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Particulate matter (PM) in air has been proven to be hazardous to human health. Here we focused on analysis of PM data we obtained from the same campaign which was presented in our previous study. Multivariate linear and random forest models were used for the calibration and analysis. In our linear regression model the inputs were PM, temperature and humidity measured with low-cost sensors, and the target was the reference PM measurements obtained from SEPA in the same timeframe.

Scalable and effective calibration is a fundamental requirement for Low Cost Air Quality Monitoring Systems and will enable accurate and pervasive monitoring in cities. Suffering from environmental interferences and fabrication variance, these devices need to encompass sensors specific and complex calibration processes for reaching a sufficient accuracy to be deployed as indicative measurement devices in Air Quality (AQ) monitoring networks. Concept and sensor drift often force calibration process to be frequently repeated. These issues lead to unbearable calibration costs which denies their massive deployment when accuracy is a concern. In this work, We propose a zero transfer samples, global calibration methodology as a technological enabler for IoT AQ multisensory devices which relies on low cost Particulate Matter (PM) sensors. This methodology is based on field recorded responses from a limited number of IoT AQ multisensors units and machine learning concepts and can be universally applied to all units of the same type. A multi season test campaign shown that, when applied to different sensors, this methodology performances match those of state of the art methodology which requires to derive different calibration parameters for each different unit. If confirmed, these results show that, when properly derived, a global calibration law can be exploited for a large number of networked devices with dramatic cost reduction eventually allowing massive deployment of accurate IoT AQ monitoring devices. Furthermore, this calibration model could be easily embedded on board of the device or implemented on the edge allowing immediate access to accurate readings for personal exposure monitor applications as well as reducing long range data transfer needs.

Atmospheric aerosols in urban areas typically consist of particles of different diameters, which can range in size from a few nanometers to a few micrometers and can have a strong impact on human health [1,2]. This motivates the need to measure aerosol concentration accurately, but it is often also necessary to combine results from several instruments, with fundamentally different measurement principles. In this work, methods based on the measurement of the electrical mobility of particles, for the range of diameters from 10nm to 420nm, and the measurement of the equivalent optical diameter, for the range of diameters from 300nm to 10um, were used. Combining the overlapping region in two size distribution spectra can be used to infer equivalent optical properties of the ambient aerosol, and examples of measured and combined spectra in several urban hot spots in Bay of Kotor are analyzed in some detail. These examples will illustrate several aspects of urban aerosol properties not readily available in a typical regulatory monitoring setting, such as distribution of modes in number and mass concentration, as well as optical properties of measured aerosol. As the main result, examples of combining particle size spectrums are presented. In the process of combining the particle size spectra, it is possible to modify the distribution obtained by optical measurements by searching for the optimal value of the refractive index of the particles to obtain the best possible agreement with the size distribution obtained by measuring the electrical mobility. An equivalent refractive index as well as the equivalent shape factor of the ambient aerosol is obtained using Mie scattering theory as a theoretical framework [3]. The measurement results from the mobile monitoring campaign in Bay of Kotor in 2017 were used to elucidate the main principles of size spectrum combination, as well as to showcase diversity of equivalent optical properties of urban aerosols. Funding for this work

In numerous epidemiological studies, exposure to particulate matter (PM) has been associated with negative health outcomes. It has been established so far that the detrimental health effects of particles cannot be explained by a single parameter, such as particle mass, as the complexity of chemical composition and reactivity of particles are not always represented by the mass loadings. The oxidative potential (OP) of aerosol particles represents a promising indicator of their potential toxicity. To develop strategies and regulations at improving the air quality, an increasing number of studies are focused on the application of source apportionment (SA) of PM., while a limited number of SA investigations have been applied to OP. In this review previous research of SA of atmospheric PM OP and proposed guidelines for future studies are summarized. Most of the research studies were carried out in an urban area and focused on PM2.5, while few studies examined other PM fractions. It was noted that the three dominant contributors to OP were biomass burning (9-97%), secondary aerosols (6-67%), and traffic/vehicles (16-88%). The presence of other factors that contributed to the in-crease of OP to a lesser extent depended on the location and season. Further, a considerable discrepancy in the contribution of various OP vs. PM sources was discovered using SA models. Because of this, the use of SA is not equivalent when considering the mass of PM and its toxicity.

Atmosferski aerosoli u urbanim sredinama se sastoje od čestica različitih dijametara, koje mogu imati veličinu od par nanometara do par mikrometara. Stoga je za merenje koncentracije aerosola često neophodno koristiti više instrumenata, sa principijelno različitim metodama merenja. U ovom radu su korišćene metode zasnovane na merenju električne pokretljivosti čestica, za opseg dijametara od 10nm do 420nm, i merenju ekvivalentnog optičkog dijametra, za opseg dijametara od 300nm do 10um. Kao glavni rezultat, prikazani su primeri kombinovanja spektara veličina čestica koji su dobijeni pomoću ove dve komplementarne metode merenja. U procesu kombinovanja spektara veličina čestica moguće je modifikovati raspodelu dobijenu optičkim merenjima traženjem optimalne vrednosti indeksa prelamanja čestica tako da se dobije što bolje slaganje sa raspodelom dobijenom merenjem električne pokretljivosti. Kao ulazni podaci su korišćeni rezultati merenja iz kampanje mobilnog monitoringa u Novom Sadu 2022.

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.

Changes in air pollution in the region of the city of Novi Sad due to the COVID-19 induced state of emergency were evaluated while using data from permanently operating air quality monitoring stations belonging to the national, regional, and local networks, as well as ad hoc deployed low-cost particulate matter (PM) sensors. The low-cost sensors were collocated with reference gravimetric pumps. The starting idea for this research was to determine if and to what extent a massive change of anthropogenic activities introduced by lockdown could be observed in main air pollutants levels. An analysis of the data showed that fine and coarse particulate matter, as well as SO2 levels, did not change noticeably, compared to the pre-lockdown period. Isolated larger peaks in PM pollution were traced back to the Aralkum Desert episode. The reduced movement of vehicles and reduced industrial and construction activities during the lockdown in Novi Sad led to a reduction and a more uniform profile of the PM2.5 levels during the period between morning and afternoon air pollution peak, approximately during typical working hours. Daily profiles of NO2, NO, and NOX during the state of emergency proved lower levels during most hours of the day, due to restrictions on vehicular movement. CO during the state of the emergency mainly exhibited a lower level during night. Pollutants having transportation-dominated source profiles exhibited a decrease in level, while pollutants with domestic heating source profiles mostly exhibited a constant level. Considering local sources in Novi Sad, slight to moderate air quality improvement was observed after the lockdown as compared with days before. Furthermore, PM low-cost sensors’ usefulness in air quality assessment was confirmed, as they increase spatial resolution, but it is necessary to calibrate them at the deployment location.

The International Workshop and Conference, Particulate Matter: Research and Management - WeBIOPATR is a biennial event held in Serbia since 2007. The conference addresses air quality in general and particulate matter specifically. Atmospheric particulate matter arises both from primary emissions and from secondary formation in the atmosphere. It is one of the least well understood local and regional air pollutants, has complex implications for climate change, and is perhaps the pollutant with the highest health relevance. It also poses many challenges to monitoring. [from Preface]

U ovoj disertaciji ispitan je hemijski sastav i oksidativni potencijal (OP) dve frakcije respirabilnih čestica (PM2.5 i PM10), u različitim sredinama. Za utvrĎivanje sezonskih promena, prvo istraţivanje sprovedeno je u urbanoj (UB) i urbano-industrijskoj (UI) sredini tokom leta i zime. Kako bi se ispitale promene OP-a tokom dana, drugo istraţivanje sprovedeno je u urbanoj sredini pod uticajem saobraćaja. Rezultati prvog istraţivanja ukazuju da su prosečne koncentracije obe ispitivane frakcije čestica, u UB i UI, bile vrlo slične tokom leta. Tokom zime, u UB koncentracije PM2.5 bile su tri puta više, a PM10 dvostruko više u odnosu na koncentracije izmerene u UI. U obe ispitivane sredine, tokom obe sezone, PM2.5/PM10 odnos bio je visok, što ukazuje na značajan udeo finih čestica u gruboj frakciji, koje prvenstveno imaju antropogeno poreklo. Dominantnu vrstu u obe frakcije čestica, kao i u obe ispitivane sredine, činila je organska materija, čiji je procenat varirao u zavisnosti od godišnjeg doba. Prosečni OC/EC odnosi, kao i koncentracije WSOC-a, u obe frakcije čestica, bili su značajno viši tokom zimskog perioda u UB, što je posledica prisustva velike količine sekundarnih organskih aerosola. Prosečne koncentracije jonskih vrsta i 22 kvantifikovana elementa, tokom obe sezone, bile su više u UI. Primenom DTT i DCFH eseja, u obe ispitivane sredine, više vrednosti OP-a utvrĎene su za PM2.5, a primenjeni eseji pokazali su suprotne trendove. U obe ispitivane sredine, primenom DTT eseja, OP vrednosti bile su više tokom letnjeg perioda, dok su DCFH esejom više vrednosti utvrĎene tokom zime. U drugom istraţivanju, najveća količina ROS-ova izmerena je oko 14 h, što moţe biti posledica maksimalne količine saobraćaja ili velikog doprinosa SOA. Umerena, statistički značajna korelacija utvrĎena je izmeĎu BPEAnit i DCFH eseja, što ukazuje na veću toksičnost koja potiče od organskih vrsta prisutnih u vazduhu. Kombinovanjem rezultata više eseja preciznije je utvrĎen kvalitet vazduha, In this dissertation, the chemical content and oxidative potential (OP) of two fractions of respirable particles (PM2.5 and PM10) were examined in different еnvironments. The first study was conducted in urban (UB) and urban-industrial (UI) environments during summer and winter to determine the seasonal changes. The second study was conducted in an urban environment influenced by the traffic to examine the differences in OP during the day. The results of the first study indicate that the average concentrations of both analyzed particle fractions, in UB and UI, were very similar during the summer. During the winter, PM2.5 levels in UB were three times higher and PM10 twice as high as in UI level. In both examined environments, during both seasons, the PM2.5/ PM10 ratio was high, which indicates a significant contribution of fine particles in the coarse fraction, which are primarily of anthropogenic origin. In both examined environments, the dominant particle fraction was the organic matter, the percentage of which varied depending on the season. Average OC/EC ratios, as well as WSOC concentrations, in both particle fractions, were significantly higher during the winter period in UB, due to the presence of a large amount of secondary organic aerosols. The average concentrations of ion species and 22 quantified elements, during both seasons, were higher in the UI. Using DTT and DCFH assays, in both examined environments, higher OP values were determined for PM2.5, and the applied assays showed opposite trends. In both urban environments, using DTT assays, OP values were higher during the summer period, while DCFH assays were higher values determined during the winter. In another study, the largest amount of ROS was measured around 2 p.m., which may be due to maximum traffic or a significant contribution from SOA. A moderate, statistically significant correlation was found between BPEAnit and DCFH assays, indicating higher toxicity derived from organic species present i

U ovoj disertaciji ispitan je hemijski sastav i oksidativni potencijal (OP) dve frakcije respirabilnih čestica (PM2.5 i PM10), u različitim sredinama. Za utvrĎivanje sezonskih promena, prvo istraţivanje sprovedeno je u urbanoj (UB) i urbano-industrijskoj (UI) sredini tokom leta i zime. Kako bi se ispitale promene OP-a tokom dana, drugo istraţivanje sprovedeno je u urbanoj sredini pod uticajem saobraćaja. Rezultati prvog istraţivanja ukazuju da su prosečne koncentracije obe ispitivane frakcije čestica, u UB i UI, bile vrlo slične tokom leta. Tokom zime, u UB koncentracije PM2.5 bile su tri puta više, a PM10 dvostruko više u odnosu na koncentracije izmerene u UI. U obe ispitivane sredine, tokom obe sezone, PM2.5/PM10 odnos bio je visok, što ukazuje na značajan udeo finih čestica u gruboj frakciji, koje prvenstveno imaju antropogeno poreklo. Dominantnu vrstu u obe frakcije čestica, kao i u obe ispitivane sredine, činila je organska materija, čiji je procenat varirao u zavisnosti od godišnjeg doba. Prosečni OC/EC odnosi, kao i koncentracije WSOC-a, u obe frakcije čestica, bili su značajno viši tokom zimskog perioda u UB, što je posledica prisustva velike količine sekundarnih organskih aerosola. Prosečne koncentracije jonskih vrsta i 22 kvantifikovana elementa, tokom obe sezone, bile su više u UI. Primenom DTT i DCFH eseja, u obe ispitivane sredine, više vrednosti OP-a utvrĎene su za PM2.5, a primenjeni eseji pokazali su suprotne trendove. U obe ispitivane sredine, primenom DTT eseja, OP vrednosti bile su više tokom letnjeg perioda, dok su DCFH esejom više vrednosti utvrĎene tokom zime. U drugom istraţivanju, najveća količina ROS-ova izmerena je oko 14 h, što moţe biti posledica maksimalne količine saobraćaja ili velikog doprinosa SOA. Umerena, statistički značajna korelacija utvrĎena je izmeĎu BPEAnit i DCFH eseja, što ukazuje na veću toksičnost koja potiče od organskih vrsta prisutnih u vazduhu. Kombinovanjem rezultata više eseja preciznije je utvrĎen kvalitet vazduha, In this dissertation, the chemical content and oxidative potential (OP) of two fractions of respirable particles (PM2.5 and PM10) were examined in different еnvironments. The first study was conducted in urban (UB) and urban-industrial (UI) environments during summer and winter to determine the seasonal changes. The second study was conducted in an urban environment influenced by the traffic to examine the differences in OP during the day. The results of the first study indicate that the average concentrations of both analyzed particle fractions, in UB and UI, were very similar during the summer. During the winter, PM2.5 levels in UB were three times higher and PM10 twice as high as in UI level. In both examined environments, during both seasons, the PM2.5/ PM10 ratio was high, which indicates a significant contribution of fine particles in the coarse fraction, which are primarily of anthropogenic origin. In both examined environments, the dominant particle fraction was the organic matter, the percentage of which varied depending on the season. Average OC/EC ratios, as well as WSOC concentrations, in both particle fractions, were significantly higher during the winter period in UB, due to the presence of a large amount of secondary organic aerosols. The average concentrations of ion species and 22 quantified elements, during both seasons, were higher in the UI. Using DTT and DCFH assays, in both examined environments, higher OP values were determined for PM2.5, and the applied assays showed opposite trends. In both urban environments, using DTT assays, OP values were higher during the summer period, while DCFH assays were higher values determined during the winter. In another study, the largest amount of ROS was measured around 2 p.m., which may be due to maximum traffic or a significant contribution from SOA. A moderate, statistically significant correlation was found between BPEAnit and DCFH assays, indicating higher toxicity derived from organic species present i

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.

In this work we explore the relationship between particulate matter (PM) and small ion (SI) concentration in a typical indoor elementary school environment. A range of important air quality parameters (radon, PM, SI, temperature, humidity) were measured in two elementary schools located in urban background and suburban area in Belgrade city, Serbia. We focus on an interplay between concentrations of radon, small ions (SI) and particulate matter (PM) and for this purpose, we utilize two approaches. The first approach is based on a balance equation which is used to derive approximate relation between concentration of small ions and particulate matter. The form of the obtained relation suggests physics based linear regression modelling. The second approach is more data driven and utilizes machine learning techniques, and in this approach, we develop a more complex statistical model. This paper attempts to put together these two methods into a practical statistical modelling approach that would be more useful than either approach alone. The artificial neural network model enabled prediction of small ion concentration based on radon and particulate matter measurements. Models achieved median absolute error of about 40 ions/cm3 and explained variance of about 0.7. This could potentially enable more simple measurement campaigns, where a smaller number of parameters would be measured, but still allowing for similar insights.

In this work we explore the relationship between particulate matter (PM) and small ion (SI) concentration in a typical indoor elementary school environment. A range of important air quality parameters (radon, PM, SI, temperature, humidity) were measured in two elementary schools located in urban background and suburban area in Belgrade city, Serbia. We focus on an interplay between concentrations of radon, small ions (SI) and particulate matter (PM) and for this purpose, we utilize two approaches. The first approach is based on a balance equation which is used to derive approximate relation between concentration of small ions and particulate matter. The form of the obtained relation suggests physics based linear regression modelling. The second approach is more data driven and utilizes machine learning techniques, and in this approach, we develop a more complex statistical model. This paper attempts to put together these two methods into a practical statistical modelling approach that would be more useful than either approach alone. The artificial neural network model enabled prediction of small ion concentration based on radon and particulate matter measurements. Models achieved median absolute error of about 40 ions/cm3 and explained variance of about 0.7. This could potentially enable more simple measurement campaigns, where a smaller number of parameters would be measured, but still allowing for similar insights. © 2020 by the authors.

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.

Substantial knowledge is available on the association of the indoor school environment and its effect among schoolchildren. In the same context, the SINPHONIE (School indoor pollution and health: Observatory network in Europe) conducted a study to collect data and determine the distribution of several indoor air pollutants (IAPs), physical and thermal parameters and their association with eye, skin, upper-, lower respiratory and systemic disorder symptoms during the previous three months. Finally, data from 115 schools in 54 European cities from 23 countries were collected and included 5175 schoolchildren using a harmonized and standardized protocol. The association between exposures and the health outcomes were examined using logistic regression models on the environmental stressors assessed in classroom while adjusting for several confounding factors; a VOC (volatile organic compound) score defined as the sum of the number of pollutants to which the children were highly exposed (concentration > median of the distribution) in classroom was also introduced to evaluate the mul tiexposu re - outcome association. Schoolchildren while adjusting for several confounding factors. Schoolchildren exposed to above or equal median concentration of PM2.5, benzene, limonene, ozone and radon were at significantly higher odds of suffering from upper, lower airways, eye and systemic disorders. Increased odds were also observed for any symptom (sick school syndrome) among schoolchildren exposed to concentrations of limonene and ozone above median values. Furthermore, the risks for upper and lower airways and systemic disorders significantly increased with the VOCs score. Results also showed that increased ventilation rate was significantly associated with decreased odds of suffering from eye and skin disorders whereas similar association was observed between temperature and upper airways symptoms. The present study provides evidence that exposure to IAPs in schools is associated wit

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.