Theoretical Potential of TanSat-2 to Quantify China’s CH<sub>4</sub> Emissions

Theoretical Potential of TanSat-2 to Quantify China’s CH<sub>4</sub> Emissions

Satellite-based monitoring of atmospheric column-averaged dry-air mole fraction (XCH<sub>4</sub>) is essential for quantifying methane (CH<sub>4</sub>) emissions, yet uncharacterized spatially varying biases in XCH<sub>4</sub> observations can cause misattribution...

Full description

Saved in:

Bibliographic Details
Main Authors:	Sihong Zhu, Dongxu Yang, Liang Feng, Longfei Tian, Yi Liu, Junji Cao, Minqiang Zhou, Zhaonan Cai, Kai Wu, Paul I. Palmer
Format:	Article
Language:	English
Published:	MDPI AG 2025-07-01
Series:	Remote Sensing
Subjects:	TanSat-2 methane emission inversion OSSEs
Online Access:	https://www.mdpi.com/2072-4292/17/13/2321
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Satellite-based monitoring of atmospheric column-averaged dry-air mole fraction (XCH<sub>4</sub>) is essential for quantifying methane (CH<sub>4</sub>) emissions, yet uncharacterized spatially varying biases in XCH<sub>4</sub> observations can cause misattribution in flux estimates. This study assesses the potential of the upcoming TanSat-2 satellite mission to estimate China’s CH<sub>4</sub> 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 <i>pseudo</i> 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 XCH<sub>4</sub> observations in these regions to support the correction of satellite-derived biases and improve the reliability of satellite-constrained inversion results.
ISSN:	2072-4292