摘要
【目的】研究新疆农业碳排放的时空特征及驱动因素,为该地区推动农业农村绿色发展、实现“双碳”目标提供参考。【方法】以种植业、畜牧业、农业能源终端消费的19类碳源为原始数据,对2007—2021年新疆农业碳排放量和碳排放强度进行测算;以种植业和畜牧业的15类碳源为原始数据,对2010、2015、2020年新疆14个地州(市)碳排放量和碳排放强度进行测算;运用LMDI(对数平均除以指数法)模型对其驱动因素进行分析;运用灰色预测模型对新疆2022—2030年农业碳排放的发展进行趋势预测。【结果】2007—2021年新疆农业碳排放量总体呈现“平稳—上升—下降—上升”的趋势,农业碳排放强度总体呈现“下降—上升—下降”的趋势;2010、2015、2020年伊犁哈萨克自治州碳排放总量最高、克拉玛依碳排放总量最低、克孜勒苏柯尔克孜自治州碳排放强度最高,2010年巴音郭楞蒙古自治州碳排放强度最低,2015、2020年吐鲁番碳排放强度最低;农业碳排放驱动因素影响大小为:农业经济水平效应>农业结构效应>农业人口规模效应>农业生产效率;2022—2030年,预测新疆的农业碳排放量呈现增长趋势、强度呈现下降趋势。【结论】2007—2021年新疆农业碳排放总量整体呈现上升趋势,农业碳排放强度整体呈现下降趋势;农业经济水平效应对农业碳排放的增加有促进作用,农业结构效应、农业人口规模效应、农业生产效率对农业碳排放的增加有抑制作用;预计在2022—2030年,新疆农业碳排放量将逐年增加、农业碳排放强度将逐年下降,新疆农业减排固碳潜力巨大。
【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.
作者
黄馨慧
王志强
欧阳绮雯
黄昕
康文钦
HUANG Xinhui;WANG Zhiqiang;OUYANG Qiwen;HUANG Xin;KANG Wenqin(College of Public Administration,Xinjiang Agricultural University,Urumqi 830052,China;Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences,Hohhot 010031,China)
出处
《北方农业学报》
2024年第1期112-124,共13页
Journal of Northern Agriculture
基金
新疆维吾尔自治区专家顾问团决策研究与咨询项目(Jz202315)
国家自然科学基金项目(72164035)。
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
Agricultural carbon emission
Spatial-temporal variation tendency
LMDI model
Grey prediction model
Xinjiang
