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Spatial-Temporal Characteristics and LMDI-Based Impact Factor Decomposition of Agricultural Carbon Emissions in Hotan Prefecture, China

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  • Chuanhe Xiong

    (Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Degang Yang

    (Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Jinwei Huo

    (Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

Abstract

Greenhouse gas emissions from the agricultural ecosystem account for 7%–20% of the world’s total greenhouse gas emissions, while approximately 17% of China’s carbon emissions are from agriculture. In this study, based on the scientific calculation system of carbon emissions in agriculture, we calculated the carbon emissions of agriculture in the Hotan prefecture between 1999 and 2013 and analyzed their spatial-temporal characteristics; next, we used the LMDI model to study the driving factors of agricultural carbon emissions. The results demonstrated the following: (1) in time series, the agricultural carbon emissions showed three stages of change, i.e. , “decline, continued to rise and decline”, during the period of 1999 to 2013 in the Hotan prefecture; (2) In space, the carbon emissions from agricultural land use, paddy fields, enteric fermentation, and manure management were different due to the different sizes of cities and counties. The intensity of agricultural carbon emissions was varied and high, but the agricultural production structure, agricultural carbon emissions structure and other aspects had a high degree of consistency and homogeneity in the cities and counties of the Hotan prefecture; (3) Regarding the driving mechanism, the labor factor, agricultural labor productivity, and planting-animal husbandry carbon intensity are the main factors that increase agricultural carbon emissions in the Hotan prefecture. Compared with 1999, three major factors cumulatively achieved a 199.68% carbon emission increment from 2000 to 2013, of which the labor factor cumulatively increased by 120.04%, the agricultural labor productivity factor cumulatively increased by 54.94% and the planting-animal husbandry carbon intensity factor cumulatively increased by 24.70%. The agricultural production structure factor largely inhibited agricultural carbon emissions of the Hotan prefecture, which cut 99.74% of the carbon emissions from 2000 to 2013. Finally, we proposed policy recommendations, including the acceleration of labor transfer, the innovation and promotion of science and technology, the scientific breeding and rational disposal of livestock waste, and the adjustment and optimization of the agricultural industry structure.

Suggested Citation

  • Chuanhe Xiong & Degang Yang & Jinwei Huo, 2016. "Spatial-Temporal Characteristics and LMDI-Based Impact Factor Decomposition of Agricultural Carbon Emissions in Hotan Prefecture, China," Sustainability, MDPI, vol. 8(3), pages 1-14, March.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:3:p:262-:d:65480
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    1. Kragt, Marit E. & Pannell, David J. & Robertson, Michael J. & Thamo, Tas, 2012. "Assessing costs of soil carbon sequestration by crop-livestock farmers in Western Australia," Agricultural Systems, Elsevier, vol. 112(C), pages 27-37.
    2. Liu, Lan-Cui & Fan, Ying & Wu, Gang & Wei, Yi-Ming, 2007. "Using LMDI method to analyze the change of China's industrial CO2 emissions from final fuel use: An empirical analysis," Energy Policy, Elsevier, vol. 35(11), pages 5892-5900, November.
    3. Bruce A. McCarl & Uwe A. Schneider, 2000. "U.S. Agriculture's Role in a Greenhouse Gas Emission Mitigation World: An Economic Perspective," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 22(1), pages 134-159.
    4. Duro, Juan Antonio & Padilla, Emilio, 2006. "International inequalities in per capita CO2 emissions: A decomposition methodology by Kaya factors," Energy Economics, Elsevier, vol. 28(2), pages 170-187, March.
    5. Zaman, Khalid & Khan, Muhammad Mushtaq & Ahmad, Mehboob & Khilji, Bashir Ahmad, 2012. "The relationship between agricultural technologies and carbon emissions in Pakistan: Peril and promise," Economic Modelling, Elsevier, vol. 29(5), pages 1632-1639.
    6. Duro, Juan Antonio, 2013. "Weighting vectors and international inequality changes in environmental indicators: An analysis of CO2 per capita emissions and Kaya factors," Energy Economics, Elsevier, vol. 39(C), pages 122-127.
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