Urban Scale Research Articles

SHP2SIM: a python pipeline for Modelica based district and urban scale energy simulations

ABSTRACT Energy simulation models are crucial to estimate the energy demand of buildings, especially for prospective planning on a district or city scale. As required input data is not available in many cases, an automated model generation workflow is needed. Existing workflows have several disadvantages, including: (i) dependence on large input datasets of existing buildings; (ii) no 3D representation to support the planning process; (iii) they are proprietary solutions. The pipeline ‘SHP2SIM’ is an open-source python pipeline enabling enrichment and generation of building energy simulation models based on little input data for district and urban scale. The pipeline is tested by simulating the heat load for a district with 27 buildings and validated for one building: R squared is 0.9825, CV(RMSE) is 22.10%, and NMBE is 4.06% on a monthly basis. To enable reproducibility and encourage open science, input data, output models, and the pipeline are openly available (https://github.com/tug-cps/shp2sim).

Changes in commuting mode and the relationship with psychological stress: A quasi-longitudinal analysis in urbanizing China

Emerging longitudinal research on the relationship between commuting mode and psychological wellbeing draws exclusively from cities in developed countries and the findings are not consistent. Our study contributes to the evidence base from urban China, where rapid urban growth has raised great concerns for urbanites’ commuting problems and psychological stress risks. Drawing upon the China Health and Nutrition Survey (2006–2015), we followed a quasi-longitudinal design to examine changes in commuting mode and the associations with long-term psychological stress. Crucially, the neighbourhood-level urbanicity scale was incorporated to analyse geographic variations in the commuting-stress relationship over time. The results show that maintaining car commuting and long-duration active commuting were associated with lower levels of psychological stress, while long-duration motorised commuting trips by car or public transport were predictive of higher stress levels. Moreover, high-urbanicity areas involved more active commuting trips and short motorised commuting trips, which were beneficial to long-term psychological wellbeing. In contrast, the commuting-related stress risks were noticeable in medium urbanicity areas, where the commuting duration by public transport was extremely high. Based on the socio-institutional context of urban growth in China, we recommend that urban governments should change the focus from expanding urban development land to improving urban amenities and urbanites’ wellbeing.

Enhancing urban ecological resilience through integrated green technology progress: evidence from Chinese cities.

The effective resolution of environmental pollution caused by carbon haze through coordinated progress in green technology and urban ecological resilience is a crucial approach towards promoting sustainable development in Chinese cities. In this study, panel data from 281 cities in China from 2007 to 2019 were analyzed using the entropy method and the coupling coordination degree model to determine the coupling coordination degree between green technology progress and urban ecological resilience. The coordinated influence model and threshold model were applied to investigate coupled coordination types and influencing factors. Results indicate that green technology progress levels have shown an upward trend with increasing volatility from east to west and decreasing volatility with urban scale expansion. Ecological resilience levels have also steadily increased, albeit at a reduced rate. The coupling coordination degree of green technology progress and urban ecological resilience has evolved overall from low to high levels; however, the coupling coordination type has regressed to some extent, with most regions exhibiting lagging green technological progress. Pressure resilience has a positive impact on the coupling coordination degree, while state resilience and response resilience have a negative impact. Green technology progress has a dual threshold effect on the coupling coordination degree. By exploring the coupling and coordination mechanism between green technology progress and urban ecological resilience, this study not only facilitates collaborative management of pollutants and greenhouse gases in cities but also provides a comprehensive reference for the construction of an institutional system for collaborative carbon and haze management.

Computational procedure of solar irradiation: A new approach for high performance façades with experimental validation

Promoting sustainable strategies at the urban scale requires reliable assessment of solar irradiation received by buildings envelope. This will guide modelers, urban planners, and policymakers in optimizing building designs and incorporating renewable energy modules. Existing tools for irradiation prediction suffer from several limitations, including high computational burden and reliance on data availability, which can impact the tool's reliability. This paper advances a recently developed trigonometric model by the authors for irradiation prediction that effectively captures the details of the surrounding environment while maintaining accurate results, compared to pixel counting and polygon clipping techniques. The new model successfully accounted for the discontinuities in the surroundings profile and the presence of multiple rows of surrounding buildings. Beam, diffuse, and reflected irradiation were correlated to different density indicators such as ground-space index, floor-space index, and spaciousness index. A statistical model was applied to investigate the impact of key variables on the irradiation span and the feasibility of solar modules. The computation time per façade was significantly reduced from 6.1 min to 0.8 s, with an acceptable error of 5.1%.

Disentangling relations between dynamic urban structure and its efficiency in 287 cities across China

Conventionally urban structures are mainly inferred from the spatial arranges of related urban elements such as land use and population density. China's unprecedented urbanization process has significantly changed urban spatial structure and it is not clear how urban structure impacts the sustainability and livability of cities across a large geographic space. Furthermore, urban structure always shows dynamical variations during the day and over the night, which are a challenge to be captured by the conventional research methods and data. In this paper, we evaluated and compared the characteristics of the urban structure of the 287 cities in China by examining the dynamic changes of urban human activities distribution inferred from location requests collected by Tencent's platform. We developed two new indexes, the Dispersion Variation Index (DVI) and Spatial Dispersion Variation Index (SDVI), using the Lorenz curve, Gini coefficient, and adjusted Ripley's K function to describe the overall agglomeration intensity and the temporal variability of human activities. We also applied the urban scaling law to create two further indexes, the Scale-Adjusted Metropolitan Indicator DVI (SAMI_DVI) and the Scale-Adjusted Metropolitan Indicator SDVI (SAMI_SDVI), which enable us to evaluate the efficiency of urban structures. Our results show that the daily fluctuations of the urban structure are related to urban population, and also impacted by urban planning, topography, and other factors. The 1st-tier cities have the highest DVI (median: 0.020) and SDVI (0.052) values, which suggest the most volatile urban structure during the day. The 2nd-tier cities have the lowest urban structure efficiency, as suggested by higher SAMI_DVI (0.17) and SAMI_SDVI (0.28) values. Also, 69.2% and 76.9% of the 2nd-tier cities have DVI and SDVI values over the predicted values based on their population sizes. We also demonstrate that cities with high unstable structural characteristics tend to exhibit lower commuting efficiency and higher carbon emission intensity. Our framework outperforms previous metrics, is highly scalable, and can be implemented at little cost, allowing studies to be conducted even in small and medium-sized cities with little traditional data.

Applied Digital Twin Concepts Contributing to Heat Transition in Building, Campus, Neighborhood, and Urban Scale

The heat transition is a central pillar of the energy transition, aiming to decarbonize and improve the energy efficiency of the heat supply in both the private and industrial sectors. On the one hand, this is achieved by substituting fossil fuels with renewable energy. On the other hand, it involves reducing overall heat consumption and associated transmission and ventilation losses. In addition to refurbishment, digitalization contributes significantly. Despite substantial research on Digital Twins (DTs) for heat transition at different scales, a cross-scale perspective on heat optimization still needs to be developed. In response to this research gap, the present study examines four instances of applied DTs across various scales: building, campus, neighborhood, and urban. The study compares their objectives and conceptual frameworks while also identifying common challenges and potential synergies. The study’s findings indicate that all DT scales face similar data-related challenges, such as gathering, ownership, connectivity, and reliability. Also, hierarchical synergy is identified among the DTs, implying the need for collaboration and exchange. In response to this, the “Wärmewende” data platform, whose objectives and concepts are presented in the paper, promotes research data and knowledge exchange with internal and external stakeholders.

Investigating the Synergy between CO2 and PM2.5 Emissions Reduction: A Case Study of China’s 329 Cities

The synergetic reduction of CO2 and PM2.5 emissions has received much attention in China in recent years. A comprehensive evaluation of the synergy between CO2 emission reduction (CER) and PM2.5 emission reduction (PER) would provide valuable information for developing synergetic control policies. Thus, we constructed a comprehensive CO2-PM2.5-emission-reduction index system and evaluated the synergy between CER and PER, using the coupling coordination degree (CCD) and relative development degree (RDD) model in China’s 329 cities from 2003 to 2017. The spatiotemporal characteristics of the CCD were analyzed on the national, regional, and urban scales. Furthermore, we used the spatial autocorrelation analysis, kernel density estimation, and Dagum Gini coefficient to investigate the spatial autocorrelation, evolutionary characteristics, and regional differences of the CCD. The results indicate that (1) the synergy between CO2 and PM2.5 emissions’ reductions showed an upward trend, and the lowest CCD values occurred in NW and Shanghai on the regional and urban scales, respectively; (2) the CCD showed obvious spatial clustering characteristics, with 75% of the cities located in the “High–High” or “Low–Low” clustering zones in the Moran scatter plots in 2017; (3) the polarization of CCD in SC, MYR, and SW showed intensified trends; (4) and the hypervariable density was the largest contributor to the overall difference in the CCD. Our findings suggest that more attention should be paid to the top-level design of the policies, technological innovation, and cross-regional or intercity cooperation.

Subordinate housing financialization: tracing global institutional investment into Lisbon’s urban development

ABSTRACT This article contributes to scholarship on housing financialization and core–periphery relations by exploring the role of transnational institutional investors in housing production in Lisbon. Using a “follow-the-money” approach, I trace current investments into large-scale housing developments, finding a dominance of capital-rich institutional actors originating primarily in core economies. The resulting developments are largely build-to-sell projects, which are framed as a necessary response to existing housing demands. I argue that such investment reflects and reinforces subordinate financialization through housing, as Lisbon’s status as a city of the semi-periphery dependent on outside investment provides fertile ground for investors to build projects to fit their criteria. This in turn produces uneven development on the urban scale. Using an independently-built database of projects and investors along with qualitative methods, the paper connects global relations of financial subordination to housing development, and adds to our understanding of institutional investors – increasingly powerful actors in real estate.

Does urban air pollution have an impact on public health? Empirical evidence from 288 prefecture-level cities in China

The impact of air pollution on public health is a popular topic among socio-economists and environmental researchers everywhere. Although much research has been conducted on it, the connection between air pollution and public health at the urban scale in China is still not well understood. This study employs a spatial econometric model using panel data from 288 Chinese cities from 2000 to 2021 to explore the spatial impact of air pollution on public health and to investigate regional heterogeneity across regions. The findings indicate that there is a significant spatial correlation between the level of public health and the level of air pollution in various cities in China, and air pollution has spillover effects between these cities; air pollution, as well as GDP per capita, industrial structure, green space per capita, population density, and number of physicians per 10,000 people, all have positive or negative effects on public health; in the eastern, central and western regions, air pollution and the impact of control variables on population mortality are different, from a regional perspective, the impact of air pollution on public health varies significantly from region to region. This study enriches the research on air pollution and public health, and the conclusions obtained have strong practical significance for improving urban air pollution and ensuring residents' health.

Does a scaling exist in urban ecological infrastructure? A case for sustainability trade-off in China.

So far, urban scaling theory has proven that urban area, infrastructure, and economic output have a scaling relation with population. But if we consider ecological space as a part of urban infrastructure, would the same scaling characteristics exist? What is the scaling relationship between ecological spaces and economic social development in different stages of urbanization? This paper is based on this question and explores the trade-off between social economic system and ecosystem in 370 cities of China. The results show that the relationship between population and urban ecological space generally follows the scaling theory in terms of different types of ecological spaces and ecosystem services. For every 10-fold increase in population size, the total area of ecological space and ecosystem services increase by approximately 4 times. The manifestation of ecological space following the scaling laws is the aggregation behavior of better network connectivity. There is a trade-off between urban ecological space and socioeconomic development, with flow equilibrium reached at a population of 2 million and efficiency equilibrium reached at a population of 1 million. Starting from type I and type II megapolis, urban development gradually tends to stabilize, and there may even be a trend of slow decline in urban development potential. In the absence of ecological space, virtual network space can serve as a substitute for ecological space. The driving factors affect scaling behavior of ecological space, including connectivity of ecological space, spatial heterogeneity of natural conditions, and disturbance of economic and social activities. This research can help city to expand ecological space, promoting the added value of urban ecological assets and keeping the urban development potential within the optimal threshold range continuously.

Assessing resilience, equity, and sustainability of future visions across two urban scales

AbstractCities need to take swift action to deal with the impacts of extreme climate events. The co-production of positive visions offers the potential to not only imagine but also intervene in guiding change toward more desirable urban futures. While participatory visioning continues to be used as a tool for urban planning, there needs to be a way of comparing and evaluating future visions so that they can inform decision-making. Traditional tools for comparison tend to favor quantitative modeling, which is limited in its ability to capture nuances or normative elements of visions. In this paper, we offer a qualitative method to assess the resilience, equity, and sustainability of future urban visions and demonstrate its use by applying it to 11 visions from Phoenix, AZ. The visions were co-produced at two different governance scales: five visions were created at the village (or borough) scale, and six visions were created at the regional (or metropolitan) scale. Our analysis reveals different emphases in the mechanisms present in the visions to advance resilience, sustainability, and equity. In particular, we note that regional future visions align with a green sustainability agenda, whereas village visions focus on social issues and emphasize equity-driven approaches. The visions have implications for future trajectories, and the priorities that manifest at the two scales speak of the political nature of visioning and the need to explore how these processes may interact in complementary, synergistic, or antagonistic ways.

Evaluation of urban flooding and potential exposure risk in central and southern Liaoning urban agglomeration, China

Urban flooding is an important natural hazard that affects urban security in the context of global climate change and urbanization. The simulation of stormwater inundation and risk assessment in urban environments is critical for the sustainable development of urban agglomerations. However, few studies have focused on rainstorm flooding at the urban agglomeration scale. In this study, the Central and Southern Liaoning Urban Agglomeration (CSLN) was selected a case study. A method was proposed to assess the urban flooding and potential exposure risk. The urban flooding of CSLN was characterized by the average flooding depth (AFD) of each sub-catchment, and exposure risk was indicated by potential regional and population exposure risk. The results illustrate that the AFD increased with an increase in the rainfall return period, especially in the urban core. The AFD of each city in the CSLN ranged from 10 to 80 mm, and there were strong differences among cities. The spatial distribution of urban flooding in the nine cities presented aggregation characteristics, and hotspots were mainly concentrated in the old urban districts. The potential regional exposure risk tended to increase as the rainfall return period increased from 10 to 100 years; however, there were significant differences among cities. Among them, the area of potential regional exposure risk in Shenyang was the largest, increasing from 365 km2 under a 10-year rainfall return period to 463 km2 under a 100-year rainfall return period. The largest proportion of potential regional exposure risk was in Anshan, which increased from 3% under 10-year to 13.8% under 100-year rainfall return periods. Most cities had some potential population exposure risk. More residents in populous cities, such as Shenyang and Dalian, were subject to higher exposure risks. However, Benxi, Anshan, and Tieling had a high proportion of severely affected areas, although the size of their cities is much smaller than that of Shenyang and Dalian. Urban flooding and potential exposure risk were apparently higher in the business and government zones than in the industrial and greenspace zones. These methods and results may provide references for rainstorm flooding mitigation through urban planning in urban agglomeration areas.

Statistical parametric and non-parametric control charts for monitoring residential water consumption

The adoption of strategies for monitoring water consumption is essential for water resources management, contributing to the promotion of the sustainability in the water sector. Statistical process control (SPC) charts, which are widely used in the industrial sector, are statistical methods developed to improve the quality of products and processes. The application of this method has reached other areas over the last decades and has recently been identified as an option for environmental monitoring. In this context, the application of SPC charts emerges as an option for water consumption monitoring, whether in a building or an urban scale. Thus, this article aims to analyze the application of statistical process control charts in the monitoring of water consumption of two housing compounds in Joinville, southern Brazil. The methodological procedures include the use of the Shewhart and the EWMA control charts in addition to the non-parametric alternative, the EWMA-SN, assessing the effectiveness of these techniques in detecting water leaks in residential apartment buildings. The data sets, obtained through a telemetry metering system from the water utility, represent a period of 243 days. The results show that control charts are a powerful tool in identifying changes in water consumption patterns, with the EWMA chart flagging the leaks sooner.

Building energy demand of urban blocks in Xi'an, China: Impacts of high-rises and vertical meteorological pattern

High-rise buildings have been promoted in high-density cities. The impact degree of urban high-rises on the building energy demand at the urban block scale is determined by many factors, including the effects of the vertical meteorological pattern (VMP), which have been discussed insufficiently. In this study, the VMP of urban areas in Xi'an, China was observed, and a building energy simulation model that revealed the “urban block form–outdoor climate–building energy” nexus was developed with the URBANopt plugin on the Grasshopper platform. The impacts of the VMP on the building heating and cooling energy demands of different urban blocks were then predicted. In January, the VMP led to building heating load increases of 0.7–1.6 kWh/m2 (16–52%) and 0.0–1.1 kWh/m2 (0–35%) in the residential and mixed-use blocks, respectively. In July, the ranges of the building cooling load changes produced by the effects of the VMP were 0.0–0.1 kWh/m2 (0–1%) and −0.3–0.2 kWh/m2 (−2%) in the residential and mixed-use blocks, respectively. Furthermore, the VMP affected the relationship between the urban block form and the building energy demand. Based on the relationship, we provided form-optimization advice for different functional urban blocks. The urban high-rise mechanisms in high-density cities and their impacts on the building energy demand were discovered in this study. This can help decision-makers to optimize urban planning while promoting urban sustainability.

The Scale of Urbanism

While scale is an essential factor in discussions about sustainable cities, there is no common understanding of what scale is or how it should be measured. This paper sheds light on the issue of scale by suggesting how it might be measured and evaluated. My purpose is to offer both a methodological and empirical contribution to the understanding of scale, using Chicago as a case study. Using historical Sanborn maps, I first investigate scale change over time, focusing on a selection of 31 sites that are now “mega-developments” but were originally composed of small-scale buildings and blocks. I quantify that the historical urban fabric had five times as many buildings, and a much higher percentage of buildings with mixed use. I then look at the city as a whole and compare urban scale to pedestrian quality to assess whether there is a quantifiable difference between large- and small-scale urbanism. I find that, at least for Chicago, small scale urbanism is associated with higher pedestrian quality. For the third part of the analysis, I correlate scale and socio-economic characteristics at the census tract level. The results illuminate a mixed set of differences between scale and socio-economic characteristics like income and housing value.

Accelerated convergence for city-scale flow fields using immersed boundaries and coupled multigrid

Fast and accurate prediction of Chemical, Biological and Radiological (CBR) dispersion patterns and toxic extents is important for public safety as conventional and non-conventional airborne threats released into the built environment can pose serious dangers to human health ranging from difficulty breathing and eye irritation to incapacitation and death. Computational fluid dynamics (CFD) is routinely used for gas dispersion modeling when increased accuracy over traditional Gaussian-based methods is required, although CFD requires greater modelling efforts. The combination of structured Cartesian meshes and immersed boundary methods reduces this effort and has been resurging in popularity over the past decade.Due to a lack of related literature, a simple and robust methodology was developed by the authors to treat immersed boundaries at multigrid levels, and this integration focused on a segregated multigrid approach using structured Cartesian meshes with adaptive mesh refinement. In the current work, a coupled multigrid treatment is adapted to the integrated immersed boundary methodology and adaptive mesh approach and compared to the segregated technique in terms of convergence rates. To accelerate convergence, the coupled approach selectively applies grid refinement at coarse grid levels, and by design, neither methodology detects the immersed boundaries on coarse grid levels.The two multigrid approaches are compared at three flow scales: wind tunnel, mock-urban and full-urban. At the wind tunnel scale, the coupled multigrid solver shows 39.3 times speed up over single grid and 10.4 times improvement over the baseline segregated approach. At the full urban scale, the coupled approach is shown to converge wind fields with a 6.3 times speed improvement over the previous segregated approach and therefore is suitable for CFD-based CBR assessment tools.

Spatial‐temporal evolution characteristics of residential land prices based on the 2010–2019 land transfer data in China

AbstractStudying spatial‐temporal change in residential land prices (RLP) can help implement real estate regulations to promote the healthy development of the residential land market. This study applied the urban scaling law to explore the spatial‐temporal pattern of RLP from 2010 to 2019 in China. We found rapid growth in RLP across China from 2010 to 2019, with a growth rate of 179.12%. Among them, the Eastern Region had the highest RLP and growth rates. Furthermore, differences in RLP between large cities and small‐medium cities widened, indicating a trend of the Matthew effect in prefecture‐level cities. Moreover, the scale‐adjusted metropolitan indicator (SAMI) indicated urban agglomerations including Beijing‐Tianjin‐Hebei (BTH), Yangtze River Delta (YRD), Guangdong‐Fujian‐Zhejiang Coastal (GFZ), and Pearl River Delta (PRD) located in the Eastern Region had higher RLP than urban agglomerations with the same population size. In addition, the SAMI also highlighted disproportionately high RLP in some small‐medium cities compared to equivalent cities, warranting regulatory policy attention.

Understanding place identity in urban scale Smart Heritage using a cross-case analysis method

PurposeSmart Heritage is a recently established discourse that entwines smartness and the heritage discipline. Studies have shown that place identity is at the core of value-based frameworks of built heritage. This study aims to unveil the role of identity in existing Smart Heritage frameworks, which is currently a gap in existing research.Design/methodology/approachTo better understand place identity in the Smart Heritage context and facilitate future framework establishments, this study uses a cross-case analysis method to scrutinise common trends in the identity development of seven current best practices.FindingsThe results show that current best practices involve smart technologies in sustaining or rebuilding heritage identities, mostly mapped on the local scale. Catered solutions are essential in this context due to historic cities’ variegated pursuits of identity. Most current Smart Heritage projects are at the transitioning stage from digital to smart, as the autonomous ability of smart innovations is yet to be fully realised on the city or the global scale. Researchers are encouraged to draw essence from existing heritage frameworks considering the built heritage’s place identity, which is at the core of culturally sustainable Smart Heritage transitions.Originality/valueThis study concludes with five recommendations for addressing heritage identity in Smart Heritage frameworks, targeting future research avenues. Also, this study furthers the discussion on the linkage of Smart Heritage, place identity and marketing strategy, contributing to the city branding and tourism management field. Future research should extend the case-study selection beyond Europe, which is a recognised limitation of this study.

Retracted: Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model

Retracted: Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model

Green technology diversification, technology vertical spillovers, and energy intensity in Chinese cities

Drawing from patent data spanning 2011-2016 in 249 Chinese prefecture-level cities and urban scale multi-region input-output (MRIO) table data, this paper empirically demonstrates that as green technological diversification levels escalate, the energy intensity of Chinese prefecture-level cities exhibits an initial increase followed by a decline. Green technological diversification indirectly influences urban energy intensity through vertical spillovers of green technology across the upstream and downstream sectors within the supply chain. Medium-sized cities, service industry-oriented cities, and those in the early stages of industrialization need to prioritize development of multiple green technologies to surpass the diversification turning point. The finding suggests a strategic transition for Chinese cities from a single green technology agglomeration model to a cluster model of collaborative development of multiple green technologies.