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A high-resolution infrared Fourier Transform Spectrometer (FTS) has been operational at the Toronto Atmospheric Observatory (TAO)since May 2002. An optimal estimation retrieval technique is used to analyse the observed spectra and provide regular total and partial column measurements of trace gases in the troposphere and stratosphere as part of the Network for the Detection of Atmospheric Composition Change. The quality of these results were assessed through two ground-based validation campaigns, comparisons with three satellite instruments, and comparison with a three-dimensional chemical transport model. The two ground-based campaigns involved two lower-resolution FTS instruments: the University of Toronto FTS and the Portable Atmospheric Research Interferometric Spectrometer for the Infrared. The first campaign took place over the course of four months and is the longest side-by-side intercomparison of ground-based FTS instruments, to date. The second campaign was more focused and involved all three instruments measuring over a two-week period. Simultaneous measurements of O3, HCl, N2O, and CH4 were recorded and average total column differences were all < 3.7% in the extended campaign, and < 4.5% in the focused campaign. Satellite-based comparisons were done with the SCanning and Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Optical Spectrograph and InfraRed Imager System (OSIRIS). Total column CO, CH4, and N2O compared with SCIAMACHY all had average differences < 10% with results from the TAO-FTS being as good as, or better, than that of other instruments. Validation with the ACE-FTS showed that average partial columns of O3, NO2, N2O, CH4, and HCl were within 10% while observations of CO and NO each had an average bias of about 25%. Comparisons of monthly average partial column O3 and NO2 with OSIRIS were highly correlated (R = 0.82-0.97) with monthly mean differences of < 3.1% for O3 and < 2.6% for NO2. Finally, comparisons with the GEOS-Chem chemical transport model revealed that the model consistently over-estimates tropospheric columns of CO and C2H6 observed at TAO. It was determined that the enhanced CO values were partially due to the North American emissions specified in the model, but more work must be done in the future if the source of this discrepancy is to be fully explained.

A high-resolution infrared Fourier Transform Spectrometer (FTS) has been operational at the Toronto Atmospheric Observatory (TAO)since May 2002. An optimal estimation retrieval technique is used to analyse the observed spectra and provide regular total and partial column measurements of trace gases in the troposphere and stratosphere as part of the Network for the Detection of Atmospheric Composition Change. The quality of these results were assessed through two ground-based validation campaigns, comparisons with three satellite instruments, and comparison with a three-dimensional chemical transport model. The two ground-based campaigns involved two lower-resolution FTS instruments: the University of Toronto FTS and the Portable Atmospheric Research Interferometric Spectrometer for the Infrared. The first campaign took place over the course of four months and is the longest side-by-side intercomparison of ground-based FTS instruments, to date. The second campaign was more focused and involved all three instruments measuring over a two-week period. Simultaneous measurements of O3, HCl, N2O, and CH4 were recorded and average total column differences were all < 3.7% in the extended campaign, and < 4.5% in the focused campaign. Satellite-based comparisons were done with the SCanning and Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Optical Spectrograph and InfraRed Imager System (OSIRIS). Total column CO, CH4, and N2O compared with SCIAMACHY all had average differences < 10% with results from the TAO-FTS being as good as, or better, than that of other instruments. Validation with the ACE-FTS showed that average partial columns of O3, NO2, N2O, CH4, and HCl were within 10% while observations of CO and NO each had an average bias of about 25%. Comparisons of monthly average partial column O3 and NO2 with OSIRIS were highly correlated (R = 0.82-0.97) with monthly mean differences of < 3.1% for O3 and < 2.6% for NO2. Finally, comparisons with the GEOS-Chem chemical transport model revealed that the model consistently over-estimates tropospheric columns of CO and C2H6 observed at TAO. It was determined that the enhanced CO values were partially due to the North American emissions specified in the model, but more work must be done in the future if the source of this discrepancy is to be fully explained.

Atmospheric fine particulate matter (PM2.5), which is mostly formed in the atmosphere from precursor gases, contributes to numerous environmental and health concerns. Quantifying the ambient concentrations of PM2.5 and precursor gases can be challenging. Hence, many scientific questions about the formation, chemical composition, and gas/particle partitioning of PM2.5 remain unanswered. Ambient Ion Monitor - Ion Chromatography (AIM-IC) was characterized and utilized to measure the water-soluble composition of PM2.5 (dominated by pNH4+, pSO42-, and pNO3-) and associated precursor gases (dominated by NH3(g), SO2(g), and HNO3(g)) during two field campaigns. The AIM-IC detection limits for hourly sampling were determined to be 3 - 45 ng m-3. The response time for “sticky” gases was significantly improved with a nylon denuder membrane. A novel inlet configuration for the AIM-IC, which minimizes sampling inlet losses and carryover in sample analyses, was implemented. Measurements from the BAQS-Met 2007 campaign were utilized to assess the accuracy of the AURAMS model and investigate gas/particle partitioning in SW Ontario. Due to high sulphate levels, NH3(g) was the limiting chemical factor in the formation and gas/particle partitioning of PM2.5. The errors in the predictions of relative humidity and free ammonia were responsible for the poor agreement iii between modelled and measured pNO3- values. The AIM-IC measurements from the CalNex 2010 study were compared to the CMAQ model and utilized to investigate the gas/particle partitioning in Bakersfield, CA. Very high NH3(g) concentrations were observed, and the formation and partitioning of PM2.5 was limited by HNO3(g) and H2SO4. Evidence of rapid removal of HNO3(g) by interactions with super-micron dust particles, and possibly with the alkaline surface was found. CMAQ exhibited significant biases in the predicted concentrations of pSO42-, NH3(g) and HNO3(g).

Atmospheric fine particulate matter (PM2.5), which is mostly formed in the atmosphere from precursor gases, contributes to numerous environmental and health concerns. Quantifying the ambient concentrations of PM2.5 and precursor gases can be challenging. Hence, many scientific questions about the formation, chemical composition, and gas/particle partitioning of PM2.5 remain unanswered. Ambient Ion Monitor - Ion Chromatography (AIM-IC) was characterized and utilized to measure the water-soluble composition of PM2.5 (dominated by pNH4+, pSO42-, and pNO3-) and associated precursor gases (dominated by NH3(g), SO2(g), and HNO3(g)) during two field campaigns. The AIM-IC detection limits for hourly sampling were determined to be 3 - 45 ng m-3. The response time for “sticky” gases was significantly improved with a nylon denuder membrane. A novel inlet configuration for the AIM-IC, which minimizes sampling inlet losses and carryover in sample analyses, was implemented. Measurements from the BAQS-Met 2007 campaign were utilized to assess the accuracy of the AURAMS model and investigate gas/particle partitioning in SW Ontario. Due to high sulphate levels, NH3(g) was the limiting chemical factor in the formation and gas/particle partitioning of PM2.5. The errors in the predictions of relative humidity and free ammonia were responsible for the poor agreement iii between modelled and measured pNO3- values. The AIM-IC measurements from the CalNex 2010 study were compared to the CMAQ model and utilized to investigate the gas/particle partitioning in Bakersfield, CA. Very high NH3(g) concentrations were observed, and the formation and partitioning of PM2.5 was limited by HNO3(g) and H2SO4. Evidence of rapid removal of HNO3(g) by interactions with super-micron dust particles, and possibly with the alkaline surface was found. CMAQ exhibited significant biases in the predicted concentrations of pSO42-, NH3(g) and HNO3(g).