Affiliation:
1. School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
2. Hebei Collaborative Innovation Center for Aerospace Remote Sensing Information Processing and Application, Langfang 065000, China
3. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Abstract
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.
Funder
Hebei Natural Science Foundation
National Natural Science Foundation of China
Science and Technology Research Project of Universities in Hebei
China High Resolution Earth Observation Project
North China Institute of Aerospace Engineering Foundation of Doctoral Research
Hebei Province Graduate Student Innovation Ability Training Funding Project
National Science and Technology Major Project of High Resolution Earth Observation System
Subject
General Earth and Planetary Sciences
Reference46 articles.
1. A Machine Learning Model to Estimate Ambient PM2.5 Concentrations in Industrialized Highveld Region of South Africa;Zhang;Remote Sens. Environ.,2021
2. World Health Organization (2021). WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide, World Health Organization.
3. Long-Term Trend and Spatial Pattern of PM2.5 Induced Premature Mortality in China;Xie;Environ. Int.,2016
4. The Concentration-Response between Long-Term PM 2.5 Exposure and Mortality; A Meta-Regression Approach;Vodonos;Environ. Res.,2018
5. Air Pollution, Environmental Chemicals, and Smoking May Trigger Vitamin D Deficiency: Evidence and Potential Mechanisms;Mousavi;Environ. Int.,2019
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