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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ESSDD</journal-id>
<journal-title-group>
<journal-title>Earth System Science Data Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">ESSDD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Earth Syst. Sci. Data Discuss.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1866-3591</issn>
<publisher><publisher-name></publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/essd-2026-590</article-id>
<title-group>
<article-title>HBPG-CO&lt;sub&gt;2&lt;/sub&gt;: a global gridded monthly anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emission dataset at 0.05&amp;deg; resolution for 1970&amp;ndash;2025</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Antezana Lopez</surname>
<given-names>Franz Pablo</given-names>
<ext-link>https://orcid.org/0000-0002-9200-330X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhou</surname>
<given-names>Guanhua</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhang</surname>
<given-names>Kai</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Casallas</surname>
<given-names>Alejandro</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ali</surname>
<given-names>Aamir</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jiang</surname>
<given-names>Hongzhi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Alanoca Limachi</surname>
<given-names>Jose Luis</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Instrumentation Science and Optoelectronic Engineering, Beihang University, Beijing 100191, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Hangzhou International Innovation Institute, Beihang University, Hangzhou, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Institute of Science and Technology Austria, Klosterneuburg 3400, Austria</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>Atmospheric Chemistry Department, Max Planck Institute for Chemistry, 55128 Mainz, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>05</day>
<month>08</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>27</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Franz Pablo Antezana Lopez et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-590/">This article is available from https://essd.copernicus.org/preprints/essd-2026-590/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-590/essd-2026-590.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-590/essd-2026-590.pdf</self-uri>
<abstract>
<p>Carbon dioxide emissions, as geospatial information, are necessary to analyze seasonal and regional variability, as well as the changing distribution of anthropogenic activity. However, the availability of continuous data with high spatial and temporal resolution is limited, both sectorial and global. Therefore, in this study, we present the Hierarchical Bayesian Physics-Guided Carbon Dioxide (HBPG-CO&lt;sub&gt;2&lt;/sub&gt;) emission dataset, a global dataset of emissions from multiple sources for energy, industry, buildings, land transport, agriculture, waste, and fuel production. This dataset is based on multi-information harmonization and downscaling using geospatial information from multiple sources (nighttime lighting, roads, land use, population, settlements, meteorology, and point source data support temporal reconstruction and spatial refinement), various emissions inventories such as annual and monthly data from the Emissions Database for Global Atmospheric Research (EDGAR), as well as the Open source Data Inventory for Anthropogenic Carbon dioxide (ODIAC), Community Emissions Data System (CEDS), and daily estimates by country and sector. To integrate all the data, a hierarchical Bayesian component is applied to reconstruct monthly variability outside the directly observed period, while a physics-based component restricts the specific spatial allocation for each sector and preserves emissions data, while also allowing for area expansion based on decision trees. Furthermore, the integration of fossil fuel-related covariates that are underrepresented or absent in the original EDGAR fields helps reconstruct this dataset spatially and temporally. The resulting dataset contains 672 monthly layers per sector and global layers corresponding to the date range from 1970-01 to 2025-12. Comparisons with CEDS, ODIAC, EDGAR, and other studies show strong temporal and spatial consistency, while also preserving additional small-scale structure. Therefore, HBPG-CO&lt;sub&gt;2&lt;/sub&gt; provides a long-term, high-resolution, sector-specific emissions record for atmospheric inversion, Earth system modeling, carbon cycle analysis, and regional emissions assessment. The complete HBPG-CO₂ dataset is openly accessible through Zenodo at &lt;a href=&quot;https://doi.org/10.5281/zenodo.21507026&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://doi.org/10.5281/zenodo.21507026&lt;/a&gt; (Antezana Lopez, 2026).</p>
</abstract>
<counts><page-count count="27"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>42471425</award-id>
</award-group>
</funding-group>
</article-meta>
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