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The reduction of greenhouse gas emissions is a shared challenge encountered by nations worldwide. As China is on its way toward a green economy, it is worth studying whether producer services agglomeration, a key driver of economic transition, can promote low-carbon urban development. Using panel data of 257 cities across China from 2006 to 2019, this paper examines the influence of producer services agglomeration on urban carbon emissions with spatial econometric models. The findings reveal a positive spatial correlation in regional carbon emissions. The agglomeration of producer services notably decreases the intensity of local carbon emissions, yet it appears to have minimal influence on the emissions from adjacent regions. Enhancing energy efficiency and adjusting the industrial structure are two critical mechanisms by which producer services agglomeration reduces urban carbon emissions. This beneficial effect varies with city type, the abatement effect of producer services agglomeration is more pronounced in non-resource-based cities. When considering city size, the carbon reduction potential of producer services agglomeration is not apparent in smaller cities. As city size increases, the emission reduction effect becomes more apparent. However, in mega-cities, this impact is somewhat diminished. Accordingly, this paper proposes exploring methods of coordinated air pollution management across cities, promoting producer services agglomeration in line with market mechanisms, and driving low-carbon urban development in a manner tailored to local conditions. [ABSTRACT FROM AUTHOR]

Carbon emission reduction is crucial for mitigating global climate change, and green fiscal policies, through providing economic incentives and reallocating resources, are key means to achieve carbon reduction targets. This paper uses data covering 248 cities from 2003 to 2019 and applies a multi-period difference-in-differences model (DID) to thoroughly assess the impact of energy conservation and emission reduction (ECER) fiscal policies on enhancing carbon emission (CE1) reduction and carbon efficiency (CE2). It further analyzes the mediating role of Green Innovation (GI), exploring how it strengthens the impact of ECER policies. We find that: (1) ECER policies significantly promote the improvement of carbon reduction and CE2, a conclusion that remains robust after excluding the impacts of concurrent policy influences, sample selection biases, outliers, and other random factors. (2) ECER policies enhance CE1 reduction and CE2 in pilot cities by promoting green innovation, and this conclusion is confirmed by Sobel Z tests. (3) The effects of ECER policies on CE1 reduction and the improvement of CE2 are more pronounced in higher-level cities, the eastern regions and non-resource cities. This research provides policy makers with suggestions, highlighting that incentivizing green innovation through green fiscal policies is an effective path to achieving carbon reduction goals. [ABSTRACT FROM AUTHOR]

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]

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]

The accountability audit of natural resources (AANR) is a major institutional arrangement for advancing the construction of an ecological civilization in China. Based on the panel data of 271 cities in China from 2005 to 2017, this paper investigates the relationship between the AANR and carbon dioxide (CO2) emissions using a multi-period difference-in-differences (DID) model. The results show that AANR significantly increases the CO2 emission reduction rate by 0.009 units at the 5% significance level. The results still hold after a series of robustness tests. Given all else being equal, this significant effect is 0.001. Further analyses show that AANR improves pilot cities' CO2 emission reduction rates mainly by enhancing their green innovation capability. The mediating effect of cities' green technology innovation capability accounts for 96.00%, while the AANR's direct effect only accounts for 4.00%. The AANR has significantly positive effects of 0.017% and 0.029% for western cities and cities with high fiscal pressure at the 5% and 1% significance levels, respectively. Therefore, strengthening AANR implementation by enhancing the mediating efficiency of cities' green technology innovations and implementing dynamically differentiated AANR policies in Chinese meso-cities will contribute to the achievement of China's carbon peaking and carbon neutrality targets. [ABSTRACT FROM AUTHOR]

This paper analyzes the theoretical mechanism by which urbanization and consumption structure upgrading exert an impact on carbon emissions in the context of promoting higher quality and efficiency in urbanization, advancing the transition and upgrading of consumption structure, and achieving carbon peaking and carbon neutrality ("dual carbon") goals. By establishing an extended STIRPAT model and an intermediary model, this paper takes nine prefecture-level cities in Fujian Province from 2011 to 2021 as samples to investigate the effects of urbanization and consumption structure upgrading on carbon emission reduction in Fujian Province, revealing the interrelationship and transmission mechanism among the three. The results of this study show that: (i) The relationship between urbanization and carbon emissions in Fujian Province from 2011 to 2021 shows an inverted U-shaped curve, i.e. urbanization accelerated carbon emissions in the early stage and inhibited carbon emissions in the later stage; (ii) the regional heterogeneity analysis shows that under the current urbanization background, the upgrading of consumption structure in western and southern Fujian can significantly reduce carbon emissions, while the relationship between consumption structure upgrading and carbon emission reduction in eastern Fujian is not significant; (iii) the upgrading of consumption structure can help achieve and promote carbon emission reduction through increasing the proportions of the tertiary industry and immaterial consumption and enhancing the level of culture and education, while exerting little effect on carbon emission reduction through consumption in transportation, communication and health care. [ABSTRACT FROM AUTHOR]

Reducing greenhouse gas emissions is a crucial challenge in urban areas characterized by high energy consumption and reduced exposure to nature. In this context, the urban green system could play a pivotal role. In the literature, scholars have analyzed both the ability of species-specific and layout-specific green infrastructure to increase carbon sequestration and the best location sites for new green infrastructure to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement based on vegetation species-specific performance and the local carbon emissions of city components. This paper uses tree inventory data from a medium-sized city in central Italy (Perugia) to develop a spatial analysis of urban park performance in carbon sequestration. Then, the method evaluates the carbon emission of a public city building to generate a spatialized balance between building demand and tree supply to support local decisions about the best locations for new green infrastructure and the choice between species. The paper contributes to GIS-based tools that vary the recommended location sites and species for new green infrastructure based on the demanded ecosystem service. [ABSTRACT FROM AUTHOR]

Under the goal of " carbon peaking and carbon neutrality," how to create a low-carbon and green development path for cities is an urgent problem in China. One of the effective ways to solve this problem is through industrial collaborative agglomeration. In this paper, panel data of 276 prefecture-level cities in China from 2010 to 2020 was selected to investigate the relationship between the collaborative agglomeration of manufacturing and producer service and carbon emission intensity by using a fixed-effects model, intermediary model, and SDM in multiple dimensions. The study found that the collaborative agglomeration of manufacturing and producer service industries significantly influences carbon emission intensity with an inverted U-shaped curve, and the agglomeration of manufacturing and producer service industries can influence carbon emission intensity through technological progress. In addition, the inverted U-shaped impact of collaborative agglomeration of manufacturing and producer services on carbon emission intensity has a spatial spillover effect, and the spatial spillover effect generated is stronger than the impact on the local area. Moreover, from the perspective of industry heterogeneity, compared with low-end producer services, the agglomeration of manufacturing and high-end producer services can play a better role in carbon emission reduction. Regarding regional heterogeneity, compared with the central and western regions, the impact of manufacturing and production services agglomeration on carbon intensity is far more obvious in the more economically developed eastern regions. [ABSTRACT FROM AUTHOR]

Since 2010, the Chinese government has developed several batches of low-carbon pilot provinces and cities continuously. And in the backdrop of carbon peak and carbon neutralisation recently, the carbon emission reduction policies and achievements of China have attracted more and more worldwide attention. In the field of human health, this paper investigates whether the Low-carbon Province Pilot Policy of China has positive effects on residents' health based on the micro data of China Family Panel Studies (CFPS) from 2010 to 2016. Using the time-varying difference-in-difference model to solve the endogeneity problem commonly faced in the literature, we find that Low-carbon Province Pilot Policy has a positive impact on public health through air quality improvement and the unemployment level alleviation mainly. And in urban areas, the policy effect is more obvious than that in rural regions. This paper expands the content of national low-carbon governance effects to residents' health further and contribute to China's low-carbon development. Specifically, it reminds us to focus on the dynamic adjustment and effective continuation of the policy, and also the all-round support for 'the disadvantaged' in environmental governance process. [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]

This paper aims to establish a more standardized and regulated carbon emission accounting model for sponge cities by unifying the accounting content for carbon emissions and clarifying the relationships between carbon reduction benefits, carbon reduction effects, and carbon sequestration, in order to evaluate the carbon reduction outcomes and mechanisms of sponge city construction. Based on a Life Cycle Assessment (LCA) carbon emission accounting model using the carbon emission factor method, a newly constructed residential area in Tianshui City, Gansu Province, was selected as a case study, and the carbon emission reduction effect of sponge city construction was then investigated. Results indicated that the 30-year full life cycle carbon emissions for sponge city construction in the newly constructed residential area amounted to 828.98 tons, compared to 744.28 tons of CO2 reduction in traditional construction, representing a 47.31% reduction in carbon emissions. Over a 30-year life cycle, this equated to a total carbon emission reduction effect of 1460.31 tons. Additionally, under various rainfall scenarios in a typical year, the carbon emission reduction effect of sponge city construction exceeded the carbon emissions, achieving carbon neutrality within 22 to 30 years of operation. This demonstrates that the carbon emission reduction effect of sponge city communities is significant. The findings of this study provide data and a theoretical basis for the low-carbon construction of sponge cities in China. [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]

As urbanization continues to accelerate worldwide, the consequential rise in CO2 emissions has caused substantial environmental challenges. Urban regeneration has emerged as a promising approach to reducing carbon emissions and developing low-carbon cities. Even though both urban regeneration and carbon emissions reduction have been researched from various perspectives, a thorough review is still required to completely reveal their multifaceted relationship. Based on 231 papers published between 2001 and 2023, a bibliometric analysis was conducted to understand the overall trajectory and main focus of the existing research. Then, we qualitatively analyzed the main findings from bibliometric results in terms of key regeneration elements, specific regeneration strategies, research methodologies, as well as research trends and agendas. The results indicated that research in this field is gradually becoming more specialized and comprehensive. Buildings and energy have always been two key urban regeneration elements and research hotspots. Additionally, as a systematic project, reducing carbon emissions requires further exploration of other regeneration elements' contributions and their interactions in the urban system, which needs the corresponding support of more specific regeneration strategies and research methodologies. These findings can advance the development of innovative and impactful pathways for low-carbon oriented urban regeneration, leading ultimately to sustainable cities. [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]

Urban carbon emissions are an important area for addressing climate change, and it is necessary to establish scientific and effective carbon emission prediction models to formulate reasonable emission reduction policies and measures. In this paper, a novel model based on Lasso regression, an ARIMA model, and a BPNN is proposed. Lasso regression is used to screen the key factors affecting carbon emissions, and the ARIMA model is used to extract the linear components of the carbon emission sequences, while the BPNN is used to predict the residuals of the ARIMA model. The final result is the sum of that from the ARIMA model and the BPNN. The carbon peak, carbon neutralization time, and emissions were analyzed under different scenarios. Taking Suzhou City as an example, the results show that the electricity consumption of the whole population is one of the key drivers of carbon emissions; the carbon emission prediction accuracy and stability of the ARIMA-BPNN combined model are better than those of the single model, which improves the reliability as well as the accuracy of the model's prediction. However, under the constraints of the current policies, the goal of achieving carbon peaking by 2030 in Suzhou City may not be realized as scheduled. This novel carbon emission prediction model built was validated to provide a scientific basis for low-carbon urban development. This study presents an important reference value for predicting carbon emissions and formulating emission reduction measures in other cities. [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]

• We study the relationship between GVC embedding and carbon emission density. • A mediation effect model was established to test the mechanism. • There is a U-shaped relationship between urban GVC embedding and carbon emission density. To achieve its carbon peak and neutrality plan, whether China's global value chain (GVC) embedding has a carbon emission reduction effect is a question worthy of attention. This paper measures the GVC embedding degree of 218 Chinese cities from 2000 to 2016, and constructs a panel data model to investigate the impact and its mechanism of GVC embedding on carbon emission intensity. This study finds that there is a significant U-shaped relationship between GVC embedding and carbon emission intensity, and a series of robustness test results support this conclusion. Export scale, energy consumption structure and technological innovation play a mediation role in the impact path of GVC embedding on carbon emission intensity. Based on this, this paper proposes that while participating in GVC, China needs to actively utilize the emission reduction effect of GVC, promote the transformation of export mode to high quality, reduce the use and dependence on high-carbon resources such as coal, and encourage companies to innovate. [ABSTRACT FROM AUTHOR]

The variation in the urban spatial structure (USS) has profound impacts on carbon emissions. Studying the relationship between the two can provide guidance for carbon neutrality strategies and the construction of low-carbon cities in China. However, there is currently a lack of comparative research on the different regions within a province. In this paper, the spatiotemporal evolution of the USS and carbon emissions, at five-year intervals from 2000 to 2020, is investigated in 21 prefecture-level cities in Guangdong Province, China, and the overall relationship of the USS to carbon emissions and their spatiotemporal variations are analyzed by using a two-way fixed-effects model and a geographically and temporally weighted regression model, respectively. The results show that, first, over the past twenty years, the scale of cities has continued to expand, with increasing continuity and aggregation in the built-up areas, while the complexity and fragmentation of their shapes have gradually decreased. Second, the gap in carbon emissions between the Pearl River Delta and other regions in Guangdong shows a trend of first decreasing and then increasing, with high values concentrated in the Pearl River Delta region and the city of Shantou in the east. Third, compared to socio-economic factors, the USS has a more direct and pronounced impact on carbon emissions. Urban expansion and the increased complexity of land patches promote carbon emissions, whereas improving urban spatial continuity and compactness can reduce carbon emissions. Fourth, the dominant spatial structure indicators of carbon emissions differ among the regions of eastern, western, and northern Guangdong and the Pearl River Delta. This study proposes spatial optimization strategies for the low-carbon development of cities in Guangdong Province, providing a new perspective for integrating urban layout and emission reduction policies. [ABSTRACT FROM AUTHOR]

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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 reliance solely on the government or enterprises to promote climate governance is contingent upon the vested interests of economic entities and the regulatory bodies' efficiency in governance. Can the model of government-enterprise green collaborative governance evolve into a long-term mechanism for addressing the climate crisis and achieving the goals of sustainable development? By crawling data on public-private partnerships (PPP), employing ChatGPT to identify green PPP projects, and building a generalized difference-in-differences framework based on the Guidance on Building a Green Financial System issued in 2016, this present study investigates whether the involvement of private capital in government-led environmental and climate governance can effectively facilitate government-enterprise green collaborative governance, thereby mitigating urban carbon emissions. The study finds government-enterprise green collaborative governance can significantly reduce urban carbon emissions. The conclusion remains valid even after several rounds of robustness tests, including removing the influence of pertinent climate policies, adjusting the settings of independent and dependent variables, and removing self-selection issues. Heterogeneity tests show, on the first hand, the carbon emission reduction effect of government-enterprise green collaborative governance differs due to the differences in the characteristics of green PPP(Pubic-private partnership) projects such as project return mechanism, project investment volume, and project cooperation term; on the other hand, the carbon emission reduction effect also shows heterogeneity with various urban characteristics such as geographical location, city type and city size. Mechanism tests indicate government-enterprise green collaborative governance affects urban carbon emissions mainly through structural effects, technological effects and co-investment effects. This paper offers a valuable framework for effectively promoting environmental and climate co-governance between governmental bodies and enterprises, while enhancing the market's role in resource benefit allocation within climate governance to mitigate the risks associated with climate change. • This paper first verifies the effectiveness of the green PPP model in carbon emission control. • The use of ChatGPT to identify green PPP projects, which provides an innovative method for data processing. • The carbon reduction effect varies with the characteristics of green PPP projects and cities. • This paper offers a valuable framework for effectively promoting climate co-governance between governmental and enterprises. [ABSTRACT FROM AUTHOR]

Road transport has been one of the largest contributors to global carbon emissions. In the Philippines, one such measure is the introduction of a relatively new public transport mode called the “Premium Point-to-Point (P2P) Bus Service”, which features shorter travel time and lower emission intensity than conventional buses. In light of the significant deficiency in transport emission studies for Philippine cities, this paper presents a scenario-based method for quantifying the potential emission reduction benefits of the P2P bus in Metropolitan Manila. Based on a pro rata mode shift assumption, it is estimated that a 1% mode shift of passengers from existing motor modes to P2P buses would lead to 0.64% reduction of total emissions over selected travel routes in Metro Manila. The analytical method addresses the acute emission data scarcity in the Philippines, and provides early evidence on the aggregate environmental benefits of P2P buses. Extensive sensitivity tests are conducted to verify the simulation results and identify key determinants of emission reduction. The tests confirm the robustness of research findings and further uncover the great potential of increasing vehicle occupancy levels to mitigate vehicle emissions in Metro Manila. Policy implications for enhancing the environmental benefits of P2P buses are provided. [ABSTRACT FROM AUTHOR]

The map of radiative cooling potential shows that the radiative cooling power can reach up to 100 W/m2 for its application in different climatic zones. However, the effect of building deployment on the city-scale application of radiative cooling is generally ignored in majority of existing studies, which overestimates the cooling benefit. This paper investigates the cooling benefit of implementing radiative cooling on a city-scale by considering building deployment. To determine the effect of building deployment on the radiative cooling potential, the city of Xi'an in China is modeled using COMSOL and verified with real weather data. Then, the thermal response of buildings with radiative cooling envelopes is discussed in detail. Finally, carbon emission reduction is derived at the city-scale by applying radiative cooling considering building deployment. The results show that the estimated radiative cooling power is approximately decreased by 14.7% for the ideal broadband surface and 47.1% for the ideal selective surface on the selected day by considering building deployment on a city-scale. Furthermore, carbon emission reductions of 0.52 gCO 2 /(m2⋅h) and 0.16 gCO 2 /(m2⋅h) can be achieved from the roof and walls on the selected day by applying radiative cooling material on both the roof and walls. This study can provide guiding significance for the large-scale application of radiative cooling in cities. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

Addressing global warming is one of the most pressing environmental challenges and a crucial agenda for humanity. In this literature study, we employed bibliometrics to reproduce nearly two decades of research on carbon emission reduction in China, the largest carbon emitter worldwide. The scientometrics analysis was conducted on 1570 academic works published between 2001 and 2021 concerning China's carbon emission reduction to characterize the knowledge landscape. Using CiteSpace and VOSviewer, the basic characteristics, research forces, knowledge base, research topic evolution, and research hotspots were identified and revealed. The analysis results show that the attention to and research on China's carbon emissions have increased in recent years, giving rise to leading institutions and relatively stable core journal groups in this field. The research disciplines are relatively concentrated, but the research collaboration needs strengthening. The research hotspots are mainly carbon emission causes, impacts, and countermeasures in China, and the research frontiers have been constantly advanced and expanded. In the future, research on countermeasures needs more effort, and research cooperation needs to strengthen. The changing landscape of hotspot clusters reveals China's transition towards a low-carbon economy. Through comprehensive analysis of the potential and obstacles to China's transition to low-carbon development, we identified three promising areas of action (low-carbon cities, low-carbon technologies and industries, and transforming China's energy system) and proposed research directions to address remaining gaps systematically. [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]

In this paper, 41 prefecture level cities in the Yangtze River Delta (YRD) are selected as the research objects. Based on the semantic mining model, the policy data information from three dimensions namely national, provincial and municipal levels is integrated to build data-driven multiple scenarios. Then the long short-term memory neural network optimized by particle swarm optimization (PSO-LSTM) is further used to predict the peaking time of the YRD urban agglomeration under multiple scenarios. The results show that the YRD urban agglomeration as a whole can achieve carbon peaking on time under all three simulation paths, but the peaking situation of specific cities within the region will be significantly different due to differentiated policy orientations. Under the business as usual scenario, some cities in the north of the region cannot achieve carbon peaking by 2030. Under the stable growth scenario, more cities cannot achieve carbon peaking on time. However, under the low carbon scenario, all cities within the region can achieve carbon peaking by 2030. Therefore, when exploring effective carbon peaking paths, adopting more stringent policies and measures to limit carbon emissions can help achieve the regional carbon peaking goal earlier, ensure that all cities within the region can achieve carbon peaking on time, and can also narrow the gap between cities within the region in terms of peaking time. This paper explores a new scenario analysis parameter setting and carbon emission prediction method, which overcomes the subjectivity of current scenario analysis research in parameter setting to a certain extent, and also provides a scientific reference for predicting the diversified development trend of carbon emission. • The semantic mining method is used to determine the scenario parameters. • PSO-LSTM is used to improve the accuracy of carbon emission prediction. • Multiple scenarios of carbon emission development trends. • Differentiated emission reduction paths for cities. [ABSTRACT FROM AUTHOR]

The current research investigating the effectiveness of policy-driven transformation in resource-based cities has focused mainly on city-level impacts and has overlooked firm-level evidence. This paper filled this gap by focusing on its impact on firm-level carbon emissions. Drawing on the quasi-natural experiment of China's reform of resource-based city transformation, we utilize a difference-in-differences (DID) model based on nationwide firm-level tax survey data from 2009 to 2016. The findings indicate a noteworthy reduction in firms' carbon emissions due to the reform, particularly in growing-type resource-based cities and within the manufacturing industry. The empirical results provide evidence that the implementation of the "Plan" has effectively enhanced the level of urban resilience. Moreover, the findings demonstrate stronger effects on large firms, publicly owned firms, and firms in municipal districts. • Resource-based city transformation is effective at mitigating firm carbon emissions and enhancing urban resilience. • Different development stages exhibit heterogeneity in the effectiveness of firm emissions reductions. • Sector- and firm-specific characteristics play a significant role in reduction in firms' carbon emissions. [ABSTRACT FROM AUTHOR]

This study employs panel data from 30 provinces and cities in China from 2004 to 2019 to empirically estimate the relationship between producer services agglomeration (PSA) and manufacturing carbon emissions. The findings suggest that such agglomeration is beneficial for lowering carbon emissions in manufacturing, and this conclusion passes multiple robustness tests. Heterogeneity analysis results show that PSA in the east and west regions significantly lowers manufacturing carbon emissions, while its impact in the central region is not significant. High-end PSA is beneficial for cutting carbon emissions in manufacturing, but the inhibitory effect of middle- and low-end PSA is not significant. PSA significantly suppresses carbon emissions from capital- and technology-intensive manufacturing, while it has little impact on carbon emissions from labor-intensive manufacturing. Further analysis reveals that PSA has a dual-threshold impact based on absorptive capacity and a single-threshold effect based on infrastructure level on manufacturing carbon emissions. As the absorption capacity crosses the second threshold or the infrastructure level crosses the first threshold, the inhibition effect of PSA on manufacturing carbon emissions begins to become prominent and shows a trend of enhancement. Our research findings provide theoretical and empirical bases for lowering carbon emissions in the manufacturing sector and fostering its ascent to the highest position of the value chain. [ABSTRACT FROM AUTHOR]

Land use directly affects the carbon emissions and carbon stock of the ecosystem, and indirectly affects the carbon emissions from anthropogenic activities, which occur more frequently in coastal regions. Taking Nantong City as an example, detailed carbon emission projects were classified and calculated for different land use types by combining land use images of five typical years. Based on the complex relationship between land use carbon emissions and socio-economic factors, the system dynamics model (SD) was used to simulate the land use carbon emissions from 2005 to 2060, and to construct carbon-neutral policy scenarios. Compared with inlands, carbon emissions from land use in Nantong are more pronounced than inland areas, and unique land use types, such as shallows, play an important role as carbon sinks. Total land use carbon emissions show an upward trend from 2005 to 2020 and carbon emissions from construction land dominate. Under the natural development condition, the total net carbon emissions of Nantong are about 4,298,250 tons in 2060, failing to achieve carbon neutrality. The scenario with all four policies adjusted (LO, IO, TP, and PC) has the best emission reductions, peaking at 10,949,010 tons of net carbon emissions in 2029 and reducing them to 1,370,202 tons in 2060, which is the scenario closest to the carbon-neutral target. Overall, this study provides a meaningful conclusion for the study of land use carbon emission characteristics and low-carbon pathways in coastal cities, which can guide the formation of government policies. [ABSTRACT FROM AUTHOR]

Based on the panel data of Guangxi from 2005 to 2017, the spatiotemporal characteristics and determinants of urban carbon emissions in Guangxi were analyzed using the extended STIRPAT model and the Geographically and Temporally Weighted Regression (GTWR) model. The main findings of our research can be summarized as follows. While the total carbon emissions of cities in Guangxi consistently increased from 2005 to 2014, the growth trend slowed after 2014, leading to a stabilization in the total emissions. In addition, there are significant differences in the total carbon emissions among the cities. The central and northeastern regions have higher emissions, while the southwestern region has lower emissions. Finally, there are variations in the degrees and directions of the impacts that factors have on carbon emissions among the different time periods and cities. Urban land use is a key factor driving carbon emissions, and it has a negative impact on most cities in Guangxi. Meanwhile, factors such as industrial structure, population urbanization, population concentration, and economic growth have significant positive effects on carbon emissions in Guangxi. The influence of urban roads on carbon emissions is generally positive, while the degree of openness to the outside world and environmental regulations has relatively weaker impacts on emissions. In summary, in order to promote the low-carbon transition of Guangxi and achieve high-quality development, the cities in Guangxi should implement differentiated urban carbon reduction strategies that are focused on optimizing urban land use and industrial structure. [ABSTRACT FROM AUTHOR]

• The spatiotemporal interactions of carbon emission efficiency(CEE) were explored. • A MGWR model was used to estimate the scale effects of factors influencing CEE. • The evolution of the spatial pattern of CEE had strong spatial integration. • CEE agglomeration changes had path dependence and spatial locking. • The factors influencing CEE exhibit obvious scale heterogeneity. Exploring the spatiotemporal evolution and influencing factors of carbon emission efficiency (CEE) is crucial for achieving the goal of urban carbon neutrality. However, most of the existing studies ignore the temporal dependence of the spatial pattern evolution of CEE and the scale variability of the factors influencing CEE. With the help of an exploratory spatiotemporal data analysis framework, this paper examined the spatiotemporal interactions of CEE across 110 cities in the Yangtze River Economic Belt (YREB). In addition, a multiscale geographically weighted regression model was employed to reveal the scale effects of influencing factors on CEE. The main conclusions are as follows: first, the CEE of cities in the YREB shows a fluctuating upward trend, but the overall level is still low, and a certain polarization phenomenon exists. Second, the spatial pattern of the CEE of cities in the YREB is generally relatively stable, with strong spatial integration and path dependence. Finally, the factors influencing CEE exhibit obvious scale variability and spatial heterogeneity. Our findings can provide a basis for localized and differentiated carbon emission reduction decision-making at the city level, as well as new insights for the formulation of sustainable urban spatial planning and low-carbon development strategies. [ABSTRACT FROM AUTHOR]

In Sharm El Sheikh, Egypt, representatives from 198 countries convened for the 27th Conference of the Parties to the United Nations Framework Convention on Climate Change (COP27) held between November 6 and 20, 2022. A consensus emerged regarding the imperative of embracing a "bottom-up" approach to tackling climate change. The phased introduction of dual-stage measures within the low-carbon city pilot policy in China affords a reputable natural experiment and establishes a treatment cohort for gauging carbon emissions within these zones. Empirical estimation of the abatement impact of China's low-carbon city pilot policy on carbon emissions is undertaken herein, leveraging a comprehensive dataset composed of information on carbon dioxide emissions and economic indicators spanning the years 2000–2017. Key findings are: (1) The low-carbon city pilot policy effectively reduces carbon emissions by 0.2808 Mt and decreases emission intensity by 11.59%. (2) China can achieve 40.28% of its emissions reduction target outlined in the 14th Five-Year Plan due to the efficacy of low-carbon cities. (3) The emissions reduction effect of the policy significantly increases with the implementation of Emissions Trading Scheme pilots. 4) The primary-stage initiatives of the low-carbon city pilot policy drive its emissions reduction effect, while the secondary-stage policy has limited impact due to rational public expectations. This research presents a model for low-carbon city development, proposing strategies that align with a "bottom-up" approach to tackle climate change. These insights may encourage member parties to strengthen commitments and adopt net-zero goals at COP meetings. [ABSTRACT FROM AUTHOR]

Forecasting the future emission trajectories and the relating sensitive driving factors of emissions for cities is of great significance to formulate realizable CO 2 mitigation policies. To proceed the forecasting, studies on peak prediction and quantification of reduction potential at the city level are essential. However, the studies in the area are very limited. Selecting the Beijing-Tianjin-Hebei urban agglomeration (BTH) as the study region, this paper aims to contribute to the research area and provides implications for other cities or urban agglomerations. The Kaya identity and multi-scenario simulation were employed to predict the dynamic evolution pathways of CO 2 emissions from 2021 to 2035 and explore the differential CO 2 peak time, peak value, and reduction potential for 13 cities in BTH. Monte Carlo simulation, Mann-Kendall trend test and Sen's slope estimation method are jointly used to reduce uncertainties in estimation. The Monte Carlo simulation results show that most cities in BTH have already reached their CO 2 emissions peak, while Tianjin, Langfang, Cangzhou and Tangshan are expected to reach their peaks between 2025 and 2030. Among them, 5 and 8 cities have the risk of not reaching their peak before 2035 in the high consumption scenario (HCS) and extensive development scenario (EDS) respectively. Comparative analysis reveals that low-carbon scenario (LCS) and sustainable development scenario (SDS) have significant effects on emissions reductions. The top three cities in terms of accumulative emission reduction in 2021–2035 are Tianjin, Tangshan and Cangzhou, estimated as 117.82–250.75 Mt CO 2 in LCS and 217.77–454.10 Mt CO 2 in SDS, respectively. The results of sensitivity analysis reveal that the most critical driver of CO 2 emissions in Beijing is population, while that is GDP per capita for Tianjin. Langfang and Hengshui showed the highest sensitivity to energy intensity. Accordingly, these cities have differentiated concerns and priorities to achieve their carbon peak goal as scheduled. • Kaya identity and scenario simulation are combined to predict future CO 2 emissions. • The BTH would reach CO 2 emission peak by 2025, but the time varies on city-level. • Tangshan, Langfang, and Cangzhou are at greater risk of not reaching the peak by 2030. • Tianjin, Tangshan and Cangzhou have the greatest potential to reduce emissions. • Differentiated priorities are suggested for specific city's CO 2 mitigation targets. [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]

Reducing carbon emissions is of paramount importance to the accomplishment of the 2030 Sustainable Development Goals. The effect of rural e-commerce on agricultural carbon emissions (ACEs) is controversial, and particularly the mechanism behind the effect is unknown. To identify the impact of rural e-commerce on agricultural carbon emissions and its mechanisms, we take advantage of China's Rural E-Commerce Demonstration County Program (REDCP) as a quasi-natural experiment and use the multi-period difference-in-difference (DID) model to investigate the relationship between rural e-commerce and agricultural carbon emissions. Our data are based on panel data of 355 prefecture-level cities from 2010 to 2019 in China. We identify that rural e-commerce can reduce agricultural carbon emissions by an average of 14.4%, but this effect is not long-lasting. Mechanism analyses suggest that the reduction effect of rural e-commerce on agricultural carbon emissions is mainly due to fostering agricultural economic growth, increasing the share of low-carbon industry, and improving agricultural total factor productivity (TFP). Further heterogeneity analyses demonstrate that rural e-commerce has better carbon emissions reduction performance in eastern cities as well as in non-major grain-producing cities in China. [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]

This study aims to develop a framework linking New-Type Urbanization (NTU) and carbon emissions, considering both direct and spillover effects. Firstly, the paper constructs a multi-dimensional index to measure NTU and documents the spatial patterns of NTU levels in China, showing remarkable inequality between the eastern and western regions. Secondly, the study evaluates the effectiveness of pilot policies aimed at achieving Smart City and NTU goals. Using the Difference-in-Difference model based on panel data collected from 108 cities in the Yangtze River Economic Belt from 2006 to 2019, the study provides empirical evidence that these policies can significantly reduce carbon emissions in terms of production and consumption. Moreover, the study finds that the policies have significant spatial spillover effects on neighboring cities based on the Spatial Panel Durbin Model. The findings suggest that such policies can effectively reduce carbon emissions in areas with significant human activity and have important policy implications for achieving sustainable development in China. • The research assesses how New-Type Urbanization affects emission reduction. • Policy pilots for Smart City & New-type Urbanization reduced environmental emissions. • The impact of emission reduction is spatially heterogeneous. • New-Type Urbanization can increase environmental emissions in nearby cities. [ABSTRACT FROM AUTHOR]

The power industry is a major source of carbon emissions in China. In order to better explore the driving factors of carbon emissions in China's power industry and assist the Chinese government in formulating emission reduction strategies for the power industry, this study applies the improved production-theoretical decomposition analysis (PDA) method to analyze the carbon emission drivers of China's power industry. This study investigates the impact of energy intensity, per capita GDP, population density, power generation structure, and environmental climate on carbon emissions in China's power industry in 30 provinces from 2005 to 2020. It was found that the carbon emission ratios of the power sector in all provinces and cities are basically greater than 1, which indicates that carbon emissions in most of the power sectors in the country are still increasing as of 2020. Overall, the effects of potential thermal fuel carbon emission efficiency, potential thermal energy consumption efficiency, the carbon emission efficiency of thermal power generation, economic scale, population density, and annual rainfall change are mostly greater than 1 and will promote the growth of carbon emissions in the power sector. Moreover, the effects of thermal power generation energy efficiency technology, thermal power generation emission reduction technology, power generation structure, and power generation per unit GDP are mostly less than 1 and will inhibit the growth of carbon emissions in the power sector. However, each of these drivers does not have the same degree of influence and impact effect for each province and city. Based on the research results, some policy recommendations are proposed. [ABSTRACT FROM AUTHOR]

Using the difference-in-difference model and panel data from 283 Chinese cities from 2006 to 2019, this study assesses the effect on CO2 emissions of an innovative city pilot policy and analyzes its mechanism using the mediation effect model. The findings demonstrate that the pilot policy significantly reduces urban carbon emissions overall, and this finding holds even after conducting several stability tests. Innovative pilot cities can cut carbon emissions by 11.5% compared to nonpilot cities and thus significantly impact carbon reduction. Reducing carbon emissions is possible through three mechanisms. These are the enrichment of cultural resources, the development of technological innovation levels, and the optimization of industrial structure. There is a significant lag in how the innovative city pilot policy affects this reduction. The emission reduction effects of innovative pilot policies on different pollution levels, regions, and cities of various sizes are heterogeneous. In the long run, the scope of pilot projects needs enlargement in an orderly manner, and specific policies should be implemented according to local conditions. Meanwhile, advanced technologies are required in cities of different scales to build innovative development mechanisms for carbon peaking and carbon neutrality, and environmental regulations should be strengthened to implement in urban areas the concept of green and sustainable ecological development. [ABSTRACT FROM AUTHOR]

There has always been controversy over how renewable energy technologies can play a role in reducing carbon emissions. Based on the energy patent data and the economic data of 244 prefecture-level cities from 2007 to 2017 in China, we explore the carbon reduction effect of renewable energy technology and its mechanism from the perspective of energy production, conservation, and management. The two-way fixed effect, instrumental variable, spatial Durbin, and mediation effect models are employed to explore empirical results. We found that (1) the impact of renewable energy technologies on carbon emissions is nonlinear, with an inverted U shape. However, this inverted U-shaped relationship only exists locally in cities and there are uncertainties in adjacent cities, which indicates that cross-regional cooperation in renewable energy technology needs to be improved. (2) The mechanism analysis shows that industrial agglomeration and energy consumption scale are the channels that renewable energy technologies affect carbon emissions. Thus, the implicit carbon emissions generated by industrial agglomeration and the failure to green upgrade energy consumption are the main reasons for the inverted U-shaped relationship. (3) The carbon reduction effect of renewable energy technologies of conservation type takes effect first, and renewable energy technologies of production type do not reduce carbon emissions in non-eastern cities, which means that non-eastern cities are likely to become pollution havens. This study provides evidence for renewable energy technologies to achieve efficient carbon emission reduction and cross-regional technical cooperation. [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]

The pilot free trade zone (PFTZ) policy is an important strategic initiative to lead green and high-quality economic development. Based on panel data from 2012 to 2019 of 287 Chinese cities, this study systematically investigates the effect of the PFTZ policy on carbon emissions by building the staggered difference-in-difference (DID) model. The results showed that the PFTZ policy significantly reduced carbon emissions and that this reduction effect increased over time. These findings hold true after robustness tests. Additionally, the heterogeneity analysis showed that the carbon emission reduction effect was more significant in coastal areas. In terms of impact mechanisms, the main driving force of carbon emission reduction from the PFTZ policy is technological progress. Furthermore, the PFTZ policy has a spatial spillover effect, which can drive neighboring cities to reduce their carbon emissions. This study provides useful policy insights for building a green low-carbon trade system and helps achieve carbon peaking and carbon neutrality goals. [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]