Spatial mapping and analysis of aerosols during a forest fire using computational mobile microscopy

Forest fires are a major source of particulate matter (PM) air pollution on a global scale. The composition and impact of PM are typically studied using only laboratory instruments and extrapolated to real fire events owing to a lack of analytical techniques suitable for field-settings. To address t...

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Bibliographic Details
Published inarXiv.org
Main Authors Wu, Yichen, Shiledar, Ashutosh, Luo, Yi, Wong, Jeffrey, Chen, Cheng, Bai, Bijie, Zhang, Yibo, Tamamitsu, Miu, Ozcan, Aydogan
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 05.02.2018
Subjects
Aerosols
Air monitoring
Air pollution
Air quality
Air sampling
Aspect ratio
Environmental monitoring
Field tests
Forest fires
Image analysis
Laboratory equipment
Machine learning
Mapping
Microscopy
Mobile computing
Particulate emissions
Portable equipment
Soot
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Summary:Forest fires are a major source of particulate matter (PM) air pollution on a global scale. The composition and impact of PM are typically studied using only laboratory instruments and extrapolated to real fire events owing to a lack of analytical techniques suitable for field-settings. To address this and similar field test challenges, we developed a mobile-microscopy and machine-learning-based air quality monitoring platform called c-Air, which can perform air sampling and microscopic analysis of aerosols in an integrated portable device. We tested its performance for PM sizing and morphological analysis during a recent forest fire event in La Tuna Canyon Park by spatially mapping the PM. The result shows that with decreasing distance to the fire site, the PM concentration increases dramatically, especially for particles smaller than 2 microns. Image analysis from the c-Air portable device also shows that the increased PM is comparatively strongly absorbing and asymmetric, with an aspect ratio of 0.5-0.7. These PM features indicate that a major portion of the PM may be open-flame-combustion-generated element carbon soot-type particles. This initial small-scale experiment shows that c-Air has some potential for forest fire monitoring.
ISSN:2331-8422