The relationship between thermal sensation and cardiovascular patients' admission rates in Tabriz, Iran.

Atmospheric conditions in any place can affect people's health. In recent years, researchers have focused on heat stress and its effect on the exacerbation of some diseases. The main objective of this study is to identify the bioclimatic conditions and its relationship with the admission rate of cardiovascular patients in of Tabriz city. In addition to meteorological variables, daily cardiovascular patient admission rates were obtained from Shahid Madani Heart Hospital in Tabriz during the statistical period of March 27th, 2007 to February 17th, 2017. To do so, the bioclimatic conditions of Tabriz were identified on a daily scale based on bioclimatic indices including Perceived Temperature (PT), Physiological Equivalent Temperature (PET) and Predicted Mean Vote (PMV). Then, the relationship between each bioclimatic condition and the number of cardiovascular patients' referrals in Tabriz was investigated using Kruskal-Wallis test. Findings illustrated that the impact of cold stress in the rate of cardiovascular patients was more than that of the warm stress, which was obtained for all study indicators in a similar way. On the other hand, the results showed that based on PET and PMV indices, there is a significant difference between various bioclimatic classes in the rate of cardiovascular patients' admission. The results of Kruskal-Wallis test include Sig = 0.040 and Sig = 0.049 for PET and PMV, respectively. However, Sig values for and PT indice showed no significant difference between bioclimatic classes in the rate of admission of cardiovascular patients. Generally, it was found that there is a significant difference (Sig = 0.000) between the three classes of bioclimatic cold, warm and comfort with the number of hospital admissions of cardiovascular patients.

Quantifying the cooling effect of rain events on outdoor thermal comfort in the southern coastal stations of the Caspian Sea.

Pleasant outdoor thermal conditions depend on a wide range of climatic elements. The impact of rainfall events, as important climatic elements, on providing thermal comfort, has been less explored in the available literature. The work presented herein investigates the impact of Rainy Days as well as a Day Prior to (Dprior) and a Day Post rain (Dpost) events on thermal conditions in the southern coastal region of the Caspian Sea. In this study, rainfall events during 1961-2017 observational period were categorized based on their intensity. Then, human thermal comfort during non-rainy (sunny) and rainy days was estimated and compared by using the radiation-driven Physiological Equivalent Temperature (PET) index, Universal Thermal Climate Index (UTCI) and Perceived Temperature (PT) index. Furthermore, difference between the average of thermal conditions in rainy days compared to a day prior and a day post rain events was calculated separately for comfort, cold and heat stress thresholds of each bioclimatic index. Finally, the correlation between the average of indices for rainy days and the frequency of rainfall events of each specific year was computed. Results suggested that overall average of studied indices for all rainy days is lower than the average for days prior and post the rain events. PET index has shown to be most impacted and reduced as a result of rain events and therefore more indicative of a cool ing effect. The observed difference in total average of PET in rainy days compared to non-rainy days were 8.30 °C, 5.86 °C and 8.85 °C for Babolsar, Rahst and Gorgan stations, respectively. Generally, the cooling effect of rain events on the temperature for a day prior rain events is higher than a day post rainfall. Finally, the trend analysis on rainy days in the studied period revealed that the average of bioclimatic indices in western stations (Babolsar and Rasht) are increasing whereas a decreasing trend was observed for Gorgan as more of an eastern station.

Evaluating the wind cooling potential on outdoor thermal comfort in selected Iranian climate types.

Wind is one of the main factors affecting people's outdoor thermal sensation. Ongoing urbanization and urban densification are transforming the urban climate and complicating the pedestrian-level wind environment. Therefore, the main aim of this research is to evaluate the potential wind-cooling effect on human outdoor thermal conditions. Accordingly, the current research attempts determine the best wind directions for thermal comfort at the studied stations and how these factors will be changed under the effects of global warming. Outdoor thermal conditions were modeled based on the physiologically equivalent temperature (PET) thermal index using RayMan software for the decades of the 2000s and the 2040s in different climate types of Iran (Csb, BWh, Csa, and BSh) To estimate the potential cooling effect of wind, the PET was calculated (1) under actual wind conditions, and (2) under calm wind (0.05 m/s) conditions. Then, the ΔPET for these two conditions, which indicates the cooling potential effect (CPE) of the wind, was calculated for four representative stations (Ardebil, Bandar Abbas, Gorgan, and Shiraz). In comparison with the 2000s, the results indicated that by the 2040s, the predicted wind cooling potential will have increased in Ardebil, Shiraz, Bandar Abbas and Gorgan (CPE of 13.2 °C, 13.1 °C, 11.2 °C, and 11 °C, respectively). Based on the overall average of two climate change scenarios (A2 and B1) used in this study, the occurrence of "comfortable" conditions by the 2040s will have increased in Bandar Abbas, Shiraz, and Ardebil by 1.1%, 0.4%, and 0.3%, respectively, while it will have decreased in Gorgan by 1.5%. Accounting for the cooling effect of wind, the comfort cooling potential of wind is predicted to rise by an average of 1.6 °C in the 2040s compared with the 2000s in all the studied stations. Therefore, this will affect the microclimates positively and could reduce the urban heat island effects.

Developing a thermal stress map of Iran through modeling a combination of bioclimatic indices.

Thermal stress poses significant direct and indirect risks to human health. Under climate change, both mean temperature and the frequency and intensity of extreme thermal stress events are projected to increase. Located within an arid to semi-arid region, Iran is anticipated to experience particularly intense temperature and humidity changes under climate change, potentially heightening the public health challenges associated with thermal stress. To facilitate improved adaptation to these thermal threats, accurate high spatial resolution thermal heat stress risk maps are important. This study combines various climate indices to produce such a thermal stress risk map for the reference period 1980-2010, with RCP4.5 projections for the period 2020-2049. Although the results of the various indices are statistically significantly correlated, each index returned a remarkably different spatial distribution and risk classification. Therefore, a fuzzy approach was followed through a geographical information system (GIS) to combine the results of the five bioclimatic indices and prepare a final thermal stress risk map. Based on the RCP4.5 scenario, the results indicate a notable 24.5% reduction in the areas susceptible to thermal stress at the high-risk and very high-risk levels, compared with the reference period. The lowest projected risk is for the central parts of Iran, while the southern and northern coasts of Iran were the zones of the highest risk, for which adaptation responses are most necessary.

Assessment of the climatic potential for tourism in Iran through biometeorology clustering.

This study presents a spatiotemporal analysis of bioclimatic comfort conditions for Iran using mean daily meteorological data from 1995 to 2014, analyzed through Physiological Equivalent Temperature (PET) index and Universal Thermal Climate Index (UTCI) indices, and bioclimatic clustering. The results of this study demonstrate that due to the climate variability across Iran during the year, there is at any point in time a location with climatic condition suitable for tourism. Mean values demonstrate maxima in bioclimatic comfort indices for the country in late winter and spring and minima for summer. Seven statistically significant clusters in bioclimatic indices were identified. Comparing these with clustering performed on PET and UTCI, the maximum overlaps between the two indices. In the following, the outputs of this research showed that most appropriate bioclimatic clustering for Iran includes seven clusters. These clustering locations according to climatic suitability for tourism provide a valuable contribution to tourism management in the country, particularly through marketing destinations to maximize tourist flow.

Analysis and Comparison of Spatial-Temporal Entropy Variability of Tehran City Microclimate Based on Climate Change Scenarios.

Urban microclimate patterns can play a great role for the allocation and management of cooling and heating energy sources, urban design and architecture, and urban heat island control. Therefore, the present study intends to investigate the variability of spatial and temporal entropy of the Effective Temperature index (ET) for the two basic periods (1971-2010) and the future (2011-2050) in Tehran to determine how the variability degree of the entropy values of the abovementioned bioclimatic would be, based on global warming and future climate change. ArcGIS software and geostatistical methods were used to show the Spatial and Temporal variations of the microclimate pattern in Tehran. However, due to global warming the temperature difference between the different areas of the study has declined, which is believed to reduce the abnormalities and more orderly between the data spatially and over time. It is observed that the lowest values of the Shannon entropy occurred in the last two decades, from 2030 to 2040, and the other in 2040-2050. Because, based on global warming, dominant areas have increased temperature, and the difference in temperature is reduced daily and the temperature difference between the zones of different areas is lower. The results of this study show a decrease in the coefficient of the Shannon entropy of effective temperature for future decades in Tehran. This can be due to the reduction of temperature differences between different regions. However, based on the urban-climate perspective, there is no positive view of this process. Because reducing the urban temperature difference means reducing the local pressure difference as well as reducing local winds. This is a factor that can effective, though limited, in the movement of stagnant urban air and reduction of thermal budget and thermal stress of the city.

Long-term trends in tourism climate index scores for 40 stations across Iran: the role of climate change and influence on tourism sustainability.

Tourism is a rapidly growing international sector and relies intrinsically on an amenable climate to attract visitors. Climate change is likely to influence the locations preferred by tourists and the time of year of peak travel. This study investigates the effect of climate change on the Tourism Climate Index (TCI) for Iran. The paper first calculates the monthly TCI for 40 cities across Iran for each year from 1961 to 2010. Changes in the TCI over the study period for each of the cities are then explored. Increases in TCI are observed for at least one station in each month, whilst for some months no decreases occurred. For October, the maximum of 45% of stations demonstrated significant changes in TCI, whilst for December only 10% of stations demonstrated change. The stations Kashan, Orumiyeh, Shahrekord, Tabriz, Torbat-e-Heidarieh and Zahedan experienced significant increases in TCI for over 6 months. The beginning of the change in TCI is calculated to have occurred from 1970 to 1980 for all stations. Given the economic dependence on oil exports, the development of sustainable tourism in Iran is of importance. This critically requires the identification of locations most suitable for tourism, now and in the future, to guide strategic investment.

Increasing frost risk associated with advanced citrus flowering dates in Kerman and Shiraz, Iran: 1960-2010.

Flowering dates and the timing of late season frost are both driven by local ambient temperatures. However, under climatic warming observed over the past century, it remains uncertain how such impacts affect frost risk associated with plant phenophase shifts. Any increase in frost frequency or severity has the potential to damage flowers and their resultant yields and, in more extreme cases, the survival of the plant. An accurate assessment of the relationship between the timing of last frost events and phenological shifts associated with warmer climate is thus imperative. We investigate spring advances in citrus flowering dates (orange, tangerine, sweet lemon, sour lemon and sour orange) for Kerman and Shiraz, Iran from 1960 to 2010. These cities have experienced increases in both T max and T min, advances in peak flowering dates and changes in last frost dates over the study period. Based on daily instrumental climate records, the last frost dates for each year are compared with the peak flowering dates. For both cities, the rate of last frost advance lags behind the phenological advance, thus increasing frost risk. Increased frost risk will likely have considerable direct impacts on crop yields and on the associated capacity to adapt, given future climatic uncertainty.

Climate change effect on outdoor ambiences in Iranian cities.

In present research work the effect of climate change over the humidex in Iran is analyzed. From this research, we can conclude that the PDIAQ index showed a special sensibility to changes in temperature and relative humidity, hence, it can be an interesting tool, may be even better than the humidex to show the expected effect of climate change in perception of air quality. Thus, it was found that the humidex expected in the future will be more elevated than that in the preceding period and, on the other hand, the PDWRC has clearly reached a lower value than in the preceding period. The same effects, other than those using the earlier indexes in a more detailed manner, were observed with the PDIAQ. This index showed a higher sensitivity to variations in temperature and relative humidity, than the humidex. Finally, the main results obtained must be considered at the time of design and during construction of future buildings, since buildings that are being constructed today will be occupied in the future years of the 2100s.

Environmental impacts of shifts in surface urban heat island, emissions, and nighttime light during the Russia-Ukraine war in Ukrainian cities.

As recent geopolitical conflicts and climate change escalate, the effects of war on the atmosphere remain uncertain, in particular in the context of the recent large-scale war between Russia and Ukraine. We use satellite remote sensing techniques to establish the effects that reduced human activities in urban centers of Ukraine (Kharkiv, Donetsk, and Mariupol) have on Land Surface Temperatures (LST), Urban Heat Islands (UHI), emissions, and nighttime light. A variety of climate indicators, such as hot spots, changes in the intensity and area of the UHI, and changes in LST thresholds during 2022, are differentiated with pre-war conditions as a reference period (i.e., 2012-2022). Findings show that nighttime hot spots in 2022 for all three cities cover a smaller area than during the reference period, with a maximum decrease of 3.9% recorded for Donetsk. The largest areal decrease of nighttime UHI is recorded for Kharkiv (- 12.86%). Our results for air quality changes show a significant decrease in carbon monoxide (- 2.7%, based on the average for the three cities investigated) and an increase in Absorbing Aerosol Index (27.2%, based on the average for the three cities investigated) during the war (2022), compared to the years before the war (2019-2021). The 27.2% reduction in nighttime urban light during the first year of the war, compared to the years before the war, provides another measure of conflict-impact in the socio-economic urban environment. This study demonstrates the innovative application of satellite remote sensing to provide unique insights into the local-scale atmospheric consequences of human-related disasters, such as war. The use of high-resolution satellite data allows for the detection of subtle changes in urban climates and air quality, which are crucial for understanding the broader environmental impacts of geopolitical conflicts. Our approach not only enhances the understanding of war-related impacts on urban environments but also underscores the importance of continuous monitoring and assessment to inform policy and mitigation strategies.

The case of Tehran's urban heat island, Iran: Impacts of urban 'lockdown' associated with the COVID-19 pandemic.

The increasing expansion of urban environments with associated transformation of land-cover has led to the formation of urban heat islands (UHI) in many urbanized regions worldwide. COVID-19 related environmental impacts, through reduced urban activities, is worthy of investigation as it may demonstrate human capacity to manage UHI. We aim to establish the thermal impacts associated with COVID-19 induced urban 'lockdown' from 20 March to 20 April 2020 over Tehran. Areal changes in UHI are assessed through Classification and Regression Trees (CART), measured against background synoptic scale temperature changes over the years 1950-2020. Results indicate that monthly Tmean, Tmax and Tmin values during this time were considerably lower than long-term mean values for the reference period. Although the COVID-19 initiated shutdown led to an identifiable temperature anomaly, we demonstrate that this is not a product of upper atmospheric or synoptic conditions alone. We also show that the cooling effect over Tehran was not spatially uniform, which is likely due to the complexity of land uses such as industrial as opposed to residential. Our findings provide potentially valuable insights and implications for future management of urban heat islands during extreme heat waves that pose a serious threat to human health.

Modeling the impact of climate change on energy consumption and carbon dioxide emissions of buildings in Iran.

In this study, it has been attempted to quantify model climate change effects of the coming decades on energy demand and carbon dioxide emissions of a dominant building brigade under hot and humid climates on the southern coast of Iran, based on three stations of Bushehr, Bandar Abbas and Chabahar. In this research, the Meteonorm and DesignBuilder software have been used for climate and thermal simulation of building. One of the results of this study is the increase in temperature and relative humidity for the coming decades for all three study stations. The findings of this study showed that the average annual temperature for the 2060s compared to the present decade, will increase by 2.82 °C for Bandar Abbas, by 2.79 °C for Bushehr and for Chabahar it will reach 2.14 °C. This increase in temperature has led to an increase in discomfort warmer days and a decrease in discomfort cold days. But given the climatic type of the area, a decrease in the heating energy demand for the coming decades will not have a significant effect on the pattern of energy consumption inside buildings. Because for two stations of Bandar Abbas and Chabahar, more than 95% of the energy demand for the 2060s is for cooling energy demand, which is about 80% of energy for Bushehr. In total, due to the increased demand for cooling energy in the coming decades, this will further increase carbon dioxide emissions, which is higher in Chabahar than in other study stations.

A new procedure to analyze the effect of air changes in building energy consumption.

BACKGROUND: Today, the International Energy Agency is working under good practice guides that integrate appropriate and cost effective technologies. In this paper a new procedure to define building energy consumption in accordance with the ISO 13790 standard was performed and tested based on real data from a Spanish region. RESULTS: Results showed that the effect of air changes on building energy consumption can be defined using the Weibull peak function model. Furthermore, the effect of climate change on building energy consumption under several different air changes was nearly nil during the summer season. CONCLUSIONS: The procedure obtained could be the much sought-after solution to the problem stated by researchers in the past and future research works relating to this new methodology could help us define the optimal improvement in real buildings to reduce energy consumption, and its related carbon dioxide emissions, at minimal economical cost.

Effect of climate change on outdoor thermal comfort in humid climates.

BACKGROUND: Galicia, in northwest Spain, experiences warm summers and winters. However, the higher relative humidity that prevails the whole year through and the location of the summer hot points are related to real weather heat stroke in the hottest season. However, Planet Global Heating was recently analyzed for the climate in Galicia. Climate change was found to be able to trigger effects that involve a new situation with new potential regions of risk. In this paper, 50 weather stations were selected to sample the weather conditions in this humid region, over the last 10 years. From these results, new regions with a potential for heat stroke risk in the next 20 years were identified using the humidex index. RESULTS: Results reveal that during the last 10 years, the winter season presents more comfortable conditions, whereas the summer season presents the highest humidex value. Further, the higher relative humidity throughout the whole year reveals that the humidex index clearly depends upon the outdoor temperature. CONCLUSIONS: Global Planet Heating shows a definite effect on the outdoor comfort conditions reaching unbearable degrees in the really hottest zones. Therefore, this effect will clearly influence tourism and risk prevention strategies in these areas.

Modeling Caspian Sea water level oscillations under different scenarios of increasing atmospheric carbon dioxide concentrations.

The rapid rise of Caspian Sea water level (about 2.25 meters since 1978) has caused much concern to all five surrounding countries, primarily because flooding has destroyed or damaged buildings and other engineering structures, roads, beaches and farm lands in the coastal zone. Given that climate, and more specifically climate change, is a primary factor influencing oscillations in Caspian Sea water levels, the effect of different climate change scenarios on future Caspian Sea levels was simulated. Variations in environmental parameters such as temperature, precipitation, evaporation, atmospheric carbon dioxide and water level oscillations of the Caspian sea and surrounding regions, are considered for both past (1951-2006) and future (2025-2100) time frames. The output of the UKHADGEM general circulation model and five alternative scenarios including A1CAI, BIASF, BIMES WRE450 and WRE750 were extracted using the MAGICC SCENGEN Model software (version 5.3). The results suggest that the mean temperature of the Caspian Sea region (Bandar-E-Anzali monitoring site) has increased by ca. 0.17°C per decade under the impacts of atmospheric carbon dioxide changes (r=0.21). The Caspian Sea water level has increased by ca. +36cm per decade (r=0.82) between the years 1951-2006. Mean results from all modeled scenarios indicate that the temperature will increase by ca. 3.64°C and precipitation will decrease by ca. 10% (182 mm) over the Caspian Sea, whilst in the Volga river basin, temperatures are projected to increase by ca. 4.78°C and precipitation increase by ca. 12% (58 mm) by the year 2100. Finally, statistical modeling of the Caspian Sea water levels project future water level increases of between 86 cm and 163 cm by the years 2075 and 2100, respectively.

Studying wind chill index as a climatic index effective on the health of athletes and tourists interested in winter sports.

PURPOSE: Estimating wind chill index as one of the indexes effective in body comfort, specifically for athletes and tourists interested in winter sports. METHODS: Meteorology data including temperature and the percentage of relative humidity of 6 synoptic stations of Chaharmahal-Bakhtiyrai province, Iran from 1990 to 2007 were extracted from Iranian Meteorology Site. In order to calculate the values of wind chill, the innovative formula of NOAA Meteorology Services Center [T (WC)= 35.74+0.6215T-35.75V+0.4275TV] was used. RESULTS: After analyzing wind in all stations, it became evident that the great percentage of wind calm related to fall, and spring had the most wind distortions. In studying the mean temperature during this studying period, Koohrang station with mean of 9.8°C was identified as the coldest station and Lordegan with a mean of 17°C represented the warmest station of the region observed. According to degrees derived from wind chill index, Koohrang station in January with a mean of -28.75 was known as the coldest and roughest station. CONCLUSION: Among the studied stations, Koohrang had the most intensive degrees of wind chill occurrence and Lordegan had the calmest conditions. Therefore, athletes and tourists should use warmer clothes and covers in cold seasons in Koohrang in comparison with other studied regions, in order to protect themselves from the negative effects of sudden cold and occurrence of intense wind chills.