XU Li, QU Jian-sheng, WU Jin-jia, et al. Spatial-Temporal Dynamics and Prediction of Carbon Emission From Agriculture and Animal Husbandry in China[J]. Journal of Ecology and Rural Environment, 2019, 35(10): 1232-1241. DOI: 10.19741/j.issn.1673-4831.2018.0884
    Citation: XU Li, QU Jian-sheng, WU Jin-jia, et al. Spatial-Temporal Dynamics and Prediction of Carbon Emission From Agriculture and Animal Husbandry in China[J]. Journal of Ecology and Rural Environment, 2019, 35(10): 1232-1241. DOI: 10.19741/j.issn.1673-4831.2018.0884

    Spatial-Temporal Dynamics and Prediction of Carbon Emission From Agriculture and Animal Husbandry in China

    • Based on the data of major grain crops, agricultural inputs and animal husbandry, agriculture and animal husbandry carbon emissions from 1997 to 2016 in 31 provinces were calculated. Their temporal and spatial variations were analyzed by means of changing index, barycenter model and the standard deviation ellipse. Based on trend extrapolation, grey prediction and ARIMA model as well as standard deviation optimal combination model were used to predict carbon emissions from agriculture and animal husbandry from 2017 to 2022. The results show that from 1997 to 2016, the agricultural environment improved, the carbon emission increased, the core moved toward northwest and the main area was on the right side of Hu Huanyong line. However, the animal husbandry carbon emissions in many provinces were reduced, and the core wiggled in Henan Province. The main area expanded and turned to the southeast-northwest. The high volume area of agricultural carbon emission transferred to the 3 northeastern provinces and north China plain, and the high volume area of animal husbandry carbon emission was concentrated in the traditional region and the central region. The combined model is better than the single model. By 2022, the agricultural carbon emissions will follow the historical trend but the annual growth rate will decrease. Animal husbandry carbon emission will reach 1.13×108 t and the annual growth rate will increase.
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