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西部大开发地区种植业净碳汇时空格局及驱动因素
摘要点击 259  全文点击 50  投稿时间:2024-07-18  修订日期:2024-09-24
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中文关键词  西部大开发地区  种植业  净碳汇  时空格局  驱动因素  GBR模型
英文关键词  West China Development Area  planting industry  net carbon sink  spatial-temporal patterns  driving factors  GBR model
DOI  10.13227/j.hjkx.202407194
作者单位E-mail
汤李琛 中国人民大学生态环境学院, 北京 100872 tanglichen2352@163.com 
李洁 中国人民大学生态环境学院, 北京 100872  
陈慧 湖北大学商学院, 武汉 430062  
陈宓 中国人民大学人口与健康学院, 北京 100872 m18811641259@163.com 
曾贤刚 中国人民大学生态环境学院, 北京 100872 zengxg@ruc.edu.cn 
张仲元 中国人民大学经济学院, 北京 100872  
中文摘要
      在测算2001~2022年西部大开发地区种植业净碳汇时空格局变化的基础上,运用GBR模型揭示其关键驱动因素及非线性响应机制. 结果表明:①考察期内,西部大开发地区种植业净碳汇量(以C计)呈现上升态势,但增速逐渐放缓,由2001年的12 564.13万t增至2022年的21 910.61万t. ②种植业净碳汇量高值地区以西南地区省份为主,处于净碳汇量高值区间的省份数量持续上升,并呈现少数集聚转为大范围集聚的扩大趋势. 种植业净碳汇强度存在明显空间集聚和非均衡特征,在考察期内所有省份净碳汇强度逐步下降. ③产业结构因素对种植业净碳汇呈现“倒U型”关系,农业生产结构、农业受灾率、城乡收入差距及城镇化率因素具有波动的抑制作用,其他因素呈现显著的促进作用. 在不同时期,农田灌溉条件及农业机械化水平因素的重要性较为突出.
英文摘要
      On the basis of calculating the spatiotemporal pattern changes of net carbon sink in the planting industry in the West China Development Area from 2001 to 2022, the GBR model was used to reveal its key driving factors and nonlinear response mechanisms. The results showed that: ① During the inspection period, the net carbon sink of the planting industry in the West China Development Area (calculated as C) showed an upward trend, but the growth rate gradually slowed, increasing from 125.641 3 million tons in 2001 to 219.106 1 million tons in 2022. ② The high value areas of net carbon sink in the planting industry were mainly in the southwest region, and the number of provinces in the high value range of net carbon sink continued to increase, showing an expanding trend from a few clusters to large-scale clusters. The net carbon sink intensity of planting industry exhibited obvious spatial agglomeration and non-equilibrium characteristics, and the net carbon sink intensity of all provinces gradually decreased during the inspection period. ③ The industrial structure factor had an inverted U-shaped relationship with the net carbon sink of the planting industry. The agricultural production structure, agricultural disaster rate, urban-rural income gap, and urbanization rate factors had a fluctuating inhibitory effect, while other factors had a significant promoting effect. At different periods, the importance of farmland irrigation condition and agricultural mechanization level factors were prominent.

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