Carbon Transfer Decision Model Based on LMDI Method

Qi, Yawei; Rao, G.U.K.; Zha, Lei; Chen, Lu; Niu, Yuping

doi:10.1155/2022/3970880

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Existing studies have adequately applied the multiregional input-output (MRIO) model to calculate the international and domestic carbon emissions transfer from both the producers’ and consumers’ perspectives 45 – 48 . However, few scholars have studied aviation carbon transfer, so we cannot draw more inspiration from it.…”

Section: Methodsmentioning

confidence: 99%

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021

Cui,

Chen

2023

Sci Data

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As an underdeveloped region, the aviation industry in Africa is developing rapidly, and its carbon emissions play an essential role in achieving carbon neutrality in the aviation industry in underdeveloped areas. However, the problem of carbon transfer caused by passenger flow on international routes has not been addressed, especially in Africa. This paper first calculates the CO2 emissions of African international routes from 2019 to 2021 based on the Modified Fuel Percentage Method (MFPM) and the ICAO standard methods. Then, we measure African routes’ carbon transfer and carbon compensation. The most carbon transfer routes between African countries and from countries outside Africa to African countries are from Ethiopia to Kenya and from Honduras to Ghana. Relatively poor countries bear a significant amount of carbon transfer.

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Section: Methodsmentioning

confidence: 99%

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021

Cui,

Chen

2023

Sci Data

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“…In the research of decomposition of agricultural carbon emission drivers, commonly used decomposition models include IPAT model, STIRPAT model, LMDI model, Kaya formula, etc (Qi et al, 2022). The Kaya constant equation was proposed by the Japanese scholar Yoichi Kaya in 1989 at a workshop organized by the United Nations Intergovernmental Panel on Climate Change (IPCC) and gives the main drivers of carbon emissions, but does not have accounting significance (Ortega-Ruiz et al, 2022).…”

Section: Decomposition Of the Drivers Of Agricultural Carbon Emissionsmentioning

confidence: 99%

Research on the Drivers of Agricultural Carbon Emissions and Decoupling Effects in Jiangsu Province, China

Fan

2022

Preprint

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This paper measures and analyzes the characteristics of changes in agricultural carbon emissions, structure and intensity from 2005 to 2020 based on agricultural input-output data, explores the drivers of agricultural carbon emissions using the LMDI model, and uses the TAPIO decoupling model to explore the relationship between agricultural economic development and agricultural carbon emissions in Jiangsu province. The research indicate that: (1) From 2005 to 2020, the agricultural carbon emissions in Jiangsu Province showed a three-stage change of "decline - rise - decline", with an average annual decrease of 0.34%; Carbon emissions per 10,000 yuan of total agricultural output value decreased from 701.43 kg in 2005 to 215.96 kg in 2020, with an average annual decrease of 7.55%. (2) The factors of agricultural production efficiency, agricultural production structure and agricultural labor scale all contribute to agricultural carbon emission reduction to different degrees, while the factors of agricultural economic level and total population contribute to agricultural carbon emission reduction to different degrees. (3) The decoupling elasticity index of agricultural carbon emissions and agricultural economic level in Jiangsu Province lies between -3.3217 and 3.6546, and the decoupling types are mainly weak and strong decoupling. According to our research results, agricultural production efficiency should be improved, the structure of the plantation industry should be optimized, and the transfer of agricultural labor to secondary and tertiary industries should be promoted in order to promote high-quality development of agriculture.

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“…However, relying solely on the Kaya model for detecting changes in carbon emissions poses challenges in accurately determining their actual impact on total emissions and fails to account for variations in economic and social trends. Qi et al [22] conducted a calculation of carbon emissions from both producer and consumer perspectives, while also analyzing the decision-making process behind inter-provincial net carbon emission transfers. Additionally, the LMDI method was employed to decompose the factors influencing the province's net carbon emissions into technology, structure, input-output, and scale effects.…”

Section: Introductionmentioning

confidence: 99%

Research on Influencing Factors of Residential Building Carbon Emissions and Carbon Peak: A Case of Henan Province in China

Yang,

Sima,

et al. 2023

Sustainability

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Buildings are considered to have significant emission reduction potential. Residential building carbon emissions, as the most significant type of building-related carbon emissions, represent a crucial factor in achieving both carbon peak and carbon neutrality targets for China. Based on carbon emission data from Henan Province, a large province located in central China, between 2010 and 2020, this study employed the Kaya-LMDI decomposition method to analyze seven driving factors of carbon emission evolution, encompassing energy, population, and income, and assessed the historical reduction in CO2 emissions from residential buildings. Then, by integrating Kaya identity static analysis with Monte Carlo dynamic simulation, various scenarios were established to infer the future evolution trend, peak time, and potential for carbon emission reduction in residential buildings. The analysis results are as follows: (1) The carbon emissions of residential buildings in Henan exhibited a rising trend from 2010 to 2020, albeit with a decelerating growth rate. (2) Per capita household disposable income is the main driving factor for the increase in carbon emissions, but the household housing purchase index inhibits most of the growth of carbon emissions for the residential buildings in Henan, with the total carbon emission reduction of residential buildings reaches 106.42 million tons of CO2 during the research period. (3) During the period from 2020 to 2050, residential buildings in Henan Province will exhibit an “inverted U-shaped” trend in carbon emissions under the three static scenarios. The base scenario predicts that carbon emissions will reach their peak of 131.66 million tons in 2036, while the low-carbon scenario forecasts a peak of 998.8 million tons in 2030 and the high-carbon scenario projects a peak of 138.65 million tonnes in 2041. (4) Under the dynamic simulation scenario, it is anticipated that residential buildings in Henan Province will reach their carbon peak in 2036 ± 3 years, with a corresponding carbon emission of 155.34 million tons. This study can serve as a valuable reference for the future development of low-carbon pathways within the building sector.

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Carbon Transfer Decision Model Based on LMDI Method

Cited by 6 publications

References 12 publications

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021

Research on the Drivers of Agricultural Carbon Emissions and Decoupling Effects in Jiangsu Province, China

Research on Influencing Factors of Residential Building Carbon Emissions and Carbon Peak: A Case of Henan Province in China

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