The effects of summer ambient temperature on total mortality in Serbia.

In the context of recent climate change, temperature-attributable mortality has become an important public health threat worldwide. A large number of studies in Europe have identified a relationship between temperature and mortality, while only a limited number of scholars provided evidence for Serbia. In order to provide more evidence for better management of health resources at the regional and local level, this study aims to assess the impact of summer temperature on the population in Serbia, using daily average temperature (Ta) and mortality (CDR (crude death rate) per 100,000). The analysis was done for five areas (Belgrade, Novi Sad, Nis, Loznica, and Vranje), covering the summer (June-August) period of 2001-2015. In order to quantify the Ta-related CDR, a generalized additive model (GAM) assuming a quasi-Poisson distribution with log as the link function was used. Five regression models were constructed, for each area, revealing a statistically significant positive relationship between Ta and CDR in four areas. The effect of Ta on CDR was defined as the relative risk (RR), which was obtained as the exponential regression coefficient of the models. RR indicates that a 1 °C increase in Ta at lag0 was associated with an increase in CDR of 1.7% for Belgrade, Novi Sad, and Nis and 2% for Loznica. The model for Vranje did not quantify a statistically significant increase in CDR due to Ta (RR=1.006, 95% CI 0.991-1.020). Similar results were confirmed for gender, with a slightly higher risk for women. Analysis across lag structure showed different exposure, but the highest effect of Ta mainly occurs over the short term and persists for 3 days.

Analysis of long- and short-term biometeorological conditions in the Republic of Serbia.

Long- and short-term biometeorological conditions in the Republic of Serbia were analyzed using official meteorological data from numerous weather stations located across the country. Selected biometeorological indices HUMIDEX, Physiologically Equivalent Temperature (PET), and Universal Thermal Climate Index (UTCI) are calculated based on air temperature, relative humidity, wind speed, and cloudiness data from the meteorological stations on annual and summer level as well as during selected heat wave periods during 2000-2020. Application of different biometeorological indices provides similar but somewhat different results. For example, average annual HUMIDEX and UTCI values indicate no thermal stress and no discomfort at all stations, while PET indicates the occurrence of slight to moderate cold stress at all stations. Average summer PET and UTCI indicate the occurrence of slight to moderate heat stress throughout the country, while HUMIDEX indicates no discomfort. Trends of biometeorological indices on annual and summer level show a general increase throughout the country. Furthermore, heat wave analysis indicated that the most populated cities of Serbia are under dangerous and extreme heat stress during these extreme temperature events, which can influence human health and well-being. The obtained biometeorological information can be used for the preparation of climate adaptation strategies that consider the human biometeorological conditions, with a special focus on developing climate-sensitive and comfortable cities.

Hospital admission tendencies caused by day-to-day temperature changes during summer: a case study for the city of Novi Sad (Serbia).

Increased temperature risk in cities threatens the health and well-being of urban population and is fueled by climate change and intensive urbanization. Consequently, further steps must be taken for assessing temperature conditions in cities and their association with public health, in order to improve public health prevention at local or regional level. This study contributes to solving the problems by analyzing the connection between extreme temperatures and the tendencies of all-cause hospital admissions. The analyses used (a) 1-h air temperature data, and (b) daily data of all-cause hospital admissions. The datasets include the summer period (June, July, August) for the years 2016 and 2017. We tested the effects of two temperature indices, day-to-day change in maximum temperature - Tmax,c and daily temperature range - Tr, with all-cause hospital admission subgroups, such as all-cause cases - Ha, hospital admissions in the population below 65 - Ha<65, and hospital admissions in the population aged 65 and over - Ha≥65. The results show the highest values of Ha when Tmax,c is between 6 and 10 °C. Therefore, more intensive hospital admissions can be expected when Tmax increases from day-to-day (positive values of Tmax,c), and it is more visible for Ha and Ha<65 (1 °C = 1% increase in hospital admissions). Also, Tr values between 10 °C and 14 °C cause an increase in the number of hospital admissions, and it is more noticeable for Ha≥65.

Analysis of air temperature dynamics in the "local climate zones" of Novi Sad (Serbia) based on long-term database from an urban meteorological network.

A comprehensive analysis of air temperature (Ta) dynamics in "local climate zones" (LCZs) of Novi Sad (Serbia) was based on measurements from 17 stations during 3 years. Hourly changes of Ta, cooling rates (CR), heating rates (HR), and urban heat island (UHI) intensity were assessed on seasonal and annual level and during heat wave (HW) and cold wave (CW) periods. Substantial differences are observed for minimum (Tmin) and mean temperatures (Tmean) between LCZs. Two-phase nocturnal cooling was recognized with the first cooling phase characterized by intensive LCZ dependent cooling starting at 1-3 h before sunset and lasting until 3-4 h after sunset. The second cooling phase lasts until sunrise and is characterized by less intensive and LCZ nondependent cooling. The most intensive cooling (CRpeak) was observed in first cooling phase of HW and ranged from - 1.6 °C h-1 in street canyon (LCZ 2) to - 3.9 °C h-1 in forest (LCZ A). Furthermore, a new cooling indicator (CRtotal) was introduced. Due to cooling differences, the most intensive UHI of 5.5 °C was noticed between LCZs 2 and A at sunset + 1 h during HW. Two-phase diurnal heating was also recognized in LCZs with the first heating phase characterized by intensive LCZ dependent heating starting at sunrise and lasting until 4-7 h afterwards. The most intensive heating (HRpeak) ranged from 2.0 °C h-1 in street canyon to 3.0 °C h-1 in industrial area (LCZ 8) during HW. The second heating phase lasts until sunset and is characterized by less intensive heating and smaller HR differences between LCZs.

Progressing urban climate research using a high-density monitoring network system.

An increasing number of urban meteorological networks (UMNs) and automated data acquisition are irreplaceable tools in modern urban climate monitoring, evaluation, and analysis. The most serious issue in such systems is data loss, caused primarily by communication problems between stations and servers. The Novi Sad Urban Network (NSUNET) consists of 28 remote stations and 2 servers built solely on open-source technologies. It is used for monitoring climate peculiarities and acquiring long-term meteorological data from the urban area of Novi Sad, as well as for the early warning notification to the city emergency services of the current urban weather conditions. Since its deployment, the system has managed to overcome most of the problems related to today's UMNs, to operate at a low Internet service fee, and ensure high reliability and performance on low-budget hardware. This study includes details on how to develop such a system and it presents a statistical analysis of the NSUNET system's performances and the measurement data. Furthermore, this kind of monitoring system provides good results in the analysis of air/surface temperature and outdoor human thermal comfort in the local climate zones (LCZs) of urban and surrounding areas and can help identify hot spots/districts in the urban area.

Air Temperature and Relative Humidity Datasets from an Urban Meteorological Network in the City Area of Novi Sad (Serbia).

This data article describes two groups of datasets which capture, firstly - 10-minutes air temperature (Ta) and relative humidity (RH) data from 27 urban and non-urban sites over a period of 3.5 years covering 2014-2018; and secondly - hourly Ta data from 12 urban sites over a period of 2 years covering 2016 and 2017. Both datasets are from urban meteorological network located in the Novi Sad city (Serbia). These datasets have 2 different types of information in the collection: one type provides details about the monitoring sites at which the Ta and RH sensors are placed, while the second type contains Ta and RH data at all sensor locations. In all, the 10-minutes dataset contains about 185,000 instances of Ta and RH data, and the hourly datasets contain 17,544 instances of Ta data. The 10-minutes datasets were not quality controlled, but the hourly Ta data has been cleaned and gap-filled so there are 24 measures at each site for each day. There are multiple potential uses, where this data can be applied. It can provide insights in understanding intra-urban and inter-urban research, urban climate modeling on local or micro scales, heat-related public health investigations and urban environment inquiries. It can also be used in machine learning experiments, for example, to test the accuracy of classification algorithms or to build and validate spatio-temporal machine learning functions, either for classification purposes or for gap filling. These datasets are directly citable through its DOIs and available for download from the Zenodo platform or from the Fair Micromet Portal.

Mask wearing behavior in hot urban spaces of Novi Sad during the COVID-19 pandemic.

Urban overheating (due to climate change and urbanization) and COVID-19 are two converging crises that must be addressed in tandem. Fine-scale, place-based, people-centric biometeorological and behavioral data are needed to implement context-specific preventative measures such as mask-wearing. This study collected local biometeorological measurements in diverse urban spaces (square, urban park, river quay) in Novi Sad, Serbia on hot sunny summer days (27-30 August 2020) during the COVID-19 pandemic. Observations were supplemented by an online survey asking questions about thermal sensation, comfort, and concurrent protective behavior of the local population. Biometeorological measurements show that the main square in the city center was the most thermally uncomfortable area. According to the survey, it was also perceived as the least safe space to not contract the virus. The urban park was perceived as the most thermally comfortable area in the morning and during midday. It was also considered the safest urban space for outdoor activities. In the evening, the river quay was the most thermally comfortable area in the city. Intra-urban differences in Physiologically Equivalent Temperatures were highest during midday, while differences in air temperatures were highest in the evening. More than 70% of the respondents did not wear face masks when it was hot because of breathing issues and feeling warmer than without mask. Most people wearing a mask felt "slightly warm" in the morning and evening, while the majority of respondents felt "hot" during midday. Only 3% of the respondents felt comfortable while wearing a mask, while 97% experienced some degree of discomfort (from slight discomfort to very uncomfortable). Our study shows that fine scale temporal and spatial urban biometeorological data and population surveys should be included in decision-making processes during the pandemic to develop climate-sensitive health services that are place-based, people-centric, and facilitate planning towards green, resilient, and inclusive cities.

Modelled spatiotemporal variability of outdoor thermal comfort in local climate zones of the city of Brno, Czech Republic.

This study uses the MUKLIMO_3 urban climate model (in German, Mikroskaliges Urbanes KLImaMOdell in 3-Dimensionen) and measurements from an urban climate network in order to simulate, validate and analyse the spatiotemporal pattern of human thermal comfort outdoors in the city of Brno (Czech Republic) during a heat-wave period. HUMIDEX, a heat index designed to quantify human heat exposure, was employed to assess thermal comfort, employing air temperature and relative humidity data. The city was divided into local climate zones (LCZs) in order to access differences in intra-urban thermal comfort. Validation of the model results, based on the measurement dates within the urban monitoring network, confirmed that the MUKLIMO_3 micro-scale model had the capacity to simulate the main spatiotemporal patterns of thermal comfort in an urban area and its vicinity. The results suggested that statistically significant differences in outdoor thermal comfort exist in the majority of cases between different LCZs. The most built-up LCZ types (LCZs 2, 3, 5, 8 and 10) were disclosed as the most uncomfortable areas of the city. Hence, conditions of great discomfort (HUMIDEX >40) were recorded in these areas, mainly in the afternoon hours (from 13.00 to 18.00 CEST), while some thermal discomfort continued overnight. In contrast, HUMIDEX values in sparsely built-up LCZ 9 and non-urban LCZs were substantially lower and indicated better thermal conditions for the urban population. Interestingly, the model captured a local increase of HUMIDEX values arising out of air humidity in LCZs with the presence of more vegetation (LCZs A and B) and in the vicinity of larger bodies of water (LCZ G).