Acta Geographica Sinica ›› 2022, Vol. 77 ›› Issue (3): 650-664.doi: 10.11821/dlxb202203011

• Carbon Budget and Ecosystem Services • Previous Articles     Next Articles

Developing FFCO2 emission inventory with high spatio-temporal resolution: Methodology and prospects

MA Li1(), WANG Jingxu1, ZHANG Didi1, WANG Mingzhu1, SONG Yubiao1, ZENG Hui2()   

  1. 1. School of Earth Science and Engineering Hebei University of Engineering, Handan 056038, Hebei, China
    2. Shenzhen Graduate School, Peking University, Shenzhen 518071, Guangdong, China
  • Received:2021-06-15 Revised:2021-12-02 Online:2022-03-25 Published:2022-05-23
  • Contact: ZENG Hui E-mail:mali@hebeu.edu.cn;zengh@pkusz.edu.cn
  • Supported by:
    Shenzhen steady support project(GXWD20201231165807007-20200812142216001);Shenzhen Basic Research Free-exploration Project(JCYJ20180302150417674);National Natural Science Foundation of China(41871191)

Abstract:

According to the statistics of the United Nations Environment Program (UNEP), fossil fuel (FF) CO2 emission comprises a major proportion of global anthropogenic greenhouse gas emissions. The inverse modeling approach was proposed to verify the results of the traditional bottom-up inventory based on atmospheric concentration (remote sensing and ground-based measurement) in the refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories on the 49th IPCC Plenary Session in 2019. This approach would further promote the development of high-resolution FFCO2 emission inventory which serves as the spatially and temporally distributed form of emission inventory and the prior input data for the inverse model. This paper hereby summarized the spatial distribution and temporal disaggregation approaches of high-resolution FFCO2 emission inventory from global and national scales to a city-wide scale, and put forward the future research prospects based on the specific requirements for high-resolution emission inventories in this 2019 refinement to the IPCC Guidelines: (1) the refined IPCC methodology will help to further improve the spatial and temporal resolution and the accuracy of FFCO2 emission inventories; and the high-resolution FFCO2 emission inventory concerning indirect emissions is emerging. (2) It is a good practice to compile a high-resolution FFCO2 emission inventory with the detailed spatial and temporal information from facility-level emission data, the remote sensing images and the intelligent transportation big data, while the use of geospatial surrogate data or proxy variables, and modeling such as regression, assimilation and artificial neural network, is also necessary to improve the accuracy of the estimates both spatially and temporally when the directly applicable data are unavailable. (3) The uncertainty information of the spatial distribution and temporal disaggregation should be qualitatively or quantitatively analyzed. The atmospheric inversion verification approach, as an independent and objective accounting method, will play an important role in QA/QC and verification of the high-resolution FFCO2 emission inventory.

Key words: emission inventory, high-resolution, carbon emissions, inversion, spatio-temporal pattern