Inter-continental variability in the relationship of oxidative potential and cytotoxicity with PM2.5 mass

Sudheer Salana, Haoran Yu, Zhuying Dai, P. S. Ganesh Subramanian, Joseph V. Puthussery, Yixiang Wang, Ajit Singh, Francis D. Pope, Manuel A. Leiva G., Neeraj Rastogi, Sachchida Nand Tripathi, Rodney J. Weber and Vishal Verma ()
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Sudheer Salana: University of Illinois at Urbana Champaign
Haoran Yu: University of Illinois at Urbana Champaign
Zhuying Dai: University of Illinois at Urbana Champaign
P. S. Ganesh Subramanian: University of Illinois at Urbana Champaign
Joseph V. Puthussery: University of Illinois at Urbana Champaign
Yixiang Wang: University of Illinois at Urbana Champaign
Ajit Singh: University of Birmingham
Francis D. Pope: University of Birmingham
Manuel A. Leiva G.: Universidad de Chile, Las Palmeras 3425, Ñuñoa
Neeraj Rastogi: Physical Research Laboratory
Sachchida Nand Tripathi: Indian Institute of Technology Kanpur
Rodney J. Weber: Georgia Institute of Technology
Vishal Verma: University of Illinois at Urbana Champaign

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract Most fine ambient particulate matter (PM2.5)-based epidemiological models use globalized concentration-response (CR) functions assuming that the toxicity of PM2.5 is solely mass-dependent without considering its chemical composition. Although oxidative potential (OP) has emerged as an alternate metric of PM2.5 toxicity, the association between PM2.5 mass and OP on a large spatial extent has not been investigated. In this study, we evaluate this relationship using 385 PM2.5 samples collected from 14 different sites across 4 different continents and using 5 different OP (and cytotoxicity) endpoints. Our results show that the relationship between PM2.5 mass vs. OP (and cytotoxicity) is largely non-linear due to significant differences in the intrinsic toxicity, resulting from a spatially heterogeneous chemical composition of PM2.5. These results emphasize the need to develop localized CR functions incorporating other measures of PM2.5 properties (e.g., OP) to better predict the PM2.5-attributed health burdens.

Date: 2024
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DOI: 10.1038/s41467-024-49649-4

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