Carbon Reduction Potential of Resource-Dependent Regions Based on Simulated Annealing Programming Algorithm

Abstract

In recent years, developing countries, especially resource-dependent regions, have been facing the paradox of ensuring both emissions reduction and economic development. Thus, there is a strong political desire to forecast carbon emissions reduction potential and the best way to achieve it. This study constructs a methodology to assess carbon reduction potential in a resource-dependent region. The Simulated Annealing Programming algorithm and the Genetic algorithm were introduced to create a prediction model and an optimized regional carbon intensity model, respectively. Shanxi Province in China, a typical resource-dependent area, is selected for the empirical study. Regional statistical data are collected from 1990 to 2015. The results show that the carbon intensity of Shanxi Province could drop 18.78% by 2020. This potential exceeds the 18% expectation of the Chinese Government in its '13th Five-Year Work Plan' for Controlling Greenhouse Gas Emissions. Moreover, the carbon intensity of the province could be further reduced by 0.97 t per 10,000 yuan GDP. The study suggests that the carbon emissions of a resource-dependent region can be reduced in the following ways; promoting economic restructuring, upgrading coal supply-side reform, perfecting the self-regulation of coal prices, accelerating the technical innovation of the coal industry, and establishing a flexible mechanism for reducing emissions.

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“…It implies that strong leadership with rigid regulation on air pollution may lead the private sector to participate in a more effective manner. In the study to assess carbon reduction potential in the heavily resource-dependent Shanxi Province in China from 1990 to 2015, Li et al concluded that the carbon intensity could drop by 18.78% by 2020 [12]. This potential exceeds the 18% expectation of the Chinese government in its '13th Five-Year Work Plan' for controlling GHG emissions.…”

“…Unfortunately, this regulation on the carbon intensity of the province could further be reduce by 0.97 GHG ton per 10,000 yuan GDP. Due to this reduction on the local GDP, they suggested a flexible mechanism for reducing emissions, instead of the too strong and rigid regulation [12]. In order to examine the relationship between Beijing's urbanization efficiency and economic growth rate over time, Qi et al developed a comprehensive index system for assessing Beijing's economic growth rate and urbanization efficiency at the district (county) level for the period 2005-2014 [13].…”

“…This could happen, especially in China, due to the strong government leadership of the Communist party. Certainly, there have been many studies which have shown the effective role of regulation by the Chinese government for sustainable development [11][12][13][14].…”