Cost-Effectiveness of Agricultural Carbon Reduction in China

Kai Tang*, Dong Wang

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    2 Citations (Scopus)

    Abstract

    Agriculture accounts for approximately 15% of China’s total greenhouse gas emissions, 90% of N2O emissions, and 60% of CH4 emissions. As such, agriculture is expected to make a great contribution to China’s carbon–neutral progress. This chapter conducts a whole-farm bioeconomic analysis to investigate the variations in enterprises, on-farm GHG emissions, and marginal abatement costs with various levels of market-based incentives. The analysis includes livestock enterprise and focuses on cropping-livestock mixed farming. The results imply that high emission tax rate induces crop-dominating enterprises in the mixed farming. More dry-pea-included rotations are chosen in the optimized enterprise mix. In addition, moderate emission tax rates are expected to result in considerable cuts in on-farm emissions and the accompanied loss of net gross margin may be small. The marginal abatement costs of 8, 17 and 30% emissions could be less than ¥50/tCO2e,¥100/tCO2e and ¥150/tCO2e, respectively. The analysis indicates that reducing agricultural carbon emissions are cost-effective in China. Considerable reduction might be achieved in agriculture if it could be provided incentives at similar market levels. The estimated results may shed new light on the implications of China’s agricultural reduction practices and policies.

    Original languageEnglish
    Title of host publicationCarbon-Neutral Pathways for China
    Subtitle of host publicationEconomic Issues
    PublisherSpringer Singapore
    Pages81-94
    Number of pages14
    ISBN (Electronic)9789811955624
    ISBN (Print)9789811955617
    DOIs
    Publication statusPublished - 1 Jan 2022

    Fingerprint

    Dive into the research topics of 'Cost-Effectiveness of Agricultural Carbon Reduction in China'. Together they form a unique fingerprint.

    Cite this