Search the repository

A+ | A- | | SLO | ENG

Abstract: Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.
Keywords: particulate matter, PM2.5, air quality, low-cost sensors, optical particle counter
Published in RUNG: 10.05.2024; Views: 12; Downloads: 0
Link to file
This document has many files! More...

Abstract: Abstract. Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected “true” values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here, especially in periods between seasons. The results of this multi-site comparison coincide with the synthetic dataset in terms of rolling–seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the results of this study provide solid evidence of the robustness of both methods and of the overall efficiency of the recently proposed rolling PMF approach.
Keywords: particulate matter, synthetic dataset comparison, source apportionment, organic aerosols
Published in RUNG: 10.05.2024; Views: 12; Downloads: 0
Full text (2,03 MB)
This document has many files! More...

Keywords: multi-time resolution, source apportionment, submicronic particulate matter, positive matrix factorisation, PMF, multilinear engine, SoFi, ME2, organic sources, metals
Published in RUNG: 24.10.2023; Views: 754; Downloads: 6
Full text (3,23 MB)
This document has many files! More...

Abstract: Household dust (HD) and road dust (RD) are widespread and easily accessible urban sediments, which are influenced by deposition of airborne particulate matter (PM). Since airborne PM is considered to be one of the most important pollutants in urban areas, with significant adverse effects on human health, a better understanding of its elemental composition and dispersion mechanisms is needed. The present study examines whether the HD and RD elemental composition can be used as a quick alternative method for the determination of corresponding PM elemental composition over a selected area. In summer 2016, HD, RD, and topsoil samples were collected from 249 sampling locations distributed across rural, urban, and industrial areas in Slovenia. The collected samples were sieved for particle diameters below 63 μm and analysed for 53 elements with ICP-MS after aqua regia digestion. SEM/EDS analyses were applied for the determination of characteristic particles at the microlevel. Finally, the elemental composition of HD and RD was compared with the PM10 elemental composition obtained from National Network for Ambient Air Quality Monitoring governed by Slovenian Environmental Agency (ARSO) to determine any potential connection between them. The results show that HD and RD are considerably enriched with a large set of elements compared to the topsoil. Correlations and factor analyses show that spatial distribution of factor scores in RD revealed strong regional trends, connected with soil resuspension (Al, Ce, Ga, K, La, Li, P, Rb, Sc and Y) or with anthropogenic sources such as traffic (Ag, Bi, Cu, Sb and Sn), steel mill emissions (Cr, Mo, Mn, Ni and W) and construction material decomposition (Ca and Sr). In contrast, HD elemental composition was highly variable between sampling locations. Variability was probably caused by indoor sources, such as smoking (Ce and La), biomass combustion (K, P and Rb), construction material decomposition (Ca and Sr) and residents’ professional occupation: dental care employees (Ag, Au, Pd) and employees in the metal-processing industry (Cr, Mo, Ni). Among deposited particles in RD, urbanization processes, such as fossil fuel combustion and traffic emissions, including brake pad abrasion and tyre wear, contributed the largest share of particles with anomalous elemental composition. Brake pad abrasion, for instance, contributed Ba-, Cu-, Sn-, and Zn-enriched irregular, angular and tabular particles, while tyre wear produced elongated rubber particles with traces of Ba, Cu, and Zn. RD from urban areas showed significantly higher elemental levels of Ag, Bi, Ca, Cd, Cr, Cu, Hg, Fe, Mo, Nb, Pb, Pt, Sb, Sn, Sr, Ti, Zn, and W in comparison to the rural environment, indicating the strong impact of urbanization on RD elemental composition. Another important anthropogenic source of deposited particles in RD were steel mills. Strong anomalies of Cr, Mo and Ni were detected in their vicinity. Their elemental levels decreased with distancing from the plan location, reaching urban background levels between 15 and 20 km from the mills. SEM/EDS analyses identified enrichments of Cr, Mn, Mo, Ni, V, and W in spherical particles and particles with partially melted surfaces, which were found only in the proximity of steel mills, indicating their influence of the PM deposition. Comparison of RD and the corresponding PM10 elemental composition showed that the RD fraction with particle diameters below 63 μm reflects PM10 elemental composition for the last 30 to 90 days for Cr, Cu, Mo and Zn and can be used as a predictor for PM10 elemental levels. This is not true for HD, as indoor particle sources prevail over the deposition of ambient PM10.
Keywords: household dust, road dust, particulate matter, PM10, pollution, Slovenia, steel mills, topsoil, traffic, urbanization
Published in RUNG: 02.12.2020; Views: 3769; Downloads: 186
Full text (17,40 MB)