Factor Decomposition Analysis of Energy-Related CO2 Emissions in Tianjin, China

Wang, Zhe; Zhao, Lin; Mao, Guozhu; Wu, Ben

doi:10.3390/su7089973

Cited by 19 publications

(9 citation statements)

References 34 publications

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“…Therefore, household share of total CO 2 emissions will continue to grow as these emerging economies are expected to make transitions to higher industrialization and higher income levels [21]. Given the strong prospects for continued rapid economic growth and higher future CO 2 emissions, a number of studies have explored key factors influencing changes of CO 2 emissions in the residential sector, with a special focus on China and India [11][12][13]22,23].…”

Section: The Logarithmic Mean Divisia Index (Lmdi) Methodsmentioning

confidence: 99%

“…Sustainability 2015, 7, In the case of China, Wang et al [22] decomposed China's CO 2 emissions at the regional level (focusing on Tianjin city) and concluded that income and population effects were the dominant positive factors affecting the growth in CO 2 emissions for all sectors. Zhao et al [13] concluded that price effects resulting from price deregulation in the energy sector contributed to reduction of energy consumption, and thus slowed down CO 2 emissions.…”

Section: The Logarithmic Mean Divisia Index (Lmdi) Methodsmentioning

confidence: 99%

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Driving Forces of CO2 Emissions in Emerging Countries: LMDI Decomposition Analysis on China and India’s Residential Sector

et al. 2015

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Abstract:The main objective of this paper is to identify and analyze the key drivers behind changes of CO 2 emissions in the residential sectors of the emerging economies, China and India. For the analysis, we investigate to what extent changes in residential emissions are due to changes in energy emissions coefficients, energy consumption structure, energy intensity, household income, and population size. We decompose the changes in residential CO 2 emissions in China and India into these five contributing factors from 1990 to 2011 by applying the Logarithmic Mean Divisia Index (LMDI) method. Our results show that the increase in per capita income level was the biggest contributor to the increase of residential CO 2 emissions, while the energy intensity effect had the largest effect on CO 2 emissions reduction in residential sectors in both countries. This implies that investments for energy savings, technological improvements, and energy efficiency policies were effective in mitigating CO 2 emissions. Our results also depict that the change in CO 2 emission coefficients for fuels which include both direct and indirect emission coefficients slowed down the increase of residential emissions. Finally, our results demonstrate that changes in the population and energy consumption structure drove the increase in CO 2 emissions.

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Section: The Logarithmic Mean Divisia Index (Lmdi) Methodsmentioning

confidence: 99%

Section: The Logarithmic Mean Divisia Index (Lmdi) Methodsmentioning

confidence: 99%

Driving Forces of CO2 Emissions in Emerging Countries: LMDI Decomposition Analysis on China and India’s Residential Sector

et al. 2015

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“…For example, it has been used to study energy consumption and carbon emissions in China, the European Union 27, and in other regions [26][27][28][29][30]. Many studies of energy consumption and carbon emissions have been conducted at provincial level [31][32][33][34][35][36] and city level [37]. Research has also been conducted at sector level-for example, Choi and Oh [38] studied the energy consumption and carbon emissions associated with Korea's manufacturing industry, while Zhang et al [39] investigated the energy consumption of transportation services in China.…”

Section: Introductionmentioning

confidence: 99%

What Drove Changes in the Embodied Energy Consumption of Guangdong’s Exports from 2007–2012?

Tang

Zou²,

2018

Sustainability

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China's economy has been highly reliant on exports in recent years, with Guangdong its biggest province in export trade volume. Despite the global financial crisis of 2008, exports from Guangdong continued to increase significantly; however, the energy consumption embodied in exports is unknown. In this study, we investigate the changes of energy embodied in exports from 2007 to 2012 in Guangdong Province. We use EIO (Environmental Input-Output) and LMDI (Logarithmic Mean Divisia Index) method to find out the drivers of such changes embodied in total exports and export of each sector. Our results show: Firstly, from 2007 to 2012, the export structure in Guangdong has changed, reflecting in low energy intensity industry experiencing faster growth in exports than high energy intensity industry. Secondly, the growth rate of embodied energy consumption in Guangdong's exports is slowing, with average annual growth from 2007 to 2012 of 6.8%. Thirdly, though Guangdong's exports grew significantly, the energy consumption embodied therein decreased by 23% from 2007 to 2012, representing a drop of 50.51 Mtce. Finally, the most prominent change driver differed across sectors: For low value-added industries, such as metal smelting and rolling, the main contributor was export structure change, whereas for high value-added industries, such as communications, computers, and other electronic equipment, the main contributor was technical change. Guangdong is playing a leading role in industrial upgrading in China, and this has made the embodied energy consumption decreased obviously in Guangdong. It will be interesting to further investigate the trends of embodied energy consumption of other provinces in China, as this would give us deeper understanding of Chinese resource and environment problems.

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“…During the 12th FYP period (2011-2015), the Tianjin government proclaimed a quantitative target of a 19% reduction in carbon emission intensity [38]. Several factors can affect energy-related CO2 emissions, such as economic development, energy intensity, industrial structure, and the ultimate energy consumption structure [28,39]. In line with the changing trend that has been evident from 2011, fulfillment of the established target should be feasible.…”

Section: An Eco-efficiency Analysis Of the Environmentmentioning

confidence: 99%

Eco-Efficiency Trends and Decoupling Analysis of Environmental Pressures in Tianjin, China

et al. 2015

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This study analyzes Tianjin's eco-efficiency trends during the period [2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013] and reasons for their changes, with the aim of contributing to efforts to ensure the city's sustainable development. While eco-efficiency of all of the indicators that we analyzed showed improvements during the study period, a gap remained in comparison to the more advanced eco-efficiency observed both domestically and internationally. We subsequently introduced decoupling indices to examine the decoupling relationship between environmental pressure and economic growth. This analysis demonstrated that some progress occurred during the study period resulting from the implementation of existing policies and measures entailing resource conservation and reduction in the emission of pollutants. The latter applied, especially, to sulfur dioxide (SO2) and chemical oxygen demand (COD), which both retained strong decoupling states from 2006 to 2013. Other indicators showed an apparent tendency toward decoupling, but most displayed weak decoupling. These findings indicate that further efforts are urgently required to promote strong decoupling. At the end of the twelfth Five-Year Plan period, Tianjin should consider formulating policies from the perspectives of resource consumption and pollutant emissions reduction to promote further sustainable development.

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Factor Decomposition Analysis of Energy-Related CO2 Emissions in Tianjin, China

Cited by 19 publications

References 34 publications

Driving Forces of CO2 Emissions in Emerging Countries: LMDI Decomposition Analysis on China and India’s Residential Sector

Driving Forces of CO2 Emissions in Emerging Countries: LMDI Decomposition Analysis on China and India’s Residential Sector

What Drove Changes in the Embodied Energy Consumption of Guangdong’s Exports from 2007–2012?

Eco-Efficiency Trends and Decoupling Analysis of Environmental Pressures in Tianjin, China

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