Driving effects of spatial differences of water consumption based on LMDI model construction and data description

Yao, Longqin; Zhang, Hengquan; Zhang, Chenjun; Zhang, Wanli

doi:10.1007/s10586-018-2038-x

Cited by 11 publications

(12 citation statements)

References 16 publications

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“…Earlier studies (e.g. OECD, 2017;Yao et al, 2019) associate water productivity with water efficiency in the sense that an increase in water productivity indicates a more efficient water input in crop production, ideally leading to a decrease in overall water consumption. However, our findings provide evidence that water productivity cannot be utilized for the assessment of water efficiency.…”

Section: Discussionmentioning

confidence: 99%

“…the inverse of water productivity) for the evolution of water use (e.g. aggregated level: Yao et al, 2019; for industrial at regional level: Shang et al, 2016). With regard to agricultural water use, Zhao and Chen (2014) also include water intensity as a driver, whereas Xu et al (2015) use the ratio of water per biomass production as a proxy for water efficiency, and finally Zhang et al (2018) include irrigation area among other parameters.…”

Section: Lmdi Decomposition Analysismentioning

confidence: 99%

“…In order to ensure efficient water management, governments and international organizations need to develop adequate policies and frameworks that are in line with the global targets, like the SDGs and build upon indicators, which allow monitoring the evolution of water use and analyzing the success of the adopted means (EASAC, 2016;EEA, 2016;Hassing et al, 2018). Many indicators have been suggested within the literature to support policy development and monitor the progress in water efficiency management (Ekins et al, 2017;World Bank Group, 2017;Yao et al, 2019). Water productivityor its inverse water intensityis the most-widely used indicator by decision-makers and academia, which is computed as generated value added per volume of water use (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…Existing research tends to focus on understanding the impact of economic development which is measured by GDP per capita rather than the economic productivity over the evolution in water consumption (i.e. Yao et al, 2019;Zhao and Chen, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Indicating the wrong track? A critical appraisal of water productivity as an indicator to inform water efficiency policies

Ozcelik

Rodrı́guez

Lutter

et al. 2021

Resources, Conservation and Recycling

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Section: Discussionmentioning

confidence: 99%

Section: Lmdi Decomposition Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Indicating the wrong track? A critical appraisal of water productivity as an indicator to inform water efficiency policies

Ozcelik

Rodrı́guez

Lutter

et al. 2021

Resources, Conservation and Recycling

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“…This work took into account energy structure, energy intensity, industrial structure and output scale. Yao et al (2018) used the LMDI model to study the driving effect of spatial differences in provincial water consumption, decomposing the driving effect into intensity, structure, income and population effects.…”

Section: Introductionmentioning

confidence: 99%

Low-carbon economic development in Central Asia based on LMDI decomposition and comparative decoupling analyses

Chen

et al. 2019

J. Arid Land

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Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilization to achieve the sustainable economic development. In this study, the logarithmic mean Divisia index (LMDI) decomposition method was used to explore the influence factors of CO 2 emissions in Central Asia (including Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan) during the period 1992-2014. Moreover, decoupling elasticity and decoupling index based on the LMDI decomposition results were employed to explore the relationship between economic growth and CO 2 emissions during the study period. Our results show that the total CO 2 emissions decreased during the period 1992-1998, influenced by the collapse of the Soviet Union in 1991 and the subsequent financial crisis. After 1998, the total CO 2 emissions started to increase slowly along with the economic growth after the market economic reform. Energy-related CO 2 emissions increased in Central Asia, mainly driven by economic activity effect and population effect, while energy intensity effect and energy carbon structure effect were the primary factors inhibiting CO 2 emissions. The contribution percentages of these four factors (economic activity effect, population effect, energy intensity effect and energy carbon structure effect) to the total CO 2 emissions were 11.80%, 39.08%,-44.82% and-4.32%, respectively, during the study period. Kazakhstan, Uzbekistan and Turkmenistan released great quantities of CO 2 with the annual average emissions of 189.69×10 6 , 45.55×10 6 and 115.38×10 6 t, respectively. In fact, their economic developments depended on high-carbon energies. The decoupling indices clarified the relationship between CO 2 emissions and economic growth, highlighting the occurrence of a ''weak decoupling'' between these two variables in Central Asia. In conclusion, our results indicate that CO 2 emissions are still not completely decoupled from economic growth in Central Asia. Based on these results, we suggest four key policy suggestions in this paper to help Central Asia to reduce CO 2 emissions and build a resource-conserving and environment-friendly society.

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The impact of globalization on the decoupling of water consumption and economic growth in BRICS and N11 countries—Linear and nonlinear approaches

Wang,

2023

Sustainable Development

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In the context of globalization, the 2030 sustainable development goals pose a huge challenge to the coordinated development of economy and environment in emerging economies. The purpose of this article is to investigate whether globalization contributes to balance water consumption and economic growth in emerging economies. China is the largest developing country and the largest trader of goods in the world. From holistic and representative perspectives, this article analyzes the mechanisms affecting economic growth and water consumption in BRICS countries, Next Eleven (N11) countries and China. Combining decoupling model and econometric models, fully modified ordinary least squares (FMOLS) linear model and threshold panel nonlinear model are constructed. Both linear and nonlinear effects of trade and foreign investment on economic growth and water consumption are considered. The results show that, from a holistic perspective, globalization helps balance economic growth and water consumption in emerging economies. The impact of trade on water consumption in BRICS countries is negative. And with the increase of trade, its positive coefficient on water consumption in N11 countries gradually decreases. Foreign direct investment (FDI) plays a positive role in the coordinated development of economic growth and water environment in BRICS and N11 countries. Taking China as a representative country, there is a decoupling phenomenon between economic growth and water use during the study period. With the trade crossing the threshold successively, the promoting effect on economy increases first and then decreases, and the inhibiting effect on water consumption weakens. With the increase of foreign investment, its positive effect on GDP increases, and its positive coefficient on water consumption decreases. The conclusions from representative country and holistic perspective are consistent. Finally, some policy recommendations are put forward.

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Driving effects of spatial differences of water consumption based on LMDI model construction and data description

Cited by 11 publications

References 16 publications

Indicating the wrong track? A critical appraisal of water productivity as an indicator to inform water efficiency policies

Indicating the wrong track? A critical appraisal of water productivity as an indicator to inform water efficiency policies

Low-carbon economic development in Central Asia based on LMDI decomposition and comparative decoupling analyses

The impact of globalization on the decoupling of water consumption and economic growth in BRICS and N11 countries—Linear and nonlinear approaches

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