AI Medical Compendium Journal:
Environmental science & technology

Showing 21 to 30 of 131 articles

Combination of Density Functional Theory and Machine Learning Provides Deeper Insight of the Underlying Mechanism in the Ultraviolet/Persulfate System.

Environmental science & technology
The competition between radical and nonradical processes in the activated persulfate system is a captivating and challenging topic in advanced oxidation processes. However, traditional research methods have encountered limitations in this area. This ...

IodoFinder: Machine Learning-Guided Recognition of Iodinated Chemicals in Nontargeted LC-MS/MS Analysis.

Environmental science & technology
Iodinated disinfection byproducts (I-DBPs) pose significant health concerns due to their high toxicity. Current approaches to recognize unknown I-DBPs in mass spectrometry (MS) analysis rely on negative ionization mode, in which the characteristic I ...

Predicting Toxicity toward Nitrifiers by Attention-Enhanced Graph Neural Networks and Transfer Learning from Baseline Toxicity.

Environmental science & technology
Assessing chemical environmental impacts is critical but challenging due to the time-consuming nature of experimental testing. Graph neural networks (GNNs) support superior prediction performance and mechanistic interpretation of (eco-)toxicity data,...

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO Emissions.

Environmental science & technology
Satellite data provides essential insights into the spatiotemporal distribution of CO concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and...

Constructing the 3D Spatial Distribution of the HCHO/NO Ratio via Satellite Observation and Machine Learning Model.

Environmental science & technology
The satellite-based tropospheric column ratio of HCHO to NO (FNR) is widely used to diagnose ozone formation sensitivity; however, its representation of surface conditions remains controversial. In this study, an approach to construct the 3D spatial ...

Climate Sustainability through AI-Crypto Synergies and Energy Transition in the Digital Landscape to Cut 0.7 GtCOe by 2030.

Environmental science & technology
The rapid expansion of artificial intelligence (AI)-enabled systems and cryptocurrency mining poses significant challenges to climate sustainability due to energy-intensive operations relying on fossil-powered grids. This work investigates the strate...

Deciphering and Mitigating of Dynamic Greenhouse Gas Emission in Urban Drainage Systems with Knowledge-Infused Graph Neural Network.

Environmental science & technology
Deciphering and mitigating dynamic greenhouse gas (GHG) emissions under environmental fluctuation in urban drainage systems (UDGSs) is challenging due to the absence of a high-prediction model that accurately quantifies the contributions of biologica...

Data-Driven Insights into Resin Screening for Targeted Per- and Polyfluoroalkyl Substances Removal Using Machine Learning.

Environmental science & technology
In this study, we address the challenge of screening resins and optimizing operation conditions for the removal of 43 perfluoroalkyl and polyfluoroalkyl substances (PFASs), spanning both long- and short-chain fluorocarbon variants, across diverse wat...

An Enhanced Protocol to Expand Human Exposome and Machine Learning-Based Prediction for Methodology Application.

Environmental science & technology
The human exposome remains limited due to the challenging analytical strategies used to reveal low-level endocrine-disrupting chemicals (EDCs) and their metabolites in serum and urine. This limits the integrity of the EDC exposure assessment and hind...

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...