Driving factors of global carbon footprint pressure: Based on vegetation carbon sequestration

Chen, Jiandong; Fan, Wei; Li, Ding; Liu, Xin; Song, Malin

doi:10.1016/j.apenergy.2020.114914

Cited by 99 publications

(40 citation statements)

References 50 publications

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“…Finally, based on the conversion coefficient (i.e., 1.62/0.45) used by Chen et al . 30 , we obtained the carbon sequestration values of terrestrial vegetation, including Evergreen Needleleaf Forest (ENF), Evergreen Broadleaf Forest (EBF), Deciduous Needleleaf Forest (DNF), Deciduous Broadleaf Forest (DBF), Mixed forests (MF), Closed Shrublands (CShrub), Open Shrublands (OShrub), Woody Savannas (WSavanna), Savannas (Savanna), grassland (Grass), and Croplands (Crop). Based on vector cutting, we obtained the county-level nighttime light values and carbon sequestration values of vegetation.…”

Section: Methodsmentioning

confidence: 99%

“…Among them, terrestrial vegetation plays a significant role in CO 2 sequestration, and methods of estimation of its sequestration capacity have advanced and have been widely adopted 29 . Therefore, we also estimate the county-level carbon sequestration values of terrestrial vegetation, which facilitates more comprehensive research on reducing CO 2 emissions in China and evaluating sustainable develoment 30 .…”

Section: Background and Summarymentioning

confidence: 99%

“…The method of calculation of carbon sequestration value of terrestrial vegetation is consistent with that in Chen et al . 30 and, therefore, was deemed a reliable measure. With regard to the validity of energy-related carbon emissions based on the nighttime light data, we made use of the national and provincial energy-related CO 2 emissions provided by existing studies 17 , 60 , 61 to conduct a comparison with the summary of our simulated energy-related carbon emissions.…”

Section: Technical Validationmentioning

confidence: 99%

“…Second, considering that vegetation plays a significant role in sequestrating and reducing CO 2 emissions, the dataset of the 2,735 county-level carbon sequestration values of vegetation can be combined with our provided county-level energy-related CO 2 emissions. Evidently, the dataset could facilitate further comprehensive analyses and research on China’s emissions mitigation 30 , 64 , 65 , the gap between CO 2 emissions and carbon sequestration, and comprehensive evaluation of sustainable development 65 .…”

Section: Usage Notesmentioning

confidence: 99%

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County-level CO2 emissions and sequestration in China during 1997–2017

et al. 2020

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With the implementation of China’s top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions in China.

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Section: Methodsmentioning

confidence: 99%

Section: Background and Summarymentioning

confidence: 99%

Section: Technical Validationmentioning

confidence: 99%

Section: Usage Notesmentioning

confidence: 99%

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County-level CO2 emissions and sequestration in China during 1997–2017

et al. 2020

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“…Mean Divisia Index (LMDI) decomposition approach 41 can be used to separate the contribution of drivers to CO 2 emissions 42,43 . This approach is simple, not affected by the time-span, and can realize the zero residual decomposition 44,45 .…”

Section: Decomposition Model Of Co 2 Emissions the Combination Of Kamentioning

confidence: 99%

China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data

Chen

Gao

Cheng

et al. 2021

Sci Rep

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Accurate, long-term, full-coverage carbon dioxide (CO2) data in units of prefecture-level cities are necessary for evaluations of CO2 emission reductions in China, which has become one of the world’s largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program’s Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data, and estimates the CO2 emissions of 334 prefecture-level cities in China from 1992 to 2017. Results indicated that the eastern and coastal regions had higher carbon emissions, but their carbon intensity decreased more rapidly than other regions. Compared to previous studies, we provide the most extensive and long-term CO2 dataset to date, and these data will be of great value for further socioeconomic research. Specifically, this dataset provides a foundational data source for China’s future CO2 research and emission reduction strategies. Additionally, the methodology can be applied to other regions around the world.

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The sustainability prism of structural changes in the European Union agricultural system: The nexus between production, employment and energy emissions

Jurkėnaitė¹,

Baležentis²,

Štreimikienė³

2021

Bus Strat Env

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Over the recent decades, the evolution of the European Union (EU) agricultural system has resulted in significant structural changes in member states. Knowledge about the nature and main patterns of structural change is critical to select a sustainable development path for the EU agriculture. This paper contributes to the academic discourse on structural changes in agriculture demonstrating the nexus between socioeconomic and environmental aspects of development. In this regard, results are important to understand the contribution of the EU agriculture to climate change, because study deals with energy use and greenhouse gas emissions. The research covers period from 2008 to 2018 and investigates the fundamental structural change measures, namely, gross value added, labour and agriculture-related energy emissions, in EU member states. Structural changes are investigated applying a shift-share analysis that allows calculating a performance of individual member states, compared to the EU economy. The applied shift-share model investigates the situation of individual member states employing three components. The first component tracks the development of the selected measures with the EU economy growth, the second component shows the change due to effect of economic activities and the third shows competitiveness of agriculture in member states. The shift-share analysis empowers ranking member states in accordance with their progress towards the sustainable development. Findings suggest that EU economy faces the outflow of labour from agriculture and this trend is common for most countries. The changes of gross value added and emissions for fuel combustion demonstrate both upward and downward trends. However, research results suggest that new member states often face more fundamental changes.

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Driving factors of global carbon footprint pressure: Based on vegetation carbon sequestration

Cited by 99 publications

References 50 publications

County-level CO2 emissions and sequestration in China during 1997–2017

County-level CO2 emissions and sequestration in China during 1997–2017

China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data

The sustainability prism of structural changes in the European Union agricultural system: The nexus between production, employment and energy emissions

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