Urban Energy Efficiency Research Articles

Does urban shrinkage impact energy efficiency?: Evidence from Chinese Counties

Some cities in China are facing challenges due to population loss while also attempting to address energy conservation and emissions reduction. Although urban shrinkage can relieve pressure from energy consumption demands, such as water, electricity and gas, does it improve urban energy efficiency? This study attempts to answer this question. Based on Point of Interest (POI) big data and Global Human Settlement Layer (GHSL) raster data, this study identifies urban shrinkage from the coupling perspective of administrative and economic boundaries. It also examines the impact of urban shrinkage on energy efficiency. The results suggest that Chinese counties’ overall energy efficiency is experiencing a four-stage "decline-rise-decline-rise" trend, and the urban shrinkage of Chinese counties exists in three major areas: the Northeast, the Southwest, and the Centre. Compared to non-shrinking cities, urban shrinkage has a significant negative impact on improving energy efficiency. This impact exhibits significant heterogeneity. Specifically, compared with mature resource cities and cities in Western China, regenerative cities, non-resource cities and cities in Central China have less impact on energy efficiency. In addition, urban shrinkage may impede energy efficiency improvement by hindering industrial structure transformation and upgrading, energy-saving technology innovation, and financial development. Clarifying the relationship between urban shrinkage and energy efficiency is helpful for shrinking cities to change their development strategies, which is critical for sustainable development.

Internet infrastructure, digital development and urban energy efficiency

Internet infrastructure, digital development and urban energy efficiency

The service trade with AI and energy efficiency: Multiplier effect of the digital economy in a green city by using quantum computation based on QUBO modeling

This research examines the energy efficiency of city districts through the Malmquist–DEA model and investigates the spatial effects of the service trade and the digital economy on energy efficiency in urban green development. The study also delves into the specific context of the AI service trade to gain insights into and align with the emerging digital intelligence industry. The interplay of the service trade with the digital economy, alongside the AI service trade with innovation, significantly enhances urban energy efficiency and demonstrates positive externalities. Building on the empirical findings, this research employs cluster analysis to explore the green development of city districts and uses AI technology to program green communication and cooperation mechanisms across district clusters, employing quantum computation based on QUBO modeling. This study contributes to a deeper understanding of the cofunction of the service trade and the digital economy in terms of energy efficiency and aids in developing new quality productivities for green cities through quantum-based AI advancements. This research has clear implications for cutting-edge interdisciplinary applications of green AI technologies in social computing science.

Research on energy saving effect of spatial correlation network of digital infrastructure: based on the analysis of network centrality.

Accurately portraying the spatially linked network characteristics of digital infrastructure and exploring its energy-saving effects are highly valuable for enhancing the synergy in digital infrastructure development and expanding its network spillover effects on energy conservation. This paper uses panel data at the city level in China and employs a modified gravity model to calculate the centrality of digital infrastructure spatial correlation network nodes. Based on this, an econometric model is constructed, incorporating variables such as digital infrastructure spatial correlation network node centrality and urban green total factor energy efficiency. The model is used to analyze the effects and transmission paths of digital infrastructure network node centrality on urban green total factor energy efficiency. The analysis yields the following conclusions: (1) Digital infrastructure spatial correlation network node centrality significantly improves urban green total factor energy efficiency, with considerable variability due to city geographic location, city scale, and city attributes. (2) Nonlinear testing results indicate that as digital infrastructure construction advances, its impact on urban green total factor energy efficiency shifts from inhibitory to promotional. (3) The impact mechanism shows that digital infrastructure node centrality enhances urban green total factor energy efficiency through green technology innovation. Additionally, it promotes advanced industrial structures and reduces capital mismatch, further influencing energy efficiency. (4) Digital infrastructure node centrality not only boosts urban green total factor energy efficiency but also facilitates regional convergence, increasing the convergence rate from 0.094 to 0.170%. The findings of the research offer policy guidance for the government on advancing digital transformation initiatives and enhancing energy efficiency.

Urban green total factor energy efficiency and its decomposition under a multidimensional heterogeneity framework: a case study of the Yellow River Basin, China.

Assessing and monitoring the green total factor energy efficiency (GTFEE) of cities while considering technology heterogeneity is crucial for the development of energy-conservation and emission-reduction policies. Considering that the heterogeneity of production technologies encompasses several dimensions, this paper proposes a 3E3S (Economy-Environment-Energy-Society-Science-Space) heterogeneity framework and integrates it with the improved meta-frontier global SBM-undesirable to analyze GTFEE and its decomposition. Empirical analysis of cities in the Yellow River Basin of China (YRBC) highlights the following: (1) The 3E3S heterogeneity framework facilitates the classification of all cities into three distinct groups, a finding that contrasts significantly with previous outcomes documented in the literature that relied solely on criteria such as geographic location. (2) The three groups identified under the meta-frontier exhibit substantial energy-saving potentials of 24.49%, 35.17%, and 52.46%, respectively. Additionally, there are spatiotemporal variations in GTFEE, with cities located in the central part of YRBC, particularly those in Shanxi province, demonstrating poor GTFEE performance. (3) The decomposition analysis of GTFEE indicates that technological progress plays a pivotal role in enhancing GTFEE on the whole, albeit with varying approaches for improving GTFEE depending on individual cities.

Examining Sustainable Urban Design Pattern by Explaining the Compatibility Model based on Density in Residential Fabrics of District 4th in Tehran City

Concerns about energy and climate change have taken center stage in urban studies in recent years. Buildings are the primary focus of the problem of maximizing energy efficiency in cities, and among the energy Additionally, the most crucial aspects of urban energy efficiency research are consumption, solar radiation energy on the one hand, and thermal energy demand on the other. These factors, together with other climatic factors, primarily influence the standard of life in urban areas. The main aim of research is to establish a model of sustainability in the physical form of the city, the primary objective of the current research is to extract the ideal framework and also the proposed model in the form of a structure for the concept of urban design in urban morphology, which is, on the one hand, the architectural scale of the buildings of the urban fabrics. In terms of structure, the current research is analytical-descriptive, and the method of data collection is in the form of documentation, survey, modeling and simulation using energy analysis software in the field of energy with a micro-analytical approach of urban climate such as Envi-met. For this reason, 4 morpho-types were evaluated in the context of the 4th district of Tehran, and the findings of the research show the difference between the optimal state and the current state of the evaluated parameters, and the amount of difference and the effect of added density in each morphological type of the effective range based on the index It explains that the high-rise building type has the most positive changes in the proposed conditions, and the compact types have lower values respectively. In the future researches, other morphological variables and adaptation modes with climatic parameters can also be investigated in order to achieve energy efficiency in other modes. DOI: https://doi.org/10.52783/pst.545

Improving Urban Energy Efficiency Through the Collaborative Effect of Policy Mix – Urban Panel Analysis Based on China

Improving Urban Energy Efficiency Through the Collaborative Effect of Policy Mix – Urban Panel Analysis Based on China

A Roadmap for the Implementation of Building Energy Efficiency Codes Compliance in Tripoli-Lebanon: Key Actions in the Familiarity Stage

Objective: The objective of this study is to provide policy recommendations for strengthening governance and institutional capabilities to ensure effective climate action and sustainable development in Tripoli-Lebanon and to propose a multi-staged implementation framework for T-BEEC, focusing on familiarity, with the aim o To facilitate Lebanon's transition towards sustainable energy sources by implementing an effective Building Energy Efficiency Code (T-BEEC) in Tripoli. Theoretical Framework: The study employs environmental science, urban planning, and socio-economic theories, focusing on policy adoption and the diffusion of technological innovations to enhance urban energy efficiency and sustainability. Method: A mixed-methods approach is adopted, incorporating both qualitative and quantitative research methods. Data collection involved semi-structured interviews with key personnel at the Tripoli Municipality Permit Office and thematic analysis of the barriers and facilitators to BEEC implementation. Comparative case studies from different geopolitical regions provide a broader perspective on the challenges and strategies of energy code compliance. Results and Discussion: Findings emphasize the critical need for infrastructure and resource optimization, including vehicle maintenance and replacements, spatial layout reorganization, and the prompt repair of computers and printers, to ensure operational efficiency. Additionally, the pursuit of diverse financial support sources highlights the reliance on municipal fees, international aid, NGO contributions, and educational partnerships to overcome financial and resource constraints Research Implications: This study impacts urban energy management theory and practice, providing key insights for policymakers and planners in similar settings. Originality/Value: This study outlines a unique approach to implementing energy codes during Tripoli's familiarity period, enhancing urban sustainability and policy effectiveness.

Towards a high-energy efficiency world: Assessing the impact of artificial intelligence on urban energy efficiency

Global warming has increased the frequency of natural disasters, making enhancing energy efficiency an inevitable choice to address the worsening global climate risks. Whether industrial robots, as a crucial component of artificial intelligence, can contribute to improving energy efficiency remains a subject of debate. This study employs the SBM and super-efficiency SBM models to assess the energy efficiency of 262 Chinese cities from 2010 to 2020. We investigate the impact and mechanisms of industrial robots at the city level on energy efficiency. The research findings indicate that the application of industrial robots promotes enhanced energy efficiency, which remains robust after subjecting it to a battery of tests, including SYS-GMM and instrumental variable analyses. However, a significant nonlinear relationship exists between industrial robot utilization and energy efficiency, with diminishing marginal effects. Mechanism analysis reveals that the fundamental mechanisms facilitating this improvement are the digital economy, industrial structural adjustments, and innovations in green technology. Heterogeneity analysis suggests that industrial robots have a more pronounced impact on cities with higher energy efficiency, greater manufacturing levels in resource-dependent areas, and lower population densities. Furthermore, the application of industrial robots can influence the energy efficiency of neighboring regions through spatial spillover effects.

Exploring the dynamics of urban energy efficiency in China: A double machine learning analysis of green finance influence

Analysing the impact of green finance policies on urban energy efficiency contributes to finding solutions to promote the development of China's low-carbon energy system and the global reduction of greenhouse gas emissions. Utilizing Chinese urban data from 2006 to 2021, the study employs an enhanced non-radial distance function (NDDF) model to evaluate the energy efficiency of 282 prefecture-level cities. It examines the 'Green Finance Reform and Innovation Pilot Zone' policy as a quasi-natural experiment. It uses a double machine learning model to analyze its effect on urban energy efficiency and its mechanisms. The research demonstrates that green finance policies significantly improve energy efficiency, mainly through strengthening environmental regulation, fostering green technology innovation, and optimizing industrial structure. Additionally, an in-depth analysis of regional heterogeneity reveals variations in the policy's effectiveness across eastern, central, and western regions and between resource-rich and resource-poor cities. The findings suggest that the efficacy of green finance policies, while generally positive, is influenced by regional economic development and resource endowment differences. The study suggests targeted strategies to improve the green finance system, customize policies according to regional specifics, incentivize corporate green innovation, and foster cross-sectoral collaboration. By offering novel insights into sustainable development and providing actionable policy recommendations, this research contributes to advancing Chinese urban centres' economic and environmental sustainability through the strategic application of green finance.

The impact of smart city construction on urban energy efficiency: evidence from China

The impact of smart city construction on urban energy efficiency: evidence from China

The Impact of Artificial Intelligence Development on Urban Energy Efficiency—Based on the Perspective of Smart City Policy

China’s economy is stepping into a new stage of high-quality development. The shift not only marks the optimization and upgrading of the economic structure, but also reflects the in-depth implementation of the concept of sustainable development. In this context, the development of AI technology is playing an important role in balancing economic growth and ecological protection with its unique advantages. This paper empirically studied the impact of AI development on urban energy efficiency by constructing panel data for 282 prefecture-level cities from 2006 to 2019 and then using the super-efficiency SBM model based on non-expected outputs to evaluate the urban energy efficiency indicators of prefecture-level cities. It was discovered that the development of AI had a key influence on increasing urban energy efficiency and the optimization of the energy structure by speeding up green technology innovation and digital economy development, which in turn improved urban energy efficiency. In terms of heterogeneity analysis, AI development had a greater impact on urban energy efficiency in the eastern region, which has higher levels of human capital, financial independence, and government intervention. This study combined the smart city pilot policy with a multi-period DID model, based on the treatment of endogeneity issues, in order to perform a parallel trend test and investigate further the effects of policy implementation on the advancement of AI in the context of improving urban energy efficiency. Accordingly, to achieve green and sustainable urban development, the relevant government departments should increase funding for AI research and development, pay attention to the introduction and cultivation of professionals, establish a platform for international exchanges and cooperation between AI and energy management, and continue to advocate for the pilot development of smart cities to increase urban energy efficiency.

Assessing the impact of prefabricated buildings on urban green total factor energy efficiency

Prefabricated buildings (PB) are assembled using prefabricated components, known for their cost-effectiveness and high efficiency. They are seen as an effective means to achieving sustainable development goals and mitigating climate change. This paper examines the impact of prefabricated buildings on urban green total factor energy efficiency (GTFEE) using panel data from 278 cities in China. The analysis is conducted through the application of a super-efficiency slack-based measure (SBM) model and a difference-in-differences model. The results of the study indicate that the promotion of PB can significantly improve urban GTFEE; there is heterogeneity in the improvement of urban GTFEE by PB; the innovation effect, industrial effect and marketization effect of PB are the main ways to improve urban GTFEE. Specifically, PB exerts an innovation effect by promoting technological innovation. It influences consumer and investor demand, leading to increased activity in the secondary industry, thereby creating an industrial effect. Moreover, PB facilitates the marketization effect by phasing out outdated industries, encouraging autonomous enterprise innovation, and fostering the growth of new advanced enterprises. This study reveals the critical role of PB in urban GTFEE improvement. It clarifies its mechanism of action, which provides a reference for urban sustainable development strategies and energy efficiency.

Waste-Based Vertical Planting System Proposal to Increase Productivity in Sustainable Horticulture; “PETREE”

The problems experienced with the decrease in agricultural areas per capita against the uncontrolled population growth in the World and in Turkey are becoming increasingly evident. Especially the manpower engaged in horticulture is increasingly experiencing the problems of migration, economic reasons, and inefficient production methods. For healthy and efficient production, agricultural lands need a sequential cycle that includes cultivation and fallow periods. Agricultural lands, the salt they contain, etc. When left fallow, the soil area needs to rest to re-establish the mineral balance. It is now vital for small producers, whose production areas are gradually shrinking due to global conditions, to continue production while their lands are resting to produce more continuously and efficiently. In the face of increasing demands, decreasing production amounts and areas, the constantly increasing prices of economically simple agricultural products “fresh vegetables” and affecting the easy accessibility of local products, it has become inevitable to seek new and alternative solutions. This study includes an innovative solution proposal to increase the production efficiency of low-scale producers and individual gardeners, especially those producing in small agricultural areas. Critical problems of large-scale greenhouse systems, interactions of agricultural practices within the framework of urban life, water and energy efficiency in agriculture, and sustainability and waste management of the proposed system are examined. To meet changing conditions and maintain productivity in small areas, it is envisaged that mobile and vertical production stations, which can produce by increasing productivity even in fallow areas while the soil is resting, can be an alternative solution to the problems of small producers. The vertical planting system “PETREE” develops mobile units for sustainable agriculture by collecting 5th LT-PET packages, which have a natural lifespan of about 90 years, and reusing them as plant pots and some recycled plastic pieces as structures. With efficient and environmentally friendly design suggestions, the system also examined the possibilities of more efficient gardening with mobile production stations in small agricultural areas, and efficient and enjoyable gardening that suits the needs of urban consumers “production with local seeds and seedlings” with the increase in environmental awareness and food safety concerns.

Can low-carbon city pilot policies improve urban energy efficiency? evidence from a quasi-natural experiment in China

In the context of global efforts to alleviate climate change, this study focuses on investigating the significance and impact of low-carbon city pilot policies (LCCPP), a key strategy in the reduction of greenhouse gas emissions. Drawing on data from prefecture-level cities spanning 2004 to 2019, the study explores the potential of LCCPP in enhancing green total factor energy efficiency (GTFEE) employing a multitemporal Difference-in-Differences (DID) model and examines its transmission mechanisms. First, LCCPP is shown to be effective in enhancing GTFEE. Second, heterogeneity testing indicates that the impact of LCCPP on GTFEE is more pronounced in “two control zones”, namely, in developing and mature resource cities. Third, industrial restructuring is identified as the key mechanism through which LCCPP influences GTFEE.

Government auditing and urban energy efficiency in the context of the digital economy: Evidence from China's Auditing System reform

Government auditing plays a crucial role in enhancing energy efficiency and advancing green and low-carbon economic development. Given that audit oversight's quality and efficiency are influenced by the independence of auditing institutions, this study utilizes the vertical management reform of government auditing institutions as an exogenous shock, and empirically examines its impact on urban energy efficiency (UEE) using a Difference-in-Differences model (DID). We find that the audit reform improved UEE by 0.023 which is both economically and statistically significant. Concurrently, the audit reform and the development of the digital economy play substitutive roles in enhancing UEE. Finally, the results of the mediation analysis using the stepwise regression method indicate that the improvements in audit efficiency, green technology innovation, and energy structure optimization have mediated the promotion of UEE in the audit reform process, accounting for respective mediation effects of 4.35%, 4.35%, and 8.69%.

Mapping the Evolution of Green Finance Research and Development in Emerging Green Economies

Research on green and sustainable finance is increasing, crucial for advancing a green financial system and economic growth. Utilizing a Scopus database, this paper collects data and, through bibliometric analysis in R studio, visually explores research trends, hotspots, and fronts in green finance and sustainable development across top emerging green economies. From 2001 to 2022, publications in this field have grown annually, with China leading globally. Significant hotspots include urban total factor energy efficiency, reducing carbon emissions, regional economic development, climate adaptation, technological progress, green innovation, and transitioning from linear to circular economy models. The study anticipates future research to focus on refining industrial and financial structures that align sustainable, green development with superior ecological environment protection, highlighting the evolving nature of green finance research and its impact on promoting sustainable economic practices.

Sustainable energy efficiency in China from the perspective of environmental development: A comprehensive analysis of regional disparities and policy implications

Global agreements have emerged in order to achieve carbon neutrality as the needs for renewable energy sources and carbon reduction continue to grow. To achieve the global carbon neutrality goals, China, one of the largest carbon emitters, must improve urban energy efficiency. Using a three-stage slacks-based measure (SBM) technique, this study analyses the total factor energy efficiency of 270 prefecture-level cities from 2011 through 2020. It tries to monitor and evaluate energy efficiency without taking into account variations in the outside environment. China's total factor energy efficiency shows an overall rising trend, despite significant regional variations. Improved energy efficiency levels can be attributed to technical advancements, while limitations in technology contribute to lower energy efficiency in certain areas. The study highlights the importance of considering external environmental factors in evaluating energy efficiency, able to avoid an overestimation of China's overall energy efficiency. It is noteworthy that the eastern region consistently outperforms the national average in terms of energy use efficiency. Even after taking environmental factors out of the equation, the central, west, and northeast regions still have worse energy efficiency and slower rates of growth. On this basis, from strengthening energy management and planning; facilitating cross-regional sharing of expertise; take targeted policy measures to adapt to the characteristics of the western and northeastern regions and put forward policy suggestions. These guidelines contribute to international energy cooperation and carbon reduction initiatives, while promoting sustainable energy development in China.

Evaluating the Role of Green Infrastructure in Microclimate and Building Energy Efficiency

This study investigates how permeable and cool pavements, green roofs, and living walls affect microclimatic conditions and buildings’ energy consumption in an arid urban setting: Shiraz. The study aims to evaluate the role of green infrastructure in mitigating urban heat island effects and enhancing outdoor conditions. By utilizing environmental modeling tools, specifically the ENVI-met 5.1.1 and Design Builder 7.0.2 software, a comprehensive analysis was conducted across various scenarios during both the summer and winter seasons. The results show that permeable pavements with 80% grass coverage reduced the mean average air temperature by 1.18 °C in summer mornings compared to the reference case. In both the summer and winter scenarios, the living wall intervention consistently emerged as the most effective strategy, showcasing substantial reductions in cooling consumption, CO2 emissions, and electricity consumption. With a 25% reduction in cooling consumption, a 14.7% decrease in CO2 emissions, and an impressive 53.4% decline in electricity consumption, the living wall excelled in its environmental impact, and it stands out for its substantial electricity savings. While the green roof and permeable pavement scenarios demonstrated more modest gains, their integration could offer a synergistic solution, warranting further exploration for optimized energy efficiency and environmental sustainability. These findings indicate the intrinsic connection between sustainable landscaping strategies and their influence on urban microclimate and building energy efficiency.

The influence of smart city policy on urban green energy efficiency -- A quasi-natural experiment based on 196 cities

Based on 196 prefecture-level cities in China from 2006 to 2021, this paper constructs a weight matrix of urban economic geography and uses the spatial differential model to verify the impact of smart city policies on urban green energy efficiency. The results show that the efficiency value of green energy fluctuates in Chinese cities. Different test results show that smart city policies can effectively improve urban green energy efficiency, but mainly from the time effect rather than the individual effect. It means the improvement in urban green energy efficiency comes more from the fast-growing of the Chinese economy and urban construction in this period than from the country's smart city pilot policy. In addition, from the spatial spillover effect result, China needs to design a better urban spatial development plan to improve the capacity of smart city energy services and vigorously develop intelligent technology represented by information and communication science.