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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-2026-237</article-id>
<title-group>
<article-title>A 1-km dataset of crop residue production and usage pathways in the conterminous U.S. from 2001 to 2021</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhang</surname>
<given-names>Yikun</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>Yan</surname>
<given-names>Hua</given-names>
<ext-link>https://orcid.org/0000-0002-6960-4369</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jiao</surname>
<given-names>Wenzhe</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>Kang</surname>
<given-names>Yanghui</given-names>
<ext-link>https://orcid.org/0000-0001-8563-1503</ext-link>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Schmer</surname>
<given-names>Marty R.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Stewart</surname>
<given-names>Ryan D.</given-names>
<ext-link>https://orcid.org/0000-0002-9700-0351</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Tracy</surname>
<given-names>Benjamin F.</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>You</surname>
<given-names>Yongfa</given-names>
<ext-link>https://orcid.org/0000-0002-8916-2940</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, USA</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Department of Ecology and Conservation Biology, Texas A&amp;M University, College Station, TX, USA</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA, USA</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>USDA-Agricultural Research Service, Agroecosystem Management Research Unit, Lincoln, NE, USA</addr-line>
</aff>
<pub-date pub-type="epub">
<day>29</day>
<month>04</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>24</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Yikun Zhang 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-2026-237/">This article is available from https://essd.copernicus.org/preprints/essd-2026-237/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-237/essd-2026-237.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-237/essd-2026-237.pdf</self-uri>
<abstract>
<p>Crop residues represent an important biomass resource that supports soil organic carbon maintenance, livestock production, and emerging bioeconomy sectors. In the United States, crop residue production is concentrated in a few dominant cropping systems, whereas residue demand for livestock and other off-field uses is often geographically separated from production regions. However, spatially explicit datasets that jointly quantify crop residue production, allocation pathways, and spatial imbalances between production and consumption remain limited. Here, we developed a 1 km &amp;times; 1 km gridded dataset of crop residue production and usage pathways across the conterminous United States for 2001&amp;ndash;2021, covering nine major crops. A mass-balance framework was applied to reconcile residue production and consumption, allocating residues into four pathways: left on field, animal-use, off-field use, and burnt. An implied domestic transfer layer was also derived as an indicator of spatial mismatches between residue production and consumption. Results indicate that total U.S. residue production averaged 4.91&amp;times;10&lt;sup&gt;11&lt;/sup&gt; kg/yr, with corn residue consistently contributing over 60 % of the total biomass. Residues left on field dominated nationally, accounting for 86.4 % of total residue production. Livestock use and off-field uses represented smaller but spatially heterogeneous pathways (13.4 % combined), while burnt residue accounted for less than 0.2 %. Residue production was concentrated in the Midwest, whereas higher consumption demand occurred in the Southeast, West Coast, and the Southern Great Plains. The national production-consumption mismatch ratio increased from 7.6 % to 8.4 % over the study period, highlighting a growing spatial imbalance between residue availability and consumption demand. By providing 1-km gridded, mass-balanced estimates of residue production, allocation pathways, and regional production-consumption mismatches, this dataset offers a spatially explicit foundation for quantifying crop residue flows across U.S. agricultural landscapes and supports improved representation of residue management in terrestrial biosphere models, soil carbon dynamics assessments, and sustainable residue biomass utilization strategies. The dataset is available at &lt;a href=&quot;https://doi.org/10.5281/zenodo.18453064&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://doi.org/10.5281/zenodo.18453064&lt;/a&gt; (Zhang et al., 2026).</p>
</abstract>
<counts><page-count count="24"/></counts>
</article-meta>
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