Skip to main content

Advertisement

SpringerLink
Log in

Selecting low-carbon technologies and measures for high agricultural carbon productivity in Taihu Lake Basin, China

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

In this paper, Delphi method was used to evaluate the low-carbon technologies and measures for high agricultural carbon productivity in Taihu Lake Basin. We established the selecting process and standards and obtained the final list of low-carbon technologies and management measures of high agricultural carbon productivity in Taihu Lake Basin: (1) the initial list of low-carbon technologies and measures of planting industry included 19 items, of which 10 items were included in the final list. The 10 technologies and measures included in the final list were reducing fertilizers, mixed use of organic fertilizer and chemical fertilizer, soil testing and formulated fertilization, application of controlled release fertilizer, deep application of fertilizers, cultivation of new variety, extension of conservation tillage, extension of midseason/alternate drainage, paddy-upland rotation (rice-rape/rice-wheat), and reducing pesticides. (2) The initial list of low-carbon technologies and measures of animal husbandry included 11 items, of which 4 items were included in the final list. The 4 technologies and measures included in the final list were reasonable ratio of concentrate to roughage in ration, treatment straw feed by silage/ammoniation/shredding, application of nutritive cube/dietary additives, and promotion of high productivity livestock breeds. (3) Low-carbon agricultural technologies and management measures need to be adapted to local conditions according to different geographical, climatic, and socio-economic development characteristics, and it is necessary to form a regionally differentiated system of low-carbon agricultural technologies and management measures. The final list of low-carbon technologies and management measures of high agricultural carbon productivity can provide decision-making reference for the formulation of agricultural carbon emission reduction technology system and low-carbon agricultural development planning of provinces and cities in Taihu Lake Basin. At the same time, the final list can be considered a priority for the promotion of agricultural low-carbon technologies and measures in China and even in the world.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Data availability

Not applicable.

References

  • Arunrat N, Wang C, Pumijumnong N, Sereenonchai S, Cai W (2017) Farmers’ intention and decision to adapt to climate change: a case study in the Yom and Nan basins, Phichit province of Thailand. J Clean Prod 143:672–685

    Article  Google Scholar 

  • Burney JA, Davis J, Lobell DB (2010) Greenhouse gas mitigation by agricultural intensification. PNAS 7(26):12052–12057

    Article  Google Scholar 

  • Cai Z, Tsuruta H, Gao M, Xu H, Wei C (2003) Options for mitigating methane emission from a permanently flooded rice field. Glob Chang Biol 9(1):37–45

    Article  Google Scholar 

  • Carlson KM, Gerber JS, Mueller ND, Herrero M, Macdonald GK, Brauman KA et al (2017) Greenhouse gas emissions intensity of global croplands. Nat Clim Chang 7:63–68

    Article  CAS  Google Scholar 

  • Charkovska N, Horabik-Pyzel J, Bun R, Danylo O, Nahorski Z, Jonas M, Xiangyang X (2019) High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector. Mitig Adapt Strateg Glob Chang 24(6):881–905

    Article  Google Scholar 

  • Clark MA, Domingo NGG, Colgan K, Thakrar SK, Tilman D, Lynch J, Azevedo IL, Hill JD (2020) Global food system emissions could preclude achieving the 1.5 and 2°Cclimate change targets. Science 370:705–708

    Article  CAS  Google Scholar 

  • Dong HM, Li YE, Tao XP, Peng XP, Li N, Zhu ZP (2008) China greenhouse gas emissions from agricultural activities and its mitigation strategy. Transactions of the CSAE 24(10):269–273 (In Chinese)

    Google Scholar 

  • FAO (2016) The State of Food and Agriculture Climate Change, Agriculture and Food Security. Rome, Italy, 15-16.

  • Gilbert E, Metealf JMR (2008) Policy options for controlling greenhouse gas emissions: implications for agriculture. Choices l:34–37

  • IPCC (2014) In: Core Writing Team, Pachauri, R.K., Meyer, L.A. (Eds.), Climate Change2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland.

  • Izaurralde RC, McGill WB, Robertson JA, Juma NG, Thurston JJ (2001) Carbon balance of the Breton classical plots over half a century. Soil Sci Soc Am J 65(2):431–441

    Article  CAS  Google Scholar 

  • Kragt ME, Pannell DJ, Robertson MJ, Thamo T (2012) Assessing costs of soil carbon sequestration by crop-livestock farmers in Westerm Australia. Agric Syst 112:27–37

    Article  Google Scholar 

  • Lal R (2004) Carbon emission from farm operations. Environ Int 30:981–990

    Article  CAS  Google Scholar 

  • Linstone H A, Turoff M (2002) The Delphi method: techniques and applications. New York: Olaf Helmer Press.

  • Mariano MJ, Mariano R, Fleming E (2012) Factors influencing farmers’ adoption of modern rice technologies and good management practices in the Philippines. Agric Syst 110:41–53

    Article  Google Scholar 

  • Mi S (2013) Study on China’s low carbon modern agriculture development. Hangzhou: Zhejiang University. (In Chinese)

  • NOAA (2015) Featuring NOAA-ESRL data of May, 5, 2015. http://co2now.org/.

  • Pimentel D, Hepperly P, Hanson J (2005) Environmental, energetic and economic comparison of organic and conventional farming system. Bioscience 55(7):573–582

    Article  Google Scholar 

  • Springmann M, Clark M, Mason-D’Croz D, Wiebe K, Bodirsky BL, Lassaletta L, de Vries W, Vermeulen SJ, Herrero M, Carlson KM, Jonell M, Troell M, DeClerck F, Gordon LJ, Zurayk R, Scarborough P, Rayner M, Loken B, Fanzo J, Godfray HCJ, Tilman D, Rockström J, Willett W (2018) Options for keeping the food system within environmental limits. Nature 562:519–525

    Article  CAS  Google Scholar 

  • Steenbli R, Moise E (2010) Counting the carbon emissions from agricultural products: technical complexities and trade implications [R]. [2010-03-04].

  • Su W, Gu C, Yang G, Chen S, Zhen F (2010) Measuring the impact of urban sprawl on natural landscape pattern of the Western Taihu Lake watershed, China. Landsc Urban Plan 95(1):61–67

    Article  Google Scholar 

  • Tian Y, Zhang JB (2013) Fairness research of agricultural carbon emissions between provincial regions in China. J Arid Land Resour Environ 23:36–44 (In Chinese)

    Google Scholar 

  • Tian Y, Zhang JB, He YY (2014) Research on spatial-temporal characteristics and driving factor of agricultural carbon emissions in China. J Integr Agric 13(6):1393–1403

    Article  Google Scholar 

  • Tubiello FN, Salvatore M, Ferrara AF, House J, Federici S, Rossi S, Biancalani R et al (2015) The contribution of agriculture, forestry and other land use activities to global warming, 1990–2012. Glob Chang Biol 21:2655–2660

    Article  Google Scholar 

  • USEPA (2019) Global anthropogenic non-CO2 greenhouse gas emissions: 1990–2030. Washington (DC): United States Environmental Protection Agency, (No. 430-R-12-006); [cited 2019 Oct].

  • West TO, Post WM (2002) Soil organic carbon sequestration rates by tillage and crop rotation: a global data analysis. Soil Sci Soc Am J 66(6):1930–1946

    Article  CAS  Google Scholar 

  • Wu XR, Zhang JB, Kulatunga AK, Tian Y (2014) Provincial agricultural carbon emissions in China: Calculation, efficiency change and convergence test. J Food Agric Environ 12(2):503–508

    Google Scholar 

  • Xiong C, Yang D, Xia F, Huo J (2016a) Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China. Sci Rep 6:36912

    Article  CAS  Google Scholar 

  • Xiong C, Yang D, Huo J (2016b) Spatial-temporal characteristics and LMDI-based impact factor decomposition of agricultural carbon emissions in Hotan Prefecture, China. Sustainability 8(3):262

    Article  Google Scholar 

  • Xiong C, Chen S, Yang D (2019) Selecting counties to participate in agricultural carbon compensation in china. Pol J Environ Stud 28(3):1443–1449

    Article  Google Scholar 

  • Xiong C, Chen S, Xu L (2020) Driving factors analysis of agricultural carbon emissions based on extended STIRPAT model of Jiangsu province, China. Growth Chang 51:1401–1416

    Article  Google Scholar 

  • Zhang L, Cai Z, Niu L (2010) Low carbon economy and rural development in China. Ecol Econ 9:73–76

    Google Scholar 

  • Zhao Q, Qian H (2009) Low carbon economy and thinking of agricultural development. Ecol Environ Sci 18:1609–1614 (In Chinese)

    Google Scholar 

  • Zou X, Li Y, Gao Q et al (2011) How to reduce greenhouse gas (GHG) emissions in agriculture: An analysis of measures and actions taken in China. Ecol Environ Sci 20(8-9):1348–1358 (In Chinese)

    Google Scholar 

Download references

Acknowledgements

I am very grateful to the editors and anonymous reviews for reviewing this paper.

Funding

This work was supported by the Jiangsu Natural Science Foundation (BK20181105).

Author information

Authors and Affiliations

  1. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography & Limnology, Chinese Academy of Sciences, Nanjing, 210008, China

    Chuanhe Xiong, Weizhong Su & Qun Gao

  2. School of Geographic Science, Nantong University, Nantong, 226007, China

    Guiling Wang

Authors
  1. Chuanhe Xiong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guiling Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weizhong Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qun Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Chuanhe Xiong: data curation, methodology, writing–original draft. Guiling Wang: visualization. Weizhong Su: writing–review and editing. Qun Gao: editing.

Corresponding author

Correspondence to Chuanhe Xiong.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent to publish

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Philippe Garrigues

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xiong, C., Wang, G., Su, W. et al. Selecting low-carbon technologies and measures for high agricultural carbon productivity in Taihu Lake Basin, China . Environ Sci Pollut Res 28, 49913–49920 (2021). https://doi.org/10.1007/s11356-021-14272-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-021-14272-z

Keywords

Search

Navigation