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Review

Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review

by
João Monteiro
1,
Nuno Sousa
2,3,
João Coutinho-Rodrigues
2,4 and
Eduardo Natividade-Jesus
2,5,*
1
Research Centre for Territory, Transports and Environment (CITTA), 4200-465 Porto, Portugal
2
Institute for Systems Engineering and Computers of Coimbra (INESCC), 3030-790 Coimbra, Portugal
3
Department of Sciences and Technology, Universidade Aberta, 1269-001 Lisbon, Portugal
4
Department of Civil Engineering, University of Coimbra, 3004-531 Coimbra, Portugal
5
Department of Civil Engineering, Polytechnic Institute of Coimbra, 3045-093 Coimbra, Portugal
*
Author to whom correspondence should be addressed.
Energies 2024, 17(2), 409; https://doi.org/10.3390/en17020409
Submission received: 16 December 2023 / Revised: 3 January 2024 / Accepted: 12 January 2024 / Published: 14 January 2024

Abstract

:
This article reviews the critical issues surrounding the development of sustainable urban environments, focusing on the impact of transport and urban form on energy consumption and greenhouse gas emissions. The aim is to provide an overview of the state-of-the-art on the subject and to unravel what directions the literature suggests for sustainable urban planning. Current research and practices are synthesized, highlighting the interdependence of urban design and transportation systems in achieving sustainability goals. Important dimensions and practices of city planning and transport policies are explored, including urban form, urban sprawl, mixed land use, densification and infill, and urban public spaces, and how these directly influence transport dynamics, including modal choices and energy consumption. Innovative approaches in urban planning, such as transit-oriented development, and technological advancements, such as electric mobility, are also examined and their potential roles in sustainable urban transport. The conclusion underscores the urgency of adopting holistic and adaptable strategies to foster sustainable urban environments, calling for concerted efforts from policymakers, urban planners, and communities. Awareness of the conclusions can help municipal decision-makers in planning their cities for a sustainable future. Finally, the authors analyze important directions for future research and practical applications towards developing cities that are environmentally sound, socially equitable, and economically viable.

1. Introduction

Urban population has been rising for the past decades, with currently more than half (55%) of the world’s population living in cities, a number expected to increase to 68% by 2050 [1,2,3]. Cities are the main engines of global economic growth, and despite occupying just 3% of the earth’s surface [3], they are responsible for more than 75% of a country’s gross domestic product [4,5]. Cities consume large quantities of energy and require an uninterrupted supply, totaling 78% of global primary energy, leading to 70% of annual global carbon emissions [2,3,4,6]. Urban transport and buildings encompass most of this energy consumption and carbon emissions [2,7]. In fact, urban transport accounts for 4 billion tons of CO2-eq/year, making up more than 40% of the transport sector’s total emissions, while buildings consume more than one-third of the final energy consumption globally, and this value is even higher in developed countries [8]. It has become essential to optimize resource consumption in cities [9], as cities are often associated with energy inefficiency, misuse of land and non-renewable resources, and air, sound, and water pollution [10]. There is a growing mismatch between energy supply and demand in developing countries, as supply remains stable while demand grows 7% annually due to increased population growth, rapid urbanization, and expanding economies [4], leading to frequent blackouts [11,12,13]. The relationship between cities and climate is reciprocal [14], and it is of extreme importance to create, develop, and aim for a more sustainable built environment. Planning to improve city sustainability is crucial for city dwellers’ quality of life and our planet’s overall sustainability.
Because energy consumption in urban areas is very high and on the rise, it got under the spotlight of local and worldwide research and decision-makers [15,16], and the choices made by municipal authorities and urban planners can significantly impact a city energy efficiency and emissions [17], as well as the thermal comfort of city dwellers [18]. Those choices inevitably act on the built environment, which is linked to urban form, transport systems, and human behavior. A simple form to define the built environment, and the one used for the purpose of this review, is a multidimensional concept that “comprises urban design, land use, and the transport system, and encompasses patterns of human activity within the physical environment” [19]. Handy et al. [19] identified six dimensions of the urban built environment: density and intensity, mixed land use, street connectivity, street scale, aesthetic qualities, and regional structure. A desirable and pleasant urban built environment has to be able to improve energy efficiency, environmental quality, accessibility, comfort, feel-at-ease sensation, and overall quality of life of urban residents [19,20,21]. This focus on the built environment positions it as an instrumental piece for paving the development of cities and has been an important avenue of research in both spatial and transport planning fields [19].
As the form and function of the built environment impact energy consumption, urban design strategies are crucial to reach energy efficiency and climate targets [22,23,24]. City-level energy planning presents itself as a strenuous task, typically referred to as “wicked problems”, implying ill-defined, multi-faceted, and dynamic problems that require carefully curated strategies and policies, facing many obstacles and additional challenges [25]. One of the biggest challenges is the consolidated urban built environment, i.e., existing urban areas, where changes, regeneration, or renovation is demanding and also requires altering people’s behavior in order to reduce energy consumption [26].
City resiliency, i.e., its ability to withstand a wide array of shocks and stresses [27,28,29], is another central component of sustainable development and has been an active avenue of research in urban planning [27,30,31,32,33,34,35,36]. Technical and economically viable solutions are needed to reduce the cost of urban energy transition towards sustainable and resilient cities. Otherwise, the transition could be too expensive to undertake [22,35,36,37,38].
Given the number of publications on energy efficiency and consumption of the built environment, this literature review focuses only on transport and spatial planning dimensions. It aims to be a review of recent research, highlighting the most important results and discoveries of the past decade, and provides insights on what could be the focus of future research in the spatial and transport planning energy dimensions of the urban built environment. The conclusions of this review can help municipal decision-makers to plan their cities for a sustainable future, in addition to suggesting research directions to other academics working in the field. For more reviews regarding the different topics presented in this article, please see [39,40,41,42,43,44,45,46]. The term built environment can also refer to buildings, but these are not the focus of this review. The authors suggest the MDPI Energies Special Issue “Thermal Behaviour, Energy Efficiency in Buildings and Sustainable Construction” [47] and the review from Quan et al. (2021) [48] for a deep dive into buildings energy consumption and efficiency.
Figure 1 provides an overall view of the topics focused on this review. An extensive list of all the references cited herein can be found on the Supplemental Materials.
Section 2 reviews the relations between transport and the built environment. This is followed by a discussion on developments concerning urban form and energy efficiency in Section 3. Finally, in Section 4, the findings are put together and summarized, and a direction for sustainable urban development is proposed. Section 4 ends with suggestions for new research avenues.

2. Transport and the Built Environment

Transport has a crucial role in the development and daily life of our societies [49]. However, it remains an essential source of harmful air pollutants [50,51], surpassing one-fifth of global CO2 emissions in 2021 [52,53,54] (21–23%, depending on the source). The urban form and built environment directly influence the travel mode choice of dwellers, with consequences on transport energy consumption [26,55,56,57,58]. Numerous studies over the past decades looked at the relationship between the urban form and CO2 emissions and transport energy consumption [59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74]. Reducing fuel consumption and associated emissions is possible by focusing on three main areas: fuel type, fuel efficiency, and vehicle miles traveled [75,76,77]. While the first two areas are not directly related to the built environment, the latter is, as research shows that land use and urban design policies can help reduce motorized modal share and transport energy consumption in the urban environment [78,79,80,81]. The high modal share of private motorized transport is one of the main causes of high transport energy consumption in cities [82]. Urban regeneration policies must be part of the solution by creating new infrastructure and fostering a jumpstart of active mobility (walking, cycling), mobility as a service, and zero-emission vehicles [83]. City size and spatial clustering also have a significant impact, as high-density development can help reduce commuting distance and time, as well as fight back against urban sprawl and its long-term negative consequences [55].
Understanding which factors can improve travel patterns, reduce energy consumption, and promote an urban environment with low-carbon and sustainable development has been, and remains, an active research topic for urban planners [63].

2.1. Commuting and Urban Trips

The relationship between the built environment and commuting trips has received continuous interest, as shown by the research [59,84,85,86]. Recently, the work [87] demonstrated the potential for commuting trips to significantly increase CO2 emissions in two major cities in China and India. Economic growth and motorization in those cities are inducing fast urbanization and urban sprawl, leading to an expected increase in the annual average CO2 emissions per person from 0.22 t in 2012 up to 1.6 t in 2030, a 727% rise if “business as usual” conditions are maintained.
A study on vehicle miles traveled (VMT) in the Baltimore area (USA) confirmed that the built environment affects commuting trips, but also that its influence extends to non-commuting trips [88]. For commuting trips, employment density, street connectivity, and accessibility are statistically significant regressors for reduced VMT, as closer jobs and more job opportunities, smaller blocks, and denser intersections provide shorter paths and alternative travel modes. For non-commuting trips, mixed land use and street connectivity were found to be positively significant, as higher street connectivity provides closer opportunities, as does a higher mixed land use [88,89]. When comparing residents’ density at neighborhood locations with employment density in business areas, [85] the latter has more impact on vehicle miles traveled. This dependence on trip purpose (commuting or non-commuting) was also studied by Yang et al. [90], who examined the effects of the built environment on CO2 emissions for different trip purposes in Guangzhou, China. An important conclusion was that urban planning should consider both types of trips, as some built environment elements may be specific to a particular purpose (e.g., bus stop density, distance to city public centers). The authors also state that urban growth should avoid the expansion of the urban periphery and a polycentric development should be advocated for. Higher mixed land use is desirable, as it enables shorter trips, a reduction in the number of trips, and higher active mobility levels.
Other studies confirm that polycentric urban conglomeration policies, which aim for a higher road density, even if narrow, are more effective in reducing travel time than wide arterial roads that can encourage urban sprawl [64]. Likewise, population densification was also proven to be an effective strategy to reduce VMT [91]. According to a study made in California, a 10% increase in residential density may be able to reduce VMT by 1.9% [92]. Densification also leads to more social opportunities nearby, which is usually also sought-after by inhabitants.

2.2. Active Mobility

The built environment can impact active mobility in many ways [93,94,95]. Often praised by policymakers and a prominent research topic, active modes are nevertheless still underused while motorized private transport is overused [78,96,97,98]. In the study on how the built environment can affect physical activity, Handy et al. [19] highlight the importance of the former in increasing the number of pedestrians and cyclists on urban trips, with physical exercise as a by-product. Mixed land use, street connectivity, and an overall thoughtful design were proven to enhance the attractiveness and feasibility of both active transport modes [19].
Other built environment characteristics can influence active mobility ridership as well [93,94,95,99,100]. Street aspect ratio and direction [101,102,103,104,105], street vegetation, and shade availability [106,107,108] were found to play a role in pedestrian thermal comfort and overall city walkability. Christiansen et al. [99] confirmed positive associations of active modes of transport with four characteristics: mixed land use, residential density, intersection density, and number of parks. However, not all were linear, suggesting that optimum values may exist for each component and that going beyond them will not bring benefits. In particular, residential densities over 12,000 dwellings/km2 do not seem to improve walking for transport. Also, the physical aspect of the built environment influences citizen perception of neighborhood pleasantness, which in turn affects the propensity to use active modes, as pleasant environments are more likely to be threaded [100,109,110,111,112].
Fostering active mobility is one way to reduce transport energy consumption and CO2 emissions [59,78]. A study by Monteiro et al. [78] analyzed the cycling full potential of Coimbra (Portugal) based purely on trip distances and frequencies; results showed that if the full cycling potential were to be achieved, active mobility (walking plus cycling) would increase by 154%, directly leading to a reduction of 22% in transport energy consumption. A study for the same city showed, by evaluating the exposure to pollutants while commuting, that a reduction of approximately one-third in the inhalation of traffic pollutants could be achieved by using a route that is on average only 6% longer in comparison with the shortest route [113].
These studies highlight the importance that the built environment can have in encouraging active mobility. Municipal authorities should provide the necessary walking and cycling infrastructure, with safe and comfortable bike lanes and street furniture (bicycle parking, rest places, etc.), and adopt policies that reward active mobility, such as the coordination with public transport and discouragement of motorized transport.

2.3. Public Transport

Public transport is an intrinsic part of urban mobility whose impact on transport energy efficiency and greenhouse gas (GHG) emissions is widely recognized [15,114,115,116,117]. Increased public transport rideability is necessary to ensure a good public transport service by decreasing waiting time and increasing lines. Built environment characteristics, such as high population density in residential neighborhoods and high job density in business districts, can lead to high rates of traffic congestion and parking difficulties, inducing a widespread use of public transport in lieu of private motorized transport [118], resulting in lower transport energy consumption and emissions. Nevertheless, a study by Li and Zhao [89] that explored car ownership and car use near metro stations in Beijing concluded that proximity to metro stations was not that impactful in reducing car ownership and use. This finding is a reminder that stand-alone policies and strategies to improve transit ridership might not be as impactful as could be expected. Additionally, the effects of the built environment on the reduction in private motorized transport usage can also be limited if, e.g., free parking is provided at destinations [118].

2.4. Vehicle Electrification

At the time of writing, almost every major car brand offers electric vehicles (EVs) in their model range and has committed to an entire model range of just EVs in the foreseeable future [119,120]. International and national authorities are showing signs of commitment to ensuring zero-emission new car sales in the next decade [121]. EV market share is also steadily increasing and it is expected that GHG emissions, air pollution, and the depletion of natural resources for the production of fossil fuels will slowly decline [49,122].
The growth of EV driving around requires creating adequate charging infrastructure in the built environment [123]. EVs are also being considered for mobility as a service solution and the built environment may need to be optimized for parking and charging stations for this mobility solution, as Gonçalves et al. [124] highlighted. A study by Fernández-Rodríguez et al. [51], based on two case studies from Italy and Spain, analyzed the potential use of railway and metro power supply facilities to charge EVs, as that would simplify the deployment of charging infrastructure in cities and allow for harvesting a significant amount of braking energy from trains. Karan et al. [125] analyzed an integrated building and transportation energy use to design a comprehensive GHG mitigation strategy in Pennsylvania, USA. Initial results showed that, on average, each individual produced around 20 lbs (9.1 kg) of CO2 per day, of which 62% was from transport. Changing fossil fuel motorized transport for EVs powered by solar electricity, a 12.2% CO2 reduction per day could be achieved.
Electrification of public transport vehicles can also play an important role [126] and has proven to have economic benefits [127]. Replacing internal combustion engine (ICE) public transport fleets with electric trains and hybrid buses could decrease their share in GHG emissions by 32% [128]. Also, new methodologies to analyze the efficient energy consumption of electric public transport based on the route topology, traffic schedule, and vehicle specifications are being developed [129]. Electric buses can additionally provide other environmental and financial advantages, in terms of improved air quality, noise levels, and reduced cost of ownership and maintenance. However, their acquisition cost is a significant disadvantage, with a premium of over $100,000/vehicle compared to ICE buses [130].
The future of urban mobility might evolve into the massification of EVs, electrification of public transport, and micromobility, e.g., bicycles, scooters, in a mobility as a service or increased ownership basis. It is nowadays becoming clear that vehicle electrification is part of the solution, and many researchers and municipal authorities are actively working on promoting a zero-emission urban transport system.

3. Urban Form: Spatial Planning and Energy Efficiency

This section discusses the relationship between spatial planning and energy efficiency, highlighting the most relevant research and research avenues.
The challenges that the urban built environment faces in the transition to sustainable, low-carbon energy systems are massive [131], and urban design and planning play an undeniable role in addressing them, by means of implementing policies that privilege energy efficiency [132,133]. However, in the past, energy efficiency and sustainability have not been on the radar of urban planners very often. Considering land use as an example: Although it is considered a planning tool for energy efficiency, in many cities, the lack of coordination between urban planning and city-wide energy planning led to large patches of single land use, an inefficient solution [25,133,134,135]. Nowadays the relationship between urban and energy planning is largely present in current energy-optimized city planning [133,136,137,138,139]. For a detailed critical literature review on the importance of coordinating urban and energy planning, see [44]. At a larger scale, initiatives such as the European Commission initiative Covenant of Mayors, Local Governments for Sustainability, and C40 Cities Network (ICLEI) [6,140,141,142], can bring together municipal authorities to collaborate towards more efficient and sustainable cities.
It is important to note that advances in computer-based technologies provided spatial planners with new resources and tools that can yield quantitative and expedited analyses of energy consumption and sustainability measures [143,144,145,146]. A study by Ferrari et al. [147] evaluated the practical usage of these tools by urban planners.

3.1. Eco-Districts: Harvesting Renewable Energy within the Built Environment

The development of more ecologically based and liveable cities has been advocated as a priority when aiming for sustainability [148] Integrating renewable energies into spatial planning, i.e., the creation of eco-districts, was suggested in [149,150] as a possible path to achieve this goal. Eco-districts should aim not only for their own energy independence but also to exchange surpluses with neighboring districts [151,152]. However, studies by Lombardi and Trossero [153] and by Bracco et al. [154] showed that self-sufficiency may be hard to achieve on a large scale, as it requires harnessing multiple renewable energy sources locally and the means to deal with their intermittencies.
Solar power is a renewable energy source that can be harvested in the urban environment and is a prime candidate for eco-district development. Integrating solar systems into the built environment can have several advantages, e.g., exploiting unused urban surfaces, limiting losses associated with long-distance transmission of electricity, and creating a more resilient electric network, capable of supporting extreme weather conditions [155,156]. Incentives for the installation of solar photovoltaic energy and solar energy solutions in cities are a possible policy to foster a transition to eco-districts [157,158]. Indeed, a study in the city of Daejeon, South Korea, found that the citywide deployment of solar energy via rooftop photovoltaic panels could fulfil over half of the city’s energy needs [159]. A similar study in San Francisco, USA, found slightly lower but still significant savings, namely, 23–38% [160]. For an in-depth review on the deployment of renewable energy sources in urban areas, see [45].

3.2. Urban Sprawl

Urban sprawl is an extensive low-density, single-type land use that creates a lack of continuity and directedly impacts spatial, transport, and environmental planning [161,162]. Strong negative correlations exist between urban sprawl, energy consumption, and emissions [163,164]. Sprawled city development leads to large commuting distances, which in turn requires extensive roads that inevitably end up congested by excessive private car use. Other consequences are an increase in both air and noise pollution, a significant reduction in public transport ridership, and negative socio-economic consequences [163,165,166,167,168,169]. Studies [79,170] showed the clear effects of residential location on traveling distances, modal share, and transport energy consumption. Dwellers of sprawled suburbs have the worst accessibility and are restricted to motorized transport modes, as walking or cycling is not possible with homes being so distant from destinations. Consequently, transport energy consumption is high, as motorized private transport remains the best (most of the time the only) modal choice option for suburbs dwellers [78].
To avoid deepening the negative consequences of urban sprawl, cities must stop planning strategies that can result in sprawled neighborhoods and fight existing sprawl with policies that can infill central urban spaces [79,170]. The solution might lie in the past, within the utopian city plans developed by Howard or Le Corbusier [78,164,171,172]. A study by Monteiro et al. [143] compared a real city with sprawled districts with its redraft as a Garden City. Results showed that the Garden City layout improved accessibility to urban facilities and jobs by 41%, which can directly lead to a reduction in transport energy consumption and better public transport planning. This result provides a glimpse of what can be gained by planning cities and their expansions in a more thoughtful way.
An urban compact design is usually seen as a sustainable urban form [173]. Compact development leads to densification and mixed land use, which reduces distances and improves accessibility. These efficient land use policies reduce commuting time and private car use, directly impacting transport energy consumption [168,174,175,176]. A study by Zahabi et al. [128] found statistical significance between built environment variables and transport emissions in Montreal, Canada: A 10% increase in accessibility to public transport, density, and mixed land use results in a 3.5%, 5.8%, and 2.5% reduction in GHG, respectively. Likewise, a study on the Puget Sound region, Washington, USA, revealed that a 100% increase in mixed land use, residential, and intersection density in urban areas would reduce transport emissions by 31.2–34.4% [177]. Stone et al. (2007) [178] found similar results and highlighted the importance of compactness in reducing VMT. Wang and Zhou et al. (2017) [179] presented a literature review on the relationship between the built environment and travel behavior in urban China. The authors confirmed a strong connection between high density and mixed land use with shorter trips and larger active modal shares. In contrast, residents in the suburbs spend more time communing and have greater motorized transport dependency. Wu et al. [26] used survey data with over 22,000 traffic trip samples from nine streets in Ningbo, China, to analyze transport energy consumption with a regression analysis. With respect to built environment variables, they found that an increase of 1% in population density, mixed land use, and road intersection density lead, respectively, to decreases of 0.094%, 0.415%, and 0.079% in total transport energy consumption.
Although several studies show a positive impact of mixed land use and sprawl reduction on energy consumption, other aspects may arise. If, on the one hand, mixed land use can decrease transport energy consumption; on the other hand, it can increase overall building energy consumption, making it important to understand the relationship between the spatial arrangement of buildings in a high mixed land use zone and their electricity demands [180]. Similarly, densification and infill (see Section 3.3. for definitions) can compromise perceived neighborhood pleasantness [21]. It is thus important that urban planners and municipal authorities understand and analyze the positive and negative consequences of planning strategies and policies before fully committing to them.

3.3. Densification and Infill

Densification, i.e., the increase in population density, and infill, i.e., rededication and development of previously derelict or underused land to new land uses or construction, of urban conglomerations may come in many guises. It can lead to reductions in transport energy consumption and environmental impacts [79,181,182,183,184,185].
Transit-oriented development (TOD) is a medium to highly dense, mixed land use urban design concept in which public transport-based mobility defines the urban planning, with public transport catchment areas below 600 m [80,81,186,187,188]. A study by Nahlik and Chester [81] on the impact of TOD on VMT showed that residents of TOD areas tend to drive less compared to residents of non-TOD areas. The impact of a TOD solution in Las Vegas was analyzed by Nahlik and Chester [80]; the authors concluded that it could decrease GHG emissions by 470,000 t of CO2 equivalent per year and reduce PM10-equivalents and smog formation by 28–35%. Silva et al. [189,190] evaluated the energy implications of six urban development alternatives for the city of Porto, Portugal (infill, consolidated development, modern development, multi-family housing, TOD, and green infrastructure), having found that TOD comes on top, with a 15% reduction in transport travel, followed by consolidated development, with 9% reduction.
Concerning infill, Monteiro et al. [79] analyzed the infill potential in the city of Coimbra, Portugal, strictly following the Municipal Master Plan and national regulations for buildings. They found an increase of 36% in the potential per capita active modal share and a reduction of 76% in transport energy consumption in comparison to the real city, proving that the infill is a viable strategy to combat urban sprawl.
Densification also relates to building energy consumption. This subject is addressed in Section 3.7.
Different strategies provide different results, and local context should always be considered when aiming to densify a city.

3.4. The D-Variables of Compact Planning

The D-variables were proposed to guide planners when considering a densification or infill strategy [174,175]. Their impact on transport energy is as follows [174,175]:
D-ensity measures: higher population and job density can reduce the number of trips and trip length, as origins and destinations are closer to one another.
D-iversity measures: high mixed land use can reduce motorized transport and encourage active transport.
D-esign measures: network design can reduce motorized traffic, e.g., street networks with a large number of intersections decrease motorized traffic and network distances and encourage active transport modes.
D-estination accessibility: higher number of urban facilities and employment opportunities reduce trip distances and trip numbers and increase the viability and convenience of active transport modes.
D-istance to transit: adequate coverage of catchment areas for public transport reduces private transport and incentivizes active mobility.
To measure the impact of these variables, statistical models are commonly used and results are typically presented in percentage changes between the scenarios being studied [175]. Although these studies provide important prediction data, their practical application is still limited [175]. Stevens [175] highlights that planners and researchers
“should probably not automatically assume that compact development will be very effective at achieving that goal. If anything, planners should probably assume for now that compact development will have a small influence on driving, until and unless they are given a compelling reason to believe otherwise. At a minimum, planners and municipal decision makers should not rely on compact development as their only strategy for reducing vehicles miles travelled unless their goals for reduced driving are very modest and can clearly be achieved at a low cost.”
The above is a warning that infill and densification are not universal solutions to reduce transport energy consumption, due to both local constraints and densification itself [69,191]. A study on perceived neighborhood physical pleasantness showed that, in general, people prefer detached and single-family housing [21]. Indeed, the authors of [192] found that, in response to this market demand, development trends on a dynamic tourist coastal privileged detached urbanism, rather than compact buildings.
As different strategies provide different results, so do different cities behave differently in response to those strategies, further emphasizing the importance of local context when considering an urban layout. As [193] highlights, distinctions should be made according to urbanization levels and dynamics, history, culture, and social and economic inequalities.

3.5. Urban Public Spaces

Urban public spaces, i.e., outdoor or indoor spaces with free public access where people can gather or pass through (e.g., parks, squares, streets, public shopping malls, streets, walkways), are an essential part of a city’s built environment [194,195,196]. If urban public spaces offer some protection against motorized traffic, people tend to feel more secure, comfortable, and less annoyed [197]. Research suggests that policymakers and municipal authorities should focus on the creation of inclusive and safe urban public spaces [197]. Existing urban green infrastructure (such as parks and urban forests) should be protected and new ones should be promoted and built [198].
Additionally, retrofitting renewable energy sources in urban public spaces should become a common norm [199]. Passive strategies that use the intrinsic characteristics of the materials composing the built environment are being studied and implemented for higher energy efficiency and CO2 emissions reduction [200,201]. The use of green areas and vegetation, as well as cool and reflective materials, is well documented [202,203]. A study by Rosso et. al. [204] tested the application of photoluminescent materials on the built environment, for example, on sidewalk pavements, and demonstrated that it can be used as a passive strategy to reduce energy consumption by contributing to public space lighting with no energy consumption. Similarly, Akbari and Matthews [203] evaluated the installation of cool pavements to mitigate summer urban heat islands and improve outdoor air quality and comfort. Nevertheless, although the energy efficiency and thermal comfort capabilities are clear, using cool coatings for buildings and city infrastructure may cause increased glare to pedestrians and increase walking discomfort [205]. Pavement energy harvesting is considered to be a sustainable energy source, with the potential to yield efficiencies of around 40–65% [206]. Heat-harvesting pavements and road pavements capable of converting vehicles’ mechanical energy into electric energy [207,208] have also been proven as possible energy recovery solutions. However, energy-harvesting pavements require more examination to assess their power output, durability, and lifetime [209].

3.6. Urban Geometry and Buildings Energy Consumption

Buildings energy consumption can be evaluated based on four main factors: urban geometry, building design, system efficiency, and occupant behavior [210]. For this review, the focus is on the design and form of the cities, i.e., the urban geometry, the intersecting factor of urban planning, and building energy consumption. Urban geometry and morphology typically relate to the availability of daylight, outdoor temperature, wind speed, and air and noise pollution [211], all of which can create microclimates within a certain urban environment, such as urban heat islands (UHI) and street canyons (SC). It also influences building energy consumption patterns, heat losses, and solar exposure [212,213,214,215]. Thanks to computing advances, simulations of the built environment and urban form become possible, providing an important theoretical base for the relationship between urban geometry and building energy consumption [210,216].
A study by Silva et al. [217] used a spatially explicit methodological framework based on neural networks to assess the effect of urban form on energy demand. Results show that urban form can explain around 78% of the variation in energy use, with features such as number of floors and mix of uses as the most relevant. Studies using digital elevation models (DEMs) are also an important part of the research regarding the relationship between the urban environment and building energy consumption [210]. Shaping and grouping buildings are long known [218]; the novelty of recent research is that computer capabilities now enable quantitative analyses and comparisons between different urban forms. A study by Taleghani [219] analyzed the impact of thermal comfort on energy use in the Netherlands, based on different urban block types. The authors concluded that between single, linear, and courtyard urban blocks layout, the three-story courtyard presented the best results, with 22% less use of energy and 9% less thermal discomfort in comparison to the single urban blocks layout.
The impact of densification from high-rise construction can also be estimated. Densification has been associated with lower per capita energy use, unlike detached housing, whose heat-energy efficiency is low [220,221,222]. However, tall buildings that are too close mutually shade each other, reducing their access to natural light and negatively impacting energy efficiency [223,224], creating a push–pull effect. Building solutions, such as improved thermal insulation of the building envelope, can help mitigate these compactness issues [225]. Actual figures on building energy demands can be estimated from 3D geometric models and data on building construction, as demonstrated by Eicker et al. [226]. These authors found that separating buildings can increase energy demand for heating by 10–20% and reduce renewable energy integration by up to 50%, while mutual shading can increase heating energy demand by 10%. Because of the above findings, some authors proposed moderate compactness as a compromise solution between compact and detached development [225,226,227,228].
Harvesting wind within the urban environment has also been an active research topic recently [229,230]. Gil-García et al. [229] analyzed the potential for harvesting urban wind in the region of Cádiz, Spain, and found that over 68,000 kWh/year could be generated, for an investment return rate of just six years.
Passive solar design should also be incorporated into house plans at the design stage, as suggested in [231]. Cheng et al. [232] developed 18 models to assess the solar potential of urban geometric types, based on the built form, site coverage, and land plot ratio. Other estimations of solar potential based on the urban built environment include [233,234]. Urban geometry can also impact the energy collected from facades and roof tops, with the potential to improve the thermal comfort of buildings [219].
The attention that UHI and SC have received from researchers in the last decades justifies a more in-depth review of these topics, which is carried out in the next two subsections.

3.6.1. Urban Heat Islands

The development of urban areas usually leads to a reduction in green areas, an increase in waterproof surfaces, the use of high solar absorptance materials, and a reduction in natural ventilation. These are all factors that can lead to an urban heat island effect, as they change surface albedo, emissivity, and evapotranspiration [235,236]. The UHI effect can be defined as a thermal phenomenon in which temperatures in urban cores are higher than in their rural surroundings [235,237,238]. It has an impact on energy efficiency [239,240,241] because increased temperatures raise the energy needs for cooling [242]. An analysis of the UHI effect and microclimate variability in Hong Kong found clear connections between urban morphology and local meteorological factors and concluded that the degree of the UHI phenomenon is more severe in areas of high public activity and heavy transportation [243].
Strategies to reduce the UHI effect include the use of materials with high albedo ratings for surfaces such as pavements [238,244,245,246], the creation or regeneration of urban waterbodies [247,248,249], and the use of vegetation cover [5,250]. Urban green spaces can contribute to reducing UHI effects [202,251,252,253] and are one of the most effective solutions in comparison to other mitigation strategies [254]. A study by Das et al. [255] quantified the cooling effect of urban parks in a tropical mega metropolitan area in India. Findings revealed that urban parks help regulate outdoor temperature, an effect that is proportional to size and greenness. Correct conservation of urban parks is thus essential for climate mitigation in tropical cities [253,255]. Further evidence that urban greenery is important in regulating the UHI effect can be found in [42,256,257,258,259]. Vegetation solutions can come in many guises, such as green urban parks [260,261], urban forests [262], buildings roofs and facades [263,264,265], and street sidewalk vegetation [266,267,268]. Quantitative results include that of Klemm et al. [268], who found that a 10% tree cover in a street can lower average radiant temperature by about 1 °K, and [42], [239], in which the combination of different vegetation solutions is examined, having found such combinations can achieve reductions in temperature between 1.5 and 2.0 °C [45] or 2.0 °C [239], along with improving the outdoor environment and thermal comfort [223,266,269,270].
Regulating outdoor temperature can also reduce building energy consumption. In some studies [271,272], an up to 10% reduction was found. Urban parks can directly reduce building energy consumption, but only within a certain radius of around 300 m, according to Kim et al. (2019) [272]. Another study on the cooling effect of urban parks was carried out by Xu et al. [273], who evaluated the situation in Beijing. The best results were achieved by the combination of manmade shading devices, trees, grass, and waterbodies, which together can reduce heating up to 102,069 J.m−3 during the period between 10:00 h and 16:00 h. A study by Kaloustian and Dias [274] in Beirut, Lebanon, found that areas with larger garden fractions can have a difference of up to 6 °C cooler temperatures in comparison to surrounding denser areas. This can lead to lower cooling energy demands of 270 W/m2 (80 W/m2 vs. 350 W/m2). Similar results were obtained by Brown et al. (2015) [275], who tested the Park Cool Islands (PCI) design of urban parks in five cities. Results show that reductions between 52 and 60 W/m2 could be achieved in the cities of Alice Springs, Australia; Kyoto, Japan; and Toronto, Canada, demonstrating that decreasing air temperature through a PCI was a moderately effective strategy [275].
Urban greenery solutions can also make active mobility more attractive by providing more pleasant travel conditions [257,261,276,277,278].
Another strategy to mitigate UHI effects is to correctly execute high-rise [279]. Compact high-rise buildings can prevent cool winds from entering city centers and remove the accumulated heat [280]. A study by Wang et al. [276] concluded that high-rise building construction in adjacent areas of green spaces should be sparser, instead of more compact alternatives, and take advantage of existing water bodies, as they can also directly impact building energy consumption. Adjacent construction areas of urban parks should be planned in accordance with one another, as the impact that each has on the other should always be taken into consideration [276].
A study by Okeil [281] presents a holistic approach to buildings’ energy efficiency based on their form. The author provides a systematic comparison and an evaluation between the urban built environment and energy efficiency by maximizing solar exposure in winter and reducing heat gains in summer to mitigate UHI effects. The result is an optimized urban form model based on square blocks, with buildings along the edges whose height varies continuously (see [281] for figures and details).

3.6.2. Street Canyons

Street canyon refers to a street flanked by tall buildings on both sides, giving it a canyon-like appearance [282,283]. SCs can cause changes in wind, air quality, and temperature [284,285,286], creating a microclimate within the SC and its surroundings. These effects depend on street orientation, aspect ratio, materials albedo, and obstruction angles [212,216,266,287,288] and typically aggravate climate comfort, both indoor and outdoor. SCs are a very complex phenomenon but essentially their main effect is to increase the heat island effect [266,289,290,291,292]. Albeit canyons can increase shading, the reflectivity of buildings traps heat outdoors due to parallel facades, increasing outdoor temperature [14,212]. E-W-oriented canyons are particularly stressful in this respect because they receive sunlight the whole day [104]. Concerning indoor comfort, canyons can increase building climatization energy spending by up to +30% for offices and +19% for housing [212], depending on canyon geometry.
Pollution is another concern, as buildings shield the outdoor space from all winds (except those flowing parallel to the street), causing vortices between buildings that stop the pollutants from naturally dispersing [284,293,294,295]. A study in Athens, Greece, showed that the potential for natural ventilation for both single-side and cross-ventilation is seriously reduced within canyons by 82% and 68%, respectively [295]. When wind flows parallel to the street, pollution escapes but the wind chill effect is exacerbated, causing outdoor discomfort and additional needs for heating in the buildings in winter [212]. The placement of deciduous trees and design features, such as high aspect ratios, larger street width, galleries, and overhanging facades, can mitigate the SC effect and improve outdoor thermal comfort [14,266,268,287]. Narrow streets can, however, limit overheating in the summer, and this knowledge should be considered in due context when planning new neighborhoods.
Urban development policies need to take UHI and SC effects into account and make proper use of effective ways to reduce excessive urban heat. Achieving this goal requires a comprehensive understanding of these effects in their local and regional context. Ideally, building density, urban surface fraction, building materials, and canyon structure should all be considered in urban design together with the characteristics of the city’s climate [290].

3.7. Additional Challenges in Developing Countries

In developing countries, lack of infrastructure creates added difficulties, and some authors suggested that energy sustainability strategies must go hand-in-hand with sanitation, solid waste management, and food security strategies to eradicate poverty [296,297].
Rapid urbanization and climate change are worsening the vulnerability of undeveloped urban areas of the global south [298]. As societies evolve from the primary sector to the secondary and tertiary ones, more full-time, higher-income jobs are created. Given that economic growth is correlated with transport energy consumption and CO2 emissions [299], urbanization and development are expected to increase emissions in developing countries [300]. Despite the wide promotion of built environment sustainability, these countries lack the means and opportunities to make an adequate energy transition, and thus, this transition remains far from implemented in most developing countries [301,302]. Indeed, and in practice, research in India has shown that the increase in private transport between 1981 and 2005 accentuated environmental degradation [303].
Two studies on African cities show that, even though globalization brought ideas and policies derived from developed countries, those cities still face additional challenges [301,304], making the transition to sustainable energy not as straightforward as research from the global north might suggest. Cities in Africa are very unique and diverse in culture and other contextual issues, requiring different perspectives on how to make that transition [305]. Challenges relate, among others, to insufficient and inconsistent data [306,307], as well as weak governance systems and high percentage of informal economic activities, which hinder the implementation of the necessary strategies [307,308], mostly due to the mismatch between the availability of resources and their fair distribution. The authors of [301] summarize the concerns that African countries are facing into two main groups: (a) general barriers in developing countries—basic needs, not fully implemented sustainability, and inequitable resources distribution; (b) barriers specific to African countries—developing economics, urban poverty, population and poor utilities, and the dichotomy between the different countries.
In general, the studies [301,304,309] suggest that the widespread use of renewable energy resources and a focus on developing a sustainable built environment would highly benefit developing countries, acting as a step to minimize poverty rates and to overcome current and future environmental problems.

4. Conclusions

Jane Jacobs in “The Death and Life of Great American Cities” [310] stressed the importance of the built environment and presented criteria that planners should have in mind: a high concentration of population, buildings of mixed use, shorter city blocks, and an attention to the wide-range age gap. These strategies, Jacobs argues, would help retain diversity, create better living conditions, and improve quality of life [310].
As the urban population grows, so does their energy consumption, making efficiency critical to mitigate emissions and resource use. Thus, spatial and transport planning must include energy efficiency and their strategies, as these are vital to urban sustainability. In this sense, compactness has been shown to have many positive aspects that serendipitously go much in line with Jacobs’ ideas. The urban environment is expected to host a growing number of dwellers in the coming decades, and compact urbanism is one possible solution to keep energy consumption under control while providing all the benefits of proximity. Lower VMT, higher active modal share, and better public transport service all contribute to lower energy consumption and emissions, in contrast with urban sprawl, which increases motorized transport dependency and inefficiencies due to traffic congestion near, and at, arrival at the destination. However, to capitalize on proximity benefits policies must also include better accessibility (e.g., higher mixed land use), adequate active transport provisions (e.g., infrastructure investments, rights-of-way privileges), improvement of public transport (more/faster lines, stops density, electrification), and discouragement of private car use.
Nevertheless, there are many factors that come into play to make a liveable and vibrant urban environment. For example, the perceived physical pleasantness of the urban environment, which can attract or repulse people from cities, seems to decrease with excessively concentrated environments and tall buildings [21,311]. Excessive concentration also creates heat island and canyon effects, inefficiencies from shading, and makes it easier for pandemics, such as COVID-19, to spread [312]. Polycentric development and moderate concentration development can be good compromise solutions in this respect. In any case, energy efficiency integration within municipal plans and strategies is key for the future development of cities [313]. Land use policies can be more effective if supportive transportation policies are developed [118].
The above development guidelines can lead to new proposals for urban layouts or forms. Nowadays these layouts are put to test, owing to advances in computational power and tools. Research on benchmarking of city layouts has already started [21,78,79,143,311,314] and can provide quantitative predictive data for public discussion, prior to decision-making.
The diagram of Figure 2 clarifies how the concepts and topics of Figure 1 interconnect and summarizes the relationships between the reviewed materials. It is a proposal for path towards sustainable urban planning.
Briefly, the diagram shows that urban form planning should aim at some densification while retaining provisions for public and active transport, which in turn should form the core of a properly integrated urban transport system. Interconnecting urban form and transport will lead to new city concepts, which can be benchmarked before being put into public discussion. Ultimately, this discussion will lead to political decisions when opportunities arise to expand city limits or intervene in the existing urban space.

Directions for Future Research

There are many challenges ahead to achieve truly sustainable cities, and opportunities are plenty for future research and practical applications in the spatial and transport planning fields towards efficient and sustainable cities. Some major directions include the following:
  • Find and benchmark urban forms that compromise between efficiency and pleasantness. Densification provides efficiency but can feel unappealing to inhabitants. Designing and experimenting with new urban forms can lead to new solutions, in which people enjoy living while maintaining efficient and sustainable energy consumption. Classic urban form concepts can also be looked at as development solutions. The Garden City and neighborhood unit development, revamped as the 15-Min City [315], are just two concepts that are now being reconsidered.
  • City expansions. As cities grow, new neighborhoods frequently need to be added. Research should be carried out on how to improve urban expansions based on quantitative indicators and scenario simulations. Expansions can also be a testbed for new urban forms that later provide valuable field data.
  • City infill and sprawl-combating measures. Decision-makers deal with problems of real and sprawled cities. Reducing its impact and filling in cities requires developing infill planning methods and policies to bring people closer to the center.
  • Smart cities and energy efficiency. Big data can provide information on the built environment [316], and evidence mounts that the Internet of Things (IoT) can be used in smart cities to reduce energy consumption. Research and development are necessary to fulfil this potential.
  • There is a growing research avenue on green energy harvesting in cities. The transition to the practical application should be more supported and stimulated.
  • Research and practical solutions for developing countries. Global North solutions may not fit developing countries. Alternative, tailormade solutions need to be researched.
  • Integration of spatial planning with building planning to reduce the impact of heat islands and streets canyons. It is especially important that municipal master plans predict the UHI and SC effects and take adequate mitigating actions.
  • Energy planning integration with both spatial and transport planning. Nowadays urban planning implies cooperation between spatial and transport planning, although in practice, they are still commonly treated separately. A truly integrated urban planning based on spatial, transport, and energy dimensions can provide clear strategies and policies towards more sustainable cities.
“City growth has caused climate change, but that growth is also what’s going to get us out of it” [317]. The challenges ahead for sustainable cities are numerous and worrying, but research over the past decade has shown that spatial, transport, and energy planning fields are aware of and facing the problems. It will be up to the politicians to implement the solutions. Many already exist.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/en17020409/s1, Table S1: List of references with authors, publication date, location of research and topic of research.

Author Contributions

Conceptualization, J.M.; methodology, J.M. and N.S.; validation, J.M., E.N.-J. and N.S.; formal analysis, N.S. and E.N.-J.; investigation, J.M.; resources, J.C.-R.; data curation, J.M.; writing—original draft preparation, J.M.; writing—review and editing, N.S., E.N.-J. and J.C.-R.; visualization, J.M. and E.N.-J.; supervision, J.C.-R.; project administration, J.C.-R.; funding acquisition, E.N.-J. and J.C.-R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Portuguese Foundation for Science and Technology (FCT), grant numbers UIDB/00308/2020 and PD/BD/150589/2020. https://doi.org/10.54499/UIDB/00308/2020.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. World Urbanization Prospects The 2018 Revision; United Nations: New York, NY, USA, 2018.
  2. International Energy Agency. Empowering Cities for a Net Zero Future; International Energy Agency: Paris, France, 2021; p. 111. [Google Scholar]
  3. Starace, F.; Tricoire, J.-P. Net Zero Carbon Cities: An Integrated Approach. Available online: https://www.weforum.org/publications/net-zero-carbon-cities-an-integrated-approach/ (accessed on 2 November 2023).
  4. UN-Habitat. Urban Energy. Available online: https://unhabitat.org/topic/urban-energy (accessed on 15 April 2023).
  5. Gago, E.J.; Roldan, J.; Pacheco-Torres, R.; Ordóñez, J. The City and Urban Heat Islands: A Review of Strategies to Mitigate Adverse Effects. Renew. Sustain. Energy Rev. 2013, 25, 749–758. [Google Scholar] [CrossRef]
  6. Asarpota, K.; Nadin, V. Energy Strategies, the Urban Dimension, and Spatial Planning. Energies 2020, 13, 3642. [Google Scholar] [CrossRef]
  7. Hickman, R.; Banister, D. Transport, Climate Change and the City; Routledge: London, UK, 2014; ISBN 978-0-415-66002-0. [Google Scholar]
  8. Energy Information Administration U.S. Energy Information Administration—EIA—Independent Statistics and Analysis. Available online: https://www.eia.gov/totalenergy/data/browser/index.php?tbl=T02.01A#/?f=A&start=1949&end=2022&charted=6-9-12-18 (accessed on 2 November 2023).
  9. Toboso-Chavero, S.; Nadal, A.; Petit-Boix, A.; Pons, O.; Villalba, G.; Gabarrell, X.; Josa, A.; Rieradevall, J. Towards Productive Cities: Environmental Assessment of the Food-Energy-Water Nexus of the Urban Roof Mosaic. J. Ind. Ecol. 2019, 23, 767–780. [Google Scholar] [CrossRef] [PubMed]
  10. Moraci, F.; Errigo, M.F.; Fazia, C.; Burgio, G.; Foresta, S. Making Less Vulnerable Cities: Resilience as a New Paradigm of Smart Planning. Sustainability 2018, 10, 755. [Google Scholar] [CrossRef]
  11. Gertler, P.J.; Lee, K.; Mobarak, A.M. Electricity Reliability and Economic Development in Cities: A Microeconomic Perspective. 2017. Available online: https://escholarship.org/uc/item/96s8s43z (accessed on 11 January 2024).
  12. Jha, A.; Preonas, L.; Burlig, F. Blackouts: The Role of India’s Wholesale Electricity Market 2021. Available online: https://www.nber.org/papers/w29610 (accessed on 11 January 2024).
  13. Nkosi, N.P.; Dikgang, J. Pricing Electricity Blackouts among South African Households. J. Commod. Mark. 2018, 11, 37–47. [Google Scholar] [CrossRef]
  14. van Esch, M.M.E.; Looman, R.H.J.; de Bruin-Hordijk, G.J. The Effects of Urban and Building Design Parameters on Solar Access to the Urban Canyon and the Potential for Direct Passive Solar Heating Strategies. Energy Build. 2012, 47, 189–200. [Google Scholar] [CrossRef]
  15. de Casas Castro Marins, K.R. A Method for Energy Efficiency Assessment during Urban Energy Planning. Smart Sustain. Built Environ. 2014, 3, 132–152. [Google Scholar] [CrossRef]
  16. Yıldırım, H.H.Y.; Gültekin, A.B.; Tanrıvermiş, H. Evaluation of Cities in the Context of Energy Efficient Urban Planning Approach. IOP Conf. Ser. Mater. Sci. Eng. 2017, 245, 072051. [Google Scholar] [CrossRef]
  17. Hukkalainen, M.; Virtanen, M.; Paiho, S.; Airaksinen, M. Energy Planning of Low Carbon Urban Areas—Examples from Finland. Sustain. Cities Soc. 2017, 35, 715–728. [Google Scholar] [CrossRef]
  18. Baruti, M.M.; Johansson, E.; Åstrand, J. Review of Studies on Outdoor Thermal Comfort in Warm Humid Climates: Challenges of Informal Urban Fabric. Int. J. Biometeorol. 2019, 63, 1449–1462. [Google Scholar] [CrossRef]
  19. Handy, S.L.; Boarnet, M.G.; Ewing, R.; Killingsworth, R.E. How the Built Environment Affects Physical Activity: Views from Urban Planning. Am. J. Prev. Med. 2002, 23, 64–73. [Google Scholar] [CrossRef] [PubMed]
  20. Ma, Y.; Yang, Y.; Jiao, H. Exploring the Impact of Urban Built Environment on Public Emotions Based on Social Media Data: A Case Study of Wuhan. Land 2021, 10, 986. [Google Scholar] [CrossRef]
  21. Sousa, N.; Monteiro, J.; Natividade-Jesus, E.; Coutinho-Rodrigues, J. The Impact of Geometric and Land Use Elements on the Perceived Pleasantness of Urban Layouts. Environ. Plan. B Urban Anal. City Sci. 2023, 50, 740–756. [Google Scholar] [CrossRef]
  22. Jank, R. Annex 51: Case Studies and Guidelines for Energy Efficient Communities. Energy Build. 2017, 154, 529–537. [Google Scholar] [CrossRef]
  23. Strasser, H. Implementation of Energy Strategies in Communities—From Pilot Project in Salzburg, Austria, to Urban Strategy; International Energy Agency: Paris, France, 2015; Volume 121, pp. 176–184. [Google Scholar]
  24. Caputo, P.; Pasetti, G. Overcoming the Inertia of Building Energy Retrofit at Municipal Level: The Italian Challenge. Sustain. Cities Soc. 2015, 15, 120–134. [Google Scholar] [CrossRef]
  25. Cajot, S.; Peter, M.; Bahu, J.-M.; Guignet, F.; Koch, A.; Maréchal, F. Obstacles in Energy Planning at the Urban Scale. Sustain. Cities Soc. 2017, 30, 223–236. [Google Scholar] [CrossRef]
  26. Wu, W.; Xue, B.; Song, Y.; Gong, X.; Ma, T. Investigating the Impacts of Urban Built Environment on Travel Energy Consumption: A Case Study of Ningbo, China. Land 2023, 12, 209. [Google Scholar] [CrossRef]
  27. White, I.; O’Hare, P. From Rhetoric to Reality: Which Resilience, Why Resilience, and Whose Resilience in Spatial Planning? Environ. Plan. C Gov. Policy 2014, 32, 934–950. [Google Scholar] [CrossRef]
  28. Natividade-Jesus, E. Editorial: COP27 and the Sustainable Urban Resilience Agenda. Proc. Inst. Civ. Eng.-Munic. Eng. 2022, 175, 175–176. [Google Scholar] [CrossRef]
  29. Leichenko, R. Climate Change and Urban Resilience. Curr. Opin. Environ. Sustain. 2011, 3, 164–168. [Google Scholar] [CrossRef]
  30. Davidson, K.; Nguyen, T.M.P.; Beilin, R.; Briggs, J. The Emerging Addition of Resilience as a Component of Sustainability in Urban Policy. Cities 2019, 92, 1–9. [Google Scholar] [CrossRef]
  31. Coaffee, J.; Therrien, M.-C.; Chelleri, L.; Henstra, D.; Aldrich, D.P.; Mitchell, C.L.; Tsenkova, S.; Rigaud, É.; Participants, T. Urban Resilience Implementation: A Policy Challenge and Research Agenda for the 21st Century. J. Contingencies Crisis Manag. 2018, 26, 403–410. [Google Scholar] [CrossRef]
  32. Collier, M.J.; Nedović-Budić, Z.; Aerts, J.; Connop, S.; Foley, D.; Foley, K.; Newport, D.; McQuaid, S.; Slaev, A.; Verburg, P. Transitioning to Resilience and Sustainability in Urban Communities. Cities 2013, 32, S21–S28. [Google Scholar] [CrossRef]
  33. Pizzo, B. Problematizing Resilience: Implications for Planning Theory and Practice. Cities 2015, 43, 133–140. [Google Scholar] [CrossRef]
  34. Ahern, J. Urban Landscape Sustainability and Resilience: The Promise and Challenges of Integrating Ecology with Urban Planning and Design. Landsc. Ecol. 2013, 28, 1203–1212. [Google Scholar] [CrossRef]
  35. COP27: Low Carbon Transport for Urban Sustainability; UN-Habitat: Nairobi, Kenya, 2022.
  36. COP27 Presidency Sustainable Urban Resilience for the Next Generation (SURge); UN-Habitat: Nairobi, Kenya, 2022.
  37. Juvara, M. COP 27 Shows Cities Moving Faster than Nations in Addressing. Available online: https://www.transportxtra.com/publications/local-transport-today/news/72419/cop-27-shows-cities-moving-faster-than-nations-in-addressing-climate-emergency/ (accessed on 2 November 2023).
  38. UN-Habitat. United Nations Cities and Climate Change. Available online: https://unhabitat.org/cities-and-climate-change (accessed on 2 November 2023).
  39. Keirstead, J.; Jennings, M.; Sivakumar, A. A Review of Urban Energy System Models: Approaches, Challenges and Opportunities. Renew. Sustain. Energy Rev. 2012, 16, 3847–3866. [Google Scholar] [CrossRef]
  40. Anderson, J.E.; Wulfhorst, G.; Lang, W. Energy Analysis of the Built Environment—A Review and Outlook. Renew. Sustain. Energy Rev. 2015, 44, 149–158. [Google Scholar] [CrossRef]
  41. Al-Obaidi, K.M.; Hossain, M.; Alduais, N.A.M.; Al-Duais, H.S.; Omrany, H.; Ghaffarianhoseini, A. A Review of Using IoT for Energy Efficient Buildings and Cities: A Built Environment Perspective. Energies 2022, 15, 5991. [Google Scholar] [CrossRef]
  42. Lai, D.; Liu, W.; Gan, T.; Liu, K.; Chen, Q. A Review of Mitigating Strategies to Improve the Thermal Environment and Thermal Comfort in Urban Outdoor Spaces. Sci. Total Environ. 2019, 661, 337–353. [Google Scholar] [CrossRef]
  43. Rickwood, P.; Glazebrook, G.; Searle, G. Urban Structure and Energy—A Review. Urban Policy Res. 2008, 26, 57–81. [Google Scholar] [CrossRef]
  44. De Pascali, P.; Bagaini, A. Energy Transition and Urban Planning for Local Development. A Critical Review of the Evolution of Integrated Spatial and Energy Planning. Energies 2019, 12, 35. [Google Scholar] [CrossRef]
  45. Perea-Moreno, M.-A.; Hernandez-Escobedo, Q.; Perea-Moreno, A.-J. Renewable Energy in Urban Areas: Worldwide Research Trends. Energies 2018, 11, 577. [Google Scholar] [CrossRef]
  46. Silva, M.; Oliveira, V.; Leal, V. Urban Form and Energy Demand: A Review of Energy-Relevant Urban Attributes. J. Plan. Lit. 2017, 32, 346–365. [Google Scholar] [CrossRef]
  47. Santos, P. MDPI Energies Special Issue “Thermal Behaviour, Energy Efficiency in Buildings and Sustainable Construction”. Available online: https://www.mdpi.com/journal/energies/special_issues/Buildings_and_Sustainable_Construction (accessed on 2 November 2023).
  48. Quan, S.J.; Li, C. Urban Form and Building Energy Use: A Systematic Review of Measures, Mechanisms, and Methodologies. Renew. Sustain. Energy Rev. 2021, 139, 110662. [Google Scholar] [CrossRef]
  49. Alahmad, M.; Hasna, H.; Sordiashie, E. IAddressable and Energy Management System for the Built Environment. In Proceedings of the 2011 IEEE Vehicle Power and Propulsion Conference, Chicago, IL, USA, 6–9 September 2011; pp. 1–6. [Google Scholar]
  50. Dias, D.; Pina, N.; Tchepel, O. Characterization of Traffic-Related Particulate Matter at Urban Scale. Int. J. Transp. Dev. Integr. 2019, 3, 144–151. [Google Scholar] [CrossRef]
  51. Fernández-Rodríguez, A.; Fernández-Cardador, A.; Cucala, A.P.; Falvo, M.C. Energy Efficiency and Integration of Urban Electrical Transport Systems: EVs and Metro-Trains of Two Real European Lines. Energies 2019, 12, 366. [Google Scholar] [CrossRef]
  52. IEA Transport—Energy System. Available online: https://www.iea.org/energy-system/transport (accessed on 24 November 2023).
  53. IEA Global Energy Review: CO2 Emissions in 2021—Analysis. Available online: https://www.iea.org/reports/global-energy-review-CO2-emissions-in-2021-2 (accessed on 24 November 2023).
  54. UN. Fact Check—Climate Change. In Proceedings of the Second United Nations Global Sustainable Transport Conference, Beijing, China, 14–16 October 2021. [Google Scholar]
  55. Engelfriet, L.; Koomen, E. The Impact of Urban Form on Commuting in Large Chinese Cities. Transportation 2018, 45, 1269–1295. [Google Scholar] [CrossRef]
  56. Dydkowski, G. The Impact of Cities’ Spatial Planning on the Development of a Sustainable Urban Transport. In Proceedings of the Smart and Green Solutions for Transport Systems; Sierpiński, G., Ed.; Springer International Publishing: Cham, Switzerland, 2020; pp. 13–25. [Google Scholar]
  57. Zhu, P.; Wang, K.; Ho, S.-N.; Tan, X. How Is Commute Mode Choice Related to Built Environment in a High-Density Urban Context? Cities 2023, 134, 104180. [Google Scholar] [CrossRef]
  58. Eldeeb, G.; Mohamed, M.; Páez, A. Built for Active Travel? Investigating the Contextual Effects of the Built Environment on Transportation Mode Choice. J. Transp. Geogr. 2021, 96, 103158. [Google Scholar] [CrossRef]
  59. Cao, X.; Yang, W. Examining the Effects of the Built Environment and Residential Self-Selection on Commuting Trips and the Related CO2 Emissions: An Empirical Study in Guangzhou, China. Transp. Res. Part D Transp. Environ. 2017, 52, 480–494. [Google Scholar] [CrossRef]
  60. Newman, P. The Environmental Impact of Cities. Environ. Urban. 2006, 18, 275–295. [Google Scholar] [CrossRef]
  61. Ewing, R. Is Los Angeles-Style Sprawl Desirable? J. Am. Plan. Assoc. 1997, 63, 107–126. [Google Scholar] [CrossRef]
  62. Kenworthy, J.R.; Laube, F.B. Automobile Dependence in Cities: An International Comparison of Urban Transport and Land Use Patterns with Implications for Sustainability. Environ. Impact Assess. Rev. 1996, 16, 279–308. [Google Scholar] [CrossRef]
  63. Newman, P.W.G.; Kenworthy, J.R. Gasoline Consumption and Cities: A Comparison of U.S. Cities with a Global Survey. J. Am. Plan. Assoc. 1989, 55, 24–37. [Google Scholar] [CrossRef]
  64. Shim, G.-E.; Rhee, S.-M.; Ahn, K.-H.; Chung, S.-B. The Relationship between the Characteristics of Transportation Energy Consumption and Urban Form. Ann. Reg. Sci. 2006, 40, 351–367. [Google Scholar] [CrossRef]
  65. Lu, I.J.; Lin, S.J.; Lewis, C. Decomposition and Decoupling Effects of Carbon Dioxide Emission from Highway Transportation in Taiwan, Germany, Japan and South Korea. Energy Policy 2007, 35, 3226–3235. [Google Scholar] [CrossRef]
  66. Alford, G.; Whiteman, J. Macro-Urban Form and Transport Energy Outcomes: Investigations for Melbourne. Road Transp. Res. 2009, 18, 53–67. [Google Scholar]
  67. Hankey, S.; Marshall, J.D. Impacts of Urban Form on Future US Passenger-Vehicle Greenhouse Gas Emissions. Energy Policy 2010, 38, 4880–4887. [Google Scholar] [CrossRef]
  68. Aguiléra, A.; Voisin, M. Urban Form, Commuting Patterns and CO2 Emissions: What Differences between the Municipality’s Residents and Its Jobs? Transp. Res. Part A Policy Pract. 2014, 69, 243–251. [Google Scholar] [CrossRef]
  69. Yang, W.; Li, T.; Cao, X. Examining the Impacts of Socio-Economic Factors, Urban Form and Transportation Development on CO2 Emissions from Transportation in China: A Panel Data Analysis of China’s Provinces. Habitat Int. 2015, 49, 212–220. [Google Scholar] [CrossRef]
  70. Ding, G.; Guo, J.; Pueppke, S.G.; Yi, J.; Ou, M.; Ou, W.; Tao, Y. The Influence of Urban Form Compactness on CO2 Emissions and Its Threshold Effect: Evidence from Cities in China. J. Environ. Manag. 2022, 322, 116032. [Google Scholar] [CrossRef] [PubMed]
  71. Shi, F.; Liao, X.; Shen, L.; Meng, C.; Lai, Y. Exploring the Spatiotemporal Impacts of Urban Form on CO2 Emissions: Evidence and Implications from 256 Chinese Cities. Environ. Impact Assess. Rev. 2022, 96, 106850. [Google Scholar] [CrossRef]
  72. Liu, Y.; Huang, L.; Onstein, E. How Do Age Structure and Urban Form Influence Household CO2 Emissions in Road Transport? Evidence from Municipalities in Norway in 2009, 2011 and 2013. J. Clean. Prod. 2020, 265, 121771. [Google Scholar] [CrossRef]
  73. Liu, X.; Sweeney, J. Modelling the Impact of Urban Form on Household Energy Demand and Related CO2 Emissions in the Greater Dublin Region. Energy Policy 2012, 46, 359–369. [Google Scholar] [CrossRef]
  74. Van der Borght, R.; Pallares Barbera, M. How Urban Spatial Expansion Influences CO2 Emissions in Latin American Countries. Cities 2023, 139, 104389. [Google Scholar] [CrossRef]
  75. Litman, T. Efficient Vehicles versus Efficient Transportation. Comparing Transportation Energy Conservation Strategies. Transp. Policy 2005, 12, 121–129. [Google Scholar] [CrossRef]
  76. Xue, X.; Ren, Y.; Cui, S.; Lin, J.; Huang, W.; Zhou, J. Integrated Analysis of GHGs and Public Health Damage Mitigation for Developing Urban Road Transportation Strategies. Transp. Res. Part D Transp. Environ. 2015, 35, 84–103. [Google Scholar] [CrossRef]
  77. Cervero, R.; Murakami, J. Effects of Built Environments on Vehicle Miles Traveled: Evidence from 370 US Urbanized Areas. Environ. Plan. A Econ. Space 2010, 42, 400–418. [Google Scholar] [CrossRef]
  78. Monteiro, J.; Sousa, N.; Natividade-Jesus, E.; Coutinho-Rodrigues, J. The Potential Impact of Cycling on Urban Transport Energy and Modal Share: A GIS-Based Methodology. ISPRS Int. J. Geo-Inf. 2023, 12, 48. [Google Scholar] [CrossRef]
  79. Monteiro, J.; Para, M.; Sousa, N.; Natividade-Jesus, E.; Ostorero, C.; Coutinho-Rodrigues, J. Filling in the Spaces: Compactifying Cities towards Accessibility and Active Transport. ISPRS Int. J. Geo-Inf. 2023, 12, 120. [Google Scholar] [CrossRef]
  80. Nahlik, M.J.; Chester, M.V. Transit-Oriented Smart Growth Can Reduce Life-Cycle Environmental Impacts and Household Costs in Los Angeles. Transp. Policy 2014, 35, 21–30. [Google Scholar] [CrossRef]
  81. Nasri, A.; Zhang, L. The Analysis of Transit-Oriented Development (TOD) in Washington, D.C. and Baltimore Metropolitan Areas. Transp. Policy 2014, 32, 172–179. [Google Scholar] [CrossRef]
  82. Dingil, A.E.; Schweizer, J.; Rupi, F.; Stasiskiene, Z. Updated Models of Passenger Transport Related Energy Consumption of Urban Areas. Sustainability 2019, 11, 4060. [Google Scholar] [CrossRef]
  83. Gattuso, D.; Cassone, G.C.; Malara, M. Integrated Urban Regeneration Policy and Soft Mobility Planning for Transport Energysaving. Instrum. Mes. Metrol. 2018, 18, 527–547. [Google Scholar] [CrossRef]
  84. Mendiola, L.; González, P.; Cebollada, À. The Link between Urban Development and the Modal Split in Commuting: The Case of Biscay. J. Transp. Geogr. 2014, 37, 1–9. [Google Scholar] [CrossRef]
  85. Ding, C.; Lin, Y.; Liu, C. Exploring the Influence of Built Environment on Tour-Based Commuter Mode Choice: A Cross-Classified Multilevel Modeling Approach. Transp. Res. Part D Transp. Environ. 2014, 32, 230–238. [Google Scholar] [CrossRef]
  86. Zhao, P.; Lü, B.; de Roo, G. Impact of the Jobs-Housing Balance on Urban Commuting in Beijing in the Transformation Era. J. Transp. Geogr. 2011, 19, 59–69. [Google Scholar] [CrossRef]
  87. Wang, Y.; Yang, L.; Han, S.; Li, C.; Ramachandra, T.V. Urban CO2 Emissions in Xi’an and Bangalore by Commuters: Implications for Controlling Urban Transportation Carbon Dioxide Emissions in Developing Countries. Mitig. Adapt. Strat. Glob. Chang. 2017, 22, 993–1019. [Google Scholar] [CrossRef]
  88. Ding, C.; Liu, C.; Zhang, Y.; Yang, J.; Wang, Y. Investigating the Impacts of Built Environment on Vehicle Miles Traveled and Energy Consumption: Differences between Commuting and Non-Commuting Trips. Cities 2017, 68, 25–36. [Google Scholar] [CrossRef]
  89. Li, S.; Zhao, P. Exploring Car Ownership and Car Use in Neighborhoods near Metro Stations in Beijing: Does the Neighborhood Built Environment Matter? Transp. Res. Part D Transp. Environ. 2017, 56, 1–17. [Google Scholar] [CrossRef]
  90. Yang, W.; Cao, X. Examining the Effects of the Neighborhood Built Environment on CO2 Emissions from Different Residential Trip Purposes: A Case Study in Guangzhou, China. Cities 2018, 81, 24–34. [Google Scholar] [CrossRef]
  91. Kosai, S.; Yuasa, M.; Yamasue, E. Chronological Transition of Relationship between Intracity Lifecycle Transport Energy Efficiency and Population Density. Energies 2020, 13, 2094. [Google Scholar] [CrossRef]
  92. Heres-Del-Valle, D.; Niemeier, D. CO2 Emissions: Are Land-Use Changes Enough for California to Reduce VMT? Specification of a Two-Part Model with Instrumental Variables. Transp. Res. Part B Methodol. 2011, 45, 150–161. [Google Scholar] [CrossRef]
  93. Xiong, R.; Zhao, H.; Huang, Y. Spatial Heterogeneity in the Effects of Built Environments on Walking Distance for the Elderly Living in a Mountainous City. Travel Behav. Soc. 2024, 34, 100693. [Google Scholar] [CrossRef]
  94. Boakye, K.; Bovbjerg, M.; Schuna, J.; Branscum, A.; Mat-Nasir, N.; Bahonar, A.; Barbarash, O.; Yusuf, R.; Lopez-Jaramillo, P.; Seron, P.; et al. Perceived Built Environment Characteristics Associated with Walking and Cycling across 355 Communities in 21 Countries. Cities 2023, 132, 104102. [Google Scholar] [CrossRef]
  95. Carboni, A.; Pirra, M.; Costa, M.; Kalakou, S. Active Mobility Perception from an Intersectional Perspective: Insights from Two European Cities. Transp. Res. Procedia 2022, 60, 560–567. [Google Scholar] [CrossRef]
  96. Dias, A.M.; Lopes, M.; Silva, C. More than Cycling Infrastructure: Supporting the Development of Policy Packages for Starter Cycling Cities. Transp. Res. Rec. 2022, 2676, 785–797. [Google Scholar] [CrossRef]
  97. Bucher, D.; Buffat, R.; Froemelt, A.; Raubal, M. Energy and Greenhouse Gas Emission Reduction Potentials Resulting from Different Commuter Electric Bicycle Adoption Scenarios in Switzerland. Renew. Sustain. Energy Rev. 2019, 114, 109298. [Google Scholar] [CrossRef]
  98. Pisano, C. Strategies for Post-COVID Cities: An Insight to Paris En Commun and Milano 2020. Sustainability 2020, 12, 5883. [Google Scholar] [CrossRef]
  99. Christiansen, L.B.; Cerin, E.; Badland, H.; Kerr, J.; Davey, R.; Troelsen, J.; van Dyck, D.; Mitáš, J.; Schofield, G.; Sugiyama, T.; et al. International Comparisons of the Associations between Objective Measures of the Built Environment and Transport-Related Walking and Cycling: IPEN Adult Study. J. Transp. Health 2016, 3, 467–478. [Google Scholar] [CrossRef]
  100. Ma, L.; Dill, J. Associations between the Objective and Perceived Built Environment and Bicycling for Transportation. J. Transp. Health 2015, 2, 248–255. [Google Scholar] [CrossRef]
  101. Johansson, E. Influence of Urban Geometry on Outdoor Thermal Comfort in a Hot Dry Climate: A Study in Fez, Morocco. Build. Environ. 2006, 41, 1326–1338. [Google Scholar] [CrossRef]
  102. Giannopoulou, K.; Santamouris, M.; Livada, I.; Georgakis, C.; Caouris, Y. The Impact of Canyon Geometry on Intra Urban and Urban: Suburban Night Temperature Differences Under Warm Weather Conditions. Pure Appl. Geophys. 2010, 167, 1433–1449. [Google Scholar] [CrossRef]
  103. Matzarakis, A.; Rutz, F.; Mayer, H. Modelling Radiation Fluxes in Simple and Complex Environments—Application of the RayMan Model. Int. J. Biometeorol. 2007, 51, 323–334. [Google Scholar] [CrossRef] [PubMed]
  104. Ali-Toudert, F.; Mayer, H. Effects of Asymmetry, Galleries, Overhanging Façades and Vegetation on Thermal Comfort in Urban Street Canyons. Sol. Energy 2007, 81, 742–754. [Google Scholar] [CrossRef]
  105. Perini, K.; Magliocco, A. Effects of Vegetation, Urban Density, Building Height, and Atmospheric Conditions on Local Temperatures and Thermal Comfort. Urban For. Urban Green. 2014, 13, 495–506. [Google Scholar] [CrossRef]
  106. Vailshery, L.S.; Jaganmohan, M.; Nagendra, H. Effect of Street Trees on Microclimate and Air Pollution in a Tropical City. Urban For. Urban Green. 2013, 12, 408–415. [Google Scholar] [CrossRef]
  107. Srivanit, M.; Hokao, K. Evaluating the Cooling Effects of Greening for Improving the Outdoor Thermal Environment at an Institutional Campus in the Summer. Build. Environ. 2013, 66, 158–172. [Google Scholar] [CrossRef]
  108. Johansson, E.; Spangenberg, J.; Gouvêa, M.L.; Freitas, E.D. Scale-Integrated Atmospheric Simulations to Assess Thermal Comfort in Different Urban Tissues in the Warm Humid Summer of São Paulo, Brazil. Urban Clim. 2013, 6, 24–43. [Google Scholar] [CrossRef]
  109. Acker, V.V.; Derudder, B.; Witlox, F. Why People Use Their Cars While the Built Environment Imposes Cycling. J. Transp. Land Use 2013, 6, 53–62. [Google Scholar] [CrossRef]
  110. Lin, L.; Moudon, A.V. Objective versus Subjective Measures of the Built Environment, Which Are Most Effective in Capturing Associations with Walking? Health Place 2010, 16, 339–348. [Google Scholar] [CrossRef] [PubMed]
  111. Gebel, K.; Bauman, A.E.; Sugiyama, T.; Owen, N. Mismatch between Perceived and Objectively Assessed Neighborhood Walkability Attributes: Prospective Relationships with Walking and Weight Gain. Health Place 2011, 17, 519–524. [Google Scholar] [CrossRef] [PubMed]
  112. Ewing, R.; Handy, S.; Brownson, R.C.; Clemente, O.; Winston, E. Identifying and Measuring Urban Design Qualities Related to Walkability. J. Phys. Act. Health 2006, 3, S223–S240. [Google Scholar] [CrossRef]
  113. Giménez-Gaydou, D.A.; dos Santos, A.C.; Mendes, G.; Frade, I.; Ribeiro, A.S.N. Energy Consumption and Pollutant Exposure Estimation for Cyclist Routes in Urban Areas. Transp. Res. Part D Transp. Environ. 2019, 72, 1–16. [Google Scholar] [CrossRef]
  114. Zheng, S.; Kroll, A. Public Transportation|MIT Climate Portal. Available online: https://climate.mit.edu/explainers/public-transportation (accessed on 27 November 2023).
  115. U.S. Department of Transportation. Public Transportation’s Role in Responding to Climate Change. 2010. Available online: https://www.transit.dot.gov/sites/fta.dot.gov/files/docs/PublicTransportationsRoleInRespondingToClimateChange2010.pdf (accessed on 11 January 2024).
  116. Pei, A. 5 Environmental Benefits of Sustainable Transportation. Available online: https://transportation.ucla.edu/blog/5-environmental-benefits-sustainable-transportation (accessed on 27 November 2023).
  117. Bleviss, D.L. Transportation Is Critical to Reducing Greenhouse Gas Emissions in the United States. WIREs Energy Environ. 2021, 10, e390. [Google Scholar] [CrossRef]
  118. Ding, C.; Cao, X.; Wang, Y. Synergistic Effects of the Built Environment and Commuting Programs on Commute Mode Choice. Transp. Res. Part A Policy Pract. 2018, 118, 104–118. [Google Scholar] [CrossRef]
  119. Riley, C. The Race to the Electric Car Is Just Getting Started. Available online: https://www.cnn.com/interactive/2019/08/business/electric-cars-audi-volkswagen-tesla (accessed on 21 April 2023).
  120. Motavalli, J. Every Automaker’s EV Plans through 2035 and Beyond. Available online: https://www.forbes.com/wheels/news/automaker-ev-plans/ (accessed on 21 April 2023).
  121. European Commission EU Deal to End Sale of New CO2 Emitting Cars by 2035. Available online: https://ec.europa.eu/commission/presscorner/detail/en/ip_22_6462 (accessed on 21 April 2023).
  122. Fuels & Technologies. Available online: https://www.iea.org/fuels-and-technologies (accessed on 13 April 2023).
  123. Sousa, N.; Almeida, A.; Coutinho-Rodrigues, J. A Multicriteria Methodology for Estimating Consumer Acceptance of Alternative Powertrain Technologies. Transp. Policy 2020, 85, 18–32. [Google Scholar] [CrossRef]
  124. Gonçalves Duarte Santos, G.; Birolini, S.; de Almeida Correia, G.H. A Space-Time-Energy Flow-Based Integer Programming Model to Design and Operate a Regional Shared Automated Electric Vehicle (SAEV) System and Corresponding Charging Network. Transp. Res. Part C Emerg. Technol. 2023, 147, 103997. [Google Scholar] [CrossRef]
  125. Karan, E.; Mohammadpour, A.; Asadi, S. Integrating Building and Transportation Energy Use to Design a Comprehensive Greenhouse Gas Mitigation Strategy. Appl. Energy 2016, 165, 234–243. [Google Scholar] [CrossRef]
  126. Csuzi, I.; Csuzi, B. The Urban Electric Bus, a Sustainable Solution to Increase Energy Efficiency of Public Transport and Reduce Atmospheric Pollution in the Cities. In Proceedings of the 2017 Electric Vehicles International Conference (EV), Bucharest, Romania, 5–6 October 2017; pp. 1–6. [Google Scholar]
  127. Pietrzak, O.; Pietrzak, K. The Economic Effects of Electromobility in Sustainable Urban Public Transport. Energies 2021, 14, 878. [Google Scholar] [CrossRef]
  128. Zahabi, S.A.H.; Miranda-Moreno, L.; Patterson, Z.; Barla, P.; Harding, C. Transportation Greenhouse Gas Emissions and Its Relationship with Urban Form, Transit Accessibility and Emerging Green Technologies: A Montreal Case Study. Procedia-Soc. Behav. Sci. 2012, 54, 966–978. [Google Scholar] [CrossRef]
  129. Gyurov, V.; Bezhanov, N. Possibilities for Energy Planning in Electric Power Supply Systems of Urban Electric Transport. In Proceedings of the 2019 11th Electrical Engineering Faculty Conference (BulEF), Varna, Bulgaria, 11–14 September 2019; pp. 1–6. [Google Scholar]
  130. Wang, S.; Lu, C.; Liu, C.; Zhou, Y.; Bi, J.; Zhao, X. Understanding the Energy Consumption of Battery Electric Buses in Urban Public Transport Systems. Sustainability 2020, 12, 10007. [Google Scholar] [CrossRef]
  131. Rydin, Y.; Thomas, S.; Beddington, J. Briefing: Energy and the Built Environment. Proc. Inst. Civ. Eng.-Urban Des. Plan. 2010, 163, 95–99. [Google Scholar] [CrossRef]
  132. Petersen, J.-P.; Heurkens, E. Implementing Energy Policies in Urban Development Projects: The Role of Public Planning Authorities in Denmark, Germany and the Netherlands. Land Use Policy 2018, 76, 275–289. [Google Scholar] [CrossRef]
  133. de Almeida Collaço, F.M.; Simoes, S.G.; Dias, L.P.; Duic, N.; Seixas, J.; Bermann, C. The Dawn of Urban Energy Planning—Synergies between Energy and Urban Planning for São Paulo (Brazil) Megacity. J. Clean. Prod. 2019, 215, 458–479. [Google Scholar] [CrossRef]
  134. Huang, H.; Li, Q.; Yang, Y.; Zhang, L.; Dong, Z. Research on Urban Comprehensive Energy Planning System Based on Hierarchical Framework and CAS Theory. Energy Rep. 2022, 8, 73–83. [Google Scholar] [CrossRef]
  135. Maya-Drysdale, D.; Krog Jensen, L.; Vad Mathiesen, B. Energy Vision Strategies for the EU Green New Deal: A Case Study of European Cities. Energies 2020, 13, 2194. [Google Scholar] [CrossRef]
  136. Fremouw, M.; Bagaini, A.; De Pascali, P. Energy Potential Mapping: Open Data in Support of Urban Transition Planning. Energies 2020, 13, 1264. [Google Scholar] [CrossRef]
  137. Guo, J.; Bissuel, C.; Courtot, F. Integrated Urban Energy Planning: A Casestudy Using Optimization. Front. Artif. Intell. Appl. 2021, 341, 375–384. [Google Scholar] [CrossRef]
  138. Castro, L.F.C.; Freitas, B.B.; Carvalho, P.C.M. A Review on the Integration between Urban and Energy Planning Considering the Planning Tools. Renew. Energy Power Qual. J. 2021, 19, 189–194. [Google Scholar] [CrossRef]
  139. Tsangas, M.; Papamichael, I.; Zorpas, A.A. Sustainable Energy Planning in a New Situation. Energies 2023, 16, 1626. [Google Scholar] [CrossRef]
  140. Covenant of Mayors—Europe|Covenant of Mayors—Europe. Available online: https://eu-mayors.ec.europa.eu/en/home (accessed on 18 April 2023).
  141. ICLEI Europe. Available online: https://iclei-europe.org/ (accessed on 19 April 2023).
  142. C40 Cities—A Global Network of Mayors Taking Urgent Climate Action. Available online: https://www.c40.org/ (accessed on 19 April 2023).
  143. Monteiro, J.; Sousa, N.; Natividade-Jesus, E.; Coutinho-Rodrigues, J. Benchmarking City Layouts—A Methodological Approach and an Accessibility Comparison between a Real City and the Garden City. Sustainability 2022, 14, 5029. [Google Scholar] [CrossRef]
  144. Derix, C. Digital Masterplanning: Computing Urban Design. Proc. Inst. Civ. Eng.-Urban Des. Plan. 2012, 165, 203–217. [Google Scholar] [CrossRef]
  145. Geertman, S.; Stillwell, J. Planning Support Systems: An Inventory of Current Practice. Comput. Environ. Urban Syst. 2004, 28, 291–310. [Google Scholar] [CrossRef]
  146. Reinhart, C.F.; Cerezo Davila, C. Urban Building Energy Modeling—A Review of a Nascent Field. Build. Environ. 2016, 97, 196–202. [Google Scholar] [CrossRef]
  147. Ferrari, S.; Zagarella, F.; Caputo, P.; Bonomolo, M. Assessment of Tools for Urban Energy Planning. Energy 2019, 176, 544–551. [Google Scholar] [CrossRef]
  148. Kenworthy, J.R. The Eco-City: Ten Key Transport and Planning Dimensions for Sustainable City Development. Environ. Urban. 2006, 18, 67–85. [Google Scholar] [CrossRef]
  149. Roger-Lacan, C. Urban Planning and Energy: New Relationships, New Local Governance. In Local Energy Autonomy; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2019; pp. 1–18. ISBN 978-1-119-61629-0. [Google Scholar]
  150. Marrone, P.; Fiume, F.; Laudani, A.; Montella, I.; Palermo, M.; Fulginei, F.R. Distributed Energy Systems: Constraints and Opportunities in Urban Environments. Energies 2023, 16, 2718. [Google Scholar] [CrossRef]
  151. Koutra, S.; Becue, V.; Gallas, M.-A.; Ioakimidis, C.S. Towards the Development of a Net-Zero Energy District Evaluation Approach: A Review of Sustainable Approaches and Assessment Tools. Sustain. Cities Soc. 2018, 39, 784–800. [Google Scholar] [CrossRef]
  152. De Lotto, R.; Micciché, C.; Venco, E.M.; Bonaiti, A.; De Napoli, R. Energy Communities: Technical, Legislative, Organizational, and Planning Features. Energies 2022, 15, 1731. [Google Scholar] [CrossRef]
  153. Lombardi, P.; Trossero, E. Beyond Energy Efficiency in Evaluating Sustainable Development in Planning and the Built Environment. Int. J. Sustain. Build. Technol. Urban Dev. 2013, 4, 274–282. [Google Scholar] [CrossRef]
  154. Bracco, S.; Delfino, F.; Ferro, G.; Pagnini, L.; Robba, M.; Rossi, M. Energy Planning of Sustainable Districts: Towards the Exploitation of Small Size Intermittent Renewables in Urban Areas. Appl. Energy 2018, 228, 2288–2297. [Google Scholar] [CrossRef]
  155. Croce, S.; Vettorato, D. Urban Surface Uses for Climate Resilient and Sustainable Cities: A Catalogue of Solutions. Sustain. Cities Soc. 2021, 75, 103313. [Google Scholar] [CrossRef]
  156. Paatero, J.V.; Lund, P.D. Effects of Large-Scale Photovoltaic Power Integration on Electricity Distribution Networks. Renew. Energy 2007, 32, 216–234. [Google Scholar] [CrossRef]
  157. Formolli, M.; Lobaccaro, G.; Kanters, J. Solar Energy in the Nordic Built Environment: Challenges, Opportunities and Barriers. Energies 2021, 14, 8410. [Google Scholar] [CrossRef]
  158. Lobaccaro, G.; Croce, S.; Lindkvist, C.; Munari Probst, M.C.; Scognamiglio, A.; Dahlberg, J.; Lundgren, M.; Wall, M. A Cross-Country Perspective on Solar Energy in Urban Planning: Lessons Learned from International Case Studies. Renew. Sustain. Energy Rev. 2019, 108, 209–237. [Google Scholar] [CrossRef]
  159. Taminiau, J.; Byrne, J.; Kim, J.; Kim, M.; Seo, J. Infrastructure-Scale Sustainable Energy Planning in the Cityscape: Transforming Urban Energy Metabolism in East Asia. WIREs Energy Environ. 2021, 10, e397. [Google Scholar] [CrossRef]
  160. Chen, Y.; Hong, T.; Piette, M.A. Automatic Generation and Simulation of Urban Building Energy Models Based on City Datasets for City-Scale Building Retrofit Analysis. Appl. Energy 2017, 205, 323–335. [Google Scholar] [CrossRef]
  161. Urban Sprawl in Europe—Joint EEA-FOEN Report—European Environment Agency. Available online: https://www.eea.europa.eu/publications/urban-sprawl-in-europe (accessed on 21 February 2023).
  162. Frumkin, H. Urban Sprawl and Public Health. Public Health Rep. 2002, 117, 201–217. [Google Scholar] [CrossRef]
  163. Glaeser, E.L.; Kahn, M.E. The Greenness of Cities: Carbon Dioxide Emissions and Urban Development. J. Urban Econ. 2010, 67, 404–418. [Google Scholar] [CrossRef]
  164. Amado, M.; Poggi, F.; Amado, A.R. Energy Efficient City: A Model for Urban Planning. Sustain. Cities Soc. 2016, 26, 476–485. [Google Scholar] [CrossRef]
  165. Kakar, K.A.; Prasad, C.S.R.K. Impact of Urban Sprawl on Travel Demand for Public Transport, Private Transport and Walking. Transp. Res. Procedia 2020, 48, 1881–1892. [Google Scholar] [CrossRef]
  166. Dupras, J.; Marull, J.; Parcerisas, L.; Coll, F.; Gonzalez, A.; Girard, M.; Tello, E. The Impacts of Urban Sprawl on Ecological Connectivity in the Montreal Metropolitan Region. Environ. Sci. Policy 2016, 58, 61–73. [Google Scholar] [CrossRef]
  167. Artmann, M.; Inostroza, L.; Fan, P. Urban Sprawl, Compact Urban Development and Green Cities. How Much Do We Know, How Much Do We Agree? Ecol. Indic. 2019, 96, 3–9. [Google Scholar] [CrossRef]
  168. Jin, J. The Effects of Labor Market Spatial Structure and the Built Environment on Commuting Behavior: Considering Spatial Effects and Self-Selection. Cities 2019, 95, 102392. [Google Scholar] [CrossRef]
  169. Fujii, H.; Iwata, K.; Managi, S. How Do Urban Characteristics Affect Climate Change Mitigation Policies? J. Clean. Prod. 2017, 168, 271–278. [Google Scholar] [CrossRef]
  170. Naess, P. Residential Location, Travel, and Energy Use in the Hangzhou Metropolitan Area. J. Transp. Land Use 2010, 3, 27–59. [Google Scholar] [CrossRef]
  171. Howard, E. To-Morrow: A Peaceful Path to Real Reform; Cambridge Library Collection—British and Irish History, 19th Century; Cambridge University Press: Cambridge, UK, 2010; ISBN 978-1-108-02192-0. [Google Scholar]
  172. Corbusier, L. The City of Tomorrow; MIT Press: Cambridge, MA, USA, 1972; ISBN 978-0-262-62017-8. [Google Scholar]
  173. Osman, T.; Divigalpitiya, P.; Osman, M.M. The Impact of Built Environment Characteristics on Metropolitans Energy Consumption: An Example of Greater Cairo Metropolitan Region. Buildings 2016, 6, 12. [Google Scholar] [CrossRef]
  174. Nelson, A.C. Compact Development Reduces VMT: Evidence and Application for Planners—Comment on “Does Compact Development Make People Drive Less?”. J. Am. Plan. Assoc. 2017, 83, 36–41. [Google Scholar] [CrossRef]
  175. Stevens, M.R. Does Compact Development Make People Drive Less? J. Am. Plan. Assoc. 2017, 83, 7–18. [Google Scholar] [CrossRef]
  176. Hsieh, S.; Schüler, N.; Shi, Z.; Fonseca, J.A.; Maréchal, F.; Schlueter, A. Defining Density and Land Uses under Energy Performance Targets at the Early Stage of Urban Planning Processes. Energy Procedia 2017, 122, 301–306. [Google Scholar] [CrossRef]
  177. Hong, J.; Goodchild, A. Land Use Policies and Transport Emissions: Modeling the Impact of Trip Speed, Vehicle Characteristics and Residential Location. Transp. Res. Part D Transp. Environ. 2014, 26, 47–51. [Google Scholar] [CrossRef]
  178. Stone, B.; Mednick, A.C.; Holloway, T.; Spak, S.N. Is Compact Growth Good for Air Quality? J. Am. Plan. Assoc. 2007, 73, 404–418. [Google Scholar] [CrossRef]
  179. Wang, D.; Zhou, M. The Built Environment and Travel Behavior in Urban China: A Literature Review. Transp. Res. Part D Transp. Environ. 2017, 52, 574–585. [Google Scholar] [CrossRef]
  180. Woo, Y.-E.; Cho, G.-H. Impact of the Surrounding Built Environment on Energy Consumption in Mixed-Use Building. Sustainability 2018, 10, 832. [Google Scholar] [CrossRef]
  181. Kaza, N. Urban Form and Transportation Energy Consumption. Energy Policy 2020, 136, 111049. [Google Scholar] [CrossRef]
  182. Conticelli, E.; Proli, S.; Tondelli, S. Integrating Energy Efficiency and Urban Densification Policies: Two Italian Case Studies. Energy Build. 2017, 155, 308–323. [Google Scholar] [CrossRef]
  183. Muñoz, P.; Zwick, S.; Mirzabaev, A. The Impact of Urbanization on Austria’s Carbon Footprint. J. Clean. Prod. 2020, 263, 121326. [Google Scholar] [CrossRef]
  184. Yao, X.; Kou, D.; Shao, S.; Li, X.; Wang, W.; Zhang, C. Can Urbanization Process and Carbon Emission Abatement Be Harmonious? New Evidence from China. Environ. Impact Assess. Rev. 2018, 71, 70–83. [Google Scholar] [CrossRef]
  185. Luqman, M.; Rayner, P.J.; Gurney, K.R. On the Impact of Urbanisation on CO2 Emissions. Npj Urban Sustain. 2023, 3, 6. [Google Scholar] [CrossRef]
  186. Lyu, G.; Bertolini, L.; Pfeffer, K. Developing a TOD Typology for Beijing Metro Station Areas. J. Transp. Geogr. 2016, 55, 40–50. [Google Scholar] [CrossRef]
  187. Calthorpe, P. The Next American Metropolis: Ecology, Community, and the American Dream; Princeton Architectural Press: New York, NY, USA, 1993; ISBN 978-1-878271-68-6. [Google Scholar]
  188. Calthorpe Associates. Transit-Oriented Development Design Guidelines; Calthorpe Associates: San Diego, CA, USA, 1992. [Google Scholar]
  189. Silva, M.; Leal, V.; Oliveira, V.; Horta, I.M. A Scenario-Based Approach for Assessing the Energy Performance of Urban Development Pathways. Sustain. Cities Soc. 2018, 40, 372–382. [Google Scholar] [CrossRef]
  190. Berawi, M.A.; Ibrahim, B.E.; Gunawan; Miraj, P. Developing A Conceptual Design of Transit-Oriented Development To Improve Urban Land Use Planning. J. Des. Built Environ. 2019, 19, 40–48. [Google Scholar] [CrossRef]
  191. Neuman, M. The Compact City Fallacy. J. Plan. Educ. Res. 2005, 25, 11–26. [Google Scholar] [CrossRef]
  192. Santos, T.; Deus, R.; Rocha, J.; Tenedório, J.A. Assessing Sustainable Urban Development Trends in a Dynamic Tourist Coastal Area Using 3D Spatial Indicators. Energies 2021, 14, 5044. [Google Scholar] [CrossRef]
  193. Weisz, H.; Steinberger, J.K. Reducing Energy and Material Flows in Cities. Curr. Opin. Environ. Sustain. 2010, 2, 185–192. [Google Scholar] [CrossRef]
  194. Zamanifard, H.; Alizadeh, T.; Bosman, C.; Coiacetto, E. Measuring Experiential Qualities of Urban Public Spaces: Users’ Perspective. J. Urban Des. 2019, 24, 340–364. [Google Scholar] [CrossRef]
  195. Costamagna, F.; Lind, R.; Stjernström, O. Livability of Urban Public Spaces in Northern Swedish Cities: The Case of Umeå. Plan. Pract. Res. 2019, 34, 131–148. [Google Scholar] [CrossRef]
  196. Mandeli, K. Public Space and the Challenge of Urban Transformation in Cities of Emerging Economies: Jeddah Case Study. Cities 2019, 95, 102409. [Google Scholar] [CrossRef]
  197. Weijs-Perrée, M.; Dane, G.; van den Berg, P. Analyzing the Relationships between Citizens’ Emotions and Their Momentary Satisfaction in Urban Public Spaces. Sustainability 2020, 12, 7921. [Google Scholar] [CrossRef]
  198. Carter, J.G. Urban Climate Change Adaptation: Exploring the Implications of Future Land Cover Scenarios. Cities 2018, 77, 73–80. [Google Scholar] [CrossRef]
  199. Ozgun, K. Towards a Sustainability Assessment Model for Urban Public Space Renewable Energy Infrastructure. Energies 2020, 13, 3428. [Google Scholar] [CrossRef]
  200. Hu, J.; Yu, X.B. Adaptive Thermochromic Roof System: Assessment of Performance under Different Climates. Energy Build. 2019, 192, 1–14. [Google Scholar] [CrossRef]
  201. Lim, X. The Super-Cool Materials That Send Heat to Space. Nature 2019, 577, 18–20. [Google Scholar] [CrossRef] [PubMed]
  202. Akbari, H.; Kolokotsa, D. Three Decades of Urban Heat Islands and Mitigation Technologies Research. Energy Build. 2016, 133, 834–842. [Google Scholar] [CrossRef]
  203. Akbari, H.; Matthews, H.D. Global Cooling Updates: Reflective Roofs and Pavements. Energy Build. 2012, 55, 2–6. [Google Scholar] [CrossRef]
  204. Rosso, F.; Fabiani, C.; Chiatti, C.; Pisello, A.L. Cool, Photoluminescent Paints towards Energy Consumption Reductions in the Built Environment. J. Phys. Conf. Ser. 2019, 1343, 012198. [Google Scholar] [CrossRef]
  205. Pisello, A.L. State of the Art on the Development of Cool Coatings for Buildings and Cities. Sol. Energy 2017, 144, 660–680. [Google Scholar] [CrossRef]
  206. Couto, R.; Duarte, F.; Magalhães, A. Mechanical Systems for Pavement Energy Harvesting: A State-of-the-Art. Energy Sources Part A Recovery Util. Environ. Eff. 2022, 44, 6957–6969. [Google Scholar] [CrossRef]
  207. Duarte, F.; Ferreira, A. Energy Harvesting on Road Pavements: State of the Art. Proc. Inst. Civ. Eng.-Energy 2016, 169, 79–90. [Google Scholar] [CrossRef]
  208. Duarte, F.; Ferreira, A.; Fael, P. Road Pavement Energy–Harvesting Device to Convert Vehicles’ Mechanical Energy into Electrical Energy. J. Energy Eng. 2018, 144, 04018003. [Google Scholar] [CrossRef]
  209. Qin, Y. A Review on the Development of Cool Pavements to Mitigate Urban Heat Island Effect. Renew. Sustain. Energy Rev. 2015, 52, 445–459. [Google Scholar] [CrossRef]
  210. Ratti, C.; Baker, N.; Steemers, K. Energy Consumption and Urban Texture. Energy Build. 2005, 37, 762–776. [Google Scholar] [CrossRef]
  211. Tchepel, O.; Monteiro, A.; Dias, D.; Gama, C.; Pina, N.; Rodrigues, J.P.; Ferreira, M.; Miranda, A.I. Urban Aerosol Assessment and Forecast: Coimbra Case Study. Atmos. Pollut. Res. 2020, 11, 1155–1164. [Google Scholar] [CrossRef]
  212. Strømann-Andersen, J.; Sattrup, P.A. The Urban Canyon and Building Energy Use: Urban Density versus Daylight and Passive Solar Gains. Energy Build. 2011, 43, 2011–2020. [Google Scholar] [CrossRef]
  213. Vartholomaios, A. A Parametric Sensitivity Analysis of the Influence of Urban Form on Domestic Energy Consumption for Heating and Cooling in a Mediterranean City. Sustain. Cities Soc. 2017, 28, 135–145. [Google Scholar] [CrossRef]
  214. Li, Z.; Quan, S.J.; Yang, P.P.-J. Energy Performance Simulation for Planning a Low Carbon Neighborhood Urban District: A Case Study in the City of Macau. Habitat Int. 2016, 53, 206–214. [Google Scholar] [CrossRef]
  215. Oh, M.; Kim, Y. Identifying Urban Geometric Types as Energy Performance Patterns. Energy Sustain. Dev. 2019, 48, 115–129. [Google Scholar] [CrossRef]
  216. Oh, M.; Jang, K.M.; Kim, Y. Empirical Analysis of Building Energy Consumption and Urban Form in a Large City: A Case of Seoul, South Korea. Energy Build. 2021, 245, 111046. [Google Scholar] [CrossRef]
  217. Silva, M.C.; Horta, I.M.; Leal, V.; Oliveira, V. A Spatially-Explicit Methodological Framework Based on Neural Networks to Assess the Effect of Urban Form on Energy Demand. Appl. Energy 2017, 202, 386–398. [Google Scholar] [CrossRef]
  218. Olgyay, V. Design with Climate; Princeton University Press: Princeton, NJ, USA, 2015; ISBN 978-0-691-16973-6. [Google Scholar]
  219. Taleghani, M.; Tenpierik, M.; van den Dobbelsteen, A.; de Dear, R. Energy Use Impact of and Thermal Comfort in Different Urban Block Types in the Netherlands. Energy Build. 2013, 67, 166–175. [Google Scholar] [CrossRef]
  220. Wang, S.; Wang, J.; Fang, C.; Li, S. Estimating the Impacts of Urban Form on CO2 Emission Efficiency in the Pearl River Delta, China. Cities 2019, 85, 117–129. [Google Scholar] [CrossRef]
  221. Lee, J.H.; Lim, S. The Selection of Compact City Policy Instruments and Their Effects on Energy Consumption and Greenhouse Gas Emissions in the Transportation Sector: The Case of South Korea. Sustain. Cities Soc. 2018, 37, 116–124. [Google Scholar] [CrossRef]
  222. Falahatkar, S.; Rezaei, F. Towards Low Carbon Cities: Spatio-Temporal Dynamics of Urban Form and Carbon Dioxide Emissions. Remote Sens. Appl. Soc. Environ. 2020, 18, 100317. [Google Scholar] [CrossRef]
  223. Steemers, K. Energy and the City: Density, Buildings and Transport. Energy Build. 2003, 35, 3–14. [Google Scholar] [CrossRef]
  224. Pisello, A.L.; Taylor, J.E.; Xu, X.; Cotana, F. Inter-Building Effect: Simulating the Impact of a Network of Buildings on the Accuracy of Building Energy Performance Predictions. Build. Environ. 2012, 58, 37–45. [Google Scholar] [CrossRef]
  225. Loeffler, R.; Österreicher, D.; Stoeglehner, G. The Energy Implications of Urban Morphology from an Urban Planning Perspective—A Case Study for a New Urban Development Area in the City of Vienna. Energy Build. 2021, 252, 111453. [Google Scholar] [CrossRef]
  226. Eicker, U.; Monien, D.; Duminil, É.; Nouvel, R. Energy Performance Assessment in Urban Planning Competitions. Appl. Energy 2015, 155, 323–333. [Google Scholar] [CrossRef]
  227. Rodríguez-Álvarez, J. Urban Energy Index for Buildings (UEIB): A New Method to Evaluate the Effect of Urban Form on Buildings’ Energy Demand. Landsc. Urban Plan. 2016, 148, 170–187. [Google Scholar] [CrossRef]
  228. Resch, E.; Bohne, R.A.; Kvamsdal, T.; Lohne, J. Impact of Urban Density and Building Height on Energy Use in Cities. Energy Procedia 2016, 96, 800–814. [Google Scholar] [CrossRef]
  229. Gil-García, I.C.; García-Cascales, M.S.; Molina-García, A. Urban Wind: An Alternative for Sustainable Cities. Energies 2022, 15, 4759. [Google Scholar] [CrossRef]
  230. Gough, M.; Lotfi, M.; Castro, R.; Madhlopa, A.; Khan, A.; Catalão, J.P.S. Urban Wind Resource Assessment: A Case Study on Cape Town. Energies 2019, 12, 1479. [Google Scholar] [CrossRef]
  231. Morrissey, J.; Moore, T.; Horne, R.E. Affordable Passive Solar Design in a Temperate Climate: An Experiment in Residential Building Orientation. Renew. Energy 2011, 36, 568–577. [Google Scholar] [CrossRef]
  232. Urban Form, Density and Solar Potential; Cheng, V.; Steemers, K.; Montavon, M.; Compagnon, R. (Eds.) InfoScience: HongKong, China, 2006. [Google Scholar]
  233. Byrne, J.; Taminiau, J.; Kurdgelashvili, L.; Kim, K.N. A Review of the Solar City Concept and Methods to Assess Rooftop Solar Electric Potential, with an Illustrative Application to the City of Seoul. Renew. Sustain. Energy Rev. 2015, 41, 830–844. [Google Scholar] [CrossRef]
  234. Redweik, P.; Catita, C.; Brito, M. Solar Energy Potential on Roofs and Facades in an Urban Landscape. Sol. Energy 2013, 97, 332–341. [Google Scholar] [CrossRef]
  235. Azevedo, J.A.; Chapman, L.; Muller, C.L. Quantifying the Daytime and Night-Time Urban Heat Island in Birmingham, UK: A Comparison of Satellite Derived Land Surface Temperature and High Resolution Air Temperature Observations. Remote Sens. 2016, 8, 153. [Google Scholar] [CrossRef]
  236. Oke, T.R. Boundary Layer Climates, 2nd ed.; Routledge: London, UK, 1987; ISBN 978-0-203-40721-9. [Google Scholar]
  237. Wang, Z.-H. Reconceptualizing Urban Heat Island: Beyond the Urban-Rural Dichotomy. Sustain. Cities Soc. 2022, 77, 103581. [Google Scholar] [CrossRef]
  238. Santamouris, M. Using Cool Pavements as a Mitigation Strategy to Fight Urban Heat Island—A Review of the Actual Developments. Renew. Sustain. Energy Rev. 2013, 26, 224–240. [Google Scholar] [CrossRef]
  239. Battista, G.; Carnielo, E.; De Lieto Vollaro, R. Thermal Impact of a Redeveloped Area on Localized Urban Microclimate: A Case Study in Rome. Energy Build. 2016, 133, 446–454. [Google Scholar] [CrossRef]
  240. Charalampopoulos, I.; Tsiros, I.; Chronopoulou-Sereli, A.; Matzarakis, A. Analysis of Thermal Bioclimate in Various Urban Configurations in Athens, Greece. Urban Ecosyst. 2013, 16, 217–233. [Google Scholar] [CrossRef]
  241. Hamstead, Z.A.; Farmer, C.; McPhearson, T. Landscape-Based Extreme Heat Vulnerability Assessment. J. Extr. Even. 2018, 5, 1850018. [Google Scholar] [CrossRef]
  242. Yan, H.; Wu, F.; Dong, L. Influence of a Large Urban Park on the Local Urban Thermal Environment. Sci. Total Environ. 2018, 622–623, 882–891. [Google Scholar] [CrossRef] [PubMed]
  243. Wong, P.P.-Y.; Lai, P.-C.; Low, C.-T.; Chen, S.; Hart, M. The Impact of Environmental and Human Factors on Urban Heat and Microclimate Variability. Build. Environ. 2016, 95, 199–208. [Google Scholar] [CrossRef]
  244. Pacheco-Torgal, F. 1—Introduction to Eco-Efficient Materials to Mitigate Building Cooling Needs. In Eco-Efficient Materials for Mitigating Building Cooling Needs; Pacheco-Torgal, F., Labrincha, J.A., Cabeza, L.F., Granqvist, C.-G., Eds.; Woodhead Publishing: Oxford, UK, 2015; pp. 1–9. ISBN 978-1-78242-380-5. [Google Scholar]
  245. Li, H.; Harvey, J.; Kendall, A. Field Measurement of Albedo for Different Land Cover Materials and Effects on Thermal Performance. Build. Environ. 2013, 59, 536–546. [Google Scholar] [CrossRef]
  246. Li, X.; Zhou, W.; Ouyang, Z. Relationship between Land Surface Temperature and Spatial Pattern of Greenspace: What Are the Effects of Spatial Resolution? Landsc. Urban Plan. 2013, 114, 1–8. [Google Scholar] [CrossRef]
  247. Gunawardena, K.R.; Wells, M.J.; Kershaw, T. Utilising Green and Bluespace to Mitigate Urban Heat Island Intensity. Sci. Total Environ. 2017, 584–585, 1040–1055. [Google Scholar] [CrossRef] [PubMed]
  248. Moyer, A.N.; Hawkins, T.W. River Effects on the Heat Island of a Small Urban Area. Urban Clim. 2017, 21, 262–277. [Google Scholar] [CrossRef]
  249. Daniel, M.; Lemonsu, A.; Viguié, V. Role of Watering Practices in Large-Scale Urban Planning Strategies to Face the Heat-Wave Risk in Future Climate. Urban Clim. 2018, 23, 287–308. [Google Scholar] [CrossRef]
  250. Mackey, C.W.; Lee, X.; Smith, R.B. Remotely Sensing the Cooling Effects of City Scale Efforts to Reduce Urban Heat Island. Build. Environ. 2012, 49, 348–358. [Google Scholar] [CrossRef]
  251. Huang, C.; Yang, J.; Jiang, P. Assessing Impacts of Urban Form on Landscape Structure of Urban Green Spaces in China Using Landsat Images Based on Google Earth Engine. Remote Sens. 2018, 10, 1569. [Google Scholar] [CrossRef]
  252. Kadaverugu, A.; Kadaverugu, R.; Chintala, N.R.; Gorthi, K.V. Flood vulnerability assessment of urban micro-watersheds using multi-criteria decision making and InVEST model: A case of Hyderabad City, India. Model. Earth Syst. Environ. 2021, 1, 3447–3459. [Google Scholar] [CrossRef]
  253. Aram, F.; Higueras García, E.; Solgi, E.; Mansournia, S. Urban Green Space Cooling Effect in Cities. Heliyon 2019, 5, e01339. [Google Scholar] [CrossRef] [PubMed]
  254. O’Malley, C.; Piroozfar, P.; Farr, E.R.P.; Pomponi, F. Urban Heat Island (UHI) Mitigating Strategies: A Case-Based Comparative Analysis. Sustain. Cities Soc. 2015, 19, 222–235. [Google Scholar] [CrossRef]
  255. Das, M.; Das, A.; Momin, S. Quantifying the Cooling Effect of Urban Green Space: A Case from Urban Parks in a Tropical Mega Metropolitan Area (India). Sustain. Cities Soc. 2022, 87, 104062. [Google Scholar] [CrossRef]
  256. Farhadi, H.; Faizi, M.; Sanaieian, H. Mitigating the Urban Heat Island in a Residential Area in Tehran: Investigating the Role of Vegetation, Materials, and Orientation of Buildings. Sustain. Cities Soc. 2019, 46, 101448. [Google Scholar] [CrossRef]
  257. Zölch, T.; Maderspacher, J.; Wamsler, C.; Pauleit, S. Using Green Infrastructure for Urban Climate-Proofing: An Evaluation of Heat Mitigation Measures at the Micro-Scale. Urban For. Urban Green. 2016, 20, 305–316. [Google Scholar] [CrossRef]
  258. Norton, B.A.; Coutts, A.M.; Livesley, S.J.; Harris, R.J.; Hunter, A.M.; Williams, N.S.G. Planning for Cooler Cities: A Framework to Prioritise Green Infrastructure to Mitigate High Temperatures in Urban Landscapes. Landsc. Urban Plan. 2015, 134, 127–138. [Google Scholar] [CrossRef]
  259. Chow, W.T.L.; Brazel, A.J. Assessing Xeriscaping as a Sustainable Heat Island Mitigation Approach for a Desert City. Build. Environ. 2012, 47, 170–181. [Google Scholar] [CrossRef]
  260. Buyadi, S.N.A.; Mohd, W.M.N.W.; Misni, A. Vegetation’s Role on Modifying Microclimate of Urban Resident. Procedia-Soc. Behav. Sci. 2015, 202, 400–407. [Google Scholar] [CrossRef]
  261. Aram, F.; Solgi, E.; Holden, G. The Role of Green Spaces in Increasing Social Interactions in Neighborhoods with Periodic Markets. Habitat Int. 2019, 84, 24–32. [Google Scholar] [CrossRef]
  262. Brandt, L.; Derby Lewis, A.; Fahey, R.; Scott, L.; Darling, L.; Swanston, C. A Framework for Adapting Urban Forests to Climate Change. Environ. Sci. Policy 2016, 66, 393–402. [Google Scholar] [CrossRef]
  263. Santamouris, M. Cooling the Cities—A Review of Reflective and Green Roof Mitigation Technologies to Fight Heat Island and Improve Comfort in Urban Environments. Sol. Energy 2014, 103, 682–703. [Google Scholar] [CrossRef]
  264. Alcazar, S.S.; Olivieri, F.; Neila, J. Green Roofs: Experimental and Analytical Study of Its Potential for Urban Microclimate Regulation in Mediterranean–Continental Climates. Urban Clim. 2016, 17, 304–317. [Google Scholar] [CrossRef]
  265. Besir, A.B.; Cuce, E. Green Roofs and Facades: A Comprehensive Review. Renew. Sustain. Energy Rev. 2018, 82, 915–939. [Google Scholar] [CrossRef]
  266. Lobaccaro, G.; Acero, J.A. Comparative Analysis of Green Actions to Improve Outdoor Thermal Comfort inside Typical Urban Street Canyons. Urban Clim. 2015, 14, 251–267. [Google Scholar] [CrossRef]
  267. Shahidan, M.F.; Shariff, M.K.M.; Jones, P.; Salleh, E.; Abdullah, A.M. A Comparison of Mesua ferrea L. and Hura crepitans L. for Shade Creation and Radiation Modification in Improving Thermal Comfort. Landsc. Urban Plan. 2010, 97, 168–181. [Google Scholar] [CrossRef]
  268. Klemm, W.; Heusinkveld, B.G.; Lenzholzer, S.; van Hove, B. Street Greenery and Its Physical and Psychological Impact on Thermal Comfort. Landsc. Urban Plan. 2015, 138, 87–98. [Google Scholar] [CrossRef]
  269. Yezioro, A.; Capeluto, I.G.; Shaviv, E. Design Guidelines for Appropriate Insolation of Urban Squares. Renew. Energy 2006, 31, 1011–1023. [Google Scholar] [CrossRef]
  270. Shashua-Bar, L.; Potchter, O.; Bitan, A.; Boltansky, D.; Yaakov, Y. Microclimate Modelling of Street Tree Species Effects within the Varied Urban Morphology in the Mediterranean City of Tel Aviv, Israel. Int. J. Clim. 2010, 30, 44–57. [Google Scholar] [CrossRef]
  271. McPherson, E.G.; Simpson, J.R.; Peper, P.J.; Maco, S.E.; Xiao, Q.; Hoefer, P.J. Northern Mountain and Prairie Community Tree Guide. In Forest Service, Pacific Southwest Research Station, Center for Urban Forest Research; U.S. Department of Agriculture: Davis, CA, USA, 2003; p. 88. [Google Scholar]
  272. Kim, K.; Yi, C.; Lee, S. Impact of Urban Characteristics on Cooling Energy Consumption before and after Construction of an Urban Park: The Case of Gyeongui Line Forest in Seoul. Energy Build. 2019, 191, 42–51. [Google Scholar] [CrossRef]
  273. Xu, X.; Sun, S.; Liu, W.; García, E.H.; He, L.; Cai, Q.; Xu, S.; Wang, J.; Zhu, J. The Cooling and Energy Saving Effect of Landscape Design Parameters of Urban Park in Summer: A Case of Beijing, China. Energy Build. 2017, 149, 91–100. [Google Scholar] [CrossRef]
  274. Kaloustian, N.; Diab, Y. Effects of Urbanization on the Urban Heat Island in Beirut. Urban Clim. 2015, 14, 154–165. [Google Scholar] [CrossRef]
  275. Brown, R.D.; Vanos, J.; Kenny, N.; Lenzholzer, S. Designing Urban Parks That Ameliorate the Effects of Climate Change. Landsc. Urban Plan. 2015, 138, 118–131. [Google Scholar] [CrossRef]
  276. Wang, P.; Yang, Y.; Ji, C.; Huang, L. Positivity and Difference of Influence of Built Environment around Urban Park on Building Energy Consumption. Sustain. Cities Soc. 2023, 89, 104321. [Google Scholar] [CrossRef]
  277. Harlan, S.L.; Brazel, A.J.; Prashad, L.; Stefanov, W.L.; Larsen, L. Neighborhood Microclimates and Vulnerability to Heat Stress. Soc. Sci. Med. 2006, 63, 2847–2863. [Google Scholar] [CrossRef] [PubMed]
  278. Sarrat, C.; Lemonsu, A.; Masson, V.; Guedalia, D. Impact of Urban Heat Island on Regional Atmospheric Pollution. Atmos. Environ. 2006, 40, 1743–1758. [Google Scholar] [CrossRef]
  279. Priyadarsini, R.; Hien, W.N.; Wai David, C.K. Microclimatic Modeling of the Urban Thermal Environment of Singapore to Mitigate Urban Heat Island. Sol. Energy 2008, 82, 727–745. [Google Scholar] [CrossRef]
  280. Fu, J.; Wang, Y.; Zhou, D.; Cao, S.-J. Impact of Urban Park Design on Microclimate in Cold Regions Using Newly Developped Prediction Method. Sustain. Cities Soc. 2022, 80, 103781. [Google Scholar] [CrossRef]
  281. Okeil, A. A Holistic Approach to Energy Efficient Building Forms. Energy Build. 2010, 42, 1437–1444. [Google Scholar] [CrossRef]
  282. Kastner-Klein, P.; Berkowicz, R.; Britter, R. The Influence of Street Architecture on Flow and Dispersion in Street Canyons. Meteorol. Atmos. Phys. 2004, 87, 121–131. [Google Scholar] [CrossRef]
  283. Li, X.-X.; Liu, C.-H.; Leung, D.Y.C.; Lam, K.M. Recent Progress in CFD Modelling of Wind Field and Pollutant Transport in Street Canyons. Atmos. Environ. 2006, 40, 5640–5658. [Google Scholar] [CrossRef]
  284. Vardoulakis, S.; Fisher, B.E.A.; Pericleous, K.; Gonzalez-Flesca, N. Modelling Air Quality in Street Canyons: A Review. Atmos. Environ. 2003, 37, 155–182. [Google Scholar] [CrossRef]
  285. Kiprop, V. What Is a Street Canyon? Available online: https://www.worldatlas.com/articles/what-is-a-street-canyon.html (accessed on 24 April 2023).
  286. Kumar, P.; Morawska, L.; Martani, C.; Biskos, G.; Neophytou, M.; Di Sabatino, S.; Bell, M.; Norford, L.; Britter, R. The Rise of Low-Cost Sensing for Managing Air Pollution in Cities. Environ. Int. 2015, 75, 199–205. [Google Scholar] [CrossRef] [PubMed]
  287. Ali-Toudert, F.; Mayer, H. Numerical Study on the Effects of Aspect Ratio and Orientation of an Urban Street Canyon on Outdoor Thermal Comfort in Hot and Dry Climate. Build. Environ. 2006, 41, 94–108. [Google Scholar] [CrossRef]
  288. Todhunter, P.E. Microclimatic Variations Attibutable to Urban-Canyon Asymetry and Orientation. Phys. Geogr. 1990, 11, 131–141. [Google Scholar] [CrossRef]
  289. Oke, T.R. Canyon Geometry and the Nocturnal Urban Heat Island: Comparison of Scale Model and Field Observations. J. Clim. 1981, 1, 237–254. [Google Scholar] [CrossRef]
  290. Li, Y.; Schubert, S.; Kropp, J.P.; Rybski, D. On the Influence of Density and Morphology on the Urban Heat Island Intensity. Nat. Commun. 2020, 11, 2647. [Google Scholar] [CrossRef]
  291. Dirksen, M.; Ronda, R.J.; Theeuwes, N.E.; Pagani, G.A. Sky View Factor Calculations and Its Application in Urban Heat Island Studies. Urban Clim. 2019, 30, 100498. [Google Scholar] [CrossRef]
  292. Marciotto, E.R.; Oliveira, A.P.; Hanna, S.R. Modeling Study of the Aspect Ratio Influence on Urban Canopy Energy Fluxes with a Modified Wall-Canyon Energy Budget Scheme. Build. Environ. 2010, 45, 2497–2505. [Google Scholar] [CrossRef]
  293. Ahmad, K.; Khare, M.; Chaudhry, K.K. Wind Tunnel Simulation Studies on Dispersion at Urban Street Canyons and Intersections—A Review. J. Wind Eng. Ind. Aerodyn. 2005, 93, 697–717. [Google Scholar] [CrossRef]
  294. Liu, C.-H.; Leung, D.Y.C.; Barth, M. On the Prediction of Air and Pollutant Exchange Rates in Street Canyons of Different Aspect Ratios Using Large-Eddy Simulation. Atmos. Environ. 2005, 39, 1567–1574. [Google Scholar] [CrossRef]
  295. Georgakis, C.; Santamouris, M. Experimental Investigation of Air Flow and Temperature Distribution in Deep Urban Canyons for Natural Ventilation Purposes. Energy Build. 2006, 38, 367–376. [Google Scholar] [CrossRef]
  296. Swilling, M.; Annecke, E. Building Sustainable Neighbourhoods in South Africa: Learning from the Lynedoch Case. Environ. Urban. 2006, 18, 315–332. [Google Scholar] [CrossRef]
  297. Mohsin, M.M.; Beach, T.; Kwan, A. Pulbic Perceptions of Urban Sustainable Challenges in Developing Countries; WIT Press: Bristol, UK, 2017; pp. 131–140. [Google Scholar]
  298. John, R. Flooding in Informal Settlements: Potentials and Limits for Household Adaptation in Dar Es Salaam City, Tanzania. Am. J. Clim. Chang. 2020, 9, 68–86. [Google Scholar] [CrossRef]
  299. Wang, H.; Ou, X.; Zhang, X. Mode, Technology, Energy Consumption, and Resulting CO2 Emissions in China’s Transport Sector up to 2050. Energy Policy 2017, 109, 719–733. [Google Scholar] [CrossRef]
  300. Alshehry, A.S.; Belloumi, M. Study of the Environmental Kuznets Curve for Transport Carbon Dioxide Emissions in Saudi Arabia. Renew. Sustain. Energy Rev. 2017, 75, 1339–1347. [Google Scholar] [CrossRef]
  301. GhaffarianHoseini, A.; Tookey, J.; GhaffarianHoseini, A.; Naismith, N.; Bamidele Rotimi, J.O. Integrating Alternative Technologies to Improve Built Environment Sustainability in Africa: Nexus of Energy and Water. Smart Sustain. Built Environ. 2016, 5, 193–211. [Google Scholar] [CrossRef]
  302. Almulhim, A.I.; Bibri, S.E.; Sharifi, A.; Ahmad, S.; Almatar, K.M. Emerging Trends and Knowledge Structures of Urbanization and Environmental Sustainability: A Regional Perspective. Sustainability 2022, 14, 13195. [Google Scholar] [CrossRef]
  303. Sudhakara Reddy, B.; Balachandra, P. Urban Mobility: A Comparative Analysis of Megacities of India. Transp. Policy 2012, 21, 152–164. [Google Scholar] [CrossRef]
  304. Hannan, S.; Sutherland, C. Mega-Projects and Sustainability in Durban, South Africa: Convergent or Divergent Agendas? Habitat Int. 2015, 45, 205–212. [Google Scholar] [CrossRef]
  305. Buyana, K.; Byarugaba, D.; Sseviiri, H.; Nsangi, G.; Kasaija, P. Experimentation in an African Neighborhood: Reflections for Transitions to Sustainable Energy in Cities. Urban Forum 2019, 30, 191–204. [Google Scholar] [CrossRef]
  306. Patel, Z.; Greyling, S.; Simon, D.; Arfvidsson, H.; Moodley, N.; Primo, N.; Wright, C. Local Responses to Global Sustainability Agendas: Learning from Experimenting with the Urban Sustainable Development Goal in Cape Town. Sustain. Sci. 2017, 12, 785–797. [Google Scholar] [CrossRef] [PubMed]
  307. Pieterse, D.E.; Parnell, S. Africa’s Urban Revolution; Bloomsbury Publishing: London, UK, 2014; ISBN 978-1-78032-522-4. [Google Scholar]
  308. Huchzermeyer, M. Cities with “Slums”: From Informal Settlement Eradication to a Right to the City in Africa; UCT Press: Cape Town, South Africa, 2011; ISBN 978-1-919895-39-0. [Google Scholar]
  309. Pretty, J.; Toulmin, C.; Williams, S. Sustainable Intensification in African Agriculture. Int. J. Agric. Sustain. 2011, 9, 5–24. [Google Scholar] [CrossRef]
  310. Jacobs, J. The Death and Life of Great American Cities; Reissue edition; Vintage: New York, NY, USA, 1992; ISBN 978-0-679-74195-4. [Google Scholar]
  311. Monteiro, J.; Carrilho, A.C.; Sousa, N.; de Oliveira, L.K.; Natividade-Jesus, E.; Coutinho-Rodrigues, J. Do We Live Where It Is Pleasant?. Correlates of Perceived Pleasantness with Socioeconomic Variables. Land 2023, 12, 878. [Google Scholar] [CrossRef]
  312. Monteiro, J.; Sousa, N.; Pais, F.; Coutinho-Rodrigues, J.; Natividade-Jesus, E. Planning Cities for Pandemics: Review of Urban and Transport Planning Lessons from COVID-19. Proc. Inst. Civ. Eng.-Munic. Eng. 2023, 176, 125–138. [Google Scholar] [CrossRef]
  313. Amado, M.; Poggi, F.; Ribeiro Amado, A.; Breu, S. E-City Web Platform: A Tool for Energy Efficiency at Urban Level. Energies 2018, 11, 1857. [Google Scholar] [CrossRef]
  314. Pais, F.; Monteiro, J.; Sousa, N.; Coutinho-Rodrigues, J.; Natividade-Jesus, E. A Multicriteria Methodology for Maintenance Planning of Cycling Infrastructure. Proc. Inst. Civ. Eng.-Eng. Sustain. 2022, 175, 248–264. [Google Scholar] [CrossRef]
  315. Moreno, C.; Allam, Z.; Chabaud, D.; Gall, C.; Pratlong, F. Introducing the “15-Minute City”: Sustainability, Resilience and Place Identity in Future Post-Pandemic Cities. Smart Cities 2021, 4, 93–111. [Google Scholar] [CrossRef]
  316. Liu, X.; Huang, B.; Li, R.; Wang, J. Characterizing the Complex Influence of the Urban Built Environment on the Dynamic Population Distribution of Shenzhen, China, Using Geographically and Temporally Weighted Regression. Environ. Plan. B Urban Anal. City Sci. 2021, 48, 1445–1462. [Google Scholar] [CrossRef]
  317. Mele, C.; McLeskey, M.H. Pro-Growth Urban Politics and the Inner Workings of Public-Private Partnerships. In The Routledge Handbook on Spaces of Urban Politics; Routledge: London, UK, 2018; ISBN 978-1-315-71246-8. [Google Scholar]
Figure 1. Summary of topics addressed in this review.
Figure 1. Summary of topics addressed in this review.
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Figure 2. Towards sustainable urban planning: relations between urban form, transport systems, and decision-making for new city concepts.
Figure 2. Towards sustainable urban planning: relations between urban form, transport systems, and decision-making for new city concepts.
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MDPI and ACS Style

Monteiro, J.; Sousa, N.; Coutinho-Rodrigues, J.; Natividade-Jesus, E. Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review. Energies 2024, 17, 409. https://doi.org/10.3390/en17020409

AMA Style

Monteiro J, Sousa N, Coutinho-Rodrigues J, Natividade-Jesus E. Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review. Energies. 2024; 17(2):409. https://doi.org/10.3390/en17020409

Chicago/Turabian Style

Monteiro, João, Nuno Sousa, João Coutinho-Rodrigues, and Eduardo Natividade-Jesus. 2024. "Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review" Energies 17, no. 2: 409. https://doi.org/10.3390/en17020409

APA Style

Monteiro, J., Sousa, N., Coutinho-Rodrigues, J., & Natividade-Jesus, E. (2024). Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review. Energies, 17(2), 409. https://doi.org/10.3390/en17020409

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