Résumé
As extreme temperature events become increasingly frequent, there is a growing need for daily CO2 emissions data to quantify their impacts. However, such data are available only from 2019 onward. To address this gap, we compiled over two million near-real-time observations of electricity generation, traffic activity, natural gas consumption or heating degree days (HDD), and industrial output since 2019, and used these high-frequency data to construct a daily CO2 emissions dataset for 2019–2024. We then applied machine-learning models and degree-day methods to disaggregate non-residential and residential monthly CO2 emissions for 1970–2018 to a daily basis. The historical dataset was then merged with the 2019–2024 dataset to produce a global daily CO2 emissions dataset spanning 1970 to 2024 for 14 countries and regions, covering four sectors: power, industry, residential, and transport (including ground transport and aviation). The resulting long-term dataset will enable robust analyses of extreme-temperature impacts on emissions and enhance the accuracy of chemical transport model inversions of carbon fluxes.
| langue originale | Anglais |
|---|---|
| Numéro d'article | 605 |
| journal | Scientific Data |
| Volume | 13 |
| Numéro de publication | 1 |
| Les DOIs | |
| état | Publié - 1 déc. 2026 |
Empreinte digitale
Examiner les sujets de recherche de « Global daily CO2 emissions from 1970 to 2024 ». Ensemble, ils forment une empreinte digitale unique.Contient cette citation
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver