publications
hadi currenlty seems to have 2 book chapter(s), 0 non-reviewed preprint(s), 25 paper(s), 2 report(s), and 7 conference paper(s) to show off.
chapters
- Support Place-Based and Inclusive Supply Chain, Employment and Skills Strategies for Housing-Energy RetrofitRachel Macrorie, Hadi Arbabi, Will Eadson, Richard Hanna, Kaylen Camacho McCluskey, Kate Simpson, and Faye WadeIn Strengthening European Energy Policy: Governance Recommendations From Innovative Interdisciplinary Collaborations, 2024
To achieve the recommendation stated in the chapter title, we propose the following:Member States should empower municipalities with resources and training to develop Building Renovation Plans supported by One-Stop Shops focused on inclusive local supply chain development, employment and skills priorities, as well as serving housing retrofit consumers.Municipalities should use procurement frameworks and Direct Labour Organisations to ensure a pipeline of retrofit work and support training for good quality employment.Member States should implement licensing or minimum competency standards for housing retrofit professionals, ensuring certification schemes encompass a wider range of skills.Retrofit is an opportunity to enable new groups to enter the construction sector. Municipalities should co-create partnerships alongside employees, and support unionisation, to promote training and work opportunities for women and minorities.Developing inclusive pathways to a skilled housing-energy retrofit workforce is a socio-technical problem, requiring insights from social, policy, building and engineering disciplines, because retrofit interweaves human and technical practices and processes.
- Resource Effectiveness in and Across Urban SystemsHadi Arbabi, and Ling Min TanIn The Palgrave Encyclopedia of Urban and Regional Futures, 2020
papers
- RSOSParametric Contribution of Building Form to Whole-Life Carbon Decision-MakingDanielle Abbey, Hadi Arbabi, and Danielle Densley TingleyRoyal Society Open Science, Jul 2025
Existing buildings generate 30% of global emissions because of the energy required to heat, cool and power them. Mass improvements in building fabric efficiency and heating/cooling systems are therefore imperative. Fast-running modelling approaches are thus necessary to identify appropriate interventions for the global building stock. This paper presents a new parametric formulation to determine the best whole-life carbon intervention as a function of building form. We demonstrate that buildings of inefficient form have greater potential for energy savings, providing a useful prioritization tool for future planning decisions. We present results as a novel graphical tool, which can be used to identify the lowest carbon scenario for any building form across a combination of building storeys and glazing ratios. This is applied to a cool-temperate climate, comparing a retrofit scenario, to the option of replacement with new construction. Finally, we apply the formulation to a subset of the UK educational building stock, assessing 15 193 forms. For this scenario, we conclude that retrofit always results in lower whole-life carbon compared to replacement with attainable new construction standards. This work provides practical assistance with early stage decision-making and theoretical understanding of how form influences energy consumption and whole- life carbon emissions.
- RSPAAn Emergent Optimal Resource Allocation for Climate Resilience of Transport Infrastructure NetworksQianqian Li, Hadi Arbabi, and Giuliano PunzoProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Jul 2025
Current infrastructure networks must be climate resilient to continue meeting service demand into the next decades with climate change rapidly pushing infrastructure assets towards or beyond their initial design envelope. At system level, this corresponds to the ability to deliver services when parts of the infrastructure become isolated following local asset failures. Local shielding strategies are typically formulated using abstract network metrics or global optimization methods. The former are agnostic to the specificity of infrastructure systems, while the latter tend to be hardly scalable for large infrastructure networks. Here, we develop an optimal limited-resource allocation strategy to increase network resilience, combining the input sparsity of abstract network metrics with transparency of optimization methods. We focus on transport networks and maximizing the expected throughput of services. We consider upgrading costs as proportional to the desired increase in failure load from climate shocks. We benchmark our method by applying it to the UK freight railway considering shocks induced by an end-of-century RCP8.5 climate change scenario. A closed-form solution naturally emerges for the ranking of the network assets that allows for optimal distribution of limited asset reinforcement investments. We show that this attains better resilience improvements compared to existing heuristic global optimization methods.
- EnergBuildLearning from Other Cities: Transfer Learning Based Multimodal Residential Energy Prediction for Cities with Limited Existing DataYulan Sheng, Hadi Arbabi, Wil Oc Ward, and Martin MayfieldEnergy and Buildings, Jul 2025
Reliable prediction of residential energy consumption is essential for informing energy efficiency policies and retrofit strategies. However, traditional data-driven approaches are often constrained by the availability and quality of data. This study presents a novel approach combining multimodal neural networks with a transfer learning framework, leveraging both tabular and visual data to enhance prediction accuracy and enable knowledge transfer from data-rich to data-poor regions. Case studies conducted in Barnsley, Doncaster, and Merthyr Tydfil demonstrated that the proposed approach outperforms traditional mono-modal models. The multimodal model improved prediction accuracy significantly, achieving a MAPE reduction from 1.15 (with only visual data) and 0.86 (with only tabular data) to 0.43 (with both visual and tabular data), while the inclusion of transfer learning offers further performance improvements in data-scarce regions, with up to 63.6 % error reduction. Explainable AI is utilised to validate the model’s interpretability, confirming key features such as floor and wall insulation conditions as pivotal in energy consumption predictions. This integrated framework offers actionable insights for policymakers, facilitating data-driven decisions to enhance energy efficiency in diverse urban settings.
- SciRepCity-Scale Residential Energy Consumption Prediction with a Multimodal ApproachYulan Sheng, Hadi Arbabi, Wil O. C. Ward, Mauricio A. Álvarez, and Martin MayfieldScientific Reports, Feb 2025
The key role of buildings in tackling climate change has gained global recognition. To avoid unnecessary costs and time wasted, it is important to understand the conditions and energy usage for existing housing stock to identify the most important features affecting energy consumption and to guide the relevant retrofit measures. This paper investigated how the spatial, morphological and thermal characteristics of residential houses contribute to housing energy consumption. Additionally, it presents a rapid assessment tool using minimum data input to answer two main questions: 1) What type of properties may need retrofit? 2) What building elements/features may be prioritised to be retrofitted? A case study was performed with around 143,000 residential properties in Sheffield. An automated machine approach was applied which successfully estimated the energy consumption of target buildings with an \\R^2\\score of 0.828. Permutation feature importance and partial dependence of the features were examined against energy consumption. The results indicate that housing sizes and conditions of the external walls are found to be the most important features when estimating the energy consumption of residential buildings in Sheffield. Relatively larger and older detached houses in neighbourhoods with higher build density may benefit the most from home upgrading projects for energy consumption reduction.
- RegStudBuilding Geodemographic Regions: Commuting, Productivity and Uneven Spatial Development in England and WalesRegional Studies, Feb 2025
We develop and apply a novel geodemographic classification of commuting flows to delineate 486 functional labour market areas (LMAs) across six commuter groups in England and Wales. Framed by the north–south divide, we then use settlement scaling to examine how economic and infrastructural agglomeration influence productivity, using the geodemographic LMAs as our base units. We find that disparities in mobility and infrastructure contribute to spatial productivity differences, with poorer intra-city connectivity in northern regions. Even among LMAs with similar commuter profiles, productivity diverges across the divide, highlighting how economic and infrastructural inequalities reinforce commuting interactions and regional productivity gaps.
- ESTComponent-Level Residential Building Material Stock Characterization Using Computer Vision TechniquesMenglin Dai, Jakub Jurczyk, Hadi Arbabi, Ruichang Mao, Wil Ward, Martin Mayfield, Gang Liu, and Danielle Densley TingleyEnvironmental Science & Technology, Feb 2024
Residential building material stock constitutes a significant part of the built environment, providing crucial shelter and habitat services. The hypothesis concerning stock mass and composition has garnered considerable attention over the past decade. While previous research has mainly focused on the spatial analysis of building masses, it often neglected the component-level stock analysis or where heavy labor cost for onsite survey is required. This paper presents a novel approach for efficient component-level residential building stock accounting in the United Kingdom, utilizing drive-by street view images and building footprint data. We assessed four major construction materials: brick, stone, mortar, and glass. Compared to traditional approaches that utilize surveyed material intensity data, the developed method employs automatically extracted physical dimensions of building components incorporating predicted material types to calculate material mass. This not only improves efficiency but also enhances accuracy in managing the heterogeneity of building structures. The results revealed error rates of 5 and 22% for mortar and glass mass estimations and 8 and 7% for brick and stone mass estimations, with known wall types. These findings represent significant advancements in building material stock characterization and suggest that our approach has considerable potential for further research and practical applications. Especially, our method establishes a basis for evaluating the potential of component-level material reuse, serving the objectives of a circular economy.
- IEEEA Novel Approach to Climate Resilience of Infrastructure NetworksQianqian Li, Giuliano Punzo, Craig Robson, Hadi Arbabi, and Martin MayfieldIEEE Systems Journal, Feb 2024
With a changing climate, the frequency and intensity of extreme weather events are likely to increase, posing a threat to infrastructure systems’ resilience. The response of infrastructure systems to localised failures depends on whether assets are affected randomly, in a targeted strategic way, or any way in between. More than that, infrastructure decisions today, including new routes or improvements to existing assets, will underpin the behaviour of the systems over the next century. It is important to separate and analyse the case of climate-based disruptions and how they affect systems’ resilience. This paper presents a probabilistic resilience assessment framework where failure scenarios and network disruptions are generated using weather propdf data from climate prediction models with component-level fragility functions. A case study is then carried out to quantify the resilience of Great Britain’s railway passenger transport system to high-temperature-related track buckling under the Representative Concentration Pathway 8.5 (RCP8.5) climate change scenario. A 95-year horizon on the resilience of the railway system is drawn. The results also reveal the non-linear responses of the railway system to the increasing temperature and show that models considering random asset failures overestimate the system’s resilience.
- PiRSRegional Economic Resilience, Trophic Characteristics, and Ecological AnalogiesHadi Arbabi, and Giuliano PunzoPapers in Regional Science, Dec 2023
Works on regional resilience have at times borrowed from the engineering and ecological framing of system resilience. In ecological contexts, system resilience is rooted in network structure and its characteristics. Here, we empirically investigate the relationship between regional economic resilience and regional trophic characteristics across regional and national boundaries. We consider 249 NUTS2 regions across 24 countries during the 2000-2010 period. We observe strong links between regional resilience and trophic metrics borrowed from the ecological literature. Our results further highlight regional trophic characteristics as a spatially heterogeneous intermediary for feedback effects between economic structure and output of regions.
- JIEBuilt Environment Stocks in the Context of a Master Planned City: A Case Study of Chandigarh, IndiaWill Mihkelson, Hadi Arbabi, Stephen Hincks, and Danielle Densley TingleyJournal of Industrial Ecology, Jul 2023
Construction materials accumulate in the built environment forming material stocks of buildings and infrastructure, providing various services to society that result in a nexus of human development and environmental impact. Meanwhile, unprecedented urbanization in the Global South is set to put significant demand on the resources required to ensure adequate standards of living in new and existing urban areas. This is particularly important within India, however no study has yet explored material stocks within cities in India or within master planned urban areas designed to accommodate urbanization and a high standard of living. The present study begins to fill these gaps and aims to investigate patterns of built environment material stock accumulation in Chandigarh, an exceptionally quickly developed city master planned to ensure universally high standards of living through a unique urban form. We adopt a bottom-up approach to quantify the residential building and road material stocks at the city and sub-city scale. The results reveal that the master plan, while enabling high standards of living, has resulted in a relative accumulation of road to building stock that is significantly larger than in other cities. This is shown to be environmentally detrimental as future urban development is limited and promotes demolition of existing stocks, whose composition severely limits their potential as secondary resources. The study therefore provides empirical evidence to support the integration of material stock assessments into urban planning and development to ensure resource efficient provisioning of key services.
- BAEEstimating Energy Consumption of Residential Buildings at Scale with Drive-by Image CaptureWil O. C. Ward, Xinyi Li, Yushu Sun, Menglin Dai, Hadi Arbabi, Danielle Densley Tingley, and Martin MayfieldBuilding and Environment, Mar 2023
Data driven approaches to addressing climate change are increasingly becoming a necessary solution to deal with the scope and scale of interventions required to reach net zero. In the UK, housing contributes to over 30% of the national energy consumption, and a massive rollout of retrofit is needed to meet government targets for net zero by 2050. This paper introduces a modular framework for quantifying building features using drive-by image capture and utilising them to estimate energy consumption. The framework is demonstrated on a case study of houses in a UK neighbourhood, showing that it can perform comparatively with gold standard datasets. The paper reflects on the modularity of the proposed framework, potential extensions and applications, and highlights the need for robust data collection in the pursuit of efficient, large-scale interventions.
- ERLTowards an Automated Workflow for Large-Scale Housing RetrofitLing Min Tan, Hadi Arbabi, Wil Ward, Xinyi Li, Danielle Densley Tingley, Ahsan Khan, and Martin MayfieldEnvironmental Research Letters, Mar 2023
- STOTENThe Intrinsic Cybernetics of Large Complex Systems and How Droughts Turn into FloodsGiuliano Punzo, and Hadi ArbabiScience of The Total Environment, Mar 2023
The cyber-physical nature of engineering systems requires the smooth integration of decision making across soft and hard infrastructure. This need is common to any systems where decision making considers multiple complex systems such as the climate, the natural and built environment, and the dynamics of large organisations. As an example, in the Anthropocene, acute droughts and floods cannot only be imputed to more extreme variations of the climate patterns, but also to the alteration of the habitable environment and of the resources that support it, hence to their governance and management. In this discussion paper we present arguments about the extent to which the natural environment is modified to support urbanisation. We expose the cyber-physical nature of large infrastructure systems taking as an example the events of the 2011 Brisbane flood and the operations of the damming system of the river Brisbane. Using literature resources and data, we show how flood defence devices had to provide for a population of almost 2 million people, while being engineered when the population was less than one million, with increase in water withdrawal mainly due to residential utilities. We show how the cyber-physical aspects of the problem materialised in moth-long delays in the governance and management structure and made the flood event transcend the boundary of a purely climatic or engineering incident. Looking beyond the Brisbane example, our conclusions point at overcoming the discontinuity between operation, management and political layers when operating on cyber-physical systems such as freshwater networks.
- MDPIScalable Residential Building Geometry Characterisation Using Vehicle-Mounted Camera SystemEnergies, Mar 2022
Residential buildings are an important sector in the urban environment as they provide essential dwelling space, but they are also responsible for a significant share of final energy consumption. In addition, residential buildings that were built with outdated standards usually face difficulty meeting current energy performance standards. The situation is especially common in Europe, as 35% of buildings were built over fifty years ago. Building retrofitting techniques provide a choice to improve building energy efficiency while maintaining the usable main structures, as opposed to demolition. The retrofit assessment requires the building stock information, including energy demand and material compositions. Therefore, understanding the building stock at scale becomes a critical demand. A significant piece of information is the building geometry, which is essential in building energy modelling and stock analysis. In this investigation, an approach has been developed to automatically measure building dimensions from remote sensing data. The approach is built on a combination of unsupervised machine learning algorithms, including K-means++, DBSCAN and RANSAC. This work is also the first attempt at using a vehicle-mounted data-capturing system to collect data as the input to characterise building geometry. The developed approach is tested on an automatically built and labelled point cloud model dataset of residential buildings and shows capability in acquiring comprehensive geometry information while keeping a high level of accuracy when processing an intact model.
- RSERNet Zero by 2050: Investigating Carbon-Budget Compliant Retrofit Measures for the English Housing StockXinyi Li, Hadi Arbabi, George Bennett, Tadj Oreszczyn, and Danielle Densley TingleyRenewable and Sustainable Energy Reviews, Mar 2022
The UK has enacted one of the most ambitious carbon reduction targets striving for net zero emissions by 2050. A major challenge to achieving this is decarbonizing heating demand with almost 25 m homes in need of retrofit. This paper explores a range of retrofit interventions to the English residential stock. These are deployed immediately in 2021 to investigate the maximum carbon reduction that could be achieved. The impact of these interventions on embodied and operational carbon emissions is estimated from 2021 to 2050. The resulting emissions are compared to estimated national carbon budgets, in order to ascertain, if, and with what combination of retrofit measures, the English housing stock can stay within carbon budgets. The results show that mass deployment of air source or ground source heat pumps can reliably achieve combined embodied and operational emissions within national carbon budgets by 2050. The careful selection of insulation materials is key in bringing down the embodied emissions, particularly to meet stricter carbon budgets. The identified scale and pace of deployment thus needed to stay within carbon budgets is likely to pose enormous practical challenges. To overcome these challenges, we argue for (a) urgently increasing both heat pump deployment, and renewable generation targets beyond existing pledges, (b) increasing social awareness of residential retrofit benefits, and (c) providing more attractive financing options to incentivise and facilitate retrofit uptake.
- JIEA Scalable Data Collection, Characterization, and Accounting Framework for Urban Material StocksHadi Arbabi, Maud Lanau, Xinyi Li, Gregory Meyers, Menglin Dai, Martin Mayfield, and Danielle Densley TingleyJournal of Industrial Ecology, Mar 2022
Building stocks represent an extensive reservoir of secondary resources. However, common bottom-up characterization of these, often based on archetypal classification of buildings and their corresponding material intensity, are still not suitable to adequately inform circular economic strategies. Indeed, these approaches typically result in a loss of building-specific details, and a building stock characterization in terms of material mass, for example, glass, rather than component, for example, window. To deliver this higher resolution of details, a scalable approach to urban stock characterization, that enables a bottom-up estimation of building stocks at the building component level, is needed. In this paper, we present a framework to automate the characterization of urban stock. By using and combining a mobile-sensing approach with computer vision, urban stocks can be captured as 3D surface maps allowing the identification and semantic classification of stock objects, components, and materials. We demonstrate the potential of this framework through a case study of a neighborhood in Sheffield, UK, by using a prototype workflow comprising a custom-made mobile-sensing platform and an existing suite of neural network models to calculate an estimate count of buildings external doors and windows. The prototype implementation of the framework achieves comparable total and building-level component counts with those achieved through manual human counts. Such automated estimation of components enables an understanding of opportunities across the circular economic hierarchies and informs stakeholders across the supply chain to better prepare for the implementation of circular strategies including building refurbishments.
- MDPIComment on Bettignies et al. The Scale-Dependent Behaviour of Cities: A Cross-Cities Multiscale Driver Analysis of Urban Energy Use. Sustainability 2019, 11, 3246Sustainability, Mar 2022
Bettignies et al. examine power-law relationships between drivers of energy use and urban features at city and infra-city levels for ten different cities in six countries across four continents, featuring a wide distribution of urban indicators from various data sources. The authors employ univariate linear regression models using selected log-transformed indicators to investigate whether the intensity of energy use scales with urban indicators such as population size, density, and income. Bettignies et al. suggest that based on their findings, the urban energy-use drivers are in fact scale-dependent, and that their results reveal a substantial heterogeneity across and within cities. They reference this as why more consideration needs to be paid to local factors when devising urban policy. On this note, we argue that Bettignies et al. appear to have not only misunderstood the urban scaling literature they have cited, but have also employed flawed methodological design in their analysis that ultimately leaves their conclusions unsubstantiated.
- npjUrbSusMapping Resource Effectiveness across Urban Systemsnpj Urban Sustainability, Mar 2021
Cities and their growing resource demands threaten global resource security. This study identifies the hotspots of imports in cities to redirect resources to where they are most needed, based on the system overall resource effectiveness to maximise the use of all resources available. This paper develops a taxonomy of resource-use behaviour based on the clustering patterns of resource utilisation and conversion across interconnected urban systems. We find high tendencies of consumer-like behaviour in a multi-city system because tertiary sectors are concentrated in urban areas while the producing sectors are located outside and hence, results in high utilisation but low output. The clustering taxonomy emphasises that the absence of producers in the system causes cities to rely on the imported resources for growth. Cities can be resource-effective by having a more diversified industrial structure to extend the pathways of resource flows, closing the circularity gap between the suppliers and consumers.
- RSOSOn the Use of Random Graphs in Analysing Resource Utilization in Urban SystemsHadi Arbabi, Giuliano Punzo, Gregory Meyers, Ling Min Tan, Qianqian Li, Danielle Densley Tingley, and Martin MayfieldRoyal Society Open Science, Mar 2020
Urban resource models increasingly rely on implicit network formulations. Resource consumption behaviours documented in the existing empirical studies are ultimately by-products of the network abstractions underlying these models. Here, we present an analytical formulation and examination of a generic demand-driven network model that accounts for the effectiveness of resource utilization and its implications for policy levers in addressing resource management in cities. We establish simple limiting boundaries to systems’ resource effectiveness. These limits are found not to be a function of system size and to be simply determined by the system’s average ability to maintain resource quality through its transformation processes. We also show that resource utilization in itself does not enjoy considerable size efficiencies with larger and more diverse systems only offering increased chances of finding matching demand and supply between existing sectors in the system.
- JRSS AProductivity, Infrastructure and Urban Density—an Allometric Comparison of Three European City Regions Across ScalesHadi Arbabi, Martin Mayfield, and Philip McCannJournal of the Royal Statistical Society: Series A (Statistics in Society), Mar 2020
Agglomeration-based arguments citing Dutch and German city regions have been a primary driver in advocating intercity transport strategies in the north of England.We adopt an allometric urban model investigating the applicability and transferability of these transport-led agglomerative strategies promoted to address England’s regional economic underperformance. This is undertaken through a comparative study of the size–cost performance balance of three city regions and the overall urban networks in the Netherlands and Germany, and England and Wales by using city units defined at different spatial scales. Although our results support a case for better mobility and transport comparing the three urban networks regardless of the spatial scales, comparisons of specific city regions indicate a more nuanced interplay of productivity, mobility infrastructure and urban density.
- SEAOn the Development Logic of City-Regions: Inter- versus Intra-City Mobility in England and WalesHadi Arbabi, Martin Mayfield, and Philip McCannSpatial Economic Analysis, Mar 2019
This paper combines an allometric urban model with a hierarchical clustering method in order to investigate the effects of distance and spatial scale on the geography of transport-led agglomerative strategies implemented to address comparative regional economic underperformance. The study is undertaken in the context of the urban system in England and Wales by constructing agglomerated city-regions using city units defined at different spatial scales. As is shown, a greater importance than is currently given lies in local and intra-city mobility as compared with longer distance transport schemes promoted using agglomeration theory principles. This signals a need for prioritization of mobility improvements at smaller intra-urban distances coupled with long-term densification efforts as integral to the performance of longer distance inter-city pairings.
- RegStudUrban Performance at Different Boundaries in England and Wales through the Settlement Scaling TheoryHadi Arbabi, Martin Mayfield, and Gordon DabinettRegional Studies, Mar 2019
The relationship between transport-led agglomeration and economic performance is evaluated in an English and Welsh context. We examine the effects of scale, i.e., inter- versus intra-city mobility infrastructure, on urban size–cost performance. An additional contribution of this paper lies in its use of power-law scaling models of urban systems, enabling an assessment of optimality in the trade-off between economic output and mobility costs accounting for ease of access within cities coupled with their built density. Findings suggest economic underperformance coincides with inadequate mobility at both inter- and intra-city scales, while overperformance is accompanied by overgrown urbanized area and escalating mobility costs.
- ApplEnergAn Ecological-Thermodynamic Approach to Urban Metabolism: Measuring Resource Utilization with Open System Network Effectiveness AnalysisApplied Energy, Mar 2019
Cities have evolved as centers of economic growth and often described as open systems where the intake of resources is heavily dependent on flows imported from the external environment. The question is, how much of the resource available in cities is effectively utilized? In response, this paper develops an ecological-thermodynamic approach to assess the ability of a system to make full use of the resources available and reduce the demand for new resources. In this work, open system network effectiveness analysis is introduced as a novel assessment method to investigate the cities’ producer and consumer behaviors by studying the resource flow connections and the interactions between the socio-economic sectors. Investigation on the urban flows network evaluates the ability of the system to utilize the resource imported through the effectiveness of utilization indicator and the ability to convert the resource imported to useful products through the effectiveness of conversion indicator. The effectiveness indicators, utilization and conversion, represent the consumption and production characteristics of the system respectively. This is tested through a case study conducted for Singapore city over the time period 2005–2014. The effectiveness results show that the city, on average, has utilized 45% of the maximum extractable usefulness from the resources imported throughout the years, with the lowest effectiveness, 39%, and the highest effectiveness, 50%, in the years 2007 and 2014 respectively. The trajectory of effectiveness results throughout the years suggests a trade-off relationship between the producers and consumers to balance the production and consumption of resources in the city.
- RCREcological Network Analysis on Intra-City Metabolism of Functional Urban Areas in England and WalesLing Min Tan, Hadi Arbabi, Qianqian Li, Yulan Sheng, Danielle Densley Tingley, Martin Mayfield, and Daniel CocaResources, Conservation and Recycling, Mar 2018
The UK has one of the world’s most urbanised societies where nearly 83% of the total population lives in cities. The continuing population growth could lead to increases in environmental pollutions and congestion within cities. The framework of urban metabolism uses an analogy between cities and ecosystems to study the metabolic processes within complex urban systems akin to natural biological systems. It remains as a challenge to fully understand the complicated distribution of resource flows within an urban network. In this paper, Ecological Network Analysis was applied to study the intra-city flows between economic sectors in 35 functional urban areas in order to investigate their respective metabolic relationships. The intra-city flows network of each area was also supplemented with the geographical distance between the workplace zones to study the impacts of spatial distribution on the density of resource flows. The metabolic systems were dominated by 64% of exploitative relationships with an average mutualism index of 0.93 and synergism index of 3.56 across all 35 areas. The consumption-control and production-dependency relationships revealed the hierarchical orders among the sectors resembling the pyramidal structure of an urban ecosystem. Network community classification emphasized the importance of inter-relationship within the organisation of each community class. The producer-type and consumer-type communities showed the tendencies of those sectors to cluster based on their respective hierarchical roles in the ecosystem. This work provides an insight into the wide range of intra-city ecological metabolic characteristics which can potentially expand to a multi-scale assessment of urban metabolism across the country.
- RCRComments on ‘A Multi-Level Framework for Metabolism in Urban Energy Systems from an Ecological Perspective’ by Pulido Barrera et al. (2018)Hadi Arbabi, Ling Min Tan, and Martin MayfieldResources, Conservation and Recycling, Mar 2018
- MDPIUrban and Rural—Population and Energy Consumption Dynamics in Local Authorities within England and WalesHadi Arbabi, and Martin MayfieldBuildings, Mar 2016
The formulation of feasible and pragmatic policies that mitigate climate change would require a thorough understanding of the interconnectivity that exists between environment, energy, and the composition of our settlements both urban and rural. This study explores the patterns of energy consumption in England and Wales by investigating consumption behavior within domestic and transport sectors as a function of city characteristics, such as population, density, and density distribution for 346 Local Authority Units (LAU). Patterns observed linking energetic behavior of these LAUs to their respective population and area characteristics highlight some distinctly contrasting consumption behaviors within urban and rural zones. This provides an overview of the correlation between urban/rural status, population, and energy consumption and highlights points of interest for further research and policy intervention. The findings show that energy consumption across cities follows common power law scaling increasing sub-linearly with their population regardless of their urban/rural classification. However, when considering per capita and sector specific consumptions, decreasing per capita consumption patterns are observed for growing population densities within more uniformly populated urban LAUs. This is while rural and sparsely populated LAUs exhibit sharply different patterns for gas, electricity, and transport per capita consumption.
reports
- SYSCReport on Intra- and Inter-Generated Traffic in South YorkshireSamantha Ivings, Hadi Arbabi, and Giuliano PunzoMar 2024
This report provides quantitative insights into how much traffic passing through each of the four South Yorkshire Local Authorities is generated inside and outside of the region. Data used was collected by The Floow via car-mounted devices. These sensors are black boxes mounted on a small proportion of private cars, so total figures are obtained by expanding the data available to the volume of the circulating fleet. Origin-destination data describing estimated daily traffic counts for journeys made on weekdays in 2019 was used for the report. The data refers to all vehicles that transited through South Yorkshire in 2019, regardless of their origin and destination, which could be within or outside South Yorkshire.
- PINQuantifying Agglomeration Productivity Potential in Long-Term Infrastructure PlanningHadi Arbabi, Jordan Pannell, Stephen Hincks, and Giuliano PunzoMar 2020
confs
- Fabric Energy Efficiency in Housing Retrofit: The Role of Whole-Life Operational and Embodied Carbon EmissionsMay Zune, Hadi Arbabi, and Danielle Densley TingleyIn PLEA 2024: (Re)Thinking Resilience, Mar 2024
UK housing decarbonization through retrofit faces massive challenges to be consistent with 2050 Zero Carbon targets, considering the large proportion of inefficient building stock. As the design for fabric-energy-efficiency and the demand for energy consumption from modern lifestyle increases, its trade-off with the embodied carbon investment and the unintended consequences from a high-performance building envelope becomes increasingly important. We developed a model which considered both building performance metrics and existing UK Energy Performance Certificates (EPCs) metrics to investigate long-term quality and acceptability of retrofits, i.e., overheating mitigation and ventilation improvement, considering a 20- and 50-year building lifespan. The model combines energy demand assessment, indoor environmental assessment, the Future Homes Standard and EPC’s cost-energy-carbon metric. A dynamic simulation study for seven predominant built forms in the South Yorkshire housing stock was designed to investigate deep retrofit results under predicted future climate conditions in the 2030s, 2050s and 2080s. The study focused on whole life emissions from operational and embodied carbon over different timescales whilst considering a healthy indoor environment in buildings. The findings present an efficient way of combining building performance metrics and EPC metrics in a housing retrofit model that aids decision-making for homeowners, stakeholders and policymakers.
- EGUExtreme Climate Change Impacts on Urban Infrastructure and Support SystemsTom Wood, Hadi Arbabi, and Martin MayfieldIn EGU General Assembly 2023, Apr 2023
In this study we present synthesised evidence from the most extreme estimates of climate change effects such as extreme temperatures, precipitation, flooding, drought, wildfire, storms and sea-level rise from ECC scenarios, assessing the potential worst-case impacts on urban systems with a focus on heterogeneous regional impacts and the potential need for significant pre-emptive adaptation efforts. Global cities are ranked according to their potential vulnerability to ECC impacts with the aim of identifying cities where critical infrastructure is at risk of failure and what ECC effects they are likely to experience. We highlight gaps in current understanding and the need to focus research in this area while outlining a research agenda to explore ECC effects on urban infrastructure, including case studies of infrastructure systems in cities identified as vulnerable, with the aim of generating evidence for use in policy development.
- IOPDemolish or Reuse? – The Balance between Operational and Embodied Emissions in the Retrofit of Commercial BuildingsDanielle Abbey, Hadi Arbabi, Charles Gillott, Wil O. C. Ward, and Danielle Densley TingleyIn IOP Conference Series: Earth and Environmental Science, Apr 2022
There are two clear options for reducing the emissions of poorly-performing buildings: refurbishment of the space to a higher standard or demolition and replacement with a better performing building. Non-residential buildings are subject to the latter of these options more than dwellings due to higher rates of ownership changes. This study assesses the carbon emissions of each of the above options for a poorly-performing retail building in Sheffield, UK. The embodied carbon and operational performance of each scenario are calculated to identify the most sustainable option over a 50 year lifespan. The scenario with the lowest emissions is found to be a retrofit case study relying upon electricity as its sole fuel source. The new build scenarios emitted significantly more carbon over the building’s lifespan despite performing better operationally than the refurbishment scenario. It was also found that, due to the decarbonisation of the national grid, relying on gas boilers instead of electric fuel sources would make carbon emissions approximately 2.5x bigger in the refurbishment model, despite being legal under UK building regulations.
- IOPDeep Multimodal Learning for Residential Building Energy PredictionYulan Sheng, Wil O. C. Ward, Hadi Arbabi, Mauricio Álvarez, and Martin MayfieldIn IOP Conference Series: Earth and Environmental Science, Apr 2022
The residential sector has become the second-largest energy consumer since 1987 in the UK. Approximately 24 million existing dwellings in England made up over 32% of the overall energy consumption in 2020. A robust understanding of existing buildings’ energy performance is therefore critical in guiding proper home retrofit measures to accelerate towards meeting the UK’s climate targets. A substantial number of predictions at a city scale rely on available data, e.g., Energy Performance Certificates (EPCs) and GIS products, to develop statistical and machine learning models to estimate energy consumption. However, issues with existing data are not negligible. This work adopted the idea of deep multimodal learning to study the potential for using Google Street View (GSV) images as an additional input for residential building energy prediction. 20,031 GSV images of 5,933 residential buildings in central Barnsley, UK, have been selected for a case study. All images were pre-processed using a state-of-the-art object detection algorithm to minimise the noise caused by other elements that may appear nearby. Building specifications that cannot be easily determined by the appearance are extracted from existing EPC information as text-based inputs for prediction. A multimodal model was designed to jointly take images and texts as inputs. These inputs are first propagated through a convolutional neural network and multi-layer perceptron, respectively, before being combined into a connected network for final energy prediction. The multi-input model was trained and tested on the case study area and predicted an annual energy consumption with a mean absolute difference of 0.01kWh/m2 per annum on average compared with what is recorded in the EPC. The difference between the predicted results and the EPC may also provide some hints on the bias the certificates potentially contain.
- IOPMeasuring the Cityscape: A Pipeline from Street-Level Capture to Urban QuantificationIn IOP Conference Series: Earth and Environmental Science, Apr 2022
Any solution to achieving climate targets must be performed at scale. Data driven methods allow expert modelling to be emulated over a large scope. In the UK, there are nearly 30 million residential properties, contributing to over 30% of the national energy consumption. As part of the UK Government’s requirement to meet net-zero emissions by 2050, retrofitting residential buildings forms a significant part of the national strategy. This work addresses the problem of identifying, characterising and quantifying urban features at scale. A pipeline incorporating photogrammetry, automatic labelling using machine learning, and 3-D geometry has been developed to automatically reconstruct and extract dimensional and spatial features of a building from street-level mobile sensing.
- WSBEThe Importance of Understanding the Material Metabolism of the Built EnvironmentDanielle Densley Tingley, Hadi Arbabi, and Michael DurkinIn World Sustainable Built Environment Conference, Apr 2017
Construction materials are a crucial part of our built environment, but whilst the energy use of buildings is often discussed, rarely is their material consumption. Furthermore, with increasing populations and urbanisation, demand for these materials continues to increase, and in turn, so will the embodied environmental impacts created from the extraction, processing, transport and maintenance of these materials. Shorter building lifetimes are also becoming more prevalent, in part due to densification in urban areas. This creates both wasted materials and embodied impacts. A suggested greenhouse gas mitigation strategy is therefore to extend the lifetime of materials/components, e.g. through reuse, in order to displace the need for new materials and their associated impacts. However, this calls for a new way of thinking about the built environment, it becomes a system of stocks and flows, where the output flows should be redirected into inputs. However, this requires a much greater understanding of this system, which is in essence the material metabolism of the built environment. To date, research in this area has largely focused on single buildings, and techniques such as design for deconstruction and reuse that seek to improve the availability of reused materials, this could be thought of as a circular economic approach. However, for a true assessment of circular economic potential, a single building is not sufficient, as it provides a limited feedstock for future buildings. To capture the full extent of flow interactions, a wider system should be investigated-that of a neighbourhood/city-enabling better identification of the interdependencies that exist and potential synergies to be made between these flows, across multiple scales. This paper presents the background literature and an initial scoping exercise of such an assessment, focusing on a neighbourhood in Sheffield, England.
- Renewable Energy Technologies in Campus-Sized Developments: A Spatial StudyHadi Arbabi, Boris R Lazarov, and Martin MayfieldIn CIBSE Technical Symposium, Apr 2015
Using hourly energy and water consumption data and theoretical models representing low-carbon and green energy production technologies, such as photovoltaic panels, wind turbines, combined heat and power, solar collectors, and seasonal thermal energy storage, an integrated node-based static model has been developed. Assembled in MATLAB and Simulink, and based on an integrated resource management approach, it reproduces annual hourly energy consumption and production values for hypothetical campus-sized developments with onsite energy generation. For three configurations of generation technologies, results are then presented from simulations exploring the spatial characteristic and requirements of the development. Also, the article concludes that alteration in the composition of the technologies used has significant spatial impact and implications on achieving carbon-neutral developments.
thesis
- phdUrban Productivity & Spatial Patterns Across Scales: A Multi-Scale Exploration of Urban Networks and Their Hierarchical ConfigurationsHadi ArbabiUniversity of Sheffield, Apr 2019
Understanding the nuances at play across different spatial scales is of crucial importance when considering urban economic-energetic size-cost performance, specifically when longer-term consequences are considered. Through the application of an allometric understanding of cities, a more nuanced narrative is offered highlighting the interplay of urban productivity and spatial configurations of human interactions across scales. This is presented in three parts. In the initial examination of the urban economic-energetic size-cost balance across spatial scales, we seek new insights on the effects of scale in relation to urban connectivity and density for maximizing urban size-cost balance. For this, we use the urban system in England and Wales as a topical testbed where agglomeration-based arguments have been used in support of better inter-city connectivity in order to address a historic North-South regional economic productivity divide. The inadequate connectivity thought to be affecting the economic performance across the urban network in England and Wales, however, is shown to permeate across spatial scales. More broadly, this points at a scale-induced hierarchy of urban connectivity concerning potential improvements needed at inter- and intra-city scales. This is followed by an examination of the universality and transferability of scaling insights, and their nuances, between different cities and systems of cities. Considering the current transport schemes designed to address the North-South economic gap, we examine the continental comparisons drawn specifically from the inter-city transport infrastructure connecting the Randstad in the Netherlands and Rhine-Ruhr metropolitan region in Germany. Our examination points towards fundamental differences that exist in the structure and distribution of population density across the countries and their city-regions across various scales. Additionally, the cross comparison demonstrates that, although scaling insights are transferable between urban systems, a simple multi-scale assessment of individual systems of cities in isolation is sufficient when investigating urban connectivity from an urban allometric point of view. Finally, returning full circle to the effects of spatial scales and distance on the geographical patterns of urban connectivity, we review a mathematically grounded approach to sort and organize the intra- and inter-city connectivity hierarchy while matching complementary infrastructural needs based on size-cost balances for a number of different scenarios. Together, this narrative provides a somewhat enhanced and most crucially spatially multi-scale examination of the arguments regarding connectivity and agglomeration in an urban context.