Optimal strategies for carbon reduction at dual levels in China based on a hybrid nonlinear grey-prediction and quota-allocation model

Wang, Xingwei; Cai, Yanpeng; Xu, Y. Jun; Zhao, Huazhang; Chen, Jiajun

doi:10.1016/j.jclepro.2014.07.015

Cited by 41 publications

(16 citation statements)

References 40 publications

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“…The metabolic grey model (MGM), metabolic residual-error grey model (MREGM), and the metabolic Markov-residual-error grey model (MMREGM) were proposed by Chen [13] and used to predict the capacity of lithium-ion batteries in relation to discharge cycles throughout their lifetimes. The GM (1, 1) model is currently one of the most widely used grey prediction models for predicting carbon emissions [14,15].…”

Section: Introductionmentioning

confidence: 99%

Trend Prediction and Decomposed Driving Factors of Carbon Emissions in Jiangsu Province during 2015–2020

Tang

et al. 2016

Sustainability

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According to the economic and energy consumption statistics in Jiangsu Province, we combined the GM (1, 1) grey model and polynomial regression to forecast carbon emissions. Historical and projected emissions were decomposed using the Logarithmic Mean Divisia Index (LMDI) approach to assess the relative contribution of different factors to emission variability. The results showed that carbon emissions will continue to increase in Jiangsu province during 2015-2020 period and cumulative carbon emissions will increase by 39.5487 million tons within the forecast period. The growth of gross domestic product (GDP) per capita plays the greatest positive role in driving carbon emission growth. Furthermore, the improvement of energy usage efficiency is the primary factor responsible for reducing carbon emissions. Factors of population, industry structure adjustment and the optimization of fuel mix also help to reduce carbon emissions. Based on the LMDI analysis, we provide some advice for policy-makers in Jiangsu and other provinces in China.

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Section: Introductionmentioning

confidence: 99%

Trend Prediction and Decomposed Driving Factors of Carbon Emissions in Jiangsu Province during 2015–2020

Tang

et al. 2016

Sustainability

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“…In those studies, a wide spectrum of optimization techniques were used, such as linear programming, non-linear programming, dynamic programming, mixed-integer programming, and multi-objective programming. Among these methods, linear programming-based methods have been extensively used due to their high computational efficiency and easy application to large-scale problems [11][12][13][14][15]. The management of agricultural land and water resources is a complex problem with multi-faceted implications on the economy, society and eco-environment.…”

Section: Introductionmentioning

confidence: 99%

Optimal Use of Agricultural Water and Land Resources through Reconfiguring Crop Planting Structure under Socioeconomic and Ecological Objectives

Tan

Shan

2017

Water

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Many economic, social and ecological problems can be attributed to the scarcity and mismanagement of water and land resources. In this study, a multi-objective fuzzy-robust programming (MOFRP) method was developed for supporting the optimal use of land and water resources in agriculture. MOFRP improved existing methods through taking ecological services of crop cultivation into account. It was also capable of reflecting fuzziness in preferences, priorities and parameters that were largely neglected in previous agricultural decision making. This method was applied to address a case in arid northwestern China. Optimal plans of crop cultivation reconfiguration were generated for sustaining local development under economic, ecological and social objectives as well as physical restraints in water and land resources. Compared to the status quo, the optimized plan would increase economic and ecological benefits by 12.2% and 18.8%, respectively. The efficiency of irrigation water could also be enhanced with the economic and ecological benefits per unit water being raised and the water consumption per unit land being reduced. The comparisons of the MOFRP model to four alternatives validated that it was capable of achieving satisfactory benefits and reducing system-violation risks without neglecting valuable uncertain information and ecological services of crops. The proposed method was also applicable to other multi-objective management problems under uncertainty without loss of generality.

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“…Liao et al employed benchmark, grandfathering, and the Shapley value to simulate the initial allocation of Shanghai carbon emissions trading [28]. Wang et al developed a hybrid nonlinear grey-prediction and quota allocation model which have proved helpful to the carbon emissions reduction in China at both departmental and provincial levels [29]. Zhou et al proposed an interprovincial emissions reduction quota trading scheme in China and proved the feasibility by simulating its economic performance [30].…”

Section: Introductionmentioning

confidence: 99%

Impact of Carbon Quota Allocation Mechanism on Emissions Trading: An Agent-Based Simulation

Jiang

Liu

2016

Sustainability

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This paper establishes an agent-based simulation system of the carbon emissions trading in accordance with the complex feature of the trading process. This system analyzes the impact of the carbon quota allocation mechanism on emissions trading for three different aspects including the amount of emissions reduction, the economic effect on the emitters, and the emissions reduction cost. Based on the data of the carbon emissions of different industries in China, several simulations were made. The results indicate that the emissions trading policy can effectively reduce carbon emissions in a perfectly competitive market. Moreover, by comparing separate quota allocation mechanisms, we obtain the result that the scheme with a small extent quota decrease in a comprehensive allocation mechanism can minimize the unit carbon emission cost. Implementing this scheme can also achieve minimal effects of carbon emissions limitation on the economy on the basis that the environment is not destroyed. However, excessive quota decrease cannot promote the emitters to reduce emission. Taking into account that several developing countries have the dual task of limiting carbon emissions and developing the economy, it is necessary to adopt a comprehensive allocation mechanism of the carbon quota and increase the initial proportion of free allocation.

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Optimal strategies for carbon reduction at dual levels in China based on a hybrid nonlinear grey-prediction and quota-allocation model

Cited by 41 publications

References 40 publications

Trend Prediction and Decomposed Driving Factors of Carbon Emissions in Jiangsu Province during 2015–2020

Trend Prediction and Decomposed Driving Factors of Carbon Emissions in Jiangsu Province during 2015–2020

Optimal Use of Agricultural Water and Land Resources through Reconfiguring Crop Planting Structure under Socioeconomic and Ecological Objectives

Impact of Carbon Quota Allocation Mechanism on Emissions Trading: An Agent-Based Simulation

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