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Food consumption has resulted in great carbon emissions in recent years. China has been facing the new mitigation challenge of carbon emissions with its emerging middle-income groups, especially in urban areas. This paper analyzes and predicts carbon emissions from food consumption (CEFC) of middle-income groups in the Yangtze River Economic Belt (YREB), which has a higher emerging middle-income group and the highest economic corridor in China. Few studies address CEFC analysis from middle-income groups perspective; thus, this paper calculates urban–rural CEFC of middle-income groups spanning 2010–2018 and predicts them in 2025, 2030 and 2035 using the extended IPAT model. Results are as follows: (1) YREB's urban–rural CEFC of middle-income groups show an upward trend and present a spatial pattern of "low–high–low–high" from the western region to the eastern region. Urban CEFC of middle-income groups are significantly higher than that of rural areas; (2) rural CEFC of middle-income groups in the YREB will first increase in 2025 and then decrease in 2030 and 2035. The growing trend of urban CEFC of middle-income groups will show a significant downward from 2025 to 2035. The growing proportion of urban CEFC of middle-income groups will exhibit an objective growth in 2035. Understanding the changing trend of CEFC of middle-income groups provides governments with differentiated and forward-looking suggestions toward coordinating middle-income groups' expansion and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

How the transformation of trade patterns affects carbon emissions is an important topic in the field of trade and the environment. Based on the panel data of Chinese cities from 2000 to 2016, this paper uses fixed effect model, instrumental variable model and threshold estimation model to investigate the impact of the transformation of export trade patterns on carbon emissions and its internal mechanism. We find that during the investigation period, the transformation of export trade pattern has a significant "U"-shaped nonlinear impact on carbon emissions, and the research results still hold after a series of robustness checks and instrumental variable estimation; through the mechanism analysis of the threshold effect, it is found that in the process of the impact of trade patterns transformation on carbon emissions, there are double thresholds for energy structure transition; the nonlinear impact of export trade pattern transformation on carbon emissions has significant heterogeneity in different regions, city categories, and different periods; the mechanism analysis results show that industrial structure upgrading, industrial co-agglomeration, and green technology innovation are the main paths that the transformation of export trade patterns affects carbon emissions. Under the dual goals of fulfilling China's commitment to "carbon peak in 2030 and carbon neutrality in 2060" and implementing corporate social governance to promote green and sustainable development, this paper will provide suggestions for realizing the goal of low-carbon emission reduction from the perspective of the transformation of export trade patterns. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]

As the digital economy grows rapidly around the world, how would it impact carbon emissions? This paper discusses this issue from the perspective of heterogeneous innovation. Based on the panel data of 284 cities in China from 2011 to 2020, this paper empirically examines the impact of the digital economy on carbon emissions as well as the mediating and threshold effects of different innovation modes. The study finds that the digital economy can significantly reduce carbon emissions; this conclusion holds after a series of robustness tests. Independent innovation and imitative innovation are important channels through which the digital economy affects carbon emissions, but technological introduction is not an effective way. For regions with high levels of financial investment in science and innovative talents, the reduction in carbon emissions from the digital economy is more significant. Further research shows that the effect of the digital economy on carbon emissions has a threshold feature, with an inverted U-shaped relationship between the two, and that an increase in autonomous innovation and imitation innovation can enhance the digital economy's carbon reduction effect. Therefore, it is necessary to strengthen the capacity of independent innovation and imitation innovation to exploit the carbon-cutting effect of the digital economy. [ABSTRACT FROM AUTHOR]

China, as the world's largest carbon dioxide emitter, is bound to assume the important responsibility of energy conservation and emission reduction. To this end, each city, led by representative municipalities, must enhance efforts in carbon emission reduction to jointly realize China's low-carbon transition. Taking four representative municipalities, namely, Beijing, Tianjin, Shanghai, and Chongqing as the case cities, this paper establishes a decomposition analysis for the driving factors of carbon emissions by applying the LMDI method covering data from 2007 to 2017. Kaya identity is used to decompose the effects into eight driving factors: GDP effect, industrial structure effect, energy intensity effect, overall energy structure effect, population effect, urbanization effect, per capita energy consumption effect, urban and rural energy structure effect. The results show that at the municipality level, the driving factors that contribute to carbon emissions are the GDP growth effect and the population effect, with the former still being the most important factor in the municipalities with faster economic growth; and industrial structure effect is the most important factor that inhibits carbon emissions, followed by energy structure effect. This paper considers the driving factors of both the production side and the residential consumption side from the city level. The research reveals the main driving factors that effect the carbon emissions of megacities in developing countries, and highlights the leading role of megacities in terms of carbon emission reduction in China and even the world. The paper thereby puts forward policy implications for China's economic policies. [ABSTRACT FROM AUTHOR]

It will contribute to ameliorating the national carbon trading system and further benefit the realization of China's carbon peaking and carbon neutrality goals through in-depth study and summarize the effectiveness of carbon trading policy implementation in pilot areas. Based on the multi-phase difference-in-differences approach and synthetic control method, this paper utilizes China's provincial panel data from 2006 to 2020 to comprehensively assess the Porter effect (including the economic and green innovation effects) and carbon mitigation effect of carbon trading policy from the overall and local perspectives. Then the robustness test and mechanism analysis are carried out. The findings show that: (1) from the overall effect, the carbon trading policy brings a noticeable carbon mitigation effect and Porter effect, and the intensity of the impact keeps changing over time; (2) there is significant heterogeneity in the local effects of this policy on the eight pilot provinces and cities, with only Chongqing obtaining both the Porter effect and the carbon mitigation effect, while the rest of the regions do not yield the triple dividend of economic, environmental, and green innovation simultaneously; (3) there are much more prominent environment and green innovation effects in the developed regions, while the underdeveloped ones have better economic development and no green innovation effect; (4) the policy can bring environmental and economic dividends through energy structure optimization. However, due to the carbon rebound effect, stimulating green innovation pathways can only boost the economy while carbon emissions increase instead. The research conclusions can provide the decision support and policy direction for policies related to China's carbon market. [ABSTRACT FROM AUTHOR]

Industrial land is currently the main carrier and important source of global carbon emissions, and as the world's largest developing country, China's large-scale and diversified industrial land supply has made it the world's largest carbon emitter. Therefore, researching the impact of different supply methods of industrial land on carbon emissions and its impact paths in China can help provide a reference for other countries to reduce carbon emissions from the perspective of urban industrial land management, which is of great significance for effectively promoting global carbon reduction. Based on this, this paper analyses the impact of different supply methods of industrial land on carbon emissions and its urban heterogeneity using the SYS-GMM and chain-mediated effects models for 285 cities in China from 2008 to 2020. The study found that, in general, the impact of different industrial land transfer modes on carbon emission has hysteresis and persistence. Agreement and listing transfer with government intervention can significantly exacerbate carbon emissions, while more market-based bidding and auction transfer can dampen carbon emissions. In terms of intermediary effects, the transfer of industrial land by agreement and listing will inhibit the rationalization and advancement of industrial structure, thus aggravating carbon emissions. The transfer of industrial land by bidding and auction will create barriers to entry and a crowding-out effect, promote the rationalization of industrial structure and the transformation and upgrading of industrial structure and moderate carbon emissions. In terms of city heterogeneity, there is urban heterogeneity in the impact of industrial land transfer on carbon emissions in cities with different economic types. Bidding and auction transfer for industrial land in both economically developed and less developed cities can promote carbon pollution. While the more developed urban economy makes the intermediary effect of industrial structure not significant. In the future, it is necessary to strictly control the scale of industrial land supply; the whole process supervision mechanism of industrial land allocation and differentiated industrial land supply strategies will provide useful experience for many developing countries in allocating industrial land to mitigate carbon emissions, generating effective contributions to global carbon emission reduction. [ABSTRACT FROM AUTHOR]

An accurate evaluation of carbon emission efficiency (CEE) at the city level can provide guidelines for understanding low carbon performance, which is crucial to achieving dual carbon targets. Existing CEE studies focused on national, industrial, and provincial scales while neglecting the city level and failing to consider competing relationships among decision-making units in their measurement models. To fill these gaps, this paper introduces the data envelopment analysis game cross-efficiency model (DEA-GCE) to measure urban CEE performance and compares it with the traditional Super-SBM model using the data from 283 Chinese cities between 2006 and 2019. The results show that (1) the DEA-GCE method provided more intensive and stable results. (2) Overall CEE of Chinese cities declined slightly amidst fluctuations during this period. (3) CEE in cities exhibits spatial clustering characteristics. CEE performance in Northeast China has improved, while CEE in Northwest China continues to lag behind. This study introduced an innovative method for calculating urban CEE and conducted an empirical study of 283 Chinese cities, which has implications for formulation of emission reduction policies. [ABSTRACT FROM AUTHOR]

Considering the opening of high-speed railway (HSR) as a quasi-natural experiment, this paper explores the emission reduction effect of HSR opening and its mechanisms and heterogeneity characteristics based on the panel data of 272 cities in China from 2006 to 2019 by staggered DID model and the mediating effect model. It is found that (1) the opening of HSR significantly reduces the carbon emission level of cities, and the conclusion still holds after controlling the endogeneity issue and a series of robustness tests; (2) Bancon decomposition and negative weight diagnostics both show that the estimated average treatment effect bias is small and the robust estimators are more robust; (3) by reducing production costs and promoting inter-regional industrial division of labor, the opening of HSR promotes intra-industrial structural transformation and inter-industrial structural transformation, respectively, thus reducing urban carbon emissions. At the same time, HSR achieves urban carbon emission reduction by promoting free movement of population and human capital agglomeration; and (4) further study finds that there is regional heterogeneity in the emission reduction effect of HSR opening, and the carbon reduction effect is mainly reflected in large and medium-sized cities, near provincial capitals, non-resource-based cities, and cities with rich educational resources, which indicates that the location of future HSR should be combined with the city's own characteristics and be tailored to the city. [ABSTRACT FROM AUTHOR]

The formulation of long-term step-by-step emission reduction plan is an important step for effective scientific emission reduction. This paper takes Shanghai as the research object, constructs PSO-LSTM model on the basis of STIRPAT model, and further constructs three dynamic policy scenarios combined with China's actual situation and makes short-, medium-, and long-term multivariate predictions for them. The study finds that only the improvement of energy consumption structure has a promotion effect on carbon emission reduction, and urbanization, industrial structure, technology level, population, and economic level all have an increasing effect, and secondly, the carbon emission reduction path of Shanghai basically achieves the core objective of steady decrease under the three scenarios. Secondly, under the three scenarios, Shanghai's carbon emission reduction path basically achieves the core objective of steady decline, but the decline in the GU scenario is more significant. It is recommended that Shanghai further adjusts its industrial structure, optimizes its energy consumption structure, promotes technological innovation and progress, and promotes the development of the circular economy model. [ABSTRACT FROM AUTHOR]

The low-carbon transition is a systemic economic and social change that will inevitably have an impact on many areas of the urban system. Has China's ongoing low-carbon transition impacted urban resilience (UR) systems while achieving urban energy saving and carbon emission reduction goals? This paper uses the implementation of the carbon emissions trading pilot policy (CETPP) as a "quasi-natural experiment." It evaluates the impact of the policy on UR using a difference-in-differences model based on the data of prefecture-level cities from 2008 to 2020. The study shows that pilot carbon trading policies favor UR, and the market mechanism of carbon emissions has a heterogeneous cause influence on UR. The impact of pilot carbon trading policies on UR varies according to the respective moderating effects of institutional factors, green technology innovation, industrial structure rationalization, and output effects. [ABSTRACT FROM AUTHOR]

The establishment of green finance reform and innovation pilot zones is an important practical exploration to achieve carbon emission reduction goals through green finance in China. Based on the panel data of 282 Chinese prefecture-level cities from 2006 to 2019, this paper examines the mechanism of China's green financial reform and innovation pilot zone policy (GFRI) on urban carbon emissions (CE) and carbon emission efficiency(CEE) using difference-in-differences model. The study shows that GFRI has a significant carbon emission reduction effect, which is reflected in the significant reduction of urban CE and the improvement of urban CEE. GFRI achieves carbon emission reduction by promoting urban green innovation, while the mediating effect of financial agglomeration has not been verified. The results of heterogeneity analysis show that GFRI has more significant effects on carbon emission reduction in non-resource-based cities, large-scale cities and cities with strict environmental regulation. Financial development and digital infrastructure play a positive moderating role on the carbon emission reduction effect of GFRI. This study provides empirical evidence and policy insights from the Chinese city level for deepening the green finance policy and promoting urban low-carbon development. [ABSTRACT FROM AUTHOR]

The construction of high-speed railways and the smart city pilot (HSR-SCP) demonstrates the synergy of traditional and new infrastructure upgrades, which has a significant influence on the economic transition and green economic growth. However, little study has been conducted on the impact of HSR-SCP synergy on carbon emissions. Applying China's prefecture-level panel data, this paper, therefore, attempts to investigate the effect of HSR-SCP on carbon emissions and uncover its in-depth mechanism through the multi-period difference-in-differences model. Notably, an appropriate instrumental variable for HSR-SCP is introduced to address possible endogeneity. The main conclusions indicate that the construction of HSR-SCP plays an essential role in cutting carbon emissions, which is still valid after adopting the instrumental variable method and some robustness tests. Furthermore, green technology innovation plays a crucial intermediary role in that relationship. Finally, the carbon reduction effect of HSR-SCP is significant in Mid-Eastern China and cities with high population sizes and administrative levels, but not in other cities or regions. The research conclusions demonstrate the significant synergy of traditional and new infrastructure upgrades on carbon reduction and provide an empirical foundation for developing countries to realize low-carbon development through optimizing smart infrastructure and promoting green technology innovation. [ABSTRACT FROM AUTHOR]

Institutions are the fundamental determinants of carbon emission performance. However, the environmental impact of intellectual property institution, especially its impact on carbon emissions, has been paid little attention. Therefore, the main purpose of this study is to assess the effect of intellectual property institution on carbon emission reduction, revealing a new solution to control carbon emissions. To achieve the goal, this study regards the National Intellectual Property Demonstration City (NIPDC) policy in China as a quasi-natural experiment of intellectual property institution construction and exploits the difference in difference approach to objectively evaluate the impact of intellectual property institution on carbon emission reduction based on the panel data of China's cities. The study draws the following important conclusions. First, compared with non-pilot cities, the NIPDC policy has reduced urban carbon emissions by 8.64% in pilot cities. In particular, the "carbon emission reduction dividend" of the NIPDC policy is in the long term but not in the short term. Second, the influence mechanism analysis shows that the NIPDC policy can promote carbon emission reduction by stimulating technology innovation, especially breakthrough innovation. Third, the space overflow analysis reveals that the NIPDC policy can mitigate carbon emissions in adjacent areas, resulting in obvious spatial radiation effect. Fourth, the heterogeneity analysis confirms that the carbon emission reduction effect of the NIPDC policy is more obvious in low administrative hierarchic cities, small and medium-sized cities, and western cities. As a result, Chinese policymakers should orderly promote the construction of NIPDCs, strengthen technology innovation, give full play to the spatial radiation role of NIPDCs, and optimize the role of government, so as to better release the carbon emission abatement effect of intellectual property institution. [ABSTRACT FROM AUTHOR]

Green and low carbon transition is a broad and profound economic and social systematic change. Green innovation is a critical way to promote energy saving and emission reduction. Has China continuously promoted a carbon emission trading policy to significantly promote green innovation cooperation? Taking the implementation of the carbon emission trading pilot policy as a "quasi-natural experiment," this study answers this question by exploring the impact of the policy on green innovation cooperation. Based on data on 274 cities from 2008 to 2020, the multi-time difference-in-differences model is used to evaluate the impact of the policy on green innovation cooperation. The results reveal that the carbon emission trading pilot policy significantly improved inter- and intra-city green innovation cooperation through the upgrading effect of industrial structure and the coverage effect of digital finance compared with the non-pilot cities at the city level. In addition, there are significant differences in the policy effects among cities with different degrees of openness to the outside world and command-and-control environmental regulation. [ABSTRACT FROM AUTHOR]

Exploring the relationship between economic development and carbon emissions is a hot issue of concern to academia. Taking Chinese cities as the research object, this study constructed an allometric growth model of economic scale and carbon emissions to analyze the spatial–temporal evolution of their allometric growth from 2000 to 2017. Additionally, the geographical detector model was used to reveal the driving mechanism of allometric growth. The findings were as follows. (1) The spatial–temporal patterns of economic scale and carbon emissions were dominated by hot spots. Additionally, their size distribution was in an equilibrium stage. (2) The gap between the economic growth rate of Chinese cities and the growth rate of carbon emissions grew, reflecting the remarkable achievements in carbon emission reduction in Chinese cities as a whole. The scaling exponent declined from east to the west during 2000–2008, but showed the opposite trend during 2009–2017. The proportion of cities with negative allometric growth in the sample cities increased from 76.49 to 97.86%. (3) The influence of city investment intensity, energy utilization efficiency, technological development level, social consumption level, fiscal investment level and economic development level on allometric growth gradually decreases. These factors were also the main factors affecting the spatial–temporal heterogeneity of allometric growth. (4) The impact of various factors had a synergetic enhancement effect. These factors can be classified as economic factors, environmental factors and a combination of them. Under the nonlinear coupling of multiple factors, a spatially differentiated pattern of allometric growth was formed. [ABSTRACT FROM AUTHOR]

Technological progress is considered an effective means to reduce carbon emissions, and an innovative city pilot scheme may contribute to this target. However, the impact of innovation city construction on carbon emissions has not been systematically studied. Based on panel data of 285 cities at prefecture level and above in China from 2003 to 2017, this study employs the difference-in-differences approach to evaluate the impact of innovative city pilots on CO2 emissions. The results show that CO2 emissions in pilot cities are 17.1% lower than that in non-pilot cities, indicating that the scheme contributes significantly to carbon emission reduction. Meanwhile, the spatiotemporal characteristics suggest that the local effect increases over time and the spillover effect is significant within 150–250 km. Additionally, a heterogeneity analysis shows that the impact of the pilot scheme on CO2 emissions is mainly reflected in the central region and prefecture-level cities. Lastly, mechanism analysis indicates that the pilot policy reduces CO2 emissions by promoting technological innovation, industrial upgrading, and environmental governance, of which technological innovation plays the most important mediating role. [ABSTRACT FROM AUTHOR]

As a gathering place for human production activities, cities are the main places where energy consumption and carbon dioxide emissions occur. How to accurately measure city size and test the impact mechanism of city size on carbon emissions of different city levels is still controversial. This study uses the global nighttime light data to identify urban bright areas and built-up areas, and accordingly constructs the city size index of 259 prefecture level cities in China from 2003 to 2019. It avoids the problem of only considering the single index of population size or space size, and makes the measurement of city size more reasonable. We use a dynamic panel model to study the impact of city size on urban carbon emissions per capita, and discuss the heterogeneity of various cities under different population levels and economic development levels. The empirical results indicate that in the scale of cities in China showed a fluctuating growth trend in recent years. The city size index of most cities is clustered at medium and high values. The city size index of cities with different economic development levels and different population-scale levels shows obvious gradient differences but maintains an upward trend. The expansion of supercities (with a population of more than 5 million) introduces a drastic increase in carbon emissions. The carbon emissions growth caused by the expansion of cities that are classified as third tier and below is the smallest, while that caused by the expansion of cities that are classified as first-tier is the largest. The findings suggest differentiated emissions reduction suggestions for cities with different sizes. [ABSTRACT FROM AUTHOR]

Against achieving carbon peaking by 2030 and carbon neutrality by 2060 context in China, the new energy demonstration city policy (NEDCP) has a crucial function to perform in promoting resource utilization efficiency, building the green development policy system, and facilitating carbon emission reduction. However, existing research has rarely investigated the contribution of NEDCP on carbon reduction. To investigate the policy effect of NEDCP, the differences-in-differences (DID) model is introduced to quantify the influence of NEDCP on carbon reduction, taking a statistical sample of 285 Chinese cities over the period 2005–2017 on the basis of exploring the intrinsic mechanism of NEDCP on carbon emissions. The statistical results reveal that NEDCP significantly inhibits carbon emissions. NEDCP's dampening impact on carbon reduction is more pronounced in the eastern area but not in other areas. City size and resource endowment heterogeneity results suggest that NEDCP significantly inhibits the output of carbon emissions in non-resource-based and large cities but insignificantly in resource-based and small- and medium-sized cities. Finally, we conclude that policy-makers should not only broaden the scope of NEDCP implementation continuously but also design relevant policy combination tools following the basic characteristics of each city to provide institutional guarantees for achieving carbon emission reduction. [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]