International Journal of Environmental Research and Public Health Article Effects of Road Dust Particle Size on Mineralogy, Chemical Bulk Content, Pollution and Health Risk Analyses Dídac Navarro-Ciurana 1,2, * , Mercè Corbella 1 and Daniel Meroño 1 1 Departament de Geologia, Facultat de Ciències, Universitat Autònoma de Barcelona (UAB), Edifici Cs s/n, 08193 Bellaterra, Spain; merce.corbella@uab.cat (M.C.); daniel.meronog@autonoma.cat (D.M.) 2 Grup MAiMA, SGR Mineralogia Aplicada, Geoquímica i Hidrogeologia, Departament de Mineralogia, Petrologia i Geologia Aplicada, Facultat de Ciències de la Terra, i Institut de Recerca de l’Aigua (IdRA), Universitat de Barcelona (UB), c/ Martí i Franquès s/n, 08028 Barcelona, Spain * Correspondence: didac.navarro@uab.cat Abstract: Because of the rising environmental and health concerns associated with atmospheric pollution caused by potentially toxic elements (PTEs), several road dust studies have been performed across the world in recent decades. This paper illustrates the effects of particle size on the PTE contents, mineralogical composition, environmental pollution and health risk assessments in road dust from Barcelona (Spain). The samples were sieved into five size fractions ranging from <45 to 500–800 µm. Although the major mineral contents (tectosilicates, phyllosilicates, and carbonates) were profuse in all fractions, the identified inhalable PTE particles (e.g., Fe, Cr, Cu, Zn, Ni, and REE), with size < 10 µm, were more pervasive in the finest fraction (<45 µm). This is consistent with the concentrations measured: the finest fractions were richer in PTEs than the coarser ones, resulting in a direct correlation with the enrichment factor (EFx ), geo-accumulation (Igeo ), and non-carcinogenic (HI) and carcinogenic (CRI) values. Igeo and EFx values can be appropriate tracers for some common elements (e.g., Zn, Sb, Sn, Cu, and Cr), but they do not seem adequate for anthropogenic particles accumulated at concentrations similar to the geogenic background. Overall, the HI and CRI values obtained in Barcelona were acceptable, reflecting no serious health impacts in the study area, except for Cr. Our results suggest that fine dust particles are a more suitable fraction to conduct pollution Citation: Navarro-Ciurana, D.; and health risk assessments than coarser ones, although the EFx , Igeo , HI, and CRI threshold values Corbella, M.; Meroño, D. Effects of should be redefined in the future to include all emergent pollutants as well. In summary, monitoring Road Dust Particle Size on Mineralogy, Chemical Bulk Content, programs should include at least the road dust evaluation of <45 µm particles, which can be performed Pollution and Health Risk Analyses. with a simple sieving method, which is both time- and cost-effective. Int. J. Environ. Res. Public Health 2023, 20, 6655. https://doi.org/10.3390/ Keywords: road dust; size fractions; potentially toxic elements; pollution; health risk ijerph20176655 Academic Editor: Giacomo Alessandro Gerosa 1. Introduction Received: 2 June 2023 Ambient particulate matter (PM) pollution is one of the global challenges plaguing Revised: 28 July 2023 modern society [1]. PM that is deposited on roads, usually called “road deposited sedi- Accepted: 31 July 2023 ments”, “street dust”, or “road dust”, are significant pollutants of the urban environment Published: 26 August 2023 because it contains high levels of poisonous metals and organic contaminants [2–4]. Road dust particles function as carriers of potentially toxic elements (PTEs) [5]. They are per- sistent and non-biodegradable, and they often tend to remain in the environment for Copyright: © 2023 by the authors. decades after the termination of the source of the emissions [6]. Therefore, characterizing Licensee MDPI, Basel, Switzerland. the dust particle sources and chemical and mineralogical conformations on urban road This article is an open access article surfaces is essential for developing an appropriate pollution evaluation and designing distributed under the terms and mitigation strategies. conditions of the Creative Commons Road dust in the urban environment is a heterogeneous composite from multiple Attribution (CC BY) license (https:// natural geogenic and anthropogenic sources [7–10]. Potential geogenic sources of road creativecommons.org/licenses/by/ deposited particles include erosion of surrounding soil and local geological formations, as 4.0/). well as atmospheric deposition of transported geogenic particles [11,12]. Anthropogenic Int. J. Environ. Res. Public Health 2023, 20, 6655. https://doi.org/10.3390/ijerph20176655 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2023, 20, 6655 2 of 26 sources of particle pollutants in road dust include industrial emissions (power plants, coal combustion, the metallurgical industry, auto repair shops, the chemical industry, etc.) and traffic-related activities, such as tire and brake abrasion products, automotive three-way catalytic abrasion and wear, vehicular combustion exhaust, pavement wear, construction materials, road salt, road paint, and pedestrian debris [9,10,12–14]. Furthermore, road dust is subject to mixing processes with particles from different sources. Therefore, the charac- terization and determination of the source of road-deposited particles can be complex [15]. In the last two decades, a large number of studies have been carried out all over the world to determine the concentrations of pollutants in road dust, with the aim of identifying their sources and transport pathways, as well as their spatial distribution, bioavailability, and related health risks [16]. From low-income countries, where long-term exposure to traffic-generated dust has been estimated to cause 1.5 to 2 million premature deaths every year (mostly children and women) [17], to high- and middle-income coun- tries, the awareness of the potential adverse impacts of dust on health has increased in recent decades. The components of road dust particles have been associated with mul- tiple health effects, especially on the respiratory and cardiovascular systems, including allergy, carcinoma, asthma, chronic obstructive pulmonary disease, and emergency car- diovascular disease issues [3]. Despite the fact that the concentrations of pollutants in road dust depend on its mineralogical composition and the particle size and shape, miner- alogical and morphological studies of road dust particles are scarcer than chemical bulk composition studies. In attempts to identify metal pollutant sources and assess health risks, dust samples have been fractionated according to the particle sizes in several studies. In a review by Lanzerstorfer [18], the highest metal pollutant concentrations were found in the finest size fractions of the road dust. As demonstrated by Lanzerstorfer and Logiewa [19], the heavy metal concentration of a road dust sample with a size fraction of <37 µm can be eight times larger than the same sample with an upper size fraction limit of 2000 µm. Many road dust publications contain tables and figures comparing concentration results of road dust samples from different studies, illustrating quite different particle size distributions, sometimes ranging from 2 to 2000 µm. Although this could lead to misinterpretations [18], and efforts have been taken to standardize the optimal particle size range to be studied in road dusts, there is still no consensus among researchers. For instance, in air quality studies, road dust particles of <10 µm in size are widely used [8], whereas in stormwater runoff studies, fractions of <38 µm, <63 µm, or <75 µm are applied [20–22]. In addition, pollution and health risk assessment studies of road dust PTEs have used a wide range of upper particle size limit fractions: 63 µm, 100 µm, 125 µm, 850 µm, or up to 2000 µm [23–26]. The use of this wide range of road dust fraction sizes hinders the implementation of standardized and intercomparable pollution and health risk monitoring programs. The present study aims to determine the effects of road dust particle size on the mineralogical composition, heavy metal contents (environmental pollution), and health risk assessments in order to suggest the most feasible size fraction for future implementation in road dust PTE monitoring programs. The study area chosen to illustrate the road dust particle size effect, Barcelona (northeast Iberian Peninsula), is one of the most air-polluted urban areas in Western Europe [27]. 2. Materials and Methods 2.1. Study Area The study was carried out in the outskirts of Barcelona, with the sampling sites located also in the adjacent municipalities of Hospitalet del Llobregat and Sant Feliu de Llobregat/Sant Joan Despí (Figure 1). Barcelona is one of the European cities with the highest vehicle density (6.100 vehicles·km−2 ; [28]) and is the second most densely populated city of Spain (16.114 inhabitants km−2 ; [29]). Hospitalet del Llobregat, a city geographically adjacent to Barcelona, has also high traffic-clogged urban areas and is even denser than Barcelona (21.407 inhabitants km−2 ; [29]). In both city centers, the Int. J. Environ. Res. Public Health 2023, 20, x FOR PEER REVIEW 3 of 27 Int. J. Environ. Res. Public Health 2023, 20, 6655 3 of 26 city of Spain (16.114 inhabitants km−2; [29]). Hospitalet del Llobregat, a city geographically adjacent to Barcelona, has also high traffic-clogged urban areas and is even denser than predominance of Barcelona narrow(21.407 inhabitants streets km−2; [29]). (street canyons) andIn both city centers, a dearth of greentheareas predominance hinder theof narrow streets (street canyons) and a dearth of green areas hinder dispersion of pollutants. The Zona Franca-La Pedrosa is an industrial neighborhood ofthe dispersion of pollutants. The Barcelona located toZona the SFranca-La Pedrosa of Hospitalet is an industrial de Llobregat neighborhood (Figure 1), which alsoof Barcelona includes located variousto the S of Hospitalet de Llobregat (Figure 1), which also includes various logistics and customs logistics and customs areas. It currently has a total surface area of 600 hectares, which areas. It currently has a total surface area of 600 hectares, which represents 6% of Barce- represents 6% of Barcelona’s total land, and comprises more than 400 companies. Emissions lona’s total land, and comprises more than 400 companies. Emissions from these, plus from these, plusthose those from heavy motor traffic, coupled with the Mediterranean climate from heavy motor traffic, coupled with the Mediterranean climate (warm and hu- (warm and humid) andthe mid) and the geography geography ofzone, of the the zone, contribute contribute to the accumulation to the accumulation of of airborne pollutants airborne pollutants over over the city. the city. Figure location Figure 1. Geographical 1. Geographical location of the road dustofsampling the road dust sitessampling sites (H1 to H6) in(H1 theto H6) in municipali- outskirt the outskirt munici- palities of Barcelona (modified from [30]). ties of Barcelona (modified from [30]). Sant Feliu de Llobregat and Sant Joan Despí are located to the SW of Barcelona and Sant Feliu de Llobregat and Sant Joan Despí are located to the SW of Barcelona and Hospitalet de Llobregat. Both cities have a large-scale industrial development, with a sig- Hospitalet de Llobregat. Both cities have a large-scale industrial development, with a nificant transport infrastructure involving trains and abundant road traffic. Since 1967, significant transport infrastructure there has involving been a cement trains and plant operating abundant in Sant Feliu deroad traffic.municipality Llobregat Since 1967,(Figure there has been a1).cement plant This plant operatingtointhe contributes Sant Feliuofde release Llobregat PTEs municipality in the area, (Figure which in turn 1). constitute an This plant contributes additionaltosource the release ofthe of dust in PTEs in roads nearby the area, which in turn and surrounding constitute environment [31].an The total additional source of dustunder population in thepotential nearby direct roadsinfluence and surrounding environment of the cement, [31]. industrial and The emis- transport total populationsions under potential is 44,400 direct in inhabitants, influence ofaround an area of the cement, 20 km2 industrial [29]. and transport emissions is 44,400 inhabitants, in an area of around 20 km2 [29]. 2.2. Sample Sites and Dust Sampling 2.2. Sample Sites andRoad Dust dust Sampling samples were collected in July and October of 2022 (Table 1). As wash-off Road dust from rainfall samples wereremoves a portion collected of the in July androad dust available October of 2022 on the surface (Table 1). As[32–36], wash-offsampling was performed in all localities after 15 dry days. Three road types were from rainfall removes a portion of the road dust available on the surface [32–36], sampling(Figure sampled was performed in all localities after 15 dry days. Three road types were sampled (Figure 1 and Table 1): (i) roads located in urban and suburban residential zones (H1, H2, H3 and H6); (ii) roads ubicated in land areas with intense industrial activity (H4); and (iii) roads situated in mixed residential and industrial areas (H5). Road dusting is performed in the place with the highest amount of road dust within a radius of 200 m around each sampling site, in order to collect sufficient material for chemical and mineralogical analyses. Int. J. Environ. Res. Public Health 2023, 20, 6655 4 of 26 Table 1. Samples and sampling sites. Geographical Area Coordinates 1 Sample Weight Sample Date Altitude (masl) 2 Area Type Road and Sample Locations Swept (g) Easting Northing (m2 ) Hospitalet de Llobregat Mare de Déu H1 15 July 2022 425,328 4,577,568 7 Urban/residential de Bellvitge Ave. Paved shoulder of a 41 5662 divisional island near to Hospital Hospitalet de Llobregat La Marina H2 15 July 2022 424,994 4,578,775 8 Urban/residential Blvd.Paved shoulder adjacent to 30 1998 Elementary School Hospitalet de Llobregat Fabregada Ave. H3 15 July 2022 425,351 4,579,051 8 Urban/residential 19 1020 Paved shoulder of a median strip Hospitalet de Llobregat Botànica St. H4 16 July 2022 426,418 4,577,595 6 Industrial 87 3150 Paved shoulder Urban/residential Barcelona Guayaquil St. Paved H5 27 October 2022 433,650 4,588,295 14 732 5438 and industrial shoulder and clogged sewer Sant Feliu de Llobregat BV-2001 Suburban/ H6 29 October 2022 419,948 4,580,789 17 carriageway Paved shoulder and bike 945 9455 residential lane near to crops 1 WGS84, UTM zone 31; 2 masl: m above sea level. Int. J. Environ. Res. Public Health 2023, 20, 6655 5 of 26 Approximately 27 kg of composite road dust, between 1 and 9 kg for each selected site (Table 1), were collected sweeping the selected roads with plastic bristle brushes and dustpans; the sampled material was stored in plastic bags. In Hospitalet de Llobregat, four samples (H1 to H4) were collected in different residential and industrial zones of the city. A sample was swept in the paved shoulder of a divisional island in a high-traffic avenue (H1, 41 m2 swept: Figure 2a and Table 1), which constitutes one of the entrances of the Bellvitge Hospital, that is perpendicular to the C-31 dual carriageway access road to Barcelona in the SW (Figure 1), one of the busiest roads of the city (avg. 70,000 vehicles per day). Additionally, in Hospitalet de Llobregat city center, a road dust sample was obtained by sweeping the paved shoulder of a medium-traffic street (H2, 30 m2 swept: Figure 2b and Table 1), which is located adjacent to an elementary school. Another road dust composite was collected in the paved shoulder of a medium-traffic avenue median strip (H3, 19 m2 swept: Figure 2c and Table 1) that crosses a residential zone of Hospitalet del Llobregat. As a representative of an industrial zone, a road dust sample was swept from the paved Int. J. Environ. Res. Public Health 2023, 20, x FOR PEER shoulder REVIEW of a low-traffic Hospitalet de Llobregat Street median strip (H4, 87 m2 swept: 5 of 27 Figure 2d and Table 1) in the Zona Franca-La Pedrosa area. Figure2.2.Location Figure Locationof ofsampling samplingsites: sites:(a) (a)Hospitalet HospitaletdedeLlobregat LlobregatMare MarededeDéu DéudedeBellvitge BellvitgeAvenue; Avenue; (b) Hospitalet de Llobregat La Marina Boulevard; (c) Hospitalet de Llobregat Fabregada (b) Hospitalet de Llobregat La Marina Boulevard; (c) Hospitalet de Llobregat Fabregada Avenue; Avenue; (d) Hospitalet de Llobregat Botànica Street; (e) Barcelona Guayaquil Street; (f) Sant Feliu de Llobre- (d) Hospitalet de Llobregat Botànica Street; (e) Barcelona Guayaquil Street; (f) Sant Feliu de Llobregat gat BV-2001 suburban road. The red lines indicate the swept road surface. BV-2001 suburban road. The red lines indicate the swept road surface. 2.3. Sample Treatment Other two samplesand Mineralogical (H5 and H6) wereandobtained Chemicalin Analysis Barcelona and Sant Feliu de Llobre- Road gat/Sant dust Joan samples Despí were dried at limit, respectively. In 40 °C and the Barcelona, then dry-sieved sample using stainless was obtained steel in the paved sieves with shoulder roada range and a of aperture clogged sizes sewer of 800, 500, disposed on a250, 125concrete street and 45 µm to obtain gutter m2subsam- five (H5, 732 swept: ples per Figure 2esample. and TableThese 1), asieve size ranges low-traffic road were selected that runs for comparison parallel with carriageway to the B-10 dual soil categori- zation:road access 500–800 µm (coarse to Barcelona citysand), center250–500 µmThis in the NE. (medium accesssand), road is125–250 µm (fine the second sand), busiest in 45–125 the city (very (avg. fine sand) 110,000 and <45per vehicles (siltday). and clays). Finally,The large in the sizeFeliu Sant fraction (subsamples del Llobregat andofSant >800 Joan µm)Despí BV-2001 suburban was discarded road, which as it contained visibleseparates extraneousthe cities matterwith sucha crop zone, as leaf the asphalt litter, paved particles, small pieces of brick, glasses, plastics, and concrete and other debris. The other weighed subsamples were homogenized and quartered into three subsets for geochemical and mineralogical analysis. The chemical composition of the 30 obtained subsamples was determined using In- ductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) and ICP-Mass Spec- Int. J. Environ. Res. Public Health 2023, 20, 6655 6 of 26 shoulder road’s median strip and a bike lane were swept (H5, 732 m2 swept: Figure 2f and Table 1). 2.3. Sample Treatment and Mineralogical and Chemical Analysis Road dust samples were dried at 40 ◦ C and then dry-sieved using stainless steel sieves with a range of aperture sizes of 800, 500, 250, 125 and 45 µm to obtain five subsamples per sample. These sieve size ranges were selected for comparison with soil categorization: 500–800 µm (coarse sand), 250–500 µm (medium sand), 125–250 µm (fine sand), 45–125 (very fine sand) and <45 (silt and clays). The large size fraction (subsamples of >800 µm) was discarded as it contained visible extraneous matter such as leaf litter, asphalt particles, small pieces of brick, glasses, plastics, and concrete and other debris. The other weighed subsamples were homogenized and quartered into three subsets for geochemical and mineralogical analysis. The chemical composition of the 30 obtained subsamples was determined using Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) and ICP-Mass Spectrometry (ICP-MS) in accordance with the standards applied at Activation Laboratories Ltd. of Ancaster, Ontario, Canada [37]. Actlabs is a SCC GLP (Standards Council of Canada, Good Laboratory Practice) compliant facility with 45 techniques certified by ISO/IEC 17025:2017 (International Organization for Standardization/International Electrotechnical Commission) and is FDA (Food and Drug Administration) registered and inspected. The ICP-OES method was used to determine the concentrations of major oxides (SiO2 , Al2 O3 , Fe2 O3 , MnO, MgO, CaO, Na2 O, K2 O, TiO2 and P2 O5 ) and selected trace elements (Ba, Be, Sr, V and Zr). In total, 1 g of sample was mixed with lithium metaborate and lithium tetraborate and fused in an induction furnace. Subsequently, the molten material was poured into a solution of 5% nitric acid containing an internal standard and mixed continuously during ~30 min until it dissolved completely [37]. The samples are run for major oxides and selected trace elements (Code 4B: [37]) on a combination simultaneous/sequential Thermo Jarrel-Ash ENVIRO II ICP or a Varian Vista 735 ICP spectrometers. Total contents should be between 98.5% and 101%. Those samples with lower results were scanned for minor and trace elements using ICP-MS. Samples with low totals, however, were automatically re-fused and re-analyzed. Low reported totals may indicate the presence of sulfidic/sulfated sulfur, as well as other elements like Li or F, which had not been scanned [37]. The detection limits (LODs) for elements analyzed using ICP-OES are shown in Table S1. The ICP-MS method, which was used to determine the concentrations of minor and trace elements (As, Ce, Co, Cr, Cs, Cu, Dy, Er, Eu, Ga, Gd, Hf, Ho, La, Lu, Mo, Nb, Nd, Ni, Pb, Pr, Rb, Sb, Sc, Sm, Sn, Ta, Tb, Th and Y), involves melting 1 g of sample with a lithium metaborate and lithium tetraborate mixture in an induction furnace. A 0.25 g fused and dried sample aliquot is digested with a mixture of HClO4 , HNO3 , HCL and HF at 200 ◦ C until fumed and is then diluted volumetrically with an aqua regia to 250 mL. The diluted samples were analyzed for trace elements (Code 4B2: [37]) with the Perkin Elmer Sciex ELAN 6000, 6100 or 9000 ICP-MS. The instrument is recalibrated every 40 samples. The LODs and upper detection limits for elements analyzed via ICP-MS are shown in Table S1. Quality control and quality assurance (QC/QA) of chemical composition results was achieved through the analysis of reagent blank, 14 certified reference materials (CRMs, Table S2: [38–46]) and 17% of analytical duplicates (Table S3). The concentration of analytes in reagent blanks were measured using the same method described above in order to evaluate external metal contamination from analytical procedures. Blank samples showed no detectable analytes, indicating no contamination (Table S1). The measurement accuracy was monitored with the CRMs used (Table S4). Mean recovery rates of the CRMs major oxides and trace elements are between 89% and 118%, showing good accuracy as values are between 70% and 120% [47]. Nevertheless, recoveries for MnO, MgO, and CaO in NIST 696 (>200%) were unacceptably high due to the concentration of analytes being close to the LOD. On the other hand, mean recovery rates of the CRMs trace elements are between Int. J. Environ. Res. Public Health 2023, 20, 6655 7 of 26 95% and 104%, showing good accuracy. The precision of the analysis was calculated for each analyte as median values of the Relative Difference (RPD) between road dust sample duplicates. Median RPD values ranged from 0 to 9% for most analytes. Higher median RPD values were obtained for Pb (median RPD: 12%), Th (median RPD: 14%) and W (median RPD: 16%). For Loss on Ignition (LOI) determination, 10 g of each dust subsample was taken and carefully poured in a clean crucible and weighed using an analytical balance (gravimetric method). The weighed samples were then placed in an electric muffle furnace and heated for 1 h at 950 ◦ C to determine the loss on ignition. LOI, with a LOD of 0.01%, is the combined loss of volatile matter such as combined structural water (H2 O) and carbon dioxide coming from carbonates. The principal mineralogy of each dust subsample (30 in total) was determined via X-ray diffraction (XRD) analysis of powdered build-up solids, previously powdered to <30 µm using an agate mortar and then deposited on aluminum discs. The analy- ses were performed using X’Pert PRO MPD ALFA 1 (Marvel Panalytical, Almelo, The Netherlands) with a θ-θ geometry, an incident Cu-Kα, and a Cu anode X-ray tube and a PIXcel1D detector at the Servei de Difracció de Raig X of the Universitat Autònoma de Barcelona (UAB). The analytical conditions were 40 kV and 40 mA working power, with 3◦ divergence window and 0.05◦ reception window. The selected count time was 0.026◦ (2θ) angular step every 50 s in a 2θ angular range from 5◦ and 60◦ . The software X’Pert High Score and the PDF2 data base (ICDD: International Center for Diffraction Data) were used to evaluate the analyzed spectra. The mineral reference patterns data used are shown in Table S5 [48–55]. The mineralogical study was complemented with a particulate characterization, where representative fractions of each sample were embedded as a thin “layer” in 5 cylindrical (d = 2.5 cm) resin mounts (hereafter called monolayers). After conducting a metallograph- ically polished of monolayers using a monocrystalline shape edges diamond abrasive paste of 1 µm, an ultrasonic bath was used to remove any remaining polishing material from the sample. To exclude contamination of the abrasive paste used, control dust sam- ples were mounted directly on pin stubs. The samples were coated with Au-Pd alloy to improve conductivity and better image resolution after mounting the monolayers on a carbon tape attached to aluminum studs. The morphological and textural features and the semi-quantitative composition of particles in the roadside dust samples embedded in monolayers were examined at the Servei de Microscòpia at UAB using a Zeiss Merlin (Zeiss, Jena, Germany) field emission scanning electron microscope (FE-SEM) equipped with an Energy Dispersive X-ray spectroscope (EDX) to characterize the elements. The operating conditions were an accelerating voltage of 20 kV, a beam current of 1 nA and a working distance of 15 mm, with a mean EDX count time of 30 s per analysis. Acquisition of FE-SEM images allowed to determine the size distribution of road dust particles, which was based on the longest Feret diameter size and conducted using Oxford-Inca software. 2.4. Pollution Assessment Methodology To evaluate road dust source and the impact of human activities on heavy metal enrichment, it is a common practice to calculate the enrichment factor of an element X (EFx ) in the sampled material with respect to its natural abundance in the earth’s crust, according to the following equation (e.g., [56]): (Xi /Eref )sample EFx = (1) (Xi /Eref )background where Xi is the concentration of the element of interest and Eref the reference element concentration for normalization. Eref should have low variability and is used to determine the degree of metal pollution. Consequently, caution must be exercised in the choice of the reference substrate due to the great variability in trace element contents of rocks of Int. J. Environ. Res. Public Health 2023, 20, 6655 8 of 26 even similar bulk composition [14]. To minimize possible error sources, the average crustal composition was not used in this study, as it may be different from the substrate of the study area; instead, the sum of Al2 O3 , MgO, Na2 O, K2 O, TiO2 , and P2 O5 concentrations reported in the Congost River basin (Table S6: [57]), which is located in the Barcelona Province, was chosen as the geochemical background. Pollution degrees according to EFx are classified into five categories [56,58,59]: (i) EFx < 2 means deficiency to minimal enrichment; (ii) 2 ≤ EFx < 5 corresponds to moderate enrichment; (iii) 5 ≤ EFx < 20 means significant enrichment; (iv) 20 ≤ EFx < 40 indicates very high enrichment; and (v) EFx ≥ 40 means extremely high enrichment. The geo-accumulation Index (Igeo ) of metals is another indicator of the presence and intensity of anthropogenic contaminant deposition on road dusts. It is defined with the following equation [60]:   Cn Igeo = log2 (2) 1.5Bn where Cn is the measured concentration of the elements in road dust samples and Bn refers to the element background value in the Congost River basin (Table S6: [57]). The constant 1.5 helps to observe natural fluctuations and detect very small anthropogenic influences of elements. Müller [60] defined seven Igeo classes: (i) Igeo ≤ 0 indicates no contamination; (ii) 0 < Igeo ≤ 1 refers to uncontaminated to moderate contamination; (iii) 1 < Igeo ≤ 2 means moderate contamination; (iv) 2 < Igeo ≤ 3 indicates moderate to heavy contamination; (v) 3 < Igeo ≤ 4 corresponds to heavy contamination; (vi) 4 ≤ Igeo < 5 means heavy to extreme contamination; and (vii) Igeo ≥ 5 indicates extremely contaminated material. 2.5. Health Risk Assessment Methodology The model used in this study to identify human exposure to road dust PTEs and the associated health risks (non-carcinogenic and carcinogenic) for children and adults in different fractionated samples is based on those developed by the United States Environ- mental Protection Agency (USEPA: [61,62]). The model applied assumes that local residents are exposed to metals in road dust through three pathways: direct ingestion, inhalation through mouth and nose and dermal absorption of dust particles. According to the Exposure Factors Handbook [63] and the Technical Report of USEPA [64], the equations for calculating the average daily dose (ADD: mg kg−1 day−1 ) of PTEs through the three exposure routes are as follows: C × IngR × CF × EF × ED ADDing = (3) BW × AT C × InhR × EF × ED ADDinh = (4) PEF × BW × AT C × SA × CF × AF × ABF × EF × ED ADDdermal = (5) BW × AT where the ADDing , ADDinh and ADDdermal are the average daily dose (mg kg−1 day−1 ) exposure to metals through ingestion, inhalation, and dermal contact, respectively. The detailed description of the values of exposure factors for children and adults applied to the above models are presented in Table 2. Int. J. Environ. Res. Public Health 2023, 20, 6655 9 of 26 Table 2. Values of exposure factors for heavy metals doses for children and adults. Factor Description Unit Children Adults References C Concentration of metals in road dusts mg kg−1 Current study IngR Ingestion rate of road dust mg day−1 200 100 [65,66] EF Exposure frequency days year−1 27 27 [67] ED Exposure duration years 6 24 [65,66] BW Average body weight kg 15 70 [62,68] AT Average time days 365 × ED 365 × ED [68] CF Conversion factor kg mg−1 1 × 10−6 1 × 10−6 [67] InhR Inhalation rate of road dust m3 day−1 7.63 12.8 [65,69] PEF Particular emission factor m3 kg−1 1.36 × 109 1.36 × 109 [65,66] SA Surface area of skin exposed to road dust cm2 1600 4350 [69] AF Skin adherence factor mg cm−2 0.2 0.7 [70,71] ABF Absorption factor (Dermal) unitless 0.001 0.001 [67] In order to analyze the human health risks due to PTEs exposure in the road dust, the HQ (chronic hazards quotient), HI (cumulative non-carcinogenic hazard index) and CRI (carcinogenic risk index) were computed for some selected elements and pathways applying the flowing equations: ADDx HQx = (6) Rf D HI = ∑ HQx = HQing + HQinh + HQdermal (7) CRI = LADD × SF (8) where x refers to the pathway considered (ingestion, inhalation and dermal), Rf D and SF are the values of reference’s dose and chronic slope factor, respectively, and LADD (mg kg−1 day−1 ) is the lifetime average daily dose exposure to carcinogen metals, for cancer risk, which is expressed as C × EF   CRchild + EDchild CRadult + EDadult LAAD = × + (9) AT × PEF BWchild BWadult where CR is the contact frequency. In this study, CR for ingestion is the same value of IngR × CF, for inhalation route is equal to InhR /PEF, and dermal pathway is expressed as CRdermal = SA × AF × ABS × CF [72]. The Rf D values for ingestion inhalation and dermal contact used for HQ and HI calculations were available for the three pathways for most of the elements considered in this study (Al, Fe, Mn, V, Ba, Cr, Co, Ni, Cu, Zn, As, Mo, Sb, and Pb) except for Sr, Tl and U, wherein the Rf D values for inhalation were not available (Table S7). HQ ≤ 1 indicates that adverse effects are not likely to occur, and thus can be considered to have negligible hazard, while HQ > 1 suggests that there is a high probability of non-carcinogenic effects to occur [68]. To estimate the overall developing hazard of non-carcinogenic effects, it is assumed that toxic risks have additive properties. Therefore, HI value, which is the sum of HQ for different substances through each pathway, refers to the total risk of non- carcinogenic for a signal PTE [69,73]. Values of HI ≤ 1 imply that no significant risk of non-carcinogenic effects is likely to occur. On the other hand, there is a chance that non- carcinogenic effects occur when HI >1, and the probability increases with increasing HI values [65,66]. The CRI estimates values which act as a probability for an individual to develop any type of cancer through lifetime exposure to carcinogenic hazards [24,73]. In this study, the carcinogenic risk from road dust was estimated for the carcinogens including Cd, Co, Cr and Ni, Pb and As through the possible routes. Slope factors were available for inhalation pathway only for the most carcinogen elements considered in this study (Cr, Co, Ni, As, Int. J. Environ. Res. Public Health 2023, 20, 6655 10 of 26 and Pb), except for As and Pb, for which slope factors for ingestion and dermal absorption pathways were also available (Table S7). The USEPA recommended that the value of CRI < 1 × 10−6 can be regarded as negligible, whereas CRI > 1 × 10−4 is likely to be harmful to human beings. Therefore, the acceptable or tolerable risk for regulatory purposes is in the range of 1 × 10−6 to 1 × 10−4 [65,66,68]. Nonetheless, other regulatory agencies use a lower threshold value of 1 × 10−5 [67]. 3. Results 3.1. Road Dust Size Distribution As expected, the mass of road dust obtained per unit area, calculated using the data of Table 1, was highest in the high-traffic road (130 g m−2 ; H1), followed by areas with Int. J. Environ. Res. Public Health 2023, 20, x FOR PEER REVIEW 10 of 27 medium-traffic (55–66 g m−2 ; H2 and H3) and low-traffic (7–36 g m−2 ; H4, H5 and H6) volumes. But the mass collected was also dependent on the fraction size and road use (Figure 3). The mass percentages ranges of the fractions (<45 µm, 45–125 µm, 125–250 µm, 250–500 of fraction µm,the500–800 studiedµm and >800 samples µm) were contained high2.6–10.0%, amounts6.2–23.0%, of organic 14.8–25.4%, 13.5–21.2%, matter as decomposed 7.6–12.5% leaf and 10.4–55.2%, litter, except with in industrial meanwhich zones, valuesinofthe 4.3%, 15.8%, studied 19.3%, area 17.2% 10.0% and are characterized by a33.5%, scar- respectively city of green(Figure 3a). vegetation areas with Fractionation of bulk or soils. samplesatolarger Although various particle number of sizes revealed samples that collected theindustrial in >800 µm was and the dominant in mixed landmass usesfraction would of bethe dust from necessary all sites,their to accept except the industrial apparent differ- ones with ence (Figure 3b). Nevertheless, industrial the size and residential distribution areas of studied as statistically road dusts significative, discarding our data the still reflect >800 µm mass fraction depicts maximum values in the 125 to 500 µm size range. a distribution dependence of road dust particles with the use of land, as it occurs in other This result is consistent world with the size distribution study of other worldwide road dusts (e.g., [74]). sites [75,76]. Figure 3. Particulate Figure 3. Particulate size size distribution distribution of of road road dusts: dusts: (a) (a) size-fractional size-fractional relation relation to to mass mass percentage; percentage; (b) average size distribution of particles in road dust according to the land use (b) average size distribution of particles in road dust according to the land use type; type; (c) (c) average average cumulative mass percentage of road dust with respect to land use cumulative mass percentage of road dust with respect to land use type. type. 3.2. Road Dustfrom Samples Chemical urbanComposition and suburban residential areas contained less mass percentage of fine Theparticles (<45 µm;of3.0%) concentrations andminor major, more and masstrace of coarse particles elements (>800 in road dusts 38.5%) than µm;separated by industrial ones or with mixed land uses (Figure 3b). Furthermore, the cumulative size are shown in Table S8 and summarized in Figure 4. Overall, the highest concentration particle size of distribution most major, minor curves andof road trace dust from elements wereindustrial associated and withurban/suburban the fine (<45 µm) residential size frac- zoneswhich tion, were slightly different, although is in concordance both showed with previous worldwide similar casetrends studies(Figure 3c).The [76–79]. Road dust excep- contained tions are formore K2O,mass Na2fraction O and Ba.percentages (less than also These components 800 µm) in industrial present zones in relation a direct correlation trend to urban and between size suburban fraction andresidential areas and concentration, of mixed which land uses. is opposite to theThe larger other size fraction components. of The the studied samples contained high amounts of organic matter as decomposed most abundant trace metal measured (in weight) was Ba (average for all fractions: 1013 leaf litter, except mg kg−1in industrial ). Other tracezones, metalswhich in the studied that followed were Zn, area Cu,areZr,characterized Cr, rare earth by a scarcity elements (REE) of green areas with vegetation or soils. Although a larger number of samples and Ni with an average concentration value in the finest fraction of 1006.67, 511.67, 397.17, collected in industrial and in mixed land uses would be necessary 288.33, 174.65 and 75.00 mg kg−1, respectively (Figure 4). to accept their apparent difference with industrial and residential areas as statistically significative, our data still reflect a distribution dependence of road dust particles with the use of land, as it occurs in other world sites [74,75]. Int. J. Environ. Res. Public Health 2023, 20, 6655 11 of 26 3.2. Road Dust Chemical Composition The concentrations of major, minor and trace elements in road dusts separated by size are shown in Table S8 and summarized in Figure 4. Overall, the highest concentration of most major, minor and trace elements were associated with the fine (<45 µm) size fraction, which is in concordance with previous worldwide case studies [75–78]. The exceptions are for K2 O, Na2 O and Ba. These components also present a direct correlation trend between size fraction and concentration, which is opposite to the other components. The most abundant trace metal measured (in weight) was Ba (average for all fractions: 1013 mg kg−1 ). Other trace metals that followed were Zn, Cu, Zr, Cr, rare earth elements (REE) and Ni Int. J. Environ. Res. Public Health 2023, with an PEER 20, x FOR average concentration value in the finest fraction of 1006.67, 511.67, 397.17, REVIEW 11 of 288.33, 27 174.65 and 75.00 mg kg−1 , respectively (Figure 4). Figure Figure4.4.Box Boxplots plotsofofroad roaddust dustcomponent component concentrations concentrationsdistribution per per distribution sizesize fraction of major fraction of major (a), minor (b) and trace elements (c). The color bars for each element refer to the sample (a), minor (b) and trace elements (c). The color bars for each element refer to the sample size size fraction, with red color fraction, with representing the finer parts red color representing concentrations the finer and green color parts concentrations representing and green the coarser the color representing ones. coarser ones. 3.3. Road Dust Mineral Components The mineralogical composition of the dust samples is shown in Table S9 and the sta- tistical analysis with respect to size distribution for the studied road dusts is displayed in Figure 5. Regardless of the sampled site, all studied road dusts are constituted with the same major mineral components: tectosilicates, phyllosilicates and carbonates. The most tional to grain size. Overall, the average mass proportion of albite, anorthite and chlorite was constant regardless of grain size. Furthermore, anomalies in the XRD background signal of the 250–500 µm and 500–800 µm fractions of the H3 sample were identified, sug- gesting a significant proportion of amorphous components, such as glasses. The results obtained were consistent with previously published research data (e.g., [80]). Int. J. Environ. Res. Public Health 2023, 20, 6655 12 of 26 It is important to note that phyllosilicate crystals tend to orientate during sample preparation, modifying the XRD intensity of reflection compared to a random orientation. This preferred orientation leads to an interference mainly with the quartz XRD peak, 3.3. Road which Dust Mineral commonly leadsComponents to overestimation of clay minerals and mica mass percentages and quartz Theunderestimation mineralogical (e.g., [81]). Nevertheless, composition of the dust this serious samples interference is shown must in Table S9have oc- and the curred statisticalin all samples, analysis withand thus fractionated respect road dust to size distribution forsamples can be the studied compared road with each dusts is displayed other in Figureanyway. The massofmineral 5. Regardless content the sampled site,calculated all studied and compared road dusts arewith the totalwith constituted weight the of each fractionated dust sample is shown in Figure 6. Except for same major mineral components: tectosilicates, phyllosilicates and carbonates. The mostorthoclase, a high posi- tive correlation abundant of weights mineral between(KAl was muscovite mineral content 3 Si3 O 10 (OH)and total35%), 2 : avg. dust followed for each size fractions by anorthite (CaAl in 2 Si2 O8 : avg. all sampling sites18%), quartz is clear. (SiO2 : avg. The relations 15%),mineral between albite (NaAlSi mass and3 O8fraction : avg. 11%) mass andare calcite although linear, (CaCO3 : theavg. 11%).logarithmic doubly Other mineral components plot appear found as curves. Thewere chlorite equations (avg.these relating 5%), dolomite two (avg.have variables 4%)higher and orthoclase slopes for(avg. 6%), which muscovite (0.31, were present R2: 1.00) thanonly in aquartz for the few fractions and an- of the studied orthite (0.17, R2samples. These : 0.99), calcite mineral (0.10, phases R2: 0.98), were albite also (0.09, R2observed under (0.06, : 0.92), dolomite FE-SEM-EDX, R2: 0.87) constituting or the main chlorite (0.04, matrix R2: 0.92) of the (Figure 6f).fractionated studied dusts. Figure Figure 5. 5. Bow Bowand whisker and plots whisker of major plots mineral of major mass mass mineral proportions respectrespect proportions to road to dust particle road dust sizes. particle sizes. The mass percentage of muscovite was directly proportional to grain size, whereas quartz and carbonates (calcite and dolomite) mass proportions were inversely proportional to grain size. Overall, the average mass proportion of albite, anorthite and chlorite was constant regardless of grain size. Furthermore, anomalies in the XRD background signal of the 250–500 µm and 500–800 µm fractions of the H3 sample were identified, suggesting a significant proportion of amorphous components, such as glasses. The results obtained were consistent with previously published research data (e.g., [79]). It is important to note that phyllosilicate crystals tend to orientate during sample preparation, modifying the XRD intensity of reflection compared to a random orientation. This preferred orientation leads to an interference mainly with the quartz XRD peak, which commonly leads to overestimation of clay minerals and mica mass percentages and quartz underestimation (e.g., [80]). Nevertheless, this serious interference must have occurred in all samples, and thus fractionated road dust samples can be compared with each other anyway. The mass mineral content calculated and compared with the total weight of each fractionated dust sample is shown in Figure 6. Except for orthoclase, a high positive correlation of weights between mineral content and total dust for each size fractions in all sampling sites is clear. The relations between mineral mass and fraction mass are linear, although the doubly logarithmic plot appear as curves. The equations relating these two variables have higher slopes for muscovite (0.31, R2 : 1.00) than for the quartz and anorthite (0.17, R2 : 0.99), calcite (0.10, R2 : 0.98), albite (0.09, R2 : 0.92), dolomite (0.06, R2 : 0.87) or chlorite (0.04, R2 : 0.92) (Figure 6f). Int. Int.J. J.Environ. Environ.Res. Res.Public PublicHealth 2023,20, Health2023, 20,6655 x FOR PEER REVIEW 13 13 ofof2726 Figure 6. Figure 6. Plots Plotsofof major majormineral mass mineral content mass (in a (in content logarithmic scale) vs. a logarithmic totalvs. scale) weight totalfor the different weight for the different fractions of road dust: (a) <45 µm fraction; (b) 45–125 µm fraction; (c) 125–250 µm(d) fractions of road dust: (a) <45 µm fraction; (b) 45–125 µm fraction; (c) 125–250 µm fraction; 250– fraction; 500 µm fraction; (e) 500–800 µm fraction; (f) <800 µm fraction. Vertical color bars correspond to the (d) 250–500 µm fraction; (e) 500–800 µm fraction; (f) <800 µm fraction. Vertical color bars correspond different sample localities (H1 to H6) and color curves are the best fitting functions for each mineral to thefraction. and different sample localities (H1 to H6) and color curves are the best fitting functions for each mineral and fraction. FE-SEM-EDX revealed that small heavy microparticles (size < 10 µm) are more per- FE-SEM-EDX revealed that small heavy microparticles (size < 10 µm) are more per- vasive in the finest (<45 µm) than in coarser dust fractions. Therefore, the microparticle vasive in the finest (<45 µm) than in coarser dust fractions. Therefore, the microparticle sizes and compositions of the finest dust fraction (<45 µm) are more suitable for studies of sizes and compositions of the finest dust fraction (<45 µm) are more suitable for studies of heavy metal or PTE characterization of road dust than any other fraction. Figure 7 shows heavy metal or PTE characterization of road dust than any other fraction. Figure 7 shows the mineral distribution of 234 PTE microparticles from the finest fraction of sample H1 the mineral distribution of 234 PTE microparticles from the finest fraction of sample H1 in a surface of 120 mm22 (Figure 7a). Although the studied heavy metal particles diameter in a surface of 120 mm (Figure 7a). Although the studied heavy metal particles diameter ranges from 1.5 to 15.3 µm, 71% of them were between 2 and 5 µm (Figure 7b). Most of ranges from 1.5 to 15.3 µm, 71% of them were between 2 and 5 µm (Figure 7b). Most of the the particles (63%) constituted of only Fe with sizes between 1.5 and 15.3 µm, suggesting particles (63%) constituted of only Fe with sizes between 1.5 and 15.3 µm, suggesting they they were native Fe or Fe-(oxi)hydroxides, and 13.2% corresponded to Fe-alloys with Cr, were native Fe or Fe-(oxi)hydroxides, and 13.2% corresponded to Fe-alloys with Cr, Ni, Cu, Ni, Cu, Ti, W and Zn with sizes of 2.3 to 10.1 µm. This abundance of Fe microparticles is Ti, W and Zn with sizes of 2.3 to 10.1 µm. This abundance of Fe microparticles is consistent consistent with the high Fe concentration in the finest road dust fractions (Figure 4). with the high Fe concentration in the finest road dust fractions (Figure 4). A small number of particles (3.8%) with Ba and S, corresponding to barium sulfate A small number of particles (3.8%) with Ba and S, corresponding to barium sulfate as was reported in previous works (e.g., [14]), were present with diameters between 2.8 as was reported in previous works (e.g., [14]), were present with diameters between 2.8 and 4.6 µm. As barium is a heavy element, it may correspond with the high overall Ba and 4.6 µm. As barium is a heavy element, it may correspond with the high overall Ba concentration obtained (Figure 4). Furthermore, Cu microparticles are less abundant concentration obtained (Figure 4). Furthermore, Cu microparticles are less abundant (1.3%): (1.3%): their size ranges from 2.0 to 9.4 µm and correspond to native Cu or Cu-(oxi)hy- their size ranges from 2.0 to 9.4 µm and correspond to native Cu or Cu-(oxi)hydroxide, droxide, Cu-Zn alloys and Cu sulfates or sulfides. Metallic Ni, Ti and Zn, as well as Zn-Ti Cu-Zn alloys and Cu sulfates or sulfides. Metallic Ni, Ti and Zn, as well as Zn-Ti alloy alloy particles were identified with diameters ranging from 2.3 to 13.7 µm. Microparticles particles were identified with diameters ranging from 2.3 to 13.7 µm. Microparticles of Ca, of Ca, which could correspond to Ca-(oxi)hydroxide and Ca-silicate (10.7%), were identi- which could correspond to Ca-(oxi)hydroxide and Ca-silicate (10.7%), were identified with fied with spherical morphologies and sizes ranging from 2.7 to 12.1 µm. It is important to spherical morphologies and sizes ranging from 2.7 to 12.1 µm. It is important to remark Int. J. Environ. Res. Public Health 2023, 20, x FOR PEER REVIEW 14 o Int. J. Environ. Res. Public Health 2023, 20, 6655 14 of 26 remark that 1.7% of heavy particles were constituted by rare earth elements (REE), ma that 1.7% of heavy particles were constituted by rare earth elements (REE), mainly Ce Ce andand La. La. Figure 7. Characterization of road dust particles with diameters of less than 45 µm: (a) backscattered Figure 7. Characterization of road dust particles with diameters of less than 45 µm: (a) backscatt electron image identifying toxic heavy metal particles in a representative section; (b) histogram of electron image identifying toxic heavy metal particles in a representative section; (b) histogra PTE particle size distribution and composition determined with FE-SEM-EDX. PTE particle size distribution and composition determined with FE-SEM-EDX. 3.4. Evaluation of the Road Dust Pollution 3.4. Evaluation Enrichmentoffactors the Road (EFxDust ) werePollution calculated for each size fraction of road dust and it allowed for the distinction Enrichment factorsbetween natural (EFx) were sources from calculated for anthropic each sizeorigins of metals. fraction of road Cudust an was the most enriched element in the studied road dust samples followed by Zn, Sb and allowed for the distinction between natural sources from anthropic origins of metals Sn. The average EFx values for these elements in all road dust fractionated samples were was the 5most between and 9enriched (Table S10),element in athe indicating studiedenrichment significant road dustand samples followed therefore a dominantby Zn, Sb Sn. The average anthropogenic EFx values contribution. or non-geogenic for these elements inthe The rest of allconsidered road dustmetals fractionated EFx averagesamples w between values were5 andlower 9 (Table than 5, S10), indicating and more commonly a significant lower thanenrichment 1, suggestingand that therefore they coulda domin mainly have natural anthropogenic or sources (Table S10). non-geogenic Moreover, it can contribution. Thealso be of rest observed that the averaged the considered metals EFx a EF values for most metals were inversely proportional to age values were lower than 5, and more commonly lower than 1, suggesting x particle size (Figure 8), that is, that t the finest dust (<45 µm) was more easily enriched and more susceptible to having anthropic could mainly have natural sources (Table S10). Moreover, it can also be observed that origins than coarser dust (500–800 µm). Except for Zn, road dust with sizes between 500 averaged and 800 µmEF x values for most metals were inversely proportional to particle size (Fig showed EFx values lower than 5 (Figure 8), indicating a minimal to moderate 8), that is, the enrichment with finest dust respect (<45 to the µm) was more background valueseasily and wereenriched and morea susceptible thus considered priori to to h ing haveanthropic been mainly origins derivedthan fromcoarser natural dust (500–800 sources. Overall,µm). Except forfactors the enrichment Zn, road of Zn,dust Sb, with s Sn and Cu500 between wereandsimilar, 800with µm the EFx being showed EFxhigher valuesinlower the finest thanfractions (avg. 8), 5 (Figure Zn indicating = 10.8; avg. a mini Sb moderate to = 12.2; avg.enrichment Sn = 9.0; avg.with Cu =respect 9.3) thantointhe coarser dust (avg.values background Zn = 5.7; andavg. were Sb thus = 4.3; conside avg. Sn = 1.5; avg. Cu = 5.9) (Figure 8). Zn and Sb EFx with size <45 µm was twice as large aaspriori to have been mainly derived from natural sources. Overall, the enrichment fac the same dust sample with a size of 500–800 µm, whereas for Cu and Sn, EFx ’s were of Zn,and three Sb,sixSntimes andhigher, Cu were similar, with the EFx being higher in the finest fractions (a respectively. Zn = 10.8; avg. Sb = 12.2; avg. Sn = 9.0; avg. Cu = 9.3) than in coarser dust (avg. Zn = avg. Sb = 4.3; avg. Sn = 1.5; avg. Cu = 5.9) (Figure 8). Zn and Sb EFx with size <45 µm twice as large as the same dust sample with a size of 500–800 µm, whereas for Cu and EFx’s were three and six times higher, respectively. Int. Int.J.J.Environ. Environ.Res. Res.Public PublicHealth 2023, 20, Health2023, 20, 6655 x FOR PEER REVIEW 15 15 of of2726 Figure 8. Bow Figure 8. Bow and whisker plots of EFxx of ofselected selectedelements elementsfor forthe thedifferent differentroad roaddust dustparticle particlesize size fractions (color fractions (color codes codes as in Figure 4). The The geo-accumulation geo-accumulationindex index(I(Igeo geo) values values for for the theselected selectedmetals metalsininterms termsofofthethevarious vari- dust size size ous dust fractions are are fractions presented presented in in Figure 9. 9.Except Figure Exceptfor forCu, Cu, Zn, Sn,Ni, Zn, Sb, Sn, Ni,Cr Crand andZr, Zr, and and based based on on Muller Muller scales [60], [61], the average average Igeo valuesfor geovalues forall alldust dustsizes sizeswere werenegative, negative, suggesting suggesting no no contamination with respect respect to to those those elements elements(Table (TableS10). S10).Nevertheless, Nevertheless,asas with the EF values, with the EFxx values, the average I for most metals increased with decreasing geo for most metals increased with decreasing particle geo particle size (Figure 9). Overall, size (Figure 9). Overall, average I values indicate that road dust <45 µm is geovalues indicate that road dust <45 µm is moderately geo moderately to to heavily heavilypolluted pollutedby byZn, Zn,Sb, Sb,Sn Snand andCu, Cu,moderately moderatelycontaminated contaminatedbybyCr, Zr,Zr, Cr, P2 P O25O, 5Hf, Ni , Hf, and Ca,Ca, Ni and unpolluted unpolluted to to moderately moderately polluted pollutedbybyPb, Pb,Nb, Nb,Mo, Mo,TiO TiO22,, Fe2OO33,,Mn MnandandSr, Sr,and and unpolluted unpolluted by by the the rest of the analyzed metals, metals, such such as as Co, Co, REE REEor orV, V, among amongothers. others. 3.5. Health Risk Characterization 3.5.1. Exposure Assessment The average daily exposure doses of dust contaminants in the Barcelona area for both children and adults (∑ADD for the three routes) are listed in Tables S11 and S12 (ADDing , ADDinh and ADDdermal ). Overall, the toxic metal exposure amounts for children are one order of magnitude higher than values for adults (Table S11). In terms of total exposure amounts, Mn, Sr, Cr, Cu and Zn were one order of magnitude higher (children: 1 × 10−4 mg kg−1 d−1; adults: 1 × 10−5 mg kg−1 d−1) than V, Ni and Pb (children: 1 × 10−5 mg kg−1 d−1; adults: 1 × 10−6 mg kg−1 d−1) and two orders higher than Co, As, Mo and U (children: 1 × 10−6 mg kg−1 d−1; adults: 1 × 10−7 mg kg−1 d−1). The maximum exposure doses for children and adults were 3.9 × 10−2 and 4.3 × 10−3 mg kg−1 d−1, respec- tively, both for Al in the finest fraction (<45 µm) and by Fe (children: 3.7 × 10−2 mg kg−1 d−1; adult: 4.1 × 10−3 mg kg−1 d−1; Table S11). Total metal exposure amounts for the two people groups according to the particle sizes was very different. Similar to EFx and Igeo , the daily exposure amounts of each considered PTE was inversely proportional to particle size, as these values are mainly controlled by the metal concentrations of fractionated road dust samples. The contribution of the finest road dust (<45 µm) to the total toxic metal exposure ranged from 19.1 to 38.5%, being 1.6 to 2.2 times higher than the contribution of the coarsest dust (500–800 µm), which varied from 8.6 to 19.1%. Int. Int.J. J.Environ. Environ.Res. Res.Public PublicHealth 2023,20, Health2023, 20,6655 x FOR PEER REVIEW 16 16 ofof2726 Figure9.9. Bow Figure Bow and and whisker whisker plots plots of of the the geo-accumulation geo-accumulation index index (I (Igeo) for selected elements in the geo ) for selected elements in the different road dust particle size fractions (color codes as in previous figures). different road dust particle size fractions (color codes as in previous figures). 3.5. Health 3.5.2. Risk Characterization Non-Carcinogenic Risk of PTEs 3.5.1.The Exposure chronicAssessment hazard quotient (HQ) and cumulative non-carcinogenic hazard index (HI) valuesThe foraverage PTEs are summarized daily exposure doses in Table S13 and of dust Table S14,inrespectively. contaminants the Barcelona The constituent area for both PTEs of the children and non-carcinogenic adults (∑ADD for riskthefor bothroutes) three childrenareandlistedadults are illustrated in Tables S11 and S12 in (ADD Figureing10. , HQ ADD indices inh andfor ADD thedermal three exposurethe ). Overall, routes toxiccalculated for individual metal exposure amountsroad for dust PTEsare children didonenot exceed order ofthe acceptable magnitude levelthan higher of 1 values (Table for S13), thus(Table adults indicatingS11). negligible non-carcinogenic toxic risk [66]. In concordance with PTEs average In terms of total exposure amounts, Mn, Sr, Cr, Cu and Zn were daily exposures, theoneaverage order HQ values of magni- indicate that the non-carcinogenic human health risk tude higher (children: 1 × 10 mg kg d ; adults: 1 × 10 mg kg d ) than V, Ni and −4 −1 −1 was −5 higher −1 for−1 children than it was Pb for adults. For children and adults, risk of Cr was (children: 1 × 10 mg kg d ; adults: 1 × 10 mg kg d ) and two orders higher than Co, −5 −1 −1 −6 −1the−1 highest with 32.5%, followed by Sb, As,Al, MoMn, andPb, Ba, Fe and U (children: 1 ×Cu. 10 Risk −6 mg values kg d ;ofadults: −1 −1 Sr and1 Co × 10were −7 mgthekg lowest, −1 d ). The −1 meaning maximum they were leastdoses exposure hazardous to human for children and health. adults were The contribution 3.9 × 10−2 andpercentage 4.3 × 10−3 mg ofkgSb−1and d−1, Al were respec- 18.2% tively,and both11.0%, for Al in respectively, whereas the finest fraction (<45forµm)theand otherby considered Fe (children:PTEs 3.7 × the 10−2 contribution mg kg−1 d−1; percentages were less than 5%. Cr in the road dust, adult: 4.1 × 10 mg kg d ; Table S11). Total metal exposure amounts for the two −3 −1 −1 which is mainly sourced from Fe-Cr people alloys groups according to the particle sizes was very different. Similar to EFx and Igeo, the dailyof (Figure 7) of the <45 µm fraction, showed the highest HI values, with a maximum 0.18. Nevertheless, exposure amounts the sumconsidered of each of individual PTEHQs wasfor all PTEsproportional inversely considered,to which determines particle size, as the hazard index (HI), did not exceed the threshold value these values are mainly controlled by the metal concentrations of fractionated road dust of 1 [66] for both children and adults samples. and Theforcontribution all studied of fractionated the finest road samples. dust (<45This µm)implies that there to the total are no toxic metal harmful exposure health rangedeffects from 19.1 due to to 38.5%, the PTE loads being 1.6intothe 2.2investigated times higherroad thandust. the contribution of the coars- In addition, est dust (500–800 µm), HI values whichfor varied bothfrom people 8.6 togroups 19.1%. differed greatly according to par- ticle sizes (Figure 10): (i) for Cr, Co, Mn and Sb, the non-carcinogenic health risk of particles <45 µm was 3.4Risk 3.5.2. Non-Carcinogenic to 4.0 oftimes PTEs higher than particles with range sizes between 500 and 800The chronic hazard quotient Zn µm; (ii) for Mn, V, Ni, Cu, (HQ) andand U, the contribution cumulative of particles with non-carcinogenic size smaller hazard index than 45 µm to the non-carcinogenic health risk is 2.3 (HI) values for PTEs are summarized in Table S13 and Table S14, respectively. The to 2.9-fold higher than particles constit-of 500–800 uent PTEs µm; ofand (iii) for Al, Fe, Ba,risk the non-carcinogenic andfor Pb,both the children finest particles and adultscontribute 1.0 to 1.9 are illustrated intimes Fig- more ure 10.to HQ non-carcinogenic indices for the risk three than coarseroutes exposure ones. calculated for individual road dust PTEs did not exceed the acceptable level of 1 (Table S13), thus indicating negligible non-carcino- genic toxic risk [67]. In concordance with PTEs average daily exposures, the average HQ values indicate that the non-carcinogenic human health risk was higher for children than it was for adults. For children and adults, risk of Cr was the highest with 32.5%, followed by Sb, Al, Mn, Pb, Ba, Fe and Cu. Risk values of Sr and Co were the lowest, meaning they 18.2% and 11.0%, respectively, whereas for the other considered PTEs the contribution percentages were less than 5%. Cr in the road dust, which is mainly sourced from Fe-Cr alloys (Figure 7) of the <45 µm fraction, showed the highest HI values, with a maximum of 0.18. Nevertheless, the sum of individual HQs for all PTEs considered, which deter- mines the hazard index (HI), did not exceed the threshold value of 1 [67] for both children Int. J. Environ. Res. Public Health 2023, 20, 6655 17 of 26 and adults and for all studied fractionated samples. This implies that there are no harmful health effects due to the PTE loads in the investigated road dust. Figure 10. Figure 10. Mean Meanhazard hazardindex index(HI) (HI)values valuesof of PTEs forfor PTEs children andand children adults calculated adults fromfrom calculated the dif- the ferent road dust particle size fractions concentrations. different road dust particle size fractions concentrations. 3.5.3.In addition, HIRisk Carcinogenic values for both people groups differed greatly according to particle of PTEs sizesThe (Figure 10): (i) for Cr, carcinogenic risks were Co, Mn and Sb,for calculated the Cr,non-carcinogenic As, Pb, Co and Nihealth(Tablerisk S15),ofreflecting particles <45 likelihood the µm was 3.4 of to 4.0 times being infectedhigher with than cancer particles with dust due to road range sizes between ingestion, dermal500 and 800 absorption µm; inhalation and (ii) for Mn,of V, these Ni, Cu, Zn andOfU,the metals. thefive contribution of particles with selected carcinogenic sizein metals smaller than road dust, 45 µm Cr to the non-carcinogenic contributed between 92.0%health risk isto2.3the and 99.7% to overall 2.9-foldrisk, higher than particles followed by As. of A500–800 similar µm; and (iii)of observation forcarcinogenic Al, Fe, Ba, and risk,Pb, the finest mainly particles Cr, from roadcontribute dust exposure1.0 tohas 1.9 been timesreported more to non-carcinogenic risk than coarse ones. in other cities [62,81,82]. As can be seen in Figure 11, the carcinogenic risk of Cr was in the tolerable range (between 1 × 10−6 and 1 × 10−4 ), whereas for Pb, Co and Ni, it could 3.5.3. be Carcinogenic ignored. Only the Risk of PTEs finest fraction (<45 µm) showed a tolerable carcinogenic risk of As, whereasThefor the coarsest carcinogenic fractions risks (>45 µm), for were calculated the Cr, riskAs, wasPb,inCo theand limit Nibetween tolerable (Table S15), and reflecting negligible carcinogenic threshold. It is noticeable that all the samples the likelihood of being infected with cancer due to road dust ingestion, dermal absorption fractionated to sizes lower than 45 µm 1 × 10 −5 level, which and inhalation of showed carcinogenic these metals. Of the five risk selected values for Cr above the carcinogenic metals in road dust, Cr was deemedbetween contributed unacceptable92.0% byandmany99.7%regulatory agencies to the overall [67], but by risk, followed notAs. USEPA (threshold A similar obser- value vationof × 10−6 : [65,66]). of 1carcinogenic This carcinogenic risk, mainly Cr, from roadrisk dustlevel for Crhas exposure also decreased been reportedwith the in other increase in particle sizes: about 66% of the total fractionated samples at 45–125 cities [63,82,83]. As can be seen in Figure 11, the carcinogenic risk of Cr was in the tolerable µm and less than range16.6% of samples (between 1 × 10−6with andsize ranges 1 × 10 between −4), whereas for125 Pb,and Co800andµmNi,showed it couldCRI values on be ignored. the Only 1the 10−5 order. × finest fraction (<45 µm) showed a tolerable carcinogenic risk of As, whereas for the coarsest fractions (>45 µm), the risk was in the limit between tolerable and negligible car- cinogenic threshold. It is noticeable that all the samples fractionated to sizes lower than 45 µm showed carcinogenic risk values for Cr above the 1 × 10−5 level, which was deemed unacceptable by many regulatory agencies [68], but not USEPA (threshold value of 1 × 10−6: [66,67]). This carcinogenic risk level for Cr also decreased with the increase in particle Int. J. Environ. Res. sizes: about Public Health 66% 2023, 20, of the total fractionated samples at 45–125 µm and less than 16.6% of 6655 18 of 26 samples with size ranges between 125 and 800 µm showed CRI values on the 1 × 10−5 order. Figure 11. MeanFigure 11. Mean carcinogenic carcinogenic risk index (CRI)riskvalues index of(CRI) valuesPTEs selected of selected PTEs with with respect respect to the to the intake route intake by theroad route by the different different dustroad dustsize particle particle size (in fractions fractions (in µm). µm). Limits of Limits of CRIs according CRIs according to USEPAto USEPA [65,66] and DeetMiguel [66,67] and De Miguel al. [68]et(other al. [67] (other agencies). agencies). 4. Discussion 4. Discussion 4.1. Particle Size Effect in Road Dust Geochemical Features 4.1. Particle Size Effect in Road Dust Geochemical Features Grain size has a large impact on particle hazard level [83]. Particles smaller than Grain sizeapproximately has a large impact 100–125on particle µm could hazard easilylevel [84]. Particlesunder be re-suspended smaller than ap- dynamic conditions, such proximately 100–125 µm could easily be re-suspended under dynamic conditions, as wind and vehicles running, and can enter the nose and mouth during normal breathing. such as wind and vehicles running, and Consequently, the can enter with particles the nose sizesand mouth µm <100–125 during can normal breathing. be considered as health hazards. Consequently,Although the particles the number of samples collected is reduced, adding up hazards. with sizes <100–125 µm can be considered as health the percentages of <45 Although the number µm and of samples 45–125 µm collected fractions is reduced, (Figure 3b),adding up the the highest riskpercentages to humansof in<45 Barcelona occurs µm and 45–125inµm fractions (Figure 3b), the highest risk to humans in Barcelona industrial parts (33.0%), followed by mixed urban/residential and industrial areas occurs in industrial parts (18.6%)(33.0%), and urban followed by mixed and suburban urban/residential (residential) and industrial zones (17.3%). The study areas by Acosta et al. [79] (18.6%) and urban and higher reported suburban mass(residential) percentages zones of fine (17.3%). Theµm) dust (<50 studyonby Acosta et industrial al. (33.6–59.3%) zones [80] reported higher mass percentages of fine dust (<50 µm) on industrial zones than urban areas (26.2–38.8%) of Murcia city (Spain), which is in accordance with our study (33.6– 59.3%) than urban areas (Figure 3). (26.2–38.8%) Nonetheless,ofvehicle Murciaexhausts city (Spain), did notwhich is in accordance dominate the sourceswithof the study road our study (Figure 3). Nonetheless, vehicle exhausts did not dust particles, as they are mostly smaller than 10 µm in diameterdominate the sources of Thus, [84]. the weathering study road dust particles, soils, as theyand road erosion are pavement mostly smaller than 10 atmospheric degradation, µm in diameter [85]. Thus, particles and anthropogenic weathering soils, roadseem matter erosion and pavement to control the main degradation, mass of dust sourcesatmospheric particlesbyand as suggested an- Ferreira-Baptista and thropogenic matter seem [24] De Miguel to control the main mass and Hjortenkrans et al.of[85]. dust sources as suggested by Fer- reira-Baptista and De TheMiguel [24] and of dependency Hjortenkrans geochemical et al. [86]. composition of road dust on their particles The dependency of geochemical size (Figure composition 4) has significant healthof road dust on their implications. Fineparticles sizeenriched particles (Fig- with PTEs ure 4) has significant are more health easily implications. resuspendedFine [24],particles whereasenriched with PTEs larger particles are more eas- are mobilized typically through ily resuspended saltation and creeping [24], whereas larger [86,87], particles thus arebeing mobilizedable to deteriorate typically to smaller through particles, increas- saltation ing the health and creeping [87,88], thus beingrisk. Although the finest to able to deteriorate particles smallerare more reactive, particles, larger increasing theparticles could also have health risk. Although theafinest negative impact particles on thereactive, are more environment, as they could also larger particles be transferred have and mo- bilized to soils and be dissolved to runoff water causing pollution (e.g., [88]). In any case, given that the highest levels of PTEs were unequivocally associated with the finest fraction (<45 µm; Figure 4), a detailed mineralogic characterization under FE-SEM-EDX, specifically on heavy metal particles, was deemed necessary [89]. Int. J. Environ. Res. Public Health 2023, 20, 6655 19 of 26 4.2. Mineralogical Composition of Fractionated Road Dust As the major mineral content for each fraction was similar across sample sites (Figure 6), irrespective of traffic density, as commonly occurs in other world roads dusts (e.g., [90–92]), it was deduced that there must be a unique source unrelated to traffic or land use for the most abundant minerals present in road dust (muscovite, anorthite, quartz, albite, calcite, chlorite, dolomite, and orthoclase). Some studies confirmed that there are inputs from surrounding soils and weathered rocks to the road surfaces [90,92,93]; nev- ertheless, other potential anthropogenic contributions, common in all roads (cement, gravel, building materials, road paint or degraded aggregates from asphaltic pavement [94–96]), cannot be ruled out. These common minerals also pose human health risk. For example, the carbonatic dust with particle size of <10 µm causes eye and respiratory tract irritation [97], or the typical sharp edges of mica (i.e., muscovite) are also hazardous [79], as they cause “mica pneumoconiosis”, and in some cases interstitial pulmonary fibrosis [98]. Therefore, the composition of these particles is also an important determinant of health effects [99] and should be considered in risk assessment studies. The essentially constant major mineral components in the different fractions of road dust (Figure 6) could be a key to remediation. A recent investigation [100] reveals the potential of road dust to be used as glass-based products for PTEs retention. As the optical, thermal, and rheological properties of glasses are directly influenced by the mineralogical composition of raw material, the uniformity of road dust content on major mineral con- stituents makes it a potential candidate for metal and dust remediation at an industrial scale by means of vitrification and manufacturing glasses. The distribution and mineralogical characteristics of pollutants within the finest size fractions of road dust is quite important because this is the dust that can be resuspended. According to a study by Amato et al. [8], the contribution of road dust re-suspension to PM10 in Barcelona was 37%. In our study, the majority of finest identified PTE particles show size ranges between 2 and 5 µm (Figure 7) of the so called thoracic dust (<10 µm, can pass through the nose and throat, reaching the lungs); only a small portion corresponds to respirable dust (<2.5 µm), which will penetrate into the gas exchange region of the lungs [62]. The mineralogical features of most heavy particles observed in finest dust points to an anthropic origin, as previous studies have demonstrated [89,101]. For instance, barium sulfate is used as vehicles brake pad composites, similarly to metal sulfides such as covellite (Cu), pyrite (Fe), as well as chalcopyrite (Cu-Fe), sphalerite (Zn) and native elements like Cu (e.g., [9]). In addition, zinc apportionment to roads and urban areas could originate from tire wear, corrosion of safety fences and other traffic-related sources [102]. On the other hand, metallic Fe and alloys of different composition, like Fe-Ni and Fe-Cr, are typically applied as films on stainless steel (e.g., [103]), whereas the enriched microparticles with Ca could originate from concrete, which commonly are constituted by Ca-oxides and hydrated calcium silicates compounds in the SiO2 -CaO-H2 O system. Moreover, REE particles are probably emitted to the environment through a metastable CeZrOx segregation at the autocatalyzer under vehicles’ engine operating conditions [14]. Although road dust REE concentrations are typically in the range of geogenic values, Navarro-Ciurana et al. [14] suggested that they are a significant environmental and health hazard, and they should be included in pollution and health risk assessments. Consequently, the presence of all these heavy metal and lighter particles in the studied road dusts are probably related to the degradation of vehicle parts or other road related items and products. 4.3. Road Dust Pollution Evaluation and Health Risk Assessment Shortcomings The use of Igeo and EFx values can be appropriate tracers for some common road dust’ elements (e.g., Zn, Sb, Sn, Cu, and Cr; Figures 8 and 9). Nevertheless, as discussed by Navarro-Ciurana et al. [14], elements with an anthropic origin but with low concentrations within the range of the geogenic substrate would have values of Igeo and EFx around 1, and hence, they might be mistakenly considered as unpolluted samples. Therefore, the Int. J. Environ. Res. Public Health 2023, 20, 6655 20 of 26 use of the defined Igeo and EFx values for emergent particulate pollutants at low contents in road dust, such as REEs, might not reflect the real source nor their health risk. This limitation can be minimized through detailed mineralogical PTE studies under FE-SEM- EDX. In addition, since most of the road dust pollutants have sizes lower than 10 µm, the Igeo and EFx calculated exclusively for this extremely finest road dusts (<10 µm) would increase considerably, probably more appropriately returning their negative impact on human health. The children group was exposed to more road dust PTEs than adults through each of the three considered pathways (Figure 10). This result is similar to other study areas (e.g., [82,104–107]). As children in warm climate countries tend to spend a larger part of their daily lives outdoors and tend to have higher hand-to-mouth interaction during playtime [108], they are much more susceptible to PTEs health risk. Although the HI values indicate that the children of Barcelona are not under threat by road dust, it is to be noted that the non-carcinogenic health risk in children is almost nine-fold higher than that of adults. Moreover, the possibility that these metals, mainly Cr, may cause serious health effects in children (neurological and developmental disorders; [24]), through their accumulation in body tissues with time. This bioaccumulation toxicity effect does not seem sufficiently reflected in the present health risk models. Faced with the potential risks of Cr, it would be worth paying more attention to this metal concentration and take some measures to reduce it in Barcelona’ road dusts. Overall, most of the values of carcinogenic and non-carcinogenic risk calculated in this study are within the acceptable range (Figures 10 and 11). Therefore, the results reflect that exposure to toxic metals from road dust would not cause serious health impact in the study area population. However, other aspects should be taken into account. On one hand, the calculated risk values only consider a few well known PTEs, but other emergent PTEs, not often mentioned in the literature nor by competent regulatory agencies such as REE [109], which can also enter human bodies, should be included to obtain more realistic risk values. On the other hand, the road dust PTEs exposure route risk differs noticeably, and consequently, directly impacts the human risk assessment. Particle ingestion was the dominant intake route for both subpopulations, followed by inhalation and dermal contact (Figure 11, Tables S11–S14). Thus, as coarser particles (i.e., <800 µm) are easily ingested, and their mass is the highest, ingestion is the most harmful problem in relation to road dust. This exposure pattern confirms previous risk assessment results of road dust throughout the world [4,105,110]. The calculated risk (HQ, CRI) of dermal absorption seems almost negligible for adults and children alike (Figure 11 and Tables S12, S13 and S15). However, particles of 40 nm in dimeter and smaller can successfully penetrate the skin stratum corneum, whereas larger particles cannot [111]. Therefore, the exposure doses, chronic hazard quo- tient and carcinogenic risk index calculations through dermal absorption of the finest particle (<45 µm) of the current models may be too simple and unrealistic. Although it is a common practice to assess risk dermal absorption of road dust particles with fractionated samples at the micrometric scale [104,105,107], it should be clearly evaluated through the analysis of particles at the nanometric scale. This would require a completely different set of techniques of separation and identification and could be very time consuming. 4.4. Towards a Road Dust Fraction Size Standard in Monitoring Programs Because of the clear road dust particle size effect on PTE concentrations, and con- sequently in the pollution and health risk assessments, it is proposed here to fractionate road dust samples and use only the finest fraction (i.e., <45 µm) in monitoring programs instead of whole bulk samples that include all size particles. The results obtained in the current study suggests that analyzing and monitoring the road dust finest fraction would be enough to assess the pollution of most common PTEs, while minimizing the related costs of analyses. There are studies that segregate particles smaller than 20 µm (e.g., [77]) using air separation or flocculation methods. Such studies have also proven the enrichment Int. J. Environ. Res. Public Health 2023, 20, 6655 21 of 26 of heavy metals in the finest size fraction (1.58 ± 0.04 µm) compared to the whole road dust at <200 µm, similar to the investigation of Acosta et al. [79]. However, the techniques that allow this further fractionation to <20 µm are time and cost-consuming. This could delay monitoring programs in comparison with the sieved fractionation method used in the present study. In alignment with Bartz et al. [89], we recommend the FE-SEM-EDX method as an affordable and highly detailed technique for obtaining information on particle size and frequency, particle shape and form, as well as their mineralogical composition and origin. Furthermore, Bartz et al. [89] suggest that the combined analysis of the chemical com- position and size of atmospheric particles, carried out using an SEM-EDX analyzer, is a valuable tool for identifying potential pollutants and assessing the extent of their impact. This finding aligns with the results of our study. In addition, the EFx and Igeo limit values and classification should be defined by each road dust size fraction, especially for emergent pollutants with low concentration. In order to readjust the classification limits for pollution assessment according to fraction sizes, a comparison of EFx and Igeo values calculated in the finest dust separated by air (<20 µm) with sieved dust (<45 µm) would be necessary. In any case, our data indicate that EFx and Igeo values of fine particle dust (<45 µm) are more sensitive indicators to discriminate anthropogenic from geogenic sources, and to evaluate the pollution level for most common metals, than values of coarse particle dust (e.g., 500–800 µm: Figures 8 and 9). The cumulative non-carcinogenic hazard (HI) and carcinogenic risk (CRI) index values are mainly constrained by the road dust PTE concentrations and the reference dose (Rf D) and chronic slope (SF) factors. These values are assumed constant regardless of the road dust size fraction studied, but our results indicate that the calculated HI and CRI values of road dust PTEs through the three ingestion routes are influenced by size fraction. Therefore, a readjustment of Rf D and SF or the HI and CRI classification limits proposed in the literature according to road dust size fraction would improve the health risk assessment evaluation. As discussed for EFx and Igeo values inter-comparative studies between finest dust separated by air (<20 µm) with sieved dust (<45 µm) could allow to define more realistic new limits to conduct health risk monitoring programs using size fractions more efficiently in laboratories. To sum up, monitoring programs, in city areas similar to Barcelona, should be stan- dardized and include at least the pollution and health risk evaluation of particles with sizes lower than 45 µm. Moreover, a recalculation of either Rf D and SF or HI and CRI specifics for the smaller particles is needed; moreover, the risk formulas should include the possible bioaccumulation time as well as the effect of non-common PTEs. The effect of nanoparticles on dermal absorption intake is another aspect to be considered for realistic estimations of road dust risk on human health. 5. Conclusions Road dust mass in the urban area of Barcelona is dominated by coarse particles (>800 µm) when sampling is fractionated into five fractions: <45 µm, 45–125 µm, 125–250 µm, 250—500 µm and 500–800 µm. Regardless of the sampled site, all studied road dusts contained the same major mineral components for all sites: muscovite (avg. 35%), anorthite (avg. 18%), quartz (avg. 15%), albite (avg. 11%), calcite (avg. 11%), chlorite (avg. 5%), dolomite (avg. 4%) and orthoclase (avg. 6%), suggesting a unique source (road and traffic components). Except for orthoclase, a high positive mass correlation between mineral content and total dust for each size fractions in all sampling sites occurred, indicating a homogeneous major mineral content irrespective of land use and road traffic. In addition, the highest concentrations of potential toxic elements (PTEs) were unequivocally associated with the finest fraction (<45 µm), which is consistent with the mineralogical observation of heavy metal particles under FE-SEM-EDX. The anthropogenic PTE microparticles in the finest fraction were constituted by Fe (63%), Fe-alloys with Cr, Ni, Cu, Ti, W and Zn (13%), barium sulfate (4%), as well as native Cu or Cu-(oxi)hydroxide, Cu-Zn alloys, Cu Int. J. Environ. Res. Public Health 2023, 20, 6655 22 of 26 sulfates or sulfides, metallic Ni, Ti and Zn, Zn-Ti alloys, Ca-(oxi)hydroxide, Ca-silicate, and Ce-La particles. The calculated enrichment factor (EFx ), geo-accumulation (Igeo ) and non-carcinogenic (HI) and carcinogenic (CRI) index values indicate that the finest road dust fraction is more dangerous for the environment and human health. Moreover, according to this study, samples with the highest risk to humans in Barcelona occur in industrial parts (33.0%), followed by mixed urban and industrial areas (18.6%) and urban and suburban zones (17.3%). The Igeo and EFx values can be appropriate tracers for some common road dust elements (e.g., Zn, Sb, Sn, Cu, and Cr), but not for all. Overall, the HI and CRI values of Barcelona dusts were found according to the formulas of the United State Environmental Protection Agency, reflecting no serious health impacts in the study area. Nevertheless, Cr contributed between 92.0% and 99.7% to the overall risk. It is noticeable that all the samples fractionated to sizes < 45 µm showed carcinogenic risk values for Cr above the E-05 level, which is deemed unacceptable by many other regulatory agencies. The results presented herein suggest that fine particle dust (<45 µm) is more suitable to conduct pollution and health risk assessments than coarser ones. Moreover, monitoring programs are suggested to rethink the EFx , Igeo , HI and CRI thresholds or formulas to consider the effect of road dust particle size. Supplementary Materials: The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijerph20176655/s1, Table S1: Results for analyzed stan- dards, as reported by ActLabs Ltd.; Table S2: Certified reference materials (CRMs); Table S3: Re- sults for analyzed duplicates, as reported by ActLabs Ltd.; Table S4: Quality control measure- ments; Table S5: X-ray diffraction (XRD) reference patterns data; Table S6: Average reference val- ues for normalization [57]; Table S7: Rf D (reference dose) and SF (chronic slope factor) reference values [61,67,69,72]; Table S8: Major, minor and trace element concentrations of the different stud- ied road dust samples; Table S9: Mineral phase identification (wt. %) using XRD at each site; Table S10: Average EFx and Igeo values of selected elements in road dusts from study area. Values >2 (enriched) for EFx and >1 (polluted) for Igeo are marked in bold; Table S11: Total exposure amounts (∑ADD) of metals in urban road dust to children and adult expressed as mg kg−1 d−1 ; Table S12: Daily exposure amounts (ADD) of road dust PTEs to children and adult through three routes, expressed as mg kg−1 d−1 ; Table S13: Chronic hazard quotient (HQ) of road dust PTEs for children and adult through three routes; Table S14: Hazard index (HI) of road dust PTEs for children and adult; Table S15: Chronic hazard quotient (HQ) of road dust PTEs for children and adult through three routes. Author Contributions: The formulation of the concepts was the responsibility of D.N.-C. The initial research and data collection were carried out by D.N.-C. and D.M. The methodological development and curation of the data were performed by D.N.-C. and D.M. The accuracy and validation of the methodology were verified by D.N.-C. The statistical analysis of the study data was carried out by D.N.-C. and D.M. Creation, writing, translation, and critical review were carried out by D.N.-C. and M.C. M.C. supervised the process, while project management was the responsibility of D.N.-C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by POC2022_2 to D. Navarro and M. Corbella granted by the Universitat Autònoma de Barcelona (Proof of Concept), the Spanish projects PID2019-109018RB-I00 to M. Corbella granted by the Spanish Ministerio de Ciencia e Innovación (MICINN). Support for the research was received also through the project 2022-SGR-00308 (Consolidate Research Group MAG) from the Catalan Government of Spain. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: All relevant data within the manuscript are available from the corre- sponding author upon reasonable request. 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