A Calibration Model Maintenance Roadmap

Atmospheric particulate matter characterization by Fourier Transform Infrared spectroscopy: a review of statistical calibration strategies for carbonaceous aerosol quantification in US measurement networks

“…Calibration maintenance and transfer learning addresses the problem of updating a calibration model developed under one set of conditions to continue providing accurate predictions for samples measured under new conditions (Feudale et al, 2002;Torrey and Shavlik, 2009;Pan and Yang, 2010;Wise and Roginski, 2015). This topic has not yet been addressed for TOR OC and EC calibrations using FT-IR, but we can nonetheless make a few remarks for future research needs.…”

“…In this way, a significant investment of resources required by model building (consisting of data 15 collection and evaluation) may be avoided. For changes in instrument performance or installation of a separate spectrometer, commonly applied modifications range from simple linear corrections of predictions to calibration transfer algorithms to convert spectra to resemble that which may have been acquired from the primary instrument in its original state so that the original model remains applicable (Wise and Roginski, 2015;Chen et al, 2016b;Malli et al, 2017). The contribution from PTFE can presumably be removed with the appropriate baseline correction technique (Section 3.3.2).…”

“…The contribution from PTFE can presumably be removed with the appropriate baseline correction technique (Section 3.3.2). Though not been tested 20 extensively across various filter types, successful prediction has been reported between two PTFE filter types (Weakley et al, 2018b (Ottaway et al, 2012;Kalivas, 2012;Wise and Roginski, 2015), though also requires evaluation. Changing atmospheric composition can be addressed by updating the calibration set with new samples which contain new analytes or different regimes in concentration.…”

“…5), equivalent to the product of latent variables unused for calibration. In an analytical chemistry context, high values of T 2 result from extreme values or unusual combinations of the same chemical components as those in the calibration set, whereas introduction of new analytes or interferences that result in spectroscopic response lying outside of the modeled domain would be carried in the residuals (Wise and Roginski, 2015). In 10 practice, the separation of unfamiliar contributions to the spectra is likely not as clean, particularly with respect to nonlinear phenomena (e.g., scattering) which can be spread over multiple factors, and the portion of the spectroscopic signal associated with new substances may not be entirely apportioned to the residuals.…”

Evaluation of time-gated Raman spectroscopy for the determination of nitric, sulfuric and hydrofluoric acid concentrations in pickle liquor

“…Once again, it has to be noted that when using reference results for calibration, the uncertainty of the reference measurements also increases the uncertainty of the calibration model. The validity assessment and updating 25,26 of the calibration model during longer measurement periods and in industrial conditions requires further studies.…”