Industrial production: Pursuing scale expansion or pollution reduction? Judgment based on the Copeland-Toylor model

Yang, Guanglei; Zhang, Wei; Zha, Donglan

doi:10.1016/j.jclepro.2019.01.144

Cited by 21 publications

(7 citation statements)

References 45 publications

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“…This may have also occurred because input biased technological progress can improve marginal productivity, expanding the scale of production. The scale effect increases demand for fossil energy, generating more pollutant emissions (Yang et al, 2019). Moreover, input biased technological progress can significantly reduce energy costs, which also contributes to the increase in non-renewable energy consumption (Yi et al, 2020).…”

Section: Benchmark Regression Resultsmentioning

confidence: 99%

How does biased technological progress affect haze pollution? Evidence from APEC economies

Yang

Zha

2022

Environ Sci Pollut Res

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Biased technological progress is the act of energy conservation and emission reduction by changing the marginal rate of substitution. In this study, we introduced renewable energy into a production function, and proposed a method of identifying biased characteristics of technological progress, based on marginal productivity theory.A panel dataset for the Asia-Pacific Economic Cooperation (APEC) economies from 2000-2017 was analyzed to explore the effect of biased technological progress in reducing particulate matter (PM2.5). We found that input biased technological progress tended to use more non-renewable energy. Input biased technological progress aggravated haze pollution; however, this effect decreased as the PM2.5 concentration increased. Output biased technological progress significantly reduced haze pollution in high-income economies, but increased it in low-income economies. The effect of neutral technological progress on haze pollution was the opposite of the effect from output biased technological progress. We also found that increasing renewable energy consumption and reducing energy intensity were separate effective paths for input and output biased technological progress, respectively, to mitigate haze pollution. For neutral technological progress, improving total factor productivity was an important way to mitigate haze pollution. Finally, several policy recommendations are proposed to mitigate haze pollution in APEC economies.

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Section: Benchmark Regression Resultsmentioning

confidence: 99%

How does biased technological progress affect haze pollution? Evidence from APEC economies

Yang

Zha

2022

Environ Sci Pollut Res

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“…Greenstone and Hanna [36] evaluated the introduction of environmental regulations in India by examining air quality issues and the water environment, concluding that the 1981 Air Act has been effective, but the 1974 Water Act has had relatively few positive results. Yang et al [37] employed the Propensity Score Matching and DID (PSM-DID) method to verify the effect that the construction of a high-speed railway has on environmental pollution, showing that there has been a significant 7.35% reduction in the pollution. As ULE conforms to an exogenous policy exerted to control emissions, we used the DID approach to estimate the abatement results of SO 2 , NO x , and smoke dust in China.…”

Section: Review On Policy Testing Methodsmentioning

confidence: 99%

Did an Ultra-Low Emissions Policy on Coal-Fueled Thermal Power Reduce the Harmful Emissions? Evidence from Three Typical Air Pollutants Abatement in China

Xia

Xiong

et al. 2020

IJERPH

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Thermal power generation based on coal-fired power plants has the advantages of stability and controllability and has been the largest source of electricity supply in China. Coal-fired power plants, however, are also accompanied by high carbon emissions and the release of harmful substances (mainly including sulfur dioxide, nitrogen oxides, and smoke dust), and are even regarded as the “chief criminal” in terms of air pollution. However, thermal power is also a pioneering industry involved in several environmental regulations and cleaner production techniques before other industries. Evidence of this is China’s ultra-low emissions (ULE) policy on coal-fired power plants, implemented in 2015. To verify this policy’s effect, this study treats ULE as an exogenous impact variable, examining its emissions reduction effect on SO2, NOx, and smoke dust in Eastern and Central China using the difference-in-difference method (DID). The results show that the total emissions of the three pollutants were abated by 0.133%, 0.057% and 0.036% in Eastern, and by 0.120%, 0.035% and 0.043% in Central China at every 1% rise of thermal power generated after ULE. In addition, several other factors can also argue for the promotion of thermal power. Other industries, such as steel or chemical, have proven that they can contribute significant SO2 and NOx emissions. Based on these results, we provide suggestions on synergistic emissions reduction among multiple industries, as well as a discussion on the necessity of implementing ULE in Western China.

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“…The scale of industrial production may inflate the discharge of industrial pollutants. The effect on industrial wastewater is considerably stronger than that on air pollution or waste [24].…”

Section: Introductionmentioning

confidence: 91%

Industrial agglomeration and air pollution: A new perspective from enterprises in Atmospheric Pollution Transmission Channel Cities (APTCC) of Beijing-Tianjin-Hebei and its surrounding areas, China

et al. 2021

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Air quality in China has gradually been improving in recent years; however, the Beijing-Tianjin-Hebei (BTH) region continues to be the most polluted area in China, with the worst air quality index. BTH and its surrounding areas experience high agglomeration of heavy-polluting manufacturers that generate electric power, process petroleum and coal, and carry out smelting and pressing of ferrous metals, raw chemical materials, chemical products, and non-metallic mineral products. This study presents evidence of the air pollution impacts of industrial agglomeration using the Ellison–Glaeser index, Herfindahl–Hirschman index, and spatial autocorrelation analysis. This was based on data from 73,353 enterprises in “2+26” atmospheric pollution transmission channel cities in BTH and its surrounding areas (herein referred to as BTH “2+26” cities). The results showed that Beijing, Yangquan, Puyang, Kaifeng, Taiyuan, and Jinan had the highest Ellison–Glaeser index among the BTH “2+26” cities; this represents the highest enterprise agglomeration. Beijing, Langfang, Tianjin, Baoding, and Tangshan also showed a low Herfindahl–Hirschman index of pollutant emissions, which have a relatively high degree of industrial agglomeration in BTH “2+26” cities. There was an inverted U-shaped relationship between enterprise agglomeration and air quality in the BTH “2+26” cities. This means that air quality improved with increased industrial agglomeration up to a certain level; beyond this point, the air quality begins to deteriorate with a decrease in industrial agglomeration.

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Industrial production: Pursuing scale expansion or pollution reduction? Judgment based on the Copeland-Toylor model

Cited by 21 publications

References 45 publications

How does biased technological progress affect haze pollution? Evidence from APEC economies

How does biased technological progress affect haze pollution? Evidence from APEC economies

Did an Ultra-Low Emissions Policy on Coal-Fueled Thermal Power Reduce the Harmful Emissions? Evidence from Three Typical Air Pollutants Abatement in China

Industrial agglomeration and air pollution: A new perspective from enterprises in Atmospheric Pollution Transmission Channel Cities (APTCC) of Beijing-Tianjin-Hebei and its surrounding areas, China

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