Spatiotemporal Evolution Pattern of FFCO2 Emissions in the Guangdong-Hong Kong-Macao Greater Bay Area Based on Kalman Filter Using Multi-Source Emission Inventory Fusion
Due to technical gaps in using satellite carbon observations for regional emission reduction,high-resolution,global-scale Fossil Fuel Carbon Dioxide(FFCO2)emission inventories have become the main data sources for regional FFCO2 emission research.However,there are still significant uncertainties in use of existing global-scale FFCO2 emission inventories for regional research.Therefore,this paper quantitatively analyzed the differences and variabilities of high-resolution FFCO2 emission inventories(ODIAC 2020b,EDGAR v6.0,and PKU-CO2-v2)at the regional scale and fused these three inventories based on Kalman filtering algorithm.Then,this paper explored the spatial and temporal evolution pattern of FFCO2 emissions in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA).The results show that:(1)There were significant differences and variability among the current FFCO2 emission inventories.Taking the GBA as an example,under the optimal representation spatial resolution of 3 km×3 km,the average difference of grid cells within the region reached 140%,and the coefficient of variation was 16.3%.The use of a single global scale FFCO2 emission inventory data for regional or urban FFCO2 emission studies resulted in inaccurate results;(2)The reconstructed long term data from 2000 to 2018 using Kalman filter showed that the uncertainty decreased from±15%～20%to±10%;(3)From 2000 to 2018,the overall pattern of FFCO2 emissions in the GBA was characterized by high emissions in Guangzhou,Shenzhen,Hong Kong,and Macao,low emission areas in the peripheral areas,and an emission transfer path from Shenzhen,Hong Kong → Guangzhou → Foshan,Dongguan → Zhongshan.The approach for regional FFCO2 emissions proposed in this paper is demonstrated in the GBA and is applicable to other regions and cities.The conclusions of this research will provide a scientific basis for the optimal layout of energy and resources in the Greater Bay Area,which is of great significance for low-carbon transformation,high-quality development,and the construction of Beautiful Bay Area.
NETL
NSTL
万方数据
