Implementation of human thermal comfort information in Köppen-Geiger climate classification-the example of China

Lower COVID-19 Incidence in Low-Continentality West-Coast Areas of Europe

In March 2020, the first known cases of COVID-19 occurred in Europe. Subsequently, the pandemic developed a seasonal pattern. The incidence of COVID-19 comprises spatial heterogeneity and seasonal variations, with lower and/or shorter peaks resulting in lower total incidence and higher and/or longer peaks resulting higher total incidence. The reason behind this phenomena is still unclear. Unraveling factors that explain why certain places have higher versus lower total COVID-19 incidence can help health decision makers understand and plan for future waves of the pandemic. We test whether differences in the total incidence of COVID-19 within five European countries (Norway, Sweden, Germany, Italy, and Spain), correlate with two environmental factors: the Köppen-Geiger climate zones and the Continentality Index, while statistically controlling for crowding. Our results show that during the first 16 months of the pandemic (March 2020 to July 2021), climate zones with larger annual differences in temperature and annually distributed precipitation show a higher total incidence than climate zones with smaller differences in temperature and dry seasons. This coincides with lower continentality values. Total incidence increases with continentality, up to a Continentality Index value of 19, where a peak is reached in the semicontinental zone. Low continentality (high oceanic influence) appears to be a strong suppressing factor for COVID-19 spread. The incidence in our study area is lowest at open low continentality west coast areas.

The use of sun-shade on safe heat exposure limit on a sunny summer day: a modelling study in Japan

Sustainable methods are required to reduce the risks of thermal strain and heat-related illness without exacerbating greenhouse gas emissions. We investigated the effects of sun-shade use on safe heat exposure limit on a sunny summer day using historical climate data in Japan. We simulated a heat-acclimatised person standing at rest (metabolic heat production, 70 W·m^-2) and during light work (100 W·m^-2) on an asphalt pavement in the sun and sun-shade. Japan has three Köppen climate regions: tropical, temperate and cold. We analysed one city in the tropical region (24°N), three cities in the temperate region (31°N, 35°N and 39°N) and one city in the cold region (40°N). Hourly data were collected from 7 AM to 6 PM, June to September, from 2010 to 2019. The day with the longest daylight hours and the greatest solar radiation intensity was used for analysis. With sun-shade (a white polyester tarpaulin/awning), ambient temperature, global solar radiation and ground surface temperature were assumed to be 0.5°C, 45% and 6°C lower than in the sun, respectively. Sun-shade use eliminated the days with at least 1 hour exceeding safe heat exposure limit at rest in all cities. The same was observed for light work in the temperate and cold cities, although the tropical city had 2 days exceeding safe heat exposure limit during the decade. Sun-shade use on a sunny summer day can be an effective and sustainable method to reduce heat exposure hazard at rest and during light work in tropical, temperate and cold climate regions.

Comments about Urban Bioclimate Aspects for Consideration in Urban Climate and Planning Issues in the Era of Climate Change

In the era of climate change, before developing and establishing mitigation and adaptation measures that counteract urban heat island (UHI) effects [...]

Approaching environmental human thermophysiological thresholds for the case of Ankara, Turkey

The disclosed study undertook a 'human centred-approach' that ascertained and categorised environmental human thermophysiological risk factors by relating them to the human biometeorological system through the use of three widely utilised energy balance model (EBM) indices, the physiologically equivalent temperature (PET), the modified PET, and the universal thermal climate index (UTCI). The disclosed assessment was carried out over the past decade (i.e., 2010-2019) with a 3-h temporal resolution for the case of Ankara through two WMO meteorological stations to compare both local urban and peri-urban environmental conditions. The study recognised extreme annual variability of human physiological stress (PS) during the different seasons as a result of the biometeorological processing of the singular variables, which in the case of average PET for both stations, varied by up to 75 °C between the winter and summer for the same annual dataset (2012). In addition, all EBMs indicated higher heat stress within the city centre that were conducive of both urban extreme heatwaves and very hot days during the summer months, with extreme heat stress levels lasting for longer than a week with PET values reaching a maximum of 48 °C. Similar cold extremes were found for the winter months, with PET values reaching - 30 °C, and average PS levels varying lower in the case of the peri-urban station. Graphical abstract.

The association between PM2.5 exposure and daily outpatient visits for allergic rhinitis: evidence from a seriously air-polluted environment

Limited evidence was seen as the association between fine particulate matter (PM_2.5) and physician visits for allergic rhinitis (AR), especially in countries with extreme air pollution exposure. This paper addressed the issues about the association between PM_2.5 and daily outpatient visits for AR among individuals residing in Beijing, China. Data on daily outpatient visits for AR obtained from Beijing Medical Claim Data for Employees and daily PM_2.5 concentrations available from US embassy reports were linked by date from January 1, 2010, to June 30, 2012. A time-series analysis was conducted with a generalized additive Poisson model to assess the association between PM_2.5 and AR, adjusting for daily average temperature, relative humidity, day of the week, calendar time, and public holiday. Totally, 229,685 outpatient visits for AR were included in the analysis. The daily mean (SD) concentration of PM_2.5 was 99.5 (75.3) μg/m³ during the study period. We found that a 10-μg/m³ increase in PM_2.5 content was associated with a 0.47% (95% CI: 0.39% to 0.55%) increase in the number of outpatient visits on the same day. Furthermore, results from subgroup analyses suggested that the association was consistently significant among the groups of different ages (< 65 years and ≥ 65 years) and gender. However, this study failed to find a statistically significant association in the autumn season but found significant positive associations during the spring and summer seasons (P for interaction < 0.001). This study indicated a possible association between PM_2.5 and AR outpatients, which may benefit further researches in studying PM_2.5 and its influence on diseases in a real and seriously air-polluted context.

Implications of climate and outdoor thermal comfort on tourism: the case of Italy

Whether a journey is pleasant or not usually depends on the climatic conditions which permit to perform outdoor activities. The perception of climatic conditions, determined by physiological and psychological factors, can vary according to different adaptation phenomena related to the person involved and the weather conditions of the place where they live. Studying the bioclimatology of a country characterized by a high flux of tourism, as e.g. Italy, can provide some important information about where and when is it better to visit a place. Some differences have to be specified though, like the local tourism, which is used to that type of climate, and international tourism, which is formed by people coming from countries with different types of climates. Therefore this paper examined the climatic conditions and outdoor thermal comfort through the Mediterranean Outdoor Comfort Index (MOCI) for local tourism and through the predicted mean vote (PMV) for international tourism. The cities examined were three (Venice, Rome and Palermo located in the North, Centre and South of Italy, respectively), where average information were collected every week for an entire year. Finally, a map of the entire Italian territory reporting the seasonal average values of these indexes was also reported.