Efficiency evaluation for urban industrial metabolism through the methodologies of emergy analysis and dynamic network stochastic block model

Frequent economic activities in cities have exacerbated irreversible environmental degradation. It is urgent to balance the relationship between economic growth, resource investment and environmental protection. With the concept of urban metabolism, this study attempts to clarify the internal structure of urban system metabolism and the metabolic relationship between specific economic sectors. And then, it determines the metabolic level of current urban industrial development by means of metabolic efficiency evaluation, which can help more accu-rately reveal the sustainability of urban metabolic activities. Based on them, this study proposes a metabolic efficiency evaluation model combined with emergy analysis and slack-based measure dynamic network Data Envelopment Analysis (DEA). Through the multi-period and multi-stage network DEA model, the internal structure of urban industrial metabolism is opened. And considerring industrial waste as an undesirable carry-over will be regarded as additional inputs in future period to reflect the impact on industrial metabolic efficiency. Using the proposed model, the industrial metabolic efficiency of 18 first-tier cities in China from 2016 to 2020 was analyzed. It is found that all cities are inefficient, which indicates that all evaluated cities need to make appropriate adjustments to improve their weak stages. In response to the specific problems of inefficiency in each city, an improvement framework is proposed to help each city better realize the sustainable development of the urban economy.

Automated summary

Frequent economic activities in cities have worsened irreversible environmental degradation. It is urgent to find a balance between economic growth, resource investment, and environmental protection. This study proposes a metabolic efficiency evaluation model that combines emergy analysis and a dynamic network Data Envelopment Analysis (DEA) to assess the sustainability of urban metabolic activities. The results show that all evaluated cities in China from 2016 to 2020 are inefficient and need to make appropriate adjustments to improve weak stages. An improvement framework is proposed to help each city achieve sustainable development of the urban economy.