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Abstract In this study, we aim to compare the climatic conditions of Surface Urban Heat Island (SUHI) in Tehran and its suburbs using day/night time data from three satellites. A high-resolution Land Surface Temperature (LST) data from MODIS Aqua, Sentinel-3, and Landsat 8 were selected to facilitate this study. The highest values of LST/UHI are observed in downtown Tehran and suburban areas at night. The temperature difference also shows an increase at night in Tehran and the western suburbs, while it decreases during the day. When comparing LST/UHI with altitude in different directions, it is found that urban areas and the south, southeast, southwest, and west suburban areas experience higher temperatures at night. MODIS LST products are more appropriate for checking nighttime SUHI in Tehran's Great area in comparison to other products. Moran's I indicates that the highest positive values occur during seasonal and annual periods at night. The Getis index demonstrates a consistent pattern across all seasons, and this trend persists throughout the year. The seasonal and annual UHI difference between Tehran and its suburbs is 5 °C. The LST diagram reveals that higher temperatures occur during warm months. The temporal NDVI distribution indicates lower NDVI values from June to February and summer to winter. The spatial distribution shows that due to the lack of NDVI index in urban areas, LST/UHI values are higher at night in Tehran compared to the suburbs. UHI is not limited to urban areas but has also spread beyond the city borders. As a result, the highest UHI values are found in downtown Tehran and its southeast, south, southwest, and west suburbs.

In recent decades, severe climate change, decreased precipitation, temperature rise, and increased evapotranspiration (ET) have significantly reduced waterbodies. Furthermore, governments have prioritized the study of water level fluctuations of lakes to protect them from degradation nationally and regionally. The present study investigated the physical changes in lakes Bakhtegan and Tashk due to climatic parameters. To this end, Landsat satellite imagery and the NDWI were employed to calculate the area of the waterbodies from 1986 to 2018. The results showed that the area had decreased during the study period-- since 2009, Lake Bakhtegan had dried up completely. In 2008 and 2010, the lowest precipitation was 127.82 and 107.7 mm, respectively. During the study period (1986 to 2018), the average temperature was 19.44 °C, with an increase of 0.6 °C. Among the climatic parameters, precipitation, with a correlation coefficient of 0.55, and potential evapotranspiration (PET), with a correlation coefficient of about −0.68, were more strongly correlated with changes in the area of the waterbodies. To predict temperature and precipitation in the study area in the coming decades (2020–2050), the HadCM2 model of the CORDEX Project -WAS (South Asia) was used under two scenarios: RCP4.5 and RCP8.5. These scenarios revealed the decrease in precipitation and increase in temperature trends. As a result, the waterbodies’ areas were estimated using the projected precipitation and PET for the period 2050–2020, indicating a decrease in the areas of the waterbodies.

Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0–7 (0.9 °C). An IQR increase in inter-day TV0–7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0–7 and inter-day TV0–7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

Assessing the association between temperature frequency and mortality can provide insights into human adaptation to local ambient temperatures. We collected daily time-series data on mortality and temperature from 757 locations in 47 countries/regions during 1979–2020. We used a two-stage time series design to assess the association between temperature frequency and all-cause mortality. The results were pooled at the national, regional, and global levels. We observed a consistent decrease in the risk of mortality as the normalized frequency of temperature increases across the globe. The average increase in mortality risk comparing the 10th to 100th percentile of normalized frequency was 13.03% (95% CI: 12.17–13.91), with substantial regional differences (from 4.56% in Australia and New Zealand to 33.06% in South Europe). The highest increase in mortality was observed for high-income countries (13.58%, 95% CI: 12.56–14.61), followed by lower-middle-income countries (12.34%, 95% CI: 9.27–15.51). This study observed a declining risk of mortality associated with higher temperature frequency. Our findings suggest that populations can adapt to their local climate with frequent exposure, with the adapting ability varying geographically due to differences in climatic and socioeconomic characteristics.

Background: The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent. Objectives: To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries. Methods: We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 μm (PM10), PM ≤ 2.5 μm (PM2.5), nitrogen dioxide (NO2), and ozone (O3) from 620 cities in 36 countries in the period 1995–2020. We restricted the analysis to the six consecutive warmest months in each city. City-specific data were analysed with over-dispersed Poisson regression models, followed by a multilevel random-effects meta-analysis. The joint association between air temperature and air pollutants was modelled with product terms between non-linear functions for air temperature and linear functions for air pollutants. Results: We analyzed 22,630,598 deaths. An increase in mean temperature from the 75th to the 99th percentile of city-specific distributions was associated with an average 8.9 % (95 % confidence interval: 7.1 %, 10.7 %) mortality increment, ranging between 5.3 % (3.8 %, 6.9 %) and 12.8 % (8.7 %, 17.0 %), when daily PM10 was equal to 10 or 90 μg/m3, respectively. Corresponding estimates when daily O3 concentrations were 40 or 160 μg/m3 were 2.9 % (1.1 %, 4.7 %) and 12.5 % (6.9 %, 18.5 %), respectively. Similarly, a 10 μg/m3 increment in PM10 was associated with a 0.54 % (0.10 %, 0.98 %) and 1.21 % (0.69 %, 1.72 %) increase in mortality when daily air temperature was set to the 1st and 99th city-specific percentiles, respectively. Corresponding mortality estimate for O3 across these temperature percentiles were 0.00 % (-0.44 %, 0.44 %) and 0.53 % (0.38 %, 0.68 %). Similar effect modification results, although slightly weaker, were found for PM2.5 and NO2. Conclusions: Suggestive evidence of effect modification between air temperature and air pollutants on mortality during the warm period was found in a global dataset of 620 cities.

Summary: Background: Identifying how greenspace impacts the temperature-mortality relationship in urban environments is crucial, especially given climate change and rapid urbanization. However, the effect modification of greenspace on heat-related mortality has been typically focused on a localized area or single country. This study examined the heat-mortality relationship among different greenspace levels in a global setting. Methods: We collected daily ambient temperature and mortality data for 452 locations in 24 countries and used Enhanced Vegetation Index (EVI) as the greenspace measurement. We used distributed lag non-linear model to estimate the heat-mortality relationship in each city and the estimates were pooled adjusting for city-specific average temperature, city-specific temperature range, city-specific population density, and gross domestic product (GDP). The effect modification of greenspace was evaluated by comparing the heat-related mortality risk for different greenspace groups (low, medium, and high), which were divided into terciles among 452 locations. Findings: Cities with high greenspace value had the lowest heat-mortality relative risk of 1·19 (95% CI: 1·13, 1·25), while the heat-related relative risk was 1·46 (95% CI: 1·31, 1·62) for cities with low greenspace when comparing the 99th temperature and the minimum mortality temperature. A 20% increase of greenspace is associated with a 9·02% (95% CI: 8·88, 9·16) decrease in the heat-related attributable fraction, and if this association is causal (which is not within the scope of this study to assess), such a reduction could save approximately 933 excess deaths per year in 24 countries. Interpretation: Our findings can inform communities on the potential health benefits of greenspaces in the urban environment and mitigation measures regarding the impacts of climate change. Funding: This publication was developed under Assistance Agreement No. RD83587101 awarded by the U.S. Environmental Protection Agency to Yale University. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. Research reported in this publication was also supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD012769. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also, this work has been supported by the National Research Foundation of Korea (2021R1A6A3A03038675), Medical Research Council-UK (MR/V034162/1 and MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), Academy of Finland (Grant ID: 310372), European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655 and 874990), Czech Science Foundation (22-24920S), Emory University's NIEHS-funded HERCULES Center (Grant ID: P30ES019776), and Grant CEX2018-000794-S funded by MCIN/AEI/ 10.13039/501100011033 The funders had no role in the design, data collection, analysis, interpretation of results, manuscript writing, or decision to publication.

Introduction:Hyperthyrotropinemia (HT) can be transient or permanent. There is no specific protocol in confirmatory tests to discriminate between transient and permanent forms. The aim of this study was to investigate the prevalence of transient HT and the factors that help to discriminate transient from permanent HT. Methods:This was an observational prospective study in all neonates diagnosed with HT referred to the pediatric clinic of Boali Hospital, affiliated to Islamic Azad University Tehran Faculty of Medicine, Tehran, Iran during September 2017 and January 2019. The recovery rate was investigated during a three-month follow-up while withholding medical treatment. Data were analyzed with SPSS Version 22.0. Results: Totally, 80 neonates (65% girls) were enrolled in this study. Among them, 62 participants (77.5%) recovered without any treatment during the three months of follow-up. The recovery rate was significantly higher in term newborns (p < 0.01). The mean weight of recovered neonates (2767.7 ± 440.2 gr) was significantly higher than that of the neonates who did not recover (2141.7 ± 755.2) (p < 0.01). The mean level of thyroid-stimulating hormone (TSH) of the recovered neonates (9.4 ± 3.0 mIU/L) was significantly lower than in the neonates who did not recover (22 ± 6.5 mIU/L) (p < 0.01). Conclusion: The outcome of HT became mostly permanent in patients with a higher level of TSH. The prematurity and low birth weight were the influential factors on TSH level, which could indirectly increase the risk of HT permanence.

Summary: Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2–4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7–5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3–10·4), followed by Europe (4·4%, 2·2–5·6) and Africa (3·3, 1·9–4·6). Interpretation: Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability. Funding: Australian Research Council, Australian National Health & Medical Research Council.

Summary: Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council.

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Future projection of drought vulnerability is vital for northern provinces of Iran, including North Khorasan, Khorasan-Razavi, and South Khorasan, due to the highly dependent of their economy on agriculture. The study is motivated by the fact that no research has been conducted to project the future Drought Vulnerability Index (DVI). DVI consist of three components of exposure, sensitivity, and adaptation capacity. More exposure levels of drought, higher sensitivity value, and lower adaptation capacity lead to a higher amount of vulnerability. Combined ERA-Interim-observation meteorological data, CMIP5 models under RCP4.5 and RCP8.5 scenarios, and national census data are used to estimate DVI in the past and future periods. CanESM2, GFDL-ESM2M, and CNRM-CM5 General Circulation Model (GCM) are selected from CMIP5 based on Taylor diagram results. The delta-change technique was selected for statistical downscaling of GCM outputs because it is most widely used. The study period is regarded as 1986–2005 as observation and four future 20-years periods during 2021–2100. Results indicated that the dissipation of the class of “very low” vulnerability is eminent in the near future period of 2021–2040 under the RCP4.5 scenario, and all provinces would experience a new worse class of “very high” vulnerability at 2081–2100, both under RCP4.5 and RCP8.5 scenarios.

One of the uses of climate in the environmental planning is recognizing the bioclimatic potentials of different regions. In this research, bioclimatic condition inIslam Abade-Gharb City analyzed based on monthly scale climatic data and bioclimatic indices, Beaker, Terjung, Stress, Chilling and Olgay. The cooling and heating requirements in Islam Abade-Gharb city specified by using of daily temperature data and active growth degree days (GDD) method in different thermal thresholds. The results show that, the months of April, May, October and November have comfort bioclimatic and December, January February and March months due to chill stress and June, July, August and September due to heat stress are out of comfort zone. The results of Terjung, Olgay and Chilling indices are more consistent with the climate conditions of the region. Based on the threshold of 10 °C, the thermal potential of the study area from mid-June to end of September reaches to the highest level, In this time period, human bioclimatic is out of the comfort zone and cooling requirements are necessary for adjust of temperature. With respect to the location of this city in semi-cold climate, and the necessity of 207 cooling degree days and 2273 heating degree days, the needs for planning of climate design in order to reduction of energy consumption is necessary.The highest deviation from the optimal thermal conditions occurs from November to December, which necessitate the use of heating to adjust the temperature.The results of this study are important in terms of optimization of energy consumption and the management of heating and cooling systems in residential areas.

Climate classification and identifying the most effective factors and elements of each area is one way of understanding identity of the climate zones. Therefore, to identify Guilan climate mapping new methods such as factor analysis and hierarchical cluster were performed. For this, we used 20 climate variables of the 16weather stations in the study area. Then, using interpolation method, a matrix with dimensions of 20×106 data was obtained. Climate mapping of the province with factor analysis showed that the climate of the province is made up of two factors. These two factors are: humid-rain–wind and temperature–cloudy factors. Results also indicated that these two factors explain 99.44 percent of the variance of the primary variables. The contribution of each factor was 64.49, 34.95 percent respectively. Finally, cluster analysis on two climatic factors identified three climatic regions in the provinces. These three regions are: moderate and humid, mountainous, semi humid and cold.

مقدمه: ناخنك یکی از بیماری‌های شایع چشمی است که از عناصر اقلیمی تأثیر می‌پذیرد. هدف از انجام این پژوهش، بررسی میزان تأثیر عناصر آب ‌و‌هوایی بر بیماری ناخنک چشم در شهرهای مشهد و زاهدان در نیمه‌ی شرقی ایران است. روش‌ها: از آمار مراجعین به کلینیک‌های چشم‌پزشکی الزهرا (س) زاهدان با تعداد 130464 بیمار و تعداد 28776 بیمار مبتلا به ناخنک چشم و خاتم‌الانبیا (ص) مشهد با تعداد 974542 بیمار و تعداد 20222 بیمار مبتلا به ناخنک چشم از طریق نمونه‌گیری مبتنی بر هدف در بازه‌ی زمانی (1390-1385) استفاده شد. با توجه به هدف مطالعه، بیماران به طور تصادفی از تمام شغل‌ها انتخاب شدند. داده‌های مربوط به عناصر اقلیمی شامل ساعات آفتابی، روزهای گرد ‌و ‌غباری، سرعت باد، تابش ‌کل، حداکثر و حداقل دما و رطوبت برای دو ایستگاه هواشناسی زاهدان و مشهد از سازمان هواشناسی کشور اخذ گردید. جهت بررسی و مقایسه‌ی ارتباطات از مدل‌ همبستگی، برای تأخیرهای زمانی از توابع خودهمبستگی، بررسی تفاوت‌های فصلی شیوع بیماری ناخنک از آزمون ANOVA و برای مقایسه‌ی شیوع بیماری در بین مراجعین چشمی در دو شهر از آزمون Student-t استفاده شد. یافته‌ها: در شهر زاهدان روزهای گرد‌ و ‌غباری، ساعات آفتابی، سرعت باد، شاخص ماورای بنفش و تابش به ترتیب بیشترین تأثیر را بر بیماری ناخنک نشان می‌دهند. در شهر مشهد سرعت باد، روزهای گرد‌ و ‌غباری و شاخص ماورای ‌بنفش در اولویت تأثیرگذاری قرار دارند. مدل ANOVA تفاوت معنی‌داری از حیث شیوع بیماری در فصول مختلف نشان نمی‌دهد. همچنین نتایج آزمون Student-t نشان داد که شیوع بیماری در بین مراجعین بیماران چشمی در شهر زاهدان بیشتر از مشهد می‌باشد. اعمال تأخیرهای زمانی نیز حاکی از وجود یک تأخیر زمانی فصلی در تأثیرپذیری بیماری ناخنک از عناصر آب و هوایی است. نتیجه‌گیری: به طور کلی می‌توان نتیجه گرفت که بروز بیماری ناخنک در زاهدان بیشتر از مشهد می‌باشد و عناصر آب و هوایی در زاهدان نقش پر رنگ‌تری در بروز و تشدید این بیماری دارند.