County-level CO2 emissions and sequestration in China during 1997–2017

TLDR

China’s top‑down CO₂ reduction strategy highlights the need to account for regional differences, and county‑level data better capture heterogeneity than provincial or city‑level estimates, yet prior studies have largely focused on national or provincial scales. The study aims to estimate county‑level CO₂ emissions across China from 1997–2017 by applying a PSO‑BP algorithm to harmonize DMSP/OLS and NPP/VIIRS satellite data. The authors used a PSO‑BP model to integrate DMSP/OLS and NPP/VIIRS imagery and additionally calculated county‑level terrestrial vegetation carbon sequestration. The resulting county‑level CO₂ emission and sequestration estimates fill data gaps and support the design of targeted emission‑reduction strategies in China.

Abstract

Abstract With the implementation of China’s top-down CO 2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO 2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO 2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO 2 emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO 2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO 2 emissions in China.