City Clusters Research Articles

Topological Analysis of U.S. City Demographics

AbstractWe apply persistent homology, the main method in topological data analysis, to the study of demographic data. Persistence diagrams efficiently summarize information about clusters or peaks in a region’s demographic data. To illustrate how persistence diagrams can be used for exploratory analysis, we undertake a study of the 100 largest U.S. cities and their Black and Hispanic populations. We use our method to find clusters in individual cities, determine which cities are outliers and why, measure and describe change in demographic patterns over time, and roughly categorize cities into distinct groups based on the topology of their demographics. Along the way, we highlight the advantages and disadvantages of persistence diagrams as a tool for analyzing geospatial data.

Research on the evolution and driving factors of the coupling relationship among tourism industry, urbanization and human settlements of the urban agglomeration in the middle reaches of the Yangtze River.

This study examines the evolution of the coupling relationship among the tourism industry, urbanization, and human settlements of the urban agglomeration in the middle reaches of the Yangtze River from 2005 to 2019. By employing a constructed evaluation index system and a quantitative analysis model, the study aims to characterize and analyze this relationship. The key findings are as follows: (1) The coupling coordination level of the three major systems exhibits a continuous upward trend over the study period, albeit with a gradually slowing growth rate. The Changsha -Zhuzhou-Xiangtan urban agglomeration shows the highest average growth rate, followed by the Wuhan metropolitan area and the Poyang Lake urban agglomeration. (2) The variation coefficient and Taylor index of the coupling coordination degree demonstrate a fluctuating downward trend, indicating a convergence in spatial differences in interregional coupling coordination levels. Internal differences between city clusters within urban agglomerations are identified as the main source of overall differences in coupling coordination levels. (3) The coupling coordination levels of the three major systems follow an evolutionary trajectory characterized by "serious imbalance, moderate imbalance, mild imbalance". Clear features of level transitions are observed among various cities. (4) The endowment of tourism resources emerges as the primary factor driving the evolution of the coupling relationship among the tourism industry, urbanization, and human settlements. The study highlights the increasing diversification of driving forces and significant spatiotemporal heterogeneity in interregional driving forces for coupling relationship evolution factors.

The impact of green behavior on spatial heterogeneity of city green development-the case of Yangtze River Delta city cluster

The impact of green behavior on spatial heterogeneity of city green development-the case of Yangtze River Delta city cluster

Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS

Abstract. In this study, we develop an advanced retrieval algorithm for tropospheric nitrogen dioxide (NO2) from the geostationary satellite instruments and apply it to Geostationary Environment Monitoring Spectrometer (GEMS) observations. Overall, the algorithm follows previous heritage for the polar-orbiting satellites Global Ozone Monitoring Experiment-2 (GOME-2) and Tropospheric Monitoring Instrument (TROPOMI), but several improvements are implemented to account for specific features of geostationary satellites. The DLR GEMS NO2 retrieval employs an extended fitting window compared to the current fitting window used in GEMS operational v2.0 NO2 retrieval, which results in improved spectral fit quality and lower uncertainties. For the stratosphere–troposphere separation in GEMS measurements, two methods are developed and evaluated: (1) STRatospheric Estimation Algorithm from Mainz (STREAM) as used in the DLR TROPOMI NO2 retrieval and adapted to GEMS and (2) estimation of stratospheric NO2 columns from the Copernicus Atmosphere Monitoring Service (CAMS) Integrated Forecast System (IFS) cycle 48R1 model data, which introduce full stratospheric chemistry as it will be used in the operational Sentinel-4 NO2 retrieval. While STREAM provides hourly estimates of stratospheric NO2, it has limitations in describing small-scale variations and exhibits systematic biases near the boundary of the field of view. In this respect, the use of estimated stratospheric NO2 columns from the CAMS forecast model profile demonstrates better applicability by describing not only diurnal variation but also small-scale variations. For the improved air mass factor (AMF) calculation, sensitivity tests are performed using different input data. In our algorithm, cloud fractions retrieved from the Optical Cloud Recognition Algorithm (OCRA) adapted to GEMS level 1 data are applied instead of the GEMS v2.0 cloud fraction. OCRA is used operationally in TROPOMI and Sentinel-4. Compared to the GEMS level 2 cloud fraction which is typically set to around 0.1 for clear-sky scenes, OCRA sets cloud fractions close to or at 0. The OCRA-based cloud corrections result in increased tropospheric AMFs and decreased tropospheric NO2 vertical columns, leading to better agreement with results from existing TROPOMI observations. The effects of surface albedo on GEMS tropospheric NO2 retrievals are assessed by comparing the GEMS v2.0 background surface reflectance (BSR) and TROPOMI Lambertian-equivalent reflectivity (LER) climatology v2.0 product. The differences between the two surface albedo products and their impact on tropospheric AMF are particularly pronounced over snow/ice scenes during winter. A priori NO2 profiles from the CAMS forecast model, applied in the DLR GEMS algorithm, effectively capture variations in NO2 concentrations throughout the day with high spatial resolution and the advanced chemical mechanism, which demonstrates its suitability for geostationary satellite measurements. The retrieved DLR GEMS tropospheric NO2 columns show good capability for capturing hotspot signals at the scale of city clusters and describe spatial gradients from city centres to surrounding areas. Diurnal variations of tropospheric NO2 columns over Asia are well described through hourly sampling of GEMS. Evaluation of DLR GEMS tropospheric NO2 columns against TROPOMI v2.4 and GEMS v2.0 operational products shows overall good agreement. The uncertainty of DLR GEMS tropospheric NO2 vertical columns varies based on observation scenarios. In regions with low pollution levels such as open-ocean and remote rural areas, retrieval uncertainties typically range from 10 % to 50 %, primarily due to uncertainties in slant columns. For heavily polluted regions, uncertainties in tropospheric NO2 columns are mainly driven by errors in tropospheric AMF calculations. Notably, the total uncertainty in GEMS tropospheric NO2 columns is most significant in winter, particularly over heavily polluted regions with low-level clouds below or near the NO2 peak.

Promoting coordinated spatial governance of mega-cities in China via spatial organization of metropolitan areas

Super large-sized cities and very large-sized cities (“mega-cities” for short) have become the backbone of China's socio-economic development, but they also face outstanding challenges of "urban diseases" due to their high concentration. In comparison to their foreign counterparts, China's mega-cities possess unique characteristics such as rapid growth, high population density, and large numbers of residents. They naturally have the attributes of metropolitan areas due to an administrative management system of an urban system within city territory. Promoting coordinated spatial governance of mega-cities via spatial organization of metropolitan areas not only helps mega-cities better allocate resources at a larger scope and helps expedite the transformation of development patterns, but is also crucial for better implementing new-type urbanization strategies. In response to the issues in China’s previous research and practices related to mega-cities and metropolitan areas, leveraging the “Critical Technology for Spatial Optimization of Metropolitan Areas of City Clusters” of the national key R&D plan in the “14th Five-year Plan” period, we have employed a scientific approach that combines data and models to propose spatial governance strategies. These strategies encompass both the overall metropolitan area level and the cross-border regional level. Our primary focus lies in optimizing the spatial layout of the “three domains” – ecological space, production space, and living space, facilitating functional dispersal, enhancing spatial patterns, adjusting land use structures and spatial resource allocation, coordinating rail transit and the organization of functions along transit lines, and innovating service management for improvement of administrative efficiency. Through the implementation of these diverse measures, we aim to establish a comprehensive composite collaborative system.

Can subsidy policies achieve fuel cell logistics vehicle (FCLV) promotion targets? Evidence from the beijing-tianjin-hebei fuel cell vehicle demonstration city cluster in China

Fuel cell logistics vehicle (FCLV) plays a pillar role in achieving carbon neutrality in the freight sector. Due to high costs and imperfect infrastructure, millions of subsidies are granted to develop FCLV and fulfill promotion targets set by the government. To examine the effectiveness of this action, the study proposes a tripartite evolutionary game theory (EGT) model to simulate the interactions between local governments, private investors, and consumers, and explores the fulfillment of promotion targets in the Beijing-Tianjin-Hebei fuel cell vehicle demonstration city cluster. The obtained results show that: (i) the FCLV promotion targets of demonstration cities except Tangshan could be substantially achieved under the current subsidy; (ii) purchase subsidies for consumers can help achieve promotion targets at a faster pace, while construction subsidies for investors have a limited incentive effect, so more non-financial incentives need to be provided to investors, such as innovative operating models and priority approval of land for hydrogen refueling station construction; (iii) a comparison of subsidies in different cities reveals that Beijing's subsidies are the most efficient and that there is an optimal allocation between consumers and private investors that allows for the faster accomplishment of promotion targets without increasing the fiscal burden.

Mortality attributable to ambient PM2.5 exposure across regions in China from 2005 to 2020

BackgroundChina has implemented rigorous clean air policies since 2013 to address PM2.5 pollution particularly affecting economically developed regions. The Fusion relative risk model was recently developed to better capture the association between long-term PM2.5 exposure and mortality risk, but it has not been used in China. MethodsWe estimated cause-specific PM2.5 attributable deaths among adults (≥ 25 years) across China over 2005–2020 at a 0.1° × 0.1° spatial resolution using the Fusion model, and also adopted the Global Exposure Mortality Model (GEMM) for comparison. We investigated 31 provinces and targeted five mega city clusters: Beijing–Tianjin–Hebei cluster (BTH), Yangtze River Delta cluster (YRD), Pearl River Delta cluster (PRD), Cheng–Yu cluster (CY) and Middle reaches of the Yangtze River cluster (MYR). ResultsThe Fusion model estimated PM2.5 attributable deaths increased from 2.38 million (95 % UI: 2.06-2.64) in 2005 to 2.68 million (95 % UI: 2.33-2.95) in 2013 (12.6 %), then declined by 11.6 % to 2.37 million (95 % UI: 2.04-2.65) in 2020. Ischemic Heart Disease (IHD) and Stroke contributed most to the total attributable deaths (33.4 % and 35.0 % in 2020). Compared with the GEMM, the Fusion model generated higher attributable mortality estimates for IHD, Stroke and Chronic Obstructive Pulmonary Disease, but lower estimates for Lung Cancer and Lower Respiratory Infections. PM2.5 attributable deaths were clustered in densely populated and highly polluted regions, with Henan and Shandong bearing the highest mortality burden among the 31 provinces. PM2.5 attributable deaths in BTH, YRD, PRD, CY and MYR declined by 5.3 %, 11.5 %, 18.0 %, 25.4 % and 18.6 % respectively over 2013–2020, with greater declines in attributable mortality rates (18.9 %, 23.8 %, 33.8 %, 27.3 % and 24.1 %). ConclusionsFuture clean air policies in China should consider regional disparities and continue prioritizing highly polluted and densely populated urban areas, including the five mega city clusters.

A hybrid spatiotemporal model combining graph attention network and gated recurrent unit for regional composite air pollution prediction and collaborative control

Machine learning (ML) models have been extensively applied in air quality prediction. However, many of these models often failed to unveil complex mechanisms and regional spatiotemporal variations of composite air pollution. This brings uncertainties in using ML models for effective composite air pollution control. The present study developed a novel hybrid spatiotemporal model framework combining Graph Attention Network (GAT) and Gated Recurrent Unit (GRU), namely the GAT-GRU model, to foresee composite air pollutions with a focus on PM2.5 and O3. By extracting attention matrices for PM2.5O3 composite pollution and applying the Louvain algorithm, the framework established effective community network divisions for coordinated control of PM2.5O3 composite pollution. The framework was applied and tested in China's “2 + 26″ cities, a city cluster with most heavy PM2.5 and O3 pollution and precursor emission sources. The results demonstrate that the framework successfully captured spatiotemporal evolution of combined PM2.5 and O3 pollution. The attention matrix is autonomously generated during course of the model learning process with the aim to interpret the complex interactions among “2 + 26″ cities. The framework provides a new perspective for the interpretability of artificial intelligence models and offers a methodological support and scientific evidence for formulating regional pollution cooperative governance strategies.

Sustainable urban water management index for developing countries. A case study in Puebla City, Mexico

Several indicator and index frameworks have been reported to assess management efficiency and promote transparency, facilitating decision-making and innovation. However, they cannot be applied in cities with limited information, making them impractical. This study proposes a Sustainable Urban Water Management Index (SUWMI) for such cities, selecting six AquaRating indicators plus two indexes recommended in the Sustainable Development Goal 6, yielding a simplified and practical version for diagnosing the management performance rate of the Water Operating Systems (WOS) in cities. Conceptual and mathematical models were defined for SUWMI, and the eight selected terms were hierarchized based on a decision tree with the participation of an expert panel and further multicriteria decision-making methodology by the Analytic Hierarchy Process (AHP) to calculate the weighting parameters. The selected indicators represent five categories on a percentage scale. The highly populated Puebla City Metropolitan Zone in Mexico was the case study. Information was gathered from five Water Operation Systems (WOS) from 2002 to 2020. The tap water area's coverage and physical efficiency improved despite the population growth due to an adequate political strategy after 2014. The SUWMI values of each WOS diagnoses its performance, highlighting their differences and providing a valuable tool for guiding urban water public policy programs. The paper proposes a simple, fast, and easy-to-calculate index that can be helpful for a broader cluster of cities and urban settlements with deficient available information, which is common in developing countries.

Research on the dynamic characteristics and improvement path of urban sustainable development level: Based on gravitational model and scenario simulation method

The rapid expansion of cities has brought new challenges to sustainable development (SD). Therefore, how to balance between SD and the economic growth has become the key to regional development. With the aim of enhancing the research system of SD level, founded on the deep research of SD level from a new perspective of “input-output” and the dynamic evolution law of SD level, this paper has explored the path for cities to improve their level of SD to achieve regional coordinated development. By virtue of the Super-efficiency Slack-Based Measure model based on unexpected output (unexpected super efficiency SBM model), it has measured the SD level of 21 cities in Sichuan from 2010 to 2019. Using methods such as equilibrium coefficient, obstacle analysis and gravitational model, this paper has studied the spatiotemporal evolution law of SD level and constructed six scenarios to simulate the future trend of SD level. The results have indicated that the level of SD in Sichuan is showing a gradual decline with significant constraints. The focus of SD in Sichuan is gradually shifting from Chengdu to a city cluster centered around Chengdu, Ziyang, and Meishan. In an ideal development scenario, the level of SD has significantly improved. This study has revealed the current status and potential of SD in Sichuan. In the future, with more concentration on the role of core urban agglomerations, Sichuan should adjust policies to address input–output barriers to promote SD throughout the province.

Spatial and temporal dynamics of sewage sludge phosphorus recovery potential in the cities of Yangtze River Zone in China: Implications for regional recycling policies

Sewage sludge phosphorus (P) recovery presents opportunities to sustainably recycle P from cities to agriculture and alleviate global P scarcity. However, limited research explores sustainable recovery targets considering spatial-temporal variations in sludge generation and implications based on city-level local P demand. This study analyzed sludge production form 2009–2021 across 130 cities in China's Yangtze River Zone, which increased by almost 35 % from 2009 to 2021. Per capita gross domestic product (GDP), influent chemical oxygen demand (COD), and per capita drainage infrastructure were identified as the main significant influencing factors. City-level analysis revealed pronounced spatial-temporal disparities, with yearly sludge generation spanning five orders of magnitude (62–5.4 × 105 t/a). An indicator, “Potential of P recovery to local P demand”, was defined, indicating the average city-level P recycle contribution increased from 5.3 % to 18.9 % from 2009–2021. A novel frame paradigm classified cities into six types based on the local P supply-demand characteristics, prioritizing sludge P recovery and implementing strategic management. City-specific dynamics and possibilities of broader “city clusters” to match supply and demand should be considered for policy implement. Recovering P from livestock manure and kitchen waste alongside sludge can further strengthen urban P cycles. This study provides novel city-scale analysis and strategic considerations for regional sludge P recycling policies in China and beyond.

Study on the Coupled Coordinated Development of New Urbanization and Urban Resilience in Huaihe River Basin

The coupled and coordinated development of new urbanization and urban resilience can promote the disaster response, disaster resistance and high-quality development of urban agglomerations in the Huaihe River Basin. The article constructs a new urbanization system and a chain-type urban resilience evaluation system with the mechanism of "pressure-feedback", selects the central city of Huaihe River Basin as the research object, and measures the new urbanization and urban resilience level and change trend of the central city of Huaihe River Basin in 2012-2021 with the help of the coupling coordination model. Using the entropy value method, we measured the new urbanization and urban toughness level and the trend of change of the central cities in Huaihe River Basin from 2012 to 2021, measured the type of city cluster coupling coordination and its internal factors with the help of the coupling coordination model, and analyzed the coupling coordination relationship between the two.

Spatio-temporal interplay between ecosystem services and urbanization in the Yangtze River Economic Belt: A new perspective for considering the scarcity effect

The expeditious trajectory of urbanization has profound ramifications on the configuration and functioning of the natural milieu. Given the constrained opulence of natural capital and its indispensable bestowal of ecosystem services in different regions, meticulous contemplation of the relationship between urbanization and the ecosystem service scarcity value (ESSV) while formulating decisions is imperative. This study focuses on the Yangtze River Economic Belt (YREB), where ESSV is quantified by combining the dynamic changes in market supply and demand factors. The influence of supply and demand changes on the ESSV is discussed and analyzed in four scenarios. Subsequently, a multidimensional urbanization comprehensive evaluation index system was established to explore the spatiotemporal interactive response mode between ESSV and urbanization. Our findings manifest a notably augmented ESSV in the YREB from 1990 to 2020, particularly prominent between 2000 and 2010. Moreover, the growth in public goods services outpaced that in private goods services within the same period. Demand-driven scarcity has emerged as the foremost determinant of ESSV. Urbanization levels gradually increased from 1990 to 2020, with a uniform allocation of heightened ESSV and urbanization throughout the region. The urbanization level of YREB, as a whole, exhibited conspicuous spatial heterogeneity, with the downstream region significantly surpassing the middle and upper reaches, and the downstream Yangtze River Delta city cluster and the middle reaches of the Chengdu-Chongqing city cluster notably outpacing that in the surrounding region. The coupling coordination degree (CCD) between the ESSV and urbanization in the YREB develops in a harmonious direction during the study period, accompanied by palpable spatial disparities. The area of unbalanced development gradually decreased, and the area proportion of the coordinated development type of ESSV and urbanization increased continuously. Overall, this study elucidates regional disparities in the reciprocal relationship between the ESSV and urbanization in the YREB, thereby unveiling the extent of incongruity between regional urbanization and the ecosystem. It serves to identify the juncture at which ecological sustainability and urbanization converge harmoniously, thus offering novel insights in achieving comprehensive, high-caliber, and synchronized development in the YREB.

Evolution of regional collaborative innovation network by the ‘two-wheel drive' of external proximity and endogenous gravity

ABSTRACT Collaborative innovation is the key support for promoting high-quality regional development. Taking Guangdong, Fujian and Zhejiang coastal city clusters as an example, this paper analyzes the evolution mechanism of collaborative innovation network based on the ‘two-wheel drive' perspective of external proximity and endogenous gravity. The results show that the difference of resource control ability among nodes in the network is decreasing, and the inverted ‘V’ structure with Xiamen and Putian as the main apex has evolved into a more robust ‘dual core’ (Fuzhou-Xiamen) radiation-type spatial structure. In addition, the evolution of regional collaborative innovation network is driven by ‘two wheels’. In external proximity, institutional proximity plays the strongest role in promoting, followed by geographical proximity, and the promoting role of technological proximity is gradually weakened. In the endogenous gravity, the influence of investment in science and education is strengthening, while the influence of the administrative level is declining.

Exploring the temporal-spatial characteristics and determinants of high-quality development of city clusters in China

The complexity, severity, and uncertainty of the international situation have prompted the development of city clusters to focus more on resilience and the building of infrastructures and safeguards. Chinese-style modernization proposes a new realization path for the high-quality development (HQD) of city clusters, based on which an evaluation system for HQD indicators of city clusters is constructed. We also measured the HQD levels of 19 city clusters from 2011 to 2021 and analyzed their spatial differentiation characteristics, agglomeration evolution characteristics, and influencing factors by using kernel density, standard deviation ellipse, Moran's index, geographic detector, and geographically weighted regression. The study revealed that (1) the overall level of HQD of China's city clusters shows a trend of continuous growth, and there is obvious polarization in the high quality of city clusters in different regions. (2) The spatial distribution of HQD in city clusters decreased in the "East, Center and West" direction, but the spatial patterns of "Southeast highlighting" and "Northwest rising" became more obvious. (3) The HQD of city clusters shows obvious spatial agglomeration characteristics and overall presents a spatial pattern of "hot in the east and cold in the west", with the scope of the cold spot area gradually shrinking, and the hot spot area tends to spread outward, with mature city clusters at the core. (4) The influencing factors of HQD in Chinese city clusters are diverse, with financial levels, digital economics, human capital and green innovations having decreasing influence on HQD in city clusters but showing an obvious two-factor enhancement trend, with financial levels being able to effectively stimulate the driving potential of other factors. Financial levels can effectively stimulate the driving potential of other factors. (5) The coefficients of the driving factors affecting the HQD of city clusters vary significantly spatially, with human capital, financial levels and green innovations showing a north‒south hierarchical banded distribution of "high in the south and low in the north", and digital economy shows an east-west hierarchical belt distribution of "high west and low east". Based on the above conclusions, the realization path of accelerating the HQD of China's city clusters is proposed by optimizing the functional division of labor of the city clusters, giving full play to the comparative advantages of the hinterland city clusters, and relying on the high level of the city clusters for opening up.

Analysis of the spatio-temporal variability and convergence of green development efficiency of city clusters in the middle reaches of the Yangtze River in China

The advantageous geographical location of the middle reaches of the Yangtze River (YRMR) plays an important role in promoting high-quality development in China and accelerating the development of the Yangtze River Economic Belt(YREB). In the new stage of development, green development efficiency (GDE) is an important metric for assessing the balance between economic development and ecological civilization. Therefore, taking three city clusters in China's YRMR as the study area, this research employs the Super-SBM model to assess their GDE in 2010–2020 in order to analyze the problem of GDE at the city scale. On this basis, spatio-temporal analyses, dynamic evolution, and convergence analyses have been carried out using the Thiel index, GML index model, and convergence model. The findings indicate that overall GDE has not yet reached an effective level and generally exhibits a two-stage fluctuating upward trend. Spatially, the pattern of distribution is "high in the southwest, low in the northeast". The differences within the city clusters in the YRMR in terms of green development are gradually narrowing, with differences within the same regions contributing the most to overall differences. The GML index shows a trend of fluctuating growth, indicating that the overall GDE growth is in good condition. GDE has grown significantly as a result of technological advancements, with the Wuhan metropolitan area (cluster A) experiencing the fastest growth in this regard, followed by the Chang-Zhu-Tan and the Poyang Lake rim city clusters (clusters B and C). The YRMR and its three major city clusters exhibit both σ- and β-convergence patterns. The convergence of GDE is simultaneously affected by several factors, including economic development (RGDP), urbanization level (UR), industrial structure (IND), technological development (TEC), and the level of openness (LO). Regional heterogeneity also exists. The above study provides decision-making references and empirical evidence for promoting green development in China's city clusters in the YRMR and advancing the improvement of economic-environmental incongruence in this area.

Analysis of the Characteristics and Driving Mechanisms of Carbon Emission Decoupling in the Hu-Bao-O-Yu City Cluster under the “Double Carbon” Target

The Hu-Bao-O-Yu urban area is a major source of carbon emissions in China. It is also a major source of energy exports and high-end chemicals in China. Reaching peak carbon emissions early is especially important for meeting the national peak goal. For urban areas that rely on natural resources, we need to make it clearer how carbon emissions and economic growth affect each other and slowly break the strong link between the two. Therefore, in this paper, based on the data on carbon emissions, the decoupling state and the driving mechanism of carbon emissions in the Hu-Bao-O-Yu City group are researched by using the Tapio decoupling model and GDIM method. A new decoupling index model is constructed by combining GDIM and the traditional decoupling model. The main findings are as follows: (1) The Hu-Bao-O-Yu urban agglomeration, Ordos City, Baotou City and Yulin City have significant growth trends in annual carbon emissions, with Yulin City being the most important carbon source for the Hu-Bao-O-Yu urban agglomeration and its economic contribution to carbon emissions of the whole urban agglomeration is the most efficient. (2) The decoupling of Hu-Bao-O-Yu, Huhhot City, Baotou City, and Ordos City is dominated by expansionary negative decoupling, whereas Yulin City has strong negative decoupling. (3) The Hu-Bao-O-Yu urban cluster mainly affects the carbon intensity of fixed asset investments and output carbon intensity, which is a key part of the carbon separation process. The energy scale and structure also play a part in this process over time. (4) Changes in GDP per capita are a bigger part of changes in carbon emissions in the Hu-Bao-O-Yu urban agglomeration. These changes also determine the direction for changes in carbon emissions in the Hu-Bao-O-Yu urban agglomeration. In the future, the Hu-Bao-O-Yu urban agglomeration needs to coordinate its economic growth. Ordos and Yulin need to speed up the optimisation and transformation of their energy structures. Baotou needs to push for the low-carbon transformation of its industries. Huhhot needs to do more research on carbon sequestration technology and spend more on environmental protection. This will make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration and improve its ability to reduce emissions.

Location dynamics of coworking spaces in China: insights from Beijing metropolitan

ABSTRACT This paper explores the location determinants of coworking spaces (CSs) in the Chinese capital of Beijing, thus filling the gap in the literature about CS location in urban China. The study applies a count data model (CDM) to the data collected in 2022 to answer three research questions: (1) Where are CSs located and what are the location determinants? (2) How does Beijing’s urban structure affect CS location determinants? (3) What role do creative industry specialisation, variety, government facilities and incentives play in CS location? The findings reveal that CSs in Beijing – most of them promoted by public authorities – tend to cluster in the central city where there is a high diversity of knowledge-intensive and creative industries. The semi-polycentric urban structure of Beijing affects the location of CSs by creating localised activity hubs. Furthermore, the study finds evidence that creative industry specialisation and variety are crucial factors in CS location. In addition, government facilities and incentives play a key role in driving their locations.

Identification of key areas for ecological restoration of territorial space based on ecological security pattern analysis: A case study of the Taihu Lake city cluster.

The identification of key areas for ecological restoration of national land space based on the ecological security pattern is an important way to balance environmental protection and social development in the new era. With the Taihu Lake city cluster as the study area, we identified the ecological source from both structural and functional aspects, and used the minimum cumulative resistance model to identify the ecological corridors on the basis of constructing the resistance surface. Coupled the landscape ecological risk evaluation, we determined the appropriate width of each ecological corridor in the study area, identified the key restoration zones through the circuit theory. Then, we constructed the ecological security pattern of "six zones and four belts" and controlled by zoning. The results showed that the 32 ecological source areas in the Taihu Lake city cluster presented a spatial pattern of "more in the east and less in the west-mountains and lakes are connected" and 70 ecological corridors were concentrated in the west and the center. The suitable width of most of the ecological corridors was 1500-2000 m. The ecological restoration zones of the national land space were concentrated in the eastern part of the Lake Taihu, Changxing County, and Liyang City. According to the characteristics of the study area and the actual situation of the restoration area, we proposed specific protection and restoration measures, such as protecting the core ecological source, optimizing and restoring the important corridors, and reasonably planning land use of the ecological pinch points and obstacle points.

Clustering Open Data for Predictive Modeling of Residential Energy Consumption across Variable Scales: A Case Study in Andalusia, Spain

The energy budget of households, linked to residential energy consumption (REC), serves as a critical indicator of quality of life and economy trends. Despite the lack of widely available accurate statistics at regional or smaller scales, they are of crucial interest for a better understanding of the features influencing REC and its impact on energy poverty, wellbeing, and the climate crisis. This research aims to present a new information model for predictive parameters and REC forecasting through an innovative use of available open data. Geoprocessing, data mining, and machine learning clustering algorithms were applied to open datasets of location, population, and residential building stock parameters highly correlated with their REC, on the ensemble of 785 municipalities of Andalusia, Spain. The model identified 65 clusters of towns sharing the same potential REC, with 73% of the population concentrated in 10 of these. The resulting data-driven bottom-up model of provincial REC had a mean absolute error of only 0.63%. Furthermore, it provided the territorial distribution, with local resolution, of the identified clusters of cities with similar characteristics. This methodology, with a flexible regional- to city-scale analysis, provides knowledge generation that offers numerous practical applications for energy policy planning. Its future implementation would assist stakeholders and policymakers in enhancing the performance and decarbonization of the residential building stock.