Spatio-Temporal Distribution and Spatial Spillover Effects of Net Carbon Emissions: A Case Study of Shaanxi Province, China

Scientifically evaluating net carbon dioxide (CO2) emissions is the pivotal strategy for mitigating global climate change and fostering sustainable urban development. Shaanxi Province is situated in central China, and boasts robust energy resources in the north and a significant carbon-sink zone in the southern Qinling Mountains. Therefore, uncovering the spatial distributions of net CO2 emissions and identifying its influencing factors across cities in Shaanxi Province would furnish a crucial theoretical foundation for advancing low-carbon development strategies. In this research, the net CO2 emissions of cities in Shaanxi Province from 2005 to 2020 are calculated using the carbon-emission-factor calculation model, then the Geodetector is utilized to evaluate the single-factor explanatory power and two-factor interactions among the fourteen various influencing variables, and then the spatial econometric model is employed to analyze the spatial spillover effects of these key factors. The results show the following: (1) The net CO2 emissions present significant regional differences among the ten cities of Shaanxi Province, notably Xi'an City, Yulin City, and Weinan City, which have recorded remarkable contributions with the respective totals reaching 72.2593 million tons, 76.3031 million tons, and 58.1646 million tons. (2) Regarding temporal trend changes, the aggregate net CO2 emissions across whole province underwent a marked expansion from 2005 to 2019. Yulin City and Shangluo City exhibit remarkable surges, with respective average annual growth rates soaring at 7.38% and 7.39%. (3) From the perspective of influencing factors, GDP exhibits the most pronounced correlation spanning the entire province. Meanwhile, foreign investment emerges as a significant contributor specifically in Xi'an and Yulin City. Moreover, interaction detection reveals most factor combinations exhibit bi-enhancement, while a few exhibits intricate and non-linear enhancement. (4) The SDM regression and fixed-effect analysis reveal that city GDP had a positive spillover effect on neighboring cities' net CO2 emission, while investment in scientific research and technology services, along with per capita construction land, exhibit notable negative spillovers, suggesting potential emission reduction benefits across cities.