GOSAT and GOSAT-2 have simultaneously observed both reflected SWIR solar light and TIR emissions with a single FTS mechanism with the Thermal And Near-infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) and TANSO-FTS-2 since 2009 and 2018, respectively. Their linear polarization bands provide information on light-path modification and make accurate remote sensing possible, even under aerosol and thin-cloud contaminated conditions. We can retrieve the difference between the partial column-averaged dry-air mole fractions of the two individual layers of lower and upper troposphere (LT and UT) by combining TIR and SWIR spectra data simultaneously, thereby constraining the accurate total column density of XCO2 and XCH4. TANSO-FTS has a two-axis agile pointing system, which allows cross-track and along-track motions It was originally designed for grid scan observations and viewing onboard calibration sources. After the pointing mechanism was switched from primary to secondary on 26 January 2015, We decided to make more frequent target observations, by uploading AT and CT pointing angles and observation timing as commands from the ground every day About 1000 locations are allocated to target observations such as calibration and validation site, megacities, or large emission sources. We define vertical layers of LT and UT not by temperature, but by the retrieved Psurf from individual O2 A band data. The pressure-height ranges of the LT and UT were taken as 0.6–1 Psurf and 0.2–0.6 Psurf, respectively. As the LT includes the entire boundary layer, analysis using XCO2 (LT) and XCH4 (LT) can double the signal of local emissions and remove the effects of CO2 and CH4 variability in the UT, which typically extends over a much wider area. We have targeted intense measurements over mega cities since 2016. We assume the average density of the upper troposphere is a background. We define XCO2 anomalies XCO2(LT)-XCO2(UT average), which show enhancement caused by local anthropogenic emissions. In 2020, we detected lower anomalies than previous years over mega cities such as Tokyo, Beijing, and New York.