Research Data Leeds Repository

Citation

Conibear, Luke and Reddington, Carly L. and Silver, Ben J. and Chen, Ying and Knote, Christoph and Arnold, Stephen R. and Spracklen, Dominick V. (2022) Supplementary Data: Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China using Machine Learning Emulation. University of Leeds. [Dataset] https://doi.org/10.5518/1055

Dataset description

The trained emulators per grid cell in China that support the findings of this study. The emulators predict ambient fine particulate matter (PM2.5) and ozone (O3) concentrations from emission changes in five anthropogenic sectors. The README.txt file explains how to open and use these emulators.

Keywords:	Air pollution, Public health, Air Quality, Emulator, Machine learning, China, Particulate Matter, Health Impact Assessment, Emissions, Gaussian Process
Divisions:	Faculty of Environment > School of Earth and Environment
Related resources:	Location Type https://doi.org/10.1029/2021GH000570 Publication https://eprints.whiterose.ac.uk/187346/ Publication https://doi.org/10.1088/1748-9326/ac6f6f Publication https://eprints.whiterose.ac.uk/187345/ Publication
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	05 May 2022 15:21
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/957
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Conibear, Luke https://orcid.org/0000-0003-2801-8862 University of Leeds https://ror.org/024mrxd33 ror Reddington, Carly L. https://orcid.org/0000-0002-5990-4966 University of Leeds https://ror.org/024mrxd33 ror Silver, Ben J. https://orcid.org/0000-0003-0395-0637 University of Leeds https://ror.org/024mrxd33 ror Chen, Ying https://orcid.org/0000-0002-0319-4950 University of Exeter https://ror.org/03yghzc09 ror Knote, Christoph https://orcid.org/0000-0001-9105-9179 University of Augsburg https://ror.org/03p14d497 ror Arnold, Stephen R. https://orcid.org/0000-0002-4881-5685 University of Leeds https://ror.org/024mrxd33 ror Spracklen, Dominick V. https://orcid.org/0000-0002-7551-4597 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: Natural Environment Research Council, AIA Group Limited, European Research Council Consolidator Grant Grant numbers: NE/S006680/1, N/A, 771492 Publication date: 2022 Resource language: English Metadata language: English Publisher: University of Leeds Contact email: earlacoa@leeds.ac.uk Last Modified: 19 Jun 2024 11:29

Files

Documentation

README [1kB] README [1kB] README [1kB] Security: Anyone File name: README.txt Content type: Documentation Description: Instructions on how to use the emulators. Mime-Type: text/plain License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 1kB

Data

Emulators [513MB] Emulators [513MB] Emulators [513MB] Security: Anyone File name: emulators.zip Content type: Data Description: Emulators for the paper. Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 513MB