Reducing the carbon footprint per unit of economic benefit is a new method to accomplish low-carbon agriculture. A case study: adjustment of the planting structure in Zhangbei County, China.

Zhanbiao Wang,Jizong Zhang,Li-Feng Zhang

Published 2019 in The Journal of the Science of Food and Agriculture

ABSTRACT

BACKGROUND The development of low-carbon agriculture is promising for mitigating climate change. This study used adjustments to the planting structure in Zhangbei County, China, as an example to evaluate whether the carbon footprint per unit of economic benefit is a suitable indicator of low-carbon agriculture and to determine if low-carbon agriculture is not necessarily low-input non-intensive agriculture. RESULTS The results showed that total greenhouse gas emissions increased; therefore, the adjustments to the planting structure were ostensibly not a low-carbon process. However, if we obtain the same economic benefit as the actual distribution of the planting industry by adopting the scenario of planting only grain crops, then the annual greenhouse gas emissions would be 1608.00 × 103  t CO2 eq, and 5769.94 × 103  ha of farmland would be required. However, if we adopt the scenario of planting only vegetable crops, then only 82.52 × 103  ha of farmland would be required, and the annual greenhouse gas emissions would be 323.52 × 103  t CO2 eq. CONCLUSIONS These results indicated that the carbon footprint per unit of economic benefit is a suitable indicator to assess agricultural sustainability and that intensive agriculture with high input and high output is a form of low-carbon agriculture if the carbon footprint per unit of economic benefit is low. © 2019 Society of Chemical Industry.

PUBLICATION RECORD

  • Publication year

    2019

  • Venue

    The Journal of the Science of Food and Agriculture

  • Publication date

    2019-08-30

  • Fields of study

    Agricultural and Food Sciences, Chemistry, Economics, Environmental Science, Medicine

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar, PubMed

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