Multi-Species Analysis of Anthropogenic Pollution Using IASI Data
Résumé
In light of rapid urbanization and its impacts on our changing environment, it is imperative that we provide more accurate and consistent analysis of anthropogenic pollution emissions to advance our monitoring, assessment, and predictive capabilities. Here, we explore the use of multiple satellite retrieval products from the Infrared Atmospheric Sounding Interferometer (IASI) instrument on MetOp satellite (in conjunction with retrievals from other instruments like Measurement of Pollution in The Troposphere or MOPITT) towards characterizing and quantifying emissions from anthropogenic pollution. Thus far, the IASI instrument has provided long-term hyperspectral Earth observational records critical to advancing our current capabilities in Numerical Weather Prediction (NWP), atmospheric composition monitoring, and climate studies. A suite of multiple regression analysis of available collocated IASI retrievals (e.g., O3, CO, SO2, CO2, CH4, NH3 and aerosols) is conducted to derive seasonal, annual, and decadal chemical ratios over major pollution regions of the world. This analysis is based on an approach originally applied to ambient CO and NOx concentration to infer vehicular emission ratios. Data quality and data filters are systematically assessed to attain a more robust joint analysis on the patterns of these ratios and emergent relationships between species as well as across the pollution regions. Retrieval characteristics (e.g., averaging kernels, error covariances, systematic biases, pixel resolution) are taken into consideration in assessing the information content (and synergies) of these retrievals. Finally, we compare and contrast these patterns with global model simulations and reanalysis (e.g., NCAR’s Community Atmosphere Model with Chemistry or CAM-Chem, Copernicus Atmosphere Monitoring Service) to assess the ability of these models to capture these emerging patterns associated with anthropogenic pollution.