CL3.2.1

An ever-growing portion of population lives in urban areas. Cities are expanding quickly and consequently, the urban heat island effect has become a major health concern to maintain city dwellers’ thermal comfort. For this reason, city planners want to access urban meteorological databases in local areas where specific attention is needed. With the growth of connected devices, it is possible to collect unusual but massive temperature measurements from people’s activities. In this article, we study temperatures measured by thermometers embedded in everyday personal cars. To assess the quality of such opportunistic data, we first detect factors deteriorating the measurement. After pre-processing, the measurement error is then estimated thanks to two weather station networks providing a local-scale reference through Dijon and Rennes cities, France. The overall aggregation of private car temperature measurements allows to estimate very precisely the urban heat island at a 200m resolution. We detect the cooling effect of parks in Rennes and Paris urban areas. In Barcelona and Dijon, we observe the impact of regional environments and the orographic effect on the urban heat island. With our method, similar maps can be made accessible to every interested city in western Europe to target critical areas and support urban planning decisions.

How to cite: Marques, E., Masson, V., Naveau, P., Mestre, O., Dubreuil, V., and Richard, Y.: Urban heat island estimation from crowdsensing thermometers embedded in personal cars, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1802, https://doi.org/10.5194/egusphere-egu22-1802, 2022.

Air pollution is a dramatic issue that grips the majority of densely populated cities in the world. It is nowadays quite evident that there is a relationship between air quality and some types of cancers (i.e. lung and bladder cancer), as reported by the International Agency for Research on Cancer (IARC 2012). Although the time spent commuting usually represents a small portion of a person's daily time (3-6%), it is responsible around for 21% of daily personal exposure and roughly 30% of the total inhaled dose (Dons et al. 2012). To gain information on this topic, we conducted an air quality measurement campaign (six weeks between November and December 2021) on three different routes within the metropolitan city of Lyon (France). These routes were chosen to be representative of different urban areas (e.g. city centre, periphery, vegetated areas). The measurements were taken two times for day (i.e. in the morning and the evening, in order to simulate the commuters round trip) using four different modes (walk, bike, car and public transport). Two different portable air quality sensors were used to measure the pollutants: the MONICA sensors (developed by ENEA, De Vito et al. 2021) that measure PM₁, PM_2.5, PM₁₀, NO₂, CO and O₃ and the AirBeam 2 sensors (provided by ATMO AURA) that measure only the particular matters. The objective of this study is twofold: from one side to assess the exposure choosing different modes of commuting and, from the other side, to evaluate how the influence of the meteorological-climatic variables (e.i. temperature, relative humidity, precipitation, wind direction, wind speed, cloud cover, solar radiation and atmospheric boundary layer stability/instability) affect the air quality. Preliminary results show that private car users are generally affected by lower levels of air pollution with respect to the other modes (as expected, Okokon et al. 2017), but this is strongly influenced by the type of ventilation used (internal or external air recirculation, open and closed windows). 

Reference

De Vito, S., Esposito, E., Massera, E., Formisano, F., Fattoruso, G., Ferlito, S., ... & Di Francia, G. (2021). Crowdsensing IoT Architecture for Pervasive Air Quality and Exposome Monitoring: Design, Development, Calibration, and Long-Term Validation. Sensors, 21(15), 5219.

Dons, E., Panis, L. I., Van Poppel, M., Theunis, J., & Wets, G. (2012). Personal exposure to black carbon in transport microenvironments. Atmospheric Environment, 55, 392-398.

IARC Working Group on the Evaluation of Carcinogenic Risks to Humans. (2012). Chemical agents and related occupations. IARC monographs on the evaluation of carcinogenic risks to humans, 100, 9–562.

Okokon, E. O., Yli-Tuomi, T., Turunen, A. W., Taimisto, P., Pennanen, A., Vouitsis, I., ... & Lanki, T. (2017). Particulates and noise exposure during bicycle, bus and car commuting: A study in three European cities. Environmental Research, 154, 181-189.

How to cite: Peruzzi, C., Ramel-Delobel, M., Coudon, T., Fervers, B., De Vito, S., Fattoruso, G., and Salizzoni, P.: Air pollution measurements during commuting in Lyon, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13150, https://doi.org/10.5194/egusphere-egu22-13150, 2022.

We present a novel method to model spatial maps of mean radiant temperature (T_mrt) in complex urban areas using a special type of fully convolutional networks - U-Net - for image to image processing. T_mrt is one of the driving factors of daytime human thermal comfort and underlies great spatial and temporal variabilities, especially in complex urban areas. Various micro scale (building-resolving) models exist to model T_mrt in urban settings. However, these models are computational expensive, albeit to varying degrees. This means, study area and time might be limited depending on spatial and temporal resolution. While this is sufficient for case studies where micro-level processes are modelled for different neighbourhoods in limited time periods, accurate calculations over a long time period are not possible (e.g. downscaling global climate projections). To overcome these computational drawbacks of physical models, we present a U-net approach for modelling T_mrt in complex urban areas.

U-Nets are special types of encoder-decoder networks and allow precise image to image processing. In this study, T_mrt (at 1.1 m a.g.l.) is modelled by SOLWEIG model for 62 areas (500 x 500 m²) and on 54 days for the city of Freiburg, Germany. Training data is sampled randomly after clustering. The spatial and temporal input of SOLWEIG are in turn used as input features for the U-Net. The U-Net is trained on 56 areas and on 45 days and tested on the remaining areas and days. In addition, data from a T_mrt measurement campaign is used to validate SOLWEIG and U-Net model output.

Results indicate that the proposed U-Net approach is capable to provide T_mrt in complex urban areas sufficiently. A correlation of > 0.9 and a MAE of 1.53°C between SOLWEIG and the U-Net is observed. Results show a higher MAE during day than night, which can be partly explained by the difference of absolute T_mrt values at day and night, but also by more complex prediction conditions during day: cloud cover and thus varying radiation, but also low sun angle in the morning / evening. In addition, computing times for T_mrt map predictions are significantly faster than physical models. 

How to cite: Briegel, F., Makansi, O., Brox, T., Matzarakis, A., and Christen, A.: Modelling mean radiant temperature in complex urban areas using a convolutional network approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11416, https://doi.org/10.5194/egusphere-egu22-11416, 2022.

Urban morphological attributes and surface properties can largely influence near-surface air temperatures. Unpacking such morpho-thermal relationships are of particular importance in hot urban desert (HUDs) cities given the already extreme thermal bioclimatic dynamics, urban-induced heating with rapid urbanization processes, and vulnerability of residents. Satellite-derived investigations may underestimate critical system dynamics of urban thermal stimuli found within sub-diurnal phenomena and sub-meter classifications. High resolution spatiotemporal measurements are therefore required to objectively assess latent magnitudes of heat mitigation and amelioration strategies. This study utilized the natural heterogeneity of morphometric predictors with fixed ground-based measurements in a representative neighborhood unit typology within Kuwait’s residential landscape to build a composite dataset of sub-hourly air temperature measurements with sub-meter morphological attributes. The presentation will share initial findings of the study and preliminary analysis of the drivers of heating/cooling rate’s association to defined morphological factors.

How to cite: AlKhaled, S.: Urban Morphometrics and Microclimate Responses in a Typical Residential Neighborhood of a Hot Urban Desert City, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3355, https://doi.org/10.5194/egusphere-egu22-3355, 2022.

Research quantifying urban-rural differences in humidity, the so called urban dry or moisture islands (UDIs, UMIs), has been mostly confined to case-studies of single cities or regions. An analysis of the typical diurnal and seasonal patterns of UDIs at larger scale is still missing even though changes in humidity can impact human well-being, building energy consumption, and urban ecology. In this study, we use a large data set (1089 stations) of globally distributed near surface air temperature and humidity measurements to quantify the typical diurnal and seasonal patterns of UDIs, which developed due to rapid urbanization in many parts of the world, using a time for space substitution. We distinguish between “relative” and “absolute” UDIs quantified as the urban-rural difference in relative and actual humidity measurements, respectively, to account for differences in their diurnal and seasonal patterns.

We find that absolute UDI is largest during daytime with the highest humidity decrease in the late afternoon hours, while relative UDI is generally largest at night. Peak relative humidity decrease occurs during the late evening hours with magnitudes of around -10 to -11% between 20-00 local time in summer. Both relative and absolute UDI are largest during the warm season. Separating the contribution of actual humidity decrease and change in temperature to the formation of relative UDI, we find that relative UDI is mostly caused by absolute UDI during daytime and by temperature, i.e., urban heat island (UHI), during nighttime. The quantification of UDIs, as presented here, is crucial for subsequent impact analyses of urbanization on outdoor thermal comfort, urban ecology, and building energy consumption.

How to cite: Meili, N., Paschalis, A., Manoli, G., and Fatichi, S.: Diurnal and Seasonal Patterns of Urban Dry Islands Quantified with a Global Dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2105, https://doi.org/10.5194/egusphere-egu22-2105, 2022.

There is a scientific consensus on the need for spatially detailed information on urban landscapes at a global scale to support a range of environmental services, as cities are acknowledged as places of: intense resource consumption and waste generation and foci of population and infrastructure that are exposed to multiple hazards of natural and anthropogenic origin. In the face of climate change, urban data is also required for future urbanisation pathways and urban design strategies, in order to “lock in” long-term resilience and sustainability, protecting cities from future decisions that could undermine their adaptability. Eventually, these global form-based, contextually specific urban planning and urban design strategies are the ultimate guarantors of successful life cycle costs, payback, and liveability. Moreover, these strategies are needed to identify the relevant data for planning and climate on neighbourhood, city and global scales, and to become part of a basic infrastructure to support a host of studies on exposure to environmental hazards, energy demand, climate adaptation and mitigation solutions and human health, as examples. 

Therefore, a more holistic urban landscape description is required, that goes beyond the urban mask and that enables the assessment of the spatial impact of urban planning decisions that will alter urban canopy parameters (UCPs) and their climate outcome. 

The global Local Climate Zone (LCZ) map presented here serves this purpose, as the LCZ typology is the only universal classification that can distinguish urban surfaces on a holistic basis, accounting for the typical combination of micro-scale land-covers and associated physical properties, all being the consequence of historic urbanisation patterns that reflect local terrain, culture, economy, etc. The 100m resolution global LCZ map is generated by feeding an unprecedented amount of labelled training areas (partly sourced from the LCZ Generator - https://lcz-generator.rub.de/) and earth observation imagery into lightweight random forest models. Its quality is assessed using the default bootstrap-based cross validation alongside a thematic benchmark for 150 selected functional urban areas using independent global and open- source data on surface cover, surface imperviousness, anthropogenic heat and building height.

Complementing the single cities‘ LCZ maps accessible via the LCZ Generator, the global LCZ map for the first time reveals the world‘s intra-urban heterogeneity heterogeinity. In addition, as each LCZ type is associated with generic numerical descriptions of key UCPs, parameters critical to model atmospheric responses to urbanisation, the availability of this globally consistent and climate-relevant urban description is an essential prerequisite for developing fit-for-purpose integrated climate-sensitive urban planning policies.

How to cite: Kittner, J., Demuzere, M., Mills, G., Moede, C., Niyogi, D., van Vliet, J., and Bechtel, B.: A global Local Climate Zone map: revealing intra-urban heterogeneity., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6213, https://doi.org/10.5194/egusphere-egu22-6213, 2022.

To prepare future urban climate modelling and numerical weather prediction at the hectometer scale in cities with heterogeneous morphology and high-rise buildings, urban climate models have to be coupled at multiple levels with atmospheric models. Vertical profiles of the building drag coefficient and the urban mixing length need to be specified to parametrize the effect of the buildings on the flow. Building-resolving micro-scale simulations can be employed to derive these quantities.

In the present contribution, micro-scale large-eddy simulations of eleven Local Climate Zone (LCZ) based urban morphologies with various building plan and frontal density are used to provide velocity, sectional drag coefficient and mixing length reference vertical profiles for the urban environment. The micro-scale simulations, which are of 1-m resolution in both horizontal and vertical directions, are performed with the MesoNH meteorological research model. This model represents explicitly the obstacles with the Immersed Boundary Method and accounts for the impact of the large-scale turbulence structures on the urban canopy thanks to dynamical downscaling and embedded numerical domains using the grid nesting method. The micro-scale results show that, contrary to traditional assumptions, the velocity profile is generally not exponential and the mixing length is not constant in the urban canopy. This is in agreement with more recent research. The results also show that the building frontal density seems to be a key parameter for the shape of the velocity profile, within and directly above the urban canopy.

The sectional drag and mixing length profiles are then used to propose a new LCZ-based parametrization for the wind dynamics in the urban environment when using the Meso-NH model at the hectometer scale. The results show that the proposed parametrization is more efficient than the current one, consisting in a constant drag coefficient and no specific modification of the turbulent mixing length scale in the urban environment. These results open new perspectives to better parametrize the dynamic effects of real urban areas at the hectometer scale.

How to cite: Nagel, T., Schoetter, R., Bourgin, V., Masson, V., and Onofri, E.: Toward a Local Climate Zone-based drag and mixing length parametrization for the urban environment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1513, https://doi.org/10.5194/egusphere-egu22-1513, 2022.

Urban schemes in weather and climate models often characterise urban structures in a grid cell using the mean building height and street width. This does not capture the sub-grid vertical variability that impacts fluxes. The vertical distribution of wall area and building heights are ideally required but are often unavailable in cities globally. In this work, building footprint and height data from six cities are used to parameterise the geometry with varying levels of detail of input data.

We conclude the vertical distribution of buildings can be parameterised using a function of mean building height and surface building plan area. Comparisons of the parameterised building plan area fraction with height to ‘true’ data (2 km x 2 km resolution) show 90% of the profiles have bias errors (BE) of < 0.03 (‘true’ values are: 0.05 – 0.55).

Building horizontal size (or effective building diameter, D) has a six-city mean of ~21 m. As D is impacted by normalised building edge length and building plan area, we use it to parameterise building edge length. The derived D parameterisations have normalised BE (nBE) < 16%, but without total wall area as an input the nBE increases to 26%.

The combined parameterisations are used with the radiative transfer model SPARTACUS-Urban to simulate total absorption of shortwave (SW) radiation and effective SW albedo. The latter is impacted 2-10% (cf. simulations using ‘true’ data). Larger errors occur when simulating  within-canyon absorption fluxes. Larger errors also occur when fewer morphology inputs are used, with total wall area having the most benefit.

We conclude urban vertical variability can be acceptably characterised for numerical weather prediction using three parameters: surface building plan area, mean building height, and effective building diameter.

How to cite: Stretton, M., Hogan, R., and Grimmond, S.: Characterising the vertical structure of buildings for use in atmospheric models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11468, https://doi.org/10.5194/egusphere-egu22-11468, 2022.

This study is devoted to analysis of Urban Heat Island (UHI) and Urban Pollution Island (UPI) effects in Minsk, Belarus by means of high-resolution atmospheric urban modelling. We present first results of our implementation of the WRF-BEP+BEM modelling system for Minsk with two different approaches to urban morphology: one involving the Local Climate Zones (LCZ) methodology and the other being based on direct representation of urban parameters on the model grid. For that purpose, we combine satellite remote sensing data with geoinformation systems (GIS), centralized city planning databases and Open Street Maps (OSM) vector data to implement description of land use / land cover for Minsk urban territory and the surrounding area along with a representation of buildings data and other urban parameters with a level of detail necessary for high resolution modelling (500 m, 300 m and 100 m grids). Different configurations of the WRF-BEP+BEM modelling system are then used to perform a series of  simulations involving various meteorological conditions over Minsk, Belarus to investigate manifestations of the UHI and UPI effects. In modelling results validation special emphasis is made on analysis of surface temperature parameters and near-surface atmospheric circulation, the latter being important for atmospheric pollutants transport in the urban area. For validation, we use observational data of surface temperature, wind fields and atmospheric pollution from ground-based measurements (including both regular meteorological stations and crowdsourced data from citizen weather stations) and satellite remote sensing for Minsk urban area and the surrounding region. Analysis results reveal the degree of applicability of each approach to urban morphology representation in WRF-BEP+BEM for Minsk and similar urban territories on high-resolution modelling grids.

How to cite: Barodka, S., Schlender, T., Darozhka, N., Bruchkouski, I., Baravik, A., Alieva, M., Zhukovskaya, N., Yarash, Y., Birukou, M., and Tabalchuk, T.: High-resolution WRF-BEP+BEM modelling of urban heat island and urban pollution island effects for Minsk, Belarus with different approaches to urban morphology representation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12883, https://doi.org/10.5194/egusphere-egu22-12883, 2022.

The application of nature-based solutions in urban areas to mitigate the harmful effects of urban overheating and to make cities more resilient to heat waves has gained the attention of city planners and researchers in the last decades. Street trees are an important driver of street microclimate through shadowing and transpiration cooling, which are key components in the improvements of thermal comfort. While several observational campaigns have been carried out in low and medium-density residential areas, little research has been focused in highly-compact city centres, where the impact of built elements on the local climate is expected to be stronger. In this context, Urban canopy models (UCM) with integrated trees are useful tools because they represent the impact of street trees on neighbourhood-scale climate, resolving the interactions between buildings, trees and the atmosphere. These models enable the assessment of outdoor human thermal exposure for diverse urban morphologies and allow the evaluation of greening scenarios.

In this study, we present the results of a micrometeorological measurement campaign inside the city of Barcelona (Spain) for two cloud-free summer days. Vehicle transects were completed along two parallel streets with different tree densities but identical street geometry, recording upward and downward radiation fluxes, air temperature and humidity. Assessment of urban tree impacts on microclimate is supplemented by meteorological simulations using the multi-layer UCM Building Effect Parameterization with Trees (BEP-Tree), which considers the vertical variation of the combined impacts of vegetation and building on urban canopy layer climate. Comparing observed pedestrian level air temperatures between the two canyons, we can see that the impact of tree densities varies with the regional weather, with air temperatures up to 2.7 ^oC higher in the street with low tree density compared to the one with denser trees for a day with the wind direction perpendicular to the direction of the streets. The BEP-Tree simulations demonstrate good agreement with the observations in terms of temperature and radiation, and they are able to capture the different diurnal evolution of temperature and radiation between the two streets.

How to cite: Segura, R., Krayenhoff, S., Martilli, A., Badia, A., Estruch, C., Ventura, S., and Villalba, G.: Observational and numerical evaluation of the pedestrian-level microclimatic effect of street trees in a highly-compact city, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9195, https://doi.org/10.5194/egusphere-egu22-9195, 2022.

Within the scope of the research project “Strategies for Reduction of Critical Urban Climate Load Situations in Augsburg” (MIKA), which is part of the research programme "Urban Climate Under Change” [UC²], the LES model PALM-4U is applied in the medium-sized city of Augsburg, Southern Germany. As a first aim of the project, simulations with focus on air temperature have been performed. The simulations cover a large part of the city and its surroundings (approx. 8x6 km), and two areas of special interest are resolved in more detail. Meteorological boundary conditions are provided by the COSMO-D2 model. Two different summer days have been selected for the simulations. One day has anticyclonic conditions, is part of a heat wave and, thus, thermal stress is expected in the city. The other day, which serves as a reference day, has moderate temperatures and more mixed conditions than the day with heat stress. Furthermore, it is part of an intense observation period (IOP), which means that vertical profiles of air temperature and humidity have been measured at different sites in the city each hour with unmanned aerial vehicles (UAV) accompanied by mobile measurements with a bicycle. This is favourable for evaluating the model results.

This contribution presents some first results of the evaluation and comparison of these two PALM-4U simulations.

How to cite: Straub, A., Beck, C., and Philipp, A.: Simulation of thermal conditions in Augsburg, Southern Germany, using PALM-4U, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12446, https://doi.org/10.5194/egusphere-egu22-12446, 2022.

Urban decision makers rely on evidence-based climate information tailored to their needs to adequately adapt and prepare for future climate change impacts. Regional climate models, with grid sizes between 50-10 km, are a useful outset to understand potential future climate change impacts in urban regions. The recently developed convection-permitting models have grid sizes less than 5 km, and better resolve smaller scale atmospheric processes such as convection, and its interactions with the land surface, by also better representing complex terrain, for instance cities. This study investigates how the convection-permitting resolution affects the simulation of climate change conditions in the urban-rural context, demonstrated through three impact cases: influenza spread and survival; ragweed pollen dispersion, and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041-2050) under emission scenario RCP8.5. Taking the Berlin region as a testbed, the findings show that the change signal reverses for the 3 km compared to the 12.5 km grid resolution for the impact cases pollen, and mold, which indicates an added value. More pollen days are projected in Berlin under future climate conditions. Less mold days can be expected, but longer consecutive periods, under future climate conditions. For influenza, the convection-permitting resolution intensifies the decrease of influenza days, nevertheless longer periods of consecutive influenza days are found under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts for urban regions to support decision makers, and in order to build the resilient cities of tomorrow. 

How to cite: Langendijk, G., Rechid, D., and Jacob, D.: Improved models, improved information? Exploring how climate change impacts pollen, influenza, and mold in Berlin and its surroundings, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1517, https://doi.org/10.5194/egusphere-egu22-1517, 2022.

Buildings are a major source of anthropogenic heat emissions, impacting energy use and human health in cities. The difference between building energy consumption and building anthropogenic heat emission magnitudes and time lag and are poorly quantified. Energy consumption (Q_EC) is a widely used proxy for the anthropogenic heat from buildings (Q_F,B). Here we revisit the latter’s definition. If Q_F,B is the heat emission to the atmosphere due to human activities within buildings, we can derive it from the changes in energy balance fluxes between occupied and unoccupied buildings. Our derivation shows the difference between Q_ECand Q_F,B is attributable to a change in the storage heat flux induced by human activities (ΔS_o-uo). Using building energy simulation (EnergyPlus) we calculate the energy balance fluxes for an isolated building with different occupancy states. The non-negligible differences in diurnal patterns between Q_F,B and Q_ECcaused by thermal storage. With this definition negative Q_F,B can occur as human activities reduce heat emission from buildings but are associated with a larger storage heat flux. Building operations (e.g., open windows, use of HVAC system) modify the Q_F,B by affecting not only Q_EC but also the ΔS_o-uo diurnal profile. This study demonstrates the difference between Q_F,B and Q_EC and the proposed new method for estimating Q_F,B could provide data for future parameterization of both anthropogenic heat and storage heat fluxes from buildings.

How to cite: Liu, Y., Luo, Z., and Grimmond, S.: The difference between building anthropogenic heat flux and building energy consumption, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3188, https://doi.org/10.5194/egusphere-egu22-3188, 2022.

The increasing accessibility to high resolution land surface temperature (LST) data unbalances recently the investigation of the urban heat island (UHI) towards approaches based on these remote sensing tools. However, for a holistic assessment of UHI, a need of comparison of the resulted surface urban heat island (SUHI) with the air urban heat island(AUHI) remains of great interest. In our study we respond to this demand by taking to account all the MODIS LST images and their corresponding synchronous air temperature observations from 9 in-situ monitoring points evenly distributed over the city of Iași for 2013-2020. This way, using a total of 2901 satellite images, the main diurnal and seasonal characteristics of clear-sky SUHI have been outlined for Iași city.

The results obtained describe accurately the intensity of the SUHI, but also its relation with the urban land use categories. During summer season in daytime the spatial extent of SUHI reaches its maximum, SUHI being bounded by the 35°C isotherm in direct relation with the highest imperviousness ratio. In the winter season instead, SUHI is almost absent during the day especially due to the high frequency of temperature inversions in this area. Also, the geometry of SUHI tends to be compact and regular during the nighttime and more irregular during the daytime, as a result of the higher and more complex energy input.

The comparison with the in-situ observations indicates that the differences between SUHI and AUHI are highest during the daytime in spring and summer, when LST is 5 to 7°C higher than the air temperature in classical sheltered conditions, while during winter no major difference can be observed. For the nighttime the LST is 1 to 3°C lower than air conditions regardles of the seasons. The analysis is detailed with the influence of land use categories and imperviousness ratio on SUHI, but also on the difference between SUHI and AUHI. As well, using a k-means atmospheric circulation classification we identified the weather patterns that are capable to increase both the SUHI intensity, and the difference between SUHI and AUHI.

How to cite: Sfica, L., Cretu, C., Ichim, P., Breaban, I.-G., and Hritac, R.: Differences between surface and air urban heat island for clear sky conditions in Iasi city (Romania) and their relation with atmospheric circulation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13410, https://doi.org/10.5194/egusphere-egu22-13410, 2022.

The continuous heat release over cities/urban areas during night owing to urban heat island effect causes turbulent mixing and sustained supply of moisture and cloud condensation nuclei to the boundary layer. This sustained supply of moisture helps in persistence of low-level clouds over these urban areas as compared to rural/suburban areas during night. The various dynamical process including cloud formation, transport and dispersion of moisture and pollutant at boundary level at night time is highly influenced by the nocturnal low-level jets .These nocturnal low-level jets are found to be stronger over urban . These low-level jets are associated with high vertical wind shear production which enhances the turbulent mixing below boundary layer and plays a critical role in formation of nocturnal stratus clouds. In this study we have identified the vertical location of low-level jets using radiosonde data.  We get two peak for the frequency of occurrence of low-level jets, first at around 500-1000 m (boundary-level jets) and another at 1500 m altitude for winter, pre-monsoon, monsoon and post-monsoon seasons. We have also shown the diurnal (morning and evening) variation in the low-level jet frequency for these four seasons. The measurements from radiosonde in this study are taken at 05:30 am Local time (00:00 UTC) and 5:30 pm (12:00 UTC). We have also identified the types of clouds classified on the basis of number of layers over the study areas and associated it with the occurrence of low-level jets.

How to cite: Sharma, S. and Mishra, A. K.: Occurrence of low-level jets and multi-layer clouds over various urban agglomerations located in Indo-Gangetic Plain, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12345, https://doi.org/10.5194/egusphere-egu22-12345, 2022.

Whether the urban heat island (UHI) is affected by air pollution in urban areas has attracted much attention. By analyzing the observation data of automatic weather stations and environmental monitoring stations in Beijing from 2016 to 2018, we found a seasonally dependent interlink of the UHI intensity (UHII) and PM_2.5 concentration in urban areas. PM_2.5 pollution weakens the UHII in summer and winter night, but strengthens it during winter daytime. The correlation between the UHI and PM_2.5 concentration has been regulated by the interaction of aerosol with radiation, evaporation and planetary boundary layer (PBL) height. The former two change the surface energy balance via sensible and latent heat fluxes, while the latter affects atmospheric stability and energy exchange. In summer daytime, aerosol-radiation interaction plays an important role, and the energy balance in urban areas is more sensitive to PM_2.5 concentration than in rural areas, thereby weakening UHII. In winter daytime, aerosol-PBL interaction is dominant, because aerosols lower the PBL height and stabilize atmosphere, weaken the heat exchange with the surrounding, with more heat accumulated in the urban areas and the increased UHII. Changes in evaporation and radiation strengthen the relationship. At night, the change of UHII more depends on the energy stored in the urban canopy. Aerosols effectively reduce the incident energy during daytime, and the long-wave radiation from the buildings of urban canopy at night becomes less, leading to a weakened UHII. Our analysis results can improve the understanding of climate-aerosols interaction in megacities like Beijing.

How to cite. Yang, G., Ren, G., Zhang, P., Xue, X., Tysa, S. K., Jia, W., Qin, Y., Zheng, X., and Zhang, S.: PM_2.5 Influence on Urban Heat Island (UHI) Effect in Beijing and the Possible Mechanisms, Geophys Res Atmos, 126, https://doi.org/10.1029/2021JD035227, 2021.

How to cite: Yang, G.: PM2.5 influence on Urban Heat Island (UHI) effect in Beijing and the possible mechanisms, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4581, https://doi.org/10.5194/egusphere-egu22-4581, 2022.

Urban temperatures are generally higher in cities than in their non-urbanized surroundings, both during day and night. This phenomenon, known as the Urban Heat Island effect, represents a hazard, as it exacerbates heat-related illnesses and mortality. Its intensity can be estimated from remote sensing retrievals of Land Surface Temperature (LST), and in such conditions it is usually referred to as Surface Urban Heat Island (SUHI). Past global studies analyzed this phenomenon in terms of urban and/or annual/seasonal means, but the impact on human health depend on short-term heat stress experienced locally. On the other hand, local studies are often performed on time-limited and not always representative empirical cases, employ different types of measurements and methodologies, making them difficult to intercompare. Moreover, they cover extensively a few developed areas, such as Northern America, Europe and Eastern Asia, leading to a knowledge gap with respect to less studied regions.

To fill this gap, here we developed a high resolution (1 km) dataset of observations of day and night SUHI based on 18 years of MODIS Aqua imagery, which offers an unprecedented insight into the short-time and short-range behavior of the Urban Heat Island. Our results show that 3-day SUHI extremes are on average more than twice as high as the warm-season median SUHI, with local exceedances up to 10 K, and with hotspots of intense heat and relatively cooler areas are clearly observable within the same city. Furthermore, over this period, SUHI extremes have increased more rapidly than warm-season medians, and averaged worldwide are now 1.04 K or 31% higher compared to 2003. This can be linked with increasing urbanization, more frequent heatwaves, and greening of the earth, processes that are all expected to continue in the coming decades.

These data provide clear evidence of the importance of high space-time resolution in studying the Urban Heat Island and the threat it poses. They can be used in a range of applications, from the day-by-day assessment of urban heat, to the calibration of models of the urban climate (Mentaschi et al., 2022).

References

Mentaschi, L., Duveiller, G., Zulian, G., Corbane, C., Pesaresi, M., Maes, J., Stocchino, A. and Feyen, L.: Global long-term mapping of surface temperature shows intensified intra-city urban heat island extremes, Glob. Environ. Chang., 72, 102441, doi:10.1016/j.gloenvcha.2021.102441, 2022.

How to cite: Mentaschi, L., Duveiller, G., Zulian, G., Corbane, C., Pesaresi, M., Maes, J., Stocchino, A., and Feyen, L.: Daily mapping of global surface temperature reveals intensified local extremes of Surface Urban Heat Island, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9654, https://doi.org/10.5194/egusphere-egu22-9654, 2022.

The impact of cities on the local climate is a well-known and -studied phenomenon. In particular, cities increase local air temperature, particularly at night, and creating what is called the urban heat island (UHI). The UHI in the UK’s capital city of London was one of the first to be quantified by Luke Howard around 1830. Since then, many studies have measured, or modelled, the impact of urbanization on local temperatures, and considered the potential impacts on heat-related mortality. Nevertheless, these studies are often: i) focused on short-time periods – e.g., constrained to few days of heatwave; ii) lack spatial density and/or representativity of measurements; or iii) don’t report a method that would make their results and outcomes comparable to other cities.

Our aim is to make coherent spatio-temporal estimations of the burden that cities bring in terms of heat-related mortality. To achieve this, we ran two 3-months (June to August) regional climate simulations at 1 km horizontal resolution using the Weather and Research Forecasting (WRF) which consist of two simple scenarios: with and without the city. For both scenarios, the model was parameterized using the new standardized WUDAPT-TO-WRF python tool. In the natural scenario, surrounding natural pixels from MODIS were considered most probable land covers and replace the city. In the urban scenario, urban canopy parameters were obtained from the European Local Climate Zones (LCZ) map. We used the complex three-dimensional Building Effect Parameterization urban canopy model with its Building Energy Model (BEP-BEM) to represent the urban effect in the urban scenario. The simulations were run for the 2018 summer and its 4 heatwaves over London and the south east of England. The model was evaluated for its urban scenario against a variety of earth observations and meteorological measurements from official and crowd-sourced data. Finally, we bias-corrected the urban and the natural scenario using an innovative method that relies on official automatic and citizen weather stations. This way, me make sure that the calculated heat anomaly induced by the city is as representative as possible , and allows us to quantify the proportion of heat related mortality which we attribute to the urban heat island in London.

Our study is considered one of the first to model a whole seasonal impact of a city on its local climate using a highly complex urban canopy model and a standardized method of parameterization. Our bias-correction method is also expected to provide key perspectives on the joint utility of modelled and crowd-sourced weather data for heat-related epidemiological studies.

How to cite: Brousse, O., Simpson, C., Kenway, O., and Heaviside, C.: Modelling the urban heat island of London, and implications for heat-related mortality during the 2018 summer heatwave, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7205, https://doi.org/10.5194/egusphere-egu22-7205, 2022.

Despite extensive efforts in the past few decades, it still remains a big challenge to reach a coherent and concrete conclusion on how urbanization modifies precipitation for differently located and configured cities. To investigate the impacts of urbanization on summer precipitation characteristics over Montreal, the second most populous city in Canada, two sets of high-resolution numerical simulations using the Global Environmental Multiscale (GEM) model, for consecutive summers (2015-2019), one with detailed urban representation using the Town Energy Balance (TEB) model and one without TEB, are used in this study.

To validate the performance of GEM, the simulation results are directly compared with observations from Environment and Climate Change Canada weather stations, spread across the city. Results show that GEM is able to capture the general climate characteristics such as diurnal cycles of 2-meter air temperature, relative humidity, 10-meter wind pattern, and precipitation intensity distribution reasonably well over Montreal. Comparison of the two sets of simulations shows that urbanization induces a general reduction of the total summer precipitation amount over Montreal due to decreased evapotranspiration caused by land surface modification. Results also suggest an increasing tendency of extreme precipitation amount at higher temperatures in the simulations with TEB, catalyzed by enhanced surface convergence and moisture supply. Additional sensitivity experiments helped understand how urbanization has impacted the management of various engineering systems, such as road infrastructure.  

How to cite: Yin, H., Sushama, L., and Teufel, B.: Impacts of urbanization on summer precipitation and management of engineering infrastructure systems for Montreal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5182, https://doi.org/10.5194/egusphere-egu22-5182, 2022.

The problems of climate change, high-impact weather phenomena and human thermal comfort in urban areas nowadays receives more and more attention not only from urban scientific community, but also from professionals in related fields as well as from general public.

Today, publicly available weather-focused web services and applications experience rapid development and expansion. However, such services focused on urban climate are very rare and have limited usability. In this presentation, we share our experience in development of web-mapping application for urban climate monitoring & research for Moscow megacity in Russia. We aim to develop the web-application which provides observation-based evidence about current and historical weather conditions and human thermal comfort in Moscow region. Such application could be a valuable tool not only for urban climate researchers, but also for citizens planning their outdoor activity, weather and climate enthusiasts, weather-focused media, popularization of science, school and university education, etc.

Previously, we have developed a prototype of such web-mapping application, which collects and maps observations at official weather stations and crowdsourced observations at Netatmo citizen weather stations (Varentsov et al., 2020).  Application backend includes software for automated data collection, PostgreSQL database, data preprocessing tools (quality control for Netatmo data, spatial interpolation, simple model for on-the-fly calculations of Universal Thermal Climate Index representing human thermal comfort), GIS-server Geoserver for showing raster data. The application frontend is based on the OpenLayers web mapping library. The database is accessed by using the supplementary Node.js server application.

Current stage of development includes several new tasks. Firstly, we plan to increase the timespan of historical data available in the application by 2005-2022. Secondly, we plan to develop interactive tools for data analysis, including time series plots and temporal averaging. Finally, we plan to supplement the application by the catalogue of illustrative weather events, such as cases with intense urban heat island, extreme precipitation, and dangerous thermal stress, and to provide popular description of such cases. The recent version of web-application under development is available at http://carto.geogr.msu.ru/mosclim2/.

Acknowledgements: Development of web-application was supported by Russian Geographic Society under grant No. 03/2021-Р. Selection of intense precipitation cases for catalogue of illustrative weather events was supported by the grant of President of Russian Federation for young PhD scientists No. МК-5988.2021.1.5. Data analysis performed by Mikhail Varentsov was also funded by Non-commercial Foundation for the Advancement of Science and Education INTELLECT.

Reference: Varentsov M. I., Samsonov T. E., Kargashin P. E., Korosteleva P. A., Varentsov A. I., Perkhurova A. A., & Konstantinov P. I. (2020). Citizen weather stations data for monitoring applications and urban climate research: an example of Moscow megacity. IOP Conference Series: Earth and Environmental Science, 611(1), 012055. https://doi.org/10.1088/1755-1315/611/1/012055

How to cite: Varentsov, M., Samsonov, T., Kargashin, P., Konstantinov, P., Shurygina, A., and Yarinich, Y.: Development of a web-mapping application for urban climate monitoring & research: experience from Moscow, Russia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11268, https://doi.org/10.5194/egusphere-egu22-11268, 2022.

Heat-related hazards pose major risks to our cities and the projected climate changes indicate substantial increases in impacts, and a better understanding of the interactions between environmental changes and human health are particularly critical for improving the living quality in urban areas in the climate change context. The considerable progress of monitoring, modelling, and analysing methods has addressed the increasing demand for enhanced accuracy, finer resolution, and better accessibility of climate products and services, including the specific needs of the built-up areas.

This study informs the present Heat Hazard-Risk (HHR) over the 262 cities of Romania using a risk matrix approach that aggregates the hazard triggered by high temperatures (i.e. Land Surface Temperature), and elements of vulnerability associated with the structure (i.e. Local Climate Zones - LCZ), and population density (i.e. number of inhabitants per 100 m² in each urban area).

The MODIS LST_cci products used in this study are customised TERRA_MODIS_L3C and AQUA_MODIS_L3C daily day/night 0.01° resolution data on an equal angle latitude/longitude data over Romania produced within the project LST_cci+ (CCI Land Surface Temperature, 2020), and covering the period 2000-2018. The LCZ values were extracted from a European database characterizing the urbanised landscapes derived within the World Urban Database and Access Portal Tools (WUDAPT) project. The population density was retrieved from the Joint Research Centre (JRC) database.

Generally, the HHR is higher in the central parts of the cities, but industrial and residential areas contribute to high-risk values towards the marginal perimeters too. The size and the industrial profile of a city impact the extent of the heat risk. For example, the biggest cities in the southern areas hold the most extended areas at risk at the country level. The land cover is a significant factor that controls the thermal hazard risk in the urban areas of Romania: the highest HHR values correspond to the discontinuous urban fabric, industrial and commercial units, and construction sites, while the lowest values stand for the urban forest, and water bodies.

This study has received funding from the European Space Agency (ESA) within the framework of the Land Surface Temperature project under the Climate Change Initiative (LST_cci), contract number 4000123553/18/I-NB.

How to cite: Cheval, S., Dumitrescu, A., Irașoc, A., Paraschiv, M.-G., Amihăesei, V., and Ghent, D.: A country scale assessment of the heat hazard-risk in the urban areas of Romania, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11749, https://doi.org/10.5194/egusphere-egu22-11749, 2022.

Heat waves are one of the most often experienced impacts of climate change. In recent years, there has been a significant increase in heat extremes during the summer months. According to the German Weather Service (DWD), the three hottest summers in measured history were all in the 2000s: In Germany, the summers of 2003, 2018 and 2019.

The Federal Ministry of Education and Research (BMBF) funded project ZURES II – Application and continuation of future-oriented climate and vulnerability scenarios in selected instruments and planning processes – aims to apply methods for urban development targeting heat stress resilience to planning processes of the City of Ludwigsburg. By identifying and evaluating climate change and future changes in social vulnerability in the City of Ludwigsburg, it was possible to link the previously juxtaposed concerns of climate and social urban development. A constant dialogue with municipal representatives in Ludwigsburg resulted in the recognition of urban development plans as a key instrument to achieve an integrative perspective – considering the processes of changes in climate and urban society together.

The primary goal of the continuation phase is thus to strengthen urban resilience and adaptation to heat stress through an integrated planning framework with information on urban society and climate, and to overcome the isolated consideration of social and climatic aspects through transdisciplinary application research. This aim is to be achieved in dialogue with the city and citizen participation measures.

Communicating dimensions of vulnerability

The proposed contribution is an integrated approach of different communication strategies from both the observational (surveys on household and city level) and modelling perspective (urban climate map), examining urban planning processes, the efficacy of various strategies to reduce heat stress, and measures highlighting how the city of Ludwigsburg is already using science data and products from the research project ZURES that facilitate planning and policies on adaptation to heat stress. A special focus will be on the communication of different vulnerabilities and how the project addresses the fundamental question of what constitutes a meaningful basis of information for sustainable and resilient urban development, especially with regard to resilience to heat stress. Up to now, climate analyses and scenarios have often been used to determine risks and adaptation needs as a basis for information. However, this practice is not entirely innovative, as it is unlikely, for example, that the population in 2030 or 2050 will be the same as in 2019. Therefore, the ZURES project aims to develop small-scale vulnerability and risk assessments, which includes further development of climate modelling as well as advancing methodologically innovative scenario techniques to describe future vulnerability to heat stress.

How to cite: Katzschner, A. and the ZURES II: Communicating dimensions of vulnerability with respect to heat stress, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7891, https://doi.org/10.5194/egusphere-egu22-7891, 2022.

Future urban climates are likely to warm substantively in coming decades as a result of climate change, and greater heat wave severity is anticipated. Moreover, the urban heat island contributes additional heat, especially during evening and night. Infrastructure-based heat reduction strategies can reduce canopy air temperatures during daytime, and to some extent at night. These strategies also have several additional effects beyond air temperature reduction. Here, we apply an early coupling of the WRF mesoscale model with the BEP-Tree urban canopy model to simulate extreme heat events representative of both contemporary and projected future climates for the metropolitan region of Toronto, Canada. Urban and non-urban land cover is derived using the state-of-the-art LCZ Generator methodology. Subsequently, the effectiveness of heat mitigation strategies, including highly reflective surfaces and vegetation, is quantified for the future scenario in the context of the increase in heat wave intensity. Specifically, the neighbourhood- and city-scale climate impacts of street trees across the diurnal cycle are quantified, and the diurnal progression of their local climate effects is discussed with reference to their modifications to multiple physical processes in the canopy. Effects of all heat mitigation strategies on canopy climate, building energy use, and thermal comfort indices are evaluated.

How to cite: Krayenhoff, E. S., Jiang, T., Martilli, A., Moede, C., and Demuzere, M.: Assessment of infrastructure-based reductions of future heat wave intensity with advanced mesoscale modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8744, https://doi.org/10.5194/egusphere-egu22-8744, 2022.

Concerns about the cooling requirements of buildings and negative health effects from heat exposure are increasing with the public’s awareness of climate change. Green roofs have been considered a powerful mitigative and/or adaptive tool to reduce negative impacts of heat. In fact, they can reduce summer indoor-temperatures, as evapotranspiration increases latent heat-flux from a building’s roof. The cooling effect seems to be small on outdoor air temperatures, according to past studies, although green roofs have other benefits in terms of biodiversity, carbon storage, improved building thermal performance and flood management. As the need for sustainable and climate resilient building designs becomes the norm in cities, it is important to assess the status of green roofs coverage and explore potential for future implementation. Accurate information on the prevalence and characteristics of existing green roofs is indeed required to estimate any effect of green roofs on outdoor and indoor temperatures, although this information is often lacking.

Surveying Greater London, we identified existing green roofs and estimated the potential for buildings to be retrofitted with green roofs. Existing green roofs were identified using automated classification of aerial and satellite imagery. Potential for retrofit is assessed using a geospatial database of building characteristics, together with a digital surface model.

The current total green roof area in Greater London is around 1.5 square kilometres (around 0.5% of built area). We estimate that retrofitting existing suitable buildings could add another 3 square kilometres, corresponding to around 2% to the built area in Central London, and around 1% outside Central London. Existing green roofs appear mainly on new buildings rather than being retrofitted, and mainly occur on office and commercial buildings in Central London and residential blocks in redeveloped areas. Potential for retrofit may be highest in the borough of Tower Hamlets, largely on residential blocks with flat roofs.

 This work has direct relevance to sustainable planning policy, especially the London Plan Overheating and cooling policy, and will enable modelling of the building-stock and city-scale effects of green roofs.

How to cite: Simpson, C., Brousse, O., and Heaviside, C.: The Potential of Green Roofs in London, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7671, https://doi.org/10.5194/egusphere-egu22-7671, 2022.

Heat-related mortality and flooding are pressing challenges for the >4 billion urban population worldwide, exacerbated by increasing urbanization and climate change. Urban greening, such as green roofs and parks, can potentially help address both problems, but the geographical variation of the relative hydrological and thermal performance benefits of such interventions are unknown. Here we quantify globally how climate driven trade-offs exist between modelled hydrological retention and cooling potential of urban greening. Water retention generally increases with aridity in water limited environments, while cooling potential favors lower aridity, energy limited, climates. Urban greening cannot yield high performance simultaneously for addressing both urban heat-island and urban flooding problems in most cities globally. However, in more arid locations, where sustainable, irrigation might be used to improve potential cooling benefits while maintaining retention performance. We demonstrate that as precipitation becomes increasingly variable with climate change, the hydrological and thermal performance of thinner substrates would both diminish more quickly compared to thicker and more deeply vegetated systems, presenting challenges for urban greening strategies. Our results provide a conceptual framework and geographically targeted quantitative guide for urban development, renewal and policymaking.

(See further details in the forthcoming paper Cuthbert et al. (In Press) in the journal Nature Communications, which is a more developed version of the pre-print available here: https://eartharxiv.org/repository/view/2100/)

How to cite: Cuthbert, M., Rau, G., Ekstrom, M., O'Carroll, D., and Bates, A.: Global climatic controls on the hydrological and thermal trade-offs of urban greening, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7789, https://doi.org/10.5194/egusphere-egu22-7789, 2022.

In times of rapid global urbanization, the ability to accurately predict the expansion and impact of urban densification on the local climate is critical to the health and wellbeing of the society. Urban densification is the phenomenon of increasing the number or size of urban structures without increasing urban footprint. The characteristics of urban areas such as- the types of building materials, the geometry or orientation, and the land use zoning including amount of green spaces, all contributes to the urban thermal composition, and intensity of urban warming. However, densification reduces the amount of shade and green or free space per structure, whilst also increasing the paved surface area, thus creating a “heat island (UHI)” due to the mutual heating of building structures and the surrounding infrastructures. In this study, we examine the potential of mitigating the heat island effects through leveraging on thermally massive, low-embodied carbon earth building materials. Such materials have been shown to absorb excess heat, and so may buffer heat island effects whilst simultaneously reducing overall air conditioning energy demands. The effect of adopting these earth materials is examined at the neighborhood scale using state of the earth ENVI-met CFD simulation for urban microclimate and outdoor human thermal comfort modelling. Thus, to understand the consequent impact on neighborhood level changes in urban heat after changing housing materials, the study analyzed different residential neighborhood types (compact, open and sparse low-rise) using the Local Climate Zones (LCZ) classification. Also, various types of earth-based wall construction methods were modelled to evaluate the corresponding impact on the immediate outdoor atmospheric and human thermal comfort conditions. In this contribution, we investigate the hypothetical scenario of replacing conventional cement building materials with traditional earth based alternatives in mitigating emerging UHI effects and show results across different residential neighborhoods.  Ultimately, our findings will help modify construction practices in urbanizing areas to counter urban heat island phenomena effectively.

How to cite: Ibitolu, H., Zhao, Q., Beckett, C., and Fosas, D.: Earthen Building materials to mitigate Urban Heat: An Urban Microclimate and Human Thermal Comfort Study across various neighborhood types, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8188, https://doi.org/10.5194/egusphere-egu22-8188, 2022.

Due to climate change, homes are increasingly becoming unacceptably hot, especially during heat waves and therefore create health risks for citizens. To combat heat indoors, active cooling systems, such as air conditioning, are very effective. However, this also comes with negative effects such as increasing energy demand, the use of cooling liquid and releasing heat into the surrounding outdoor environment. Housing associations in particular want to know how they can take possible overheating into account when renovating homes (e.g., for the energy transition). That is why, on behalf of the national government, it was investigated which characteristics on three different levels (the urban area, the building, and the inhabitant) make homes especially vulnerable to heat and which measures can limit that heat.

Desk research (literature study, simulation study and panel discussion) has been carried out in which different situations and the effectiveness of heat-reducing measures have been compared and ranged. For two common housing types in the Netherlands that cover a substantial part of the Dutch housing stock owned by housing corporations, the hourly temperature has been simulated for a representative summer. This was done for many combinations of factors like: green surroundings or urban heat islands effects, solar heat gain (windows, sunscreens), insulation, green roofs, ventilation and use of curtains.

The research shows that the entrance of sun in particular determines overheating of houses and that measures that reduce solar heat gain therefore have the greatest positive effect. Orientation of the house, location and size of windows, and sunscreens are key factors in preventing heat gain. Purge ventilation during the night is the second most important measure, as this helps cooling the house. For this reason night time city temperatures are important. Better insight in those urban night time temperatures is required. The study also showed that human behaviour is an important factor. Correct ventilation and use of sunscreen have a large impact on overheating of houses. Finally, the focus on thermal insulation without sufficient attention on ventilation greatly increases the risks of overheating. The outcome of the research is presented in a guideline for housing associations that ranges the measures in very effective, medium effective and undesirable actions.

How to cite: Corpel, L., Solcerova, A., de Vries, S., Kluck, J., van der Strate, E., Mesdaghi, B., and van Walsum, R.: Most effective measures to combat heat indoors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7910, https://doi.org/10.5194/egusphere-egu22-7910, 2022.

The problem of particulate matter concentration, especially PM2.5 and PM10, is a major concern for all million-plus cities worldwide. Depending upon the scale of implementation of the available technologies and emission reduction policies, the levels of these particulate matter vary over time and space. In this study, we evaluated the effect of wetlands in reducing the concentration of PM2.5 in the air over one of the highest polluted cities in the world, New Delhi, in the Indian region. The PM2.5 was modeled considering the distance-to-wetlands - from the in-situ pollution monitoring stations - as an influential factor, including other determining environmental covariates such as meteorological parameters, atmospheric optical parameters, surface greenness, and land use and land cover (LULC) type (Experiment Set 1). We also conducted a similar experimental setup to build a predictive model excluding the variable distance-to-wetlands (Experiment Set 2). The data of PM2.5 from 21 monitoring stations and all other covariates corresponding to these stations were collected at a daily temporal scale from January 2016 to August 2019. Due to the complexity of the relationships as well as the distribution patterns of all independent variables, a series of machine learning (ML) and artificial intelligence (AI) based analytics, such as random forest (RF), gradient boosting (GB), support vector machine (SVM), and artificial neural net (ANN) regression, were used to model the PM2.5 at monthly and seasonal time scale spatially. All these AI/ML models were trained on 70% of the observations through a random selection. The remaining 30% of the data was used for evaluating the models’ performance. The performances of the models were then compared for both sets of experimental setups. The statistics for model performance diagnostic shows a higher R² for RF-regression than other AI/ML regression models at the training stage under both sets of experimental setups (R² ≥ 0.69 for Experiment Set 1; R² ≤ 0.66 for Experiment Set 2 under RF regression; R² ≤ 0.64 for other models under both experimental setups). The variable influence score (VIS) under RF-regression manifests that the proximity of wetlands is important than the variation of precipitation and LULC type (VIS: 4.12% for distance-to-wetlands, VIS: 2.61%, and 0.24% for precipitation and LULC type, respectively). The predictability of the RF-regression model, while evaluated with the test data, shows R² ~ 0.66, with RMSE of 80.4 µg m^-3 for the Experimental Set 1, and R² ~ 0.63 with RMSE of 83.7 µg m^-3 for the Experimental Set 2. It was noticed from the analysis that within a 1000 m buffer distance from the wetlands, the concentration of PM2.5 remains relatively lower than a distance greater than 1000 m. Such difference is benign, yet the key factor behind such a benign effect is related to the variation in surface area of the wetlands. Larger wetlands may have a distant impact on keeping the PM2.5 low. The study, thus, concludes that restoring the wetlands might be one of the practical solutions to keep the PM level within the ambit of NAAQ standards.  

How to cite: Acharya, P., Gayen, B. K., and Dutta, D.: Can wetlands be an effective option to reduce the particulate matter pollution in the air in urban spaces?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8380, https://doi.org/10.5194/egusphere-egu22-8380, 2022.

In the context of the COVID-19 outbreak, a strict lockdown was ordered by Belgian authorities from 18/03/2020 till 04/05/2020. This led to a limitation of industrial production, human activities and transport use where only essential motorized transport were permitted. This research is an attempt to study the impact of these measures on the canopy layer urban heat island intensity in the city of Ghent. We used the high-accuracy observational MOCCA (MOnitoring the City’s Climate and Atmosphere) network. This network is monitoring the urban climate of the city of Ghent since July 2016. The network consists of six weather stations in the Ghent region and provides a database of hourly observation including 2m temperature at six locations (including dense urban, industrial and suburban). Only clear-sky days with an average wind speed lower than 3 m/s were selected for both the confinement period in 2020 and for similar periods in the reference years 2017, 2018 and 2019. For the years 2017, 2018 and 2019 respectively 3, 3 and 7 reference days were retained to compare with 9 selected days of the 2020 confinement period. Results indicate a lower UHI intensity during the day for 2020 compared to the reference years for the dense, industrial and suburban site. A statistically significant difference was found at 15h, 16h, and 17h for the dense urban site (Provinciehuis). The statistical test did not give significant difference for the suburban site (Wondelgem). Human activities in the urban dense areas release a large amount of heat, which can directly heat the air and during the daytime around 16h when the storage heat flux switch from positive to negative values with weak value of the net radiation fluxes, the external source of energy due to the anthropogenic heat can drive the surrounding hot air to mix with local air and further warm near‐surface air temperature (2 m above ground level). However, during the lockdown period this external contribution to the surface energy balance was absent inducing a cooling gradient of the temperature in the dense urban site (Provinciehuis) up to 0.4°C/h around 18h-19h stronger in 2020 compared to the references years. During nighttime the UHI intensity becomes larger mainly driven by the release of energy stored during the day and the UHI intensities are similar for 2020 and the reference years indicating that the lockdown measures will not have had an impact on the UHI intensity during the night.

How to cite: Hamdi, R., Tronquo, E., Bogaerts, E., Hoang, K.-M., Loudeche, C., Claeys, E., Caluwaerts, S., Duchêne, F., Van Schaeybroeck, B., and Termonia, P.: The impact of COVID-19 confinement measures on the canopy urban heat island intensity of Ghent (Belgium), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7193, https://doi.org/10.5194/egusphere-egu22-7193, 2022.