AIMC Topic: Aerosols

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Separating Daily 1 km PM Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data.

Environmental science & technology Apr 28, 2023
Fine particulate matter (PM) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model si...
China Environmental Monitoring Air Pollutants Reproducibility of Results Deep Learning Aerosols Inorganic Chemicals Respiratory Aerosols and Droplets Particulate Matter Seasons Air Pollution
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Modelling and optimization study to improve the filtration performance of fibrous filter.

Chemosphere Dec 27, 2022
Fibrous filter made up of non-woven material was utilized in many industrial applications for increasing the collection efficiency and the quality factor. But there exists a competing effect among the fibre diameter, filtration efficiency, pressure d...
Filtration Neural Networks, Computer Aerosols
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Virtual Impactor-Based Label-Free Pollen Detection using Holography and Deep Learning.

ACS sensors Nov 22, 2022
Exposure to bio-aerosols such as pollen can lead to adverse health effects. There is a need for a portable and cost-effective device for long-term monitoring and quantification of various types of pollen. To address this need, we present a mobile and...
Holography Pollen Particulate Matter Deep Learning Aerosols
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Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations.

The Science of the total environment Sep 29, 2022
The latest Multi-angle Imaging Spectro Radiometer (MISR) Version (V) 23 aerosol optical depth (AOD) products were released, with an improved spatial resolution of 4.4 km, providing an unprecedented opportunity for the refined regional application. To...
Humans Reproducibility of Results Robotics Forests Aerosols
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Dynamic Imaging and Characterization of Volatile Aerosols in E-Cigarette Emissions Using Deep Learning-Based Holographic Microscopy.

ACS sensors Jun 3, 2021
Various volatile aerosols have been associated with adverse health effects; however, characterization of these aerosols is challenging due to their dynamic nature. Here, we present a method that directly measures the volatility of particulate matter ...
Deep Learning Microscopy Aerosols Electronic Nicotine Delivery Systems Propylene Glycol
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Understanding global changes in fine-mode aerosols during 2008-2017 using statistical methods and deep learning approach.

Environment international Jan 29, 2021
Despite their extremely small size, fine-mode aerosols have significant impacts on the environment, climate, and human health. However, current understandings of global changes in fine-mode aerosols are limited. In this study, we employed newly devel...
Seasons Aerosols India Environmental Monitoring Australia Air Pollutants Mexico Humans Deep Learning China
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New interpretable deep learning model to monitor real-time PM concentrations from satellite data.

Environment international Sep 10, 2020
Particulate matter with a mass concentration of particles with a diameter less than 2.5 μm (PM) is a key air quality parameter. A real-time knowledge of PM is highly valuable for lowering the risk of detrimental impacts on human health. To achieve th...
Beijing Aerosols Cities Environmental Monitoring China Air Pollution Particulate Matter Air Pollutants Humans Deep Learning
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Raman spectroscopy of potential bio-hazards commonly found in bio-aerosols.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 31, 2020
Pathogenic bio-aerosols are a threat to public health today, and thus quick detection and identification is of paramount importance. In this study, Raman spectroscopy was used to test 14 types of pollens, one type of fungus and two types of bacteria ...
Aerosols Bacteria Support Vector Machine Principal Component Analysis Spectrum Analysis, Raman
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Heavy metals in submicronic particulate matter (PM) from a Chinese metropolitan city predicted by machine learning models.

Chemosphere Jul 8, 2020
The aim of this study was to establish a method for predicting heavy metal concentrations in PM (aerosol particles with an aerodynamic diameter ≤ 1.0 μm) based on back propagation artificial neural network (BP-ANN) and support vector machine (SVM) me...
Environmental Exposure Neural Networks, Computer Pneumonia, Viral Air Pollutants Environmental Monitoring Pandemics Air Pollution Aerosols Seasons COVID-19 Meteorological Concepts Particulate Matter Support Vector Machine Metals, Heavy Coronavirus Infections Humans Betacoronavirus SARS-CoV-2 China Computer Simulation Cities Wind
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Fast Pathogen Identification Using Single-Cell Matrix-Assisted Laser Desorption/Ionization-Aerosol Time-of-Flight Mass Spectrometry Data and Deep Learning Methods.

Analytical chemistry May 11, 2020
In diagnostics of infectious diseases, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) can be applied for the identification of pathogenic microorganisms. However, to achieve a trustworthy identification fr...
Aerosols Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Deep Learning Gram-Negative Bacteria Single-Cell Analysis Gram-Positive Bacteria
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