Les villes et le climat : Bâtiments et urbanisme

Urban policies and city inhabitants behaviors are at the forefront of global environmental issues. We live indeed in an urbanizing world, and cities are responsible for approximately two third of global energy consumptions. How buildings are built, and how cities are organized are both key drivers of greenhouse gases emissions. Making them coherent with environmental constraints often lead to co-benefits with other urban issues such as economic competitiveness or social inclusiveness. This explains why cities are globally active concerning climate change, even if much still needs to be done

Les villes et le climat : Bâtiments et urbanisme

Urban policies and city inhabitants behaviors are at the forefront of global environmental issues. We live indeed in an urbanizing world, and cities are responsible for approximately two third of global energy consumptions. How buildings are built, and how cities are organized are both key drivers of greenhouse gases emissions. Making them coherent with environmental constraints often lead to co-benefits with other urban issues such as economic competitiveness or social inclusiveness. This explains why cities are globally active concerning climate change, even if much still needs to be done

Cities: the core of climate change mitigation

Cities, the core of the global climate change mitigation and strategic low-carbon development, are shelters to more than half of the world population and responsible for three quarters of global energy consumption and greenhouse gas (GHG). This special volume (SV) provides a platform that promotes multi- and inter- disciplinary analyses and discussions on the climate change mitigation for cities. All papers are divided into four themes, including GHG emission inventory and accounting, climate change and urban sectors, climate change and sustainable development, and strategies and mitigation action plans. First, this SV provides methods for constructing emission inventory from both production and consumption perspectives. These methods are useful to improve the comprehensiveness and accuracy of carbon accounting for international cities. Second, the climate change affects urban sectors from various aspects; simultaneously, GHG emissions caused by activities in urban sectors affect the climate system. This SV focuses on mitigation policies and assessment of energy, transport, construction, and service sectors. Third, climate change mitigation of cities is closely connected to urban sustainable development. This SV explores the relationships between climate change mitigation with urbanization, ecosystems, air pollution, and extreme events. Fourth, climate change mitigation policies can be divided into two categories: quantity-based mechanism (e.g., carbon emission trading) and price-based mechanism (e.g., carbon tax). This SV provides experiences of local climate change mitigation all over the world and proposes the city-to-city cooperation on climate change mitigation

Will climate mitigation ambitions lead to carbon neutrality? An analysis of the local-level plans of 327 cities in the EU

Cities across the globe recognise their role in climate mitigation and are acting to reduce carbon emissions. Knowing whether cities set ambitious climate and energy targets is critical for determining their contribution towards the global 1.5 °C target, partly because it helps to identify areas where further action is necessary. This paper presents a comparative analysis of the mitigation targets of 327 European cities, as declared in their local climate plans. The sample encompasses over 25% of the EU population and includes cities of all sizes across all Member States, plus the UK. The study analyses whether the type of plan, city size, membership of climate networks, and its regional location are associated with different levels of mitigation ambition. Results reveal that 78% of the cities have a GHG emissions reduction target. However, with an average target of 47%, European cities are not on track to reach the Paris Agreement: they need to roughly double their ambitions and efforts. Some cities are ambitious, e.g. 25% of our sample (81) aim to reach carbon neutrality, with the earliest target date being 2020.90% of these cities are members of the Climate Alliance and 75% of the Covenant of Mayors. City size is the strongest predictor for carbon neutrality, whilst climate network(s) membership, combining adaptation and mitigation into a single strategy, and local motivation also play a role. The methods, data, results and analysis of this study can serve as a reference and baseline for tracking climate mitigation ambitions across European and global cities

Urban dynamics modelling : application to economics assessment of climate change

Parce qu'elles concentrent plus de la moitié de la population et l'essentiel de l'activité économique mondiales, les villes sont des acteurs majeurs des problématiques environnementales globales. Les politiques de transport, d'urbanisme et de logement sont ainsi reconnus comme des moyens nécessaires et efficaces d'action pour réduire les émissions ainsi que pour réduire la vulnérabilité aux impacts du changement climatique. Jusqu'à présent, malheureusement, il n'y a pas de consensus sur ce qui doit être fait, et encore moins sur comment le faire. Trois difficultés, au moins, expliquent cela. Tout d'abord, les politiques climatiques interagissent avec les autres objectifs des politiques urbaines, comme la compétitivité économique ou les problèmes sociaux, entrainant des synergies et des conflits. Ensuite, les inerties sont un facteur-clef à prendre en compte : les modifications structurelles des villes s'opèrent très lentement. Si l'on veut que les villes soient adaptées au climat de la fin du XXIème siècle, il est indispensable de commencer à agir dès maintenant. Enfin, les effets des politiques urbaines dépendent de nombreux facteurs exogènes, et inconnus au moment où la décision doit être prise : les changements démographiques, socio-économiques culturels politiques et technologiques vont jouer un rôle majeur. Ces trois difficultés ne sont cependant pas insurmontables, et nous illustrerons comment une modélisation intégrée peut permettre de répondre à une partie de ces problèmesBecause they are home to more than half of the world population, and because most of the world economic activity takes place within them, cities are at the forefront of global environmental issues. Land use planning, urban transport and housing policies are now recognized as major tools for the reduction of both greenhouse gases emissions and vulnerability to climate change impacts. So far, however, how to use these tools efficiently remains unclear. At least three main difficulties explain this, and play a key role in urban climate policies analysis. First, urban climate policies are also not developed or implemented in a vacuum; they interact with other policy goals, such as economic competitiveness or social issues, giving rise to both synergies and conflicts. Second, inertia is a key factor when designing optimal climate policies : structural modifications in cities occur slowly over a long time horizon. Some immediate actions are required if cities are to be adapted to a different climate or to help reduce greenhouse gases emissions within a few decades. Third, the evolution of a city depends on several external factors, on which local policy-makers do not generally have much influence : demographic, socio-economic, cultural, political and technological changes will play a major role. This uncertainty has to be taken into account, and climate policies have to be robust against future possible global evolutions is important. These three difficulties are not, however, impossible to overcome, and we will illustrate how integrated city modelling can help address these issue

Modélisation des dynamiques urbaines : application à l’analyse économique du changement climatique

Because they are home to more than half of the world population, and because most of the world economic activity takes place within them, cities are at the forefront of global environmental issues. Land use planning, urban transport and housing policies are now recognized as major tools for the reduction of both greenhouse gases emissions and vulnerability to climate change impacts. So far, however, how to use these tools efficiently remains unclear. At least three main difficulties explain this, and play a key role in urban climate policies analysis. First, urban climate policies are also not developed or implemented in a vacuum; they interact with other policy goals, such as economic competitiveness or social issues, giving rise to both synergies and conflicts. Second, inertia is a key factor when designing optimal climate policies : structural modifications in cities occur slowly over a long time horizon. Some immediate actions are required if cities are to be adapted to a different climate or to help reduce greenhouse gases emissions within a few decades. Third, the evolution of a city depends on several external factors, on which local policy-makers do not generally have much influence : demographic, socio-economic, cultural, political and technological changes will play a major role. This uncertainty has to be taken into account, and climate policies have to be robust against future possible global evolutions is important. These three difficulties are not, however, impossible to overcome, and we will illustrate how integrated city modelling can help address these issuesParce qu'elles concentrent plus de la moitié de la population et l'essentiel de l'activité économique mondiales, les villes sont des acteurs majeurs des problématiques environnementales globales. Les politiques de transport, d'urbanisme et de logement sont ainsi reconnus comme des moyens nécessaires et efficaces d'action pour réduire les émissions ainsi que pour réduire la vulnérabilité aux impacts du changement climatique. Jusqu'à présent, malheureusement, il n'y a pas de consensus sur ce qui doit être fait, et encore moins sur comment le faire. Trois difficultés, au moins, expliquent cela. Tout d'abord, les politiques climatiques interagissent avec les autres objectifs des politiques urbaines, comme la compétitivité économique ou les problèmes sociaux, entrainant des synergies et des conflits. Ensuite, les inerties sont un facteur-clef à prendre en compte : les modifications structurelles des villes s'opèrent très lentement. Si l'on veut que les villes soient adaptées au climat de la fin du XXIème siècle, il est indispensable de commencer à agir dès maintenant. Enfin, les effets des politiques urbaines dépendent de nombreux facteurs exogènes, et inconnus au moment où la décision doit être prise : les changements démographiques, socio-économiques culturels politiques et technologiques vont jouer un rôle majeur. Ces trois difficultés ne sont cependant pas insurmontables, et nous illustrerons comment une modélisation intégrée peut permettre de répondre à une partie de ces problème

A gridded dataset on densities, real estate prices, transport, and land use inside 192 worldwide urban areas

This work presents a gridded dataset on real estate and transportation in 192 worldwide urban areas, obtained from the Google Maps API and the web scraping of real estate websites. For each city of the sample, these data have been associated with the corresponding population density and land cover data, extracted from the GHS POP and ESA CCI data respectively, and aggregated on a 1 km resolution grid, allowing for an integrated analysis. This dataset is the first to include spatialized real estate and transportation data in a large sample of cities covering 800 million people in both developed and developing countries. These data can be used as inputs for urban modeling purposes, transport modeling, or between-city comparisons in urban forms and transportation networks, and allow further analyses on e.g. urban sprawl, access to transportation, or equity in housing prices and access to transportation

Une taxe carbone peut-elle rendre l’agglomération parisienne plus dense ?

L’agglomération parisienne peut être bien décrite par un modèle mono-centrique. A partir de ce modèle, nous étudions l’impact d’une taxe carbone de 100€/tonne de CO2, intégralement redistribuée aux ménages.La pression immobilière et la variation des loyers incitent les promoteurs immobiliers à augmenter la densité de l’agglomération, en construisant plus en centre-ville. La densification obtenue est cependant limitée, avec une réduction finale de la distance moyenne des ménages au centre de Paris d’au maximum 10 % (soit environ 1 700 m) par rapport à la situation initiale, et ce dans le cas extrême où l’on néglige de nombreux phénomènes comme le transfert modal ou le progrès technologique, qui limitent en pratique l’effet de la taxe. Ceci suggère qu’une taxe carbone seule n’aura pas grand effet sur cette distance moyenne : en vue d’agir sur cette dernière, la taxe ne doit pas être substituée aux autres mesures possibles, comme la taxe foncière différenciée, des investissements publics dans les transports et le bâti, ou la régulation et l’usage de plans d'occupation des sols par exemple

Pourquoi les villes continuent-elles à s’étendre ?

International audienceDespite the fact that urban sprawl has been studied since the early twentieth century, and although its environmental consequences are well documented, its regulation is notoriously ineffective. The causes: the imprecision of the usual definitions, the focus of public and scientific debates on large metropolises and developed countries, and the issues linked to the social acceptance of those policies.Bien que le phénomène d’étalement urbain ait été étudié depuis le début du xxesiècle, et que ses conséquences environnementales soient connues, les politiques publiques qui visent à le maîtriser sont notoirement inefficaces. L’imprécision des définitions généralement utilisées, la focalisation du débat public et scientifique sur les grandes métropoles et les pays développés, ou encore les enjeux liés à l’acceptabilité sociale des politiques en sont responsables

Simulations of urban heat island effect in Paris Region during various types of heatwaves, and in different adaptation scenarios

Content - These data present air temperature, in the shade, 2m above grounds in Paris Region (projection: RGF93/Lambert 93, EPSG:2154) at different times of the day, for various heat waves conditions, and in different prospective scenarios for the built-up evolution and adaptation actions implementations. - more information can be found here : https://www.umr-cnrm.fr/ville.climat/spip.php?rubrique45 Classification of the data - the first 5 letters (e.g. "CDFFA") present the prospective scenario - the 4 following letters (e.g. "HW34") present the type of heat wave - the following 2 letters (e.g. "D8") present the length of the heat wave (number of days after the beginning of the heat wave) - the final letters (e.g. H15) represent the time (UTC : one hour should be added for French time) of the day Prospective scenarios - the first letter is always C - the second letter represents the expansion scenario. They are presented here : Lemonsu, A., Viguié, V., Daniel, M., Masson, V., 2015. Vulnerability to heat waves: Impact of urban expansion scenarios on urban heat island and heat stress in Paris (France). Urban Climate 14, 586–605. - D stands for "dense development" - F for business as usual scenario ("fil de l'eau" in French) - V for a scenario with 10% more parks - the third letter represents the building evolution scenario - F stands for business as usual scenario - V for a scenario with more insulation and reflective roofs - the third letter represents AC use - F stands for strong AC use - M for moderate AC use - N for no AC use - the fourth letter represents vegetation watering - N stands for no watering - A for watering Heat waves - the figure (e.g. "34" in "HW34") represents the intensity class, in °C of the heat wave. It is more precisely the maximum daily temperature observed without the impact of the urban heat island effect. (Tmax=34, 38, 42, or 46°C). Other information - see the file "aggregated data.xls" for more information and data about energy consumption for AC, and averages of temperatures in the city over the entire day