In this context, the session will address issues concerning health, warning systems and measures in place to mitigate adverse impacts, and the models used to evaluate the heat load and cold stress on organisms. This will include the thermal component from the environment, weather sensitivity, actinic and chemical components of stress factors. Modelling studies and experimental studies on how environmental management, urban planning and design or traffic regulation can improve living conditions and decrease emissions are particularly welcome.
In addition, the session will consider the impacts of weather processes on human well-being and health. Since several methods are in use to compile bio-weather forecasts, we are looking forward to discussing such approaches and the way to convey such information to the public, but also to special target groups. Another aim is to describe ways, how climate data and information should be transferred and addressed for issues on tourism, recreation and other economic sectors.
The session will also address efforts to combine different environmental impacts on humans into one single index, as it is well known that humans react to the whole mix of atmospheric stimuli. Our aim is to improve the requested information and to look for more efficient ways of conveying the message on a regular basis in order to enable citizens to make the best use of such information in their everyday activities.
This year, the European Environment Agency published a report in which heat stress is defined as the most dangerous climate risk for the health sector. Society is expected to suffer from increasing heat stress events in the coming years. Moving towards impact-based forecasting, the Royal Netherlands Meteorological Institute (KNMI) has recently adopted the heat stress indicator Wet Bulb Globe Temperature (WBGT) as part of their Early Warning Centre.
The WBGT presented here is computed analytically from air temperature, relative humidity, wind speed and global radiation using the theoretical Liljegren approximation. These WBGT values are compared with WBGT values as derived from black bulb (globe) and air temperature observations for a specific station in the Netherlands.
We present a characterization of WBGT based on hourly observations made by Automatic Weather Stations (AWS) in the Netherlands and compare the safety levels as defined by the US Army, the world athletic organization and the Dutch fire brigade. By assessing the trends in WBGT over the past decades, we find a significant increase of hourly intervals where critical threshold values are exceeded for all five investigated stations. The safety levels of these organizations are based on the absolute values of WBGT. The effective WBGT (WBGTeff) also considers the effects of clothing and a person's activity. The total time in a day that the WBGTeff is above a certain threshold can therefore be used for warnings for specific work environments.
Looking into a case study of a Dutch triathlon (25 June 2023) with a combination of hot weather conditions which resulted in a high amount of heat strokes and hospitalizations, we show spatial variations of WBGT for that day using detailed maps based on AWS and crowd-sourced data.
How to cite: van den Besselaar, E., Koning, M., van der Schrier, G., de Baar, J., and Hartmann, H.: Wet Bulb Globe Temperature (WBGT) in the Netherlands, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-751, https://doi.org/10.5194/ems2024-751, 2024.
This paper investigates the daytime microclimate of street trees and their potential cooling effects on pedestrians in a Dutch neighbourhood.
Heat emissions from buildings, traffic, and industrial activities contribute to the warming of urban areas, intensifying the urban heat island effect. Street green infrastructure, like deciduous trees that provide shade, plays a crucial role in reducing heat stress and promoting pedestrian comfort in various domains. However, studying the physiological response to urban shade is challenging due to difficulties in controlling street-level meteorological variables and recruiting participants. We plan to use semi-controlled outdoor methods to study how shade affects bodies, with a limited sample size. This research aims to better understand the role of tree shades in adapting to urban heat and contributing to global goals for climate action (SDG 13), sustainable cities (SDG 11), and health and well-being (SDG 8).
We conducted an explorative biometeorological study using a juvenile tree (Tilia x europaea, 12m in height) located in a social housing neighbourhood in Den Haag. The measurement campaign adopted mobile weather stations to gather meteorological data surrounding the Tilia tree. This took place from 10 am to 5 pm on a sunny day in July 2023. Two heat-stress trackers (Kestrel 5400) were used; one was placed in direct sunlight and the other in the shade of a tree. The shaded tracker was relocated every thirty minutes to adjust for the moving tree shade. Two measurements showed how tree shade cools the air by comparing differences in temperature, humidity, globe temperature, and wind speed between sun and shade. Additionally, sixteen iButton thermocron sensors were taped to different body parts of two participants according to international standard (ISO 9886:2004). We tested a sun-shade relay protocol, tracking skin temperature changes as subjects moved and sat between sun and shade every 20 minutes, across fifteen intervals from 11 am to 4 pm.
The preliminary results are two-fold: 1) Heat stress analysis showed maximum UTCI and PET in the sun at around 3:30 pm were 36.3°C and 39.9°C, respectively, with tree shade significantly reducing UTCI by over 10°C and PET by over 15°C. 2) Heat recovery analysis revealed that the maximum skin warming rate in the sun (1.14°C/min) was higher than the cooling rate in the shade (-0.79°C/min). An additional interesting finding is that, while the PET contrast between sun and shade remains constant at 15°C from morning to afternoon, the skin's heat recovery capacity is compromised by approximately 1.24°C in the afternoon, possibly due to the overall increases in PET of around 3°C.
The discussion and conclusions focus on the choice of outdoor thermal indices, particularly for urban shade studies, and their applicability for future research on dynamic thermal comfort and thermal alliesthesia.
How to cite: Peng, Z. and Maiullari, D.: Exploring Tree Shade: Cooling Effects and Skin Temperature Recovery in Urban Environments, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-386, https://doi.org/10.5194/ems2024-386, 2024.
The temperature in Taiwan is expected to continue to rise in the future based on the worst-case scenario of global warming (SSP5-8.5). And the average annual temperature in the middle /end of the 21st century may rise by more than 1.8 ℃/ 3.4 ℃; and the number of days with high temperatures above 36 ℃ will increase in various places. Under the worst scenario (SSP5-8.5), in the middle/ late 21st century, the increase will be approximately 8.5 days/ 48.1 days, with the increase in urban areas being more significant than in other areas. In the future, the summer period will extend from the current approximately 130 days to 155-210 days, and the winter period will decrease from the current approximately 70 days to 0-50 days. Taiwan will face more severe conditions in the future.
Although Taiwan has gradually begun to address climate change and urban high temperature issues, there are no specific urban high temperature implementations and regulations, and there is a lack of tools and mechanisms to effectively quantify or assess urban high temperature risks. Since Taiwan does not have exclusive regulations on high temperature response, extreme high temperature has been viewed as one of the natural disasters, such as typhoons, earthquakes, droughts, etc. Which is highly dependent on the disaster prevention and response capabilities of individual local governments. The implementation process is different in different counties and cities, and the results cannot be reviewed uniformly. Moreover, there are differences between cities and counties, with different problems, geographical environments, social vulnerability, etc., making it difficult to compare the risks of high temperatures and share experiences.
The urban built environment is critical to outdoor thermal comfort and heat stress risks. Case studies of several outdoor activities of different scales show that under different environmental conditions, participants of different identities will have different thermal risks and different thermal perception/behavior patterns. After understanding the impact of outdoor thermal comfort and related differences in feelings and behaviors, we can further analyze the impact of outdoor high temperatures on the "built environment" and "social vulnerability".
How to cite: Yu, S.-Y. and Lin, T.-P.: Urban Heat Assessment, and Heat Risk Identification in Taiwan’s Built Environment., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-516, https://doi.org/10.5194/ems2024-516, 2024.
In the context of climate change and extreme weather, urban heat island (UHI) phenomenon is exacerbated, affecting people's quality of life and environmental comfort. In the hot and humid climate of Asia, urban ventilation and heat dissipation play a crucial role in improving the thermal environment and reducing heat-related risks. Previous studies have mostly focused on urban wind corridor planning, lacking sufficient evidence of the ventilation benefits of such corridors. This study aims to fill this gap by using Tainan City as a case study to demonstrate the ventilation benefits of urban wind corridors through corridor identification and long-term measurements.
Utilizing the 2-kilometer resolution historical climate reconstruction grid data (TReAD) built by the Taiwan Climate Change Projection and Information Platform (TCCIP) of the National Science and Technology Center for Disaster Reduction (NCDR), the heat island phenomenon in Tainan City is examined, and prevailing wind directions are summarized. Geographic information software is employed to calculate the roughness length and formulate urban wind corridors. Mobile observations are conducted to select and evaluate measurement points for assessing the ventilation efficiency of the corridors, followed by long-term observations to obtain high-density data and confirm the ventilation benefits of urban wind corridors.
The analysis of corridor formulation and observation yields the following research findings (1) Large open spaces in urban areas significantly increase wind speeds. For instance, at the elementary school near Tainan Park, the hourly average wind speed reaches 1.8 m/s compared to a decrease of 0.9 m/s at points without nearby open spaces, such as roads with a width of 23 meters on both sides. (2) The alignment of road traffic direction with wind direction is the primary factor affecting ventilation efficiency, followed by road width. For example, on Road A with a width of 3 meters and aligned with the wind direction, the hourly average wind speed is 0.7 m/s, compared to an increase of 0.4 m/s at Road B with a width of 21 meters but misaligned with the wind direction. (3) Wind speeds are more stable in crossroad areas. For instance, at the intersection of two road, where dual-directional ventilation occurs, the hourly average wind speed is 0.9 m/s, falling between the efficiency levels of a second-level corridor (1.2 m/s) and a third-level corridor (0.8 m/s).The results of this study can serve as a basis for future urban wind corridor planning, effectively guiding the implementation of strategies to cool urban areas and mitigate the urban heat island effect.
How to cite: Lin, T.-P., Chen, Y.-L., and Liu-Chen, W.: Urban Wind Corridor Identification and Verification of Thermal Comfort Enhancement in Urban Area, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-478, https://doi.org/10.5194/ems2024-478, 2024.
This study aims to explore how to utilize RayMan to generate simplified thermal comfort index assessment formulas, leveraging solar radiation data exported from simulation software, and to achieve simplified evaluation and application of thermal comfort index maps at different scales.
Through comparing data from relevant journals, meteorological agencies, and software-exported solar radiation data, it was found that the solar radiation values from Insight and ARGIS are reasonably accurate. At the site scale simulation, Insight was chosen, providing data in a grid format where each point represents the radiation conditions within one square meter. It also presents values reduced due to shading, which can be considered as corrected Sky View Factor data. Therefore, the influence of Sky View Factor on thermal comfort need not be further considered in subsequent research.
For urban scale analysis, ARGIS was employed, capable of producing data including direct radiation, diffuse radiation, and their combination. RayMan attempted to decompose the regression formulas of Tmrt and PET using extensive data, yielding significantly high R-squared values and significance. Among the variables, temperature, solar radiation, and wind speed were included.
The research results demonstrate that with these three variables, outdoor thermal comfort can be rapidly assessed, with higher accuracy particularly when radiation values exceed 600 (W/m²). Solar radiation data obtained through simulation software can be converted into thermal comfort indices using simple formulas. Ultimately, it is anticipated to utilize other visualization tools such as Dynamo and GIS to visualize thermal comfort indices as grid maps, aiding architects in identifying outdoor thermal discomfort spots on sites and implementing corresponding design improvements.
How to cite: Lin, T.-P. and Wu, Y.-C.: Developing outdoor comfort prediction models and their applications based on long-term climate data. , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-487, https://doi.org/10.5194/ems2024-487, 2024.
The Urban Heat Island (UHI) phenomenon has become a significant concern in urban areas worldwide as urbanization continues to intensify. This process leads to notable changes in microclimates within cities, resulting in higher temperatures compared to their surrounding rural areas. Referred to as the Urban Heat Island effect, this phenomenon is mainly caused by human activities such as industrialization, transportation, and construction, which alter land surfaces and increase heat retention.
Identifying hot spots within cities necessitates a thorough understanding of various contributing factors, including land use patterns, building density, surface materials, and the distribution of green spaces. ENVImet modeling facilitates this understanding by allowing precise simulation of microclimates, enabling researchers and planners to pinpoint areas with elevated temperatures and analyze their underlying causes. Once hot spots are identified, ENVImet plays a crucial role in devising optimized mitigation scenarios. By simulating interventions like increasing green space coverage, implementing cool roofs and pavements, optimizing urban layouts for improved airflow, and integrating water bodies, ENVImet enables stakeholders to assess the effectiveness of each strategy in reducing temperatures and mitigating UHI effects.
The objective of this study is to optimize the urban design of established infrastructure within cities experiencing different microclimatic conditions, such as Aspropyrgos in the greater Athens area and Tripolis in central Peloponnese, Greece. We conduct urban design simulations by:
i) Increasing green spaces to absorb heat, provide shade, and promote evapotranspiration, thereby reducing surface temperatures and mitigating UHI effects.
ii) Implementing shading structures and urban canopies to offer shelter from direct sunlight.
iii) Integrating water features to assess the effectiveness of incorporating water bodies like ponds, lakes, and fountains in the studied urban environments. Water features act as natural heat sinks, dissipating excess heat through evaporation and creating cooling microclimates.
Furthermore, the model's optimization capabilities allow for fine-tuning these scenarios to achieve the best outcomes. By iteratively adjusting parameters and variables, planners can tailor mitigation strategies to specific urban contexts, considering factors such as local climate, population density, and infrastructure constraints. Optimizing mitigation scenarios for UHI hot spots represents a proactive approach toward enhancing urban resilience and sustainability. By leveraging simulation and optimization, cities can develop targeted interventions that mitigate heat-related risks and foster more livable and resilient urban environments for current and future generations.
How to cite: Nastos, P. T., Polychroni, I., Nastou, M.-P. P., Charalampopoulos, I., Solomos, S., and Zerefos, S.: Improving urban design to address human thermal discomfort in urban agglomerations characterized by different microclimatic conditions, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-574, https://doi.org/10.5194/ems2024-574, 2024.
Anthropogenic activities and land cover changes within cities can result in unique climate conditions in settlements. One of the major phenomena of the city’s climate is the “Urban Heat Island” (UHI), defined as an amplification of temperatures inside cities compared to its rural surroundings arising from the inadvertent development of cities and associated human activity. Apart from remote sensed platforms, the UHI can be measured via two different approaches; fixed meteorological stations and mobile climate measurements. Usually, fixed meteorological stations measure climate information continuously 24 hours a day. However, they are limited in number and cover relatively a small area close to them for their instrumental source area. On the other hand, mobile climate measurements are flexible in terms of instrumental source area, their quantity is greater compared to stationary stations and therefore they can cover larger areas in shorter time intervals, which makes them relevant for biometeorological research.
Recently, the development of mobile micrometeorological cars such as MaRTy (Middel et al. 2019) enables measurement of key microclimate parameters (e.g., air temperature (TA), relative humidity (RH), Wind Direction (WD), shortwave and longwave radiation across three dimensions, and wind speed (WS). That can be subsequently used to estimate outdoor thermal comfort (OTC). MaRTy is named after the key climate variable it calculates: Mean radiant temperature (MRT). Since 2019, MaRTy carts have been used in several cities worldwide mainly to assess OTC conditions, as well as to evaluate microclimate models e.g. ENVI-Met.
This study examined, for the first time, data from the SMaRTy platform (The Singaporean version of MaRTy) to conduct mobile climate measurements along a designated route in an urban park in Singapore during different monsoon seasons. The study's aims were: (1) To test the influence of the walking speed of the SMaRTy cart on the measured climate variables e.g., TA, RH, and WS. (2) To calibrate the mobile climate measurements of the SMaRTy cart along a designated route in an urban park in Singapore based on data from fixed meteorological stations. (3) To apply the calibration equations on SMaRTy cart data, and to create a spatial model of the climate variables in the urban park. Initial results suggest that mobile microclimate measurements via the SMaRTy platform along a designated route yield useful data that can be applied towards OTC analysis, but seasonal variations in model calibration occur across temporal measurements from SMaRTy.
How to cite: Mandelmilch, M. E., Yik, S. K., Crank, P., and Chow, W.: Calibration of Mobile Micrometeorological Measurements in a tropical urban park: Analysis of SMaRTy data on Urban Warming , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-720, https://doi.org/10.5194/ems2024-720, 2024.
In recent years, the concept of urban ‘walkability’ has become common in multiple fields connected to urban geography, urban planning, and has both social and environmental benefits. In the last decade urban climatology research has paid more attention to the effect of urban outdoor thermal conditions on walkability. Walkability can be defined as the extent to which the built environment enables, supports and encourages walking, by providing pedestrians on the move friendly and safety environment, visual interest in street network’ and thermal comfort
This study examined the relations between outdoor thermal conditions and walkability in the Mediterranean City of Tel Aviv, aiming to: (1) assess the relationship between urban morphology at street level on the objective and subjective thermal comfort of pedestrians on the move, (2) quantify the influence of land use and centrality of streets on pedestrians' thermal perception, and (3) evaluate the seasonal and hourly effect of thermal comfort on pedestrian volume.
Field campaigns were conducted in summer and winter, in six different types of streets including micro-climatic measurements, pedestrian observation and counting, and a bio-meteorology questionnaire survey.
The results showed that the effect of thermal comfort is more pronounced in summer than winter thus during summer less pedestrian volume was observed during the hottest hours of the day. The pedestrian volume in winter is much higher than in summer. In commercial streets, the relation between thermal perception and pedestrian volume is weak, compared to noncommercial streets. During the summer the pedestrian volume in boulevards and shaded streets is higher compared to exposed streets.
The findings indicate that thermal conditions affect pedestrian volume, but this is dependent upon the street network structure and type of land use.
How to cite: Potchter, O., Cohen, P., Ferenez, M., Mandelmilch, M., and Omer, I.: The Effect of Outdoor Thermal Conditions on Daily and Seasonally Pedestrian Behavior in Various Streets of Mediterranean City, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-922, https://doi.org/10.5194/ems2024-922, 2024.
Prior research has studied the utility of various metrics of thermal comfort in an effort to elucidate the nuanced relationship between temperature and human mortality. Synoptic-scale air masses (AMs) – sometimes referred to as surface weather types – are one of these metrics. Within the last 5 years, a new global-scale AM classification dataset was published – the GWTC2 – which has not yet been evaluated in terms of its relationship to human mortality. The GWTC2 is a system of multivariate surface AM classification, identifying spatiotemporally-relative AMs, and frontal passages, for every day (from 1979-present) at every location (at 0.5° x 0.5° spatial resolution) across the globe. Thus, this research leverages the GWTC2 to examine the lagged relationship between AMs and anomalous mortality for 61 cities across various climates zones of the continental United States. Results show that AMs are significantly related to human mortality, at most locations and in all seasons of the year. The Humid-Warm (HW) and Warm (W) AMs yielded significant and immediate (at 0-1 day lag times) increases in mortality in summer, though the immediate increases after HW occurred were not followed by decreases in mortality – indicating a lack of the “mortality displacement” effect highlighted in some prior research. Meanwhile, the Dry-Cool (DC) and Cool (C) AMs both resulted in a delayed, but extended period (from 1 to 19 days of lag) of excess mortality in all seasons outside of summer, generally peaking 2 to 4 days after the occurrence of the DC or C air mass. Of note, warm front passages (increased mortality) and cold front passages (decreased mortality) yielded significant anomalous mortality responses one day after their occurrence in every season of the year – the most seasonally-consistent AM-mortality relationship discovered. Furthermore, many of these results were consistent across the majority of the 61 cities examined. Finally, artificial neural network (ANN)-based modeling revealed that a meta-model (i.e., a model developed on the combined data of all 61 locations) was more skillful in predicting AM-mortality relationships for many cities than developing 61 individual ANN models for each city. Future research should explore whether the consistency of these results holds up when exploring the impact of GWTC2 air masses in other parts of the globe.
How to cite: Lee, C., Silva, A., Ibebuchi, C., and Sheridan, S.: Relating synoptic air masses to human mortality, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-166, https://doi.org/10.5194/ems2024-166, 2024.
Climate change is expected to increase various health effects on human health such as increased temperature-related mortality and morbidity and spread of different vector or viral borne new diseases. Finland is a sparsely populated country which generates challenges and uncertainties in modelling heat-related mortality and morbidity.
In this presentation, we will present preliminary results on future temperature-mortality relationships from different wellbeing areas in Finland using mortality and climate model data. In the results we will show how future projections of heat-related mortality will look like until 2100 with selected CMIP6 models under two climate change scenarios, SSP2-4.5 and SSP5-8.5. Heat-related mortality is heterogeneous in different regions of the country and in the future the most heat vulnerable areas are found in the capital region and the southern parts of Finland. For other regions, such as the northern, central and western parts of the country the results are mixed and present only a slight increase in the heat-related mortality change.
Extreme temperatures also influence on ambulance operations in various ways. We will show examples how ambulance operations are affected by extreme temperatures in Helsinki applying a distributed lag nonlinear model (DLNM). Understanding associations between weather and different emergency service operations is important for resource management and preparing for the future.
Modelling future heat-related mortality and analyzing ambulance service weather dependencies include limitations and uncertainties and these factors are also discussed from different perspectives. Longer and more frequent heatwaves might also lead to higher than estimated mortality rates in other regions of the country than expected and thus people living in these areas should also implement heatwave adaptation plans.
How to cite: Haga, L. and Ruuhela, R.: Health risks of extreme temperatures on mortality and ambulance operations in Finland, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-308, https://doi.org/10.5194/ems2024-308, 2024.
The increase in hot nights in the last decades and the projected increase due to climate change makes increasing knowledge about their impact important and critical for measures of public health actions and adaptation planning. However, few studies have addressed the importance of hot nights, which may prevent necessary nocturnal rest. This study estimated the association between hot-night excess (the sum of excess heat during the nighttime above a threshold) and duration (the percent of nighttime with a positive excess) and daily mortality in the warm season over multiple locations worldwide. We fitted time series regression models to mortality in 178 locations across 44 countries using a distributed lag non-linear model over lags of 0-3 days, controlling for daily maximum temperature. Next, we used a multivariate meta-regression model to pool results. We found a positive, increasing mortality risk with hot-night excess and duration. The pooled relative risks of death associated with extreme excess and duration, defined as the 90th percentile with respect to 0 in each index, were both 1.03 (95% CI, 1.02; 1.04). The overall estimated attributable fractions were also observed to be almost similar at 0.59% (95% CI, 0.00; 1.13%) and 0.58% (95% CI, 0.00; 1.10%), respectively. The magnitude of effects ranged from an RR of 1.02 to 1.04, slightly higher in tropical and arid climates. The highest overall estimated attributable fractions with hot-night excess were found for the arid climate, at 1.11% (95% CI, 0.00; 2.35%), while the largest burden has been estimated for the tropical climate zone, at 1.19% (95% CI, 0.00; 2.38%). This study provides new evidence that hot night indices considering excess and duration were strongly associated with an increase in the risk of mortality. A clear advantage of these exposure metrics is that they more realistically reflect thermal exposure over the entire night period rather than a single-moment temperature, such as minimum temperature. The use of hourly data allows for a more detailed assessment of the thermal characteristics of warm season nights, making it possible to accurately assess the risk of hot nights for population health and wellbeing. Modeling thermal characteristics' sub-hourly impact on mortality during the night could improve decision-making for long-term adaptions and preventive public health strategies.
How to cite: Royé, D., Sera, F., Tobías, A., Hashizume, M., Honda, Y., Kim, H., Armstrong, B., and Iñiguez, C. and the MCC Collaborative Research Network: Short-term association between hot nights and mortality: a multicountry analysis in 178 locations. , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-449, https://doi.org/10.5194/ems2024-449, 2024.
In Taiwan, the birth rate is declining annually, and by 2024, a quarter of the cities will be super-aged societies. With the highly dense development of urban areas, many cities have experienced the urban heat island phenomenon. In addition, climate change has led to rising temperatures in various regions in recent years. However, there has been a lack of research exploring the potential hazards and impacts on the health and well-being of the elderly resulting from these two phenomena. Due to the limited number of monitoring stations established by the Central Weather Administration, and the fact that some of these stations are located in higher altitude areas, the measured data are unable to clearly depict the extent and intensity of urban heat island phenomena. Additionally, future climate data will need to be simulated using global atmospheric models and scenario of global warming. This study analyzed the differences in indoor thermal comfort and annual cooling energy consumption by using high-resolution simulated climate data to assess the effects of the urban heat island phenomenon, and evaluated the impact of global warming scenario.
The National Science and Technology Center for Disaster Reduction (NCDR) adopted the high-resolution global atmospheric models developed by the Geophysical Fluid Dynamics Laboratory (GFDL) at Princeton University to conduct global climate estimation simulations under the RCP8.5 warming scenario. Subsequently, the data was downscaled to a 5-kilometer resolution for the Taiwan region using the Weather Research and Forecasting (WRF) model. The simulation periods included the baseline period (1995-2014) and a 2°C temperature increase scenario under RCP8.5 (2034-2053). This study focused on the densely developed built-up areas of Taipei City and New Taipei City as the research area, comprising a total of 38 delineated zones. EnergyPlus was employed to simulate indoor temperatures and cooling energy consumption for aggregated residential households across these different zones. The results showed that during the baseline period, the urban heat island center areas had an average indoor temperature 0.4 degrees Celsius higher and an average annual cooling energy consumption 320 kWh/year higher compared to surrounding areas in summer. Furthermore, under the global warming scenario, the indoor temperatures became more severe. The urban heat island phenomenon not only leads to increased indoor temperatures in residential buildings but also exacerbates health risks and economic burdens for the elderly due to climate change. The results can serve as a reference for local governments in developing climate adaptation strategies.
Keywords: Global Warming Scenario, Urban Heat Island, Health Risk for the Elderly, Indoor Comfort, Cooling Energy Consumption
How to cite: Cheng, C.-Y. and Lin, T.-P.: Impact of Climate Change Scenarios on Indoor Comfort and Cooling Energy Consumption in Urban Heat Island Residential Areas, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-228, https://doi.org/10.5194/ems2024-228, 2024.
Heatstroke mortality during nighttime sleep is expected to rise as global warming and urban heat islands (UHI) become more prevalent. Measures that can reduce nighttime temperatures include greening and anthropogenic heat reduction. However, it is difficult to compare health impacts using the same temperature index because the peak time period when temperature reduction is most effective, varies greatly between measures. Therefore, this study proposed a daily temperature index that can consider health effects by time of day and used this index to compare and evaluate the mortality risk reduction effects of measures on nocturnal UHI.
When the human body is exposed to a certain temperature, health effects can last for days or even weeks. This study used a distributed lag nonlinear model (DLNM) to assess the relationship between temperature indices and mortality risk taking into account the lag effect. The study was conducted in the Tokyo metropolitan area from 2000 to 2010, using data from demographic surveys on air temperature and mortality. First, a mortality risk prediction model was developed using the DLNM, with the temperature every hour of the day as the explanatory variable, and the optimal temperature with the lowest mortality risk was determined for each hour. Next, the mean deviation between the optimal temperature and the observed temperature at each time of day was calculated for each of three time periods (2–9, 10–17, and 18–1 h), and the daily weighted average deviation ΔTday was calculated using the combination of weight coefficients that minimizes the Quasi Akaike Information Criterion (QAIC) of the forecast model. This combination (0.67, 0.13, and 0.20) suggests that the temperature deviations have a five-fold greater impact at night (2–9 h) than during the daytime (10–17 h). The model with ΔTday had a lower QAIC and higher prediction accuracy than models with daily maximum or daily mean temperatures.
Three countermeasure scenarios for nocturnal UHI were compared and evaluated: ground greening (doubling the area of green space), electric vehicles (with 100% penetration), and air-source heat pump (HP) water heaters (with 100% penetration) that emit cold exhaust heat at night. The evaluation target area included the entire 23 wards of Tokyo, and the daily ΔTday was estimated on a mesh-by-mesh basis using an urban canopy model to compare and evaluate heat-related excess mortality risk reduction rates in August. The results showed that the three scenarios had similar mortality risk reduction effects for the entire area, but their effects had different geographic distribution characteristics. The HP water heater scenario showed particularly large impact in residential areas with large nighttime populations.
How to cite: Yamaguchi, K., Iwanaga, H., Takane, Y., and Ihara, T.: Evaluation of the mortality risk reduction effects of countermeasures to nocturnal UHI, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-296, https://doi.org/10.5194/ems2024-296, 2024.
Climate change poses a substantial threat to both the Earth’s ecosystems and human society. In
Mediterranean countries like Cyprus, extreme temperatures and especially heatwaves during summer
months are increasingly common as it is observed in the past years due to anthropogenic climate
change. While cold waves are less frequent, they also pose significant health risks, as some studies
show that more deaths actually occur during cold weather than hot, especially in warmer cities
(southern) rather than colder (northern) in Europe. Extreme temperatures leads to heightened
bio-climatic stress and can adversely affect the human body, disrupting physiological functions and
exacerbating preexisting health conditions, ranging from discomfort and severe illnesses that require
hospitalization to mortality.
This study examines temperature trends in Cyprus over the past four decades, focusing on extreme
temperature events from 2000 to 2019. Using ERA5-Land reanalysis data, we analyzed both maximum
and minimum daily temperatures for both the warm (May-Oct) and the cold (Nov-Apr) season.
Extreme hot days were defined as those where both maximum and minimum temperatures exceeded
the 95th percentile of each month in the warm season. Conversely, extreme cold days were defined as
those where both temperatures fell below the 5th percentile in the cold season. Our analysis revealed
an upward trend in temperatures over the past four decades, with a statistically significant increase
in the number of extreme hot days and a decrease in extreme cold days for the last 20 years. Statistical
and machine learning methods, including Distributed Lag Models (DLMs) and Generalized
Additive Models (GAMs), were employed to estimate mortality and morbidity risks over a 21-day lag
period using health statistics from Ministry of Health and Statistical Service in Cyprus. We observed
a notable increase in mortality risk associated with both high and low temperatures extremes. In
contrast, the morbidity risk showed a different profile; overall morbidity risks were lower compared
to mortality and the maximum risk occurred at lower temperatures. In general, lower temperatures
exhibited pronounced health risks compared to higher temperatures. Additionally, we calculated
the optimal temperatures that corresponded to the lower risk as well as the attributable fraction of
deaths and hospitalizations for extreme temperature days and extreme temperature events, lasting
from two or more consecutive days. The findings indicated that both deaths and hospitalizations
were notably higher during the cold period in comparison to the warm period. Nevertheless, during
periods of extreme high temperatures, the rate of increase in attributable deaths was greater than
during the cold period when compared to days with non-extreme temperatures.
How to cite: Kekkou, F., Lazoglou, G., Economou, T., and Anagnostopoulou, C.: Temperature Extremes and Human Health in Cyprus: Investigating the Impact of Heat and Cold Waves, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-185, https://doi.org/10.5194/ems2024-185, 2024.
One of the major concerns of climate change is the impact on human health. To that end, there is a lot of research on quantifying the effects of environmental exposure such as heat and air pollution on human health. The main challenge encountered in such research is the availability of health data. For short-term exposure effects, such as the impact of heat on daily mortality, daily data is required which can be obtained at country-level, but is generally not open-source or available at at a wider spatial extend (e.g., at continent or global scale).
It is also true however, that open-source repositories do contain health-related data at a large spatial scale, albeit at non-optimal temporal resolution. A bright example is Eurostat, which contains (but is not limited to) health data (e.g., mortality) at weekly time steps for the EU member states but also other countries peripheral to Europe.
The primary tool for quantifying the effect from various exposures on mortality and morbidity is the framework of Distributed Lag Non-linear Models (DLNMs). These models, applied to daily data, can capture the effects from environmental exposure across many days (lags). In this work, we exploit the mathematical properties of the Poisson distribution to enable the implementation of DLNMs on temporally aggregated data, and demonstrate that the loss of information is minimal, particularly when the goal is to understand aggregated quantities such as the attributable number of deaths. Using simulated data, we demonstrate that using the framework of Generalized Additive Models enables the application of DLNMs to weekly data, to emulate the situation of using data from databases such as Eurostat. We further illustrate our framework using real mortality data from the city of Thessaloniki, Greece and from Cyprus.
Another implication of our suggested framework is that large scale studies (e.g., at continental or global scale) can be made more optimal when the goal is to estimate aggregate risk measures. For instance, aggregating daily data to weekly data, reduces the amount of data by a factor of 7. We present a sensitivity analysis to the level of aggregation that can be performed before significant loss of information in the estimates starts to occur.
How to cite: Economou, T.: Maximising information in open source health data: A statistical approach for modelling aggregated time series of health outcomes, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-171, https://doi.org/10.5194/ems2024-171, 2024.
The impact of various environmental factors on human health is often assessed in a non-interactive way, yet emerging evidence suggests synergy among multiple risk factors on health outcomes. In Thessaloniki, frequent exposure to air pollution, primarily O3 in summer and PM10 in winter, coupled with elevated air temperatures, has been linked to high mortality risks, exacerbated under the influence of an Urban Heat Island. In the present we apply an innovative statistical framework to investigate the combined effect of thermal stress (maximum apparent temperature, Tappmax) and air quality (PM10, NO2, and O3 concentrations) on daily mortality. We estimate heat and cold effects as the percentage change in all-cause, cardiovascular disease (CVD) and respiratory disease (RD) mortality between a) the 75th and 99th, and b) the 1st and 25th percentiles of Tappmax, respectively, and their variation across low, medium, and high levels of pollutants, defined as the 5th, 50th, and 95th of the sample percentiles.
Overall, heat exhibits a more pronounced impact than cold, as exposure to outdoor conditions is limited during winter. High levels of PM10, NO2 and O3 are associated with increases in heat-related all-cause mortality by 43.7%, 37%, and 31%, respectively, while the corresponding increases for cold are 14%, 19%, and 1.7%. A consistent increase in the effect of heat on mortalities is observed, particularly at high pollutant levels. It is worth noting that RD mortality decreases with increasing PM10 and NO2 levels, potentially reflecting protective adaptations among urban residents during adverse conditions. Only the highest pollutant concentrations impact mortalities in the cold part of the Tappmax range, albeit at lower levels than heat. Notably, cold-related RD mortality is prominently affected by high NO2 levels (39%), followed by PM10 (30%), indicating a more pronounced influence of these pollutants on the respiratory system.
The present research captures the impact of concurrent exposure to environmental stressors over time, providing insight into the effects of extended periods of poor air quality and heat stress on human health. By understanding these results, public health interventions, such as the enhancement of heat resilience and targeted healthcare services to sensitive populations, can be effectively tailored to address the specific health risks stemming from exposure to extreme temperature conditions and poor air quality.
How to cite: Parliari, D., Economou, T., Giannaros, C., Kushta, J., Melas, D., Matzarakis, A., and Lelieveld, J.: Investigating heat, cold and air pollution effects on mortality in a coastal Mediterranean city , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-105, https://doi.org/10.5194/ems2024-105, 2024.
Human health faces a significant threat from climate change, especially in regions like the Mediterranean, and the Middle East and North Africa, which have experienced extreme temperatures in recent decades. Extreme heatwaves are becoming common in these areas, impacting enclosed populations more severely. However, hot weather is experienced in different ways by different demographics. This is an aspect that must be accounted for in any analysis aiming at studying the human health related effects of heat exposure. For this, here, were use the modified Physiologically Equivalent Temperature (mPET) – an advanced human-biometeorological index, which is capable of considering the variability of thermo-physiological responses among different population groups. mPET in particular combines temperature, humidity, wind and radiation loads with anthropometric (e.g. age), activity and clothing factors to assess human thermal comfort for a wide variety of sub-populations. Focusing on Cyprus, a Mediterranean island, mPET was computed in the present study based on population-weighted climate data derived from Copernicus European Regional Reanalysis (CERRA), at 5.5 km spatial resolution and at 1 h temporal resolution, using the RayMan Pro Model. The mPET estimates were specifically provided for the five districts of Cyprus and for six different population groups: female and male children, adults, and seniors. Regarding epidemiological data, we considered daily mortality counts and daily morbidity records associated with cardiovascular and respiratory diseases (ICD10 codes: I00-I99 and J00-J99), spanning nearly two decades (2004-2019). To understand how the thermo-physiologically relevant heat stress affects mortality and morbidity rates, we applied Distributed Lag non-Linear models (DLNMs) within the general framework of Generalized Additive Models (GAMs). This modelling framework produces estimates of the temporally distributed effect of mPET on mortality/morbidity rates. We demonstrate how the health risk varies across the various population sub-groups and districts in Cyprus and that using mPET rather than single heat-related meteorological metrics enables such differences to be better highlighted. This is the first time that health risks arising from heat were assessed for various demographics in Cyprus, providing crucial information for better understanding the climate change impact in the country.
How to cite: Tzyrkalli, A., Giannaros, C., Kekkou, F., and Economou, T.: Effects of the modified Physiologically Equivalent Temperature on mortality and morbidity in the Mediterranean, a case study for Cyprus, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-256, https://doi.org/10.5194/ems2024-256, 2024.
Gridded climate datasets have been significantly developed and improved since the release of the first multi-year global retrospective analyses (reanalyses) in the 1990s. Today, they are widely used in various weather- and climate-related applications. In the field of human bioclimate specifically, the wealth of data provided by both global and regional reanalyses allows for developing datasets of spatially explicit thermal stress metrics, including rational indices, such as UTCI (Universal Thermal Climate Index), that account for both the environmental and personal/physiological factors associated with the human thermal environment. However, to date, no such dataset has been developed considering the variability of anthropometric factors (e.g. age), activity and clothing among different population groups. This diminishes the value of human thermoregulation responses, which are critical for characterizing and dealing with the increased sensitivity of specific populations (e.g. outdoor workers) to the thermal environment. To address this significant gap, here we present the first human thermal bioclimate dataset for diverse populations, along with outcomes related to the dataset’s replicability and exploitability. Initially developed for Greece, using the Copernicus European Regional Reanalysis (CERRA) at 5.5 km spatial resolution, population data and human energy balance modeling, the dataset consists of hourly, population-weighted values of the modified physiologically equivalent temperature (mPET) for 10 population subsets (female and male adults and seniors, and three different profiles of female and male outdoor workers) in 72 regional units and combinations thereof at the NUTS-3 (Nomenclature of Territorial Units for Statistics-3) level, covering a 30-year period (1991-2020). The dataset also includes the main environmental drivers of mPET (e.g. temperature) at the same spatiotemporal resolution. The data are publicly available at an open access repository (https://doi.org/10.5281/zenodo.10893914), facilitating access to high-quality data for human-biometeorological and environmental epidemiological applications. Open access is also provided to the code used for the dataset development (https://doi.org/10.5281/zenodo.10793067) for assisting its replication in other European counties. Within this framework, the dataset has been recently expanded to include hourly, population-weighted values of mPET and its environmental drivers for six populations (female and male children, adults and seniors) in five districts of Cyprus at the LAU-1 (Local Administrative Units-1) level, between 1991 and 2020. In terms of exploitability, the dataset is currently used for conducting an environmental epidemiological study in Greece, aiming at specifying regional mPET-based heat-related warning thresholds associated with increased mortality risks. In Cyprus, environmental epidemiological studies are also performed for identifying the impact of vapor pressure on human health and for appraising the relationship between mPET and morbidity. In both national studies, the differences in human thermoregulation responses among diverse populations are considered in order to better understand, assess and cope with human thermal stress vulnerability.
How to cite: Giannaros, C., Agathangelidis, I., Galanaki, E., Cartalis, C., Kotroni, V., Lagouvardos, K., Giannaros, T. M., Tzyrkalli, A., Economou, T., and Matzarakis, A.: Hourly values of an advanced human-biometeorological index for diverse populations from 1991 to 2020: Replicability and exploitability aspects, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-54, https://doi.org/10.5194/ems2024-54, 2024.
Heat is one of the most important adaptations possibilities, which cannot only be helpful for the reduction of mortality and morbidity but also an issue in term of work productivity and in general for quality of life worldwide. For the quantification of heat and heat stress, methods from urban climatology and human biometeorology can provide results and information which can be directly applied for combatting/assessing climate impact and for the development of strategies and action against heat. Heat health action plans (HHAP) are a comprehensive tool, which focuses on short, medium and long term goals/aims and are relevant for the protection of vulnerable and risk groups. They consider factors, such as coordination and responsibilities of the Plans, heat health early warning system, information ways and plans, possibilities of reduction of indoor heat, specific actions for the protection of vulnerable people (mostly elderly), education options for health sectors, urban planning options for reduction of heat and finally the monitoring of actions and their evaluation. The evaluation factor considers the monitoring of the actions. The mitigation of heat and the implication on human health bring several disciplines together and the application and implementation of actions require scientific results and analysis based not only on measurements but also the application of micro scale models, under consideration validation of results. In addition, the knowledge of quantification of heat implications and the use of heat health warning systems are crucial for the protection of human life from extreme heat and heat waves. Finally, HHAPs should be often updated and consist from a preparation and post-processing part and are an issue not only during summer and extreme heat conditions and heat waves.
How to cite: Matzarakis, A.: Heat Health Action Plans - The Role of Human Biometeorology and Urban Climatology, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-271, https://doi.org/10.5194/ems2024-271, 2024.
Weather and climate constitute vital resources exploited by the tourism sector. Climate influences the behaviour of tourists through their motivation to travel and destination selection. Climate change is a major challenge for tourism, significantly affecting tourism supply and demand. Thus, the recognition of the observed and expected future climate suitability for a given region or destination is of outstanding importance. In the research, I evaluate the impacts of climate change for the area of Hungary based on two tourism climate metrics: a modified form of the Tourism Climate Index (mTCI, Kovács et al. 2016) and the urban Holiday Climate Index (HCI:Urban, Scott et al. 2016). The observed tourism climate conditions are quantified for the period 1971–2000 using the grid point based observational database CarpatClim-HU at 10 km horizontal resolution. Future conditions are described for the periods 2041–2070 and 2071–2100 based on two regional climate models (ALADIN and REMO) driven by different global climate models. Two emission scenarios (RCP4.5 and RCP8.5) are used to describe the future anthropogenic activity in the models. This multi-model and multi-scenario ensemble method allows taking into consideration the uncertainties in climate model predictions. The spatial distribution of indices are displayed on maps on a Hungarian district scale as well as on a monthly basis. In the present period, based on both indices, the shoulder months (April, May, September and October) are characterised with the most favourable conditions, while there is a slight deterioration in climate suitability in summer. According to future tendencies, both metrics indicate that less favourable conditions are expected in the summer months in large parts of the country. Certain scenarios also show a slight drop in May and September. However, most shoulder months (March, April, October and November) seem to bring more pleasant circumstances for tourism. The winter period is likely to be characterised with the same or slightly better conditions in the future. The results demonstrate that climate change will have an apparent impact on tourism in Hungary.
Project no. 142335 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the PD_22 funding scheme.
How to cite: Kovács, A.: Evaluation of climate change impacts for tourism in Hungary based on tourism climate metrics, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-95, https://doi.org/10.5194/ems2024-95, 2024.
Under climate warming, urban areas with concentrated populations and high-density development are facing the challenge of increasing temperature. Due to Taiwan’s diverse geographical environment, the features of the urban heat island effect are affected by various geographical factors. It is necessary to rely on long-term observational climate data in order to present the complex urban microclimate changes. This study aims to identify hot spots in urban areas, comprehensively compareing the impact of different geographical environmental features on urban heat islands, and establish predictive models and adaptative strategies.
Our research team established a high-density street-level air temperature observation network (HiSAN) in Taiwan cities such as Taipei, Taichung, Tainan and Kaohsiung to collect hourly temperature data at the urban block scale from 2020 to 2023. Through these data, a comparative analysis of the heat island effect is carried out, taking into account the geographical features of each place, such as basins and sea-land breezes, and visualizing them with climate maps. The study found that, in summer, Taipei often experiences temperatures 2-3°C higher than surrounding areas, as the basin topography restricts air circulation, leading to the accumulation of warm air in the city which exacerbates the heat island effect. Taichung city demonstrates a relatively uniform temperature distribution and maintains temperatures 1-2°C above suburban averages. Tainan city’s temperatures are approximately 2°C higher than suburban averages. In Kaohsiung City, the urban temperatures often 3-4°C higher than suburban areas, especially in central areas, with high building density and less green space, the urban heat island effect is most obvious.
The research results also show that the heat island effect in Taipei and Taichung is closely related to the topography of their basins, while Tainan and Kaohsiung are more affected by sea-land breezes. The terrain features of Taipei and Taichung urban areas cause the urban heat storage area to be located in the basin; while the terrain of Tainan and Kaohsiung urban areas is flat, the urban heat island phenomenon is affected by the distance from the sea (sea-land breeze), and the heat island center moves significantly during the day and night. The high-density street-level air temperature observation network system contributes to urban microclimate research. It also helps to identify hot spots in urban areas, and provides useful information in analyzing the temperature and outdoor human thermal comfort of local climate zones in cities and surrounding areas. The research results also provide important references for urban planning and climate adjustment.
Keywords: urban heat island, geographical environment features, sea-land breeze, high-density street-level air temperature observation network
How to cite: Hsieh, C.-J. and Lin, T.-P.: The Analysis of Utilizing Urban High-Density Street-level Air Temperature Observation Networkto Analyze the Urban High Temperature Changes with Different Geographical Environment Features, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-227, https://doi.org/10.5194/ems2024-227, 2024.
: With the rapid increase in global warming, the impact of extreme temperatures on morbidity and mortality related to respiratory diseases has attracted considerable attention. In the current study, we quantified the relative risks (RRs) of mortality for respiratory diseases in three capital cities in Northeast China. We used a distributed lag nonlinear model (DLNM) based on a generalized additive model (GAM) to estimate the impact of extreme temperatures on respiratory mortality in Shenyang, Changchun, and Harbin from 2014 to 2016. The results revealed that the maximum cumulative RRs and 95% confidence intervals (CIs) were 1.52 (1.28–1.80), 1.42 (1.07–1.89), and 1.38 (1.21–1.58) in Shenyang, Changchun, and Harbin respectively when the median temperature was used as reference. The effect of extremely high temperature (99th percentile relative to 90th percentile) on respiratory mortality was found to be strongest in Shenyang (at the lowest latitude), while the effect of extreme low temperature (1st percentile relative to 10th percentile) on respiratory mortality was strongest in Harbin (at the highest latitude). In Shenyang and Changchun, the effects of high temperatures were much more intense and pronounced in females. Furthermore, the effect of high temperatures was more acute, whereas the effect of low temperatures was longer lasting. Conclusions are as follows: extreme temperatures have significant effects on morbidity related to respiratory diseases in Northeast China. At lower latitudes, the effect of high temperatures was lower and that of cold temperatures was higher. The heat effect was acute and short lasting, whereas the cold effect was weaker but longer lasting. Moreover, the heat effect was stronger among the female population than among the male population. The results of this study could provide suggestions for reducing the impact of extreme temperatures on human health.
How to cite: Ma, Y.: Extreme temperatures and respiratory mortality in the capital cities at high latitudes in Northeast China, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-112, https://doi.org/10.5194/ems2024-112, 2024.
A hot summer or heatwave event induces heat stress-related human deaths. Reducing the number of those deaths is stated on one of social issues for urban resilience and sustainability. This study aims to evaluate a change in the deaths if energy-saving or temperature-decreasing measures in urban modifications would be installed as the climate change adaptation in the whole urban area, from a novel approach combined machine learning (ML) techniques with meteorological model simulations. In this study, the WRF-CMBEM (the WRF, the urban multi-layer, and building energy models) was used to simulate spatiotemporally urban meteorological conditions, while the ML was applied to perform and predict daily heat stress-related deaths in an urban area.
We covered the most populated Tokyo's 23 wards in Japan and demonstrated the extremely hot summer of 2018. As expected urban modification scenarios, the cases of a ground surface greening (GRN), no anthropogenic heat from buildings to atmosphere (noAH), rooftop photovoltanic (PV), and cool roofs (CRF) were evaluated in this study.
The ML performed well for heat-related daily deaths from heatstroke (HS) and ischaemic heart disease (IHD) by detecting important meteorological factors. After meteorological changes from a control case to four urban modification scenarios were predicted by the WRF-CMBEM, potential reductions in heat-related deaths were estimated using previous successful ML-trained models. As a result in July–August 2018, the GRN case performed the most effective decreases of 0.28 °C (50%ile), 0.37 °C (90%ile), and 0.56 °C (Max) in the outdoor surface air temperature of all grids resolved at 1 km. The temperature changes reduced HS deaths by 43% and IHD deaths by 18% during a peak period of the deaths in the summer 2018. The second effective modification was the CRF case, which showed temperature decreases of 0.23 °C (50%ile), 0.31 °C (90%ile), and 0.36 °C (Max), and a 14% reduction in HS deaths and a 13% reduction in IHD deaths. These demonstrations suggest that the combined implementation of urban modifications is more effective in reducing heat stress-related deaths, especially during heatwaves and extreme hot summers.
How to cite: Ohashi, Y., Nakajima, K., Takane, Y., Kikegawa, Y., Ihara, T., and Oka, K.: Machine learning approach to predict mortality reduction from summer heatstroke and heart disease through urban modification scenarios for climate change adaptation, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-202, https://doi.org/10.5194/ems2024-202, 2024.
Mosquito-borne diseases are among the most dangerous threats for all people living in tropical areas and Dengue fever is one of the fastest growing disease in the world (Watts et al. 2019). Previous research has shown that the highest incidence of mosquito-borne diseases is associated with a particular type of weather (usually wet and hot) as mosquitos’ activity and development are highly dependent on meteorological conditions. However, short-term associations (on the scale of days up to a few weeks) have been less understood.
In this study, we collected weekly data on the incidence of Dengue on a municipality level (obtained from Secretaria de Estado da Saúde de São Paulo). These were aggregated into 17 Regional Health Departments (DRSs) in the state of Sao Paulo, Brazil, 2016–2022 and standardized by population count in each DRS. Additionally, environmental and socioeconomic characteristics of the 17 DRSs were collected and matched with ERA5-based weather characteristics (ambient temperature, relative humidity, wind speed and precipitation). Consequently, we employed a mixed meta-regression model with a random effect in order to analyse the links between Dengue incidence and weather variables, while taking into account the modifying effects of environmental and socioeconomic characteristics.
Our preliminary results suggest the largest relative risk of Dengue incidence at week 0 to 3 after a warm and humid period and up to 12 weeks after a heavy rainfall. Further analysis is needed to identify spatial differences in these patterns based on socioeconomic conditions. This study will contribute to better understanding of short-term links between weather variability and Dengue outbreaks.
Watts, N et al. (2019). The 2019 report of The Lancet Countdown on health and climate change: ensuring that the health of a child born today is not defined by a changing climate. The Lancet, 394(10211), 1836–1878. https://doi.org/10.1016/S0140-6736(19)32596-6
How to cite: Urban, A., Araújo, J., Oliveira, S., S. Celina, S., and Černý, J.: Links between weather variability and Dengue outbreaks in Sao Paulo, Brazil, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-204, https://doi.org/10.5194/ems2024-204, 2024.
Population exposure to hot weather and heat waves endangers human liveability and survivability. The assessment of heat exposure spatiotemporal patterns in both recent past and future can provide essential guidance for targeted adaptation measures. However, existing studies on the topic focus only on environmental heat loads, using single meteorological variables (e.g. air temperature) or simple composite indices (e.g. heat index) to define heat. This diminishes the value of human physiological and behavioral responses to heat. Here, we extend the heat exposure concept to account for these factors and their variability among different population subsets when characterizing heat. For this purpose, we employ a novel, open-access 30-year (1991-2020) human thermal bioclimate dataset that includes hourly values of mPET (modified physiologically equivalent temperature) for diverse populations (https://doi.org/10.5281/zenodo.10893914). We focus on the Athens Urban Area (AUA), which consists of five regional units at the local administrative level, and it is situated in the eastern Mediterranean climate change hot spot. At a first stage, we analyze the long-term trends of acclimatization-based strong heat stress (accliSHS) experienced by male and female adults and seniors in the five AUA regional units. This stage of analysis accounts for accliSHS duration and frequency, as these factors are key in relation to adverse heat-related health outcomes. Then, we combine the mPET estimates with population data for each targeted group and regional unit to compute accliSHS exposure and assess its long-term trends. At this stage, contributions arising for variations in accliSHS and population sizes are decoupled and discussed, focusing on the differences between the examined populations and regional units in AUA. This work is conducted in the framework of the HEAT-ALARM research project and provides valuable insights with respect to population heat exposure for diverse groups of people under a comprehensive human-biometeorological context.
How to cite: Galanaki, E., Agathangelidis, I., and Giannaros, C.: Assessing the exposure of diverse populations to heat under a thermo-physiologically consistent approach in a large Mediterranean urban area, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-297, https://doi.org/10.5194/ems2024-297, 2024.
A thermal stress on human is determinated by a combination of various meteorological variables, such as temperature, humidity, etc. Many indices have been created for the determination of level of thermal stress. Here, we select the universal thermal climate index (UTCI), which is created with the use of temperature, humidity, wind speed, and mean radiant temperature. The UTCI index can be acquired from observed data, however, the calculation of UTCI is also incorporated in some reanalyses and climate models too. Recently, it has been demonstrated that UTCI in central Europe increased in the last 30 years, with the largest increase detected in both summer and winter after 1990. While rising UTCI in winter reflects decreasing thermal stress on human, on the contrary, the rapid increase observed in summer indicates the opposite. The combination of rising temperature and humidity is the main cause behind the increase in the index. In this contribution, we bring the topic to the next level as we analyze the changes in UTCI in the Czech Republic for the entire 21st century. The future evolution of several meteorological variables, including the UTCI index, is incorporated in the Aladin-CLIMATE/CZ model, the domain of which covers the broad area of central Europe. Two scenarios are analyzed: SSP2-4.5 (the intermediate scenario) and SSP5-8.5 (the high scenario). It is evident that UTCI will rise in both annually and seasonally step over almost the whole Czechia, the largest increase being found in the lowlands regions of the country. The substantial increase in thermal stress arising from the changing meteorological conditions in the future is a concerning message, influencing lives of people, mainly in the urban areas.
How to cite: Hynčica, M., Novák, M., and Procházková, S.: Climate projections of UTCI in the Czech Republic, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-306, https://doi.org/10.5194/ems2024-306, 2024.
Tourism has grown in recent years and now involves one sixth of the world's population. However, its dynamics are subject to many economic, social, political and environmental factors. Although the role of weather in the tourist experience is widely recognised, this issue has become increasingly important in recent years as the sector faces the impacts of anthropogenic climate change. Tourist perceptions are important in understanding these impacts. Ratings and reviews shared on websites, social networks and tourism comparison platforms are a useful way of understanding the impact of weather and climate on public perceptions and individual satisfaction.
The aim of this study is to investigate tourists' weather preferences in three of the most visited tourist facilities in Cantabria (northern Spain). First, all TripAdvisor reviews for these facilities were systematically downloaded using automated web scraping techniques. Next, all comments containing information or references were filtered using libraries of weather and climate terms. Finally, the comments were categorised according to the conditions expressed.
Tourists visiting the Cabárceno Nature Park prefer cooler and cloudier days. As most of the activities take place outdoors and usually last several hours, they need to protect themselves from the heat and high levels of radiation. Opinions on rainfall are divided between those who consider it a negative factor and those who appreciate it, while most visitors consider wind to be a negative factor. On the other hand, tourists prefer clear skies at Fuente Dé, as it is a well-known mountain viewpoint. In addition, high temperatures are considered a positive factor almost all year round, while low temperatures are avoided. Rain and wind are generally perceived as negative factors, but usually only for short treks. In Altamira, the influence of the weather is much less obvious, and the only meteor mentioned is rain, but there is no consensus, since for some people rainy days are ideal for visiting the museum, if they don't have to wait in the rain and get wet.
The perception of the weather and its influence on tourism is important and must be considered in the coming years. However, the analysis must be carried out separately for each destination and each type of tourism. Nevertheless, it should be borne in mind that opinions may differ and be partial and therefore need to be critically analysed and combined with local surveys and frequentation data.
How to cite: Conde-Oria, F., Rasilla, D. F., and Toribio Pérez, M.: Analysis of tourists' perceptions regarding the weather influence in Cantabria based on TripAdvisor reviews, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-469, https://doi.org/10.5194/ems2024-469, 2024.
Numerous studies have thoroughly documented the contribution of non-optimal temperatures and acute respiratory infections (ARIs) to increased mortality. However, there is still a gap in understanding how these factors interact together to affect human mortality during the cold season, and how this impacts population susceptibility to heat waves in the summer.
In this study we conduct an analysis over a period spanning 38 years (1982–2019), utilizing: a) daily all-cause mortality counts across the Czech Republic, b) daily proxies of acute respiratory infections (ARIs) incidence, interpolated from weekly healthcare surveillance data, and distinguished regarding three dominant influenza viruses (A/H3N2, A/H1N1, and B), and c) a suite of weather variables, sourced from E-OBS gridded data, including daily mean, maximum, and minimum temperatures, daily precipitation, daily mean sea level pressure, daily mean wind speed, daily mean relative humidity, and radiation level.
To investigate the complex associations between mortality rates, ARI incidence, and weather variability, we employ a distributed lag non-linear model (DLNM) with multiple cross-bases. This approach facilitates the adjustment for confounding meteorological variables and provides a better understanding of their impact as fluctuating confounders. From these refined models, we derived the fraction of mortality attributable to ARIs and low temperatures, offering a quantification of their impact on excess mortality in the cold season. Additionally, we analyse changes in seasonal patterns of mortality according to the meteorological and epidemiological characteristics and assess temporal associations between air temperature and mortality in summer considering factors like intensity of ARI outbreaks and the mean winter temperature in the previous cold season. Our results contribute to better understanding of the links between temperature variability, respiratory infection dynamics and the seasonal variations in mortality.
How to cite: Borisova, E., Urban, A., Hanzlíková, H., Plavcová, E., Kyselý, J., Kynčl, J., and Ballester, J.: The compound effect of acute respiratory infections and temperatures on mortality in the Czech Republic, 1982–2019, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-602, https://doi.org/10.5194/ems2024-602, 2024.
Climate change poses a threat to the tourism industry, potentially shifting travel patterns and destination preferences. The aim of the research was to assess the risks in Slovenian Istria, propose appropriate measures and discuss their feasibility in stakeholders’ workshops. The analysis of past climate data from the archive of Slovenian Environment Agency showed that since 1950, the number of hot days (with maximal daily temperature above 30°C) has increased by about 4.5 days per decade, and tropical nights (with minimum daily temperature above 20°C) by 2–5 days per decade. Precipitation patterns are changing. Climate projections show the trend is expected to continue with an increase in hot days by an average of 10 (RCP4.5) to 19 (RCP8.5) in the first period (2011–2040), and 19 (RCP4.5) to even 30 (RCP8.5) in the second period (2041–2070). Tropical nights are also projected to become more common. Climate index for beach tourism (CIT:3S) shows an increase in ideal days during summer months since 1971–2000. While the overall share of ideal and marginal days for beach tourism is projected to further increase from May to September across all scenarios, the number of ideal days in July and August is expected to decline, particularly under RCP8.5 by the end of the century. The season is likely to extend primarily into September. An index for urban tourism suitability (HCI) shows over ¾ of days from May to September are ideal, with a slight decrease in July recently. The percentage of ideal days is rising significantly in March, April, and October. All scenarios predict a year-round extension of the season.
Global warming threatens to make Slovenian Istria a less comfortable destination, especially during peak season. More frequent and severe heat waves and floods threaten tourist infrastructure and safety. Frequent droughts could exacerbate water shortages, impacting both residents and tourists. Despite the challenges, there are also potential opportunities for extending the tourist season into spring and autumn. Slovenian Istria can adapt with investments in water-saving measures, building seawalls, and thermal insulation of the buildings. Promoting Istria as a year-round destination with events and activities in spring and autumn can reduce reliance on summer tourism. Additionally, implementing early warning systems, providing natural and artificial shade, drinking fountains, staff training on self-protective measures, and adaptations like scheduling activities outside peak heat hours can ensure tourists' safety and comfort.
By implementing an appropriate adaptation strategy, the region can remain a competitive tourist destination. However, financial and logistical limitations may exist. We will also present the results of workshops where tourism stakeholders in four tourist destinations discussed the feasibility of adaptation measures.
How to cite: Pogačar, T., Kokot, K., and Turnšek, M.: Assessing climate change risks and exploring feasible adaptation measures for the tourism sector in Slovenian Istria , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-655, https://doi.org/10.5194/ems2024-655, 2024.
Climate change is highly likely to increase both the frequency and severity of heatwaves, posing a significant challenge to global health. Heatwaves are associated with an increased risk of human mortality, particularly during extreme events that exceed local acclimatization thresholds. However, the impact of heatwaves is not uniformly distributed across all populations. Certain demographic groups, especially the elderly and children, are at a higher risk due to physiological and socioeconomic factors. Moreover, the literature indicates that environmental and socioeconomic factors, such as access to green spaces and income level, also play a crucial role in determining vulnerability to heatwaves. These factors are known to affect thermal comfort, thereby influencing the ability of individuals to cope with extreme heat. Therefore, to mitigate heat-related health outcomes, it is necessary to evaluate the heat vulnerability of districts in Prague and identify where mitigation measures and interventions are most urgently required.
We use geographically weighted principal components analysis (GWPCA) to determine the role of meteorological (mean summer air temperature, mean number of heatwave days), environmental (proportion and type of greenery, urban coverage ratio), and socioeconomic factors (demographic structure, unemployment rate, mean income) on heat vulnerability (daily heat-related mortality and ambulance call outs spanning the period 2001–2023) in 22 districts of Prague, Czechia. To investigate the influence of air temperature, we utilize a novel ALADIN/CLIMATE-CZ reanalysis with high spatial resolution (2.3 x 2.3 km). Finally, a multivariate meta-regression model is used to determine the risk of mortality and ambulance call-outs associated with high temperature in each district, taking into account the modifying effect of the district characteristics (i.e., principal components from the GWPCA).
Our findings will provide new insights to the heat vulnerability assessment in Prague and will enable us to determine the most at-risk areas of Prague regarding its population structure and environmental conditions. The study contributes to a comprehensive understanding of the underlying drivers of heat vulnerability in Prague and informs targeted interventions to mitigate the impacts of extreme heat on vulnerable populations.
How to cite: Dogan, T. and Urban, A.: Socioeconomic and Environmental Determinants of Heat Vulnerability in Prague, Czechia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-793, https://doi.org/10.5194/ems2024-793, 2024.
