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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]

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]

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]

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]

As development progresses over time and changes in the environment take place, carbon finance development has become a very interesting research topic for many scholars worldwide. This paper proposes a hybrid MCDM method that combines the distance solutions of the TOPSIS and VIKOR methods. The contribution of this paper combines TOPSIS and VIKOR, incorporating AISM models to obtain the development ranking of Chinese carbon finance pilot cities as related to the Chinese carbon finance development pilot provinces and cities. The conclusion notes that Guangdong and Beijing are the most preferred investment locations for carbon investors. In addition, technological innovation, financial sector development, and an active ETS market can effectively drive the level of local carbon finance. Additionally, the MCDM methodology in this paper provides new ideas in environmental and economic development assessment. [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]

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]

Urban rail transit emergencies in China's large cities are frequent occurrences but currently, operation managers lack effective analysis tools that can help in reducing them. In this study we present a knowledge graph tool, developed using historical emergency text information from Beijing's urban rail transit fault logs from which an information model is developed enabling key information to be mined and subsequently analyzed so that interrelationships within the text can be determined. The knowledge graph tool assists urban rail transit operation managers to analyze more effectively, through knowledge query and semantic search, the relations and attributes of emergencies enabling more insight into their root causes. Compared with traditional first and second order text parsing algorithms, the extended high order parsing algorithm proposed in this paper has better performance in the extraction of both phrases and inter-phrase relations, with an extraction accuracy of more than 85%. Furthermore, compared with traditional failure mode effect analysis methods, the extended method proposed in this paper can also calculate phrase attributes and therefore provide a reference for quantitative risk calculations. [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]

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]

In this paper, we empirically study the spatial association network of PM2.5 and the factors influencing those correlations using the gravity model, social network analysis (SNA), and the quadratic assignment procedure (QAP) based on data from the Beijing–Tianjin–Hebei urban agglomeration (BTHUA) in China from 2005 to 2018. We draw the following conclusions. First, the spatial association network of PM2.5 exhibits relatively typical network structure characteristics: the network density and network correlations are highly sensitive to efforts to control air pollution, and there are obvious spatial correlations within the network. Second, cities in the center of the BTHUA have large network centrality values, while cities in the peripheral region have small centrality values. Tianjin is a core city in the network, and the spillover effect of PM2.5 pollution in Shijiazhuang and Hengshui is the most noticeable. Third, the 14 cities can be divided into four plates, with each plate having obvious geographical location characteristics and linkage effects. The cities in the association network are divided into three tiers. Beijing, Tianjin, and Shijiazhuang are located in the first tier, and a considerable number of PM2.5 connections are completed through these cities. Fourth, differences in geographical distance and urbanization are the main drivers of the spatial correlations of PM2.5. The greater the urbanization differences, the more likely the generation of PM2.5 links is, while the opposite is true for differences in geographical distance. [ABSTRACT FROM AUTHOR]

In this paper, an improved aerosol optical depth (AOD) retrieval algorithm is proposed based on Sentinel-2 and AErosol RObotic NETwork (AERONET) data. The surface reflectance for AOD retrieval was estimated from the image that had minimal aerosol contamination in a temporal window determined by AERONET data. Validation of the Sentinel-2 AOD retrievals was conducted against four Aerosol Robotic Network (AERONET) sites located in Beijing. The results show that the Sentinel-2 AOD retrievals are highly consistent with the AERONET AOD measurements (R = 0.942), with 85.56% falling within the expected error. The mean absolute error and the root-mean-square error are 0.0688 and 0.0882, respectively. In addition, the AOD distribution map obtained by this algorithm well reflects the fine-spatial-resolution changes in AOD distribution. These results suggest that the improved high-resolution AOD retrieval algorithm is robust and has the potential advantage of retrieving high-resolution AOD over urban areas. [ABSTRACT FROM AUTHOR]

As an important urban infrastructure, rail transit not only has transportation function, but also has a close connection and harmonious development with the surrounding urban space. Taking Beijing Metro Line 5 as an example, each station of Beijing Metro Line 5 was analyzed by GIS software and Echarts chart based on POI data. The functions of subway site type were divided into main function, secondary function and no signifi cant function, and various types of sites within the main functional characteristics of urban functions were discussed in details. The paper presents a new method for identifying urban functional features, which can be applied to not only other metro stations in Beijing but also the same type of cities. Moreover, it lays a foundation for the research of rail transit subway stations and their related researches. [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]

The daily home-office commute of millions of people in crowded cities strains air quality and increases travel time, which motivates the generation of ridesharing. Ridesharing offers many benefits, such as reducing travel costs, congestion, and pollution. Commuter ridesharing is an important theme of urban transportation. This paper studies a ridesharing problem aiming at enlarging the ridesharing market at a limited cost, which enlighten the decision-making problem in city logistics. We establish a novel multi-objective optimisation model based on cumulative prospect theory (CPT) to address the preferred travel mode of commuters. The commuters' perceived value influences their choice of travel mode. Meanwhile, the perceived value changes with the commuters' experience of travel mode choice. We give the NP-hardness proof of the ridesharing scheduling problem and develop a heuristic algorithm to solve it in a small-scale scenario. For large-scale problems, a hybrid VNS-NSGAII algorithm combining variable neighbourhood search (VNS) with NSGAII (Non-dominated Sorting Genetic Algorithm II) is proposed to generate an approximate optimal Pareto front. A series of computational experiments are conducted to demonstrate the effectiveness and efficiency of the proposed algorithm based on the actual traffic data in Beijing, China. [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]

• 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]

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]

This paper attempts to answer the question: How can community micro-regeneration projects in Chinese cities be situated and contextualized as particular kinds of practices to build resilient communities? Amidst rapid urbanization and social transformation over the past four decades, historical areas in Chinese cities have faced neglect, exacerbating inequalities and marginalization. The emerging strategy of micro-regeneration, emphasizing public participation and co-production, addresses this issue by revitalizing small community spaces using local resources and empowering grassroots efforts. This research contextualizes micro-regeneration within the global discourse on community resilience, highlighting communities’ agency and collaborative strength in adapting to change. Through the analysis of co-productive micro-regeneration cases in Beijing and Shanghai, this study offers insights into resourcefulness and the transformative potential of resilience, shedding light on China’s urban regeneration shift toward co-production and heightened social focus. [ABSTRACT FROM AUTHOR]

This paper investigates the life experiences of creative expats and the associated impact of, and on, the built environment of their host localities. Grounded on participants' testimonies, we develop the concept of transient mentality as a potential mediating factor in-between such reciprocal relations. Employing an interview and survey-based research approach and drawing on grounded theory for data collection and analysis in Beijing, China, we found that the prevalence of a transient mentality among creative expats is influenced by the nature of their occupations, the fluidity of their social relationships, and the rapid transformations in the built environment. This transient mentality, in turn, affects the production of the cityscape through the consumption preferences of these expats. We argue that understanding such a transient mentality is crucial for urban planning and cultural policy, particularly in (emerging) global cities that work to brand themselves as international creative hubs. [ABSTRACT FROM AUTHOR]

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 the first-tier cities, subway has become an important carrier and life focus of people's daily travel activities. By studying the distribution of POIs of public service facilities around Metro Line 10, using GIS to quantitatively analyze the surrounding formats of subway stations, discussing the functional attributes of subway stations, and discussing the distribution of urban functions from a new perspective, this paper provided guidance and advice for the construction of service facilities. [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]

Given that PM2.5 concentration is not only related to local pollutants, but also affected by long-distance transmission of PM2.5 in adjacent areas, the key to improving the prediction accuracy of PM2.5 concentration is to comprehensively consider the effect of local influencing factors and the transmission effect of PM2.5 in adjacent areas. For this purpose, a novel seasonal discrete multivariable grey prediction model, encompassing spatial influencing factors, has been established. Firstly, we analyze the mechanism of spatial influencing factors and the reasonableness of using PM2.5 concentration in adjacent areas as the spatial influencing factors. Secondly, based on the spatial agglomeration characteristics of PM2.5 concentration, the K - means clustering algorithm is used to cluster adjacent cities with similar PM2.5 concentration, then the comprehensive value of PM2.5 concentration in each city cluster is calculated by weighted average combination. On this basis, a driving term of spatial influencing factors and a cosine trigonometric function term are introduced into the novel model to characterize the effect of spatial influencing factors on PM2.5 concentration and the seasonal fluctuation of itself, respectively. More importantly, the Genetic Algorithm Toolbox is employed to optimally determine the emerging parameters of this model, and the time response function of the novel model is calculated by mathematical induction method. Lastly, the new model is deemed valid through testing its PM2.5 concentration predictions for the cities of Beijing, Tianjin, and Baoding in the Beijing-TianjinHebei region. Based on the original observations from 2018Q1 to 2023Q2, the novel model is built for PM2.5 concentration prediction in 2023Q3 to 2024Q2 for the three cities. The findings imply that the newly developed model outperforms its competitors significantly and has the potential to serve as a robust tool for predicting PM2.5 concentration. [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]

Copyright of Journal of Beijing Institute of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office 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.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office 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.)

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 long as maps produced by the official Chinese state mapping agency at scales larger than 1:1,000,000 remain inaccessible, Soviet General staff maps provide the best alternative. Although toponyms are given only in cyrillicized form, vernacular script equivalents may be found on pre-1945 Japanese military survey maps as well as on some maps of the US Army Mapping Service (AMS). A unique feature of the Soviet 1:200,000 map series is the accompanying spravka or descriptive text on the reverse of each sheet, probably constituting in aggregate the most detailed description of China ever compiled. Soviet General Staff plans of Chinese cities include 'objects' of military significance, many of which are omitted or not identified on any other mapping. This paper presents translations of the spravka from a representative sheet of the 1:200,000 series and from the city plan of Beijing, together with an evaluation of the reliability of their content. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department 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.)

• This paper takes Beijing as a case to study regional economic resilience. • We systematically explore the effects of COVID-19 on industrial dynamics. • Individual-owned firms located in high-risk regions are more vulnerable. • The epidemic shock leads to cascading effects among the local industrial network. The COVID-19 epidemic has altered the economic geographies of cities. However, the academic focus on urban industries and their structural dynamics is far from enough. In this paper, we integrate literature from economic geography, business studies and network sciences, and design an adaptation framework to theorize urban economic resilience. Taking the COVID-19 outbreak in Xinfadi, Beijing during the summer of 2020 as a case study, we use Logit regressions and DID estimations to identify the impacts of the epidemic on local industrial dynamics. Our results support that the COVID-19 outbreak significantly increases the number of business exits. The negative impacts are concentrated in high-risk regions, pointing to specific industries and individual-owned firms. Furthermore, we use a machine learning method to visualize the dynamics of industry networks in a small-scale urban area, and then simulate the transmission paths of industry-failure. In doing so, we contribute to current economic resilience literature that firm-level adaptation and industrial dynamics complement regional adaptation theory, while the cascading effects in the industry network underpin the micro foundations of resilience formation. [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]

Beijing Municipal Administrative Center (Beijing MC) in Tongzhou District has inherited the non-capital core functions of Beijing's central urban area, and its rapid construction and development urgently require a scientific understanding of the pattern of land use evolution in the region. This paper analyzes the pattern of land use evolution in Tongzhou District over the past 40 years, from 1980 to 2020. According to the historical evolutionary characteristics of land use and urban development planning goals, combined with the driving factors of cultural tourism development, the Future Land-use Simulation (FLUS) model is used to simulate the spatial distribution of land use in Beijing MC (Tongzhou District) in 2035 under three scenarios of urbanization acceleration, deceleration and sustainable development. The results show three major trends. (1) Beijing MC (Tongzhou District) is dominated by urban development and construction. During the high-speed urbanization stage from 1980 to 2010, the urban expansion pattern of "along the Sixth Ring Road and along the Grand Canal" was formed. During the low-speed urbanization stage from 2010 to 2020, the land distribution was stable, and Tongzhou District formed a pattern of urban-rural differentiation and land intensification from northwest to southeast. As a typical area of Tongzhou District's urbanization, Beijing MC has the same characteristics of the temporal and spatial evolution as Tongzhou as a whole. (2) By 2035, there are significant differences in land use among the three scenarios with respect to the magnitude of change and spatial distribution. The area and distribution of ecological land under the urban sustainable development scenario are optimal, which is conducive to the realization of sustainable urban development. In analyzing the degree of conformity with the three Beijing MC zoning plans, the prediction simulation under the sustainable development scenario is highly consistent with the land use of the "Beijing Municipal Administrative Center Regulatory Detailed Planning (Block Level) (2016–2035)" (hereinafter referred to as "Planning") issued by the municipal government. However, there are certain deviations between the simulation predictions in the cultural tourism function area and the livable living scenery area and the corresponding "Planning" expectations. During the urban construction process, the internal ecological land area still needs to be increased. (3) Tongzhou District may lack a close connection between the urban and rural areas in the southeast. Potential risks such as the imbalance in the development of northern and southern townships require further attention in the development process. The prediction and simulation results of the model can provide certain data and methodological support for the construction of a harmonious and livable city in Beijing MC (Tongzhou District). [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality quickly and deal with urban greenhouse effect, it is necessary to study the energy consumption of urban buildings. Energy consumption prediction is an important step in planning and managing energy use in buildings. At present, few studies have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings in urban built-up areas. In this paper, a spatial data-driven framework is introduced for the analysis and assessment of building energy consumption. The framework is grounded in the building centroid and is combined with single photon radar and point of interest data through the utilization of the nearest neighbor classification algorithm. Two megacities, Beijing and Shanghai, are taken as examples to illustrate the method and to generate the regional building energy use database. The results show that: a) building physical feature (geometric form, functional type) have a significant impact on energy consumption, and energy consumption is correlated with the economic level of the region; b) Energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphon effect is obvious in region with high energy consumption. The contribution of the framework is to provide insights into the feasibility of employing multiple spatial data fusion for the analysis of energy consumption within urban built-up areas. This can be employed to address energy planning concerns and help promote sustainable environmental practices in urban areas worldwide. • This paper attempts to provide a feasible framework for analyzing urban building energy use by utilizing real-time urban semantic perception information and building features. • The proposed framework have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings. • The proposed methodology can obtain regional energy consumption stocks and produce spatial distribution results, thus improving the interpretability of the data. • The results show that energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphoning effect is obvious in regions with high energy consumption. [ABSTRACT FROM AUTHOR]

Against the background of the international dialogue and action agendas regarding climate change and the protection of biodiversity, China has embarked during the past years on a new urbanisation approach, gradually advancing from an era of high-speed sprawl to one of more high-quality, green and low-carbon city development. Several national policies and strategies have been put in place, which are consequently rolled out at the sub-national level in provinces and cities. Energy efficiency in urban areas, nature-based solutions and new green ecological site developments are particularly important planning priorities fuelling the national government's ambition to transform cities to be more liveable and sustainable. Further priorities are digitalisation and smart city approaches, as well as responding to COVID-19 implications in the sense of 'green recovery'. This paper summarises the low-carbon development policy framework in China and provides three case studies of selected projects from the capital city, Beijing. [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]

Taking Beijing's Songzhuang Art District as an example, this paper conducts an integrated evolutionary and multi-scalar governance analytical framework through participant's observations, in-depth qualitative interviews, and extensive evaluations of policy documents. It aims to explore the transformation modes of art districts under the intervention of multi-scalar spatial governance and the roles of local governments in the course of development. The research places the spatial development into a wider theoretical context of local developmental state, local state corporatism, and entrepreneurial state, as well as to combine the socio-political objectives together with economic goals of the local government. The study argues that Songzhuang has witnessed a unique form of artistic urbanism, a process of rapid urbanization of villages in the art-led development. Local governments have competed for taking control of spatial governance through actions characterized by decentralization, alliance, and entrepreneurship, following the logic of performing an overall control over the socio-political, economic, and cultural aspects of art districts, and profiting from land market. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology 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.)

• 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]

Taking 13 cities in Beijing, Tianjin and Hebei as the research objects, this paper constructed the urban smart development index system from three aspects: smart space construction, smart element allocation and smart welfare performance, measured the urban smart development level in Beijing, Tianjin and Hebei from 2008 to 2018, and used ArcGIS software to realize the temporal and spatial measurement performance of smart development level. The obstacle degree model was used to reveal the criterion-level factors that hinder the smart development of Beijing, Tianjin and Hebei cities. The main conclusions are as follows: (1) The smart development level in Beijing, Tianjin and Hebei is low, the research period shows a weak fluctuation and downward trend, and there is room for improvement. (2) From the spatial difference of smart development level, the double core trend with Beijing and Tianjin as the high level is obvious, showing a downward trend from the center to the surrounding. (3) From the overall barrier performance of study area, smart welfare performance accounts for the largest proportion, smart space construction takes the second place, and smart factor allocation is the lowest. (4) The obstacles to smart development in different cities vary. The obstacles in Beijing and Tianjin are mainly focused on smart welfare performance. As the main core area to undertake Beijing's noncapital functions, smart space construction and smart element allocation are the obstacles in most cities. [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]

The rapid adoption of electric vehicles (EVs) has led to dramatic increase in charging demands that poses great challenges for efficient charging infrastructure rollout and operation. It is crucial to accurately assess charging demand in urban areas to optimize the siting and sizing of charging infrastructure. This paper proposes a novel urban charging load forecasting model for private passenger EVs based on massive operating data of EVs in Beijing. First, the characteristics of travel patterns for private passenger EVs, urban road network, functional area distribution and charging infrastructure distribution within the entire Beijing area are identified. Then a charging load forecasting model that can simultaneously simulate trip chains for EVs is constructed by considering the occupancy states of public charging piles and the interactions among different EVs. Finally, the effectiveness of the proposed charging load forecasting model is verified based on comprehensive test data. Our findings imply that the number of EVs at recharge and the charging power can be reliably predicted with the accuracy of over 84.73 % and 81.92 %, respectively. It provides the foundation for optimal charging infrastructure planning and charging scheduling. [ABSTRACT FROM AUTHOR]