Coupling thermodynamic theory with measurements to characterize acidity of atmospheric particles

Pradeep Saxena, Peter K. Mueller, Yong P. Kim, John H. Seinfeld, Petros Koutrakis, Yong P. Kim

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


The reference method currently being used in community health studies to characterize the acidity of atmospheric particles is based upon measuring the pH of aqueous extracts of atmospheric particles collected on filter media. These measurements represent total extractable acidity, i.e., hydrogen ion concentration at sufficient dilution of the sample, rather than the actual acidity of airborne particles. In contrast, models based upon chemical equilibrium theory can be used to estimate the hydrogen ion concentration and water content of atmospheric particles from the observed concentration of major solutes (sulfate, nitrate, chloride, ammonium, and sodium). Using about 100 data points from an intensive measurement study in Uniontown, Pennsylvania during 1990, we examined the nature and the causes of the deviations between measured and estimated hydrogen ion concentrations. We found that the measured hydrogen ion concentrations were substantially higher than the estimated concentrations because dilution of the sample during extraction promoted dissociation of bisulfate ions and hence increased the hydrogen ion concentration. Because total extractable acidity as measured by the pH method only partially characterizes particles, our results demonstrate that models should be used to augment and improve the information derived from these measurements, particularly to estimate the actual acidity of airborne particles.

Original languageEnglish
Pages (from-to)279-293
Number of pages15
JournalAerosol Science and Technology
Issue number3
StatePublished - 1993

Bibliographical note

Funding Information:
We thank Mary Ann Allan of Electric Power Research Institute (EPRI) and George Allen of Harvard University who managed the Uniontown experiment (EPRI Project RP1630-59) for providing us validated data and Charleen Mueller of Diversified Programming for assistance with data analysis and graphics. We are grateful to Larry Goldstein of EPRI and Richard Schlesinger of New York University Medical Center for their useful comments on the section dealing with application to exposure experiments. This work was supported by EPRI under RP3189-03.


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