Source apportionment for indoor air pollution: Current challenges and future directions.

Source apportionment (SA) for indoor air pollution is challenging due to the multiplicity and high variability of indoor sources, the complex physical and chemical processes that act as primary sources, sinks and sources of precursors that lead to secondary formation, and the interconnection with the outdoor environment. While the major indoor sources have been recognized, there is still a need for understanding the contribution of indoor versus outdoor-generated pollutants penetrating indoors, and how SA is influenced by the complex processes that occur in indoor environments. This paper reviews our current understanding of SA, through reviewing information on the SA techniques used, the targeted pollutants that have been studied to date, and their source apportionment, along with limitations or knowledge gaps in this research field. The majority (78 %) of SA studies to date focused on PM chemical composition/size distribution, with fewer studies covering organic compounds such as ketones, carbonyls and aldehydes. Regarding the SA method used, the majority of studies have used Positive Matrix Factorization (31 %), Principal Component Analysis (26 %) and Chemical Mass Balance (7 %) receptor models. The indoor PM sources identified to date include building materials and furniture emissions, indoor combustion-related sources, cooking-related sources, resuspension, cleaning and consumer products emissions, secondary-generated pollutants indoors and other products and activity-related emissions. The outdoor environment contribution to the measured pollutant indoors varies considerably (<10 %- 90 %) among the studies. Future challenges for this research area include the need for optimization of indoor air quality monitoring and data selection as well as the incorporation of physical and chemical processes in indoor air into source apportionment methodology.

Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence.

A novel statistical model based on a two-layer, contact and information, graph is suggested in order to study the influence of disease prevalence on voluntary general population vaccination during the COVID-19 outbreak. Details about the structure and number of susceptible, infectious, and recovered/vaccinated individuals from the contact layer are simultaneously transferred to the information layer. The ever-growing wealth of information that is becoming available about the COVID virus was modelled at each individual level by a simplified proxy predictor of the amount of disease spread. Each informed individual, a node in a heterogeneous graph, makes a decision about vaccination "motivated" by their benefit. The obtained results showed that disease information type, global or local, has a significant impact on an individual vaccination decision. A number of different scenarios were investigated. The scenarios showed that in the case of the stronger impact of globally broadcasted disease information, individuals tend to vaccinate in larger numbers at the same time when the infection has already spread within the population. If individuals make vaccination decisions based on locally available information, the vaccination rate is uniformly spread during infection outbreak duration. Prioritising elderly population vaccination leads to an increased number of infected cases and a higher reduction in mortality. The developed model accuracy allows the precise targeting of vaccination order depending on the individuals' number of social contacts. Precisely targeted vaccination, combined with pre-existing immunity, and public health measures can limit the infection to isolated hotspots inside the population, as well as significantly delay and lower the infection peak.

Comparison of fine particulate matter level, chemical content and oxidative potential derived from two dissimilar urban environments.

Urban airborne particles contain a wide spectrum of components, known to have harmful effects on human health. This study reports a detailed investigation of fine particulate matter (PM2.5), chemical content and oxidative potential derived from two different urban environments. During summer and winter, 20-day campaigns were conducted at Belgrade city center (urban-background site - UB) and Bor (urban-industrial site - UI). Using various analytical techniques, carbonaceous compounds, water-soluble inorganic ions, major and trace elements were determined, while the oxidative potential of PM2.5 was estimated by dichloro-dihydro-fluorescein diacetate (DCFH-DA) assay (OPDCFH values). The mean PM2.5 concentrations in both urban environments were above the recommended daily value, and the dominant PM2.5 mass contributor was organic matter (29-55%). The OC/EC ratio was significantly higher at UB site during winter, which was an indication of a considerable contribution of secondary organic carbon to the overall organic carbon (OC). Water-soluble organic carbon (WSOC) was also higher at UB than at UI site, and it probably came from the same sources as OC. In general, the different partition of secondary organic aerosol (SOA) in warm and cold periods affected the number of organic components. Sulfates and nitrates were the most abundant ions at both sites and they counted approximately 40% (summer) and 50% (winter) of total ions. Further, the concentrations of the most elements, particularly some potentially carcinogenic elements such as As, Cd and Pb were significantly higher at UI, due to the emissions from the copper smelter complex in the vicinity. The mean OPDCFH values were similar during the summer at both sampling sites, whereas a statistically significant difference between sites was noticed in favor of UB environment in winter.

Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays.

To estimate the oxidative potential (OP) of particulate matter (PM), two commonly used cell-free, molecular probes were applied: dithiothreitol (DTT) and dichloro-dihydro-fluorescein diacetate (DCFH-DA), and their performance was compared with 9,10-bis (phenylethynyl) anthracene-nitroxide (BPEAnit). To the best of our knowledge, this is the first study in which the performance of the DTT and DCFH has been compared with the BPEAnit probe. The average concentrations of PM, organic carbon (OC) and elemental carbon (EC) for fine (PM2.5) and coarse (PM10) particles were determined. The results were 44.8 ± 13.7, 9.8 ± 5.1 and 9.3 ± 4.8 µg·m-3 for PM2.5 and 75.5 ± 25.1, 16.3 ± 8.7 and 11.8 ± 5.3 µg·m-3 for PM10, respectively, for PM, OC and EC. The water-soluble organic carbon (WSOC) fraction accounted for 42 ± 14% and 28 ± 9% of organic carbon in PM2.5 and PM10, respectively. The average volume normalized OP values for the three assays depended on both the sampling periods and the PM fractions. The OPBPEAnit had its peak at 2 p.m.; in the afternoon, it was three times higher compared to the morning and late afternoon values. The DCFH and BPEAnit results were correlated (r = 0.64), while there was no good agreement between the BPEAnit and the DTT (r = 0.14). The total organic content of PM does not necessarily represent oxidative capacity and it shows varying correlation with the OP. With respect to the two PM fractions studied, the OP was mostly associated with smaller particles.

An evaluation tool kit of air quality micro-sensing units.

Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors' capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors' performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25 MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors' performance. The SET was implemented in R and the code is available on the first author's website.

Association between ambient air pollution, meteorological conditions and exacerbations of asthma and chronic obstructive pulmonary disease in adult citizens of the town of Smederevo.

INTRODUCTION: Smederevo is the only town in Serbia with a steel factory, whose exhausts contribute to air pollution. Therefore, the city conducts continuous monitoring of air quality. In recent years, high levels of particulate matter (PM) including coarse (PM10) and fine (PM2.5) particles in the air have frequently been recorded. The aim of this study was to assess association between exacerbation of asthma or chronic obstructive pulmonary disease (COPD) in adults and air pollution or meteorological conditions. METHODS: The study was conducted in the secondary care General Hospital in Smederevo covering approximately 81,000 inhabitants living in the area of about 7 km around the automatic station for air quality monitoring from which the verified data were collected. Data on patients were obtained from medical records. The correlation between the incidence of diseases exacerbation and the number of days with exceedance of air pollutants limit level per month, as well as meteorological conditions, was tested with parametric Pearson bivariate correlation test in program SPSS. RESULTS: The study population consisted of adults registered as asthma or COPD suffering patients (n = 1,624) with 570 episodes of remarkable exacerbations (moderate or severe) of the disease in 2011. Asthma exacerbation was significantly more frequent in women than in men. The number of days with high levels of PM2.5 per month was statistically significantly associated with the total number of exacerbation (moderate and severe of both asthma and COPD) episodes among the female patients. There was also a statistically significant association between the number of days with PM2.5 exceedance and the number of moderate exacerbations in the subgroups of non-smokers and obese patients. A significant correlation of the number of days with the exceedance of PM10 limit level was shown only for the subgroup of obese, non-smoking patients with moderate exacerbation. A significant negative association with the average ambient temperature was proven for the obese female patients and obese non-smoking patients with moderate asthma exacerbations. The number of COPD exacerbation was in positive correlation with the average air pressure for the subgroup of female smokers, but the connection with air pollution was not proven. CONCLUSION: Exposure to airborne particles in the town of Smederevo, mainly to PM2.5, and to low temperature may trigger asthma exacerbation requiring emergency care. The most vulnerable may be women and obese patients.

On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter.

Respirable particulate matter present in outdoor and indoor environments is a health hazard. The particle concentrations can quickly change, with steep gradients on short temporal and spatial scales, and their chemical composition and physical properties vary considerably. Existing networks of aerosol particle measurements consist of limited number of monitoring stations, and mostly aim at assessment of compliance with air quality legislation regulating mass of particles of varying sizes. These networks can now be supplemented using small portable devices with low-cost sensors for assessment of particle mass that may provide higher temporal and spatial resolution if we understand the capabilities and characteristics of the data they provide. This paper overviews typical currently available devices and their characteristics. In addition it is presented original results of measurement and modelling in the aim of one low-cost PM monitor validation.