Title: Net-zero transition of the global chemical industry with CO2-feedstock by 2050: feasible yet challenging
Authors:  Jing Huo, Zhanyun Wang, Christopher Oberschelp, Gonzalo Guillén-Gosálbez and  Stefanie Hellweg
Institution: ETH Zurich; Dept. of Civil, Environmental and Geomatic Engineering; Institute of Environmental Engineering; Ecological Systems Design
Contact: jhuo@ethz.ch
Version: 1.0
Date: 2023-07-10

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Table of contents:

1. General information
2. Version history
3. Licence

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1. General information

This dataset contains supplementary data and code for the following publication:

Title: Net-zero transition of the global chemical industry with CO2-feedstock by 2050: feasible yet challenging
Authors: Jing Huo, Zhanyun Wang, Christopher Oberschelp, Gonzalo Guillén-Gosálbez and  Stefanie Hellweg
Year: 2023
Journal: Green Chemistry
Issue: 25
Pages: 415-430
Publisher: Royal Society of Chemistry
Direct link: https://doi.org/10.1039/D2GC03047K

The file "master_file.xlsx" contains two main tabs. "Emission_CO2" tab contains data of CO2 emissions from cement kilns, steel mills, power plants and pulp mills in 2019 and projected emissions under two scenarios in 2050 by region. "Demand_CO2" tab contains data of key chemical production in 2019 and projected production under two scenarios in 2050 by region. It contains further estimated CO2 demand as the chemical feedstock to produce the corresponding chemicals.

The file "chemical_manufacturing_sites_CN_RME.xlsx" contains production capacity of each single chemical manufacturing sites of urea, ethylene, propylene, and BTX aromatics in China and Region Middle East with geometric information. It further forecast the CO2 demand in 2050 under two scenarios to satisfy the demand.

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2. Version history

2023-07-10: Release of version 1.0

Change notes version 1.0: -

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3. Licence

This dataset is released under a CC BY 4.0 (Creative Commons Attribution 4.0 International) licence. This licence allows you to share, copy and modify the dataset as long as you give credit to the authors, provide a link to the CC BY license, and indicate if changes were made. In this specific case, please reference the scientific publication that is the original data source of the dataset (https://doi.org/10.1039/D2GC03047K). You may not use the dataset in a way that suggests the rights holder has endorsed you or your use of the dataset. Further permissions are required for the content within the dataset that is identified as belonging to a third party.

For further information, please have a look at https://creativecommons.org/licenses/by/4.0/.