Atmospheric carbon monoxide (CO) is a product of incomplete combustion and a byproduct of the oxidation of hydrocarbons. It plays a key role in controlling the oxidative capacity of the atmosphere since it is the main sink for the hydroxyl radical (OH), the primary tropospheric oxidant. As a result of its lifetime, CO is a useful tracer of long-range transport in models. However, estimates of the regional sources of CO are uncertain. Inverse modeling has become a widely used approach for better quantifying the sources, but a fundamental assumption in these inversions, which is typically not valid, is that the observations and models are unbiased. In this thesis, the GEOS-Chem model and observations of CO from the Measurement Of Pollution In The Troposphere (MOPITT) instrument are employed to study the impact of systematic model errors on inversion analyses of CO. The impact of the treatment of biogenic non-methane volatile organic compounds (NMVOCs), aggregation errors, and discrepancies in the meteorological fields and OH distribution on the CO source estimates are examined. The influence of vertical transport errors on the source estimates is assessed using newly available MOPITT version 5 (V5) retrievals in a comparative inversion analysis employing surface level, profile, and column data. To quantify the potential impact of discrepancies in long-range transport on the source estimates, a high-resolution, regional inversion over North America, with optimized lateral boundary conditions, was conducted and compared with the results of a global inversion. The influence of the spatial-temporal distribution of the observations on the source estimates was also assessed through a comparison of the inversion analyses of MOPITT data and aircraft data from the Intercontinental Transport Experiment – North America, Phase A (INTEX-A) aircraft campaign. The results presented in the thesis provide a more comprehensive understanding of the potential impact of system model errors on inversion analyses of CO. This work also represents the first inverse modeling analysis of the MOPITT v5 retrievals. The results demonstrate the potential utility of these new data for characterizing vertical transport errors in models and they reveal that the new data can provide reliable constraints in regional CO source estimates.

Atmospheric carbon monoxide (CO) is a product of incomplete combustion and a byproduct of the oxidation of hydrocarbons. It plays a key role in controlling the oxidative capacity of the atmosphere since it is the main sink for the hydroxyl radical (OH), the primary tropospheric oxidant. As a result of its lifetime, CO is a useful tracer of long-range transport in models. However, estimates of the regional sources of CO are uncertain. Inverse modeling has become a widely used approach for better quantifying the sources, but a fundamental assumption in these inversions, which is typically not valid, is that the observations and models are unbiased. In this thesis, the GEOS-Chem model and observations of CO from the Measurement Of Pollution In The Troposphere (MOPITT) instrument are employed to study the impact of systematic model errors on inversion analyses of CO. The impact of the treatment of biogenic non-methane volatile organic compounds (NMVOCs), aggregation errors, and discrepancies in the meteorological fields and OH distribution on the CO source estimates are examined. The influence of vertical transport errors on the source estimates is assessed using newly available MOPITT version 5 (V5) retrievals in a comparative inversion analysis employing surface level, profile, and column data. To quantify the potential impact of discrepancies in long-range transport on the source estimates, a high-resolution, regional inversion over North America, with optimized lateral boundary conditions, was conducted and compared with the results of a global inversion. The influence of the spatial-temporal distribution of the observations on the source estimates was also assessed through a comparison of the inversion analyses of MOPITT data and aircraft data from the Intercontinental Transport Experiment – North America, Phase A (INTEX-A) aircraft campaign. The results presented in the thesis provide a more comprehensive understanding of the potential impact of system model errors on inversion analyses of CO. This work also represents the first inverse modeling analysis of the MOPITT v5 retrievals. The results demonstrate the potential utility of these new data for characterizing vertical transport errors in models and they reveal that the new data can provide reliable constraints in regional CO source estimates.

This thesis presents the characterization and calibration of the MOPITT-A instrument which uses the technique of correlation spectroscopy to ensure carbon monoxide in the atmosphere. A theoretical model is developed for the instrument and compared to MOPITT-A measurements collected under controlled laboratory conditions, which were designed to emulate atmospheric signals. It is shown that the model and measurements are in very good agreement with each other and that the MOPITT-A instrument behaves as expected. It was found that the gain of the instrument varies with time. The cause of the gain variation is not known but it is suggested that frosting inside the detector nest would be consistent with the observed nature of the variation.

This thesis presents the characterization and calibration of the MOPITT-A instrument which uses the technique of correlation spectroscopy to ensure carbon monoxide in the atmosphere. A theoretical model is developed for the instrument and compared to MOPITT-A measurements collected under controlled laboratory conditions, which were designed to emulate atmospheric signals. It is shown that the model and measurements are in very good agreement with each other and that the MOPITT-A instrument behaves as expected. It was found that the gain of the instrument varies with time. The cause of the gain variation is not known but it is suggested that frosting inside the detector nest would be consistent with the observed nature of the variation.

This thesis presents a methodological approach to developing the capability of the Infrared Atmospheric Sounding Interferometer (IASI) instrument to inform on the atmospheric concentrations of carbon monoxide (CO), focussing on three key studies: 1) an assessment of the radiometric accuracy of the instrument; 2) the development of the University of Leicester IASI Retrieval Scheme (ULIRS) to convert measured radiances into a CO product; and 3) an investigation into the reliability and possible use of the ULIRS product. An intercomparison between the radiances as measured by the IASI and Advanced Along Track Scanning Radiometer (AATSR) instruments is performed, and absolute differences at 11 µm of less than 0:1K are observed. Given the radiometric behaviour across the IASI instrument as a whole, it is also concluded that the IASI instrument is radiometrically accurate to < 0.3K in the 12 and 4.7 µm spectral regions. A retrieval scheme, the ULIRS, is developed with explicit digital elevation and emissivity information, and a correction for solar surface reflection with a high resolution solar spectrum. Typical random errors over the African region relating to the profiles are found to be ~10% at 5 and 12 km, and on the total columns to be ~12 %. The ULIRS dataset and the operational CO products from the Measurements Of Pollution In The Troposphere (MOPITT) are inter-compared. A methodology which uses the same a priori statistics, and which reduces the smoothing bias between the two sets of data shows that there is only a small bias between the ULIRS and MOPITT V4 products. A simplified top-down approach to estimating CO emissions from fires is also presented, highlighting the need for a better understanding of the correct detection of burnt area from space-based measurements.