A calibration equation for oxygen optodes based on physical properties of the sensing foil

Abstract

We present a new physically based calibration equation for Aanderaa Inc. oxygen sensing optodes. We use the two site fluorescence quenching model of Demas et al. (1995) to describe the nonlinear Stern-Volmer response of the optode foil to oxygen partial pressure. Seven (minimally six) coefficients quantify foil response to oxygen and temperature; another quantifies response to hydrostatic pressure. These eight coefficients are related, theoretically, to basic physical properties of the foil. The equation provides a framework to study causes of variability and drift in optodes and to develop better quality control and handling procedures. We tested the equation using factory calibrations of 24 optode foils. When accurate multi-point calibration data are unavailable, two additional coefficients empirically correct the usually large differences observed between factory foil calibrations and post-factory laboratory/field calibrations; we cannot eliminate this major cause of uncertainty in optode calibrations. Excluding two potentially anomalous foils, the calibration equation fits 13 similarly calibrated foils, totaling 455 calibration points over 3 -40°C to -0.57 ± 1.48 mbar. Analysis of the resulting best fit coefficients reveals an underlying variability in optodes associated with variability in site 2 and site 1 Stern-Volmer coefficients of 32% and 20%, respectively. The fraction of unquenched fluorophores responding with the more accessible site 1 quenching characteristics varies by only 3%. The equation fits multi-point data for two optodes within manufacturer's specifications, the greater of ± 2.5 μmol . kg -1 and ± 1.5%. Detailed measurements of calibration changes over time will be required to understand the causes of optode drift.

Tackling Oxygen Optode Drift: Near-Surface and In-Air Oxygen Optode Measurements on a Float Provide an Accurate in Situ Reference

“…In reality, optodes deviate from a linear Stern-Volmer behavior and a number of parametric models exist to relate sensor data (phase shift and temperature) to oxygen (e.g., Aanderaa high-order polynomials; Uchida et al 2008;McNeil and D'Asaro 2014). While numbers vary somewhat with the choice of the model, the drift characteristic ( Fig.…”

Oxygen Optode Sensors: Principle, Characterization, Calibration, and Application in the Ocean

“…These models include high-order polynomials (e.g., Aanderaa Data Instruments AS, 2009, Appendix 6), parametric models inspired by Stern-Volmer (Uchida et al, 2008(Uchida et al, , 2010Sea-Bird Electronics, 2013; this work), and two-site physics (McNeil and D'Asaro, 2014). Their output can either be an oxygen concentration c O 2 (Uchida et al, 2008;Aanderaa Data Instruments AS, 2009;Sea-Bird Electronics, 2013) or an oxygen partial pressure pO 2 (Bittig et al, 2012;McNeil and D'Asaro, 2014;this work), which both can be converted using temperature and salinity . More details about these calculations can be found in section 5.2.…”

Pressure Response of Aanderaa and Sea-Bird Oxygen Optodes

“…It evolved from a polynomial approach (e.g., Aanderaa Data Instruments 2009, appendix 6) over variants of a Stern-Volmer inspired, parametric function (Uchida et al 2008(Uchida et al , 2010Sea-Bird Electronics 2013) to a model approximating two-site physics (McNeil and D'Asaro 2014). The calculated oxygen quantity is either the (freshwater) c O 2 (Aanderaa Data Instruments 2009; Uchida et al 2008;Sea-Bird Electronics 2013), which requires subsequent salinity correction, or the pO 2 (Bittig et al 2012;McNeil and D'Asaro 2014), which can be converted to concentration via the oxygen solubility c O 2 * (Garcia and Gordon 1992) [see Eq. (6) in section 2a].…”