中国省际灰水足迹测度及荷载系数的空间关联分析

The spatial correlation of the provincial grey water footprint and its loading coefficient in China

借鉴Hoekstra等提出的灰水足迹计算公式,从农业、工业及生活三方面计算了1998—2012年中国31个省市(自治区)的灰水足迹及其灰水足迹荷载系数。结果表明:1研究期间全国灰水足迹呈现波动趋势,1998年至2006年的灰水足迹呈现波动上升趋势;2007年开始,全国灰水足迹呈现下降趋势;农业在总灰水足迹的贡献率最高、工业最低;231个省市(自治区)15a灰水足迹荷载系数整体呈现小幅波动趋势。在全国内部也存在着明显的地区差异,大体分为5类,分别为高荷载地区、较高荷载区、中度荷载区、较低荷载区、低荷载区。3借助全局与局部空间自相关对全国31个省市(自治区)灰水足迹荷载系数进行空间关联格局分析可知,中国省级灰水足迹存在空间集聚现象且集聚现象逐渐减弱,其中H-H集聚区主要集中在华北地区,L-L集聚区主要集中在南方与青藏地区。通过全国灰水足迹测度与灰水足迹荷载系数空间关联格局分析为灰水足迹分析提供新的研究思路同时为区域可持续发展提供理论支持。

Water is one of our most important resources, being closely linked to the development of society and human beings. With the rapid development of its economy, water scarcity and water pollution have become very serious problems in China. The total volume of water resources in China is rather large, but the per capita water resources are much lower than the global average. The discharge of waste and polluted water increased from 593 × 10^8 t in 1998 to 785 × 10^8 t in 2012. Traditionally, the volume of water resources and water pollution are studied separately, with little research comprehensively evaluating both. Thus, the concept of the grey water footprint was introduced in this context. Hockstra and Chapagain first presented the concept of the grey water footprint in 2008, after which the idea was further developed by a few of the Water Footprint Network＇s grey water footprint groups. The grey water footprint is defined as the volume of freshwater needed to dilute the load of contaminants based on existing environmental water quality standards. The concept of the grey water footprint provides a metric for the comprehensive assessment of water resource scarcity due to pollution. Overall, studies that investigate the assessment of grey water footprints from a regional perspective, and analyze the spatial correlation patterns of grey water footprints are few. Applying the formula for calculating grey water footprints designed by Hoekatra, this study calculated the grey water footprint and grey water footprint load coefficient of 31 provinces, municipalities, and autonomous regions in China, from 1998 to 2012. Spatial autocorrelation methods were used to study the grey water footprint, loadcoefficient, partial correlation pattern, and tendency towards change. In this paper, analyses of the agricultural, industrial, and domestic sectors will be presented. The results show that： 1 ） the total grey water footprint of China is increased from 5078.58 × 10^8 m3 in 1998 to 4400.85 × 10^8 m3 in 2012; however, the grey water footprint fluctuated during those 15 years. The contribution of each source to the grey water footprint is as follows： agriculture produces the most, and industry the least ; 2） the grey water footprint load coefficient of China also tended to fluctuate during this period. The average grey water footprint load coefficient of China over the 15 years surveyed was divided into five categories ： the first, which have high grey water footprint load coefficients, include Tianjin and Ningxia; the second is an area with a higher-than-average grey water footprint load coefficient, and it includes Beijing, Hebei, Shanghai, Shandong, Shanxi, and Henan ; the third is an area comprising 9 provinces of wbich each has a medium grey water footprint load coefficient, and it includes Jiangsu, Gansu, Shannxi Liaoning, Jilin, Heilongjiang, Inner Mongolia, Anhui, and Hubei; the fourth is an area of 9 provinces with a lower than average grey water footprint load coefficient, and includes Zhejiang, Hunan, Guangdong, Guangxi Hainan Chongqing, Sichuan, Guizhou, and Xinjiang ; the last is an area comprising 5 provinces of which each has low grey water footprint load coefficients, and includes Fujian, Jiangxi, Qinghai, Yunnan, and Xizang. 3） Through the analysis of the global spatial autocorrelation index of grey water footprint load coefficients in China from 1998 to 2012 shows that the grey water footprint load coefficient exists a spatial cluster feature, but the cluster phenomenon was attenuated year by year. By analyzing its local spatial autocorrelation index, it was found that the regions with an H-H correlation are mainly located in northern China, whereas the regions with L-L correlations are mainly located in southern of China. The spatial correlation pattern of grey water footprint load coefficients is closely related with regional water resources and grey water footprints.