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. 2026 Oct 8;60(41):29515–29526. doi: 10.1021/acs.est.6c10850

Aerosol Deposition in the Human Respiratory System from Distinct Urban Sources Using Multiple Exposure Metrics

Imre Salma †,*, Máté Vörösmarty †, Árpád Farkas ‡
PMCID: PMC13689813  PMID: 42899668

Abstract

Targeting specific aerosol sources offers more effective air-quality control than focusing solely on ambient concentrations. Using source apportionment, major contributors to particle number concentrations in the diameter range of 6–1000 nm in urban background of Budapest, Hungary were identified, and their size distributions applied in lung deposition modelling under reference breathing conditions. In this study, we find that most particles penetrate to the deep lung with a maximum deposition at airway generations 17 to 21 depending on physical activity. Deposition fractions vary substantially by source, ranging from 76% (new particle formation) to 27% (solid fuel combustion). Exercise enhances overall deposition, and redistributes the deposited particles within the respiratory tract by decreasing extra-thoracic deposition and increasing the alveolar fraction. Our results also show that deposition rates are more sensitive to physical activity than deposition fractions. These deposition curves exhibit a levelling-off tendency in the extra-thoracic region, while continuing to increase in the lung. Particle number and particle surface area deposition curves are similar in shape, although the relative importance of aerosol sources and the most affected respiratory regions differ. We point that surface-density deposition rates are three orders of magnitude higher in the nose and mouth than in the lung.

Keywords: ultrafine aerosol particles, new particle formation, road vehicle traffic emissions, solid fuel combustion, secondary inorganic aerosol, biopersistent particles, soot, lung-deposited surface area

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1. Introduction

Aerosols in the ambient air can exert adverse effects on human health. − The respiratory system serves as the primary target organ for such exposure. The deposition in the airways together with the subsequent fate of deposited particles – including bioprocessing in affected tissues, accumulation, systematic translocation to other organs and clearance – is highly dependent on particle size. − Particles with aerodynamic diameters smaller than 10 μm (PM10) and 2.5 μm (PM2.5), as well as ultrafine (UF) particles with mobility diameters below 100 nm, are especially significant in terms of exposure to particulate matter (PM).

The biological effects of the particles deposited in the respiratory tract, especially those soluble in the respiratory epithelial fluid, are primarily associated with mass concentrations of potentially toxic components. − In this context, larger (accumulation- and coarse-mode) particles contribute more to the overall mass dose than UF particles. In contrast, the biological effects of deposited particles that are insoluble are primarily attributed to their vast number, large and active total surface area, extremely small size and surface reactivity and to the particular morphology of the individual particles. ,,−

An increasing body of epidemiological, toxicological and clinical evidence is suggesting significant associations between exposure to UF particles and a range of morbidity and mortality outcomes. ,,− Repeated exposure to elevated levels of UF particles can induce both reversible and persistent lung inflammation. This irritation may trigger the release of pro-inflammatory mediators, which may reach distant organs via the systemic circulation. The inflammation and the resulting respiratory distress can further compromise cardiovascular function, contributing to elevated blood pressure and heart disorders. Additionally, UF particles can induce genotoxicity, disrupt the central nervous system, − and affect reproductive health. Long-term exposure to these particles has also been linked to increased risk of cancer. It is important to note that conclusive understanding of the health effects of UF particles remains limited, primarily due to the absence of representative datasets. ,

It was reported that deposition of insoluble UF particles may pose an excess health risk related to larger particles with a similar chemical composition. ,, The smallest UF particles (nanoparticles) are capable of penetrating through the cell wall and entering the blood circulation or the lymphatic system, therefore they can be translocated to distant organs. , Consequently, UF or total particle number concentrations are increasingly recognized as a relevant exposure metric in research and regulation. , Particle surface area concentrations may also be an important exposure metric given the direct interactions between particle surfaces and cells or subcellular components. , In addition, particles with a reactive surface can also adsorb potentially harmful molecules, viruses or radionuclides from the air, which may intensify their health impacts.

The deposition of UF particles in the human respiratory tract is governed primarily by Brownian diffusion. Because diffusional deposition depends on particle size, hygroscopic particle growth under the high relative humidity (RH) conditions of the airways can alter particle diameters and, consequently, the deposition. The relative effect also depends on the particles’ hygroscopic properties and initial dry size. Accounting for hygroscopic particle growth is particularly important in the submicrometer diameter range. −

Recent studies have suggested that source-resolved and seasonally targeted PM mitigation strategies may yield greater public health benefits than approaches focused solely on reducing total PM mass concentrations. , Such strategies more directly address the exposure pathways and biological mechanisms underlying PM-related health effects. However, identifying explicit sources of UF particles and integrating their size distributions and hygroscopic properties into respiratory deposition modelling across multiple exposure metrics require specialized experimental datasets and advanced mathematical modelling. Consequently, comprehensive studies that combine source apportionment, particle physicochemical properties and respiratory deposition modelling remain scarce.

In the present study, we address the respiratory deposition of size-segregated submicrometer particles originating from separate urban sources in Budapest (Hungary), as a representative of continental central European cities. The main novel features of the present study are (a) explicit source-specific deposition, (b) multi-metric dosimetry, (c) seasonal and long-term analyses, and (d) consideration of hygroscopic effects in the interpretation of the results.

2. Methods

This study is grounded in a robust dataset spanning 11 years of experimentally measured particle number size distributions, which were subjected to source apportionment modelling. The major urban sources identified were utilised as input data for particle deposition modelling of the human respiratory system.

2.1. Urban Aerosol Sources And Exposure Metrics

Most of the experimental work was conducted at the Budapest platform for Aerosol Research and Training (BpART) Laboratory, which represents an urban background environment. An additional year of measurements was performed at the Konkoly Astronomical Observatory, representing a near-city background environment. Details on the measurement sites and their characteristics are provided in Section S1. The particle number size distributions were obtained by a flow-switching-type differential mobility particle sizer. A dry electrical mobility diameter range of 6 to 1000 nm was covered by 27 size channels. The urban background is characterized by a median total particle number concentration of N 6–1000 = 9.5 × 103 cm–3, and a mean UF-to-N 6–1000 ratio and standard deviation (SD) of (79 ± 10)%. The typical daily mean concentration of PM2.5 mass and elemental carbon are 28 and 1.0 μg m–3.

The size distribution dataset was adjusted for local meteorological influences using dispersion correction, and was analysed for source apportionment using positive matrix factorisation (PMF). The PMF modelling was conducted separately for each meteorological season (March, April, May as spring, June, July, August as summer, September, October, November as autumn and December, January, February as winter). The major urban sources identified and considered here include a new particle formation and growth (NPF) source, two road vehicle traffic emission sources divided into a semi-volatile fraction (TSV) and a solid­(soot)-core fraction (TSC), a secondary inorganic aerosol (SIA) occurring predominantly during the non-heating period (spring and summer), and a diffuse urban fugitive (UDF) source characteristic of the heating period (autumn and winter). In the non-heating period, the SIA is mainly associated with sulfate formation from gaseous precursors, predominantly emitted by motor vehicle exhausts. The UDF source during the heating period is primarily linked to physically and chemically aged particles from solid fossil fuel combustion and biomass burning. Details of the aerosol sources are provided in Section S2.

The size-segregated particle number concentrations were also used to derive particle surface area concentrations under the assumption of spherical particles. Both types of the main exposure metrics are presented in Figure S1, whereas their contributions to the seasonal total concentrations, and their modal diameters are summarised in Table S1.

2.2. Deposition Modelling

The deposition of aerosol particles in the human respiratory system was computed using an advanced version of the stochastic lung deposition model IDEAL (Inhalation, Deposition and Exhalation of Aerosols in the Lung). ,− Its performance among other deposition models was analysed by Asgharian et al. and Hofmann, ranking it among the most proficient methods available.

The calculations were performed for a healthy adult Caucasian male using the standardized breathing conditions. Four levels of physical activity were considered: resting (corresponding to 8% of maximum workload), sitting activity (12%), light physical exertion (32%) and heavy physical exertion (64%). These scenarios represent increasing ventilation rates and associated respiratory parameters. The physiological parameters related to these physical activities were chosen according to ICRP. Deposition was modelled by deposition fraction (DF), deposition rate (DR) and surface-density deposition rate (SDR) − using particle number concentration and particle surface area concentration as relevant exposure metrics. The DF value is defined as the ratio of the deposited number of particles to the total number of inhaled particles. This quantity expresses the deposition probability. It was modelled in each airway generation by simulating the path and fate of 10,000 inhaled particles per run. An airway generation denotes a branching level of the respiratory tract, with generation 1 beginning at the trachea and successive generations representing progressively smaller and more distal airways produced by repeated bifurcation. The DR value represents the deposited exposure metric per unit time. It was derived from the DF multiplied by the inhaled exposure metric in a unit time as DR = DF × N i × V T/T C, where N i is atmospheric concentration of the exposure metric i, V T is tidal volume and T C is breathing cycle time. Surface-density deposition rate expresses the deposition rate per unit surface area S of an airway generation or a respiratory region, thus SDR = DR/S. This quantity provides the spatial resolution of exposure at the levels of biological cells and tissues.

The above quantities were calculated along the airway generations and for the main regions of the respiratory track, namely for the extra-thoracic (ET; or oro-naso-pharyngeal) region, the tracheobronchial (TB) tree, the alveolar (AL) region and the entire lung (LN). There are both structural and functional differences between these regions, and the quantification of particle deposition in these distinct compartments is essential for understanding the associated biological and health implications.

Lung-deposited surface area (LDSA) was also considered as a composite physiological exposure metric to express the joint effect of particle surface area of biopersistent particles and their deposition in the human lung. Lung-deposited surface area is defined as atmospheric concentration of particle surface area multiplied by the DF in a lung compartment. We address here LDSA values derived for the entire lung (LDSALN) and its TB tree and AL region (LDSAAL and LDSATB, respectively). In our system of the deposition quantities, LDSA can be expressed as LDSA = N SA × DFSA = DRSA/V T × T c for each physical activity. The DFSA and DRSA denote the DF and DR metrics associated with particle surface area (SA). It is noted that LDSAAL may also be experimentally measured using methods based on diffusion charging. − Details of the deposition modelling are provided in Section S3.

2.3. Data Treatment

The seasonal mean size distributions of particle number concentrations for a given source were similar to each other as far as both their position and magnitude are concerned (Table S1, Figure S1a–d). The situation with the particle surface area size distributions was also similar (Figure S1e–h), when considering that the UDF source was active only in the heating period, whereas the SIA source was relevant only in the non-heating period. Consequently, annual mean DF, DR and SDR values and their SDs across airway generations were derived and interpreted.

The seasonal variability of the mean DF, DR, and SDR values for a given physical activity level was generally modest, with a relative SD typically below 10%. When a relative SD exceeded 25%, the maximum and minimum deposition curves were also shown in the form of shaded bands in corresponding colour around the annual mean line. In these cases, the actual seasons corresponding to the upper and lower borders of the band were indicated in the figures.

3. Results and Discussion

3.1. Deposition across Airway Generations

The differential deposition curves of particle number concentrations characteristic for various urban sources across airway generations based on the annual mean DF, DR and SDR values are presented in Figure . The plots are shown separately for the least and the most intensive breathing conditions considered, i.e., for resting and heavy physical exertion. All curves exhibited a single peak. The maxima for the DF and DR (Figure a–d) occurred between airway generations 17 and 20 depending on physical activity, and exhibited a shoulder on the lower-generation side. The NPF and TSV sources were associated with the highest DF values, and were followed by the TSC and SIA sources with values similar to each other (Figure a,b). The maximum ranged from ca. 2 to 8%, and increased monotonically with physical activity. This can be explained by the fact that both airflow in the lung and tidal volume increase with physical activity, thereby affecting the various particle deposition mechanisms differently. In particular, diffusional deposition, which is the dominant mechanism for particles in this size range, is especially sensitive to these changes in breathing patterns.

1.

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Distributions of deposition associated with the particle number concentration exposure metric across airway generations from various urban sources. Annual mean deposition fractions (a, b), deposition rates (c, d) and surface-density deposition rates (e, f) from new particle formation and growth (NPF), road vehicle traffic emission with semi-volatile fraction (TSV), road vehicle traffic emission with solid-core fraction (TSC), secondary inorganic aerosol (SIA) and diffuse urban (UDF) sources for a healthy adult male under resting (a, c, e) and heavy physical exertion (b, d, f) breathing conditions. The SIA data represent spring and summer, whereas the UDF data express autumn and winter. The error bars indicate one standard deviation. The curves serve to lead the eye.

The TSV and NPF sources showed the highest DR values, followed by the TSC source (Figure c,d). The maximum DR values reached up to 3.5 × 103 min–1 under heavy physical exertion breathing conditions. Given that the median number of airway generations in the model is 23, most deposited particles reached the deep sequences of the lung, and penetration was enhanced by physical activity. Considering that the AL region lacks mucociliary clearance and that it contains thin membranes for gas-exchange, this region is especially sensitive and susceptible to particles. With greater physical activity, both breathing frequency and volume of the breath are increased, which lead to a larger inhaled volume each minute, thus to higher DR values.

The SDR curves (Figure e,f) also displayed a single peak elevating with physical activity, and a shoulder. However, the peak uniformly appeared at much lower airway generation numbers (2–3), and its location was almost constant. The shoulder occurred on the higher-generation side of the peak. The NPF and TSV sources showed the largest SDR values followed by the TSC source. The huge particle burden at cell dimensions occurs in the first few airway generations, which can represent a serious health risk in this part of the lung. The peak location of SDR curves is in line with the fact that pre-neoplastic and primary neoplastic lesions mainly arise in the TB tree, and primarily in the segmental, lobar or tertiary bronchi (involving airway generations 2 to 3).

The deposition curves corresponding to exposure expressed in terms of particle surface area concentration (Figure S2) displayed shapes and tendencies similar to those based on particle number. Specifically, the maximum deposition of the surface area exposure metric occurred at airway generations similar to particle number. At the same time, there were major differences between the corresponding curves. For particle surface area, it was the UDF source followed by the TSC source that displayed the largest rates for both DR and SDR. These two curves stood out from all the others. The NPF source became irrelevant for the deposition rates. These alterations may imply qualitatively different biological effects, damage risk and health consequences of various urban sources, and also highlight the importance of considering different exposure metrics.

3.2. Deposition Fractions across Respiratory Regions

The curves for the annual mean DF values of particle number concentration as a function of physical activity are displayed in Figure S3, and are discussed together with those for the particle surface area exposure metric in Section S4. The compiled regional deposition fractions and the exhaled particle fractions under different breathing conditions reveal several basic differences for various aerosol sources (Figure ). The exhaled fractions associated with each source type appeared independent of physical activity level, yet exhibited substantial variability across different sources. The mean exhaled fractions and SDs were (24 ± 1)%, (42 ± 2)%, (60 ± 2)%, (64 ± 2)% and (73 ± 1)%, for the NPF, TSV, SIA, TSC and UDF sources.

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Regional deposition fractions and exhaled fractions of inhaled particles from various urban sources. Annual mean deposition fraction of particle number concentration in the extra-thoracic (ET) region, tracheobronchial (TB) tree and alveolar (AL) region and the exhaled particle fraction (all in %) from new particle formation and growth (NPF), road vehicle traffic emission with semi-volatile fraction (TSV), secondary inorganic aerosol (SIA), road vehicle emission with solid-core fraction (TSC) and diffuse urban aerosol (UDF) sources for a healthy adult male under resting (workload 8%), sitting activity (12%), light physical exertion (32%) and heavy physical exertion (64%) breathing conditions. The SIA data represent spring and summer, whereas the UDF data express autumn and winter. The sources were organized by modal diameter (d m) in ascending order. The values on the columns show the actual deposited or exhaled particle fractions.

Consequently, the DFs in the total respiratory system did not appear to vary with physical activity for each source type, while their magnitudes altered very substantially across the sources, with means and SDs from (76 ± 1)% (NPF source) to (27 ± 1)% (UDF source; Figure ). The largest DF values in the ET region were between 28% (NPF, resting) and 9% (UDF, resting), whereas the maximum values in the lung reached 62% (NPF, heavy physical exertion) and 22% (UDF, heavy physical exertion). Partitioning of the deposited particles among the main respiratory regions is discussed in more detail in Section . The very significant changes related to the sources are explained by their size distributions, since the total DF decreases with particle size in the related diameter range of 10–200 nm (see also Figure S1a–d).

As far as the particle surface area exposure metric is concerned, the tendencies are similar to those for particle number, while the exhaled fractions are larger and, consequently, the deposition fractions are smaller (Figure S4). The mean exhaled fractions and SDs for the NPF, TSV, SIA, TSC and UDF sources were (54 ± 1)%, (57 ± 1)%, (72 ± 2)%, (73 ± 1)% and (78 ± 3)%, respectively. The related extreme DF values were 15% (NPF, resting) and 6% (UDF, resting) for the ET region, and 38% (NPF, heavy physical exertion) and 19% (UDF, heavy physical exertion) in the lung.

3.3. Deposition Rates across Respiratory Regions

The annual mean DR curves of the particle number exposure metric for the ET region (Figure a) showed a modest increase with physical activity followed by a levelling off at (1–4) × 103 min–1 depending on the source type. The DR curves for the lung were increasing continuously, and reached higher values than in the ET region. The TSV, NPF and TSC sources exhibited the largest deposition rates achieving (22, 20 and 11) × 103 min–1, respectively. Their highest and the lowest seasonal DR curves were obtained for winter and summer, when the atmospheric concentrations tend to be larger and smaller, respectively. Except for the NPF source, which shows the largest and smallest occurrence frequency and thus, atmospheric concentrations during spring and winter, respectively (Figure S1a,d and Ref .). It is noted that the largest DR curves for the TSV source in winter and autumn were very similar to each other. The DR values in the TB tree and AL region increased monotonically with physical activity, and reached the largest values for the TSV, NPF and TSC sources (Figure S5a).

3.

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Deposition rates of particle number concentration in the extra-thoracic (ET) region and the lung (LN) from various urban sources. Annual mean deposition rates (a) and surface-density deposition rates (b) from new particle formation and growth (NPF), road vehicle traffic emission with semi-volatile fraction (TSV), road vehicle emission with solid-core fraction (TSC), secondary inorganic aerosol (SIA) and diffuse urban aerosol (UDF) sources for a healthy adult male under resting (workload 8%), sitting activity (12%), light physical exertion (32%) and heavy physical exertion (64%) breathing conditions. The SIA data represent spring and summer, whereas the UDF data express autumn and winter. The error bars mark one standard deviation. The upper and lower borders of the shaded bands represent the maximum and minimum seasonal values, respectively and the related season for the aerosol sources, which exhibited larger relative standard deviation over seasons. The curves serve to lead the eye.

The shapes of the annual mean SDR curves (Figure b) closely resemble those of the corresponding DR curves (Figure a), both showing a plateau in the ET region and a steadily increasing trend in the lung, as expected. However, the order of the most impacted respiratory compartment was reversed. The SDR values in the ET region exceeded those in the lung by two-three orders of magnitude. The ranking of the sources and their seasonal extremes remained virtually unchanged. The deposition of the TSV, NPF and TSC sources stood out again with values of up to 540, 500, and 240 cm–2 s–1, respectively. In the case of SDR, the depositions in the AL region were replaced by those in the TB tree (Figure S5a,b), similarly to the shift between the ET region and the lung (Figure a,b). The quantification of the relative particle deposition within the main respiratory regions is provided in Section .

The shapes of the deposition curves of particle surface area concentration (Figure ) resemble those of the particle number exposure metric (Figure ), and the most affected respiratory regions (i.e., the lung for DR, and the ET region for SDR) were also identical. However, the order and importance of the sources changed remarkably. The UDF source (in the heating period) uniformly exhibited the largest DR and SDR values for particle surface area metric at approximately 600 μm2 min–1 and 4 × 103 μm2 m–2 min–1, respectively. This ranking results from the largest concentration peak area (58% relative share) and relatively large modal diameter of this source (Table S1, Figure S1g,h). The TSC source was the next contributor (accounting for up to 65% of particle surface area in spring and summer, and 33% in autumn and winter). It became the only dominant source in the non-heating period. The other sources produced markedly lower deposition values.

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Deposition rates of particle surface area concentration in the extra-thoracic (ET) region and the lung (LN) from various urban sources. Annual mean deposition rates (a) and surface-density deposition rates (b) from new particle formation and growth (NPF), road vehicle traffic emission with semi-volatile fraction (TSV), road vehicle emission with solid-core fraction (TSC), secondary inorganic aerosol (SIA) and diffuse urban aerosol (UDF) sources for a healthy adult male under resting (workload 8%), sitting activity (12%), light physical exertion (32%) and heavy physical exertion (64%) breathing conditions. The SIA data represent spring and summer, whereas the UDF data express autumn and winter. The error bars mark one standard deviation. The upper and lower borders of the shaded bands represent the maximum and minimum seasonal values, respectively and the related season for the aerosol sources, which exhibited larger relative standard deviation over seasons. The curves serve to lead the eye.

The DR curves for the AL region increased monotonically with physical activity, and represented higher values than the curves for the TB tree (Figure S6a). The SDR curves for the TB tree were again higher than those for the AL region by 2 orders of magnitude (Figure S6b). The UDF source (in the heating period) and the TSC source uniformly made the largest contributions to the deposition rates on a particle surface area basis.

3.4. Partitioning of Particle Deposition among Respiratory Regions

The differences between particle depositions in the lung and the ET region, as well as between those in the AL region and TB tree, as a function of physical activity were quantified using their deposition ratios. The specific properties of the ratios are discussed in Section S5. As a consequence of these considerations, the regional ratios for DF and DR are identical at a given physical activity, whereas those for SDR are shifted by a constant factor of ≪1 to smaller values with respect to the DF and DR data. This shift causes the partitioning of DF and DR among the main respiratory regions to be reversed when SDR is considered.

Considering jointly the partitioning curves (Figure ) and the total DF values shown as the sum of the lower three columns (for the ET, TB and AL regions; Figure ), it can be seen that the total DF for a given source remained largely independent of physical activity, while the regional distribution of deposited particles changed substantially. In particular, a progressively larger fraction of particles was deposited in the deeper AL region with activity level. Under heavy physical exertion breathing conditions, (2.8 ± 0.2)-times more particles were deposited in the lung than in the mouth and nose with respect to resting. This behaviour was consistently observed across all sources, although at markedly different absolute deposition levels. The magnitude of these effects strongly depended on the modal diameter of the aerosol sources, with total DF decreasing from approximately 76% for NPF to 27% for UDF source at modal diameters of ca. 12 and 170 nm, respectively (Table S1).

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Partitioning of deposited particle number concentration among different respiratory regions from various urban sources. Ratios of annual mean deposition fractions (DF) or deposition rates (DR) in the lung (LN) to that in the extra-thoracic (ET) region (a); and in the alveolar (AL) region to that in the tracheobronchial (TB) tree (b) from new particle formation and growth (NPF), road vehicle traffic emission with semi-volatile fraction (TSV), road vehicle emission with solid-core fraction (TSC), secondary inorganic aerosol (SIA) and diffuse urban aerosol (UDF) sources for a healthy adult male under resting (workload 8%), sitting activity (12%), light physical exertion (32%) and heavy physical exertion (64%) breathing conditions. The SIA data represent spring and summer, whereas the UDF data express autumn and winter. The ratios at unity are marked with a dashed line. The curves serve to lead the eye.

The dependency of the LN/ET partitioning on physical activity (Figure a) appeared to be similar for all sources in both their magnitude and shape, whereas the AL/TB partitioning rates (Figure b) were separated from each other in their vertical position, while they retained a similar shape. In terms of physical interpretation, this reflects the combined effects of enhanced ventilation, increased particle penetration to deeper lung regions under higher breathing rates, and the size-dependent deposition mechanisms, which redistribute particle deposition toward the AL region. Under resting and sitting activity breathing conditions, more particles from the NPF source were deposited in the TB tree than in the AL region. This can be explained by their smallest diameter and the diffusion-controlled deposition mechanism. Under heavy physical exertion, (2.1 ± 0.2)-times more particles were deposited in the AL region than in the TB tree with respect to resting. These changes are caused by the effects of the respiratory parameters (mainly the airflow and tidal volume) for different breathing conditions. In contrast, all LN/ET and AL/TB ratios for SDR imply that this deposition prominently affected the ET region, and the TB tree within the lung (Section S5.).

The tendencies in the LN/ET and AL/TB ratios for the particle surface area exposure metric (Figure S7) resemble those for particle number. The order of the sources was similar, and the increments were also roughly equal. However, there was also a noteworthy difference between them. The LN/ET ratios for the UDF and SIA sources (Figure S7a) reached smaller final ratios than for the other sources.

Regionally resolved deposition metrics have been applied in previous lung dosimetry studies for specific, mostly urban aerosol sources, either in source-dominated environments or following source identification using chemical tracers and particle size characteristics (Section S7.). Source-resolved assessments of the partitioning of particle deposition among respiratory regions with respect to activity level and source type are still limited.

3.5. Lung-deposited Surface Area

The annual mean LDSA values of various urban sources for each physical activity level are summarised in Table . Our results align with the experimental findings from other cities, although considerable variability has been noted across urban environments, geographical regions and seasons. ,

1. Lung-deposited Surface Area From Various Urban Sources .

metric physical activity/source NPF TSV TSC SIA UDF annual
LDSALN Resting 1.04 5.7 19 5.8 29 43
  Sitting activity 1.13 6.2 21 6.5 33 48
  Light exertion 1.21 6.4 22 6.9 37 52
  Heavy exertion 1.36 7.0 25 7.8 43 59
LDSAAL Resting 0.55 3.4 12 3.8 20 29
  Sitting activity 0.63 3.8 15 4.5 24 34
  Light exertion 0.81 4.6 18 5.4 30 41
  Heavy exertion 1.00 5.5 21 6.5 37 49
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a

Annual mean LDSA in the entire lung (LDSALN) and its AL region (LDSAAL; both in μm2 cm–3) from the aerosol sources new particle formation and growth (NPF), road vehicle traffic emission with semi-volatile fraction (TSV), road vehicle emission with solid-core fraction (TSC), secondary inorganic aerosol (SIA), diffuse urban aerosol (UDF) and for all sources combined into annual mean (seasonally weighted). The SIA data represent spring and summer, whereas the UDF data express autumn and winter. Results are shown for a healthy adult male under resting, sitting activity, light physical exertion and heavy physical exertion breathing conditions. The LDSA values in the TB tree can be obtained as LDSATB = LDSALN–LDSAAL.

The LDSALN and LDSAAL values rose with physical activity, while the LDSATB data dropped. The heavy-physical-exertion-to-resting ratios were 1.4, 1.7, and 0.7 for all three LDSA metrics, respectively. Given the substantial changes, the level of physical activity should be explicitly specified together with the LDSA values. Pronounced differences were also observed among the sources. The largest LDSA values were obtained for the UDF source (in the heating period), which made up between 67% (resting) and 73% (heavy exertion) of the annual mean LDSALN values depending on physical activity. This source was followed by the TSC source with an annual mean contribution ± SD of (44 ± 1)%. Contrary, the NPF source showed the smallest annual share (<3%) and relevance (Section .). All LDSA metrics consistently increased from the non-heating to the heating period, with mean factors ± SD of 2.3 ± 0.1, 2.0 ± 0.1, and 2.4 ± 0.1 for the lung, TB tree and AL region, respectively. The largest LDSA values occurred in the AL region. The mean LDSAAL/LDSALN ratios for the UDF source were 70% for resting and 85% for heavy physical exertion. The corresponding shares and SDs for the TSC source were (66 ± 1)% and (83 ± 1)%, respectively.

The LDSAAL size distributions exhibited a single and broad peak (Figure ). The overall distributions reached their maximum values between 100 and 200 nm in the non-heating period, and between 200 and 400 nm in the heating period. The structure confirms that during the non-heating period, the most harmful and prominent source was traffic emission containing soot-core particles (TSC). During the heating period, the solid fuel combustion (UDF) source prevailed, and this was followed by the TSC source. It is noted that the size distributions for separate physical activity levels display structure and order of sources similar to the aggregate distributions. The present LDSAAL size distributions agree with the related characteristics obtained in different atmospheric microenvironments representing urban traffic, residential area and (airport-traffic related) NPF. However, considerable modifications in the structure of the aggregate size distributions can be expected at various location types due to the active aerosol sources actually present in diverse atmospheric environments.

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Size distributions of lung-deposited surface area from various urban sources. Mean size distributions in the AL region (LDSAAL) averaged separately for the non-heating period (spring and summer; a) and for the heating period (autumn and winter; b) from new particle formation and growth (NPF), road vehicle traffic emission with semi-volatile fraction (TSV), road vehicle traffic emission with solid-core fraction (TSC), secondary inorganic aerosol (SIA), diffuse urban (UDF) sources and aggregately for all sources for a healthy adult male considering all physical activity levels. The curves serve to lead the eye.

3.6. Effects of Hygroscopic Growth on Respiratory Deposition in Urban Environments

The potential effects of hygroscopic particle diameter growth under the high RH conditions of the human respiratory tract were estimated and considered in the interpretation of the deposition results. This analysis was made possible by the source-resolved modelling approach adopted in the present study together with experimentally determined hygroscopic growth factors for nearly-hydrophobic (NH) and less-hygroscopic (LH) particles measured in Budapest. Details and further arguments are provided in Section S6. The analysis indicates that neglecting hygroscopic growth leads to a systematic overestimation of regional deposition fractions and deposition densities of submicrometer-sized particles. The corresponding overestimation reaches approximately 15% for NH particles, which are primarily associated with the TSC and UDF sources, and approximately 25% for LH particles originating predominantly from the NPF, TSV and SIA sources. The modest increments are mainly due to the special chemical composition, size distribution and mixing state of urban-type aerosol.

However, the largest overestimations are associated with hygroscopic, and thus generally soluble, submicrometer particles. These particles are considered to be of lower biological relevance with respect to the particle number exposure metric than biopersistent particles or chemically similar particles in the fine and coarse size ranges. Furthermore, the contribution of these particles becomes substantially less important when particle surface area, rather than particle number, is considered as the exposure metric. Moreover, the uncertainty arising from hygroscopicity is of a similar magnitude to the intrinsic uncertainty of the deposition modelling itself (approximately 20–25% for healthy adults). Consequently, hygroscopic growth introduces a quantifiable effect on the deposition estimates, with the largest uncertainty associated with hygroscopic UF particles. Nevertheless, the implications of this uncertainty for the interpretation of biological effects and for the principal conclusions of the present study are most likely constrained.

3.7. Limitations

All deposition calculations in the present study were based on particle number size distributions measured in the diameter range of 6–1000 nm. Particles smaller than 6 nm may occur at elevated concentrations in urban air, particularly during intense NPF events or in the vicinity of certain combustion sources. Such particles exhibit the highest DFs in the ET region (Section .). Their atmospheric residence time (τ) can be assessed from the coagulation sink of 6 nm particles (CoagS6) as τ < 1/CoagS6 ≈ 1.2 h under typical pre-existing aerosol conditions in Budapest. The estimation indicates a rapid removal from the atmosphere. Moreover, these particles are relatively more soluble, and thus likely have lower relevance in terms of adverse biological effects (see Section ). Particles larger than 1000 nm may contribute to deposited surface area due to their large diameters. Such particles are primarily associated with episodic events, including dust storms from arid agricultural and construction areas within the Carpathian Basin, as well as Saharan dust intrusions. Because these events occur relatively infrequently, their influence on long-term (11-year) average deposition characteristics is expected to be limited as well.

Lung-deposited surface area calculations were performed assuming spherical particle geometry. This metric is particularly relevant for biopersistent particles, such as those associated with TSC and UDF sources. For the TSC source, this assumption is likely reasonable. In contrast, UDF particles during the heating period are dominated by emissions from solid fuel combustion, for which deviations from sphericity may be more pronounced. Direct LDSA measurements under representative environmental conditions, including urban road traffic, residential heating, and NPF events, would therefore be highly valuable for validating model-derived LDSA estimates and quantifying uncertainties related to particle morphology.

Our dedicated analysis indicated that the uncertainties associated with the mean source-specific particle size distributions over extended time periods (11 years) are smaller than those arising from the deposition modelling itself. The uncertainties associated with the predicted DFs and corresponding deposition densities are estimated to be 20–25% of the calculated values for healthy adult individuals, with additional – and in some cases larger – variability arising from inter-individual differences in morphometric parameters and respiratory physiology. Consequently, size-distribution uncertainty is not expected to substantially influence the main conclusions of this study.

The results and conclusions of the present study are representative of general urban background conditions. They may differ substantially from those in specific high-exposure microenvironments that are strongly influenced by local sources, such as road traffic, metro systems, airports, special industrial areas, extensive construction activities or residential heating during cold periods, where particle concentrations are higher and/or particle size distributions may differ markedly. A more comprehensive assessment of respiratory deposition across a range of microenvironments – including source-proximal outdoor locations and indoor environments as well – combined with time-weighted or time-activity adjusted personal exposure estimates would provide a more complete understanding of the relationships between PM sources, human exposure and health effects. Future studies could also consider sensitive or vulnerable population groups, such as infants, children, older adults and individuals with pre-existing health conditions, as well as socio-economic factors that may influence exposure patterns. In this context, the present study should be regarded as an exploratory first approximation of real-world conditions rather than a comprehensive assessment.

3.8. Implications and Future Perspectives

Based on the present modelling results and considering the expected differences in the bioavailability of various particle types, the NPF and SIA sources, and to a lesser extent the TSV source, appear to pose a lower potential health risk under conditions of high particle number concentrations sustained over extended periods. The key mechanisms driving the toxicity risk of soluble NPF and TSV particles remain to be elucidated. Conversely, the TSC and UDF sources may represent greater health risks because of the higher biopersistence of their particles. When particle number concentration is used as the exposure metric, the TSC source (vehicle traffic) emerges as the dominant potential risk factor in urban air.

When particle surface area, including its associated surface chemistry, and LDSA are considered, the UDF source (i.e., aged particles from solid fuel combustion and burning) during the heating period and the TSC source (traffic-emitted particles with soot core) become the dominant contributors. The TSC source also remains the primary contributor in the non-heating period. Particles from the UDF source during the heating period and from the TSC source during the non-heating period account for the largest relative shares of particle surface area exceeding 58% and 66%, respectively. In contrast, the contribution from the NPF source is minimal, and finally can become irrelevant if the particles are dissolved.

The highest SDR values of particles from the TSC source were observed in the ET region (Figure b), including the nose. These values were approximately three orders of magnitude larger than those in the lung. The typical size of the TSC particles, characterized by a modal diameter of 70–80 nm (Table S1), enables translocation from the upper nasal cavity via the olfactory sensory neurons, meaning that these particles bypass the blood–brain barrier and directly reach the brain. , If the coating layer of these TSC particles, likely composed primarily of condensed oxygenated organics, sulfates and nitrates also present in vehicle exhaust, is dissolved then the potential for translocation of the remaining smaller soot particles may be even further enhanced. Experimental confirmation of these potential biological effects would require special and methodologically complex experimental studies.

A possible further extension of this research would be to investigate the lung-tissue-delivered deposition dose, a recently proposed metric, and, in particular, to explore its potential relationship with the SDR.

Our results and conclusions finally provide substantial support for emerging concepts in urban air-quality mitigation, which advocate for more effective interventions through a targeted focus on specific aerosol sources and seasons. By identifying pronounced differences in particle characteristics, exposure metrics and respiratory deposition among sources and between heating and non-heating periods, our findings highlight the potential value of source- and season-specific strategies over uniform concentration-based approaches.

Supplementary Material

es6c10850_si_001.pdf (784.4KB, pdf)

Acknowledgments

The Hungarian Research, Development and Innovation Office (Advanced 150835) funded the study.

The source and primary derived data that support the findings of this study together with the source data for Figures – are available in the Zenodo repository under accession code https://zenodo.org/records/17173867?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6IjViZDMzOGYyLTk2ZTYtNDEyZC1iZjY0LWE3NmQ0YjFlMDY4NCIsImRhdGEiOnt9LCJyYW5kb20iOiIwZWFiYTJmZTM5NjQxYTY2MTYzZWI0YWYxY2U4YzdhNyJ9.4jPYbdEpn7VvtVMLZDjnyUheAs2CMAyCzp-1OVJgVCZmS9fK7IIUcBwkTez8yhvlSjYJhLQUz53CkZJU1HOXCg

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.6c10850.

  • Further details of experimental methods and modelling. Basic properties of particle number and particle surface area size distributions (Table S1). Particle number and particle surface area size distributions (Figure S1). Deposition associated with the particle surface area across airway generations (Figure S2). Deposition fractions of particle number in the main respiratory regions (Figure S3). Regional deposition fractions and exhaled fractions of inhaled particles (Figure S4). Deposition rates of particle number in the tracheobronchial tree and the alveolar region (Figure S5). Deposition rates of particle surface area in the tracheobronchial tree and the alveolar region (Figure S6). Partitioning of deposited particle surface area among the main respiratory regions (Figure S7). Assessment of hygroscopic particle growth effect. Comparison with previous studies (PDF)

I.S. conceived the study, designed and supervised the project, led the data analysis, developed the key visualisations, wrote the original draft of the manuscript, and secured funding. M.V. carried out data processing and quality control, produced figures, and contributed to interpretation of the results. Á.F. implemented methodological enhancements in the modelling framework, performed the computations, assisted with the core data analysis, interpreted the model outputs, and contributed to drafting the manuscript. All authors participated in the discussion of the results, and contributed to revising the manuscript.

The authors declare no competing financial interest.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

es6c10850_si_001.pdf (784.4KB, pdf)

Data Availability Statement

The source and primary derived data that support the findings of this study together with the source data for Figures – are available in the Zenodo repository under accession code https://zenodo.org/records/17173867?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6IjViZDMzOGYyLTk2ZTYtNDEyZC1iZjY0LWE3NmQ0YjFlMDY4NCIsImRhdGEiOnt9LCJyYW5kb20iOiIwZWFiYTJmZTM5NjQxYTY2MTYzZWI0YWYxY2U4YzdhNyJ9.4jPYbdEpn7VvtVMLZDjnyUheAs2CMAyCzp-1OVJgVCZmS9fK7IIUcBwkTez8yhvlSjYJhLQUz53CkZJU1HOXCg

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