Theoretical Potential of TanSat-2 to Quantify China’s CH4 Emissions - Sihong Zhu; Dongxu Yang; Liang Feng; Longfei Tian; Yi Liu; Junji Cao; Minqiang Zhou; Zhaonan Cai; Kai Wu; Paul I. Palmer (Remote Sensing)
Satellite-based monitoring of atmospheric column-averaged dry-air mole fraction (XCH4) is essential for quantifying methane (CH4) emissions, yet uncharacterized spatially varying biases in XCH4 observations can cause misattribution in flux estimates. This study assesses the potential of the upcoming TanSat-2 satellite mission to estimate China’s CH4 emission using a series of Observing System Simulation Experiments (OSSEs) based on an Ensemble Kalman Filter (EnKF) inversion framework coupled with GEOS-Chem on a 0.5° × 0.625° grid, alongside an evaluation of current TROPOMI-based products against Total Carbon Column Observing Network (TCCON) observations. Assuming a target precision of 8 ppb, TanSat-2 could achieve an annual national emission estimate accuracy of 2.9% ± 4.2%, reducing prior uncertainty by 84%, with regional deviations below 5.0% across Northeast, Central, East, and Southwest China. In contrast, limited coverage in South China due to persistent cloud cover leads to a 26.1% discrepancy—also evident in pseudo TROPOMI OSSEs—highlighting the need for complementary ground-based monitoring strategies. Sensitivity analyses show that satellite retrieval biases strongly affect inversion robustness, reducing the accuracy in China’s total emission estimates by 5.8% for every 1 ppb increase in bias level across scenarios, particularly in Northeast, Central and East China. We recommend expanding ground-based XCH4 observations in these regions to support the correction of satellite-derived biases and improve the reliability of satellite-constrained inversion results.