Abstract Heat pumps (HPs) have emerged as a key technology for reducing energy use and greenhouse gas emissions. This study evaluates the potential switch to air-to-air HPs (AAHPs) in Toulouse, ...France, where conventional space heating is split between electric and gas sources. In this context, we find that AAHPs reduce heating energy consumption by 57% to 76%, with electric heating energy consumption decreasing by 6% to 47%, resulting in virtually no local heating-related CO 2 emissions. We observe a slight reduction in near-surface air temperature of up to 0.5 °C during cold spells, attributable to a reduction in sensible heat flux, which is unlikely to compromise AAHPs operational efficiency. While Toulouse’s heating energy mix facilitates large energy savings, electric energy consumption may increase in cities where gas or other fossil fuel sources prevail. Furthermore, as AAHPs efficiency varies with internal and external conditions, their impact on the electrical grid is more complex than conventional heating systems. The results underscore the importance of matching heating system transitions with sustainable electricity generation to maximize environmental benefits. The study highlights the intricate balance between technological advancements in heating and their broader environmental and policy implications, offering key insights for urban energy policy and sustainability efforts.
Regional climate models provide climate projections on a horizontal resolution in the order of 10 km. This is too coarse to sufficiently simulate urban climate related phenomena such as the urban ...heat island (UHI). Therefore, regional climate projections need to be downscaled. A statistical-dynamical method for the UHI was developed and applied to provide urban climate results at a high resolution with little computational costs. For the downscaling, weather situations relevant for the UHI are determined. This is done by combining objective weather pattern classification based on a k-means cluster analysis of ERA-40 reanalysis data and a regression-based statistical model of the observed UHI of Hamburg. The resulting days for each weather pattern are simulated with the mesoscale meteorological model METRAS at 1 km horizontal resolution. To obtain the average UHI for a climate period, the mesoscale model results are statistically recombined weighted by the frequency of the corresponding weather patterns. This is done for present-day climate (1971–2000) using reanalysis data to yield the current climate UHI. For the future climate periods 2036–2065 and 2070–2099 the results of regional climate projections are employed. Results are presented for Hamburg (Germany). The present day UHI pattern is well reproduced compared to temperature data based on floristic mapping data. The magnitude of the early night-time UHI is underestimated when compared to observed minimum temperature differences. The future UHI pattern does only slightly change towards the end of the 21st century based on A1B scenario results of the RCMs REMO and CLM. However, for CLM the number of days with high UHI intensities significantly increases mainly due to a decrease in near-surface relative humidity.
In this study we produce two urban development scenarios estimating potential urban sprawl and optimized development concerning building construction, and we simulate their influence on air ...temperature, surface temperatures and human thermal comfort. We select two heat waves representative for present and future conditions of the mid 21st century and simulations are run with the Town Energy Balance Model (TEB) coupled online and offline to the Weather Research and Forecasting Model (WRF). Global and regional climate change under the RCP8.5 scenario causes an increase of daily maximum air temperature in Vienna by 7 K. The daily minimum air temperature will increase by 2–4 K. Changes caused by urban growth or densification mainly affect air temperature and human thermal comfort locally where new urbanisation takes place and does not occur significantly in the central districts. A combination of near zero-energy standards and increasing albedo of building materials on the city scale accomplishes a maximum reduction of urban canyon temperature achieved by changes in urban parameters of 0.9 K for the minima and 0.2 K for the maxima. Local scale changes of different adaptation measures show that insulation of buildings alone increases the maximum wall surface temperatures by more than 10 K or the maximum mean radiant temperature (MRT) in the canyon by 5 K. Therefore, measures to reduce MRT within the urban canyons like tree shade are needed to complement the proposed measures. This study concludes that the rising air temperatures expected by climate change puts an unprecedented heat burden on Viennese inhabitants, which cannot easily be reduced by measures concerning buildings within the city itself. Additionally, measures such as planting trees to provide shade, regional water sensitive planning and global reduction of greenhouse gas emissions in order to reduce temperature extremes are required.
In the context of climate change, the reduction of greenhouse gas emissions is a global concern. Recent publications estimate that 30–40% of total anthropogenic greenhouse gases are directly emitted ...by urban areas. This paper focuses on CO2, which is the main anthropogenic greenhouse gas, and presents an implementation of CO2 flux modelling in urban areas within the urban canopy model Town Energy Balance (TEB). Highly weather-dependent contributors to CO2 fluxes (buildings and vegetation) are explicitly modelled by TEB using the Building Energy Model (BEM) for buildings and Interactions between Soil, Biosphere and Atmosphere (ISBA) for urban vegetation. This approach allows the impacts of the urban microclimate on CO2 fluxes to be simulated. Non-weather-dependent contributors (traffic and human respiration) are simulated using simpler approaches. A sensitivity study applied to the centre of Toulouse, France, highlights the relevance of detailed input data related to traffic, building use and human behaviour to simulate accurate CO2 fluxes. The results show that traffic (48.5%) and buildings (42%) are the main contributors to the annual mean CO2 flux. A comparison of the model results with independent eddy-covariance flux data shows good agreement with a root mean square error of 15.3 μmol m−2 s−1 and demonstrates that the model is able to reproduce seasonally averaged daily cycles of CO2 fluxes. In future studies, this model can be used to quantify the impacts on CO2 fluxes of different urban development scenarios such as urban expansion, changes in urban form, changes in practices related to the heating of buildings or urban greening strategies.
This article presents a dataset of spatial nocturnal Urban Heat Island (UHI) intensities for 45 French urban agglomerations, at a horizontal resolution of 250 m. The urban influence on air ...temperature at 2 m above ground level was obtained by coupling the mesoscale atmospheric model Meso-NH with the land surface model SURFEX-TEB. For each agglomeration, two specific local weather situations that favour the development of a strong UHI in summer are simulated and described in a specfic sheet. Simulation outputs have been postprocessed to 1) identify the time of day when the UHI is the most developed, 2) to merge information from both meteorological situations in order to obtain one synthetic UHI map and 3) a geographical analysis that allows to classify each city among five spatial UHI classes (Concentrated Very High Intensity; Concentrated High Intensity; Limited Intensity; Dispersed High Intensity; and Dispersed Cool Zones). This dataset can therefore be used for several purposes, from the analysis at the scale of a city to the comparison of the urban agglomerations among them.
The urban climatic map (UCMap) is an urban climate information tool for planning purpose commonly used in German-speaking countries while local climate zone (LCZ) scheme is developed to link the ...characteristics urban climate and urban morphology at the city level world widely. These two frameworks differ with each other on the aspect of data sources, classification standards, and planning implementation. This study explores the potential of integrating these two complementary frameworks to identify problematic hot spots and propose some generic urban planning recommendations according to current urban climate standards. To address this issue, the Toulouse Metropole area is taken as a case study; a hybrid Climatope-LCZ map is derived by synthetizing the classification of climatopes, based on the German standard (VDI 3787-Part 1), and LCZs at equivalent spatial positions. Furthermore, the simulated meteorological data about wind and thermal environments of Toulouse Metropole during typical summer season are introduced as evidence for analyzing the mutual benefits on urban climate study and application. According to the results, both the heterogeneous urban geometric characteristics and urban climatic issues within a climatope are well identified spatially by the corresponding composition of LCZ. Likewise, the differences of thermal stress between climatopes but in the same LCZ are also clearly illustrated. Lastly, a list of urban climatic planning recommendations for LCZs is proposed followed by the guidelines in VDI 3787-Part 1. This study proves that hybrid Climatope-LCZ map offers more detailed urban climate information to planners or decision-makers than classic urban climate map framework.
We investigate heat waves defined as periods of at least 3 consecutive days of extremely high daily maximum temperature affecting at least 30 % of western Europe. This definition has been chosen to ...select heat waves that might impact western European electricity supply. Even though not all such heat waves threaten it, the definition allows to identify a sufficient number of events, the strongest being potentially harmful. The heat waves are characterised by their duration, spatial extent, intensity and severity. The heat wave characteristics are calculated for historical and future climate based on results of climate model simulations conducted during the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). The uncertainty of future anthropogenic forcing is taken into account by analysing results for the Representative Concentration Pathway scenarios RCP2.6, RCP4.5 and RCP8.5. The historical simulations are evaluated against the EOBS gridded station data. The CMIP5 ensemble median captures well the observed mean heat wave characteristics. However, no model simulates a heat wave as severe as observed during August 2003. Under future climate conditions, the heat waves become more frequent and have higher mean duration, extent and intensity. The ensemble spread is larger than the scenario uncertainty. The shift of the temperature distribution is more important for the increase of the cumulative heat wave severity than the broadening of the temperature distribution. However, the broadening leads to an amplification of the cumulative heat wave severity by a factor of 1.7 for RCP4.5 and 1.5 for RCP8.5.
Wind farms impact the local meteorology by taking up kinetic energy from the wind field and by creating a large wake. The wake influences mean flow, turbulent fluxes and vertical mixing. In the ...present study, the influences of large offshore wind farms on the local summer climate are investigated by employing the mesoscale numerical model METRAS with and without wind farm scenarios. For this purpose, a parametrisation for wind turbines is implemented in METRAS. Simulations are done for a domain covering the northern part of Germany with focus on the urban summer climate of Hamburg. A statistical-dynamical downscaling is applied using a skill score to determine the required number of days to simulate the climate and the influence of large wind farms situated in the German Bight, about 100 km away from Hamburg.Depending on the weather situation, the impact of large offshore wind farms varies from nearly no influence up to cloud cover changes over land. The decrease in the wind speed is most pronounced in the local areas in and around the wind farms. Inside the wind farms, the sensible heat flux is reduced. This results in cooling of the climate summer mean for a large area in the northern part of Germany. Due to smaller momentum fluxes the latent heat flux is also reduced. Therefore, the specific humidity is lower but because of the cooling, the relative humidity has no clear signal. The changes in temperature and relative humidity are more wide spread than the decrease of wind speed. Hamburg is located in the margins of the influenced region. Even if the influences are small, the urban effects of Hamburg become more relevant than in the present and the off-shore wind farms slightly intensify the summer urban heat island.
Abstract High-resolution urban climate projections are needed for local decision-making on climate change adaptation. Regional climate models have resolutions that are too coarse to simulate the ...urban climate at such resolutions. A novel statistical-dynamical downscaling approach (SDD) is used here to downscale the EURO-CORDEX ensemble to a resolution of 1 km while adding the effect of the city of Paris (France) on air temperature. The downscaled atmospheric fields are then used to drive the Town Energy Balance urban canopy model to produce high-resolution temperature maps over the period 1970-2099, while maintaining the city’s land cover in its present state. The different steps of the SDD are evaluated for the summer season. The regional climate models simulate minimum(maximum) temperatures (TN/TX) that are too high(low). After correction and downscaling, the urban simulations inherit some of these biases, but give satisfactory results for summer urban heat islands (UHI), with average biases of −0.6 K at night and +0.3 K during the day. Changes in future summer temperatures are then studied for two greenhouse gas emission scenarios, RCP4.5 and RCP8.5. Outside the city, the simulations project average increases of 4.1 K and 4.8 K for TN and TX for RCP8.5. In the city, warming is lower, resulting in a decrease in UHIs of −0.19 K at night (from 2.1 K to 1.9 K) and −0.16 K during the day. The changes in UHIs are explained by higher rates of warming in rural temperatures due to lower summer precipitation and soil water content, and are partially offset by increased ground heat storage in the city.
Taking into account meteorological data in urban planning increases in relevance in the context of changing climate and enhanced urbanisation. The present article focusses on the nocturnal urban heat ...island intensity (UHII) simulated with a physically based atmospheric model for >200,000 Reference Spatial Units (RSU), which correspond to building patches delimited by roads or water bodies in 42 French urban agglomerations. First are investigated the statistical relationships between the UHII and six predictors: Local Climate Zone, distance to the agglomeration centre, population, distance to the coast, climatic region, and elevation differences. It is found that the maximum UHII of an agglomeration increases proportional to the logarithm of its population, decreases for cities closer than 10 km to the coast, and is shaped by the regional climate. Secondly, a Random Forest model and a regression-based model are developed to predict the UHII based on the predictors. The advantage of the regression-based model is that it is easier to understand than the black box Random Forest model. The Random Forest model is able to predict the UHII with <0.5 K absolute error for 54% of the RSU. The regression-based model performs slightly worse than the Random Forest model and predicts the UHII with <0.5 K absolute error for 52% of the RSU. A future challenge is to conduct a similar investigation at global scale, which is to date limited by the availability of a robust description of urban form and functioning.
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•Physically-based simulation of the urban heat island (UHI) for 42 French cities•Quantification of the relationships between the UHI and geographical factors•Regression-based (RB) and Random Forest (RF) model developed to predict the UHI•RB and RF models predict the UHI with <0.5 K absolute error for about 50% of the building blocks.•The RB model is easier to transfer to practitioners than the black box RF.
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