Near-real-time global gridded daily CO2 emissions 2021

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Abstract

We present a near-real-time global gridded daily CO ₂ emissions dataset (GRACED) throughout 2021. GRACED provides gridded CO ₂ emissions at a 0.1° × 0.1° spatial resolution and 1-day temporal resolution from cement production and fossil fuel combustion over seven sectors, including industry, power, residential consumption, ground transportation, international aviation, domestic aviation, and international shipping. GRACED is prepared from the near-real-time daily national CO ₂ emissions estimates (Carbon Monitor), multi-source spatial activity data emissions and satellite NO ₂ data for time variations of those spatial activity data. GRACED provides the most timely overview of emissions distribution changes, which enables more accurate and timely identification of when and where fossil CO ₂ emissions have rebounded and decreased. Uncertainty analysis of GRACED gives a grid-level two-sigma uncertainty of value of ±19.9% in 2021, indicating the reliability of GRACED was not sacrificed for the sake of higher spatiotemporal resolution that GRACED provides. Continuing to update GRACED in a timely manner could help policymakers monitor energy and climate policies’ effectiveness and make adjustments quickly.

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Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement

Corinne Le Quéré, Robert B. Jackson, Matthew Jones … (2020)

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HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution

G. Janssens-Maenhout, M. Crippa, D Guizzardi … (2015)

The mandate of the Task Force Hemispheric Transport of Air Pollution (TF HTAP) under the Convention on Long-Range Transboundary Air Pollution (CLRTAP) is to improve the scientific understanding of the intercontinental air pollution transport, to quantify impacts on human health, vegetation and climate, to identify emission mitigation options across the regions of the Northern Hemisphere, and to guide future policies on these aspects. The harmonization and improvement of regional emission inventories is imperative to obtain consolidated estimates on the formation of global-scale air pollution. An emissions data set has been constructed using regional emission grid maps (annual and monthly) for SO 2 , NO x , CO, NMVOC, NH 3 , PM 10 , PM 2.5 , BC and OC for the years 2008 and 2010, with the purpose of providing consistent information to global and regional scale modelling efforts. This compilation of different regional gridded inventories – including that of the Environmental Protection Agency (EPA) for USA, the EPA and Environment Canada (for Canada), the European Monitoring and Evaluation Programme (EMEP) and Netherlands Organisation for Applied Scientific Research (TNO) for Europe, and the Model Inter-comparison Study for Asia (MICS-Asia III) for China, India and other Asian countries – was gap-filled with the emission grid maps of the Emissions Database for Global Atmospheric Research (EDGARv4.3) for the rest of the world (mainly South America, Africa, Russia and Oceania). Emissions from seven main categories of human activities (power, industry, residential, agriculture, ground transport, aviation and shipping) were estimated and spatially distributed on a common grid of 0.1° × 0.1° longitude-latitude, to yield monthly, global, sector-specific grid maps for each substance and year. The HTAP_v2.2 air pollutant grid maps are considered to combine latest available regional information within a complete global data set. The disaggregation by sectors, high spatial and temporal resolution and detailed information on the data sources and references used will provide the user the required transparency. Because HTAP_v2.2 contains primarily official and/or widely used regional emission grid maps, it can be recommended as a global baseline emission inventory, which is regionally accepted as a reference and from which different scenarios assessing emission reduction policies at a global scale could start. An analysis of country-specific implied emission factors shows a large difference between industrialised countries and developing countries for acidifying gaseous air pollutant emissions (SO 2 and NO x ) from the energy and industry sectors. This is not observed for the particulate matter emissions (PM 10 , PM 2.5 ), which show large differences between countries in the residential sector instead. The per capita emissions of all world countries, classified from low to high income, reveal an increase in level and in variation for gaseous acidifying pollutants, but not for aerosols. For aerosols, an opposite trend is apparent with higher per capita emissions of particulate matter for low income countries.

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Technologies and perspectives for achieving carbon neutrality

Fang Wang, Jean Harindintwali, Zhizhang Yuan … (2021)

Global development has been heavily reliant on the overexploitation of natural resources since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other forms of land-use change, anthropogenic activities have contributed to the ever-increasing concentrations of greenhouse gases (GHGs) in the atmosphere, causing global climate change. In response to the worsening global climate change, achieving carbon neutrality by 2050 is the most pressing task on the planet. To this end, it is of utmost importance and a significant challenge to reform the current production systems to reduce GHG emissions and promote the capture of CO2 from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.

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Author and article information

Contributors

Zhu Liu:

ORCID: http://orcid.org/0000-0002-8968-7050

zhuliu@tsinghua.edu.cn

Journal

Journal ID (nlm-ta): Sci Data

Journal ID (iso-abbrev): Sci Data

Title: Scientific Data

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2052-4463

Publication date (Electronic): 2 February 2023

Publication date PMC-release: 2 February 2023

Publication date Collection: 2023

Volume: 10

Electronic Location Identifier: 69

Affiliations

[1 ]GRID grid.12527.33, ISNI 0000 0001 0662 3178, Department of Earth System Science, , Tsinghua University, ; Beijing, 100084 China

[2 ]GRID grid.12527.33, ISNI 0000 0001 0662 3178, Department of Computer Science and Technology, , Tsinghua University, ; Beijing, 100084 China

[3 ]GRID grid.460789.4, ISNI 0000 0004 4910 6535, Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, , Université Paris-Saclay, ; Gif-sur-Yvette, France

[4 ]GRID grid.4422.0, ISNI 0000 0001 2152 3263, Key Laboratory of Marine Environment and Ecology, and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ministry of Education, , Ocean University of China, ; Qingdao, 266100 China

[5 ]GRID grid.10698.36, ISNI 0000000122483208, Environmental Sciences and Engineering, , University of North Carolina at Chapel Hill, ; Chapel Hill, USA

[6 ]GRID grid.412246.7, ISNI 0000 0004 1789 9091, Key Laboratory of Sustainable Forest Ecosystem Management, , Northeast Forestry University, ; Harbin, 150040 China

[7 ]GRID grid.33763.32, ISNI 0000 0004 1761 2484, School of Environmental Science and Engineering, , Tianjin University, ; Tianjin, 300072 China

[8 ]GRID grid.9227.e, ISNI 0000000119573309, Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, , Chinese Academy of Sciences, ; Beijing, 100101 China

[9 ]GRID grid.266093.8, ISNI 0000 0001 0668 7243, Department of Earth System Science, , University of California, ; Irvine, CA USA

[10 ]GRID grid.434554.7, ISNI 0000 0004 1758 4137, European Commission, Joint Research Centre (JRC), ; Ispra, Italy

[11 ]Product and Solution & Website Business Unit, Alibaba Cloud, Hangzhou, 311121 China

Author information

Xinyu Dou http://orcid.org/0000-0001-7783-6971

Jinpyo Hong http://orcid.org/0000-0001-7369-0303

Philippe Ciais http://orcid.org/0000-0001-8560-4943

Frédéric Chevallier http://orcid.org/0000-0002-4327-3813

Steven J. Davis http://orcid.org/0000-0002-9338-0844

Greet Janssens-Maenhout http://orcid.org/0000-0002-9335-0709

Efisio Solazzo http://orcid.org/0000-0002-6333-1101

Xuanren Song http://orcid.org/0000-0001-9075-2895

Piyu Ke http://orcid.org/0000-0003-0353-6313

Wenwen Zhou http://orcid.org/0000-0001-6973-318X

Zhu Liu http://orcid.org/0000-0002-8968-7050

Article

Publisher ID: 1963

DOI: 10.1038/s41597-023-01963-0

PMC ID: 9894514

PubMed ID: 36732516

SO-VID: 7ed542fb-69ec-4aba-920f-789328d03d97

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 2 November 2022

Date accepted : 11 January 2023

Funding

Funded by: FundRef https://doi.org/10.13039/501100004826, Natural Science Foundation of Beijing Municipality (Beijing Natural Science Foundation);

Award ID: JQ19032

Award Recipient : Zhu Liu

Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);

Award ID: 41921005

Award ID: 71874097

Award Recipient : Zhu Liu

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Keywords: projection and prediction,climate-change mitigation

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Keywords: projection and prediction, climate-change mitigation

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Near-real-time global gridded daily CO2 emissions 2021

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Climate Change: Open Access

Most cited references 17

Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement

HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution

Technologies and perspectives for achieving carbon neutrality

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Cited by 4

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