Physical Properties and Lung Deposition of Particles Emitted from Five Major Indoor Sources

The physical properties of indoor particles were measured with an Scanning Mobility Particle Sizer (SMPS) system (14.6–850 nm), an Aerodynamic Particle Sizer (APS, 0.54–18 μm) and an Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) in an apartment located in an urban background site in Prague (Czech Republic) from 15 August to 8 September, 2014. The total particle maximum number concentration was 9.38 × 10(4), 1.46 × 10(5), 2.89 × 10(4), 2.25 × 10(5) and 1.57 × 10(6) particles cm(−3) for particles released from vacuum cleaning, soap/W5 cleaning spray, smoking, incense burning and cooking (frying) activities, respectively. Particles emitted from cleaning activities showed unimodal number size distributions, with the majority of particles (>98.2 %) in the ultrafine size range (Dp <100 nm) and modes at a diameter of 19.8 nm for vacuum cleaning and 30.6 nm for soap/W5 cleaning. Smoking and incense burning predominantly generated particles in the accumulation mode with a count median diameter around 90–150 nm while cooking emissions showed a bimodal structure with a main mode at 47.8 nm. Particles from vacuum cleaning, incense burning, smoking and cooking emissions were found to be “nearly hydrophobic” with an average growth factor (G(f)) around 1.01–1.10, while particles emitted from desk cleaning using organic compounds were found to be “less-hygroscopic” (G(f) ∼1.12–1.16). Based on an adjusted MPPD model with a consideration of the hygroscopic properties of particles, the total lung deposition fractions of these particles by number when they penetrate into the human lung were 0.73 ± 0.02, 0.62 ± 0.03, 0.37 ± 0.03, 0.32 ± 0.03 and 0.49 ± 0.02 for vacuum cleaning, desk cleaning, smoking, incense burning and cooking, respectively

Number Concentrations and Modal Structure of Indoor/Outdoor Fine Particles in Four European Cities

Indoor/outdoor aerosol size distribution was measured in four European cities (Oslo-Norway, Prague-Czech Republic, Milan-Italy and Athens-Greece) during 2002 in order to examine the differences in the characteristics of the indoor/outdoor modal structure and to evaluate the effect of indoor sources to the aerosol size distributions. All the measurement sites were naturally ventilated and were occupied during the campaigns by permanent residents or for certain time periods by the technical staff responsible for the instrumentation. Outdoor particle number (PN) concentrations presented the higher values in Milan and Athens (median values 1.4 x 10(4) # cm(-3) and 2.9 x 10(4) # cm(-3) respectively) as a result of elevated outdoor emissions and led to correspondingly higher indoor values compared to Oslo and Prague. In absence of indoor activities, the indoor concentrations followed the fluctuations of the outdoor concentrations in all the measurement sites. Indoor activities (cooking, smoking, etc.) resulted in elevated indoor PN concentrations (maximum values ranging between 1.7 x 10(5) # cm(-3) and 3.2 x 10(5) # cm(-3)) and to I/O ratios higher than one. The I/O ratios were size dependant and for periods without indoor activities, they presented the lowest values for particles <50 nm (0.51 +/- 0.15) and the ratios increased with fine particle size (0.79 +/- 0.12 for particles between 100-200 nm). The analysis of the modal structure showed that the indoor aerosol size distribution characteristics differ from the outdoors under the effect of indoor sources. The percentage of unimodal size distributions increased during indoor emissions, compared to periods without indoor sources, along with the number concentration of Aitken mode particles, indicating emissions in specific size ranges according to the type of the indoor source.Peer reviewe

Lung-depositing surface area (LDSA) of particles in office spaces around Europe : Size distributions, I/O-ratios and infiltration

Air pollution, and specifically particulate matter pollution, is one of the greatest dangers to human health. Outdoor air pollution ranks third in causes for premature death. Improving indoor air quality is of immense importance, as the time spent indoors is often much greater than the time spent outdoors. In this experimental study, we evaluate the levels of particle pollution in indoor air in four offices across Europe, compare the indoor particles to outdoor particles and assess where the particles originate from. The measurements were conducted with an Electrical Low-Pressure Impactor (ELPI+) for particles between 6 nm and 1 μm. The chosen metric, lung-deposited particle surface area (LDSA), targets the health impacts of particle pollution. Based on the measurements, we determined that most of the indoor air particles infiltrated from outdoor air, although two of the offices had very limited indoor activity during the measurement campaigns and may not represent typical use. The highest median indoor LDSA concentration during daytime hours was 27.2 μm2/cm3, whereas the lowest was 2.8 μm2/cm3. Indoor air in general had lower LDSA concentrations than outdoor air, the corresponding outdoor LDSA concentrations being 35.8 μm2/cm3 and 9.8 μm2/cm3. The particle size ranges which contributed to the highest concentrations were 50–100 nm and 300–500 nm. These size ranges correspond to soot mode and accumulation mode particles, which represent local and regional sources, respectively. Based on this study, limiting particle infiltration is the key factor in keeping indoor air in offices free of lung-depositing particles.Peer reviewe

New particle formation event detection with convolutional neural networks

New aerosol particle formation (NPF) events play a significant role in altering aerosol concentrations and dispersion within the atmosphere, making them vital for both climate and air quality research. The primary objective of investigating NPF events is to precisely determine their occurrence dates. In this study, we introduced the ConvNeXt model for the first time to identify NPF events, and compared its performance with two other deep learning models, EfficientNet and Swin Transformer. Our main aim was to automate an objective identification and classification of NPF events accurately. All three models employed transfer learning to effectively capture critical features associated with NPF. Our results demonstrated that the ConvNeXt model significantly outperformed the other models, achieving an impressive accuracy rate of 95.3% on event days, surpassing EfficientNet (92.8%) and Swin Transformer (94.9%). Furthermore, we performed tests using different ConvNeXt variants (ConvNeXt-T/S/B/L/XL) and different pre-training weights, revealing that different configurations of ConvNeXt models exhibited improved NPF event recognition capabilities. Finally, we conducted generalizability experiments using the ConvNeXt-XL model, achieving the highest accuracy of 96.4% on event days. This study not only underscores the recognition prowess of ConvNeXt models but also highlights their practical utility in accurately detecting NPF events in real-world scenarios. This contribution aids in advancing our comprehension of aerosol dynamics in atmospheric environments, providing valuable insights for climate and air quality research.This study is supported by the RI-URBANS project (Research Infrastructures Services Reinforcing Air Quality Monitoring Capacities in European Urban & Industrial Areas, European Union's Horizon 2020 research and innovation program, Green Deal, European Commission, contract 101036245). This study is also supported by National Natural Science Foundation of China (42101470, 72242106), and Xinjiang Uygur Autonomous Region (2023D01A57), a grant from State Key Laboratory of Resources and Environmental Information System, in part by the Chunhui Project Foundation of the Education Department of China (HZKY20220053), and by the Hungarian Research, Development and Innovation Office (K132254). M. Savadkoohi would like to thank the Spanish Ministry of Science and Innovation for her FPI grant (PRE-2020-095498) and the support from “Agencia Estatal de Investigaci'on” from the Spanish Ministry of Science and Innovation under the project CAIAC (PID2019-108990RB-I00).Peer reviewe

Seasonality of the particle number concentration and size distribution : a global analysis retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories

Aerosol particles are a complex component of the atmospheric system which influence climate directly by interacting with solar radiation, and indirectly by contributing to cloud formation. The variety of their sources, as well as the multiple transformations they may undergo during their transport (including wet and dry deposition), result in significant spatial and temporal variability of their properties. Documenting this variability is essential to provide a proper representation of aerosols and cloud condensation nuclei (CCN) in climate models. Using measurements conducted in 2016 or 2017 at 62 ground-based stations around the world, this study provides the most up-to-date picture of the spatial distribution of particle number concentration (N-tot) and number size distribution (PNSD, from 39 sites). A sensitivity study was first performed to assess the impact of data availability on N-tot's annual and seasonal statistics, as well as on the analysis of its diel cycle. Thresholds of 50% and 60% were set at the seasonal and annual scale, respectively, for the study of the corresponding statistics, and a slightly higher coverage (75 %) was required to document the diel cycle. Although some observations are common to a majority of sites, the variety of environments characterizing these stations made it possible to highlight contrasting findings, which, among other factors, seem to be significantly related to the level of anthropogenic influence. The concentrations measured at polar sites are the lowest (similar to 10(2) cm(-3)) and show a clear seasonality, which is also visible in the shape of the PNSD, while diel cycles are in general less evident, due notably to the absence of a regular day-night cycle in some seasons. In contrast, the concentrations characteristic of urban environments are the highest (similar to 10(3)-10(4) cm(-3)) and do not show pronounced seasonal variations, whereas diel cycles tend to be very regular over the year at these stations. The remaining sites, including mountain and non-urban continental and coastal stations, do not exhibit as obvious common behaviour as polar and urban sites and display, on average, intermediate N-tot (similar to 10(2)-10(3) cm(-3)). Particle concentrations measured at mountain sites, however, are generally lower compared to nearby lowland sites, and tend to exhibit somewhat more pronounced seasonal variations as a likely result of the strong impact of the atmospheric boundary layer (ABL) influence in connection with the topography of the sites. ABL dynamics also likely contribute to the diel cycle of N-tot observed at these stations. Based on available PNSD measurements, CCN-sized particles (considered here as either >50 nm or >100 nm) can represent from a few percent to almost all of N-tot, corresponding to seasonal medians on the order of similar to 10 to 1000 cm(-3), with seasonal patterns and a hierarchy of the site types broadly similar to those observed for N-tot. Overall, this work illustrates the importance of in situ measurements, in particular for the study of aerosol physical properties, and thus strongly supports the development of a broad global network of near surface observatories to increase and homogenize the spatial coverage of the measurements, and guarantee as well data availability and quality. The results of this study also provide a valuable, freely available and easy to use support for model comparison and validation, with the ultimate goal of contributing to improvement of the representation of aerosol-cloud interactions in models, and, therefore, of the evaluation of the impact of aerosol particles on climate.Peer reviewe

On foreclosure rates and the house price index: A cross-sectional analysis

This paper attempts to firmly establish the dependence of house price index on foreclosure rates, a prerequisite to substantiating “let-sink” foreclosure policy. In our paper, we first examine a simple linear regression model to show that there are omitted variables in the model, and therefore, more variables other than just foreclosure rates have to be considered. We then continue with the multiple linear regression model by looking at the influence of foreclosure rates, education, property tax, income tax, stimulus, and legal system upon house price index. By using this model, we show that most variables do not have statistical significance, individually or jointly, except for foreclosure rates and legal system. Finally, we reject the null hypothesis and conclude that house price index is significantly dependent upon foreclosure rates and the state legal foreclosure system

An AI System for Large Open Virtual World

In recent years, computer games have reached unprecedented level of graphical fidelity to the real world. As the non-player characters (NPCs) in the game world look more and more realistic, players expect them to manifest believable behavior as well. This is accented especially in games that feature large open worlds, which players may explore freely and it is thus not possible to explicitly account for all possible player interactions. In this paper we focus mainly on ambient AI - the logic behind day to day behaviors of NPCs as they sleep, work and entertain themselves in the virtual world. In this context, it is of great importance to build a system that handles many NPCs (up to several hundreds) quickly. In this paper we report on an implementation of a particular AI system that was approved for deployment in an upcoming high-budget game. The system features a hierarchy of control similar to the subsumption architecture and a visual agent-based language inspired by behavior trees. We describe the challenges involved in building such a system and specific design decisions we have made that let us achieve a level of behavioral fidelity unmatched by existing games. Finally we evaluate the performance of the system in a realistic setting

Internal Combustion Engines as the Main Source of Ultrafine Particles in Residential Neighborhoods: Field Measurements in the Czech Republic

Ultrafine particles (UFP, diameter &lt; 100 nm) exposure has already been associated with adverse effects on human health. Spatial distribution of UFP is non-uniform; they concentrate in the vicinity of the source, e.g. traffic, because of their short lifespan. This work investigates spatial distribution of UFP in three areas in the Czech Republic with different traffic load: High traffic (Prague neighborhood—Sporilov), commuter road vicinity (Libeznice), and a small city with only local traffic (Celakovice). Size-resolved measurements of particles in the 5–500 nm range were taken with a particle classifier mounted, along with batteries, GPS and other accessories, on a handcart and pushed around the areas, making one-minute or longer stops at places of interest. Concentrations along main roads were elevated in comparison with places farther from the road; this pattern was observed in all sites, while particle number distributions both close and away from main roads had similar patterns. The absence of larger particles, the relative absence of higher concentrations of particles away from the main roads, and similar number distributions suggest that high particle number concentrations cannot be readily attributed to sources other than internal combustion engines in vehicles and mobile machinery (i.e., mowers and construction machines)

Characterization of indoor air quality by using an indoor/outdoor microenvironmental model

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