Determination of total and lung-deposited particle surface area concentrations, in central Athens, Greece.

Numerous health studies have linked the exposure to particulate matter with adverse health effects, while there is an increasing scientific interest in the particle metrics of surface area (SA) and lung-deposited SA (LDSA) concentration. In the present study, two integrated SA estimation methods, both based on widely used instrumentation, were applied at an urban traffic environment in Athens for a 6-month period. The first estimation method used the size distribution by number to estimate SA (average SA1 669.3 ± 229.0 µm2 cm-3), while the second method used a simple inversion scheme that incorporates number and mass concentrations (average SA2 1627.9 ± 562.8 µm2 cm-3). In pairwise comparisons, SA2 levels were found two times greater than the corresponding SA1, but exhibited a strong correlation (r = 0.73). SA1 and SA2 concentrations correlated well with the traffic-related pollutants NOx (r = 0.64 and 0.78) and equivalent black carbon (r = 0.53 and 0.51). The diurnal variation of SA1 concentrations by size range indicated traffic as a major controlling factor. Estimated LDSA (53.9 µm2 cm-3 on average) concentrations were also clearly affected by anthropogenic emissions with more pronounced associations in the 0.01-0.4 µm range (r = 0.66 with NOx and r = 0.65 with equivalent black carbon). Validating estimated LDSA through simultaneous measurements with a reference instrument revealed that the estimation method underestimates LDSA by a factor between 2 and 3, exhibiting, however, a high correlation (r = 0.79). Overall, the performance of estimation methods appear satisfactory and indicate that a trustworthy assessment of the temporal variability of SA and LDSA concentration metrics can be provided in real time, on the basis of relatively lower-cost instrumentation, especially in view of recent advances in particle sensing technologies.

Determinants of personal exposure to ozone in school children. Results from a panel study in Greece.

BACKGROUND: In the wider framework of the RESPOZE (ReSPiratory effects of OZone Exposure in Greek children) panel study, we investigated possible determinants of O3 exposure of school children, measured with personal passive samplers, in Athens and Thessaloniki, Greece. METHODS: Personal exposure to O3 was measured for five weeks spread along the academic year 2013-14, in 186 school children in Athens and Thessaloniki, Greece. At the same time, at-school outdoor measurements were performed and ambient levels of 8-h daily maximum O3 from fixed sites were collected. We also collected information on lifestyle and housing characteristics through an extended general questionnaire (GQ) and each participant completed daily time activity diaries (TADs) during the study period. RESULTS: Mean outdoor concentrations were higher during the warmer months, in the suburbs of the cities and in Athens. Personal exposure concentrations were significantly lower compared to outdoor. Daily levels of at-school outdoor and ambient levels of O3 from fixed sites were significant determinants of personal exposure to O3. For a 10µg/m3 increase in at-school outdoor O3 concentrations and PM10 measurements a 20.9% (95% CI: 13%, 28%) increase in personal exposure to O3 was found. For a half an hour more spent in transportation an average increase of 7% (95% CI: 0.3%, 14.6%) in personal exposure to O3 was observed. Among other possible determinants, time spent in transportation (TAD variable) and duration of open windows were the ones associated with personal O3 exposure levels. CONCLUSIONS: Our results support the use of outdoor and ambient measurements from fixed sites in epidemiological studies as a proxy of personal exposure to O3, but this has to be calibrated taking into account personal measurements and time-activity patterns.

Ozone exposure assessment for children in Greece - Results from the RESPOZE study.

Ozone exposure of 179 children in Athens and Thessaloniki, Greece was assessed during 2013-2014, by repeated weekly personal measurements, using passive samplers. O3 was also monitored at school locations of participants to characterize community-level ambient exposure. Average personal concentrations in the two cities (5.0 and 2.8ppb in Athens and Thessaloniki, respectively) were considerably lower than ambient concentrations (with mean personal/ambient ratios of 0.13-0.15). The temporal variation of personal concentrations followed the -typical for low-latitude areas- pattern of cold-warm seasons. However, differences were detected between temporal distributions of personal and ambient concentrations, since personal exposures were affected by additional factors which present seasonal variability, such as outdoor activity and house ventilation. Significant spatial contrasts were observed between urban and suburban areas, for personal concentrations in Athens, with higher exposure for children residing in the N-NE part of the area. In Thessaloniki, spatial variations in personal concentrations were less pronounced, echoing the spatial pattern of ambient concentrations, a result of complex local meteorology and the smaller geographical expansion of the study area. Ambient concentration was identified as the most important factor influencing personal exposures (correlation coefficients between 0.36 and 0.67). Associations appeared to be stronger with ambient concentrations measured at school locations of children, than to those reported by the nearest site of the air quality monitoring network, indicating the importance of community-representative outdoor monitoring for characterization of personal-ambient relationships. Time spent outdoors by children was limited (>90% of the time they remained indoors), but -due to the lack of indoor sources- it was found to exert significant influence on personal concentrations, affecting inter-subject and spatiotemporal variability. Additional parameters that were identified as relevant for the determination of personal concentrations were indoor ventilation conditions (specifically indoor times with windows open) and the use of wood-burning in open fireplaces for heating as an ozone sink.

A CFD modeling study in an urban street canyon for ultrafine particles and population exposure: The intake fraction approach.

Air quality in street canyons is of major importance, since the highest pollution levels are often encountered in these microenvironments. The canyon effect (reduced natural ventilation) makes them "hot spots" for particulate pollution contributing to adverse health effects for the exposed population. In this study we tried to characterize the influence of UFP (ultrafine particle) emissions from traffic on population exposure in an urban street canyon, by applying the intake fraction (iF) approach. One month long measurements of UFP levels have been monitored and used for the need of this study. We applied a three dimensional computational fluid dynamic (CFD) model based on real measurements for the simulation of UFP levels. We used infiltration factors, evaluated on a daily basis for the under study area, to estimate the indoor UFP levels. As a result the intake fraction for the pedestrians, residents and office workers is in the range of (1E-5)-(1E-4). The street canyon is mostly residential justifying partially the higher value of intake fraction for residents (1E-4). The above iF value is on the same order of magnitude with the corresponding one evaluated in a relative street canyon study. The total iF value in this microenvironment is one order of magnitude higher than ours, explained partially by the different use and activities. Two specific applications of iF to assess prioritization among emission sources and environmental justice issues are also examined. We ran a scenario with diesel and gasoline cars and diesel fueled vehicle seems to be a target source to improve overall iF. Our application focus on a small residential area, typical of urban central Athens, in order to evaluate high resolution iF. The significance of source-exposure relationship study in a micro scale is emphasized by recent research.

Ultrafine particles dispersion modeling in a street canyon: development and evaluation of a composite lattice Boltzmann model.

Recently, a branch of particulate matter research concerns on ultrafine particles found in the urban environment, which originate, to a significant extent, from traffic sources. In urban street canyons, dispersion of ultrafine particles affects pedestrian's short term exposure and resident's long term exposure as well. The aim of the present work is the development and the evaluation of a composite lattice Boltzmann model to study the dispersion of ultrafine particles, in urban street canyon microenvironment. The proposed model has the potential to penetrate into the physics of this complex system. In order to evaluate the model performance against suitable experimental data, ultrafine particles levels have been monitored on an hourly basis for a period of 35 days, in a street canyon, in Athens area. The results of the comparative analysis are quite satisfactory. Furthermore, our modeled results are in a good agreement with the results of other computational and experimental studies. This work is a first attempt to study the dispersion of an air pollutant by application of the lattice Boltzmann method.

Classification criteria and probability risk maps: limitations and perspectives.

Delineation of polluted zones with respect to regulatory standards, accounting at the same time for the uncertainty of the estimated concentrations, relies on classification criteria that can lead to significantly different pollution risk maps, which, in turn, can depend on the regulatory standard itself. This paper reviews four popular classification criteria related to the violation of a probability threshold or a physical threshold, using annual (1996-2000) nitrogen dioxide concentrations from 40 air monitoring stations in Milan. The relative advantages and practical limitations of each criterion are discussed, and it is shown that some of the criteria are more appropriate for the problem at hand and that the choice of the criterion can be supported by the statistical distribution of the data and/or the regulatory standard. Finally, the polluted area is estimated over the different years and concentration thresholds using the appropriate risk maps as an additional source of uncertainty.

Neural network and multiple regression models for PM10 prediction in Athens: a comparative assessment.

Particulate atmospheric pollution in urban areas is considered to have significant impact on human health. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important to improve public awareness and air quality management. This study examines the possibility of using neural network methods as tools for daily average particulate matter with aerodynamic diameter <10 microm (PM10) concentration forecasting, providing an alternative to statistical models widely used up to this day. Based on a data inventory, in a fixed central site in Athens, Greece, ranging over a two-year period, and using mainly meteorological variables as inputs, neural network models and multiple linear regression models were developed and evaluated. Comparison statistics used indicate that the neural network approach has an edge over regression models, expressed both in terms of prediction error (root mean square error values lower by 8.2-9.4%) and of episodic prediction ability (false alarm rate values lower by 7-13%). The results demonstrate that artificial neural networks (ANNs), if properly trained and formed, can provide adequate solutions to particulate pollution prognostic demands.

Comparative assessment of neural networks and regression models for forecasting summertime ozone in Athens.

A comparison study has been performed with neural networks (NNs) and multiple linear regression models to forecast the next day's maximum hourly ozone concentration in the Athens basin at four representative monitoring stations that show very different behavior. All models use 11 predictors (eight meteorological and three persistence variables) and are developed and validated between April and October from 1992 to 1999. Performance results based on a wide set of forecast quality measures indicate that the NNs provide better estimates of ozone concentrations at the monitoring sites, whilst the more often used linear models are less efficient at accurately forecasting high ozone concentrations. The violation of the European information threshold of 180 microg/m(3) is successfully predicted by the NN in 72% of the cases on average. Results at all stations are consistent with similar ozone forecast studies using NNs in other European cities.