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基于MRIO的中国省区和产业灰水足迹测算及转移分析
引用本文:孙才志,阎晓东.基于MRIO的中国省区和产业灰水足迹测算及转移分析[J].地理科学进展,2020,39(2):207-218.
作者姓名:孙才志  阎晓东
作者单位:辽宁师范大学海洋经济与可持续发展研究中心,辽宁 大连 116029
辽宁师范大学地理科学学院,辽宁 大连 116029
基金项目:国家社会科学重点基金项目(19AJY010)
摘    要:水资源短缺与水资源污染已经严重影响到人类的生存与中国的可持续发展,分析各地区与各产业水资源污染情况是解决中国环境可持续发展的关键。论文在对传统灰水足迹研究的基础上,利用2002、2007和2012年多区域投入产出表,计算中国30个省份(因数据所限,未分析西藏、香港、澳门和台湾地区)和17个产业2002—2012年中间消费和最终消费灰水足迹,以及合并后的8大区域和17个产业的总灰水足迹转移。结果表明:① 山东、河南和河北等经济规模较大的地区灰水足迹一直处于相对较高的状态,青海、宁夏和海南等经济规模较小的地区灰水足迹一直处于相对较少的状态。② 农业是灰水足迹产生的最大部门,商业及运输业等4个产业部门灰水足迹较大,但其总和却远小于农业灰水足迹;其他制造业等5个产业部门灰水足迹一直相对较少。③ 灰水足迹净输入区域为京津区域、北部沿海区域、东部沿海区域和南部沿海区域;灰水足迹转移量最大的2条路径之和呈现先增加后减少的趋势,识别出的主要灰水足迹流出—流入关系区域为中部区域—东部沿海区域。④ 农业和采选业为灰水足迹净输出部门,大部分轻工业及第三产业为灰水足迹净输入部门;识别出的主要灰水足迹流出—流入关系部门包括农业—食品制造及烟草加工业、农业—纺织服务业、农业—化学工业。各地区和产业产生的灰水足迹以及区域和产业识别出的灰水足迹路径可为减少灰水产生提供理论依据,同时为地区和产业水资源合理利用提供理论支持。

关 键 词:灰水足迹  多区域投入产出模型  中间消费  最终消费  中国  
收稿时间:2019-02-18
修稿时间:2019-05-23

Measurement and transfer analysis of grey water footprint of Chinese provinces and industries based on a multi-regional input-output model
SUN Caizhi,YAN Xiaodong.Measurement and transfer analysis of grey water footprint of Chinese provinces and industries based on a multi-regional input-output model[J].Progress in Geography,2020,39(2):207-218.
Authors:SUN Caizhi  YAN Xiaodong
Institution:Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian 116029, Liaoning, China
School of Geography, Liaoning Normal University, Dalian 116029, Liaoning, China
Abstract:Water shortage and water pollution have seriously affected human survival and China's sustainable development. Analysis of water pollution in various regions and industries is the key for addressing China's environmental sustainability problem. This study used multiregional input-output tables for 2002, 2007, and 2012 on the basis of traditional greywater footprint research, calculated the process and final consumption grey water footprints of China's 30 provinces, municipalities, and autonomous regions (not including Tibet, Hong Kong, Macao and Tianwan) and 17 industries during 2002-2012, and the total grey water footprint transfer of the eight regions and 17 industries. The results show that: 1) The grey water footprints of large economic areas such as Shandong, Henan, and Hebei have been relatively high, and the grey water footprints of relatively small economies such as Qinghai, Ningxia, and Hainan have been relatively small. 2) Agriculture is the largest sector contributing to grey water footprint. The four industries in the commercial and transportation sectors have large grey water footprints, but their total is far less than the agricultural grey water footprint. The grey water footprints of five industrial sectors, such as other manufacturing industries, have been relatively small. 3) The net input area of grey water footprint is the Beijing-Tianjin region, northern coastal region, eastern coastal region, and southern coastal region. The sum of the two paths with the largest amount of grey water footprint transfer increases first and then decreases. The identified main grey water footprint outflow-inflow area is the central area-the eastern coastal area. 4) Agriculture and mining industry are the net export sectors of grey water footprints. Most light industries and tertiary industries are the net input sectors of grey water footprints. The identified major grey water footprint outflow-inflow sectors include agriculture-food manufacturing and tobacco processing, agriculture-textile services, and agriculture-chemical industries. The grey water footprints generated by various regions and industries and the grey water footprint paths identified for the regions and industries can provide a theoretical basis for reducing grey water production, and provide theoretical support for the rational use of regional and industrial water resources.
Keywords:grey water footprint  multi-regional input-output model  intermediate consumption  final consumption  China  
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