Tropospheric NO<sub>2</sub>: Anthropogenic Influence, Global Trends, Satellite Data, and Machine Learning Application
Nitrogen dioxide (NO<sub>2</sub>) is a critical air pollutant that has significant health and environmental impacts. Tropospheric NO<sub>2</sub> refers specifically to the vertical column density of NO<sub>2</sub>, which is measured by satellites and serves as an...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/1/49 |
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| Summary: | Nitrogen dioxide (NO<sub>2</sub>) is a critical air pollutant that has significant health and environmental impacts. Tropospheric NO<sub>2</sub> refers specifically to the vertical column density of NO<sub>2</sub>, which is measured by satellites and serves as an indicator of anthropogenic NO<sub>2</sub> sources. This pollutant is frequently assessed using satellite data owing to limitations in local monitoring. This investigation employs the Spectral Angle Mapper (SAM), a geometric machine-learning model, given its advantages in simplicity and computational efficiency, and OMI satellite measurements to carry out spatially supervised classification of tropospheric NO<sub>2</sub> global patterns from 2005 to 2021. This study identifies four typical trends across developed urban centers, examining correlations with population growth, economic factors, and air quality policies. The results demonstrated regional variations, with a general downward trend in North America, Europe, and parts of Asia, underscoring the efficacy of stricter emission controls. However, upward trends persist in some Asian regions, reflecting varying policy implementations. This study revealed a pivotal inflection point around 2013, marking a shift in global NO<sub>2</sub> dynamics. Although policies have led to improved air quality in some regions, achieving absolute decoupling of economic growth from NO<sub>2</sub> emissions remains challenging. The COVID-19 pandemic has also exerted a significant influence, temporarily reducing emissions due to economic slowdowns. Overall, the SAM model effectively delineated NO<sub>2</sub> patterns and provided insights for future policy and emission control strategies. |
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| ISSN: | 2072-4292 |