Emergy-based comparative analysis of urban metabolic efficiency and sustainability in the case of big and data scarce medium-sized cities: A case study for Jing-Jin-Ji region (China)

Abstract

Abstract Emergy-based Urban Sustainability Assessment Framework (EmUSAF) is an effective and widely advocated method to evaluate the general condition at city-scale. However, applying this framework to medium-sized cities has encountered obstacles owing to the data scarcity and inconsistency problem. One the one hand, a range of data such as detailed import-export goods data are only compiled at provincial level therefore for prefectural cities the lack of data is very common. On the other hand, the original environmental data provided by local government is usually not uniform and well-formatted, meaning that the data inventory disclosed by the environmental data compilation administration in different cities are not identical, leading to the difficulty of comparison. Meanwhile, for a given year, not all elements needed in the emergy synthesis inventory are available due to the difference compilation and disclosure timelines of different statistics reports. These facts hinder both city-specific research at local scale and regional research. To address this lingering issue, we developed a methodology for deriving substitute data from extant available data of upper-level administration division and for integrating them into the EUSAF. With a case study on Jing-Jin-Ji region, covering 11 medium-sized prefecture cities, we conducted an emergy analysis of the whole region and examined the methodology discussing its uncertainties and limitations. This study contributes to emergy synthesis in four aspects: (1) Provide a solution to the enduring data scarcity and inconsistency problem of emergy-based urban sustainability assessment; (2) Establish the deduction method which can deduce data at larger scale to smaller scale when lacking physical data at smaller scale instead of using monetary estimates, and also the accuracy of the deduced data can be identified by using uncertainty analysis; (3) Investigate the strategically essential Jing-Jin-Ji region as a case, applying the new approach to get the data for prefectural cities and carrying out an emergy analysis. We found that the indicators, reflecting the specific development traits of each city, are well confirmed by the status quo in the region. This fact proves that our new method framework is affordable and could be extended in the future study of medium-sized cities suffering from data scarcity. (4) Demonstrate the significant gap between using money value and physical amount to calculate emergy of imported goods, proving the importance of physical amount data in the Emergy-based comparative analysis of urban metabolic efficiency and sustainability.