Estimation of Ground-Level PM2.5 Concentration at Night in Beijing-Tianjin-Hebei Region with NPP/VIIRS Day/Night Band

Reliable measures of nighttime atmospheric fine particulate matter (PM2.5) concentrations are essential for monitoring their continuous diurnal variation. Here, we proposed a night PM2.5 concentration estimation (NightPMES) model based on the random forest model. This model integrates the radiance o...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2023-02, Vol.15 (3), p.825
Main Authors: Ma, Yu, Zhang, Wenhao, Zhang, Lili, Gu, Xingfa, Yu, Tao
Format: Article
Language:English
Subjects:
Accuracy
Air pollution
Atmospheric aerosols
BTH
Data collection
Datasets
Diurnal variations
Estimation
Festivals
Ground stations
Humidity
Imaging radiometers
Infrared imaging
Infrared radiometers
Lunar phases
Meteorological data
Missing data
Moon
moon phase angle
Night
Nighttime
nighttime PM2.5
Outdoor air quality
Particulate emissions
Particulate matter
Pollutants
Radiance
Radiation
Radiometry
random forest
Regression analysis
Remote sensing
Root-mean-square errors
Variables
VIIRS/DNB
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Summary:Reliable measures of nighttime atmospheric fine particulate matter (PM2.5) concentrations are essential for monitoring their continuous diurnal variation. Here, we proposed a night PM2.5 concentration estimation (NightPMES) model based on the random forest model. This model integrates the radiance of the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB), moon phase angle, and meteorological data. We collected 13486 samples from the Beijing Tianjin–Hebei (BTH) region. The determination coefficient (R2) of the NightPMES model was 0.82, the root mean square error (RMSE) was 16.67 µg/m3, and the mean absolute error (MAE) was 10.20 µg/m3. The applicability analysis of the moon phase angles indicated that the amount of data available increased by 60% while the accuracy remained relatively unchanged. In the seasonal model, the meteorological factors and DNB radiance were found to be the primary factors affecting the PM2.5 concentration in different seasons. In conclusion, this study provided a method for estimating nighttime PM2.5 concentration that will improve our understanding of air pollution and associated trends in PM2.5 variation.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15030825