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Published August 2022 | public
Journal Article

Quantitative analysis of CO₂ uptake by alkaline solid wastes in China

Abstract

About two-thirds of global CO₂ emissions from the energy and industry sectors are generated in China, accounting for approximately 30% of total global CO₂ emissions. These carbon-intensive processes usually produce a large amount of so-called alkaline solid wastes e.g. blast furnace slag (BFS), which have shown great potential to serve as CO₂ absorbers. In this regard, the climate impacts of these human activities should be re-evaluated by considering the carbon offsetting effects. While recent studies have been focusing on accelerated carbonation of such 'waste' from a technical perspective, the natural carbonation of these solid residues has not been comprehensively investigated. In this research, combining experimental data, we established an analytical carbon sink accounting model to estimate the CO₂ uptake of 7 types of alkaline solid wastes produced in China between 1930 and 2020 using material flow analysis (MFA), life-cycle assessment (LCA), and Monte Carlo methods. The results show that China's alkaline solid wastes from the identified industrial and agroforestry processes in 2020 absorbed 64.27 Mt CO₂ (35.91–111.01, 95% CI), offsetting 2.2% of the CO₂ emissions from Chinese industrial production. Cumulatively, 1099.51 Mt CO₂ had been sequestered by natural carbonation, since 1930. The majority of CO₂ uptake is attributed to coal combustion ash (CCA) and biomass ash (BA), which accounted for 35.9% and 26.3% of the total uptake combined respectively. All types of solid wastes exhibited rapidly increasing sequestration from 1930 to 2020 apart from yellow phosphorous slag (YPS) and oil shale ash (OSA), with substantial interannual variability. Our results indicate that the natural carbonation of such 'waste' can reduce the carbon footprint of the corresponding industrial and agroforestry processes, and make the case for further research of their full potential.

Additional Information

This research has been supported by the National Natural Science Foundation of China (No. 41977290, No. 71874097, and No. 41921005); the CAS President's International Fellowship Initiative (2017VCB0004); Youth Innovation Promotion Association, Chinese Academy of Sciences (grant nos. 2020201 and Y202050); the Beijing Municipal Natural Science Foundation (No. JQ19032); the Liaoning Xingliao Talents Project (No. XLYC1907148); and the Natural Science Foundation of Liaoning Province (2021-MS-025).

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023