China's CO2 emission intensity and its drivers: An evolutionary Geo-Tree approach

Abstract Current studies have focused on China's CO2 emission intensity (CEI); however, its geospatial temporal effect is still not clear. Here, we constructed an evolutionary Geo-tree model in combination with spatial econometrics to examine geospatial temporal processes affecting CEI. The Geo-tree provides a schema to geovisualize the effects of CEI's drivers from 1990 to 2016. Spatial econometric outputs indicate that affluence or economic development as well as low-carbon technology has significant inhibitory effects on CEI. Furthermore, the direct inhibitory effect of affluence strengthened over time. In contrast, energy consumption structure and innovation represented by patent raise CEI. While the positive effect decreased over time for energy consumption as coal consumption fell, it remained relatively stable for patent level. Urbanization level as well as industrial development are also positive but not significant in 2006–2016. When the spatial model analysis is combined with the evolutionary Geo-tree, the geovisualization model depicts a taller green tree over time with denser foliage at the crown. As the spatial econometrics results suggest, such evolution towards a lower carbon economy among a number of provinces is likely explained by affluence and, to a lesser extent, the adoption of low-carbon technology. Geo-tree also shows that many provinces are relatively urbanized by 2016 which explains why this factor has no effect in the second period.