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However, the intrinsic mechanisms driving their size distribution remain poorly understood. This study introduces an infodynamic analysis to quantify the informational content (infodiversity) of aerosol size distributions from different respiratory activities (breathing, speaking, and coughing). By integrating experimental measurements with probabilistic physical modeling, this study reveals that human aerosols predominantly exhibit lognormal characteristics, often requiring multimodal representations involving mixtures of Lognormal, Gamma, and Weibull distributions. The results indicate that Lognormal distributions dominate aerosol size characterization (64.5%), followed by Weibull (21%), and Gamma (14.5%) distributions, quantified through differential informature values ranging from 0.21 to 5.48 nats. A novel composite normalized infodynamic gap metric was introduced, with a threshold of 0.01, to identify the best mechanistic convergence between the data and statistical models. These findings contribute to aerosol science by providing a rigorous theoretical framework to link microscopic aerosol production mechanisms to macroscopic health-relevant outcomes, thereby guiding future experimental and numerical studies aimed at disease mitigation.<\/jats:p>","DOI":"10.1063\/5.0293235","type":"journal-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T14:41:50Z","timestamp":1762526510000},"update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":1,"title":["Exploring infodynamics in the study of human aerosol droplet size distributions"],"prefix":"10.1063","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9561-9268","authenticated-orcid":false,"given":"M. R. 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