Examining partial-column density retrieval of lower-tropospheric CO2 from GOSAT target observations over global megacities

We retrieved and examined the partial-column densities of carbon dioxide (CO2) in the lower (LT, typically 0-4 km) and upper (UT, typically 4-12 km) troposphere (XCO2LT and XCO2UT) collected over six global megacities: Beijing, New Delhi, New York City, Riyadh, Shanghai, and Tokyo. The radiance spectra were collected using the Thermal And Near-infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT). Our retrieval method uniquely utilizes reflected sunlight with two orthogonal components of polarization and thermal emissions. We defined megacity concentration enhancement due to surface CO2 emissions as XCO2LT minus XCO2UT, allowing us to overcome some of the challenges in the enhancement analysis using existing column density data. We examined the relationship between the XCO2LT enhancements from the time series of intensive target observations over megacities and the inverse of simulated wind speed, which could be potentially used to estimate surface emissions. Next, we attempted to estimate the average emission intensity for each city from the linear regression slope. We also compared our obtained emission estimates with the Open-Data Inventory for Anthropogenic CO2 (ODIAC) inventory for evaluation. Our results demonstrate the potential utility of the new partial-column density retrievals for estimating megacity CO2 emissions. More frequent and comprehensive coverage characterizing the spatial distribution of emissions is necessary to reduce random error and bias associated with the obtained estimate.

Automated summary

This study examines the potential of using new partial-column density retrievals to estimate CO2 emissions in megacities and explores the relationship between concentration enhancement and inverse simulated wind speed as an indicator of surface emissions.