Efficiency evaluation for urban industrial metabolism through the methodologies of emergy analysis and dynamic network stochastic block model. (March 2023)

• Record Type: Journal Article
• Authors: Gan, Lu; Wan, Xue; Ma, Yanfang; Lev, Benjamin
• Is Part Of: Sustainable cities and society. Volume 90(2023)
• Publication Date: 2023-03
• Subjects: Urban industrial metabolism -- Dynamic network DEA -- Environmental carryover -- Undesirable carryover -- Industrial development; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2023.104396
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: The internal structure and metabolic relationship of urban metabolism is reveals. The impact of environmental pollutants on efficiency in future periods is considered. Combine emergy analysis and dynamic network DEA to complete efficiency evaluation. There is obvious heterogeneity in metabolic efficiency of China's 18 first-tier cities. Propose a renewal framework to improve the sustainability of urban development. Abstract: 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 accurately 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 carryover 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.