收藏设为首页 广告服务联系我们在线留言

干旱区地理 ›› 2023, Vol. 46 ›› Issue (7): 1145-1154.doi: 10.12118/j.issn.1000-6060.2022.455

• 生态与环境 • 上一篇    下一篇

新疆农业碳排放强度时空变化趋势与收敛分析

夏文浩1(),王铭扬1,姜磊2,3()   

  1. 1.塔里木大学经济与管理学院,新疆 阿拉尔 843300
    2.广州大学地理科学与遥感学院,广东 广州 510006
    3.广州大学华南人文地理与城市发展研究中心,广东 广州 510006
  • 收稿日期:2022-09-13 修回日期:2022-11-15 出版日期:2023-07-25 发布日期:2023-08-03
  • 通讯作者: 姜磊(1983-),男,博士,副教授,主要从事经济地理研究. E-mail: jianglei@gzhu.edu.cn
  • 作者简介:夏文浩(1998-),男,硕士研究生,主要从事农业低碳发展研究. E-mail: xiawenhao199883@163.com
  • 基金资助:
    广东省自然科学基金团队项目(2018B030312004);兵团社会科学基金项目(22YB22);塔里木大学研究生科研创新项目(TDG RI202264);国家级大学生创新创业训练计划(202210757054)

Spatiotemporal variation trends and convergence analysis of agricultural carbon emission intensity in Xinjiang

XIA Wenhao1(),WANG Mingyang1,JIANG Lei2,3()   

  1. 1. School of Economics and Management, Tarim University, Aral 843300, Xinjiang, China
    2. School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, Guangdong, China
    3. Center for Human Geography and Urban Development, Guangzhou University, Guangzhou 510006, Guangdong, China
  • Received:2022-09-13 Revised:2022-11-15 Online:2023-07-25 Published:2023-08-03

摘要:

选择农用物资、水稻种植、畜牧养殖与秸秆燃烧4个方面对新疆农业碳排放进行综合测算,揭示新疆农业碳排放总量与强度的时空差异及动态变化,然后采用空间收敛分析方法,进一步考察了新疆13个地州市农业碳排放强度的收敛趋势。结果表明:(1)2007—2019年新疆农业碳排放总量处于平稳上升态势,但农业碳排放强度持续降低。(2)2019年农业碳排放总量位居首位的是伊犁哈萨克自治州直属县市(伊犁州直),吐鲁番市最末。新疆13个地州市仅有伊犁州直与和田地区农业碳排放总量处于下降态势,其余地区均处于增长态势。总体上,新疆各地州市农业碳排放强度呈现出了“北低南高”的特征。(3)新疆各地州市农业碳排放强度的动态演进特征差异较大,核密度曲线随着时间的推移整体呈现小幅度左移趋势;农业碳排放强度的集中程度不断增强。(4)新疆各地州市的农业碳排放强度表现出显著的β收敛特征,进一步说明地州市间农业碳排放强度的差距在不断缩小。并且,还发现条件β收敛速度明显高于绝对β收敛,进一步地纳入空间因素后会加快收敛速度。研究结果对推动新疆低碳农业发展与实现“双碳”目标具有重要现实意义。

关键词: 农业碳排放, 时空变化, 核密度分析, 空间收敛模型, 新疆

Abstract:

The spatiotemporal differences and dynamic changes of total agricultural carbon emissions and intensity in Xinjiang, China, were investigated by analyzing agricultural materials, rice cultivation, livestock breeding, and straw burning. The convergence trends of agricultural carbon emissions intensity in 13 prefectures and cities were examined by performing spatial convergence analysis. The results revealed the following: (1) Although the total agricultural carbon emissions in Xinjiang from 2007 to 2019 increased steadily, the intensity of agricultural carbon emissions exhibited a decreasing trend. (2) In 2019, the total agricultural carbon emission was the highest in counties and cities of Ili Kazak Autonomous Prefecture and lowest in Turpan City. A declining trend of total agricultural carbon emissions was observed only in the counties and cities of Ili Kazak Autonomous Prefecture and Hotan region, whereas the rest of the regions exhibited an increasing trend. Generally, a “low in the north and high in the south” trend was observed in the intensity of agricultural carbon emissions in Xinjiang. (3) The dynamic evolutionary characteristics of agricultural carbon emission intensity varied widely across Xinjiang prefectures and cities. The kernel density curve showed an overall small leftward shift over time. Furthermore, the concentration of agricultural carbon emission intensity was increasing. (4) The agricultural carbon emission intensities of various prefectures and cities in Xinjiang exhibited significant β-convergence characteristics, which indicated that the gap in agricultural carbon emission intensities between prefectures and cities was narrowing. Moreover, the conditional β convergence rate was considerably higher than absolute β convergence, and the further incorporation of the spatial factor increased the convergence rate. The results of the study can be used for the development of low-carbon agriculture in Xinjiang to achieve “dual carbon” goals.

Key words: agricultural carbon emissions, spatiotemporal variations, kernel density analysis, spatial convergence model, Xinjiang