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Bridging the Data Gap: Enhancing the Spatiotemporal Accuracy of Hourly PM 2.5 Concentration through the Fusion of Satellite-Derived Estimations and Station Observations.
- Source :
- Remote Sensing; Oct2023, Vol. 15 Issue 20, p4973, 21p
- Publication Year :
- 2023
-
Abstract
- Satellite-derived aerosol optical depth (AOD) has been extensively utilized for retrieving ground-level PM<subscript>2.5</subscript> distributions. However, the presence of non-random missing data gaps in AOD poses a challenge to directly obtaining the gap-free AOD-derived PM<subscript>2.5</subscript>, thereby impeding accurate exposure risk assessment. Here, this study presents a novel and flexible framework that couples stacking and flexible spatiotemporal data fusion (FSDAF) approaches. By integrating multiple models and data sources, this framework aims to generate hourly (24-h) gap-free PM<subscript>2.5</subscript> estimates for the Beijing–Tianjin–Hebei (BTH) region in 2018. This study effectively reconstructed data at least three times more effectively than the original AOD-derived PM<subscript>2.5</subscript>, achieving the Pearson coefficient (r), the coefficient determination (R<superscript>2</superscript>), root mean squared error (RMSE), and mean absolute error (MAE) values of 0.91, 0.84, 19.38 µg/m<superscript>3</superscript>, and 12.17 µg/m<superscript>3</superscript>, respectively, based on entire samples. Such strong predictive performance was also exhibited in spatial-based (r: 0.92–0.93, R<superscript>2</superscript>: 0.85–0.87, RMSE: 18.13 µg/m<superscript>3</superscript>–20.18 µg/m<superscript>3</superscript>, and MAE: 11.21 µg/m<superscript>3</superscript>–12.52 µg/m<superscript>3</superscript>) and temporal-based (r: 0.91–0.98, R<superscript>2</superscript>: 0.82–0.96, RMSE: 3.8 µg/m<superscript>3</superscript>–21.89 µg/m<superscript>3</superscript>, and MAE: 2.71 µg/m<superscript>3</superscript>–14.00 µg/m<superscript>3</superscript>) validations, indicating the robustness of this framework. Additionally, this framework enables the assessment of annual and seasonal PM<subscript>2.5</subscript> concentrations and distributions, revealing that higher levels are experienced in the southern region, while lower levels prevail in the northern part. Winter exhibits the most severe levels, followed by spring and autumn, with comparatively lower levels in summer. Notably, the proposed framework effectively mitigates bias in calculating population-weighted exposure risk by filling data gaps with calculated values of 51.04 µg/m<superscript>3</superscript>, 54.17 µg/m<superscript>3</superscript>, 56.24 µg/m<superscript>3</superscript>, and 55.00 µg/m<superscript>3</superscript> in Beijing, Tianjin, Hebei, and the BTH region, respectively. [ABSTRACT FROM AUTHOR]
- Subjects :
- STANDARD deviations
SPRING
AUTUMN
BRIDGES
MULTISENSOR data fusion
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 15
- Issue :
- 20
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 173337947
- Full Text :
- https://doi.org/10.3390/rs15204973