Journal
ECOLOGICAL INDICATORS
Volume 99, Issue -, Pages 214-224Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolind.2018.12.019
Keywords
Urban metabolism; Material flow analysis; Network analysis; Relationship analysis; Beijing
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Funding
- Fund for Innovative Research Group of the National Natural Science Foundation of China [51721093]
- National Key Research and Development Program of China [2016YFC0503005]
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Massive consumption of resources and energy during urban development has put great pressure on the environment. To understand the urban metabolic processes that create this pressure and to identify the relationships among components of this metabolism are the keys to promoting sustainable urban development. In this study, we adopted the perspective of urban metabolism to analyze material flows, quantify changes in the total direct flows of these materials, and describe the metabolic structure of Beijing since 2000. We developed an eight-component metabolic network model to identify key metabolic entities and their relationships. We found that the total amount and structure of Beijing's metabolism changed, revealing different stages of development. Direct material inputs and consumption were mainly driven by non-metallic minerals (about 43% of the total) and industrial products (about 28%), whereas direct material outputs were mainly affected by industrial products (more than 30%) and solid waste (more than 20%), mainly due to contributions from the environment and from the mining, industry, recycling, and construction components. The network's indirect utility (resulting from flows between components that pass through one or more intermediate components) accounted for more than 70% of the total flows, and was significantly higher than the direct utility. Exploitation and control relationships (about 57.1% of the total relationships) were the dominant type. The key metabolic roles of the environment, recycling, agriculture, industry, and household consumption components were highlighted. The future policy regulation targeting above sectors can help optimize the metabolic processes to improved urban resource efficiency. These insights reveal how metabolic problems can be detected, thereby allowing managers to choose appropriate regulation and control mechanisms and helping to improve decision-making related to urban ecological management.
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