Empirical Research on China’s Carbon Productivity Decomposition Model Based on Multi-Dimensional Factors

Abstract

Based on the international community's analysis of the present CO2 emissions situation, a Log Mean Divisia Index (LMDI) decomposition model is proposed in this paper, aiming to reflect the decomposition of carbon productivity. The model is designed by analyzing the factors that affect carbon productivity. China's contribution to carbon productivity is analyzed from the dimensions of influencing factors, regional structure and industrial structure. It comes to the conclusions that: (a) economic output, the provincial carbon productivity and energy structure are the most influential factors, which are consistent with China's current actual policy; (b) the distribution patterns of economic output, carbon productivity and energy structure in different regions have nothing to do with the Chinese traditional sense of the regional economic development patterns; (c) considering the regional protectionism, regional actual situation need to be considered at the same time; (d) in the study of the industrial structure, the contribution value of industry is the most prominent factor for China's carbon productivity, while the industrial restructuring has not been done well enough.

Refined Laspeyres Decomposition-Based Analysis of Relationship between Economy and Electric Carbon Productivity from the Provincial Perspective—Development Mode and Policy

“…Therefore, most provinces would like to build thermal power plants because of the short construction period, less initial investment, and less site selection constraints to meet the high electric demand. This phenomenon is consistent with certain published work, like References [11,25], which have pointed out the regional protectionism and the limited contribution of emissions' structures. From another angle, different provinces have different natural resources for power generation like coal and its products, water resources, and solar energy, etc., which might result in different power generation forms.…”

“…Xian et al applied the nonparametric directional distance function-based data envelopment analysis technique to carbon efficiency and productivity decomposition, and then evaluated the possibility of intensity reduction target in the 13th five-year plan through scenario design [10]. Lu et al [11] designed a multi-dimensional log man divisia index model to investigate carbon productivity and the influencing factors, regional structure and industrial structure. Chen et al [12] investigated the effect of impacts factors on electric carbon productivity change, based on logarithmic mean divisia index decomposition technique.…”

Factors Affecting Energy‐Related Carbon Emissions in Beijing‐Tianjin‐Hebei Region

“…The integration of BeijingTianjin-Hebei region has become a major national strategy, defining its function of the area as world-class city group with the core of capital. The gradual expansion of economic scale in Beijing-Tianjin-Hebei region gives impetus to the augmentation of energy consumption and carbon emissions [2,3], which directly lead to low economic benefits, environmental pollution, and other problems [4]. The industrial transition is imperative and the optimization of energy structure is urgent.…”

Assessment Analysis and Forecasting for Security Early Warning of Energy Consumption Carbon Emissions in Hebei Province, China

“…By decomposing the carbon productivity, it can be found that due to the energy consumption growth, increased carbon emissions have become an increasingly important factor which threatens the success of countries all over the world to achieve sustainable development goals due to the energy consumption growth [2]. At present, energy consumption carbon emissions (ECCE) are a practical issue which runs through the political, economy, social and other fields more than a scientific problem.…”