Exploring the spatiotemporal heterogeneity and influencing factors of agricultural carbon footprint and carbon footprint intensity: Embodying carbon sink effect

Due to the combined effects of carbon emission and carbon sink, agriculture is acknowledged as an essential contributor to achieve the Chinese government's carbon neutrality goal of 2060, and carbon footprint (CF) and carbon footprint intensity are substantial indicators to reveal the carbon emission level. For these reasons, the Theil index technique and extended STIRPAT model were employed to evaluate their spatiotemporal heterogeneity and influencing factors using panel data from 31 provinces for the period 1997–2019. The findings revealed that the CF showed an increasing trend with an annual growth rate of 24.6 %. The carbon footprint intensity (CFI) indicated an evident spatiotemporal heterogeneity and transferred over time, with an average growth rate of 19.82 %. The CFI Theil index and its contribution rate both confirmed that intra-regional difference is the main source of the overall difference, among which, the CFI Theil index displayed the distribution feature of “western (11.50 %) > central (11.12 %) > eastern (10.56 %) > northeast (6.61 %). The contribution rate of CFI illustrated the spatial pattern of “eastern (33.74 %) > central (21.07 %) > western (19.87 %) > northeast (5.24 %). Furthermore, the influencing effects of GDP per capita, planting structure, population density and urbanization level on CF and CFI also demonstrate evident spatiotemporal heterogeneity. [Display omitted] •Carbon sink is considered into the CF and CFI accounting system.•Theil index method and STIRPAT model are applied to conduct empirical analysis.•CF increased 24.6 % per year and demonstrates “central > northeast > eastern > western”.•CFI presented a spatiotemporal heterogeneity with an average growth rate of 19.82 %.•The influencing effect of CF and CFI indicates obvious spatiotemporal heterogeneity.