Uncovering the roadmap of decoupling economic growth and CO2 emissions targeting energy-resource-emission-intensive industrial parks located nearby large river: Practices and implications from China

Qian, Yisen; Zhao, Jialing; Lyu, Yizheng; Liu, Yang; Tian, Jinfeng; Chen, Lyujun

doi:10.1016/j.jclepro.2023.136306

Cited by 13 publications

(4 citation statements)

References 21 publications

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“…In terms of the elasticity value, Tapio classifies the degree of decoupling into eight types. The details are shown in Figure 2.In recent years, the Tapio decoupling model has been extensively used to study the relationship between carbon emissions and economic growth in IPs [28][29][30].…”

Section: Tapio Decoupling Methodsmentioning

confidence: 99%

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

Ma,

Liu,

et al. 2024

E3S Web Conf.

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As the primary territories of regional carbon emission and energy consumption, most industrial parks only simply stack technology and policy under the urgent goal of emission reduction and carbon reduction. As a result, certain measures may even have negative impacts. As the primary means to determine the characteristics of carbon emissions in industrial parks, studying the driving factors of carbon emissions and proposing targeted measures can effectively achieve the carbon emission reduction goals. However the mechanism analysis of driving factors of carbon emission in industrial parks is the important means to study the characteristics of carbon emission. The selection of driving factors is many and complicated, and the selection of mechanism analysis methods is different, so it is difficult to have a comparison of research results Based on the quantitative relationship model between carbon emissions and driving factors and the method of action mechanism analysis in industrial parks, this paper evaluates and compares the relevant studies, summarizes their advantages and disadvantages, and makes relevant comments and prospects. For providing reference for the practice of driving factors of carbon emission in industrial parks, and put forward the basis for the research of carbon emission prediction.

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Section: Tapio Decoupling Methodsmentioning

confidence: 99%

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

Ma,

Liu,

et al. 2024

E3S Web Conf.

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“…In this research, the link between the three functions is investigated using the decoupling analysis method [44]. Currently, there are various methods used to study the decoupling state, such as the integrated analysis of change method and the IPAT model method [45]. Among them, the Tapio elasticity analysis method is widely used in the fields of economic growth and resource environments.…”

Section: Tapio Decoupling Modelmentioning

confidence: 99%

Analysis of Spatial and Temporal Pattern Evolution and Decoupling Relationships of Land Use Functions Based on Ecological Protection and High-Quality Development: A Case Study of the Yellow River Basin, China

Du,

Wang,

et al. 2024

Land

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With rapid industrialization and urbanization, the contradiction between the human exploitation of land production and living functions and natural ecosystem service functions has intensified. The issues of how to coordinate the exploitation and conservation functions of land and guide the rational distribution of human activities have become important for global sustainable development, especially considering the realization that multifunctional land use is an effective way to relieve land pressure and improve land use efficiency, that land multifunction has significant spatio-temporal heterogeneity, and that there is a mutual promotion and stress relationship between multifunctional land use. However, few existing studies have discussed the decoupling relationship among land use functions. In this study, a system of 10 sub-functions and 25 indicators was established based on the production function (PDF), living function (LVF), and ecological function (ELF) for 59 cities in the Yellow River Basin (YRB). There are both subjective and objective procedures employed to determine the weights, while an exploratory spatial data analysis is used to analyze the time-based and territorial changes in various functions of land use in the study area from 2000 to 2020. The decoupling relationship between the three functions is detected utilizing the theoretical foundation of the decoupling analysis. The results show that land use is multifunctional, LUFs develop unevenly, and their spatial distribution varies substantially. The results of the decoupling analysis demonstrate that the predominant types of correlations among the land use ELF and PDF and LVF over the research period are strong decoupling and strong negative decoupling correlations, with the former being a dilemma and the latter being a sustainable type of development.

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“…The achievement of the "3060 dual carbon target" not only relies on macroeconomic regulation at the national level but also on specific response measures at the local level. Therefore, each region needs to develop an accurate scientific understanding of the local carbon emissions situation, determine the driving factors, and then quantify and clarify emissions-reduction pathways to achieve precise emissions reduction [4,5].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Heterogeneity of the Characteristics and Influencing Factors of Energy-Consumption-Related Carbon Emissions in Jiangsu Province Based on DMSP-OLS and NPP-VIIRS

Meng

Zhang

et al. 2023

Land

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Scientific estimations and the dynamic monitoring of the development trend of carbon emissions from energy consumption with a long time series can provide the scientific basis for formulating and implementing regional carbon-reduction strategies. Based on DMSP-OLS and NPP-VIIRS night-time light data, a pixel-scale estimation model of energy-consumption carbon emissions in Jiangsu Province from 2000 to 2019 was constructed. The spatiotemporal evolution characteristics and influencing factors were analyzed using the GIS method and a GTWR (geographically and temporally weighted regression) model. The results showed that: (1) The goodness of fit of the image-fusion correction of the two night-time light data sources from 2012 to 2013 was 0.894; the goodness of fit of the carbon-emission estimation model by stages was above 0.99; and the average relative error was 7.71%, which met the requirement for the estimation accuracy. (2) During the study period, the total carbon emissions from energy consumption in Jiangsu Province continued to increase, rising from 94.7618 million tons to 313.3576 million tons, with an annual growth rate of 6.50%; and the growth rate presented an upward trend of “slow-accelerate-decelerate”. Spatially, it showed an unbalanced distribution pattern of “low north and high south”. (3) Per-capita GDP and energy intensity were the core driving factors affecting carbon emissions in Jiangsu Province over the past 20 years. Energy intensity had the greatest driving effect on carbon emissions in southern Jiangsu, while per-capita GDP had the greatest influence in central and northern Jiangsu. Coordinating the relationship between central, north, and south Jiangsu is of great significance for the realization of the sustainable economic and social development of the double carbon goal.

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Uncovering the roadmap of decoupling economic growth and CO2 emissions targeting energy-resource-emission-intensive industrial parks located nearby large river: Practices and implications from China

Cited by 13 publications

References 21 publications

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

Evaluation and Comparison of Research Methods on Driving Factors of Carbon Emission in Industrial Parks

Analysis of Spatial and Temporal Pattern Evolution and Decoupling Relationships of Land Use Functions Based on Ecological Protection and High-Quality Development: A Case Study of the Yellow River Basin, China

Spatiotemporal Heterogeneity of the Characteristics and Influencing Factors of Energy-Consumption-Related Carbon Emissions in Jiangsu Province Based on DMSP-OLS and NPP-VIIRS

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