Urban Blocks Research Articles

Influence of a City Block on ES-CFD Coupled Analysis

Coupled analysis using the complementary methods of energy simulation (ES) and computational fluid dynamics (CFD) can improve the calculation accuracy of thermal environment simulations. However, existing studies on ES-CFD coupled analyses that consider the effects of solar radiation and surrounding conditions have been insufficient. In practice, net solar radiation fluctuates, owing to the influence of urban blocks, and the solar radiation incident on the interior determines the heating range of the interior, which results in fluctuations in the convective heat transfer coefficient. This study conducted an ES-CFD coupled analysis to examine differences in the convective heat transfer coefficients due to the different insolation conditions and the surroundings of target buildings. The risk of condensation was evaluated using the dew point temperature in the analysis model, and a neutral insulation performance was employed in the set cases with the presence or absence of urban streets as a variable. Buildings within urban city blocks were observed to have a lower dew point temperature and a higher risk of condensation, which is a reasonable assessment. The results of this study will contribute significantly to the development of comprehensive simulation technologies.

From traditional to digital contexts: new characteristics of the public’s spatial perception of urban streets in the age of technology

The constant development of internet technology in the digital age has changed the way people interact with space. To explore whether and what changes have occurred in the public’s spatial perception of the street during the shift from the traditional to the digital age, this paper compares the public’s spatial perception characteristics in the two contexts through a classical theory review and empirical coding analysis with the Xiaolouxiang historic district as an empirical case. The frameworks of public spatial perception characteristics are similar in both contexts, with a focus on the three dimensions of objects, buildings and spaces, and activities. However, compared with that in the traditional context, the public’s spatial perception of the street in the digital context of Xiaolouxiang has undergone new changes in three aspects: from focusing on the three-dimensional experience of space to focusing on the two-dimensional visual aesthetics of space, from emphasizing spatial totality to focusing on spatial details, and from focusing on the use of space to emphasizing the cultural characteristics of space. Research emphasizes that, within the context of digitalization, spatial design should place greater emphasis on visual aesthetics, detail processing, and cultural expression to better meet the needs and expectations of the public. This work identifies new features of the public’s perception of urban street space in the context of digitalization and accordingly provides suggestions for the future design of urban street space. The findings of this study not only enrich the foundational research content of spatial perception theory but also offer new perspectives for designers and planners in the practice of urban block renovation.

Morphology and agents of urban transformation

The study aims to propose a method of analysis that promotes a clearer perception of the spatial transformation resulting from the action of certain social groups to shape the urban space according to their interests. The territorial transformation related to the role of different agents is investigated, through urban morphology, in order to understand the correlation between the Brazilian urban form with public management and the direction of public investments. To analyze how the city is shaping over time, the work was structured from a case study, which mapped the urban transformations of the municipalities of Cuiabá and Várzea Grande, during the 2006-2021 interval. The method adopted by the research proposes as tools for investigating the territory: the conception of thematic cartographies through the comparison of aerial images from Google Earth, the establishment of analysis categories that allow the identification of the different types of building transformations preponderant of the urban blocks and the main interventions on the road system and the impact of important events that occurred in the cities in the period studied. A quantitative analysis is presented, with the approximate values of areas in hectares (ha), which represent the categories of analysis indicated. As a result, it can be seen, through the maps, that the relationship between the different forms of urban land occupation and the road infrastructure implemented ends up reinforcing the process of socio-spatial segregation. It is concluded that the proposed method, combined with historical and socioeconomic studies, manages to reconstitute urbanization processes in order to understand them in order to intervene in the reality of our cities.

Assessing Urban Morphology's Impact on Solar Potential of High-Rise Facades in Hong Kong Using Machine Learning: An Application for FIPV Optimization

The relationship between solar potential on building façade and urban morphology at urban scale remains unclear, and the design of façade integrated photovoltaic (FIPV) lacks evidence. This study investigates high-rise, high-density commercial districts in Hong Kong (HK), using Random Forest algorithm combined with the SHapley Additive exPlanations method to assess the importance of urban morphology on solar irradiance on building facades. The results indicate that plot ratio, building floor, building density, and perimeter shape factor are the four key parameters influencing solar irradiance, with the importance rate and contribution value of the four parameters reach 43.9% and 48.7%, respectively. Based on these parameters and actual urban blocks in HK, typical urban typologies were constructed. Four scenarios were generated with plot ratio as the control parameter. The positions, amounts, and transparency of PV glass on the south and east facades were optimized to minimize the payback period and maximize power generation, using Non-dominated Sorting Genetic Algorithm II algorithm. The south façade of Scenario 1 (when the heights of surrounding buildings are lower than that of the targeted building) obtained the optimal payback period (8.44 years) and power generation (55961 kWh), with 77 opaque PV panels and 49 semi-transparent ones.

Impact of green space patterns on PM2.5 levels: A local climate zone perspective

Green spaces have been demonstrated to significantly decrease PM2.5 levels. However, the impact of green spaces on PM2.5 levels in different spatial forms of urban blocks is not yet fully understood. This research utilized ensemble machine learning algorithms to investigate the impact of green space spatial patterns, assessed through landscape pattern analysis, to PM2.5 concentrations during summer and winter based on local climate zones (LCZ). The results revealed significant differences in PM2.5 concentration across the seven types of primary LCZs, primarily influenced by meteorological factors. In winter, eight green space indicators exhibited a more substantial contribution to PM2.5 levels in comparison to the summer season. Significant discrepancies were noted in the contributions of these indicators across different LCZs. Patch density (PD) and landscape shape index (LSI) made a more substantial contribution, while relative patch richness (RPR) and Shannon's evenness index (SHEI) showed a less significant contribution. The spatial pattern of green spaces was significantly related to their contributions. Among the seven predominant LCZs, the five key indicators included PD, LSI, Shannon's diversity index (SHDI), area-weighted mean patch area (AREA_AM), and connectance index (CONNECT). Spatial heterogeneity was further observed in the positive and negative contributions of each green space indicator. This study enhances understanding of the impact of green spaces on PM2.5 across LCZs and provides valuable insights for urban management and planning.

Is LCZ Enough? Physical Properties, Thermal Environments and Cooling Effects of Green Roofs in High-Density Urban Industrial Blocks

With rapid worldwide urbanization, the urban heat island (UHI) effect is becoming more and more serious. The UHI effect is more intense in industrial areas. Green roofs are an effective way to mitigate UHIs in high-density cities, which calls for thorough examination. This study explored the associations between the block characteristics and block thermal environment in high-density industrial areas based on the widely accepted Local Climate Zone (LCZ) scheme. The pedestrian air temperature comparisons before and after virtual green roof installations presented the cooling effects of green roofs. Thirty-six typical industrial blocks were involved in the study and the simulations were conducted utilizing ENVI-met. The results showed that (1) the air temperature in LCZ4 is significantly lower than those in LCZ2 and LCZ6, but no significant differences were identified between other pairs of LCZ types; (2) the cooling effect of green roofs significantly differs among LCZs, and is associated with sky view factor (SVF), average building area (ABA) and average building shape index (ABSI); (3) in high-density urban areas, additional functional parameters and building-volume indices should be included to better address the physical characteristics, thermal environment, and green roof cooling effect of industrial blocks. This study could improve the validity of LCZ classification for high-density industrial blocks and may provide direct implications for green roof planning.

Exploring Urban Heat Distribution via Intra- and Extra-Block Morphologies with Integrated Stacked Models

The spatial variability of land surface temperature (LST) is considerably affected by urban morphology. Previous research has focused separately on the thermal effects of urban morphology and the cooling effects of water bodies and urban parks. However, the combined influence of intra- and extra-block factors on LST has not been thoroughly examined. To bridge this research gap, we conducted an extensive analysis of 17 urban morphology factors in Hangzhou by employing a novel stacked ensemble approach. Results showed that the stacked ensemble models outperformed commonly used techniques, such as random forest and boosted regression trees. Extra-block factors, alongside building density, average building height, and vegetation coverage within blocks, predominantly influenced the LST distribution across all seasons. Building density was positively correlated with LST, with a maximum influence of 1.5 °C in spring, whereas building height was negatively correlated with it, with a maximum influence of 1.8 °C in winter. The cooling distance of the Qiantang River extends up to 2500 m into the urban blocks and has a maximum effect of 2 °C in summer. These insights deepen our comprehension of the interplay between LST and intra- and extra-block urban morphologies, thus offering valuable guidance for urban planners and policymakers.

Surface energy balance-based surface urban heat island decomposition at high resolution

Urban heat island (UHI) is among the most pronounced human impacts on Earth. To formulate locally adapted mitigation strategies, a comprehensive understanding of the influencing mechanisms of UHI at high resolution is imperative. Based on surface energy balance, we attributed surface UHI (SUHI) into five biophysical terms (surface radiation, anthropogenic heat, convection, evapotranspiration and heat storage term) using Sentinel-2 and Landsat-8 images in Beijing. The simulated SUHI intensity, derived by combining all five contribution terms, exhibited a good consistency but a higher spatial resolution, than SUHI intensity extracted from Landsat-8 land surface temperature product. SUHI intensity tended to decrease from the old city to outsides, attributed to the decrease of evapotranspiration, solar radiation and anthropogenic heat term. The convection and heat storage term play a positive role in reducing SUHI. Among urban morphological blocks, low-rise and high-density blocks had the strongest SUHI, with the evapotranspiration term contributing the most. The results highlighted the capacity of the urban surface to evaporate water in affecting Beijing SUHI. The proposed method provides one useful tool to analyze the drivers of SUHI from the aspect of heat formation, which can be potentially applied worldwide for large-scale comparisons of how urbanization affects UHI.

Impacts of urban block form on carbon and pollutant emissions from urban life in China from the perspective of regional differences

Air pollution emissions (PE) and carbon emissions (CE) pose significant challenges to achieving the Sustainable Development Goals (SDGs) globally. The intensity of urban block development and spatial form can influence the relationship between PE and CE. This study analyzed 11,228 neighborhood samples from various climate zones across China using spatial statistics and an optimized random forest model to examine the impact of block spatial form on PE and CE. The findings reveal that: (1) The PE–CE correlation in non-first-tier city blocks in southern China is stronger than in those in northern China. The correlation is strongest in urban neighborhoods located in temperate climates. Additionally, the PE–CE correlation is weakest in Beijing and Shanghai. (2) The variation in explanatory power of different driving factors is more pronounced for CE than for PE, with PR, NDVI, and AH emerging as the most significant factors. (3) The synergy between PE and CE is strongest when BD is in the 20 %-30 % range. Similarly, the synergy is strongest when PR is in the 2–3 range. (4) BD in the 40 %-60 % range is most effective in reducing PE and CE, with 40 %-50 % range favoring CE reduction and 50 %-60 % range favoring PE reduction.

Applying noise mapping in studying road traffic noise influence on urban blocks

With a thriving 40 years' urbanization, China cities are facing severe noise caused by road traffic that seriously influencing residents' health. To solve such environmental pollution, urban planning and design could play a significant role at the early stage. Therefore, a study on applying noise mapping simulation to mitigate road traffic noise through making proper plan and design of urban blocks is made. In the study, a rapid urbanization city, Shenzhen, was researched. Through comparing different plan parameters and design layouts, approaches benefitting mitigating road traffic noise were thoroughly investigated. It is found that bigger block size might bring forth higher noise than smaller one. The study outcomes are useful to help in creating a tranquil urban environment, particularly in urban planning & design stage.

An urban agricultural block construction method based on low-carbon concepts: A case study of the Beijing-Tianjin area in China

With the ongoing progress of urbanization, various issues such as resource scarcity, climate change, and carbon emissions overload have gradually emerged. Urban agriculture (UA) is recognized as a pivotal strategy to promote sustainable urban development. In this context, the study proposes a spatial scale hierarchy, encompassing “single building - building cluster - urban block," to formulate spatial strategies for the theoretical model of urban agricultural blocks. The theoretical model integrates production spaces, production methods, and spatial systems based on relevant design principles and the needs of residents. Nankai District's Qingfeng Road East Block in Tianjin is used as the site for applying and simulating the theoretical model. The results of the study show that UA in a 500m × 500m block can ideally eliminate the need for external food inputs by 100% for starchy vegetables, legumes and fruits, and meat/poultry, while achieving a 254.73% self-sufficiency rate for fungi. Additionally, it can reduce energy inputs by 28.33%, water inputs by 38.13%, and completely eliminate waste output for 8754 people. Carbon emission analysis indicates that the urban agricultural block can reduce approximately 2250.01t CO2 emissions from buildings and waste, with greater carbon-neutral potential in transportation and agriculture, forestry, and other land uses (AFOLU). This is significant for tackling various urban challenges and enhancing future development.

Evaluation of pedestrian thermal comfort from a whole-trip perspective: An outdoor empirical study

Pedestrian thermal comfort is a critical factor influencing urban livability and sustainability. However, existing models often overlook its cumulative impact from dynamic thermal experiences throughout the whole-trip. This study builds on previous findings, conducting outdoor mobile observations in Guangzhou's urban blocks on clear summer days. Methods for assessing thermal comfort during pedestrian travel were tested and refined, taking into account participants' skin temperatures and accumulated heat storage. The research found that the dynamic changes and non-uniform distribution of radiant temperature are the main characteristics of pedestrians' thermal experiences during summer clear weather and are critical factors affecting their thermal comfort. Non-uniform exposure to direct solar radiation can cause variations in pedestrians' instantaneous thermal sensations, and dynamic thermal experiences can lead to the formation of memorized thermal sensations, causing a deviation between instantaneous and whole-trip thermal sensations. There is a significant correlation between pedestrians' mean skin temperature and heat storage and their thermal experiences over the past 10–25 min. Regression analysis provided different weights that could represent the memory component in whole-trip thermal sensations. The findings provide a theoretical basis for understanding pedestrian thermal comfort in dynamic outdoor environments and will help improve the thermal quality of outdoor travel spaces.

A novel method of high-density urban block form generation based on multi-objective solar performance optimization: A case study of Nanjing

Efficiently harnessing solar radiation in high-density urban environments to optimize block forms holds significant potential for advancing urban low-carbon development. This paper introduces a novel method for generating high-density block forms based on comprehensive solar utilization. Grasshopper was used to compile an automated workflow for block form generation, solar simulation, and multi-objective optimization algorithms. Leveraging maximum solar radiation within and surrounding the block and effective photovoltaic utilization ratio are the three objectives in the multi-objective optimization process. From 60,000 generated samples, 1200 block forms were selected as the Pareto fronts. As the plot ratio of the generated blocks increases from 3 to 7, the annual mean solar radiation around the block decreases from 891.3 kWh/m2 to 863.5 kWh/m2, a reduction of only 3.1 %. When the number of blocks within the block increases from 1 to 4, the average solar radiation inside the block increases from 484.8 kWh/m2 to 516.1 kWh/m2, an increase of about 6.5 %. Additionally, as site coverage increased from 30 % to 60 %, the average solar radiation inside the block decreased from 549.2 kWh/m2 to 459.8 kWh/m2, a decrease of approximately 17 %. Notably, the photovoltaic power generation fell from 90.3 kWh/m2 to 61.2 kWh/m2, a decrease of about 32 %. The results indicate that the grid modeling method and multi-objective optimization algorithm adopted in this study can significantly improve the diversity of block morphology and achieve multiple solar performance requirements. The findings support designers in swiftly assessing building volume rationality and solar utilization potential at the early stages of urban design.

How do urban block built environments affect older adults' walking activities and health effects: a case study in Nanjing, China.

Research on the relationship between microscale built environments and physical activity among older adults in densely populated old urban areas with high aging rates is scarce. Particularly, the relationship between urban block land-use pattern and older adults' walking activities have not yet been completely understood. This study examined the daily walking habits and socioeconomic attributes of older adults in 17 blocks with different built environment characteristics in Nanjing City, China. A multi-layer linear model was used to quantitatively analyse the mechanism underlying the effects of various factors on the health of older adults. The result shows significant positive correlation between neighborhood walkability and the enhancement of walking frequency and activity. For every 10% increase in pedestrian road connectivity and land use, the walking activity volume increased by 22.4 and 12%, and the BMI increased by 9.1 and 7.3% toward the standard range, respectively. For every 10% increase in distance between residence and plaza and park, the walking activity volume decreased by 5.4 and 3.2%, and BMI decreased by 9.9 and 6.3%, respectively. For every 10.4% increase in land mixed-use rate and per capita green area, BMI increased by 19.4%. Furthermore, higher household income and number of family members have significant correlation with walking activities and health effects. Moreover, the block-scale built environment and walking activities jointly affected health, with a cross-functional relationship between multiple factors.

An examination and analysis of the clustering of healthcare centers and their spatial accessibility in Tehran metropolis: Insights from Google POI data

Metropolises, as centers of diverse activities, encounter numerous challenges, including equitable access to healthcare services. This study examines the inequality in healthcare center accessibility in Tehran, a critical factor for sustainable urban development. Utilizing Google Point of Interest data, healthcare center clusters in Tehran were identified, and various clustering algorithms were tested. The Mean Shift Cluster algorithm was the most effective method. The study also mapped accessibility by analyzing the radius of neighborhoods around urban blocks. The findings reveal a significant imbalance in the distribution of healthcare centers in the city, with a concentration in the city center that does not align with population density—a key indicator of demand. Notably, District 7, despite being centrally located, relatively has a higher clusters' concentration of lower-quality healthcare centers. The findings reveal that four sub-districts situated in the peripheral regions of Tehran city, which collectively account for approximately 6.3% of the city's total area, exhibit significantly lower accessibility to the healthcare centers compared to other sub-districts. Overall, the areas with superior accessibility are predominantly found in the city center and extend towards the north, with accessibility decreasing as one moves towards the outskirts of the city. These results underscore the need for targeted urban planning to address the uneven distribution of healthcare resources and promote equitable access across Tehran.

Urban multi-scale ecological network sequence and spatial structure optimization: A case study in Nanjing city, China

Rapid urbanization has had a segmented effect on the ecological land and natural environment in cities. Constructing an ecological network is of vital importance to protect ecological resources and maintain regional ecological security. However, ecological spaces at different administrative scales have their own ecological functions and elemental characteristics. Therefore, we formed the ecological network sequence to present the integrative connection of multi-scale with municipal area (MA), main urban area (MUA) and central urban area (CUA) in Nanjing. Ecological sources were identified through “landscape—function—structure” framework, and ecosystem services value (ESV) was used as an auxiliary method to identify supplementary sources. Ecological corridors and some key points were identified through circuit theory. The results show that the area of ecological sources in MA, MUA and CUA was 427.3 km2, 62.5 km2 and 16.2 km2, respectively. By integrating sources of three scales, we got 14 sources (442.7 km2) in the first sequence and 10 sources (7.7 km2) in the second sequence. Apart from that, we also got 4 new supplementary sources with area of 13.5 km2. The length of ecological corridors in MA, MUA and CUA was 252.5 km, 263.9 km and 22.7 km, respectively. By integrating corridors of three scales, we found that the western corridors between the ecological sources had a higher gravitation. The ecological nodes are generally distributed in the landscape heterogeneity transition zone, ecological resource fringe zone and ecological spatial contiguous zone. The ecological pinch points are generally distributed along the water system. The ecological barrier points are generally distributed in the combination area among the urban block, village and road. In conclusion, this study made up for the research gap of finding the nesting and integration relationship among ecological networks at multi-scale.

The Impact of Wind Movement on Providing Thermal Comfort in Urban Design

The wind movement is a crucial factor in enhancing thermal comfort, forming an essential part towards friendly and sustainable urban environment. Air movement, as a prominent climatic factor, reduces heat stress with improving ventilation quality. Effective natural ventilation and heat stress mitigation can be achieved by orientation, planning and shaping the urban blocks in urban environments. Air movement represents the most important element in improving environmental adaptation, as the rapid airflow reaching buildings can significantly reduce their temperature. Site planning requires precise knowledge of the main wind directions and speeds. The research utilized the ENVI-met Models program for modeling urban environments and predicting thermal effects in the built environment. This program plays a crucial role in understanding and analyzing environmental conditions and their impact on thermal comfort. The research addressed the knowledge gap and lack of local studies in highlighting the role of wind movement in enhancing thermal comfort in urban environments using ENVI-met Models. The research aimed to provide specific knowledge in measuring wind movement and its role in enhancing thermal comfort in urban environments using the program. The research hypothesized that analyzing and modeling wind movement with ENVI-met Models can effectively contribute to understanding and improving thermal comfort in urban environments. One of the key findings is that studying the impact of wind movement with this program is essential for providing scientific and technical foundations to improve urban design and enhance thermal comfort in urban areas, promoting sustainability and environmental quality in cities

An integrated framework utilizing machine learning to accelerate the optimization of energy-efficient urban block forms

An integrated framework utilizing machine learning to accelerate the optimization of energy-efficient urban block forms

The role of Nature-Based Solutions for the water flow management in a Mediterranean urban area

Due to climate change and rapid urban sprawl, central Mediterranean regions are subjected to short but intensive storm events resulting in a significant increase of flow rates and runoff volumes in low-lying coastal urban areas. Within the framework of green urban infrastructures (GUIs), a suitable combination of Nature-Based Solutions (NBS) with traditional grey infrastructures should be adopted to mitigate flood risk effects in urban and sub-urban areas contributing at the same time to achieve multiple benefits for both the environment and the community. The aim of this study is (i) to evaluate flood hazard maps for identifying the areas within a Sicilian hydrological river basin (Toscano catchment) with a high risk of flooding by implementing the HEC-RAS model at catchment scale; (ii) to quantify the peak flow and floodplain area reduction; (iii) to assess the effectiveness of small-scale NBS (green roofs, porous pavements, rain gardens and rain barrel), in terms of peak flow and runoff volume reductions, at urban block scale by using the EPA SWMM model Model simulations are performed integrating the hydraulic (HEC-RAS) and hydrological (EPA SWMM) models for return periods of 10, 50 and 200 years. The results showed that the estimated peak flow (m3 s−1) obtained from the simulations performed at catchment scale for each T in the current scenario (without NBS) using HEC-RAS and EPA SWMM models are very close to each other (R2 = 0.99). In addition, the utopian scenario simulation showed the HEC-RAS model sensitivity to CN calibration achieving a peak flow reduction up to about 60% with the floodplain area decreasing up to about 17%. Finally, the model EPA SWMM shows its sensitivity to NBS implementation at urban block scale with a peak flow reduction up to about 16% and a runoff volume (mm) reduction up to about 24%. These reductions decrease as T increases with a higher NBS mitigation effects for the lowest T. The results highlighted that the integration of NBS in urban areas could have hydrological and hydraulic positive effects, particularly in terms of peak flow and runoff volume reduction. Furthermore, the results suggest that small-scale NBS have a potential to be effective to smaller rainfall events, but a combination with large-scale NBS is necessary to cope with extreme events.

Generative design of walkable urban cool spots using a novel heuristic GAN×GAN approach

Enhancing pedestrian-level outdoor thermal comfort (OTC) and walkability in urban environments is vital for mitigating thermal risks induced by global warming. This study introduces walkable urban cool spots (WUCS), a novel concept which incorporates pedestrian walkability into the design of thermally comfortable urban street blocks. The methodology combines OTC simulation, pedestrian walkability analyses, and surrogate models based on integrated generative adversarial networks (GAN×GAN)-enhanced genetic generative design (GGD) approach. And maximize the design metrics of WUCS through the multi objective optimization algorithm in GGD. The method is tested in To Kwa Wan, an urban renewal area in Hong Kong. Results demonstrate that it can efficiently identify high-performing WUCS solutions, with proportion of WUCS areas increasing from 53.3 % to 74 %, and the number of walkable urban cool spots increasing by 51 %. The average universal thermal climate index (UTCI) in high walkability areas decreasing from 31.7 °C to 30.5 °C, and total average UTCI during extreme heat days dropping from 31.73 °C to 31.22 °C. This research thus contributes an efficient design tool for enhancing both pedestrian-level OTC and walkability in urban environments.