摘要
本文采用网络SBM-DEA模型和Meta-frontier模型对1997—2021年中国省际水资源—能源—粮食(WEF)系统效率进行测度,采用改进后的GTWR模型探讨了其影响因素,结果表明:①不同前沿下WEF系统效率存在较大差异;技术落差比率则呈现东、中、西部依次降低的态势;②动态空间坐标弥补了以往GTWR模型中存在较多的重合的空间坐标而导致模型最终评价结果接近于以时间维度进行研究的线性回归结果的不足,并验证了该模型在本研究中的适用性;③在时间变化上,能源生产量、产业结构合理化指数、清洁能源生产占比、R&D经费投入强度的拟合系数呈现先增加并逐渐趋于平稳的态势;单位GDP能耗拟合系数则表现为逐年下降的趋势,而工业能源消耗强度拟合系数的变化趋势则与之相反;其余影响因素的拟合系数则呈现波动变化后趋于平稳的态势;④在空间变化上,人均水资源量、单位农业GDP耗水、灰水足迹载荷系数的影响程度均表现为北方地区大于南方地区;西南地区受能源生产量和清洁能源生产占比影响程度较大;产业结构合理化指数、工业能源消耗强度以及R&D经费投入强度的影响程度高值区主要分布在东部沿海;单位GDP能耗的影响程度自动向西逐渐减小;交通密度的影响程度则表现出一定的区域特色。
This study considered 30 provincial-level administrative units in China as the research object.The network SBM-DEA model and meta-frontier model were used to measure the efficiency of the interprovincial WEF system in China from 1997 to 2021 under the meta-frontier and group-frontier.The improved GTWR model was used to explore the influencing factors.The study produced several results:(1)There are significant differences in the efficiency of WEF systems under different frontiers.The average technology gap ratio of WEF system efficiency in the eastern region was 0.961,whereas that of the central and western regions was 0.673 and 0.455,respectively.(2)In previous studies,there were many overlapping spatial coordinates in the GTWR model,causing the final evaluation results of the model to be close to the linear regression results assessed in the time dimension.To compensate for this deficiency,this study constructed dynamic spatial coordinates and verified the applicability of the model.(3)In terms of temporal change,the GTWR model results showed that the fitting coefficients of energy production,industrial structure rationalization index,proportion of clean energy production,and R&D investment intensity displayed a trend of increasing first and then gradually stabilizing.The fitting coefficient of energy consumption per unit GDP revealed a downward trend year by year,while the change trend of the industrial energy consumption intensity fitting coefficient showed the opposite trend.The fitting coefficients of the remaining influencing factors showed a trend of stability after some fluctuations.(4)In terms of spatial variation,the fitting results of the GTWR model showed that the influencing factors were significantly different between regions and that the influence degrees of per capita water resources,water consumption per unit of agricultural GDP,and gray water footprint load coefficient were all greater in the northern region than in the southern region.The fitting coefficients of energy production and clean ener
作者
郝帅
孙才志
翟小清
HAO Shuai;SUN Caizhi;ZHAI Xiaoqing(Key Research Base of Humanities and Social Sciences of Ministry of Education,Institute of Marine Sustainable Development,Liaoning Normal University,Dalian 116029,China;University Collaborative Innovation Center of Marine Economy High-Quality Development of Liaoning Province,Dalian 116029,China)
出处
《地理学报》
EI
CSCD
北大核心
2024年第9期2389-2406,共18页
Acta Geographica Sinica
基金
辽宁师范大学博士启动科研项目(2023BSL001)。
