黄河流域工业水资源效率及扰动因子评估

Evaluation of industrial water resources efficiency and influencing factors in the Yellow River Basin

  • 摘要: 为系统评价黄河流域9省(区)工业水资源效率,分析其差异及扰动因子,以2014—2023年黄河流域9省(区)工业水资源为研究对象,采用考虑非合意产出的超效率EBM模型评价静态工业水资源效率,通过差异系数分析静态时空演变,基于效率评价结果分析黄河流域工业污染冗余情况。结合Malmquist (ML)全要素生产率指数对水资源效率进行动态分解,采用经LLC等方法检验的Tobit模型对工业水资源效率扰动因子进行分析。结果表明:黄河流域9省(区)工业水资源效率均值为0.783,整体呈上升态势,空间演变差异系数均值为0.22,区域间工业水资源效率水平差距大。四川省COD、NH3-N、挥发酚冗余率分别为0.73%、0.84%、0.03%,污染物冗余水平为黄河流域9省(区)最低;宁夏回族自治区COD、甘肃省NH3-N、山西省挥发酚冗余率为黄河流域9省(区)最高,分别为22.70%、27.90%、45.90%,污染治理形势严峻。从绝对量看,ML指数提高的主要驱动力为规模效率与技术进步,纯技术效率对ML指数增长有负向调节效果。从增长量看,ML指数从0.95提高到1.12,水资源效率呈动态增长,技术效率、纯技术效率、技术进步分别由0.95、0.81、1.00提升至1.00、1.00、1.03,对水资源效率增长的贡献加强,规模效率从1.19降至1.07,对水资源效率增长的贡献下降;水资源禀赋和工业废水排放强度是制约工业水资源效率的关键因素,经济发展水平、环境管制力度、技术创新水平、节水措施是提升工业水资源效率的有效途径。

     

    Abstract: In order to systematically evaluate the efficiency of industrial water resources in the Yellow River Basin and analyze its differences and influencing factors, the industrial water resources of nine provinces ( autonomous regions ) in the Yellow River Basin from 2014 to 2023 were studied. The super-efficiency EBM model considering undesirable output was used to evaluate the efficiency of static industrial water resources. The static spatial and temporal evolution was analyzed by the difference coefficient. Based on the efficiency evaluation results, the industrial pollution redundancy of the Yellow River was analyzed. The Malmquist (ML) index was used to dynamically decompose the water resources efficiency. The Tobit model tested by LLC and other methods was used to analyze the influencing factors of industrial water resources efficiency. The results showed that the average value of industrial water resources efficiency in the nine provinces ( autonomous regions ) of the Yellow River Basin was 0.783, showing an overall upward trend. The average value of the spatial evolution difference coefficient was 0.22, and there was a large gap in the level of industrial water resources efficiency between regions. The redundancy rates of COD, NH3-N and volatile phenol in Sichuan Province were 0.73 %, 0.84 % and 0.03 %, respectively, and the redundancy level of pollutants was the lowest in the nine provinces (autonomous regions). The redundancy rates of COD in Ningxia Hui Autonomous Region, NH3-N in Gansu Province and volatile phenol in Shanxi Province were the highest in the nine provinces ( autonomous regions ), which were 22.70%, 27.90 % and 45.90 %, respectively. The pollution control situation was severe. From the perspective of absolute quantity, the main driving forces for the improvement of the ML index were scale efficiency and technological progress, and pure technical efficiency had a negative moderating effect on the growth of the ML index. From the perspective of growth, the ML index increased from 0.95 to 1.12, and the water resources efficiency showed a dynamic growth. The technical efficiency, pure technical efficiency, and technological progress increased from 0.95, 0.81, and 1.00 to 1.00, 1.00 and 1.03, respectively. The contribution to the growth of water resources efficiency was strengthened, the scale efficiency decreased from 1.19 to 1.07, and the contribution to the growth of water resources efficiency decreased. Water resources endowment and industrial wastewater discharge intensity are the key factors restricting the efficiency of industrial water resources. The level of economic development, environmental regulation, technological innovation and water-saving measures are effective ways to improve the efficiency of industrial water resources.

     

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