Machine Learning Approach To Estimate Hourly Exposure to Fine Particulate Matter for Urban, Rural, and Remote Populations during Wildfire Seasons-Reference-Cited by-同舟云学术

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Machine Learning Approach To Estimate Hourly Exposure to Fine Particulate Matter for Urban, Rural, and Remote Populations during Wildfire Seasons

Published:2018-10-24 Issue:22 Volume:52 Page:13239-13249
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Yao Jiayun¹^ORCID,Brauer Michael¹^ORCID,Raffuse Sean²,Henderson Sarah B.¹³^ORCID

Affiliation:

1. School of Population and Public Health, University of British Columbia, Vancouver V6T 1Z3, Canada

2. Air Quality Research Center, University of California, Davis, California 95616, United States

3. Environmental Health Services, British Columbia Centre for Disease Control, Vancouver V5Z 4R4, Canada

Funder

Australian Research Council

British Columbia Lung Association

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.8b01921

Reference70 articles.

1. Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity

2. Detecting the effect of climate change on Canadian forest fires

3. Large wildfire trends in the western United States, 1984-2011

4. Climate-induced variations in global wildfire danger from 1979 to 2013

5. Trend analysis of fire season length and extreme fire weather in North America between 1979 and 2015

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1. Seasons of smoke and fire: preparing health systems for improved performance before, during, and after wildfires;The Lancet Planetary Health;2024-08

2. An assessment of existing wildfire danger indices in comparison to one-class machine learning models;Natural Hazards;2024-07-25

3. Improving Air Quality Prediction via Self-Supervision Masked Air Modeling;Atmosphere;2024-07-19

4. Leveraging the power of internet of things and artificial intelligence in forest fire prevention, detection, and restoration: A comprehensive survey;Internet of Things;2024-07

5. PM2.5 concentration forecasting: Development of integrated multivariate variational mode decomposition with kernel Ridge regression and weighted mean of vectors optimization;Atmospheric Pollution Research;2024-06

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