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In this work we propose an approach to solving a source estimation problembased on representation of carbon dioxide surface emissions as a linearcombination of a finite number of pre-computed empirical orthogonalfunctions (EOFs). We used National Institute for Environmental Studies(NIES) transport model for computing response functions and Kalman filterfor estimating carbon dioxide emissions. Our approach produces resultssimilar to these of other models participating in the TransCom3 experiment. </br>Using the EOFs we can estimate surface fluxes at higher spatial resolution,while keeping the dimensionality of the problem comparable with that in theregions approach. This also allows us to avoid potentially artificial sharpgradients in the fluxes in between pre-defined regions. EOF resultsgenerally match observations more closely given the same error structure asthe traditional method. </br>Additionally, the proposed approach does not require additional effort ofdefining independent self-contained emission regions

atmospheric chemistry and physics

Technical Note: A novel approach to estimation of time-variable surface sources and sinks of carbon dioxide using empirical orthogonal functions and the Kalman filter