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This study examines the effects of short-term exposure to PM10 and O3 on all-cause, cardiorespiratory, and cerebrovascular mortality in the urban area of Thessaloniki, Greece. An analysis was performed on the vulnerable subgroup (the elderly population). The primary effect estimates employed were the relative risks for every 10 µg/m3 increase in air pollutant concentrations. Strong associations between PM10 and O3 levels on mortality were reported, with the elderly people becoming frailer. An increase of 10 μgr/m3 in PM10 concentration resulted in a 2.3% (95% CI: 0.8–3.8) and 2% (95% CI: 0.1–4.5) increase in total and cardiorespiratory mortality, respectively. O3 concentrations showed even stronger associations for all-cause (3.9%, 95% CI: 2.5–5.3) and cardiorespiratory deaths (5.3%, 95% CI: 3.1–7.7) with 10 μgr/m3 increases; no statistically significant associations were found for cerebrovascular causes, while both pollutants presented stronger impacts on health between day 0 and 3. Concerning the elderly, the total mortality rose by 3.2% (95% CI: 1.5–5) due to PM10 concentrations and by 4.4% (95% CI: 2.9–6) due to O3 concentrations. In total, 242 (170) all-cause deaths were annually attributed to the PM10 (O3) level in Thessaloniki. In the efforts towards achieving a sustainable environment for humanity, health benefits resulting from two air pollution abatement scenarios (a 20% reduction in PM10 levels and full compliance to the European Union PM10 limits) were quantified. The analysis led to a respective decrease in total excess mortality by 0.4% and 1.8%, respectively. This outcome stresses the necessity of appropriate civil protection actions and provides valuable scientific knowledge to national and regional administrations in order to develop proper health and air quality plans.

This study aims to investigate, in microscale, the pollutant emissions due to road traffic under traffic-congested conditions at street level and the impacts on air quality of traffic emissions reduction scenarios by applying an Integrated Modelling Tool (IMT) for a main road axis in Thessaloniki, Greece. ΙΜΤ links a real-world traffic model, a dynamic emissions model and a Lagrangian dispersion model coupled with a boundary layer flow module. Pollutant emissions from cars at edges with traffic lights were + 30% higher than those estimated at other edges while NOx emissions were + 22% higher at the edges with bus stops. A comparison of the IMT and COPERT Street Level emissions results showed that the IMT emissions were higher than the COPERT Street Level emissions for roads with traffic lights or bus stops, characterized by high variability in vehicle speed per second due to stopping and accelerating. This resulted in up to 2 times higher NOx emissions. IMT was applied to assess the impact on the atmospheric environment of the redesign of the road axis promoting sustainable urban transportation. A reduction by − 20% of the cars and motorcycles traffic flows in combination with the increase by a factor of 2 of the frequency in the circulation of city buses replaced with battery electric vehicles will result in lower pollutant and CO2 emissions ranging from − 29 to − 41%. Reductions of about − 65% in the road traffic NOx maximum concentration levels were also estimated.

The ongoing climate change over Central and Southeast Europe has a great potential to affect significantly the public energy demands and in particular the energy consumption in the residential heating and cooling sector. The linkage of the ambient daily extreme and mean temperatures and the energy needs for condition or heat buildings can be quantified as numerical indicators as the heating and cooling degree-days. In the present study, these indicators are calculated according the UK Met Office methodology from the daily mean and extreme temperatures, which, in turn, are computed from the output of the MESCAN-SURFEX system in the frame the FP7 UERRA project. The study, which is performed in a very high resolution, is dedicated on the analysis of the spatial patterns as well as assessment of the magnitude and statistical significance of the temporal evolution of the heating and cooling degree-days. It reveals general tendencies which are coherent with the regional climate warming, but with high spatial heterogeneities. The study confirms the essential impact of the ongoing climate change on the heating, ventilating and air-conditioning industry over Central and Southeast Europe.

In this article, we aim to show the capabilities, benefits, as well as restrictions, of three different air quality-related information sources, namely the Sentinel-5Precursor TROPOspheric Monitoring Instrument (TROPOMI) space-born observations, the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) ground-based measurements and the LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) chemical transport modelling system simulations. The tropospheric NO2 concentrations between 2018 and 2021 are discussed as air quality indicators for the Greek cities of Thessaloniki and Ioannina. Each dataset was analysed in an autonomous manner and, without disregarding their differences, the common air quality picture that they provide is revealed. All three systems report a clear seasonal pattern, with high NO2 levels during winter-time and lower NO2 levels during summer-time, reflecting the importance of photochemistry in the abatement of this air pollutant. The spatial patterns of the NO2 load also showed, in both space-born observations and model simulations, the undeniable variability of the NO2 load within the urban agglomerations. The diurnal variability was furthermore clearly identified by the ground-based measurements, which also unquestionably revealed a Sunday minimum NO2 load effect, alongside the rest of the sources of air quality information. Within their individual strengths and limitations, the space-born observations, the ground-based measurements and the chemical transport modelling simulations, demonstrate unequivocally their ability to report on the air quality situation in urban locations.

The main aim of this study is the identification of the most appropriate measures and policies to combat particulate air pollution in the city of Thessaloniki, Greece through a methodology including the calculation of emissions by sector and the application of an air quality modeling system. The identification of the current air quality situation showed that the exceedances of the mean PM10 daily levels occur during the cold winter months with residential heating being the major contributor representing a 73% share of total PM10 emissions. Moreover, the effect of the biomass consumption for heating purposes on PM10 concentrations has been verified and quantified by implementing a regression model identifying that a PM10 emissions reduction by 45% would result in the elimination of the exceedances of the mean PM10 daily values. Based on the above, a set of cost-effective measures and policies were defined and their impact on PM10 emissions was estimated. Finally, the air quality modeling system was applied for the mitigation scenarios selected, leading to a significant reduction of 67% in the number of exceedances observed and ensuring compliance with the limit of 35 exceedances of the daily value limit per year pursuant to European Legislation.

The Mediterranean is recognized among the most responsive regions to climate change, with annual temperatures projected to increase by 1–5 °C until 2100. Large cities may experience an additional stress discomfort due to the Urban Heat Island (UHI) effect. In the present study, the WRF-ARW numerical weather prediction model was used to investigate the climate change impact on UHI for two Mediterranean cities, Rome and Thessaloniki. For this purpose, three 5-year time-slice simulations were conducted (2006–2010, 2046–2050, 2096–2100) under the Representative Concentration Pathway (RCP) 8.5 emission scenario, with a spatial resolution of 2 km. In order to comprehensively investigate the urban microclimate, we analyze future simulation data across sections crossing urban/non-urban areas, and after grouping them into three classes depending on the location of the grid cells. The urban areas of both cities present increased average minimum temperature (Tmin) in winter/summer compared to other rural areas, with an UHI of ~+1.5–3 °C on average at night/early morning. Considering UHI under future climate change, we found no significant variations (~±0.2 °C). Finally, we found that the numbers of days with Tmin ≥ 20 °C will mostly increase in urban coastal areas until 2100, while the largest increase of minimum Discomfort Index (DImin) is expected in urban low-ground areas.

In this study the exposure levels from Quercus pollen in the greater area of Thessaloniki are estimated. The estimation is implemented with a modeling system, comprising the meteorological model WRF, the Natural Emissions Model (NEMO) for the calculation of the Quercus pollen emissions and the chemistry-transport model CAMx for the advection and the deposition of the pollen particles. The period of 2016 with the highest potential is selected, based on the available measurements for the area of interest. The modeling system is evaluated with meteorological and pollen measurements, as well on the expected exposure levels, indicating a satisfactory overall performance. The modeling system is finally utilized for the estimation of exposure levels in the greater area of Thessaloniki, showing that the city of is not going to experience significant number of days with high Quercus pollen concentrations, although other, smaller cities and towns might be affected.

The current study investigated the impact of the Weather Research and Forecasting (WRF) (a) surface layer (SL), (b) land surface and (c) planetary boundary layer (PBL) physics on the short-term simulation of the meteorological and human thermal comfort conditions during 15 heat waves identified between 2004 and 2013 in the southeast Mediterranean and Balkan Peninsula. Four widely used PBL-SL schemes (YSU-MM5, MYJ-Eta, ACM2-Revised MM5, YSU-Revised MM5) and land surface models (LSMs; Noah, Noah-MP, CLM4, RUC) were tested. Comparisons with ground-based observations in 60 measuring sites showed that the WRF model is characterized by a cold bias leading to the underestimation of the extreme heat stress conditions over the entire study region. The MYJ-Eta experiment simulated greater sensible heat fluxes compared to the other PBL-SL scenarios due to the high surface heat exchange coefficient provided by the Eta SL scheme. This contributed to the high MYJ-Eta-modeled daytime 2-m air temperature (T2) and physiologically equivalent temperature (PET) values that were close to the observations. The ACM2 PBL algorithm produced significantly higher PBL heights compared to rest of the tested PBL parameterizations reflecting the strong vertical mixing generated in this scheme. This contributed to the most accurate ACM2-Revised MM5-modeled T2 and PET results in overall. The use of the RUC LSM strengthened significantly the modeled sensible heat fluxes contributing directly to the satisfactory replication of the observed T2 and PET values. However, the RUC-induced enhanced sensible heating relative to the latent heating is may related to a possible underestimation of the soil moisture, as indicated by the notable dry biases during the RUC experiment. Thus, the most accurate T2 and PET results provided by the RUC model may arise from the wrong reason.

In this study a high resolution modeling system is developed to simulate Quercus pollen concentrations in the greater area of Thessaloniki, Greece, under an a priori oak phenological season. The modeling system consists of three models in series, the Weather Research and Forecasting (WRF) meteorological model, the natural emissions model NEMO for Quercus pollen emissions and the chemistry-transport model CAMx. The modeling system is evaluated with daily meteorological and pollen measurements during the phenological season of 2016 of Quercus taxa. The modeling system's performance is satisfactory on both meteorology and Quercus pollen concentrations, although for the latter the relative uncertainty is slightly above the 50% criterion usually applied in air quality modeling. Additional analysis was performed on three parameters related to pollen emissions, namely the assigned pollen production, the spread of the phenology and the assigned diameter. The analysis shows that the greatest impact on Quercus pollen concentrations, on both near the sources as well at remote areas, is the assigned pollen production, followed by the spread and the assigned diameter.

Middle East Area and especially the central part is a dust dominated domain and therefore estimation of natural dust emissions is critical. Aim of this study is to assess the sensitivity of state-of-the art dust modules, utilized in multiple modelling schemes, and especially of their three main components; namely the horizontal mass flux, the drag partition and the sandblasting efficiency. To accomplish this, several simulations with the Natural Emission MOdel (NEMO), driven by the Weather Research and Forecasting (WRF) model, were made for the period April–June 2015 focusing in the central Middle East (CME). First, the meteorological model was evaluated over the study period, as well as during a Shamal event, showing a satisfactory performance on wind speed which is the most important meteorological variable inserted in the dust modules. Second, dust emissions were found to be a few tenths of μg/m2s on average, while the daily amount exceeds 1000 mg/m2day. Over the studied period, the fluxes range from 15 to 750 g/m2. The total emissions in CME were estimated with the NEMO's basic configuration at 139 Tg. The most active areas are associated with clay content ranging between 17 and 25%, highlighting the importance of soil texture on the definition of the dust sources. During a Shamal event in the second half of June 2015, the mean dust emission fluxes reached up to several hundreds of μg/m2s, contributing 21 Tg in CME. Few such events could cover a large portion of the dust emissions. Finally, concerning the sensitivity of the total emissions, the drag partition scheme has the largest effect, followed by sandblasting efficiency and horizontal mass flux. The total dust emissions budget, among the 16 simulations was found to be in the range of 21–139 Tg, with the choice of the drag partition scheme to be mandatory for the narrowing of the total emissions in CME.

This study presents a comprehensive modeling approach for simulating the spatiotemporal distribution of urban air temperatures with a modeling system that includes the Weather Research and Forecasting (WRF) model and the Single-Layer Urban Canopy Model (SLUCM) with a modified treatment of the impervious surface temperature. The model was applied to simulate a 3-day summer heat wave event over the city of Athens, Greece. The simulation, using default SLUCM parameters, is capable of capturing the observed diurnal variation of urban temperatures and the Urban Heat Island (UHI) in the greater Athens Area (GAA), albeit with systematic biases that are prominent during nighttime hours. These biases are particularly evident over low-intensity residential areas, and they are associated with the surface and urban canopy properties representing the urban environment. A series of sensitivity simulations unravels the importance of the sub-grid urban fraction parameter, surface albedo, and street canyon geometry in the overall causation and development of the UHI effect. The sensitivities are then used to determine optimal values of the street canyon geometry, which reproduces the observed temperatures throughout the simulation domain. The optimal parameters, apart from considerably improving model performance (reductions in mean temperature bias from 0.30 °C to 1.58 °C), are also consistent with actual city building characteristics - which gives confidence that the model set-up is robust, and can be used to study the UHI in the GAA in the anticipated warmer conditions in the future. © 2017 Elsevier B.V.

One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32 × 1015 and 10.21 ± 8.87 × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71 × 1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01 × 1015 molecules cm−2.

This study presents the evaluation of a state-of-the-art numerical weather prediction model, namely the Weather Research and Forecasting (WRF), with respect to the simulation of wind. Numerical simulations were carried out for a 1-year period, focusing on Greece, a study area that constitutes a challenging testbed due to its highly complex terrain. Wind measurements, derived from a network of surface synoptic weather stations, were employed for assessing model performance. The evaluation procedure focused on investigating the ability of the model to reproduce the basic features of the wind field over Greece, as well as on examining its capacity with regards to reproducing the wind resource. Results suggest an overall satisfactory model performance. In particular, the computed model errors were found to be within acceptable ranges, suggesting overestimation of weak and underestimation of strong winds. Seasonal variations of model performance were evident, along with differentiations depending on whether continental or maritime areas were considered. The wind resource of the study area, represented by the Weibull probability density function, was reproduced adequately well in the numerical simulations, while the spatiotemporal variations of the average monthly wind speed were also captured well.

This study aims towards an accurate regional dust modeling system in the central Middle East area (CME), through the implementation of the state-of-art dust parameterizations. The modeling system consists of the natural emission model NEMO, the meteorological model WRF and the chemistry transport model CAMx. An extensive evaluation of 16 different configurations has been realized, incorporating all the combinations of the components utilized in the state-of-art dust modeling approaches, namely the drag partition, the sandblasting efficiency, the horizontal mass flux, as well two commonly used soil particle size distributions. Daily mean PM10 measurements in Doha, as well the satellite AOD products of MODIS have been used for the quantitative and the qualitative assessment of the simulations. Noteworthy, each of these assessments did not yield to the exact same ranking of the configurations (e.g. best five) but they assisted on identifying clear patterns. For example, a consistent overestimation of the daily mean PM10, when the MacKinnon's drag partition scheme is utilized, was found. On the other hand, the assessments led to best three performing configurations, with common components the Raupach's drag partition scheme and Alfaro and Gomes sandblasting efficiency. Although their overall performance is good, several issues were found i.e. on individual dust events and a mean underestimation during the studied period, ranging from −49 to −75 μg/m3. One cause of this underestimation could be the aerodynamic entrainment, a mechanism usually neglected from the dust modeling approaches. Another cause could be missed regional and/or local sources or underestimation of their emission rates.

The main objective of this work is the study of the impact of windblown dust, sea-salt aerosol and biogenic emissions on particle pollution levels in Europe. The Natural Emissions MOdel (NEMO) and the modelling system consisted of the Weather Research and Forecasting model (WRF) and the Comprehensive Air Quality model with extensions (CAMx) were applied in a 30 km horizontal resolution grid, which covered Europe and the adjacent areas for the year 2009. Air quality simulations were performed for different emission scenarios in order to study the contribution of each natural emission source individually and together to air quality levels in Europe. The simulations reveal that the exclusion of windblown dust emissions decreases the mean seasonal PM10 levels by more than 3.3 μg/m 3 (∼20%) in the Eastern Mediterranean during winter while an impact of 3 μg/m 3 was also found during summer. The results suggest that sea-salt aerosol has a significant effect on PM levels and composition. Eliminating sea-salt emissions reduces PM10 seasonal concentrations by around 10 μg/m 3 in Mediterranean Sea during summer while a decrease of up to 6 μg/m 3 is found in Atlantic Ocean during autumn. Sea-salt particles also interact with the anthropogenic component and therefore their absence in the atmosphere decreases significantly the nitrates in aerosols where shipping activities are present. The exclusion of biogenic emissions in the model runs leads to a significant reduction of secondary organic aerosols of more than 90% while an increase in PM2.5 levels in central Europe and Eastern Mediterranean is found due to their interaction with anthropogenic component.

The aim of this study is the application and evaluation of a new computer model used for the quantification of emissions coming from natural sources. The Natural Emissions Model (NEMO) is driven by the meteorological data of the mesoscale numerical Weather Research and Forecasting (WRF) model and it estimates particulate matter (PM) emissions from windblown dust, sea salt aerosols (SSA) and primary biological aerosol particles (PBAPs). It also includes emissions from Biogenic Volatile Organic Compounds (BVOCs) from vegetation; however, this study focuses only on particle emissions. An application and evaluation of NEMO at European scale are presented. NEMO and the modelling system consisted of WRF model and the Comprehensive Air Quality Model with extensions (CAMx) were applied in a 30 km European domain for the year 2009. The computed domain-wide annual PM10 emissions from windblown dust, sea salt and PBAPs were 0.57 Tg, 20 Tg and 0.12 Tg, respectively. PM2.5 represented 6% and 33% of emitted windblown dust and sea salt, respectively. Natural emissions are characterized by high geographical and seasonal variations; windblown dust emissions were the highest during summer in the southern Europe and SSA production was the highest in Atlantic Ocean during the cold season while in Mediterranean Sea the highest SSA emissions were found over the Aegean Sea during summer. Modelled concentrations were compared with surface station measurements and showed that the model captured fairly well the contribution of the natural sources to PM levels over Europe. Dust concentrations correlated better when dust transport events from Sahara desert were absent while the simulation of sea salt episodes led to an improvement of model performance during the cold season.

Measurements of air temperature and humidity in the urban canopy layer during July 2009 in 26 sites in Athens, Greece, allowed for the mapping of the hourly spatiotemporal evolution of the urban heat island (UHI) effect. City districts neighboring to the mountains to the east were the hottest during the afternoon, while being among the coolest during the early morning hours. While during the early morning some coastal sites were the hottest, the warm air plume slowly moved to the densely urbanized center of the city until 14:00–15:00, moving then further west, to the Elefsis industrial area in the afternoon. Results from the UrbClim model agree fairly well with the observations. Satellite-derived land surface temperature (LST) data from AATSR, ASTER, AVHRR and MODIS, for pixels corresponding to ground stations measuring Tair, showed that LST can be up to 5 K lower than the respective Tair during nighttime, while it can be up to 15 K higher during the rest of the day. Generally, LST during late afternoon as acquired from AATSR is very near to Tair for all stations and all days, i.e., the AATSR LST afternoon retrieval can be used as a very good approximation of Tair. The hourly evolution of the spatial Tair distribution was almost the same during days with NE Etesian flow as in days with sea breeze circulation, indicating that the mean wind flow was not the main factor controlling the diurnal UHI evolution, although it influenced the temperatures attained. No unambiguous observation of the urban moisture excess (UME) phenomenon could be made.

Shipping is a growing transport sector representing a relevant share of atmospheric pollutant emissions at global scale. In the Mediterranean Sea, shipping affects air quality of coastal urban areas with potential hazardous effects on both human health and climate. The high number of different approaches for investigating this aspect limits the comparability of results. Furthermore, limited information regarding the inter-annual trends of shipping impacts is available. In this work, an approach integrating emission inventory, numerical modelling (WRF-CAMx modelling system), and experimental measurements at high and low temporal resolution is used to investigate air quality shipping impact in the Adriatic/Ionian area focusing on four port-cities: Brindisi and Venice (Italy), Patras (Greece), and Rijeka (Croatia). Results showed shipping emissions of particulate matter (PM) and NOx comparable to road traffic emissions at all port-cities, with larger contributions to local SO2 emissions. Contributions to PM2.5 ranged between 0.5% (Rijeka) and 7.4% (Brindisi), those to PM10 were between 0.3% (Rijeka) and 5.8% (Brindisi). Contributions to particle number concentration (PNC) showed an impact 2-4 times larger with respect to that on mass concentrations. Shipping impact on gaseous pollutants are larger than those to PM. The contribution to total polycyclic aromatic hydrocarbon (PAHs) concentrations was 82% in Venice and 56% in Brindisi, with a different partition gas-particle because of different meteorological conditions. The inter-annual trends analysis showed the primary contribution to PM concentrations decreasing, due to the implementation of the European legislation on the use of low-sulphur content fuels. This effect was not present on other pollutants like PAHs. (C) 2016 Elsevier Ltd. All rights reserved.

Some extensive numerical simulations of the atmospheric composition fields in Bulgaria and Sofia have been recently performed. The US EPA Model-3 system was chosen as а modeling tool. A very extensive database was created from simulations which was used for different studies of the atmospheric composition, including the Air Quality (AQ) climate.

This paper aims to investigate students’ awareness regarding the factors that affect the environmental quality in university classrooms. For this purpose a questionnaire survey was conducted, in which 314 undergraduate students of the School of Primary Education, Aristotle University of Thessaloniki, participated. The questionnaire was developed for this survey and includes questions related to indoor thermal comfort (ITC) conditions and indoor air quality (IAQ). The analysis revealed that the vast majority of the students were aware that temperature and humidity are the two factors that mainly determine the ITC levels. In general, they are also aware that the ITC levels are affected by classroom’s and individual’s characteristics. The most accepted factors considered by the students to affect the IAQ were smoking (95%) and dust (90%), while the less accepted factors were furniture (17%), wallpapers (21%) and use of printer, photocopier (29%). The results underline the need to improve students’ knowledge about the factors that affect IEQ and that measures can be taken to improve it. &nbsp

This paper studies the characteristics of the heat waves that were observed in Athens, Greece since 1951. A heat wave is detected when two temperature criteria are fulfilled at the city centre: the daily maximum temperature value is at least 37 oC and the daily average temperature value is at least 31 oC. Information about the intensity, duration, timing in season and annual frequency of occurrence of heat waves were extracted. The slope of the linear fit of the annual number of heat wave days indicated that 1.30 more heat wave days per year were observed after 1992. The intensity and the duration of heat waves have also increased since 90s, while heat wave days have been detected during the whole summer since then, even during the first days of September. Additionally, air quality at the centre and at a suburb of Athens during the heat wave days that were identified during the last decade is examined. The daily average value of PM10 concentration exceeded 50 μg m-3 in 65% and 59% of the heat wave days at the urban and the suburban site, respectively, while the information and the alert O3 threshold were exceeded in 17% and 5% of the heat wave days, respectively, at the suburban site. The degradation of air quality during heat wave days is also verified by the means of the common air quality index. Moreover, it was found that O3 levels decrease when heat waves last more than 6 days. &nbsp

The evaluation of thermal bioclimate can be conducted employing either observational or modeling techniques. The advantage of the numerical modeling approach lies in that it can be applied in areas where there is lack of observational data, providing a detailed insight on the prevailing thermal bioclimatic conditions. However, this approach should be exploited carefully since model simulations can be frequently biased. The aim of this paper is to examine the suitability of a mesoscale atmospheric model in terms of evaluating thermal bioclimate. For this, the numerical weather prediction Weather Research and Forecasting (WRF) model and the radiation RayMan model are employed for simulating thermal bioclimatic conditions in Greece during a 1-year time period. The physiologically equivalent temperature (PET) is selected as an index for evaluating thermal bioclimate, while synoptic weather station data are exploited for verifying model performance. The results of the present study shed light on the strengths and weaknesses of the numerical modeling approach. Overall, it is shown that model simulations can provide a useful alternative tool for studying thermal bioclimate. Specifically for Greece, the WRF/RayMan modeling system was found to perform adequately well in reproducing the spatial and temporal variations of PET.

A strong positive correlation between the seasonal changes of the tropopause height and the concentration of 7Be in the surface air (R = 0.94, p

To investigate whether air pollution is a potential risk factor for airways obstruction.A prospective cohort study (11.3 +/- 2.9 years) that took place in two areas (Eordea where concentration of PM10 was high and Grevena, Greece). We used the MRC questionnaire, spirometry, and anterior rhinomanometry at both visits.Initially we examined 3046 subjects. After excluding chronic obstructive pulmonary disease (COPD) patients, we re-examined 872 subjects and 168 of them had developed COPD (Grevena: 24.3%, Eordea: 18.5%). Multivariable logistic regression analysis showed that the area of residence and thus exposure to air pollution was not a risk factor for the development of COPD (OR: 0.51, 95% CI: 0.18-1.46, P = 0.21). On the other hand, residence in Eordea was strongly related to the development of severe nasal obstruction (OR: 11.47, 95% CI: 6.15-21.40, P0.001). Similar results were found after excluding patients with COPD stage I as well as in the subgroup of never smokers.Air pollution was associated with severe nasal obstruction but not with COPD development.

This study presents a methodology for modeling and mapping the seasonal and annual air temperature and precipitation climate normals over Greece using several topographical and geographical parameters. Data series of air temperature and precipitation from 84 weather stations distributed evenly over Greece are used along with a set of topographical and geographical parameters extracted with Geographic Information System methods from a digital elevation model (DEM). Normalized difference vegetation index (NDVI) obtained from MODIS Aqua satellite data is also used as a geographical parameter. First, the relation of the two climate elements to the topographical and geographical parameters was investigated based on the Pearson’s correlation coefficient to identify the parameters that mostly affect the spatial variability of air temperature and precipitation over Greece. Then a backward stepwise multiple regression was applied to add topographical and geographical parameters as independent variables into a regression equation and develop linear estimation models for both climate parameters. These models are subjected to residual correction using different local interpolation methods, in an attempt to refine the estimated values. The validity of these models is checked through cross-validation error statistics against an independent test subset of station data. The topographical and geographical parameters used as independent variables in the multiple regression models are mostly those found to be strongly correlated with both climatic variables. Models perform best for annual and spring temperatures and effectively for winter and autumn temperatures. Summer temperature spatial variability is rather poorly simulated by the multiple regression model. On the contrary, best performance is obtained for summer and autumn precipitation while the multiple regression model is not able to simulate effectively the spatial distribution of spring precipitation. Results revealed also a relatively weaker model performance for precipitation than that for air temperature probably due to the highly variable nature of precipitation compared to the relatively low spatial variability of air temperature field. The correction of the developed regression models using residuals improved though not significantly the interpolation accuracy.

In this study, the Weather Research and Forecasting (WRF) model coupled with the Noah land surface model was tested over the city of Athens, Greece, during two selected days. Model results were compared against observations, revealing a satisfactory performance of the modeling system. According to the numerical simulation, the city of Athens exhibits higher air temperatures than its surroundings during the night (>4 °C), whereas the temperature contrast is less evident in early morning and mid-day hours. The minimum and maximum intensity of the canopy-layer heat island were found to occur in early morning and during the night, respectively. The simulations, in agreement with concurrent observations, showed that the intensity of the canopy-layer heat island has a typical diurnal cycle, characterized by high nighttime values, an abrupt decrease following sunrise, and an increase following sunset. The examination of the spatial patterns of the land surface temperature revealed the existence of a surface urban heat sink during the day. In the nighttime, the city surface temperature was found to be higher than its surroundings. Finally, a simple data assimilation algorithm for satellite-retrieved land surface temperature was evaluated. The ingestion of the land surface temperature data into the model resulted to a small reduction in the temperature bias, generally less than 0.2 °C, which was only evident during the first 4–5 h following the assimilation.

Raingauge data from four meteorological stations in Chalkidiki peninsula (Greece) were used to identify the characteristics of the synoptic circulation patterns associated with cold-season heavy rainfall events and corresponding flooding over the area. Precipitation climatology over the complex topography of Chalkidiki is characterized by limited annual rainfall, but in the occurrence of heavy rainfall episodes daily accumulations are exceptionally high with increased precipitation rates, leading often to severe flooding. Fifty-five cases of high daily accumulations for the period of 1997 to 2010, mostly observed during December and October, were classified into eight clusters by applying S-Mode Factor Analysis and Cluster Analysis to the ERA-Interim grid point reanalysis data. The results revealed that, in most cases, intense rainfall and flooding is produced by synoptic scale disturbances that generate and sustain cyclonic activity over south Italy, the Ionian, and less frequently over the Aegean Sea. In particular, the atmospheric circulation patterns associated with heavy rainfall are characterized by the presence of a southeasterly–easterly low-level humid flow over Chalkidiki in conjunction with the potentially unstable lower troposphere influenced by mid-level cyclonic vorticity advection and enhanced low-level convergence over the complex terrain.

High resolution model estimates (10 × 10 km2) of tropospheric NO2 column amounts from the Comprehensive Air Quality Model (CAMx) for the Balkan Peninsula are compared with OMI/Aura measurements (13 × 24 km2 at nadir) for the year April 2009 to March 2010. The Balkan area contributes significantly to the NO2 burden in European air and so numerous urban, industrial and rural regions are studied aiming to investigate the consistency of both satellite retrievals and model predictions at high spatial resolution. It has already been shown that OMI can detect the tropospheric column of NO2 over polluted Balkan cities due to its fine horizontal resolution and instrument sensitivity (Zyrichidou et al., 2009). In this study the improved OMI DOMINO v2.0 satellite retrievals showed that over South-Eastern Europe the monthly mean NO2 tropospheric column density fluctuated between 2.0 and 5.7 ± 1.1 × 1015 molecules/cm2 over urban areas, 1.6–5.0 ± 0.7 × 1015 molecules/cm2 over large industrial complexes and 1.1–2.2 ± 0.4 × 1015 molecules/cm2 over rural areas for the year studied. The Comprehensive Air Quality Model with extensions (CAMx) version 4.40 is a publicly available open-source computer modeling system for the integrated assessment of gaseous and particulate air pollution. The anthropogenic emissions used in CAMx for the Greek domain being studied were compiled employing bottom-up approaches (road transport sector, off-road machinery, etc.) as well as other national registries and international databases. The rest of the Balkan domain has natural and anthropogenic emissions based on the TNO emission inventory of 2003. The high-resolution CAMx simulations reveal consistent spatial and temporal patterns with the OMI/Aura data. The annual spatial correlation coefficient between OMI and CAMx computed in this high spatial resolution analysis is of the order of 0.6, somewhat improved over those estimated in Zyrichidou et al. (2009) (R ≈ 0.5). However, in such a validation study it is important to take into account the averaging kernel (AK) information in order to achieve the creation of comparable data sets. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of limiting the effect of the a priori profile on the comparison is on average small. The main aim of the paper, which was to evaluate OMI retrieved and high resolution simulated tropospheric NO2 column densities over South-Eastern Europe and to assess the use of the averaging kernels, is achieved and the two data sources are being employed further in an inverse emission inventory creation study ( Zyrichidou et al., in preparation ).

Over the last years, the capabilities of chemical transport models have been greatly improved and the need for more accurate emission data has increased as well. In the past, a number of emission models have been developed and present different functionalities and applications. The majority of these though cover very specific needs. This paper describes the development of a new emission model namely computer model for the construction of model-ready emission inventories (MOSESS) which is used to compile high-resolution emission inventories or improve existing ones, utilizing complex GIS techniques. The model aims in helping chemical modelers to obtain a better overview of their modeling application by having a comprehensive understanding of the emission input. MOSESS incorporates more than 70 different emission calculation methodologies, and it is capable of handling external emission databases (such as EMEP and EPER) from which emissions can be extracted. The temporal variation (annual/daily and diurnal processing), chemical speciation of NMVOCs and particles, vertical distribution and point source treatment, as well as the spatial disaggregation of emissions (utilizing numerous spatial proxies including high-resolution landuses) can help create model-ready emission inventories which can be used for contemporary modeling applications.

The main issue arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two datasets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which was lasted for about six months was held at the greater area of Thessaloniki, Greece. Three DOAS/MAX-DOAS systems performed measurements of tropospheric NO2 columns at different sites representative of urban, sub-urban and rural conditions. The direct comparison of these ground-based measurements with corresponding OMI/Aura and GOME-2/MetOp-A and GOME2/MetOp-B products showed good agreement only over the rural area. GOME2A and GOME2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 9.12 ± 7.33 × 1015 and 9.58 ± 8.21 × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.03 ± 6.04 × 1015 molecules cm−2), mainly due to the higher spatial resolution of OMI. OMI data were adjusted using factors calculated by an air quality modelling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multi-scale photochemical transport model. This approach resulted to significant improvement of the comparisons over the urban monitoring site. The average negative difference of OMI observations from Phaethon measurements was reduced to 1.15 ± 6.32 × 1015 molecules cm−2.