Toward an adequate quantification of CH4 emissions from land ecosystems: Integrating field and in-situ observations, satellite data, and modeling

• Qianlai Zhuang
• A. David McGuire
• Jerry M. Melillo
• Ronald G. Prinn

Abstract
Emissions of CH4 from natural and managed land ecosystems account for a significant source of greenhouse gases to the atmosphere. In recent decades, extensive field observations of CH4 emissions and atmospheric CH4 concentrations have been made during a time in which process-based and inversion modeling approaches have matured as powerful tools in estimating regional and global CH4 emissions. However, there are still substantial uncertainties in estimating CH4 exchange with the atmosphere. Much of this uncertainty arises from uncertainties in the extent of wetland distributions and incomplete understanding of the controls and mechanisms of methanogenesis, methanotrophy, and CH4 transport pathways to the atmosphere. Furthermore, there is variability in which factors control CH4 production and consumption in different natural and managed ecosystems. For example, in northern high latitudes, permafrost dynamics significantly influences emissions, while the seasonality of wetland extent is critical in determining emissions from tropical regions. For managed ecosystems (e.g., rice paddies), irrigation and fertilization significantly impact both methanogenesis and methanotrophy. Here we propose a Working Group to make progress in synthesis of CH4 dynamics through three activities: 1) to identify key issues in quantifying CH4 emissions from land ecosystems through conducting comparisons of model and field observations for different geographical locations and ecosystems; 2) to parameterize and extrapolate process-based models at regional and global scales and explore the uncertainty of CH4 emissions; and 3) to couple process-based estimates with inversion modeling approaches to constrain the uncertainty with air-borne, satellite, and in-situ observed datasets and to identify the factors, mechanisms, and controls to the uncertainty of emissions at large-scales.