厦门空气污染指数与地面气象要素的关系分析

利用相关统计法分析2006—2008年厦门市地面气象要素对空气污染指数变化的影响规律。结果表明：风速、气温、降水、相对湿度和水汽压对空气污染指数有显著负效应作用,气压起显著正效应作用;风向影响较为复杂, NNW-N-E-ESE风起正效应作用, SE-S-W风起负效应作用,厦门风向总体不利于空气质量提高,全年仅夏季盛行SE-S-W风。API指数与风向、气温、降水、气压、相对湿度和水汽压的季节变化规律有高相关性。API指数与气象要素中的水汽压关系最相关,其次是气压。     

Influence of the atmospheric conditions on PM<Subscript>10</Subscript> concentrations in Poznań, Poland

This study investigates atmospheric conditions’ influence on the mean and extreme characteristics of PM₁₀ concentrations in Poznań during the period 2006–2013. A correlation analysis was carried out to identify the most important meteorological variables influencing the seasonal dynamics of PM₁₀ concentrations. The highest absolute correlation values were obtained for planetary boundary layer height (r = ?0.57), thermal (daily minimum air temperature: r = ?0.51), anemological (average daily wind speed: r = ?0.37), and pluvial (precipitation occurrence: r = ?0.36) conditions, however the highest correlations were observed for temporal autocorrelations (1 day lag: r = 0.70). As regulated by law, extreme events were identified on the basis of daily threshold value i.e. 50 μg m^?3. On average, annually there are approximately 71.3 days anywhere in the city when the threshold value is exceeded, 46.6 % of those occur in winter. Additionally, 83.7 % of these cases have been found to be continuous episodes of a few days, with the longest one persisting for 22 days. The analysis of the macro-scale circulation patterns led to the identification of an easy-to-perceive seasonal relations between atmospheric fields that favour the occurrence of high PM₁₀ concentration, as well as synoptic situations contributing to the rapid air quality improvement. The highest PM₁₀ concentrations are a clear reaction to a decrease in air temperature by over 3 °C, with simultaneous lowering of PBL height, mean wind speed (by around 1 m s^?1) and changing dominant wind directions from western to eastern sectors. In most cases, such a situation is related to the expansion of a high pressure system over eastern Europe and weakening of the Icelandic Low. Usually, air quality conditions improve along with an intensification of westerlies associated with the occurrence of low pressure systems over western and central Europe. Opposite relations are distinguishable in summer, when air quality deterioration is related to the inflow of tropical air masses originating over the Sahara desert.     

Precipitation–altitude relationships on different timescales and at different precipitation magnitudes in the Qilian Mountains

It is generally accepted that altitude is the main variable governing the spatial distribution of precipitation in the mountains. This study mainly discusses the precipitation–altitude relationships on different timescales and at different individual precipitation magnitudes in the entire study period (April 2012 to September 2015), wet season (May to September), and dry season (October to April), and tries to find a threshold to determine whether the correlation between precipitation and altitude is significant. In this study, the half-hourly data, including precipitation, wind speed, and air temperature, from April 2012 to September 2015 are obtained by six automatic meteorological stations located on the north slope of Qilian Mountains, which range from 2980 to 4484 m a.s.l., and horizontal distance is approximately 7000 m. Results indicate that (i) if all samples in the entire study period are to be investigated, the individual precipitation had to reach about 30 or 40 mm, then the sample may pass the significance test at p < 0.05 or at p < 0.01, respectively. The thresholds in wet season are same as that during entire study period. The thresholds in dry season are about 10 and 15 mm (ii) with increasing timescale, the percentage of samples that pass the test increases. However, it is until the monthly scale whether it is wet or dry season or the entire study period, the precipitation–altitude relationships have statistical significance and using the monthly or yearly scale as the time unit can be better applied to the research, which is based on the precipitation–altitude relationships.     

Multiscale evolution of surface air temperature in the arid region of Northwest China and its linkages to ocean oscillations

Reference crop evapotranspiration (ETo) is one of the most important links in hydrologic circulation and greatly affects regional agricultural production and water resource management. Its variation has drawn more and more attention in the context of global warming. We used the Penman-Monteith method of the Food and Agriculture Organization, based on meteorological factors such as air temperature, sunshine duration, wind speed, and relative humidity to calculate the ETo over 46 meteorological stations located in the Yangtze River Delta, eastern China, from 1957 to 2014. The spatial distributions and temporal trends in ETo were analyzed based on the modified Mann-Kendall trend test and linear regression method, while ArcGIS software was employed to produce the distribution maps. The multiple stepwise regression method was applied in the analysis of the meteorological variable time series to identify the causes of any observed trends in ETo. The results indicated that annual ETo showed an obvious spatial pattern of higher values in the north than in the south. Annual increasing trends were found at 34 meteorological stations (73.91 % of the total), which were mainly located in the southeast. Among them, 12 (26.09 % of the total) stations showed significant trends. We saw a dominance of increasing trends in the monthly ETo except for January, February, and August. The high value zone of monthly ETo appeared in the northwest from February to June, mid-south area from July to August, and southeast coastal area from September to January. The research period was divided into two stages—stage I (1957–1989) and stage II (1990–2014)—to investigate the long-term temporal ETo variation. In stage I, almost 85 % of the total stations experienced decreasing trends, while more than half of the meteorological stations showed significant increasing trends in annual ETo during stage II except in February and September. Relative humidity, wind speed, and sunshine duration were identified as the most dominant meteorological variables influencing annual ETo changes. The results are expected to assist water resource managers and policy makers in making better planning decisions in the research region.     

Relative importance of parameters affecting wind speed prediction using artificial neural networks

In traditional artificial neural networks (ANN) models, the relative importance of the individual meteorological input variables is often overlooked. A case study is presented in this paper to model monthly wind speed values using meteorological data (air pressure, air temperature, relative humidity, and precipitation), where the study also includes an estimate of the relative importance of these variables. Recorded monthly mean data are available at a gauging site in Tabriz, Azerbaijan, Iran, for the period from 2000 to 2005, gauged in the city at the outskirt of alluvial funneling mountains with an established microclimatic conditions and a diurnal wind regime. This provides a sufficiently severe test for the ANN model with a good predictive capability of 1 year of lead time but without any direct approach to refer the predicted results to local microclimatic conditions. A method is used in this paper to calculate the relative importance of each meteorological input parameters affecting wind speed, showing that air pressure and precipitation are the most and least influential parameters with approximate values of 40 and 10 %, respectively. This gained knowledge corresponds to the local knowledge of the microclimatic and geomorphologic conditions surrounding Tabriz.     

Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

Soil temperature (T _s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T _s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T _s. For this aim, the monthly mean data of the T _s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T _min, T _max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R _s, R _n, R _a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u ₂); and water vapor pressure (V_p) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R ²) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T _max, T _min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R ² = 0.995) and for RH, V _p, P, and u ₂ inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R ² = 0.996), respectively.     

Modeling monthly meteorological and agronomic frost days,based on minimum air temperature,in Center-Southern Brazil

Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F _MET) and agronomic (F _AGR) frost day models, based on minimum shelter air temperature (T _MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T _MN, once the frost day models were based on this variable. All T _MN regression models were statistically significant (p < 0.001), presenting adjusted R ² between 0.69 and 0.90. Center-Southern Brazil is mainly hit by frosts from mid-fall (April) to mid-spring (October). The period from November to March is considered as frost-free, being very rare a frost day within that period. Monthly F _MET and F _AGR presented significant sigmoidal relationships with T _MN (p < 0.0001), with adjusted R ² above of 0.82. The residuals of the frost day models were random, which means that the sigmoidal models performed quite well for interpreting the frost day variability throughout the study area. The highlands of Santa Catarina, Rio Grande do Sul, São Paulo, and Minas Gerais had in average more than 25 and 13 frosts per year, respectively, for F _MET and F _AGR. The F _MET and F _AGR maps developed in this study for Center-Southern Brazil is a useful tool for farmers, foresters, and researchers, since they contribute to reduce frost spatial and temporal uncertainty, helping in planning project for strategic purposes. Furthermore, the monthly F _MET and F _AGR maps for this Brazilian region are the first zoning of these variables for the country.     

Statistical modelling of the main features of the <Emphasis Type="Italic">Artemisia</Emphasis> pollen season in Wrocław,Poland, during the 2002–2011 time period

The aim of this article is to present statistical forecasting models concerning the dynamics of Artemisia pollen seasons in Wroc?aw, including the start and end, the date of maximum pollen concentration and seasonal pollen index (SPI). For statistical evaluation, use was made of aerobiological and meteorological data from the last 10 years (2002–2011). Based on this data, agroclimatic indicators, i.e. crop heat units (CHUs), were determined for various averaging periods. The beginning of the Artemisia pollen season in the studied time period, on average, took place on 23 June. Its length usually varied between 26 and 45 days, and maximum daily concentrations occurred between 31 July and 18 August. It was found that the beginning of the pollen season depends, above all, on the values of CHUs and photothermal unit (PTU) (p?<?0.05) in the period from March to June, for various thermal thresholds. The date of maximum daily concentration correlates with sunshine duration, PTU and air temperature for June and July (p?<?0.05). On the other hand, SPI is connected with thermal variables, i.e. average, maximum and minimum air temperatures and CHUs and heliothermal unit (HTU) for July (p?<?0.05) and the beginning of spring. Based on the correlation analysis and the chosen variables, regression models for the beginning date of Artemisia pollen season and SPI were prepared, which were then verified by using leave-one-out cross-validation. A better fit between modelled and actual values was found for the analysis concerning the season start date than for the SPI.     

Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province,China

Assessing the regional impact of climate change on agriculture, hydrology, and forests is vital for sustainable management. Trustworthy projections of climate change are needed to support these assessments. In this paper, 18 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to simulate regional climate change in Zhejiang Province, Southeast China. Simple graphical approaches and three indices are used to evaluate the performance of six key climatic variables during simulations from 1971 to 2000. These variables include maximum and minimum air temperature, precipitation, wind speed, solar radiation, and relative humidity. These variables are of great importance to researchers and decision makers in climate change impact studies and developing adaptation strategies. This study found that most GCMs failed to reproduce the observed spatial patterns, due to insufficient resolution. However, the seasonal variations of the six variables are simulated well by most GCMs. Maximum and minimum air temperatures are simulated well on monthly, seasonal, and yearly scales. Solar radiation is reasonably simulated on monthly, seasonal, and yearly scales. Compared to air temperature and solar radiation, it was found that precipitation, wind speed, and relative humidity can only be simulated well at seasonal and yearly scales. Wind speed was the variable with the poorest simulation results across all GCMs.     

2003广西主要城市空气质量评价及空气污染物浓度与气象条件关系

从南宁、桂林、北海三城市空气质量自动监测站监测到二氧化硫(SO2),二氧化氮(NO2),可吸入颗粒物(PM10)的日均浓度数据计算的空气污染指数API得出:2003年三城市空气质量状况整体为 级"优"或 级"良",达到了国家环境保护总局对城市环境规定的标准,特别是桂林市的空气质量最好。对各种污染物月平均浓度值与地面气象要素关系进行相关分析,发现相关性非常好,其中与气压呈正相关,与气温、水汽压、相对湿度、降雨量、风速、0厘米地温等要素呈反相关。各种污染物日平均浓度值与地面风速相关也非常好。     

Measurements of ozone and its precursor nitrogen dioxide and crop yield losses due to cumulative ozone exposures over 40 ppb (AOT40) in rural coastal southern India

Measurements of ground level ozone (O₃), nitrogen dioxide (NO₂) and meteorological parameters (air temperature, relative humidity and wind speed and direction) has been made for 3 years from March 2007 to February 2010 at Nagercoil (8.2°N, 77.5°E, 23 m above sea level), an equatorial rural coastal site of southern India. The monthly average of daytime maximum of O₃ concentrations ranged from 28 to 50 parts per billion (ppb) with an annual average of 19.8 ppb. Similarly, monthly average of NO₂ concentration ranged from 3.4 ppb to 7.7 ppb with an annual average of 5.3 ppb. The monthly variation of meteorological parameters shows the little changes being a coastal site. The estimated summer crops yield losses by 1.1–15.6 % from present O₃ concentration level associated with AOT40 index 3.1–5 ppm h.     

2001-2012年北京市空气污染指数节气分布及其与气象要素的关系

利用2001年1月1日-2012年12月31日北京市空气污染指数资料和地面气象观测数据,对北京市API的节气变化特征及其与气象因子在节气尺度上的相关关系进行统计分析。结果表明：2001-2012年北京市春季和冬季分别以清明和小雪节气API最高,空气质量最差;立秋节气API最低,空气质量最好。春分至霜降节气空气首要污染物是PM₁₀,SO₂作为首要污染物出现在立冬~大寒和立春~惊蛰节气,小寒达到最大。温度、风速和相对湿度是影响北京空气质量主要气象因子,立春~谷雨主要受气压影响,立冬~大寒受相对湿度和日照时数影响较大,立夏~霜降与平均气温和最低气温显著相关,风速主要影响春秋节气。     

Predictability of the Meteorological Conditions Favourable to Radiative Fog Formation During the 2011 ParisFog Campaign

Radiative fog formation is a complex phenomenon involving local physical and microphysical processes that take place when particular meteorological conditions occur. This study aims at quantifying the ability of a regional numerical weather model to analyze and forecast the conditions favourable to radiative fog formation at an instrumental site in the Paris area. Data from the ParisFog campaign have been used in order to quantify the meteorological conditions favorable to radiative fog formation (pre-fog conditions) by setting threshold values on the key meteorological variables driving this process: 2-m temperature tendency, 10-m wind speed, 2-m relative humidity and net infrared flux. Data from the ParisFog observation periods of November 2011 indicate that use of these thresholds leads to the detection of 87 % of cases in which radiative fog formation was observed. In order to evaluate the ability of a regional weather model to reproduce adequately these conditions, the same thresholds are applied to meteorological model fields in both analysis and forecast mode. It is shown that, with this simple methodology, the model detects 74 % of the meteorological conditions finally leading to observed radiative fog, and 48 % 2 days in advance. Finally, sensitivity tests are conducted in order to evaluate the impact of using larger time or space windows on the forecasting skills.     

岳阳城区空气污染的变化特征及气象影响因素

根据2003年12月至2013年12月空气污染资料, 对岳阳城区空气污染的变化特征及气象影响因素进行了分析,探讨了2013年岳阳城区出现的典型空气污染过程的天气实况、大尺度环流背景及成因。结果表明：近10年来,岳阳城区API指数呈显著下降趋势。冬季空气污染最严重且年际变化较大,而夏季空气污染相对较轻且年际变化较小。1—12月API指数基本呈V形变化,且具有冬半年（10月至次年3月）偏高,夏半年（4—9月）偏低的变化规律。工业布局、主导风向、地理条件等导致岳阳城区空气质量具有显著的时空分布。气温日较差大、逆温等大气处于稳定状态下空气污染加重。本地气象和外地输入因素导致2013年岳阳城区出现一次比较典型的空气污染过程。用多元回归方法建立的API指数预报方程表明,气象要素和天气现象对岳阳城区API指数有显著影响。     

Geo-spatial analysis of temporal trends of temperature and its extremes over India using daily gridded (1°×1°) temperature data of 1969–2005

Daily gridded (1°×1°) temperature data (1969–2005) were used to detect spatial patterns of temporal trends of maximum and minimum temperature (monthly and seasonal), growing degree days (GDDs) over the crop-growing season (kharif, rabi, and zaid) and annual frequencies of temperature extremes over India. The direction and magnitude of trends, at each grid level, were estimated using the Mann–Kendall statistics (α = 0.05) and further assessed at the homogeneous temperature regions using a field significance test (α=0.05). General warming trends were observed over India with considerable variations in direction and magnitude over space and time. The spatial extent and the magnitude of the increasing trends of minimum temperature (0.02–0.04 °C year^?1) were found to be higher than that of maximum temperature (0.01–0.02 °C year^?1) during winter and pre-monsoon seasons. Significant negative trends of minimum temperature were found over eastern India during the monsoon months. Such trends were also observed for the maximum temperature over northern and eastern parts, particularly in the winter month of January. The general warming patterns also changed the thermal environment of the crop-growing season causing significant increase in GDDs during kharif and rabi seasons across India. The warming climate has also caused significant increase in occurrences of hot extremes such as hot days and hot nights, and significant decrease in cold extremes such as cold days and cold nights.     

An investigation of near surface wind speed trends in arid and semiarid regions of Iran

Wind plays an important role on the ecosystems and hydrological cycles besides other meteorological parameters such as temperature, precipitation, sunshine, and relative humidity. It strongly affects evapotranspiration, especially in arid and semiarid regions where there are serious problems in regard to water resource management. Evaluating the wind speed trend can provide good information for future agricultural planning. This study was conducted in order to investigate the wind speed trends over 24 synoptic meteorological stations located in arid and semiarid regions of Iran from 1975 to 2005. Near-surface wind speed was trended by nonparametric Mann–Kendall test spatially and temporally in three time scales (annual, seasonal, and monthly). Then, Sen’s slope estimator was used to determine the amount of the changes; furthermore, 10-year moving average low-pass filter was applied to show general trends. Finally, the smoothed time series derived from the mentioned filter were classified in three clusters for each time series and then mapped to show their spatial distribution pattern. Results showed insignificant and significant, increasing and decreasing trends during the surveyed time. Wind speeds in less than 50 % of stations changed statistically in all time scales, and in most cases, the frequency of the upward trends was more than that of downward ones. The spatial distribution of significant wind speed showed that the increase mostly occurred in eastern part. Clustering gave us the turning point around 1990. Clearly, when clusters were mapped, they indicated the same pattern as the Z value maps derived from Mann–Kendall test which meant that the outputs of the mentioned method confirmed the other one. As the wind speed trends in different stations likely to follow the previous evapotranspiration (ET₀) trend results in Iran, it confirms that wind speed was an effective parameter on ET₀, even though other parameters should be considered too.     

Wind-Speed Undulations Over Swell: Field Experiment and Interpretation

Results of field measurements of the swell-induced undulation of the wind speed taken from a Black Sea platform are presented. The wind speed and its fluctuations were measured at several heights between 1.3 and 21 m above the mean sea level under various wind and swell conditions. Parameters of the swell-induced undulations were derived from cross spectra of the wind-speed fluctuations and the sea-surface displacement. As found, the phase and the amplitude of the wind speed undulation in the layer from k _p z = 0.1 to k _p z = 3 (k _p is the swell wavenumber) are in good agreement with the theory of inviscid shear flow over a wavy surface. The main feature of the vertical profile of the swell-induced undulation is the exponential attenuation of its amplitude with height typical for the potential flow over the fast running waves. At the lowest levels the potential undulations are significantly distorted by the wind-speed variations caused by the vertical displacements of the shear airflow relative to a fixed sensor. No direct impact of swell on the mean properties of the turbulent boundary layer at k _p z > 0.1 is revealed. In particular, the mean wind-speed profile and spectra of the horizontal velocity in the inertial subrange obey Monin-Obukhov similarity theory.     

Compilation method for 1 km grid data of monthly mean air temperature for quantitative assessments of climate change impacts

A new method is proposed to compile 1 km grid data of monthly mean air temperature by dynamically downscaling general circulation model (GCM) data with a regional climate model (RCM). The downscaling method used is a technique referred to as the pseudoglobal warming method to reduce GCM bias. For the grid data, RCM data were corrected with data from an existing meteorological network. The correction model for the RCM bias was developed by stepwise multiple regression analysis using the difference in the monthly mean air temperatures between the observation and RCM output as a dependent variable and the geographical factors as independent variables. Our method corrected the RCM bias from 1.69°C to 0.58°C for the month of August in the 1990s (1990–1999).     

Changes in daily and monthly rainfall in the Middle Yellow River,China

Highly concentrated precipitation, where a large percentage of annual precipitation occurs over a few days, may include a high risk of flooding and severe soil erosion. Thus, areas with severe erosion such as the Loess Plateau in China are particularly vulnerable to highly concentrated precipitation events due to climate change. In this study, we investigated spatial and temporal patterns in the concentration of rainfall in the Middle Yellow River (MYR) from the last 56 years (1958–2013). We used daily and monthly precipitation data from 26 meteorological stations in the study area to calculate the precipitation concentration index (PCI) and the concentration index (CI). The southern and northern parts of the MYR were characterized by a lower CI with a decreasing trend, while the middle parts had a higher CI with an increasing trend. High PCI values occurred in the southern MYR, while lower PCIs with a more homogenous rainfall distribution were found mainly in the northern parts of the MYR. The annual PCI and CI exhibited positive trends at most stations, although only a minority of stations had significant trends (P < 0.05). At seasonal scales, CI exhibited significantly increasing trends in winter at most stations, while a few stations had significant trends in the other three seasons. These findings provide important reference information to facilitate ecological restoration and farming operations in the study region.     

Human thermal perception related to Föhn winds due to Saharan dust outbreaks in Crete Island,Greece

Crete Island is located in the southmost border of East Mediterranean basin, facing exacerbating atmospheric conditions (mainly concentrations of particulates) due to Saharan dust outbreaks. It is worth to note that these episodes are more frequent during spring and autumn, when mild biometeorological conditions become intolerable due to the synergy of the so called Föhn winds. Cretan mountains, especially Psiloritis Mt. (summit at 2456 m), are orientated perpendicularly to the southwest air mass flow, generating the Föhn winds. Propagating from the leeward of the mountains, these dry, hot winds have an effect on prevailing biometeorological conditions. While descending to the lowlands on the leeward side of the range, the wind becomes strong, gusty, and desiccating. This wind often lasts less than an hour to several days, with gradual weakening after the first or the second day. Sometimes, it stops very abruptly. In this work, the authors examined and analyzed the abrupt changes of human thermal perception within specific case studies during which Föhn winds appeared in Heraklion city at the leeward of Psiloritis Mt, associated with extreme Saharan dust episodes, observed within the period 2006–2010. In order to verify the development of Föhn winds, Meteorological Terminal Aviation Routine Weather Reports (METARs, meteorological observations every half hour), were acquired from the Heraklion meteorological station installed by the Hellenic National Meteorological Service (HNMS). The biometeorological conditions analyzed are based on human thermal bioclimatic indices such as the Physiologically equivalent temperature (PET) and the Universal Thermal Climate Index (UTCI). METAR recordings of meteorological variables, such as air temperature, vapor pressure, wind speed, and cloudiness, were used as input variables in modeling the aforementioned thermal indices, so that to interpret the grade of the thermo-physiological stress. The PET and UTCI analysis was performed by the use of the radiation and bioclimate model, “RayMan,” which is well-suited to calculate radiation fluxes and human biometeorological indices. The results of the performed analysis showed even an increase of air temperature from 20 to 30 °C within 5 h, associated with a decrease in the vapor pressure from 11.5 to 9.3 hPa. In addition, the wind speed at 10 m increased from 5.1 to 20.1 m/s, 3.7 to 14.3 m/s with respect to 1.1 m height, during the events of Föhn winds. The biometeorological analysis has given evidence that slight/moderate heat stress classes of the examined thermal indices appear during Saharan dust episodes. Such conditions are uncommon at the beginning of spring season, indicating that Saharan dust episodes are not only responsible for acute health impacts but also for adverse biometeorological conditions, due to the very likely development of Föhn winds towards the wider area of Heraklion, a coastal city in the eastern Mediterranean.