title: Improving the correlations of ambient tapered element oscillating microbalance PM2.5 data and SHARP 5030 Federal Equivalent Method in Ontario: a multiple linear regression analysis.
abstract: Tapered element oscillating microbalances equipped with sample equilibration system (TEOM-SES) used by the province of Ontario for the ambient monitoring of PM2.5 (particulate matter with an aerodynamic diameter < or = 2.5 microm) in its air quality index (AQI) network were collocated with the Synchronized Hybrid Ambient Real-time Particulate monitor (SHARP 5030) at two monitoring sites for a period spanning approximately 2 years to determine the similarities and differences between the measurement outputs of both instrumental systems. Due mainly to mass loss observed with the TEOM-SES in cooler months, the province has recently switched its PM2.5 instrumentation at all stations in its monitoring network from the TEOM-SES to the SHARP 5030, which has the U.S. Environmental Protection Agency (EPA) Federal Equivalent Method (FEM) Class III designation. Thus, it has become imperative to develop corrections for historical and future TEOM measurements for the purpose of making them more agreeable to the new FEM method. This work details the authors' multiple linear regression analyses (MLRAs) of particulate matter data from both instrumental monitors, with the inclusion of operational parameters of physicochemical relevance for both cases of transformations of historical TEOM and TEOM measurements to be made in the future. For historical TEOM data, it was observed that the transformations only benefited winter and fall months. Furthermore, comparisons of the transformed historical TEOM data with PM2.5 concentrations determined from the Federal Reference Method (FRM) sampler at seven locations within the province showed marked improvements over the observed TEOM-FRM comparisons.
  
  
  CONCLUSIONS
  This work provides a path to correcting the historically observed underreporting of particulate mass in winter and fall in Ontario by making the TEOM-based continuous data resemble the new FEM outputs (in this case, more SHARP-like). It is possible that the transformation of mainly winter TEOM data as detailed in this work may potentially lead to revisions in historical annual composite mean PM2.5 concentrations and total annual number of days PM2.5 exceeded the Canada-wide Standard (CWS) metric across the province.
authors.forename: Uwayemi
authors.initials: U
authors.lastname: Sofowote
authors.forename: Yushan
authors.initials: Y
authors.lastname: Su
authors.forename: Melynda M
authors.initials: MM
authors.lastname: Bitzos
authors.forename: Anthony
authors.initials: A
authors.lastname: Munoz
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods*; D016014:Linear Models; D009864:Ontario; D010316:Particle Size; D052638:Particulate Matter / Q000737:chemistry*; D012621:Seasons
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter