AIMC Topic: Vehicle Emissions

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A method for delineating traffic low emission control zone based on deep learning and multi-objective optimization.

Environmental monitoring and assessment Apr 8, 2025
Current methods for defining traffic low emission control zones (TLEZ) often face limitations that hinder their widespread implementation and effectiveness. This study addresses these challenges by employing a comprehensive approach to analyze PM con...
Deep Learning Cities Air Pollution Particulate Matter Vehicle Emissions Environmental Monitoring Air Pollutants
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Explainable AI analysis for smog rating prediction.

Scientific reports Mar 8, 2025
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...
Vehicle Emissions Machine Learning Environmental Monitoring Humans
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An ML-Enhanced Laser-Based Methane Slip Sensor Using Wavelength Modulation Spectroscopy.

ACS sensors Jan 15, 2025
Natural gas (NG) is a promising alternative to diesel for sustainable transport, potentially reducing GHG and air quality emissions significantly. However, the GHG benefits hinge on managing methane slip, the unburned methane in the exhaust of NG eng...
Spectrum Analysis Machine Learning Lasers Methane Natural Gas Vehicle Emissions
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Machine learning helps reveal key factors affecting tire wear particulate matter emissions.

Environment international Dec 19, 2024
Tire wear particles (TWPs) are generated with every rotation of the tire. However, obtaining TWPs under real driving conditions and revealing key factors affecting TWPs are challenging. In this study, we obtained a TWPs dataset by simulating tire wea...
Air Pollutants Air Pollution Particulate Matter Machine Learning Environmental Monitoring Vehicle Emissions
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Forecasting air pollution with deep learning with a focus on impact of urban traffic on PM10 and noise pollution.

PloS one Dec 10, 2024
Air pollution constitutes a significant worldwide environmental challenge, presenting threats to both our well-being and the purity of our food supply. This study suggests employing Recurrent Neural Network (RNN) models featuring Long Short-Term Memo...
Vehicle Emissions Air Pollution Noise Deep Learning COVID-19 Environmental Monitoring Particulate Matter Air Pollutants Cities Forecasting Humans Neural Networks, Computer
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Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study.

Environmental science & technology Dec 5, 2024
The sulfuric acid (SA)-amine nucleation mechanism gained increasing attention due to its important role in atmospheric secondary particle formation. However, the intrinsic enhancing potential (IEP) of various amines remains largely unknown, restraini...
Ethanol Vehicle Emissions Amines Machine Learning Sulfuric Acids Gasoline
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Urban road BC emissions of LDGVs: Machine learning models using OBD/PEMS data.

Chemosphere Sep 14, 2024
Urban Black Carbon (BC) emissions from light-duty gasoline vehicles (LDGVs) are challenging to quantify in real-world settings. This study employed a Portable Emission Measurement System (PEMS) to assess BC emissions from five LDGVs on urban roads. W...
Environmental Monitoring Machine Learning Gasoline Air Pollutants China Soot Vehicle Emissions Cities
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Combining Google traffic map with deep learning model to predict street-level traffic-related air pollutants in a complex urban environment.

Environment international Sep 6, 2024
BACKGROUND: Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varies sharply at the street level, posing a challenge for air quality modeling. Traditional land use regression models combined with data from fixed monit...
Air Pollution Hong Kong Nitrogen Oxides Traffic-Related Pollution Vehicle Emissions Environmental Monitoring Deep Learning Air Pollutants Cities
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Characterizing sector-oriented roadside exposure to ultrafine particles (PM) via machine learning models: Implications of covariates influences on sectors variability.

Environmental pollution (Barking, Essex : 1987) Jul 23, 2024
Ultrafine particles (UFPs; PM) possess intensified health risk due to their smaller size and unique spatial variability. One of major emission sources for UFPs is vehicle exhaust, which varies based on the traffic composition in each type of roadside...
Particle Size Humans Air Pollutants Inhalation Exposure Child Air Pollution Machine Learning Particulate Matter Vehicle Emissions Environmental Monitoring Adult Environmental Exposure
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VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM.

Environmental science and pollution research international Apr 26, 2024
Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing...
Neural Networks, Computer Support Vector Machine Volatile Organic Compounds Vehicle Emissions Gas Chromatography-Mass Spectrometry Odorants
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