The Drivers of China’s Regional Carbon Emission Change—A Structural Decomposition Analysis from 1997 to 2007

Yang, Ling; Lahr, Michael L.

doi:10.3390/su11123254

Cited by 8 publications

(4 citation statements)

References 34 publications

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“…The choice of carbon emission coefficients for energy sources also impacts the estimation results. Yang and Lahr [22], based on IPCC (Intergovernmental Panel on Climate Change) coefficients, calculated the adjusted emission coefficients for China, and we adopt their results (as shown in Table 1). Notes: The units for standard quantities are "10,000 tons/10,000 tons"; except for the physical quantities of Coke Oven Gas, Other Gas, and Natural Gas, which are "10,000 tons/100 million cubic meters", the units for physical quantities of all other energy sources are "10,000 tons/10,000 tons".…”

Section: Energy Consumption Amountsmentioning

confidence: 99%

The Carbon Emission Reduction Effects of the Quality and Quantity of R&D Activities: Evidence from Chinese Provinces

Li,

2024

Sustainability

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Research and Development (R&D) have significant impacts on carbon emissions, yet the specific data on R&D capital stock and carbon emissions have not been released by Chinese officials, hindering in-depth analysis. In light of this, this study calculates the R&D capital stock of Chinese provinces based on the SNA2008 framework and the BEA method, and estimates the carbon emissions from energy consumption and cement production using the carbon emission factor method. It then examines the carbon emission reduction effects of the quality and quantity of R&D activities at the provincial level. We find that the quality of R&D activities has a significant carbon emission reduction effect, which is stronger in regions with high levels of economic growth and marketization, and this effect strengthens over time. Moreover, mechanism analysis shows that both the quality and quantity of R&D activities reduce carbon emissions by promoting industrial structure upgrading. This paper expands the analytical approach and framework for the carbon reduction effects of R&D activities and offers significant policy and practical implications.

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Section: Energy Consumption Amountsmentioning

confidence: 99%

The Carbon Emission Reduction Effects of the Quality and Quantity of R&D Activities: Evidence from Chinese Provinces

Li,

2024

Sustainability

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“…Given the relationship between carbon emissions among various industries, clarifying the responsibilities of each industry and adjusting the industrial structure according to the responsibility for emissions reflect the fairness of emission reduction initiatives. Furthermore, the use of renewable energy and environmentally friendly materials is an important way of reducing the pressure around emission reduction in highly polluting industries and achieving a low-carbon development from a sustainability perspective [45].…”

Section: Conclusion and Policy Recommendationsmentioning

confidence: 99%

Embodied Carbon Emissions and Regional Transfer Characteristics—Evidence from China

2022

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China has a considerable impact on climate change, as it is the world’s largest developing country. Its carbon emissions are also a global concern. This research employed a multi-region input–output model to estimate the local emission effect and the regional spillover effect caused by the demand for intermediate and final products, to analyze the interregional flow of carbon emissions, and to identify the main industries causing domestic carbon emissions in China from 2007 to 2012. A structural path analysis model was used to evaluate the contribution of different factors and demand types to changes in carbon emissions. The following findings were obtained in this study: (1) The regional spillover effect of carbon emissions driven by domestic demand is characterized by inland provinces’ demand leading to emissions in coastal provinces. (2) Electricity, nonmetallic minerals, and metals are the key industries for carbon emissions. (3) The results of the SDA indicate that the scale effect is the main driving force for the growth in carbon emissions caused by domestic demand in China. Fixed capital formation is the most critical demand factor influencing carbon emissions. This study provides new insights into the characteristics of regional emission transfer in China. The conclusion of this paper is helpful to China in achieving carbon peak and carbon neutrality.

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“…Lu et al put forward an interval-fuzzy possibilistic programming (IFPP) method to optimize China's energy management system with CO 2 emission constraints [11]. Moreover, a number of economic research models have been used to study the relationship between upgrading the industrial structural and carbon dioxide emissions, such as the decomposition method [12], carbon entropy model [13], and total factor industrial carbon emission efficiency evaluation model [14]. When it comes to the prediction of industrial optimization, to predict the carbon intensity trends in Hangzhou city, Lu et al conducted the component data prediction, scenario prediction, GMI (1, 1) model and other multidisciplinary approaches [15].…”

Section: Introductionmentioning

confidence: 99%

Integrated Planning for Regional Development Planning with Low Carbon Development Constraint under Uncertainty: A Case Study of Qingpu District, Shanghai

Zhang

et al. 2021

Sustainability

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Regional development planning systems contain multiple uncertainties which come from economic restructuring, resource management, carbon peak action, environmental protection, and other factors, it is difficulty to handle all of these uncertainties in one method. In order to solve this problem, a new model developed in this study combines an interval fuzzy program with an environmental quality model for regional development planning in order to provide optimal solutions. The interval fuzzy program is put forward based on interval parameter programming (IPP) and fuzzy programing (FP). The environmental quality model is used to calculate water environmental capacity and atmospheric capacity, which are set as constraint conditions in the model. In order to meet the requirements of carbon peak action, a low carbon development constraint is added to the model. In this model, decision makers can choose the satisfaction level of constraints based on their preferences. The results suggest that the methodology is applicable for the regional development planning system within the planning period. The developed model can be used to generate a series of optimization schema under multiple credibility levels, ensuring that the regional development planning system can meet both societal demands and environmental quality requirements, considering a proper balance between the expected system benefits and risks of violating the resource constraint and low carbon development constraint.

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The Drivers of China’s Regional Carbon Emission Change—A Structural Decomposition Analysis from 1997 to 2007

Cited by 8 publications

References 34 publications

The Carbon Emission Reduction Effects of the Quality and Quantity of R&D Activities: Evidence from Chinese Provinces

The Carbon Emission Reduction Effects of the Quality and Quantity of R&D Activities: Evidence from Chinese Provinces

Embodied Carbon Emissions and Regional Transfer Characteristics—Evidence from China

Integrated Planning for Regional Development Planning with Low Carbon Development Constraint under Uncertainty: A Case Study of Qingpu District, Shanghai

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