講演情報
[AAS08-P02]Development of NISMON-CO: inverse analysis system of atmospheric CO for estimating combustion emissions
*丹羽 洋介1、池田 恒平1、Suman Maity1、五藤 大輔1、八代 尚1、山下 陽介1、Jagat Bisht1、永島 達也1 (1.国立環境研究所)
キーワード：
一酸化炭素、逆解析、数値モデリング
Carbon monoxide (CO) plays a key role in atmospheric chemistry, primarily through its reactions with hydroxyl (OH) radicals, which influence the lifetimes of major greenhouse gases and air pollutants. Owing to its widespread production from combustion processes—including fossil fuel use and biomass burning—CO is also commonly used as a proxy for emissions of co-emitted atmospheric species. Despite its importance, substantial uncertainties persist in quantifying both CO emissions and its atmospheric chemical loss. These uncertainties arise from limited understanding of emission processes, such as activity data and emission factors, as well as from the complex spatiotemporal variability of OH. Spatiotemporal variations in atmospheric CO captured by global observational networks can provide valuable constraints on these sources and sinks through inverse modeling approaches.
In this study, we developed a state-of-the-art inverse modeling system for atmospheric CO, termed the NICAM-based Inverse Simulation for Monitoring CO (NISMON-CO). In NISMON-CO, the atmospheric loss is simplified by linearizing CO-OH chemistry—that is, by prescribing spatiotemporal variations of OH in the transport model NICAM-TM—while spatiotemporal variations in CO emissions are estimated in detail using atmospheric observational constraints within a four-dimensional variational (4D-Var) framework. The targeted emissions include those from combustion sources such as fossil fuel and biomass burning. Prescribed OH fields and CO production from the oxidation of non-methane volatile organic compounds (NMVOCs) are obtained from the atmospheric chemistry model NICAM-Chem, which shares the same dynamical core as NICAM-TM. In addition, atmospheric methane (CH4), a major precursor of CO, is provided by NISMON-CH4, which is tightly constrained by global CH4 observations. Through this integrated framework, NISMON-CO quantifies CO emissions in a manner that is consistent with other CO-related processes, all simulated within the common NICAM modeling system.
In this study, we developed a state-of-the-art inverse modeling system for atmospheric CO, termed the NICAM-based Inverse Simulation for Monitoring CO (NISMON-CO). In NISMON-CO, the atmospheric loss is simplified by linearizing CO-OH chemistry—that is, by prescribing spatiotemporal variations of OH in the transport model NICAM-TM—while spatiotemporal variations in CO emissions are estimated in detail using atmospheric observational constraints within a four-dimensional variational (4D-Var) framework. The targeted emissions include those from combustion sources such as fossil fuel and biomass burning. Prescribed OH fields and CO production from the oxidation of non-methane volatile organic compounds (NMVOCs) are obtained from the atmospheric chemistry model NICAM-Chem, which shares the same dynamical core as NICAM-TM. In addition, atmospheric methane (CH4), a major precursor of CO, is provided by NISMON-CH4, which is tightly constrained by global CH4 observations. Through this integrated framework, NISMON-CO quantifies CO emissions in a manner that is consistent with other CO-related processes, all simulated within the common NICAM modeling system.