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PTM concentrationsIn Table 1, the descriptive statistics of PTMs in 50 dust samples from Qom city are described. The background values were used based on the concentrations of metals in the Upper Continental Crust. The mean concentration of As, Cd, Cu, Mo, Pb, Sb, and, Zn exceeded the background value. Also, Cd, Cu, Mo, Pb, Sb, and, Zn had a coefficient of variation (C.V.) greater than 50%, indicating a severe variability in PTMs concentrations in the atmospheric dust of the studied area2. Metals with C.V.  Pb  > Zn  > As  > Cd  > Cu  > Mo  > Cr  > Mn  > Ni = Co. Antimony (38.55) and Pb (35.13) had the highest average EF values, which means they were enriched very high in the windowsill dust. Also, they had a wide range of EF values in the 50 stations: from 4.0 to 227.0 for Sb, and from 8.3 to 140.8 for Pb which might reflect the existence of discrete multiple sources in the studied area. The degree of enrichment for Pb and Sb in the industrial sector was extreme and in the commercial sector was very high; also, the other sectors were significantly enriched. Zinc and As had a more homogenous enrichment in the area. In all the functional sectors, 95% and 84% of stations were significantly enriched by As and Zn, respectively. Copper, Cd, and Mo were moderately enriched in all functional sectors, but the greenspace sector had minimal enrichment by these elements. Some areas in the industrial sector had significant to very high enrichment of Cd. The EF value indicated Co, Cr, Mn, and Ni were minimally enriched in all the stations.Figure 2Box plot of the (a) enrichment factor (EF), and (b) geo accumulation index (Igeo) for the dust samples in the studied area.Full size imageThe highest average values of Igeo were obtained in the order of Pb  > Sb  > As  > Zn. PTMs included Co, Cr, Ni, Fe, and Mn were categorized as unpolluted and Cd, Cu, and Mo were in the category of unpolluted to moderately polluted. In the industrial zone, the windowsill dust was extremely polluted with Sb and Pb. The sequence of contamination intensity with Pb, Zn and Sb according to land use was: industrial  > commercial  > residential  > greenspace. The highest concentration of arsenic in the study area belongs to the industrial area.To evaluate the pollution level based on land use, PLI and mCd indices were utilized (Fig. 3). These cumulative indices showed that the dust in Qom city is considerably contaminated with PTMs. According to the PLI index, all the stations were categorized as polluted sites. The PLIzone values were in the order of industrial (3.77)  > commercial (2.05)  > residential (1.67)  > green space (1.38). This pattern was also repeated with the mCd index. The mCd for the industrial sector ranged from 6.98 (high contamination level) to 39.60 (ultra-high contamination level). In the commercial sector, fifty percent of dust samples were classified as having a high degree of contamination. All the greenspace stations were in the moderate pollution category. This shows the possible effect of tree density in diminishing the risk of dust pollution to the receptors.Figure 3Pollution level indexes (a) mCd and (b) PLI, based on four functional areas.Full size imageSpatial distribution of PTMsThe As, Cd, Cu, Sb, Pb, and Zn content in 100% of the dust samples exceeded the background value. Spatial distribution maps were generated for the hotspot PTMs (As, Sb, Pb, Cd, Cu, Mo and Zn) by applying the inverse distance weighted (IDW) interpolation method (ArcGIS 10.3). Figure 4 demonstrates that PTMs dispersions were slightly influenced by the prevailing wind direction (from the west), suggesting they came from the point- or area- sources. On the other hand, the K–S test showed that the overall distribution of PTMs was not normal in the studied region. This might signify the influence of industrial activities and the presence of multiple sources of dust.Figure 4Spatial distribution maps of seven PTMs in windowsill dusts of Qom, Iran. This map was constructed using ArcGIS version 10.3. (https://www.esri.com/en-us/arcgis/products/arcgisdesktop/overview).Full size imageThe highest pollution load of PTMs belonged to the industrial section. The level of pollution gradually decreased from Shokouhieh to Mahmoudabad industrial zones. The reason is related to more active industries, a closed environment, and more construction existing in Shokouhieh industrial town than in Mahmoudabad industrial town.There is a clear decreasing trend from the central part to southern (downtown area) and southwestern (suburb area) parts of the city. In fact, these parts are diffusely populated and the southwestern part is almost new with lots of barren lands. Copper, Mo, and Cd show high concentrations toward the central part of the city. Educational, cultural and commercial activities are mainly located in the central part of the city. Also, historical and religious districts in the city center are accompanied by a huge influx of tourists throughout the year. For this reason, the central part of the city has various public transportations such as bus stands and taxi stations, and is dominated by a high load of motorcycles.In the eastern part of the city, some hotspots can be observed (Fig. 4). This part includes an important transportation system (like highways and a complex interchange) where exhaust traffic emissions might be a probable source of As, Sb, Pb, and Zn. Unlike Pb and Zn, several peaks of As are scattered in the western part, suggesting an area source might exist in the region. It is noteworthy that the western area is densely populated with lots of residential buildings. Bisht et al. (2022)35 also observed hotspots of As in the residential area of Dehradun, India.PTM potential sourcesTo evaluate the relationship between PTMs in dust samples, the Spearman correlation and PCA were developed (Fig. 5) and more details are given in Table S7. Statistical analysis can help to identify the potential source of contamination in urban dust. The Spearman correlation was significant at p  residential ≈ greenspace. The five PTMs with the highest overall HI are ranked as follows: Pb  > As  > Cr  > Mn  > Sb (Fig. 7). The HI values in all the sections were lower than the permissible level (1.00), except for Pb. In the industrial section, Pb recorded the highest HI value for children (HI = 1.73) which exceeded the acceptable value. The HI values were 10 times higher for children than adults indicating they are more susceptible to PTMs in the dust.The dominant pathway for noncancerous risk was ingestion followed by dermal contact and inhalation. The trend is in line with previous research25,51,52. However, for Co and Mn, the descending order was different as follows ingestion  > inhalation  > dermal contact. The highest contribution of HQinh and HQderm to HI was measured for Co (34.0%) and Cd (29.0%), respectively.In this study, the carcinogenic risk from windowsill dust was estimated for the carcinogens including Cd, Co, Cr and Ni, Pb, and As through the possible routes (Fig. 8, Table S9). The contribution of PTMs to CR decreased in the order of Cr (3.24E−05)  > As (2.05E−05)  > Pb (2.52E−06)  > Co (6.91E−09)  > Ni (1.72E−09)  > Cd (2.58E−10). The average CR values for target PTMs through inhalation ranged from 7.9E−10 to 1.7E−07, which remained in the safety zone (CR  inhalation  > dermal (Fig. 8). While the contribution of Cr to carcinogenic risk was higher through inhalation than ingestion. The reports concluded that the primary exposure route of Cr is inhalation54. Considering the predominant forms of Cr in the environment, CrVI is more toxic than CrIII. Exposure to CrVI can cause immunological diseases, dental effects and carcinogenic effects (lung cancer, nose and nasal sinus cancer, suspected laryngeal and stomach cancers)54,55.The result of health risk from target PTMs in windowsills of Qom indicates significant chronic exposure to Pb can take place for children in the industrial zone. The ingestion route is the most probable pathway for children due to their hand–to–mouth behavior56. Lead can bio-accumulate in the body without any obvious symptoms of toxicity56. The total CR values for Pb, Cr and As in different land-use types were in the range of tolerable carcinogenic risk (1 × 10−4  More

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These authors contributed equally: Laura H. Antão, Benjamin Weigel.These authors jointly supervised this work: Tomas Roslin, Anna-Liisa Laine.Research Centre for Ecological Change, Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, FinlandLaura H. Antão, Benjamin Weigel, Giovanni Strona, Maria Hällfors, Elina Kaarlejärvi, Otso Ovaskainen, Marjo Saastamoinen, Jarno Vanhatalo, Tomas Roslin & Anna-Liisa LaineDepartment of Biological Sciences, University of South Carolina, Columbia, SC, USATad DallasDepartment of Biology, Lund University, Lund, SwedenØystein H. OpedalFinnish Environment Institute (SYKE), Helsinki, FinlandJanne Heliölä, Mikko Kuussaari, Juha Pöyry & Kristiina VuorioNatural Resources Institute Finland (Luke), Helsinki, FinlandHeikki Henttonen, Otso Huitu, Andreas Lindén, Päivi Merilä, Maija Salemaa & Tiina TonteriSection of Ecology, Department of Biology, University of Turku, Turku, FinlandErkki KorpimäkiFinnish Museum of Natural History, University of Helsinki, Helsinki, FinlandAleksi LehikoinenKainuu Centre for Economic Development, Transport and the Environment, Kajaani, FinlandReima LeinonenUniversity of Helsinki, Helsinki, FinlandHannu PietiäinenDepartment of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, FinlandOtso OvaskainenCentre for Biodiversity Dynamics, Department of Biology, Norwegian University of Science and Technology, Trondheim, NorwayOtso OvaskainenHelsinki Institute of Life Science, University of Helsinki, Helsinki, FinlandMarjo SaastamoinenDepartment of Mathematics and Statistics, Faculty of Science, University of Helsinki, Helsinki, FinlandJarno VanhataloSpatial Foodweb Ecology Group, Department of Agricultural Sciences, University of Helsinki, Helsinki, FinlandTomas RoslinSpatial Foodweb Ecology Group, Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, SwedenTomas RoslinDepartment of Evolutionary Biology and Environmental Studies, University of Zürich, Zürich, SwitzerlandAnna-Liisa Laine More

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