City level water withdrawal and scarcity accounts of China.

In the context of China's freshwater crisis high-resolution data are critical for sustainable water management and economic growth. Yet there is a dearth of data on water withdrawal and scarcity regardless of whether total or subsector amount, for prefectural cities. In administrative and territorial scope, we accounted for water withdrawal of all 63 economic-socio-environmental sectors for all 343 prefectural cities in China, based on a general framework and 2015 data. Spatial and economic-sector resolution is improved compared with previous studies by partitioning general sectors into industrial and agricultural sub-sectors. Construction of these datasets was based on selection of 16 driving forces. We connected a size indicator with corresponding water-withdrawal efficiency. We further accounted for total blue-water withdrawal and quantitative water scarcity status. Then we compared different scopes and methods of official accounts and statistics from various water datasets. These disaggregated and complete data could be used in input-output models for municipal design and governmental planning to help gain in-depth insights into subsector water-saving priorities from local economic activities.

Modelling monthly-gridded carbon emissions based on nighttime light data.

Timely and accurate implementation of carbon emissions (CE) analysis and evaluation is necessary for policymaking and management. However, previous inventories, most of which are yearly, provincial or city, and incomplete, have failed to reflect the spatial variations and monthly trends of CE. Based on nighttime light (NTL) data, statistical data, and land use data, in this study, a high-resolution (1 km × 1 km) monthly inventory of CE was developed using back propagation neural network, and the spatiotemporal variations and impact factors of CE at multiple administrative levels was evaluated using spatial autocorrelation model and spatial econometric model. As a large province in terms of both economy and population, Guangdong is facing the severe emission reduction challenges. Therefore, in this study, Guangdong was taken as a case study to explain the method. The results revealed that CE increased unsteadily in Guangdong from 2013 to 2022. Spatially, the high CE areas were distributed in the Pearl River Delta region such as Guangzhou, Shenzhen, and Dongguan, while the low CE areas were distributed in West and East Guangdong. The Global Moran's I decreased from 2013 to 2022 at the city and county levels, suggesting that the inequality of CE in Guangdong steadily decreased at these two administrative levels. Specifically, at the city level, the Global Moran's I gradually decreased from 0.4067 in 2013 to 0.3531 in 2022. In comparison, at the county level, the trend exhibited a slower decline, from 0.3647 in 2013 to 0.3454 in 2022. Furthermore, the analysis of the impact factors revealed that the relationship between CE and gross domestic product was an inverted U-shaped, suggesting the existence of the inverted U-shaped Environmental Kuznets Curve for CE in Guangdong. In addition, the industrial structure had larger positive impact on CE at the different levels. The method developed in this study provides a perspective for establishing high spatiotemporal resolution CE evaluation through NTL data, and the improved inventory of CE could help understand the spatial-temporal variations of CE and formulate regional-monthly-specific emission reduction policies.

Expanding carbon neutrality strategies: Incorporating out-of-boundary emissions in city-level frameworks.

Cities are increasingly vital in global carbon mitigation efforts, yet few have specifically tailored carbon neutrality pathways. Furthermore, out-of-boundary indirect greenhouse gas (GHG) emissions, aside from those related to electricity and heat imports, are often overlooked in existing pathways, despite their significance in comprehensive carbon mitigation strategies. Addressing this gap, here we introduce an integrated analysis framework focusing on both production and consumption-related GHG emissions. Applied to Wuyishan, a service-oriented city in Southern China, this framework provides a holistic view of a city's carbon neutrality pathway, from a full-scope GHG emission perspective. The findings reveal the equal importance of carbon reduction within and outside the city's boundaries, with out-of-boundary emissions accounting for 42% of Wuyishan's present total GHG emissions. This insight highlights the necessity of including these external factors in GHG accounting and mitigation strategy development. This framework serves as a practical tool for cities, particularly in developing countries, to craft effective carbon neutrality roadmaps that encompass the full spectrum of GHG emissions.

How to perceive and map the synergy between CO2 and air pollutants: Observation, measurement, and validation from a case study of China.

Cities occupy a central position in addressing climate change and promoting sustainable regional development. Synergistic control of urban gas emissions at the city level is one of the main issues typically explored. The confounding effect and the interactions between the urban indicators of population and area have been ignored in previous studies. In this study, we examined the spatial distribution characteristics and synergy between greenhouse gases (CO2) and air pollutants (SO2 and NOX) using spatial population and gas emission data. By upgrading the city clustering algorithm (CCA), we established a method for defining active areas of gas emissions (spatial element-coupled clustering, SECC) and identified active areas of gas emissions in China. In this study, we created a research framework that can simultaneously consider the effects of population and area, as well as the possible interactions between these indicators in active areas. The superlinear scaling relationship between the above three gases was revealed at the active zone level, and the existence of synergy between the emission patterns of the three gases was confirmed. Via further model application, we measured the synergistic efficiency of the three gases. It was found that for every 1% increase in SO2 and NOX in an active zone, CO2 increases by 0.86%. In this study, we explored a new perspective and approach to explain the synergy between greenhouse gases and air pollutants. This is essential to promote national competition among cities to achieve synergistic control of CO2 and local air pollutants.

Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition.

Estimating health benefits of reducing fossil fuel use from improved air quality provides important rationales for carbon emissions abatement. Simulating pollution concentration is a crucial step of the estimation, but traditional approaches often rely on complicated chemical transport models that require extensive expertise and computational resources. In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. Applications of the framework with Chinese data reveal highly heterogeneous health benefits of avoiding premature mortality by reducing fossil fuel use in different sectors and regions in China with a mean of $19/tCO2 and a standard deviation of $38/tCO2. Reducing rural and residential coal use offers the highest co-benefits with a mean of $151/tCO2. Our findings prompt careful policy designs to maximize cost-effectiveness in the transition toward a carbon-neutral energy system.

Exploring the spatiotemporal pattern evolution of carbon emissions and air pollution in Chinese cities.

Based on data from 335 cities in China, this study employs the standard deviation ellipse method to portray unbalanced and differential spatiotemporal evolution patterns of environmental emissions and socioeconomic elements. A logarithmic mean Divisia index analysis and in-depth discussion are carried out to disclose the main driving factors and underlying reasons for the differences. Decoupling trends exist among carbon emissions, gross domestic product (GDP) and population in terms of their gravity center migrations. The standard deviation ellipse direction of carbon emissions gradually changed from 'northeast‒southwest' to 'northwest‒southeast', and the standard deviation ellipse areas of carbon emissions and air pollution continuously expanded over time; at the same time, that of GDP contracted. Economic growth has always been the main driver of carbon emissions and air pollution nationally, but its role has weakened. Moreover, decreases in the energy intensity and carbon and pollution intensities are the main factors contributing to emissions reductions. Differentiated spatiotemporal economic structure evolution, regional heterogeneities in the energy intensity and efficiency, and cross-region power energy transmissions are identified as the underlying reasons for the unbalanced spatiotemporal patterns of the environmental emissions and socioeconomic elements. Based on these findings, policy suggestions can be made to address the imbalances and promote carbon mitigation, air quality improvement and high-quality social-economic development at the city level.

Synergetic roadmap of carbon neutrality and clean air for China.

It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction, air quality improvement, and improved health. In the context of carbon peak, carbon neutrality, and clean air policies, this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 indicators. The 18 indicators cover the following five aspects: air pollution and associated weather-climate conditions, progress in structural transition, sources, inks, and mitigation pathway of atmospheric composition, health impacts and benefits of coordinated control, and synergetic governance system and practices. By tracking the progress in each indicator, this perspective presents the major accomplishment of coordinated control, identifies the emerging challenges toward the synergetic governance, and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.

Heterogeneous effects of China's low-carbon city pilots policy.

Global south countries, including China, have faced a challenging dilemma of reducing carbon emissions while maintaining rapid economic growth. The low-carbon city pilots (LCCPs) policy in China is a demonstration of how state power intervenes and commands national low-carbon development through voluntary policy tools. Our study, based on panel data of 331 cities from 2005 to 2019, evaluates the policy effect of all three batches of LCCPs and presents an analysis of time-varying effects through batch decomposition and synthetic difference-in-difference models. The study found that implementing low-carbon policies can significantly reduce total carbon emissions and carbon emissions per capita. However, the reduction in carbon emissions per unit of GDP is insignificant, and the policy effect varies according to the batches and their characteristics. The reduction effects in the first and second batches, as well as the insignificance or even increasing effects of the third batch, may be due to carbon leakage between different batches of LCCPs. Overall, this research provides novel and quantitative evidence on low-carbon development in China, making theoretical and empirical contributions to the field, and expanding econometric assessment methods to evaluate the effectiveness of environmental and climate change policies.

Facility-Level Emissions and Synergistic Control of Energy-Related Air Pollutants and Carbon Dioxide in China.

Boilers involve ∼60% of primary energy consumption in China and emit more air pollutants and CO2 than any other infrastructures. Here, we established a nationwide, facility-level emission data set considering over 185,000 active boilers in China by fusing multiple data sources and jointly using various technical means. The emission uncertainties and spatial allocations were significantly improved. We found that coal-fired power plant boilers were not the most emission-intensive boilers with regard to SO2, NOx, PM, and mercury but emitted the highest CO2. However, biomass- and municipal waste-fired combustion, regarded as zero-carbon technologies, emitted a large fraction of SO2, NOx, and PM. Future biomass or municipal waste mixing in coal-fired power plant boilers can make full use of the advantages of zero-carbon fuel and the pollution control devices of coal-fired power plants. We identified small-size boilers, medium-size boilers using circulating fluidized bed boilers, and large-size boilers located in China's coal mine bases as the main high emitters. Future focuses on high-emitter control can substantially mitigate the emissions of SO2 by 66%, NOx by 49%, PM by 90%, mercury by 51%, and CO2 by 46% at the most. Our study sheds light on other countries wishing to reduce their energy-related emissions and thus the related impacts on humans, ecosystems, and climates.

Closing the Gap between Carbon Neutrality Targets and Action: Technology Solutions for China's Key Energy-Intensive Sectors.

Facing significant carbon emissions annually, China requires a clear decarbonization strategy to meet its climate targets. This study presents a MESSAGEix-CAEP model to explore Chinese decarbonization pathways and their cost-benefit under two mitigation scenarios by establishing connections between five energy-intensive sectors based on energy and material flows. The results indicated the following: 1) Interaction and feedback between sectors should not be disregarded. The electrification process of the other four sectors was projected to increase electricity production by 206%, resulting in a higher power demand than current forecasts. 2) The marginal abatement cost to achieve carbon neutrality across all five sectors was 2189 CNY/tCO2, notably higher than current Chinese carbon emission trading prices. 3) The cost-benefit analysis indicates that a more ambitious abatement strategy would decrease the marginal abatement cost and result in a higher net carbon abatement benefit. The cumulative net benefit of carbon reduction was 7.8 trillion CNY under ambitious mitigation scenario, 1.3 trillion CNY higher than that under current Chinese mitigation scenario. These findings suggest that policy-makers should focus on the interaction effects of decarbonization pathways between sectors and strengthen their decarbonization efforts to motivate early carbon reduction.

A new method of hotspot analysis on the management of CO2 and air pollutants, a case study in Guangzhou city, China.

Emission inventory plays an important role in designing effective emission control strategies. Currently, there is unbalanced development of CO2 and air pollutant emission inventories in China and the spatial information of both cannot be obtained simultaneously, which prevents a collaborative control strategy. In this study, we developed a unified emission inventory including both CO2 and air pollutants, then utilized spatial mapping methods to identify the co-hotspots of both CO2 and air pollutants at a high spatial resolution (1 × 1 km2). We applied Guangzhou city as a case study to illustrate the method. The results showed that CO2 and air pollutants were mainly emitted from the stationary combustion sector and the transportation sector. These two sectors contributed 95 %, 67 %, and 93 % to total CO2, SO2, and NOx emissions, respectively. Up to 86 %, 86 %, 66 %, and 72 % of total CO2, SO2, NOx, and PM2.5 emissions were attributed to the top 10 % emission grids with 1 × 1 km2 resolution. However, our results showed high emission grids were not surrounded by other high emissions grids for all types of emissions analyzed in this study. The co-hotspot analysis enables accurate identification of high-emission grids, which helps environment managers to prioritize resource allocation when designing control strategies. Our study underscores the importance of managing CO2 and air pollutants simultaneously at the city level.

Accessing the Climate Change Impacts in China through a Literature Mapping.

In the 21st century, carbon dioxide emissions have led to adverse climate changes; meanwhile, the impact of climate change has imposed challenges worldwide, particularly in developing countries, and China is one of the most affected countries. Assessing the impact of climate change requires handling a large amount of data in the literature comprehensively. In this study, a text-based classification method and literature mapping were used to process the massive literature and map it according to its location. A total of 39,339 Chinese academic studies and 36,584 Chinese master's and doctoral theses, from 2000 to 2022, with evidence of the impact of climate change were extracted from the China National Knowledge Infrastructure database. Our results show that the literature on climate change impacts has exploded during the last decades. This indicates that increasing attention to the intensified impact of climate change in China has been paid. More importantly, by mapping the geolocation of the literature into spatial grid data, our results show that over 36.09% of the land area shows clear evidence of climate change. Those areas contribute to 89.29% of the gross domestic product (GDP) and comprise 85.06% of the population in China. Furthermore, the studies we collected on the climate change impacts showed a huge spatial heterogeneity. The hotspot areas of research were generally located in developed regions, such as the BTH urban agglomeration and Yangtze River Economic Zone, major agricultural production areas such as Shandong and Henan, and ecologically fragile regions including Yunnan, Xinjiang, and Inner Mongolia. Considering the imbalance spatially of the evidence of climate change can help in a better understanding of the challenges in China imposed by climate change. Appraising the evidence of climate change is of great significance for adapting to climate change, which is closely related to the natural ecosystem services and human health. This study will provide policy implications for coping with climatic events and guide future research.

Mapping carbon emissions of China's domestic air passenger transport: From individual cities to intercity networks.

As a significant carbon emission source with high growth potential, the air transport sector plays a crucial role in China's decarbonisation efforts. However, the spatial pattern and evolutionary dynamics of aviation carbon emissions in China have not been thoroughly studied. This study proposed a framework to reveal the spatial characteristics and influencing factors of aviation carbon emissions at the city level. Using data from 2019 to construct the aviation carbon emissions network of China (ACENC), the novelty of the study lies in the subdivision of carbon emissions of air passenger transport into cities and intercity lines in China, which helps to reveal the spatial characteristics of individual cities in the intercity network. Beijing, Shanghai, Shenzhen, Chengdu, and Guangzhou were the cities with the highest carbon emissions, and the routes between these cities caused a significant amount of carbon emissions. >80 % of the total carbon emissions can be attributed to two communities in the network, owing to their large size and strong connections. Correlation analysis indicates that a city's carbon emissions are significantly related to its demographic and economic attributes as well as its connection with other cities, while a city's carbon emission intensity may be influenced by its centrality in the whole network and the structure of the community to which it belongs. Overall, the presented results provide directions for stakeholders and policymakers to regulate carbon emissions from air transportation.

Unveiling the spatial and sectoral characteristics of a high-resolution emission inventory of CO2 and air pollutants in China.

Under the target of carbon neutrality as well as stringent air quality guideline, understanding the spatial characteristics of both greenhouse gases and air pollutants emissions, in particular of their mutual sources, is crucial for assessing the feasibility of achieving their concomitant emission control, which, nevertheless, remains to be unclear yet. To this end, we construct a high-resolution (10 km × 10 km) emission inventory including both CO2 and air pollutants in China, which fosters us an opportunity to examine their spatial and sectoral characteristics. The primary sources for both CO2 and air pollutant emissions are power and industry. Among different subsectors in industry, detailed information indicates cement, iron and steel are the major subsectors for both CO2 and majority of air pollutants. Analysis of the high-resolution spatial distribution indicates that for CO2, 5 % of the grids account for 90 % of the total CO2 emissions, indicative of the existence of spatial heterogeneity. These grids are the major locations with air pollutant emissions as well, i.e., 73 % for SO2 emissions, and more than 50 % for volatile organic compounds (VOCs), CO, NOx, PM10 and PM2.5, stressing the spatial consistency between greenhouse gases and air pollutant emissions. A large portion of emissions concentrate in a relatively small number of grids further implies the possibility to achieve the mutual control of both greenhouse gas emissions and air pollutant emissions, which is useful for future policy in particular of achieving the carbon neutrality and air quality improvement.

Allocating China's 2025 CO2 emission burden shares to 340 prefecture cities: methods and findings.

Peak emission is an important policy/scheme for all the countries to respond greenhouse gas mitigation. The key is how to distribute the emission burden shares to its sub-regions. This study aims to develop a prefecture city leveled CO2 emission allocation model by integrating multi-indicators method and benchmark method so that China's 2025 (end year of 14th Five-Year Plan, FYP) CO2 emission burdens can be allocated to its prefecture cities and provinces. Results show that China's total CO2 emission will reach 12 billion tons in 2025. The majority of such emission will occur in the east China due to its more developed economy and dense population. Cities with high emissions are usually allocated more emission quotas, such as Shanghai, Tianjin, Chongqing, Tangshan, Yulin, Suzhou, and Ningbo. The top five provinces with higher CO2 emission quotas are traditionally high-emission and energy-intensive provinces, including Shandong, Jiangsu, Inner Mongolia, Henan, and Hebei. The national CO2 emission intensity will decrease by 69.35% in 2025 compared to the 2005 level. The CO2 emission intensity reduction rates among the 340 Chinese cities is found to be fluctuating significantly from 16 to 74% during the 14th FYP. Finally, policy recommendations are raised for mitigating city level CO2 emissions by considering the local realities.

A systematic assessment of city-level climate change mitigation and air quality improvement in China.

China is facing dual challenges of air pollution and climate change. By using city-level data, we comprehensively assessed air quality and CO2 emission changes from 2015 to 2019 for 335 Chinese cities. We selected important regions for air pollution control and categorized all cities into different classes according to their development levels. Our novel approach revealed new insights on different patterns of changes of PM2.5, O3, and CO2 by region and city class. We found that PM2.5 concentrations decreased remarkably due to mandatory city-level reduction targets, especially in the Beijing-Tianjin-Hebei (-27%) region. Nonetheless, O3 concentrations and CO2 emissions increased in 91% and 69% of Chinese cities, respectively. Observed CO2 emission reductions in more developed cities were mainly due to prominent energy intensity reduction and energy structure improvement. Our study indicates a lack of synergy in air pollution control and CO2 mitigation under current policies in China. To address both challenges holistically, we suggest setting mandatory city-level CO2 emission reduction targets and reinforcing clean energy and energy efficiency measures.

Spatio-Temporal Heterogeneity of the Relationships Between PM2.5 and Its Determinants: A Case Study of Chinese Cities in Winter of 2020.

Fine particulate matter (PM2.5) poses threat to human health in China, particularly in winter. The pandemic of coronavirus disease 2019 (COVID-19) led to a series of strict control measures in Chinese cities, resulting in a short-term significant improvement in air quality. This is a perfect case to explore driving factors affecting the PM2.5 distributions in Chinese cities, thus helping form better policies for future PM2.5 mitigation. Based on panel data of 332 cities, we analyzed the function of natural and anthropogenic factors to PM2.5 pollution by applying the geographically and temporally weighted regression (GTWR) model. We found that the PM2.5 concentration of 84.3% of cities decreased after lockdown. Spatially, in the winter of 2020, cities with high PM2.5 concentrations were mainly distributed in Northeast China, the North China Plain and the Tarim Basin. Higher temperature, wind speed and relative humidity were easier to promote haze pollution in northwest of the country, where enhanced surface pressure decreased PM2.5 concentrations. Furthermore, the intensity of trip activities (ITAs) had a significant positive effect on PM2.5 pollution in Northwest and Central China. The number of daily pollutant operating vents of key polluting enterprises in the industrial sector (VOI) in northern cities was positively correlated with the PM2.5 concentration; inversely, the number of daily pollutant operating vents of key polluting enterprises in the power sector (VOP) imposed a negative effect on the PM2.5 concentration in these regions. This work provides some implications for regional air quality improvement policies of Chinese cities in wintertime.

Air quality benefits of achieving carbon neutrality in China.

Achieving carbon neutrality before 2060 newly announced in China are expected to substantially affect air quality. Here we project the pollutants emissions in China based on a carbon neutrality roadmap and clean air policies evolution; national and regional PM2.5 and O3 concentrations in 2030 (the target year of carbon peak), 2035 (the target year of "Beautiful China 2035" launched by the Chinese government to fundamentally improve air quality) and 2060 (the target year of carbon neutrality) are then simulated using an air quality model. Results showed that compared with 2019, emissions of SO2, NOx, primary PM2.5, and VOCs are projected to reduce by 42%, 42%, 44%, and 28% in 2030, by 57%, 58%, 60%, and 42% in 2035, by 93%, 93%, 90% and 61% in 2060 respectively. Consequently, in 2030, 2035, and 2060, the national annual mean PM2.5 will be 27, 23, and 11 µg m-3; and the 90th percentile of daily 8-h maxima of O3 (O3-8h 90th) will be 129, 123, and 93 µg m-3; 82%, 94%, and 100% of 337 municipal cities will reach the current national air quality standard, respectively. It's expected that the "Beautiful China 2035" target is very likely to be achieved, and about half of the 337 cities will meet the current WHO air quality guideline in 2060. In the near future, strict environmental policies driven by "Beautiful China 2035" are needed due to their substantial contribution to emission reductions. By 2060, the low-carbon policies driven by the carbon neutrality target are expected to contribute to larger than 80% of reductions in PM2.5 and O3-8h 90th concentrations relative to the 2020 levels, implying that more attention could be paid to low-carbon policies after 2035. Our research would provide implications for future co-governance of air pollution and climate change mitigation in China and other developing countries.

Co-benefits of peaking carbon dioxide emissions on air quality and health, a case of Guangzhou, China.

Cities play a key role in making carbon emission reduction targets achievable and tackling air pollution. Using Guangzhou city as a case, this paper explored the air quality and health co-benefits of peaking carbon dioxide emissions under three scenarios and developed an integrated assessment framework by combining a local air pollutant emission inventory, an atmospheric chemistry transport model, and a health assessment model. The results showed that SO2, PM10, and PM2.5 could achieve larger emission reductions than NH3, VOCs, and NOx among all the scenarios we examined. Under the enhanced peaking scenario with the most stringent mitigation strategies, Guangzhou could meet the local ambient air quality standard for PM2.5 (34 µg/m3), with the most reduction observed in the annual average PM2.5 concentration (28.4%) and related premature deaths (17.08%), compared with the base year 2015. We also identified hotspot grids, which were areas with high concentrations of carbon emissions, high concentrations of air pollution and poor air quality in Guangzhou. Our analysis highlighted the importance of promoting peaking carbon dioxide emission for the improvement of air quality and public health at the city level.

Characteristics of carbon dioxide emissions in response to local development: Empirical explanation of Zipf's law in Chinese cities.

Carbon emissions and city development are currently two major areas of interest worldwide. With the continuous development of cities, the problem of carbon emissions has received substantial attention. Analyzing the relationship between carbon emissions and city development is key to building low-carbon cities. This paper selects the revised Zipf's law to explore diverse carbon emission characteristics in different stages of city development and tries to verify the balance of city development and the rationality of key emitting sectors in China, thus filling a gap in this domain. Based on the analysis of different emitting sectors and diverse city categories, several discoveries are made. First, nearly 80% of Chinese cities have reached the ideal state of Zipf's law between carbon dioxide (CO2) emissions and city development. In general, carbon emissions and city development are basically matched at the present stage. Second, in cities, the carbon emissions of the agricultural and industrial processes sectors are relatively balanced and stable with the city development. In addition, only the traffic sector is in the stage of intensive development. Other sectors (industrial energy, rural household, urban household, services, and indirect emissions) need to be further optimized. Third, CO2 emissions in other type of cities are basically matched with the city development. Industrial cities, megalopolises and metropolises are in the stage of intensive development, while cities of other types (service-oriented cities and small-medium cities) need to be further optimized. Fourth, corresponding measures, such as adjusting energy and industrial structure, optimizing resource allocation, and promoting intensive production, need to be taken to optimize carbon emissions in cities of different types and in different emitting sectors. Our study provides a particular theoretical basis and practical value, for China and other countries in similar situations, to coordinate the matching correlation between city development and carbon emissions in the future.