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. Quantitative calibration of analytes using chemical ionizationmass spectrometers (CIMSs) has been hindered by the lack of commerciallyavailable standards of atmospheric oxidation products. To accuratelycalibrate analytes without standards, techniques have been recentlydeveloped to log-linearly correlate analyte sensitivity with instrumentoperating conditions. However, there is an inherent bias when applyinglog-linear calibration relationships that is typically ignored. In thisstudy, we examine the bias in a log-linear-based calibration curve based onprior mathematical work. We quantify the potential bias within the contextof a CIMS-relevant relationship between analyte sensitivity and instrumentvoltage differentials. Uncertainty in three parameters has the potential tocontribute to the bias, specifically the inherent extent to which thenominal relationship can capture true sensitivity, the slope of therelationship, and the voltage differential below which maximum sensitivityis achieved. Using a prior published case study, we estimate an average biasof 30 %, with 1 order of magnitude for less sensitive compounds in somecircumstances. A parameter-explicit solution is proposed in this work forcompletely removing the inherent bias generated in the log-linearcalibration relationships. A simplified correction method is also suggestedfor cases where a comprehensive bias correction is not possible due tounknown uncertainties of calibration parameters, which is shown to eliminatethe bias on average but not for each individual compound.

Correcting bias in log-linear instrument calibrations in the context of chemical ionization mass spectrometry