Articles | Volume 21, issue 14
https://doi.org/10.5194/acp-21-11243-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-11243-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Satellite-based estimation of the impacts of summertime wildfires on PM2.5 concentration in the United States
Zhixin Xue
Department of Atmospheric and Earth Science, The University of Alabama
in Huntsville, Huntsville, 35806 AL, USA
Pawan Gupta
STI, Universities Space Research Association (USRA), Huntsville, 35806 AL, USA
NASA Marshall Space Flight Center, Huntsville, 35806 AL, USA
Sundar Christopher
CORRESPONDING AUTHOR
Department of Atmospheric and Earth Science, The University of Alabama
in Huntsville, Huntsville, 35806 AL, USA
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Abundant aerosols are present above low-level liquid clouds over the southeastern Atlantic during late austral spring. The model simulation differences in the proportion of aerosol residing in the planetary boundary layer and in the free troposphere can greatly affect the regional aerosol radiative effects. This study examines the aerosol loading and fractional aerosol loading in the free troposphere among various models and evaluates them against measurements from the NASA ORACLES campaign.
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This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
Zhixin Xue and Sundar Christopher
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-303, https://doi.org/10.5194/amt-2022-303, 2022
Publication in AMT not foreseen
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Surface pollution estimation using satellite retrievals in thick smoke regions usually underestimates or has missing data compared to surface observations. Therefore, our work retrieves aerosol optical depth in highly polluted regions and compares it with various satellite products. Our method increased the retrievable coverage areas and improved the retrieval accuracy in thick smoke regions.
Pawan Gupta, Prakash Doraiswamy, Jashwanth Reddy, Palak Balyan, Sagnik Dey, Ryan Chartier, Adeel Khan, Karmann Riter, Brandon Feenstra, Robert C. Levy, Nhu Nguyen Minh Tran, Olga Pikelnaya, Kurinji Selvaraj, Tanushree Ganguly, and Karthik Ganesan
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Revised manuscript not accepted
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The use of low-cost sensors in air quality monitoring has been gaining interest across all walks of society. We present the results of evaluations of the PurpleAir against regulatory-grade PM2.5. The results indicate that with proper calibration, we can achieve bias-corrected PM2.5 data using PA sensors. Our study also suggests that pre-deployment calibrations developed at local or regional scales are required for the PA sensors to correct data from the field for scientific data analysis.
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Short summary
Frequent and widespread wildfires in the northwestern United States and Canada have become the
new normalduring the Northern Hemisphere summer months, which degrades particulate matter air quality in the United States significantly. Using satellite data, we show that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire-active year when compared to fire-inactive years.
Frequent and widespread wildfires in the northwestern United States and Canada have become the...
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