COVID-19-Europe-Ozone-NOx-VOC

Published: 10 February 2021| Version 1 | DOI: 10.17632/jchfxsrvsb.1
Contributors:
Amir Hossein Souri,
Kelly Chance,
Juseon Bak,
Caroline Nowlan,
Gonzalo González Abad,
Yeonjin Jung,
David Wong,
Jingqiu Mao,
Xiong Liu

Description

Data outputs from the joint inversion study done during 2020 (lockdown) and 2019 (baseline) in three months of March, April, and May over Europe. The file consists of: Lat (Latitude coordinates) (GRIDCRO2D_Europe_Covid19_2019061 ; netcdf file) Lon (Longitude coordinates) (GRIDCRO2D_Europe_Covid19_2019061 ; netcdf file) AKs_NOx (averaging kernels for top-down NOx) (*.mat) AKs_VOC (averaging kernels for top-down VOC) (*.mat) Ratio_total_NOx (ratio of the posterior to the prior emissions) (*.mat) Ratio_total_VOC (ratio of the posterior to the prior emissions) (*.mat) Prior_Cov_rel_NOx (error assumed in the a priori, they are in 0-1 relative unit with respect to the prior values). (*.mat) Prior_Cov_rel_VOC (error assumed in the a priori, they are in 0-1 relative unit with respect to the prior values). (*.mat) Post_Cov_rel_NOx (estimated errors in the a posteriori, they are in 0-1 relative unit with respect to the posterior values). (*.mat) Post_Cov_rel_VOC (estimated errors in the a posteriori, they are in 0-1 relative unit with respect to the posterior values). (*.mat)

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Institutions

University of Alaska Fairbanks, Pusan National University, Harvard-Smithsonian Center for Astrophysics, United States Environmental Protection Agency Center for Environmental Measurement and Modeling

Categories

Air Pollution, Atmospheric Chemistry, Inverse Problem, Emissions, COVID-19

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