Carbon quota allocation at the provincial level in China under principles of equity and efficiency

Yang, Baochen; Li, Xinting; Su, Yunpeng; Liu, Chuanze; Xue, Fangzhan

doi:10.1080/17583004.2019.1682755

Cited by 23 publications

(7 citation statements)

References 32 publications

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“…The initial allocation of carbon emission rights in the primary market affects the pricing of the secondary market and the normal operation of the carbon trading market. How to allocate the building carbon emission rights fairly and reasonably needs in-depth consideration, which many scholars have studied (Yang et al 2019) Initially, the studies on carbon emission allocation were mainly based on a single principle, starting from the perspective of fairness or efficiency. For example, Pan et al proposed a distribution scheme based on the principle of equal cumulative emissions per capita (Pan et al 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Carbon Allowance Allocation for Public Buildings in China Based on the Target of Carbon Emission Intensity Reduction in 2030

Zhang

Liu

2023

Preprint

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Due to the increasing energy crisis and climate warming, carbon emission reduction has attracted the attention of all countries. Carbon trading is an effective way to reduce carbon emissions. As one of the three major carbon emitters, the construction sector urgently needs to establish and improve the construction carbon trading market. Since the allocation of carbon emission rights is the first step to carbon trading, it is necessary to reasonably allocate carbon emissions to each province. This paper establishes a set of carbon emission allocation methods based on the principles of equity, efficiency, historical responsibility, emission reduction capacity and environmental level according to the relative emission reduction action target of 2030 proposed by the Chinese government. Correspondingly, urban population, carbon emission efficiency calculated by DEA model, historical cumulative CO2 emissions, ratio of R&D expenditure to GDP and forest coverage are selected as indicators and the entropy weight method is applied to allocate the amount of CO2. Taking the achievement of China's carbon peak target as an example, carbon emission quotas for public buildings in 2030 were calculated for each province. After verification of Gini coefficient and contribution coefficient, the allocation scheme is derived to be compatible with the economy, population and environment. The results show that the CO2 allocation shows a trend of gradual decrease from southeast to northwest, with Guangdong and Jiangsu having the highest carbon quotas and Qinghai and Xinjiang having the lowest. 33.3% of the provinces are under pressure to reduce emissions, with Xinjiang having the highest pressure to reduce emissions, and economically developed regions like Beijing, Zhejiang and Guangdong still face some pressure to reduce emissions. Finally, the allocation method proposed in this paper can be used as a reference for the building sector, and the allocation scheme can help policy makers in each province to formulate an effective and differentiated emission reduction strategy that ensure the successful achievement of emission reduction targets.

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Section: Literature Reviewmentioning

confidence: 99%

Research on Carbon Allowance Allocation for Public Buildings in China Based on the Target of Carbon Emission Intensity Reduction in 2030

Zhang

Liu

2023

Preprint

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“…The multiobjective optimization method has been increasingly applied, such as Xu et al [38], who used a three-level multiobjective approach to optimize carbon emission allowances in the power supply sector from three aspects, namely, government, power plants and grid companies, and an interactive genetic algorithm based on Karush-Kuhn-Tucker (KKT) conditions was employed to determine the equilibrium point. Yang et al [39] used the carbon Gini coefficient and abatement cost function to measure fairness and efficiency, respectively. A multiobjective nonlinear programming model was then introduced to realize optimal emission allowance allocation.…”

Section: Current Status Of Research On Carbon Quota Allocationmentioning

confidence: 99%

Multiobjective Optimization of Carbon Emission Reduction Responsibility Allocation in the Open-Pit Mine Production Process against the Background of Peak Carbon Dioxide Emissions

Wang

Zhang

2022

Sustainability

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In the context of the “carbon peaking” policy for mining companies, this study was conducted to clarify the amount of carbon emission reduction required for each production process to achieve the carbon peaking target for mining companies. In this paper, after determining the fair interval of the carbon emission distribution, the fair deviation index was constructed, and a multiobjective carbon emission distribution model of the mine production process was established by combining the objectives of maximum stability and maximum efficiency with the constraint of output growth. The study found: (1) More carbon emission quotas should be allocated to the beneficiation link, while fewer carbon emission quotas should be allocated to the crushing link; (2) beneficiation, mining and transportation are all responsible for emission reduction, but crushing and blasting produced a carbon emission surplus and (3) after optimization, the carbon emission intensity in the beneficiation, mining and transportation processes was reduced. This paper argues that mining companies should increase their efforts to reduce emissions in beneficiation, mining and transportation. The study’s findings have important implications for achieving carbon emission reduction targets and refining carbon emission management in open pit mines in the context of carbon peaking.

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“…Following the efficiency principle will maximize the total benefits but may increase the inequality in carbon emissions (Hubacek et al 2017 ). Therefore, after considering the equity and efficiency principles integrally, some scholars have gradually changed their views from single principle and single perspective of carbon allocation to multi-principles and multi-perspectives (Chen et al 2020b ; Yang et al 2020 ; Zhou et al 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county

Yang

Shi

Wang

et al. 2022

Environ Sci Pollut Res

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County is the center of China’s socio-economic development and the key node for urban–rural integration. Also, the county is an important carrier for promoting urban and rural green development. Improving green and low-carbon development capabilities and formulating county-level low-carbon standards will play a significant role in promoting China’s new people-oriented urbanization and rural revitalization. Although there have been extensive studies on low-carbon benchmarks, over half of the benchmarks tend to ignore the development stage of the evaluated region and its needs. When the region’s economy reaches a certain level, constraints from low-carbon targets may limit the local development process. This study firstly allocated county carbon intensity reduction targets (CIRT) by considering the differences in county carbon reduction capacity and responsibility. Secondly, a dynamic benchmark system of per capita carbon emissions (PCCE) in counties in China is constructed. Finally, we took Changxing County in Zhejiang Province as a research case to verify the dynamic benchmark of PCCE. According to the carbon intensity target reduction rate (CITRR), China’s counties can be divided into three categories: low carbon emissions reduction capability-responsible counties (L-CERCRC), medium carbon emissions reduction capability-responsible counties (M-CERCRC), and high carbon emissions reduction capability-responsible counties (H-CERCRC). The results show that (1) due to the national CO 2 emission reduction target in 2030, the carbon intensity will be 60% lower than in 2005, the CITRR for China’s 1510 counties range from 8.36 to 137.83%; the average CITRR is 48.40%. (2) Changxing County’s CITRR is 57.71%, which belongs to the H-CERCRC. The PCCE of Changxing County will be much higher than the benchmark when the carbon peak is reached in the future. (3) For reaching the aiming benchmark, Changxing County is suggested to adjust its relevant influencing factors of PCCE for converting local’s PCCE reaching to the benchmark within a certain time period. The dynamic benchmark system for PCCE in China’s counties established in this study is economically sensitive, which not only takes the differences of counties into account, but also meets the needs of counties’ diverse development form stages. This system provides counties a few coordinated directions which can improve the local’s economic development and reduce greenhouse gas (GHGs) emissions through the development progress.

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Carbon quota allocation at the provincial level in China under principles of equity and efficiency

Cited by 23 publications

References 32 publications

Research on Carbon Allowance Allocation for Public Buildings in China Based on the Target of Carbon Emission Intensity Reduction in 2030

Research on Carbon Allowance Allocation for Public Buildings in China Based on the Target of Carbon Emission Intensity Reduction in 2030

Multiobjective Optimization of Carbon Emission Reduction Responsibility Allocation in the Open-Pit Mine Production Process against the Background of Peak Carbon Dioxide Emissions

Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county

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