Evaluating Fine-Scale Winter Nighttime PM<sub>2.5</sub> Concentrations and Population Exposure Using SDGSAT-1 Glimmer Imagery

Evaluating Fine-Scale Winter Nighttime PM<sub>2.5</sub> Concentrations and Population Exposure Using SDGSAT-1 Glimmer Imagery

A comprehensive understanding of fine particulate matter (PM<sub>2.5</sub>) distribution is vital for addressing health concerns related to deteriorating air quality. While remotely sensed nighttime light (NTL) observations have proven effective in monitoring PM<sub>2.5</sub>...

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Bibliographic Details
Main Authors: Xuting Liu, Linlin Lu, Huadong Guo, Zilu Li, Xi Li, Muhammad Bilal
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Nighttime light (NTL) data
particulate matter (PM<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_2.5$</tex-math> </inline-formula> </named-content>)
population exposure
SDG11.6
SDGSAT-1
urban agglomeration (UA)
Online Access:https://ieeexplore.ieee.org/document/10759758/
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Summary:A comprehensive understanding of fine particulate matter (PM<sub>2.5</sub>) distribution is vital for addressing health concerns related to deteriorating air quality. While remotely sensed nighttime light (NTL) observations have proven effective in monitoring PM<sub>2.5</sub> concentrations, their coarse resolution limits their ability to capture the fine-scale spatial variations within urban environments. To address this limitation, an improved simple spatial random forest model was employed to estimate PM<sub>2.5</sub> concentrations using SDGSAT-1 Glimmer NTL data. The resultant PM<sub>2.5</sub> concentration maps, with a resolution of 300 m, were generated for the winter of 2021 (<italic>R</italic><sup>2</sup> &#x003D; 0.81) and cover four urban agglomerations (UAs) in China. Two population-weighted indicators were utilized to assess the nighttime population exposure to PM<sub>2.5</sub>. The findings suggest that population exposure to PM<sub>2.5</sub> is highest in the Beijing-Tianjin-Hebei UA (66.84 <italic>&#x03BC;</italic>g&#x002F;m<sup>3</sup>), followed by Chengdu-Chongqing (CC) (62.66 <italic>&#x03BC;</italic>g&#x002F;m<sup>3</sup>), Yangtze River Delta (52.04 <italic>&#x03BC;</italic>g&#x002F;m<sup>3</sup>), and Guangdong-Hong Kong-Macao Greater Bay Area (33.74 <italic>&#x03BC;</italic>g&#x002F;m<sup>3</sup>). Notably, the CC UA exhibits the highest levels of exposure among children (<inline-formula><tex-math notation="LaTeX">$ \leq $</tex-math></inline-formula> 5 years) and the elderly (<inline-formula><tex-math notation="LaTeX">$ \geq $</tex-math></inline-formula> 65 years). These findings provide valuable insights for policymakers to prioritize pollution control strategies and measures.
ISSN:1939-1404
2151-1535

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