Embodied Carbon Emissions in Export of Yangtze River Delta: Calculation and Decomposition of Driving Factors
Abstract
:1. Introduction
- This paper takes the Yangtze River Delta as the research object to conduct detailed measurement and in-depth analysis, which not only helps to alleviate the prominent problem of embodied carbon emissions in this region but also provides abundant data from the region. As a matter of fact, analysis of the embodied carbon emissions from China’s exports is useful for international consideration of carbon emissions from China.
2. Literature Review
2.1. Review
2.2. Research Gap
3. Methodology
3.1. Problem Statement
3.2. Notation List
3.3. Mathematical Model
3.3.1. Input–Output Analysis
3.3.2. LMDI Method
4. Results and Discussions
4.1. Comparison of Embodied Carbon Emission among Different Regions in the Yangtze River Delta
4.2. Comparison of the Driving Factors among Different Regions in the Yangtze River Delta
5. Conclusions and Outlook
5.1. Conclusions
- The overall export embodied carbon emissions are highly consistent with the export value. It indicates that as the scale of exports continues to expand, more carbon dioxide gas stays in the country, causing a broken environment in the Yangtze River Delta region. Since 2013, embodied carbon emissions have been decreasing, mainly due to carbon emission reduction measures. However, overall, the embodied carbon emissions from exports account for approximately 15% of the total carbon emissions in the region, which is still at a high level.
- Shanghai has been at the forefront of resource conservation, technological innovation and industrial structure optimization. The export scale of Zhejiang has been growing steadily. As e-commerce in Zhejiang is developing rapidly, its processing trade share is low, and the share of embodied carbon emissions in exports continues to decline. The export structure of Jiangsu and Anhui is on the sloppy side. Therefore, it is necessary to optimize and upgrade the export structure and advocate technological innovation.
- The scale effect is positively related to the embodied carbon in exports. It is also the main reason for the significant growth in emissions. However, as the export size of the Yangtze River Delta is in a period of steady growth, the contribution of this effect gradually decreases. In comparison, the structural effect is relatively small and differs greatly depending on the period. The technology effect is the most important driving force of carbon-emission reduction, and its effect is becoming more and more obvious with the technology advance.
5.2. Policy Implications
- We need to implement the concept of green trade. High-tech industries should be encouraged to export. Financial support should be given to enterprises that use new energy to replace highly polluting fossil energy sources. Instead, stricter carbon emission standards are required for high polluters. They are encouraged to produce their own or switch to import. Companies should be classified into different levels of energy consumption and pollution so that the government can impose different carbon tariffs according to the different levels.
- It is necessary to optimize the structure of export commodities. The only way is to optimize the export structure and change the crude export mode to a green trade mode. Meanwhile, we should upgrade the quality of export products through technological innovation, guide the shift of export commodities to high value-added and low energy consumption and promote the gradual transformation of export industries to technology-intensive and resource-green industries.
- We need to encourage companies to engage in technological innovation. There is an urgent need to actively encourage the development of new technologies and give full play to the curbing effect of technology effects on the embodied carbon emissions of export. Specific measures are to increase technological innovation and make full use of highly skilled personnel, improve regional R&D, focus on high-tech industries and modern service exports and further stimulate the technology effect of emission reduction.
- Promoting the use of clean energy is also a necessary measure. The authority can increase the financial investment of intensive green clean energy such as natural gas and electricity. At the same time, they may actively promote the adoption of new green energy, such as wind, solar and biomass, increase the proportion of green energy consumption and take a low-carbon, clean and sustainable path of green development.
5.3. Limitation and Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Refs. | Method | Driving Factors | Case Study |
---|---|---|---|
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Machado et al. [2] | I-O | - | Brazil |
Chung and Rhee [3] | I-O | - | Korea-Japan trade |
Lenzen M [4] | I-O | - | Australia |
Zhang and Sun [17] | I-O | - | China |
Greening [18] | LMDI | Technology effect | 10 OECD countries |
Mukhopadhyay Kakali [5] | I-O | - | Indian foreign trade |
Peters Glen and Hertwich E.G [6] | LCA | - | Norway |
Shui Bin and Harriss Robert C [7] | EIO-LCA | - | US-China Trade |
Liu et al. [15] | LCA | - | China Export |
Ackerman et al. [16] | I-O | - | Japan-US trade |
Qi et al. [9] | I-O | - | Chinese foreign trade |
Zhu, Q [8] | I-O | - | Chinese Export |
Yan and Zhao [10] | I-O | - | Chinese Export |
Fu [21] | I-O | - | Chinese Export |
Yin [11] | I-O SDA | Direct carbon emission coefficient intermediate input structure export effect | Chinese Export |
Guo and Luo [14] | I-O | - | Yangtze River Economic Belt of China |
Huang et al. [12] | I-O LMDI | Scale effect structural effect intensity effect | Yangtze River Economic Belt of China |
Tong and Gao [19] | I-O LMDI | Scale effect structural effect technology effect | Jiangsu, China |
Zhao and Zheng [20] | I-O SDA | Intensity effect energy structural effect industrial structural effect demand scale effect | Yangtze River Delta of China |
This research | I-O LMDI | Scale effect structural effect technology effect | Yangtze River Delta of China |
Variable | Description |
---|---|
Index of sectors | |
Index of sectors | |
Index of energy source | |
Direct consumption coefficients: the value of sector that needs to be consumed directly by sector to produce a unit value of product | |
Matrix of (n × n square) | |
Total output matrix of each sector | |
End-use matrix of each sector | |
Unit matrix | |
Leontief inverse matrix | |
Intermediate use of by the sector | |
The total output of the sector | |
Complete consumption coefficients: total value of direct and indirect consumption of the sector required to produce a unit value of product in the sector | |
Matrix of | |
Direct carbon emission factor in sector | |
Total direct carbon emissions generated by sector | |
Matrix of direct carbon emission factors | |
Complete carbon emission factor matrix | |
Actual direct carbon emission factor matrix | |
Embodied carbon emissions from exports | |
Scale factor: total value of export | |
Structural factor: share of exports in sector | |
Technology factor: complete carbon emission factor in sector | |
Total embodied carbon from export in the base period | |
Total embodied carbon from export in period | |
Combined effect from base period to period t | |
Scale effect | |
Structural effect | |
Technology effect | |
CO2 emission factor from the energy source | |
Average low-level heat generation from the energy source | |
Carbon emission factor from the energy source |
Energy | Average Low-Level Heat Generation NCV (kJ/kg) | Carbon Emission Factor CC (kg/106 kJ) | Carbon Dioxide Emission Factor (kg-CO2/kg) |
---|---|---|---|
Raw coal | 20,908 | 26.32 | 2.02 |
washed refined coal | 26,344 | 26.32 | 2.54 |
Other coal washing | 12,545 | 26.32 | 1.21 |
Coal | 18,025 | 26.32 | 1.74 |
Coke | 28,435 | 31.38 | 3.27 |
Coke oven gas | 17,981 | 21.49 | 1.42 |
Crude oil | 41,816 | 20.08 | 3.08 |
Gasoline | 43,070 | 18.90 | 2.98 |
Kerosene | 43,070 | 19.60 | 3.10 |
Diesel | 42,652 | 20.20 | 3.16 |
Fuel oil | 41,816 | 21.10 | 3.24 |
Liquefied petroleum gas | 50,179 | 20.00 | 3.68 |
Refinery dry gas | 45,998 | 20.20 | 3.41 |
Natural gas | 38,931 | 15.32 | 2.19 |
Shanghai | Jiangsu | Zhejiang | Anhui | ||
---|---|---|---|---|---|
Stage 1 | 1095.21 | 4180.56 | 2266.14 | 274.67 | |
2992.72 | 4238.08 | 2694.29 | 478.65 | ||
8.49 | 353.71 | 101.98 | −40.28 | ||
−1906.00 | −411.23 | −530.13 | −163.70 | ||
Stage 2 | 520.88 | 370.72 | 20.44 | 234.09 | |
3797.06 | 7104.50 | 3802.47 | 831.07 | ||
142.84 | 291.68 | −92.98 | 22.49 | ||
−3419.03 | −7025.46 | −3689.05 | −619.47 | ||
Stage 3 | 475.38 | −2035.10 | −646.65 | 71.60 | |
952.36 | 362.13 | 937.17 | 461.78 | ||
−262.62 | 210.23 | −38.82 | −94.95 | ||
−214.36 | −2607.47 | −1545.00 | −295.23 |
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Tong, X.; Gu, Y.; Jin, T.; Gao, S. Embodied Carbon Emissions in Export of Yangtze River Delta: Calculation and Decomposition of Driving Factors. Sustainability 2022, 14, 12415. https://doi.org/10.3390/su141912415
Tong X, Gu Y, Jin T, Gao S. Embodied Carbon Emissions in Export of Yangtze River Delta: Calculation and Decomposition of Driving Factors. Sustainability. 2022; 14(19):12415. https://doi.org/10.3390/su141912415
Chicago/Turabian StyleTong, Xia, Yutong Gu, Tingting Jin, and Shenrong Gao. 2022. "Embodied Carbon Emissions in Export of Yangtze River Delta: Calculation and Decomposition of Driving Factors" Sustainability 14, no. 19: 12415. https://doi.org/10.3390/su141912415