Articles | Volume 22, issue 13
Atmos. Chem. Phys., 22, 8617–8637, 2022
https://doi.org/10.5194/acp-22-8617-2022
Atmos. Chem. Phys., 22, 8617–8637, 2022
https://doi.org/10.5194/acp-22-8617-2022
Research article
05 Jul 2022
Research article | 05 Jul 2022

Improving NOx emission estimates in Beijing using network observations and a perturbed emissions ensemble

Le Yuan et al.

Data sets

Research data supporting "Improving NOX emissions in Beijing using network observations and a novel perturbed emissions ensembleing network observations and a novel perturbed emissions ensemble" Beijing Municipal Ecological and Environmental Monitoring Center and X. Wang https://doi.org/10.17863/CAM.85111

Model code and software

yuanle731/PEE: adjusted PEE (v1.0) L. Yuan https://doi.org/10.5281/zenodo.6778166

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Short summary
Emission estimates represent a major source of uncertainty in air quality modelling. We developed a novel approach to improve emission estimates from existing inventories using air quality models and routine in situ observations. Using this approach, we derived improved estimates of NOx emissions from the transport sector in Beijing in 2016. This approach has great potential in deriving timely updates of emissions for other pollutants, particularly in regions undergoing rapid emission changes.
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