Urban Carbon Emissions Research Articles

Spatial-temporal differentiation and influencing factors of carbon emission trajectory in Chinese cities - A case study of 247 prefecture-level cities

Cities, where human energy activities and greenhouse gas emissions are concentrated, contribute significantly to alleviating the impacts of global climate change. Utilizing the China Carbon Emissions Accounting Database (CEADs) to provide carbon dioxide emission inventories for urban areas in China at the prefecture level, this study closely examines the historical evolution trajectories of carbon emissions across 247 urban units from 2005 to 2019. The logarithmic cubic function model was employed to simulate these trajectories, evaluating urban emission peaks and classifying the different carbon emission trajectories. Further, the Geographical and Temporal Weighted Regression model was employed to explore spatiotemporal traits and essential variables that impact the variations in carbon emissions among four identified trajectory types. Our results showed that Chinese urban carbon emission trajectories can be classified into four categories: a) peaking emissions, b) fluctuating growth, c) continuous growth, and d) passive decline. Specifically, 43 cities, primarily in North China, proactively attained their emission peak post-2010, driven by the reduction in secondary industry and energy intensity. 90 cities, largely industrial hubs in the southeast coast and inland, reached an emission plateau around 2015, exhibiting fluctuating growth due to dependencies on secondary industries. 101 cities, predominantly located in western and central regions, demonstrated a clear upward trend in carbon emissions, propelled by rapid urbanization and heavy industry-oriented economic development. Lastly, 13 cities, typically in the northeastern and southwestern regions, experienced a passive decline in carbon emissions, attributable to resource depletion or economic downturns. It is evident that China's city-level carbon peaking has demonstrated some effectiveness, yet considerable progress is still required.

Improving urban CO2 spatial distribution modelling using multi-source data

Urban areas contribute approximately 70% of the total anthropogenic CO2 emissions, making them the primary focus of global carbon monitoring. However, accurate modelling of urban meteorology is challenging because of complex artificial landscapes. Reducing errors in urban meteorological simulation and improving the accuracy of modelling the spatial distribution of urban CO2 is of great significance for the “top-down” CO2 emissions estimation in urban areas. In this study, local urban datasets were constructed based on multiple data sources to overcome the limitation of insufficient information from a single data source. In the development of urban datasets, grid-by-grid data processing is realized, and the evaluation results show that the developed urban datasets are greatly improved compared with the default. The developed urban datasets were applied to WRF-Chem with 1-km spatial resolution, and the simulated column-averaged dry air mole fraction of CO2 (XCO2) was verified with the EM27/SUN observed data considering the slant observation path. The results show that urban datasets strongly influence the spatial distribution modelling of XCO2, depending on the state of the atmosphere near the surface, especially wind velocity. Accurate local urban datasets can effectively reduce the bias in urban XCO2 spatial distribution modelling and improve the capability of the atmospheric CO2 transport model in urban carbon emission estimation.

Strategies for Mitigating Urban Residential Carbon Emissions: A System Dynamics Analysis of Kunming, China

To effectively combat environmental challenges, it is necessary to evaluate urban residential building carbon emissions and implement energy-efficient, emission-reducing strategies. The lack of a specialized carbon emission monitoring system complicates merging macro- and micro-level analyses to forecast urban residential emissions accurately. This study employs a system dynamics (SD) model to examine the influence of social, economic, energy, and environmental factors on carbon emissions in urban residences in Kunming, China. The SD model forecasts household carbon emissions from 2022 to 2030 and establishes three scenarios: a low-carbon scenario (LCS), a medium low-carbon scenario (MLCS), and a high low-carbon scenario (HLCS) to assess emission reduction potentials. It predicts emissions will climb to 4.108 million tons by 2030, significantly surpassing the 2014 baseline, with economic growth, urbanization, residential energy consumption, and housing investment as key drivers. To curb emissions, the study suggests enhancing low-carbon awareness, altering energy sources, promoting research and development investment, and expanding green areas. The scenarios indicate a 5.1% to 16.1% emission reduction by 2030 compared to the baseline. The study recommends an 8.3% to 11.4% reduction in MLCS as a practical short-term target for managing urban residential emissions, offering a valuable SD approach for optimizing carbon strategies and aiding low-carbon development.

Digital infrastructure empowerment and urban carbon emissions: Evidence from China

China is accelerating its entry into the digital age, and the contribution of digital infrastructure to the reduction of carbon emissions is becoming increasingly prominent. The influence mechanism of digital infrastructure on urban carbon emissions is empirically tested in this study from the standpoint of digital empowerment using panel data from 250 cities between 2008 and 2020. According to the study, digital infrastructure greatly lowers urban carbon emissions, with each additional mobile base station reducing carbon emissions by 36 tons. This conclusion remains robust even after controlling for endogeneity issues. The mechanism examination indicates that the decarbonization effect of digital infrastructure is mainly achieved by empowering enterprises, individuals, and governments with digital capabilities. Heterogeneity analysis reveals that the effects of digital infrastructure on carbon emissions vary after considering variations in the city's administrative hierarchy, industrial structure, and resource types in China. According to the study's findings, developing countries should expand digital infrastructure construction and fully harness its potential for energy saving and emissions reduction to meet their emission reduction targets. At the same time, differentiated emission reduction policies should be formulated to adapt to the heterogeneous characteristics among cities and ensure that emission reduction measures are effectively implemented in each city.

Dynamics of urban expansion and form changes impacting carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area counties

Cities are the main carriers of social and economic development, and they are also important sources of carbon emissions. Therefore, it is essential to explore the impact of urban expansion and form changes on carbon emissions. Here, we attempted to analyzes the relationship between urban expansion and carbon emissions at the county level in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1997 to 2017. It further decomposes the driving effects of carbon emissions from multiple factors, and considers the spatial heterogeneity between different urban form changes and driving effects. The results show that: The relationship between urban expansion and carbon emissions in the GBA has gone through three stages from 1997 to 2017, with 2012 as a turning point. Optimization of economic development models and strict protection of the ecological environment can effectively control carbon emissions. After 2012, the economic development effect (GE) and population scale effect (PE) are the driving factors of carbon emissions, while the carbon emission intensity effect (CE) and urban land intensity effect (UE) are the inhibitory factors of carbon emissions. The contribution rate of UE to carbon emission reduction can reach 86 %. The impact of urban form changes on carbon emissions has spatial heterogeneity. The changes in urban form have a significant impact on the carbon emissions of counties in Dongguan and Shenzhen. The increase in fragmentation indirectly promotes carbon emissions. In 2007–2012, the increase in centrality significantly weakened the economic development effect, which is conducive to emission reduction. After 2007, the increase in compactness in counties in the eastern part of the GBA, including Zhongshan and Zhuhai, is not conducive to emission reduction.

Research on the spatial effect of digital economy development on urban carbon reduction

Cities are one of the main sources of regional carbon emissions, and reducing urban carbon emission is the key to reducing emissions. The digital economy has transformed the economic operation mode, and it is a significant approach to support the “dual carbon goals” (carbon peaking and carbon neutrality). This article considers the externalities of the digital economy and carbon emissions. And we use spatial econometric models to analyze the effectiveness of digital economy in empowering carbon emissions reduction. Besides, we explore the static and dynamic spillover effects, and use spatial Durbin panel quantile model to analyze the digital economy’s heterogeneity on carbon emissions. Research has shown that the digital economy has a remarkable carbon reduction effect, and the conclusion remains valid after considering robustness tests such as replacing the weight matrices, calculation methods, and proxy variables. The analysis of static and dynamic spillover effects indicates that the degree of the digital economy’s impact on carbon emissions are significantly different. Heterogeneity analysis shows that as the digital economy develops from a low level to a high level, its impact on carbon emissions also shifts from positive promotion to negative suppression. This paper proposes a policy reference to help the development of digital economy and promote carbon neutrality in the face of severe environmental challenges.

How the Digital Economy Affects Urban Carbon Emissions Reduction—Research based on Panel Data of 263 Cities

How the Digital Economy Affects Urban Carbon Emissions Reduction—Research based on Panel Data of 263 Cities

The confrontation and symbiosis of green and development: Coupling coordination analysis between carbon emissions and spatial development in urban agglomerations of China

Chinese cities face challenges of uneven development, high carbon emission intensity, and low efficiency in urbanization processes. Achieving harmonization and equilibrium between urban development and carbon emissions is crucial for sustainable development. This paper analyzes the development trajectory from 2013 to 2021 of four urban agglomerations in China: Northeast China (NEC), Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD). It identifies and calculates the urban spatial development patterns and carbon emissions, comparing the spatial-temporal variations in carbon emissions under different urban development patterns. The study also explores the coupling coordination relationship between these two aspects at various stages. The findings suggest that urban spatial development and carbon emissions are often uncoordinated in shrinking cities. In terms of coordination within urban agglomerations, BTH and NEC show suboptimal development, characterized by overall lag and polarization; YRD exhibits the best development, being consistently stable and balanced; PRD is generally improving, though with some cities lagging. Planning departments should revise urban and environmental policies to optimize spatial structures and infrastructure, aligning with regional development and promoting synergy in urban agglomerations. This research provides theoretical and empirical support for China to formulate relevant policies aimed at green, coordinated, and sustainable urban development.

Can digital economy development contribute to urban carbon emission reduction? - Empirical evidence from China

In the context of global digitalization, fostering the expansion of the digital economy holds immense importance in promoting energy efficiency and reducing emissions. Utilizing a sample of 281 prefecture-level cities in China from 2003 to 2019, this research analyzes the impact of the digital economy on urban carbon emissions in China. This study employs various methods, including principal component analysis, fixed-impact model, and mediating effect model. Based on the research findings, the development of the digital economy has the potential to significantly reduce carbon emissions in metropolitan areas. Moreover, these effects are especially noticeable in cities located to the east of the Hu Huanyong Line. These cities are characterized by limited reliance on resources and a high level of marketization. Further research reveals that promoting technical innovation and modernizing industrial structures can reduce the intensity of carbon emissions in metropolitan areas. This study provides empirical evidence supporting the effective reduction of carbon emissions in developing countries during the evolution of the digital economy. It acts as a crucial cornerstone for guiding policies and executing strategies aimed at fostering top-tier economic development in the future. The findings of this study confirm the inhibitory effect of the digital economy on urban carbon emission intensity. However, this study has limitations in data samples, research scope, and depth of mechanism analysis, which prevent a full exploration of the spatial spillover effect of the digital economy and other factors. Therefore, the conclusions drawn in this study can only provide empirical evidence for identifying the relationship between the digital economy and carbon emission intensity to a certain extent. Future research should aim to expand on these aspects.

Retraction Note: Does energy consumption, economic growth, urbanization, and population growth influence carbon emissions in the BRICS? Evidence from panel models robust to cross-sectional dependence and slope heterogeneity.

Retraction Note: Does energy consumption, economic growth, urbanization, and population growth influence carbon emissions in the BRICS? Evidence from panel models robust to cross-sectional dependence and slope heterogeneity.

The divergent effects of polycentric urban form on urban carbon emissions: Spatial balance and spatial dispersion in Chinese cities

Polycentric development stands as a pivotal spatial strategy for promoting urban sustainability. However, its effectiveness in curbing urban carbon emissions (UCEs) remains debated. Few studies have unpacked drivers of these conflicting impacts. This study delves into the intricate nuances of polycentric urban form and its potential to mitigate UCEs in Chinese cities. First, we refine our understanding of polycentric form by incorporating both spatial balance (SB) and spatial dispersion (SD) as key attributes, showing SB decreases and SD increases UCEs in general. Second, SB effectively reduces industrial UCEs but has limited impacts on residential and travel-related emissions. SD drives UCEs in all sectors. Third, our multiscale geographically weighted regression (MGWR) model unveils how the impact of polycentric form on UCEs varies across different regional contexts. Notably, both impacts of SB and SD are more pronounced in the northern cities. Our decomposition of the influences from polycentric trends on UCEs contributes to the ongoing debates, offering a comprehensive understanding of the divergent sustainable effects of polycentricity. It underscores the necessity of tailoring the polycentric urban form to divergent attributes, specific UCEs sectors and regional contexts to achieve sustainability.

Impact of Green Infrastructure Investment on Urban Carbon Emissions in China

Given the increasingly severe global climate change, the reduction in urban greenhouse gas emissions has become the common goal of all nations. As a widely concerned sustainable development strategy, green infrastructure investment (GII) aims to reduce urban carbon emissions, improve the efficiency of resource utilization, and improve environmental quality. However, the construction cycle of green infrastructure is long, and the construction process itself may produce carbon emissions; so, the final effect of GII on urban carbon emissions is unclear, which deserves our in-depth study. Further, is this effect having a time-lag effect? Is there only a simple linear relationship between GII and urban carbon emissions? Based on panel data from 235 Chinese cities from 2006 to 2019, this study conducted an econometric regression analysis using time-lag-effect and threshold-effect models. The results showed the following: (1) GII had a negative inhibitory effect on urban CO2 emissions. Adding one unit to the GII could reduce urban CO2 emissions by 0.032 units. (2) GII exhibited a time-lag effect on urban CO2 emissions, and the greatest reduction in CO2 emissions occurred in the third lag period. (3) GII had a threshold effect on urban CO2 emissions based on technological progress (TP). This paper used the static and dynamic panel threshold models to research separately, and obtained the corresponding regression results. In the static panel, the double threshold values for TP were 3.9120 and 6.8035. At different TP levels, GII had an inhibitory effect on CO2 emissions, but the coefficients were different. However, in the dynamic panel, the threshold value was 3.666. The threshold changed over time and the effect of GII on CO2 emissions shifted from facilitation to inhibition.

The impact of different transportation infrastructures on urban carbon emissions: Evidence from China

Transport infrastructure is an important source of carbon emissions, and different transport infrastructure have varying impacts on urban carbon emissions, which has been lacking in previous research. This study selects 273 cities in China from 2005 to 2020 and applied the spatial Durbin model and mediation effect model to empirically examine the direct impact effects, spatial spillover effects, scale and regional heterogeneity, and indirect pathways of highways, high-speed railways, and urban rail on urban carbon emissions. The results shows that: (1) Overall, high-speed railways have a significant reducing effect on carbon emissions, while highways and urban rail have the opposite effect. (2) Considering spatial spillover effects, highways and high-speed railways can promote carbon emissions reduction in neighboring areas, while urban rail has the opposite effect. (3) For scale heterogeneity, urban rail can reduce carbon emissions in mega-cities, while highways and high-speed railways have the opposite effect. For regional heterogeneity, all three types of transport infrastructure can reduce carbon emissions in western cities, but increase urban carbon emissions in eastern and central regions. (4) Industrial upgrading, technological progress, and population agglomeration are all pathways through which transport infrastructure indirectly affects carbon emissions, but their effects vary for different transport infrastructure.

Can intellectual property rights pilots reduce carbon emissions? Evidence from China

In this paper, panel data from Chinese cities from 2000 to 2020 were used, and the intellectual property pilot was used as a quasi-natural experiment. The double difference model mainly tests the underlying mechanism of the impact of intellectual property rights pilots on urban carbon emissions. This study revealed that IPR pilots play an important role in reducing urban carbon emissions. Heterogeneity experiments reveal that IPR pilots are conducive to reducing carbon emissions in coastal as well as high greening cities and that the underlying mechanism through which IPR pilots affect urban carbon emissions mainly occurs at the level of innovation and the optimization of the industrial structure. In addition, this paper also validates the smoothness of the model by replacing the explanatory variables and performing a placebo test, which further strengthens the reliability of the paper’s conclusions.

Establishment of Free Trade Zones Does Not Suppress Urban Carbon Emissions

Constructing free trade pilot zones is an important strategic move for promoting reform and opening up in China in the new era. However, pollution control and emission reduction are obstacles that must be overcome in this process. This study takes cities implementing free trade pilot zone policies in China as the experimental group and other cities as the control group, establishing a "quasi-natural experiment." Based on panel data from 287 cities from 2010 to 2021, the study uses the Difference-in-Differences (DID) method to empirically test the impact of free trade zone construction on carbon emissions in the cities and further analyse its influencing mechanisms. The research findings indicate: (1) the construction of free trade zones has a significant inhibitory effect on carbon emissions in the cities; (2) the establishment of free trade pilot zones can suppress carbon emissions in cities through levels of openness to the outside world, technological innovation, and upgrading of industrial structure; (3) different regions and batches of free trade zones have varying impacts on carbon emissions. In light of these findings, it is suggested to systematically expand the implementation scope of free trade pilot zone policies in China during the development of free trade pilot zones, stimulate the potential for urban carbon reduction, implement tailored low-carbon policies, and promote the coordinated development of economic and environmental benefits in free trade pilot zones.

Stackelberg game-based method towards carbon-economy equilibrium for the prefabricated construction supply planning: A case study from China

Prefabricated building systems that take advantage of modern manufacturing, transportation, and assembly approach have attracted great attention as solutions for sustainable cities and urban construction carbon emissions mitigation, especially under the 30% prefabrication of new buildings target in China’s development plan of the construction industry. Nevertheless, few research has focused on the carbon reduction/economic costs equilibrium for the integrated traditional and prefabricated construction supply planning (PCSP). Aiming at the sustainable construction for urbanization, this study develops a Stackelberg game-based method for economic and environmental equilibrium under the carbon allocation scheme in an integrated prefabricated construction supply planning. In the bi-level model, the regional authority on the upper level determines the carbon allocations and the enterprises on the lower level develop plans to maximize revenue under the prefabricated rate targets and construction supply logistics limitations. The superiority and practicality of the proposed methodology are then validated through a case study from China. The scenario analyses under different policy control levels indicate that the proposed methodology is capable of systematically controlling the integrated PCSP carbon emissions and promoting the low-carbon transformation and sustainable development of construction industry. Valuable managerial implications are also provided for the policymakers and relevant practitioners.

Digital economy, land resource misallocation and urban carbon emissions in Chinese resource-based cities

In the context of global climate change, China is actively promoting the deep integration of “digital economy" and a “low-carbon economy." Studying the impact of the digital economy on carbon emissions has become a crucial task. Therefore, this study examines the direction and channels of the digital economy's impact on urban carbon emissions using the two-way fixed effects and mediation effects model. The study shows that the digital economy significantly inhibits urban carbon emissions, and the conclusion still holds after various robustness tests. The digital economy can mitigate land resource mismatch through effective mitigation, while the rational allocation and use of land resources contribute to reducing urban carbon emissions. From the heterogeneity perspective, the digital economy's inhibitory effect on urban carbon emissions is more evident in places outside the Yangtze River Economic Belt and non-resource cities. This argues that the development of the digital economy should be fully promoted, and the allocation of land resources should be optimized to release the digital economy's environmental dividend. Meanwhile, developing regional differentiation policies is crucial to achieving carbon emission reduction.

Does China's carbon inclusion policy promote household carbon emissions reduction? Theoretical mechanisms and empirical evidence

China's carbon inclusion policy (CIP) is an innovative voluntary emission reduction mechanism that aims to drive consumption-side emission reductions and achieve dual carbon goals. However, the effectiveness of the policy has not yet been assessed. To fill this research gap, this study evaluated the impact of CIP on urban household carbon emissions based on panel data from 283 cities in China from 2006 to 2020. This was conducted using staggered difference-in-differences (DID), synthetic DID, and spatial DID methods. The results showed that the CIP significantly reduced household carbon emissions through the green consumption awareness enhancing effect and green supply capacity improving effect. Heterogeneity tests indicated that carbon reduction effects are stronger in electricity and gas consumption and relatively modest in the heating and transportation domains. Cities with higher financial technology levels and greater government intervention had better policy outcomes. CIP also exhibited spatial spillover effects on household carbon emissions and synergistically reduced air pollution. Despite incurring certain economic costs, it ultimately promoted regional economic growth. This study can provide theoretical and empirical evidence for China to promote CIP and achieve its dual carbon goals.

THE SPATIAL SPILLOVER EFFECT OF INNOVATIVE CITY POLICY ON CARBON EFFICIENCY: EVIDENCE FROM CHINA

The strengthening of the deep integration of innovation and green is a necessary measure for sustainable urban development. Based on the improved Global-EBM, this study regards the innovative city policy as a quasi-natural experiment and evaluates its spatial spillover effects and potential impact channels. The results show that (1) The innovative city policy enhances the urban total factor carbon emission efficiency (TFCEE) and has positive spatial spillover effects on surrounding regions. (2) The mechanism test shows that the effective channels for innovative city policies to enhance TFCEE and generate spatial spillover effects come from improving the degree of green technology and resource allocation. (3) The spillover effect of innovation city policy is more significant for developed, coastal and advanced industrial structures. This study strengthens the theoretical foundation for promoting cross-regional green coordinated development and provides valuable suggestions for policymakers.

Future Scenarios of Urban Nighttime Lights: A Method for Global Cities and Its Application to Urban Expansion and Carbon Emission Estimation

As of 2018, approximately 55% of the world’s population resides in cities, and it is projected that this proportion will reach 68% by 2050. Population growth in urban areas leads to various impacts on society and the environment. In this study, we have developed a method for generating future scenarios of nighttime lights. What makes this method unique is its ability to (1) generate future gridded nighttime light intensity scenarios for cities, (2) generate future scenarios that preserve the distribution pattern of nighttime light intensity, and (3) generate scenarios that reflect urban policies. By applying this developed method, we have estimated nighttime light data for 555 cities worldwide and predicted future urban expansion and changes in carbon emissions for each SSP scenario. Consequently, both urban areas and carbon emissions are estimated to increase for the entire set of target cities, with patterns varying among cities and scenarios. This study contributes to the advancement of urban scenario research, including the estimation of future urban area expansion and carbon emissions.