Structural path decomposition of carbon emission: A study of China's manufacturing industry

Tian, Yushen; Xiong, Siqin; Ma, Xiaoming; Ji, Junping

doi:10.1016/j.jclepro.2018.05.047

Cited by 89 publications

(37 citation statements)

References 59 publications

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“…As far as the influencing factors are concerned, resource endowment, investment intensity, industrial structure, market factors, technological effects, industrial policies and other factors have an impact on the production and development of the high-carbon manufacturing industry [17][18][19][20][21][22][23][24] and cause the regional lock-in of carbon emissions from different aspects. In the early stage of the economic development of the high-carbon manufacturing industry, due to industry attribute factors, the areas with abundant mineral resources lead to a higher return rate on capital and the increasing return on scale makes the capital continuously concentrate to the areas with higher resource endowment levels, which leads to the continuous expansion of production scale.…”

Section: Carbonmentioning

confidence: 99%

“…In order to reflect the regional influence factors in the carbon emissions of the high-carbon manufacturing industry under the background of rapid industrialization, referring to the existing literature [16][17][18][19][20][21][22][23] and combining the availability of data and the problem of multi-collinearity among independent variables, this paper selected variables such as scale effect, structural effect, technological effect, resource endowment and foreign direct investment (Table 1). (1) Scale effect (P): There are obvious regional differences in the impact of scale effect on high-carbon manufacturing carbon emissions.…”

Section: Index Selection Of Carbon Emissions Influencing Factorsmentioning

confidence: 99%

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Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

et al. 2020

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There are industry lock-in and regional lock-in phenomena in China's manufacturing industry carbon emissions. However, the existing researches often focus on global carbon emissions, which is not adverse to finding the main problems of manufacturing industry carbon emissions. The biggest contributions of this study are the identification of the industry lock-in and regional lock-in of China's manufacturing industry and the finding of the regional factors that affect the carbon lock-in of the manufacturing industry, which points out the direction for the low-carbon transformation of the local manufacturing industry. This paper is based on the IPCC (Intergovernmental Panel on Climate Change) carbon emissions coefficient method and energy consumption data from 2000 to 2016 to count the manufacturing industry carbon emissions of 30 provinces in China (except Hong Kong, Macao, Taiwan and Tibet). On this basis, the paper uses a spatial-temporal geographical weighted regression (GTWR) model to analysis the regional influencing factors of the high-carbon manufacturing industry. Results demonstrate that China's high-carbon manufacturing industry mainly concentrates on the ferrous metal processing industry, non-metallic mineral manufacturing industry and other sectors. In addition, the carbon emissions of high-carbon manufacturing industries are mainly concentrated in Bohai Bay and the North China Plain. The industrial structure and economic scale are the main reasons for the regional carbon lock-in of the high-carbon manufacturing industry, and the strength of the lock-in has continued to increase. Resource endowment is a stable factor of carbon lock-in in high-carbon regions. Technological progress helps to unlock carbon, while foreign direct investment results in the enhancement of carbon regional lock-in. This study focuses on the regional factors of carbon lock-in in the manufacturing industry, hoping to provide decision support for the green development of China's manufacturing industry.

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Section: Carbonmentioning

confidence: 99%

Section: Index Selection Of Carbon Emissions Influencing Factorsmentioning

confidence: 99%

Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

et al. 2020

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“…We construct a non-competitive input-output table 2015 according to the methods of Tian et al (2018)，which could eliminate the impact of imported goods and services (Su and Ang, 2013). The total capital formation in China is the final demand Y for investment in the construction industry after excluding imported products.…”

Section: Input-output Tablementioning

confidence: 99%

Analysis of economic and energy consumption driving factors of China’s construction industry investment in 2015

Zou

Bai

2020

E3S Web Conf.

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This paper uses the input-output model to analyse the economic and energy consumption impact of China's construction investment in 2015, and finds that it can drive economic growth of 15.11 trillion in total, with direct and indirect impacts of 27.22% and 72.78% respectively ， and investment can actively promote the development of integrated services and finance and insurance sectors. Additionally, the direct energy consumption caused by the investment is 20.98Mtce, accounting for only 1.23%, while the indirect energy consumption is 1701.10Mtce, accounting for 98.77%, of which the largest energy consumption sector is the industry of Production and supply of electricity and heat, the industry of Metal smelting and rolling processing, the industry of non-metallic mineral products, indicating that the construction industry development of china has a strong dependence on traditional energy sources. In the future, we are supposed to focus on indirect energy consumption in the construction industry and formulate morae effective clean energy-saving policies.

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“…Industri manufaktur dapat menerapkan mesin hemat energi untuk mengurangi emisi karbon (Elias et al, 2019). Namun, hal tersebut menimbulkan biaya yang mahal, dan dibutuhkan sumber daya manusia yang sebagian besar tidak dimiliki oleh industri manufaktur kecil dan menengah (Tian et al, 2018b). Sementara itu, beberapa peneliti menggunakan penjadwalan produksi untuk meminimasi emisi karbon (Zhang et al, 2017, Xu et al, 2018.…”

Section: Pendahuluanunclassified

Algoritma ant-lion optimizer untuk meminimasi emisi karbon pada penjadwalan flow shop dependent sequence set-up

Utama

Baroto²,

Maharani³

et al. 2019

JLI Padang

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Structural path decomposition of carbon emission: A study of China's manufacturing industry

Cited by 89 publications

References 59 publications

Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

Analysis of economic and energy consumption driving factors of China’s construction industry investment in 2015

Algoritma ant-lion optimizer untuk meminimasi emisi karbon pada penjadwalan flow shop dependent sequence set-up

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