ArticleAtmospheric environment (Oxford, England : 1994)2020
Excitation Emission Matrix Fluorescence Spectroscopy for Combustion Generated Particulate Matter Source Identification.
Article in Atmospheric environment (Oxford, England : 1994), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 28 citations in OpenAlex.
- Exploring the nexus between particulate matter and infertility: Multiple mechanistic insights and potential control strategies.iScience · 2026Review
- Integrated smart dust monitoring and prediction system for surface mine sites using IoT and machine learning techniques.Scientific reports · 2024Article
- Fluorescent spectroscopy paired with parallel factor analysis for quantitative monitoring of phenanthrene biodegradation and metabolite formation.Chemosphere · 2023Article
- Source Apportionment of Environmental Combustion Sources using Excitation Emission Matrix Fluorescence Spectroscopy and Machine Learning.Atmospheric environment (Oxford, England : 1994) · 2021Article
- Solid-phase excitation-emission matrix spectroscopy for chemical analysis of combustion aerosols.PloS one · 2021Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
The inhalation of particulate matter (PM) is a significant health risk associated with reduced life expectancy due to increased cardio-pulmonary disease and exacerbation of respiratory diseases such as asthma and pneumonia. PM originates from natural and anthropogenic sources including combustion engines, cigarettes, agricultural burning, and forest fires. Identifying the source of PM can inform effective mitigation strategies and policies, but this is difficult to do using current techniques. Here we present a method for identifying PM source using excitation emission matrix (EEM) fluorescence spectroscopy and a machine learning algorithm. We collected combustion generated PM
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.