Impact of Manufacturing Transfer on SO2 Emissions in Jiangsu Province, China

Peng, Ying; Cui, Jian; Cao, Youhui; Du, Yingxun; Chan, Andy; Yang, Fumo

doi:10.3390/atmos7050069

Cited by 11 publications

(5 citation statements)

References 46 publications

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“…However, some studies found that industrial structure adjustment has little effect on environmental pollution (Calbick & Gunton, 2014;Cheng et al, 2018;Cole & Elliot, 2003). Some studies even presented the view that industrial structure adjustment does not have an obvious effect on environmental quality (Bruvoll & Medin, 2003;Peng et al, 2016). Other studies found that industrial structure adjustment has a negative effect on environmental quality (Shandra et al, 2008;Guo et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Are Industrial Structure Adjustment and Technical Progress Conducive to Environmental Improvement?

Jia

Zhang

2021

Journal of Global Information Management

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China actively broadens its channels for environmental protection and limits pollutant emissions through industrial structure adjustment and technical progress. Based on panel data of 30 provinces in China from 2003 to 2017, this study investigated the effects of industrial structure adjustment and technical progress on environmental pollution using spatial Dubin models. The findings show the following. (1) As the economy develops, the situation of environmental pollution in various regions deteriorates; moreover, spatio-temporal dependence is an aspect of environmental pollution. (2) Industrial structure adjustment and technical progress are beneficial to environmental improvement. Furthermore, there are spillover effects in factors such as industrial structure and technical progress to varying degrees. Thus, this study suggests that the path of coupling between industrial structure and technical progress should be explored to establish a pollution filtering mechanism, thereby improving environmental quality.

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Section: Literature Reviewmentioning

confidence: 99%

Are Industrial Structure Adjustment and Technical Progress Conducive to Environmental Improvement?

Jia

Zhang

2021

Journal of Global Information Management

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“…The city data come from the CHINA CITY STATISTICAL YEARBOOK [37] and the official websites of these cities' Statistics Bureaus, while national and provincial data come from the CHINA ENVIRONMENT YEARBOOK [38]. According to lots of previous work, such as the study of Peng et al [39] and Lehoczki and Sleszynski [40], this study chooses industrial SO2 emissions intensity (GDP and per capita GDP used in this paper are based on the benchmark of 2003 at constant price) as an EFT reform evaluation indicator, and the specific equation such as Equation (7). Due to the difference of each city's SO2 emission intensity, the direct use of the difference of emission reduction intensity is not scientific.…”

Section: Data and Sample Selectionmentioning

confidence: 99%

“…In March 2004, Premier Wen Jiabao proposed the "Rise of Central China" [44], followed by a series of plans to stimulate the central region's economy, including Hubei Province. Correspondingly, Hubei Province According to lots of previous work, such as the study of Peng et al [39] and Lehoczki and Sleszynski [40], this study chooses industrial SO 2 emissions intensity (GDP and per capita GDP used in this paper are based on the benchmark of 2003 at constant price) as an EFT reform evaluation indicator, and the specific equation such as Equation (7). Due to the difference of each city's SO 2 emission intensity, the direct use of the difference of emission reduction intensity is not scientific.…”

Section: Data and Sample Selectionmentioning

confidence: 99%

Using Machine Learning in Environmental Tax Reform Assessment for Sustainable Development: A Case Study of Hubei Province, China

Zheng

2016

Sustainability

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During the past 30 year of economic growth, China has also accumulated a huge environmental pollution debt. China's government attempts to use a variety of means, including tax instruments to control environmental pollution. After nine years of repeated debates, the State Council Legislative Affairs Office released the Environmental Protection Tax Law (Draft) in June 2015. As China's first environmental tax law, whether this conservative "Environmental Fee to Tax (EFT)" reform could improve the environment has generated controversy. In this paper, we seek insights to this controversial issue using the machine learning approach, a powerful tool for environmental policy assessment. We take Hubei Province, the first pilot area as a case of EFT, and analyze the institutional incentive, behavior transformation and emission intensity reduction performance. Twelve pilot cities located in Hubei Province were selected to estimate the effect of the reform by using synthetic control and a rapid developing machine learning method for policy evaluation. We find that the EFT reform can promote emission intensity reduction. Especially, relative to comparable synthetic cities in the absence of the reform, the average annual emission intensity of Sulfur Dioxide (SO 2 ) in the pilot cities dropped by 0.13 ton/million Yuan with a reduction rate of 10%-32%. Our findings also show that the impact of environmental tax reform varies across cities due to the administrative level and economic development. The results of our study are also supported by enterprise interviews. The EFT improves the overall environmental costs, and encourages enterprises to reduce emissions pollution. These results provide valuable experience and policy implications for the implementation of China's Environmental Protection Tax Law.

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“…Some scholars explored China's SO 2 and NO x discharges from the perspectives of agriculture (Yang et al 2002), transportation, aviation (Qu et al, 2016;Fan et al, 2012), trends, characteristics (Wang et al 2002;Tian et al 2013;Song and Yang 2014), scenarios, forecasting (Vallack et al 2001;Lu et al 2014), and the radiative transfer (Sun et al 2006). Some other scholars have studied the relationship between the two pollutants and respiratory diseases (Ma et al 2016), their co-benefits with carbon reduction (Nam et al 2013), and the assessment of related mitigation policies or strategies (Graus and Worrell 2007;Ying et al 2007;Zhao et al 2013;Peng et al 2016). However, few scientists have studied the drivers of SO 2 and NO x discharges in China from both the periodic Five-Year Plan and the industrial structural perspectives.…”

Section: Introductionmentioning

confidence: 99%

Multi-perspective comparisons and mitigation implications of SO2 and NO x discharges from the industrial sector of China: a decomposition analysis

Jia

Gong

et al. 2018

Environ Sci Pollut Res

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This study is the first attempt to investigate the drivers of Chinese industrial SO and NO emissions from both periodic and structural perspectives through a decomposition analysis using the logarithmic mean Divisia index (LMDI). The two pollutants' emissions were decomposed into output effects, structural effects, clean production effects, and pollution abatement effects. The results showed that China's industrial SO discharge increased by 1.14 Mt during 2003-2014, and the contributions from the four effects were 23.17, - 1.88, - 3.80, and - 16.36 Mt, respectively. Likewise, NO discharge changed by - 3.44 Mt over 2011-2014, and the corresponding contributions from the four effects were 2.97, - 0.62, - 1.84, and - 3.95 Mt. Thus, the output effect was mainly responsible for the growth of the two discharges. The average annual contribution rates of SO and NO from output were 14.33 and 5.97%, respectively, but pollution abatement technology presented the most obvious mitigating effects (- 10.11 and - 7.92%), followed by the mitigating effects of clean production technology (- 2.35 and - 3.7%), and the mitigation from the structural effect was the weakest (- 1.16 and - 1.25%, respectively), which meant pollutant reduction policies related to industrial structure adjustment should be a long-term measure for the two discharges. In addition, the sub-sectors of I20 (manufacture of raw chemical materials and chemical products), I24 (manufacture of non-metallic mineral products), and I26 (smelting and pressing of non-ferrous metals) were the major contributors to both discharges. Thus, these sub-sectors should be given priority consideration when designing mitigation-related measures. Last, some particular policy implications were recommended for reducing the two discharges, including that the government should seek a technological discharge reduction route.

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Impact of Manufacturing Transfer on SO2 Emissions in Jiangsu Province, China

Cited by 11 publications

References 46 publications

Are Industrial Structure Adjustment and Technical Progress Conducive to Environmental Improvement?

Are Industrial Structure Adjustment and Technical Progress Conducive to Environmental Improvement?

Using Machine Learning in Environmental Tax Reform Assessment for Sustainable Development: A Case Study of Hubei Province, China

Multi-perspective comparisons and mitigation implications of SO2 and NO x discharges from the industrial sector of China: a decomposition analysis

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