Investigating the Impacts of Winds on SO2 Concentrations in Bor, Serbia

Air pollution is one of the most important environmental problems in the town of Bor, situated in the eastern of Serbia. The main source of air pollution with sulphur dioxide, heavy metals and other toxic and carcinogenic elements present in particulate matter (PM) and aero sediments is the Copper Mining and Smelting Complex Bor. The distribution of air pollutants is mainly determined by the copper smelter operation mode, as well as by meteorological parameters such as wind speed and direction. While information on air pollution with heavy metals and carcinogenic elements in the form of PM has been monitored and reported for longer period, availability of data related to the relationship between air pollutants and meteorological parameters in the Republic of Serbia is still limited. In the present study, the relationships between daily mean concentrations of SO2 and the speed and wind direction were analysed. The analysis includes data collected in 2011 from the four monitoring stations (Park, Jugopetrol, Institute, and Brezonik) situated in a wider town area. Pearson correlation coefficients between daily average SO2 and daily average speed and direction of winds are calculated. High wind speed reduces SO2 concentration due to the dilution effect. Hence, correlations between SO2 and the speed and direction of winds at almost all monitoring stations were negative, with one exception (Jugopetrol). This could be explained by the fact that winds, blowing from the north-west (NW) direction, carry polluted air towards this station. Moderate negative correlation found between SO2 and wind direction at monitoring station Park. Generally, the observed correlations between SO2 and wind speed and direction are weak, due to frequent changes in SO2 emissions, wind speed and direction during the day

Towards widespread adoption of low cost air quality sensors - a necessity for effective calibration procedures

One of the most important factors for increasing usefulness and relevance of air pollution data on a personal level would certainly be an increase in its spatial resolution. Current state of affairs in air quality monitoring networks at state or local level is such that they typically provide a wealth of high resolution temporal data, but monitoring stations are on the other hand mainly located at a few strategically important places in urban area. This low spatial resolution is a big barrier towards providing personally relevant information to citizens which would then be able to answer questions such as: what is the level of air pollution on routes and places they frequent, what are the associated health risks, and finally what can they do about it and at what cost? Part of the solution to this complex puzzle may be in low-cost air quality sensors (LCS). LCS’s are an emerging technology and are now commercially available for gases, particulate matter and meteorological parameters in a wide variety of designs and capabilities. However, the data sets generated by devices composed of selected LCS are often of questionable data quality. There are some protocols for calibration LCS in laboratory and in the field, but such procedures are extensive and appropriate for testing performance only during sensor development, but are certainly not practically feasible for testing of each commercial LCS [1, 2]. Developing, optimizing, and refining experiments and statistical modelling techniques for LCS-AQ calibration and validation is the mandatory step on the route of obtaining reliable and meaningful data [3, 4]. This work elaborates an important part of LCS deployment – its effective calibration procedure. We will describe our current work on calibration procedures for sensors for gaseous pollutants: ozone and carbon monoxide and sensors for particulate matter. In validation campaigns described in this work we have used combination of quality checks and mid-level validation, together with several statistical modeling approaches in order to observe which sensors have desirable level of performance and to later derive calibration curves or more complex calibration models. Calibration models were based on simple linear regression (LR), multiple linear regression (MLR) and artificial neural networks (ANN). Mid-level validation of particulate matter low cost sensors was done via collocation with lab-grade instruments in laboratory office space in Institute Vinca and the results were collected for several weeks. Low cost instruments included two Sharp GP2Y1010AU0F compact optical dust sensors connected to Arduino platform (1 channel output), Alphasense CompactOPC sensor (16 channels from 0.38 to 17 μm) and Dylos DC1700 PM unit (2 channels corresponding to “large” and “small” particles). Lab grade instruments included TSI NanoScan SMPS Model 3910 and TSI Optical particle sizer 3330 (17 channels from 0.3um to 10um). Basic quality check of two Sharp sensors showed that they did not have malfunctions and are surprisingly reliable when used in combination with Arduino platform. Sharp sensors mutually correlate with correlation coefficient cc~0.98. In comparison with lab grade instruments, they correlate best with OPS first channel cc~0.75 and cc steadily declines for channels corresponding to larger particles. Dylos channels best correlate with OPS 0.5-0.721μm for “small” particles with cc~0.60, and with OPS 2.156 μm for “large” particles with cc~0.978. Best performing low cost sensor was certainly Alphasense OPC with cc over 0.90 for corresponding channels. Performed validation steps clearly show to which particulate matter size range individual sensor channels correspond, enabling one to derive meaningful calibration curves. LCS’s for gaseous pollutants were deployed within multi-sensor platform AQMesh. Platforms were collocated with Automatic Monitoring Station Stari Grad belonging to the State Network run by the Serbian Environmental Protection Agency (SEPA), in two 1-month periods in late summer and early autumn 2015. CO and O3 sensors in AQMesh platform passed low level validation (criteria was percentage of collected data), and were considered for development of calibration models. Choice of predictors for MLR and ANN models utilized both statistical reasoning and heuristics to avoid overfitting calibrated sensor with co-varying gas species. Improvements in sensor performance with sophisticated ANN models compared to LR were significant, resulting in relative residuals less than 15% for concentration of pollutant approximately ranging from 175 μg/m3 to 400 μg/m3 , while for O3 in the range from 40 μg/m3 to 120 μg/m3 .8th Symposium Chemistry and Environmental Protection : May 30 - June 1, Kruševac, 2018

The possible role of the surface active substances (SAS) in the airborne transmission of SARS-CoV-2

Surface active substances (SAS) have the potential to form films at different interfaces, consequently influencing the interfacial properties of atmospheric particulate matter (PM). They can be derived from both human activities and natural processes and can be found in an indoor and outdoor environment. This paper’s fundamental question is the possible role of the SAS in stabilizing respiratory aerosols in the closed space. In that context, we discuss results of preliminary measurements of the SAS and dissolved organic carbon (DOC) concentrations in the water-soluble fractions of PM2.5 and PM10 that were sampled simultaneously in primary school inside and outside of the building. The concentrations of SAS were determined using highly sensitive electrochemical measurements. It was observed that SAS and DOC concentrations have been enhanced indoor in both PM fractions. Consistent with these results, a discussion arises on the possibility that SAS could play a crucial role in respiratory droplet dispersion as stabilizers, especially in a closed space. At the same time, we assume that they could prolong the lifetime of respiratory aerosols and as well viability of some (possible SARS-CoV-2) virus inside of the droplets

Optimization of the source apportionment solution using the rotational tools in US EPA PMF 5.0 software

Positive matrix factorization (PMF) is a dimension reduction method used to model the covariance structures of observable variables in order to impel a smaller number of latent nonnegative factors. It resolves receptor modeling problem, which is based on the chemical mass balance equation (CMB) and may discover hidden patterns in the environmental data, where each extracted factor is accompanied by an actual source of emission. In this paper, PMF source apportionment analyses of fine aerosol fraction (PM2.5 mode) at Belgrade suburban background site, in 2016/17 year, have been performed by processing a data set of 130 PM2.5 mass concentrations and twenty-one elemental concentrations and soot concentrations in each PM2.5 sample (mode). The PM2.5 mass concentrations in collected samples have been determined following SRPS EN 12341:201 procedure, elemental concentrations were obtained by PIXE alanytical technique in the frame of the regional IAEA project, in the Institute of Nuclear Research, Hungarian Academy of Sciences, and soot concentrations were analyzed by smoke stain reflectometry in accordance with ISO 9835:1993 (E). The EPA PMF program ver 5.0, was used to solve the PMF model. Since the determination of an optimal PMF solution is a strongly heuristic procedure, there is a necessity of finding a more quantitative ways to reduce the arbitrariness of this technique. In order to reduce the range of possible solutions, we have analyzed how the values of model parameters changes as a function of the number of factors. PMF modeling was performed in a robust mode. For the purpose of finding the best fit solution wich minimize the object function Q, we varied the number of factors in the range from 4 to 8. Additionally, influence of rotations are also analyzed in iterative steps by varying FPEAK function in the range -1 to +1 with an increment of 0.5. Obtained results indicated significant role of Q/Qexp ratio analysis for optimal solution choice. In optimization process, number of factors with Q/Qexp ratio less than 1, were rejected as a possible solutions. This paper shows that optimization procedure should include examination of rotational matrix in which the rotational degree of freedom of solution is considered. Solutions with a steep change in their rotational degree of freedom were rejected. Finally, the additional improvement can be done by optimizing the parameters representing the scaled mean value (IM) and the scaled standard deviation (IS) of the each individual column in scaled residual matrix.IX International Conference on Radiation in Various Fields of Research : RAD 2021 : book of abstracts; June 14-18, 2021; Herceg Novi, Montenegr

Assessment and differentiation of light absorbing carbon in atmospheric aerosols

Light Absorbing Carbon (LAC) or Black carbon (BC) is one of the most important components of fine particulate matter (PM2.5), which is formed through the incomplete combustion of fossil fuels, biofuels and biomass. Based on a number of studies, it has been shown that carbonaceous particles significantly affect air quality/environment and they are an important factor in the carbon cycle and climate change. BC, as one of the constituents of carbonaceous respirable particles, has the property of absorbing light and leads to an increase in the annual average air temperature. Therefore, its quantitative analysis and differentiation for determination of potential radiative effects is extremely important. The BC concentration is usually determined by using thermal or optical methods. In this paper, the results of the application of multiwavelength optical technique for BC estimation which is based on measuring the intensity of absorption/transmission of light through samples of deposited aerosols on PTFE filters, are presented. Sample collection was conducted at Belgrade suburban background site, in heating and nonheating seasons, using low-volume air samplers. In order to estimate the BC concentration of different particle diameters, measurements were performed by using the MABI ANSTO instrument, with LEDs that emit light at seven different wavelengths: 405 nm, 465 nm, 525 nm, 639 nm, 870 nm, 940 nm and 1050nm. The measurement procedure is started by determination of the value of light transmission I0 through an unexposed or blank filter at different wavelengths. After sampling, the estimation of light transmission I through the exposed filters was performed. Before estimation of BC concentration, the light-absorbing coefficient (babs) at each wavelength was determined separately. More intense variations in the values of babs were observed, which most likely occur due to the change in the nature of the pollution sources at the sampling site. The accuracy of the BC concentration depends on the value of the mass absorption coefficient (ε) estimated experimentally and whose values are compared with the predefined manufacturer values. BC generated by combustion at lower temperatures is better absorbed at shorter wavelengths. On the other hand, BC generated through high-temperature processes is better absorbed in the infrared region of the electromagnetic spectrum. Therefore, the differences of BC concentrations at two boundary wavelengths: 405 nm and 1050 nm were analyzed. Finally, seasonal BC variations were observed, with increased values in the winter and autumn periods compared to the summer period.X JUBILEE International Conference on Radiation in Various Fields of Research : RAD 2022 (Spring Edition) : book of abstracts; June 13-17, 2022; Herceg Novi, Montenegr

PARTICULATE MATTER (PM10 AND PM2.5) CONCENTRATIONS IN NATURALLY VENTILATED OFFICES IN BOR, SERBIA

Monitoring of particulate matter (PM) mass concentrations in indoor air are important for human health risk assessments, since most of the individuals in developed countries spend the majority of their time indoors. The mass concentrations of particulate matter (PM10 and PM2.5 fractions) were measured in several naturally ventilated offices and hallway in the Mining and Metallurgy Institute Bor, Serbia. The measurements are carried out with a portable, direct reading, aerosol monitoring device Turnkey OSIRIS. Several sampling campaigns were conducted in the time interval from 2009 to 2014 in the six selected offices and in a hallway near the main entrance. The average daily mass concentrations of PM in the offices during the summer period (April – September) were 21.9 mg/m3 for PM10 and 8.4 mg/m3 for PM2.5. The average daily mass concentrations of PM in the offices during the winter period (October – March) were 20.3 mg/m3 for PM10 and 10.9 mg/m3 for PM2.5. The indoor air quality seems satisfactory with respect to the both observed fractions of PM. Particle monitor used in the study proved to be practical for PM measurements in the indoor environments, as it is portable and quiet enough not to disturb occupants in the offices

Application of the final flotation waste for obtaining the glass-ceramic materials

This work describes the investigation of the final flotation waste (FFW), originating from the RTB Bor Company (Serbia), as the main component for the production of glass-ceramic materials. The glass-ceramics was synthesized by the sintering of FFW, mixtures of FFW with basalt (10%, 20%, and 40%), and mixtures of FFW with tuff (20% and 40%). The sintering was conducted at the different temperatures and with the different time duration in order to find the optimal composition and conditions for crystallization. The increase of temperature, from 1100 to 1480°C, and sintering time, from 4 to 6h resulted in a higher content of hematite crystal in the obtained glass-ceramic (up to 44%). The glass-ceramics sintered from pure FFW (1080°C/36h) has good mechanical properties, such as high propagation speed (4500 m/s) and hardness (10800 MPa), as well as very good thermal stability. The glass-ceramics obtained from mixtures shows weaker mechanical properties compared to that obtained from pure FFW. The mixtures of FFW with tuff have a significantly lower bulk density compared to other obtained glass-ceramics. Our results indicate that FFW can be applied as a basis for obtaining the construction materials

Evaluation of black carbon in fine atmospheric particulate matter on various filter types by multi-wavelength light absorption technique

Besides the evident harmful impact to human health, black carbon (BC) is considered as second important contributor to climate change due to its sunlight absorption and warming effects. It is a major component of fine atmospheric particulate matter emitted during the incomplete combustion of fossil fuels and biomass burning emissions from both natural and anthropogenic sources. Atmospheric carbon was recognized in forms of soot, black carbon, elemental carbon, inorganic carbon, organic carbon, brown carbon, etc, depending on the origin and absorption characteristics. Measurement methodologies for BC analysis in aerosol samples are mostly based on optical and thermal properties of carbon species. Here are presented results of the application of the optical analytical technique which relies on the multi-wavelenght light attenuation by black carbon component of fine particulate matter deposited on filter media. For that purpose, standard polytetrafluoroethylene (PTFE), quartz and carbon nanotube filters with different qualitative features and pore diameters were exposed to fine aerosol fraction at urban background monitoring site in heating and non heating seasons, using low-volume air samplers with 2.3 m3/h air flow. A multi wavelength absorption black carbon instrument (MABI) with 405 nm, 465 nm, 525 nm, 639 nm, 870 nm, 940 nm and 1050 nm LEDs was used for blank and exposed filters analysis and black carbon evaluation. Differences in obtained BC values are discussed in relation to various absorption potential of different filter media, taking into account absorption coefficients dependence on the wavelength and density. Main advantage of this method is simplicity and complementarity with nondestructive nuclear analytical techniques (EDXRF, PIXE) for elemental analysis of fine aerosol fraction on specific filter media. Differentiation between black carbon coming from fossil fuels combustion and from biomass burning sources would be additional information valuable for source apportionment analysis using positive matrix factorization and reliable discussion of air pollution observed at selected receptor site.IX International Conference on Radiation in Various Fields of Research : RAD 2021 : book of abstracts; June 14-18, 2021; Herceg Novi, Montenegr