福建省灰水足迹时空变化及驱动因素

灰水足迹是稀释水污染物至达标需要的淡水体积，是评价水污染程度与水环境质量的重要方法，对灰水足迹进行核算与分析，可以促进福建省提高水环境质量，构建可持续的水生态环境。借鉴Hoekstra等提出的灰水足迹核算方法，对福建省及各地市2001-2017年的灰水足迹进行核算，对其时空变化特征进行评价并使用对数平均迪式指数分解法（Logarithmic Mean Divisia Index Method，LMDI）模型对灰水足迹变动的驱动因素进行分解。结果表明：a）总氮是决定灰水足迹总量的主要污染物，非点源污染是灰水足迹的最主要来源但占比由68.25%降至63.35%；b）福建省灰水足迹总量降低了9.58%，且各项指标都呈下降趋势，在空间上，灰水足迹总量及剩余灰水足迹东南多西北少，人均灰水足迹及灰水足迹强度东少西多；c）福建省灰水足迹变动的驱动因素中，经济因素是最大正向驱动因素，产生2932.96亿m³的贡献量，技术因素是最大负向驱动因素，产生-2630.31亿m³的贡献量。最后，针对福建省水污染问题提出建议：a）开展非点源污染防治专项；b）加快速度提高城镇生活污水处理水平；c）优化产业结构，提高灰水足迹效率；d）切实落实生态补偿制度，调动各市水环境保护积极性；e）加强环境监管力度，加大技术投入。

Spatio-temporal variations and driving factors of grey water footprint in Fujian Province

The grey water footprint is the amount of freshwater required to assimilate the load of water pollutants in order to meet ambient water quality standards and it is an effective method to evaluate the degree of water pollution and the quality of water. By accounting and analyzing of grey water footprint, it will contribute to improve the water environment and promote sustainable water ecology in Fujian province. We accounted the grey water footprint of Fujian province and 9 local cities from 2001 to 2017 by reference to the grey water footprint accounting method proposed by Hoekstra et al, analyzed the spatio-temporal variations, and applied the Logarithmic Mean Divisia Index Method (LMDI) to investigate the contributions of five driving factors. The results showed as follows. a) The total nitrogen (TN) was considered as the major pollutant of total grey water footprint of Fujian province. Non-point pollution was the major resource of grey water footprint but its proportion have decreased from 68.25% to 63.35%. b) The total grey water footprint decreased by 9.58%, and there was a downtrend of all other indicators. The total grey water footprint and the remaining grey water footprint amount was more in the southeast than that in the northwest, while the west amount was more than that in the east for the per capita grey water footprint and grey water footprint intensity. c) Among the driving factors of Fujian''s grey water footprint, the economic factor was dominantly positive, making a contribution of 293.296 billion m³, while the technical factor was the most negative one, making -263.031 billion m³ contribution. Therefore, we suggest that:a) launching a project to prevent and control non-point pollution; b) Speeding up the enhancement of urban sewage treatment technique; c) Optimizing the industrial structure and improving the efficiency of grey water footprint; d) Implying a mechanism for ecological compensation, fully mobilizing the initiative of all quarters to protect water environment; and e) Strengthening the supervision of environment and taking efforts to achieve the integration of technological advance and economic rationality.