Application of Proper Orthogonal Decomposition to Elucidate Spatial and Temporal Correlations in Air Pollution Across the City of Liverpool, UK
Understanding the spatiotemporal distribution of air pollution is critical for improving urban air quality. Advances in wireless sensor networks have made it possible to monitor air pollution across cities at higher spatiotemporal resolutions. The new spatial coverage allows the novel implementation...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Urban Science |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2413-8851/9/5/166 |
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| Summary: | Understanding the spatiotemporal distribution of air pollution is critical for improving urban air quality. Advances in wireless sensor networks have made it possible to monitor air pollution across cities at higher spatiotemporal resolutions. The new spatial coverage allows the novel implementation of advanced statistical methods to detect spatially important, coherent patterns in environmental flows. In this study, we apply proper orthogonal decomposition to a spatial distribution derived from 34 particulate matter sensors, which collected data over 250 days across the Liverpool City Region in England, to identify a set of spatially orthogonal modes. The dominant mode exhibits a daily periodicity in the increases of particulate matter, with higher increases in residential areas interpreted as changes driven by daily commutes. The second mode highlights seasonal changes, and the third mode alludes to pollution transportation with simultaneous increases and decreases. In contrast with traditional time series and spatial analyses, proper orthogonal decomposition enables the elucidation of patterns that otherwise might remain hidden. Our findings highlight the benefits of urban wireless sensor networks and demonstrate the applicability of proper orthogonal decomposition in studying the movements of polluted areas and their correlations with meteorological variables and anthropogenic factors. |
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| ISSN: | 2413-8851 |