Liang Ruosi, Zhang Yuzhong, Hu Qiwen, Li Tingting, Li Shihua, Yuan Wenping, Xu Jialu, Zhao Yujia, Zhang Peixuan, Chen Wei, Zhuang Minghao, Shen Guofeng, Chen Zichong
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, Zhejiang 310030, China.
Environ Sci Technol. 2024 Dec 31;58(52):23127-23137. doi: 10.1021/acs.est.4c09822. Epub 2024 Dec 11.
Rice cultivation is one of the major anthropogenic methane sources in China and globally. However, accurately quantifying regional rice methane emissions is often challenging due to highly heterogeneous emission fluxes and limited measurement data. This study attempts to address this issue by quantifying regional methane emissions from rice cultivation with a high-resolution inversion of satellite methane observations from the Tropospheric Monitoring Instrument (TROPOMI). We apply the method to the largest rice-producing province (Heilongjiang) in China for 2021. Our satellite-based estimation finds a rice methane emission of 0.85 (0.69-1.03) Tg a from the province or an average emission factor of 22.0 (17.8-26.6) g m a when normalized by rice paddy areas. The satellite-based analysis reveals a 2 to 4 times lower bias in widely used global and national inventories, which lack up-to-date regional information. The inversion reduces the uncertainty of regional rice emissions by 73% relative to bottom-up estimates based on field flux measurements. The satellite inversion also shows that the highest rice methane emissions occur in June during the tillering stage of rice, decreasing toward ripening, indicating that the predominant water management practice in the region involves drainage and intermittent flooding after initial flooding. Process-based modeling further suggests that this practice can lead to a reduction of methane emissions by more than 50% compared to continuous flooding of rice paddies and natural wetlands.
水稻种植是中国乃至全球主要的人为甲烷排放源之一。然而,由于排放通量高度不均且测量数据有限,准确量化区域水稻甲烷排放量往往具有挑战性。本研究试图通过利用对流层监测仪(TROPOMI)的卫星甲烷观测数据进行高分辨率反演,来量化水稻种植的区域甲烷排放量,从而解决这一问题。我们将该方法应用于2021年中国最大的水稻种植省份(黑龙江)。我们基于卫星的估算发现,该省水稻甲烷排放量为0.85(0.69 - 1.03)Tg a,以稻田面积归一化后,平均排放因子为22.0(17.8 - 26.6)g m a。基于卫星的分析显示,缺乏最新区域信息的广泛使用的全球和国家清单中的偏差要低2至4倍。与基于实地通量测量的自下而上估算相比,反演将区域水稻排放的不确定性降低了73%。卫星反演还表明,水稻甲烷排放量最高发生在水稻分蘖期的6月,随着水稻成熟排放量逐渐减少,这表明该地区主要的水管理做法是在初次淹水后进行排水和间歇性淹水。基于过程的模型进一步表明,与水稻田和天然湿地的持续淹水相比,这种做法可使甲烷排放量减少50%以上。