کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8106152 | 1522170 | 2014 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Spatial-temporal patterns and driving factors for industrial wastewater emission in China
ترجمه فارسی عنوان
الگوهای فضایی-زمانی و عوامل موثر در انتشار فاضلاب صنعتی در چین
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Cleaner Production - Volume 76, 1 August 2014, Pages 116-124
Journal: Journal of Cleaner Production - Volume 76, 1 August 2014, Pages 116-124
نویسندگان
Yong Geng, Meiling Wang, Joseph Sarkis, Bing Xue, Lin Zhang, Tsuyoshi Fujita, Xiaoman Yu, Wanxia Ren, Liming Zhang, Huijuan Dong,