scholarly journals Quantification of Industrial Wastewater Discharge From the Major Cities in Sichuan Province (China) from 2003 to 2018

Author(s):  
Hui Guo ◽  
Yawen Zhang ◽  
Zhen’an Yang

Abstract Wastewater discharge is produced as a side effect of socio-economic activities and exerts severe pressure on the environment, its characteristics depend on the rate of urbanization and industrialization. We used spatial autocorrelation, environmental Kuznets curve (EKC), and logarithmic mean Divisia index (LMDI) model to study the spatial characteristics and driving factors of industrial wastewater discharge in Sichuan province (2003–2018). We showed that the amount of industrial wastewater discharge in Sichuan province for the period was reduced from 116580 to 42064.96 million tons as observed from the Moran index ranging from -0.31 to 0.30. We identified five types of the EKC (monotonically decreasing, N, inverted N, U, and inverted U shape) in 18 major cities of Sichuan province. The technical effect (from -0.28 to -16.37) can reduce the discharge of industrial wastewater, while structure effect (0.05–3.83), economy effect (0.19–7.79) and population effect (from -0.08 to 0.46) can promote the industrial wastewater discharge. Our findings suggest that industrial wastewater discharge was reduced and showed a scattered distribution characteristic in Sichuan Province from 2003 to 2018. It is necessary to strengthen technical management measures to reduce industrial wastewater discharge in Sichuan province.

2021 ◽  
Author(s):  
Zhen’an Yang ◽  
Yawen Zhang ◽  
Hui guo ◽  
Zhaoxu Ma

Abstract Wastewater discharge is produced as a side effect of socio-economic activities and exerts severe pressure on the environment, its characteristics depend on the rate of urbanization and industrialization. We used spatial autocorrelation, environmental Kuznets curve (EKC), and logarithmic mean Divisia index (LMDI) model to study the spatial characteristics and driving factors of industrial wastewater discharge in Sichuan province (2003–2018). We showed that the amount of industrial wastewater discharge in Sichuan province for the period was reduced from 116580 to 42064.96 million tons as observed from the Moran index ranging from -0.31 to 0.30. We identified five types of the EKC (monotonically decreasing, N, inverted N, U, and inverted U shape) in 18 major cities of Sichuan province. The technical effect (from -0.28 to -16.37) can reduce the discharge of industrial wastewater, while structure effect (0.05–3.83), economy effect (0.19–7.79) and population effect (from -0.08 to 0.46) can promote the industrial wastewater discharge. Our findings suggest that industrial wastewater discharge was reduced and showed a scattered distribution characteristic in Sichuan Province from 2003 to 2018. It is necessary to strengthen technical management measures to reduce industrial wastewater discharge in Sichuan province.


2020 ◽  
Vol 202 ◽  
pp. 03023
Author(s):  
Andryan Setyadharma ◽  
Shanty Oktavilia ◽  
Yayu Tika Atmadani ◽  
Indah Fajarini Sri Wahyuningrum

Natural resources play as vital inputs for economic activities, mainly in developing countries. However, massive use of natural resources puts more pressure on the environment and as the result, the quality of environment is deteriorating. The body of economic literature have shown that income is associated with harm to the natural environment. The relationship between income and degradation of the environment is known as the Environmental Kuznets Curve (EKC) hypothesis. Previous studies of EKC hypothesis in Indonesia are still limited and the results are inconclusive due to different results. Therefore, the aim of this study is to present a new insight of the existence of EKC in Indonesia using different method. Most of previous studies of EKC in Indonesia employ Autoregressive distributed lag (ARDL) method, while this study uses data panel regression method from 33 provinces in Indonesia during 2012 to 2018. The result confirms the existence of EKC hypothesis in Indonesia. This study also estimates the turning point, a level of income that starts give positive impact on the environment. This result gives new insight to the existing literature. The policy implication for policymakers are straightforward, i.e. improve wealth of the society through higher income for the protection of the environment.


PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0257498
Author(s):  
Kaiyang Zhong

In recent years, digital finance has become a crucial part of the financial system and reshaped the mode of green finance in China. Digital finance has brought certain impact on economic growth, industrial structure, and resident income, which may affect pollution. The nexus of digital finance and environment in China is thus worth exploring. By revising the traditional Environmental Kuznets Curve model with income inequality variable, this paper decomposes the environmental effects of economic activities into income growth effect, industrial structure effect and income inequality effect, and use panel data of China’s provinces to conduct an empirical analysis. The results reveal the following: (1) the Environmental Kuznets Curve is still valid in sample, and digital finance can reduce air and water pollution (as measured through SO2 and COD emission) directly; (2) in the influence mechanism, digital finance can alleviate income inequality and promote green industrial structure, thus reducing pollution indirectly, but the scale effect of income growth outweighs the technological effect, which increases pollution indirectly; and (3) digital finance has a threshold effect on improving the environment, then an acceleration effect appears after a certain threshold value. From the regional perspective, digital finance development in eastern regions is generally ahead of central and western regions, and the effects of environmental improvement in the eastern regions are greater. According to the study, this paper suggest that digital finance can be an effective way to promote social sustainability by alleviating income inequality and environmental sustainability by reducing pollution.


2019 ◽  
Vol 11 (16) ◽  
pp. 4364 ◽  
Author(s):  
Tsiantikoudis ◽  
Zafeiriou ◽  
Kyriakopoulos ◽  
Arabatzis

The evolution of human societies along with efforts to enhance economic welfare may well lead to the deterioration of the environment. Deforestation is a usual process throughout evolution that poses pressing and potentially irreversible environmental risks, despite the ecological and modernization processes that aim to limit those risks. The economic growth–environmental degradation relationship—namely, the environmental Kuznets curve (EKC) hypothesis—is studied in alignment with the autoregressive distributed lag (ARDL) approach. The novelty of the study is attributed to the use of the carbon emissions equivalent derived by deforestation as an index for environmental degradation in Bulgaria as a new entrant into the European Union (EU). In addition, we use the gross domestic product (GDP) per capita as a proxy for income, being determined as an independent variable. Research findings cannot validate the inverted U-shape of the EKC hypothesis; instead, an inverted N pattern is confirmed. The implementation of appropriate policies aiming at the protection of the environment through the diversification of economic activities is related to the use of forest land and other resources, or related sectors (agroforestry, ecotourism activities, and scientific research), rather than only the direct utilization of forested areas; the limitation of afforestation processes and their negative impacts on citizens’ welfare are also addressed.


2020 ◽  
Vol 9 (4) ◽  
pp. 326-333
Author(s):  
Manuel Cantavella

This paper examines the influence of services activity in the environmental Kuznets curve (EKC) model regarding carbon dioxide (CO2) emissions. The analysis is applied for Spain during the period 1940-2014. It compares the standard environmental Kuznets curve model and its modification by isolating the evolution of services effect. The results through the autoregressive distributed-lag (ARDL) estimation strategy confirm that even though all economic activities tend to be more and more sustainable, it is the evolution of services sector that becomes fundamental in the reduction of per capita CO2 emissions.


1998 ◽  
Vol 5 (12) ◽  
pp. 761-763 ◽  
Author(s):  
Pingo Wang ◽  
Alok K. Bohara ◽  
Robert P. Berrens ◽  
Kishore Gawande

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