Integrating IPAT and CLUMondo Models to Assess the Impact of Carbon Peak on Land Use

Wang, Han; Jin, Yujie; Xingming, Hong,; Tian, Fuan; Wu, Jianxian; Nie, Xin

doi:10.3390/land11040573

Cited by 13 publications

(3 citation statements)

References 64 publications

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“…Since 2006, China has been the world's largest carbon emitter and is considered a region for international carbon reduction efforts [2]. According to the "Statistical Review of World Energy 2021," which is published by Beyond Petroleum (BP), China's carbon emissions increased from 7.71 billion tons in 2009 to 9.90 billion tons in 2020, an increase of 30.7% which places the country first in the world in terms of emissions growth [3].…”

Section: Background Of the Studymentioning

confidence: 99%

Urbanization Influences CO2 Emissions in the Pearl River Delta: A Perspective of the “Space of Flows”

Zhao

Chen

Sun

et al. 2022

Land

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As the largest carbon emitter in the world, China is facing increasing challenge to reduce CO2 emissions. Given this issue, exploring the influencing factors is of great significance for scientific low-carbon emission policymaking. Although previous literature has explored the effects of urbanization on CO2 emissions, the impact of the space of flow on urban carbon emissions have been less explored. Due to the increasing connection between cities, its impact on urban carbon emissions cannot be ignored. Thus, this paper takes the space of flows into account as an aspect of urbanization to supplement the existing literature and empirically examines the multiple effects of urbanization on CO2 emissions in the Pearl River Delta (PRD) urban agglomeration. By using a STIRPAT model, statistical data, and web crawler data, we examined impacts of different types of urbanization on CO2 emissions. Our empirical results show that: (1) Within the PRD urban agglomeration, urban linkage intensity is strongly connected to urban socioeconomic growth, establishing a geographical structure with Guangzhou and Shenzhen as the double core. (2) Our results show that urbanization exerts two opposite effects on CO2 emissions: positively connects carbon emissions with population urbanization, integrated urban linkage flow, and energy intensity, whereas economic urbanization and social urbanization are shown to be negatively correlated. However, spatial urbanization has no significant positive effect on urban CO2 emissions. (3) It is worth noting that urban linkage flows are the second most important factor affecting urban carbon emissions after economic urbanization. Our study could formulate effective planning suggestions for future CO2 emission reduction paths and development modes in the PRD.

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Section: Background Of the Studymentioning

confidence: 99%

Urbanization Influences CO2 Emissions in the Pearl River Delta: A Perspective of the “Space of Flows”

Zhao

Chen

Sun

et al. 2022

Land

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“…To better determine the transition rules in land change modeling, scientists have proposed admirable models and algorithms based on CA, such as multi-criteria evaluation (MCE) [20], logistic regression (LR) [21], multiple layer perception (MLP)-ANN [22], GEO-MOD [23], the SLEUTH model [24], conversion of land use and its effects (CLUE) family models [25][26][27], and the future land use simulation (FLUS) model [28]. However, most available models are weak in detecting the driving factor's contribution to land use change and capturing the evolutionary rules of the multiple-type patches.…”

Section: Introductionmentioning

confidence: 99%

Scenario Simulation of Land Use and Cover under Safeguarding Ecological Security: A Case Study of Chang-Zhu-Tan Metropolitan Area, China

Deng,

Quan,

Zhang

et al. 2023

Forests

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Scenario-based simulation in land use and cover change (LUCC) is a practical approach to maintaining ecological security. Many studies generally set constraints of LUCC utilizing ecological patches but without consideration of corridors connecting these patches. Here, we constructed a framework to balance urban growth and ecological security by integrating ecological security patterns (ESPs) into the PLUS model. This study selected Chang-Zhu-Tan Metropolitan Area (CZTMA) in central China as a typical case. Specifically, coupling quantitative demand with spatial constraints of multiple levels of ESPs, this study designed four scenarios, including historical tendency (HT), urban growth (UG), ecological conservation (EC), and coordinating city development and ecological protection (CCE). Then, the transformations and landscape patterns of LUCC were analyzed to evaluate the future land change from 2020 to 2050. The results show sixty-one key ecological sources in the CZTMA, mainly in higher-elevation forested areas. Forty-six ecological corridors were estimated using circuit theory. The building expansion was driven by accessibility to transportation and government locations and will contribute to the loss of forest and cropland in the future. The feature of different scenarios in alleviating the increasing fragmentation of patches and reducing the loss amount of ecological land showed EC > CCE > HT > UG. This study developed the ESP-PLUS framework and its modeling idea, which has the potential to be applied in other regions. This extension would assist decision-makers and urban planners in formulating sustainable land strategies that effectively reconcile eco-environmental conservation with robust economic growth, achieving a mutually beneficial outcome.

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“…To date, a large number of studies on land-use carbon emissions have been conducted from multiple angles and aspects at home and abroad [10], including the calculation of emissions on multiple scales and for different regions and methods [11][12][13]; influencing factors [14,15]; economic, social, and ecological effects [7,16]; optimization and control methods [17,18], and predictions [19][20][21]. The calculation of land-use carbon emissions can be summarized in two categories: "top-down" methods, starting from the social economy, including material balance, emission coefficients, actual measurements, and factor decomposition, and "bottom-up" methods, starting from ecological nature, including model simulations, sample plot inventories, and remote sensing estimations [22].…”

Section: Introductionmentioning

confidence: 99%

Spatial–Temporal Change Analysis and Multi-Scenario Simulation Prediction of Land-Use Carbon Emissions in the Wuhan Urban Agglomeration, China

Zhang

Dong

et al. 2023

Sustainability

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In the context of global warming, the Wuhan Urban Agglomeration is actively responding to China’s carbon peak and carbon neutrality goals and striving to achieve a reduction in carbon sources and an increase in carbon sinks. Therefore, it is critical to investigate carbon emissions from land use. This study uses the carbon emission coefficient method to calculate carbon emissions from land use in the Wuhan Urban Agglomeration, analyzes its temporal and spatial changes and differences in urban structure, and couples with the Markov–PLUS model to simulate and predict the carbon emissions of four scenarios of land use in 2035. The research found the following: (1) during the Wuhan “1+8” City Circle stage, carbon sources and emissions increased steadily, with average annual growth rates of 1.92% and 1.99%, respectively. Carbon sinks remained stable and then decreased, with an average annual growth rate of −0.46%. (2) During the Wuhan Metropolitan Area stage—except for 2020 and 2021, which were affected by COVID-19—carbon sources, sinks, and emissions continued to grow in general, and the average annual growth rates increased to 4.46%, 1.58%, and 4.51%, respectively. (3) In terms of urban structure differences, Wuhan is a high-carbon optimization zone; Xianning, Huangshi, and Huanggang are ecological protection zones; other cities, such as Ezhou, Xiaogan, and Xiantao are comprehensive optimization zones; and there is no low-carbon development zone. (4) The multi-scenario simulation results show that carbon sources and emissions are the highest under the economic development scenario, with values of 100.2952 and 9858.83 million tons, respectively, followed by cropland protection, natural development, and low-carbon development scenarios. Under low-carbon development, carbon sinks were the highest, with values of 1.9709 million tons, followed by natural development, economic development, and cropland protection scenarios. The research results are conducive to the formulation of carbon peak and neutrality goals as well as low-carbon development plans for the Wuhan Urban Agglomeration.

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Integrating IPAT and CLUMondo Models to Assess the Impact of Carbon Peak on Land Use

Cited by 13 publications

References 64 publications

Urbanization Influences CO2 Emissions in the Pearl River Delta: A Perspective of the “Space of Flows”

Urbanization Influences CO2 Emissions in the Pearl River Delta: A Perspective of the “Space of Flows”

Scenario Simulation of Land Use and Cover under Safeguarding Ecological Security: A Case Study of Chang-Zhu-Tan Metropolitan Area, China

Spatial–Temporal Change Analysis and Multi-Scenario Simulation Prediction of Land-Use Carbon Emissions in the Wuhan Urban Agglomeration, China

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