Input-output analysis of embodied emissions: Impacts of imports data treatment on emission drivers

Su, Bin; Ang, B.W.; Sun, Yongming

doi:10.1016/j.eneco.2022.105875

Cited by 42 publications

(7 citation statements)

References 23 publications

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“…Input-output is a commonly used industry correlation effect analysis method [ 42 , 43 ]. In order to judge the correlation of resource industry sectors in the study area, reaction coefficient and influence coefficient are selected to reflect the interaction between sectors.…”

Section: Methodsmentioning

confidence: 99%

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China

Liu,

Zhang,

Hou

et al. 2024

PLoS ONE

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In order to solve the problem of coordinated development among mining economy, social governance and environmental conservation in global resource-based cities, we choose Guangxi Zhuang Autonomous Region as the research area. The advantage of resource endowment and resource industry was measured by location quotient and input-output method. The panel data related to mining governance from 2010 to 2021 were selected to build the evaluation and coupling analysis model between mining economic, social governance and environmental conservation, and the spatial-temporal heterogeneity and coupling effect of them were analyzed by comprehensive empowerment evaluation, spatial autocorrelation analysis and barrier degree methods. The results show that: (1) Except for the overall upward trend of social governance, the development level of mining economy and environmental conservation are basically stable; (2) The resource-rich areas have obvious mining economic advantages, and the central cities have good social governance capabilities, and the environmental conservation effectiveness is uncertain; (3) The coupling effect between mining economy and social governance is stronger than that between mining economy and environment conservation, and the synergistic coupling effect of the three is relatively random. Finally, we put forward some policy response strategies to Guangxi, and theoretical and practical reference would be provided for resource-based cities around the world.

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Section: Methodsmentioning

confidence: 99%

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China

Liu,

Zhang,

Hou

et al. 2024

PLoS ONE

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“…The MRIO tables employed in this study are “non-competitive” tables. That is, the imported products are explicitly distinguished from domestic products, which allows us to conveniently calculate the production-based emissions without additional data splitting. , However, due to the data limitation, the MRIO tables available in this study have only one row of import data, that is, they shows only the total import amount of different products, without product-mix details and detailed import source countries; thus, emissions from imports are not able to be included when accounting consumption-based emissions in this study.…”

Section: Methods and Data Sourcementioning

confidence: 99%

Common Driving Forces of Provincial-Level Greenhouse Gas and Air Pollutant Emissions in China

Liu

Liang

Shuai

2023

Environ. Sci. Technol.

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By developing a filtering framework and a sector-level multi-regional input–output structural decomposition model, this study identifies key common emission sources, motivation sources, and inter-provincial emission flows of both GHGs and air pollutants and reveals the key driving forces of changes in different emissions from 2012 to 2017. Results show that key common emission sources are electricity sector, non-metallic mineral products, and smelting and processing of metals in Shandong and Hebei. However, key common motivation sources are the construction sectors in Guangdong, Henan, Jiangsu, Zhejiang, and Shandong. The key inflow regions include Guangdong and Zhejiang and key outflow regions include Jiangsu and Hebei. The emission reductions are attributed to the emission intensity effect of the construction sector; contrastingly, the emission increase is from the investment scale of the construction sector. Here, Jiangsu could be a key target for future emission reduction because of its high absolute emissions and low past reduction. The scale of investment in construction might be a significant factor in reducing emissions in Shandong and Guangdong. Henan and Zhejiang could concentrate on sound new building planning and resource recycling.

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“…A k F. Consequently, the production activities required to meet final demand extend beyond the production of the final good. This indicator provides valuable insights into the direct and indirect inputs required throughout the production chain for the final good, thereby highlighting the interdependencies among different industrial sectors [39,50,66,67].…”

Section: Input-output Model For Measuring Agricultural Wagesmentioning

confidence: 99%

Exploring the drivers of agricultural wages growth in China: A comprehensive framework utilizing input-output and structural decomposition methods

Zheng,

Li,

2024

PLoS ONE

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This study explores the factors driving agricultural wages growth in China from 1981 to 2020. We propose a comprehensive framework that combines input-output analysis and structural decomposition analysis to investigate the drivers of agricultural wages growth from four perspectives: supply, demand, industrial linkages, and agricultural support policies. The findings indicate that changes in consumer demand, investment demand, and labor mobility play significant roles in driving the growth of agricultural wages in China. Additionally, agricultural support policies have contributed to an increase in agricultural wages to some extent. However, changes in industrial linkages negatively affect agricultural wages growth. A notable strength of this study lies in the methodology employed, which ensures a comprehensive and systematic analysis encompassing diverse factors rather than a restricted perspective.

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Input-output analysis of embodied emissions: Impacts of imports data treatment on emission drivers

Cited by 42 publications

References 23 publications

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China

Common Driving Forces of Provincial-Level Greenhouse Gas and Air Pollutant Emissions in China

Exploring the drivers of agricultural wages growth in China: A comprehensive framework utilizing input-output and structural decomposition methods

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