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A Comprehensive Analysis of Ground-Level Concentrations of Aerosols and Criteria Pollutants Using the CAMS Reanalysis Dataset over the Himawari-8 Observational Area, including China, Indonesia, and Australia (2016-2023)
Version 1
: Received: 25 June 2024 / Approved: 25 June 2024 / Online: 26 June 2024 (00:09:29 CEST)
How to cite:
Sowden, M. A Comprehensive Analysis of Ground-Level Concentrations of Aerosols and Criteria Pollutants Using the CAMS Reanalysis Dataset over the Himawari-8 Observational Area, including China, Indonesia, and Australia (2016-2023). Preprints2024, 2024061764. https://doi.org/10.20944/preprints202406.1764.v1
Sowden, M. A Comprehensive Analysis of Ground-Level Concentrations of Aerosols and Criteria Pollutants Using the CAMS Reanalysis Dataset over the Himawari-8 Observational Area, including China, Indonesia, and Australia (2016-2023). Preprints 2024, 2024061764. https://doi.org/10.20944/preprints202406.1764.v1
Sowden, M. A Comprehensive Analysis of Ground-Level Concentrations of Aerosols and Criteria Pollutants Using the CAMS Reanalysis Dataset over the Himawari-8 Observational Area, including China, Indonesia, and Australia (2016-2023). Preprints2024, 2024061764. https://doi.org/10.20944/preprints202406.1764.v1
APA Style
Sowden, M. (2024). A Comprehensive Analysis of Ground-Level Concentrations of Aerosols and Criteria Pollutants Using the CAMS Reanalysis Dataset over the Himawari-8 Observational Area, including China, Indonesia, and Australia (2016-2023). Preprints. https://doi.org/10.20944/preprints202406.1764.v1
Chicago/Turabian Style
Sowden, M. 2024 "A Comprehensive Analysis of Ground-Level Concentrations of Aerosols and Criteria Pollutants Using the CAMS Reanalysis Dataset over the Himawari-8 Observational Area, including China, Indonesia, and Australia (2016-2023)" Preprints. https://doi.org/10.20944/preprints202406.1764.v1
Abstract
This study evaluated ground-level concentrations (GLCs) of aerosols and criteria pollutants using the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis dataset over the Himawari-8 observational land area, including China, Indonesia, and Australia, for the past eight years. A square root transformation of the data was used to normalize and mitigate skewness. Monthly-hourly long-term averages were subtracted to determine abnormalities and identify significant pollution events. Geographic Weighted Regression (GWR) and the Jacobian matrix (dY/dX) methods were used to determine the spatial variability in pollutant concentrations and correlations with meteorological factors. The findings revealed complex interactions between atmospheric dynamics, such as wind components, specific humidity, and pollutant distribution. The analysis highlighted the limitations of traditional point monitoring methods and the need for incident-based spatiotemporal approaches to understand pollution dynamics. This comprehensive evaluation, covering roughly 10% of the globe, demonstrated CAMS's effectiveness in providing detailed insights into air quality trends, which can support targeted public health interventions and compliance with sustainability goals. Integrating CAMS data with high-resolution satellite data like Himawari-8 could revolutionize air quality monitoring by delivering dynamic, near real-time outputs with high spatiotemporal resolution.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
