4.7 Article

Water resources and water pollution emissions in China's industrial sector: A green-biased technological progress analysis

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 229, Issue -, Pages 1412-1426

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.03.216

Keywords

Green total factor productivity growth; Directional distance function; Biased technological progress

Funding

  1. National Natural Science Foundation of China [71473068]
  2. National Social Science Fund of China [18ZDA064]

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Prior to the 21st century, China's industrialisation was mainly driven by investment; by contrast, it now relies on innovation-driven and environmentally friendly technology to achieve sustained and healthy 11th 13th growth. Spanning China's 11.3 Five-Year Plans (2006-2020), chemical oxygen demand and ammonia nitrogen emissions have been the key pollutants that require monitoring for waste water pollution management. To fit well into one of the focus areas under China's government policy direction, the main objectives of this study are to measure input- and output-based technological progress and their determinants for 30 provinces and regions in China from 1999 to 2015. A green-biased technological progress model based on the directional distance function is adopted in this study. The results reveal that sustainable growth in total factor productivity was primarily due to green-biased technological progress. Most provinces and regions in China overused water resources for industrial production, as demonstrated by the high water consumption over the study period, while output-biased technological progress exacerbated the discharge of water pollutants before the implementation of China's 11th Five-Year Plan (2006-2010). Technological progress in the eastern region was more likely to promote industrial growth, while progress in the central and western regions was likely to promote increased pollutant emissions. Furthermore, industrial research and development investment, governance of waste water treatment investment, the educational level of the labour force, and water prices contributed significantly to biased technological progress in China over the study period. Overall, this study has important policy implications and can provide guidance for emissions reductions to promote cleaner production and optimise resource allocation in China's industrial sector. (C) 2019 Elsevier Ltd. All rights reserved.

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