Influencing factors and decoupling analysis of carbon emissions in China’s manufacturing industry

2021 ◽  
Author(s):  
Baoling Jin ◽  
Ying Han
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Decoupling Analysis

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

2020 ◽  
Vol 12 (4) ◽  
pp. 1502 ◽  
Author(s):  
Xia Wang ◽  
Lijun Zhang ◽  
Yaochen Qin ◽  
Jingfei Zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Ferrous Metal ◽  
Bohai Bay ◽  
High Carbon ◽  
Intergovernmental Panel ◽  
Resource Endowment ◽  
Regional Factors ◽  
Lock In

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.

scholarly journals Analysis on Measurement, Decoupling Effect and Influencing Factors of Agricultural Carbon Emissions in Major Grain Producing Areas—Taking Henan Province as An Example

2021 ◽  
Vol 261 ◽  
pp. 04030
Author(s):  
YiLin Shen ◽  
Shu Yu
Keyword(s):  
Economic Development ◽  
Agricultural Economic ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Henan Province ◽  
Total Output ◽  
Chemical Fertilizers ◽  
Decoupling Analysis ◽  
Decoupling Effect ◽  
First Time

Based on the scientific calculation of agricultural carbon emissions in Henan Province, the Tapio decoupling model is used to analyze its relationship with economic development, and its driving factors are analyzed in combination with the LMDI model. The results show that the total amount of agricultural carbon emissions in Henan Province from 2010 to 2019 is on the rise, of which chemical fertilizers are the largest source of carbon emissions. The decoupling analysis shows that before 2019, the weak decoupling between agricultural carbon emissions and the total output value of the planting industry was mainly weak, and a strong decoupling state appeared for the first time in 2019. This means that the level of agricultural economic development is the main force driving the growth of carbon emissions.

scholarly journals Sustainability Assessment Based on Integrating EKC with Decoupling: Empirical Evidence from China

2021 ◽  
Vol 13 (2) ◽  
pp. 655
Author(s):  
Donghui Lv ◽  
Ruru Wang ◽  
Yu Zhang
Keyword(s):  
Economic Growth ◽  
Sustainable Development ◽  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Assessment Methods ◽  
Short Term ◽  
Decoupling Analysis ◽  
Long Term Trends ◽  
The Relationship

In September 2020, the Chinese government proposed a climate change commitment that aims to make carbon emissions peak before 2030 and achieve carbon neutrality by 2060. In this context, it is important to examine the relationship between economic growth and carbon emissions. The Environmental Kuznets Curve (EKC) and decoupling analysis are commonly used assessment methods for regional sustainable development. Each method has a particular emphasis: the former focuses on long-term trends and the latter on short-term change. Integrating the EKC hypothesis with decoupling analysis is helpful to diagnose the relationship between economic growth and the carbon emissions of the manufacturing industry from the perspective of long-term trends and short-term changes. The results showed that the EKC passed the inflection point for both China’s entire manufacturing industry and manufacture of nonmetallic mineral product subsector (MNM), but not in the other four main subsectors from 1995 to 2017. Strong decoupling, weak decoupling, and expansive coupling were observed between CO2 emissions and the value added in China’s entire manufacturing industry, in which weak decoupling accounted for the largest proportion. The decoupling index showed a downward trend on the whole. The decoupling status of subsectors from 1995 to 2017 was mainly weak decoupling, but different subsectors also showed characteristics of differentiation. At present, integrating EKC with decoupling has only occurred across the entire manufacturing industry and MNM. This study will provide suggestions for carbon reductions in China and will enrich the assessment methods of sustainable development.

Influencing Factors and Decoupling Analysis of Carbon Emissions in China's Manufacturing Industry

2021 ◽  
Author(s):  
baoling jin ◽  
ying Han
Keyword(s):  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Energy Intensity ◽  
Value Added ◽  
Carbon Intensity ◽  
Energy Structure ◽  
Investment Efficiency ◽  
Fixed Asset ◽  
Carbon Productivity ◽  
Fixed Asset Investment

Abstract The manufacturing industry directly reflects national productivity, and it is also an industry with serious carbon emissions, which has attracted wide attention. This study decomposes the influential factors on carbon emissions in China’s manufacturing industry from 1995 to 2018 into industry value added (IVA), energy consumption (E), fixed asset investment (FAI), carbon productivity (CP), energy structure (EC), energy intensity (EI), investment carbon intensity (ICI) and investment efficiency (IE) by Generalized Divisia Index Model (GDIM). The decoupling analysis is carried out to investigate the decoupling states of the manufacturing industry under the pressure of "low carbon" and "economy.” Considering the technological heterogeneity, we study the influential factors and decoupling status of the light industry and the heavy industry. The results show that: (1) Carbon emissions of the manufacturing industry present an upward trend, and the heavy industry is the main contributor. (2) Fixed asset investment (FAI), industry value added (IVA) are the driving forces of carbon emissions. Investment carbon intensity (ICI), carbon productivity (CP), investment efficiency (IE), and energy intensity (EI) have inhibitory effects. The impact of the energy consumption (E) and energy structure (EC) are fluctuating. (3) The decoupling state of the manufacturing industry has improved. Fixed asset investment (FAI), industry value added (IVA) hinder the decoupling; carbon productivity (CP), investment carbon intensity (ICI), investment efficiency (IE), and energy intensity (EI) promote the decoupling.

scholarly journals Probing the carbon emissions in 30 regions of China based on symbolic regression and Tapio decoupling

2021 ◽  
Author(s):  
Haiying Liu ◽  
zhiqun zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Symbolic Regression ◽  
Car Ownership ◽  
Emissions Reduction ◽  
Policy Recommendations ◽  
The World ◽  
Urbanization Rate

Abstract Against the background of energy shortages and severe air pollution, countries around the world are aware of the importance of energy conservation and emissions reduction; China is actively achieving emissions reduction targets. In this study, we use a symbolic regression to classify China's regions according to the degree of influencing factors, and calculate and analyze the inherent decoupling relationship between carbon emissions and economic growth in each region. Based on our results, we divided the 30 regions of the country into six categories according to the main influencing factors: GDP (13 regions), energy intensity (EI; 7 regions), industrial structure (IS; 3 regions), urbanization rate (UR; 3 regions), car ownership (CO; 2 regions), and household consumption level (HCL; 2 regions). Then, according to the order of the average carbon emissions in each region from high to low, these regions were further categorized as type-EI, type-UR, type-GDP, type-IS, type-CO, or type-HCL regions. The decoupling index of each region showed a downward trend; EI and GDP regions were the most notable contributors to emissions, based on which we provide policy recommendations.

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