AJSST › Volume 1, Issue 1 › Article 1
Review Article · Article 1 · 14 pages · Published October 10, 2026Advancing Aerosol Measurement Traceability, AI and Machine Learning, Regulatory Standards, and Cross-Disciplinary Harmonization for Climate Change and Sustainability
1Department of Biotechnology, Sathyabama Institute of Science and Technology, Chennai, 600119, India
2Department of Materials Science and Engineering, University of Houston, TX 77004, United States
3Department of Engineering Data Science, University of Houston, TX 77004, United States
4Department of Bachelor of Science, Annamalai University, Tamil Nadu - 608002, India
5Department of Computer Science & Engineering, Vinayaka Missions University, India
*Corresponding author: indumathi.biotech@sathyabama.ac.in
Abstract
Aerosols exert diverse influences on human health, agriculture, air quality, and climate systems. Despite continuous progress in aerosol measurement technologies and methodologies, significant uncertainties persist in quantifying their physical properties across many applications. Accurate characterization of airborne particles particularly in terms of number and mass concentrations, size distributions, and light adsorption properties is essential for understanding their atmospheric behavior and environmental fate. This study evaluates the physical properties of aerosols with a focus on measurement protocols and documentary standards that ensure traceability and enable interoperability of data obtained using different instruments across spatial and temporal scales. To enhance awareness and highlight inconsistencies in measurement practices across aerosol science subfields, existing standards and regulatory frameworks related to air quality and particle emissions from transportation (automobiles, aviation, shipping) and stationary sources are critically reviewed. Emphasis is placed on the urgent need for harmonization of measurement methodologies, supported by specific examples and practical recommendations. Owing to its comprehensive treatment of aerosol measurement practices and documentary standards across multiple disciplines, this review serves as a valuable reference for researchers and policymakers seeking to improve measurement accuracy and consistency.
Keywords: Atmospheric aerosols: Nanoparticles; Health impacts; Climate change; Radioactive aerosols, Exposure assessment.
How to cite
Subburao S, Ravichandran, Srinivasan D, et al. (2026). Advancing Aerosol Measurement Traceability, AI and Machine Learning, Regulatory Standards, and Cross-Disciplinary Harmonization for Climate Change and Sustainability. American Journal of Sustainable Science and Technology, 1(1), Article 1. https://aasrtresearch.org/articles/ajsst-2026-001.html
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| Journal | American Journal of Sustainable Science and Technology |
| ISSN | 3144-735X (online) |
| Volume / Issue | Volume 1, Issue 1 (October 2026) |
| Article number | 1 |
| Article type | Review Article |
| Pages | 14 |
| Published | October 10, 2026 |
| DOI | To be assigned |
| Full text | Download PDF |
| Corresponding author | indumathi.biotech@sathyabama.ac.in |
| Publisher | American Association of Scientific Research and Technology (AASRT) |
| Copyright | © 2026 American Association of Scientific Research and Technology. All rights reserved. |
| Reuse | Free to read and download for personal research and teaching. Authors may reuse their own article in teaching and in a thesis or dissertation. Redistribution or other reuse requires written permission from AASRT. See Copyright and licensing. |