Spatial decomposition of city-level CO2 emission changes in Beijing-Tianjin-Hebei

Yu, Xiaohong; Liang, Zifen; Fan, Jiajia; Zhang, Jialing; Luo, Yihang; Zhu, Xiaoyuan

doi:10.1016/j.jclepro.2021.126613

Cited by 37 publications

(13 citation statements)

References 11 publications

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“…Until now, effort made in energy mix has already benefited Jing-Jin-Ji to a large extent. For example, due to improving the use of secondary energy sources, such as coke, gasoline, diesel, Beijing, and Tianjin reduced large CO 2 emissions (Yu et al, 2021). But, although emissions intensity of both Beijing and Tianjin have declined obviously, cities in Hebei province still have room for that.…”

Section: Discussionmentioning

confidence: 99%

The Consumption‐Based Carbon Emissions in the Jing‐Jin‐Ji Urban Agglomeration Over China's Economic Transition

et al. 2021

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After the 2008 financial crisis, China entered a new stage of economic transition, formulated as "the new normal," in which economic patterns shifted from rapid to lower growth but with a focus on higher quality (Mi et al., 2018;Zheng et al., 2020). The pattern of economic growth gradually shifted toward low investment and high consumption (Grubb et al., 2015), with a move away from heavy manufactory sector toward service industry and high value-added manufacturing (Green & Stern, 2015). In the new normal era, China prioritized environmental sustainability and a low carbon society, by developing clean energy and cleaning the energy mix (Zheng, Mi, et al., 2019;Zheng, Zhang, et al., 2019). This shift in economic growth patterns

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Section: Discussionmentioning

confidence: 99%

The Consumption‐Based Carbon Emissions in the Jing‐Jin‐Ji Urban Agglomeration Over China's Economic Transition

et al. 2021

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“…In 2015, the CO 2 emissions in the BTH region accounted for approximately 10.03% of the national total, with Hebei contributing the largest amount. From 2002 to 2016, the proportion of Hebei’s CO 2 emissions in the BTH region rose from 72% to 86.2%, while Beijing and Tianjin’s share declined [ 69 ].…”

Section: Study Area Methodology and Datamentioning

confidence: 99%

Does Industrial Transfer Change the Spatial Structure of CO2 Emissions?—Evidence from Beijing-Tianjin-Hebei Region in China

Yue

Zhu

Yao

2021

IJERPH

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As an important cause of global warming, CO2 emissions have become a research hotspot in recent years. Industrial transfer impacts regional CO2 emissions and is related to the low-carbon development of regional industries. Taking the Beijing-Tianjin-Hebei region (BTH region) as an example, this study analysed industrial transfer’s direct and indirect impacts on CO2 emissions based on a mediating model and two-way fixed effect panel regression. The results obtained indicate that industrial transfer-in has promoted CO2 emissions to a small extent, and the positive impact of industrial transfer-in on CO2 emissions wanes over time. Industrial transfer affects CO2 emissions by acting on the economic level, on population size, and on urbanisation level, but the indirect effect is weaker than the direct effect. Industrial transfer does not lead to technological upgrading, but the latter is an effective means of carbon emission reduction. Industrial transfer-in has shown a positive effect on CO2 emissions for most cities, but there are exceptions, such as Cangzhou. In the future, the BTH region should maintain coordinated development among cities and improve the cooperative innovation mechanism for energy conservation and emission reduction.

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“…Recently, land use-related carbon emissions has become a research hotspot. For large developed cities in eastern China, such as Beijing, Shanghai, and Shenzhen, as well as for particular economically developed regions, such as the Beijing-Tianjin-Hebei, the Pearl River Delta, and the Yangtze River Delta urban agglomeration, many previous studies have examined carbon emissions linked to LUCC, and the result shows that optimizing land use structure is an effective means to reduce carbon emissions (Li et al, 2013;Fang and Zhao 2018;Han et al, 2019;Yu et al, 2021). However, there has been little study on western China's developing and relatively undeveloped cities and areas, where there are significant differences from eastern cities and areas in terms of landform, climate, and social and economic background (Yang et al, 2019;Nie et al, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of low-carbon land use in Chengdu based on multi-objective linear programming and the future land use simulation model

Lan

Cao

et al. 2022

Front. Environ. Sci.

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Optimizing the structure of land use is essential to the low-carbon sustainable development of a region. This article takes Chengdu, a typical western China city, as the case study. First, carbon emission coefficients of land use are used to calculate the carbon emissions. Then, based on multi-objective linear programming (MOP), economic development priority scenario (S1), low-carbon economic development scenario (S2), and strengthening low-carbon economic scenario (S3) are proposed. Finally, the future land use simulation (FLUS) model is used to predict the spatial layout of land use under the three scenarios. The result shows that from 1990 to 2020, the carbon emissions increased by 7,617.61 thousand tons, with an annual growth rate of 3.75%. The main difference among the three scenarios is the occupied degree of farmland caused by the expansion of construction land, and the potential carbon reduction is 969.72 (5.2%), 2414.31 (13.1%), and 3878.89 tons (21.0%) in S1, S2, and S3, respectively. The FLUS model shows that conversion mainly occurs around the urban built-up area of Chengdu. This research can provide planning suggestions for the low-carbon development of Chengdu and a reference for other regions.

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Spatial decomposition of city-level CO2 emission changes in Beijing-Tianjin-Hebei

Cited by 37 publications

References 11 publications

The Consumption‐Based Carbon Emissions in the Jing‐Jin‐Ji Urban Agglomeration Over China's Economic Transition

The Consumption‐Based Carbon Emissions in the Jing‐Jin‐Ji Urban Agglomeration Over China's Economic Transition

Does Industrial Transfer Change the Spatial Structure of CO2 Emissions?—Evidence from Beijing-Tianjin-Hebei Region in China

Optimization of low-carbon land use in Chengdu based on multi-objective linear programming and the future land use simulation model

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