The mechanism for selecting low carbon urban experimentation cases in the literature and its impact on carbon emission performance

Lu, Haiyan; Meng, Haili; Lu, C; Shang, Di; Wang, Dong; Jiang, Hong

doi:10.1016/j.jclepro.2023.138191

Cited by 5 publications

(1 citation statement)

References 37 publications

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“…In light of this, increasing attentions have been given from academia to the exploration of the driving factors that contribute to improving urban carbon emission performance in recent years. A number of studies have examined the various drivers of carbon emission performance from different insights, including economic growth (Schröder and Storm, 2020;Yang and Zhao, 2023), energy efficiency (Bilgili et al, 2023;Lu et al, 2023), foreign direct investment (FDI) (Zhu et al, 2016;Song et al, 2021), internet development (Lin and Zhou, 2021;Pan et al, 2023), corporate governance (Ferrat, 2021;Lv et al, 2021), and digital economy (Zhang et al, 2022;Zhao et al, 2023). However, it is worth noting that there is a scarcity of studies that have specifically examined the potential impacts of domestic research and development (R&D) activities, particularly in the energy field, on the improvement of urban carbon emission performance.…”

Section: Introductionmentioning

confidence: 99%

The impact of energy-saving R&D on urban carbon emission performance: evidence from 218 prefecture-level cities in China

Abudureheman,

Yiming

2024

Front. Environ. Sci.

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Different from the previous studies that mainly focus on the environmental and economic benefits of the total R&D, we specifically focus on the R&D activities in the energy field, namely, energy-saving R&D in this study, and explored the spatial impacts of energy-saving R&D on urban carbon emission performance and its internal transmission mechanisms for the first time. The heterogeneity analysis from the perspectives of different-types of R&D and different urban groups were also conducted. Results indicate that: Energy-saving R&D has obvious promoting effect on the improvement of urban carbon emission performance, among which the utility-type energy-saving R&D plays a more important role than the invention-type R&D. Energy-saving R&D promotes urban carbon performance mainly through the transmission mechanism of technical effects, while structural effect and urbanization effect negatively affects carbon emission performance due to the existence of energy rebound. Furthermore, there exists significant spatial spillover effects of energy-saving R&D on urban carbon emission performance, and economic factors play a more important role in this spatial effect. In addition, the impact of energy-saving R&D on carbon emission performance has obvious urban group heterogeneity. Finally, we proposed several policy suggestions based on the main conclusions of this study.

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Section: Introductionmentioning

confidence: 99%

The impact of energy-saving R&D on urban carbon emission performance: evidence from 218 prefecture-level cities in China

Abudureheman,

Yiming

2024

Front. Environ. Sci.

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How to promote the construction of low‐carbon cities in China? An urban complex ecosystem perspective

Zhu,

2024

Sustainable Development

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The escalation of carbon emissions has propelled global warming into a global issue requiring urgent attention. As primary contributors to global carbon emissions, cities constitute the central battleground for efforts aimed at carbon emission reduction. Notably, China, the world's largest carbon emitter, has channeled substantial human and financial resources towards the development of low‐carbon cities. However, the multifaceted challenges confronting Chinese low‐carbon city construction (LCC), including the lack of clearly defined construction strategies and deficiencies in government policy implementation, underscore the need for a systematic exploration of the influencing factors and mechanisms to overcome these obstacles. In response to this pressing need, this study utilizes a conceptual framework that is deeply rooted in the complex urban social‐economic‐natural‐management ecosystem. Within this framework, the study meticulously identified 12 influencing factors and, employing the pressure‐state‐response (PSR) model, categorized them to elucidate the dynamic and multidimensional nature of low‐carbon city construction. Subsequently, the DEMATEL method was employed to explore the causality and centrality of these 12 factors, and the ISM method was used to analyze the hierarchical structure and influencing factors and mechanisms of LCC. Three paths from LCC pressure to LCC response were established. Finally, three major implications were proposed to help Chinese LCC: (i) improve urban strategic planning applicability in a one‐city‐one‐policy manner, (ii) strengthen the green economy's long‐term development mechanism, and (iii) use the enthusiasm of market forces and public participation.

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Evaluation of urban low-carbon development efficiency: evidence from 30 cities in China

Xiang,

Li,

Liu

2024

Environ. Res. Commun.

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With the acceleration of global urbanization, the issues faced by urban development are becoming increasingly apparent. Some countries and regions have placed less emphasis on low-carbon emissions in the development process and prioritized urban development. However, blindly pursuing rapid urbanization has led to excessive urban carbon emissions, which outweigh the gains. Therefore, based on panel data from 30 cities in China from 2010 to 2019, this study combines the super-efficiency slacks-based measure (SBM) model and the Malmquist index, taking urban carbon emissions as undesirable outputs, to evaluate urban development efficiency. Through a multidimensional comparative analysis, this study reveals the developmental challenges encountered by various cities. The results show that: statically, the overall urbanization progress of these 30 cities is commendable, but significant fluctuations are observed in the development trend. The mean super-efficiency of cities in the eastern coastal areas is relatively high, whereas other regions exhibit instances of ineffective mean super-efficiency. Dynamically, there are few periods of efficiency improvement during 2010–2019, and there is an imbalance in the sources of efficiency improvement. Shanghai and Hangzhou exhibit the best continuous dynamic improvement status, with small fluctuations in dynamic efficiency, whereas Guiyang has the worst dynamic efficiency improvement status, indicating poor urban development. This study underscores the urgent need for a balanced approach to urban development that incorporates low-carbon initiatives to ensure sustainable progress and mitigate adverse environmental impacts.

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The mechanism for selecting low carbon urban experimentation cases in the literature and its impact on carbon emission performance

Cited by 5 publications

References 37 publications

The impact of energy-saving R&D on urban carbon emission performance: evidence from 218 prefecture-level cities in China

The impact of energy-saving R&D on urban carbon emission performance: evidence from 218 prefecture-level cities in China

How to promote the construction of low‐carbon cities in China? An urban complex ecosystem perspective

Evaluation of urban low-carbon development efficiency: evidence from 30 cities in China

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