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Material Flows Embodied in China–Japan Trade

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Application of Intelligent Systems in Multi-modal Information Analytics (MMIA 2019)

Abstract

China–Japan trade has developed rapidly over the past four decades. Studying the hidden environmental impact of China–Japan trade can help policy makers identify which categories of import and export commodities exert major impacts on the country’s environment. In this paper, we use material flow analysis and hidden flow analysis to identify products with the largest material flows, hidden flows, and value flows in China–Japan trade between 1993 and 2015. We summarize the analysis results of five major types of materials. During this 23-year period, the total volume of material flows exported by China changed little from 33.0 GT to 32.7 GT, a decline of 0.96%. The total volume of imported material flows increased substantially from 12.5 GT to 24.9 GT, a surge of 98.74%. The total volume of hidden flows imported by China also grew dramatically from 44.7 GT to 123.2 GT, an increase of 175.32%. The total volume of exported hidden flows increased from 34.3 GT to 74.6 GT, a 116.97% jump. The largest proportion of material flow export product from China was coal, including bitumen; the largest proportion of material flow export products from Japan were iron filings and iron-containing scrap; the largest proportion of hidden flow import products from China were precious metals; and the largest proportion of hidden flow import products from Japan were iron alloys.

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Acknowledgements

This research was supported by College Students’ Innovation and Entrepreneurship Project of Northeastern University of China (180081), National Natural Science Foundation of China (41871204, 41401636, and 71403175) and Fundamental Research Funds for the Central Universities (N172504026).

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Correspondence to Heming Wang .

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Wang, H., Zhao, X., Zhang, Z., Li, S., Yuan, J. (2019). Material Flows Embodied in China–Japan Trade. In: Sugumaran, V., Xu, Z., P., S., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2019. Advances in Intelligent Systems and Computing, vol 929. Springer, Cham. https://doi.org/10.1007/978-3-030-15740-1_49

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