Search

Purpose: To study the relationship between three variables, namely, the number of supermarkets around, the average distance to medical institutions designated to be covered by basic medical insurance, and the presence of parks around, and the sustainable development of elderly care institutions.Patients and Methods: This paper is based on the census database of elderly care institutions in Beijing. We ran a self-developed Python program to mine the database after adding three variables, namely, the number of supermarkets around, the average distance to medical institutions designated to be covered by basic medical insurance (hereinafter referred to as "designated medical institutions"), and the presence of parks around, and then used the least squares method in regression analysis.Results: The number of years of depreciation for fixed assets had some degree of influence on the occupancy rate of an elderly care institution under sustained operation. The occupancy rate of above 80% was efficient for an elderly care institution. There was a progressive relationship between the external spatial factors and the internal resources of an elderly care institution in terms of influencing the occupancy rate of the institution. Optimizing the spatial distribution of elderly care institutions should first optimize the choice of location.Conclusion: The occupancy rate of an elderly care institution was closely related to the convenience of living conditions and that site selection was crucial for such a facility. We arrived at two recommendations for the future development of elderly care institutions, 1. Reducing the number of the institutions in areas with unfavorable geographic positions and serving senior care needs within an appropriate close distance, so as to better optimize the spatial distribution of senior care facilities, improve the efficiency of resource allocation. 2. Strike a balance between the economic benefits of operating entities and the social benefits associated with older people. [ABSTRACT FROM AUTHOR]

In response to the international appeal of developing low-carbon economy and realizing carbon peaking and neutrality goals, China has been exploring the construction of the carbon emissions trading market for years. Without the guidance of advanced technology, there would not be a low-carbon economy in the first place. Based on panel data of 30 provinces and cities in China from 2005 to 2020, this paper takes Beijing—which is the first pilot city in China—as the only treated group and uses the Synthetic Control Method to study the impact of the pilot policy on low-carbon technology innovation. The results show that, firstly, the number of low-carbon technology patents in Beijing increases significantly after the implementation of the pilot policy, proving a positive influence on technology innovation. Secondly, the policy effect has a certain time lag and is sensitive to the shock from both domestic and foreign carbon market, but this effect is gradually stable over time. This paper confirms that technological innovation is the key means of promoting the development of the low-carbon economy and calls on various carbon trading markets to pay attention to the internal mechanism of promoting low-carbon technology innovation to stimulate the vitality of market entities. [ABSTRACT FROM AUTHOR]

In the knowledge economy era, innovation has become a key emphasis for urban competitions. This paper constructs a theoretical research framework that integrates the basic understandings, influencing factors and ensuing results of intercity innovative competition relations. On the basis of data from the general programs of the National Natural Science Foundation of China from 2005 to 2019, this paper constructs intercity innovative competition relations in China, analyses their spatial distribution and quantitative characteristics, and quantitatively investigates the impact of urban innovation capacity and multidimensional proximity (e.g., geographical proximity, institutional proximity and cognitive proximity) on intercity innovative competition relations through a negative binomial model. The study obtained the following findings: (1) In terms of the overall intercity innovative competition relations, the intensity of China's intercity innovative competition relations gradually increased from 2005 to 2019, with a spatial clustering towards cities with high administrative ranks (e.g., municipalities directly under the central government, sub-provincial cities and provincial capitals); Beijing is always at the centre of innovative competition relations, but its standing has slightly slipped in recent years. (2) From the perspective of disciplines, cities can become benchmarks in particular fields of innovative competitions by competing according to their disciplinary strengths; intercity innovative competition relations in China vary across various academic disciplines. (3) In terms of influencing factors, urban innovation capacity has significant positive effects on intercity innovative competition relations; geographical proximity, institutional proximity and cognitive proximity all have significant positive effects on innovative competition relations; and interactions occur between multidimensional proximities, including a complementary effect between geographical proximity and institutional proximity, a substitutive effect between cognitive proximity and geographical proximity, and a substitutive effect between cognitive proximity and institutional proximity. [ABSTRACT FROM AUTHOR]

Industrial heritage is regarded as an important stock of spatial resources in cities, which highlights its utilization value for urban regeneration in high-density urban areas. With the dramatic increase in the number of industrial heritage reuse projects, how to scientifically evaluate the satisfaction with their spatial reuse is a key part of the solution for the mutual balance between heritage preservation and urban renewal. This paper takes eight industrial heritage conversion and utilization projects in the high-density core area of Beijing's central city as examples; establishes an evaluation system for the satisfaction with the spatial reuse through six dimensions, namely, functional replacement, transportation accessibility, carrying capacity, public space, boundary form, and recognition of value; and uses the IPA method to evaluate the cases. This method is used to determine the degree of user satisfaction with the spatial reuse of industrial heritage in the core area of Beijing's central city and to summarize the advantages and problems of its reuse. The results of this study reveal a trend toward the "community-oriented" re-generation of industrial heritage in the core area of Beijing's central city, and this paper proposes recommendations for adaptive use to support high-quality urban regeneration work. [ABSTRACT FROM AUTHOR]

China is in the transition period of urbanization, and the imbalance of land use generated during the original rapid development of megacities still exists, resulting in the preservation of a large number of urban villages in the peripheral areas of cities. Unlike formal housing, these villages are heavily influenced by the confrontation and interweaving between top-down policies of local governments and bottom-up spontaneous construction by local villagers, resulting in a diverse and complex status quo. At the same time, self-built housing in urban villages has become a gathering place for a large number of low-income migrants due to its relatively low rental prices. In terms of the research of urban villages on the current situation of housing, the real needs of users and housing performance are mostly subjective judgments and conclusions. Therefore, the entry point of this paper is the leased space and the leasers, taking Laojuntang Village in Chaoyang District of Beijing as the research object and analyzing its current problems and the real needs of users. This paper adopts an integrated approach of fuzzy Kano model evaluation and building performance simulation. After analyzing the data and discussing the influencing factors, this paper identifies the specific problems and user needs that exist in leased spaces in Laojuntang Village: (1) The architectural performance of leased space is a Must-be Quality, which is the bottom-line requirement and must be improved. (2) The quality of the basic facilities and equipment of the leased space is mostly a One-dimensional Quality, Attractive Quality, and the degree of importance is lower than that of the building performance. (3) The external activity facilities of the leased space are mostly undifferentiated needs, for which the local users are not particularly prominent. (4) The scale and plot ratio of local housing is relatively high, and users are dissatisfied and complaining, which falls under the category of Reverse Quality. [ABSTRACT FROM AUTHOR]

Many developed cities in the world put forward a spatial development strategy in their construction planning. Analyzing the development level of the urban spatial structure and the influence of driving factors has become a hot topic. Based on 709,232 points of interest data in Beijing, China, this paper integrates nighttime light data and population density data to select eight key driving factors from three perspectives: urban function configuration, economic activity intensity and population spatial distribution. Geodetector is used to optimize data discreteness and highlight the spatial heterogeneity of the development level. We use the technique for order of preference by similarity to ideal solution (TOPSIS) model improved with the entropy weight method to grade the spatial differentiation characteristics of the comprehensive development level. The driving factors and their effects on space are further discussed using Geodetector. The results are as follows: (1) The quartile method can achieve the optimal dispersion of all urban functions. The standard deviation can achieve the optimal dispersion of economic activity intensity and population spatial distribution; (2) A comparison with the "Beijing Urban Master Plan (2016–2035)", finds that the optimized evaluation system can effectively reflect the spatial heterogeneity of urban spatial structure development. It verifies the rationality of the evaluation methods and factors; (3) The driving force of the population under single-factor driving is 0.8428. The dual-factor driving force with population participation ranges from 0.8992 to 0.9550. The results of the study are significant and reflect the prominent role of population on the development level of spatial structure in Beijing. This paper aims to provide a new idea for the study of the interior space planning of large inland cities. [ABSTRACT FROM AUTHOR]

The issues of housing and traffic in China's mega cities have become increasingly pressing problems, particularly for middle/low-income tenant workers. These tenants are from less advantaged socioeconomic backgrounds, which has resulted in a significant geographical separation between their workplace and their residence. Although a large number of studies have confirmed that built environment factors have a solid impact on residents' commuting distance, few studies have investigated the mechanism underlying the nonlinear influence on middle/low-income tenants. This paper aims to provide an in-depth analysis of the key factors and nonlinear influencing mechanism of the built environment on middle/low-income tenant workers' commuting distance by establishing a gradient-boosting decision tree model, using Beijing as an empirical case. The paper reveals three primary findings: (1) An important nonlinear relationship between the surrounding built environment and peoples' jobs–housing spatial proximity can be observed for those middle/low-income tenant workers who use slow and public modes of commuting. Specifically, the density of public transport stations, road networks, and workplaces, and the land use mix play a dominant role. (2) A limited effect of built environment factors can be found for the same group of tenant workers who choose cars as their mode of commuting. (3) The differences in self-selected commuting modes have a significant mediating effect on the relationship between the built environment and jobs–housing situation among middle/low-income tenant workers. Given this, effective policy guidance for residents' travel modes is necessary to optimize the built environment indicators to achieve the best effect. In addition, we should consider giving priority to the matching indicators such as land use mix and resident population density. Another possibility is to strengthen the connection to the public transport stations, which in turn can optimize the walkability in residential environments. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei integration plan rose to the status of a national-level strategy in 2014. This paper provides a deep analysis of the Beijing-Tianjin-Hebei area's inter-city commuter big data. This research analyzed the overview of spatial structure, polycentric structure, hierarchical structure and clustering characteristics of the BTH based on network analysis methods. It reveals that the inter-city commuter network exhibits clear polycentric characteristics, with Beijing acting as the central hub. The degree of network correlation between cities in Tianjin and Hebei is notably low, indicating that the flow of people primarily revolves around Beijing, while interactions between other cities remain limited. Therefore, it is necessary to further decentralize Beijing's non-capital core functions. The level of connectedness among the areas surrounding the Bohai Rim is not very high, and it has not developed the coastal advantage. The cooperation could be strengthed among the cities within Bohai Rim. The polycentric structure has initially taken shape, but it exhibits obvious polarization characteristics. It is necessary to strengthen the interaction of talents between cities to form secondary central units in BTH. [ABSTRACT FROM AUTHOR]

Analyzing the spatio-temporal relationship between socio-economics and land-use structure at the micro-scale is crucial for effective spatial governance in large cities. This paper focuses on Beijing, utilizing long time-series remote sensing images and multi-source data spanning 30 years. We employ spatio-temporal clustering based on kilometer grid cells and a community-scale multi-factor aggregation method to categorize the linkages and spatio-temporal matching of population, GDP, land development, and ecological protection at the community level in a problem-oriented approach. Results indicate significant changes in Beijing's population, GDP, and land use, with a 11.53% increase in land development intensity. We identify significant temporal and spatial disparities between population–GDP dynamics, population–land development trends, and GDP–land development patterns, underscoring the multifaceted challenges inherent in urban governance. Areas characterized by lagging population concentration, sluggish economic growth, rampant land development, and ecological fragility collectively encapsulate notable portions of Beijing's expansive urban terrain. Mismatches pose governance risks, with medium to high-risk communities comprising 18.08% of community units and high-risk types representing 4.27% in Beijing. These discrepancies pose formidable governance risks, with communities ranging from moderate to high-risk categories, necessitating tailored interventions to address their unique challenges. This systematic exploration of comprehensive governance issues within mega-cities promises to furnish decision-makers with invaluable insights, facilitating nuanced and strategic urban governance approaches tailored to the intricacies of urban dynamics and challenges. [ABSTRACT FROM AUTHOR]

Care facilities are the mainstay of social services for the elderly. As the trend of empty nesting among elderly families intensifies due to the aging population, it is becoming difficult for families to take on the responsibility of caring for the elderly on their own, and the elderly need more formal care to be provided by society. The contradiction between the lag in the construction of care facilities and the growth in the social demand for elderly care has been highlighted, and the spatial equality of care facilities is an important means of achieving an optimal allocation of resources for elderly care. In this paper, we use the two-step floating catchment method to measure the spatial accessibility of care facilities from a fine-grained perspective, using big data, including mobile phone signaling data and points of interest. Then, we use the Gini coefficient to analyze the equality of the spatial allocations of different types of urban care facilities. The results of the study show that, first, the spatial equality of care facilities is good in terms of the Gini coefficient, but the overall spatial accessibility of care facilities is at a relatively low level compared to that in developed cities. This means that the layout of Changchun's care facilities is good, but there is insufficient service capacity. Second, the spatial accessibility of residential care facilities is characterized by a gradual decline, with high levels in the core and low levels in the periphery. Fewer facilities are located in the peripheral areas of the city, and spatial accessibility is at a lower level, a characteristic different from that seen in cities with a higher level of economic development, such as Beijing. Third, the spatial accessibility of community care facilities showed a polycentric, contiguous distribution. The effect of the study scale on the spatial accessibility of community care facilities was more pronounced, with large scales obscuring the high values of the spatial accessibility of community care facilities in peripheral areas. Fourth, Changchun has better overall equality of care facilities, with differences in the different types and areas of care provided. The spatial balance of care facilities in the core area is better than that observed in other regions. In conclusion, this paper underscores the value of big data, such as mobile phone signaling data, in supporting refined urban research. Furthermore, our comprehensive analysis of social care facility equality can inform policy making and spatial planning. [ABSTRACT FROM AUTHOR]

This paper examines the effects of interventions to reduce air pollution during two international events on air quality in Beijing and its neighbor cities. Air quality data were gathered from China's Ministry of Environmental Protection, meteorological data from the China Meteorological Administration and economic data from the China Statistical Yearbook. The paper uses fixed-effect panel data models to empirically evaluate air quality improvement in Beijing and other affected cities before, during, and after the 2008 Olympic Games and the 2014 Asia-Pacific Economic Cooperation summit. Results show substantial improvement in air quality in Beijing and neighboring cities during the two events. However, some of the air quality improvement achieved reverted within a year after the games and within a week after the summit. Furthermore, the improvement achieved during the summit completely reverted and air quality deteriorated severely five days after the summit. It is also found that air quality in China, at least in the cities included in this study, gradually improved over the past 15 years or so. The findings suggest that sustainable interventions and incentive-based programs to reduce emissions from industry production and traffic are the key to maintaining the air pollution reduction achieved during the events. [ABSTRACT FROM AUTHOR]

• To solve the forecasting problems of time-lead and nonlinearity in a system, a novel grey multivariable model is proposed. • To reduce the morbidity of the model, the solution of the proposed model is deduced through a derivation method. • The grey prediction evolution algorithm is employed to find the optimal value of parameters. • The validity of the new model was verified by three examples and applied to house price forecasting. Time lags or leads and non-linearity of complex systems are critical to address in accurate scientific prediction. However, few studies have focused on time-lead and nonlinear models with limited information. Therefore, this paper aims to develop a novel grey multivariate model with time-lead operator τ and nonlinear factor r from the perspective of this problem. Next, the solution of the proposed model is deduced through a derivation method to reduce the morbidity of the model. Then, the parameter identification of the model is given on the basis of the least-squares method. The grey prediction evolution algorithm is employed to find the optimal value of parameters τ and r to meet the minimum errors. Finally, house prices of Wuhan, Beijing and Shanghai in China are performed to verify the validity and reliability of the new model. The results demonstrate the model we proposed has satisfactory prediction precision, demonstrating that time-lead and nonlinear factor in the model is reasonable. At the end of the paper, the house prices of these three cities from 2022 to 2028 are also predicted. The average annual growth rate in the three regions is 2.49%, 3.57% and 2.97%, respectively. These results are useful to policy analysis regarding house price correlations. They provide insights for market investors and policy makers. [ABSTRACT FROM AUTHOR]

Suburban railways in megacities exert a pivotal role in propelling urbanization and shaping urban agglomeration. However, previous study endeavors have overlooked the transformations occurring in urban expansion along suburban railways, with a particular dearth of attention on the spatio-temporal evolution of landscape ecology and urban function. Therefore, this study employs the megacity of Beijing as an example. It utilizes remote sensing and point-of-interest (POI) data spanning from 2008 to 2022 to construct an indicator system from two essential dimensions: urban form and function. We explored the spatio-temporal characteristics of alterations in urban expansion within the gradient buffer zone adjacent to the suburban railway network in Beijing. The results showed that: (1) The rates of urban expansion were highest in 2008–2013 and lowest in 2013–2018; moreover, suburban railways had the greatest impact on the built-up area within 2–4 km along the route, and the impact gradually decreased beyond 4 km. (2) The direction of urban expansion shifted northward in the direction of latitude and eastward in the direction of longitude from 2008 to 2022, with the shift in latitude being more distinct. (3) The number of urban functions gradually increased from 2008 to 2018, but the number of medical services suddenly increased and the number of other urban functions decreased from 2018 to 2022; in addition, urban functions other than scenic spots were mainly distributed in the main urban areas, with very few clusters distributed near stations. (4) The landscape shape index became more irregular and fragmented from the center along the route to the edge of the buffer zone from 2008 to 2013, and the degree of fragmentation was highest in the 2–4 km buffer zone. In summary, this paper analyzes the spatio-temporal characteristics of urban expansion along suburban railways through four indexes, namely expansion rate, expansion direction, urban function, and landscape shape, and the results of this study are of great significance to the development and planning of suburban railways in megacities. [ABSTRACT FROM AUTHOR]

Urban-scale green spaces have been a central topic as of late, but community-scale green spaces are overlooked in urban studies. This paper takes community green spaces in the main urban area of Beijing as the case to quantitatively interpret the spatial-temporal patterns of their service efficiency and distribution characteristics. The measurement section of the paper includes two parts: the first part compares the applicability of two major green space service efficiency measurement methods on the community scale and determines that the Shortest Time Distance method performs better in describing the spatial-temporal patterns of service efficiency. The second part applies the Time Distance Entropy method to initially identify the locational relationship between community green spaces and neighboring residential buildings, then proposes the Green Space Distribution Coefficient method based on this relationship to analyze the 'courtyard', 'mixed', and 'centralized' distribution types alongside the transition relationships between them, and the spatial-temporal patterns of distribution characteristics are measured. The results of service efficiency reveal that the community paradigms transform from 'humanistic-oriented' to 'benefit-oriented' as the Shortest Time Distance measurement values show an ascending trend with the passage of years and the outward expansion of the ring roads. The results of distribution characteristics reveal that the community residential culture transforms from 'closeness' to 'detachment' as Green Space Distribution Coefficient measurement values show a descending trend under the same conditions. Based on the measurements, this paper further provides several optimizing strategies for community green spaces in the central urban area of Beijing. [ABSTRACT FROM AUTHOR]

Instrumental data from the pre–Industrial Revolution period are important to -understand climate change. In this paper, the observations made by the French missionary J. Amiot in present-day central Beijing during 1757–62 were processed and analyzed. The observations represent the earliest continuous dataset of meteorological records found in China that have been digitized recently. Comparisons between the Amiot annual temperature range and extreme values with modern observations showed that the observations were read at approximately 0800 and 1500 local solar time (LST) in a well-ventilated outdoor site. The daily maximum, minimum, and mean temperatures (T-max, T-min, and T-mean, respectively) during 1757–62 were determined by examining the relationship between temperature at 0800 and 1500 LST and T-max, T-min, and T-mean in modern reference series. Nearly 260 years ago, Beijing's climate was typical of an inland temperate monsoon zone with annual T-mean, annual mean T-max, and annual mean T-min being 11.5°, 17.8°, and 6.1°C, respectively; further, the temperatures did not vary considerably from the 1951–1980 temperatures, but differed evidently compared to relatively recent decades (1981–2020). The difference was larger than the magnitudes of global and regional temperature changes. Thus, climate warming since the pre–Industrial Revolution period in the urban areas of Beijing has dominantly occurred over the last four decades. Uncertainties related to the thermometer and observational conditions 260 years ago and the interpolation method used have also been discussed in this paper. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Soil & Water Conservation (1009-2242) is the property of Institute of Soil & Water Conservation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The undergoing rapid urbanization is bringing dramatic economic development and social improvement for cities, but also a series of problems associated with the urban energy metabolism, which hinders the transition toward a carbon–neutral society. Optimizing the energy metabolic processes has been one of the key solutions to cure the metropolis disease that are caused by the enormous energy throughputs in urban areas. This paper highlights the heterogeneity of components in urban energy metabolic system and evaluates the related impacts on urban energy metabolism based on gravity model. Using the data from Beijing's 17 sectors during 2005 ~ 2018, in combination with the "de-coalification" and "non-capital function dispersal" policies in Beijing, this paper testifies that each sector has different impacts on Beijing's energy metabolism and conducted the scenario analysis based on Beijing's recent supply and demand side control policies. It is found that the supply control policies are losing the effectiveness on Beijing's energy metabolism, and may even cause energy shortage up to 0.09 mtce; the demand-control policies can reduce the total energy consumptions up to 1.44 mtce, and improve the energy metabolic processes in the manufacture and education sectors, but will increase the energy consumption in the transportation and wholesale trade sectors. The method proposed in this paper expands the analytical framework for the optimization of urban energy metabolic system, and the results provide suggestions for the policy making of urban carbon–neutral transition. [ABSTRACT FROM AUTHOR]

Industrial upgrading and transfer is one of the three key areas in the coordinated development of Beijing-Tianjin-Hebei Region. Meetings, incentives, conferences and exhibitions (MICE) are important means of promoting industrial upgrading. Urban MICE industry, as an important carrier of event activities, become an important gripper for coordinated development of Beijing-Tianjin-Hebei Region. City exhibition space structure plays an dominant role in regional economic development, and it will greatly promote smooth implementation of the coordinated development strategy of Beijing-Tianjin-Hebei Region. In this paper, 13 prefecture-level cities in Beijing, Tianjin and Hebei were selected as research objects, and the data from 2012 to 2018 were selected to establish a gravity model of the attractiveness of MICE cities. With the help of UCINET software, the network density, centrality, cohesive subgroup and core-edge of nodes researches were obtained to analyze the spatial structure characteristics of the attractiveness of MICE cities in Beijing-Tianjin-Hebei Region. The influencing factors of the spatial characteristics of MICE city attractiveness are analyzed by using geographically weighted regression model. The results show that: (1) Beijing, as the overall core area, act as a prominent role. Beijing strengthens the attraction to the superior resources of the surrounding areas, but the network of MICE cities tends to be unbalanced. (2) Overall space forms a subgroup from a single independent subgroup to a subgroup that is spatially separated from each other and acts as an intermediary channel to connect each other, and the core region decreases from 3 to 2. Langfang was removed from the list, leaving Beijing and Tianjin as the core. (3) The influence of supporting facilities, urban environment and population factors on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is increasing gradually. The influence of tourism development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is decreasing gradually. The influence of economic development level and Internet development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region remains unchanged. [ABSTRACT FROM AUTHOR]

The implementation of grey and green infrastructure is an effective means to address urban flooding and nonpoint source pollution, but due to the complexity of the process and the diversity of benefits, there is a lack of measurement of the comprehensive benefits. Adopting a typical university in Beijing as an example, this paper simulated the multidimensional benefits of the water quantity, water quality, and ecology of grey and green facility renovation by coupling the storm water management model (SWMM) and InfoWorks Integrated Catchment Management (ICM). Monetization methods and economical means were employed to characterize the comprehensive benefits. The results showed that grey and green infrastructure retrofitting reduced the number of severe overflow nodes in the study area by 54.35%, the total overflow volume by 22.17%, and the nonpoint source pollution level by approximately 80% under the heavy rain scenario and 60% under the rainstorm scenario. The annual benefits of grey and green infrastructure renovation reached CNY764,691/year: of this amount, CNY275,726/year was from hydrological regulation, CNY270,895/year was from nonpoint source pollution reduction, and CNY218,070/year was from ecological improvement. The benefits of green facilities were higher than those of grey facilities, and the combined benefits were negatively correlated with the rainfall level, with a total benefit–cost ratio of 1.19. The results provide methodological and data support for grey and green infrastructure retrofitting within the context of sponge cities. [ABSTRACT FROM AUTHOR]

Clarifying the pattern of the urban greenhouse gas (GHG) budget and its influencing factors is the basis of promoting urban low-carbon development. This paper takes Beijing and Shenzhen—the capital city and the most rapidly developing city in China, respectively—as case studies, comprehensively accounts their GHG budgets from 2005 to 2020, and investigates and compares the factors affecting their GHG budgets. The total GHG emissions in Beijing were lowest in 2005 (160.3 TgCO2 equivalents) and peaked at 227.7 TgCO2 equivalents in 2019, and then decreased to 209.1 TgCO2 equivalents in 2020. Meanwhile, the total GHG emissions in Shenzhen gradually increased from 36.0 TgCO2 equivalents in 2005 to 121.4 TgCO2 equivalents in 2019, and then decreased to 119.1 TgCO2 equivalents in 2020. The energy activity sector was the greatest contributor to GHG emissions in this period, accounting for 82.5% and 76.0% of the total GHG emissions in Beijing and Shenzhen, respectively. The carbon sink of the ecosystems of these two cities could absorb only small parts of their emissions, and the neutralization rates of sinks ranged from 1.7% to 2.3% in Beijing and from 0.3% to 1.5% in Shenzhen. The enhancement of population, economic product, and consumption increased the greenhouse gas emissions in both cities. A 1% increase in population size, per capita GD (gross domestic product), and residential consumption level would increase total GHG emissions by 0.181%, 0.019%, and 0.030% in Beijing, respectively. The corresponding increases in Shenzhen would be 0.180%, 0.243%, and 0.172%, respectively. The household size had opposite effects on the two cities, i.e., a 1% increase in household size would increase GHG emissions by 0.487% in Shenzhen but reduce them by 2.083% in Beijing. Each 1% increase in secondary industry and energy intensity would reduce GHG emissions by 0.553% and 0.110% in Shenzhen, respectively, which are more significant reductions than those in Beijing. [ABSTRACT FROM AUTHOR]

In recent years, with the continuous improvement of urban public transportation capacity, citizens' travel has become more and more convenient, but there are still some potential problems, such as morning and evening peak congestion, imbalance between the supply and demand of vehicles and passenger flow, emergencies, and social local passenger flow surged due to special circumstances such as activities and inclement weather. If you want to properly guide the local passenger flow and make a reasonable deployment of operating buses, it is necessary to grasp the changing law of public transportation short-term passenger flow. This paper builds a short-term passenger flow prediction model for urban public transportation based on the idea of integrated learning. The goal is to use the integrated model to accurately predict the short-term passenger flow of urban public transportation, using Multivariable Linear Regression (MLR), K-Nearest Neighbor (KNN), eXtreme Gradient Boosting (XGBoost), and Gated Recurrent Unit (GRU) as the four seed models, and then use regression algorithm to integrate the model and predict the passenger flow, station boarding and landing, and cross-sectional passenger flow data of the typical representative line 428 in the "Huitian Area" of Beijing from January 1, 2020, to May 31, 2020. Finally, the prediction results of the submodels are compared with those of the integrated model to verify the superiority of the integrated model. The research results of this paper can enrich the short-term passenger flow forecasting system of urban public transportation and provide effective data support and scientific basis for the passenger flow, vehicle management, and dispatch of urban public transportation. [ABSTRACT FROM AUTHOR]

This paper, set against the backdrop of expanding urban rail networks and dynamic urban development, focuses on the distribution and evolution of commercial Points of Interests (POIs) within the central urban rail transit areas of Beijing. The study examines data from four different years—2008, 2013, 2017, and 2020—to observe the temporal evolution of commercial entities. It identifies stable explanatory variables affecting the distribution and evolution of commercial POIs, which include rail transit accessibility, characteristics of the working and residential population distribution around stations, and the construction intensity in the vicinity of station areas. Through statistical analysis and model building, relatively stable linear regression equations were established, with R 2 values generally maintained above 0.5 (except for 2017). The study advances our understanding of the influence of rail transit on urban commercial spaces and how this influence shifts with temporal and urban developmental changes. It elucidates the correlation between changes in the number of businesses and spatial configuration, offering insights and information for urban planners and policy makers. This research also serves as a model for exploring the interplay between urban rail transit and commercial spaces in other major cities. [ABSTRACT FROM AUTHOR]

In urban development, balancing the ecological services of park green space with residents' daily life and recreational needs, achieving sustainable development is an important issue in urban construction. The satellite cities of megacities have large development potential and are suitable research objects. This paper takes the Daxing District of Beijing as the research target and measures the integrated level of supply and demand by selecting unique evaluation indicators by integrating various dimensions and using the improved coupled coordination model and indicators with an expanded selection range at the smallest administrative unit of Chinese community unit scale innovatively. The study shows that: (1) The spatial heterogeneity between the supply and demand of parkland in 85 community units in Daxing New Town is obvious, the overall performance conforms with "demand exceeds supply", and the supply and demand are generally positively correlated. (2) The correlation degree of the matched supply and demand is analyzed, and it is found that 55 community units show a mismatch between supply and demand and 53 community units have a low level of coordinated development. (3) The superposition analysis shows that the comprehensive level of supply and demand decreases from north to south and from the center to the surrounding area. (4) According to the Daxing New City Park Green Space Coupling Coordination Relationship and Policy Document, we divided the community units in Daxing New Town into six types, and provided differentiated development suggestions. The results of the study can help to guide the sustainable construction of Daxing New City and provide a basis for the future construction of satellite cities in other megacities. [ABSTRACT FROM AUTHOR]

Traffic infrastructure safety is a core topic in traffic construction and development. As the impact of global climate change becomes more and more significant, extreme weather brings more and more safety issues to the normal operation of subway systems. Therefore, it is an urgent issue in the construction of subway systems to fully prepare for extreme weather and improve system resilience under external disturbances. The resilience of a complex system generally refers to its ability to adapt to external disturbances and return to a functional state. As one of several key infrastructure systems in large cities, a subway system needs to be highly resilient to cope with various risks, and it needs to recover quickly under uncertain weather conditions and other external damage events. In order to achieve the goal of conducting a real-time resilience assessment of a subway system, this study adopts the Bayesian network and the traditional failure mode and effect analysis (FMEA) method to realize resilience assessment with multiple performance indicators. Combined with the risk matrix method from FMEA, multiple important indicators of a subway system under the influence of extreme weather are obtained. These important indicators are integrated into the resilience assessment of the subway system within a Bayesian method. In this paper, the feasibility and applicability of the proposed method are verified by taking the Changping Line of the Beijing subway under extreme rainfall weather (>10 mm) as a case. [ABSTRACT FROM AUTHOR]

Nighttime PM2.5 detection by remote sensing can expand understanding of PM2.5 spatiotemporal patterns due to wider coverage compared to ground monitors and by supplementing traditional daytime detection. However, using remote sensing data to invert PM2.5 at night is still challenging. Compared with daytime detection, which operates on sunlight, nighttime detection operates on much weaker moonlight and artificial light sources, complicating signal extraction. Moreover, as the attempts to sense PM2.5 remotely using satellite data are relatively recent, the existing nighttime models are still not mature, overlooking many important factors such as stray light, seasonality in meteorological effects, and observation angle. This paper attempts to improve the accuracy of nighttime PM2.5 detection by proposing an inversion model that takes these factors into consideration. The Visible Infrared Imaging Radiometer Suite/Day/Night Band (VIIRS/DNB) on board the polar-orbiting Suomi National Polar-orbiting Partnership (Suomi NPP) and National Oceanic Atmospheric Administration-20 (NOAA-20) was used to establish a nighttime PM2.5 inversion model in the Beijing area from 1 March 2018 to 28 February 2019. The model was designed by first studying the effects of these factors through a stepwise regression, then building a multivariate regression model to compensate for these effects. The results showed that the impact of satellite viewing zenith angle (VZA) was strongest, followed by seasonality and moonlight. Total accuracy was measured using correlation coefficient (R) compared to ground measurements, achieving 0.87 over the urban area and 0.74 over the suburbs. Specifically, the proposed method works efficiently at subsatellite points, which in this case correspond to VZA from 0 and 5°. In spring, summer, autumn, and winter, the R reached 0.95, 0.93, 0.94, and 0.97 at subsatellite points in the urban area, while it was 0.88, 0.82, 0.85, and 0.77 in the suburbs. [ABSTRACT FROM AUTHOR]

The understanding of wind field characteristics during thunderstorms is key to structural design for resistance to thunderstorms. In this paper, the directional thunderstorm wind model is adopted to analyze the characteristics of vertical variations of the wind field in a typical thunderstorm event in the Beijing urban area, based on the measured data. First, the longitudinal and lateral fluctuating wind speed components were decoupled and the change of direction was obtained. Then, variation of the wind speed, wind direction, turbulence intensity, turbulence integral length scale, and gust factor with the height and time were studied. The measured thunderstorm wind spectrum and the coherence function of horizontal longitudinal reduced turbulent fluctuations were analyzed and compared with empirical models. The results showed that the wind speed profile presented an obvious "nose shape" near the peak wind speed. The longitudinal turbulence integral scale was larger than the lateral one. The Von Karman spectrum is relatively effective in fitting the thunderstorm wind spectrum. Compared with synoptic winds, the gust factor during the pass of thunderstorm wind is larger, so it seems necessary to consider the influence of thunderstorm wind in engineering design. [ABSTRACT FROM AUTHOR]

As the most concentrated area of human activities, cities consume many natural resources and discharge a large amount of waste into the natural environment, which has a huge environmental impact. Most of the ecological and environmental problems, such as environmental pollution, global climate change, and loss of biodiversity, are related to urban systems. How to coordinate urban development with the urban ecological carrying capacity is related to the destiny of the city itself, and also to whether its surrounding areas can successfully achieve the goal of high environmental quality and sustainable development. At present, the theory and methods of urban ecological carrying capacity research are relatively new, which has caused problems for policy makers in practical applications. This paper proposes a theoretical framework for urban ecological carrying capacity assessment based on the analysis of ecosystem services supply and demand. Combined with multi-source spatial data and spatial model methods, the supply and demand of ecosystem services were spatially quantified. The capital city of China, Beijing, was the case study area for this research. The spatial differentiation of the supply–demand relationship of ecosystem services is formed. The priority areas for ecological carrying capacity improvement at pixel scale and at the administrative level are obtained, respectively. The results show that the first priority area is concentrated in the center of the urban area, accounting for 31.11% of the total area of Beijing. According to the secondary zone and the specific ecosystem service type, the ecological carrying capacity improvement strategy of different zones is proposed. This study provides a new perspective for investigating urban ecological carrying capacity and for identifying the priority areas for ecological carrying capacity improvement, and helps the policy-makers to design tailored policy actions. [ABSTRACT FROM AUTHOR]

Together with rapid development of location-based services and big-data platforms especially in urban areas, huge amount of spatiotemporal data are collected without properly used; on the other hand, state-of-the-art quantitative policy effect assessment techniques usually require panel data as input. To solve both issues, this paper follows the following approach: obtaining panel data by aggregating spatiotemporal data and feeding them to the effect assessment module. With the help of high-performance computing techniques which are able to deal with huge amount of data, we build framework Aggr-analysis which applies clustering algorithms to shrink the raw data set and find associations between different data sets via co-location analysis. Finally, we prove the effectiveness by an example: analysis of resident activities during the COVID-19 Pandemic. We apply Aggr-analysis to process the share-bike usage data and POI (Point Of Interest) data in Beijing, then obtain the panel data required by DID (Difference-in-Differences) method. Supplemented with environmental data, we conclude the net effect of the COVID-19 breakout on society and economy - the pandemic has reduced the overall resident mobility by 64.8% within two months. [ABSTRACT FROM AUTHOR]

Over the past few decades, due to human activities, industrialization, and urbanization, air pollution has become a life-threatening factor in many countries around the world. Among air pollutants, Particulate Matter with a diameter of less than 2.5 μ m ( P M 2.5 ) is a serious health problem. It causes various illnesses such as respiratory tract and cardiovascular diseases. Hence, it is necessary to accurately predict the P M 2.5 concentrations in order to prevent the citizens from the dangerous impact of air pollution beforehand. The variation of P M 2.5 depends on a variety of factors, such as meteorology and the concentration of other pollutants in urban areas. In this paper, we implemented a deep learning solution to predict the hourly forecast of P M 2.5 concentration in Beijing, China, based on CNN-LSTM, with a spatial-temporal feature by combining historical data of pollutants, meteorological data, and P M 2.5 concentration in the adjacent stations. We examined the difference in performances among Deep learning algorithms such as LSTM, Bi-LSTM, GRU, Bi-GRU, CNN, and a hybrid CNN-LSTM model. Experimental results indicate that our method "hybrid CNN-LSTM multivariate" enables more accurate predictions than all the listed traditional models and performs better in predictive performance. [ABSTRACT FROM AUTHOR]

• We investigate driving forces of different land-use types to BSD. • Diversified machine learnings are proposed for spatial interpolation fusion. • Hotspot detection establishes sampling points for reducing the MAUP effect. • Fusion models improve the interpolation performance: accuracy and stability. • Word clouds identifies predominant facility names in each land-use type. Land use plays a crucial role in promoting the bike-sharing demand. Traditionally, studies on bike-sharing demand (BSD) are mainly focused on its prediction through regression methods, but the influence of MAUP (modifiable areal unit problem) in modeling is ignored. This paper aims to model spatial BSD distribution and prove the driving forces of different land use types to BSD through a machine-learning-based multiple interpolation fusion method. The hotspot detection model is employed to establish sample points covering different land use types in urban areas. In order to capture the differences in adaptations among different urban regions and for different data sizes, six machine learning methods are applied and evaluated to improve BSD estimation by fusing five spatial interpolation algorithms, including Inverse Distance Weight, Spline, Kriging, Natural Neighborhood and Trend. The methodological verification of Beijing City shows that the fusion models improve the estimation performance compared with individual interpolation algorithms, and that GRNN (generalized regression neural network) method is superior to all the others. According to fitting results of all POIs based on the GRNN fusion model, we identify which types of facilities correspond to customers that will have a stronger preference for bike-sharing and demonstrate which facility names are more prominent in each land use type. The conclusions presented here enrich our understanding relationships between land-use and BSD, which provide a valuable foundation for the bike-sharing development. Compared with implementing regression in an analysis zone or a square grid, troubles caused by the MAUP are effectively solved through this method. [ABSTRACT FROM AUTHOR]

The severe land subsidence could lead to ground collapse, building damage and a series of disasters. Up to now, the land subsidence has occurred in more than 50 cities in China, which seriously affects the life and production safety of local people and restricts the development of cities. While, Beijing is one of the most serious cities. This paper takes the urban area of Beijing as an example. PS-InSAR technology is used to process 40 scenes of Terra SAR images from 2010 to 2015, and the high-coherence points are selected by fusing the two algorithms of coherence coefficient and amplitude deviation. In order to verify the reliability of the results, the second-level measurement results are compared with the PS-InSAR deformation results, and five leveling points are used to evaluate the accuracy. The results show that: the maximum absolute error between the Leveling results and the InSAR measurement result is 8.87 mm, and the standard error is 3.22 mm, which meets the accuracy requirements. And areas with serious subsidence occur in Changping District, Haidian District, Daxing District, and Chaoyang District; there is no obvious subsidence trend in the central and eastern parts of Dongcheng, Xicheng and Fengtai District, and the surface is relatively stable. The subsidence in Tongzhou and Shunyi District is serious relatively, the subsidence in these two areas is -6 mm/a~-67 mm/a and -11 mm/a~-22 mm/a respectively. Finally, the spatial relationship between fault zones and land subsidence was preliminarily discussed. The results show that, the subsidence of the south of Changping was so serious than others while the Nankou-Sunhe fault zone crossed with Babaoshan and Huangzhuang-Gaoliying fault zone through this area respectively. [ABSTRACT FROM AUTHOR]

Urban green spaces are increasingly recognized for their positive impact on well-being, quality of life, and public health. Researchers have explored how green space characteristics, such as size, theme, and convenience, influence urban movement. However, an important aspect that has received limited attention is the relative attractiveness of green spaces. When residents have access to similar green spaces nearby, their inclination to visit more distant ones decreases. This leads to the central research question: How does the relative attractiveness of urban green spaces affect urban movements? The existing literature lacks a comprehensive theory to address this question. To bridge this gap, this paper introduces the Potential to Kinetic Energy (PKE) framework, inspired by principles from physics. In this framework, potential energy represents the relative attractiveness of green spaces between the travel origin and destination, while kinetic energy signifies the urban movement resulting from the this attractiveness. To demonstrate the PKE framework's applicability, this paper analyzes green space data and smart card subway ridership records from Beijing. The results show that a unit increase in size, cultural, attraction, proximity, and location potential energy is associated with a 0.22%, 0.27%, 0.14%, 0.19%, and 0.02% increase in urban movement. The findings provide compelling evidence for the significant role of relative attractiveness in shaping urban movements and offer valuable insights for urban planning and policy development. The proposal of the PKE framework encourages interdisciplinary discussions among urban planners, environmental scientists, and transportation experts, fostering collaborative efforts to enhance the sustainability of cities. • A Potential to Kinetic Energy (PKE) framework is introduced to investigate the relationship between green space attractiveness and urban movements. • Potential energy contains five sub-concepts: size, culture, attraction, proximity and location. • Kinetic energy represents urban movement that characterizes the motion of objects resulting from potential energy conversion. • Empirical analysis of Beijing shows the significant role of relative green space attractiveness in shaping urban movement patterns. • The PKE framework supports urban planners to evaluate green space attractiveness, examine the impact of landscape change, and promote inclusive urban environments. [ABSTRACT FROM AUTHOR]

Input-output analysis has been proven to be a powerful instrument for estimating embodied (direct plus indirect) energy usage through economic sectors. Using 9 economic input-output tables of years 1987, 1990, 1992, 1995, 1997, 2000, 2002, 2005, and 2007, this paper analyzes energy flows for the entire city of Beijing and its 30 economic sectors, respectively. Results show that the embodied energy consumption of Beijing increased from 38.85 million tonnes of coal equivalent (Mtce) to 206.2 Mtce over the past twenty years of rapid urbanization; the share of indirect energy consumption in total energy consumption increased from 48% to 76%, suggesting the transition of Beijing from a production-based and manufacturing-dominated economy to a consumption-based and service-dominated economy. Real estate development has shown to be a major driving factor of the growth in indirect energy consumption. The boom and bust of construction activities have been strongly correlated with the increase and decrease of system-side indirect energy consumption. Traditional heavy industries remain the most energy-intensive sectors in the economy. However, the transportation and service sectors have contributed most to the rapid increase in overall energy consumption. The analyses in this paper demonstrate that a system-wide approach such as that based on input-output model can be a useful tool for robust energy policy making. [ABSTRACT FROM AUTHOR]

As the capital and one of the metropolises in China, Beijing has met with a number of serious so-called "urban diseases" in the process of rapid urbanization such as blind expansion of urban areas, explosion of population and the increase of urban heat island effect. To treat these "urban diseases" and make the metropolis develop healthful and sustainable in Beijing in the future, the spatial characteristics of metropolis developments in Beijing are explored in this paper. The urban built-up areas in Beijing are extracted using the DMSP-OLS nighttime light data from 1992 to 2013. The characteristics of the urban developments of Beijing are studied, including spatial and temporal scales of urban developments, urban barycenter of Beijing and its transfer trajectory, variations of urban spatial forms and the differences of urban internal developments. The results have shown that the built-up areas had been increasing and circling extending from the central urban areas to the outer spaces in the last 21 years. The built-up area had expanded by 878km2 in 1992–2013, and the built-up area in 2013 had expanded to three times comparing to that of 1992. The expanding area of the built-up area in the northeast is the largest. The expansion of the urban had mainly occurred in 1996–2007, and the expanded area had accounted for 92% of the total research period. During the whole research period, the urban barycenter of Beijing had moved 5000.71 meters towards Northeast 28° of its original place from Dongcheng District to Chaoyang District. The development level of each municipal district had been increasing year by year, and the development differences among the municipal districts had been gradually reduced; the spatial forms of Beijing had been alternately changed between extensive and intensive expansion. The results of this study can help to plan urban land use and people migration of Beijing. [ABSTRACT FROM AUTHOR]

The metro system is an important component of the urban transportation system due to the large volume of transported passengers. Hub stations connecting metro and high-speed railway (HSR) networks are particularly critical in this system. When HSR trains are delayed due to a disruption on the HSR network, passengers of these trains arriving at the hub station at night may fail to get their last metro connection. The metro operator can thus decide to schedule extra metro trains at night to serve passengers from delayed HSR trains. In this paper, we consider the extra metro train scheduling problem in which the metro operator decides how many extra metro trains to dispatch and their schedules. The problem is complex because (i) the arrival of delayed HSR trains is usually uncertain, and (ii) the operator has to minimize operating costs (i.e., number of additional trains and operation-ending time) but maximize the number of served passengers, which are two conflicting objectives. In other words, the problem we consider is stochastic and biobjective. We formulate this problem as a two-stage stochastic program with recourse and use an epsilon-constrained method to find a set of nondominated solutions. We perform extensive numerical experiments using realistic instances based on the Beijing metro network and two HSR lines connected to this network. We find that our stochastic model outperforms out-of-sample a deterministic model that relies on forecasts of the delay by a range of 3–5%. Moreover, we show that our solutions are nearly optimal by computing a perfect information dual bound and obtaining average optimality gaps below 1%. [ABSTRACT FROM AUTHOR]

Two global cities of China, Beijing and Shanghai, have completely different development statuses with their hinterlands. There is a large economic development gap between Beijing and its hinterland, Hebei Province, while Shanghai has formed a highly integrated region with its hinterland, the Yangtze River Delta. According to the Outline of Collaborative Development of Beijing, Tianjin, and Hebei Province, enterprise linkages between Beijing and Hebei should be strengthened in order to narrow the economic gap between the center and the hinterland. On this basis, this paper proposes two hypotheses. (1) The economic gap between Beijing and Hebei has not really changed, because more enterprise linkages of Beijing are nonlocal. (2) The gradual narrowing of the economic gap between Shanghai and Jiangsu as well as Zhejiang is due to the fact that more enterprise linkages of Shanghai are local. We have used enterprise data on business registration from the State Administration for Industry and Commerce of China and have selected two indicators, namely, the number of headquarters-branches offices and the amount of enterprise investment, to examine the enterprise linkages between Beijing/Shanghai and their hinterlands as well as the hinterworld, and have verified these two hypotheses. The results show that nonlocal enterprise linkages based on the hinterworld are the main form in Beijing, while local enterprise linkages based on the hinterland are the main form in Shanghai. In addition, we have analyzed the mechanisms of formation of the enterprises linkages of the two cities and have put forward some policy suggestions. [ABSTRACT FROM AUTHOR]

Surface albedo is a crucial parameter in land surface radiation budget. As bias exists between the model simulated and observed surface albedo, data assimilation is an important method to improve the simulation results. Moreover, surface albedo is associated with the wavelength of the sunlight. So, solar radiation partitioning is important to parameterize the surface albedo. In this paper, the moderate resolution imaging spectroradiometer- (MODIS-) retrieved direct visible, direct near-infrared, diffuse visible, and diffuse near-infrared surface albedos were assimilated into the integrated urban land model (IUM). The solar radiation partitioning method was introduced to parameterize the surface albedo. Based on the albedo data from MODIS and the solar radiation partitioning method, the surface albedo data set for the Beijing municipal area was generated. Based on the surface albedo data set and the IUM, the impacts of the surface albedo on the surface radiation budget were discussed quantitatively. Surface albedo is inversely proportional to the net radiation. For urban areas, after assimilation, the annual average net radiation decreases about 5.6%. For cropland, grassland, and forest areas, after assimilation, the annual average net radiations increase about 20.2%, 24.3%, and 18.7%, respectively. [ABSTRACT FROM AUTHOR]

With the recent emergence of big data, there has been significant progress in the study of big data mining and rapid developments in urban computing. With the integration of planning and management in urban areas, there is an urgent need to focus on the identification of urban functional areas (UFAs) based on big data. This paper describes the concept of communication activity intensity, which is more meaningful than the number of communication activities or the user density in identifying UFAs. The impact of diverse geographical area subdivisions on the accuracy of UFA recognition is discussed, and a k-means clustering method for dynamic call detail record data and kernel density estimation technique for static point of interest data are established at the traffic analysis zone level. A case study on the region within Beijing's 3rd Ring Road is conducted, and the results of UFA identification are qualitatively and quantitatively verified. The causes of large passenger flows on certain metro lines in Beijing are also analyzed. The highest identification accuracy is obtained for park and scenery areas, followed by residential areas and office areas. In conclusion, the proposed method offers a significant improvement over the identification accuracy of previous techniques, which verifies the reliability of the method. [ABSTRACT FROM AUTHOR]

As urbanization speeds up, the concept of healthy cities is receiving more focus. This article compares Chongzuo and Nanning in Guangxi with Beijing to assess the development gaps in cities in Guangxi. An indicator system for healthy cities was designed from six dimensions—healthy economy, healthy population, healthy healthcare, healthy environment, healthy facilities, and healthy transportation—and 26 secondary indicators, which were selected from 2005 to 2022, and an improved factor analysis was used to synthesize a healthy city index (HCI). The number of factors was determined by combining characteristic roots and the variance contribution rate, and the HCI was weighted using the entropy-weighted Topsis method. A comprehensive evaluation of the urban health status of these cities was conducted. The results showed that extracting six common factors had the greatest effect, with a cumulative variance contribution rate of 93.83%. Chongzuo city scored higher in the field of healthcare. The healthy environment score of Nanning was relatively high, which may be related to continuous increases in green measures. In terms of the healthy economy dimension, Beijing was far ahead. However, in recent years, the healthy economy level in Chongzuo has increased, and the GDP growth rate has ranked among the highest in Guangxi. In addition, the growth rate of healthy facilities in Nanning was relatively fast and has been greater than that in Chongzuo in recent years, which indicates that the Nanning Municipal Government believes urban construction and municipal supporting facilities are highly important. In terms of healthy transportation, Chongzuo and Nanning scored higher than Beijing. This may be because the transportation in these two cities is convenient and the traffic density is more balanced than that in Beijing, thereby reducing traffic congestion. Chongzuo had the highest score for a healthy population, and a steadily growing population provides the city with stable human resources, which helps promote urban economic and social development. Finally, relevant policy recommendations were put forwards to enhance the health level of the cities. [ABSTRACT FROM AUTHOR]

In recent years, the development of China's megacities has entered the stage of stock renewal. Research and practice concerning old city renewal in cities with a long history, represented by Beijing, has also become a hot spot for researchers and designers in the fields of urban planning, architecture and landscape architecture. As one of the main spatial components of the old city, Beijing's traditional quadrangles are closely related to the spatial perception and emotional experience of citizens and tourists due to their near-human scale characteristics. However, current research focuses more on the evaluation of the historical value of the quadrangles in the early stage of renovation and the specific design and construction methods in the process of renovation, and few studies pay attention to the characteristics of the built environment that promote the emotional experience of users after renovation is completed. Under these circumstances, the study focuses on the emotional attachment between people and the spatial composition and built environment characteristics of the renovated traditional Beijing quadrangles; the avant garde small-scale quadrangle renovation type, which has a wider coverage, more types of user, and pays more attention to people's emotional experience in the renovated space, was selected as the research object. Four typical quadrangle cases were selected for in-depth discussion. Based on the theory of emotional attachment from a multidisciplinary perspective, this study constructed a series of scales that can measure the degree and dimension of emotional attachment between people and the built environment, coupled with local observation and interviews, to obtain multi-dimensional data reflecting attachment, and used SPSS to conduct correlation analysis and exploratory factor analysis to quantitatively explore the effects of different built environment characteristics on attachment. The results show that: (1) As for the material characteristics, the organic integration of traditional and modern materials, structures and colors can effectively enhance people's positive emotional experience and promote the establishment of emotional attachment. The combination of these characteristics and the process of people's three-dimensional spatial experience can further enhance the degree of attachment. In addition, the consistency of materials and technologies, the organic integration of the old and the new, and the carrying capacity of the renovation method for traditional history and culture are the basis for promoting this kind of emotional attachment, which needs to be further explored and considered. (2) As for the non-material characteristics, the diverse, variable, recognizable, unique, and digital spatial function settings that respond to changes in people's need and current developments can significantly promote the establishment of emotional attachment between people and the environment. This further emphasizes the importance of positioning the space in the early stage of the renovation and the operation of the space in the later stage. (3) The results further support the validity and rationality of the series of scales constructed in this study in quantitatively measuring the attachment characteristics between people and the built environment. As a result, the study provides a reference for emotion-oriented design means, research logic and quantitative evaluation methods in the practice and research of urban renovation and renewal in the future. [ABSTRACT FROM AUTHOR]

The coordinated development of urban public infrastructure system and urban economic, social, and environmental system is an important goal for the integrated management and sustainable development of urban public infrastructure system. This paper constructs a research model of the degree of coupling coordination between urban public infrastructure system and urban economic, social, and environmental system using the analytic network process (ANP), the analytic hierarchy process (AHP), a combination evaluation method based on game theory, and a coupling coordination degree model. Using Beijing data from 2000 to 2016, the degree of coupling coordination between the Beijing urban public infrastructure system and the urban economic, social, and environmental system is empirically analyzed. This study finds that (1) the supply level of Beijing's urban public infrastructure system has an obvious impact on the degree of coupling coordination between the two systems. (2) The global financial crisis reduced the supply speed of the urban public infrastructure system in Beijing, and put the dynamic coupling state of the two systems in the low-level symbiosis stage. Beijing needs to improve the supply of urban public infrastructure to support the development of the urban economic, social, and environmental system. (3) Improving the supply level of the urban environmental infrastructure in Beijing, especially improving sewage disposal capacity and increasing the number of special vehicles for urban sanitation and the amount of domestic waste clearance, will positively affect the degree of coupling coordination between two systems. (4) An increase in the GDP of Beijing has a direct positive impact on the degree of coupling coordination. In addition, the increase in the social development level of the employees in three industries in Beijing has a significant impact on the degree of coupling coordination. [ABSTRACT FROM AUTHOR]

The construction of metropolitan area gives urban rail transit a new historical mission, and the construction of regional express line is the development direction of urban rail transit in the future. The demand of vehicle operation and maintenance of regional express line is different from that of subway and intercity railway, and the relevant standards and specifications of regional express line construction are lack of practical engineering verification. Based on the analysis of the general situation of Daxing Airport Line Project, the main technical parameters of key vehicle equipment, the status of routine maintenance and repair of vehicles, and the collected data of wheel-set from online detection equipment, this paper optimizes the vehicle maintenance standards of Daxing Airport Line, presents vehicle maintenance and maintenance standards, which takes train technical inspection, monthly inspection as routine maintenance and scheduled repair, and un-wheeling repair (A, B) and overhaul as regular overhaul, and analyzes the economic benefits under the new vehicle maintenance standards, with reference to the requirements of vehicle suppliers, the technical level of domestic vehicle components and the industry's experiences in maintenance. The implementation of the new standards can effectively control the construction scale of vehicle base, reduce the cost of vehicle operation and maintenance, and improve vehicle utilization rate, thus providing a theoretical basis for the construction of regional express vehicle base of urban rail transit and the network resource sharing in the future. [ABSTRACT FROM AUTHOR]

Understanding human movement patterns is crucial for comprehending how a city functions. It is also important for city planners and policymakers to create more efficient plans and policies for urban areas. Traditionally, human movement patterns were analyzed using origin–destination surveys, travel diaries, and other methods. Now, these patterns can be identified from various geospatial big data sources, such as mobile phone data, floating car data, and location-based social media (LBSM) data. These extensive datasets primarily identify individual or collective human movement patterns. However, the impact of spatial scale on the analysis of human movement patterns from these large geospatial data sources has not been sufficiently studied. Changes in spatial scale can significantly affect the results when calculating human movement patterns from these data. In this study, we utilized Weibo datasets for three different cities in China including Beijing, Guangzhou, and Shanghai. We aimed to identify the effect of different spatial scales on individual human movement patterns as calculated from LBSM data. For our analysis, we employed two indicators as follows: an external activity space indicator, the radius of gyration (ROG), and an internal activity space indicator, entropy. These indicators were chosen based on previous studies demonstrating their efficiency in analyzing sparse datasets like LBSM data. Additionally, we used two different ranges of spatial scales—10–100 m and 100–3000 m—to illustrate changes in individual activity space at both fine and coarse spatial scales. Our results indicate that although the ROG values show an overall increasing trend and the entropy values show an overall decreasing trend with the increase in spatial scale size, different local factors influence the ROG and entropy values at both finer and coarser scales. These findings will help to comprehend the dynamics of human movement across different scales. Such insights are invaluable for enhancing overall urban mobility and optimizing transportation systems. [ABSTRACT FROM AUTHOR]

Exploring urban spatial structures through spatial coupling analysis methods is an important method to provide theoretical support for the construction of sustainable urban structures. In order to make up for the neglect of POI species differences in previous studies, information entropy was introduced to calculate POI confusion, and a comprehensive POI index was constructed by combining kernel density and the entropy weight method; impervious surface coverage was extracted based on land cover data. The spatial distribution of the Beijing–Tianjin–Hebei urban agglomeration and some typical cities was analyzed by coupling two types of data using the dual-factor mapping method. The research indicates the following: (1). The spatial distribution of the two sets of data in the Beijing–Tianjin–Hebei region is highly consistent, indicating a state of high spatial coupling; Beijing has the highest proportion of coupling in the same region at the city level (73.39%). (2). The areas with different coupling of the two types of data are mainly distributed in the urban fringe areas transitioning from the city center to the suburbs, as well as in large-scale areas with single functionality such as airports, scenic spots, and ports. This study shows that analysis combining the POI comprehensive index and impervious surface coverage can effectively characterize urban spatial structure characteristics, providing a new perspective for the study of the spatial structure of the Beijing–Tianjin–Hebei urban agglomeration. It is of great significance for a deeper understanding of the laws of urban agglomeration spatial structures and guiding the coordinated development of the Beijing–Tianjin–Hebei urban agglomeration. [ABSTRACT FROM AUTHOR]

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided. [ABSTRACT FROM AUTHOR]

Purpose: Retailers have recently leveraged store-loyal customers' store attachment to maintain customer relationships and motivate patronage intentions. However, the COVID-19 outbreak has driven customer migration from offline to mobile channels. Mobile retail applications (APPs) have been used by numerous retailers to reach their customers. Nonetheless, it has yet to be determined (1) whether store attachment can facilitate (or impede) the adoption of mobile retail APPs and (2) whether store-loyal customers will continue visiting offline stores in the post-pandemic era. To address these questions, we propose a theoretical account using integrated theories on trust transfer and store attachment. Design/methodology/approach: We conducted multi-stage, longitudinal field surveys in two cities of mainland China: Beijing and Guangzhou. From two rounds of data collection, 237 and 103 responses were obtained in March 2022. Hypotheses were tested by partial least squares – structural equation modelling (PLS–SEM). Findings: Results showed that customer trust in an offline retailer can be transferred to the retailer's mobile APP at the pre-adoption stage, facilitating APP adoption. Notably, store-loyal customers who exhibited a strong attachment to the physical store of a retailer were more inclined to transfer their trust to the mobile APP of the retailer. This occurrence leads to an increased adoption rate, enhanced post-adoption satisfaction and increased inclination to continue (rather than discontinue) usage. Originality/value: This study is the first to investigate the changes in store-loyal customers' shopping behaviour in the mobile retail era and in the post-COVID-19 pandemic recovery. Our findings elucidate the role of physical store attachment in the trust-transfer mechanism. Furthermore, store attachment may not prevent customers' channel migration behaviour. Retailers may have to re-consider how to manage channel cannibalisation issues in the post-pandemic recovery. [ABSTRACT FROM AUTHOR]

The city of Beijing has increasingly been re-integrated with the world since the 1980s, thereby entering into closer, but more complex relationships with the global system. To understand the implications for urban planning, it is important to appreciate that Beijing is handling these global-local relationships amid delicate 'local' relationships with the Chinese state, in ways that are obviously different from those of the West. The objective of this paper is to throw light on how new global and local forces have infl uenced planning in Beijing, fi rst by understanding the nature of urban government in Beijing and then by examining master plans for the city. From a Foucauldian perspective, it tries to describe state practices, including urban planning, of the Chinese governmentality. It focuses on the effectiveness of government during this new era, taking into account non-state practices, including those adopted from the outside world. It argues that the state needs to invent new toolkits and conceive urban problems differently to cope with these new forces. The paper illustrates this argument by investigating the formulation of the two master plans for Beijing, the 1954 and 2005 Plans, and documents how the latter has been updated to incorporate these new global and local forces. It concludes that there is no uni-directional interaction between global and local. [ABSTRACT FROM AUTHOR]

The intensification of global heat wave events is seriously affecting residents' emotional health. Based on social media big data, our research explored the spatial pattern of residents' sentiments during heat waves (SDHW). Besides, their association with urban functional areas (UFAs) was analyzed using the Apriori algorithm of association rule mining. It was found that SDHW in Beijing were characterized by obvious spatial clustering, with hot spots predominately dispersed in urban areas and far suburbs, and cold spots mainly clustered in near suburbs. As for the associations with urban function areas, green space and park areas had significant effects on the positive sentiment in the study area, while a higher percentage of industrial areas had a greater impact on negative SDHW. When it comes to combined UFAs, our results revealed that the green space and park area combined with other functional areas was more closely related to positive SDHW, indicating the significance of promoting positive sentiment. Subdistricts with a lower percentage of residential and traffic areas may have a more negative sentiment. There were two main combined UFAs that have greater impacts on SDHW: the combination of residential and industrial areas, and the combination of residential and public areas. This study contributes to the understanding of improving community planning and governance when heat waves increase, building healthy cities, and enhancing urban emergency management. [ABSTRACT FROM AUTHOR]

Promoting sustainable development in manufacturing is a paramount goal, with a focus on advancing green innovation. This study constructs a system for evaluating green innovation efficiency and employs the Super-EBM model, incorporating unexpected output, to assess the efficiency of green innovation in 13 cities across the Beijing-Tianjin-Hebei region from 2011 to 2020. The study further conducts dynamic analysis using the Malmquist-Luenberger index. Results reveal that, statically, the overall green innovation efficiency in the manufacturing industry of the Beijing-Tianjin-Hebei region is inefficient. There exists a considerable gap in green innovation efficiency among Beijing, Tianjin, and Hebei, with Beijing and Tianjin demonstrating superior performance compared to Hebei. Substantial variations exist in the green innovation efficiency of manufacturing across different cities in the Beijing-Tianjin-Hebei region. Only Beijing, Qinhuangdao, and Baoding achieve DEA-effective green innovation efficiency in the manufacturing industry, while the other cities do not. Dynamically, the green innovation efficiency of the manufacturing industry in the Beijing-Tianjin-Hebei region is on the rise. There is a varying degree of improvement in green innovation efficiency in Beijing, Tianjin, and Hebei, with Hebei showing the highest improvement, Tianjin ranking second, and Beijing having the least improvement. With the exception of Langfang and Hengshui, the green innovation efficiency in the manufacturing industry is improving in most cities in the Beijing-Tianjin-Hebei region, with Hebei witnessing the most significant improvement. This study aims to integrate "environmental pollution" into the evaluation index system for green innovation efficiency. It assesses green innovation efficiency in the manufacturing industry of the Beijing- Tianjin-Hebei region, considering both static and dynamic perspectives. This clarification offers insights into the level of green innovation, contributing valuable information for the advancement of high-quality development in the regional manufacturing industry. [ABSTRACT FROM AUTHOR]

Expressways in urban agglomerations are important in connecting cities, thus attracting great attention from researchers in the expressways risk assessment. However, there is a lack of safety assessment models suitable for the characteristics of expressways in Chinese urban agglomerations, and the nature and mode of dynamic risks on Chinese highways are still unclear. Therefore, this study adopts the Adaptive Neural Fuzzy Inference System (ANFIS) and the method of decision tree, combined with data from the Beijing section of the Beijing Harbin Expressway, to model the risk of accident-prone highways in urban agglomerations. To determine the optimal model, we evaluated the model's bias at different time intervals. In addition, key factors affecting highway safety were analyzed, providing scientific support for the risk prevention of highways in urban agglomerations in China. [ABSTRACT FROM AUTHOR]