Spatiotemporal variations of atmospheric XCH4 in China based on multiple spatially continuous satellite-derived products

Yibo Liu; Siqing Zhang; Shanlei Sun; Hao Song; Ningxuan Jiang; Danqi Wei; Ruoyi Zhou; Yanlian Zhou; Wei Xiao

doi:10.1016/j.jenvman.2025.126309

Spatiotemporal variations of atmospheric XCH₄ in China based on multiple spatially continuous satellite-derived products

J Environ Manage. 2025 Jun 26:390:126309. doi: 10.1016/j.jenvman.2025.126309. Online ahead of print.

Authors

Yibo Liu¹, Siqing Zhang², Shanlei Sun³, Hao Song⁴, Ningxuan Jiang⁵, Danqi Wei⁵, Ruoyi Zhou⁵, Yanlian Zhou⁶, Wei Xiao⁷

Affiliations

¹ Yale-NUIST Center on Atmospheric Environment, State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 21004, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, 210044, China. Electronic address: yiboliu@nuist.edu.cn.
² Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
³ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, 210044, China.
⁴ Beijing Institute of Earth Science and Resources, China University of Geosciences (Beijing), Beijing, 100083, China.
⁵ Yale-NUIST Center on Atmospheric Environment, State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 21004, China.
⁶ School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
⁷ Yale-NUIST Center on Atmospheric Environment, State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 21004, China. Electronic address: wei.xiao@nuist.edu.cn.

PMID: 40577866
DOI: 10.1016/j.jenvman.2025.126309

Abstract

Spatiotemporally continuous satellite CH₄ column concentrations (XCH₄) are crucial for accurately assessing variations in atmospheric CH₄. However, most existing studies rely on single or a limited number of spatiotemporally discontinuous XCH₄ satellite observations. This study evaluates the accuracy of three newly developed spatiotemporally continuous reconstructed XCH₄ products -Song-XCH₄, Wang-XCH₄, and Jin-XCH₄ using ground-based data from the Total Carbon Column Observing Network (TCCON) and the World Data Centre for Greenhouse Gases (WDCGG), and analyzes the spatiotemporal variations of XCH₄ across China. Results show that: 1) All three products exhibit good consistency with ground-based observations, except the Lulin station. The three products align better with TCCON data overall than with WDCGG data, with Wang-XCH₄ demonstrates the best overall agreement. 2) All three products consistently reveal a gradient from high values in the southeast to low values in the northwest of China. The national annual average XCH₄ from Wang-XCH₄ is approximately 10 ppb higher than that from Song and Jin-XCH₄, with the largest regional average differences (18.0-33.3 ppb) observed in North, Central, and Southwest China. 3) Although the national annual mean XCH₄ increased significantly at an approximate rate of 8.0 ppb yr^-1 from 2010 to 2020, Song-XCH₄ showed greater spatial variability. It exhibited the highest seasonal growth rates in summer and autumn (8.0 ppb) and the lowest in spring (7.4 ppb), whereas Wang-XCH₄ showed the fastest increase in autumn (8.1 ppb) but the slowest in summer (6.9 ppb). Our findings highlight the importance of exercising caution when using satellite-based reconstructed XCH₄ products.

Keywords: China; GOSAT; Satellite remote sensing; Spatiotemporally continuous; TROPOMI; XCH(4).