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1.
Sci Total Environ ; 751: 141855, 2021 Jan 10.
Article in English | MEDLINE | ID: mdl-32889477

ABSTRACT

PM2.5 is an air pollution metric widely used to assess air quality, with the European Union having set targets for reduction in PM2.5 levels and population exposure. A major challenge for the scientific community is to identify, quantify and characterize the sources of atmospheric particles in the aspect of proposing effective control strategies. In the frame of ICARUS EU2020 project, a comprehensive database including PM2.5 concentration and chemical composition (ions, metals, organic/elemental carbon, Polycyclic Aromatic Hydrocarbons) from three sites (traffic, urban background, rural) of five European cities (Athens, Brno, Ljubljana, Madrid, Thessaloniki) was created. The common and synchronous sampling (two seasons involved) and analysis procedure offered the prospect of a harmonized Positive Matrix Factorization model approach, with the scope of identifying the similarities and differences of PM2.5 key-source chemical fingerprints across the sampling sites. The results indicated that the average contribution of traffic exhausts to PM2.5 concentration was 23.3% (traffic sites), 13.3% (urban background sites) and 8.8% (rural sites). The average contribution of traffic non-exhausts was 12.6% (traffic), 13.5% (urban background) and 6.1% (rural sites). The contribution of fuel oil combustion was 3.8% at traffic, 11.6% at urban background and 18.7% at rural sites. Biomass burning contribution was 22% at traffic sites, 30% at urban background sites and 28% at rural sites. Regarding soil dust, the average contribution was 5% and 8% at traffic and urban background sites respectively and 16% at rural sites. Sea salt contribution was low (1-4%) while secondary aerosols corresponded to the 16-34% of PM2.5. The homogeneity of the chemical profiles as well as their relationship with prevailing meteorological parameters were investigated. The results showed that fuel oil combustion, traffic non-exhausts and soil dust profiles are considered as dissimilar while biomass burning, sea salt and traffic exhaust can be characterized as relatively homogenous among the sites.

2.
Environ Monit Assess ; 190(3): 155, 2018 Feb 20.
Article in English | MEDLINE | ID: mdl-29464404

ABSTRACT

Nowadays, the advancement of mobile technology in conjunction with the introduction of the concept of exposome has provided new dynamics to the exposure studies. Since the addressing of health outcomes related to environmental stressors is crucial, the improvement of exposure assessment methodology is of paramount importance. Towards this aim, a pilot study was carried out in the two major cities of Greece (Athens, Thessaloniki), investigating the applicability of commercially available fitness monitors and the Moves App for tracking people's location and activities, as well as for predicting the type of the encountered location, using advanced modeling techniques. Within the frame of the study, 21 individuals were using the Fitbit Flex activity tracker, a temperature logger, and the application Moves App on their smartphones. For the validation of the above equipment, participants were also carrying an Actigraph (activity sensor) and a GPS device. The data collected from Fitbit Flex, the temperature logger, and the GPS (speed) were used as input parameters in an Artificial Neural Network (ANN) model for predicting the type of location. Analysis of the data showed that the Moves App tends to underestimate the daily steps counts in comparison with Fitbit Flex and Actigraph, respectively, while Moves App predicted the movement trajectory of an individual with reasonable accuracy, compared to a dedicated GPS. Finally, the encountered location was successfully predicted by the ANN in most of the cases.


Subject(s)
Environmental Monitoring/instrumentation , Mobile Applications , Environmental Monitoring/methods , Exercise , Female , Geographic Information Systems , Greece , Humans , Neural Networks, Computer , Pilot Projects , Smartphone
3.
Environ Sci Pollut Res Int ; 23(8): 7814-27, 2016 Apr.
Article in English | MEDLINE | ID: mdl-26758302

ABSTRACT

Source contribution to atmospheric particulate matter (PM) has been exhaustively modelled. However, people spend most of their time indoors where this approach is less explored. This evidence worsens considering elders living in Elderly Care Centres, since they are more susceptible. The present study aims to investigate the PM composition and sources influencing elderly exposure. Two 2-week sampling campaigns were conducted-one during early fall (warm phase) and another throughout the winter (cold phase). PM10 were collected with two TCR-Tecora(®) samplers that were located in an Elderly Care Centre living room and in the correspondent outdoor. Chemical analysis of the particles was performed by neutron activation analysis for element characterization, by ion chromatography for the determination of water soluble ions and by a thermal optical technique for the measurement of organic and elemental carbon. Statistical analysis showed that there were no statistical differences between seasons and environments. The sum of the indoor PM10 components measured in this work explained 57 and 53 % of the total PM10 mass measured by gravimetry in warm and cold campaigns, respectively. Outdoor PM10 concentrations were significantly higher during the day than night (p value < 0.05), as well as Ca(2+), Fe, Sb and Zn. The contribution of indoor and outdoor sources was assessed by principal component analysis and showed the importance of the highways and the airport located less than 500 m from the Elderly Care Centre for both indoor and outdoor air quality.


Subject(s)
Air Pollution, Indoor/analysis , Particulate Matter/analysis , Particulate Matter/chemistry , Aged , Air Pollutants , Carbon/analysis , Environmental Monitoring/statistics & numerical data , Homes for the Aged/statistics & numerical data , Humans , Particle Size , Principal Component Analysis , Seasons , Weather
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