从甲烷大气化学过程、传输模式和反向模拟机理等方面综述了大气甲烷浓度变化及其源汇研究的主要进展及存在的问题。基于数据同化算法的反向模拟能有效降低全球及国家尺度甲烷排放估计的不确定性。但在具体的算法实施中,先验的甲烷排放估计和地面站大气甲烷浓度测定的不确定性量化仍然主要是经验性的,缺乏严格和系统性的量化算法。相对于有限的地面站测定,基于卫星平台的大气甲烷浓度变化监测数据极大地提高了数据的空间覆盖度,进一步促进了反向模拟的应用。当前的反向模拟研究在全球尺度上确认了自然湿地甲烷排放对大气甲烷浓度年际波动的决定性作用;在国家尺度上,反向模拟在国家温室气体清单的“可核查”方面也有广泛的应用前景。

By reviewing the advances in chemical processes, transport models and inverse modeling technologies concerning the atmospheric methane, problems in exploiting the sources and sinks of the atmospheric methane were discussed. The inverse modelling with the atmospheric chemical transport models significantly reduced the uncertainty in the estimation of methane emissions from the terrestrial and oceanic methane sources, when the observational data of the atmospheric methane concentration were assimilated in the inverse modeling. But at present, the quantification of the uncertainty in a priori estimations and the measurements of the atmosphere methane concentration were primarily empirically assigned and no scientifically reliable algorithm is available. Remotely sensed observations of the atmospheric methane concentration dynamics of global covering have greatly promoted the availability of the observations and thereafter improved the efficiency of the inverse modeling. With inverse modeling, the methane emission from natural wetland was identified as the major contributor to the inter-annual variation of the atmospheric methane concentration on global scale. And on regional scales, the inversion modeling has been used to revise national methane emission inventories in some countries and will be an option for verifying the national inventory in compliance with the UNFCCC articles.