Supplementary Datasets for Regional Wintertime SOA Regimes in PM2.5 across Five Northeast Asian Cities

This record contains machine-readable Supplementary Datasets S1–S4 associated with the manuscript “WSOC-Based SOC Estimates and FT-ICR MS Fingerprints Differentiate Regional Wintertime SOA Regimes in PM2.5 across Five Northeast Asian Cities.” The datasets support analyses of wintertime PM2.5, water-soluble organic carbon (WSOC), secondary organic carbon (SOC), source-diagnostic correlations, FT-ICR MS molecular-formula annotations, and putative molecular-transformation patterns across five Northeast Asian sampling sites: Ulaanbaatar (UB), Beijing (BJ), Seosan (SS), Seoul (SE), and Noto (NT). The coordinated winter campaign was conducted from 15 December 2020 to 14 January 2021. The deposited files include: Supplementary Dataset S1: Daily aerosol composition, harmonized levoglucosan concentrations, WSOC-based biomass-burning correction, WSOCBB, SOC, and POC estimates. Supplementary Dataset S2: Source-diagnostic paired data used for K⁺–OC and Ca²⁺–OC/PM2.5 correlation analyses. Supplementary Dataset S3: Full FT-ICR MS molecular-formula annotation dataset, including sample-level and site/type-level summaries. Supplementary Dataset S4: Molecular-transformation rule datasets, including the full 30-rule mass-shift database and the curated 20-rule set used in the manuscript analyses. For SOC estimation, a uniform (WSOC/OC)BB value of 0.70 was applied across all sites. The site-specific effective OCBB/levoglucosan conversion factors used for biomass-burning correction were 7.76, 4.41, 4.35, 4.25, and 4.28 for UB, BJ, SS, SE, and NT, respectively. Levoglucosan concentrations were harmonized to µg m⁻³, and the SE levoglucosan values were corrected for a 1000-fold scale difference before SOC calculation. The formatted Supporting Information file, including supplementary tables, figures, and methodological details, is submitted separately through the journal submission system. This Zenodo record is intended to provide the underlying machine-readable datasets supporting the manuscript.