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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/egusphere-2026-2485</article-id>
<title-group>
<article-title>Classification-Constrained Retrieval of PM&lt;sub&gt;2.5&lt;/sub&gt; Vertical Profiles from Fluorescence&amp;ndash;Raman&amp;ndash;Mie Polarization Lidar</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Chen</surname>
<given-names>Siying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Shu</surname>
<given-names>Yingjie</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>Chen</surname>
<given-names>He</given-names>
</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>Guo</surname>
<given-names>Pan</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>Jiang</surname>
<given-names>Yurong</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>Hu</surname>
<given-names>Guoxing</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>Xiaolei</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>Yang</surname>
<given-names>Haokai</given-names>
<ext-link>https://orcid.org/0009-0000-2240-5314</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>Feng</surname>
<given-names>Mengjun</given-names>
<ext-link>https://orcid.org/0009-0006-5381-312X</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>Cao</surname>
<given-names>Yue</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>Kaitong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314019, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>National Key Laboratory on Near-Surface Detection, Beijing, 100072, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>03</day>
<month>08</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>27</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Siying Chen 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://egusphere.copernicus.org/preprints/2026/egusphere-2026-2485/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2485/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2485/egusphere-2026-2485.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2485/egusphere-2026-2485.pdf</self-uri>
<abstract>
<p>The vertical distribution of PM&lt;sub&gt;2.5&lt;/sub&gt; during urban haze events is jointly affected by aerosol composition, boundary-layer structure, and regional transport. Empirical PM&lt;sub&gt;2.5&lt;/sub&gt; retrievals based on lidar-derived extinction coefficients can be biased by the optical contribution of coarse-mode mineral particles. This study used fluorescence&amp;ndash;Raman&amp;ndash;Mie polarization lidar observations in Beijing to identify anthropogenic pollution aerosols (APA), desert dust (DD), and mineral dust (MD) using the particle depolarization ratio (PDR) and fluorescence capacity (&lt;em&gt;G&lt;sub&gt;f&lt;/sub&gt;&lt;/em&gt;). The classification results were incorporated into the construction and application of an empirical extinction&amp;ndash;PM&lt;sub&gt;2.5&lt;/sub&gt; relationship. For mixed-aerosol samples, the APA component fraction and its associated extinction contribution were estimated before retrieving the vertical PM&lt;sub&gt;2.5&lt;/sub&gt; distribution.&lt;/p&gt;
&lt;p&gt;To quantify the effect of classification constraints, three linear models were developed: a model without aerosol-type constraints, a PDR-only screening model, and a model constrained by combined PDR&amp;ndash;&lt;em&gt;G&lt;sub&gt;f&lt;/sub&gt;&lt;/em&gt; classification. Near-surface, date-separated validation using 411 hourly samples from 69 observation dates showed that the combined-classification model achieved an RMSE of 17.32 &lt;em&gt;&amp;micro;&lt;/em&gt;g m&lt;sup&gt;&amp;minus;3&lt;/sup&gt;, an MAE of 13.54 &lt;em&gt;&amp;micro;&lt;/em&gt;g m&lt;sup&gt;&amp;minus;3&lt;/sup&gt;, and a Bias of 3.30 &lt;em&gt;&amp;micro;&lt;/em&gt;g m&lt;sup&gt;&amp;minus;3&lt;/sup&gt;. Compared with the model without aerosol-type constraints, the RMSE, MAE, and Bias decreased by 38.2 %, 45.0 %, and approximately 83.0 %, respectively. Uncertainty analysis showed that classification end-member and aerosol-type-dependent lidar-ratio perturbations affected the quantitative PM&lt;sub&gt;2.5&lt;/sub&gt; estimates under mixed-aerosol conditions, whereas the residual scatter and parameter stability of the empirical extinction&amp;ndash;PM&lt;sub&gt;2.5&lt;/sub&gt; relationship were the dominant sources of prediction uncertainty.&lt;/p&gt;
&lt;p&gt;For a mixed-to-pollution aerosol evolution episode in Beijing in November 2024, the classification-constrained PM&lt;sub&gt;2.5&lt;/sub&gt; vertical structure was physically consistent with temperature stratification, wind fields, and backward trajectories. Seasonal testing showed no stable and consistent improvement from season-specific fitting. The proposed method provides classification-constrained estimates of the PM&lt;sub&gt;2.5&lt;/sub&gt; vertical structure under APA-dominated conditions in Beijing. Model parameters should be recalibrated using local observations when applied to regions, seasons, or aerosol conditions with substantially different composition.</p>
</abstract>
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