A two-step approach for relating tapered element oscillating microbalance and dichotomous air sampler PM_2.5 measurements

Abstract

A method for transforming continuous monitoring (CM) fine particulate matter (aerodynamic diameter <2.5 μm; PM_2.5) 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.

Acknowledgment

The authors would like to thank the Environment Canada National Air Pollution Surveillance Network for providing the data used in this paper, and Yang Chen and Tengzhou Lun for assistance with data analysis and validation. The authors are grateful for the useful comments from the three reviewers and constructive suggestions from Dr. Allan Legge and Dr. Rongcai Yang.

Additional information

Notes on contributors

Long Fu

Long Fu is a science manager with the Alberta Environmental Monitoring, Evaluation and Reporting Agency, Edmonton, Alberta, Canada.

Thompson Nunifu

Thompson Nunifu is an environmental statistician and Bonnie Leung is an analytical chemist with Alberta Environment and Sustainable Resource Development, Edmonton, Alberta, Canada.

Bonnie Leung

Thompson Nunifu is an environmental statistician and Bonnie Leung is an analytical chemist with Alberta Environment and Sustainable Resource Development, Edmonton, Alberta, Canada.