•PNC and PNSD in transportation environments were studied.•Highest urban PNC are found close to road traffic, regardless of the commuting mode.•Lack of studies in harbors, inside airplanes, trains ...and specific commuting modes.•Need of harmonization of measurements, especially at lower detection particle sizes.•A reduction of road traffic emissions is necessary to minimize the exposure to UFP.
Ambient air ultrafine particles (UFP, particles with a diameter <100 nm) have gained significant attention in World Health Organization (WHO) air quality guidelines and European legislation. This review explores UFP concentrations and particle number size distributions (PNC-PNSD) in various transportation hotspots, including road traffic, airports, harbors, trains, and urban commuting modes (walking, cycling, bus, tram, and subway). The results highlight the lack of information on personal exposure at harbors and railway stations, inside airplanes and trains, and during various other commuting modes. The different lower particle size limits of the reviewed measurements complicate direct comparisons between them. Emphasizing the use of instruments with detection limits ≤10 nm, this review underscores the necessity of following standardized UFP measurement protocols.
Road traffic sites are shown to exhibit the highest PNC within cities, with PNC and PNSD in commuting modes driven by the proximity to road traffic and weather conditions. In closed environments, such as cars, buses, and trams, increased external air infiltration for ventilation correlates with elevated PNC and a shift in PNSD toward smaller diameters. Airports exhibit particularly elevated PNCs near runways, raising potential concerns about occupational exposure. Recommendations from this study include maintaining a substantial distance between road traffic and other commuting modes, integrating air filtration into ventilation systems, implementing low-emission zones, and advocating for a general reduction in road traffic to minimize daily UFP exposure. Our findings provide important insights for policy assessments and underscore the need for additional research to address current knowledge gaps.
We review the major features of desert dust outbreaks that are relevant to the assessment of dust impacts upon human health. Our ultimate goal is to provide scientific guidance for the acquisition of ...relevant population exposure information for epidemiological studies tackling the short and long term health effects of desert dust. We first describe the source regions and the typical levels of dust particles in regions close and far away from the source areas, along with their size, composition, and bio-aerosol load. We then describe the processes by which dust may become mixed with anthropogenic particulate matter (PM) and/or alter its load in receptor areas. Short term health effects are found during desert dust episodes in different regions of the world, but in a number of cases the results differ when it comes to associate the effects to the bulk PM, the desert dust-PM, or non-desert dust-PM. These differences are likely due to the different monitoring strategies applied in the epidemiological studies, and to the differences on atmospheric and emission (natural and anthropogenic) patterns of desert dust around the world. We finally propose methods to allow the discrimination of health effects by PM fraction during dust outbreaks, and a strategy to implement desert dust alert and monitoring systems for health studies and air quality management.
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•We discuss on exposure relevant dust and meteorological patterns relevant to epidemiological studies.•We suggest evaluating health effects for mineral dust and anthropogenic PM during the episodes, as well as bulk PM.•Short term health effects of desert dust in different world regions might be differently associated with these PM types.•A harmonized way of evaluating these health effects is needed to compare results from different regions.•A strategy to monitor these PM components and to implement desert dust alert systems for health studies is presented.
Proximity to road traffic involves higher health risks because of atmospheric pollutants. In addition to outdoor air, indoor air quality contributes to overall exposure. In the framework of the ...BREATHE study, indoor and outdoor air pollution was assessed in 39 schools in Barcelona. The study quantifies indoor and outdoor air quality during school hours of the BREATHE schools. High levels of fine particles (PM2.5), nitrogen dioxide (NO2), equivalent black carbon (EBC), ultrafine particle (UFP) number concentration and road traffic related trace metals were detected in school playgrounds and indoor environments. PM2.5 almost doubled (factor of 1.7) the usual urban background (UB) levels reported for Barcelona owing to high school-sourced PM2.5 contributions: 1 an indoor-generated source characterised mainly by organic carbon (OC) from organic textile fibres, cooking and other organic emissions, and by calcium and strontium (chalk dust) and; 2 mineral elements from sand-filled playgrounds, detected both indoors and outdoors. The levels of mineral elements are unusually high in PM2.5 because of the breakdown of mineral particles during playground activities. Moreover, anthropogenic PM components (such as OC and arsenic) are dry/wet deposited in this mineral matter. Therefore, PM2.5 cannot be considered a good tracer of traffic emissions in schools despite being influenced by them. On the other hand, outdoor NO2, EBC, UFP, and antimony appear to be good indicators of traffic emissions. The concentrations of NO2 are 1.2 times higher at schools than UB, suggesting the proximity of some schools to road traffic. Indoor levels of these traffic-sourced pollutants are very similar to those detected outdoors, indicating easy penetration of atmospheric pollutants. Spatial variation shows higher levels of EBC, NO2, UFP and, partially, PM2.5 in schools in the centre than in the outskirts of Barcelona, highlighting the influence of traffic emissions. Mean child exposure to pollutants in schools in Barcelona attains intermediate levels between UB and traffic stations.
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•39 schools in Barcelona monitored (indoor and outdoor) for air quality assessment.•Higher levels of traffic pollutants at schools than at urban background station.•OC, Ca & Sr are mainly school sourced: organic emissions, textile fibres and chalk.•Mineral matter (mixed with urban pollutants) is resuspended by children activities.•BC, NO2, UFP & few metals good traffic tracers but not PM2.5 due to school sources.
Road dust resuspension is one of the main sources of particulate matter with impacts on air quality, health and climate. With the aim of characterising the thoracic fraction, a portable resuspension ...chamber was used to collect road dust from five main roads in Oporto and an urban tunnel in Braga, north of Portugal. The PM10 samples were analysed for: i) carbonates by acidification and quantification of the evolved CO2, ii) carbonaceous content (OC and EC) by a thermo-optical technique, iii) elemental composition by ICP-MS and ICP-AES after acid digestion, and iv) organic speciation by GC–MS. Dust loadings of 0.48±0.39mgPM10m−2 were obtained for asphalt paved roads. A much higher mean value was achieved in a cobbled pavement (50mgPM10m−2). In general, carbonates were not detected in PM10. OC and EC accounted for PM10 mass fractions up to 11% and 5%, respectively. Metal oxides accounted for 29±7.5% of the PM10 mass from the asphalt paved roads and 73% in samples from the cobbled street. Crustal and anthropogenic elements, associated with tyre and brake wear, dominated the inorganic fraction. PM10 comprised hundreds of organic constituents, including hopanoids, n-alkanes and other aliphatics, polycyclic aromatic hydrocarbons (PAH), alcohols, sterols, various types of acids, glycerol derivatives, lactones, sugars and derivatives, phenolic compounds and plasticizers. In samples from the cobbled street, these organic classes represented only 439μgg−1PM10, while for other pavements mass fractions up to 65mgg−1PM10 were obtained. Except for the cobbled street, on average, about 40% of the analysed organic fraction was composed of plasticizers. Although the risk via inhalation of PAH was found to be insignificant, the PM10 from some roads can contribute to an estimated excess of 332 to 2183 per million new cancer cases in adults exposed via ingestion and dermal contact.
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•Dust loadings<1mgPM10m−2 were obtained for asphalt paved roads.•These values are lower than those reported for other cities.•Dust loadings about 50 times higher were found for a cobbled pavement.•OC & EC accounted for small PM10 mass fractions, while inorganic components dominate.•OC comprised hundreds of organic constituents; plasticizers were the most abundant.
•A dataset of 370 CTG signals has been collected in clinical environment.•A custom-made automatic software was used to extract 17 features from the CTGs.•J48, RF, GBT, ADA-B of J48 and decorate were ...used to classify patients according to their delivery.•The procedures of 10 folds cross-validation and SMOTE were also applied.•Several evaluation metrics were computed for comparing the algorithms.
Cardiotocography (CTG) is the most employed methodology to monitor the foetus in the prenatal phase. Since the evaluation of CTG is often visual, and hence qualitative and too subjective, some automated methods have been introduced for its assessment.
In this paper, a custom-made software is exploited to extract 17 features from the available CTG. A preliminary univariate statistical analysis is performed; then, five machine learning algorithms, exploiting ensemble learning, were implemented (J48, Random Forests (RF), Ada-boosting of decision tree (ADA-B), Gradient Boosting and Decorate) through Knime analytics platform to classify patients according to their delivery: vaginal or caesarean section. The dataset is composed by 370 signals collected between 2000 and 2009 in both public and private hospitals. The performance of the algorithms was evaluated using 10 folds cross validation with different evaluation metrics: accuracy, precision, sensitivity, specificity, area under the curve receiver operating characteristic (AUCROC).
While only two features were significantly different (gestation week and power expressed by the high frequency band of FHR power spectrum), from the statistical point of view, machine learning results were great. The RF obtained the best results: accuracy (91.1%), sensitivity (90.0%) and AUCROC (96.7%). The ADA-B achieved the highest precision (92.6%) and specificity (93.1%). As expected, the lowest scores were obtained by J48 that was the base classifier employed in all the others empowered implementations. Excluding the J48 results, the AUCROC of all the algorithms was greater than 94.9%.
In the light of the obtained results, that are greater than those ones found in the literature from comparable researches, it can be stated that the machine learning approach can actually help the physicians in their decision process when evaluating the foetal well-being.
Sufficient conditions for the finite-time stability (FTS) of impulsive dynamical linear systems (IDLSs) have been provided in Amato, Ambrosino, Cosentino, and De Tommasi (2011). In this brief note ...we show that, when time-dependent IDLSs are dealt with, the sufficient condition for FTS derived in Amato, Ambrosino, Cosentino et al. (2011) is also necessary. Moreover, an alternative necessary and sufficient condition for FTS is proposed, which is based on the solution of a coupled differential–difference Lyapunov equation. This condition turns out to be more efficient from the computational point of view. The proposed approach is illustrated through some examples.
Hourly-resolved aerosol chemical speciation data can be a highly powerful tool to determine the source origin of atmospheric pollutants in urban environments. Aerosol mass concentrations of seventeen ...elements (Na, Mg, Al, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Sr and Pb) were obtained by time (1 h) and size (PM2.5 particulate matter < 2.5 μm) resolved aerosol samples analysed by Particle Induced X-ray Emission (PIXE) measurements. In the Marie Curie European Union framework of SAPUSS (Solving Aerosol Problems by Using Synergistic Strategies), the approach used is the simultaneous sampling at two monitoring sites in Barcelona (Spain) during September-October 2010: an urban background site (UB) and a street canyon traffic road site (RS). Elements related to primary non-exhaust traffic emission (Fe, Cu), dust resuspension (Ca) and anthropogenic Cl were found enhanced at the RS, whereas industrial related trace metals (Zn, Pb, Mn) were found at higher concentrations at the more ventilated UB site. When receptor modelling was performed with positive matrix factorization (PMF), nine different aerosol sources were identified at both sites: three types of regional aerosols (regional sulphate (S) - 27%, biomass burning (K) - 5%, sea salt (Na-Mg) - 17%), three types of dust aerosols (soil dust (Al-Ti) - 17%, urban crustal dust (Ca) - 6%, and primary traffic non-exhaust brake dust (Fe-Cu) - 7%), and three types of industrial aerosol plumes-like events (shipping oil combustion (V-Ni) - 17%, industrial smelters (Zn-Mn) - 3%, and industrial combustion (Pb-Cl) - 5%, percentages presented are average source contributions to the total elemental mass measured). The validity of the PMF solution of the PIXE data is supported by very good correlations with external single particle mass spectrometry measurements. Some important conclusions can be drawn about the PM2.5 mass fraction simultaneously measured at the UB and RS sites: (1) the regional aerosol sources impact both monitoring sites at similar concentrations regardless their different ventilation conditions; (2) by contrast, local industrial aerosol plumes associated with shipping oil combustion and smelters activities have a higher impact on the more ventilated UB site; (3) a unique source of Pb-Cl (associated with combustion emissions) is found to be the major (82%) source of fine Cl in the urban agglomerate; (4) the mean diurnal variation of PM2.5 primary traffic non-exhaust brake dust (Fe-Cu) suggests that this source is mainly emitted and not resuspended, whereas PM2.5 urban dust (Ca) is found mainly resuspended by both traffic vortex and sea breeze; (5) urban dust (Ca) is found the aerosol source most affected by land wetness, reduced by a factor of eight during rainy days and suggesting that wet roads may be a solution for reducing urban dust concentrations.
Despite their importance, current scientific knowledge on non-exhaust emissions by road traffic is scarce, severely hampering a reliable description of these particles in atmospheric dispersion ...models. Consequently, it is still very difficult to convincingly evaluate population exposure to traffic-related components in large cities, especially given the significant variation in traffic-related air pollution concentrations on a small scale (e.g. within 100–1000 m of a busy road). One factor contributing to this uncertainty is the lack of a reliable emission estimate for vehicular non-exhaust emissions. Emissions vary from location to location due to the impact of climate, road surface characteristics and traffic conditions, but the geographical coverage for which Emission Factors are available and the amount of knowledge regarding the variability within a city environment are very limited.
The present study investigates the spatial and chemical properties of the strength of the emission source (road dust particles below 10 μm) in three contrasting European urban environments: two Spanish cities (Barcelona and Girona), and a Swiss city (Zürich). Loadings of road dust <10 μm from the 8 sites sampled in Zürich ranged from 0.2 to 1.3 mg m
−2, the lowest loadings of the study. The minimum loadings in Girona (Spain) were as high as the maximum in Zürich, with a range of 1.3–7.1 mg m
−2. By far the most polluted site in terms of road dust <10 μm mass loading is Barcelona (Spain), where a range of 3.7–23.1 mg m
−2 was recorded in the city center samples. Four main sources were found to drive the variability of road dust particles <10 μm: Mineral (road wear and urban dust generated mostly by construction emissions), Motor Exhaust, Brake wear and Tire wear. Road wear/Mineral is the dominating source in Spanish cities (∼60%), but represents only 30% of road dust loadings in Zürich where contributions are more equally distributed among the four main sources of road dust. Regardless of the city categories loadings of OC, EC, Fe, Cr, Mn, Cu, Zn, Mo, Sn, Sb, Cs, Ba, W, Pb and Bi (μg m
−2) increase by a factor of 1.2–2.2, from streets with <15 kveh to streets with 15–40 kveh day
−1. At highly trafficked sites (>40 kveh day
−1) loadings were again increasing by a further factor of 2.6–10.1. Finally, agreement was found between the composition of sampled materials and the composition (available from literature) of PM10 material emitted by vehicles via resuspension (both in Zürich and Barcelona). This permitted to find a relationship, potentially able to calculate emission factors from known amount of deposited pollutants in those cities/environment where no real-world EFs are available from literature.
► In this study we investigate loadings and sources of inhalable (<10 μm) road dust particles, in three European cities. ► Dry Mediterranean cities showed higher particles loadings with respect to a Central European city. ► The road wear/Mineral source was found to be dominant in Spanish cities. ► In the Swiss city contributions from different sources are similar. ► Loadings of OC, EC, Fe, Cr, Mn, Cu, Zn, Mo, Sn, Sb, Cs, Ba, W, Pb and Bi were found to increase with traffic intensity.
Children spend a third of their day in the classroom, where air pollution levels may differ substantially from those outdoors due to specific indoor sources. Air pollution exposure assessments based ...on atmospheric particle mass measured outdoors may therefore have little to do with the daily PM dose received by school children. This study aims to investigate outdoor and indoor sources of PM2.5 measured at 39 primary schools in Barcelona during 2012. On average 47% of indoor PM2.5 measured concentrations was found to be generated indoors due to continuous resuspension of soil particles (13%) and a mixed source (34%) comprising organic (skin flakes, clothes fibers, possible condensation of VOCs) and Ca-rich particles (from chalk and building deterioration). Emissions from seven outdoor sources penetrated easily indoors being responsible for the remaining 53% of measured PM2.5 indoors. Unpaved playgrounds were found to increase mineral contributions in classrooms by 5–6μg/m3 on average with respect to schools with paved playgrounds. Weekday traffic contributions varied considerably across Barcelona within ranges of 1–14μg/m3 outdoor and 1–10μg/m3 indoor. Indoors, traffic contributions were significantly higher (more than twofold) for classrooms with windows oriented directly to the street, rather than to the interior of the block or to playgrounds. This highlights the importance of urban planning in order to reduce children’s exposure to traffic emissions.
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•We collected PM2.5 samples at indoor and outdoor environments of 39 primary schools.•Seven outdoor sources and two children-activity-related sources were identified.•In classrooms, 47% of PM2.5 was indoor generated, mostly organics.•Unpaved playgrounds increased PM concentrations in classrooms by 5–6μg/m3.•Traffic contributions were higher at classrooms with windows oriented directly to the street.
In this note, we consider the finite-time stabilization of discrete-time linear systems subject to disturbances generated by an exosystem. Finite-time stability can be used in all those applications ...where large values of the state should not be attained, for instance in the presence of saturations. The main result provided in the note is a sufficient condition for finite-time stabilization via state feedback. This result is then used to find some sufficient conditions for the existence of an output feedback controller guaranteeing finite-time stability. All the conditions are then reduced to feasibility problems involving linear matrix inequalities (LMIs). Some numerical examples are presented to illustrate the proposed methodology.