Decomposition of Net CO2 Emission in the Wuhan Metropolitan Area of Central China

Yang, Xin; Ma, Chunbo; An-lu, Zhang

doi:10.3390/su8080784

Cited by 9 publications

(4 citation statements)

References 34 publications

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“…As reported in the decomposition literature [ 74 , 75 ], energy intensity is the main reason for the reduction in total carbon emissions, which means that improved energy intensity plays an important role in reducing carbon emissions. Over the period, energy intensity has become an important constraint index of national economic development.…”

Section: Discussionmentioning

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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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: Discussionmentioning

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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“…As Hubei Province's economic hub and a key strategic region for the rise of central China, WMA is a comprehensive reform pilot for building China's environmentally friendly society and resource-saving (Wang et al 2021). In 2013, with the extension of the strategy of low-carbon development, Wuhan became the seventh carbon emission trading center "China Hubei Emission Exchange" in China (Yang et al 2016). WMA has entered a phase of rapid development with the promotion of integrated construction.…”

Section: Study Areamentioning

confidence: 99%

Construction and optimization of ecological security patterns based on ecosystem services in the Wuhan metropolitan area

Chen,

Zhu,

Liu

et al. 2024

Preprint

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Context: Rapid urbanization has affected ecosystem stability, which can be effectively mitigated by building an Ecological Security Pattern (ESP). Previous research has mainly focused on ESP identification in a single year, ignoring the change of various landscape elements in ESP on a time scale. Objectives: We sought to improve the solution. We aimed to construct and optimize ESPs in different years, analyze their variations over time, and provide references for ecological security protection. Methods: We developed a framework in 2000, 2010, and 2020 to study the Wuhan Metropolitan Area (WMA) ESP. The ESPs were established by circuit theory and were optimized by the Centrality Mapper and the gravity model. Results: The findings indicated that the research area's key landscape elements exhibited clear spatial aggregation, they were mostly located in the east and south and gradually expanded to the north over the previous 20 years. From 2000 to 2020, there was a first decrease and then an increase in ecological source and corridor numbers. This change was also reflected in pinch points and barriers. We eventually obtained the optimized ESP in the three periods, among which the ESP in 2020 includes 9 primary, 21 secondary, and 48 tertiary ecological sources, 141 primary, and 37 secondary corridors, with 170.46 km2 barriers and 197.42 km2 pinch points. Conclusion: This research framework extends the time scale of ESP construction, providing the theoretical basis and reference for regional sustainable development and landscape pattern optimization in the process of urbanization.

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“…WMA is rich in water resources due to the highly developed regional water system and numerous rivers and lakes. The WMA is chosen as the typical case of the study, not only because of its role of the first nationwide comprehensive reform experimental area of the resource-saving and environment-friendly society in China [42], but also the factors of its new-type urbanization development, complex shape and local dispersion, and increased ecological environment problems.…”

Section: Study Areamentioning

confidence: 99%

Construction and Evaluation of the Integrated Perception Ecological Environment Indicator (IPEEI) Based on the DPSIR Framework for Smart Sustainable Cities

Liu

Chen

et al. 2020

Sustainability

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Ecological environment evaluation is of great significance to achieve the Sustainable Development Goals (SDGs) and promote the harmonious development of economy, society, and environment. To evaluate environmental SDGs, single environmental indicators have been analyzed at national or large regional scale in some literature, while the urban integrated environment is ignored. Therefore, it is necessary to systematically and quantically evaluate the sustainability of ecological environment integrating the water, soil, and air environment at the urban scale. This study aims to construct the Integrated Perception Ecological Environment Indicator (IPEEI) based on the Driver-Pressure-State-Impact-Response (DPSIR) framework to solve the above-mentioned problems. The IPEEI model was proposed based on the three-level association mechanism of the Domain-Theme-Element, and the DPSIR framework conforming to the relevant standards for indicator determination. Moreover, the multi-dimensional, multi-thematic, and multi-urban quantitative evaluations were conducted using the entropy weight method, and the comprehensive evaluation grades by the Jenks natural breaks classification method of the geospatial analysis. Nine cities in the Wuhan Metropolitan Area were selected as the experimental areas. The results were consistent with the Ecological Index and local government’s planning and measures, which demonstrated that IPEEI can be effectively verified and applied for the evaluation of urban ecological environment sustainability.

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Decomposition of Net CO2 Emission in the Wuhan Metropolitan Area of Central China

Cited by 9 publications

References 34 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

Construction and optimization of ecological security patterns based on ecosystem services in the Wuhan metropolitan area

Construction and Evaluation of the Integrated Perception Ecological Environment Indicator (IPEEI) Based on the DPSIR Framework for Smart Sustainable Cities

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