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This paper constructs a model to accurately estimate the urban CO2 emissions in 2000, 2005, and 2013 in China, using the combined data of DMSP/OLS nighttime light data and the provincial energy statistical yearbook data. We calculate and analyze the growth of urban built-up areas and carbon emissions in different time periods both all over the country and the four economic zones in China. It was shown a good fitting relationship between urban growth and carbon emissions, with the R2 at 0.6188 in 2000, 0.7132 in 2005, and 0.7195 in 2013. The growth rate of developed land area was 13.4% from 2000 to 2005 and 15.9% from 2005 to 2013. During the same period, CO2 emissions had been increasing as well, at an average annual growth rate of 12.2% from 2000 to 2005 and 6.5% from 2005 to 2013. From a spatial point of view, carbon emissions are far greater in the eastern region of China than in western China. The carbon emissions are the highest in major metropolitan cities such as Beijing, Shanghai, and Guangzhou. Per capita carbon emissions are also higher in eastern China, which is consistent with the people's higher living standards. In some cities with large energy and heavy industry concentrations, especially in the northeastern and western regions, the growth rate of carbon emissions has risen faster than in other cities. [ABSTRACT FROM AUTHOR]

Urban form is closely related to CO2 emissions and the accurate estimation of the impact of urban form on CO2 emissions plays an important role in tackling climate change caused by the emission of greenhouse gases. In this paper, we quantitatively investigate the effects of urban form on CO2 emission and its efficiency from three perspectives: urban expansion, compactness, and complexity. By using panel quantile regression with fixed effects, we show that: (1) The estimation results about the relationship between urban form and CO2 emission and its efficiency are consistent with the literature. (2) The partial effects of urban form without controlling for socioeconomic factors are heterogeneous throughout the conditional distribution of CO2 emission and its efficiency. (3) Taking into consideration that the partial effects of urban form on CO2 emission and its efficiency might depend on the magnitude of socioeconomic factors, we include interaction terms into our model and find that the interaction effects between socioeconomic factors and urban form are heterogeneous across cities with different levels of CO2 emission and its efficiency. Our empirical findings shed light on the optimization of urban form in improving the CO2 emission efficiency, providing policy makers with effective ways of reducing CO2 emissions across cities with different levels of CO2 emissions. [ABSTRACT FROM AUTHOR]

This paper constructed the mismatch index of land supply structure by cities in China from 2010 to 2019 and analyzed the direct effect and spatial spillover effect of land supply structure mismatch on urban carbon emission efficiency using the spatial Durbin econometric model. The results showed that: ① There were obvious regional differences and interactive forms of spatial strategies in the mismatch of urban land supply structures in China. The mismatch index of urban land supply structure in the eastern region was the lowest, while that in the northeast region was the highest. There was a 'race to the top' type of spatial strategic interaction in residential land supply mismatch, industrial land supply mismatch, and commercial service land supply mismatch. ② Due to the competitive effect of economic growth among cities, urban carbon emission efficiency had a significant positive spatial spillover effect. The estimation results of the spatial Durbin econometric model showed that the mismatch of land supply structures inhibited the improvement of the carbon emission efficiency of cities themselves as well as spatially related cities. ③ In terms of the degree of land supply mismatch in different industries, urban residential land supply mismatch, industrial land supply mismatch, and commercial service land supply mismatch were not conducive to improving the carbon emission efficiency of cities themselves as well as spatially related cities. ④ The mechanism analysis showed that, with the intensification of competition in attracting investment and fiscal and tax competition between cities, the negative effect of the mismatch of land supply structure on the carbon emission efficiency of spatially related cities and cities themselves was greater. In dimensional terms, the supply mismatch of residential land and commercial service land only inhibited the carbon emission efficiency of spatially related cities and cities themselves through fiscal and tax competition, while the supply mismatch of industrial land only inhibited the carbon emission efficiency of spatially related cities and cities themselves through competition in attracting investment. In order to improve the efficiency of urban carbon emissions, local governments should improve the lowcarbon oriented urban land governance system, curb the vicious competition of land resource allocation among local governments, constantly eliminate the micro-factors of urban land supply structure mismatch, and promote regional collaborative carbon emission reduction. [ABSTRACT FROM AUTHOR]

As urbanization has developed, a variety of urban clusters have gradually emerged with important effects on regional economic growth and carbon emissions. This paper constructs a multi-period difference-in-difference (DID) model for testing how urban cluster synergistic development policy (UCSDP) affects urban carbon productivity in 148 cities of China with 13 urban clusters as the experimental group from 2003 to 2019. According to the results, the UCSDP improves carbon productivity, mainly via reducing energy intensity. In addition, UCSDP improves carbon productivity by adjusting energy structure, increasing green innovation, altering city greening levels, and accelerating the process of urbanization. Moreover, it can produce synergistic effects in terms of energy structure, green innovation, greening level, and urbanization level. Furthermore, the UCSDP has heterogeneous effects on the carbon productivity in various cities. Specifically, the carbon productivity of high-status, high-rank, and resource-based cities responds more significantly to UCSDP. Therefore, policymakers should strengthen the integration of urban clusters, offer targeted development suggestions for different cities, modify the energy and greening structure, accelerate the process of urbanization, and focus on the formulation of reasonable environmental regulation policies. • Exploring the impact of UCSDP on carbon productivity with multi-period DID model. • The improvement of carbon productivity by UCSDP mainly comes from the decrease of energy intensity. • UCSDP increases carbon productivity by affecting energy structure, green innovation, greening level and urbanization level. • UCSDP produces synergistic effects in terms of energy structure, green innovation, greening level and urbanization level. • The impact of UCSDP on carbon productivity varies by city status, city rank and city type. [ABSTRACT FROM AUTHOR]

This study examines the relationship between urbanization, economic growth, industrial transformation, technological change, public services, demographical change, urban and natural environmental changes, and carbon emissions using a dataset of 182 prefecture-level cities in China between 2001 and 2010. Specifically, this paper differs from previous studies in two aspects. First, the extant literature has focused on how economic processes accompanying rapid urbanization affect carbon emissions in urban areas but gives little attention to the other dimensions of urbanization, including social and environmental changes, which may have important effects on carbon emissions. We assessed the effects of 17 key processes accompanying urbanization in a full range of economic, social, and environmental dimensions on carbon dioxide emissions in urban areas. The results showed that social processes accompanied with rapid urbanization had distinct effects on carbon emissions, compared to economic and environmental processes. Specifically, improvement in public services, indicated by education and cultural developments, reduces the increase in carbon emissions during urbanization, while economic growth and urban construction reinforces the growth in carbon emissions. Second, we examined the impact of various urbanization processes on carbon dioxide emissions using a unique dataset of 182 prefecture-level cities that covers a wide span of regions in China. The results of our analyses on the city level have important implications for the formulation of comprehensive policies aimed at reducing carbon dioxide emission in urban areas, focusing on different urbanization processes in economic, social, and environmental phases. [ABSTRACT FROM AUTHOR]

Under the threat of global climate change, China has proposed a dual carbon goal of peak carbon and carbon neutrality. As the vital carrier for territorial spatial planning, production–living–ecological (PLE) spaces drive carbon emissions and are important to the dual carbon goals. In this study, carbon emissions and sinks of PLE spaces in cities in Heilongjiang Province from 2005 to 2020 were calculated and spatial–temporal changes were analyzed. The carbon emission structure was analyzed in segmentation sectors. The land use changes and socioeconomic factors on carbon emissions were analyzed, and emission reduction strategies were implemented. The results show the following: (1) Carbon emissions from production and living spaces increased yearly. Carbon sinks were smaller than emissions, but capacity was stable. (2) Higher-emission cities were concentrated in southwest Heilongjiang, and carbon emission differences between regions gradually increased. (3) Among carbon emission sectors, agricultural and household made up smaller proportions, while animal husbandry, industrial, transportation, and traffic travel contributed most. Carbon emission structures were transformed by adjusting urban development and industrial structure. (4) For most cities, industrial space was the main emission space, but agricultural production and urban–rural living spaces dominated in some cities. (5) GDP, urbanization rate, and area of city paved roads suppressed emissions in cities with decreased carbon emission grades. The industrial structure and coal consumption inhibited emissions in cities with maintaining and increasing carbon emissions grades. [ABSTRACT FROM AUTHOR]

Exploring the effect of new-type urbanization (NTU) on urban carbon abatement is of great practical significance for promoting urban green construction and coping with the challenge of global climate change. This study used data from 250 cities in China from 2008 to 2020 and constructed the NTU evaluation indicator system from five dimensions. We used classical panel regression models to examine the effects of NTU on urban CO2 emissions, and further used spatial econometric models of SEM, SAR, and SDM to identify the spatial spillover effects of NTU on urban CO2 emissions. The main results are that China's NTU and CO2 emissions are generally rising, and NTU has a significantly negative effect on urban CO2 emissions, with an impact coefficient of −0.9339; the conclusions still hold after subsequent robustness tests. Heterogeneity analysis reveals that NTU's carbon abatement effect is more pronounced in resource-based cities, old industrial areas, and cities with lower urbanization levels and higher innovation levels. Mechanism analysis shows that improving urban technological innovation and optimizing resource allocation are important paths for realizing urban CO2 emission reduction. NTU's effect on urban CO2 emissions has a noticeable spatial spillover. Our findings provide policy makers with solid support for driving high-quality urban development and dual-carbon targets. [ABSTRACT FROM AUTHOR]

Rooftop photovoltaics (RPVs) are crucial in achieving energy transition and climate goals, especially in cities with high building density and substantial energy consumption. Estimating RPV carbon mitigation potential at the city level of an entire large country is challenging given difficulties in assessing rooftop area. Here, using multi-source heterogeneous geospatial data and machine learning regression, we identify a total of 65,962 km2 rooftop area in 2020 for 354 Chinese cities, which represents 4 billion tons of carbon mitigation under ideal assumptions. Considering urban land expansion and power mix transformation, the potential remains at 3-4 billion tons in 2030, when China plans to reach its carbon peak. However, most cities have exploited less than 1% of their potential. We provide analysis of geographical endowment to better support future practice. Our study provides critical insights for targeted RPV development in China and can serve as a foundation for similar work in other countries. Potential rooftop photovoltaic in China affords 4 billion tons of carbon mitigation in 2020 under ideal assumptions, equal to 70% of China's carbon emissions from electricity and heat. Yet most cities have exploited the potential to a limited degree. [ABSTRACT FROM AUTHOR]

The supply of built-up land determines the depths of human activities, leading to the differences in scale and intensity of carbon emissions. However, the relationship between the composition of built-up land and carbon emissions has not been fully investigated. In response, this study collects the panel data of 88 cities along the Yangtze River Economic Belt, China, and uses the fixed effect model and system GMM model, to explore the impacts of specific subtypes of built-up land on carbon emissions averaged by economic output and urban land. The findings show that industrial land and commercial land are the main contributors to increase carbon emissions; the increased proportions of land subtypes related to supporting facilities and infrastructures show significant restraining effects; carbon emission was a dynamic process with time-lagged effects. As a result, reallocating the structure of urban built-up land can directly and indirectly adjust the intensity of carbon emissions. Policy recommendations focus on the balanced supplies of production and ecological land. [ABSTRACT FROM AUTHOR]

Improving carbon emission efficiency is the most direct and effective way to reduce pollution. Leading the construction of a resource-saving and environment-friendly society is an important goal of the coordinated development of urban agglomerations in the middle reaches of the Yangtze River. However, there is no systematic evidence to prove whether this policy can improve carbon emission efficiency. Taking 31 cities in the urban agglomeration in the middle reaches of the Yangtze River as the research area, we aimed to use the index decomposition method, the super-efficiency slack-based model, and the difference-in-difference model to examine the effect of policies on improving carbon efficiency. The results show that (1) regional coordinated development policies have a significant effect on improving the carbon emission efficiency of urban agglomerations, and there is an obvious imbalance in carbon emission efficiency among cities. (2) The impact of regional coordinated development policies on urban carbon emission efficiency is heterogeneous. We have grouped 31 cities according to their centrality, industrial transfer characteristics, and urban cluster characteristics. Policies have heterogeneous effects on cities with different functions and positioning. (3) Policy effects have opposite effects on urban carbon emission efficiency through urbanization rate and population density, while the effect of urban greening rate is not significant. The research results can provide a reference for China's urban agglomeration to achieve sustainable development and promote the construction of low-carbon cities. [ABSTRACT FROM AUTHOR]

This study attempts to analyze the impact of population, property, technology, energy factors, and spatial agglomeration in the logistics industry on carbon emissions. To achieve the goal of peak carbon and carbon neutrality, the relationship between influencing factors and carbon emissions was analyzed based on panel data from the logistics industry for 30 provinces in China from 2003 to 2017 using an improved STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model and a spatial lag model (SLM). The results show that population, property, technology, and energy factors in the logistics industry all have different degrees of influence on carbon emissions, wherein population, energy, and property have a greater influence, which implies that carbon emission reduction policies can be carried out considering the relevant aspects. In addition, under the influence of spatial agglomeration, the degree of influence of freight mileage (FM), total fixed-asset investment (TFAI), and industry population (IPOP) on carbon emissions decreases, and the degree of influence of energy intensity (EI) and industry per capita GDP (IPCG) increases. This suggests that corresponding emission reduction policies should be formulated for large urban areas based on technological innovation, infrastructure, and talent training, while smaller urban areas can focus on developing new energy and industrial economies. These findings help to complement the existing literature and provide policymakers with some insights related to urban logistics development. [ABSTRACT FROM AUTHOR]