Impact of uncertainty on regional carbon peak paths: an analysis based on carbon emissions accounting, modeling, and driving factors

Zhao, Kuokuo; Cui, Xuezhu; Zhou, Zhanhang; Huang, Peixuan

doi:10.1007/s11356-021-16966-w

Cited by 15 publications

(8 citation statements)

References 59 publications

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“…Furthermore, Anser et al ( 2021a ) found that EPU had a negative impact on the environment in the top 10 carbon emitter countries. Atsu and Adams ( 2021 ) found similar results for BRICS countries; Khan et al ( 2022 ) for East Asian economies; Lei et al ( 2022 ) for China; Nakhli et al ( 2022 ) for USA; Shabir et al ( 2022 ) for 24 developing and developed countries; Syed et al ( 2022 ) for BRICST 6 countries; Ullah et al ( 2022 ) for low and high globalised OECD economies; Xue et al ( 2022 ) for France; Yu et al ( 2021 ) for Chinese manufacturing firms; Zakari et al ( 2021 ) for OECD 7 countries; Zhang et al ( 2022 ) for USA and China; Zhao et al ( 2022 ) for China; Adams et al ( 2020 ) for resource-rich countries; Adedoyin and Zakari ( 2020 ) for UK; Jiang et al ( 2019 ) for USA; Pirgaip and Dinçergök ( 2020 ) for G7 countries; and Ulucak and Khan ( 2020 ) for USA. Our findings, however, contradict those of Ahmed et al ( 2021 ), who reported that EPU lowers CO 2 emissions in the USA.…”

Section: Empirical Results and Their Discussionmentioning

confidence: 99%

“…Another group of studies, on the other hand, found that EPU degrades environmental quality (Adedoyin et al 2021 ; Amin and Dogan 2021 ; Anser et al 2021a ; Atsu and Adams 2021 ; Khan et al 2022 ; Lei et al 2022 ; Nakhli et al 2022 ; Shabir et al 2022 ; Syed et al 2022 ; Ullah et al 2022 ; Xue et al 2022 ; Yu et al 2021 ; Zakari et al 2021 ; Zhang et al 2022 ; Zhao et al 2022 ; Adams et al 2020 ; Adedoyin and Zakari 2020 ; Jiang et al 2019 ; Pirgaip and Dinçergök 2020 ; Ulucak and Khan 2020 ). Adedoyin et al ( 2021 ), for example, used the dynamic panel system-GMM technique to evaluate the environmental effect of EPU in Sub-Saharan Africa from 1996 to 2014, and found that EPU degrades environmental quality.…”

Section: Literature Review and Contributions Of The Studymentioning

confidence: 99%

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Investigating the moderating role of economic policy uncertainty in environmental Kuznets curve for South Africa: Evidence from the novel dynamic ARDL simulations approach

Udeagha

Muchapondwa

2022

Environ Sci Pollut Res

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South Africa, one of the emerging markets and fast-developing economies in Sub-Saharan Africa recognised for varying world’s natural assets on the international market, has recorded significant economic growth in the previous several years. However, aside from the ecological repercussions of energy generation, how economic uncertainties moderate the effects of energy intensity, renewable and non-renewable energy usage, and economic complexity on the environment has largely gone unnoticed. As a result, this paper addresses an important empirical vacuum by exploring the moderating influence of economic policy uncertainty in the environmental Kuznets curve for South Africa from 1960 to 2020. Results from the novel dynamic autoregressive distributed lag simulations framework reveal the following key findings: (i) economic policy uncertainty accelerates environmental degradation in both the short and long run; (ii) economic growth (as measured by the scale effect) increases environmental degradation, whereas the square of economic growth (as measured by the technique effect) slows it down, confirming the presence of the environmental Kuznets curve (EKC) hypothesis; (iii) environmental quality is deteriorated by energy intensity, economic complexity, non-renewable energy usage, and trade openness; (iv) the use of renewable energy and technological innovation increase environmental quality; (v) whereas the moderating effects of economic policy uncertainty on the environmental impacts of energy intensity, renewable and non-renewable energy consumption result in an increase in environmental destruction, its moderating effect on environmental implication of economic complexity plays an important role in improving environmental quality. These findings permit us to draw important policy recommendations for South Africa for improving environmental quality.

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Section: Empirical Results and Their Discussionmentioning

confidence: 99%

Section: Literature Review and Contributions Of The Studymentioning

confidence: 99%

Investigating the moderating role of economic policy uncertainty in environmental Kuznets curve for South Africa: Evidence from the novel dynamic ARDL simulations approach

Udeagha

Muchapondwa

2022

Environ Sci Pollut Res

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show abstract

“…In the ridge trace map, if the correlation coefficient tends to be stable after a certain point, the K value corresponding to that point is the best K value of the model. At the same time, the smaller the K value, the better the fitting effect of the model (Marquardt & Snee, 1975 ; Wang et al, 2019 ; Zhao et al, 2022 ). After determining the best K value, the K value can be actively entered into the model to acquire the ridge regression model’s estimated result.…”

Section: Methodology and Datamentioning

confidence: 99%

Influencing factors and trend prediction of PM2.5 concentration based on STRIPAT-Scenario analysis in Zhejiang Province, China

Zhang

et al. 2022

Environ Dev Sustain

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The government’s development of eco-environmental policies can have a scientific foundation thanks to the fine particulate matter (PM 2.5 ) medium- and long-term change forecast. This study develops a STRIPAT-Scenario analysis framework employing panel data from 11 cities in Zhejiang Province between 2006 and 2020 to predict the changing trend of PM 2.5 concentrations under five alternative scenarios. The results reveal that: (1) urbanization development ( P ), economic development ( A ), technological innovation investment ( T ) and environmental regulation intensity have a significant inhibitory effect on PM 2.5 concentration in Zhejiang Province, while industrial structure, industrial energy consumption and the number of motor vehicles ( TR ) have a significant increase on PM 2.5 concentration. (2) Under any scenario, the PM 2.5 concentration of 11 cities in Zhejiang Province can reach the constraint target set in the 14th Five-Year plan. The improvement in urban PM 2.5 quality is most obviously impacted by the high-quality development scenario (S4). (3) Toward 2035, PM 2.5 concentrations of 11 cities in Zhejiang Province can reach the National Class I level standard in most scenario models, among which Hangzhou, Jiaxing and Shaoxing are under high pressure to reduce emissions and are the key areas for PM 2.5 management in Zhejiang Province. However, most cities cannot reach the 10 μg/m 3 limit of WHO’s AQG2005 version. Finally, this study makes recommendations for reducing PM 2.5 in terms of enhancing industrial structure and funding science and technology innovation.

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“…The emissions inventory approach is more in line with the fundamental issue of provincial carbon emissions. 15,16 Existing emission inventory studies do not take carbon transfers from electricity input and output into account. 17 In particular, as a major power exporter in China, Sichuan province needs to consider the transfer of carbon emissions generated by power output.…”

Section: Literature Reviewmentioning

confidence: 99%

Decoupling analysis and peak prediction of carbon emission in less developed provinces: A case study of Sichuan province, China

Chen

Liu

et al. 2023

Greenhouse Gases

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With the increasing severity of climate change, the unevenness of economic development has resulted in the heterogeneity of carbon peaking in different regions. Under the dual‐carbon target strategy, the peak research in China's less developed provinces is significant. This study uses the emission factor method to calculate the carbon emission inventory of an economically underdeveloped province (Sichuan) and 15 major cities from 2010 to 2020. The carbon emissions in the Sichuan province showed a fluctuating trend, and the emission intensity decreased year by year. This study analyzes the decoupling effect of carbon emissions and GDP gold content (GDPgc). Sichuan's economy and carbon emissions have not been strongly decoupled. Finally, under three scenarios, it forecasts the peak carbon emissions in Sichuan province. Sichuan province will peak in 2029 (361.74 million tons) under the simultaneous peak scenario. This study provides an important reference for formulating and implementing energy‐saving and emission‐reduction policies in relatively poor regions. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

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Impact of uncertainty on regional carbon peak paths: an analysis based on carbon emissions accounting, modeling, and driving factors

Cited by 15 publications

References 59 publications

Investigating the moderating role of economic policy uncertainty in environmental Kuznets curve for South Africa: Evidence from the novel dynamic ARDL simulations approach

Investigating the moderating role of economic policy uncertainty in environmental Kuznets curve for South Africa: Evidence from the novel dynamic ARDL simulations approach

Influencing factors and trend prediction of PM2.5 concentration based on STRIPAT-Scenario analysis in Zhejiang Province, China

Decoupling analysis and peak prediction of carbon emission in less developed provinces: A case study of Sichuan province, China

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