Life Cycle Building Carbon Emissions Assessment and Driving Factors Decomposition Analysis Based on LMDI—A Case Study of Wuhan City in China

Gong, Yanyun; Song, Deyong

doi:10.3390/su71215838

Cited by 42 publications

(28 citation statements)

References 29 publications

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“…Results have documented that improvements in the urbanization quality have contributed to reducing CO 2 emissions [ 26 ]. Many studies, such as Zhang et al [ 24 ], Ding et al [ 27 ], and Gong et al [ 28 ], describe urbanization in terms of rapid increase in the proportion of urban population. The different comprehensive effects from urbanization’s various aspects may have different impacts on the dynamic changes of carbon emissions [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

“…The Logarithmic Mean Divisia Index (LMDI), one type of IDA which does not produce a residual term, is more suitable for temporal analysis and has been widely used in the decomposition analysis of carbon emissions [ 46 ]. Research that applied the LMDI to decompose CO 2 emissions focused not only on energy-related and industrial sectors but also on sectors such as transportation, land use, and agriculture [ 28 , 31 , 47 , 48 , 49 , 50 , 51 ].…”

Section: Introductionmentioning

confidence: 99%

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Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River

Zhang

Wang

et al. 2021

IJERPH

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The urban agglomerations in the middle reaches of the Yangtze River (MYR-UA) are facing a severe challenge in reducing carbon emissions while maintaining stable economic growth and prioritizing ecological protection. The energy consumption related to land urbanization makes an important contribution to the increase in carbon emissions. In this study, an IPAT/Kaya identity model is used to understand how land urbanization affected carbon emissions in Wuhan, Changsha, and Nanchang, the three major cities in the middle reaches of the Yangtze River, from 2000 to 2017. Following the core idea of the Kaya identity model, sources of carbon emissions are decomposed into eight factors: urban expansion, economic level, industrialization, population structure, land use, population density, energy intensity, and carbon emission intensity. Furthermore, using the Logarithmic Mean Divisia Index (LMDI), we analyze how the different time periods and time series driving forces, especially land urbanization, affect regional carbon emissions. The results indicate that the total area of construction land and the total carbon emissions increased from 2000 to 2017, whereas the growth in carbon emissions decreased later in the period. Energy intensity is the biggest factor in restraining carbon emissions, followed by population density. Urban expansion is more significant than economic growth in promoting carbon emissions, especially in Nanchang. In contrast, the carbon emission intensity has little influence on carbon emissions. Changes in population structure, industrial level, and land use vary regionally and temporally over the different time period.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River

Zhang

Wang

et al. 2021

IJERPH

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“…(2) The lower 10 th and 10 th -25 th quantile provinces should further expand R&D expenditure and personnel investment in emission reduction technologies. Technological progress is the fundamental way to reduce CO 2 emissions [38]. Large-scale R&D funds and personnel investment are two indispensable elements of technological innovation.…”

Section: Conclusion and Policymentioning

confidence: 99%

Which Influencing Factors Cause CO2 Emissions Differences in China’s Provincial Construction Industry: Empirical Analysis from a Quantile Regression Model

Wang¹,

Song²,

Chen³

2019

Pol. J. Environ. Stud.

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Massive demand for energy caused by economic growth has led to a substantial increase in carbon dioxide emissions. The International Energy Agency (IEA) announced that global carbon dioxide emissions reached 325 billion tons in 2017. Accumulated global carbon dioxide emissions have brought about a series of environmental problems, such as global warming and the frequent emergence of extreme weather [1]. Owing to huge industrial scale and long-term extensive economic growth, China has become the largest carbon

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“…The zoning's results do not reflect the internal differences in governance elements that could affect external differences in carbon emissions, so it was difficult to derive a governance strategy. In fact, governance elements such as population, land use, and facilities, can affect carbon emissions by affecting the energy consumption of the building and transportation sectors [50][51][52][53]. Therefore, to establish a zoning system oriented toward carbon emission governance, it is essential to find the effects of governance elements on carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

Carbon Emission Governance Zones at the County Level to Promote Sustainable Development

Peng

et al. 2021

Land

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Low-carbon governance at the county level has been an important issue for sustainable development due to the large contributions to carbon emission. However, the experiences of carbon emission governance at the county level are lacking. This paper discusses 5 carbon emission governance zones for 1753 counties. The zoning is formed according to a differentiated zoning method based on a multi-indicator evaluation to judge if the governance had better focus and had formulated a differentiated carbon emission governance system. According to zoning results, there is 1 high-carbon governance zone, 2 medium-carbon governance zones, and 2 low-carbon zones. The extensive high-carbon governance zone and medium-carbon zones are key governance areas, in which the counties are mainly located in the northern plain areas and southeast coastal areas and have contributed 51.88% of total carbon emissions. This paper proposes differentiated governance standards for each indicator of the 5 zones. The differentiated zoning method mentioned in this paper can be applied to other governance issues of small-scale regions.

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Life Cycle Building Carbon Emissions Assessment and Driving Factors Decomposition Analysis Based on LMDI—A Case Study of Wuhan City in China

Cited by 42 publications

References 29 publications

Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River

Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River

Which Influencing Factors Cause CO2 Emissions Differences in China’s Provincial Construction Industry: Empirical Analysis from a Quantile Regression Model

Carbon Emission Governance Zones at the County Level to Promote Sustainable Development

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