关键词: 农业碳排放, 时空变化趋势, LMDI模型, 灰色预测模型, 新疆

Abstract: 【Objective】Study the spatial-temporal characteristics and driving factors of agricultural carbon emissions in Xinjiang,to provide references for promoting green development of agriculture and rural areas and achieving the“dual carbon”goals in the region.【Methods】Using 19 types of carbon sources from plantation,livestock and agricultural energy end-consumption as raw data,the agricultural carbon emissions and carbon emission intensities of Xinjiang from 2007 to 2021 were measured. Using 15 types of carbon sources from plantation and livestock as raw data,the carbon emissions and carbon emission intensities of fourteen prefectures（cities） in Xinjiang in 2010,2015,and 2020 were measured. The driving factors were analyzed by the LMDI（logarithmic mean divisia index） model. The grey prediction model was used to predict the trend of agricultural carbon emissions development in Xinjiang from 2022 to 2030.【Results】During 2007 to 2021,Xinjiang agricultural carbon emissions had the overall trend of“steady-increasing-decreasing-increasing”,while carbon emission intensities had the overall trend of “decreasing-increasing-decreasing”. In 2010,2015 and 2020,Ili Kazak Autonomous Prefecture had the highest total carbon emissions,Karamay had the lowest total carbon emissions,Kizilsu Kirgiz Autonomous Prefecture had the highest carbon emission intensities. Bayingol Mongolian Autonomous Prefecture had the lowest carbon emission intensities in 2010. Turpan had the lowest carbon emission intensities in 2015 and 2020. The impacts of driving factors on agricultural carbon emissions were：agricultural economic level effect > agricultural structure effect > agricultural population scale effect > agricultural production efficiency. From 2022 to 2030,the agricultural carbon emissions in Xinjiang were predicted to have an increasing trend while the intensities have a decreasing trend.【Conclusion】From 2007 to 2021,the total agricultural carbon emissions in Xinjiang showed an overall upward trend,while the agricultural carbon emission intensity showed an overall downward trend. Agricultural economic level effect promoted the increase of agricultural carbon emissions,while agricultural structure effect,agricultural population scale effect,and agricultural production efficiency restrained the increase of agricultural carbon emissions. It was predicted that from 2022 to 2030,the agricultural carbon emissions in Xinjiang will increase year by year,while the agricultural carbon emission intensities will decrease year by year. Xinjiang agricultural carbon reduction and fixation has enormous potential.

Key words: Agricultural carbon emission, Spatial-temporal variation tendency, LMDI model, Grey prediction model, Xinjiang