Lung Deposited Surface Area Concentrations Research Articles

Particle number, mass, and surface area concentrations inside an underground metalliferous mine in Kazakhstan

Considerable scientific evidence shows that inhalation of diesel exhaust particles is associated with a wide range of adverse health effects. This study examined the concentrations of diesel particles in five stations of the operational phases of an underground mine in Kazakhstan. Real-time monitoring of particulate number concentration (PNC), lung deposited surface area (LDSA) concentrations, PM1, PM2.5, and PM10 concentrations in the mining operational area, and the breathing zone of the loader driver inside the loader cabin was conducted. The results showed that the highest average PNC and LDSA concentrations were 7 × 105 cm−3 and 4 × 103 μm2 cm−3, respectively, and most of the particles were in the sub-100 nm range. The concentrations level in the loader cabin area (LA), and operational area (OA) of mine was similar with respect to PM1 and PM2.5 as a result of the homogenous distribution of the PM inside the mine's operational phase. The major source of the PM1 and PM2.5 was the diesel engine, while the low LA/OA ratio for PM10 in this study suggested the source of the coarse particles was dust resuspension around the loader cabin.

Ambient air particulate total lung deposited surface area (LDSA) levels in urban Europe

This study aims to picture the phenomenology of urban ambient total lung deposited surface area (LDSA) (including head/throat (HA), tracheobronchial (TB), and alveolar (ALV) regions) based on multiple path particle dosimetry (MPPD) model during 2017–2019 period collected from urban background (UB, n = 15), traffic (TR, n = 6), suburban background (SUB, n = 4), and regional background (RB, n = 1) monitoring sites in Europe (25) and USA (1). Briefly, the spatial-temporal distribution characteristics of the deposition of LDSA, including diel, weekly, and seasonal patterns, were analyzed. Then, the relationship between LDSA and other air quality metrics at each monitoring site was investigated. The result showed that the peak concentrations of LDSA at UB and TR sites are commonly observed in the morning (06:00–8:00 UTC) and late evening (19:00–22:00 UTC), coinciding with traffic rush hours, biomass burning, and atmospheric stagnation periods. The only LDSA night-time peaks are observed on weekends. Due to the variability of emission sources and meteorology, the seasonal variability of the LDSA concentration revealed significant differences (p = 0.01) between the four seasons at all monitoring sites. Meanwhile, the correlations of LDSA with other pollutant metrics suggested that Aitken and accumulation mode particles play a significant role in the total LDSA concentration. The results also indicated that the main proportion of total LDSA is attributed to the ALV fraction (50 %), followed by the TB (34 %) and HA (16 %). Overall, this study provides valuable information of LDSA as a predictor in epidemiological studies and for the first time presenting total LDSA in a variety of European urban environments.

90 Graphene – Exposure and Emissions at Two Pilot Plants

Abstract Graphene is a nanomaterial suitable for a wide variety of applications. The industrial production and use of graphene is, hence, increasing rapidly. The main challenge in assessing graphene exposure is that graphene is a carbon structure, making it comparable to look for a needle in a haystack. We have explored the possibility to analyze elemental carbon and black carbon as a measure of personal graphene exposure. Exposure and emission measurements for graphene were conducted at two pilot plants using on- and off-line techniques. One plant produces graphene, up to 10 tons per year, using liquid exfoliation technique. The other plant uses graphene to coat paper in a conventional roll-to-roll process. The measurements were conducted both stationary (in the emission zone and in the background) and as personal measurements (in the breathing zone of the workers). We have analyzed elemental carbon and black carbon as a measure of the personal exposure. In the emission and background zone we have measured number of particles and lung deposited surface area concentration of particles <300nm, mass concentration, and we have collected samples for electron microscopy analysis. The exposure was in general low, but we identified tasks with an increase emissions. Measurements of elemental carbon is a promising technique for occupational hygienists to find possible exposure to graphene.

126 Emission and Exposure Characterization During Metal Waste Recycling

Abstract Waste of electrical and electronic equipment (WEEE) is one of the fastest-growing waste streams in the EU. The airborne occupational and environmental exposures generated by this waste handling are poorly quantified, and the growing use of nanomaterials in electronics adds to the uncertainty of risk assessment. Emission and personal exposure measurements were carried out during industrial recycling for three different metal waste flows: WEEE, metal scrap and cables. Size distributions and number-, mass- and lung deposited surface area concentrations were assessed by on-line techniques, and filter samples were collected for gravimetric analyses, metal content, and electron microscopy. Samples for elemental analyses with Particle Induced X-ray Emission (PIXE) was collected by a 12-stage low-pressure impactor . Additionally, low-cost sensors were deployed for long term monitoring. By number, the size distributions from all three flows were heavily dominated by particles <100 nm. Electron microscopy showed that there are many different elements in the same particle and that the composition of different particles vary considerably. Abundant elements, according to ICP-MS, were Fe, Al, Zn, and Cu, but Pb, Mn, Ba, and Co were also detected. PIXE analysis showed that the chemical composition indeed is different in different particle sizes, with e.g. Cr almost exclusively being present in particles < 200 nm. Low-cost sensors, not previously used for monitoring in highly polluted industrial settings, functioned well after 30 days. This study shows that detailed particle characterization is crucial for understanding of today’s and tomorrow’s waste recycling exposures, and as input to future toxicological assessments.

Effect of urban green infrastructure on pedestrian exposure to ultrafine particles: A case study of Guangzhou, China

Traffic emissions, as the dominant source of urban Ultrafine Particles (UFP), pose great potential health risks to pedestrians who commute near busy roads. Green infrastructure is regarded as an effective measure for urban particulate pollution abatement. In this study, two weeks of mobile measurements of pedestrian UFP exposure were performed during morning and evening rush hours, along greenway and sidewalk with and without vegetation barrier near an arterial road. UFP concentration was observed to be 28.7% lower with weakened fluctuations on vegetation barrier sidewalk than on open sidewalk in average, while UFP lung-deposited surface area concentration decreased by 21.1% accordingly. Vegetation mitigated UFP concentration in general, however, locally intense heavy-duty vehicles activities might weaken this effect occasionally. The weekly and diurnal variations of UFP concentration and the greenery effect performance were attributable to the combined effect of practical traffic situations, meteorological conditions, and crowd activities. Gray relational analysis indicated that temperature (γ = 0.814), relative humidity (γ = 0.787), traffic volume (γ = 0.764) and heavy-duty vehicles count (γ = 0.741) were the top four impact factors on roadside UFP concentration during observation.

RETRACTED: Health risks and respiratory intake of submicron particles in the working environment: A case study

Background: Powder-coating processes have been extensively used in various industries. The submicron particles generated during the powder-coating process in the workplace have complex compositions and can cause serious diseases. The purpose of this study was to better understand the health risks and respiratory intake of submicron particles during the powder coating process.Methods: The concentrations of and variations in submicron particles were measured using real-time instruments. The health risks of submicron particles were analyzed using the Stoffenmanager Nano model. A new computational fluid dynamics model was used to assess the respiratory intake of ultrafine particles (UFPs), which was indicated by the deposited dosage of UFPs in the olfactory area, nasal cavity, and lungs. The deposited doses of UFPs were used to calculate the average daily doses (ADDs) of workers, according to the method described by the Environmental Protection Agency.Results: The number concentration (NC), mass concentration, surface area concentration, personal NC, and lung-deposited surface area concentration of submicron particles were >105 pt/cm3, 0.2–0.4 mg/m3, 600–1,200 μm2/cm3, 0.7–1.4 pt/cm3, and 100–700 μm2/cm3, respectively. The size distribution showed that the submicron particles mainly gathered between 30 and 200 nm. The health risk of submicron particles was high. Upon respiratory intake, most UFPs (111.5 mg) were inhaled into the lungs, a few UFPs (0.272 mg) were trapped in the nasal cavity, and a small minority of UFPs (0.292 mg) were deposited in the olfactory area. The ADD of male workers with 10 years of exposure in the olfactory area, nasal cavity, and lung were 1.192 × 10–3 mg/kg·d−1, 1.11 × 10–3 mg/kg·d−1, and 0.455 mg/kg·d−1, respectively.Conclusion: Owing to the high concentrations of submicron particles, the workers involved in the powder-coating process are at a high health risk. Moreover, the respiratory intake of UFPs by workers is high, which is suggested by the highly deposited dosage of UFPs in the lungs and the corresponding high ADD in workers. Control measures, including engineering control, management control, and personal protective equipment, must be improved for the protection of workers.

Measurements and modelling of the three-dimensional near-field dispersion of particulate matter emitted from passenger ships in a port environment

The maritime sector poses significant challenges in controlling the emission of harmful pollutants, such as particulate matter, and reducing their impact on coastal areas and the atmospheric environment. Efforts to regulate the sector necessitate new knowledge and methods to characterise the evolution and physicochemical transformation of maritime particle emissions dispersing in port areas. An experimental campaign at the Port of Rafina, Greece, was conducted with this in mind. In this paper, we report on the first multi-characteristic particle measurements, including particle number (PN), lung deposited surface area (LDSA), and black carbon (BC), performed at both land and sea using a novel instrument set-up mounted on an unmanned aerial vehicle (UAV). Land-based measurements showed that LDSA averages, which are influenced by particle number and size, increase up to 20 times above background levels as an emission plume progresses downwind, whereas BC concentrations, which are dominated by mass, are ∼12 times higher than the background concentration. Ground and UAV-based particle comparisons showed that PN and LDSA measurements exhibit greater differences than BC relative to the plume's location. Ground-based sensors had ∼50% lower LDSA and PN concentrations, whereas BC was about equal. The experimental observations are further substantiated by coupling a Gaussian plume dispersion model and a new computationally attractive approach, known as the Incompletely Stirred Reactor Network (ISRN) method, to predict the three-dimensional evolution of particle characteristics considering the effects of dilution, segregation, and physicochemical transformations, such as coagulation. Based on simplifying assumptions for the particle size distribution sources within the port area, the ISRN estimates suggest that the discrepancy between various metrics can be partly explained by coagulation, responsible for a non-linear increase in particle size, depending on the local level of dilution and mixing intensity, leading up to a ∼25% decrease in PN and LDSA compared to BC. Combined, measurements and modelling highlight the effect of the sampling location and the importance of monitoring more than one particle metric to characterise particle evolution.

Personal exposure to various size fractions of ambient particulate matter during the heating and non-heating periods using mobile monitoring approach: A case study in Augsburg, Germany

In this study, the exposure to ambient particulate matter metrics (PM1, PM2.5, PM10, black carbon (BC), brown carbon (BrC), ultraviolet particulate matter (UVPM), particle number concentration (PNC), and lung deposited surface area (LDSA)) were measured along a fixed walking route with specific focus on three typical micro-environments (park, central business district (CBD), and traffic) in different time of day during the non-heating (May–Oct.) and heating (Nov.–Apr.2nd year) periods from 2018 to 2020 in the downtown Augsburg, Germany. The spatio-temporal exposure to ambient PM metrics exhibited substantial heterogeneity during the observation period, with park environment having lowest exposure and traffic area having the highest exposure. Generally, the higher LDSA concentrations were found in traffic area and CBD during the observation periods, while the lower concentrations were found in the park, which is similar with other ambient PM metrics (PMX, eUVPM, eBC, and PNC). The correlations between LDSA and other ambient PM metrics were higher during the heating than non-heating period in most of investigated environments, indicating the different PM sources. Overall, this study provides a comprehensive assessment of personal exposure that complements fixed-site ambient PM metrics measurements in the context of health risk assessment and epidemiological studies.

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.

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.

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.

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.

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 (>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 (>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.

Assessment of the Integrated Personal Exposure to Particulate Emissions in Urban Micro-environments: A Pilot Study

City dwellers’ personal exposure to PM is influenced by numerous daily activities in multiple indoor and outdoor micro-environments (MEs). This study assessed the integrated personal exposure to PM across urban MEs together with the recording individual time-activity patterns. We evaluated simultaneously the exposure to PM2.5, black carbon (BC), and ultrafine particles (UFPs) in the Central Business District (CBD) area of Singapore. In addition, we quantified the lung-deposited surface area (LDSA) concentration, which is an indicator of the potential health impacts of UFPs. The field study was conducted over a 7-km walking route to identify air pollution hotspots. Subsequently, the personal exposure to PM2.5, BC, and UFPs was measured at five selected hotspots for 1 hour each and across indoor and outdoor MEs during diverse daily human activities for 24 hours. The PM concentrations were found to vary considerably in both space and time in the CBD area. During the 1-hour personal exposure measurement, extremely high concentrations of PM2.5 (215 ± 129.5 µg m–3 and 36.4 ± 12.5 µg m–3) and BC (20.9 ± 10.4 µg m–3 and 18.1 ± 12.0 µg m–3) were observed at a temple and a bus stop, and elevated UFP number concentrations (320.8 ± 131.1 × 103 # cm–3) and high LDSA concentrations (564.6 ± 276.5 µg2 cm–3) were measured at a food court. The estimated potential health risk suggests that the continued inhalation of large amounts of PM2.5 emitted from combustion sources is likely to lead to adverse long-term health effects among the exposed individuals. Overall, we provide insight into an individual’s total exposure to PM based on time-activity patterns. The results of this work form a scientific basis for developing air pollution control measures to mitigate personal exposure to PM on a city scale.

Variability of aerosol mass and number concentrations during taconite mining operations

This study characterized concentration metrics of airborne nanoparticles and their time series across major operations of a taconite mine through monitoring respirable and ultrafine particle concentrations at four major processing departments of the mine: crushing, dry milling, wet milling, and pelletizing (United Taconite Mine, Iron Junction, MN, USA). We used three area stations of direct-reading instruments to estimate concentration metrics including PM1 (particles with an aerodynamic diameter <1 µm), respirable dust (particles sampled according to the respirable convention with a 50% sampling efficiency at an aerodynamic diameter of 4 µm), PN (total number concentration of particles), and lung-deposited surface area concentrations (LDSA) of particles smaller than 300 nm, on two different days. Results for each station were compared using bivariate correlation analysis to obtain insight into the spatial distribution, and intra-class correlation coefficients (ICCs) to evaluate the between-day repeatability between the measurements. Comparability of the LDSA concentrations measured by two different devices was also investigated using linear regression. Results revealed that the pelletizing operation produced the highest average LDSA concentration on both days (with a maximum concentration of 199 ± 48 µm2/cm3 in pelletizing, 141 ± 52 µm2/cm3 in crushing, 91 ± 9 µm2/cm3 in dry milling, and 85 ± 7 µm2/cm3 in wet milling). Concentrations in all operations showed a fair to excellent between-day repeatability but they were significantly different within stations of each operation. Measured LDSA concentrations did not show a linear correlation between different instruments, except for crushing.

The effect of route selection on PM2.5, particle number count and lung deposited surface area concentrations during bicycle commuting

TPS 651: Air pollution exposure modeling 1, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM Aim: The aim was to evaluate the difference in fine particle (PM2.5; particles <2.5 µm in diameter), particle number count (PNC) and lung-deposited surface area (LDSA) concentrations during cycling between more and less road traffic-impacted routes to find out whether cyclists can influence their exposure to particulate air pollutants with route selection. Methods: Measurements were conducted in the Helsinki metropolitan region, Finland, in October/November 2016, March/April 2017 and June 2017, representing autumn, spring and summer. Measurements were done simultaneously on two bicycling routes, which had the same starting and end points and starting time. One route followed busy streets in traffic environments (‘Traffic’) and another utilized side-streets and parks (‘Green’). Seven bicycling route pairs were selected for air pollution measurements conducted during and outside rush hours on weekdays. The cyclist carried portable measurement devices in a backpack. Every route was biked back and forth at least two times both in the mornings and in the afternoons in each season. For each trip, the median of measured concentrations was calculated to represent a typical exposure level during a one-way trip. The Wilcoxon Signed-Rank test was used to compare the concentration ratios of studied air pollutants between Traffic and Green routes. Results: A total of 173, 145, and 145, pairs of one-way trips were included in the analysis for PM2.5, PNC, and LDSA, respectively. Length of Traffic and Green routes ranged between 3.9-5.5 km and 4.7-6.7 km, respectively. Cyclist was exposed on average 1.3-times higher median PM2.5 and LDSA concentrations on Traffic route compared to Green route, and 1.4-times higher PNC concentration. The differences between levels in studied route pairs were greater during rush hours. Conclusion: Cyclists can influence their exposure to air pollution with route selection. Thus, alternative routes further away from busy road traffic should be planned in urban areas.

Applicability of Optical and Diffusion Charging-Based Particulate Matter Sensors to Urban Air Quality Measurements

ABSTRACT High spatial resolution particulate matter measurements are necessary to accurately characterize urban air quality issues. This study investigates how sensors can be used in an urban area to complement existing air quality measurements. A measurement campaign was conducted during winter in Helsinki, Finland, where the performance of a custom-built optical instrument—the Prototype Aerosol Sensor (PAS; uses Shinyei PPD60PV and PPD42NS sensor modules)—and three commercial diffusion charging-based sensors (Pegasor AQ Urban, DiSCmini and Partector) was evaluated against reference instruments. The results showed that the PAS was able to measure the coarse (PM2.5-10; range: 0–400 µg m–3) and fine (PM2.5; range: 0–50 µg m–3) fractions with reasonably high correlations (R2 = 0.87 and 0.77) when compared to a gravimetric monitor. Likewise, the lung deposited surface area (LDSA) concentrations delivered by the three diffusion charging sensors indicated good performance (R2: 0.92–0.97) when compared to LDSA concentrations calculated from the size distribution data of the differential mobility particle sizer. A clear correlation (R2 = 0.77) between the black carbon and Pegasor-measured LDSA concentrations, as well as similar diurnal cycles, was observed, suggesting a common source. The optical sensors were useful for measuring the mass concentrations of coarse local particles. By contrast, the diffusion charging sensors were applicable in urban environments, where ultrafine particles from traffic or other local combustion sources affect air quality.