Spatial-temporal patterns and driving factors for industrial wastewater emission in China

Spatial-temporal patterns and driving factors for industrial wastewater emission in China
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中国工业废水排放时空格局及驱动因素

DOI:
10.1016/j.jclepro.2014.04.047
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发表时间:
2014-08-01
影响因子:
11.1
通讯作者:
Dong, Huijuan
Dong, Huijuan
中科院分区:
环境科学与生态学1区
文献类型:
--
作者:
Geng, Yong;Wang, Meiling;Dong, Huijuan

文献摘要

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中国超常的经济增长、工业化和城市化,加上基础供水和处理基础设施投资不足,导致工业水污染日益严重。然而,由于发展不平衡,工业废水排放呈现出明显的地区差异。工业废水管理的差异需要对不同区域的空间和时间模式进行更深入的研究,以确定适当和有效的缓解政策,同时考虑实际和局部现实。本文通过对中国所在的31个省份1995年-2010年工业废水排放的时空特征和驱动因素的分析,解决了这一问题,并提供了新的认识。运用对数平均分化指数法(LMDI),结果表明,经济因素是各省工业废水排放量变化的主要驱动因素。研究还发现,技术进步大大抵消了排放的增加。利用这些研究成果,提出了控制工业废水排放的一般和具体措施,从而可以提高中国乃至其他地方的整体工业用水效率。(C)2014爱思唯尔有限公司。保留所有权利。
China's extraordinary economic growth, industrialization and urbanization coupled with inadequate investment in basic water supply and treatment infrastructures, have resulted in increasing industrial water pollution. However, due to imbalanced development, industrial wastewater emissions present significant regional disparity. Industrial wastewater management disparity requires more in-depth study on both spatial and temporal patterns across different regions for identification of appropriate and effective mitigation policies while considering practical and localized realities. This paper addresses this issue and contributes to new knowledge by analyzing the spatial-temporal characteristics and driving forces of industrial wastewater emission variations in China's 31 provinces during the years 1995-2010. Using the Logarithmic Mean Divisia Index (LMDI) method, the results show that economic factors are the main driving factors of industrial wastewater emission changes in all provinces during the study period. It is also found that technology improvement considerably offsets emission increases. Using these research findings, both general and specific measures for controlling industrial wastewater emissions are offered so that the overall industrial water efficiency can be improved, in China and potentially elsewhere. (C) 2014 Elsevier Ltd. All rights reserved.