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Searching for new Urban Metabolism techniques: A review towards future development for a city-scale Urban Metabolism Digital Twin
... Sociodemographic factors (e.g., income inequality due to accessibility of education, culture, etc.) reflect consumption preferences and patterns and their influence on accessibility, accountability, and inclusivity (Lyons et al., 2018). The dynamic transformation in culture, economy, infrastructure, technology, environment, and climate is closely related to these trends Geremicca and Bilec, 2024), indicating the dire need to adopt it as a tool. The following section is viewed at two levels-the global (international context) and national (Indian context)/ regional-and touches upon subjects rarely represented in UM studies at each level and addresses two tangents within the same category. ...
... A study that surveyed 35 cities in China (Wang et al., 2020) found that the performance increased μ1 0.1435 in 2008 to 0.1832 in 2017 due to investment in infrastructure delivery with the latest technology and reinforcing urban infrastructure carriers to benefit urban resilience. However, embracing uncertainty for various possible futuristic scenarios, where the risk could be a cooperative and close scenario in the case of physical connectivity or a global-local scenario in the case of digital connectivity (Lyons et al., 2018;Geremicca and Bilec, 2024), based on the lifestyle expressions of the people, "whole system" thinking is ideal for encouraging physical accessibility, spatial relatedness, and digital connectedness. The centripetal and centrifugal forces are not just affected by regulatory or market incentives to invest in urban ICT infrastructure; initiatives by policymakers to develop more collaborative consumption of resources can also lead to more socially resilient and environmentally sustainable solutions. ...
Urban Metabolism is derived from a biological-based mechanism wherein a city is metaphorically analyzed from a biological perspective, which tracks the transformation of resources and addresses key questions related to self-sufficiency and consumer behavior. This research, for the first time, explores Urban Metabolism as a tool to evaluate sustainability-related framework and standards for urban regions on both global and local scales to address regional disparity and better means to devolve powers to local planning institutions. In the first half of the study, an adaptive approach was used to categorize the concept and find its connection with SDGs, wherein it was inferred that a new section under economic ecology has evolved, which requires policy interventions as its application at regional context creates lacunae in terms of UPE (Urban Political Economy). Furthermore, the study explores case studies and identifies the characteristics of urban metabolic systems to comprehend the trend in the idea and the necessity of using the UM lens at two different scales with two different narratives to solve entirely different challenges under the same component. The second part of the article looks at how the concept is used within current research. The results of the “perspective methods” were compared to gathered standard guidelines, and their shortcomings were noted to help close the implementation gap between researchers and practitioners. This suggests that policies, frameworks, guidelines, and other documents should adopt the discussed integrated approach to devolve power to local planning areas.
... The IoT facilitates realtime data collection and monitoring through sensors embedded in infrastructure, enabling dynamic management of resources and systems [220,221]. AI enhances data analysis, predictive maintenance, and energy efficiency, while Geographic Information Systems (GIS) integrate spatial data for improved urban and infrastructure planning [222,223]. Additionally, 3D scanning and VR provide accurate visualization and simulation capabilities, enabling better planning and execution of infrastructure projects [209,224,225]. ...
... Establishing global standards for data interoperability and exchange will address current fragmentation and enable seamless collaboration [233]. Finally, expanding DT applications to integrate environmental, economic, and social sustainability goals will align infrastructure projects with broader sustainability objectives [215,223]. ...
Digital Twin (DT) technology is revolutionizing industries by integrating the physical and digital realms, driving advancements in real-time monitoring, predictive analytics, and process optimization under Industry 4.0. With the emergence of Industry 5.0, DTs are expanding their roles, emphasizing human-centric innovation and sustainability. This review provides a comprehensive analysis of how DTs are transforming industrial practices and their potential to shape the next industrial paradigm. The study begins with an overview of Industry 5.0, contrasting its human-centric, sustainable goals with Industry 4.0's efficiency-driven framework. Ten enabling technologies, including DTs, collaborative robots, artificial intelligence, and extended reality, are examined alongside the challenges and opportunities of Industry 5.0. The principles and key concepts of DTs, such as real-time synchronization, feedback loops, and lifecycle management, are explored, emphasizing their ability to bridge innovation and operational excellence. DT applications in Industry 4.0 and their evolution in Industry 5.0 are analyzed, highlighting 10 technological integrations, including IoT, big data, blockchain, and edge computing. DTs' roles in fostering human-centric innovation and sustainable resource management are discussed. Applications of DTs across seven key sectors including manufacturing, infrastructure, energy, logistics, mining, agriculture, and healthcare are examined, showcasing their transformative impact. The benefits of DTs, such as enhanced efficiency, sustainability, and innovation, are discussed alongside challenges like data security, high costs, and standardization issues. The review concludes by highlighting the implications of DTs for fostering collaboration, resilience, and sustainability. Future research directions include integrating DTs with the industrial metaverse, cognitive twins, and ethical AI practices. As industries transition to Industry 5.0, DTs are positioned to enable sustainable, resilient, and human-centric operations, paving the way for a transformative and inclusive industrial future.
... Emergy analysis [24][25][26] and material flow analysis [27][28][29] are two primary accounting methods of urban metabolic flows. Emergy refers to the total available energy (exergy) use, including both direct and indirect use, that is used in the production processes of goods and services 30 . ...
... Similar to prior studies on urban metabolism 34,35 , we focused on the critical material and energy flows that could reflect urban metabolic patterns. Compared with national-level planning that often prioritizes comprehensive management of all metabolic flows, urban systems can benefit more from concentrating key metabolic flows 26,36 . These critical flows play important roles in local metabolic systems and have a huge impact on urban functions. ...
Cities exhibit diverse urban metabolism patterns in terms of the natural environment, industrial composition, energy, and material consumption. A chronicled city-level quantification of emergy metabolic flows over time can significantly enhance the understanding of the temporal dynamics and urban metabolism patterns, which provides critical insights for the transitions to sustainability. However, there exists no city-level urban emergy metabolism dataset in China that can support detailed spatial-temporal analysis. In this study, we present a city-level urban emergy metabolism dataset of China’s 281 cities between 2000 and 2020. This dataset meticulously describes the production and import of 41 resource types that sustain metabolic activities in 281 Chinese cities over a span of 21 years. This database, for the first time, provides insights into the historical metabolic changes of China’s cities by detailing emergy flows including production, consumption, and import of resources. Furthermore, these emergy flow inventories serve as valuable resources for studying urban metabolic characteristics, evaluating policy impacts, and formulating sustainable development strategies for China’s cities.
... Digital twins serve as virtual representations of physical assets and processes, replicating their realworld counterparts in real time to create enriched, data-driven models of urban infrastructures. These virtual models facilitate predictive maintenance, early fault detection, and proactive system management, thereby enhancing operational efficiencies and informing strategic urban planning [12]. Nonetheless, current implementations of digital twins in smart cities frequently grapple with scalability issues, data integration challenges, and security vulnerabilities, which impede their comprehensive adoption and utility [13]. ...
The rapid urbanization of modern cities presents significant challenges in resource management and public infrastructure optimization. This research addresses these issues by integrating digital twin technology with the Industrial Internet of Things (IIoT) to enhance the efficiency, scalability, and resilience of smart city infrastructures. The primary objective is to overcome existing limitations in data integration, real-time adaptability, and predictive accuracy through a novel framework that employs advanced data fusion methodologies, machine learning algorithms, and high-performance computing resources. The study utilizes supervised learning models such as random forests and gradient boosting, alongside unsupervised methods like k-means clustering for anomaly detection and predictive maintenance. The experimental setup involved high-fidelity simulations using IIoT-generated real-time data streams, with performance evaluated through metrics like Mean Absolute Error, Root Mean Square Error, and F1-scores. Results demonstrated a significant improvement in predictive accuracy and operational efficiency, alongside reduced energy consumption, validating the framework's applicability in real-world smart city scenarios. This research contributes to the body of knowledge by providing a scalable and robust solution for urban management and offers a foundation for future studies focused on refining computational resource management and extending digital twin applications across diverse urban domains.
... Initially, digital twin technology was primarily applied in manufacturing to optimize product design, manufacturing processes, and maintenance management [95]- [97]. As the technology has evolved, its application scope has gradually expanded to urban planning, smart city construction, environmental monitoring, and landscape design [40], [98]- [101]. ...
The application of digital twin (DT) technology in studying public environmental perception and associated health benefits is emerging, yet most research has focused on static green spaces, providing limited insights into dynamic waterscapes. This study aims to systematically evaluate the effects of waterfront and non-waterfront environments on public physiological and psychological responses using a DT platform. A high-precision 3D virtual replica of a suburban park was constructed using UAV oblique photogrammetry and handheld lidar scanning technologies. Real-time environmental data were integrated into the DT using IoT devices, establishing a dynamic link between the digital environment and physical worlds. Participants underwent field tests in both environments, measuring physiological indicators (e.g., heart rate and blood oxygen saturation) and psychological indicators (e.g., pleasure and relaxation). We found that waterfront environments outperformed non-waterfront environments in terms of relaxation and vitality, while no significant differences were observed between the two environments regarding physiological indicators. Additionally, ANCOVA and random forest analyses identified temperature and sunlight intensity as key environmental factors influencing heart rate and psychological well-being. The study reveals specific mechanisms through which different environmental characteristics impact public well-being and demonstrates the DT platform's capabilities in real-time environmental data collection and landscape quantification. These findings provide valuable insights for urban planners and public health policymakers in designing landscapes that enhance urban residents' health and well-being.
... The method of evaluating UGI network stability mainly focuses on the centrality and connectivity of corridors and nodes, resulting in a lack of comprehensive comparative assessments of UGI source patterns. In the future, we will explore the relationship between the UGI and mental health, economic development, urban metabolism digital twins, etc. [59,60]. ...
The construction and optimization of urban green infrastructure (UGI) are regarded as effective strategies for harmonizing the natural landscape with human activities, particularly in ecologically vulnerable areas in the Upper Yellow River Basin, China. However, there is little attention paid to the scale effects and object effects as well as an absence of comprehensive assessments regarding landscape stability. Taking the Four-Lake Hydrographic Network (FLHN) in Shizuishan, a prefecture-level city, as an example, this study focuses on identifying the important sources of UGI by integrating both regional and interregional perspectives utilizing morphological spatial pattern analysis (MSPA). UGI networks were constructed and optimized based on trade-offs and synergizing relationships between individual objects using the minimum cumulative resistance (MCR) model, and the UGI network’s stability combined centrality and connectivity aspects, which were subsequently assessed. The results showed that a total of 19 important sources covering an area of 105.07 km² were identified in the FLHN, integrating both regional and interregional levels. It was deemed unnecessary to maintain lengths of 7.79 km key corridors, 9.42 km general corridors, and 29.89 km fragile corridors; furthermore, there was no longer a requirement to upgrade an additional 5.51 km of general corridors and 25.78 km of any corridor, as UGI corridors were extracted based on a trade-off and synthesized objective methodology. The overall connectivity index value (OG) of UGI stability with respect to the multi-objective model demonstrated superior performance compared to the same index in scenarios involving the use of a single-objective approach and the straightforward overlay of each object. This study reveals the multifaceted requirements of urban landscape security and sustainability, indicating that multi-scale and multi-objective approaches in territorial space planning not only ensure the integrity of the landscape patterns but also reduce the costs associated with landscape construction. This model can be utilized to implement urban landscape entity protection and restoration for landscapes with various geographical characteristics, and it can provide valuable guidance for similar areas.
... Smart City is committed to making urban construction and development more scientific and efficient and improving the efficiency of urban services through transparent and sufficient information acquisition, extensive and safe information transmission, and effective and scientific information processing to improve the operation efficiency of the city. For the research scope of smart cities, existing literature includes infrastructure [91,105], energy utilization [106,107], intelligent operation and maintenance [111][112][113], transportation systems [108], emergency management [114], etc. ...
Digital Twin (DT) technologies have demonstrated a positive impact across various stages of the Architecture, Engineering, and Construction (AEC) industry. Nevertheless, the industry has been slow to undergo digital transformation. The paper utilizes the Systematic Literature Review (SLR) approach to study a total of 842 papers on the application of DT in buildings, landscapes, and urban environments (BLU) from 2018 to 2024. Based on the research results, suggestions have been made for future research and practical directions. Meanwhile, it provides assistance to BLU’s designers, constructors, managers, and policymakers in establishing their understanding of the digital transformation of the AEC industry. The existing relevant research can be mainly divided into three categories: case study, framework study, and technology study. Compared with the buildings and urban environment industries, the number and depth of research in the landscape industry are relatively low. Through in-depth analysis of BLU projects, three research trends in the future are determined: (1) research and application of DT framework in the design and planning stage; (2) development of design tools and basic theory based on DT model; (3) application and exploration of DT technology in the landscape industry.
... The advancement of DT-related technologies has not only revolutionized urban planning but also expanded the horizons of what can be achieved in simulating and optimizing urban scenarios (Geremicca and Bilec, 2024;Elnabawi and Raveendran, 2024). ...
Urban Digital Twins (UDTs) offer a promising avenue for advancing sustainable urban development by mirroring physical environments and complex urban dynamics. Such technology enables urban planners to predict and analyze the impacts of various urban scenarios, addressing a global priority for sustainable urban environments. However, their potential in public engagement for environmental perception remains unfulfilled, with existing research lacking the capability to analyze urbanscapes' visual features and predict public perceptions based on photo-realistic renderings. To fill the gap, our study developed and implemented a UDT platform designed for the dual purposes of objective feature evaluation and subjective visual perception, alongside the prediction of perceptions in simulated scenarios. We incorporated DeepLabV3, a deep learning model for imagery semantic segmentation, to quantify a series of visual features within the built environment, such as the proportion of vegetation and architectural elements. Subjective visual perceptions (e.g. safety and lively) are captured using immersive virtual reality to gather public perceptions of different scenarios and learn patterns. Further, utilizing a photo-realistic rendering engine, high-quality renderings of textures and materials for UDT were achieved, and we proved their veracity based on a perception experiment. Afterwards, we employ the random forest algorithm for automated perception predictions of rendering scenarios. The implementation was demonstrated with a case study on an urban greenway in the central area of Singapore. We compared both the objective evaluation and subjective perception results, followed by a demonstration of automated visual perception prediction through photo-realistic scenario simulations, such as modifying vegetation density or introducing new architectural elements to the skyline, to predict the perception of scenarios before they are built, leading to more efficient and automated urban planning.
Digital Twin (DT) technology is transforming industrial systems by integrating physical assets with digital models, enabling real-time monitoring, predictive analytics, and process optimization, particularly within the framework of Industry 4.0 (I4.0). As the global industrial landscape shifts toward Industry 5.0 (I5.0), DTs are increasingly being redefined to support human-centric innovation, sustainability, and system resilience. This review examines the evolving role of DTs in bridging the efficiency-driven goals of I4.0 with the inclusive, sustainable objectives of I5.0. It explores ten enabling technologies such as artificial intelligence (AI), internet of things, blockchain, cloud and edge computing, and extended reality, while discussing both the opportunities and challenges posed by I5.0. The study emphasizes key principles of DTs, including real-time synchronization, feedback mechanisms, and lifecycle integration. A detailed sectorial analysis across manufacturing, infrastructure, energy, transportation, mining, agriculture, and healthcare illustrates how DTs are being applied in diverse contexts to enhance operational efficiency, product quality, and decision-making. The mapping of applications by country, sector, and industrial focus reveals growing trends toward I5.0 in areas such as logistics and infrastructure. Common application domains include monitoring, optimization, prediction, and decision support. Despite their potential, DT adoption faces challenges including high implementation costs, data integration issues, cybersecurity concerns, and lack of standardization. The review discusses these barriers alongside the importance of validation and security for trusted deployment. It concludes by identifying future directions, including cognitive twins, industrial metaverse integration, and ethical AI. DTs are positioned as foundational technologies for advancing sustainable, resilient, and human-centered industrial systems.
The built environment requires extraction and consumption of enormous quantities of raw materials, water, and energy. While these materials remain in use for several years or decades, growing global populations and aging infrastructure are driving widespread generation of one of the largest and most challenging waste streams to manage. There is growing interest from communities in integrating circular economy (CE) strategies in the context of construction & demolition (C&D) material management. Many approaches for doing so focus on small-scale CE applications like individual products, materials, or projects. However, greater understanding is needed at the city-scale given communities’ complex position at the frontlines of local development, resource consumption, and waste management. This study summarizes the development of an evaluative framework for community-based C&D circularity at a city or regional level. The framework expands upon a mixed methods approach called the Circularity Assessment Protocol (CAP), which integrates aspects of urban metabolism, geospatial analysis, and qualitative research methods to examine plastic waste management in communities. To advance convergent CE research, here, we aim to adapt the CAP framework to C&D. We describe our adaptation of the CAP to C&D through a conceptual review describing research, methods, and strategies related to seven elements of a local CE context: C&D Analytics, Building Material and Design, Community, Use, Collection, End-of-Cycle, and C&D Emissions. This work describes a novel yet preliminary conceptualization for developing a baseline understanding of circular C&D material management and a holistic examination of barriers, affordances, and opportunities for improving city-wide circularity.
Artificial intelligence (AI) is emerging as an impactful feature of the life, planning and governance of 21st-century cities. Once confined to the realm of science fiction and small-scale technological experiments, AI is now all around us, in the shape of urban artificial intelligences including autonomous cars, robots, city brains and urban software agents. The aim of this article is to critically examine the nature of urbanism in the emergent age of AI. More specifically, we shed light on how urban AI is impacting the development of cities, and argue that an urbanism influenced by AI, which we term AI urbanism, differs in theory and practice from smart urbanism. In the future, the rise of a post-smart urbanism driven by AI has the potential to form autonomous cities that transcend, theoretically and empirically, traditional smart cities. The article compares common practices and understandings of smart urbanism with emerging forms of urban living, urban governance and urban planning influenced by AI. It critically discusses the limitations and potential pitfalls of AI urbanism and offers conceptual tools and a vocabulary to understand the urbanity of AI and its impact on present and future cities.
In Egypt, planning practice is physical and rooted in design principles, resulting in plans that seldom consider the impact of land use and land cover changes on the environment. Most used planning models are static. The paper offers urban metabolism and dynamic modeling as an alternative mode for decision making. It models population growth and expanded economic activities that characterize rapid urbanization and induce changes in land use affecting various urban economic sectors using the Greater Cairo Region (GCR) as a case study. Urban transportation contributes to climate change. The authors used secondary data and satellite images to detect land use and cover changes since 2005. After building a stock-flow diagram to describe the system’s structure, they used dynamic modeling and GIS to assess the impact of transportation on air quality. Results indicate that the population of GCR will range from 33.348 to 40.334 million in 2050. The emissions from transportation will be around 52,521.2 Gg, which is beyond the ability of the region’s ecosystems to store carbon. These findings shed doubt about the ability of GCR to reach carbon neutrality and, therefore, call for strict measures to control emitting GHGs and change in planning practices and education.
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As we approach an era where more than 60% of the global population lives in cities, urban areas must be our focal point in the transition to the flourishing societies of future decades. While much attention has been paid to understanding urban consumption patterns over the past decade, the overwhelming majority of recent urban metabolism research has focused on larger cities with populations over 1 million inhabitants. Meanwhile, estimates show that more people live in urban areas with populations between 300,000 and 1 million people than in mega cities. Indeed, given their relatively small size, there are many more of these cities to study than larger cities; many more urban governments need to be informed of the solutions that are relevant to the context of their less dense populations. Our goals to decarbonize and dematerialize societies require discussions of measures that are applicable to different types of urban areas across various population scales. We take the example of the town of Reading, United Kingdom to illustrate how per capita urban metabolic flows differ within small‐ and medium‐sized cities, as well as for megacities. For example, relative to Reading, we find that there is substantial variability in energy demand for small cities (i.e., Le Mans is 150% higher) and for larger cities (50% higher for other European and North American megacities). This underscores the need to explore this under‐researched area of urban metabolism, as well as the development of a typology to enable comparisons and differentiate strategies for sustainability transitions.
Rapid urbanization boosts the material demand of cities and leads to serious environmental problems, such as water shortage and air pollution. To achieve better governance of cities, stakeholders need to deeply understand urban material utilization. Taking 327 cities in China as examples, this study analyzes the urban material characteristics from a metabolic perspective. We investigated the spatiotemporal changes in the material base of these cities from 2000 to 2020, including material flow and material stock. We further explored the allometric growth patterns of urban material flow and material stock at different scales (e.g., individual, group, and community). Results show that cities have metabolic processes as natural organisms; they differentiate into many types and exhibit allometric growth patterns. There is a consistency of material metabolic patterns in most cities. The growth of material flows (+43%) and material stocks (+135%) was evident in all cities during 2000–2020. However, the material metabolism of Chinese cities exhibits diverse allometric growth patterns across the individual, group, and community scales. This study can provide simple but effective quantitative indicators for the investigation of urban material utilization, and can support distinct policy implications for sustainable urban material‐based planning and management.
A waste management strategy needs accurate data on the generation rates of construction and demolition waste (CDW). The objective of this study is to provide a robust methodology for predicting CDW generation in Tanta City, one of the largest and most civilized cities in Egypt, based on socioeconomic and waste generation statistics from 1965 to 2021. The main contribution of this research involves the fusion of remote sensing and geographic information systems to construct a geographical database, which is employed using machine learning for modeling and predicting the quantities of generated waste. The land use/land cover map is determined by integrating topographic maps and remotely sensed data to extract the built-up, vacant, and agricultural areas. The application of a self-organizing fuzzy neural network (SOFNN) based on an adaptive quantum particle swarm optimization algorithm and a hierarchical pruning scheme is introduced to predict the waste quantities. The performance of the proposed models is compared against that of the FNN with error backpropagation and the group method of data handling using five evaluation measures. The results of the proposed models are satisfactory, with mean absolute percentage error (MAPE), normalized root mean square error (NRMSE), determination coefficient, Kling–Gupta efficiency, and index of agreement ranging between 0.70 and 1.56%, 0.01 and 0.03, 0.99 and 1.00, 0.99, and 1.00. Compared to other models, the proposed models reduce the MAPE and NRMSE by more than 92.90% and 90.64% based on fivefold cross-validation. The research findings are beneficial for utilizing limited data in developing effective strategies for quantifying waste generation. The simulation outcomes can be applied to monitor the urban metabolism, measure carbon emissions from the generated waste, develop waste management facilities, and build a circular economy in the study area.
The environmental and social crises in cities call for radical future visions that can incite transformative change. Yet, urban metabolism research typically adopts an explanatory, retrospective approach to the drivers of urban flows and stocks, resulting in conservative, business‐as‐usual future outlooks. In this study, we present the results of a narrative literature review on drivers and futures of urban metabolism, and consequently use these results to propose and apply a framework that can be used by researchers (i) to systematically identify the drivers of urban metabolism, and (ii) to critically engage with these drivers for the development of transformative future visions. The framework comprises seven thematic categories of drivers (demographic, economic, cultural, political, technological, environmental, and infrastructural) and an eighth category (power) to be used as the lens through which the interactions between drivers, activities, and flows in the city are critically examined. Applying the framework to the case study of biowaste management in Rennes, France, we found it useful for the systematic identification of often overseen drivers. The proposed framework, allowing for a combined analysis of flows and drivers, can become a useful tool toward a solution‐oriented urban metabolism research.
The growing urban population is intensifying global resource shortages. It is essential for scholars and policy-makers to better understand the material-based metabolism of cities for sustainable urban resource management. Taking the Beijing-Tianjin-Hebei region of China as a representative case, this study quantifies domestic material consumption (DMC) and material stock (MS) and reveals the dynamics of the material-based urban metabolism of cities during 2000-2017 based on the allometric scaling law. The results show that the DMC and MS of each city exhibited an overall increasing trend during 2000-2017, with Beijing, Tianjin, Shijiazhuang, Baoding, Handan, and Tangshan having larger material bases than the other cities. Cities at different stages of development usually follow different material-based allometric scaling law relationships. Most cities in this region (9 out of 13) follow a superlinear relationship, indicating excessive consumption of resources in these cities. The scaling coefficient of Beijing is most similar to the value (0.75) that has been observed in many types of biological research, which suggests that Beijing has reached a relative stabilization stage of development. This study provides key points for future resource allocation and industrial optimization related to urban material metabolism in the Beijing-Tianjin-Hebei region. The findings of this study can enrich the theoretical and empirical bases for urban allometry research and provide urban managers with additional insights for consideration to achieve sustainable urban resource management.
Urban development trajectories in sub-Saharan Africa are unsustainable. Fast-growing cities constitute nutrient sinks relying on nutrient-poor hinterlands. We propose a pragmatic waste flow assessment providing authorities with a cross-sectoral view of a city’s nutrient sink status. Following a nested approach, we focus on the origin and fate of a city’s nutrient-containing waste flows, constituting a partial urban metabolism. Application of this method for nitrogen to Maradi, Niger, and Ouagadougou, Burkina Faso, shows that the city of Maradi is a nitrogen sink in a still rather sustainable city region food system. Maradi’s Territorial Sustenance index, expressing net N provision from within the territorial system as a share of urban throughput, is around 79%. But Maradi may well be set to evolve towards a situation similar to that of Ouagadougou: a large nitrogen sink with no significant city-hinterland recycling. Ouagadougou exhibits a Territorial Sustenance index of about 5%. Urination constitutes the dominant nitrogen loss pathway and urine-collecting initiatives could provide valuable fertilizer adapted to local agricultural requirements and constraints, increasing the urban system’s sustainability by enhancing regional food provision as well as by reducing sanitation-induced urban water pollution.
The active participation of stakeholders is a crucial requirement for effective land-use planning (LUP). Involving stakeholders in LUP is a way of redistributing the decision-making power and ensuring social justice in land-management interventions. However, owing to the growing intricacy of sociopolitical and economic relations and the increasing number of competing claims on land, the choice of dynamic land use has become more complex, and the need to find balances between social, economic, and environmental claims and interests has become less urgent. These facts reflect a paradigm shift from top-down, noninteractive, and one-directional policymaking approaches to a more negotiable, bottom-up, deliberative, and responsible one. Geospatial industries claim that digital twin technology is a potential facilitator that improves the degree of stakeholder participation and influences land-use planning. The validity of this claim is, however, unknown. By adopting the integrative literature review, this study identifies where in LUP is stakeholder participation much needed and currently problematic, as well as how digital twin could potentially improve. The review shows that digital twins provide virtual visualisation opportunities for the identification of land-use problems and the assessment of the impacts of the proposed land uses. These offer the opportunity to improve stakeholder influence and collaboration in LUP, especially in the agenda-setting phase, where land-use issues could be identified and placed on the LUP agenda. This relies on the ability and willingness of local planning institutions to adopt digital twins, and stakeholders’ perception and willingness to use digital twins for various land-use goals. Despite the assertion that digital twins could improve the influence of stakeholders in LUP, the focus and the development of digital twins have not accomplished much for those features of the technology that could improve stakeholder influence in LUP. By adopting the principles of the social construction of technology, this study proposes a “technological fix” of digital twins to focus more on improving stakeholder influence on land-use planning.
Cities are complex systems with a key role in economic development and in improving the environmental sustainability of nations. Therefore, a comprehensive understanding of urban systems is fundamental to designing relevant policies and initiatives. Urban metabolism characterization may provide a holistic framework for analyzing urban systems in the context of the broader national metabolism. This paper provides a methodology to characterize the metabolism of an urban area, such as the Lisbon metropolitan area, taking as a source of data the socioeconomic metabolism of the country. The national metabolism is established by computing physical input-output tables. The downscaling to the urban level is accomplished with a variety of sector-specific parameters, from which an urban mass balance is established for a set of economic activities. The results obtained for the case study of Portugal and the city of Lisbon suggest that the share of services and the type of manufacturing industries in the economic structure of Lisbon, together with the higher resource productivity in the most representative economic sectors, are key aspects of the metabolism that contribute to Lisbon having higher overall resource productivity. The representation of the metabolism flows revealed key differences between the supply chains of Lisbon and the national flows, as well as a strong dependence of the Lisbon economy on material flows from other regions.
Cities need to improve sustainability levels demanded by climate change mitigation efforts. The use of big data analytics is crucial for understanding its dynamics and deploying solid public policies. Nevertheless, data availability poses great challenges, being difficult to produce reliable analyses. Delivering trustable cross-sectorial energy datasets with high spatial and temporal resolution is thus critical to provide valuable insights for informed policymaking.
This paper describes the MetaExplorer, a GIS-platform, which gathers trustable energy-related datasets, at municipal level for Portugal, providing a user-friendly georeferenced visualisation tool that can be used to derive statistical models, and support policymaking. Publicly available data was collected and cleaned, divided on five thematic areas: energy demand, buildings, mobility, waste management, and socio-economic, while a visualisation tool was developed to provide the possibility to further explore relations between indicators and support the energy transition at local level, delivering customised analyses with a global perception.
Urban digital twins (UDTs) have been identified as a potential technology to achieve digital transformative positive urban change through landscape architecture and urban planning. However, how this new technology will influence community resilience and adaptation planning is currently unclear. This article: (1) offers a scoping review of existing studies constructing UDTs, (2) identifies challenges and opportunities of UDT technologies for community adaptation planning, and (3) develops a conceptual framework of UDTs for community infrastructure resilience. This article highlights the need for integrating multi-agent interactions, artificial intelligence, and coupled natural-physical-social systems into a human-centered UDTs framework to improve community infrastructure resilience.
Anthropogenic stocks are increasingly seen as potential reserves for secondary resources, which has led to a rapid development in research of urban metabolic systems. With regard to buildings and their associated material stocks and flows, one of the most critical shortcomings in the state-of-the-art is the knowledge gap for drivers, dynamics, patterns and linkages that affect the urban metabolism. This paper is premised on the idea that urban planning stirs up these material flows, so it should also adopt their sustainable management on its agenda. It presents an approach that highlights the intertwined nature of changing urban morphology and building material stocks and flows in space and time. An analytical framework, based on the principles of material flow analysis, is provided for an integrated, spatiotemporal study of urban morphology and urban metabolism of buildings, using building and plot data as the input and identifying internal processes of the urban metabolism as the output. The identified processes include greenfield development, infill construction , building replacement and shrinkage, each of which can be expected to have tangible yet very different material and environmental consequences in the form of embodied materials and CO2. The use of the framework is demonstrated with a case study in the Finnish city of Vantaa in 2000-2018. The case study shows patterns pertaining to a growing city unrestricted by geographic or historic factors, manifested as vast greenfield developments and replacement of a notably young building stock. As sustainability may soon call into question both these strategies, uncovering the material consequences of a city's past urban (re)development strategies lay the foundation for using the presented approach proactively in planning support, in pursuit of more circular economy-based and low carbon cities.
Urbanization plays a key role in the human activities causing and feeding climate change. At present, climate change and other environmental issues are directly or indirectly related to the metabolism of cities. However, cities may also play a central role in the fight against climate change. This is the reason why Urban Metabolism (UM) has become a powerful concept to account for and understand the way in which complex systems such as cities use and dispose of material resources, also suggesting measures to change their operational regimes. The rightsizing and optimization of UM is basically a matter of social innovation. It implies changes in the way a city collectively produces and reproduces its physical stocks and provides services to its inhabitants. This article aims at identifying strategies, scenarios, and pathways to slow down urban metabolic processes while improving their efficiency, thus managing a successful transition to an urban (more) circular economy, as well as decreasing the material intensity of the urban economy. The main objectives of the article are the following:
1. The development of a renewed approach for studying Urban Metabolism based on transdisciplinary approaches and methods aimed to model metabolic agents' patterns of practices.
2. The definition of urban patterns of resource use of different agents shaping urban metabolism (households, corporate agents, communities, and public authorities).
3. The exploration of the main policies and administrative tools that cities use to manage environmental problems leading to different urban regulation regimes.
4. A tool for generating future scenarios and roadmaps to reach a low-carbon future. This tool is crucial for engaging experts, stakeholders and the public looking for new solutions.
Cities are responsible for about 75% of the global greenhouse gas emissions. Various materials and energy sources, which are mostly produced by the rural areas rather than the cities, are consumed by the cities, and their waste is released back into the rural areas, thereby causing evident environmental damages. The Rural–Urban Metabolism approach can offer a comprehensive tool to understand the flux of resources that cross the urban environments and plan for more sustainable cities. Considering the strength of the relationship between the urban and rural areas, this paper offers a new perspective regarding the Rural–Urban Metabolism and its application in the Autonomous Province of Trento is discussed. The methodological approach consists of four main steps: data collection and management to support strategic territorial/urban plans; data assessment to critically evaluate the existing context; data mapping to visualize the data and territorial dynamics; and finally, the definition of the strategic and integrated development plan and actions. The Rural–Urban Metabolism proved to be a strategic approach for urban planning and design to monitor the flow of it, assess the impacts of it and promote more sustainable and circular urban policies.
The urban built environment has accumulated massive amounts of resources, which is the main “hot spot” of construction materials and energy consumption in cities. To effectively monitor and manage resources use and waste disposal toward sustainability, this study intended to explore different metabolic paths of the urban built environment, as well as strategies for new and old urban areas separately with the help of material stock and flow analysis. Based on snapshots of 2003, 2010, and 2017 and combined with big data, a four‐dimensional geographic information system buildings database of Lixia District in Jinan, China, was compiled for bottom‐up stock modeling. Finally, the environmental impact assessment of the buildings’ demolition and disposal stage was carried out. The results showed that the building material stock was 142.31 Mt in 2017, with an increase of 69% from 2003. The reinforced concrete buildings increased rapidly from 2003 to 2017, especially in new urban areas, which has boosted demand for steel and cement by more than 150% during these 15 years. The material stock of the old urban area tends to be saturated, whereas the new urban area has experienced a rapid expansion with the material inflow four times as large as the material outflow. Potential recycling of waste concrete can reduce the generation of building demolition waste by 50%, save 0.15 km2 of land occupation, increase raw material substitution by nearly 10 times, and reduce CO2 emissions by 2.5 times.
Understanding building metabolism is critical for guiding urban resource management and addressing challenges in urban sustainable development. Key attributes of buildings, including geolocation, footprint, height, and vintage, are crucial to characterizing spatiotemporal patterns of building metabolism. However, these attributes are usually challenging to obtain broadly and automatically, which obscures a comprehensive understanding and accurate assessment of urban metabolism. Moreover, the lack of a finer spatial pattern of these attributes shadows a spatially explicit characterization of material stock and flow in cities. In this study, we took Shenzhen—whose urbanization over the past three decades has been unprecedented in China and even around the world— has been taken as an example to develop a city-level building dataset based on a random-forest model and quantify the spatiotemporal patterns of material metabolism at relatively high spatial resolution (in 500 m × 500 m grids) by combing material flow analysis (MFA) with geographic information system (GIS). The results show that Shenzhen grew from a small town with 281.02 × 10⁶ m³ of buildings in the 1990s to a mega-city with 3585.5 × 10⁶ m³ of buildings in 2018 and expanded both outward and upward from downtown to suburban areas. The urban “weight” (material stock) increased from 92.69 Mt in the 1990s to 1667.8 Mt in 2018 and tended to be saturated, with an average growth rate of 9.5% per year. Spatially, the south-central areas were the largest container of material stocks and generated the most demolition waste. The spatially explicit maps of building three-dimensional (3-D) form and vintage provide detailed information for architectural conservation and could support the decision-making for urban renewal planning. The spatiotemporal patterns of in-use material stocks and potential generation of construction and demolition waste (CDW) provide a benchmark of environmental risk assessment and potential secondary resources to reduce “original” material consumption, which could help alter urban renewal to an environmental-friendly and sustainable trajectory.
Urban metabolism has emerged over the past decades as an important new paradigm of regional and urban sustainability governance towards a Chinese national scheme of ‘carbon neutrality’ by 2060. Hebei province in China faces twin pressures related to its supply of water and energy resources, which has brought humans and nature into conflict. Overcoming this tension in the human-land relationship in Hebei and determining a suitable development path for the future has become a core issue for the achievement of coordinated development within the Beijing–Tianjin–Hebei region. This paper constructs a system to simulate the metabolism of water, energy, and human relationships, and uses this model to carry out simulations for Hebei province. The model establishes five scenarios: a natural development scenario, economic growth scenario, water conservation development scenario, energy conservation development scenario, and low carbon scenario. The simulation results show that, without intervention, the natural development scenario results in greater pressure on supply gaps and a greater demand for water and energy, with more production of industrial waste gas and domestic wastewater discharges. The economic growth, water conservation development, and energy conservation development scenarios focus on single economic, water conservation, and energy conservation measures by looking at core economic, water, and energy elements within the metabolic system; however, solving issues with individual elements merely leads to other, remaining problems. Under the low carbon scenario, issues with multiple elements in Hebei’s metabolic system are considered more comprehensively, so the simulation results are better than those in the other scenarios, and it better fits the future orientation of sustainable development of Hebei province.
Increasing pressures on ecosystems in the Latin American region, as well as the adoption of multilateral conservation commitments, have led to the implementation of instruments that are economic in nature but oriented towards the recovery, conservation, and functioning of ecosystems such as Payment for Ecosystem Services (PES). In the Peruvian Andes, hydro-climatic factors and land-use changes are affecting the capacity of the ecosystems of the glaciated Cordillera Blanca to provide water services, in terms of both quality and quantity, to the main users of the Santa River basin. Thus, this study analyses how the socio-ecological interactions affect, and are affected by, the planned introduction of water-related PES in the Quillcay sub-basin, the most populated sub-basins along the Santa River basin. We use a conceptual model based on the current evolution of the water metabolism approach to integrate into a common language of analysis the multiple dimensions of water: water as an ecological fund, as a service, and as a political asset. To explore the interface of these three domains of analysis we rely on a mixed-method data collection: primary data collection through a stakeholder survey and interviews and a review of information from secondary sources. The result of our case study shows that both the ecological dimension and the social dimension affect on the PES project and vice versa. These complex interactions could result in the design of a mechanism in which not all stakeholders benefit equally. This raises the need to recognise the multidimensional nature of water in the design and implementation of policies, and the importance of identifying processes and barriers which affect the success of these policies without making invisible the direct effect they also have on social-ecological systems.
The COVID-19 pandemic and the related lockdown restrictions have imposed a wide range of impacts that need to be analysed based on the specific characteristics of countries. By comparing socio-economic and energy data for the four quarters of 2020 to the same period of 2019, the MuSIASEM approach is used, for the first time, to investigate the energy metabolism of UK during a period of economic downturn. Results show that the commercial and the public administration activities have been able to achieve energy efficiency increases, and the residential sector has accounted for energy-related economies of scale. The industrial and the other activity sectors, on the contrary, have raised the energy intensity of production. Comparted to time series data, scenarios, and modelling exercises, the MuSIASEM approach integrates a wide range of intensive and extensive variables across different scales of analysis and investigate how specific socio-economic and energy structures have reacted to the COVID-19 crisis. The methodology can be easily replicated for other case studies and results can support the design of recovery and sustainable transition strategies.
The social and ecological impacts of urbanization require integrated management of cities and their resource metabolism for long-term sustainability and economic prosperity. Traditionally, network models are used to study internal metabolic processes in cities, complementing the traditional “black box” urban models to account for the input of material and energy resources and the output of final products and wastes. This study introduces a multi-criteria assessment framework by integrating a unique hybrid-unit input-output model with the emergy accounting method to estimate the environmental support provided to urban socio-economic systems, applied here to the case of Vienna, Austria. By focusing on the internal organisation and functioning of urban socio-economic systems, the proposed framework strengthens the understanding of ecological and socio-economic flows exchanged among industries and the environment. The results suggest that resources can be saved by applying supply-side and demand-side interventions and improving share of renewables. The multi-criteria assessment framework developed in this study allows to investigate the urban metabolism of cities and regional contexts through the identification of sustainable pathways rooted in material circularity and resource efficiency, supporting the design of policies in line with the “integrated wealth assessment” and “circular economy” principles.
To meet the global need for carbon neutrality, we must first understand the role of urban carbon metabolism. In this study, we developed a land–energy–carbon framework to model the spatial and temporal variation of carbon flows in Beijing from 1990 to 2018. Based on the changes in carbon sequestration and energy consumption, we used ecological network analysis to identify the critical paths for achieving carbon neutrality during land-use changes, thereby revealing possible decarbonization pathways to achieve carbon neutrality. By using GIS software, changes in the center of gravity for carbon flows were visualized in each period, and future urban construction scenarios were explored based on land-use policy. We found that the direct carbon emission peaked in 2010, mostly due to a growing area of transportation and industrial land. Total integrated flows through the network decreased at an average annual rate of 3.8%, and the change from cultivated land to the socioeconomic sectors and the paths between each socioeconomic component accounted for 29.5 and 31.7% of the integrated flows during the study period. The socioeconomic sectors as key nodes in the network should focus both on their scale expansion and on using cleaner energy to reduce carbon emissions. The center of gravity gradually moved southward, indicating that the new emission centers should seek a greener mixture of land use. Reducing carbon emission will strongly relied on transforming Beijing’s energy consumption structure and increasing green areas to improve carbon sinks. Our results provide insights into carbon flow paths that must be modified by implementing land-use policies to reduce carbon emission and produce a more sustainable urban metabolism.
Urban metabolism studies provide valuable insights that can improve resource efficiency at the city scale. However, only a limited number of such studies include spatially explicit data to inform planning practitioners. In this article, we argue that integrating spatially explicit urban metabolism data in urban planning can leverage resource‐efficient development and management of open space networks. Based on this premise, our research presents a methodological strategy to investigate how the use of GIS data can improve the applicability of metabolic studies in urban planning and the management of open space networks in particular. A GIS‐based urban metabolism assessment of Mexico City was performed at the city scale, including data on vulnerable communities, communal lands, and indigenous areas. After mapping selected GIS layers, a detailed resource‐efficiency analysis was performed through the compilation of a Borough Pattern Scan, based on quantification of resource use, total areas of resource infrastructure, and public open spaces. The results of our multiscale spatially explicit analysis provide an improved understanding of borough metabolic profiles, which can leverage a more resource‐efficient development of open space networks in Mexico City.
Cities are complex sociotechnical systems, of which buildings and infrastructure assets (built stocks) constitute a critical part. As the main global users of primary energy and emitters of associated greenhouse gases, there is a need for the introduction of measures capable of enhancing the environmental performance of built stocks in cities and mitigating negative externalities such as pollution and greenhouse gas emissions. To date, most environmental modeling and assessment approaches are often fragmented across disciplines and limited in scope, failing to provide a comprehensive evaluation. These approaches tend to focus either on one scale relevant to a discipline (e.g., buildings, roads, parks) or particular environmental flows (e.g., energy, greenhouse emissions). Here, we present a framework aimed at overcoming many of these limitations. By combining life cycle assessment and dynamic modeling using a nested systems theory, this framework provides a more holistic and integrated approach for modeling and improving the environmental performance of built stocks and their occupants, including material stocks and flows, embodied, operational, and mobility‐related environmental flows, as well as cost, and carbon sequestration in materials and green infrastructure. This comprehensive approach enables a very detailed parametrization that supports testing different policy scenarios at a material, element, building, and neighborhood level, and across different environmental flows. We test parts of our modeling framework on a proof‐of‐concept case study neighborhood in Melbourne, Australia, demonstrating its breadth. The proposed modeling framework can enable an advanced assessment of built stocks that enhances our capacity to improve the life cycle environmental performance of cities.
The real-world urban systems represent nonlinear, dynamical, and interconnected urban processes that require better management of their complexity. Thereby, we need to understand, measure, and assess the structure and functioning of the urban processes. We propose an innovative and novel evidence-based methodology to manage the complexity of urban processes, that can enhance their resilience as part of the concept of smart and regenerative urban metabolism with the overarching intention to better achieve sustainability. We couple Life Cycle Thinking and Machine Learning to measure and assess the metabolic processes of the urban core of Lisbon's functional urban area using multidimensional indicators and measures incorporating urban ecosystem services dynamics. We built and trained a multilayer perceptron (MLP) network to identify the metabolic drivers and predict the metabolic changes for the near future (2025). The prediction model's performance was validated using the standard deviations of the prediction errors of the data subsets and the network's training graph. The simulated results show that the urban processes related to employment and unemployment rates (17%), energy systems (10%), sewage and waste management/treatment/recycling, demography & migration, hard/soft cultural assets, and air pollution (7%), education and training, welfare, cultural participation, and habitat-ecosystems (5%), urban safety, water systems, economy, housing quality, urban void, urban fabric, and health services and infrastructure (2%), consists the salient drivers for the urban metabolic changes. The proposed research framework acts as a knowledge-based tool to support effective urban metabolism policies ensuring sustainable and resilient urban development.
The concept of urban metabolism has been profusely used by various disciplines over the last and current century to describe different urban phenomena. One theme that appears to gain importance in the interdisciplinary field of urban metabolism is the spatial dimension. In this article, we have carried out a bibliometric and qualitative analysis of the use of this multi-faceted notion in order to understand the place of space in urban metabolism research. Our results show that several communities within the urban metabolism field use and manipulate space for their research according to different approaches (territorial economic, socio-political, socio-ecological, governance and urban planning, and modeling). We discuss recent contributions of these communities and their approaches, their limitations, and a future agenda that might cross-fertilize them in order to embed space more consistently in urban metabolism research.
Pollution mitigation and environmental adaptation are two major strategies to fight for environmental sustainability. Both adaptation and mitigation require enormous resources, investments, and careful planning. Most related studies focus on coordinating adaptation and mitigation policies at global international scales. However, a variety of adaptation and mitigation actions occurs at local and regional levels.
The authors survey various decision-support approaches used to justify rational adaptation and mitigation activities focusing on middle level management policies relevant to regions and large cities. Such decisions heavily depend on the economy, geography, and resources of a region.
This review describes adaptation and mitigation activities at regional level and discusses classification, advantages, and limitations of related models, modeling methodologies, their logistics and data support. Both quantitative and qualitative methods and models are discussed. The authors emphasize the importance of multi-disciplinary modeling of urban adaptation and mitigation in interaction with other areas of city planning and management.
The globalisation of exchanges has resulted in excessive growth of material and immaterial flows. The disconnection among the supply, production, decision-making and consumption sites generates new spatial interdependencies. It determines local socio-economic dynamics and affects ecosystems. In this context, the question arises if territorial capability—“localized collective capacity to serve territorial development”—influences, from local level, these globalised flows systems. By combining territorial economic principles and territorial ecology approaches, we study the industrial metabolism of the Maurienne valley in France. The Maurienne case shows how territorial characteristics contribute to the economic resilience in rural areas. The calculation of wealth flows provides information on the local economic base, the weight of industry and its social impact. The analysis of physical flows reveals the materiality of this industry and the dependence on external resources and international companies. It highlights the various pressures and risks on the environment. To deal with these constraints, companies rely on relational and geographic proximities with local subcontractors. These relationships determine both the proper functioning of the local industrial system and the territorial capability to maintain and transform industrial activities. Most rural European territories experience the same industrial issues and environmental challenges. Therefore, this study offers new research perspectives to better understand and promote ecological transition in old and often rural industrial areas.
The article examines the impact of the virtual public sphere on how urban spaces are experienced and conceived in our data-driven society. It places particular emphasis on urban scale digital twins, which are virtual replicas of cities that are used to simulate environments and develop scenarios in response to policy problems. The article also investigates the shift from the technical to the socio-technical perspective within the field of smart cities. Despite the aspirations of urban scale digital twins to enhance the participation of citizens in the decision-making processes relayed to urban planning strategies, the fact that they are based on a limited set of variables and processes makes them problematic. The article aims to shed light on the tension between the real and the ideal at stake during this process of abstracting sets of variables and processes in the case of urban scale digital twins.
Landfill mining has become an emerging issue in urban metabolism research and environmental remediation practices. Comprehensive understanding of the quantity and distribution of material stocks in landfills, as well as identifying hotspots of landfill mining potential, is of crucial importance. However, high-resolution datasets and systematic analytical tools remain insufficient. This study established a time-series landfill material stock inventory at prefecture level in China. An evaluation system for mining potential of landfills at prefecture level was then constructed using an integrated expert scoring and entropy weight method, based on ten indicators across five dimensions, including environmental impact, energy recovery, resource cycling, economic cost, and social aspect. The results show that over the past twenty years, the material stock in landfills was 2321.07 Tg (106 tons) in China, among which, soil-like materials, ash & stone and plastic & rubber were the three largest fractions, accounting for 61.06 wt%, 18.96 wt%, and 12.69 wt% of the total stock. Regional differences in landfill mining potential were found to be significant, with South China presenting the largest mining potential, while Southwest China showed the lowest. Cities with better economic development in China show the possibility to have greater landfill mining potential. This study established a methodology for the assessment of landfill mining potential for China or other countries, and provided scientific evidences for formulating regional-specific policies on landfill mining in China.
The challenges and impacts from rapid urbanisation coupled with the impacts of climate change and other global planetary boundary issues are prompting cities to take urgent action toward safeguarding the sustainability of the urban fabric – reducing environmental and social impacts while improving liveability. The advent of sustainability-oriented technology is being recognised as having a predominant role in this process. However, these solutions are often claimed as part of the Smart City technology arsenal when often they have little to do with digital data systems. Thus, the agenda of Smart Cities in the past has claimed digital technology upgrades will automatically help solve sustainability problems; however, the simple provision of more digital capacity does not necessarily mean this will happen. New approaches to sustainability where smart systems are made an integrated part of the metabolism of cities can provide solutions that also can lead to increased liveability levels.
Since the mineral, phosphorus (P), has dual properties of being limited resources for use, and being a pollutant for studying sustainable management of anthropogenic P flows in wetlands and soils, currently P receives the highest interests among researchers around the world. This study has successfully mapped P flows for a reference year (2017) and a future year (2030) using different scenarios of food production and consumption system (hereafter 'system') in the Mwanza region (Tanzania). The results showed that the total P input and output for 2017 alone were 9770 t and 7989 t, respectively. However, as high as 1781 tP accumulated in the system and the potentially recyclable P found, is yet to be recovered due to economic reasons and the lack of market. The main anthropogenic P input to the system occurred via imported feed, fertilizer, and crop food, accounting for about 99.72 % of the total input flow. The output was comprised of animal products exported with 3428 tP, and various P-contained wastes which were lost to water bodies with 4561tP. Analysis of the 2030 scenario showed that setting P management objectives from different perspectives such as the total P budget balance, potential recyclable P, and P emission, can help develop differentially preferred management strategies and measures in the Mwanza region. The combination of diet change, precision feeding, and integrated waste management practices presents the best prospects for decreasing P budget and losses, and the amount of P that can be potentially recovered from the system. We propose a package of integrated P management measures for the Mwanza region. Given the similarity of regional socio-economic development background around the Lake Victoria basin, the model can be used to guide the study of anthropogenic P flow analysis in other areas along the shore of Lake Victoria (Africa).
Modeling Water-Energy-Food (WEF) nexus is necessary for integrated water resources management (IWRM), especially in urban areas. This paper presents a new urban water metabolism-based methodology for WEF nexus modeling and management. A behavioral simulation model is used to incorporate the characteristics of stakeholders in an urban area. Modified versions of the Borda count, Copeland rule, and fallback bargaining procedures are implemented to choose the socially acceptable management scenarios. Finally, the selected scenarios’ effectiveness is evaluated using the fairness and total utility indices.
The applicability of the proposed methodology is evaluated by applying it to the Kan River basin, Tehran, Iran, which is suffering from some water and environmental issues. The considered management scenarios include adding new water sources, leakage control plans, using rubber dams for enhancing groundwater recharge, revising water allocation priorities, and developing semi-centralized or decentralized reuse strategies for reclaimed wastewater. Results illustrate that considering different fluxes (i.e., water quantity, pollutants, energy, greenhouse gases (GHG), and materials) is as important as incorporating the social characteristics of stakeholders. Simulating the socially acceptable scenario shows that the aquifer's average water level improves by 3 (), and its average nitrate concentration reduces by 16 () in comparison with the business as usual (BAU) scenario. In addition, by implementing different water reuse strategies, which are energy-intensive, total energy consumption is reduced by 5% due to less groundwater pumping. Also, the selected scenario decreases GHG emissions by 18% and increases the sequestrated carbon dioxide by 20%. In conclusion, the proposed decision support tool can provide policies for sustainable water resources management considering water quality and quantity issues, energy usage, and GHG emission.
Material metabolism in a Chinese megacity, Shanghai, was investigated with an integrated approach. Production-based raw material input, city-wide waste output and carbon emissions were compiled for the period 1995-2020, by computing hundreds of products and by-products. Decoupling of these resource and environmental flows from economic development was assessed, and the socio-economic and technical drivers were decomposed. The research demonstrated the hypothesis that flows of primary resources, waste, and carbon emissions displayed a certain level of synchronicity in the past decades. An order effect was seen with waste indicators usually performing better than carbon indicators, and carbon indicators are better than resource indicators in terms of material/environmental intensity and decoupling. There might be a resource leverage leading to the synchronicity of environmental emissions. Improvement in resource efficiency was decomposed as the most significant driver to urban metabolism, bringing about >33 % of resource reduction, 32 % of carbon mitigation, and 30 % of waste diminution from the 2010 values. A greater extent in emission reduction than resource use was attributed to the decrease of fossil fuels share in total resource use and carbon intensity per energy consumption. Continuous increase in post-use waste flows caused a rebound of waste indicators in the recent five-year period (2016-2020) and broke up the synchronicity. This potentially foresees the shift of material metabolism from production to consumption side in major cities in China and calls for reforms of environmental policies.
Materials and energy consumed by urban systems are one of the main sources of greenhouse gas emissions. Measuring these flows and their associated emissions is necessary to estimate the impact of cities on climate change in the future. In this research we developed a dynamic model for measuring the carbon footprint of cities’ urban metabolism using an integrated socio-ecological systems approach. Illustrated with a case study in Montreal we modelled the urban carbon footprint between 2000 and 2018, and simulated on to 2030 under four scenarios: baseline, increasing adoption of plant-based diets (PBD), pavement/road material circularity (PMC), and a combined approach of the latter two. By simultaneously modelling Montreal's population growth the GHG per capita trend was compared to the anticipated 2030 global threshold of 2.9 t CO2e per person needed to meet the 1.5°C Paris Agreement target. All scenarios result in decreased per capita emissions from 15.0 t CO2e/capita in 2018, in part due to the increasing urban population. The baseline scenario estimates a decrease to 12.7 t CO2e by 2030; the PBD and PMC scenarios estimate respective reductions to 10.8 and 12.4 t CO2e/capita by 2030. The combined scenario estimates a greater reduction to 10.5 t CO2e/capita, but this is still 7.6 t CO2e/capita over the Paris Agreement target for 1.5°C global warming.
The development of urbanization accelerates the construction of urban buildings, infrastructure, and the production of artifacts to support the basic socioeconomic activities in cities. To prepare for future urban development and enhance urban resilience, it is necessary to understand the scale of existing buildings, infrastructure and artifacts in cities. Taking Beijing, Shanghai, Guangzhou, Wuhan, and Chengdu as an example, this study used material flow analysis to calculate the material stock of urban buildings, infrastructure, and artifacts from 1978 to 2018, explored the accumulation process and structural changes of urban material stock, and analyzed the driving factors of material stock changes. The results showed that urban material stock had accumulated rapidly, and its constituent structure was dominated by buildings (60-82%) and infrastructure (14-31%), while the artificial products were relatively low (3-7%), and its material structure was dominated by sand and gravel (66-70%). Economic development and urban population were the main drivers for material stock growth, while material intensity and urban-rural structure showed an inhibition effect. The results can provide a scientific basis for sustainable construction and management of material stock in urban buildings, infrastructure and artifacts.
The metabolic processes of cities and their embedded regions have received great attention, but it is still unclear how the metabolic processes change at the scale from cities to urban agglomerations. In view of the lack of multi-scale research in the field of urban metabolism, this study took Beijing-Tianjin-Hebei region, one of the urban agglomerations with largest economic scales in China, as a case to construct metabolic network models at two scales of city and urban agglomeration. The material transfers between nodes were calculated, and the connection degree index was put forward in the ecological network analysis to quantify the influence of a single node on the network when multi-level transfers were considered. On this basis, the similarities and differences of metabolic nodes at the two scales were analyzed. The results showed that nearly 97% of the volume of material transfers in the urban agglomeration was concentrated within the cities, among which the transfer volumes of Tangshan, Handan, and Shijiazhuang were more than 600 Mt. Manufacturing and environment were the major contributors to material transfers. The connection degrees of nodes had both commonness and differences at the two scales. In general, the connection degrees at the urban scale were relatively homogeneous, while their difference was large at the urban agglomeration scale. The connection degrees of nodes in Langfang were prominent at the urban agglomeration scale. The connection degrees of environment and manufacturing ranked top 3 at both scales. Meanwhile, the connection degree of energy conversion at the urban scale was relatively high, while its influence was replaced by mining sector at the urban agglomeration scale. The analysis of material metabolic nodes in Beijing-Tianjin-Hebei region can provide theoretical supports to position the key points in the process of material utilization in the cities or the urban agglomeration, and help to identify the breakthrough points for subsequent regulatory.
Energy and water are rapidly consumed as the most basic strategic resources of various nations. It is of vital importance to systematically explore the environmental and economic impacts of energy-water co-management policies. This study is to develop a multiperspective-driven factorial metabolic network analysis framework (MPDF) to (a) investigate the direct/indirect/total resource consumption response mechanisms induced by changes in production and consumption; (b) explore the factor interactions of different policies in diverse energy and water metabolic networks by initiating factorial analysis; (c) quantify the economic effects of co-management policies by proposing multiple vulnerability indicators. A typical energy-dependent region, Shanxi Province, China was selected as a case study. The results indicated that the production- and consumption-oriented policies have various guidelines for reducing direct and indirect energy–water consumption. Significant interactions in simulation results suggest synergistic effects across sectors. Considering that Shanxi's energy-water nexus economic vulnerability is as high as 2.22%, it is recommended to prioritize the allocation of resources to sectors with significant factor effects to avoid economic losses. Implementing corresponding resource conservation policies for light industry, machinery manufacturing, construction can reduce water consumption by 18.8%. The findings are expected to provide a solid scientific basis for formulating co-management strategies to alleviate resource scarcities.
Urban areas with large population and economic activity are responsible for the increased resource and environmental challenges, making circular economy an important issue. Sustainable development and targeted suggestions for local areas are essential for policy implementation. In this study, a circular urban metabolism (CUM) framework was developed to assess resource use patterns for potential identification and policy initiatives of circular development. The framework was conceived as a circular process for sectoral material flow mechanisms, which was followed by resource use calculations and circularity potential analysis. In the Shanghai case, the CUM framework was testified and revealed dramatic increases of material inputs and outputs, doubled during 2000–2019. Close relationship with external areas was indicated by large resource consumption and pollution discharge. Specified by CUM, the expanded in-use stock, mainly consisted of non-metallic minerals used in construction sector, were one of the obstacles towards circularity. Energy-induced pollution was the other obstacle, which were suggested by mixed energy use initiatives. Sectoral policy to improve resource use patterns were finally provided at the city level.
Humanity is facing major societal challenges that are complex and systemic in the nature of their drivers, interactions, and impacts. Because buildings and cities play a substantial role in these societal challenges, we need reliable approaches that can be used to assess their resilience and sustainability. Given that building and urban systems are usually tightly coupled, we critically review nine building-scale assessment frameworks and seven urban-scale assessment frameworks, ranking them from high to low in terms of the causality among component systems. We identify four major knowledge gaps that, to varying degrees, span the entire range of assessment frameworks: (1) causality among component systems and their subsystems is limited; (2) sustainability and resilience are too narrowly defined; (3) social systems are inadequately addressed; and (4) building- and urban-scale assessments are poorly connected. To address these limitations, we briefly introduce several closely-related fields of research including integrated assessment and modeling, social-ecological systems research, land systems science, socio-environmental systems modeling, modeling of human behavior, multi-scale modeling, and multi-fidelity modeling. Building on these rapidly emerging research domains, we conclude by proposing a more holistic, multi-scale, system-of-systems approach that connects across building and urban scales using several common systems.
Urban activities are an important driver of ecosystem services decline. Sustainable urbanisation necessitates anticipating and mitigating these negative socio-ecological impacts, both within and beyond city boundaries. There is a lack of scalable, dynamic models of changes to ecosystems wrought by urban processes. We developed a system dynamics model, ESTIMUM, to predict locations, types, and magnitude of changes in ecosystem services. We tested the model in Lisbon (Portugal) under four specific urban development scenarios – a base case scenario and three local sustainability-driven scenarios – to the year 2050. Our results show that urban sustainability policies focused on reducing impacts within Lisbon can be undermined by increased impacts in the extended regions that supply resources to the city. In particular, carbon sequestration from urban greening pales in comparison to growing greenhouse gases from the consumption of food, energy and construction materials. We also find that policies targeted at these extended environmental impacts can be much more effective than those with a limited focus on the urban form. For example, dietary shifts could support positive changes outside that city to increase global climate regulation by 54% compared to a mere 1% increase through intensive urban greening. This highlights the urgent need for a reframing of urban sustainability in policy and scholarly circles from city-centric focus towards an expanded multi-scalar conceptualisation of urban sustainability that accounts for urban impacts beyond the city boundaries.
The functional roles and environmental effects of long-lived buildings, infrastructure, and durable goods can determine both the benefits to natural environment and a city's human residents. However, their overall lifecycle metabolic processes are complicated and previous studies mainly considered specific materials or products. Here, we provide a more comprehensive picture of flows and stocks for Beijing's materials, products (61), and sectors (9). Based on a multi-level material stock–flow network model, we obtained insights into the city's material inputs and outputs of each urban sector, the cumulative flows of materials and products, and the waste sources for end-of-life products. From 2000 to 2018, the total system throughflow increased from 269 to 435 Mt by 2007, then decreased to 317 Mt. Beijing's main sector of consumed resources and discharged wastes both shifted from Fabrication and Manufacturing to Construction. The local extraction and production weights decreased by half, whereas the inflows to the Construction and Transportation sectors increased greatly, mainly (92%) as imports (from regions other than Beijing). The main destinations of these materials were buildings and pipelines, which were also main waste sources. Notably, resource demand and waste discharge from vehicles and railways increased greatly. Although Beijing's recycling increased, it must increase further to meet final waste generation, which has increased 5-fold, to 52 Mt in 2018 during the city's socioeconomic development. Additional actions should be taken to reduce waste streams and promote reuse and recycling to achieve the UN Sustainable Development Goals.