Urban Domain Research Articles

Siting Background Towers to Characterize Incoming Air for Urban Greenhouse Gas Estimation: A Case Study in the Washington, DC/Baltimore Area

AbstractThere is increased interest in understanding urban greenhouse gas (GHG) emissions. To accurately estimate city emissions, the influence of extraurban fluxes must first be removed from urban greenhouse gas (GHG) observations. This is especially true for regions, such as the U.S. Northeastern Corridor‐Baltimore/Washington, DC (NEC‐B/W), downwind of large fluxes. To help site background towers for the NEC‐B/W, we use a coupled Bayesian Information Criteria and geostatistical regression approach to help site four background locations that best explain CO2 variability due to extraurban fluxes modeled at 12 urban towers. The synthetic experiment uses an atmospheric transport and dispersion model coupled with two different flux inventories to create modeled observations and evaluate 15 candidate towers located along the urban domain for February and July 2013. The analysis shows that the average ratios of extraurban inflow to total modeled enhancements at urban towers are 21% to 36% in February and 31% to 43% in July. In July, the incoming air dominates the total variability of synthetic enhancements at the urban towers (R2 = 0.58). Modeled observations from the selected background towers generally capture the variability in the synthetic CO2 enhancements at urban towers (R2 = 0.75, root‐mean‐square error (RMSE) = 3.64 ppm; R2 = 0.43, RMSE = 4.96 ppm for February and July). However, errors associated with representing background air can be up to 10 ppm for any given observation even with an optimal background tower configuration. More sophisticated methods may be necessary to represent background air to accurately estimate urban GHG emissions.

Ventilation and Air Quality in City Blocks Using Large-Eddy Simulation—Urban Planning Perspective

Buildings and vegetation alter the wind and pollutant transport in urban environments. This comparative study investigates the role of orientation and shape of perimeter blocks on the dispersion and ventilation of traffic-related air pollutants, and the street-level concentrations along a planned city boulevard. A large-eddy simulation (LES) model PALM is employed over a highly detailed representation of the urban domain including street trees and forested areas. Air pollutants are represented by massless and passive particles (non-reactive gases), which are released with traffic-related emission rates. High-resolution simulations for four different city-block-structures are conducted over a 8.2 km 2 domain under two contrasting inflow conditions with neutral and stable atmospheric stratification corresponding the general and wintry meteorological conditions. Variation in building height together with multiple cross streets along the boulevard improves ventilation, resulting in 7–9% lower mean concentrations at pedestrian level. The impact of smaller scale variability in building shape was negligible. Street trees further complicate the flow and dispersion. Notwithstanding the surface roughness, atmospheric stability controls the concentration levels with higher values under stably stratified inflow. Little traffic emissions are transported to courtyards. The results provide urban planners direct information to reduce air pollution by proper structural layout of perimeter blocks.

Variation in soil chemistry related to different classes and eras of urbanisation in the London area

Systematic mapping of the chemical environment of urban areas from around the world has demonstrated the strong impact of urbanisation on topsoil geochemical distributions originally controlled by the underlying parent material (PM). The variance of some elements including As, Ba, Ca, Cr, Cu, Mo, P, Pb, Sb, Se, Sn and Zn in urban domains appears to be impacted by a mixture of geogenic and anthropogenic controls. This study evaluates how soil chemistry has been influenced by different eras of urbanisation within London and other UK urban areas using (a) the pre-1940 Dudley Stamp First Land Utilisation Survey data and (b) the modern urban domain principally defined by the aggregate classes of the 2007 Land Cover Map. In the London area, calcium, and possibly a substantial proportion of Cu, Pb, Sn and Zn enrichment observed in soils impacted by pre-1940 urbanisation relative to soils impacted only by post-1940 urbanisation, may be partly related to the destruction of buildings during the period 1940–1941 rather than from the disposal or aerial dispersion of coal ash from domestic fires. Some Pb, Cu, Sb, Sb, Sn and Zn contamination appears to be caused by road traffic (leaded petrol and brake dust). The relationships between pre- and post-1940 urbanised areas in London also characterise most of 20 other urban centres in England and Wales for which BGS holds soil chemistry data.

The IoT for smart sustainable cities of the future: An analytical framework for sensor-based big data applications for environmental sustainability

The Internet of Things (IoT) is one of the key components of the ICT infrastructure of smart sustainable cities as an emerging urban development approach due to its great potential to advance environmental sustainability. As one of the prevalent ICT visions or computing paradigms, the IoT is associated with big data analytics, which is clearly on a penetrative path across many urban domains for optimizing energy efficiency and mitigating environmental effects. This pertains mainly to the effective utilization of natural resources, the intelligent management of infrastructures and facilities, and the enhanced delivery of services in support of the environment. As such, the IoT and related big data applications can play a key role in catalyzing and improving the process of environmentally sustainable development. However, topical studies tend to deal largely with the IoT and related big data applications in connection with economic growth and the quality of life in the realm of smart cities, and largely ignore their role in improving environmental sustainability in the context of smart sustainable cities of the future. In addition, several advanced technologies are being used in smart cities without making any contribution to environmental sustainability, and the strategies through which sustainable cities can be achieved fall short in considering advanced technologies. Therefore, the aim of this paper is to review and synthesize the relevant literature with the objective of identifying and discussing the state-of-the-art sensor-based big data applications enabled by the IoT for environmental sustainability and related data processing platforms and computing models in the context of smart sustainable cities of the future. Also, this paper identifies the key challenges pertaining to the IoT and big data analytics, as well as discusses some of the associated open issues. Furthermore, it explores the opportunity of augmenting the informational landscape of smart sustainable cities with big data applications to achieve the required level of environmental sustainability. In doing so, it proposes a framework which brings together a large number of previous studies on smart cities and sustainable cities, including research directed at a more conceptual, analytical, and overarching level, as well as research on specific technologies and their novel applications. The goal of this study suits a mix of two research approaches: topical literature review and thematic analysis. In terms of originality, no study has been conducted on the IoT and related big data applications in the context of smart sustainable cities, and this paper provides a basis for urban researchers to draw on this analytical framework in future research. The proposed framework, which can be replicated, tested, and evaluated in empirical research, will add additional depth to studies in the field of smart sustainable cities. This paper serves to inform urban planners, scholars, ICT experts, and other city stakeholders about the environmental benefits that can be gained from implementing smart sustainable city initiatives and projects on the basis of the IoT and related big data applications.

Assessment and Improvement of the Accuracy of Radiation Heat Transfer Estimation in Simplified Urban Canopy Models

Detailed modelling of the interaction between buildings and the urban environment is best implemented using Computational Fluid Dynamics (CFD). However, due to the often prohibitive computational cost of CFD models of a realistic urban domain, a number of simplified Urban Canopy Models (UCM) have been proposed since 2000: Town Energy Balance (TEB), Square Prism Urban Canopy (SPUC), Temperatures of Urban Facets in 3D (TUF3D), Urban Weather Generator (UWG), etc. The main goal is to estimate the intensity of the Urban Heat Island (UHI) intensity, in other words, the differential between the urban air temperature and the temperature measured at a reference rural station. These models are a lot faster than CFD models. However, the spatial organization of the surfaces (slopes, orientations, shape factors), and their physical characteristics (albedo, emissivity, thermal conductivity) need to be simplified as well thereby affecting the accuracy of the outcome. In particular, the models necessarily rely on overly simplified representations of short-wave (solar) and long-wave (infrared) radiation heat transfer. The contribution of the paper is twofold. First, it assesses the comparative validity of the radiation heat transfer approximations proposed by the different simplified modelling approaches in comparison to exact solutions calculated for an actual urban district. Second, it proposes to improve existing simplified models by replacing their approximate radiation transfer calculations with much more accurate ones determined by reference to the detailed geometry of the urban district under consideration. This approach is validated using the case of a district in downtown Abu Dhabi.

The core enabling technologies of big data analytics and context-aware computing for smart sustainable cities: a review and synthesis

Data sensing, information processing, and networking technologies are being fast embedded into the very fabric of the contemporary city to enable the use of innovative solutions to overcome the challenges of sustainability and urbanization. This has been boosted by the new digital transition in ICT. Driving such transition predominantly are big data analytics and context-aware computing and their increasing amalgamation within a number of urban domains, especially as their functionality involve more or less the same core enabling technologies, namely sensing devices, cloud computing infrastructures, data processing platforms, middleware architectures, and wireless networks. Topical studies tend to only pass reference to such technologies or to largely focus on one particular technology as part of big data and context-aware ecosystems in the realm of smart cities. Moreover, empirical research on the topic, with some exceptions, is generally limited to case studies without the use of any common conceptual frameworks. In addition, relatively little attention has been given to the integration of big data analytics and context-aware computing as advanced forms of ICT in the context of smart sustainable cities. This endeavor is a first attempt to address these two major strands of ICT of the new wave of computing in relation to the informational landscape of smart sustainable cities. Therefore, the purpose of this study is to review and synthesize the relevant literature with the objective of identifying and distilling the core enabling technologies of big data analytics and context-aware computing as ecosystems in relevance to smart sustainable cities, as well as to illustrate the key computational and analytical techniques and processes associated with the functioning of such ecosystems. In doing so, we develop, elucidate, and evaluate the most relevant frameworks pertaining to big data analytics and context-aware computing in the context of smart sustainable cities, bringing together research directed at a more conceptual, analytical, and overarching level to stimulate new ways of investigating their role in advancing urban sustainability. In terms of originality, a review and synthesis of the technical literature has not been undertaken to date in the urban literature, and in doing so, we provide a basis for urban researchers to draw on a set of conceptual frameworks in future research. The proposed frameworks, which can be replicated and tested in empirical research, will add additional depth and rigor to studies in the field. In addition to reviewing the important works, we highlight important applications as well as challenges and open issues. We argue that big data analytics and context-aware computing are prerequisite technologies for the functioning of smart sustainable cities of the future, as their effects reinforce one another as to their efforts for bringing a whole new dimension to the operating and organizing processes of urban life in terms of employing a wide variety of big data and context-aware applications for advancing sustainability.

Tectonic perspectives for urban ambiance? Towards a tectonic approach to urban design

Urban challenges derived from climate prospects and densification call for a renewed engagement with the question of the liveability of the built environment. Within this context, the economic and technical concept of our cities is an increasingly dominant aspect, whereas the fragile but vital question of ambiance that seemingly signifies our sense of liveability is often suppressed. This requires us, as architects and urban designers, to refine our descriptions of ambiance as an integral part of the technical construction principles applied in the built environment, hereby considering it a continuous space, as suggested in theories of landscape urbanism. By recalling the etymological meaning of tectonics as a contextual joining of aesthetics and technology at the architectural scale, the paper states that this can be understood as a tectonic challenge which crosses the architectural and urban domains. As a result, the potential is opened up to develop further the theory of landscape urbanism by juxtaposing it with tectonic architectural theory. The paper investigates this potential through a combined conceptual and analytical case, studying whether it is possible to define and describe urban ambiances across scale, in relation to the concept of the built environment, when applying an “urban tectonic” perspective.

Places of urban disorder? Exposing the hidden nature and values of an English private urban allotment landscape

Increasing urbanisation is placing significant development pressure upon our urban spaces and green infrastructure. Allotments have strong cultural roots in the urban domain with emerging evidence of multiple health and quality of life benefits associated with their existence, use and management. However, they represent a remnant landscape; out of order and unproductive according to conventional economic and market assessments of urban land use. Consequently, allotments represent highly contested spaces; as opportunity spaces for redevelopment to meet housing demands or as growing spaces for escape and socialisation. This paper employs a phenomenological approach to explore the values and perceptions of plotholders, residents, planning managers and allotment bodies relating to one privately owned allotment site in Dudley, West Midlands, UK. Our focus on private allotments fills an important research (lack of information on ownership and spatial extent) and policy (treated differently to public allotments as open space in planning policy) gap. Semi-structured interviews reveal that the allotment site is valued by plotholders and nearby residents on a wide range of ecosystem services and community benefits with only minor concerns evident about modern allotment infrastructure and bonfires. This positive picture reflected strong local governance and community relationships. However, there was a misunderstanding among residents that this private allotment had the same level of protection as a municipal site. It is recommended that planning policy treats both municipal and private sites equally and that more research is conducted on the ownership, distribution and governance of private allotment sites given their importance a in urban planning and placemaking.

A Hybrid Approach to Process Planning: The Urban Traffic Controller Example

Automated planning and scheduling are increasingly utilised in solving evsery day planning task. Planning in domains with continuous numeric changes present certain limitations and tremendous challenges to advanced planning algorithms. There are many pertinent examples to the engineering community; however, a case study is provided through the urban traffic controller domain. This paper introduce a novel hybrid approach to state-space planning systems involving a continuous process which can be utilised in several applications. We explore Model Predictive Control (MPC) and explain how it can be introduce into planning with domains containing mixed discrete and continuous state variables. This preserves the numerous benefits of AI Planning approach by the use of explicit reasoning and declarative modelling. It also leverages on the capability of MPC to manage numeric computation and control of continuous processes. The hybrid approach was tested on an urban traffic control network to ascertain it practicability on a continuous domain; the results show its potential to control and optimise heavy volumes of traffic.

Characterizing spatiotemporal dynamics in phenology of urban ecosystems based on Landsat data

Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observations (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14days) start-of-season (SOS) and a later (13–20days) end-of-season (EOS), resulting in an extended (5–30days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (−0.30day per year), and increasing EOS and GSL (0.50 and 0.90day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation types, and different urban-rural settings. The Landsat derived phenology information for urban domains provides more details when compared to the coarse-resolution datasets such as MODIS, thus improves our understanding of human-natural systems interactions (or feedbacks) in urban domains. Such information is very valuable for urban planning in light of rapid urbanization and expansion of major metropolitans at the national and global levels.

Numerical simulation of air pollution due to traffic flow in urban networks

As it is well known, traffic flow is the main pollution source in many urban areas, where the number of vehicles ranges from many thousands to millions. Thus, estimating the pollution emission rate due to traffic flow in big cities is a very hard task. To approach this environmental issue, in this paper we propose a methodology that consists of combining the 1D Lighthill–Whitham–Richards traffic model for road networks with a classical 2D advection–diffusion–reaction pollution model for the atmosphere. Here, the pollution model uses a source term that takes into account the traffic flow contamination by means of a Radon measure supported on a road network within an urban domain. Furthermore, we establish the existence of solution of the coupled model, and detail a complete numerical algorithm to compute it (mainly, interfacing a finite volume scheme based on the supply–demand method for the traffic model, with a characteristics-Lagrange finite element method for the pollution model). Finally, several numerical experiences for a real urban domain (the Guadalajara Metropolitan Area in Mexico) are presented.

A new model of urban cooling demand and heat island—application to vertical greenery systems (VGS)

The relationship between Urban Heat Island (UHI) and energy consumption in buildings has been widely observed and studied. The aim of this paper is to investigate the impact of large-scale deployment of indirect Vertical Greenery Systems (VGS) on the cooling demand of buildings and on the urban microclimate. VGS significantly reduces air temperature and wind speed near the walls. In doing so, it also positively impacts the UHI intensity. This is achieved mainly through the conversion of sensible heat to latent heat mediated by evaporation and transpiration from the VGS foliage. Evapotranspiration is a physically complex phenomenon and its interaction with the building and the urban climate is difficult to model accurately. We propose to use a dynamic nonlinear lumped parameter thermal network model to determine the thermal interactions between the prototypical building, the VGS, the paved road, the urban canopy air and the atmosphere. The model accounts for both sensible and latent exchanges within and outside the building. Solar (short-wave) radiation on building façade and road accounts for shading and unlimited diffuse reflections. Long-wave radiation among surfaces and between surfaces and the sky are estimated using view factors and the fully nonlinear Stefan-Bolzmann law. Building envelope infiltration rate and convective heat transfer coefficient vary with wind speed so as to properly reflect the energetic impact of wind speed attenuation near the wall due to the foliage. The thermal and aerodynamic characterization of the vegetation is based on the formulations proposed by Deardorff (1978). The evapotranspiration rate is estimated based on the Penman formula and is driven by the ‘vapor pressure deficit’ between actual vapor pressure in the ambient air and the saturation vapor pressure assumed to prevail on the surface of leaves. The calculation of sensible and latent heat fluxes between the urban canopy and the first level of the atmosphere considers buoyancy effects, using the coefficients introduced by Mascart et al. (1995). First, a base case model (no VGS) is created and validated using both building energy consumption data and urban air temperature measurements. The validated model is then used to investigate the impact of a large-scale deployment of VGS in the urban context. The weather data and the typical building thermo-physical properties are from the UAE. Comparison of the urban base case to the rural base case (both without VGS) shows a cooling load penalty, due to the UHI, of about 7%. Retrofitting VGS to all buildings in the urban domain of study results in a 5−8% reduction of the cooling load and a dramatic drop of the urban air temperature of about 0.7−0.9°C, reducing the UHI intensity by almost half.

Light and the Manifestation of Performance Place: The Experience of Spaces and Places through a Different Light

Through the practice-based lens of the Night in the Garden at the Royal Botanic Garden Edinburgh (2014) this paper explores how environments, both built and green, can become something powerfully augmented in the regeneration of cities and towns, and introduces the human experience of unexpected events as an affordance of access and belonging. In the last two decades the explosion of the ‘light festival’ as a global phenomenon has created a new night-time language of temporary performance. Our urban environments are straining to develop unique visual representations that have driven a new kind of tourism. The alien performances that play out across our urban centres bring a return to the joy of the unique and the carnivalesque and are situated within the environments that we recognise so differently during the day. This creative practice led perspective, supported exploration of audience engagement and asked questions of how personal and shared experiences are generated and broadcast; whilst recognising this approach as part of a wider place-making phenomena, where visual culture awakens sleeping spaces. The urban domain is a canvas for storytelling open to change each time the festival rolls into town, where physical structures remain unaltered, but our perception of them becomes reanimated.

A Sensitivity Study Relating to Neighbourhood-scale Fast Local Urban Climate Modelling within the Built Environment

The rapid increase in urban populations during the last century, together with the threat of climate change has motivated research focusing on the impact of land-use on urban climates. High-resolution neighbourhood-scale modelling tools developed to account for the complex three-dimensional surfaces and volumes within an urban area are able to predict temperature perturbations over an urban domain with reference to varying land-use. However, land-use classes chosen to model the urban landscape often reflect the function, rather than the material, and hence overlook different building materials that compose the built environment.The purpose of this study is to demonstrate that for a robust appraisal of local climate variations, it is important to use representative land-use parameters that account for materials that form the urban landscape, instead of functions. The response of a high-resolution local climate model to an improved parameterization of the built environment is investigated using the local-scale urban climate modelling tool, ADMS-Urban. In this study, a more elaborate set of land-use classes is collated which distinguishes between different building materials that have varying thermal parameters. A novel approach to calculating the thermal admittance is proposed, reflecting different building materials used for the building facades and the roofs.This study demonstrates that refining model input parameters to correctly represent various construction materials used within the urban tissue, as well as the proposed, advanced method for calculating thermal admittance leads to significant temperature differences compared to when broad assumptions are used, especially under low wind conditions common in equatorial cities.

Numerical simulation of urban impact on precipitation in Tokyo: How does urban temperature rise affect precipitation?

This study explored how heat island intensification affects precipitation in the Tokyo metropolitan area. Numerical experiments were made for the month of August from 2006 to 2013 using the Non-Hydrostatic Model (NHM) with a horizontal grid interval of 2km and the Square Prism Urban Canopy (SPUC) scheme. We performed the experiments with two different specifications for the Tokyo area: the current highly urbanized surface conditions (CRNT experiment) and less urbanized conditions (MDUB experiment). The simulation results suggest that the mean monthly precipitation in the central Tokyo area was approximately 10% larger in the CRNT experiment than in the MDUB experiment, associated with a mean temperature rise of as much as 1°C. We also examined the modification of daily precipitation characteristics in the two experiments. The CRNT experiment generally yielded larger amounts of area-maximum precipitation in the urban domain; however, differences between the experiments in daily precipitation varied among cases. Composite analysis was performed to investigate the processes associated with the differences in simulated precipitation. We found that in afternoon rainfall cases without preceding precipitation, a thermally induced change in circulation, particularly enhanced ascending motion, played an important role in the precipitation increase in the CRNT experiment.

Teaching urbanism: the Delft approach

The Department of Urbanism at the Faculty of Architecture and Built Environment at the Delft University of Technology has a long tradition in educating generations of internationally oriented designers, planners and researchers in urbanism. Here the domain of urbanism is defined as an interdisciplinary approach that engages in real-world sociocultural, ecological and technological issues affecting urban landscapes, from the perspective of spatial planning and design. Specifically, it combines the disciplines of spatial planning, urban design and landscape architecture, having their own theories, methods and techniques, but also sharing common grounds and being complementary. Urbanism education focuses on specific context-related design tasks, in which knowledge from different disciplines is synthesised into coherent multiscale proposals. This paper aims to elaborate on the foundations of the Delft approach to urbanism education that focuses on the urban landscape as a scale continuum, uses design research and research through design as important teaching and research strategies, and regards mapping and drawing as important tools for thinking. The typical Dutch geographic context and spatial planning traditions are the foundation for this approach. The paper addresses the backgrounds and describes the principles of the present education strategies, learning tactics and examination, and identifies their challenges.

The Intelligenter method (III) for “smarter” standards development and standardisation instruments

This paper shows the need for innovation in the development of standards and standardisation instruments. While standardisation activity overall is growing in terms of the number of standards being developed, exploration of new domains, organisations promoting standards development, etc.; the models and techniques to put forward new standards remain unchanged. This paper presents the third implementation of the Intelligenter Method, this time applied to the reinvention of the standards development model and standardisation practices in general. This new model is exemplified in this paper with a use case in the urban domain, the Cites Standards Institute (CSI 2.0). The CSI 2.0 is a pioneering format of standardisation group consisting of the partnership between a formal standards body, the British Standards Institution (BSI) and an urban innovation centre, Future Cities Catapult (FCC), both UK-based organisations. The CSI 2.0 uses the intelligenter principles to develop more user-driven and participatory-led standards development process. The Intelligenter Method principles consist of the creation of a collaboratory based on multi-stakeholder collaborations in an integrated multi-subsystems physical environment and have been successfully implemented so far in the intelligenter making of plans and projects (I) and in the drafting of policies and regulations (II). This paper presents how these collaboratories can help in the development of intelligenter standards and standardisation instruments (III).

Happiness and the city

Purpose This paper aims to introduce and apply an assessment method designed to measure city satisfaction in relation to the subjective perception of individual well-being. Design/methodology/approach A structural model of residential satisfaction assessment is developed. To test the model, the authors have carried out an empirical research study, using a representative sample (1,636 respondents) of the residents of Perm, a large Russian city. Findings This study demonstrates both the direct and indirect influence of satisfaction with urban services, respondents’ individual characteristics, life satisfaction and happiness on overall city satisfaction. Moreover, this study attempts to explore the causality between subjective well-being and city satisfaction. Research limitations/implications The empirical research is limited to the one-city case. Practical implications This study aimed to provide local policy makers with a more refined tool for decision-making in urban policy, which could be of great importance as far as the city authorities need to set up priorities in urban management, especially under the pressure of limited budgets. Originality/value The results allow for the illustration of the cumulative and hierarchical nature of city satisfaction and highlight the relation of various life and urban domains and their influence on happiness, life satisfaction and city satisfaction.

The effects of wind velocity and building geometry on air change efficiency in light shafts: Case studies

The evaluation of the air quality in light shafts requires a specific study of its air renewal ability due to building shape, dimensions and other external conditions. This research has studied the capacity of light shafts to provide natural ventilation through the air change efficiency concept. A methodology based on the limitation of the computational urban domain is used to adapt the indoor air change efficiency index for outdoor environments. Numerical simulations were performed using CFD and a model that was experimentally validated. The aim is to evaluate the effect of the centreline building width and light shaft dimensions in the air change quality within several wind climates. Results would provide a numerically proven tool for designers, summarised in some design-based strategies in order to select which one improves the air change quality. The results indicate that the light shaft dimension perpendicular to the wind direction has a negligible effect on efficiency. For the range of wind velocities studied (0.75–9.00 m/s), the efficiency decreases at higher velocities, up to −7.41% with respect to the mean. For variations in the wind velocity and the centreline building width, a mean variation of ± 18.77% in the efficiency is obtained. Practical applications: The present methodology defines a proceeding to numerically evaluate the air change efficiency in light shafts inside different dimensional cases of buildings within several urban wind conditions.

Development and application of a high resolution hybrid modelling system for the evaluation of urban air quality

A hybrid modelling system (HMS) was developed to provide hourly concentrations at the urban local scale. The system is based on the combination of a meteorological model (WRF), a chemical and transport eulerian model (CAMx), which computes concentration levels over the regional domains, and a lagrangian dispersion model (AUSTAL2000), accounting for dispersion phenomena within the urban area due to local emission sources; a source apportionment algorithm is also included in the HMS in order to avoid the double counting of local emissions.The HMS was applied over a set of nested domains, the innermost covering a 1.6 × 1.6 km2 area in Milan city center with 20 m grid resolution, for NOX simulation in 2010. For this paper the innermost domain was defined as “local”, excluding usual definition of urban areas. WRF model captured the overall evolution of the main meteorological features, except for some very stagnant situations, thus influencing the subsequent performance of regional scale model CAMx. Indeed, CAMx was able to reproduce the spatial and temporal evolution of NOX concentration over the regional domain, except a few episodes, when observed concentrations were higher than 100 ppb. The local scale model AUSTAL2000 provided high-resolution concentration fields that sensibly mirrored the road and traffic pattern in the urban domain. Therefore, the first important outcome of the work is that the application of the hybrid modelling system allowed a thorough and consistent description of urban air quality. This result represents a relevant starting point for future evaluation of pollution exposure within an urban context.However, the overall performance of the HMS did not provide remarkable improvements with respect to stand-alone CAMx at the two only monitoring sites in Milan city center. HMS results were characterized by a smaller average bias, that improved about 6–8 ppb corresponding to 12–13% of the observed concentration, but by a lower correlation, that worsened around 1–3% (e.g. from 0.84 to 0.81 at Senato site), due to the concentration peaks produced by AUSTAL2000 during nighttime stable conditions. Additionally, the HMS results showed that it was unable to correctly take into account some local scale features (e.g. urban canyon effects), pointing out that the emission spatialization and time modulation criteria, especially those from road traffic, need further improvement.Nevertheless, a second important outcome of the work is that some of the most relevant discrepancies between modelled and observed concentrations were not related to the horizontal resolution of the dispersion models but to larger scale meteorological features not captured by the meteorological model, especially during winter period. Finally, the estimated contribution of the local emission sources accounted on the annual average for about 25–30% of the computed concentration levels in the innermost urban domain. This confirmed that the whole Milan urban area as well as the outside background areas, accounting all sources outside the innermost domain, play a key role on air quality. The result suggests that strictly local emission policies could have a limited and indecisive effect on urban air quality, although this finding could be partially biased by model underestimation of the observed concentration.