A two-step approach for relating tapered element oscillating microbalance and dichotomous air sampler PM2.5 measurements

A method for transforming continuous monitoring (CM) fine particulate matter (aerodynamic diameter <2.5 μm; PM2.5) data (i.e., by tapered element oscillating microbalance [TEOM]) obtained from the Canadian National Air Pollution Surveillance (NAPS) program to meet the data quality objective (DQO) of R2 > 0.8 against the co-located federal reference method (i.e., dichotomous air sampler) is described. By using a two-step linear regression to account for the effect of the ambient temperature, 16 out of the 23 examined sites met the common model adequacy threshold of R2 > 0.8. After the transformation, 20 out of the 23 examined sites met the DQO of R2 > 0.7, as recommended by the U.S. Environmental Protection Agency (EPA). A combined two-step statistical approach was also examined and revealed similar results. The methods described herein show that the CM data can be successfully transformed to meet DQOs for representative sites across Canada using year-round (both summer and winter) data. Implications: This study provides a transformation approach to correct ambient TEOM data against the federal reference method without dividing the ambient data according to warm and cold seasons. This transformation approach will significantly improve the correlation coefficient between TEOM and dichotomous air sampler data. It is possible that TEOM data at many Canadian locations can be transformed to meet the EPA data quality objective, thus making this transformation approach useful for comparisons of ambient PM data across jurisdictions.