Evaluation of Green and Low-Carbon Development Level of Chinese Provinces Based on Sustainable Development Goals

Abstract

Green and low-carbon development are important initiatives to promote the realization of the Sustainable Development Goals (SDGs). In this study, a systematic evaluation method for regional green and low-carbon development levels was established by referring to the evaluation methods of other literature. The evaluation method includes assessing the overall green and low-carbon development levels of the evaluation objects, as well as analyzing the coupling coordination of the two subsystems of green development and low-carbon development. The results show that China’s green low-carbon development level shows a rising trend year by year from 2012 to 2021, but there is still much space for progress. As for 2021, 2 provinces are in the Fair stage, 25 provinces are in the Accepted stage, and 4 provinces are in the Good stage. Provinces with higher levels of green and low-carbon development are characterized by spatial clustering, and the level of green and low-carbon development in the southeast coastal provinces is significantly higher than that in the northwest inland provinces. This study measures the coupling coordination degree of the two subsystems of green development and low-carbon development in each province. The average coupling coordination degree of China’s green and low-carbon development shows a rising trend year by year from 2012 to 2021. By 2021, the coupling coordination degree of China’s 29 provinces belongs to the High level type, and only two provinces belong to the Low level type. This study provides a provincial map of China’s green and low-carbon development levels and a distribution map of the coupling coordination degree of the green and low-carbon development subsystems, which provides support for an in-depth understanding of the spatial–temporal distribution of and development trends in China’s green and low-carbon development level. This study provides support for a deeper understanding of the spatial and temporal distribution and development trend of China’s green and low-carbon development level. The study also provides data to support China’s efforts to promote synergies in reducing pollution and carbon emissions.

Temporal and Spatial Evolution Characteristics and Influencing Factors Analysis of Green Production in China’s Dairy Industry: Based on the Perspective of Green Total Factor Productivity

“…This article takes 29 provinces in China (excluding Hainan, Jiangxi, Hong Kong, Macao, and Taiwan due to incomplete data) as the research objects and calculates the total factor productivity of the dairy industry under the environmental constraints of carbon emissions and pollutant emissions, namely the green total factor productivity of the dairy industry. Using methods such as Kernel density estimation and Dagum Gini coefficient, the article systematically analyzes the growth trend and regional differences in China's green total factor productivity of the dairy industry to study the level of green production in China's dairy industry, and analyzes its influencing factors through a two-way fixed-effects model [7].…”