Cross-Inventory Uncertainty Analysis of Fossil Fuel CO2 Emissions for Prefecture-Level Cities in Shandong Province

Abstract

A series of carbon dioxide (CO2) emission inventories with high spatial resolutions covering China have been developed in the last decade, making it possible to assess not only the anthropogenic emissions of large administrational units (countries; provinces) but also those of small administrational units (cities; counties). In this study, we investigate three open-source gridded CO2 emission inventories (EDGAR; MEIC; PKU-CO2) and two statistical data-based inventories (CHRED; CEADs) covering the period of 2000–2020 for 16 prefecture-level cities in Shandong province in order to quantify the cross-inventory uncertainty and to discuss potential reasons for it. Despite ±20% differences in aggregated provincial emissions, all inventories agree that the emissions from Shandong increased by ~10% per year before 2012 and that the increasing trend slowed down after 2012, with a quasi-stationary industrial emission proportion being observed during 2008–2014. The cross-inventory discrepancies increased remarkably when downscaled to the city level. The relative differences between two individual inventories for half of the cities exceeded 100%. Despite close estimations of aggregated provincial emissions, the MEIC provides relatively high estimates for cities with complex and dynamic industrial systems, while the CHRED tends to provide high estimates for heavily industrial cities. The CHRED and MEIC show reasonable agreement regarding the evolution of city-level emissions and the city-level industrial emission ratios over 2005–2020. The PKU-CO2 and EDGAR failed to capture the emissions and their structural changes at the city level, which is related to their point-source database stopping updates after 2012. Our results suggest that cross-inventory differences for city-level emissions exist not only in their aggregated emissions but also in their changes over time.