scholarly journals Dynamic Input–Output Analysis of a Carbon Emission System at the Aggregated and Disaggregated Levels: A Case Study in the Northeast Industrial District

2020 ◽  
Vol 12 (7) ◽  
pp. 2708
Author(s):  
Hongkuan Zang ◽  
Lirong Zhang ◽  
Ye Xu ◽  
Wei Li

Research on carbon emissions of complex interactive activities in urban agglomerations is one of the hotspots of global climate change research. A comprehensive analysis of the urban agglomeration system’s carbon emissions is essential to reveal strategies for reduction and support sustainable development. The objective of this research is to develop an integrated carbon emission network model to explore the impact of different energy types on the Northeast Industrial District (NID), China. Four representative energy groups are considered. Specifically, at the aggregated sector-level, this research quantified the relative contributions of socioeconomic factors to carbon emission changes using structural decomposition analysis and examined the system efficiency and redundancy through robustness analysis. At the disaggregated level, the research investigated carbon emissions of different sectors from production-based, consumption-based, and income-based viewpoints. Moreover, emissions from specific categories of final demand and primary input were quantified. It was found that the increase of final demand level will proceed to push up the carbon emissions of the NID. Changing the production structure contributes to reducing emissions. The carbon emissions system has a high redundancy and low efficiency, illustrating that there are many emission pathways within the system. In addition, the use of crude oil significantly increases system redundancy and inhibits system efficiency. However, the major limitation of the model is that the long-term changes of the system are not considered. Moreover, considering the actual policies, emission reduction simulations could be added in the future.

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Guoxing Zhang ◽  
Mingxing Liu

Based on 2002–2010 comparable price input-output tables, this paper first calculates the carbon emissions of China’s industrial sectors with three components by input-output subsystems; next, we decompose the three components into effect of carbon emission intensity, effect of social technology, and effect of final demand separately by structure decomposition analysis; at last, we analyze the contribution of every effect to the total emissions by sectors, thus finding the key sectors and key factors which induce the changes of carbon emissions in China’s industrial sectors. Our results show that in the latest 8 years five departments have gotten the greatest increase in the changes of carbon emissions compare with other departments and the effect of final demand is the key factor leading to the increase of industrial total carbon emissions. The decomposed effects show a decrease in carbon emission due to the changes of carbon emission intensity between 2002 and 2010 compensated by an increase in carbon emissions caused by the rise in final demand of industrial sectors. And social technological changes on the reduction of carbon emissions did not play a very good effect and need further improvement.


2020 ◽  
Vol 12 (21) ◽  
pp. 8966
Author(s):  
Jinpeng Liu ◽  
Delin Wei

Faced with the environmental pressure of global warming, China has achieved certain results in emission reduction, but this needs to be completed more efficiently. Therefore, this article conducts a more comprehensive and in-depth study of China’s carbon emissions from the perspective of the development of national economic sectors and taps the potential for emission reduction in various sectors. Taking into account the adjustment of the national economic sector and the current status of carbon emissions, the study period was from 2003 to 2017. The logarithmic mean Divisia index (LMDI) method was used to measure and analyze the impact of seven factors, including urban construction conditions, on the carbon emissions of various sectors. According to the commonalities and differences of the impacts, 42 sectors were aggregated into four categories. At the same time, the input–output structure decomposition analysis (IO–SDA) model was used to analyze the spillover effects of intersectoral carbon emissions. According to the research results, based on the characteristics of the four types of sectors, and fully considering the spillover effects, the improvement of life cycle management to control energy consumption in the entire supply chain was taken as the leading idea. Moreover, combined with the actual development situation, four types of sectoral carbon emission reduction paths and optimization strategies are proposed to establish a more sustainable demand structure in order to achieve emission reduction.


2016 ◽  
Vol 29 (2) ◽  
pp. 137-153 ◽  
Author(s):  
Jayanthi Kumarasiri ◽  
Christine Jubb

Purpose The purpose of this paper is to apply regulatory mix theory as a framework for investigating the use of management accounting techniques by Australian large listed companies in constraining their carbon emissions. Design/methodology/approach Semi-structured interviews are conducted with senior managers involved with managing their companies’ carbon emission risks. Analysis of the interview data is undertaken with a view to provision of insight to the impact of the regulatory framework imposed to deal with carbon emissions. Findings The findings reveal that regulation impacting companies’ economic interests rather than requiring mere disclosure compliance is much more likely to be behind focusing top management and board attention and use of management accounting techniques to set targets, measure performance and incentivise emission mitigation. However, there remains much scope for increased use of accounting professionals and accounting techniques in working towards a carbon-constrained economy. Research limitations/implications The usual limitations associated with interpretation of interview data are applicable. Practical implications Under-use of management accounting techniques is likely to be associated with less than optimal constraint of carbon emissions. Social implications Carbon emissions are accepted as being involved in harmful climate change. To the extent effective techniques are under-utilised in constraining emissions, harmful consequences for society are likely to be heightened unnecessarily. Originality/value The topic and data collected are original and provide valuable insights into the dynamics of management accounting technique use in managing carbon emissions.


2019 ◽  
Vol 11 (16) ◽  
pp. 4387 ◽  
Author(s):  
Lin ◽  
Zhang ◽  
Wang ◽  
Yang ◽  
Shi ◽  
...  

The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the basis of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution routes with and without carbon emissions cost are constructed. Fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit.


2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Jing-min Wang ◽  
Yu-fang Shi ◽  
Xue Zhao ◽  
Xue-ting Zhang

Beijing-Tianjin-Hebei is a typical developed region in China. The development of economy has brought lots of carbon emissions. To explore an effective way to reduce carbon emissions, we applied the Logarithmic Mean Divisia Index (LMDI) model to find drivers behind carbon emission from 2003 to 2013. Results showed that, in Beijing, Tianjin, and Hebei, economic output was main contributor to carbon emissions. Then we utilized the decoupling model to comprehensively analyze the relationship between economic output and carbon emission. Based on the two-level model, results indicated the following: (1) Industry sector accounted for almost 80% of energy consumption in whole region. The reduced proportion of industrial GDP will directly reduce the carbon emissions. (2) The carbon factor for CO2/energy in whole region was higher than that of Beijing and Tianjin but lower than that of Hebei. The impact of energy structure on carbon emission depends largely on the proportion of coal in industry. (3) The energy intensity in whole region decreased from 0.79 in 2003 to 0.40 in 2013 (unit: tons of standard coal/ten thousand yuan), which was lower than national average. (4) The cumulative effects of industrial structure, energy structure, and energy intensity were negative, positive, and negative, respectively.


2021 ◽  
Vol 13 (20) ◽  
pp. 11138
Author(s):  
Huan Zhang

This study selects the panel data of five BRICS nations (Brazil, Russia, India, China, South Africa) from 1990 to 2019 to empirically explore the impact of technological innovation and economic growth on carbon emissions under the context of carbon neutrality. Granger causality test results signify that there exists a one-way causality from technology patent to carbon emission and from economic growth to carbon emission. We also constructed an improved Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The regression results manifest that technology patents contribute to the realization of carbon emission reduction and carbon neutralization, while the economic growth of emerging economies represented by BRICS countries significantly improves carbon emissions, but every single BRICS country shows differentiated carbon emissions conditions with their economic development stages. The impact of the interaction term on carbon emissions for the five BRICS countries also presents country-specific heterogeneity. Moreover, the Environmental Kuznets Curve (EKC) test results show that only Russia and South Africa have an inverted U-shaped curve relationship between economic growth and carbon emissions, whereas Brazil, India and China have a U-shaped curve relationship. There exists no EKC relationship when considering BRICS nations as a whole. Further robustness tests also verify that the conclusions obtained in this paper are consistent and stable. Finally, the paper puts forward relevant policy suggestions based on the research findings.


Author(s):  
Jianli Sui ◽  
Wenqiang Lv

Modern agriculture contributes significantly to greenhouse gas emissions, and agriculture has become the second biggest source of carbon emissions in China. In this context, it is necessary for China to study the nexus of agricultural economic growth and carbon emissions. Taking Jilin province as an example, this paper applied the environmental Kuznets curve (EKC) hypothesis and a decoupling analysis to examine the relationship between crop production and agricultural carbon emissions during 2000–2018, and it further provided a decomposition analysis of the changes in agricultural carbon emissions using the log mean Divisia index (LMDI) method. The results were as follows: (1) Based on the results of CO2 EKC estimation, an N-shaped EKC was found; in particular, the upward trend in agricultural carbon emissions has not changed recently. (2) According to the results of the decoupling analysis, expansive coupling occurred for 9 years, which was followed by weak decoupling for 5 years, and strong decoupling and strong coupling occurred for 2 years each. There was no stable evolutionary path from coupling to decoupling, and this has remained true recently. (3) We used the LMDI method to decompose the driving factors of agricultural carbon emissions into four factors: the agricultural carbon emission intensity effect, structure effect, economic effect, and labor force effect. From a policymaking perspective, we integrated the results of both the EKC and the decoupling analysis and conducted a detailed decomposition analysis, focusing on several key time points. Agricultural economic growth was found to have played a significant role on many occasions in the increase in agricultural carbon emissions, while agricultural carbon emission intensity was important to the decline in agricultural carbon emissions. Specifically, the four factors’ driving direction in the context of agricultural carbon emissions was not stable. We also found that the change in agricultural carbon emissions was affected more by economic policy than by environmental policy. Finally, we put forward policy suggestions for low-carbon agricultural development in Jilin province.


2019 ◽  
Vol 31 (6) ◽  
pp. 961-982 ◽  
Author(s):  
Min Su ◽  
Shasha Wang ◽  
Rongrong Li ◽  
Ningning Guo

Cities play a major role in decoupling economic growth from carbon emission for their significant role in climate change mitigation from national level. This paper selects Beijing (economic center and leader of emission reduction in China) as a case to examine the decoupling process during the period 2000–2015 through a sectoral decomposition analysis. This paper proposes the decoupling of carbon emission from economic growth or sectoral output by defining the Tapio decoupling elasticity, and combined the decoupling elasticity with decomposition technique such as Logarithmic Mean Divisia Index approach. The results indicate that agriculture and industrial sectors presented strong decoupling state, and weak decoupling is detected in construction and other industrial sectors. Meanwhile, transport sector is in expansive negative decoupling while trade industry shows expansive coupling during the study period. Per-capita gross domestic product, industrial structure, and energy intensity are the most significant effects influencing the decoupling process. Agriculture and industry are conducive to decoupling of carbon emissions from economic output, while transport and trade are detrimental to the realization of strong decoupling target between 2000 and 2015. However, construction and other industrial sectors exerted relatively little minor impact on the whole decoupling process. Improving and promoting energy-saving technologies in transport sector and trade sector should be the key strategy adjustments for Beijing to reduce carbon emissions in the future. The study aims to provide effective policy adjustments for policy makers to accelerate the decoupling process in Beijing, which, furthermore, can lay a theoretical foundation for other cities to develop carbon emission mitigation polices more efficiently.


Author(s):  
Shiran Li ◽  
Hongbing Deng ◽  
Kangkang Zhang

The study of carbon emissions is of great significance for environmental change and economic development. Gender factors is an important perspective to examine the path of carbon emissions. Based on the panel data of 30 provinces in China from 2005 to 2016, this paper selects the optimal spatial measurement model structure by using the Bayesian posterior probability model structure selection method, and studies the impact of economy on carbon emissions and the influence mechanism of gender-based “synergy effect” on carbon emissions from the National level and regional levels. The research shows that the increase of economic promotes the increase of carbon emission in this region, but it has a restraining effect on the carbon emission in the surrounding areas. Moreover, gender factors have a significant positive effect on the region at the National level and the Eastern and Northeastern regions, but not significantly in other ones, and have a significant negative impact on carbon emissions in surrounding areas. Overall, the influence intensity of economy on carbon emission increases with the increase of gender in the National level and the Eastern and Northeastern, while the influence intensity of economy of peripheral regions on carbon emission in Central Region decreases with the increase of gender factors in peripheral regions.


Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shuping Cheng ◽  
Lingjie Meng ◽  
Lu Xing

PurposeThe purpose of this paper is to examine the effects of energy technological innovation on carbon emissions in China from 2001 to 2016.Design/methodology/approachConditional mean (CM) methods are first applied to implement our investigation. Then, considering the tremendous heterogeneity in China, quantile regression is further employed to comprehensively investigate the potential heterogeneous effect between energy technological innovation and carbon emission intensity.FindingsThe results suggest that renewable energy technological innovation has a significantly positive effect on carbon emission intensity in lower quantile areas and a negative effect in higher quantile areas. Contrarily, fossil energy technological innovation exerts a negative correlation with carbon emission intensity in lower quantile areas and a positive effect on carbon emission intensity in higher quantiles areas.Originality/valueConsidering that energy consumption is the main source of CO2 emissions, it is of great importance to study the impact of energy technological innovation on carbon emissions. However, the previous studies mainly focus on the impact of integrated technological innovation on carbon emissions, ignoring the impact of energy technological innovation on carbon emissions mitigation. To fill this gap, we construct an extended STIRPAT model to examine the effects of renewable energy technological innovation and fossil energy technological innovation on carbon emissions in this paper. The results can provide a reference for the government to formulate carbon mitigation policies.


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