Urban Emissions Research Articles

Can industrial intelligence promote carbon emission efficiency? --empirical research based on the Yangtze River Economic Belt

The rapid development of intelligent technology characterized by robots under the fourth scientific and technological revolution provides a favorable opportunity for the accurate decision-making of urban pollution control and the effective achievement of the goal of carbon emission reduction in China. This research uses the robot penetration rate as a representative and characteristic index of industrial intelligence development, based on panel data from 108 cities in the Yangtze River Economic Belt (YEB) from 2006 to 2020. It then uses panel quantile regression, spatial measurement, and threshold effect models to provide a more thorough theoretical and empirical discussion of the impact, mechanism, and spatial effect of industrial intelligence development on urban carbon emission efficiency (CEE). Urban CEE may be greatly increased with the use of industrial intelligence, and this finding remains true even after endogeneity and robustness tests are controlled; From an action mechanism perspective, industrial intelligence advances technology, optimizes industrial structure, and ultimately enhances regional CEE; There is a Matthew effect on the degree of development of carbon emission efficiency, and the impact of industrial intelligence on CEE is more pronounced in non-resource-based cities and the lower portions of YEB; Urban CEE increases positively with the spatial spillover impact of industrial intelligence development. The ability for regional sustainable development will be significantly increased if cross-regional cooperative prevention and control of environmental governance can be successfully achieved. This study verifies the enabling effect of industrial intelligence development on the improvement of urban CEE, and provides enlightenment for China to improve industrial intelligence development strategies and policies to achieve regional high-quality development.

Polycentric spatial Structure, digital economy and urban green sustainable development

The urban spatial structure profoundly influences green sustainable development, while digital technology is instrumental in fostering the advancement of eco-friendly smart cities. This study explores whether optimizing urban spatial layout can utilize the transformative potential of the digital economy (DE) to achieve goals such as urban low-carbon construction, achieving "carbon neutrality" and promoting sustainable development. We examine the influence of polycentric spatial structure and the digital economy on urban carbon emissions (UCE) from a spatial perspective. We found that a polycentric spatial structure reduced local and neighboring carbon emissions significantly, and the expansion of the DE further amplifies this effect. Supported by digital technologies, three main pathways effectively reduce UCE: improving transportation infrastructure, facilitating industrial transformation and upgrading, and promoting market integration. Further analysis revealed that the effectiveness of these beneficial impacts is influenced by regional heterogeneity and urban scale. Moreover, cities with advanced green technologies and those situated within urban agglomerations are better positioned to leverage this dividend effect to foster green, low-carbon, and sustainable urban development. Lastly, based on our research findings, we provide policy recommendations aimed at promoting green and sustainable urban development.

Environmental impacts of shifts in surface urban heat island, emissions, and nighttime light during the Russia-Ukraine war in Ukrainian cities.

As recent geopolitical conflicts and climate change escalate, the effects of war on the atmosphere remain uncertain, in particular in the context of the recent large-scale war between Russia and Ukraine. We use satellite remote sensing techniques to establish the effects that reduced human activities in urban centers of Ukraine (Kharkiv, Donetsk, and Mariupol) have on Land Surface Temperatures (LST), Urban Heat Islands (UHI), emissions, and nighttime light. A variety of climate indicators, such as hot spots, changes in the intensity and area of the UHI, and changes in LST thresholds during 2022, are differentiated with pre-war conditions as a reference period (i.e., 2012-2022). Findings show that nighttime hot spots in 2022 for all three cities cover a smaller area than during the reference period, with a maximum decrease of 3.9% recorded for Donetsk. The largest areal decrease of nighttime UHI is recorded for Kharkiv (- 12.86%). Our results for air quality changes show a significant decrease in carbon monoxide (- 2.7%, based on the average for the three cities investigated) and an increase in Absorbing Aerosol Index (27.2%, based on the average for the three cities investigated) during the war (2022), compared to the years before the war (2019-2021). The 27.2% reduction in nighttime urban light during the first year of the war, compared to the years before the war, provides another measure of conflict-impact in the socio-economic urban environment. This study demonstrates the innovative application of satellite remote sensing to provide unique insights into the local-scale atmospheric consequences of human-related disasters, such as war. The use of high-resolution satellite data allows for the detection of subtle changes in urban climates and air quality, which are crucial for understanding the broader environmental impacts of geopolitical conflicts. Our approach not only enhances the understanding of war-related impacts on urban environments but also underscores the importance of continuous monitoring and assessment to inform policy and mitigation strategies.

Prediction of urban ultrafine particle emission fluxes using generalized additive models

Ultrafine particles (UFP) are abundant in urban atmospheres. To assess the strength and temporal variation of urban UFP emission sources, information on the surface-atmosphere exchange, i.e. the turbulent vertical flux of particles, is vital. A three-year time series of UFP emission fluxes (FUFP) observed at an urban site in Berlin, Germany, using the eddy covariance technique was utilized to develop and evaluate generalized additive models (GAM) for FUFP. GAM allow to account for non-linear relationships between response and predictor variables. Two separate models for summer and winter were developed. The predictors that most strongly influenced modelled FUFP in the summer model were traffic activity, friction velocity, land use, air temperature and PM10 concentration, whereas the winter model additionally incorporated relative humidity. The GAM were evaluated by ten-fold cross-validation for the first two study years, and by predicting the third year based on the model trained with observational data of the first two years. The coefficients of determination of the two validation methods were R2 = 0.52 (uncertainty of −47 to 88% for FUFP) and R2 = 0.48 (−45 to 82% for FUFP) for the winter model, whereas the summer model yielded R2 = 0.48 and 0.44 (uncertainty of −51 to 102%). GAM were shown to successfully capture the non-linear relationships between predictor variables and FUFP for the three-year data set at this urban site.

Forecasting urban passenger transportation emissions: a green and new energy approach

ABSTRACT Passenger transportation significantly contributes to urban carbon dioxide emission. Decreasing these emissions is essential to achieving low-carbon development. This research focused on Xi’an City to enhance previous research works by considering factors such as road greening, online ride-hailing, and use of vehicles with new energy sources. Using system dynamics method, a carbon dioxide emission prediction model was developed for urban passenger transportation in Xi’an. The developed model estimated total emissions from 2012 to 2021 and projected carbon dioxide emission reduction plans through six different scenarios for the time period of 2023 to 2032. The analysis identified private cars as the main contributors to carbon emission in urban passenger transportation. Single scenario simulations indicated that passenger traffic in Xi’an would not achieve carbon emission peak by 2030, but multi-scenario simulations showed it would. Specific recommendations for carbon emission reduction in urban passenger transportation were provided, focusing on travel patterns, energy sources, and promotion of green initiatives.

The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach

The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO2, CO2 per person emissions, and age-standardised mortality. We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal-Wallis test followed by a post-hoc Dunn's test. We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO2 exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health. Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.

Quantifying the impact of earthquakes on urban energy consumption and carbon emissions in Tokyo from a nexus perspective

Unexpected events can have profound impacts on urban resource supply and consumption. The Great East Japan Earthquake (3.11 hereafter) triggered not only the planned blackout in the Tokyo Metropolitan Region soon after the disaster but also the energy shift to fossil fuels to recover from the disfunction of Fukushima nuclear power plants. Previous research has mainly focused on the direct energy consumption and carbon emissions of different sectors while the intensity and extensity of the impact on industries and the environment have never been empirically addressed. This study explores energy-use efficiency and carbon emissions in Tokyo from 2011 to 2015 through a lens of nexus using environmentally extended input-output analysis and community-wide carbon analytic approaches. Results show that the energy consumption is the largest exporter and importer of carbon emissions, whereas energy losses and carbon emissions caused by energy conversion and transmission are almost twice as much as those caused by the direct parts. Strong nexus effects among building and material, transportation, and energy consumption were observed. The 3.11 greatly impacted the energy structure and carbon emission patterns because of the increased consumption of coal for electricity. The share of energy consumption and carbon emissions by raw materials for construction also increased because of the increased demand for the reparation and reconstruction of buildings and transport systems. This structural change provided new scientific evidence for governments to implement decarbonization policies while preparing for unprecedented events.

Urban emissions and land use efficiency scenarios for avoiding increments of global warming

Urban areas have key roles in climate mitigation, including increasing renewable energy penetration in smart energy systems. The potential of urban areas in limiting global warming, however, is not quantified. This research work develops a new framework to analyse urban emissions and land use efficiency scenarios with coupling to the transient climate response to cumulative carbon dioxide emissions. Two new parameters that quantify contributions to and avoidance of increments of global warming from urban areas are formulated and applied to twelve scenario combinations. The results for 465 urban areas indicate that a green-growth scenario with lower ambition in reducing urban emissions can lead up to a 0.13 °C additional increment of global warming in 2050 based on the best estimate of the transient climate response to cumulative carbon dioxide emissions. Those of the most ambitious urban emissions scenario with green-growth and renewable energy are limited to 0.06 °C. When combined with the most ambitious land use efficiency scenario for 135 urban areas, it is possible to avoid more than double or 2.09 times additional increments of global warming in comparison to other integrated urban scenarios. The mean and 5–95th percentile range of the results are compared based on 10,000 Monte Carlo simulations. Informing on the urgency to ensure ambitious mitigation action in urban areas can support a climate future that remains within critical thresholds and tipping elements of the planet.

Modelling Current-State N- and P-Fluxes into Surface Waters in Germany

For the first time, the AGRUM model consortium—consisting of the agro-economic model RAUMIS, the water balance model mGROWA, the hydrological nutrient transport models DENUZ, WeKu and MEPhos, and the urban emission model MONERIS—was jointly set up throughout Germany (357,000 km2). This provided a nationwide consistent nutrient model to capture the current status of N and P inputs to surface waters from diffuse sources and urban areas. Diffuse nutrient emissions were quantified in high spatial resolution for the input pathways’ groundwater, drainage runoff, and natural interflow (100 m × 100 m), as well as for water erosion and wash-off (25 m × 25 m). The sum of diffuse nutrient inputs to surface waters is about 385,000 metric tons N/yr and ca. 11,530 metric tons P/yr. Urban emissions were quantified either as point source inputs (wastewater treatment plants, industrial direct dischargers) or at municipality scale for different collection and treatment systems, e.g., rainwater sewers or decentralized treatment plants, and sum up to ca. 95,000 t N/yr and 7500 t P/yr. As modelled, total N and P inputs into surface waters correspond well with observed N and P loads in rivers. The model results represent valuable information for water managers, being responsible for the preparation of management plans for the third management cycle of the EC Water Framework Directive spanning from 2021 to 2027.

Digital economy's role in shaping carbon emissions in the construction field: Insights from Chinese cities

Achieving net-zero greenhouse gas emissions in the construction sector is essential to sustainable development policy. Previous studies have ignored the impact of the digital economy on carbon emissions in the construction industry. Using relevant city-level data from China from 2011 to 2021 and employing ArcGIS and Stata software, this study examines the current status of carbon emissions from the construction industry and investigates the impact of the digital economy on these emissions. The findings reveal that (1) from 2011 to 2021, carbon emissions of the construction industry have a pattern of decreasing-increasing-decreasing-increasing across the country. There is an increasing concentration of areas with high and relatively high carbon discharges in Heilongjiang, Jilin, Ningxia, Inner Mongolia, Shanxi, Guangxi, and Guizhou. (2) The standard deviation ellipse indicates the core area of carbon emissions in China's construction industry is moving northeast and becoming more decentralized. (3) Through a series of robustness tests, the digital economy has been proven to effectively reduce carbon emissions from the construction sector in municipal areas. (4) In severely cold regions, mild regions, and high-population-density cities, the digital economy reduces building sector's carbon output. However, it stimulates carbon emissions in the hot summer and cold winter regions. (5) Mechanism tests show that the digital economy reduces China's urban construction carbon emissions by fostering technological progress and green innovation. Urban resilience further strengthens the contribution of the digital economy to reducing carbon discharges in the urban construction sector of China. This article presents empirical evidence demonstrating how the digital economy empowers the construction industry to curtail emissions.

Seasonal oxidative dynamics and isotopic fractionation of NOx and SO2 in Ostrava, Czech Republic: Insights from stable isotope analysis

The city of Ostrava, NE Czech Republic, is known for its industrial pollution. It has well-characterized emission sources and stable air movement patterns. These features are conveniently used to generalize on atmospheric NOx and SO2 oxidation processes. In 2021, we conducted a series of sampling campaigns to assess the isotopic fractionation conducive to NO3− and SO42− aerosols in PM10. These sampling campaigns were timed to capture varying atmospheric conditions, including climatic inversion periods, providing also insights into urban emission dynamics over the course of the year. Gaseous NOx and SO2 were collected on passive filters, while their oxidized forms, NO3− and SO42, were captured on PM10 particle filters, enabling us to analyze the transformation dynamics of these pollutants. Isotopic analyses distinguished the sources of NOx emissions—coal combustion (δ15N = −3‰) and vehicular emissions (δ15N = −7 ‰)—and allowed quantifying isotope fractionation during their conversion to NO3− (εNOx-NO3- = 11.5 ± 1.15 ‰). This fractionation, however, was influenced by seasonal variations, and appears to be notably affected by NH4NO3 decomposition during warmer months. The correlation of the NO3− to NOx ratio with PM10 and atmospheric moisture highlighted the interplay between particulate matter and humidity in relevant atmospheric transformations. Similarly, for SO2, primarily emitted from coal combustion (δ34S = −2‰), we identified distinct fractionation patterns during oxidation to SO42− encompassing both kinetic (εSO2-H2O = −1.3 ± 0.5‰) and equilibrium (εSO2- SO42- = 2.24 ± 0.67‰) effects. The SO42−/SO2 ratio was correlated with PM10 but showed no dependence on humidity. Significantly, atmospheric inversion conditions accelerated oxidation, modifying the fractionation patterns for both NOx (εNOx-NO3- = 7‰) and SO2 (εSO2- SO42-= −0.9 ± 0.3‰). Our methodology elucidates pivotal mechanisms in atmospheric pollution transformation, underlined by the tracing of NOx and SO2 to aerosol conversions via δ15N and δ34S isotopic analyses. The isotope fractionation underscores equilibrium processes in oxidation reactions, while the effect of PM10 and humidity reveals the complexity of these atmospheric oxidative transformations. The role of wet deposition in removing SO2 highlights an essential pathway in the atmospheric sulfur cycle.

Does stricter sewage treatment targets policy exacerbate the contradiction between effluent water quality improvement and carbon emissions mitigation? An evidence from China

Rapid expansion and upgrading of wastewater treatment facilities globally, driven by stricter wastewater policies, significantly contribute to carbon emissions. China has contributed 30 % of carbon emissions in the world, 1 % of which comes from wastewater treatment, necessitating more understanding of the impact of policies, especially the stringent “10-Point Water Plan” policy. From a micro perspective, this study uses the difference-in-differences method to analyze the impact of wastewater treatment policies on water and carbon issues in China’s 2894 wastewater treatment plants (WWTPs), and delves into the heterogeneity, and mechanisms across various dimensions. The results show that stricter sewage treatment policy decrease effluent concentration of the chemical oxygen demand (COD) by 2.35 %, and also cause a 1.74 % rise in carbon emissions per 10,000 m3 of wastewater treated, intensifying the short-term contradiction, while the contradictions may fall in the long term. It is more significant in southern regions and the cities with lower environmental regulation intensity. Also, there are significant differences in different wastewater treatment technology and scale. Significant improvements in effluent water quality are observed in WWTPs with 100,000 to 200,000 m3/day capacity and those using biofilm treatment technology. Through mechanism analysis, reasonable expansion of urban pipelines and WWTPs, promotion of biofilm treatment technology, reduction of energy consumption, and improvement of pollutant reduction efficiency are feasible paths to improve water quality and reduce carbon emissions. This research provides a perspective on solving water-carbon contradictions in WWTPs, holding critical significance for urban wastewater treatment and carbon emission management.

Does energy-consuming rights trading policy achieve urban pollution and carbon reduction? A quasi-natural experiment from China

Energy-consuming rights trading (ECRT) policy represents a critical policy instrument for China striving to achieve its “dual carbon” objectives, captivating significant attention for its potential to reduce pollution and carbon emissions. This study utilizes panel data from 290 Chinese cities spanning 2010 to 2021, leveraging the ECRT policy as a quasi-natural experiment. Employing Difference-in-Differences (DID) and Propensity Score Matching-Difference-in-Differences (PSM-DID) methodologies, we assess the effect of the ECRT policy on urban pollution and carbon reduction levels. The findings indicate: 1) Relative to non-demonstration cities, the ECRT policy significantly enhances pollution and carbon reduction levels in demonstration cities; this conclusion remains robust after rigorous testing. 2) Heterogeneity analysis indicates that the policy’s effect on pollution and carbon reduction is more significant in the central and western regions, and particularly evident in key and resource-based cities. 3) Mechanism tests demonstrate that the policy facilitates urban pollution and carbon reduction by cultivating green technological innovation and industrial structure upgrading. Therefore, to further advance the ECRT policy, it is necessary to expand the breadth, depth, and flexibility of policy implementation, while also optimizing environmental regulations to fully leverage the system’s potential in enhancing urban pollution and carbon emissions.

Сравнительная экологическая оценка техногенного воздействия на воздушный бассейн территории Кировской области

The materials of federal and regional reports on the state of the environment, and control and monitoring data of the Ministry of Environmental Protection of the Kirov region, as well as on the results of scientific studies of the atmospheric air state were analyzed. Based on the analysis the comparative assessment of the atmospheric air state was carried out using the example of the Kirov Region territory as part of the Volga Federal District. The main sources of air emissions and their quantitative characteristics are noted. Despite the fact that recently the vehicle fleet has increased significantly, the stationary sources of air pollution are the main in the regions of the Volga Federal District. In a number of urban agglomerations emissions from stationary sources are inferior to mobile sources of pollution. This is confirmed by the results of the rating of the Volga Federal District regions by the total volume of atmospheric emissions from all sources of pollution for the period from 2019 to 2023. The highest quantity of air pollutant emissions is observed throughout the entire period in regions with high developed chemical, petrochemical, mining, and mechanical engineering industries. This primarily concerns the Republic of Bashkortostan, the Perm Territory, the Orenburg region and the Republic of Tatarstan. While the Chuvash and Mordovian Republics, the Republic of Mari El, the Penza, Ulyanovsk, and Kirov regions are characterized by a significantly smaller contribution of air pollutant emissions and consistently occupy a leading position in these indicators. For a number of years, the territory of the Kirov region has been consistently ranked 6th in terms of total atmospheric emissions. The results of environmental control and monitoring, and conducted scientific research indicate that the main technogenic load on the atmospheric air in the Kirov region falls on the regional center – the city of Kirov and industrially developed areas of the region: Kirovo-Chepetsky, Vyatsko-Polyansky, Omutninsky, Belokholunitsky districts. Areas with local areas of contamination are identified in each of the above.

Exploring urban spatial heterogeneity and socio-environmental attributes of household greenhouse gas emissions

Understanding urban spatial heterogeneity of greenhouse gas (GHG) emissions from sectoral household consumption is crucial to facilitate moves towards low-carbon cities. In this study, we use Xiamen city of China as a case study to reveal the emission characteristics of household GHG as well as spatial heterogeneity. We conducted a face-to-face questionnaire survey and calculated GHG emissions of districts from household energy consumption, food consumption, transportation, housing, household waste and wastewater treatment. The GHG emissions and the amount of urban residential household consumption shows obvious spatial heterogeneity across districts. Total GHG emissions of Xiamen city were 8.39 Mt. CO2e, and average household and per capita of GHG emissions were 8.11 and 2.72 tCO2e, respectively. While total GHG emissions vary from 0.41 to 2.45 Mt. CO2e across six districts and range from 0.16 to 3.39 Mt. CO2e among six sectors. Household GHG emissions differ from 7.08 to 9.40 tCO2e, while the per capita emissions range between 2.41 to 3.14 tCO2e among districts. Results also showed that more urbanized areas with higher population density have larger total urban residential GHG emissions, whereas household emissions were comparatively lower in these areas. In contrast, our study did not show an (inverted-) U relationship or linear relationship between emissions and population, nor between emissions and income level. Household energy use is the largest sector emitting GHGs. These findings will be useful to underpin policy making towards low-carbon cities.

The Impact of Urban Construction Land Expansion on Carbon Emissions from the Perspective of the Yangtze River Delta Integration, China

Regional integration plays a pivotal role in the socio-economic advancement of various global regions and is closely linked with the expansion of construction land. This expansion is a major contributor to urban carbon emissions. Utilizing a geographical regression discontinuity design (GRDD), this paper estimates the impact of urban construction land expansion on carbon emissions and explores the underlying mechanisms within the regional integration process of the Yangtze River Delta (YRD), China. The findings reveal that urban construction land expansion significantly influences carbon emissions, displaying an inverted “U”-shaped pattern. Furthermore, this expansion affects carbon emissions through the transformation of industrial structures, shifts in consumption patterns, and enhancements in scientific and technological investments. Our findings span the performance of the Yangtze River Delta from its early development stages to a relatively mature phase. This paper also partially reveals how the Yangtze River Delta, with both megacities and large- to medium-sized cities, manages urban construction land expansion during the integration process and strives for low-carbon emissions reduction. These results can provide green growth recommendations that balance socio-economic development, low-carbon emissions, and social equity not only for other urban agglomerations in China but also for similar regions in other developing countries by altering construction land utilization patterns.

Will the Low-carbon City Pilot Policy Achieve Regional Emission Reduction?

In order to address climate change and promote green and low-carbon development, the Chinese government has implemented a pilot policy for low-carbon cities since 2010 and has continuously expanded the scope of the pilots. Taking the second batch of low-carbon pilot policies as an example, this paper uses difference in difference method to study the impact of low-carbon pilot policies on reducing urban carbon emission intensity based on the panel data of prefecture level cities from 2006 to 2019. It is found that the construction of low-carbon cities has a positive effect on reducing carbon emissions,and this conclusion is still valid under the robustness test. Based on this conclusion,this paper argues that China should further promote low-carbon pilot policies and actively explore the development model of low-carbon cities, especially to improve the livable and green urban environment.

Nexus among government digital development, resource dependence, and carbon emissions in China

Government digital development uses data technology to empower data for economic and social benefits, making social governance more scientific and efficient. Using unbalanced panel data of Chinese cities from 2006 to 2019, this paper explores the relationship between government digital development, fossil energy dependence, and urban carbon emissions. The results show that government digital development can effectively curb urban carbon emissions. The " carbon curse " phenomenon does exist at the city level in China, and government digital development is an effective way to break the "carbon curse." Heterogeneity analyses show that the digitalization of government significantly reduces the carbon emissions of cities in the East-Central region and the Yangtze River Economic Belt. Promoting government digital development in large cities can effectively break the "carbon curse." In addition, government digital development can also curb urban carbon emissions through structural, innovation, and resource allocation effects. Therefore, due attention should be paid to the digital development of government, which in turn will leverage digital advantages and eliminate the adverse effects of fossil energy dependence. This is of profound theoretical and practical significance for curbing urban carbon emissions and promoting green economic development.

Emission Characteristics of Greenhouse Gases and Air Pollutants in Northern Hemisphere Cities: Comprehensive Assessment Using Ground‐Based Fourier Transform Spectrometers

AbstractDespite the importance of understanding the urban emission characteristics of greenhouse gases (GHGs) and air pollutants, few studies have conducted integrated assessments across diverse urban environments. Herein, we conducted a comprehensive evaluation of the emission characteristics of GHGs and air pollutants in seven cities in the Northern Hemisphere using ground‐based Fourier transform spectrometers. Our analysis primarily focused on emission ratios of excess column‐averaged dry‐air mole fractions of carbon monoxide (CO) to carbon dioxide (CO2) (∆XCO:∆XCO2) and those of methane (CH4) to CO2 (∆XCH4:∆XCO2). We found that the emission ratios varied significantly across cities. Xianghe (China) and Pasadena (USA), known for severe air pollution, showed the highest emission ratios. Notably, Seoul (South Korea) showed lower ∆XCO:∆XCO2 (3.32 ± 0.10 ppb/ppm) but relatively higher ∆XCH4:∆XCO2 (4.85 ± 0.04 ppb/ppm), which was comparable to the ∆XCH4:∆XCO2 value of Xianghe (5.15 ± 0.10 ppb/ppm), suggesting that targeted CH4 reduction strategies may be required for climate change mitigation in Seoul.

Decoupling state of urban development and carbon emissions and its driving factors and predictions: A case study of Chengdu metropolitan area

Prioritizing the reduction of carbon emissions in key developing urban centers is a significant step toward achieving China's carbon peaking and neutrality goals. We examined the Chengdu metropolitan area as a case study. We proposed a coupled method for inversely estimating nighttime light and carbon emissions from energy consumption, enhancing the accuracy of fitting at the county scale and addressing the issue of missing energy consumption data. We integrated the Tapio decoupling model and the Logarithmic Mean Divisia Index (LMDI) model for comprehensive analysis, mitigating the limitations arising from the use of a singular model. Furthermore, we employed a multi-scenario analysis with an extended STIRPAT model to forecast the carbon emission trajectory of the Chengdu urban agglomeration and elucidate potential pathways for achieving carbon peaking and carbon neutrality goals. The findings indicated the following:(1)carbon emissions are predominantly concentrated in regions characterized by high levels of urban development. Forested land serves as the primary carbon sink; however, its capacity in the Chengdu metropolitan area fails to offset carbon emissions from energy consumption;(2)factor decomposition analysis revealed that economic development was the principal driver of carbon emissions, leading to an increase of 23.7964 million tons. Conversely, energy intensity emerged as the primary mitigation factor, reducing carbon emissions by 11.0677 million tons;(3)The Chengdu metropolitan area is projected to reach a carbon peak by 2030, with the multi-factor coordinated optimization (MFO) model representing the most favorable trajectory, with a projected peak of approximately 15.6998 million tons. However, to achieve carbon neutrality by 2060, there is still a surplus of approximately 10.4808 million tons.