Ammonia (NH3) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to monitor NH3. This study examines long-term measurements of NH3 around Toronto, Canada, derived from three multiscale datasets: 16 years of total column measurements using ground-based Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and ten years of total columns from the Infrared Atmospheric Sounding Interferometer (IASI) sensor onboard the Metop satellites. These datasets were used to quantify NH3 temporal variabilities (trends, inter-annual, seasonal) over Toronto to assess the observational footprint of the FTIR measurements, and two case studies of pollution events due to transport of biomass burning plumes. All three timeseries showed increasing trends in NH3 over Toronto: 3.34 ± 0.44 %/year from 2002 to 2018 in the FTIR columns, 8.88 ± 2.49 %/year from 2013 to 2017 in the surface in-situ data, and 8.78 ± 0.84 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was found for coincidence criterion of ≤ 50 km and ≤ 20 minutes, with r = 0.66 and a slope of 0.988 ± 0.058. The FTIR column and in-situ measurements were standardized and correlated, with 24-day averages and monthly averages yielding correlation coefficients of r = 0.72 and r = 0.75, respectively. FTIR and IASI were also compared against the GEOS-Chem model, run at 2° by 2.5° resolution, to assess model performance and investigate correlation of the model output with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (domain spanning from 35°N to 53°N, and 93.75°W to 63.75°W) resulted in r = 0.62, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2 = 0.38, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2 = 0.26, indicating that a finer spatial resolution is needed to adequately model the variability of NH3. This study also examines two case studies of NH3 enhancements due to biomass burning plumes, in August 2014 and May 2016. In these events, enhancements in both the total columns and surface NH3, were observed.