Abstract

The study on how the variations in CO2 sources and sinks can affect the CO2 concentration over East Asia would be useful to provide information for policymaker concerning carbon emission reduction. In this study, a nested-grid version of global chemical transport model (GEOS-Chem) is employed to assess the impacts of variations in meteorological parameters, terrestrial fluxes, fossil fuel emissions, and biomass burning on inter-annual variations of CO2 concentrations over East Asia in 2004–2012. Simulated CO2 concentrations are compared with observations at 14 surface stations from the World Data Centre for Greenhouse Gases (WDCGG) and satellite-derived CO2 column density (XCO2) from the Gases Observing SATellite (GOSAT). The comparison shows that the simulated CO2 column density is generally higher than that of GOSAT by 1.33 × 10−6 (annual mean point by point biases averaged over East Asia). The model reasonably captures the temporal variations of CO2 concentrations observed at the ground-based stations, but it is likely to underestimate the peaks-to-troughs amplitude of the seasonal cycle by 50% or more. The simulated surface CO2 concentration in East Asia exhibits the largest inter-annual variation in December-January–February (DJF). The regional mean absolute deviation (MAD) values over East Asia are within (4.4–5.0) × 10−6 for all seasons. Model sensitivity simulations indicate that the inter-annual variations of surface CO2 concentrations are mainly driven by variations of meteorological parameters, and partly modulated by the inter-annual variations of terrestrial fluxes and fossil fuel emissions in local regions. The variations of the terrestrial fluxes and fossil fuel emissions may account for ∼28% of the inter-annual variation of surface CO2 concentration in southern China. The inter-annual variations of the peaks-to-troughs amplitude are dependent on variations of meteorological parameters, terrestrial fluxes and fossil fuel emissions in local regions. The influence of biomass burning emissions is relatively weak.

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