess different levels of activity performed by semi-wild horses in grassland ecosystems.

Environmental monitoring and assessment
In order to understand the role of horses in ecosystems and to effectively use their grazing in the protection of grasslands, it is important to assess where they primarily stay, followed by whether these habitats are used for grazing or resting. The...

Machine learning prediction of DOC-water partitioning coefficients for organic pollutants from diverse DOM origins.

Environmental science. Processes & impacts
This study aims to improve predictions and understanding of dissolved organic carbon-water partitioning coefficients (), a crucial parameter in environmental risk assessment. A dataset encompassing 709 datapoints across 190 unique organic pollutants ...

Urbanization intensifies deterministic selection of pathogenic bacteria in river networks: Nitrogen-driven niche partitioning and cross-scale risk forecasting through DOM-bacteria interplay.

Environmental research
Urbanization modifies the composition of dissolved organic matter (DOM) and nitrogen nutrients, profoundly affecting river microbial communities. However, the mechanisms driving pathogenic and non-pathogenic bacteria remain unclear. In this study, we...

Unraveling long-term health dynamics of impounded lakes integrating water diversion-adapted planktonic index of biotic integrity and machine learning.

Environmental research
Assessing ecosystem integrity of impounded lakes subjected to sustained water diversion is fundamental for advancing adaptive water governance. Nevertheless, drivers of lake health variation under recurrent flow regulation, particularly their multisc...

Predicting the Site-Specific Toxicity of Metals to Fishes Using a New Machine Learning-Based Approach.

Environmental science & technology
Fishes of various trophic levels play an important role in the stability and balance of aquatic ecosystems. Metal contaminants can impair the survival and population fitness of fish at elevated concentrations. When universal water quality criteria (W...

Distribution mapping and risk assessment of lead in topsoil across the Tibetan Plateau.

Ecotoxicology and environmental safety
Lead exposure poses substantial long-term health risks, accounting for over 900,000 annual deaths worldwide and impairing cognitive development in more than 800 million children. Recent studies have indicated elevated soil lead contamination levels o...

The serious loss of mangrove forest over the largest delta of Africa, Niger Delta: causes and reasons.

Marine environmental research
While global mangrove forests have suffered significant loss, raising widespread concern, little information is available on how mangrove forests have changed along Africa's coast. This study employed multi-temporal remote sensing data and machine le...

Matrix-specific PFAS source allocation machine learning-based models: Identifying differential indicators in soil and water systems.

Environmental research
PER: and polyfluoroalkyl substances (PFAS) pose a significant environmental and human health risk due to their persistence, bioaccumulation, mobility, and toxicity. Current PFAS source-allocation methods often demand data on many compounds while over...