2015Economic GeographyRequires access

The Decomposition Analysis for Hebei's Industrial Carbon Intensity Based on Industry and Energy

Wang Shao-hu

Open publisher page 2 citations

Abstract

To discuss the contribution of industrial structure and energy structure to Hebei's carbon intensity, two decomposition models of carbon intensity are built, based on the industry and energy respectively, with Logarithmic Mean Weight Divisia(LMD) method. Then, there is an empirical analysis on the characteristics of Hebei's carbon intensity for the overall, the first industrial, the second industry and the tertiary industry in 2000-2012. Results show that Hebei's overall carbon intensity or industrial carbon intensity has declined year by year basically since 2000. While the energy intensity has obvious inhibiting effect on the overall carbon intensity and industrial carbon intensity, the contribution direction of the structure factors is not stable. In detail, the industrial structure shows the sign of weak inhibiting effect on the overall carbon intensity, and the energy consumption structure shows more and more prominent inhibiting effect on the first industry carbon intensity, subtle inhibiting effect on the second industry, as well as significant promoting effect on the tertiary industry. The contribution potential of the structure factors is large, so optimizing the structure is needed to further reduce Hebei's carbon intensity.

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What this paper is about

To discuss the contribution of industrial structure and energy structure to Hebei's carbon intensity, two decomposition models of carbon intensity are built, based on the industry and energy respectively, with Logarithmic Mean Weight Divisia(LMD) method. Then, there is an empirical analysis on the characteristics of Hebei's carbon intensity for the overall, the first industrial, the second industry and the tertiary industry in 2000-2012. Results show that Hebei's overall carbon intensity or industrial carbon intensity has declined year by year basically since 2000. While the energy intensity has obvious inhibiting effect on the overall carbon intensity and industrial carbon intensity, the contribution direction of the structure factors is not stable. In detail, the industrial structure shows the sign of weak inhibiting effect on the overall carbon intensity, and the energy consumption structure shows more and more prominent inhibiting effect on the first industry carbon intensity, subtle inhibiting effect on the second industry, as well as significant promoting effect on the tertiary industry. The contribution potential of the structure factors is large, so optimizing the structure is needed to further reduce Hebei's carbon intensity.

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Available abstract

To discuss the contribution of industrial structure and energy structure to Hebei's carbon intensity, two decomposition models of carbon intensity are built, based on the industry and energy respectively, with Logarithmic Mean Weight Divisia(LMD) method. Then, there is an empirical analysis on the characteristics of Hebei's carbon intensity for the overall, the first industrial, the second industry and the tertiary industry in 2000-2012. Results show that Hebei's overall carbon intensity or industrial carbon intensity has declined year by year basically since 2000. While the energy intensity has obvious inhibiting effect on the overall carbon intensity and industrial carbon intensity, the contribution direction of the structure factors is not stable. In detail, the industrial structure shows the sign of weak inhibiting effect on the overall carbon intensity, and the energy consumption structure shows more and more prominent inhibiting effect on the first industry carbon intensity, subtle inhibiting effect on the second industry, as well as significant promoting effect on the tertiary industry. The contribution potential of the structure factors is large, so optimizing the structure is needed to further reduce Hebei's carbon intensity.

Key concepts: Energy intensity, Divisia index, Intensity (physics), Carbon fibers, Decomposition, Environmental science, Energy (signal processing), Mathematics

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