The Tapio Decoupling Principle and Key Strategies for Changing Factors of Chinese Urban Carbon Footprint Based on Cloud Computing

Bibliographic Data

ID15468493
AuthorsMin Shang (0000-0001-5176-5394, Yuxi Normal University), Ji Luo (0000-0001-9194-7723, Tsinghua University, corresponding author)
Year2021
Volume18
Issue4
Pages2101-2101
Publication date2021-02-21
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph18042101
PMID33670040
OpenAlexW3132747404
LanguageEN
Citations received16
References cited32

The expansion of Xi'an City has caused the consumption of energy and land resources, leading to serious environmental pollution problems. For this purpose, this study was carried out to measure the carbon carrying capacity, net carbon footprint and net carbon footprint pressure index of Xi'an City, and to characterize the carbon sequestration capacity of Xi'an ecosystem, thereby laying a foundation for developing comprehensive and reasonable low-carbon development measures. This study expects to provide a reference for China to develop a low-carbon economy through Tapio decoupling principle. The decoupling relationship between CO 2 and driving factors was explored through Tapio decoupling model. The time-series data was used to calculate the carbon footprint. The auto-encoder in deep learning technology was combined with the parallel algorithm in cloud computing. A general multilayer perceptron neural network realized by a parallel BP learning algorithm was proposed based on Map-Reduce on a cloud computing cluster. A partial least squares (PLS) regression model was constructed to analyze driving factors. The results show that in terms of city size, the variable importance in projection (VIP) output of the urbanization rate has a strong inhibitory effect on carbon footprint growth, and the VIP value of permanent population ranks the last; in terms of economic development, the impact of fixed asset investment and added value of the secondary industry on carbon footprint ranks third and fourth. As a result, the marginal effect of carbon footprint is greater than that of economic growth after economic growth reaches a certain stage, revealing that the driving forces and mechanisms can promote the growth of urban space

Carbon Footprint · China · Cloud computing · Driving factors · Econometrics · Economic growth · Economics · Environmental economics · Geography · Greenhouse gas · Natural resource economics · Population · Urbanization · Computer Science · Energy, Environment, Economic Growth · Environmental Impact and Sustainability · Environmental Science · Urban Transport and Accessibility · Ecology

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