Air Quality Monitoring from Space
Satellite observations provide information on air pollutants across the globe with high spatial and temporal resolution. My current research focuses on how these observations can be used to monitor air quality. In my recent work presented in Cooper et al 2020, I developed a new algorithm for inferring surface-level NO2 concentrations with greater accuracy and higher resolution than previous estimates. Applying this algorithm to the newest generation of satellite instruments like TROPOMI or the future TEMPO mission presents an exciting opportunity for air quality monitoring from space.
Satellite observations provide information on air pollutants across the globe with high spatial and temporal resolution. My current research focuses on how these observations can be used to monitor air quality. In my recent work presented in Cooper et al 2020, I developed a new algorithm for inferring surface-level NO2 concentrations with greater accuracy and higher resolution than previous estimates. Applying this algorithm to the newest generation of satellite instruments like TROPOMI or the future TEMPO mission presents an exciting opportunity for air quality monitoring from space.
Satellite Trace Gas Retrievals
Retrieval algorithms are what turn satellite observations of scattered sunlight into air pollutant concentrations. I am working to improve algorithms used to make these observations, such as accounting for aerosol impacts on retrievals (Cooper et al., 2019) and improving the treatment of surface snow cover (Cooper et al., 2018). I also work on understanding how aspects of these retrievals affect comparisons between satellite observations and models (Cooper et al., 2020)
Retrieval algorithms are what turn satellite observations of scattered sunlight into air pollutant concentrations. I am working to improve algorithms used to make these observations, such as accounting for aerosol impacts on retrievals (Cooper et al., 2019) and improving the treatment of surface snow cover (Cooper et al., 2018). I also work on understanding how aspects of these retrievals affect comparisons between satellite observations and models (Cooper et al., 2020)
Top-down Emissions Estimates
Satellite observations can provide useful constraints for estimating emission inventories. In Cooper et al., 2017 I developed an iterative finite difference mass balance approach for estimating global NOx emissions using satellite NO2 observations. For certain conditions, this method can be as accurate as more complex techniques and less computationally expensive. This method has been used in several top-down emission estimate studies.
Satellite observations can provide useful constraints for estimating emission inventories. In Cooper et al., 2017 I developed an iterative finite difference mass balance approach for estimating global NOx emissions using satellite NO2 observations. For certain conditions, this method can be as accurate as more complex techniques and less computationally expensive. This method has been used in several top-down emission estimate studies.