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Environmental Monitoring

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Quality evaluation parameter and classification model for effluents of wastewater treatment plant based on machine learning.

Water research
With the growing consensus of emerging pollutants and biological toxicity risks in wastewater treatment plant (WWTP) effluents, traditional water quality management based on general chemical parameters no longer meets the new challenges. Here, a firs...

From microplastics to pixels: testing the robustness of two machine learning approaches for automated, Nile red-based marine microplastic identification.

Environmental science and pollution research international
Despite the urgent need for accurate and robust observations of microplastics in the marine environment to assess current and future environmental risks, existing procedures remain labour-intensive, especially for smaller-sized microplastics. In addi...

Machine learning models reveal how polycyclic aromatic hydrocarbons influence environmental bacterial communities.

The Science of the total environment
Polycyclic aromatic hydrocarbons (PAHs) are harmful and widespread pollutants in the environment, posing an ecological threat. However, exploring the influence of PAHs on environmental bacterial communities in different habitats (soil, water, and sed...

Derivation of marine water quality criteria for copper based on artificial neural network model.

Environmental pollution (Barking, Essex : 1987)
The water chemical effects of copper have been a focus in the study of water quality criteria (WQC). Currently, multiple regression models are commonly used to quantitatively describe the impact of environmental factors on Cu toxicity in WQC studies....

Imaging pollen using a Raspberry Pi and LED with deep learning.

The Science of the total environment
The production of low-cost, small footprint imaging sensor would be invaluable for airborne global monitoring of pollen, which could allow for mitigation of hay fever symptoms. We demonstrate the use of a white light LED (light emitting diode) to ill...

Pharmaceuticals and personal care product modelling: Unleashing artificial intelligence and machine learning capabilities and impact on one health and sustainable development goals.

The Science of the total environment
The presence of pharmaceutical and personal care products (PPCPs) in the environment poses a significant threat to environmental resources, given their potential risks to ecosystems and human health, even in trace amounts. While mathematical modellin...

3DVar sectoral emission inversion based on source apportionment and machine learning.

Environmental pollution (Barking, Essex : 1987)
Air quality models are increasingly important in air pollution forecasting and control. Sectoral emissions significantly impact the accuracy of air quality models and source apportionment. This paper studied the 3DVar (three-dimensional variational) ...

Enhancing indoor PM predictions based on land use and indoor environmental factors by applying machine learning and spatial modeling approaches.

Environmental pollution (Barking, Essex : 1987)
The presence of fine particulate matter (PM) indoors constitutes a significant component of overall PM exposure, as individuals spend 90% of their time indoors; however, personal monitoring for large cohorts is often impractical. In light of this, th...

Deciphering the impact of cascade reservoirs on nitrogen transport and nitrate transformation: Insights from multiple isotope analysis and machine learning.

Water research
Construction of cascade reservoirs has altered nutrient dynamics and biogeochemical cycles, thereby influencing the composition and productivity of river ecosystems. The Lancang River (LCR), characterized by its cascade reservoir system, presents unc...

Enhancing local-scale groundwater quality predictions using advanced machine learning approaches.

Journal of environmental management
Assessing groundwater quality typically involves labor-intensive, time-consuming, and costly laboratory tests, making real-time monitoring impractical, especially at the local level. Groundwater quality projections at the local scale using broad spat...