Machine learning-guided integration of fixed and mobile sensors for high resolution urban PM2.5 mapping
Abstract Urban areas exhibit significant gradients in Fine Particulate Matter (PM2.5) concentration variability. Understanding the spatiotemporal distribution and formation mechanisms of PM2.5 is crucial for public health, environmental justice, and air pollution mitigation strategies. Here, we util...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-025-00984-3 |
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