Lung Deposited Surface Area Research Articles

Malondialdehyde and anion patterns in exhaled breath condensate among subway workers

BackgroundUnderground transportation systems can contribute to the daily particulates and metal exposures for both commuter and subway workers. The redox and metabolic changes in workers exposed to such metal-rich particles have yet to be characterized. We hypothesize that the distribution of nitrosative/oxidative stress and related metabolic biomarkers in exhaled breath condensate (EBC) are modified depending on exposures.ResultsParticulate number and size as well as mass concentration and airborne metal content were measured in three groups of nine subway workers (station agents, locomotive operators and security guards). In parallel, pre- and post-shift EBC was collected daily during two consecutive working weeks. In this biological matrix, malondialdehyde, lactate, acetate, propionate, butyrate, formate, pyruvate, the sum of nitrite and nitrate (ΣNOx) and the ratio nitrite/nitrate as well as metals and nanoparticle concentrations was determined. Weekly evolution of the log-transformed selected biomarkers as well as their association with exposure variables was investigated using linear mixed effects models with the participant ID as random effect. The professional activity had a strong influence on the pattern of anions and malondialdehyde in EBC. The daily number concentration and the lung deposited surface area of ultrafine particles was consistently and mainly associated with nitrogen oxides variations during the work-shift, with an inhibitory effect on the ΣNOx. We observed that the particulate matter (PM) mass was associated with a decreasing level of acetate, lactate and ΣNOx during the work-shift, suggestive of a build-up of these anions during the previous night in response to exposures from the previous day. Lactate was moderately and positively associated with some metals and with the sub-micrometer particle concentration in EBC.ConclusionsThese results are exploratory but suggest that exposure to subway PM could affect concentrations of nitrogen oxides as well as acetate and lactate in EBC of subway workers. The effect is modulated by the particle size and can correspond to the body’s cellular responses under oxidative stress to maintain the redox and/or metabolic homeostasis.

Contribution of Physical and Chemical Properties to Dithiothreitol-Measured Oxidative Potentials of Atmospheric Aerosol Particles at Urban and Rural Sites in Japan

Dithiothreitol-measured oxidative potential (OPDTT) can chemically quantify the adverse health effects of atmospheric aerosols. Some chemical species are characterized with DTT activities, and the particle diameter and surface area control DTT oxidizability; however, the physical contribution to OPDTT by atmospheric aerosols is controversial. Therefore, we performed field observations and aerosol sampling at urban and rural sites in Japan to investigate the effect of both physical and chemical properties on the variation in OPDTT of atmospheric aerosols. The shifting degree of the representative diameter to the ultrafine range (i.e., the predominance degree of ultrafine particles) was retrieved from the ratio between the lung-deposited surface area and mass concentrations. The chemical components and OPDTT were also elucidated. We discerned strong positive correlations of K, Mn, Pb, NH4+, SO42−, and pyrolyzable organic carbon with OPDTT. Hence, anthropogenic combustion, the iron–steel industry, and secondary organic aerosols were the major emission sources governing OPDTT variations. The increased specific surface area did not lead to the increase in the OPDTT of atmospheric aerosols, despite the existing relevance of the surface area of water-insoluble particles to DTT oxidizability. Overall, the OPDTT of atmospheric aerosols can be estimated by the mass of chemical components related to OPDTT variation, owing to numerous factors controlling DTT oxidizability (e.g., strong contribution of water-soluble particles). Our findings can be used to estimate OPDTT via several physicochemical parameters without its direct measurement.

Input-adaptive linear mixed-effects model for estimating alveolar lung-deposited surface area (LDSA) using multipollutant datasets

Abstract. Lung-deposited surface area (LDSA) has been considered to be a better metric to explain nanoparticle toxicity instead of the commonly used particulate mass concentration. LDSA concentrations can be obtained either by direct measurements or by calculation based on the empirical lung deposition model and measurements of particle size distribution. However, the LDSA or size distribution measurements are neither compulsory nor regulated by the government. As a result, LDSA data are often scarce spatially and temporally. In light of this, we developed a novel statistical model, named the input-adaptive mixed-effects (IAME) model, to estimate LDSA based on other already existing measurements of air pollutant variables and meteorological conditions. During the measurement period in 2017–2018, we retrieved LDSA data measured by Pegasor AQ Urban and other variables at a street canyon (SC, average LDSA = 19.7 ± 11.3 µm2 cm−3) site and an urban background (UB, average LDSA = 11.2 ± 7.1 µm2 cm−3) site in Helsinki, Finland. For the continuous estimation of LDSA, the IAME model was automatised to select the best combination of input variables, including a maximum of three fixed effect variables and three time indictors as random effect variables. Altogether, 696 submodels were generated and ranked by the coefficient of determination (R2), mean absolute error (MAE) and centred root-mean-square difference (cRMSD) in order. At the SC site, the LDSA concentrations were best estimated by mass concentration of particle of diameters smaller than 2.5 µm (PM2.5), total particle number concentration (PNC) and black carbon (BC), all of which are closely connected with the vehicular emissions. At the UB site, the LDSA concentrations were found to be correlated with PM2.5, BC and carbon monoxide (CO). The accuracy of the overall model was better at the SC site (R2=0.80, MAE = 3.7 µm2 cm−3) than at the UB site (R2=0.77, MAE = 2.3 µm2 cm−3), plausibly because the LDSA source was more tightly controlled by the close-by vehicular emission source. The results also demonstrated that the additional adjustment by taking random effects into account improved the sensitivity and the accuracy of the fixed effect model. Due to its adaptive input selection and inclusion of random effects, IAME could fill up missing data or even serve as a network of virtual sensors to complement the measurements at reference stations.

Connection between lung deposited surface area (LDSA) and black carbon (BC) concentrations in road traffic and harbour environments

Black carbon (BC) is one of the main components of ambient particulate matter. Previous studies have suggested that BC is more toxic than PM2.5 (mass concentration of all sub-2.5 μm particles). One possible reason for the greater toxicity is that BC is typically in a size range which penetrates easily into lung alveoli and BC particles have a large surface area due to their fractal structure. Due to these properties, toxic gaseous compounds can condensate on the surface of BC particles and then be transported effectively into human lungs, causing a large lung-depositing surface area (LDSA) of particles. In this study, we investigated the relationship between BC and LDSA concentrations in street canyon, highway, and harbour environments in the Helsinki Metropolitan area. In all the studied environments, BC and LDSA concentrations were strongly correlated. In the harbour, cases where marine traffic was considered as the main emission source, the average LDSA per BC mass was 2.4–2.7 times higher than in the road traffic environments. This result was linked to a larger lung depositing size of BC, suggesting that condensation and coagulation of other co-emitted compounds can have a major role in the lung deposition of BC. Thus, BC emissions from marine traffic can cause higher exposure of other co-emitted toxic compounds in the human lungs than the road traffic. The fraction of LDSA linked to BC emissions in the street canyon, the highway, and the harbour were 33%, 30%, and 47%, respectively, whereas the fractions of BC mass in PM1 concentration were 14%, 14%, and 7%, respectively. The results show that BC emissions contribute much more to LDSA than to mass concentration, which indicates that the possible strong negative health effects linked to ambient BC mass concentration could be related to the high LDSA concentration.

Characterization of particle sources and comparison of different particle metrics in an urban detached housing area, Finland

Particulate matter (PM) is emitted from various anthropogenic sources in urban areas affecting the local air quality. The aim of this study was to characterize the sources influencing air quality in detached house area in the Helsinki metropolitan area in Finland, and secondly, to explore the additional value of new particle physical properties to assess the impact of residential combustion on air quality. Measurements were conducted in an urban detached housing area between January and April 2019. Measured particle physical properties were particle number (PN), particle mass (PM1) and lung deposited surface area (LDSA) concentrations and number size distributions. In addition, particle chemical composition was measured using a soot particle aerosol mass spectrometer (SP-AMS; organic compounds, inorganic ions) and an aethalometer (black carbon (BC)). Concentrations of selected monosaccharide anhydrides and polycyclic aromatic hydrocarbons were analysed from the PM10 filter samples. The sources and characteristics of organic aerosol was investigated by applying positive matrix factorization to the mass spectra measured with the SP-AMS. Based on the variations in the measured particle physical parameters, chemical species and meteorology, the measurement period was divided into three sub periods dominated by urban background, wood burning and long-range transport (LRT) aerosols. Highest pollutant concentrations were measured during the wood burning and LRT periods. Wood burning increased the concentrations of all measured species, but the differences were most significant to levoglucosan, benzo(a)pyrene, BC and PM1 that had 12, 10, 6.4 and 3.6 times larger mean concentrations during the wood burning period compared to the urban background period, respectively. LRT affected significantly levoglucosan, PM1 and BC concentrations, since LRT pollutants partly originated from open biomass fires in Eastern Europe. The impact of local wood burning and LRT was quite small to particle number concentrations, whereas LDSA concentrations and size distributions were affected by traffic, wood combustion emissions and LRT. BC concentration correlated with the LDSA concentration during all periods suggesting a common origin. Particle number concentration was a good indicator of local combustion, especially traffic emissions, while the PM1 mass concentration together with secondary particle material was a good measure for the LRT pollutants. Benzo(a)pyrene was found to be a good indicator of local wood burning, but it was not detected in LRT biomass combustion particles.

Particulate matter in a motorcycle-dominated urban area: Source apportionment and cancer risk of lung deposited surface area (LDSA) concentrations

Source-apportioned particle concentrations are necessary to properly evaluate the health impacts of air pollution. In this study, a measurement station was established at an urban roadside in northern Taiwan to the investigate lung deposited surface area (LDSA) concentration, a relevant metric for the adverse health effects of aerosol exposure, along with PM1 and equivalent black carbon (eBC) concentrations, particle number concentration (PNC), and particle size distribution (PSD). Through positive matrix factorization and multi-linear regression analysis, we attributed 57% of LDSA to traffic emissions over the entire study. During rush hour, the motorcycle fraction increased to 0.83 and LDSA (77.6 ± 9.9 µm2/cm3) and PNC (14,000 ± 2400 particles/cm3) values peaked, while 74% of LDSA was attributed to traffic. The LDSA ratio, defined as the ratio of measured LDSA to that estimated from the particle size distribution with a spherical assumption, also increased, highlighting the greater degree of fractal morphology during rush hour. The relationship between LDSA emitted by traffic and PNC yielded a higher r2 (0.92) than the r2 between traffic LDSA and eBC (0.82). Finally, the excess lifetime cancer risk linked with traffic emission was 1.56 × 10-4 (i.e. 15.6 excess cancer cases for a population of 100,000 people) based on the LDSA apportionment results.

On the automated learning of air pollution prediction models from data collected by mobile sensor networks

ABSTRACT This paper addresses the problem of automated learning of air pollution predictive models that were trained using information gathered by a set of mobile low-cost sensors. Concretely, fast to compute machine learning methods (Decision Trees and Support Vector Machines) were used to build regression models that predict air pollution levels for a given location. The models were trained using the data collected by the OpenSense project, in particular, number of particulate matter, particle diameter, and lung deposited surface area (LDSA). We examined two different sets of attributes: one based on a geographical description of the location under analysis (e.g. distribution of households and roads), and another based on a time series of past air pollution observations in that location. Overall, we have found out that past measures lead to better pollution predictions. The best R2 score was 0.751 obtained with the model that predicts LDSA and was trained with the data set with time series attributes, while the worst R2 was 0.009 obtained with the geographical data set to predict number of particles. The performance of the best model is on par with similar air pollution systems. Moreover it can be used in a production system that requires frequent updates.

Lung deposited surface area of atmospheric aerosol particles at three observatories in Japan

The lung deposited surface area (LDSA) measured by diffusion charging (DC) method has been recently receiving increased attention as it is believed to accurately represent the surface reactivity of the particles, including ultrafine particles. To characterize regional and seasonal behaviors of the LDSA in the atmosphere and the factors controlling them, we measured the LDSA concentrations, using the DC method, and other physicochemical properties at three sites in Japan, including urban and rural areas. Comparisons among the three sites in the same season showed the highest LDSA concentration at the urban site Fukuoka, due to high concentrations and low particle sizes. In addition, this urban site frequently recorded high LDSA concentrations with high specific LDSAs, which represents the high contribution of ultrafine particles to the LDSA concentration. This is because the site was dominated by ultrafine black carbon particles emitted from surrounding cities, along with low contribution of long-range transported particles from the continent. In contrast, the dominance of these transported particles, which is typically observed at the three sites during this season, caused the specific LDSA to fall within a low and narrow range. However, even at rural areas, the active formation of organic particles in the summer caused high specific LDSAs, although their concentrations were low. Thus, the particles in urban areas, where ultrafine particles are probably emitted with high concentration from surrounding cities, have the potential to cause a greater adverse effect on human health even for the identical LDSA concentration. In addition, our observations showed that the LDSA of atmospheric aerosol particles measured by the DC method can be roughly represented by the theoretical LDSA of particles assuming spherical shape. Our characterizations using the specific LDSAs provide useful information for applying the LDSAs as the toxicity indicator of atmospheric aerosol particles, including ultrafine particles.

Household solid waste combustion with wood increases particulate trace metal and lung deposited surface area emissions

In households, municipal solid waste (MSW) is often burned along with wood to get rid of waste, to help in ignition or simply to reduce fuel costs. The aim of this study was to characterize the influence of household waste combustion, along with wood, on the physical and chemical properties of particulate emissions in a flue gas of a masonry heater.The MSW burning alongside wood increased average particulate matter (PM) mass (65%), lung deposited surface areas (LDSA, 15%), black carbon (BC, 65%) concentrations and the average particle size in the flue gas. The influence of MSW was smaller during ignition and burning phases, but especially during fuel additions, the mass, number, and LDSA concentrations increased significantly and their size distributions moved towards larger particles. For wood burning the trace metal emissions were relatively low, but significant increase (3.3–179 -fold increase over cycle) was seen when MSW was burned along the wood. High ratios were observed especially during fuel addition phases but, depending on compounds, also during ignition and burning end phases. The highest ratios were observed for chloride compounds (HCl, KCl, NaCl). The observed increase in light-absorbing particle, trace metal and BC concentrations in flue gas when adding wood with MSW are likely to have negative impacts on air quality, visibility, human health and climate. Furthermore, metals may also affect the condition and lifetime of the burning device due to corrosion.

The characteristics and size of lung-depositing particles vary significantly between high and low pollution traffic environments

Currently, only the mass of sub 2.5 μm and sub 10 μm particles (PM2.5, PM10) in ambient air is regulated and monitored closely, but the same increase in PM2.5 can cause different degrees of health effects in different cities (sometimes more harmful effects per unit mass in less polluted cities) (Li et al., 2019). In addition to mass concentration, other measurement metrics are needed to connect particle pollution data and health effects. In our measurements made in traffic-influenced environments in Helsinki, Finland (a relatively clean city), and Delhi-National Capital Region (Delhi-NCR), India (a polluted area), we noted a large difference in the median particle size for lung-deposited surface area (LDSA). In Helsinki, the median size was 80 nm, corresponding to soot particles emitted from diesel engines. However, the median size increased to 190 nm during a long-range transport event of air mass. In Delhi-NCR, surprisingly, the median size was even larger, 410 nm. These larger particles were likely to originate from regional sources rather than local traffic. The LDSA to PM2.5 ratio for particles in Helsinki was 2–4 times the amount in Delhi-NCR, potentially linked with the higher toxicity of a unit of particulate mass in Helsinki.

Fine and Ultrafine Particle Pollution Before and After a Smoking ban in the Catering Industry in Vienna

In the catering industrytobacco smoke was the primary source of fine and ultrafine particles, which are well known for their health-damaging effects. As shown in studies, attempts to reduce passive smoking in the catering industry of Vienna, like separated smoking rooms, failed to reduce fine and ultrafine particle concentrations effectively. On November 1st 2019, an enlarged non-smoker’s protection law was introduced, including a total smoking-ban in the catering industry. 40 hospitality venues with areas for smokers and non-smokers before the ban had been selected as typical Viennese cafes, pubs, bars and discotheques to be sampled unannounced. Concentrations of fine particle mass (PM10, PM2.5, PM1) and ultrafine particle number (PNC) and lung deposited surface area (LDSA) could be measured before and after the introduction of the smoking-ban in 39 venues at nearly identical locations and under comparable circumstances. Results showed a statistically significant decline in both fine and ultrafine particle concentrations in the former smoking areas for all parameters as well as in the former non-smoking areas for PM2.5, PM1 and LDSA. After the ban concentrations in former smoking areas and non-smoking areas showed no significant differences any more. From these results the smoking-ban successfully removed particles from breathing air of guests and staff, however, some outliers in the study after the ban point to the necessity of repeated controls in Vienna. Also, outside Vienna the compliance with the law should be controlled in the Austrian hospitality industry.

Concentrations and Size Distributions of Particle Lung-deposited Surface Area (LDSA) in an Underground Mine

ABSTRACT Ultrafine particles produced by diesel-powered vehicles in underground mines are largely unaccounted for in mass-based air quality metrics. The Lung Deposited Surface Area concentration (LDSA) is an alternative to describe the harmfulness of particles. We aim to study concentrations and size distributions of LDSA at various locations in an underground mine as well as to evaluate the applicability of sensor-type measurement of LDSA. This study was conducted in an underground mine in Kemi, Finland, in 2017. Our main instrument was an electrical low-pressure impactor (ELPI+) inside a mobile laboratory. Additionally, five diffusion-charging based sensors were tested. The environment was challenging for the sensors as the particle size distribution was often outside the optimum range (20–300 nm) and dust accumulated inside the instruments. Despite this, the correlations with the ELPI+ were decent (R2 from 0.53 to 0.59). With the ELPI+ we determined that the maintenance area had the lowest mean LDSA concentration (79 ± 38 µm2 cm–3) of the measured locations. At the other locations, concentrations ranged from 137 to 405 µm2 cm–3. The mode particle size for the LDSA distribution was around 100 nm at most locations, with the blasting site as a notable exception (mode size closer to 700 nm). Diffusion-charging based sensors—perhaps aided by optical sensors—are potential solutions for long-term monitoring of LDSA if dust accumulation is taken care of. Our research indicates worker exposure could be reduced with the implementation of a sensor network to show which locations need either protective gear or increased ventilation.

Development and validation of an intra-calibration procedure for MiniDISCs measuring ultrafine particles in multi-spatial indoor environments

Since the real exposure to indoor ultrafine particles depends on temporal and spatial variation of aerosol concentration, particles dynamic behavior becomes relevant in studying indoor pollution. With this aim, the characterization of Ultrafine Particles (UFPs) variability within different environments (multi-spatial indoor environments) can be regarded as a specific tool in assessing the human exposure. In the case of urban indoor environments, instruments able to measure UFPs at high time resolution with high sensitivity are needed, lightweight and silent. For this purpose, personal monitors unipolar diffusion charging based could be used for their ease of use. Among them, Miniature DIffusion Size Classifier (MiniDISC), a small, silent and wearable analyzer measures particle number concentration, particle modal size and lung deposited surface area of nanoparticles at high time resolution, for dynamic or static use. Nevertheless, the typical ±30% accuracy specified by the manufacturer does not make this sensor reliable enough to measure gradients of urban doses of UFPs occurring in multi-spatial indoor environments.The presented work aims at improving the performances of MiniDISCs for their use in simultaneous measurement of urban UFPs by a multiple set-up, such as in indoor environments inside a building.For this purpose, a new intra-calibration procedure has been developed among MiniDISCs, named Best Intra-calibration (BIC), which corrects data of electrical signals of two or more instruments to those of one selected as reference. Compared to a linear regression analysis for PNC of UFPs, BIC procedure has two main advantages. First, it makes it possible to improve simultaneously the precision of particle number concentration (PNC) and particle modal size (PMS). Secondly, it allows multiple instruments to operate as a fleet, such as a spatial delocalization of an instrument in multiple environments.The procedure was tested in realistic environmental conditions, evaluating indoor PNC and PMS of UFPs by both parallel samplings and multi-spatial samplings. Three types of monitoring campaigns were carried out: inter-comparisons between PNC of UFPs from three MiniDISCs and one Condensation Particle Counter; intra-comparisons between PNC and PMS of UFPs from three MiniDISCs; urban monitoring in-field campaign of UFPs with three MiniDISCs in an indoor workplace, a physic laboratory, in the next hallway and outside. The latter campaign aimed at evaluating how UFPs are influenced by the interaction among different environments inside the building and by the work activity. For these purposes, the dynamical behavior and the ratios Indoor to Outdoor were investigated, in addition to a novel ratio Indoor to Hallway. The BIC procedure allows increasing the precision measured by the weighted coefficients of variation CVs of about 7 times. The results support the novel Intra-calibration procedure to improve the intra variability of MiniDISCs in parallel sampling, making them attractive for measuring UFPs by both the metrics PNC and PMS in multi-spatial indoor environments.

Occupational exposure to graphene and silica nanoparticles. Part I: workplace measurements and samplings

Few-Layers Graphene (FLG) are able to improve the performance of materials, due to their chemical-physical properties. Engineered amorphous silica nanoparticles (SiO2NPs) are among the most widespread nanomaterials (NMs) in the world. Such nanomaterials are two case studies of the research project ‘NanoKey’ that integrated the exposure assessment through personal measurements and sampling in the workplace, as described in the present work (part I), with the biomonitoring of exposed workers (reported in part II). Measurement campaigns were conducted according to OECD and WHO harmonized approach in two production sites. The set of instruments included real-time devices for high-resolution measurements at the nanoscale and time-integrated samplers for the off-line gravimetric analysis and chemical and morphological (SEM-EDS) characterization of exposure in order to identify the contribution of production compared to the background. Values of particle number concentration (PNC) and lung deposited surface area (LDSA) within the FLG production resulted higher than the background far field (FF), even if they are always similar to the near field (NF) ones: the average diameter (Davg) during the production was higher than the NF background but always lower than the FF values. SEM-EDS analysis highlighted the presence of structures comparable to those produced. During the SiO2NPs production, the PBZ values showed PNC and LDSA levels higher than the background, with a decrease in the Davg probably due to NPs emission. SEM-EDS confirms the presence of rare silica nanoparticles. Since the exposure to airborne NMs cannot be excluded in both production sites, a prevention-through-design approach to mitigate the potential risk for workers has been recommended.

Determination of total and lung-deposited particle surface area concentrations, in central Athens, Greece.

Numerous health studies have linked the exposure to particulate matter with adverse health effects, while there is an increasing scientific interest in the particle metrics of surface area (SA) and lung-deposited SA (LDSA) concentration. In the present study, two integrated SA estimation methods, both based on widely used instrumentation, were applied at an urban traffic environment in Athens for a 6-month period. The first estimation method used the size distribution by number to estimate SA (average SA1 669.3 ± 229.0 μm2 cm-3), while the second method used a simple inversion scheme that incorporates number and mass concentrations (average SA2 1627.9 ± 562.8 μm2 cm-3). In pairwise comparisons, SA2 levels were found two times greater than the corresponding SA1, but exhibited a strong correlation (r = 0.73). SA1 and SA2 concentrations correlated well with the traffic-related pollutants NOx (r = 0.64 and 0.78) and equivalent black carbon (r = 0.53 and 0.51). The diurnal variation of SA1 concentrations by size range indicated traffic as a major controlling factor. Estimated LDSA (53.9 μm2 cm-3 on average) concentrations were also clearly affected by anthropogenic emissions with more pronounced associations in the 0.01-0.4 μm range (r = 0.66 with NOx and r = 0.65 with equivalent black carbon). Validating estimated LDSA through simultaneous measurements with a reference instrument revealed that the estimation method underestimates LDSA by a factor between 2 and 3, exhibiting, however, a high correlation (r = 0.79). Overall, the performance of estimation methods appear satisfactory and indicate that a trustworthy assessment of the temporal variability of SA and LDSA concentration metrics can be provided in real time, on the basis of relatively lower-cost instrumentation, especially in view of recent advances in particle sensing technologies.

Workers' Exposure Assessment during the Production of Graphene Nanoplatelets in R&D Laboratory.

Widespread production and use of engineered nanomaterials in industrial and research settings raise concerns about their health impact in the workplace. In the last years, graphene-based nanomaterials have gained particular interest in many application fields. Among them, graphene nanoplatelets (GNPs) showed superior electrical, optical and thermal properties, low-cost and availability. Few and conflicting results have been reported about toxicity and potential effects on workers’ health, during the production and handling of these nanostructures. Due to this lack of knowledge, systematic approaches are needed to assess risks and quantify workers’ exposure to GNPs. This work applies a multi-metric approach to assess workers’ exposure during the production of GNPs, based on the Organization for Economic Cooperation and Development (OECD) methodology by integrating real-time measurements and personal sampling. In particular, we analyzed the particle number concentration, the average diameter and the lung deposited surface area of airborne nanoparticles during the production process conducted by thermal exfoliation in two different ways, compared to the background. These results have been integrated by electron microscopic and spectroscopic analysis on the filters sampled by personal impactors. The study identifies the process phases potentially at risk for workers and reports quantitative information about the parameters that may influence the exposure in order to propose recommendations for a safer design of GNPs production process.

Size distribution and lung-deposited doses of particulate matter from household exposure to biomass smoke.

Exposure to high concentrations of particulate matter (PM) is associated with a number of adverse health effects. However, it is unclear which aspects of PM are most hazardous, and a better understanding of particle sizes and personal exposure is needed. We characterized particle size distribution (PSD) from biomass-related pollution and assessed total and regional lung-deposited doses using multiple-path deposition modeling. Gravimetric measurements of kitchen and personal PM2.5 (<2.5µm in size) exposures were collected in 180 households in rural Puno, Peru. Direct-reading measurements of number concentrations were collected in a subset of 20 kitchens for particles 0.3-25µm, and the continuous PSD was derived using a nonlinear least-squares method. Mean daily PM2.5 kitchen concentration and personal exposure was 1205±942µg/m3 and 115±167µg/m3 , respectively, and the mean mass concentration consisted of a primary accumulation mode at 0.21µm and a secondary coarse mode at 3.17µm. Mean daily lung-deposited surface area (LDSA) and LDSA during cooking were 1009.6±1469.8 µm2 /cm3 and 10,552.5±8261.6 µm2 /cm3 , respectively. This study presents unique data regarding lung deposition of biomass smoke that could serve as a reference for future studies and provides a novel, more biologically relevant metric for exposure-response analysis compared to traditional size-based metrics.

Influence of spray-coating process parameters on the release of TiO2 particles for the production of antibacterial textile

Titanium dioxide (TiO2) nanoparticles (NPs) are produced in high volume and widely used in manufacturing processes, raising potential occupational health concerns. Here, workers' exposure was assessed during production of antibacterial textiles, where TiO2 NPs were impregnated onto 65% polyester 35% cotton textile surface by spray-coating. The influence of pressure, web speed and number of working spray nozzles to TiO2 particles release was studied under different experimental conditions. Real-time monitoring was used to measure size-resolved particle concentration and lung-deposited surface area (LDSA) concentration using an optical particle counter and a diffusion charger, respectively, from both near- and far-field. Particles were sampled from the working area for off-line electron microscopy characterization, and suspensions of sampled particles were characterized by dynamic light scattering. Post-campaign data analysis was carried out and used for quantitative exposure safety assessment. Particle number concentration and LDSA results showed that pressure at the spraying nozzles (P) is the main parameter that influences the release of particles in the environment. Other process parameters studied (web speed and number of working spray nozzles) did not appear to significantly affect the release of particles. The particle number concentration in default experimental conditions (intermediate values for all process parameters; P = 2.3 bar, web speed = 6 m/min and number of working spray nozzles = 2) was quantified as 1.19 106 # L−1. Upon increasing the pressure, from 1.5 to 4.0 bar, near-field average mass and LDSA concentrations increased from 0.90 to 1.76 mg/m3, and from 51.8 to 290.5 μm2/cm3, respectively. Average (avg) mass concentrations were well below the maximum recommended exposure limit of 2.4 mg/m3 for fine TiO2 particles proposed by the US National Institute for Occupational Safety and Health.

Exposure to Submicron Particles and Estimation of the Dose Received by Children in School and Non-School Environments

In the present study, the daily dose in terms of submicron particle surface area received by children attending schools located in three different areas (rural, suburban, and urban), characterized by different outdoor concentrations, was evaluated. For this purpose, the exposure to submicron particle concentration levels of the children were measured through a direct exposure assessment approach. In particular, measurements of particle number and lung-deposited surface area concentrations at “personal scale” of 60 children were performed through a handheld particle counter to obtain exposure data in the different microenvironments they resided. Such data were combined with the time–activity pattern data, characteristics of each child, and inhalation rates (related to the activity performed) to obtain the total daily dose in terms of particle surface area. The highest daily dose was estimated for children attending the schools located in the urban and suburban areas (&gt;1000 mm2), whereas the lowest value was estimated for children attending the school located in a rural area (646 mm2). Non-school indoor environments were recognized as the most influential in terms of children’s exposure and, thus, of received dose (&gt;70%), whereas school environments contribute not significantly to the children daily dose, with dose fractions of 15–19% for schools located in urban and suburban areas and just 6% for the rural one. Therefore, the study clearly demonstrates that, whatever the school location, the children daily dose cannot be determined on the basis of the exposures in outdoor or school environments, but a direct assessment able to investigate the exposure of children during indoor environment is essential.

Measurement of the human respiratory tract deposited surface area of particles with an electrical low pressure impactor

Particle deposition in the human respiratory tract is considered to have negative effects on human health. The lung deposited surface area (LDSA) is an important metric developed to assess the nega...