A physiology-inspired framework for holistic city simulations

Guest Editorial: Special issue on flexible and resilient urban energy systems

Numerical and computational modelling of flow and pollutant dynamics in urban drainage systems is becoming more and more integral to planning and design. The main aim of integrated flow and pollutant models is to quantify the efficiency of different measures at reducing the amount of pollutants discharged into receiving water bodies and minimise the consequent negative water quality impact. The open source toolbox CITY DRAIN developed in the Matlab/Simulink environment, which was designed for integrated modelling of urban drainage systems, is used in this work. The goal in this study was to implement and test computational routines for representing sediment and pollutant loads in order to evaluate catchment surface pollution. Tested models estimate the accumulation, erosion and transport of pollutants--aggregately--on urban surfaces and in sewers. The toolbox now includes mathematical formulations for accumulation of pollutants during dry weather period and their wash-off during rainfall events. The experimental data acquired in a previous research project carried out by the Environmental Engineering Research Centre (CIIA) at the Universidad de los Andes in Bogotá (Colombia) was used for the calibration of the models. Different numerical approaches were tested for their ability to calibrate to the sediment transport conditions. Initial results indicate, when there is more than one peak during the rainfall event duration, wash-off processes probably can be better represented using a model based on the flow instead of the rainfall intensity. Additionally, it was observed that using more detailed models (compared with an instantaneous approach) for representing pollutant accumulation do not necessarily lead to better results.

Chengzhongcun, or ‘villages-in-the-city’, have been a major feature of China’s urban landscape in the post-Mao era. The existing literature largely casts them as side effects of rapid urbanization or a momentary oddity of market transition providing temporary solutions to urban needs until more efficient mechanisms for affordable housing and social welfare are developed. This article positions chengzhongcun within the broader system of unequal exchange that is at the heart of China’s rural–urban dual system and development model. This article argues that chengzhongcun are an inherent feature of China’s post-Mao urbanization model, a physical manifestation of its dual system that differentially regulates people and space according to their classifications as ‘rural’ or ‘urban’. China’s urban development must be understood as a product of this dual system based on the exploitation of the rural sector, including its land, property and people.

Whilst the importance of integrated modelling of urban wastewater systems is ever increasing, there is still no concise procedure regarding how to carry out such modelling studies. After briefly discussing some earlier approaches, the guideline for integrated modelling developed by the Central European Simulation Research Group (HSG - Hochschulgruppe) is presented. This contribution suggests a six-step standardised procedure to integrated modelling. This commences with an analysis of the system and definition of objectives and criteria, covers selection of modelling approaches, analysis of data availability, calibration and validation and also includes the steps of scenario analysis and reporting. Recent research findings as well as experience gained from several application projects from Central Europe have been integrated in this guideline.

In an increasingly urbanized world, there are pressures being placed on our cities to which planners, decision-makers and communities need to respond. Leading thinkers suggest a need for enhanced expertise in urban systems and call for additional and improved case studies as well as models for planning, management, policy development and decision-making. Planning support systems (PSS) offer demonstrated strengths in modelling and analysis of urban systems, communication of information and public engagement. However, in spite of the demonstrated need, a dominant thread in the planning support literature is the under-utilization and lack of implementation of systems and instruments. This chapter investigates the relevance of PSS to address urban problems in the twenty-first century by reviewing project-based use cases and the social context in which they take place. The review confirms the utility of PSS but finds that planning and governance are strongly dictated by a number of societal trends that are antithetical to effective and impactful PSS implementation.

BackgroundAchieving climate neutrality in cities is a major challenge, especially in light of rapid urbanization and the urgent need to combat climate change. This paper explores the role of advanced computational methods in the transition of cities to climate neutrality, with a focus on energy supply and transportation systems. Central to this are recent advances in artificial intelligence, particularly machine learning, which offer enhanced capabilities for analyzing and processing large, heterogeneous urban data. By integrating these computational tools, cities can develop and optimize complex models that enable real-time, data-driven decisions. Such strategies offer the potential to significantly reduce greenhouse gas emissions, improve energy efficiency in key infrastructures and strengthen the sustainability and resilience of cities. In addition, these approaches support predictive modeling and dynamic management of urban systems, enabling cities to address the multi-faceted challenges of climate change in a scalable and proactive way.Main textThe methods, which go beyond traditional data processing, use state-of-the-art technologies such as deep learning and ensemble models to tackle the complexity of environmental parameters and resource management in urban systems. For example, recurrent neural networks have been trained to predict gas consumption in Ljubljana, enabling efficient allocation of energy resources up to 60 h in advance. Similarly, traffic flow predictions were made based on historical and weather-related data, providing insights for improved urban mobility. In the context of logistics and public transportation, computational optimization techniques have demonstrated their potential to reduce congestion, emissions and operating costs, underlining their central role in creating more sustainable and efficient urban environments.ConclusionsThe integration of cutting-edge technologies, advanced data analytics and real-time decision-making processes represents a transformative pathway to developing sustainable, climate-resilient urban environments. These advanced computational methods enable cities to optimize resource management, improve energy efficiency and significantly reduce greenhouse gas emissions, thus actively contributing to global climate and environmental protection.

In response to the growing need for sustainable urban development, energy systems modelling must provide long-term carbon-neutral solutions at the city scale while balancing competing criteria. This work introduces a multi-objective optimization approach addressing technical, economic, and environmental criteria for urban smart energy systems designed to achieve 100% renewable energy integration. The analysis incorporates climate change impacts on both energy demand and production. Two optimization strategies are evaluated using Bozen-Bolzano, Italy, as a case study. Specifically, the energy systems were modelled using EnergyPLAN, integrated with Python for automation. Grid search and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were adopted as optimization methods to compare the advantages and limitations of two different approaches. The results show that both methods produce similar solutions on the Pareto front, with the grid search slightly outperforming due to the consideration of extreme input ranges. However, NSGA-II generated a significantly larger number of Pareto solutions, demonstrating its effectiveness in exploring the solution space more comprehensively. This study underscores the importance of incorporating climate change into multi-objective optimization for robust decision-making in the design of smart urban energy systems for sustainable development. • Optimal techno-economic and environmental design of 100% renewable systems. • Comparison of optimization approaches in urban energy systems modelling. • Impact of climate scenarios on energy demand and renewable integration.

ABSTRACTThis paper proposes an optimal urban expressway system model with consideration to the interaction equilibrium between transportation and land use. In the suggested model, three kinds of economic agents were examined. Government departments design an optimal urban expressway system in order to maximize the urban system’s total utility under a limited budget. However, households and firms choose their locations according to the attractiveness of each traffic zone related to road network accessibility and housing prices. In addition, this optimization problem is formulated as a bi-level program in which the upper-level subprogram maximize the urban system’s total utility from the government departments’ point of view, whereas the lower-level subprogram uses the transportation and land use equilibrium model. A Genetic Algorithm (GA) was used to solve this mixed integer non-linear programming problem. Finally, this work used numerical experiments to demonstrate the properties of the problem and the performance of our proposed model.

Early hydrologic and hydraulic numerical modeling of urban drainage systems focused on the minor system (i.e. storm sewer only). Over the past three decades th…

In order to cope with urban flooding, water scarcity and rainfall-runoff pollution comprehensively, a conceptual tank model of urban storm water system is proposed. Tank model is a multi-layer, multi-objective model, so design of urban storm water system is more complex than that of urban storm sewer system. Some principles of design of urban storm water system are discussed, such as Low Impact Development, Smart storm water management, and so on.

Under the carbon peaking and carbon neutrality goals background in China, cities are the main force of energy consumption and carbon emission, and their low‐carbon transition development has become the primary task of urban planning. The transitional development of cities not only puts forward higher requirements for the output proportion of new energy, but also puts forward higher requirements for the flexibility of energy system. This paper proposes an optimization model of urban energy system considering the uncertainty output of new energy and new energy vehicles. The uncertainty and operational flexibility of electric vehicles are taken into account at the planning level by using stochastic optimization method. The model considers the expansion and retirement of new energy units and various conversion devices in urban energy system, and ensures the achievement of carbon peaking and carbon reduction goals by imposing constraints on electric vehicles. The case results show that this model can effectively improve the economy and new energy consumption rate of urban energy system, and can meet the carbon reduction demand.

There is a growing need for urban water managers to take a more holistic view of their water resource systems as population growth, urbanization, and current resource management practices put different stresses on local water resources and urban infrastructure. Total Water Management (TWM) is an approach that examines urban water systems in a more interconnected manner, focusing on reducing water demands, increasing water recycling and reuse, creating water supply assets from stormwater management, matching water quality to end-use needs, and achieving environmental goals through multi-purpose, multi-benefit infrastructure. The goal of this study was to communicate benefits of TWM to water management decision-makers and to aid in the development of management techniques that could be adopted in order to improve urban systems. The first element of the study was a comprehensive literature review that summarized TWM principles and real-world applications in the United States and abroad. The literature review was organized into different regions of the country in order to reflect geographic water management drivers and challenges. A systems model demonstrated how TWM alternatives would perform against traditional approaches to water management. The model simulates supply reliability, total lifecycle costs, water quality of receiving waters, and a number of other environmental indicators. Water Evaluation and Planning (WEAP) software, developed by the Stockholm Environment Institute, was used to develop the systems model. A case study for TWM model was based on The City of Los Angeles, CA and used real data, within real context. The city was divided into four demand areas, each with its own connections to surface, ground, and imported water supply sources, as well as connections to downstream wastewater treatment plants and receiving bodies. TWM strategies that were evaluated included increased water conservation, expanded recycling and reuse, greywater, stormwater recharge, and rainwater harvesting. The WEAP model simulated how integrated water supply, stormwater and water quality management can provide increased opportunities for achieving urban system goals that would not exist in single-purpose, traditional planning.

Investigation and numerical modelling of roof drainage systems under extreme events

Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities

The main processes in the urban wastewater system and their representation in models have been presented in the previous chapter. The present chapter outlines the development of the integrated simulation and optimisation tool (named SYNOPSIS - “Software package for synchronous optimisation and simulation of the urban wastewater system”), which is to be used for the studies described in later chapters of this book. The development of the tool starts with the definition of a list of requirements (Section 3.1), which are based on the discussion of the previous chapter. According to these requirements, three existing software packages are selected for implementation in SYNOPSIS (Section 3.2). Section 3.3 describes their integration to an integrated simulation tool. This section also discusses the problems encountered when connecting the simulation programs. Implementation of control options is detailed in Section 3.4. Section 3.5 discusses the implementation of the optimisation procedures selected in Section 2.5 and their interfaces with the simulation tool.