How can Chinese metropolises drive global carbon emissions? Based on a nested multi-regional input-output model for China

Jiang, Mengqi; Huang, Yumeng; Yang, Bai; Wang, Qi

doi:10.1016/j.scitotenv.2022.159094

Cited by 23 publications

(7 citation statements)

References 76 publications

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“…In addition to a specific demand, the differential impacts of various demand factors on carbon emissions have been compared in several studies [17,44,45]. Xu et al [17] delineated the final demand into six parts to assess the different impact of demand factors when calculating the embodied carbon emissions in Guangdong.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Xu et al [17] delineated the final demand into six parts to assess the different impact of demand factors when calculating the embodied carbon emissions in Guangdong. Jiang et al [45] accounted for carbon emissions due to different demand factors in two typical metropolitan cities, Beijing and Shanghai, and provided targeted policy recommendations. In terms of energy, Zhang et al [44] investigated the driving effect of different demand factors on the energy consumption of Shanxi Province and located the key demands and sectors.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Zhao et al [65] constructed a pollutant transfer network for the light industry in major economies around the world and revealed its structural characteristics and key transfer pathways. In order to deeply investigate the interaction between industrial networks and carbon emissions, CNA was introduced by some scholars to explore the spatial features of carbon transfer [1,26,45,66]. Wang et al [66] utilized CNA to analyze the inter-sectoral linkages of ECEs in China and identified the key intermediary sectors.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Wang et al [66] utilized CNA to analyze the inter-sectoral linkages of ECEs in China and identified the key intermediary sectors. Jiang et al [45] constructed a citycentered I-O network and examined the driving factors of Beijing and Shanghai's networks and their role in the global carbon network. Huo et al [26] studied the evolution of ECE network features in the Chinese construction sector.…”

Section: Literature Reviewmentioning

confidence: 99%

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Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors

Li,

Chen

2023

Energies

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The development of human society has led to the growing consumption of industrial products, which generates significant amounts of carbon emissions. However, relatively few in-depth studies have been conducted on the influence of different demand factors (e.g., household consumption, government consumption, export, and capital formation) on carbon emissions, which hinders the development of targeted industrial policies. To address this issue, an analytical framework based on input–output theory, the hypothesis extraction method, and complex network analysis was established to estimate the intrinsic influence of different demand factors on the embodied carbon transfer between provinces in China. The key findings can be summed up as follows: (1) The macro direction of China’s embodied carbon transfer runs from resource-rich northern provinces to industrially developed southern provinces. (2) From the perspective of different demand factors, capital formation is the most significant contributor to China’s embodied carbon transfer, with the construction industry being the most important driver. In contrast, government consumption causes the least embodied carbon transfer, but it has the highest average carbon emission intensity. (3) According to complex network theory, the carbon transfer networks via provinces and industries caused by exports are the most concentrated, with the manufacture of electrical machinery and electronic equipment serving as the main source of demand. In contrast, the carbon transfer network resulting from household consumption exhibits a high level of decentralization, with dominant sectors including electric power, gas and water production, and supply and other services. Based on these findings, this study is expected to contribute targeted suggestions with which provinces and industries can formulate demand-side carbon reduction policies for different demand factors, which will contribute to the achievement of “carbon peaking and carbon neutrality”.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors

Li,

Chen

2023

Energies

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“…They are now widely used to study economic and environment-related issues. Examples include the use of input-output tables to analyze sectoral energy consumption, 1 carbon emission, 2 virtual water, 3 and the integration of complex network analysis methods to study sectoral linkages. 4 China’s input-output tables are typically updated every five years, with the last digit of the year is 2 or 7.…”

Section: Introductionmentioning

confidence: 99%

High-frequency sectoral carbon and environmental analysis based on monthly input-output tables compilation during 2018–2021

Xu,

Liu,

et al. 2023

iScience

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Linking local and global: Assessing water scarcity risk through nested trade networks

Wang,

Shuai,

Chen

et al. 2024

Sustainable Development

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As water scarcity escalates globally, there is a growing focus on assessing its economic impact, both locally and through trade networks, defined as water scarcity risk (WSR). Given China's pivotal role as a top importer and exporter, coupled with significant spatial disparities in water scarcity across its provinces, understanding the spread of water scarcity risks within China and their interplay with global water dynamics is imperative yet relatively unexplored. This study constructs a nested Multi‐Regional Input‐Output (MRIO) model to evaluate water scarcity risk, connecting Chinese provinces with global counterparts. Notably, we integrate the spatial heterogeneity of environmental flow requirement as a vital criterion for long‐term sustainable water management in our assessment. Our findings reveal substantial economic impacts caused by water scarcity, with a global WSR valued at $11.1 trillion, of which $6.2 trillion is attributed to trade. Critical regions, sectors, and region‐sectors are identified, offering valuable insights for targeted interventions. This study presents a unique perspective on global water scarcity risk assessment at a higher resolution scale, laying the groundwork for the formulation of effective water scarcity risk mitigation strategies aligned with sustainable development goals, particularly SDG 6 and 8.

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How can Chinese metropolises drive global carbon emissions? Based on a nested multi-regional input-output model for China

Cited by 23 publications

References 76 publications

Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors

Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors

High-frequency sectoral carbon and environmental analysis based on monthly input-output tables compilation during 2018–2021

Linking local and global: Assessing water scarcity risk through nested trade networks

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