Papers

Publications

[4] Shen, S., van Donkelaar, A., Jacobs, N., Li, C., Zhang, Y., and Martin, R. V.: Enhancing Estimation of Daily 1-km Resolution Fine Particulate Matter Concentrations for North America with Ensembled Deep Learning from Geophysical A Priori Information. (In preparation) .

[3] Shen, S. Li, C. van Donkelaar, A. Jacobs, N. Martin, R. V.: Enhancing Estimation of Fine Particulate Matter Chemical Composition across North America by Including Geophysical A Priori Information in Deep Learning with Uncertainty Quantification. (2026) ACS ES&T Air Article ASAP. DOI: 10.1021/acsestair.5c00251. Link

[2] van Donkelaar, A., Martin, R. V., Ford, B., Li, C., Pappin, A. J., Shen, S., & Zhang, D. (2024). North American Fine Particulate Matter Chemical Composition for 2000–2022 from Satellites, Models, and Monitors: The Changing Contribution of Wildfires. ACS ES&T Air. https://pubs.acs.org/doi/full/10.1021/acsestair.4c00151
[1] Shen, S., Li, C., Van Donkelaar, A., Jacobs, N., Wang, C., & Martin, R. V. (2024). Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. ACS ES&T Air. https://doi.org/10.1021/acsestair.3c00054