Ambient particulate matter (PM10) and its chemical composition in polycyclic aromatic hydrocarbons (PAHs) were studied in areas of specific interest, between September 2015 and July 2016. The principal aim of this study was to assess the different PAH source profiles in each area, as well as their potential health risk. In particular, the studied areas were (a) the semiurban industrialized zone of the Municipality of Peloponnese (Meligalas, Messini) of Messinia prefecture, due to the intensive olive-productive activity in the extensive area, (b) the industrialized zone of Oinofyta in Voiotia prefecture, and (c) the urban/traffic center of Athens (Aristotelous). Intense spatial and seasonal variations in PAH levels were observed among the study areas collectively, but also for each one individually. During the winter period, the total PAHs average concentration was 11.45 and 9.84 ng/m3 at Meligalas–Skala (S1, S2 stations), 8.84 ng/m3 at Messini (S3 station), and 6.30 ng/m3 at the center of Athens (Aristotelous). During the summer campaign, the corresponding levels were 0.99, 1.20, and 0.70 ng/m3 (S1, S2, and S3 stations), and 5.84 ng/m3 (Aristotelous), respectively. The highest potential cancer risk of the PAHs mixture was estimated based on winter season measurements taken at the Municipality of Peloponnese. In order to determine PAH sources, two different source apportionment techniques were applied, i.e., diagnostic ratios (DRs) and the positive matrix factorization (PMF) model.

Among the existing techniques to mitigate the problem of contamination in the indoor environment, photocatalytic technology is considered to be the most promising solution in terms of effectiveness and cost. To that end, in the frame of the LIFEVISIONS project, a novel photocatalytic powder (photo-powder) was mixed in paints’ matrix, producing a photocatalytic building material (photo-paint) able to improve indoor air quality (IAQ), upon its application, without downgrading paint physical properties. As a result, of IAQ improvement, less energy will be needed from ventilation systems, addressing not only health issues related to air quality but also energy reduction targets. Many powder formulae were synthesized using different synthetic pathways, concentration of dopants, and TiO2 particles’ size. They were tested in a photocatalytic reactor (lab-scale tests), according to CEN TS 16980-1:2017, under visible light and the results showed that the most promising photocatalytic performance degrades 85.4% and 32.4% of nitrogen oxide (NO) and toluene, respectively. This one was used for the production of two different kinds of paints, organic (with organic binder) and inorganic (with potassium silicate binder), in an industrial scale. Both were tested in the Demo Houses’ prototype demonstrator (real-scale tests) with an ultimate scope to estimate their effectiveness to degrade air pollutants under real-world conditions. In addition, the reduced energy consumption as a result of less ventilation needs was calculated in Demo Houses. More specifically, the energy reduction based on simulation results on Demo Houses was more than 7%. Although lab-scale tests showed better photocatalytic performance than the real scale, the efficiency of the paints under a more complicated environment was very promising.

Indoor air pollution source apportionment (SA) is an evolving field and remains challenging to adjust the gained knowledge from atmospheric studies to the indoor environment. This paper identifies ten key-questions on indoor SA. Firstly, the scientific challenges of indoor SA are presented, including the differences between indoor and outdoor SA (Q1), the appropriate tracers (Q2), the challenges for indoor organic PM and VOCs apportionment (Q3) and the effect of oxidative reactions on indoor SA (Q4). Afterwards, the advances of indoor air monitoring/analysis are discussed towards an optimized indoor air SA (Q5-6). Q7 and Q8 review the type of receptor models best applying for indoor SA and discuss how the advances in online outdoor SA can benefit indoor SA. Q9 deals with the optimization of the estimation of the outdoor sources’ contribution to indoor air. Finally, the challenge of using machine learning techniques for indoor SA is discussed in Q10.

Industrial activities nearby residential areas lead to poor local air quality. Therefore, short-term exposure to an aggravated environment and the subsequent health effects should be the subject of further research. The purpose of this study is to estimate the health risks resulting from such exposure in population groups living in an industrialized area. The risk estimation was performed using different approaches suggested in relative literature. Monitoring of the air quality in an industrial zone of Attica was carried out including 24-h measurements of PM2.5 and analysis of their chemical composition for Polycyclic Aromatic Hydrocarbons and heavy metals (Pb, Cd, As, Ni, Hg, Cu, Zn). Samples of Volatile Organic Compounds were also collected. Health effects on different population subgroups were estimated for the targeted pollutants through different mathematical approaches provided by the literature, taking into consideration different parameters (e.g., age, gender, exposure duration). Inhalation rate and body weight were important parameters to estimate the exposure dose of people, and they can vary greatly depending on the age, gender, and daily activity of the person under consideration. The results indicated that the risk for potential carcinogenic and non-carcinogenic effects varies depending on the applied methodology. In any case, the acceptable limits for cancer risk provided by the OEHHA, EPA, and WHO were not exceeded.