Carbon footprint assessment for the waste management sector: A comparative analysis of China and Japan

Abstract

Waste management is becoming a crucial issue in modern society owing to rapid urbanization and the increasing generation of municipal solid waste (MSW). This paper evaluates the carbon footprint of the waste management sector to identify direct and indirect carbon emissions, waste recycling carbon emission using a hybrid life cycle assessment and input-output analysis. China and Japan was selected as case study areas to highlight the effects of different industries on waste management. The results show that the life cycle carbon footprints for waste treatment are 59.01 million tons in China and 7.01 million tons in Japan. The gap between these footprints is caused by the different waste management systems and treatment processes used in the two countries. For indirect carbon footprints, China’s material carbon footprint and depreciation carbon footprint are much higher than those of Japan, whereas the purchased electricity and heat carbon footprint in China is half that of Japan. China and Japan have similar direct energy consumption carbon footprints. However, CO₂ emissions from MSW treatment processes in China (46.46 million tons) is significantly higher than that in Japan (2.72 million tons). The corresponding effects of waste recycling on CO₂ emission reductions are considerable, up to 181.37 million tons for China and 96.76 million tons for Japan. Besides, measures were further proposed for optimizing waste management systems in the two countries. In addition, it is argued that the advanced experience that developed countries have in waste management issues can provide scientific support for waste treatment in developing countries such as China.

Key words： waste management; waste recycling; carbon footprint; hybrid LCA

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 71461137008, 71325006, and 71311140172), the Environment Research and Technology Development Fund (3K1709 and 3K163001) and Key Technology of IOT Big Data Platform for the Periodic Renting Electric Vehicles (No.16511105204).

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