Evaluating the Ability of the Pre-Launch TanSat-2 Satellite to Quantify Urban CO2 Emissions

Abstract

TanSat-2, the next-generation Chinese greenhouse gas monitoring satellite for measuring carbon dioxide (CO2), has a new city-scale observing mode. We assess the theoretical capability of TanSat-2 to quantify integrated urban CO2 emissions over the cities of Beijing, Jinan, Los Angeles, and Paris. A high-resolution emission inventory and a column-averaged CO2 (XCO2) transport model are used to build an urban CO2 inversion system. We design a series of numerical experiments describing this observing system to evaluate the impacts of sampling patterns and XCO2 measurement errors on inferring urban CO2 emissions. We find that the correction in systematic and random flux errors is correlated with the signal-to-noise ratio of satellite measurements. The reduction in systematic flux errors for the four cities are sizable, but are subject to unbiased satellite sampling and favorable meteorological conditions (i.e., less cloud cover and lower wind speed). The corresponding correction to the random flux error is 19–28%. Even though clear-sky satellite data from TanSat-2 have the potential to reduce flux errors for cities with high CO2 emissions, quantifying urban emissions by satellite-based measurements is subject to additional limitations and uncertainties.

Sensitivity analysis of carbon dioxide inversion in near-infrared spectra for TanSat-2 satellite

“…The instrument operates in three bands: the O2-A band, the CO2 along with CH4 band, and the CO2 band. The expected inversion accuracy is less than 1 ppm for CO2 and 8 ppb for CH4 5 . The satellite has on-board autonomous cloud recognition capabilities, enabling the identification of the cloud-covered area and intelligent planning of the scanning path, which helps enhance the efficiency of overall observation data.…”