UP2.1 | Cities and urban areas in the earth-atmosphere system
Cities and urban areas in the earth-atmosphere system
Including EMS Young Scientist Conference Award lecture
Including Tromp Foundation Travel Award Lecture
Conveners: Maria de Fatima Andrade, Arianna Valmassoi, Pavol Nejedlik | Co-conveners: Ranjeet Sokhi, K. Heinke Schlünzen, Jan-Peter Schulz
Orals
| Tue, 03 Sep, 11:00–17:15 (CEST)
 
Lecture room 203, Wed, 04 Sep, 09:00–17:15 (CEST)
 
Lecture room 203
Posters
| Attendance Wed, 04 Sep, 18:00–19:30 (CEST) | Display Wed, 04 Sep, 08:00–Thu, 05 Sep, 13:00|Poster area 'Vestíbul'
Orals |
Tue, 11:00
Wed, 18:00
Cities and urban environments are a key aspect of the United Nations (UN) Agenda for Sustainable Development, and include scientific and socio-economic perspectives. As urbanisation processes continue across the world, its representation and understanding needs to be further improved to fully assess its impact on weather, air quality, water quality, energy consumption/production and climate. These aspects are crucial both for advancing current knowledge and creating effective sustainable solutions. Key challenges in accomplishing this task vary according to the level of complexity and multi-scale dimension of diverse urban environments.

This session welcomes modelling and observational studies that aim to investigate different aspects of urbanization (e.g. urban heat island, air quality, vulnerability to extreme events, urban/peri-urban agriculture) and its feedback on weather and climate systems, with a particular focus on application for sustainable adaptation plans. Novel methods that aim to assess urban representation and/or to bridge the different scales of the diversity of topologies are encouraged. The impact of cities on weather, air quality, climate and/or their extremes (e.g. drought, precipitation, air pollution episodes), as well as on climate change and on population and adaptation will also be discussed in this session.

Topics may include:
• New urban parameterizations, methods to derive urban parameters for numerical models.
• Implementation of climate mitigations, adaptation strategies (e.g. blue-green infrastructures) and self-government policies in cities and urban context.
• Impact of the different urban parameterizations on the atmospheric dynamics at different scales.
• Impact of the urbanization including estate and industrial on weather and/or climate extremes.
• Field measurements of urban climate, e.g. precipitation, CO2 concentrations and flux, boundary layer characteristics.
• Population vulnerability to urban climate and climate change.
• Extreme events' (e.g. drought, rainfall events, heat wave) impacts on urban areas.
• Urban emissions of climate forcers, air pollutants and anthropogenic heat.
• Urban air quality and meteorological interactions.
• Meteorology or air pollution modelling of all scales with focus on urban areas.
• Coupling and downscaling of global, regional and urban scale modelling approaches to quantify climate and atmospheric composition impacts and feedbacks.
• Integrated monitoring, modelling and forecast systems for urban hazards.
• Urban transition to cleaner fuels and their meteorological or AQ impacts.
• Crowd sourced data/novel data sources in cities
• Successes, challenges and limits of AI approaches for urban research
• Assimilation of 4D data and machine learning applied for air quality simulation
• Social science analyses of cities

Organised jointly with:
World Meteorological Organization (WMO) Global Atmospheric Watch Project GAW Urban Research in Meteorology and Environment (GURME)
WMO World Weather Research Programme (WWRP)

Orals: Tue, 3 Sep | Lecture room 203

Chairpersons: Arianna Valmassoi, Maria de Fatima Andrade, Jan-Peter Schulz
I. Assessment of direct urban influences
11:00–11:30
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EMS2024-1136
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solicited
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Onsite presentation
Alberto Martilli, Negin Nazarian, Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and Jose Luis Santiago

Heat stress depends on a set of metereological variables, namely, air temperature, wind speed, air humidity and mean radiant temperature. In urban areas, wind speed and mean radiant temperature are strongly spatially hetereogeneous, at scales of few meteres, much smaller than the typical resolution of mesoscale models, which is of the order of one kilometer or several hundreds of meters. This is the main obstacle to produce reliable estimates of heat stress at city scale. In this contribution, we present a methodology, built over a set of microscale simulations, to represent subgrid scale variability of wind speed and mean radiant temperature, and as a consequence heat stress. The scheme is implemented in the multilayer urban canopy parameterization BEP-BEM embedded in the mesoscale model WRF (therefore called WRF-comfort), and it opens the way to the city scale evaluation of the impact of different adaptation/mitigation strategies on heat stress, something that is essential to plan liveable future cities in the context of a changing climate. This is illustrated with a series of simulations for a summertime period over the city of Madrid (Spain). Then main outcome of the study is that the time evolution and spatial variability of UTCI (the Universal Thermal Climate Index, one of the most used heat stress indexes) are strongly affected by the urban morphology, and that the spatial pattern of UTCI at city scale is only partially similar to the one of air temperature, and dissimilar to the one of Land Surface Temperature, as it can be seen from satellite, a variable often used to assess urban overheating.

How to cite: Martilli, A., Nazarian, N., Krayenhoff, S., Lachapelle, J., Lu, J., Rivas, E., Rodriguez-Sanchez, A., Sanchez, B., and Santiago, J. L.: Assessing heat stress with a mesoscale model. An application of WRF-comfort to Madrid, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1136, https://doi.org/10.5194/ems2024-1136, 2024.

11:30–11:45
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EMS2024-337
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Onsite presentation
Tim Nagel, Margaux Rivollet, Wallois Sarah, Marine Goret, Greg Roberts, Aude Lemonsu, Valéry Masson, Minttu Havu, Julie Capo, Jean Wurtz, Cécile de Munck, Martial Haeffelin, Jean-Francois Ribaud, Simone Kotthaus, and Jean-Charles Dupont

Urban green infrastructures can regulate microclimate and mitigate urban heat island (UHI) effects. In summer, urban parks offer cooler spots where citizens are protected from the heat of the city, more particularly in the evening and the night, when the UHI arises. During heatwaves, urban parks can therefore play a key role in addressing health risks. Previous research shows that urban vegetation has the potential to mitigate temperatures at the pedestrian level depending on park size, vegetation type, topography or local climate. However, little is known concerning the impact of meteorological conditions (wind, turbulence, cloudiness, UHI intensity, atmospheric stability) on the urban park cooling effect. The cooling along the vertical dimension remains also sparsely quantified. 

One of the aims of the PANAME (for PAris region urbaN Atmospheric observations and models for Multidisciplinary rEsearch) intensive measurement campaign is to better understand and quantify the role of urban parks in regulating the microclimate during summer periods. The July 2023 special observation period (SOP) focused more particularly on investigating the horizontal and vertical cooling potential of four urban parks and woods of various sizes from late afternoon to early part of the night. The experimental set-up combined in situ surface measurements in parks and urban areas, such as profiling of the surface layer using quadcopter drones and soundings. For drone measurements, each urban park was associated with a nearby urban site, consisting in semi-enclosed to enclosed paved courtyards surrounded by buildings. Profiles were simultaneously undertaken in both urban/park environments from 16 to 20 UTC for each of the 21 days of measurements that took place for the 2023 SOP. This resulted in an innovative multi-source dataset currently being used to quantify and analyse the differences in surface and near-surface atmospheric cooling rates between an urban park and the nearby urban environment, as well as between different parks, but also to study the cooling potential related to meteorological conditions.

The first results show that the evening cooling is highly dependent on the meteorological conditions, which is in agreement with recent work establishing a link between park cooling efficiencies and weather types with contrasting UHI regimes. For some evenings, the surface park cooling between the late afternoon and the sunset can reach more than 3 K while it is often less than 1 K in the urban environment. For other meteorological conditions, the cooling rate is similar between park and urban environments. When the cooling is different between parks and urban environments, the park cooling extends vertically over several tens of meters, where a local inversion is found. For those types of meteorological conditions, significant cooling is also found in very small urban parks (less than 1 ha).

How to cite: Nagel, T., Rivollet, M., Sarah, W., Goret, M., Roberts, G., Lemonsu, A., Masson, V., Havu, M., Capo, J., Wurtz, J., de Munck, C., Haeffelin, M., Ribaud, J.-F., Kotthaus, S., and Dupont, J.-C.: Investigation of urban park cooling efficiency during summer in Paris with drones, sondes, and ground measurements, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-337, https://doi.org/10.5194/ems2024-337, 2024.

11:45–12:00
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EMS2024-418
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Onsite presentation
Minttu Havu, Tim Nagel, Jean Wurtz, Valéry Masson, Margaux Rivollet, Martial Haeffelin, Jean-Francois Ribaud, Simone Kotthaus, Jean-Charles Dupont, and Aude Lemonsu

Heat waves pose a significant risk to human health, particularly pronounced in urban areas due to the urban heat island (UHI) effect. Understanding the varying impacts of heat waves across different neighbourhoods within cities is vital, as well as recognizing the potential of urban vegetation in mitigating temperatures. The Heat and Health in Cities (H2C) project aims to enhance urban climate services to support proactive measures and policies addressing extreme heat risks in cities, with a specific focus on the Paris region. Employing a multi-source observational approach alongside numerical models, the project seeks to provide a more comprehensive assessment of environmental conditions, ranging from regional to neighbourhood scales. 

The main aim of this study is to examine the efficiency of parks and urban forests in mitigating air temperatures during summer periods including heat waves. Using the Meso-NH model, this study conducts simulations of discrete events occurring in 2022 and 2023 within Paris and the Ile-de-France region. Meso-NH, a non-hydrostatic research atmospheric model, is driven by atmospheric boundary conditions from the French convective-scale operational Numerical Weather Prediction model AROME-France. Coupled with Meso-NH is the land surface model SURFace EXternalized (SURFEX), incorporating the Town Energy Balance (TEB) model for urban elements combined with a high-resolution surface database. Simulations are based on three nested domains with respective grid resolutions of 1200 m, 300 m (over Paris region), and 100 m (over the city of Paris). Model validation of 2-m air temperatures is performed using data from the PANAME (PAris region urbaN Atmospheric observations and models for Multidisciplinary rEsearch, https://paname.aeris-data.fr/) intensive measurement campaign. 

Previous works have established through the local observations the existence of weather types with contrasting UHI regimes resulting in distinct park cooling efficiencies. The aim of this study is to determine whether hectometric-scale modelling is able to replicate these observed results. The challenge is then to be able with modelling to study and better understand the microclimatic contrasts within the city, in particular the cooling effects generated by urban parks of various sizes and the factors contributing to their variability.

How to cite: Havu, M., Nagel, T., Wurtz, J., Masson, V., Rivollet, M., Haeffelin, M., Ribaud, J.-F., Kotthaus, S., Dupont, J.-C., and Lemonsu, A.: High-resolution modelling of park cooling efficiency during summer in Paris, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-418, https://doi.org/10.5194/ems2024-418, 2024.

12:00–12:15
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EMS2024-468
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Onsite presentation
Miguel Toribio-Pérez, Francisco Conde-Oria, and Domingo F. Rasilla

“Greenness is often associated with more attractive, healthful, and wealthy urban areas since vegetation increases the urban biodiversity and reduces summer temperatures. Some analyses have pointed out a relationship between neighborhood demographics and urban vegetation that has been referred to as “luxury effect” (Leong, Dunn, and Trautwein 2018) or tree gap (Visram 2021), from which wealthy residential areas benefit from greater vegetation cover and a lower intensity of the urban heat island effect. So, this contribution relates some of the urban features, derived from remote sensing, with the dynamic of the urban heat island of Madrid, and some socio-demographic parameters at census tract level, for the summers of the 2008-2017 period.

The remote sensing indices were calculated from Landsat 5 and Landsat 8 platforms (https://earthexplorer.usgs.gov/). The urban heat island of Madrid was studied using the “Climate variables for cities in Europe from 2008 to 2017” dataset, obtained from Copernicus (https://cds.climate.copernicus.eu/cdsapp#!/software/app-health-urban-heat-islands-current-climate?tab=app), combined with observed temperature data from the Spanish Meteorological Agency (AeMet) and the Regional and Local authorities (Ayuntamiento and Gobierno Regional de Madrid). Demographic data were retrieved from the Atlas de distribución de renta de los hogares (https://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736177088&menu=ultiDatos&idp=1254735976608) and the Municipality of Madrid (https://www.madrid.es/portales/munimadrid/es/Inicio/El-Ayuntamiento/Estadistica?vgnextchannel=8156e39873674210VgnVCM1000000b205a0aRCRD).

Analyses show that Madrid's UHI is particularly intense at night, while during daytime is much weaker. This can be explained by the thermal behavior of its urban periphery, which is mainly made up of agricultural areas with rainfed crops, suffering an intense daytime heating. It is also observed that the relationship between remote sensing indices and the urban temperatures varies depending on the information provided by the indices (vegetation, built-up or aquatic surfaces density) and the time of day. The "luxury effect" is not evident, as the relationship between vegetation, heat island and various sociodemographic indicators is statistically weak. As an urban space which has evolved from many decades, Madrid offers a remarkable spatial diversity in terms of income levels or demographic composition, although some risk neighborhoods can be delimited because of the coincidence of a high amount of vulnerable population (low income, senior population, migrants) and an intense urban heat island.

How to cite: Toribio-Pérez, M., Conde-Oria, F., and Rasilla, D. F.: Luxury effect and Urban Heat Island: a reassessment in Madrid., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-468, https://doi.org/10.5194/ems2024-468, 2024.

12:15–12:30
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EMS2024-644
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Onsite presentation
Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Marvin Plein, Markus Sulzer, Dana Looschelders, and Nektarios Chrysoulakis

We describe features and results of a data system developed to allow timely access to data from novel modular atmospheric monitoring systems deployed in urban areas in multiple cities of different sizes, simultaneously. The ERC urbisphere project is collecting a wide range of atmospheric environmental data to improve weather and climate models, in order to assess the impact of cities on the atmosphere (e.g., aerosols, greenhouse gases) and human exposure to extreme events (e.g., heat waves, heavy precipitation, air pollution). Modular observing systems involving short-term deployments include customised automatic weather stations, Doppler and ceilometer lidars, scintillometers, balloon radio sounding and spectral imaging. Deployments range from streetlight-mounted to building roofs and indoors to mobile platforms (vehicles, drones). Together this creates challenges to synthesise across multiple sources of diversity.

Data are uploaded in near-time to a central data infrastructure via cell phone and IOT networks. A metadata system helps track the location and configuration of all deployed components and provides the backbone for processing instrument records into location-aware, convention-aligned and quality-assured data products according to FAIR. The data system provides services (e.g., APIs, Apps, ICEs) for inspection and computation by campaign participants. Workflow and design considerations also include collaboration tools that ensure attribution for multiple uses in near time by researchers, operational agencies and citizens.

We will demonstrate how the systematic, easily adoptable approach can simplify complex campaign workflows, for both modellers and observers. The showcase of the data system will use examples from outdoor/indoor temperature observations and spatial wind field observations from past and ongoing campaigns.

 

 

How to cite: Zeeman, M., Christen, A., Grimmond, S., Fenner, D., Morrison, W., Feigel, G., Plein, M., Sulzer, M., Looschelders, D., and Chrysoulakis, N.: Near-time atmospheric observations in urban areas: insights from concurrent operations in multiple cities, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-644, https://doi.org/10.5194/ems2024-644, 2024.

12:30–12:45
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EMS2024-739
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Onsite presentation
Tugba Dogan, Aleš Urban, and Martin Hanel

The Urban Heat Island (UHI) effect has significant implications for human thermal comfort, urban ecosystems, and energy consumption. The COVID-19 global lockdown presented a unique opportunity to explore the impact of reduced air pollution emissions and Anthropogenic Heat Flux (AHF) on UHI. While some studies have proposed that the lockdown’s reduction in AHF led to a decrease in both Atmospheric UHI (AUHI) and Surface UHI (SUHI), these findings are susceptible to inherent uncertainties due to unaccounted weather variability and urban-rural dynamics.

Our research provides a comprehensive analysis of the lockdown’s impact on AUHI and SUHI in Prague, Czechia. We selected days with similar weather conditions and compared the mean SUHI using MODIS satellite imagery and AUHI based on air temperature data from Prague weather stations during the lockdown period from March to April 2020 with a reference period spanning March to April 2017-2019.

Our findings reveal that the lockdown period, compared to the reference period, was associated with a 15% (0.1 °C) reduction in SUHI in Prague’s urbanized areas and a 0.7 °C decrease in AUHI in the city center. Furthermore, we observed a 12% and 29% decrease in satellite-based aerosol optical depth and nitrogen dioxide, respectively. These observations support our hypothesis that the observed weakening of UHI effects is linked to the reduction in anthropogenic activities during the lockdown. In addition, our study shows the largest decrease in mean SUHI magnitude was in the periphery, an area characterized by predominantly rural land cover. This highlights the importance of considering urban-rural dynamics when attributing changes in SUHI to AHF.

In conclusion, our study provides additional insights into the role of reduced anthropogenic activities in UHI dynamics during the COVID-19 lockdown. It offers policymakers a comprehensive understanding of how the complex interplay between urban and rural microclimate dynamics influences the SUHI phenomenon.

How to cite: Dogan, T., Urban, A., and Hanel, M.: Temporal variations of urban heat islands during COVID-19 lockdown in Prague, Czechia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-739, https://doi.org/10.5194/ems2024-739, 2024.

12:45–13:00
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EMS2024-898
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Onsite presentation
Basak Ilknur Toren and Tania Sharmin

The recent reports issued by the Intergovernmental Panel on Climate Change (IPCC) emphasise the need to reconsider the design of urban built environments [1]. In the past twenty years, research has demonstrated that geometry parameters of urban street canyon play a significant role in influencing the microclimatic conditions and energy performance of the buildings within urban environments [2,3]. Urban canyon geometry affects the overall energy consumption of buildings and has the potential to reduce energy usage by as much as 30% for commercial structures and 19% for residential structures. Besides, the air and surface temperatures of urban street canyons are highly influenced by sunlight access, shadowing, and other factors. Canyon’s form and parameters, such as aspect ratio (H/W) and street direction, impact sun access, shading, and ventilation, which are also affected by length-to-height ratio (L/H). The aim of this paper is to assess whether geometric parameters of urban street canyons affect the microclimates and energy consumption in cold semi-arid climate. The research was carried out in Kayseri, Turkey, which has been developing city. According to those statistics, the real heating energy consumption in residential buildings ranges between 100 and 200 kWh/m 2 (the average is obtained as 175 kWh/m2) in Turkey. However, in European countries, this value is 100 kWh/m2, including energy use of heating, cooling and ventilation [4]. A total of 18 scenarios, including both configurations with and without space between buildings, were simulated. The scenarios varied in their aspect ratio, which is the ratio of height to width (H/W). There were three types of canyons: avenue canyons (H/W < 0.5), regular canyons (H/W = 1.0), and deep canyons (H/W > 2.0). Additionally, the scenarios differed in their length-to-height (L/H) ratio. There were three types of canyons based on this ratio: short canyons (L/H < 3.0), medium canyons (L/H = 5.0), and long canyons (L/H > 7.0) [5]. The performance of the canyon was evaluated by comparing the air temperature, on the hottest and coldest day of a typical year. In parallel to microclimate analysis, energy consumption analysis was carried out for a hypothetical case study building throughout the day and night. Envi-met and EnergyPlus are used as a computational tool. The comparative study will show how and to what extent urban canyon geometry parameters, in this case, contributes to modifying the magnitude of microclimate impact on daytime and nighttime energy loads.

Keywords: Street Canyon, Urban form parameters, Urban geometry, Energy performance

How to cite: Toren, B. I. and Sharmin, T.: Urban Geometry and Microclimate of Street Canyons in Cold Semi-Arid Climate, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-898, https://doi.org/10.5194/ems2024-898, 2024.

Lunch break
Chairpersons: Maria de Fatima Andrade, K. Heinke Schlünzen, Pavol Nejedlik
14:00–14:15
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EMS2024-804
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solicited
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Tromp Foundation Travel Award Lecture
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Onsite presentation
Beatriz Sanchez, Alberto Martilli, Jose Luis Santiago, Esther Rivas, Fernando Martin, Dominc Royé, Juan Carbone, and Carlos Yagüe

One relevant effect of urbanization is the modification of atmosphere-surface interactions, which modulate urban microclimate and human thermal comfort. To quantify the impact of heat on the human body, more comprehensive biometeorological indices, such as the Universal Thermal Climate Index (UTCI), are commonly employed accounting for not only air temperature influence but also the variability of other relevant weather variables such as wind speed, air humidity and radiation. The irregularity of urban morphology (e.g. building height and layout) across the city leads to high spatial heterogeneity of the micrometeorological variables, in particular on wind speed and solar radiation (e.g. shading effects). Therefore, analyzing the impact of urban geometry and the past changes in urban land cover on heat stress contributes to understanding the potential risks that urban residents might face considering the future urban growth and future climate.

The purpose of the present work is to investigate the impact of urban development and climate on outdoor thermal comfort in Madrid for summer weather conditions under past and future climate. A modeling study is conducted using the Weather, Research and Forecasting (WRF) model adapted to estimate the heat and momentum exchanges between buildings and atmosphere (BEP-BEM urban scheme), as well as the recent development incorporated into BEP-BEM to quantify heat stress through UTCI values and its subgrid variability. Past urban scenarios are performed considering the realistic urban expansion and morphology from 1970 to 2020, and the expected urban development is used for the future scenario. The model evaluation is conducted against observations showing an overall good performance of the model in predicting near-surface meteorological parameters. Even though the urban layout has barely changed in the center of Madrid over the last 50 years, results show an increase in the UTCI values due to the influence of the surrounding urban expansion. In addition, these results show the relative contribution of urbanization and climate effects on the heat stress changes across the city under the past and future climates.

How to cite: Sanchez, B., Martilli, A., Santiago, J. L., Rivas, E., Martin, F., Royé, D., Carbone, J., and Yagüe, C.: Past and future changes in the spatiotemporal distribution of heat stress in Madrid, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-804, https://doi.org/10.5194/ems2024-804, 2024.

14:15–14:30
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EMS2024-1088
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Onsite presentation
Tomas Halenka, Ranjeet Sokhi, and Sandro Finardi

While overall the global warming with the causes and global processes connected to well-mixed CO2, and its impacts on global to continental scales are well understood with a high level of confidence, there are knowledge gaps concerning the impact of many other non-CO2 radiative forcers leading to low confidence in the conclusions. This relates mainly to specific anthropogenic and natural precursor emissions of short-lived GHGs and aerosols and their precursors. The anthropogenic origin is connected to large extent with the urban environment. These gaps and uncertainties also exist in their subsequent effects on atmospheric chemistry and climate, through direct emissions dependent on changes in e.g., agriculture production and technologies based on scenarios for future development as well as feedbacks of global warming on emissions, e.g., permafrost thaw.

The main goal of the EC Horizon Europe project FOCI, is to assess the impact of key radiative forcers, where and how they arise, the processes of their impact on the climate system, to find and test an efficient implementation of these processes into global Earth System Models and into Regional Climate Models, eventually coupled with CTMs, and finally to use the tools developed to investigate mitigation and/or adaptation policies incorporated in selected scenarios of future development targeted at Europe and other regions of the world, with final emphasis to selected cities environment. We will develop new regionally tuned scenarios based on improved emissions to assess the effects of non-CO2 forcers. Mutual interactions of the results and climate services producers and other end-users will provide feedbacks for the specific scenarios optimization and potential application to support the decision making, including climate policy.

Coupled RCM-CTM modelling experiment strategies and preliminary results will be presented in addition to the contemporary status of the project.

How to cite: Halenka, T., Sokhi, R., and Finardi, S.: Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts: Where we are and where we go, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1088, https://doi.org/10.5194/ems2024-1088, 2024.

14:30–14:45
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EMS2024-210
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Onsite presentation
Lippin Pauly and Enrico Ferrero

Rapid urbanization, compounded by climate change, exacerbates temperatures in urban regions by intensifying the urban heat island (UHI) effect. This study explores the influence of urbanization patterns on urban microclimate in Turin, Italy, through numerical simulations. Various urban design scenarios were investigated using weather research and forecast models integrated with a multilayer urban canopy model (MLUCM) over the June 2019 heatwave period. High-resolution urban land use/land cover data derived from local climate zone (LCZ) maps generated through the World Urban Database and Access Portal Tools (WUDAPT) were utilized. Results indicate a significant impact of urbanization on UHI, demonstrating an average nighttime temperature reduction of 2.4°C and daytime temperature reduction of 1.6°C in urban areas when urban built-ups are replaced with vegetation. Replacement of compact-rise buildings alone notably impacts local climatic conditions, decreasing average temperatures by 1.75°C in the city center, with an overall urban temperature decrease of 0.9°C. Conversely, the substitution of industrial zones yields a 1.4°C average urban temperature decrease, with minimal impact in city centers (0.14°C reduction). Substituting compact-rise buildings with open-rise buildings slightly reduces urban nighttime temperatures and significantly reduces the critical velocity required to mitigate UHI. Furthermore, the adoption of open-rise buildings fosters enhanced wind flow in downstream rural areas, potentially contributing to a reduction in urban temperatures on windy days by facilitating ventilation and other cooling processes. This research emphasizes the critical role of specific urban features in mitigating UHI and improving thermal comfort. By strategically incorporating green spaces, open-rise buildings, and wind-channeling designs, urban planners can create more resilient and thermally comfortable cities.

How to cite: Pauly, L. and Ferrero, E.: Numerical Experimentation to Study the Influence of Various Urban Features on Microclimate Using Different Urban Scenarios , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-210, https://doi.org/10.5194/ems2024-210, 2024.

14:45–15:00
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EMS2024-223
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Onsite presentation
Mustafa Hmoudah and Calin Baciu

Methane is a primary greenhouse gas with a relatively short lifetime in the atmosphere (~ 12 y), making it a candidate for mitigation efforts aimed at improving the climate in the near future.

Urban areas account for ~2% of our planet’s surface, but they host more than half of the world’s population and a series of potential CH4 source systems (e.g., natural gas distribution, landfills, sewages, and in some cases, natural or artificial wetlands). The role of urban areas in the global atmospheric CH4 budget is, however, uncertain.

Our understanding of the exact CH4 emission systems and related emission factors in urban areas is still limited (and unknown in Romania).

In Cluj-Napoca, the second-biggest city in Romania, our study aims at identifying potential urban sources for CH4emissions via direct detection of CH4 at potential emission sites (opposed to atmospheric monitoring, as generally done).

Our study aims to investigate potential sources in three major urban systems (natural gas distribution networks, sewage system, and aquatic systems).

We used a highly sensitive laser CH4 sensor based on Tunable Diode Laser Absorption Spectrometry (TDLAS) with a resolution of ± 0.1 ppmv.

Preliminary data show that 86% of the natural gas end-use points (74 measured) release CH4 into the atmosphere, 51% of the SEWAGE manholes (126 measured) are net sources of methane, and the aquatic systems (river and ponds, 50 sampling sites) are all oversaturated with dissolved CH4 and represent potential sources.

Due to both natural and anthropogenic CH4 sources, Cluj-Napoca can be considered a hybrid methane source. This approach helps in reducing the ambiguity in the attribution of CH4 sources when only atmospheric CH4 monitoring is performed.

This study can advance our understanding of CH4 release in urban areas and serve as the first national systematic-based approach that can be replicated to effectively take advantage of all available resources. It will also serve as a reference for future research on CH4 in the urban area.

How to cite: Hmoudah, M. and Baciu, C.: Investigating emissions of methane (CH4) to the atmosphere in Cluj-Napoca urban area , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-223, https://doi.org/10.5194/ems2024-223, 2024.

II. Climate change effects in the urban areas
15:00–15:15
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EMS2024-18
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EMS Young Scientist Conference Award lecture
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Onsite presentation
Giandomenico Vurro, Alberto Martilli, Panos Hadjinicolaou, and Salvatore Carlucci

Human-induced climate change is expected to affect the entire Mediterranean area during the 21st century; notably, the Eastern Mediterranean and Middle East (EMME) region has been recognized as a climate-change hotspot. That manifests with increased temperatures and more frequent heatwaves, posing a significant challenge for urban areas in warm periods. Furthermore, as the urban population continues to grow and urbanization expands in this area, the potential escalation of heatwaves in the already sensitive EMME environment is expected to have direct adverse effects on human health, agriculture, and the water-energy nexus. Therefore, analyzing the impact of exacerbated environmental conditions is crucial for understanding the vulnerability of cities and developing effective mitigation and adaptation strategies.

Our aim is to quantify the impact of extreme temperatures on the building energy use for space cooling, rejected heat to the ambient, and outdoor thermal comfort in Nicosia, Cyprus, over a heat wave event within the period from the 24th of July until the 10th of August 2021. To achieve this, the Weather Research and Forecasting (WRF) model is coupled with the Multilayer BEP/BEM scheme to study different adaptation and mitigation strategies evaluated against two baseline scenarios, the first without considering the air conditioning and the second where the air conditioning is on to maintain indoor thermal comfort. The adaptation/mitigation scenarios are (i) partial coverage of roofs with photovoltaic panels to increase the generation of energy from renewable energy sources, (ii) adoption of cool roofs to minimize heat absorption, and (iii) plantation of trees and expansion of green areas within the city to reduce air temperature and improve outdoor thermal comfort.

By comparing these three strategies against themselves and the baseline scenario, we can identify their contribution to reducing buildings’ energy consumption and rejected heat and increasing outdoor thermal comfort. Therefore, the outcomes of this study can provide valuable insights to policymakers and urban planners in addressing climate change impacts in city regeneration projects by increasing urban resilience against extreme heat.

How to cite: Vurro, G., Martilli, A., Hadjinicolaou, P., and Carlucci, S.: Quantifying the impact of extreme heat and adaptation strategies on urban air conditioning use and energy consumption in Nicosia, Cyprus. , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-18, https://doi.org/10.5194/ems2024-18, 2024.

15:15–15:30
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EMS2024-355
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Onsite presentation
Stephen Outten, Francesca Raffaele, Natalia Zazulie, and Silius Mortensønn Vandeskog

Europe suffers great financial loss and loss of life to extreme events every year, and while the impacts of these events may increase due to society’s increasing exposure, the hazardous events themselves are also expected to change. The accurate projection of the changes in extreme events is invaluable for many industries, including insurance, construction, and energy, but also for those stakeholders responsible for preparing the European cities to withstand future extreme events. However, such adaptation requires information that is tailored to the needs and workflow of the stakeholders.

In the EU-Impetus4Change (I4C) project, we have worked with stakeholders in four demonstrator cities across Europe to select hazard indices that are directly applicable to their ongoing work in adapting to climate change. The cities, Barcelona, Paris, Prague and Bergen, were selected because they represent a wide range of climates across Europe and face different hazardous events. There are 23 indices in total, which focus primarily on heat waves and extreme rainfall, but also include indices on drought, fire weather, and river discharge. These indices have now been calculated in 67 models from the EURO-CORDEX simulations, covering all of Europe for the period of 1980 to 2100. These indices are analyzed for both their changes over the timeseries but also at Global Warming Levels of 1, 1.5, 2, 3, and 4 degrees. In this talk we will present a description of the indices and show the first analysis of selected indices for the European domain. The full dataset of these indices is planned to be made openly available through an online, user-friendly toolkit as part of the I4C project.

How to cite: Outten, S., Raffaele, F., Zazulie, N., and Vandeskog, S. M.: Stakeholder relevant hazard indices in Euro-CORDEX models developed under the EU- Impetus4Change project, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-355, https://doi.org/10.5194/ems2024-355, 2024.

Coffee break
Chairpersons: K. Heinke Schlünzen, Maria de Fatima Andrade, Ranjeet Sokhi
16:00–16:15
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EMS2024-559
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Onsite presentation
Esther Peerlings and Gert-Jan Steeneveld

City dwellers are increasingly exposed to summer heat due to climate change and urbanization. Summer heat, which causes heat stress, is intensified especially at night in urban areas and is projected to become more extreme due to climate change. City dwellers are not just increasingly exposed to this heat outdoors but mainly indoors, as they spend the majority of their time inside their homes. However, observational and modelling studies on indoor heat stress are relatively scarce, especially concerning the interconnections between indoor and outdoor climatic conditions.

This study observes, analyses, and models the evolution of indoor air temperature during Dutch summer heat using two unique crowdsourced datasets. The first dataset consists of long observational records, spanning up to 27 years, from citizen weather stations (CWS) located in seven residences across the Netherlands. This dataset provides insight into the benefits of long-term observations at residences. The second dataset consists of indoor CWS placed by us since 2022 in 100 residences across Amsterdam. This dataset offers insight into the benefits of measuring in a large number of residences.

Conventional high-resolution building energy models are commonly validated in controlled settings. In contrast, our study utilizes real-world residences inhabited by individuals, thereby capturing actual occupant behaviour. Moreover, crowdsourced indoor climate observations, just like ours, often lack supplementary data such as building characteristics and occupant behaviour. Therefore, we adopt an analysis and modelling approach only taking indoor temperature as an input parameter of the residence. We demonstrate that indoor temperature typically warms up more slowly than outdoor temperature but also cools down more slowly. The seven residences in the first dataset had, on average, a lag difference of approximately 260 minutes in the diurnal cycle during summer. Indoor temperature also remained higher than outdoor temperature for up to 5 days after a heatwave. For the 100 residences in the Amsterdam dataset, the analysis results will be presented. To model indoor temperature evolution, we simulated daily changes in indoor temperature evolution with a physics-based statistical model. The model includes outdoor conduction, indoor conduction, and solar transfer components, calculated from indoor temperature observations and outdoor temperature, solar irradiance, and wind observations. Results of this computationally-fast model for the seven residences are promising, with on average a mean absolute error of 0.43 K day-1 during summer. Preliminary results suggest a higher model performance for modelling of the warming of the residences compared to the cooling. The model results for the 100 residences will be presented, providing insight into the variability in model performance for indoor temperature in Amsterdam.

The study's findings illustrate the high potential of the model applied to crowdsourced observations to promote understanding of the fundamental processes influencing indoor temperature response to summer heat.

How to cite: Peerlings, E. and Steeneveld, G.-J.: Unravelling indoor temperature response to summer heat through long-term crowdsourced observations in Dutch residences, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-559, https://doi.org/10.5194/ems2024-559, 2024.

16:15–16:30
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EMS2024-623
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Onsite presentation
Rita Pongrácz and Zsuzsanna Dezső

As a consequence of global warming, heat waves become longer lasting, more frequent, and more intense in extratropical regions. Summer heat stress often occurs simultaneously with drought events causing compound impacts in the affected region. In order to analyze such coincidences in a mid-latitude continental, Central/Eastern European city (i.e., Budapest, the capital of Hungary with 1.7 million inhabitants), local temperature and humidity conditions provided by satellite data, are evaluated. So, the unique 22-year-long time series of continuous measurements from the MODIS instrument on NASA's Terra and Aqua satellites was used to study the surface urban heat island (SUHI) pattern, surface temperature and humidity in detail.

A significant warming trend can already be identified in the surface temperature data during the period of 2001-2022. The analysis of summers shows that the SUHI intensity decreases as the rural area around the city becomes warmer, especially in July and August. When less water is available in the rural area in a drought event, the lack of latent heat thus facilitates the warming of the surface temperature in the rural area as well, as in the urban area, because these conditions are unable to reduce the surface temperature via the latent heat as usual. This way, the SUHI intensity is mainly determined by the rural surface temperature. The SUHI is very weak during summers with frequent and intense heat waves and droughts, due to the fact that the land surface temperatures are very high in both urban and rural areas resulting in very little difference between the built-up area and the vegetation-covered surrounding. This phenomenon is analyzed in the present study in detail for the years 2003, 2007, and 2022, when intense heat waves occurred in the region. Such detailed analysis aiming to understand the complex environmental processes in the urban environment is essential in order to develop effective adaptation strategies to the upcoming challenges of climate change, which will probably result in increasing frequency and persistence of heat waves and droughts in the future, with adverse effects to the quality of the life of the urban population.

Acknowledgements: Research leading to this study has been supported by the Hungarian National Research, Development and Innovation Fund (under grant K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).

 

How to cite: Pongrácz, R. and Dezső, Z.: Analysis of the compound impact of heat waves and droughts in the urban environment, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-623, https://doi.org/10.5194/ems2024-623, 2024.

16:30–16:45
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EMS2024-880
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Onsite presentation
Benjamin Le Roy and Diana Rechid

Extreme weather events such as heat waves and heavy precipitation are already having an impact on urban areas around the world, and their frequency and/or intensity are expected to increase as a result of ongoing global warming. Local decision-makers need high-resolution urban climate information to plan and adapt tomorrow's cities. This information needs to be tailored to their needs and to different geographical contexts (e.g. by representing mountainous areas, coastal lines or city characteristics). It must also be appropriate in terms of time scale (e.g. from a particular extreme event to climatological timescales) and cover the range of uncertainties. Today, regional climate information is often derived from Global Climate Models (GCMs) that are downscaled to the local scale using statistical tools, or Regional Climate Models (RCMs) such as those used in the CORDEX initiative. Long-term RCM simulations reach horizontal resolutions of the order of ten kilometers and offer added value in certain respects compared with their driving GCM, but these resolutions are not sufficient in certain specific contexts such as cities, or in highly heterogeneous mountainous areas or along coastlines. The latest generation of RCMs, known as Convection Permitting Regional Climate Models (CPRCMs), now achieve resolution down to the kilometer scale and can be used to better represent these heterogeneous land surfaces, potentially offering new insights into local climate change. Here, we analyze simulations carried out as part of the CORDEX Flagship Pilot Study on Convection (3 km). We first investigate the CPRCMs’ ability to represent the historical urban climate of different European cities, compared with their lower-resolution counterparts. We then study the evolution of various urban climate impact indicators in the future under a high-emissions scenario. We analyze the effects of the increased resolution, choice of urban parameterizations, land cover representation approaches (dominant versus fractional cover approaches) and land cover datasets. Finally, we compare the range of uncertainties displayed by the new high-resolution simulations against the previous CORDEX ensemble.

How to cite: Le Roy, B. and Rechid, D.: What can high-resolution regional climate simulations tell us about the future urban climate of European cities?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-880, https://doi.org/10.5194/ems2024-880, 2024.

16:45–17:00
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EMS2024-1084
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Onsite presentation
Tomas Halenka, Gaby Langendijk, and Peter Hoffmann

Cities play a fundamental role in climate at local to regional scales through modification of heat and moisture fluxes, as well as affecting local atmospheric chemistry and composition, alongside air-pollution dispersion. Vice versa, regional climate change impacts urban areas and is expected to increasingly affect cities and their citizens in the upcoming decades. Simultaneously, the share of the population living in urban areas is growing and is projected to reach about 70 % of the world population by 2050. This is especially critical in connection to extreme events, for instance, heat waves with extremely high temperatures exacerbated by the urban heat island effect, in particular during night-time, with significant consequences for human health. Thus, cities are becoming one of the most vulnerable environments under climate change.

Additionally, from the perspective of recent regional climate model development with increasing resolution down to the city scale, proper parameterization of urban processes plays an important role to understand local/regional climate change. The inclusion of the individual urban processes affecting energy balance and transport (i.e. heat, humidity, momentum fluxes, emissions) via special urban land-surface interaction parameterization of local processes becomes vital to simulate the urban effects properly. This will enable improved assessment of climate change impacts in cities and inform adaptation and/or mitigation options, as well as adequately prepare for climate-related risks (e.g. heat waves, smog conditions, etc.). Actually, IPCC is preparing the Special Report on Cities and Climate Change in 7th assessment cycle, where these aspects will be considered.

We introduced this topic to the CORDEX platform aiming to provide regional climate downscaling, within the framework of so-called flagship pilot studies on challenging issues and gaps in regional climate change knowledge. The main aims and progress of this activity will be presented, especially preliminary analysis of Stage-0 experiments using case studies of heat wave and convection episode within ensemble simulations for City of Paris by models from different groups over the world.

How to cite: Halenka, T., Langendijk, G., and Hoffmann, P.: CORDEX Flagship Pilot Study URB-RCC: Urban Environments and Regional Climate Change, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1084, https://doi.org/10.5194/ems2024-1084, 2024.

17:00–17:15

Orals: Wed, 4 Sep | Lecture room 203

Chairpersons: Ranjeet Sokhi, Maria de Fatima Andrade, Pavol Nejedlik
III. Air Quality in urban areas
09:00–09:30
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EMS2024-923
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solicited
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Onsite presentation
Mailin Samland, Ronny Badeke, David Grawe, and Volker Matthias

Air pollution is threatening human health worldwide, especially in urban areas. Legislative actions have successfully decreased pollutant concentrations in European countries. However, while exhaust emissions from road traffic have decreased over the last decades, non-exhaust emissions remain and tend to increase. 
In this study, tyre and brake wear emissions are quantified applying a bottom-up model for the city of Hamburg in 2018. Their dispersion and contribution to total particulate matter (PM) concentrations are investigated with the urban scale chemistry transport model EPISODE-CityChem. For this purpose, EPISODE-CityChem 1.8 has been extended to include six new particle components. These are tyre and brake wear in the three size classes: PM2.5, PM2.5-10 and PM10+, airborne particles with a diameter of over 10 µm. The emission factors for PM10 for tyre and brake wear from the National Atmospheric Emission Inventory of the UK are used as a starting point to derive the emission factors for the new particle classes. These are combined with the mass size distribution of the total suspended particles from EMEP.
PM concentrations at traffic stations show a higher monthly mean contribution of tyre and brake wear to the total PM2.5 and PM10 than at urban background stations. The contribution of tyre and brake wear to the total PM2.5 concentrations varies throughout the months between 9% and 16% at traffic stations and between 2% and 6% at urban background stations.
The particle concentrations from tyre and brake wear vary locally and seasonally, which could be a difficulty in adhering to the recommended guideline values for particle concentrations, especially since the inner city of Hamburg experiences considerable PM concentrations caused by tyre and brake wear emissions.
The results of this study can be transferred to other large European cities with high traffic volumes and can help to understand the problem's scope, as measurements rarely differentiate between particles caused by exhaust vs. non-exhaust emissions.

How to cite: Samland, M., Badeke, R., Grawe, D., and Matthias, V.: Estimation of particle concentrations from tyre and brake wear in an urban environment, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-923, https://doi.org/10.5194/ems2024-923, 2024.

09:30–09:45
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EMS2024-764
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Onsite presentation
Esther Rivas Ramos, Alberto Martilli, José Luis Santiago del Río, Fred Meier, Beatriz Sánchez Sánchez, and Fernando Martín Llorente

Cool roofs have higher solar reflectance and thermal emissivity than conventional roofs, decreasing the temperature of buildings during sunlight hours. This benefits the buildings (reducing the cooling loads) and the environment (improving the outdoor thermal comfort) during summer. However, cool roofs' impact on outdoor air quality is not well known.

Computational Fluid Dynamic (CFD) models allow the evaluation of environmental improvement measures at very high spatial resolution. Nevertheless, microscale studies combining outdoor thermal comfort and air quality at district or city scales have been scarce in the literature due to the computational cost involved.

The objective of this work is to estimate the impact of cool roofs on outdoor thermal comfort and air quality at the district scale. For this purpose, a CFD model is used considering:

  • atmospheric flows through a URANS (Unsteady Reynolds-Averaged Navier-Stokes) approach
  • traffic-related NOX dispersion as a passive scalar
  • thermal loads using a complete radiation model (solar radiation, radiation from the environment, transmission through non-opaque surfaces, and emission from non-transparent surfaces)
  • thermal and optical properties of the building envelope
  • energy storage in walls, floors and roofs (in glazing is negligible) through a non-steady state conjugate heat transfer model between the outdoor and indoor

Firstly, some scenarios of the COSMO experiment (Kawai et al., 2007) are simulated to evaluate the model performance. Finally, the cool roof impact is estimated during 24 hours of a heat wave episode in a district of Madrid (Spain), characterized by a regular morphology (aligned blocks of H=15 m and H/W=1).

Results show that cool roofs modify the urban meteorology (mean radiant temperature, air temperature, wind speed and turbulent kinetic energy), decreasing the Universal Thermal Climate Index, UTCI, at pedestrian height, especially upstream and during hours of higher irradiance. However, depending on the wind speed, cool roofs can generate thermal inversions at building height affecting the pollutant dispersion within the streets. This fact increases the pollutant concentration at pedestrian height.

How to cite: Rivas Ramos, E., Martilli, A., Santiago del Río, J. L., Meier, F., Sánchez Sánchez, B., and Martín Llorente, F.: Impact of cool roofs on thermal comfort and air quality at street level during a heat wave episode in Madrid, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-764, https://doi.org/10.5194/ems2024-764, 2024.

09:45–10:00
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EMS2024-232
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Onsite presentation
Lukáš Bartík, Peter Huszár, Jan Karlický, and Ondřej Vlček

The most significant environmental health risk for the European population is air pollution, especially for people living in urban areas. Fine particulate matter (PM), a mixture of aerosols with an aerodynamic diameter less than or equal to 2.5 μm, is among the pollutants with the most critical threat to human health in European urban areas. Despite the substantial spatial and temporal variability of the chemical composition of fine PM in Central Europe, it is generally dominated by organic matter and secondary inorganic aerosols, with organic matter being the main contributor to total submicron PM.

 

Modeling organic aerosol using chemical transport models (CTMs) has been problematic for decades, with CTMs often underestimating its concentrations. Potential sources of this deficiency in CTMs include:

(1) simplifying assumptions applied in the model description of organic aerosol,

(2) uncertainties in the model mechanisms describing gas phase chemistry since these mechanisms determine the concentrations of gaseous precursors of secondary organic aerosol,

(3) missing emissions of intermediate-volatility and semivolatile organic compounds (IVOCs and SVOCs) in emission inventories used in CTM simulations.

 

In this work, we focused on investigating the impacts of these sources of uncertainty on the concentrations of organic aerosol in six large cities of the Central European region (Prague, Vienna, Budapest, Berlin, Munich, and Warsaw). For this purpose, we performed a series of model simulations employing an offline coupled modeling framework consisting of the Weather Research and Forecast (WRF) Model and the Comprehensive Air quality Model with Extensions (CAMx) on the Central European domain with a horizontal resolution of 9 km for the period covering the years 2018 and 2019. More specifically, we focused on assessing the influence of two mechanisms for organic aerosol (SOAP, 1.5-D VBS), three mechanisms of gas-phase chemistry (CB6r2, CB6r5, and SAPRC07TC), and several different source-specific parameterizations of IVOCs and SVOCs.

How to cite: Bartík, L., Huszár, P., Karlický, J., and Vlček, O.: Modeling secondary organic aerosol over urban areas of Central Europe: uncertainties linked to different mechanisms and parameterizations, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-232, https://doi.org/10.5194/ems2024-232, 2024.

10:00–10:15
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EMS2024-928
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Onsite presentation
Tom Kokkonen, Giancarlo Ciarelli, Men Xia, Yongchun Liu, Chao Yan, Wei Nie, Aijun Ding, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala

Recently, Kulmala et al. (2021) proposed that in eastern China, a cluster of megacities could be classified as one huge continuous urban area – a gigacity. Already now about 10% of the global population is living in the Chinese Gigacity confined roughly by the lines Shanghai-Xian-Beijing. Gigacity region has huge areas of increased surface roughness and urban heat and pollution islands. These together can strongly influence the local scale meteorology (Ding et al., 2016; Kokkonen et al., 2019).

There are essentially three different meteorological pollution regimes in the Chinese gigacity area having different driving processes of haze: 1) strong synoptic scale winds, leads to effective ventilation of the urban areas and transports local emissions to areas outside gigacity, frequent new particle formation (NPF) due to low condensation sink with sufficient amount of precursor gases available, 2) weak synoptic scale winds, local circulation with clear diurnal cycle is dominating (e.g., mountain-valley and land-sea breeze), local emissions with frequent NPF events together with weakening boundary layer dynamics (BLD) are deteriorating the air quality and slowly pushes the conditions towards the next regime, and 3) haze formed through a mixture of long-range transport, NPF, and local emissions, suppressed radiative driven local circulation (e.g., mountain-valley breeze) and BLD, stagnant conditions with no effective ventilation and the air quality is deteriorating further.

Moreover, boundary layer dynamics – as well as meteorological conditions in general – are interlinked with the pollution regimes, e.g., changes in meteorological or pollution conditions might cause shifts in either way in different regimes described.

We are utilizing continuous, comprehensive observations of atmospheric composition and fluxes from two flagship stations in the gigacity region: the SORPES in Nanjing (Ding et al., 2016) and the BUCT-AHL in Beijing (Liu et al., 2020). In addition, the national meteorological and air quality networks will enable spatial analyses together with reanalysis data.

We are focusing especially on: 1) how boundary layer dynamics and local and synoptic scale meteorological conditions affect haze severity and vice versa, 2) the effect of gigacity heat and pollution islands and surface roughness on atmospheric circulation and precipitation. Our preliminary results have shown e.g. that in Beijing the radiative effect of haze on the BLH has a strong seasonal behaviour with a dependence on the surface heat fluxes. The effect was strongest during autumn, winter and spring months when the decrease of BLH was 40–56 % due to the haze.

Ding et al., Geophys Res Lett, 43, 2873-2879, 2016.

Kokkonen et al., Atmos Chem Phys, 19, 7001-7017, 2019.

Kulmala et al., Atmos. Chem. Phys., 21, 8313-8322, 2021.

Kulmala et al., Environ Sci Atmos, 2, 352-361, 2022.

Liu et al., Big Earth Data, 4, 295-321, 2020.

How to cite: Kokkonen, T., Ciarelli, G., Xia, M., Liu, Y., Yan, C., Nie, W., Ding, A., Kerminen, V.-M., Petäjä, T., and Kulmala, M.: The interactions of multiscale meteorology and haze in the Chinese gigacity, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-928, https://doi.org/10.5194/ems2024-928, 2024.

10:15–10:30
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EMS2024-935
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Onsite presentation
Markku Kulmala and the Working group

Large fractions of atmospheric aerosols, both locally and globally, relevant to air quality and climate are produced via new particle formation (NPF; Kerminen et al., 2018; Chu et al., 2019; Kulmala et al., 2021). Kulmala et al. (2021) showed that NPF and secondary aerosol formation contribute to over 2/3 of the haze particle number and over 80% of the corresponding mass in Beijing.

We combine the following tools to find out physical and chemical mechanisms of atmospheric NPF: i) targeted laboratory experiments, ii) comprehensive in situ observations, iii) comprehensive vertical observations, iv) satellite remote sensing and v) multi-scale modelling.

We investigated a closure on sub-6 nm atmospheric aerosol particles and clusters showing that present observations can detect a major fraction of existing atmospheric clusters (Kulmala et al. 2022a). Our second finding, based on long-term measurements in four very different environments, was that even on days traditionally considered as non-event days (no observed NPF), “quiet NPF” occurs with formation rates between 2–20% of traditional NPF event days (Kulmala et al. 2022b). Thirdly, we investigated the growth of newly-formed particles into sizes relevant to climate and air quality using simulations in two different environments: 1) Beijing, a megacity in China, and 2) SMEAR II station, a boreal forest in Finland. Our simulations for Beijing showed that NPF is capable of giving large contributions of haze particle mass and number concentrations (Kulmala et al. 2022c). The results indicate that reducing primary particle emissions may not decrease PM pollution effectively in heavily polluted environments without simultaneous reductions for precursor gases responsible for NPF and subsequent particle growth. At SMEAR II, we simulated the role of NPF in the Continental Biosphere-Atmosphere-Cloud-Climate (COBACC) feedback mechanism (Kulmala et al. 2023). We found that outside the periods when NPF events tend to be rare at SMEAR II, NPF gives a dominant contribution to both condensation sink and cloud condensation nuclei concentration – the two most relevant quantities in the COBACC feedback mechanism. As a side product of our observations, we found surprisingly low variability in growth rates of newly formed particles in both Beijing and SMEAR II. This points toward a potentially important role of multiphase reactions causing the bulk growth of newly formed atmospheric particles – a phenomenon that needs to be investigated in more detail in the future.

Chu, B. et al., Atmos. Chem. Phys., 19, 115–138, 2019.

Kerminen et al., Environ. Res. Lett., 13, 103003, 2018.

Kulmala et al., Faraday Discuss., 226, 334–347, 2021.

Kulmala et al., J. Aerosol Sci., 159, 105878, 2022a.

Kulmala et al., Front. Environ. Sci., 10, 912385, 2022b.

Kulmala et al., Environ. Sci.: Atmos., 2, 352-361, 2022c.

Kulmala et al., Boreal. Env. Res., 28, 1-13, 2023.

How to cite: Kulmala, M. and the Working group: The impact of atmospheric new particle formation on air quality, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-935, https://doi.org/10.5194/ems2024-935, 2024.

Coffee break
Chairpersons: K. Heinke Schlünzen, Ranjeet Sokhi, Jan-Peter Schulz
11:00–11:15
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EMS2024-973
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Onsite presentation
David Grawe, Ummugulsum Alyuz, Somayyeh Arghavani, Penny Boorman, Sandro Finardi, Tomas Halenka, Paola Radice, Mailin Samland, Ranjeet Sokhi, and Alberto Troccoli

Climate change and air quality research are closely related research areas that have often been investigated with different objectives. However, addressing both topics as a joint approach can lead to synergies and help to avoid counteracting effects, where mitigating one may exacerbate the other. The convergence of methods and approaches is necessary to consider on the one hand the climate trend and forcing in mitigation scenarios applied by the air quality community and on the other hand to better understand and describe the impact of short-lived climate pollutants on the regional climate.

The project FOCI aims to analyse non-CO2 forcings on both climate and air quality and therefore requires a joint approach. A core task of the project is the application of regional climate and urban scale models driven by global earth system models to describe continental to urban scale air quality under present and future climate conditions. The results of these processes will be used to investigate possible mitigation and adaptation scenario options.

The present and future anthropogenic emissions required for such model investigations need to be consistent with CMIP6 historical climate reconstruction and future scenario simulations. CMIP6 has been based on CEDS emissions that are therefore the necessary reference for FOCI activities. One critical aspect is that pollutants considered in CEDS do not include particulate matter (PM2.5 and PM10), but only its black carbon (BC) and organic carbon (OC) components. This is understandable considering the objective for which CEDS has been built, but it would cause a significant underestimation of particulate matter concentrations and raises the need to define a method to estimate the non-speciated PM2.5 and PM10 emissions from the available information.

In order to derive PM emissions for CEDS we investigate a number of approaches based on the use of different proxies from the EDGAR database. In particular, we consider the feasibility of deriving PM2.5 from BC and OC as the main components of fine particulate matter. For emission sectors where BC and OC is not available in the emission inventories, we explore the possibility of using alternative proxies including NOx. By combining the different approaches we derive PM2.5 emissions for CEDS at a spatial grid resolution of 0.1 degree and compare these for each main emissions sector.

These estimated dataset of consistent CEDS and particulate matter emissions are used in the FOCI project numerical models to describe continental to urban scale air quality under present climate conditions. We also discuss the implications of employing our approach to derive consistent emissions for particulate matter in conjunction with SSP emission data for projections to ultimately evaluate the impact of key radiative forcers on climate and societal systems.

How to cite: Grawe, D., Alyuz, U., Arghavani, S., Boorman, P., Finardi, S., Halenka, T., Radice, P., Samland, M., Sokhi, R., and Troccoli, A.: Harmonisation of historical and future emission data for climate and air quality modelling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-973, https://doi.org/10.5194/ems2024-973, 2024.

11:15–11:30
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EMS2024-999
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Onsite presentation
Clemens Drüe

This study models the dispersion of historic air pollution from pottery kilns in the Roman city Augusta Treverorum (Trier). It aims to improve the understanding of their impact on urban air quality during different historical phases. Utilizing archaeological data on pottery locations and historical urban growth patterns, we simulated air pollution levels across the city, focusing on periods before and after the relocation of pottery kilns from various sites spread out over the settlement area to a confined pottery district near the Mosel River. This district is locate in the southwest corner of the city, which is striking as this position is upwind to the city center for the most frequent wind directions along the valley axis. All modern smoke-emitting industry accordingly is found in the opposite northeastern part of the city.

For the simulation we used the German regulatory pollution dispersion model AUSTAL, driven by weather data from the European reanalysis. The sources were modeled after measurements taken during experimental pottery production by LEIZA, Mains in a reconstructed kiln. We found that pollution from the sites spread out over the city predominantly affected the city's northern half, where significant buildings such as the Emperor's Palace and temples were located. The production sites in the pottery district, in contrast, have been impacting the southern part of the city, that must have been a predominantly residential area. This impact is rather independent from the location of a kiln inside the pottery district. The results suggests that this pattern is not a random outcome, but a result urban planning decisions in Augusta Treverorum that were influenced by air pollution, demonstrating a historic example of industrial activity's environmental implications.

 

How to cite: Drüe, C.: A Simulation Study Air Pollution Impact from Roman Potteries in Augusta Treverorum (Trier), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-999, https://doi.org/10.5194/ems2024-999, 2024.

11:30–11:45
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EMS2024-93
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Onsite presentation
Yu Zou, Xianghong Guan, Rosa Flores, Xiaolu Yan, Liya Fan, Tao Deng, Xuejiao Deng, and Daiqi Ye

Oxygenated volatile organic compounds (OVOCs) affect the formation of atmospheric ozone (O3), secondary organic aerosol (SOA), and free radicals, and have complex sources such as anthropogenic and biogenic direct emissions and through series of secondary oxidation reactions of nonmethane hydrocarbons (NMHCs). However, understanding sources of OVOCs in the atmosphere still has large uncertainties. In this study, an improved OVOC source apportionment model was developed by principal component analysis (PCA) and multiple linear regression (MLR) based on the online monitoring of NMHCs and OVOCs in a dense urban agglomeration in the winter. The modelled concentrations were in good agreement with the measured concentrations (R2=0.56-0.97). The concentrations of major OVOCs, except for 2-methylacrolein, were greatly affected by anthropogenic sources (15.8-76.8%) and secondary generation (0.0-51.7%), while transport and natural sources contributed to 0.0-26.8% and 0.0-32.0%, respectively. The selection of isoprene as the natural tracer led to an underestimation of the OVOC species from primary emission and an overestimation from natural sources. In addition, photochemical reactions significantly reduced the simulation accuracy of the model for NMHCs in the afternoon, with the R2 of 0.60 ± 0.23, which was lower than the overall value of 0.82 ± 0.11. However, the R2 for OVOCs (0.83±0.14) did not decrease significantly in the afternoon due to the compensation of secondary oxidation. Furthermore, the concentration gradient distribution of the species gradually changes from a normal distribution to an exponential normal distribution with a decrease in concentration, the accuracy of the model was influenced by the degree of matching between tracer and species concentration gradient as species concentration change. Developing models with additional tracers at different concentration levels may enhance the robustness of the OVOC source apportionment model without increasing its complexity.

How to cite: Zou, Y., Guan, X., Flores, R., Yan, X., Fan, L., Deng, T., Deng, X., and Ye, D.: OVOCs source analysis based on an improved source apportionment model and its influencing factors: A case study of a dense urban agglomeration in the winter, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-93, https://doi.org/10.5194/ems2024-93, 2024.

IV. Adaptation/mitigation measures in the urban areas
11:45–12:00
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EMS2024-547
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solicited
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Onsite presentation
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Nils Eingrüber, Karl Schneider, Udo Nehren, and Verena Dlugoß

The urban population is particularly affected by the consequences of climate change. The increasing frequency and intensity of extreme weather events such as heat, drought, extreme precipitation and flooding has significant negative effects on human comfort, well-being, health and mortality rate. Sustainable urban development therefore requires the implementation of climate change adaptation measures as well as the acceptance, activation and participation of urban dwellers. The feasibility and effectiveness of climate change adaptation measures vary spatially due to the given local conditions. Additionally, the awareness, ability and willingness to act and pay differ between social milieus. The aim of this study is to analyse how a difference in the milieu-related willingness to act and operational ability to implement climate change adaptation measures affects the heat mitigation potential in two neighbourhoods in the city of Cologne/Germany with a significantly different social milieu composition. To investigate the relationship between the degree of willingness to act and the cooling effects of technical and nature-based solutions for heat mitigation, scenario analyses are performed using the physically-based, 3D gridded urban microclimate model ENVI-met for a neighbourhood in Cologne Suedstadt which is dominated by the social milieus of performers, post-materialists, neo-ecologists and conservatives. The model was parameterized based on field measurements and remote sensing data, and has been validated by a setup quality-controlled, densely-distributed microclimate sensor network in the study area. The agent-based scenarios represent a different percentage of residents willing to implement climate change adaptation measures in their living environment. These measures include facade greenings, roof greenings, cooling building materials and light surfaces. To identify the microclimate sensitivity, a scenario with a willingness to act of 0%, 25%, 50%, 75% and 100% of all dwellers in the neighbourhood is designed in the model domain. Simulation results show that the willingness to act has a significant influence on the cooling effect and thus the heat mitigation potential in this study area. In future research, the willingness to act in this upper-middle class neighborhood will be compared to a neighbourhood in Cologne Muelheim which has a significantly different social structure and is dominated by consumer-hedonism and traditional milieus. It will also be investigated how citizen science approaches, participation and activation measures can change the willingness to act and the acceptance of climate change adaptation measures in these contrary urban neighborhoods. 

How to cite: Eingrüber, N., Schneider, K., Nehren, U., and Dlugoß, V.: Climate change adaptation through citizen participation: Simulation of the effect of willingness to act on the heat mitigation potential in urban neighborhoods with different social milieu composition , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-547, https://doi.org/10.5194/ems2024-547, 2024.

12:00–12:15
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EMS2024-606
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Online presentation
Marianne Bügelmayer-Blaschek, Alexandra Millonig, and Martin Zach

As Climate Change challenges threaten future quality of life, urgent action to mitigate CO2 emissions as well as to adapt to current and future risks is mandatory. Cities are crucial for both areas: mitigation, because 2/3 of the world wide population live in urban areas and thus cause XX emissions; adaptation: because the settlements structure, mainly sealed areas, enhances the negative effects of climate change. Within the Horizon Europe Research and Innovation Action KNOWING [1] climate mitigation pathways, which represent timelines of specific interventions, are compiled for different regions.

Urban areas are a core region type within KNOWING as they are particularly vulnerable towards climate change. Over the past years cities have responded by defining strategies regarding mitigation and adaptation that identify measures for specific sectors. Although there is vast knowledge with respect to future impacts and possible mitigation and adaptation measures within different sectors (e.g. transport, energy, etc.), implementation remains inadequateExisting strategies often tackle the different sectors separately, thus ignoring possible spill-over and rebound effects of one measure taken to other areas

KNOWING develops a framework for defining Climate Mitigation Pathways based on understanding and integrated assessment of climate impacts, adaptation strategies and societal transformation. The modelling framework will be used to assess the interrelations between potential risks of climate responses, i.e., public and private adaptation and mitigation strategies. For instance, the installation of air conditioning can improve living conditions inside, but it also has a two-fold negatively impact due to its heat and CO2 emissions.

To quantify the interrelations, the chosen comprehensive approach builds upon a system dynamics (SD) model for quantifying cross-sectoral influences of measures taken in different sectors (e.g., energy, mobility, land use, construction, agriculture) affecting the overall emission budget. Therefore, specific so-called domain models for mitigation (e.g. energy demand model MAED-City, energy supply IES-opt) and adaptation (e.g. urban climate PALM4U, flooding model SFINCS, ICM-Infowork) are applied, fed with high resolution (5x5km) WRF input data. Based on this systems perspective, mitigation pathways along optimised combinations of interventions in the different sectors are developed. The framework also includes a coping behaviour model that provides guidance on how measures can be implemented in an equitable way to enable a just and broadly supported transition.

How to cite: Bügelmayer-Blaschek, M., Millonig, A., and Zach, M.: Climate Mitigation Pathways for Cities – enabling a just transition through quantified actions?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-606, https://doi.org/10.5194/ems2024-606, 2024.

12:15–12:30
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EMS2024-765
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Onsite presentation
Jesús Soler, Montserrat Martinez, Robert Goler, Marianne Bügelmayer-Blaschek, Martin Schneider, and Andrea Hochebner

Human-made climate change is increasingly impacting our living conditions, destroying infrastructure and threatening lives. The recent years and months have led to unprecedented events and record-breaking temperatures, with March being the tenth month in a row being the hottest so far (Copernicus).  

Not only rising temperatures but also altered precipitation patterns pose a challenge to the existing urban environments and thus to 2/3 of the human population (REF). Cities are especially affected since they consist of mainly sealed surfaces, which enhance climate change impacts such as increased heat or intensified precipitation events due to their different characteristics as natural areas (e.g. albedo, heat capacity, infiltration). 

Within KNOWING two climate impacts are investigated comprehensively – flooding (fluvial, pluvial) and its impact on infrastructure as well as heat and its impact on health. Therefore, two urban areas (Granollers, Spain and Tallinn, Estonia) are considered. To quantify possible interventions to adapt to current and future climate change impacts, two different models are applied: PALM-4U [1] and ICM-Infoworks. PALM-4U is an urban climate model used for quantifying the impact of greening on urban heat load. ICM-infoworks is used for assessing adaptation measures to lessen pluvial flooding. As both models rely on land use, the changes planned to adapt to heat (e.g. greening and unsealing) and those for reducing flooding (retention areas, unsealing) coincide.  

Within PALM-4U interventions such as increased tree cover, implementation of recreational parks, renaturalization of rivers and building-related measures (e.g. green roofs, retrofitting) are considered. All interventions leading to increased unsealing of areas and thus infiltration, also lessen the risk of flooding and can thus be implemented within ICM-Infoworks, quantifying the impact of the same interventions on flood risk. By assessing the impact of the same interventions within two models and concerning two different climate risks (heat and flooding) the double effectiveness is accounted for, thus allowing the holistic approach of adaptation to climate change. 

How to cite: Soler, J., Martinez, M., Goler, R., Bügelmayer-Blaschek, M., Schneider, M., and Hochebner, A.: Climate risks in cities – how flooding and heat prevention can be tackled holistically. , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-765, https://doi.org/10.5194/ems2024-765, 2024.

12:30–12:45
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EMS2024-1082
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Onsite presentation
Jacobo Gabeiras, Chantal Staquet, and Charles Chemel

The subject of this project is centered in the adaptation to climate change during heat waves in the 21st century in the area of Grenoble, France. The adaptation measures concern urban planning, such as the vegetation of the city, the increase of the albedo of buildings, design of water bodies distribution and others. Particular attention is paid to the impact of these measures on air quality. The objective is to determine, the urban planning to be implemented to combat the increase in temperatures due to climate change.

This work relies on the widely used open-source atmospheric numerical model WRF (Weather Research and Forecast). First, a calibration run is performed over a past heat wave event in the valley for verification and obtention of the conditions that produce higher fidelity results contrasted with real measures of the event. This involving especially the land cover description and model parametrization. After, an analog model run over a future heat wave event in 2052 extracted from climate projections. This is used as a control run to compare with different results, where adaptation scenarios to combat climate change are applied.

For the study of different urban planning scenarios, the WRF model is used coupled with the model BEP+BEM (Building Effect Parametrization + Building Energy Model), developed by Alberto Martilli, with whom we work in collaboration. This model parametrizes the urban-atmosphere interaction with a high-level representation of the city that allows for designing different scenarios regarding the land cover, the albedo and the urban canopy.

The location of the study makes this project of great interest as well as computationally challenging, due to the mountainous area and steeps slopes surrounding the city. These results will be of great interest to local communities and policy makers as they will inform future decisions on urban planning and will contribute to the attractiveness of cities.

How to cite: Gabeiras, J., Staquet, C., and Chemel, C.: Adaptation scenarios to climate change during heatwaves in the Grenoble metropolitan area, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1082, https://doi.org/10.5194/ems2024-1082, 2024.

12:45–13:00
Lunch break
Chairpersons: Pavol Nejedlik, Arianna Valmassoi, K. Heinke Schlünzen
V. Development and assessment of methodologies for the urban areas
14:00–14:15
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EMS2024-727
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solicited
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Tromp Foundation Travel Award Lecture
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Onsite presentation
Matej Žgela, Alberto Vavassori, and Maria Antonia Brovelli

The effects of climate change have never been as pronounced as they are now, however, simultaneously, urban areas are experiencing additional local-scale anthropogenic effects due to the modification of the natural environment. Consequently, urban heat islands form, amplifying the heat load in the cities and heightening the vulnerability of citizens to heat-related issues.

In the context of Europe, the fastest-warming continent in the world, significant impacts on living conditions will occur as a result of numerous climate risks. Furthermore, in a recently published European Climate Risk Assessment, heat risk is identified as one of the two main risks for which urgent action is needed. However, implementing mitigation measures in urban areas is often slow, highlighting the need to employ geospatial technologies to aid the process.

To address this issue, we identified high heat risk areas and heat-resilient zones in the city of Milan, Italy. High-resolution geospatial datasets, including remotely sensed imagery and official/crowd-sourced in-situ data, were utilised for producing a heat risk index. Main known drivers of heat risk were used as predictors, such as land surface and air temperature, vegetation fraction, surface material composition and others.

The produced heat risk maps were overlayed with population data, selecting the locations of public institutions most used by vulnerable populations - schools, retirement homes, and public health institutions. Institutions’ surroundings have been investigated based on urban geometry, considering their micro-urban morphology and at the neighbourhood scale with local climate zones. Moreover, the research examined the frequency of extreme temperatures occurring in various areas of the city over time and put it in relation to vulnerable population data.

Through detailed analysis of city-scale heat risk, the study has identified the main hotspots and cool spots within the city. The research findings are critical for vulnerable populations facing high heat risks, enabling targeted and straightforward implementation of appropriate heat mitigation measures. Finally, the utilisation of high-resolution geospatial information and multiscale datasets can aid city planners, providing them with crucial scientific insights for informed decisions.

How to cite: Žgela, M., Vavassori, A., and Brovelli, M. A.: A geospatial approach for heat risk estimation by integrating remotely sensed and ground-based data in Milan, Italy, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-727, https://doi.org/10.5194/ems2024-727, 2024.

14:15–14:30
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EMS2024-354
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Onsite presentation
Akshay Patil and Clara Garcia-Sanchez

Wind flow predictions in realistic urban areas are sensitive to a wide range of governing parameters such as building resolution, wind incidence, urban morphology, and underlying topography to list a few. In this study, we quantify the impact of the level of detail (LoD) of the urban built environment and the inflow direction (θ) on wind-safety for urban-air mobility using a Reynolds-Averaged Navier-Stokes (RANS) simulation framework. To isolate the effect of LoD and θ, we chose the TU Delft campus (radius of ~ 1 km) and the city of Den Haag (radius of ~ 1.5 km) as representative urban environments that contain a variety of urban fabric and incident wind conditions.

The simulation framework consists of steady state Reynolds-Averaged Navier-Stokes simulations using a second-order accurate finite volume formulation that solves the governing equations using the SIMPLE algorithm at 5-degree resolution (i.e., 72 θ’s over a 360-degree range) with a reference wind velocity of 5 m/s at 10 m above the ground. In addition to varying the inflow wind direction, we also compare two LoD’s, specifically, LoD1.2 (lower quality of building resolution, industry standard for wind engineering simulations) and LoD2.2 (higher quality of building resolution), resulting in a total of 288 simulations.

First, we assessed the effect of θ resolution on the prediction capabilities of the wind-rose weighted directionally-averaged peak wind velocities (Ua) and found that when compared to the 5-degree resolution cases with 10-, 15-, and 20-degree resolution, there is a selection bias on how accurately high-wind regions are predicted. Specifically, when the Ua is computed using 5- and 15-degree resolution, there is a better agreement as opposed to the 10- and 20-degree resolution case. These results suggest that even with a minimum resolution of 10-degree’s (for θ) the peak Ua locations can be subject to a selection bias for both, simple and relatively complex wind-roses. Next, we studied the effect of varying LoD’s and found that LoD2.2 shows substantially different peak Ua regions when compared to LoD1.2. Directly comparing these two LoDs, we find that minimally LoD2.2 should be used for cases where peak Ua are of interest at approximately 10-20 m height above the ground which are of most interest in terms of urban air mobility.

This work represents a systematic review of the effect of wind incidence direction and level of detail on the flow prediction capabilities in realistic urban environments. We anticipate that our findings will be useful to urban planners and engineers working to improve the air-quality, wind comfort, and explore the possibilities of UAV’s as a potential mode of last mile mobility within the urban-air space, to list a few.

How to cite: Patil, A. and Garcia-Sanchez, C.: Understanding the impact of varying geometry level of detail in multi-direction urban RANS simulations tailored for urban air-mobility viability., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-354, https://doi.org/10.5194/ems2024-354, 2024.

14:30–14:45
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EMS2024-382
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Onsite presentation
Nooshin Nowzamani, Björn Maronga, Lara van der Linden, and Benjamin Bechtel

The interaction between urban microclimate and building energy balance is pivotal in comprehending urban thermal behavior, with buildings' energy use contributing to waste heat that affects the intricate mass and momentum transactions characteristic of urban microclimates. Large-Eddy Simulation (LES) models have improved insights into these complex dynamics due to increased computational power. However, complexities and data uncertainties in real urban settings may compromise LES accuracy. Therefore, understanding model sensitivity to input data uncertainties is crucial for assessing potential deviations and prioritizing data collection parameters.

This study scrutinizes the PALM model 6.0's sensitivity to building typologies and parameters within a residential quarter of Bochum, Germany, examining the trade-offs of modeling detail. Four divergent scenarios are considered. The baseline scenario presupposes homogeneity in building types across the model domain. The second scenario applies PALM’s standard building categories, predominantly delineating four types aligned with building age and building use. The third scenario encompasses an array of 28 building typologies, integrating the TABULA archetypes from the IEE Project 'Typology Approach for Building Stock Energy Assessment'. The first three scenarios maintain a consistent level of architectural specificity within the parent and the child domain, configured as a nesting structure. The fourth scenario distinguishes itself by combining PALM's predefined standard building typologies within the parent domain with the 28 distinct TABULA archetypes within the child domain. ​The underlying hypothesis suggests that increasing the detail in building parameters can potentially amplify the realism of urban environment simulations and augment the accuracy of the results. However, such advancements come with heightened computational demands and more extensive data requirements. The study emphasizes the importance of balancing these considerations to ascertain the most advantageous degree of detail, tailored to various simulation pursuits.

How to cite: Nowzamani, N., Maronga, B., van der Linden, L., and Bechtel, B.: Analyzing the Sensitivity of the LES PALM Model to Building Parameters Using an Archetype-Based Approach, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-382, https://doi.org/10.5194/ems2024-382, 2024.

14:45–15:00
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EMS2024-492
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Onsite presentation
Amber Jacobs, Sara Top, Thomas Vergauwen, and Steven Caluwaerts

Gaps in urban meteorological time series are a widely known phenomenon, occurring in all sorts of urban datasets, ranging from crowd-sourced data till urban climate networks. These gaps cause a problem, since they complicate the analysis and further use of the dataset. Various gap-filling techniques exist to tackle gaps in meteorological time series, including the debiasing of ERA5 reanalysis data. Unfortunately, the evaluation of these ERA5 debiasing techniques are often performed separately and limited to rural locations. Since the ERA5 bias is highly pronounced for urban locations, a good understanding of the performances of the debiasing techniques with respect to urban data is crucial to obtain accurate gap-filling estimates.

To gain a better insight into the most optimal gap-filling techniques for urban temperature time series, we compared five techniques, including three different debiasing techniques that employ a learning period and time window to take into account the seasonal and diurnal characteristics of the ERA5 temperature bias. The evaluation, which is performed by filling manually constructed gaps, shows that small gaps are ideally filled by linear interpolation, while for larger gaps the best performance is obtained through the ERA5 debiasing techniques. For urban locations, the results indicate that it is crucial to correct for the ERA5 bias. We also investigated the most optimal length and placement of the learning period and time window, although the settings of these parameters do not seem to have a significant impact on the gap-filling performance. Based on these results, we designed a gap-filling algorithm that efficiently fills a series of gaps in urban temperature time series by selecting the most optimal gap-filling procedure for each gap. This newly designed algorithm is able to successfully reproduce the urban heat island effect, although a small over- or underestimation might occur.

How to cite: Jacobs, A., Top, S., Vergauwen, T., and Caluwaerts, S.: Filling gaps in urban temperature observations by debiasing ERA5 reanalysis data, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-492, https://doi.org/10.5194/ems2024-492, 2024.

15:00–15:15
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EMS2024-639
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Onsite presentation
Nico Bader, Nicolas Zurfluh, Jungmin Shin, and Sebastian Schlögl

Urban areas face unprecedented challenges due to the combination of growing cities and climate change, with impacts ranging from heatwaves and extreme precipitation to sea-level rise and urban flooding. Artificial surfaces in cities and the differences in the surface structure cause urban areas to overheat significantly compared to rural areas and lead to a high inner-city air temperature variability. As climate change and heat forcing increase, the urban heat island effect will intensify in the future. Understanding the future climate scenarios is crucial for effective planning of adaptation and mitigation strategies.

Climate projections referred to as Global Climate Models (GCMs) and Regional Climate Models (RCMs) do not accurately represent urban-scale climate variables. Computational constraints and limitations in simulating the complexity of earth system processes limit the spatial resolution of climate projections to the order of 10 – 100 km and the time resolution to a daily basis. Hence, climate models are not able to fully resolve the urban heat island effect and the urban air temperature variability which occur on a micro-scale.

This work highlights the importance of downscaled climate prediction data to capture localized effects and uncertainties associated with urban areas. Downscaling climate models to building-level is done by combining the meteoblue City Climate Model (mCCM) - a dynamic statistical downscaling model - with climate projections in the framework of the sixth phase of the Coupled Model Intercomparison Project (CMIP6).

The mCCM is based on a high-resolution model grid with a horizontal resolution of 10 m. It resolves the differences in the surface energy budget and help understanding the air temperature variability and dynamics in an urban environment. The model is fully driven by surface texture parameters derived from high-resolution satellites and meso-scale NWP models. In this framework, the climate signal of CMIP6 data is added to the hourly air temperature time series of the mCCM. This allows the calculation of temperature-related climate indices on a high-resolution grid of 10 m for future time periods and various SSP scenarios. Furthermore, this approach allows to estimate the probability that certain climate indices such as e.g., number of tropical nights, or number of hot days reach a critical threshold.

Enhancing the mCCM with climate predictions creates a reliable information basis for city planners, decision makers, and companies. It helps cities become more resilient, sustainable, and adaptable in the face of a changing climate, ultimately improving the quality of life for urban residents.

How to cite: Bader, N., Zurfluh, N., Shin, J., and Schlögl, S.: Enhance the meteoblue City Climate Model by Climate Projections to assess Urban Climate Hazard, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-639, https://doi.org/10.5194/ems2024-639, 2024.

15:15–15:30
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EMS2024-49
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Onsite presentation
Robert Schoetter, Robin Hogan, Cyril Caliot, and Valéry Masson

Radiative exchange in the complex 3-D urban geometry is a crucial physical process for the urban heat island, building energy consumption, and outdoor human thermal comfort. Urban canopy models calculate radiative exchange by simplifying both urban morphology (e.g. by an infinitely-long street canyon or a regular array of square blocs) and radiative transfer physics. Radiative exchanges are usually calculated with the radiosity method assuming that there is vacuum in the urban canopy layer and that urban materials have a broadband Lambertian reflectivity. This introduces systematic biases, since uniform radiosity on surfaces is assumed and because the distribution of wall-to-wall and ground-to-wall distances corresponds to the simplified morphologies and is therefore systematically different to the one in real districts. Furthermore, it is difficult to take into account a variety of building height, urban vegetation with complex shape, and physical processes like specular reflections by windows, spectral materials, and interaction of radiation with air, aerosols, or clouds in the urban canopy layer. The urban radiation model SPARTACUS-Urban is based on a more realistic hypothesis of urban morphology (exponential distribution of wall-to-wall and ground-to-wall distances), and tree geometry (cylinders). It solves radiative transfer with the Discrete Ordinate Method. This allows to take into account more complex urban geometry and the mentioned physical processes. The urban canopy model Town Energy Balance (TEB) is coupled with SPARTACUS-Urban and the new TEB-SPARTACUS is available in the open-source land surface model SURFEXv9.0. TEB-SPARTACUS keeps the geometrical simplicity of the original TEB, which is that there is no variety of building and tree height at grid point scale. The TEB-SPARTACUS results for the direct and diffuse solar, and the terrestrial urban radiation budget are evaluated for procedurally-generated urban morphologies mimicking the Local Climate Zones (LCZ). Evaluation is made by comparison with results of the newly-developed Monte-Carlo-based reference model HTRDR-Urban. HTRDR-Urban can produce reference results of radiative flux densities in complex urban geometries, including spectral and specular materials, trees with individual leaves, and the participating atmosphere. It is shown that TEB-SPARTACUS improves the solar and terrestrial urban radiation budget for all LCZ, the improvement of radiative observables can be up to 10% of the downwelling solar radiation. A considerable improvement is found for the partitioning between the direct solar radiation absorbed by the walls and the ground. This might help to improve the simulated building energy consumption, and outdoor human thermal comfort. TEB-SPARTACUS also simulates better the impact of trees on the urban radiation budget since it better represents the tree edges. Therefore, TEB-SPARTACUS could help to improve the simulated evapotranspiration or CO2 uptake by urban trees.

How to cite: Schoetter, R., Hogan, R., Caliot, C., and Masson, V.: Coupling the Town Energy Balance with the urban radiation model SPARTACUS-Urban and evaluation with a Monte-Carlo-based reference model, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-49, https://doi.org/10.5194/ems2024-49, 2024.

Coffee break
Chairpersons: Pavol Nejedlik, Arianna Valmassoi, Ranjeet Sokhi
16:00–16:15
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EMS2024-551
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Online presentation
David Santuy, Robert Monjo, and Darío Negro

The current climate change scenario raises the need to study the variability of extreme precipitation patterns of Mediterranean climates, where hydrological risk assessment plays a key role in building resilience. This is why the study of future precipitation characteristics, including concentration at different time scales, emerges as a priority. We present a sophistication of the n-index approach, useful to estimate the monofractal dimension of precipitation, allowing the seasonal characterisation of its regularity at supra-daily scale and of its concentration at a sub-daily scale. The higher the n-index, the more irregular the precipitation, that is, most of the amount is accumulated in shorter duration and more dispersed events. In contrast, if the index is close to zero, precipitation is associated with a more regular regime. By applying the FIClima statistical downscaling to ten Earth System Model outputs for three observatories located in the city of Barcelona (Spain), local climate projections of the n-index have been obtained for the period 2015-2100 under different climate change scenarios (SSP1.26, SSP2.45, SSP3.70, SSP5.85). These projections show a clear upward trend of the index, increasing with the radiative forcing implied by the scenario, and marked by interannual and multidecadal variability. Given this situation of future increase in the irregularity of precipitation for the city of Barcelona, the seasonal distribution of these increases has been studied, characterising trends for each month according to the different scenarios. Increases in rainfall concentration are expected between June and October, associated with intensified and more abrupt convection. To support the spatial coherence of our results, a climatological analysis of the daily n-index has been carried out using a high-resolution data grid (0.2°) for the period [1971-2015] covering the Northeast Spain, observing consistent trends during this period and the spatial distribution of the index. The techniques presented in this study are useful to replicate in other Mediterranean regions in order to improve decision-making in society, where water resource management becomes even more important given the projected decrease in precipitation over the Mediterranean.

How to cite: Santuy, D., Monjo, R., and Negro, D.: Monofractal technique to assess extreme precipitation concentration: A reference study of Barcelona (Spain), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-551, https://doi.org/10.5194/ems2024-551, 2024.

16:15–16:30
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EMS2024-927
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Onsite presentation
Andrea Cecilia, Giampietro Casasanta, Igor Petenko, Alessandro Conidi, and Stefania Argentini

Air temperature (Ta) plays a crucial role in numerous applications, including studies on physical stress conditions and understanding phenomena such as urban heat island (UHI). Ta measurements, acquired from in situ sensors often distributed unevenly, are limited in describing the spatial temperature field pattern. On the other hand, land surface temperature measurements (LST) obtained from geostationary satellites provide a more detailed spatial overview, but represent a different variable. In this work, a method based on machine learning algorithms is presented for converting LST detected from geostationary satellites MSG, into air temperature. To perform the conversion, a gradient boosting algorithm, which is part of the tree-structured family of machine learning algorithms, was implemented. The method is applied to LST and Ta data available for the city of Rome (Italy) during the summers of 2019 and 2020. The Ta data are sourced from 17 weather stations, predominantly consisting of amateur stations whose quality has been verified. Using predictive variables such as instantaneous LST and with delays ranging from 1 to 4 hours, along with other parameters like altitude, imperviousness, land cover, tree cover, grassland, NDVI, and temporal parameters such as time of day, Ta was estimated, designated as the target variable, at points where no in situ measurement sensors are available. The Ta predicted by the model exhibits an average error of 1.2°C during the daytime and 0.8°C at night. This model output has improved the accuracy and spatial resolution of temperature pattern analysis across the city of Rome, compared to analyses based solely on in situ measurements. Furthermore, the spatiotemporal pattern of the UHI, which can now be measured at high resolution, aligns well with the expected pattern.

How to cite: Cecilia, A., Casasanta, G., Petenko, I., Conidi, A., and Argentini, S.: A machine learning algorithm for converting land surface temperature to air temperature and testing in the determination of the urban heat island effect over the city of Rome, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-927, https://doi.org/10.5194/ems2024-927, 2024.

16:30–16:45
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EMS2024-374
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Onsite presentation
Jordi Mazon and Artemi Jaumà

One of the big challenges that the EU has proposed is the mission of 100 cities to become carbon neutral by 2030, and the whole continent by 2050. One of the key points to know is how many CO2 can capture the whole urban tress in a year. This amount of absorption depends on several parameters (type of tree, age, water requirement, …), being weather conditions during the whole year the most relevant. The amount of CO2 captured by a tree can be estimated by using different models. The method and equation proposed by Shadman et al. (2022) has been used in the Co-Carbon Trees Measurement project. This is a citizen science project developed in several cities in the metropolitanean area of Barcelona. The results of the pilot developed in the city of Viladecans (67.000 inhabitants, 15 km south to Barcelona) is presented. In this project more than 700 student measured around 1300 trees in a morning, which data allow to take a magnitude of the carbon captured by the 20.000 trees in the city, and so to know how far is the city to become, a carbon neutral. The project proposes repeat yearly this measurement in the same trees, to calculate the CO2 captures in a year, and to link with some annual meteorological parameters like average temperature and precipitation.

 

Shadman, S., Khalid, P. A., Hanafiah, M. M., Koyande, A. K., Islam, M. A., Bhuiyan, S. A., … & Show, P. L. (2022). The carbon sequestration potential of urban public parks of densely populated cities to improve environmental sustainability. Sustainable energy technologies and assessments52, 102064.

 

 

 

How to cite: Mazon, J. and Jaumà, A.: The citizen science project Co-Carbon Trees Measurement: quantifying the CO2 captured by urban trees, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-374, https://doi.org/10.5194/ems2024-374, 2024.

16:45–17:00
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EMS2024-182
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Onsite presentation
Ge Cheng and K. Heinke Schlünzen

Increasing urbanization requires a better understanding and representation of urban effects and urban canopy processes in weather and climate modelling at various scales. In this work, an urban canopy parameterization (UCP) based on an extended nudging approach is presented. The UCP is implemented in the mesoscale model METRAS with a horizontal resolution of 500 m. The city of Hamburg with heterogeneous surfaces was chosen as the study area. Urban canopy information for Hamburg, including building height and building surface fraction (i.e., the ratio of the surface area occupied by buildings to the total plan area), obtained from the 3D city model of Hamburg LoD1 (Level of Detail 1). were used as input for the UCP.

Model results show that the urban canopy parameterization based on an extended nudging approach can reproduce urban effects on the wind and temperature fields. For example, the UCP can simulate the wind reduction effects due to canopy obstacles in different model levels, with the largest wind reduction simulated in the urban areas with highest values for building surface fraction (densely built areas). In addition, the urban heat island effect as simulated with the single layer flux aggregation scheme in METRAS, was enhanced using the urban canopy parameterization, with the highest intensities in the densely built areas. The results suggest that nudging is a useful tool for modeling aerodynamic and thermodynamic urban effects, which are both important components in understanding the urban environment. Additionally, nudging is an approach that is relatively easy to implement or already implemented in many models. It can be applied to a variety of urban scenarios and resolutions and thus can be a simple approach to better represent urban effects in global-scale weather and climate models.

How to cite: Cheng, G. and Schlünzen, K. H.: Using a simple parameterization for representing the effect of heterogeneous urban canopies in atmospheric models, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-182, https://doi.org/10.5194/ems2024-182, 2024.

17:00–17:15
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EMS2024-106
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Onsite presentation
Konstantina Koutroumanou-Kontosi, Constantinos Cartalis, and Panos Hadjinicolaou

The Eastern Mediterranean and Middle East (EMME) region exhibits continuously accelerated warming, posing a significant threat to cities within this area and thus increasing their vulnerability to climate change. Regional Climate Models (RCMs) serve as valuable tools for climate simulations, but when the focus is given to the urban thermal environment the resolution of their output results is not sufficient. Downscaling techniques can be utilized to improve the spatial resolution of the RCMs and, hence, bridge this gap between the regional and the local scale. The downscaling techniques can be divided into two main categories, the dynamical (DD), and the empirical/statistical (ESD). While DD relies on physical schemes, its computational demands pose challenges for long-term simulations contrary to the ESD which is computationally inexpensive. In this study, both the DD and the ESD techniques are applied to downscale the 2m air temperature from the regional to the local scale for the city of Nicosia, the capital of Cyprus. Concerning the DD, the Weather Research and Forecasting (WRF) model is used to downscale  the ERA5 re-analysis in three different domains, over the EMME region, Cyprus, and Nicosia, with a spatial horizontal resolution of 12km×12km, 4km×4km, 1km×1km respectively, over a 5-year historical period (2008-2012). Detailed information on the urban characteristics is incorporated into the WRF model through the coupling of the Single Layer Urban Canopy Model (SLUCM) as well as with the utilization of the state-of-the-art land use/land cover CGLC-MODIS-LCZ dataset. The ESD utilizes the generated database of the WRF model to establish statistical relationships between the regional and the local scale for the same period by employing advanced machine learning techniques, including Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR). A detailed comparative analysis between the two downscaling techniques as well as an evaluation of the simulation results against observation data from two meteorological stations are performed to assess their accuracy in estimating the air temperature over Nicosia.

Key Words: WRF model; dynamical downscaling; statistical downscaling; urban climate modeling; Local Climate Zones

How to cite: Koutroumanou-Kontosi, K., Cartalis, C., and Hadjinicolaou, P.: A Comparative Analysis of Dynamic and Statistical Downscaling Techniques to Bridge the Gap Between the Regional and the Local Scale: Case Study for Nicosia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-106, https://doi.org/10.5194/ems2024-106, 2024.

Posters: Wed, 4 Sep, 18:00–19:30 | Poster area 'Vestíbul'

Display time: Wed, 4 Sep, 08:00–Thu, 5 Sep, 13:00
Chairpersons: Maria de Fatima Andrade, Arianna Valmassoi, Ranjeet Sokhi
I. Assessment of direct urban influences (posters)
VB35
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EMS2024-203
Friederike Bär, Markus Quante, Volker Matthias, and Bernd Heinold

Besides influencing dynamics, cities are major sources of anthropogenic aerosols. Activated as cloud droplets they can modify the cloud microphysical processes, which can lead to an intensification, delay or even suppression of convective precipitation. However, it is hard to separate the urban cloud aerosol effect from roughness and thermal effects related to the urban morphology and variability in meteorological conditions. Therefore, quantifying this effect is challenging due to the relatively small signal amid high variability.
In this study, we aim to better understand how urban emissions affect clouds and thereby precipitation processes. For this purpose, we use fine resolution simulations including an urban parametrization and a direct aerosol-cloud coupling. use the Consortium for Small-Scale Modeling (COSMO) model online-coupled to the multi-scale chemistry aerosol transport model MUSCAT and the double-canyon urban canopy parameterization DCEP. To simulate a direct aerosol-cloud-precipitation coupling we modified the 2-moment bulk microphysics scheme from COSMO to allow cloud condensation nuclei to be calculated directly from aerosol mass concentrations simulated with MUSCAT, instead of assuming constant cloud condensation nuclei concentrations. A 3-way nesting strategy is applied for the simulations, with the highest resolution area centered over the Leipzig metropolitan area, using a 1km grid spacing.
We employ this setup in a case study on a small-scale convective storm that passed over the City of Leipzig. Sensitivity tests have been performed to investigate how sensitive the simulated precipitation is to changing aerosol concentrations, by varying the input emissions. First results show that a doubling of emissions weakens and shifts the location of maximum precipitation further downstream the urban area. Additional simulations with chemistry boundary values set to zero enable us to assess how urban emissions are transported vertically and how they can influence the convective storm.

 

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany‘s Excellence Strategy – EXC 2037 'CLICCS - Climate, Climatic Change, and Society' – Project Number: 390683824

 

How to cite: Bär, F., Quante, M., Matthias, V., and Heinold, B.: Model Study on Urban Aerosol-Cloud Interactions and their Influence on Precipitation, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-203, https://doi.org/10.5194/ems2024-203, 2024.

VB36
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EMS2024-814
Samuel Barrao, Roberto Serrano-Notivoli, Miguel Ángel Saz, and José María Cuadrat-Prats


The aim of this communication is to use Geographic Information Technologies (GIT)  to improve the characterization of the spatial variability of temperature in urban spaces. For this purpose, an interpolation method has been developed that allows to know the spatial patterns of the maximum, mean and minimum urban temperature of Zaragoza at seasonal scale. Using as a climate database the observatory network of the Clima, Agua, Cambio global y Sistemas Naturales research group, composed of 21 thermohygrometric sensors distributed in different urban areas of the city and its surroundings. We will use daily scale temperature data from March 2015 to December 2022 to apply them in a cokriging interpolation model, complemented with spatial information of different variables. These complementary variables of satellite and territorial origin will be subjected to a previous correlation and regression analysis with temperature, including in the interpolation only those significant variables with higher correlation, discarding those correlated with other covariates. For the evaluation of the model, different combinations of model, variables and principal components were calculated using different error metrics to check which was the most appropriate option. Finally, the first three principal components of the variables Sky View Factor, DEM, Green Leaf Index, Normalized Difference Turbidity Index, Normalized Built-up Area Index and Land Surface Temperature were chosen. Finally, we obtained as a result the spatial distribution of the temperature in the city of Zaragoza at 100 meters, a seasonal average interpolation of the study period. Obtaining a complete picture of the spatial distribution of urban temperature that allows analysis at detailed scales between different urban spaces.

How to cite: Barrao, S., Serrano-Notivoli, R., Saz, M. Á., and Cuadrat-Prats, J. M.: Spatial modeling of Zaragoza urban temperature at seasonal scale, 2015-2022., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-814, https://doi.org/10.5194/ems2024-814, 2024.

II. Climate change effect in urban areas (posters)
VB37
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EMS2024-130
Arūnas Bukantis and Laurynas Klimavičius

The aim of this paper is to determine the impact of the city on the intensity and duration of heat waves. The study was carried out in Vilnius city, Republic of Lithuania. Vilnius is the capital and largest city of Lithuania, with a population of 590 000 as of 2023. The area is 401 km2 and the density is 1450/km2. The central part of the city is located in the wide and deep valleys of the Neris and Vilnia rivers, while the other districts of the city are located on the surrounding hills and their slopes. The lowest point of the city is 97 m above sea level and the highest is 234 m.

An urban heat island (UHI) can amplify and prolong heat waves. This is important for the design and assessment of the energy performance of buildings in urban areas and the impact of heat waves on human health. The role of UHI will be even greater in the future due to climate change and possible global warming, as temperatures are likely to rise and the UHI will exacerbate them.

In this study, hourly air temperature data, as well as daily average, maximum, and minimum air temperature data were collected from Vilnius University automatic meteorological station (VU MS) located in the city centre, and automatic stations at Vilnius Airport (VA) in the suburbs during the summer seasons of 2022–2023.

In Lithuania, a heatwave is a natural meteorological phenomenon where the daily maximum air temperature reaches 30 °C or more for 3 consecutive days (or more). In total, 30% of the days in the summer of 2022 had a daily maximum air temperature above 30 °C in VU MS, while only 16% of the days in the suburban VA meteorological station reached this threshold. In the summer of 2023, 20 % and 7 % of such days were found, respectively. According to the VU MS data, 7 heat waves with a total duration of 32 days have been recorded for 2022–2023, while only 3 heat waves with a total duration of 11 days have been recorded in the suburban (VA) area. In the central part of the city (VU MS), the average daily maximum air temperature during heatwaves was 3.2 °C higher than in the suburban VA. It was also found that tropical nights (daily minimum air temperature of at least 20 °C) were more frequent in the city compared to the suburbs, and the amplitude of the daily air temperature increased during the heat waves.

How to cite: Bukantis, A. and Klimavičius, L.: Urban effects on heatwave intensity and duration: a case study of the Vilnius city, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-130, https://doi.org/10.5194/ems2024-130, 2024.

VB38
|
EMS2024-244
|
Josep Maria Reñé, Mireia Udina, and Joan Bech

Nowadays, atmospheric pollution is one of the most relevant environmental issues. Some pollutants such as fine particulate matter with a diameter of 10 μm or less (PM10) have a considerable impact on human health. In Catalonia (NE Spain), Saharan Dust Intrusions are a major source of PM10. In recent decades, a positive trend of these intrusion episodes has been detected in the NW Mediterranean basin. Moreover, precipitation plays a role in pollutant scavenging processes.

In our work, we make an analysis of the changes in PM10 concentrations with the precipitation episodes. Moreover, we put a special emphasis in the precipitation episodes which happen simultaneously with a Saharan Dust Intrusion. In consequence, we have analysed PM10 concentration data from the Catalan Network for Pollution Control and Prevention and precipitation data from Automatic Weather Stations Network of the Meteorological Service of Catalonia. We use data from four measurement points in Catalonia (Montsec Observatory, Fabra Observatory, Vic and Sort) which are the unique points with precipitation and PM10 measurement instruments at the same location. Dataset contains 4-year data from 2019 to 2022. Specifically, we evaluate how daily mean PM10 concentration values for all the days in the dataset change in comparison to the values of the same variable for the previous day. Moreover, we do a separate analysis for days with observed precipitation (wet days) and days without precipitation (dry days). Also, we perform the analysis for days with Saharan Dust Intrusion and days without Saharan Dust Intrusion. Furthermore, we filter daily PM10 concentration changes for different absolute values of this daily variation to see the differences between great and small changes of daily PM10 concentration. To our knowledge, this is the first study of these characteristics in this region of study.

In general, we observe a decrease of daily PM10 mean concentration levels with precipitation in approximately 60% of the days. This percentage increases to 80% for daily changes of PM10 concentration higher than 10 µg m-3. In wet days with Saharan Dust Intrusion, daily PM10 mean concentration decreases only in 50% of the cases independently of the absolute value of PM10 concentration variation. However, in wet days without Saharan Dust Intrusion, daily PM10 mean concentration decreases approximately in 60% of the cases. This percentage grows up to 90% if we only consider changes of PM10 concentration higher than 10 µg m-3. In consequence, Saharan Dust Intrusions clearly interfere with the usual pollutant precipitation scavenging processes. In addition, we find that scavenging processes are more effective above a certain PM10 concentration variation threshold. This study was performed in the framework of the project "Towards a climate resilient cross-border mountain community in the Pyrenees (LIFE22-IPC-ES-LIFE PYRENEES4CLIMA)".

How to cite: Reñé, J. M., Udina, M., and Bech, J.: Analysis of the role of Saharan Dust Intrusions in PM10 precipitation scavenging in the NW Mediterranean Region, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-244, https://doi.org/10.5194/ems2024-244, 2024.

VB39
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EMS2024-268
Zalika Crepinsek, Zala Znidarsic, and Tjasa Pogacar

Climate change is the greatest threat and risk to urban health and manifests itself in more intense, more frequent, and longer extreme weather events. Although Ljubljana has a relatively small population compared to other European capitals, the city faces problems in summer due to the urban heat island. The aim of this study was to characterize the intensity, frequency and duration of extreme high temperature events and their variability over a 75-year period (1948–2022) for Ljubljana. This study uses 23 indices recommended by the WMO Expert Team on Climate Change Detection and Indices (ETCCDI). The indices are calculated with the Climpact-v2 software. For each index, the type of trend and significance were calculated using the Mann–Kendall test and the magnitude of the trend was calculated using Sen’s slope estimator. The trends in annual mean maximum (TXm), minimum (TNm) and daily mean (TMm) temperatures were all positive and statistically significant with rates of 0.37 °C/decade, 0.41 °C/decade and 0.39 °C/decade, respectively. Both the annual minimum value of daily TN (TNn) and the annual maximum value of daily TN (TNx) have increased significantly in recent times, showing that the coldest and hottest nights of the year in Ljubljana are now warmer, with an increase of almost 7 °C on the coldest nights and a smaller increase of 3.8 °C on the hottest nights. The number of events with a fixed threshold temperature, summer days (TX > 25 °C), hot days (TX ≥ 30 °C) and very hot days (TX ≥ 35 °C) showed statistically significant positive trends. Ljubljana has an average of 68 summer days and 18 hot days per year. Until recently, these days were only typical of summer, but now they occur in May and even continue into September. In the period 1948–2012, we could expect a very hot day only once every three years, and the average of the last 10 years, 2013–2022, is 4 very hot days per year. The number of tropical nights (TN > 20 °C) increased at a rate of 0.3 days/decade, especially after 2000. Thermal heat sum indices, heating degree days (HDDheat) and cooling degree days (CDDcool), indicators of weather-related energy consumption for heating and cooling buildings, showed a significant decrease for HDDheat and an increase for CDDcool. Heat waves (HW) are becoming a growing problem in Ljubljana as all investigated HW indices are increasing, i.e. HW number (trend 0.5 events/decade), frequency (2.0 days/decade), magnitude (0.36 °C/decade) and maximum amplitude (0.73 °C/decade).

According to the research results, it is necessary to accelerate the adoption of a heat action plan that will include observations, forecasts, warnings, and education for the city's residents.

 

How to cite: Crepinsek, Z., Znidarsic, Z., and Pogacar, T.: Analysis of long-term temperature data (1948–2022) shows the growing threat of extreme heat in the city of Ljubljana, Slovenia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-268, https://doi.org/10.5194/ems2024-268, 2024.

III. Air quality in urban areas (posters)
VB40
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EMS2024-686
Yolanda Sola, Mireia Udina, Laura Esbrí, Joan Bech, and Maria del Carmen Llasat

Air pollution is a great health concern for the governments, but also for the population, especially in urban environments. Particulate matter (PM) levels are regulated by European standards and are therefore continuously monitored by official measurement networks with precision instruments that are regularly calibrated. Although citizens often have access to open data, these networks are not usually dense. During the last years, low-cost sensors for measuring air quality have become popular, allowing the establishment of citizen science networks in which the population takes an active attitude in capturing measurements.

In the framework of the European project I-CHANGE, the Barcelona Living Lab on Extreme Events  has used eight Smart Citizen Kits of the company Fablab, with different low-cost sensors including the Plantower PMS5003 that estimates the concentration of PM10, PM2.5, PM1 (referring the number to the maximum radius of the measured particles, in micrometers). The sensors were initially installed alongside an official instrument GRIMM EDM 180 providing PM10 and PM2.5 for 3 weeks, to intercompare the ability of these devices to measure PM. These sensors together with low-cost weather stations have been distributed in different schools in Barcelona, in the context of a citizen science campaign with a double objective: to analyze the use of this type of sensors to have more detailed information on pollution in areas of Barcelona with different characteristics and to raise awareness in the school community and promote changes in habits in response to the European Green Pact.

The results of the intercomparison show that the instruments have a good performance for PM2.5 estimation, with an average determination coefficient (R2) of 0.84 with the official instrument, when comparing 10-minute averages. On the other hand, the instruments have worse quality in the estimation of PM10 (R2=0.64) as could be seen during the Saharan dust intrusion that affected the city. The laser-based measurement system does not allow a good characterization of coarse particles. Despite these differences with the official data, the agreement among low-cost sensors was good (R2 higher than 0.95 for PM10 and PM2.5), so the variations detected when displayed separately can be relied upon. During the time they have been located in schools, starting in January 2023 the longest series, they have allowed to monitor PM concentrations in different areas of the city. The comparison of PM evolution between official instruments and low-cost sensors during high concentration events have shown that the latter can have an informative and pedagogical role in raising public awareness on air quality.

This study is supported by the project “Individual Change of HAbits Needed for Green European transition (I-CHANGE)”. I-CHANGE has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 101037193.

How to cite: Sola, Y., Udina, M., Esbrí, L., Bech, J., and Llasat, M. C.: Challenges in characterizing air quality with low-cost sensors, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-686, https://doi.org/10.5194/ems2024-686, 2024.

VB41
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EMS2024-845
Kjell zum Berge, Moritz Mauz, Franziska Geske, Jens Bange, and Andreas Platis

Recent urban development trends have increased focus on air quality, drawing significant attention from the public, media, and policymakers. Key pollutants such as particulate matter and nitrogen dioxide (NO2) - primarily emitted by vehicles, energy production, and heating - pose substantial health risks. To address this, the EU has implemented several strategies, including driving bans, speed limits, and green space enhancements. Despite these efforts, the effectiveness of pollution assessments using conventional monitoring stations, which are sparse and limited, has been a topic of extensive debate in public and scientific forums.
Moreover, establishing an extensive sensor network throughout a city presents financial and logistical challenges, including high costs, intensive maintenance, and competition for public space. To circumvent these issues and bolster public support for pollution control, an innovative approach involving small, affordable unmanned aircraft systems (UAS) has been developed. This partnership, backed by the Federal Ministry for Digital and Transport and involving select municipalities, focuses particularly on enhancing NO2 measurement precision.
The system utilizes cutting-edge, high-precision NO2 sensors mounted on drones to collect accurate and flexible data on nitrogen oxides and particulate matter. This methodology, supported by recent guidelines on pollutant dispersion using UAS, enables targeted measurement campaigns both before and after the implementation of pollution reduction measures. By deploying these drones, comprehensive datasets covering particulate and gas concentrations alongside meteorological conditions can be obtained across various locations. The data are then analyzed to evaluate the efficacy of the implemented pollution control measures, thus providing a novel, high-resolution approach in NO2 measurements on a vertical scale to urban air quality management.

How to cite: zum Berge, K., Mauz, M., Geske, F., Bange, J., and Platis, A.: Nitrogen Dioxide (NO2) and Particle Measurements within Cities using a Multi-Rotor Uncrewed Aerial System, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-845, https://doi.org/10.5194/ems2024-845, 2024.

VB42
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EMS2024-710
Natália Machado Crespo, Anahí Villalba-Pradas, Shruti Verma, Jan Karlický, Peter Huszár, Michal Belda, and Tomáš Halenka

The FOCI project (“Non-CO2 Forcers and their Climate, Weather, Air Quality and Health Impacts”, https://www.project-foci.eu/wp/) aims to better understand the impacts of key non-CO2 radiative forcers, to assess where and how they arise, and their impact on the climate system, with a final goal of providing tools to investigate mitigation and adaptation policies incorporated in selected scenarios of future development, targeted at Europe and other regions of the world. As part of the Work Package 4 from the FOCI project, which is responsible for tuning, testing and performing the long-term simulations with different regional models downscaling reanalysis and global climate models, we present an assessment of initial tests in WRF and RegCM5 with different domains over Europe. This study is divided into two parts: assessing the impact of 1) the chemistry in the 27-km domain that covers Europe, by comparing with a control simulation and a reference data, and 2) the nested 9 and 3-km domains on meteorological variables, such as precipitation, temperature, and horizontal winds. The 3 km convection-permitting (CP) simulations cover the city of Prague, one of the satellite cities from FOCI project, and an extreme weather event will also be evaluated. Data from ERA5 and assimilated chemistry by Copernicus Atmosphere Monitoring Service (CAMS) are used as boundary conditions, and E-OBS for validation the outputs. Some results show that simulations with chemistry tend to be slightly drier and warmer compared with no chemistry. Furthermore, although overestimating the precipitation over the Czech Republic territory, the 3-km CP simulation shows improvement in capturing the peaks of precipitation for the event.

How to cite: Machado Crespo, N., Villalba-Pradas, A., Verma, S., Karlický, J., Huszár, P., Belda, M., and Halenka, T.: Assessment of the horizontal resolution and an emission inventory in two different regional climate models in the FOCI project, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-710, https://doi.org/10.5194/ems2024-710, 2024.

VB43
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EMS2024-763
Gabriel Moreira Beltrami, Rafael Beicker, Rogério Gonçalves dos Santos, Oriol Jorba, and Jan Mateu Armengol

The trend of urbanization is increasing due to socioeconomic factors, leading to a decline in air quality and heightened exposure for individuals. Modeling dispersion of emissions within street canyons is crucial for understanding  local-scale air pollution exposure  indicators and devising effective strategies to enhance urban air quality. However, microscale urban air quality simulations are complex and involve a large number of interacting physical processes. Phenomena taken into consideration in simulations of urban pollution dispersion largely vary from one study to another. In this context, we aim at identifying the most influential parameters governing this phenomenon. 

 

First, we present a comprehensive database of pollution dispersion in street canyon by perturbing the most important parameters. In this study, these parameters include wind speed, background concentration, emission rates, background turbulence intensity, temperature disparity between building surfaces and the atmosphere, as well as model-specific parameters. We employ COMSOL Multiphysics for the computational fluid dynamic simulations. To keep feasible computational times and create a large database, turbulence is modeled by means of the Reynolds Averaged Navier-Stokes (RANS) k-ε technique and the domain is considered two-dimensional. 

 

This simulation bank is used to develop a surrogate model based on Gradient Boosting Machine and the Principal Component Analysis to reduce system complexity. This surrogate model offers a solution to carry out a multivariate global sensitivity analysis. To this end, we compute the Sobol Indexes, providing insights into the global contributions of input factors to the resulting pollution concentrations at each point of the physical domain. 

 

Results show that, as expected, background concentration dominates the pollution field far from the emission point. The temperature of building surfaces plays a secondary role, acting mainly on the interface between the street canyon cavity and the flow above the buildings. Emission plays a fundamental role, especially in the vertical concentration profile. Other  model-specific parameters have a minor role when compared to the other physical variables. Wind speed plays a key role, along with temperature, in determining how pollution exits the cavity.

 

By integrating advanced simulation techniques with rigorous sensitivity analyses, this study aims to provide valuable insights into the factors influencing air quality in urban street canyons. Such insights are crucial to perform model calibration, and to understand the implications of typical approximations such as non-buoyancy flows.

How to cite: Moreira Beltrami, G., Beicker, R., Gonçalves dos Santos, R., Jorba, O., and Mateu Armengol, J.: Sensitivity analysis in pollution dispersion within street canyons, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-763, https://doi.org/10.5194/ems2024-763, 2024.

VB44
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EMS2024-942
Georgios Kosmopoulos, Stavros-Andreas Logothetis, and Andreas Kazantzidis

Particulate matter (PM) related ambient pollution has emerged as one of the most significant environmental and human health issues during the last decades. Thus, ambient PM concentration levels have been widely investigated through several studies. On the contrary, investigation of indoor microenvironments, where people spend most of their time, air quality conditions is rather limited.

In this study, indoor and outdoor air quality conditions were analyzed across different areas with distinct characteristics towards a better understanding of the complex relationships between indoor and outdoor air quality levels and the mechanisms governing infiltration factors. Simultaneous PM2.5 concentration measurements were conducted, using particle sensors, providing useful information for the identification of Indoor Air Quality (IAQ) variation due to sharp changes in outdoor conditions.

The dynamics of PM infiltration factor, the fraction of ambient particles that infiltrate indoors either by mechanical or natural ventilation, that provoked degraded indoor air quality conditions, have also been evaluated. Moreover, an algorithm is developed, based on regression models, to estimate the infiltration factor, through IO (indoor/outdoor) ratios. The estimated infiltration factor would facilitate the quantification of the fraction of the indoor generated particles to the total indoor concentrations.

The integration of several parameters such us as building characteristics, ventilation systems, air exchange rates, indoor activities and meteorological conditions will elucidate the mechanisms that affect relationship between outdoor and indoor measurements. These findings could provide substantial knowledge to the relationship between infiltration factor and IAQ that is crucial for promoting healthier indoor environments. The study mainly focuses on time periods where outdoor PM2.5 concentrations are dominant, to model more accurately the infiltration factor and the corresponding IAQ at each measurement site. Overall, the synergy of in situ, outdoor and indoor air quality, measurements and  physical modelling will enhance the knowledge on IAQ and could engage the adoption of better IAQ systems and practices.

How to cite: Kosmopoulos, G., Logothetis, S.-A., and Kazantzidis, A.: Indoor and outdoor air quality relationships modelling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-942, https://doi.org/10.5194/ems2024-942, 2024.

VB45
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EMS2024-767
Andreu Julian Izquierdo, Cristina Carnerero, Alvaro Criado, Albert Soret, and Jan Mateu Armengol

Urban air quality presents a significant global environmental challenge, with 77% of the urban population exposed to NO2 concentrations exceeding the 2021 guidelines established by the World Health Organization. Moreover, recent analyses show that people typically spend approximately 90% of their lives indoors. In this context, understanding indoor and outdoor air quality levels is key to better assess population exposure. Despite there is extensive research on modelling and monitoring air quality, studies modelling outdoor and indoor pollution simultaneously remain limited. In this study, we address this research gap by combining NO2 outdoor levels from the air quality model CALIOPE-Urban with indoor-outdoor parametric relations.

Bias-corrected NO2 concentration levels at the street scale (20 m x 20 m) are used. This information is based on a kriging data-fusion method that merges monitoring stations and the dispersion model CALIOPE-Urban. Additionally, it integrates a machine learning-driven microscale-Land Use Regression model, which is calibrated using observational data gathered from short, intensive passive dosimeter campaigns.

Two different parametric relations for deriving indoor-outdoor air quality levels are assessed. On the one hand, we use infiltration rates, which quantifies the fraction of outdoor pollutants  entering into buildings. On the other hand, we apply indoor-outdoor ratios, which besides infiltration also include indoor sources. Both parameters are obtained from available data in the literature. They depend on socio-demographic data (e.g., building use) and  seasonality (e.g., summer, winter, and spring-autumn) which can affect ventilation patterns.

To obtain unprecedented city-wide maps containing both indoor and outdoor NO2 concentrations, bias-corrected NO2 concentration levels and the parametric relations are combined. We present results for the 2019 annual mean of NO2 in the domain of Barcelona. Results are validated using existing indoor and outdoor measurements from various experimental campaigns available in the city. Furthermore, a sensitivity analysis is carried out to quantify  uncertainties associated with parametric relations and their effects upon final results.

This comprehensive approach allows us to refine our understanding of both indoor and outdoor air quality dynamics in Barcelona. Such findings hold promise in improving population exposure in urban environments, revealing both indoor and outdoor NO2 hotspots of pollution exposure.

How to cite: Julian Izquierdo, A., Carnerero, C., Criado, A., Soret, A., and Mateu Armengol, J.: Characterization of outdoor-indoor air pollution at a city-wide scale in Barcelona using a high-resolution urban air quality model, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-767, https://doi.org/10.5194/ems2024-767, 2024.

VB46
|
EMS2024-943
Stavros-Andreas Logothetis, Georgios Kosmopoulos, Orestis Panagopoulos, Vasileios Salamalikis, and Andreas Kazantzidis

Fine airborne particles with aerodynamic diameter lower than 2.5 μm (PM2.5) pose a pivotal atmospheric threat. High PM2.5 values are highly associated with numerous adverse health effects affecting the respiratory and cardiovascular systems. Apart from densely populated urban environments, where anthropogenic emissions are more intense and population density is constantly increasing, suburban and rural are also prone to experience severe PM2.5 related pollution events. Eventually, PM2.5 levels across many environments may report elevated concentrations that may lead to exceedances of the Word Health Organization (WHO) regulated thresholds severely affecting humans’ life, well-being, and ecosystems. A precise forecasting technique of the PM2.5 concentrations could be essential to tackle air pollution control and warn vulnerable citizens.

In this study, a novel deep learning approach (long short-term memory, LSTM) was developed, to forecast the intraday air pollution exceedances across urban and suburban environments in northern Greece (Municipality of Thermi). A three-year dataset was used for the training (two years, 2021-2022) and testing (one year, 2023) of the proposed LSTM model. PM2.5 measurements were provided by a dense low-cost PM monitoring network with approximately 28 sensors deployed across the greater measuring area.  In the scope of this study ground based PM2.5 observations from 3 regions, that share a rather similar meteorological profile, the corresponding meteorological variables, acquired from the Copernicus Atmosphere Monitoring Service (CAMS) and operated by ECMWF, and time variables related to local emissions were utilized. These data were integrated into the LSTM-based methodology, to enhance the hourly intraday PM2.5 concentrations forecasting capabilities. Additionally, the applicability of PM2.5 forecast concentrations to capture the daily exceedances of air pollution was also assessed.

The proposed model's forecasting accuracy yielded promising outcomes, revealing correlation coefficients ranging between 0.68 and 0.93 among the observed PM2.5 concentrations and LSTM forecasted data for various time horizons. Longer forecasting intervals though reported lower correlation coefficients values. Finally, regarding PM2.5 threshold exceedances, the LSTM forecasting system correctly identified over 73% of such events in the examined area. These findings underline the model's capabilities in detecting potential breaches of WHO guideline limits and provide crucial local air quality management insights.

How to cite: Logothetis, S.-A., Kosmopoulos, G., Panagopoulos, O., Salamalikis, V., and Kazantzidis, A.: A deep learning approach for PM2.5 exceedances forecasting in an urban area, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-943, https://doi.org/10.5194/ems2024-943, 2024.

IV. Adaptation/mitigation measures in the urban areas (posters)
VB47
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EMS2024-252
JiHyun Kim, Suyeon Choi, Mahdi Panahi, and Yeonjoo Kim

The anticipated increases in urban climate vulnerabilities resulting from climate shifts have led to various mitigation efforts, such as adopting green or cool roofs in urban areas. Therefore, determining the most effective roofing strategies, including type and distribution, is crucial given associated costs. This preliminary assessment typically involves employing statistical or numerical models with diverse scenario simulations, which are computationally intensive and time-consuming. In this study, we introduce a deep learning-based surrogate model designed to optimize roofing strategies for urban climate risk mitigation in the Greater Seoul area, South Korea. First, we implemented the Weather Research and Forecasting model coupled with Urban Canopy Modeling (WRF-UCM) while assigning one type of roof (e.g., 100% green roof scheme or cool roof schemes ranging from 25% to 100%) to urban grids within the study region under the business-as-usual climate scenario (RCP8.5) during the period 2090-2099. Using the outputs from the WRF-UCM model, we calculated three objective indices (heat stress index, flash flood index, and wind speed index), and trained a deep learning algorithm, Multi-residual networks (Multi-ResNet), to construct a surrogate model of the WRF-UCM. To reduce the total number of scenarios, we applied the Mini Batch K-mean method to cluster 379 urban grids into nine. Afterwards, we generated multi-type roof scenarios by assigning each roof scheme to every urban cluster (four roof schemes across nine clusters, totaling 0.3M scenarios). We then employed the surrogate model to compute the three objectives (i.e., heat, flood, and wind) for each multi-type roof scenario. Finally, we present the optimal roof configurations lying on the Pareto front, reflecting the trade-offs among objectives including cost reduction, heat mitigation, flash flood prevention, and wind speed enhancement. Our results demonstrate the potential of deep learning-based surrogate models as an effective framework for urban planning to mitigate climate risks.

This study is supported by the National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIT) (2020R1A2C2007670, 2020R1C1C1014886, and 2022R1C1C2009543) and Korea Environment Industry & Technology Institute (KEITI) through the R&D Program for Innovative Flood Protection Technologies against Climate Crisis funded by the Korean Ministry of Environment (MOE) (No. RS-2023-00218873).

 

How to cite: Kim, J., Choi, S., Panahi, M., and Kim, Y.: Optimizing roofing strategies to mitigate urban climate risks using a deep learning-based surrogate method, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-252, https://doi.org/10.5194/ems2024-252, 2024.

VB48
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EMS2024-960
Benjamin Bechtel, Charlotte Hüser, Luise Weickhmann, Panagiotis Sismanidis, Stefan Schmidt, Nooshin Nowzamani, and Christian Albert

Extreme heat endangers human health and well-being and impairs the use of public spaces. Dortmund’s Integrated Climate Adaption Master Plan prioritizes actions and measures to improve heat resilience. This project supports the city of Dortmund (Germany) in attaining this goal, by deploying a state-of-the-art biometeorological sensor network and developing a nowcasting service for monitoring thermal comfort across the city. The project aims to pioneer the integration of thermal comfort data in smart-city ecosystems and provide actionable insights for the development of Dortmund’s Heat Action Plan. In-situ, remotely sensed and Modeled data will be used to provide near-real-time information of outdoor thermal conditions including thermal comfort indices. City-Officials of Dortmund are involved in the design of the dashboard and the weather station network, ensuring they meet their needs and will be used in practice. The collected data will be used in a series of on-ground actions, supporting the evaluation of existing climate adaption measures, and the design of new ones. These actions include the mapping of areas with high potential for planting trees, the investigation of changes in human behavior during hot days, and the assessment of backyard greening strategies. To engage with the local stakeholders, promote the role of citizen scientists, and disseminate the project, a series of workshops and on-site events are planned, such as climate comfort labs, mobile measurement campaigns, or climate walks with citizens. The overall goal of the project is for the city of Dortmund to adopt and integrate the developed network and nowcasting service into its smart-city ecosystem.

How to cite: Bechtel, B., Hüser, C., Weickhmann, L., Sismanidis, P., Schmidt, S., Nowzamani, N., and Albert, C.: Data2Resilience: Data-driven Urban Climate Adaption – A Biometeorological Sensor Network for Dortmund, Germany, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-960, https://doi.org/10.5194/ems2024-960, 2024.

V. Development and assessment of methodologies for the urban areas (posters)
VB49
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EMS2024-97
Harro Jongen, Stenka Vulova, Fred Meier, Gert-Jan Steeneveld, Femke Jansen, Dörthe Tetzlaff, Birgit Kleinschmit, Nasrin Haacke, and Ryan Teuling

Evapotranspiration (ET) is a key process in the hydrological cycle that can help mitigate urban heat. ET depends on the surface cover, as the surface affects the partitioning of precipitation between runoff and evapotranspiration. In urban neighborhoods, this surface cover is highly heterogeneous. The resulting neighborhood-scale ET is observed with eddy-covariance systems. However, these observations represent the signal from wind- and stability-dependent footprints resulting in a continuously changing surface cover composition. This continuous change prevents quantitative analysis of the separate types. Here, we disentangle this neighborhood-scale ET at two urban sites in Berlin attributing the ET dynamics to the four major surface cover types in the footprint: impervious surfaces, low vegetation, high vegetation, and open water. Starting from the surface, we reconstruct ET based on patch-scale observations and conceptual models. Alternatively, we start with the eddy-covariance observations and attribute ET to the surface cover types solving a system of equations for four eddy-covariance systems with different footprints. Although starting at the surface yields more robust results, both approaches indicate that vegetation is responsible for more ET than proportional to its surface fraction, and evaporation from impervious surfaces although less cannot be neglected. The behavior of each surface cover type is separated allowing to study the response to rainfall for each type separately. Impervious surfaces exhibit a strong ET peak directly after the rainfall event, while open water is insensitive to the rainfall. High vegetation starts with high ET after rainfall and limits ET within the first days, but low vegetation does not start limiting ET until the end of the warm season likely reaching the soil moisture limit. Additionally, we confirm the intuitive relation between ET and the surface cover fractions based on a wide range of surface compositions.

How to cite: Jongen, H., Vulova, S., Meier, F., Steeneveld, G.-J., Jansen, F., Tetzlaff, D., Kleinschmit, B., Haacke, N., and Teuling, R.: Attributing urban evapotranspiration from eddy-covariance to surface cover: bottom-up versus top-down, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-97, https://doi.org/10.5194/ems2024-97, 2024.

VB50
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EMS2024-278
Jelena Radović, Michal Belda, Jan Geletič, Martin Bureš, Kryštof Eben, Pavel Krč, Jaroslav Resler, and Hynek Řezníček

The utilization of micrometeorological models for urban planning purposes, mitigation strategies development, and studying the atmospheric boundary layer of densely built urban environments has become ever-increasing. Due to the high complexity and variety of urban structures within the cities (e.g., urban fabric, transit roads, green urban areas, water bodies, sports, and leisure facilities, etc.), a comprehensive assessment of these areas and their interaction with the atmosphere is a complicated task. One of the physical processes strongly influenced by the city’s configuration, presence of trees, and buildings is the radiative transfer within the urban environment (e.g., absorption, scattering, emission, reflections between individual surfaces, etc.). Precise modeling of the radiative transfer processes is of particular importance due to their influence on the surface radiation budget, human energy balance, building energy management, etc. Hence, for a model to be operational for various purposes its validation and assessment of the radiation modeling aspect is necessary for everyday usage.  
In this study, the numerical simulations are performed by the micrometeorological model PALM. The model was configured and run in the spin-up mode, during which LSM, BSM PCM, RTM, BIO, and MESO modules were utilized. The selected domain is located in a realistic and densely built urban area within the city of Prague, has an extent of 800 x 500 m, and is simulated in 1 m resolution. For experiment purposes, we selected two different episodes with clear-sky conditions during the year 2019. The PALM model outputs have been evaluated against three different stations, both quantitatively and qualitatively.
We validate the shortwave radiation modeled by PALM at the height corresponding to the height of the sensor and show how the microscale model modifies direct and reflected shortwave radiation by performing a comparison against measurements collected at three different locations within the simulation domain. The findings of this study show and lead to a better understanding of how trees, buildings, and albedos of different surfaces affect and modify shortwave radiation in urban environments. 

How to cite: Radović, J., Belda, M., Geletič, J., Bureš, M., Eben, K., Krč, P., Resler, J., and Řezníček, H.: Influence of buildings and trees on PALM model’s shortwave radiation modeling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-278, https://doi.org/10.5194/ems2024-278, 2024.

VB51
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EMS2024-286
Minsoo Kang, Moon-Soo Park, Seok-Cheol Kim, and Kitae Baek

The urban heat island is intensified due to the continuous temperature increase caused by climate change, leading to consistent property and casualty damages in urban areas. Urban areas are more vulnerable to heatwave events than rural areas. In order to reduce the damage caused by heatwaves in urban areas, it is necessary to analyze and predict meter-scale pedestrian-feeling temperature in street canyon surrounded by high-rise buildings. This study developed a pedestrian-feeling temperature prediction (PeFT) model using the data obtained from the building-block 3-dimensional urban meteorological experiment (BBMEX) campaign, conducted at urban center in Seoul, Korea during heatwave period. The thermal comfort types (TCTs) were defined to reflect the comfortability of pedestrians in urban areas. The TCTs and meteorological variables observed by the Korea Meteorological Administration were used as input data for the PeFT model. The temperatures at surface, 0.5m, 1.5m, and 2.5m high, observed by BBMEX campaign, were trained as target data for the model. Four machine learning techniques (generalized linear model, random forest, support vector machine and automatic machine learning) and four types of input data sets were tested. The optimal PeFT model was constructed by considering the root mean square error and determination coefficient (R2). The model was applied to produce the gridded temperature at four levels in the same area during another period. The PeFT model showed a potential to produce the 3-dimentional temperature distribution with a horizontal resolution of less than 5m within 3m height using the operational air temperature.

Keywords: meter-scale, pedestrian-feeling temperature, Pedestrian-Feeling Temperature prediction (PeFT) model, street canyon, Thermal Comfort Type (TCT)

Acknowledgements: This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF , 2021R1I1A2052562) funded by the National Institute of Meteorological Sciences (NIMS). 

How to cite: Kang, M., Park, M.-S., Kim, S.-C., and Baek, K.: Development of a Pedestrian-Feeling Temperature Prediction (PeFT) Model during the Heatwave using Artificial Intelligence, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-286, https://doi.org/10.5194/ems2024-286, 2024.

VB52
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EMS2024-316
Yuya Takane, Tomoko Nitta, Sachiho A. Adachi, Kei Yoshimura, Masuo Nakano, Makoto Nakayoshi, Shiho Onomura, and Ben Crawford

We have developed ILS+Urban: a coupled model of an offline land-surface model (ILS) and an urban canopy and building energy model (SLUCM+BEM) for global urban climate and energy research. The ILS is an offline land-surface model developed by Nitta et al. (2020) that includes MATSIRO (Takata et al. 2003), a land-surface model for the global climate model MIROC5. The SLUCM+BEM is a new parametrisation for urban climate and building energy simulations developed by the authors (Takane et al. 2024), which can simply simulate anthropogenic heat from buildings (QFB) and electricity consumption (EC) from human activities. The model could reproduce urban air temperature and EC well in the Tokyo Metropolitan Area. We have implemented the SLUCM+BEM in the ILS, allowing us to simulate global urban climate and building energy with relatively low computational resources in offline mode. A test simulation of ILS+Urban shows that QFB and EC tend to be quantitatively high throughout the year in the Middle East. In the near future, we will implement a global urban database (e.g. global LCZ, anthropogenic heat emissions and morphology, air-conditioning adoption rate) and new technology parameterisations (e.g. EV, PV and heat pump water heaters) for global urban climate and building energy projections and countermeasures for urban heat and energy savings & generation. In addition, the ILS+Urban will be coupled with global climate models (e.g. MIROC and NICAM).

References:
Nitta et al. (2020) PEPS, 7, 68.
Takane et al. (2024) ESS Open Archive (under review), https://doi.org/10.22541/essoar.170960070.07397688/v1
Takata et al. (2003) GPC, 38, 209–222.

How to cite: Takane, Y., Nitta, T., Adachi, S. A., Yoshimura, K., Nakano, M., Nakayoshi, M., Onomura, S., and Crawford, B.: ILS+Urban: an offline land-surface process model for global urban climate and building energy simulations , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-316, https://doi.org/10.5194/ems2024-316, 2024.

VB54
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EMS2024-442
Anahí Villalba-Pradas, Natália Machado Crespo, Shruti Verma, Jan Karlický, Peter Huszár, and Tomáš Halenka

The main goal of the OP JAK Geohazards project is to study in detail the threats in the Earth's upper spheres, to understand the causes of their occurrence and to quantify the possible impacts on human society. Climate models will be used to evaluate the impact of climate change on risk phenomena, such as heatwaves, with analysis of their causes and assessment of their consequences in selected areas of human activity. In that sense, urban environments are hotspots of anthropogenic emissions, affect the warming rate over cities and induce changes in several relevant meteorological variables such as temperature and horizontal wind speed, which in turn affect air quality and human health. Therefore, it is important to identify how urban parameterizations impact the regional-to-local scale processes in regional climate model simulations. In order to evaluate these impacts in the long term, we need to find the “best” configuration possible for our models by choosing different parameterizations and validating them against high-quality station observations. In this study, we present preliminary results from a series of sensitivity tests focusing on a heatwave event during 2015 and over two cities in Europe, namely Paris and Prague. Simulations were performed using two models (WRF and RegCM5) with nested domains at 27, 9 and 3 km resolution. Urban schemes of different complexity are used in WRF and in RegCM. To validate the ouputs of our simulations, we use the daily gridded observational dataset from EOBS. The results show that relevant meteorological variables, such as temperature and horizontal wind speed, depend on the urban canopy scheme used as well as on the horizontal resolution.

How to cite: Villalba-Pradas, A., Machado Crespo, N., Verma, S., Karlický, J., Huszár, P., and Halenka, T.: Sensitivity study on the impact of urban scheme on the simulation of heatwaves in Europe, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-442, https://doi.org/10.5194/ems2024-442, 2024.

VB55
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EMS2024-488
Arthur Maas, Esther Peerlings, and Gert-Jan Steeneveld

The ongoing climate change results in increasing frequency of warm episodes and heat waves. While a lot of studies focuses on understanding and predicting outdoor air temperature and human comfort, less is known about indoor temperatures that are reached during these warm episodes. This is surprising since people generally spend the majority of their time indoors, e.g. at work or in their living or bed room. This study develops and evaluates a relatively simple forecasting system that aims to make five day forecasts for real world room temperatures. The system builds upon a relatively simple physical-statistical model for the heat budget of a room that is forced by outdoor weather variables like solar radiation, wind speed, air temperature. In addition, room temperature observations from ~60 houses in Amsterdam are used to train this physical-statistical model. After training the calibrated model is used for forecasting and driven by ECMWF operational forecasts of outdoor meteorological variables for the city of Amsterdam (The Netherlands) for the summer of 2023. Room temperatures are initialized daily by room temperature observations from these ~60 houses. We evaluate the forecasting system on the summer of 2023. We find the model system is well to produce a meaningful room temperature forecast for most of the houses. Forecasts for the daily mean temperature of the living room outperforms the forecast for the daily mean bed room temperatures. The median RMSE (over all 60 houses) for the living room forecast increases from 0.38 K for the one-day forecast to 0.95 K for the five-day forecast. Forecasts for daily mean temperatures are better than for daily maximum temperatures. With this forecast tool we aim to study whether citizens adapt their behaviour in protecting their homes from indoor heat when they receive the forecast information.

How to cite: Maas, A., Peerlings, E., and Steeneveld, G.-J.: “Weather forecasting” of indoor air temperatures in Amsterdam (The Netherlands) to facilitate early heat warnings., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-488, https://doi.org/10.5194/ems2024-488, 2024.

VB56
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EMS2024-528
|
Adam Jaczewski, Andrzej Wyszogrodzki, and Witold Interewicz

The rapid development of urban areas and the impacts of global climate change make cities increasingly vulnerable to environmental challenges, including extreme weather and climate events. While operational numerical weather prediction (NWP) models are crucial in supporting emergency management systems, they often lack the necessary detail and do not adequately account for the complex physical interactions between buildings, artificial surfaces, and meteorological processes. Enhancing these models could significantly improve the accuracy of weather predictions in cities, providing better guidance for preparing and responding to weather-related emergencies. This improvement is essential for safeguarding urban populations and infrastructure against the adverse effects of climate change and urbanisation.
The ICON-LAM and COSMO models have a bulk urban canopy parameterisation, TERRA_URB, which is additionally implemented with spatially variable urban canopy fields in the COSMO model based on the Local Climate Zones (LCZ) approach. By considering the varied characteristics of urban surfaces, such as their materials, structures, and layouts, we can significantly enhance the precision of urban meteorology models. This comprehensive approach allows a deeper understanding of how cities influence local weather patterns and climate conditions, ultimately leading to more accurate predictions and better urban planning strategies. 
This work presents the results of evaluating NWP hindcasts at hectometric scales for Warsaw agglomeration. For the test simulation, a period of heat wave and strong convection in the city area was selected, covering the end of June and the beginning of July 2022. The National Hydrological and Meteorological Service's measurement and observation data were used. During this period, on 26-28 June, the maximum temperature in urban areas exceeded 30°C, and on 30 June and 1 July, the highest monthly temperatures of 34°C and 36°C, respectively, were observed. On 1 July, the front passed through with heavy precipitation – the daily total of 11 mm was recorded, and there was a rapid cooling. The comparison study results show a significant enhancement in the accuracy of surface weather predictions. This is due to implementing urban parametrisation with detailed spatial land use characteristics. The findings provide strong evidence for the effectiveness of this approach in weather forecasting.

How to cite: Jaczewski, A., Wyszogrodzki, A., and Interewicz, W.: Evaluation of ICON-LAM and COSMO high-resolution simulations with urban parameterisation for Warsaw, Poland, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-528, https://doi.org/10.5194/ems2024-528, 2024.

VB57
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EMS2024-533
Katiana Constantinidou, Panos Hadjinicolaou, Giandomenico Vurro, and Jonilda Kushta

Urbanization has become a dominant factor in shaping local climate dynamics, manifesting profound impacts on the environment and human well-being. This effect is even more important over areas that are expected to become vulnerable to climate change in the future. Cyprus, which is located in the eastern Mediterranean and Middle East (EMME) region, is considered as a climate change “hot-spot”.

In this study, we employ the Weather Research and Forecasting (WRF) regional climate model driven by ERA5 reanalysis dataset coupled with different available urban parametrization schemes to simulate prevailing climatic conditions over the EMME and the island of Cyprus. The main objective of this research is to investigate the performance of -different in complexity- urban canopy models in simulating urban heat island over our region of interest, the capital city of Nicosia. The outcome of this investigation is the definition of the most suitable model set-up to be used over the area of Cyprus.

The simulations are performed at 1 km horizontal resolution for the year 2021, a year that Cyprus experienced a prolonged heatwave during summer, with 12 consecutive days of temperatures exceeding 40 degrees Celsius. We examine the seasonal variability of urban climate properties in Nicosia during this year.

The outcomes of this study provide valuable insights into the complex interactions between urbanization and climate. Understanding how different urban parametrization influence seasonal climate dynamics and selecting the best performing scheme aims in better representation of the local climatic conditions which can be further used in mitigation and adaptation assessments of the impacts of the ongoing global climate change.

 

How to cite: Constantinidou, K., Hadjinicolaou, P., Vurro, G., and Kushta, J.: Exploring Urban Climate Seasonal Dynamics over Cyprus with WRF Model: Implications of Urban Parameterizations, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-533, https://doi.org/10.5194/ems2024-533, 2024.