The optimization degree of provincial industrial ecosystem and EKC of China —based on the grey correlation analysis

In this paper, we will expand the industrial ecosystem to three subsystems: the economy subsystem, the environment subsystem, and the innovation subsystem. Based on principal component analysis and grey correlation analysis, a model of the optimizing degree of Chinese economic industrial ecosystem is developed at the provincial level, and a mathematical definition of the optimization degree is provided to evaluate the provincial industrial ecosystem from a relatively new perspective. Based on their optimization degrees, the thirty provinces of China are classified into four categories in terms of their economy-environment-innovation relation: the harmonious region, the gearing region, the rivaling region and the discordant region. By fitting the curve of Environment Kuznets Curve (EKC) with a cubic function for each category, we show that each category has its own shape of EKC: category I has the monotonically decreasing curve, category II has a inverted U shaped curve, category III has a N-shaped curve, while category IV has a U-shaped curve. Our results show how the category's optimization degree of industrial ecosystem affects the relation of economic growth to environmental quality. In particular, for the region I whose optimization degree γ>0.7, the relation between economic growth and environmental pollutants is harmonious; for the region II whose optimization degree 0.6<γ<0.7, the relation is rivaling; for the region III whose optimization degree 0.5<γ<0.6, the relation is conflicting; and for the region IV whose optimization degree γ<0.5, the relation is discordant.