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    Can low-cost sensors (LCS) enhance air quality monitoring for personal pollution exposure assessment?

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    Laboratory and field assessments of low-cost sensors (LCS) are essential for ensuring the accuracy of PM2.5 measurements collected by citizens in air quality campaigns. Evaluation of Sensirion SPS30 (LCS SPS30) in controlled laboratory setting showed a coefficient of determination (R2) ranging from 0.81–0.99 and a root mean square error (RMSE) from 0.81–61.72 μg m−3, at average concentration of 21.5 μg m−3. In contrast, co-location assessment at an average concentration of 9 μg m−3 resulted in R2 of 0.5 and a RMSE of 6.82 μg m−3. The results demonstrated that the sensor met micro-environmental monitoring standards (accuracy 0.7) only at relative humidity (RH) levels below 60%, emphasising its strong sensitivity to RH and the need for RH-dependent data corrections. The observed underestimation or overestimation of PM2.5 readings was primarily attributed to variations in particle composition and concentration. Despite accuracy variations, LCSs can effectively capture spatiotemporal urban air quality patterns and identify pollution hotspots in community monitoring, particularly in low-pollution environments. In a citizen-led PM2.5 monitoring campaign in Maribor, Slovenia, the lowest concentrations were recorded at 15:00 (2.9 μg m−3), while the highest occurred during the morning rush-hour (4.8 μg m−3), likely attributed to the planetary boundary layer’s impact on atmospheric particulate dispersion. Spatial analysis revealed that hotspots clustered near intersections, where vehicle waiting time is the longest

    Študij TIG dodajalne tehnologije na Al zlitini tipa 4043

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    Poročilo o preskusu št.: LVG 2025-169

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    Comparing methods for determining the CO2 content in CO2-Sequestering materials and natural rock

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    Carbon capture plays an important role in the decarbonation of the building sector. One way to capture carbon is through mineral carbonation, in which Ca and Mg compounds react with CO2 to form stable carbonate minerals such as calcite, dolomite, magnesite and/or siderite, permanently sequestering CO2. Various techniques are available to measure the amount of permanently bound CO2 and quantify the carbonation potential. The suitability and accuracy of a particular method are very important, as the accurate determination of CO2 is crucial to correctly assess the sequestration potential of different materials. This study compares the three methods: calcimetric, gravimetric and thermogravimetric analysis used for CO2 determination in different types of ash, slag and natural rock. While the CO2 content in natural rock is stable, the CO2 content in slag and ash can change over time as the contained minerals gradually absorb CO2 (by natural or accelerated carbonation) until they are fully carbonated. To avoid errors in testing the CO2 uptake, as-received samples were first exposed to the full carbonation process and then tested. The comparison of calcimeter, thermogravimetric and gravimetric analysis of ground and sieved samples with a particle size below 125 μm shows that the results usually differ by less than 2 %. Higher deviations could be caused by non-carbonate minerals (especially in slags) that can react with hydrochloric acid during the calcimetric and gravimetric tests and/or decompose in the range where carbonates decompose, contributing to inaccurate CO2 measurements. The measurement uncertainty was calculated for all three quantitative methods to allow a practical comparability

    Weighted Padovan graphs

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    Weighted Padovan graphs PhiknPhi^{n}_{k}, ngeq1n geq 1, lfloorfracn2rfloorleqkleqlfloorfrac2n23rfloorlfloor frac{n}{2} rfloor leq k leq lfloor frac{2n-2}{3} rfloor, are introduced as the graphs whose vertices are all Padovan words of length nn with kk 11s, two vertices being adjacent if one can be obtained from the other by replacing exactly one 0101 with a 1010. By definition, sumkV(Phikn)=Pn+2sum_k |V(Phi^{n}_{k})|=P_{n+2}, where PnP_n is the nnth Padovan number. Two families of graphs isomorphic to weighted Padovan graphs are presented. The order, the size, the degree, the diameter, the cube polynomial, and the automorphism group of weighted Padovan graphs are determined. It is also proved that they are median graphs

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