Spatial-temporal characteristics of carbon emissions from land use change in Yellow River Delta region, China

Zhang, Chunyan; Zhao, Lin; Zhang, Haotian; Chen, Meng-na; Fang, Ru-yao; Ying, Yu; Zhang, Qipeng; Wang, Qian

doi:10.1016/j.ecolind.2022.108623

Cited by 148 publications

(76 citation statements)

References 19 publications

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“…Mo et al [33] found that carbon emissions in the YRB showed a pattern of "high in the east and low in the west". Zhang et al [52] indicated that carbon emissions in the Yellow River Delta showed a larger distribution of carbon emissions in the "east-west" direction than in the "north-south" direction. However, it is not enough to study only the total amount of carbon emissions without considering economic development, and a more comprehensive understanding is needed.…”

Section: Discussionmentioning

confidence: 99%

“…Promoting coordinated regional development is one of China's major national strategies in the new era. Although many scholars have found spatial heterogeneity in carbon emissions in the YRB [33,[52][53][54], they have failed to quantify the sources of regional differences and their convergence characteristics. In this paper, the regional differences and convergence characteristics of carbon emission intensity in the YRB are analyzed in detail by using the Markov chain, Dagum Gini coefficient, and variation coefficient method.…”

Section: Discussionmentioning

confidence: 99%

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Regional Differences and Convergence of Carbon Emissions Intensity in Cities along the Yellow River Basin in China

Chen

Meng

Shi

et al. 2022

Land

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Since the ecological protection and high-quality development of the Yellow River Basin (YRB) in China have become a primary national strategy, the low-carbon economy is crucial. To formulate effective emission mitigation policies for the YRB, we need to comprehensively understand the characteristics of the spatial agglomeration of the carbon emissions intensity in the YRB and its regional heterogeneity. Therefore, based on the relevant data from 2005 to 2017, we first scientifically measure the carbon emissions intensity of 57 cities along the YRB. Then, we analyze the spatial agglomeration characteristics and long-term transfer trends of carbon emission intensity using exploratory spatial data analysis methods and Markov chains. Finally, the Dagum Gini coefficient and the variation coefficient method are used to study the regional differences and differential evolution convergence of the carbon emissions intensity in the YRB. The results show that the carbon emissions intensity of the YRB has dropped significantly with the spatial distribution characteristics “high in the west and low in the east”, and there is a significant spatial autocorrelation phenomenon. In addition, the probability of a shift in urban carbon intensity is low, leading to a “club convergence” and a “Matthew effect” in general and across regions. Inter-regional differences have always been the primary source of spatial differences in carbon emissions intensity in the YRB, and the intra-regional differences in carbon emissions intensity in the lower YRB show a significant convergence phenomenon. The research results may provide a reference for the regional coordinated development of a low-carbon economy in the YRB, and serve to guide the win-win development model of ecological environment protection and economic growth in the YRB.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Regional Differences and Convergence of Carbon Emissions Intensity in Cities along the Yellow River Basin in China

Chen

Meng

Shi

et al. 2022

Land

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“…Zhu et al explored changes in vegetation carbon storage and soil organic carbon storage due to land cover change in Zhejiang Province between 1970 and 2010 7 . Zhang et al analysed carbon emissions in the Yellow River Delta region from 2000 to 2019 in terms of spatial and temporal distribution 15 . However, the aforementioned papers mainly focused on analysing the spatial and temporal distribution of carbon emissions, and relatively few studies have analysed land cover change, carbon emissions from land cover change, land use intensity change, and the distribution of carbon sources and sinks from multiple perspectives.…”

Section: Introductionmentioning

confidence: 99%

Analysis of carbon emissions from land cover change during 2000 to 2020 in Shandong Province, China

Zhu

Xing

Hou

2022

Sci Rep

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Land cover change affects the carbon emissions of ecosystems in some way. The qualitative and quantitative understanding of carbon emissions from human activities (e.g., land cover change, industrial production, etc.) is highly significant for realizing the objective of carbon neutrality. Therefore, this paper used GlobeLand30 land cover maps, annual average normalised difference vegetation index (NDVI) data, annual average net ecosystem productivity (NEP) data and statistical yearbook data from 2000 to 2020 to explore the relationship between land cover change and carbon emissions. Specifically, it included land cover change, carbon storage changes influenced by land cover change, spatial and temporal analysis of carbon sources and sinks, land use intensity change and anthropogenic carbon emissions. The results of the study show that the main land cover changes in Shandong province during 2000–2020 was cultivated land conversion to artificial surfaces. Among them, the area of cultivated land converted to artificial surfaces from 2000 to 2010 was 4930.62 km2, and the proportion of cultivated land converted to artificial surfaces from 2010 to 2020 was as high as 78.35%. The total carbon stock of vegetation affected by land cover change decreased by 463.96 × 104 t and 193.50 × 104 t in 2000–2010 and 2010–2020 respectively. The spatial and temporal distribution of carbon sources and sinks differed more markedly from 2000 to 2020, and land use intensity changes in Shandong Province showed an upward trend. Of the total energy production, industry has the largest energy consumption, followed closely by total energy consumption in transportation, storage and postal services.

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“…The quantification of the CO 2 released by gases into the atmosphere is relevant for the evaluation of the balance between deep derivation, biogenic and anthropogenic contributions [14]. Zhang et al [15] conducted in-depth research on the Yellow River Basin of China. They analyzed the spatial and temporal distribution characteristics of carbon emissions in the Yellow River from 2000 to 2019 by constructing a carbon emission model, carbon footprint and Moran's I index.…”

Section: Introductionmentioning

confidence: 99%

Study on the Spatial and Temporal Differentiation Pattern of Carbon Emission and Carbon Compensation in China’s Provincial Areas

Huang

Jia

2022

Sustainability

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Excessive carbon emissions lead to global warming, which has attracted widespread attention in the global society. Carbon emissions and land use are closely related. An analysis of land use carbon emissions and carbon fairness can provide guidance for the formulation of energy conservation and emission reduction policies. This study uses data on agricultural production activities, land use and energy consumption and uses the carbon emission coefficient method to calculate carbon emissions and carbon absorption. The tendency value is used to analyze trends in land use carbon emissions and carbon absorption. The Gini coefficient, ecological support coefficient and economic contributive coefficient are used to analyze the fairness and difference of carbon emissions. The results showed that: (1) During the study period, there were fewer provinces with rapid growth in carbon emissions and carbon absorption and more provinces with slow growth. (2) Cultivated land and woodland are the main carriers of land use carbon absorption, and most provinces steadily maintain the type of carbon absorption to which they belong. (3) Carbon emissions from construction land are the main source of total carbon emissions, and the high concentration areas of carbon emissions are mainly located in the more economically developed areas. (4) There are obvious regional differences in the net carbon emissions. By 2015, Shanxi–Shandong High–High agglomeration areas and Yunnan–Guangxi Low–Low agglomeration areas were finally formed. (5) The distribution of carbon emissions in different provinces is not fair, and the spatial distribution is obviously different. Based on the analysis results, relevant suggestions are made from the perspectives of carbon emission reduction and carbon sink enhancement.

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Spatial-temporal characteristics of carbon emissions from land use change in Yellow River Delta region, China

Cited by 148 publications

References 19 publications

Regional Differences and Convergence of Carbon Emissions Intensity in Cities along the Yellow River Basin in China

Regional Differences and Convergence of Carbon Emissions Intensity in Cities along the Yellow River Basin in China

Analysis of carbon emissions from land cover change during 2000 to 2020 in Shandong Province, China

Study on the Spatial and Temporal Differentiation Pattern of Carbon Emission and Carbon Compensation in China’s Provincial Areas

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