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China is actively heeding the call and striving for a low-carbon and environmentally friendly development route as part of the general trend toward a global low-carbon economy. The rapid economic development of our nation has brought to light the issue of carbon emissions resulting from the consumption habits of residents. This paper delves into the topic by conducting a thorough analysis of the carbon emission of residents' consumption using the input-output method. Based on the survey findings, the disparity in carbon emission between urban and rural communities in Shandong Province is evident not only in terms of total emissions but also in different categories and regions. Urban residents generate a total carbon emission of approximately 70.2921 million tons, which is three times higher than that of rural residents at 23.7846 million tons. The carbon emission of both urban and rural residents is primarily attributed to their embodied carbon emission. In examining the composition of the implied carbon emission of residents' consumption in Shandong Province, urban residents' carbon emission is concentrated in three areas, namely, food, culture, education, entertainment, transportation, and communication, accounting for 21.45%, 20.88%, and 15.10%, respectively. Conversely, rural residents' carbon emission is concentrated in four areas, including clothing, food, culture, education, entertainment, transportation, and communication, accounting for 29.01%, 17.45%, 15.43%, and 13.36%, respectively. Finally, according to the characteristics of the consumption carbon emission of urban and rural residents in Shandong Province, we give corresponding emission reduction strategies. [ABSTRACT FROM AUTHOR]

Exploring the complex relationship between population change and surface urban heat island (SUHI) effect has important practical significance for the ecological transformation development of shrinking cities in the context of the prevalence of urban shrinkage and the global climate change. This paper compares the population change and SUHI effect between population shrinking region (Northeast Region, NR) and population growing region (Yangtze River Delta, YRD) in China, and explores their differences in driving mechanisms, using GIS spatial analysis and Geodetector model. Our results indicated that there are significant differences in population changes and SUHI intensity between these two regions. About 72.22% of the cities in the NR were shrinking, while their SUHI intensities increased by an average of 1.69°C. On the contrary, the urban population in the YRD shows a linear growth trend, while their SUHI intensities decreased by 0.11°C on average. The results of bivariate Moran's I index also indicated that the spatial correlation between the urban population changes and the SUHI intensity changes are not significant in the above regions. Furthermore, there are significant differences in the primary drivers of SUHI variations between these two regions. In the NR, underlying surface changes, including the changes of green coverage and built-up areas, are the most important driving factors. However, atmospheric environment changes, such as carbon dioxide emission and sulfur dioxide emission, are the key drivers in the YRD. Northam's theory of three-stage urbanization and environmental Kuznets curve hypothesis are powerful to explain these differences. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

Climate change is a global problem facing mankind, and achieving peak CO2 emissions and carbon neutrality is an important task for China to respond to global climate change. The quantitative evaluation of the trends of urban energy consumption and carbon emissions is a premise for achieving this goal. Therefore, from the perspective of urban expansion, this paper analyzes the complex relationship between the mutual interactions and feedback between urban population, land expansion, economic growth, energy structure and carbon emissions. STELLA simulation software is used to establish a system dynamics model of urban-level carbon emissions effects, and Changsha city is used for the case study. The simulated outputs of energy consumption and carbon emissions cover the period from 1949 to 2016. From 1949 to 2016, Changsha's total energy consumption and carbon emissions per capita have continuously grown. The total carbon emissions increased from 0.66 Mt-CO2 to 60.95 Mt-CO2, while the per capita carbon emissions increased from 1.73 t-CO2/10,000 people to 18.3 Mt-CO2/10,000 people. The analysis of the structure of carbon emissions shows that the industrial sector accounted for the largest proportion of emissions, but it had gradually dropped from between 60% and 70% to about 40%. The carbon emissions of residential and commercial services accounted for less than 25%, and the proportion of transportation carbon emissions fluctuated greatly in 2013 and 2016. From the perspective of carbon emissions effects, carbon emissions per unit of GDP had a clear downward trend, from 186.11 t-CO2/CNY104 to 1.33 t-CO2/CNY104, and carbon emissions per unit of land showed two inflection points: one in 1961 and the other in 1996. The general trend showed an increase first, followed by a decrease, then a stabilization. There is a certain linear correlation between the compactness of urban shape and the overall trend of carbon emissions intensity, while the urban shape index has no linear correlation with the growth rate of carbon emissions. The carbon emissions assessment model constructed in this paper can be used by other municipalities, and the assessment results can provide guidance for future energy planning and decision making. [ABSTRACT FROM AUTHOR]

The increase of carbon emissions accelerates global warming and causes environmental problems. Therefore, research on emission peak and carbon neutrality is of broad interest. In this paper, based on the relationships among carbon emissions, carbon absorption and urban population growth, a delayed differential equations model is established. Then, we analyze the existence and stability of a positive equilibrium point of the system and substitute the data for simulations. Eventually, according to theoretical analysis and numerical simulations, some suggestions for China to achieve the goal of emission peak and carbon neutrality are given. [ABSTRACT FROM AUTHOR]

Following the promulgation and implementation of China's 'carbon peak' and 'carbon neutrality' policies, the evaluation of the carbon footprint of the domestic catering industry is particularly important. Currently, comparative studies on the life-cycle carbon footprint of different common dining styles, such as home cooking, restaurant dining and takeaway, are scarce. Focused on three dining methods, this paper involved in-depth research on carbon footprint of the whole life cycle from the perspectives of whole industry and specific dish. The carbon footprint contribution of each stage of three different dining ways is obtained from the four stages, namely, the stage of upstream raw materials and manufactures, the stage of platform empowerment, the stage of consumer dining and the stage of waste treatment. The study found that the carbon emissions of the three dining ways in the overall industry analysis were canteen (2.9564 kgCO2e/per person) > takeaway (2.4821 kgCO2e/per person) > home cooking (2.2778 kgCO2e/per person); and the carbon emissions of honey sauce fork-fired were canteen (6.5843 kgCO2e/per person) > home cooking (6.4721 kgCO2e/per person) > takeaway (5.6718 kgCO2e/per person). The production of raw materials and products is the largest stage of carbon emissions among the three dining ways. Besides the carbon emissions of raw materials, the storage and cooking of food products are the unit processes with large carbon emissions. According to the results of sensitivity analysis, traffic travel mode is an important factor affecting the carbon footprint of canteen food. The above research can provide effective basis and data support for policy formulation. [ABSTRACT FROM AUTHOR]

In China, urbanization has been rapidly developing since the country began its economic reform in 1978. With the expansion of the urban population size and the corresponding urbanization and industrialization, the rapid increase in CO2 emissions has become a major restraint on China's economic growth. However, current studies have not paid sufficient attention to the impact of the urban population size on CO2 emissions in China due to poor data availability. In this paper, we apply index decomposition analysis (IDA) to decompose CO2 emissions into five elements, and we investigate both the direct and indirect impacts of the urban population size on total CO2 emissions and per capita CO2 emissions in China. Additionally, we empirically study the impact on 175 Chinese cities at the prefecture level and above for the first time. The results show that the urban population size significantly promotes total CO2 emissions but curbs per capita CO2 emissions in cities in China. A 1% increase in the urban population size will lead to a nearly 1% increase in total CO2 emissions and a 0.3% decrease in per capita CO2 emissions. Regarding heterogeneity, the expansion of the urban population size in the large city group drives a greater increase in CO2 emissions than the expansion of the urban population size in other city groups. The main transmission pathways are through population density, economic agglomeration and energy intensity. Regarding the mechanism variables, high economic agglomeration leads to more CO2 emissions, while an increase in population density and energy efficiency results in carbon mitigation. Moreover, public green areas, foreign direct investment (FDI) and technology innovation are conducive to reducing CO2 emissions. [ABSTRACT FROM AUTHOR]

Urban residents' travel is an important component of carbon emissions and is becoming a hot topic in discussions on how to achieve carbon neutrality by 2060. Existing studies mainly focus on low-carbon travel behaviours and intentions independently, ignoring the inconsistency between the two. This paper uses a bivariate probit model based on questionnaire survey data to explore the consistency between urban residents' intentions and behaviour. The results show that sociodemographic factors, TPB (theory of planned behaviour) factors, and situational factors all significantly impact the inconsistency. This paper provides careful analysis, and based on the results and analysis, proposes targeted suggestions to enhance the public intention of low-carbon travel and proper policies to improve low-carbon travel in cities. [ABSTRACT FROM AUTHOR]

Based on the panel data of 108 prefecture-level cities in China from 2003 to 2018, the carbon emission effect of urban density was studied by establishing a dynamic panel model. We found that there was a significant negative correlation between urban density and carbon emissions, and the increase in urban density reduced carbon dioxide emissions. The nonlinear estimation results of urban density and carbon emission show that urban density has different impacts on carbon emission at different urban population levels. With the increase in population size, the carbon emission reduction effect brought by urban density growth decreases. In medium-sized cities, increased urban density leads to the greatest reduction in carbon emissions, followed by large cities with populations of less than 5 million. In megacities with a population size of more than 5 million, the carbon emission reduction effect of urban density is not significant. Our conclusion supports the proposition of building compact cities and provides decision support for the ideal of 'beautiful China' in the process of urbanization in China. [ABSTRACT FROM AUTHOR]

This study conducts an empirical investigation into the decarbonization effects of urban polycentric structures, exploring their mechanisms and varied influences. Our findings reveal key insights. First, urban polycentric structures effectively reduce carbon emission intensity, a conclusion supported by robust tests and endogeneity analysis. Second, our analysis shows that polycentric structures significantly alleviate downtown overcrowding, reducing carbon emission intensity. These structures also impact carbon emissions through factors like labor allocation across industries and the entry of high-productivity enterprises. Third, our analysis shows that the impact of the polycentric structure on carbon emission intensity follows a 'U-shaped' pattern. In this 'U-shaped' pattern, the growth of an urban population scale can offset the potential negative impacts of this structure. Finally, government support, urban transportation networks, and communication technologies are crucial in enhancing the effectiveness of polycentric decarbonization. Our research contributes to the literature on polycentric structures and carbon emissions and offers policy implications for addressing climate change, applicable not only to China but also to other economies. [ABSTRACT FROM AUTHOR]

Under the background that China will achieve the goal of carbon neutrality by 2060, analyzing the impact of carbon neutral target constraints on the welfare of urban and rural residents is an important part of the design of a carbon emission reduction policy mechanism, in this paper, the dynamic recursive CGE(Computable general equilibrium) model is used to simulate the changes in welfare level, income consumption, and CO2 emissions of residents and their urban-rural heterogeneity under the policy of imposing a carbon tax on the fossil energy industry from 2022 to 2060. The results show that: compared with the BAU scenario, by 2060, first the income and consumption of residents will decrease slightly. Second, the target constraint of carbon neutrality makes the equivalent variation and compensate variation of urban and rural residents' welfare decrease slightly, and the equivalent variation and compensate variation of urban residents decrease more than those of rural residents. The following conclusions are drawn: first, the carbon-neutral target constraint makes the welfare of urban and rural residents decline slightly, but it will not have a strong impact on residents' income and consumption. Second, this constraint has a greater impact on the income, consumption and savings of urban residents than those of rural residents. [Display omitted] • A five-layer nested dynamic recursive CGE model is established to analyze residents' welfare. • Carbon taxes are incorporated into production decisions as a policy cost for energy companies. • The heterogeneity of the impact of carbon tax policy constraints on the welfare of urban and rural residents was analyzed. • The government needs to improve the intensive and diversified energy supply in rural areas to reduce the urban-rural gap. [ABSTRACT FROM AUTHOR]

• The factors that affecting urban carbon emissions efficiency (CEE) are explored. • The carbon emissions of 282 cities are estimated with the aid of nighttime light data. • Urban CEE has significant and positive spatial spillover effects. • Industrial agglomeration and collaboration are key to green production efficiency. This paper explores the factors that improve the efficiency of urban carbon emissions. Based on nighttime light data, the carbon emissions of 282 cities in China from 2004 to 2018 are estimated, and the carbon emission efficiency (CEE) is measured. The spatial autocorrelation results show that CEE in Chinese cities has significant and positive spatial spillover effects. The LISA low-low type cluster area of CEE presents an evolutionary trend of westward migration, and eventually formed two low-efficiency centers in the Central Plains city group and the Sichuan-Chongqing city group. The empirical results of the spatial Durbin error model show that urban population expansion, economic growth and R&D investment have effectively improved CEE, but industrial scale and agglomeration adversely affect CEE. In addition, human capital investment and foreign investment have not exerted their due green growth effects. Manufacturing agglomeration had a negative impact on local CEE, but had a warning effect on neighboring regions. Different from the manufacturing industry, the agglomeration of producer services industry can bring significant improvement to CEE, accompanied by a demonstration effect which can promote the CEE in adjacent regions. Further, this paper finds that developing the synergy between manufacturing and producer services industries can significantly restrain the negative effects of industry on CEE. This paper enriches the performance evaluation framework of low-carbon city development in theory, and varies the situations that previous researches only concerned about carbon emissions while ignoring emissions efficiency. This paper is a beneficial policy practice of the coordinated development of economic growth and ecological environmental protection in the regional coordinated development mechanism, which indicates that strengthening industrial collaboration can effectively improve the efficiency of green production in cities. [ABSTRACT FROM AUTHOR]

Low-carbon pilot cities can break the lock-in effect of living carbon emissions, which are an important strategic component of China's response to climate change. Current research on low-carbon pilot cities focuses on the production field. Insufficient attention has been paid to whether low-carbon pilot cities can promote the green transformation of residents' lifestyle. Using panel data of 285 cities in China from 2004 to 2016, this study explores the inducing effect of low-carbon pilot cities on residents' low-carbon choices from holistic and single-dual perspectives based on the difference-in-differences method and the synthetic control method. This study finds that low-carbon pilot cities can promote the green transformation of residents' lifestyle, and this policy has reduced living carbon emissions by approximately 15.3%. The transmission mechanisms are mainly green life consciousness and green habits. The conclusion considers the effects of multi-pilot policies and other living differences during the parallel period and is still valid after robustness testing using propensity score matching difference-in-differences. In addition, the policy has a snowball effect, and is stronger in larger cities. Ultimately, this paper provides useful information for the scientific implementation of carbon emission reduction plans in the field of residents' living and the improvement of the long-term mechanism of pilot cities with both quality and quantity guaranteed. • Low-carbon pilot cities (LCPCs) induce residents to make low-carbon choices. • LCPCs have reduced living carbon emissions by approximately 15.3%. • LCPCs can coexist with other policies to achieve CO 2 reduction. • The mechanisms are mainly green consciousness and green habits. [ABSTRACT FROM AUTHOR]

In the social context of mitigating climate change and achieving carbon neutrality, the improvement of carbon emissions efficiency and the protection of biological carbon sequestration have emerged as hot topics recently due to their prospects in carbon dioxide emissions reductions. A large volume of studies has identified the spatial distribution characteristics and influencing factors of carbon emissions efficiency. The contributions of our study lied in constructing a system to measure net carbon sink efficiency. Secondly, this study discussed the carbon neutrality performance of Chinese cities from three different aspects of carbon dioxide emissions, carbon sequestration of vegetation and net carbon sink efficiency. Thirdly, this paper identified the influencing factors of net carbon sink efficiency, and examined the direct and indirect effect of different factors. For this purpose, we evaluated the net carbon sink efficiency of 285 cities in China from 2012 to 2017 using a slacks-based measure model, and explored its spatial distribution characteristics, then employed a spatial Durbin model to explore the influencing factors of net carbon sink efficiency. Our main findings indicate that the net carbon sink efficiency steadily increased during the study period, whereas their spatial characteristics were "high at both ends and low in the middle" from the south to the north. There is a significant spatial autocorrelation in the net carbon sink efficiency of Chinese cities. Several kinds of measures can be applied to promote net carbon sink efficiency, such as increasing the proportion of tertiary industry, promoting economic growth, attracting foreign direct investment, increasing road area, promoting technological progress and strengthening environmental regulation. However, the increase of urban population may decrease efficiency. Nevertheless, an obvious spatial spillover effect exists in the net carbon sink efficiency of Chinese cities. The results can provide policy recommendations for the government to formulate differentiated carbon neutralization policies. [Display omitted] • The carbon sequestration is considered to calculate net carbon sink efficiency (NCSE). • The NCSE is used to discuss the carbon neutral performance of Chinese cities. • Chinese NCSE steadily increased and showed significant spatial autocorrelation. • Spatial Durbin model was adopted to study the influencing factors of NCSE. [ABSTRACT FROM AUTHOR]

Carbon emissions from civil buildings refer to the carbon emissions generated during the operation of civil buildings. With the continuous development of the urban economy and the improvement of people's living standards, this part of carbon emission puts tremendous pressure on China to achieve the goal of carbon peaking and carbon neutral. In the context of rapid urbanization, studying the spatiotemporal characteristics and influencing factors of the carbon emissions from civil buildings have strong practical significance for China to achieve the "dual carbon" goal. Based on the emission data from 104 prefecture-level cities in China, we examine the spatiotemporal characteristics of the civil building carbon emissions from the perspectives of temporal evolution trend, spatial distribution and its dynamic evolution, spatial difference and its decomposition, and spatial autocorrelation characteristics. Finally, we reveal the influencing factors of the carbon emissions from civil buildings using static panel data models and spatial dynamic panel data models. The results of the study show that: (1) During the sample period, the carbon emissions from civil buildings have increased year by year. The civil building carbon emissions have become an important source of China's overall carbon emissions. Realizing energy saving and emission reduction in the operational stage of civil buildings is crucial to realizing China's "dual carbon" goal. (2) According to the estimated results, there is a significant inverted U-shaped non-linear relationship between urbanization and civil building carbon emissions. Most Chinese cities are located in the upward part of the inverted U-shaped curve at present. Thus, the traditional economic growth model characterized by high energy consumption and high emission during rapid urbanization should be abandoned to reduce the carbon emissions from civil buildings. (3) Technological progress and fixed asset investment can effectively reduce the carbon emissions from civil buildings. At the same time, the level of marketization and social consumption expenditure positively affect the carbon emissions from civil buildings. It is necessary to improve the relevant market mechanisms, policy subsidies, and other means to encourage the application of green energy-saving technologies in civil buildings. Also, it is needed to guide the urban residents' consumption structure and lifestyle in a low-carbon direction, to reduce the energy consumption and carbon emissions during the operation of civil buildings. [ABSTRACT FROM AUTHOR]

Global climate change has become one of the greatest challenges to human development, the study of the dynamic evolution of carbon emissions at the building operation stage and its driving mechanism is of great significance for the reasonable control of carbon emissions, and helpful to provide more scientific and reasonable decision support for proposing an implementable carbon neutral pathway. According to the geospatial differences of carbon emissions at the building operation stage, this paper constructs a research framework on the influencing factors and driving mechanisms of carbon emissions at the building operation stage based on CV, kernel density, Geodetector and other methods. The study shows that first, that the carbon emissions at the building operation stage are unequally distributed in space in provinces of China, and the building carbon emissions vary greatly in structure among different regions. Second, different factors vary greatly in influence. Third, there are great differences in the driving mechanisms of carbon emissions over time, but factors such as urban population and refrigerator ownership are both key influencing factors that have a comprehensive influence on the spatio-temporal changes of carbon emissions. Fourth, all the factor pairs are bifactor-enhanced or non-linearly enhanced, and they can be classified into three types of high, medium, and low levels. Fifth, a carbon neutral pathway map for the building sector is proposed based on the spatial distribution of carbon emissions and its driving mechanism, to provide reference for foreign regions with similar conditions. • Calculated the carbon emission at the building operation stage in Chinese provinces. • Analyzed trend and composition of carbon emission at the building operation stage. • Analyze spatial-temporal changes of carbon emissions by GIS. • For the first time, analyzed driving factors of carbon emissions by Geodetector. • Proposed a carbon neutral pathway map for the building sector. [ABSTRACT FROM AUTHOR]

Personal carbon trading scheme has been pulled into the public eye with the increasing urgency of downstream carbon emission reduction, and its feasibility largely depends on public acceptability. This study established a hierarchical framework for urban residents' approach-avoidance responses to personal carbon trading; adopted Likert scale and manikin task methods to assess the current states of residents' responses by investigating 1892 respondents in eastern China; employed one-way analysis of variance to identify the demographic differences of their responses; and used regression analysis to explore the influences of psychological factors on their responses. The findings showed that urban residents' responses to personal carbon trading scheme and participation could be classified into five response hierarchies: deep avoidance, shallow avoidance, uncertain, shallow approach, and deep approach. The average of residents' responses denoted a shallow approach, with the characteristics of median stability, duration, and noise. Moreover, residents holding deep approach responses to the scheme and participation respectively accounted for 42.365% and 34.275% of the total, which indicated a gap between attitude and behavior. Urban residents' responses exhibited significant differences with respect to demographic characteristics. Most of the residents with the most avoidance response were young males (i.e., 18–20 years old), older first-line employees (i.e., older than 50 years old), and those on subsistence incomes (i.e., annual individual or household income was RMB 30,000–50,000 yuan). Additionally, residents who held egoistic values, had low senses of social responsibility, knew little about carbon reductions, and preferred comfortable life were likely to avoid the scheme and participation. Finally, policy suggestions are proposed for the enhancement of urban residents' attitudes towards personal carbon trading, thereby providing valuable references for its implementation. [ABSTRACT FROM AUTHOR]

This research attempted to investigate the impact of urbanization and spatial agglomeration on carbon emissions. To achieve the goal, the dynamic panel data model was employed to explore the nonlinear relationship between urbanization and carbon emissions for 166 cities in China taking the period 2005–2015, and the Gini coefficient of urban population size distribution in 15 urban agglomerations were calculated to analyze whether the spatial agglomeration of cities contributed to environmental protection. The results show that there is an inverted U-shaped curve between urbanization and carbon emissions; high-level urbanization development helps reduce carbon emissions; the spatial agglomeration of cities can contribute to carbon reduction to a certain extent based on the empirical results of the spatial agglomeration promotes the early arrival of the inflection point in the inverted U-shaped relationship between urbanization and carbon emissions; and the improvement of urban agglomeration level can present an abatement effect on carbon emissions at a lower urbanization level, which enhances the positive environmental effect of urbanization development compared with the decentralized urban distribution model. Furthermore, there is a significant U-shaped relationship between spatial agglomeration and carbon emissions, which indicates that the scientific planning of urban clusters will achieve economies of scale and agglomeration effect, thereby reducing carbon emissions. These findings contribute to complement the existing literature as well as provide some implications related to sustainable urban development for policymakers. [ABSTRACT FROM AUTHOR]