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白天骄,孙才志,赵良仕.人文因素对中国灰水经济生产率的影响.生态学报,2018,38(7):2536~2546 本文二维码信息
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人文因素对中国灰水经济生产率的影响
Influence of human factors on the economic productivity of grey water in China
投稿时间:2017-04-13  修订日期:2017-11-13
DOI: 10.5846/stxb201704130655
关键词灰水经济生产率  人文因素  空间Durbin模型
Key Wordseconomic productivity of grey water  human factor  spatial Durbin model
基金项目国家社会科学重点基金(16AJY009)
作者单位E-mail
白天骄 辽宁师范大学城市与环境学院, 大连 116029  
孙才志 辽宁师范大学城市与环境学院, 大连 116029
辽宁师范大学海洋经济与可持续发展研究中心, 大连 116029 
suncaizhi@lnnu.edu.cn 
赵良仕 辽宁师范大学海洋经济与可持续发展研究中心, 大连 116029  
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摘要:
促进水资源环境与经济的可持续发展,已成为当前我国亟待解决的问题。以灰水经济生产率为研究主体,将其定义为GDP与灰水足迹之比,基于对我国31个省市(香港、澳门特别行政区和台湾省数据尚未统计)2000-2014年灰水经济生产率区域特征和空间相关性的分析,利用空间Durbin模型对人文因素与灰水经济生产率的关系进行了研究。结果显示:(1)我国灰水经济生产率整体呈现上升趋势,东部地区显著高于中、西部,西部地区最低;(2)各省区灰水经济生产率在空间分布上存在显著正自相关性且空间集聚程度较高,近年来区域间的分化加剧;(3)从全国范围来看,提升产业结构优化度、城镇化水平及社会福利有利于本地灰水经济生产率增长,提高受教育程度和社会福利对邻近地区灰水经济生产率具有正向影响;(4)从各分区情况来看,提升民众受教育程度、产业结构优化度、城镇化水平和社会福利都对东部地区灰水经济生产率具有显著积极效用,城镇化建设的发展和社会福利水平的提高有利于西部地区灰水经济生产率增加;在间接效应结果中,东部民众受教育程度的提高,中部社区服务机构的减少,西部社会福利的改善都对相应邻近地区灰水经济生产率产生了显著正向影响;此外,各地需缩小城乡差距,提高农村地区GDP,促进经济与环境健康发展。提出了推动我国水环境与经济协调发展的建议。
Abstract:
There is an urgent need for solutions to enable the sustainable development of the water resource environment and economy in China. The present study investigated the economic productivity of grey water (EPGW), which was defined as the ratio of gross domestic product to grey water footprint. Based on an analysis of regional characteristics and spatial correlation of the EPGW in the 31 provinces, cities and autonomous regions in China (the data of Hongkong and Macao special administrative regions and Taiwan Province have not been counted) from 2000 to 2014, we used the spatial Durbin model to examine the relationship between human factors and the EPGW. We found that the EPGW in China increased over time and that the nationwide productivity increased from 19.85 yuan/m3 in 2000 to 107.93 yuan/m3 in 2014, and the 15-year average EPGW was 52.19 yuan/m3. In the eastern region, the EPGW was significantly higher than that of the central and western regions and was lowest in the western region. The difference in average productivity, over 15 years, between the eastern region and the central and western regions was > 50 yuan/m3. From 2000 to 2014, the EPGW in China exhibited a significant positive auto-correlation in regards to spatial distribution, and the spatial agglomeration degree was higher and not randomly distributed. In recent years, however, interregional differentiation in the EPGW has intensified. From the national perspective, the optimization of industrial structure, urbanization, and social welfare are conducive to the growth of the EPGW in local regions. Therefore, improving the level of education and social welfare has positively affected the EPGW in other areas. Improving education, urbanization, social welfare, and the proportion of tertiary industry could positively impact the EPGW of the eastern region. And improving education could also have a significant positive impact on the EPGW of the eastern region's outer area. Reducing social welfare in the central region has positively affected the EPGW of the adjoining and surrounding areas. The total effect coefficient of urbanization reached 4.8446 in the western region, and improving social welfare positively affected the EPGW of the western region's outer area. In addition, various regions need to reduce the disparity between the EPGW of urban and rural areas, improve the GDP of rural areas, and promote a healthy development in both economy and environment. On the basis of these observations, we propose various suggestions that could further promote the coordinated development of water environment and economy in China.
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