方法介绍

China Greenhouse Gas Budget (CNGHG) dataset included the sources and sinks of three GHG (i.e., CO₂, CH₄ and N₂O) for four sectors: energy, industrial processes and product use (IPPU), agriculture, forestry and other land use (AFOLU) and waste. Specifically, the estimated sources and sinks covered multiple sub-sectors of the above four sectors, followed by the IPCC guidelines for national GHG inventories. To ensure accuracy, this dataset covered the period of 2000-2023 when the statistical data available for most emission sources. Comprehensive methods were used in this dataset, including emission factor methods, process-based ecosystem models, atmospheric inversion models and data-driven models.

Emission factor methods

Emission factor methods combine activity data (AD) and emission factor (EF) to estimate total emissions (E). AD means the consumption of a given fossil fuel or the extent of industry activity, and EF indicates the emissions per unit of activity. The equation is:

E = AD × EF

Process-based ecosystem models, data-driven models and atmospheric inversions

Several process-based ecosystem models were used to estimate the carbon sink of terrestrial ecosystem, CH₄ emissions from paddy rice and wetland, natural N₂O emission, and land CH₄ sink. All of these models have been validated previously at site, regional and global scales. Land carbon sink was estimated by the mean simulations of six process-based ecosystem models (BEPS, IBIS, LPJ-GUESS, ORCHIDEE-MICT, TRIPLEX-GHG and iMAPLE). Lateral carbon transport caused by soil erosion and leaching in China along the land-river-ocean continuum was simulated by the land surface model ORCHIDEE-Clateral. Three process-based models, including CH4MOD, IBIS-CH4 and TRIPLEX-GHG, were applied to quantify CH₄ emissions across paddy rice (only CH4MOD and IBIS-CH4) and wetland. The IBIS-MicN model and TRIPLEX-GHG model were applied to quantify N₂O emissions of forest and grassland ecosystems.

Data-driven models were developed to estimate GHG emissions of lakes, reservoirs, natural soils, managed soils and nitrogen deposition in cropland. In addition, this dataset used three atmospheric inversion systems to estimate land carbon sink, two inversion systems to estimate CH₄ sectoral emissions and one inversion system for N₂O emission.