Micro- and nano-plastics (MNPs) in urban air: polymer composition, interactions and inhalation risk

Micro- and nano-plastics (MNPs) in urban air: polymer composition, interactions and inhalation risk | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Micro- and nano-plastics (MNPs) in urban air: polymer composition, interactions and inhalation risk Hartmut Herrmann, Ankush Kaushik, Anju Peter, Manuela van Pinxteren, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6790463/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Dec, 2025 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Abstract Airborne micro- and nano-plastics (MNPs) represent a long-time underestimated threat to the urban environment, directly challenging Sustainable Development Goal 3 (Good Health and Well-Being). This study characterizes the concentration and polymer composition of atmospheric MNPs in urban air by analyzing size-fractionated aerosol samples using Pyrolysis-Gas Chromatography-Mass Spectrometry. Total PM 10 MNPs concentrations averaged 0.6 ± 0.2 µg/m 3 , with fine microplastics and coarse microplastics contributing equally. Tire wear particles were dominant, constituting approximately 65% of total MNPs, and car tire tread particles were consistently abundant across all studied size fractions. The identified polymers were strongly correlated with carbonaceous aerosol markers, indicating complex atmospheric interactions. An estimated inhalation of 2.1 µg/day of airborne MNPs, combined with polymer-specific hazard index, may increase the relative risk of cardiopulmonary mortality by up to 9% and lung cancer-related mortality by up to 13%. By integrating exposure, risk assessment, and analytical data, these findings highlight the need for global policy action, emphasizing the value of region-specific research for air quality and public health initiatives. Earth and environmental sciences/Environmental sciences/Environmental chemistry/Atmospheric chemistry Earth and environmental sciences/Environmental sciences/Environmental impact Micro- and nano-plastics (MNPs) urban air polymer composition tire wear particles inhalation exposure Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction Airborne plastic particles have emerged as a concerning component of particulate matter (PM) air pollution. These materials, defined as nanoplastics (≤ 1 µm) and microplastics (1 µm-1 mm), or together as MNPs 1 , have the potential to intervene in ecological processes and impact human health 2 . Growing evidence in various environmental matrices highlights the atmosphere as a key vector for the long-range transport of MNPs 3 , facilitating their deposition even in remote environments such as the Arctic 4 , Antarctic snow 5 , Himalayan cryosphere 6 and French Pyrenees 7 . Airborne MNPs are suspected to be released from a variety of anthropogenic sources, including tire wear particles (TWPs) and brake wear particles (BWPs) 8 , incineration bottom ash residues 9 , textile fibers 10 , resuspended road and soil dust 11 – 13 , and urban surfaces 14 . In addition to that, oceanic microplastics can re-enter the atmosphere via sea spray 15 , 16 , further contributing to the global plastic cycle. Despite increasing their widespread presence, the specific single-source contribution, as well as health and environmental risks associated with inhalable MNPs, remain understudied. Since 2015, research interest in airborne MNPs has accelerated 17 – 23 as concerns mount regarding the inhalation of airborne MNPs with PM 2.5 and PM 10 2,24,25 . Inhalable MNPs can be taken into the deep lung 26 , suspected to cause oxidative stress, cytotoxicity, chronic inflammation, and potentially contribute to respiratory diseases, including interstitial lung disease and fibrosis 27 . These airborne MNPs, once airborne, have the ability to act as carriers for co-contaminants such as heavy metals 28 , polycyclic aromatic hydrocarbons 29 , pharmaceuticals 30 and carbonaceous parameters 31 , which can amplify their toxicity. There are no clear regulatory thresholds for emissions and inhalation of MNPs exist, prompting the World Health Organization (WHO) 32 and European Environment Agency 33 to call for standardized exposure assessments which support their relevance to human health within the framework of Sustainable Development Goal 3 (Good Health and Well-Being). As part of the ongoing negotiations under the Global Plastics Treaty, marine plastic pollution has now received considerable attention, but airborne MNPs appear to have been under-represented in global policy dialogues, regardless of their ubiquitous distribution and potential direct human exposure 34 . Within the present study, we address the aforementioned uncertainties by applying pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) for detailed polymer-specific characterization of size-segregated airborne MNPs in PM 10 , PM 2.5 and PM 10-2.5 . The concentration data generated through this analysis served as the foundation for the subsequent interpretation of their secondary interactions in the atmosphere by investigating how they are related to carbon sum parameters. Additionally, by integrating size-resolved exposure estimates with polymer-specific hazard index, the present study also deduces the relative risk potential associated with MNPs inhalation, highlighting the substantial health burden posed by airborne MNPs. The findings of this study are relevant with respect to air quality guidelines as well as international policy frameworks in order to reduce plastic pollution and protect public health. 2 Results and Discussions 2.1 Concentration and distribution of airborne MNPs Currently, there is no standardised method for qualitative and quantitative analysis of polymers via their pyrolysates 35 . Therefore, the present study identified and quantified polymer clusters (prefix-C is added to every analysed polymer) such as polyethylene (C-PE), polypropylene (C-PP), polyvinyl chloride (C-PVC), polyethylene terephthalate (C-PET), polystyrene (C-PS), polymethyl methacrylate (C-PMMA), polycarbonate (C-PC), polyamide-6 (C-PA6), polyurethane (MDI-PUR), car tire tread (CTT) and truck tire tread (TTT) based on the quantifiers listed in Goßmann et al. 19 , 36 , 37 , with cluster-associated compounds detailed in supplementary information (Supplementary Table 3). A cluster definition is necessary because in environmental samples, polymers are not only used as homopolymers but often as co-polymers, block polymers or composite polymers. They are also used as resins and coatings. Consequently, all detected indicator signals after thermal decomposition are mixed signals from these different sources, which can be assigned to the proportion of the respective polymer. Therefore, the respective polymer concentration is quantified as a homopolymer but indicated as a cluster 19 . All data related to the C-PVC cluster are labelled with an asterisk (*). This indicates the complex contribution of different man-made and natural sources to this cluster, as shown recently by Goßmann et al. 36 , 38 . Since thermal trace analysis of C-PVC* and related polymers only generates non-specific, aromatic indicator products, unavoidable interferences occur in complex environmental samples. Naphthalene is used as an indicator (Supplementary Table 3) for C-PVC*, despite its low specificity, due to the lack of a more selective alternative. As a result, C-PVC* is a mixed cluster with unknown proportions of chlorinated polymers on the one hand and, in particular, black carbon from various sources on the other. Since both polymers are of high (toxicological) relevance with regard to air pollutants and soot in the urban environment, which comes almost exclusively from anthropogenic sources, this cluster is both included in the overall MNPs calculations and discussed in detail. This study does not quantify C-PA6 and MDI-PUR due to undetectable signals for C-PA6 in the analysed samples and insufficient calibration points to establish a reliable calibration curve for MDI-PUR. In the present study, concentrations of MNPs in PM 10 samples are referred to as PM 10 MNPs, in PM 2.5 as fine microplastics (FMPs) and in PM 10 − 2.5 as coarse microplastics (CMPs). CMPs were calculated by subtracting the concentration of FMPs from PM 10 MNPs. This data representation approach has been applied to observe the distribution and behaviour of MNPs in different size fractions of airborne polymeric particles. The total MNPs (∑MNPs) concentration is the collective summation of all the polymers that have been quantified for their size fraction in this study. The FMPs/PM 10 MNPs and CMPs/PM 10 MNPs ratios represent the respective proportions of FMPs and CMPs within the total PM 10 MNPs. The concentration and distribution of airborne MNPs showed considerable variation across particle size fractions during the sampling days (Fig. 1 a). The variability in daily concentrations of MNPs agrees with previous studies 20 , 31 , 39 , 40 , suggesting contributions of multiple influencing factors such as emission sources 41 , atmospheric conditions, meteorological parameters 42 , and secondary formation processes 43 . 2.1.1 Temporal trends and size-segregated mass concentration During the two-week sampling period, the average mass concentration of total (∑) PM 10 MNPs was 0.6 ± 0.2 µg/m³ (0.4–0.9 µg/m³). ∑FMPs and ∑CMPs each averaged 0.3 ± 0.1 µg/m³, with ranges of 0.1–0.5 µg/m³ and 0.1–0.6 µg/m³, respectively. Both contributed equally to ∑PM 10 MNPs at 0.5 ± 0.2, indicating a balanced distribution in ambient air (Fig. 1 a, 1 b; Supplementary Table 4). The observed concentration aligns with findings from an urban study in Graz, Austria 31 , which reported 0.238 µg/m³ of MNPs in PM 2.5 but is lower than the concentrations of 1.2 µg/m³ found in size-segregated aerosols (0.45–11 µm) in Kyoto, Japan 21 and 5.6 µg/m³ in PM 2.5 samples from Shanghai, China 39 . Airborne MNPs emitted in urban areas have a long-distance travel potential and can be deposited at high alpine site 40 , over the north-south Atlantic Ocean 44 and in the northern Atlantic Ocean 19 contributing to their detection in remote regions 3 , 7 , 45 , 46 . In this study, polymers from clusters like C-PVC*, C-PMMA, C-PE, C-PET, and TTT indicated their dominance in FMPs with 0.6 FMPs/PM 10 MNPs compared to CMPs (Supplementary Table 4). On the contrary, clusters from C-PP, C-PS and C-PE have shown their predominant existence in CMPs with 0.7 CMPs/PM 10 MNPs (Supplementary Table 4). C-PC has a unique characteristic, which appears to be entirely in FMPs. This suggests that C-PC, likely originating from urban sources such as automotive components, electronics, construction- and coating materials, undergoes preferential fragmentation into smaller particles due to its brittle nature and susceptibility to environmental degradation processes like UV exposure and abrasion 47 , 48 . Typically, ratio (PM 2.5 /PM 10 ) values below 0.6 suggest that PM may originate from re-suspended soil dust, long-distance dust transport, processing industries, and other mechanical activities 49 – 51 . Interestingly, CTT and total TWPs (CTT + TTT) exhibited equal contributions in FMPs and CMPs (Supplementary Table 4), consistent with findings from a road simulator laboratory analysis 52 having PM 2.5 /PM 10 ratio of 0.5. The ambient concentrations of each quantified polymer are given in the supplementary information (Supplementary Fig. 3a to j; Supplementary Table 4). CTT has the highest concentration among all the polymers in each PM size fraction, and TTT makes a lower but significant contribution to TWPs. The high concentration of TWPs highlights the important contribution of vehicular traffic to airborne MNPs (Supplementary Table 4), attributing their prevalence to tire abrasion influenced by traffic density, driving patterns, and road conditions 8 . Following TWPs, polymers such as C-PVC*, C-PE, and C-PET were consistently dominant across PM size fractions (Supplementary Table 4). Compared to the current study, Chen et al. 39 observed elevated levels of PVC (0.5 µg/m³) and PE (0.6 µg/m³) in PM 2.5 at urban sites in Shanghai, China. Similarly, Kyoto, Japan, also reported higher levels of PE (230 ng/m 3 ), PET (39 ng/m 3 ) in particle size of 0.43–2.1µm and PS (4 ng/m 3 ) in particle size of 7.0 to 11.0µm 21 . Graz, Austria, showed moderate median PM 2.5 concentrations of PET (up to 180 ng/m³), PP (up to 40.5 ng/m³), and PE (up to 33.3 ng/m³) in different classes of region, while high alpine sites, Kau et al. 40 reported variable PET concentrations (4.1–29.5 ng/m³ in PM 1 ; 0.53–35.6 ng/m³ in PM 10 ). In another urban study in China, Luo et al. 20 noted significantly lower PE levels (5.0–10.2 pg/m³), possibly due to the selection of a different quantifier during the analysis. However, variations in methods for identifying and quantifying MNPs can lead to differing results. A study at Tokushima University, Japan, Mizuguchi et al. 53 detected lower PP (< LOD to 3.5 ng/m³) and PS (0.25–0.76 ng/m³) concentrations in PM 10 samples. A comparative overview of reported mass concentrations of MNPs in different PM size fractions across various global locations is given in supplementary information (Supplementary Table 5), emphasizing the variability in urban airborne MNPs pollution and the urgent necessity of standardized analytical methods for consistent and meaningful data and derived health risk evaluation. 2.1.2 Size-fraction dependent polymer composition Within the present study, TWPs accounted for 60–65% of the three PM size fractions (Fig. 2), which aligns with European reports 54 , attributing 64% of microplastic emissions to tire wear. According to Kraftfahrt Bundesamt 55 , in 2022, Saxony had 2,185,262 cars and 223,906 registered trucks and buses, reflecting on our findings that CTT emissions are over ten times higher than TTT (Supplementary Table 4). TWPs in the air were not limited to urban areas 36,56,57 but can also transported via wind to the open ocean 19,45 and high alpine sites 40,58 , highlighting their widespread dominance among polymers. Our study results observed that the following TWPs, C-PE (12–17%), C-PVC* (12–14%) and C-PET (4–7%), are the most prominent polymers existing in all size fractions (Fig. 2a to c). These polymers were also generally reported in a variety of environmental matrices due to their significant production in Europe 59 and consumption 60,61 . An urban area study in Oldenburg, Germany, Goßmann et al. 36 , also observed a similar trend in polymer composition from roadside spider web samples. Although C-PS, C-PP, and C-PC have significantly less contribution (0.1–0.6%) in all size fractions (Fig. 2a to c), aligning with the previous polymer analysis studies 36,46,62 , indicates their presence is still important for studying the dynamics of MNPs. Moreover, our study revealed the predominance of C-PVC*, C-PC, C-PMMA, and TTT in FMPs, while C-PP, C-PE, C-PET, and C-PS are more prevalent in CMPs. This distinction forms two different polymer groups based on size fractions, which is consistent with the discussion in section 2.1.1. 2.1.3 Relative polymer contribution The present study found that PM 10 MNPs contributed 3.6% to PM 10 , FMPs contributed 2.8% to PM 2.5 , and CMPs contributed 5.2% to PM 10-2.5 mass loads (Fig. 3). A few urban environmental studies reported 13.2% in Shanghai, China 39 , 0.67% in Graz, Austria 31 and 0.2% in Taiwan 63 contributions as FMPs in total PM 2.5 mass load. The German Environment Agency (UBA) report 64 indicated that TWPs contributed 3.1% and 4.6% of total PM 10 and PM 2.5 mass load, respectively. A study in Hamburg, Germany, Samland et al. 65 reported that 12% of PM 10 and PM 2.5 mass on major roads consists of TWPs and BWPs. In another study from Stockholm, Sweden, TWPs accounted for approximately 4–6% of total PM 10 concentrations 66 . In this study, TWPs accounted for 2.3% of PM 10 and 1.9% of PM 2.5 mass loads, respectively. Even though the contribution of MNPs to the total PM mass is below 10% compared to other chemical constituents (such as organic and inorganic) 67 , their abundance reflects the presence of an omnipresent and relevant pollutant class in the atmospheric environment. Understanding these contributions is essential for developing mitigation strategies and assessing potential health risks of MNPs. 2.2 Inter-polymer and carbon sum parameters associations Understanding interrelations between carbonaceous parameters and polymers is crucial for identifying sources and transformations in the atmosphere. Limited studies have explored inter-relationships among polymers and their association with other urban pollutants, significantly influencing their environmental fate and transport mechanisms 68 . This highlights the need for further research and data dissemination on the extent of MNPs pollution 69 . The correlation table (Supplementary Table 6a to c) shows the interaction between the detected polymers and carbon sum parameters in their respective size fractions. 2.2.1 Inter-polymer associations In the present study, C-PMMA showed better correlations with C-PE (R = 0.76) and C-PP (R = 0.56) in FMPs (Supplementary Table 6b), suggesting common sources such as cosmetics and personal care products 70 , with TTT (R = 0.61) and C-PS (R = 0.57) indicating emissions associated with TWPs and construction materials, respectively 47,62,71 . C-PVC*/C-PP (R = 0.60) and C-PP/C-PE (R = 0.61) (Supplementary Table 6b) indicated a similar fragmentation process 72 . Other correlating polymers, such as C-PE, C-PET and C-PS (R = 0.55), reflect their widespread use in single-use plastic bags, containers, construction materials, textiles, and other common sources 47,62 . A study from China 39 reported significant correlations between PS, PVC, and PE (R = 0.68–0.82), suggesting a shared emission source and such relationships were not observed in our study (Supplementary Table 6b) except for PM 10 MNPs C-PVC*/C-PE (R = 0.81) (Supplementary Table 6a). This underlines that the composition and emissions of MNPs can vary depending on study location, population density, and topography, even in urban areas. In this study, overall CMPs show weaker correlations than FMPs (Supplementary Table 6c), likely due to differences in degradation, transport, or sources 73 , with a notable CTT/C-PS correlation (R = 0.60) suggesting co-emissions from tire wear and road markings 74 . TWPs have strong correlations (R = 0.95, 0.93, and 0.96 in ∑PM 10 MNPs, ∑FMPs, and ∑CMPs, respectively). This finding highlights their substantial contribution to atmospheric MNPs loading, primarily from tire wear, representing primary MNPs 75 generated through road surface abrasion 50,76 . 2.2.2 Relationship between MNPs and carbon sum parameters Individual concentrations of all the carbon sum parameters and their relative PM ratios, are shown in Supplementary Table 4. Similar to inter-polymer associations, correlations in FMPs with carbon sum parameters are stronger compared to PM 10 MNPs and CMPs (Supplementary Table 6a to c), reflecting that fine particles offer a clearer representation of MNPs associations and possess greater sorption capacity for organic contaminants 77 . A strong correlation (R = 1.0) between TC/OC in all PM size fractions indicated that the organic fraction of carbon is dominant over the total. Additionally, the correlation value of OC/POC (R = 0.72) and OC/SOC (R = 0.91) in FMPs showed a significant existence of primary and secondary carbon in the organic fraction. In contrast, CMPs only observed their dominance as secondary rather than primary carbon (Supplementary Table 6a-c). Similarly, the correlation between POC and EC (R = 1.0) across all PM size fractions suggested a common origin, likely from incomplete combustion sources, such as diesel exhaust and biomass burning 78 . In our study, only C-PMMA, C-PVC*, and C-PE in PM 10 MNPs exhibit good correlations with all carbon parameters (R = 0.53 to 0.94), suggesting their coexistence as both POC and SOC constituents, particularly in POM form emissions (Supplementary Table 6a). The correlation of C-PET with POM (R = 0.40) and EC (R = 0.44), which is lower than the correlations observed at a high alpine site in Sonnblick, Austria 40 , is attributed to differences in source contributions and atmospheric processes. Except for SOC, ∑FMPs are strongly correlated with EC, OC, TC, POC, and POM (R = 0.67–0.80), suggesting that a significant portion of these MNPs likely originate as POM from primary sources like TWPs (Supplementary Table 6b). In comparison to our study, a weaker correlation was observed in Austria 31 between ∑MNPs and OM (R = 0.46) and EC (R = 0.51). Notably, individual polymers such as C-PET, C-PS, and C-PE showed strong correlations with OC, SOC, and POM (R = 0.51–0.80) (Supplementary Table 6b), which are in agreement with the previous results in urban samples 31 . These polymers can release volatile organic compounds (VOCs), e.g. monomers, oligomers and additives during their degradation or processing, which may undergo atmospheric reactions leading to the formation of SOA 79 . However, polymers like C-PC, CTT, TTT, and TWPs correlated strongly with EC and POC (R = 0.59–0.79), indicating their primary origin from traffic emissions such as vehicle components, tire treads and surface abrasion (Supplementary Table 6b). Since refractory polymeric carbon such as black carbon, but also PVC, is part of the C-PVC* cluster (section 2.1), its correlation with the various carbon parameters is not very conclusive. Contrary to ∑FMPs, ∑CMPs correlated poorly with OC but significantly with SOC rather than POC, suggesting SOA formation during secondary processes, particularly in C-PS and TWPs (Supplementary Table 6c). These results demonstrate that MNPs are closely associated with carbonaceous particles in the atmosphere, reflecting their role as adsorbers that influence the transport, transformation, and reactivity of airborne pollutants. 3 Estimated MNPs intake, exposure and their toxicity on humans Inhalation of airborne MNPs is increasingly recognized as a potential exposure pathway, though their health impacts are not fully understood. This section presents exposure estimates based on measured concentrations; however, where potential effects are discussed, they remain largely hypothetical. Targeted studies are needed to address current knowledge gaps and verify these assumptions. In order to observe outdoor inhalation exposure, from measured ∑MNPs concentration in ambient air, we have calculated the amount of MNPs that can enter the body (ages 20–59) through outdoor inhalation (refer section 5.5.3 and Eq. 7 for more details ). The study estimated a daily inhalation of 2.1 µg of PM 10 MNPs, which includes 1.1 µg of FMPs and 0.94 µg of CMPs (Fig. 4 a). Upscaling current inhalation exposure estimates for airborne MNPs, translating to annual intakes of 0.7 mg, 0.4 mg, and 0.3 mg, respectively, is essential for assessing long-term health risks and ensuring lab findings reflect real-world conditions for meaningful dose-response insights. These estimated annual intakes are comparable to those reported in an Australian indoor house dust study in Sydney 80 , which estimated inhalation exposure at 0.2 mg/kg-body weight/year, as well as ten times lower than European estimates, indicating an intake of approximately 2 mg/year of nanoplastics through seafood consumption 81 . According to the WHO, mass concentration is a crucial parameter for evaluating air pollution exposure and its health effects, along with developing legislation to address public exposure to MNPs 82 . An estimated daily intake of PE bound to PM₂.₅ study reported approximately 34 pg/day in Taiyuan, China 20 . Surprisingly, in Mumbai, India, a broader range of MNPs intake, from 61.85 to 102.59 µg/day was observed 83 . As the analytical methods used are neither quality-assured nor harmonized, it is currently difficult to evaluate these differences have been highlighted in section 2.1.1. Using model approaches 24 , 25 , reported estimations of daily MNPs intake via air, reported 8.23x10 − 6 µg/day and 1.07 x10 − 7 mg/capita/day, respectively. Based on these findings, it appears that airborne MNPs intake may be higher than previously estimated, emphasizing the value of analytical measurements to complement model-based exposure assessments. Moreover, a statistical analysis by Kernel Density Estimation (KDE) using the Kolmogorov-Smirnov test 24 assessed the probabilistic density of MNPs intake across different particle sizes. The test shows that a peak in FMPs intake highlights a consistent and widespread exposure level across the population (Fig. 4 b) compared to PM 10 MNPs and CMPs. Due to the small size of FMPs, they can penetrate deeper into the respiratory tract, highlighting a higher potential for long-term retention and systemic exposure 84 . Based on this assumption and to explore potential health impacts, this study calculated relative risk (RR) and attributable fraction (AF) for FMPs exposure (equations 8 and 9 ) on the basis of existing epidemiological models to estimate environmental burden of disease 63 , 85 (Supplementary Table 8). This study found indications for potential increased mortality risks of 5–9% for cardiopulmonary (RR: 1.08 ± 0.01; CI: 1.06–1.10) and 8–13% for lung cancer (RR: 1.12 ± 0.02; CI: 1.09–1.15) compared to the threshold level (Fig. 4 c; Supplementary Table 8). Although RR remained consistently higher than the threshold throughout the study period, it is closely aligned with findings from Colombia’s northern Caribbean region 86 , which reported RR values of 1.00 ± 0.001 for cardiopulmonary disease and 1.11 ± 0.06 for lung cancer. However, the risks observed in the present study are lower than those reported for Taiwan 63 (AF: 26.4 ± 12.6% for cardiopulmonary and 26.7 ± 12.9% for lung cancer) and Romania 85 (AF: 17.5–24.6% for cardiopulmonary and 25.0–34.4% for lung cancer) but notably higher than those reported in a European meta-analysis, which found PM 2.5 -associated RR of 1.03 for lung cancer incidence and 1.05 for mortality 87 . These observations suggest that, despite their small mass, prolonged exposure to airborne MNPs may pose health risks over time. The elevated RR for lung and cardiopulmonary mortality, which could be derived from the comparative assessments of this study, may be influenced by a possible polymer-specific toxicity of particulate matter 88 . Studies suspect this is in connection with lung deposition of PE, PET, PP 89 , which have also been detected in placental 90 and liver 91 tissue, and are possibly related to respiratory, fetal development and hepatic function issues. These specific polymers have been categorized as IV, III, and I, respectively, with Polymer Hazard Index (PHI) shown in Supplementary Table 7 indicating C-PE is more hazardous compared to the other polymers (C-PET and C-PP) and can cross the blood-brain barrier, potentially leading to neurotoxic effects and neurodegenerative diseases 92 , 93 . We detected substantial TWPs (Hazard Category V for CTT and TTT), which are known to carry a cocktail of harmful chemicals such as benzothiazoles and 6-phenyl-1,2,3,4-tetrahydroquinoline quinone (6-PPDQ), contributing to acute toxicity, oxidative stress, and chronic respiratory and cardiovascular issues 94 , 95 . C-PVC*, notably abundant in fine particles and having the highest PHI after TWPs are categorized as the most hazardous (Hazard Category V) polymer that can induce arterial plaque formation and systemic inflammation, increasing cardiovascular risks 96 . PVC as part of C-PVC* is produced from vinyl chloride monomer compound classified as a Group 1 carcinogen, and was assigned one of the highest hazard scores due to its strong associations with carcinogenicity and mutagenicity 97 . Complementing this, it was found that PVC is dominant in human lung tissue 98 but also and accounts as C-PVC* for over 97% of the total PHI, indicating its overwhelming contribution to health risks from inhaled microplastics. These calculations are based on the C-PVC* data, which do not allow any analytical differentiation between PVC and soot/BC. Since black carbon is also a highly toxicologically relevant polymer, the derived data remain highly relevant. C-PS, although less abundant, falls under Hazard Category II (Supplementary Table 7) and, according to previous experimental studies, it has the potential to induce cellular apoptosis, disrupt cellular integrity, and has been linked to reproductive toxicity and hormonal disruptions, including impacts on testicular functions 99 . C-PC exposure (Hazard Category IV) is associated with tissue damage, redox homeostasis in the liver and imbalance of various metabolic pathways in the human body 100 . The consistency between our risk estimates (RR, AF and PHI) and an increasingly evident polymer-specific toxicity strengthens the case that MNPs inhalation represents a genuine public health concern. It is important to emphasize that while these risk values provide insight into potential health concerns, they are based on associations and modelled estimates rather than direct causality. 4 Conclusions The present study offers a detailed characterisation of airborne MNPs in an urban environment, revealing their significant presence across PM size fractions and highlighting TWPs as the dominant source,P followed by C-PVC*, C-PE, and C-PET. FMPs enriched with hazardous polymers, such as C-PVC* and TWPs, pose greater inhalation risks due to their potential for deep lung deposition and interaction with carbon sum parameters. Our findings estimated a daily as well as annual inhalation intake of MNPs and identified elevated mortality risks for cardiopulmonary and lung cancer outcomes, which underscores the need for regulatory attention. Importantly, while this study is geographically localized, the implications are far-reaching as regional studies like this are essential to inform global exposure baselines and guide science-driven policy. Addressing MNPs pollution is critical to achieving Sustainable Development Goal (SDG) 3 (Good Health and Well-being) by reducing human exposure, SDG 11 (Sustainable Cities and Communities) by integrating air quality management into urban planning, and SDG 13 (Climate Action) by mitigating the atmospheric impact of MNPs emissions. In summary, while current evidence increasingly suggests that inhalation of MNPs, particularly FMPs, could have health implications, more longitudinal and mechanistic studies are required to confirm polymer-specific toxicities, establish safe exposure thresholds, and inform regulatory standards. Until then, our findings underscore the importance of monitoring airborne MNPs as emerging pollutants and continuing to refine health risk assessment methods. 5 Materials and methodology 5.1 Reference standards and chemicals Commercially available pure polymers were used as standards. In total, eleven polymers were selected to quantify MNPs in air. The analyzed polymers — C-PE, C-PP, C-PVC*, C-PET, C-PS, C-PMMA, C-PC, C-PA6, MDI-PUR, CTT, and TTT—along with detailed information on their standards and suppliers, are listed in Supplementary Table 1. Ethanol and Dichloromethane (DCM) was taken from Carl von Ossietzky University of Oldenburg laboratory supply store, partly further distilled to residue grade, Hexafluoro isopropanol (Sigma Aldrich, Germany), Acetone, Tetrahydrofuran and Tetra methyl ammonium hydroxide (TMAH, 25% in methanol (MeOH), Sigma-Aldrich, Germany), deuterated polystyrene solution (dPS, Sigma Aldrich, Germany). All solvents are filtered through glass fibre filter of 0.3 µm pore size (Whatman, Altmann Analytical, Germany; pretreated at 500°C/4h). 5.2 Instrumentation and calibration MNPs analysis was performed as outlined in published literature 19 , 36 , 37 , 61 by using Py-GC-MS. The instrument set-up consisted of a micro furnace pyrolyzer (EGA/Py-3030D; FrontierLabs, Japan) with an auto-shot sampler (AS1020E; FrontierLabs, Japan), which was coupled with a GC-MS (6890N-5973MSD; Agilent Technologies). The measurement was performed in Single Ion Monitoring (SIM) mode to enhance overall sensitivity. A detailed description of the instrument settings and procedural parameters can be found in the supplementary information (Supplementary Table 2). The external calibration of the device was carried out using both liquid and solid standards (Supplementary Fig. 1). For the calibration, C-PS, C-PMMA, C-PVC*, C-PC, C-PET and C-PA6 polymers standards (0.01-1.0 µg) were prepared in organic solvent according to their solubility 101 and C-PE, C-PP, CTT, TTT and PUR were weighed as solid standards (1.0–16 µg) in pyrolysis cups. One-point calibration was used to calculate the concentration of C-PP and C-PE due to their low concentration (< 1 µg) in aerosol samples by following the published procedure 19 . The current study used deuterated PS (d 8 -PS) in dichloromethane as an internal standard with 20 µL of 125 µg mL − 1 of solution injected (equivalent to 2.5 µg per cup) into pyrolysis cups along with analytes. For quantification, the ratio of peak areas of the respective selected marker compounds (supplementary table 3) to the peak areas of the internal standard (here m/z 98 from styrene trimer) was plotted against the mass of polymer used to get the calibration curve 102 . Each curve was plotted with 95% confidence and prediction bands, and the calibration linearity for each polymer was calculated as the determination coefficient (r 2 ) value using Origin 2023 (Supplementary Fig. 1). 20 µL of TMAH solution (12.5% in methanol, Sigma Aldrich, Germany) was added to each pyrolysis cup for online derivatization and thermochemolysis to enhance the signal sensitivity for C-PET and C-PC 37 , 61 . The marker compounds for C-PP, C-PE, C-PVC*, CTT and TTT were not affected by TMAH addition to the pyrolysis cups 61 , 102 . A summary of marker compounds, quantifier ions, linear equation, R 2 value, Limit of Detection (LOD) and Limit of Quantification (LOQ) is highlighted in the supplementary material (Supplementary Table 3). 5.3 MNPs collection and analysis Particulate matter (PM) samples (PM 10 and PM 2.5 fractions simultaneously) were collected at Torguer Straße, Leipzig, Germany (51.35° N, 12.42° E) using DIGITEL (DHA-80) high-volume samplers. The site was selected for its high traffic density, representing urban conditions (Supplementary Fig. 2). Samples were collected for two weeks, from 01 September 2022 to 14 September 2022. The sampler was operated at a flow rate of 500 L min - 1 for 24 hours, following Ambient air- European Standards 103 , 104 . For the collection of airborne particles, the samplers were equipped with quartz fibre filters (Munktell MK 360; Ø=150mm). There are fine and coarse fractions of particulate matter in PM 10 samples, but PM 2.5 samples only contain fine fractions. We calculated the PM 10-2.5 , a coarse fraction of particulate matter, by subtracting the PM 2.5 concentration from the PM 10 concentration. An 18 mm punch (~ 254 mm 2 of area) from the sampled filter was placed into a pyrolytic cup along with an internal standard and TMAH for analysis. The direct sample introduction without any pretreatment, as used in previous studies 20 , 35 , 39 , 53 , 105 , 106 is ideal for saving time and avoiding sample manipulations. 5.4 Analysis of carbonaceous constituents in PM samples The carbonaceous aerosol fractions, Elemental carbon (EC) and Organic carbon (OC), were analysed using a thermo-optical instrument ( EC/OC analyser: Sunset Laboratory Inc., USA) in accordance with EUSAAR2 107 . A filter punch (1.41 cm 2 ) from the sampled filter area was taken and analysed for carbon parameters using an EC/OC analyser. 5.5 Calculations and statistical analysis 5.5.1 Detection and Quantification limits of the instrument The LOD and LOQ in absolute mass (µg) for each polymer as absolute mass were calculated using: LOD = 3.3σ/s (1) LOQ = 10σ/s (2) where σ denotes the standard deviation of the peak area of the lowest standard concentration, and s denotes the slope of the calibration curve 108 . 5.5.2 Carbon sum parameters Calculated carbon sum parameters are mentioned below using the following equations: Total carbon (TC) = EC + OC (3) Primary organic carbon (POC) = (OC/EC) min x EC 109 (4) Secondary organic carbon (SOC) = OC – POC 109 (5) Particulate organic matter (POM) = 1.6 x OC 110 (6) The term (OC/EC) min is the minimum OC/EC ratio, and 1.6 is the factor which is used to calculate the particulate fraction of organic matter from OC in urban aerosol samples. 5.5.3 MNPs inhalation In the present study, we calculated the amount of MNPs that have the potential to enter the human body (Age group = 20 to 59 years) through inhalation in the outdoor environment with the following equation: $$\:\text{M}\text{N}\text{P}\text{s}\:\text{i}\text{n}\text{t}\text{a}\text{k}\text{e}\:({\mu\:}g/day)\:=IR\:\times\:\:T\:\times\:\:C\:$$ 7 Where IR represents the average inhalation rate (0.83 m 3 /hour), T represents outdoor exposure time (4 hours/day), and C represents the daily average concentration of ∑MNPs 20 , 32 , 111 . 5.5.4 Probability density estimation In the present study, a probability density function test was performed as per Chen et al. 24 . From the daily intake of MNPs dataset, a statistical analysis from Kernel Density Estimation (KDE) was applied to analyze MNPs exposure distributions, providing a smooth probability density function without arbitrary binning. It helped to identify dominant inhalation exposure levels across PM 10 , PM 2.5 , and PM 10-2.5 . The Kolmogorov-Smirnov test was used to evaluate the data distribution and goodness of fit. By smoothing the data, KDE improves exposure risk characterization and supports daily intake estimates. This method enhances statistical reliability, enabling a more precise evaluation of high-risk exposure zones in urban air and strengthening the study’s microplastic inhalation risk assessment. 5.5.5 Health risk assessments and polymer-specific toxicity The Relative Risk (RR) associated with exposure to FMPs was estimated using a log-linear exposure-response model widely utilized in environmental epidemiology to quantify the health burden attributable to air pollutants. The following equation was applied: $$\:RR={\left(\frac{X+\:1}{Xo+1}\right)}^{\beta\:}$$ 8 Where X is the measured FMPs concentration, X₀ is the background concentration of PM₂.₅ (set at 3 µg/m³) 63 , β is the risk coefficient, taken as 0.15 for cardiopulmonary mortality and 0.23 for lung cancer mortality, following WHO guidelines 63 , 112 . To quantify the proportion of mortality attributable to FMPs exposure, the Attributable Fraction (AF) was calculated using 63 , 112 , 113 : $$\:AF=\frac{\text{R}\text{R}-1}{\text{R}\text{R}}$$ 9 Where RR is calculated from Eq. ( 8 ). This helps to estimate the proportion of disease burden that could be prevented if PM 2.5 concentrations were reduced to background levels. The chemical toxicity associated with distinct polymer types is a key factor in assessing the ecological risks of MNPs. The potential hazards associated with each polymer were assessed since PM10MNPs represent the highest contribution of each polymer in this study. Based on this, the Polymer Hazard Index (PHI) was calculated specifically for PM 10 MNPs using the following Eq. 9 7 . $$\:PHI=\:\sum\:({S}_{n}\:\times\:\:{P}_{n})$$ 10 Where Sₙ is the hazard score assigned to each polymer type based on its toxicological properties 97 , Pₙ is the proportion of that polymer within the PM 10 MNPs. 5.6 Quality control (QC) and quality assurance (QA) QC and QA measures have been implemented during the whole sampling, preparation, and analysis to ensure the accuracy and reliability of data while minimizing contamination risks. All laboratory apparatus, including glassware and steel ware, was cleaned with ultrapure water and pure ethanol before use and then dried in a fume hood to prevent contamination. The chemicals used in this study were filtered with a 0.3 µm pore-sized glass fibre filter and stored in a pre-cleaned glass bottle. During all the analytical steps, no plastic material was used, a cotton laboratory coat and nitrile gloves were worn, and a clean laminar flow bench was used to process all the samples and standard preparation procedures. To ensure accurate measurements, solid standards were weighed in pyrolysis cups (Eco Cups 80 LF, Frontier Labs, Japan), which were pre-cleaned to avoid contamination with a precision microbalance (Sartorius Cubis MSE2.7S-000-DM). Variabilities in the preparation of calibrants, samples and with the instrument were corrected using internal standards 114 . Quartz fibre filters were heated at 850℃ for 3 hours before collecting the PM 10 and PM 2.5 samples. To preserve the integrity of the collected samples, they were stored at -20°C until analysis. Additionally, field blanks were placed during sample collection procedures, which were processed similarly to routine laboratory sample preparation procedures. The final concentration of the samples in this study is reported after the blank subtraction. During the analysis of samples by Py-GC-MS, blank cups were also placed to check any carryover signals and cross-contamination from the previous sample analyzed. The reproducibility of the instrument was thoroughly checked throughout the sequence by evaluating the d 8 -PS signals. During pyrolysis, the system is frequently cleaned by measuring multiple instrument blanks (GC runs without injections) to ensure accurate analysis. Declarations Acknowlegements This research was funded by the Leibniz Association (Berlin, Germany) under the Leibniz Collaborative Excellence Programme, project 'AirPlast' (Grant: K389/2021). Author Contributions H.H. and A.K. conceptualized the study. A.K. conducted sampling, Py-GC-MS measurements, data analysis, and wrote the main manuscript, including preparation of figures, tables, and supplementary material. 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Qualitative and quantitative analysis of mixtures of microplastics in the presence of calcium carbonate by pyrolysis-GC/MS. Journal of Analytical and Applied Pyrolysis 157 , 105188 (2021). Lim, H.-J. & Turpin, B. J. Origins of Primary and Secondary Organic Aerosol in Atlanta: Results of Time-Resolved Measurements during the Atlanta Supersite Experiment. Environ. Sci. Technol. 36 , 4489–4496 (2002). Turpin, B. J. & Lim, H.-J. Species Contributions to PM2.5 Mass Concentrations: Revisiting Common Assumptions for Estimating Organic Mass. Aerosol Science and Technology 35 , 602–610 (2001). USEPA. Risk Assessment Guidance for Superfund. Human Health Evaluation Manual (Part A) . https://www.epa.gov/sites/default/files/2015-09/documents/rags_a.pdf (1989). Ostro, B. Assessing the environmental burden of disease at national and local levels. (2004). WHO. WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide . (2021). Seeley, M. E. & Lynch, J. M. Previous successes and untapped potential of pyrolysis–GC/MS for the analysis of plastic pollution. Anal Bioanal Chem (2023) doi:10.1007/s00216-023-04671-1. Additional Declarations There is NO Competing Interest. Supplementary Files Supplementary.docx SUPPLEMENTAL MATERIAL Cite Share Download PDF Status: Published Journal Publication published 01 Dec, 2025 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6790463","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":470282191,"identity":"7fa0e1f2-cd94-4921-9589-f34bab7861d9","order_by":0,"name":"Hartmut Herrmann","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBACAxiDHy50gFgtkm0kazE4RqwWc/beZ59u1NzJM77f+/BxQUUdA9/xBvxaLHuOG8/OOfas2OwYu7HxjDOHGSTPELDG4EYaM3MO2+HEbcfY2KR52w4ARRIIaLn/DKjl3+HEzW1gLXVAkQeEbGFjZs5tO5y4gQ2shRkogl8Hg8EZoMNy+w4nzjiWxgzyC4/kGUIOO34M6LBvhxP7m48xgkJMju/4AQLWIANmIOYhQT1UyygYBaNgFIwCDAAAys9DDtC1UYgAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-7044-2101","institution":"Leibniz-Institut für Troposphärenforschung","correspondingAuthor":true,"prefix":"","firstName":"Hartmut","middleName":"","lastName":"Herrmann","suffix":""},{"id":470282192,"identity":"94e2d74b-8321-4f65-b3fd-887ea8b6bbd4","order_by":1,"name":"Ankush Kaushik","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ankush","middleName":"","lastName":"Kaushik","suffix":""},{"id":470282193,"identity":"fdc6b95c-8962-46b6-99ed-85f176db84ee","order_by":2,"name":"Anju Peter","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Anju","middleName":"","lastName":"Peter","suffix":""},{"id":470282194,"identity":"a21e63be-570c-4669-9cbb-4c7a1b968592","order_by":3,"name":"Manuela van Pinxteren","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Manuela","middleName":"van","lastName":"Pinxteren","suffix":""},{"id":470282195,"identity":"98675a3a-1941-4b26-934b-ce36bb436d99","order_by":4,"name":"Barbara Scholz-Böttcher","email":"","orcid":"https://orcid.org/0000-0002-3287-4218","institution":"Carl von Ossietzky Universität Oldenburg","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Scholz-Böttcher","suffix":""}],"badges":[],"createdAt":"2025-05-31 10:45:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6790463/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6790463/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s43247-025-02980-0","type":"published","date":"2025-12-01T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84725108,"identity":"4f9735fc-1881-4b7d-8dd7-eb3c5615bc0c","added_by":"auto","created_at":"2025-06-16 15:41:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10260297,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal variation and size-fractional distribution of airborne MNPs.\u003c/p\u003e\n\u003cp\u003e(a) Daily mass concentrations of each analysed polymer in total PM\u003csub\u003e10\u003c/sub\u003eMNPs (∑PM\u003csub\u003e10\u003c/sub\u003eMNPs), fine microplastics (FMPs), and coarse microplastics (CMPs) over the two-week sampling period. Error bars represent standard deviation, indicating variability in measured concentrations.\u003c/p\u003e\n\u003cp\u003e(b) Relative contributions of FMPs and CMPs to ∑MNPs in PM₁₀MNPs, expressed as FMPs/PM\u003csub\u003e10\u003c/sub\u003eMNPs and CMPs/PM\u003csub\u003e10\u003c/sub\u003eMNPs ratios.\u003c/p\u003e\n\u003cp\u003eData show an approximately equal partitioning of MNPs mass between fine and coarse modes with noticeable temporal variability.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6790463/v1/082802b1e3668cd4749c4308.png"},{"id":84725107,"identity":"a49c9d55-b43e-4034-b724-0e2fd955d597","added_by":"auto","created_at":"2025-06-16 15:41:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4460670,"visible":true,"origin":"","legend":"\u003cp\u003ePolymer-specific composition of airborne MNPs indicated by size fraction.\u003c/p\u003e\n\u003cp\u003ePercentage contribution of dominant and minor polymers in (a) PM\u003csub\u003e10\u003c/sub\u003eMNPs, (b) FMPs, and (c) CMPs. Tire wear particles (TWPs: CTT+TTT) contributed the highest fraction across all size classes, followed by C-PE, C-PVC*, and C-PET. C-PS, C-PP, and C-PC were found at lower levels.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6790463/v1/7b0bd2921b5c2401f24b5a6d.png"},{"id":84725110,"identity":"74a4c75b-14ff-410f-abb2-541a98dad667","added_by":"auto","created_at":"2025-06-16 15:41:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":7260121,"visible":true,"origin":"","legend":"\u003cp\u003eRelative contribution of MNPs to total ambient particulate matter mass.\u003c/p\u003e\n\u003cp\u003e(a) Mass proportion of PM\u003csub\u003e10\u003c/sub\u003eMNPs within total PM\u003csub\u003e10\u003c/sub\u003e mass load. (b) Mass proportion of FMPs relative to PM\u003csub\u003e2.5 \u003c/sub\u003emass load. (c) Mass proportion of CMPs to PM\u003csub\u003e10-2.5\u003c/sub\u003e mass load.\u003c/p\u003e\n\u003cp\u003eAll data reflect the integrated contribution of total polymer mass to urban ambient aerosol burdens.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6790463/v1/9bf0606d97e57075a8bd496b.png"},{"id":84724011,"identity":"602f92a0-381e-44f6-92cd-d9a978a470f1","added_by":"auto","created_at":"2025-06-16 15:33:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":6403448,"visible":true,"origin":"","legend":"\u003cp\u003eHuman inhalation exposure and health risk estimates for airborne micro- and nano-plastics (MNPs).\u003c/p\u003e\n\u003cp\u003e(a) Daily inhalation estimates of PM\u003csub\u003e10\u003c/sub\u003eMNPs, including FMPs and CMPs, for adults under average urban exposure. (b) Kernel Density Estimation (KDE) plot depicting probabilistic distribution of MNPs intake, highlighting peak exposures to FMPs. (c) Relative Risk (RR) values for lung cancer (red) and cardiopulmonary mortality (black) linked to FMP exposure across sampling days. Blue dashed line marks the RR = 1 threshold; error bars indicate variability in the measurements.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6790463/v1/94020584f0c32cd1696bcaaa.png"},{"id":97225037,"identity":"52c3242a-c578-45ca-b4b5-a24a4c325f38","added_by":"auto","created_at":"2025-12-02 08:11:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":29614543,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6790463/v1/e0017ea7-957c-4337-ab6b-ba6e087b863d.pdf"},{"id":84725106,"identity":"5a226a9c-8a0e-4dbd-ac4b-ab8390967bf9","added_by":"auto","created_at":"2025-06-16 15:41:21","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1051480,"visible":true,"origin":"","legend":"SUPPLEMENTAL MATERIAL","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-6790463/v1/b9724068081c542e2b3b1739.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Micro- and nano-plastics (MNPs) in urban air: polymer composition, interactions and inhalation risk","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAirborne plastic particles have emerged as a concerning component of particulate matter (PM) air pollution. These materials, defined as nanoplastics (\u0026le;\u0026thinsp;1 \u0026micro;m) and microplastics (1 \u0026micro;m-1 mm), or together as MNPs\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, have the potential to intervene in ecological processes and impact human health\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Growing evidence in various environmental matrices highlights the atmosphere as a key vector for the long-range transport of MNPs\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, facilitating their deposition even in remote environments such as the Arctic\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, Antarctic snow\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, Himalayan cryosphere\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and French Pyrenees\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Airborne MNPs are suspected to be released from a variety of anthropogenic sources, including tire wear particles (TWPs) and brake wear particles (BWPs)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, incineration bottom ash residues\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, textile fibers\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, resuspended road and soil dust\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, and urban surfaces\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In addition to that, oceanic microplastics can re-enter the atmosphere via sea spray\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, further contributing to the global plastic cycle. Despite increasing their widespread presence, the specific single-source contribution, as well as health and environmental risks associated with inhalable MNPs, remain understudied.\u003c/p\u003e \u003cp\u003eSince 2015, research interest in airborne MNPs has accelerated\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21 CR22\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e as concerns mount regarding the inhalation of airborne MNPs with PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e\u003csup\u003e2,24,25\u003c/sup\u003e. Inhalable MNPs can be taken into the deep lung\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, suspected to cause oxidative stress, cytotoxicity, chronic inflammation, and potentially contribute to respiratory diseases, including interstitial lung disease and fibrosis\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. These airborne MNPs, once airborne, have the ability to act as carriers for co-contaminants such as heavy metals\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, polycyclic aromatic hydrocarbons\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, pharmaceuticals\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e and carbonaceous parameters\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, which can amplify their toxicity. There are no clear regulatory thresholds for emissions and inhalation of MNPs exist, prompting the World Health Organization (WHO)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and European Environment Agency\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e to call for standardized exposure assessments which support their relevance to human health within the framework of Sustainable Development Goal 3 (Good Health and Well-Being). As part of the ongoing negotiations under the Global Plastics Treaty, marine plastic pollution has now received considerable attention, but airborne MNPs appear to have been under-represented in global policy dialogues, regardless of their ubiquitous distribution and potential direct human exposure\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWithin the present study, we address the aforementioned uncertainties by applying pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) for detailed polymer-specific characterization of size-segregated airborne MNPs in PM\u003csub\u003e10\u003c/sub\u003e, PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10-2.5\u003c/sub\u003e. The concentration data generated through this analysis served as the foundation for the subsequent interpretation of their secondary interactions in the atmosphere by investigating how they are related to carbon sum parameters. Additionally, by integrating size-resolved exposure estimates with polymer-specific hazard index, the present study also deduces the relative risk potential associated with MNPs inhalation, highlighting the substantial health burden posed by airborne MNPs. The findings of this study are relevant with respect to air quality guidelines as well as international policy frameworks in order to reduce plastic pollution and protect public health.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2 Results and Discussions","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Concentration and distribution of airborne MNPs\u003c/h2\u003e \u003cp\u003eCurrently, there is no standardised method for qualitative and quantitative analysis of polymers via their pyrolysates\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Therefore, the present study identified and quantified polymer clusters (prefix-C is added to every analysed polymer) such as polyethylene (C-PE), polypropylene (C-PP), polyvinyl chloride (C-PVC), polyethylene terephthalate (C-PET), polystyrene (C-PS), polymethyl methacrylate (C-PMMA), polycarbonate (C-PC), polyamide-6 (C-PA6), polyurethane (MDI-PUR), car tire tread (CTT) and truck tire tread (TTT) based on the quantifiers listed in Go\u0026szlig;mann et al.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, with cluster-associated compounds detailed in supplementary information (Supplementary Table\u0026nbsp;3). A cluster definition is necessary because in environmental samples, polymers are not only used as homopolymers but often as co-polymers, block polymers or composite polymers. They are also used as resins and coatings. Consequently, all detected indicator signals after thermal decomposition are mixed signals from these different sources, which can be assigned to the proportion of the respective polymer. Therefore, the respective polymer concentration is quantified as a homopolymer but indicated as a cluster\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. All data related to the C-PVC cluster are labelled with an asterisk (*). This indicates the complex contribution of different man-made and natural sources to this cluster, as shown recently by Go\u0026szlig;mann et al.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Since thermal trace analysis of C-PVC* and related polymers only generates non-specific, aromatic indicator products, unavoidable interferences occur in complex environmental samples. Naphthalene is used as an indicator (Supplementary Table\u0026nbsp;3) for C-PVC*, despite its low specificity, due to the lack of a more selective alternative. As a result, C-PVC* is a mixed cluster with unknown proportions of chlorinated polymers on the one hand and, in particular, black carbon from various sources on the other. Since both polymers are of high (toxicological) relevance with regard to air pollutants and soot in the urban environment, which comes almost exclusively from anthropogenic sources, this cluster is both included in the overall MNPs calculations and discussed in detail. This study does not quantify C-PA6 and MDI-PUR due to undetectable signals for C-PA6 in the analysed samples and insufficient calibration points to establish a reliable calibration curve for MDI-PUR.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn the present study, concentrations of MNPs in PM\u003csub\u003e10\u003c/sub\u003e samples are referred to as PM\u003csub\u003e10\u003c/sub\u003eMNPs, in PM\u003csub\u003e2.5\u003c/sub\u003e as fine microplastics (FMPs) and in PM\u003csub\u003e10\u0026thinsp;\u0026minus;\u0026thinsp;2.5\u003c/sub\u003e as coarse microplastics (CMPs). CMPs were calculated by subtracting the concentration of FMPs from PM\u003csub\u003e10\u003c/sub\u003eMNPs. This data representation approach has been applied to observe the distribution and behaviour of MNPs in different size fractions of airborne polymeric particles. The total MNPs (\u0026sum;MNPs) concentration is the collective summation of all the polymers that have been quantified for their size fraction in this study. The FMPs/PM\u003csub\u003e10\u003c/sub\u003eMNPs and CMPs/PM\u003csub\u003e10\u003c/sub\u003e MNPs ratios represent the respective proportions of FMPs and CMPs within the total PM\u003csub\u003e10\u003c/sub\u003eMNPs.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe concentration and distribution of airborne MNPs showed considerable variation across particle size fractions during the sampling days (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The variability in daily concentrations of MNPs agrees with previous studies\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, suggesting contributions of multiple influencing factors such as emission sources\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, atmospheric conditions, meteorological parameters\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, and secondary formation processes\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Temporal trends and size-segregated mass concentration\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDuring the two-week sampling period, the average mass concentration of total (\u0026sum;) PM\u003csub\u003e10\u003c/sub\u003eMNPs was 0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 \u0026micro;g/m\u0026sup3; (0.4\u0026ndash;0.9 \u0026micro;g/m\u0026sup3;). \u0026sum;FMPs and \u0026sum;CMPs each averaged 0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 \u0026micro;g/m\u0026sup3;, with ranges of 0.1\u0026ndash;0.5 \u0026micro;g/m\u0026sup3; and 0.1\u0026ndash;0.6 \u0026micro;g/m\u0026sup3;, respectively. Both contributed equally to \u0026sum;PM\u003csub\u003e10\u003c/sub\u003eMNPs at 0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2, indicating a balanced distribution in ambient air (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb; Supplementary Table\u0026nbsp;4). The observed concentration aligns with findings from an urban study in Graz, Austria\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, which reported 0.238 \u0026micro;g/m\u0026sup3; of MNPs in PM\u003csub\u003e2.5\u003c/sub\u003e but is lower than the concentrations of 1.2 \u0026micro;g/m\u0026sup3; found in size-segregated aerosols (0.45\u0026ndash;11 \u0026micro;m) in Kyoto, Japan\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e and 5.6 \u0026micro;g/m\u0026sup3; in PM\u003csub\u003e2.5\u003c/sub\u003e samples from Shanghai, China\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Airborne MNPs emitted in urban areas have a long-distance travel potential and can be deposited at high alpine site\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, over the north-south Atlantic Ocean\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e and in the northern Atlantic Ocean\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e contributing to their detection in remote regions\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, polymers from clusters like C-PVC*, C-PMMA, C-PE, C-PET, and TTT indicated their dominance in FMPs with 0.6 FMPs/PM\u003csub\u003e10\u003c/sub\u003eMNPs compared to CMPs (Supplementary Table\u0026nbsp;4). On the contrary, clusters from C-PP, C-PS and C-PE have shown their predominant existence in CMPs with 0.7 CMPs/PM\u003csub\u003e10\u003c/sub\u003eMNPs (Supplementary Table\u0026nbsp;4). C-PC has a unique characteristic, which appears to be entirely in FMPs. This suggests that C-PC, likely originating from urban sources such as automotive components, electronics, construction- and coating materials, undergoes preferential fragmentation into smaller particles due to its brittle nature and susceptibility to environmental degradation processes like UV exposure and abrasion\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Typically, ratio (PM\u003csub\u003e2.5\u003c/sub\u003e/PM\u003csub\u003e10\u003c/sub\u003e) values below 0.6 suggest that PM may originate from re-suspended soil dust, long-distance dust transport, processing industries, and other mechanical activities\u003csup\u003e\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Interestingly, CTT and total TWPs (CTT\u0026thinsp;+\u0026thinsp;TTT) exhibited equal contributions in FMPs and CMPs (Supplementary Table\u0026nbsp;4), consistent with findings from a road simulator laboratory analysis\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e having PM\u003csub\u003e2.5\u003c/sub\u003e/PM\u003csub\u003e10\u003c/sub\u003e ratio of 0.5. The ambient concentrations of each quantified polymer are given in the supplementary information (Supplementary Fig.\u0026nbsp;3a to j; Supplementary Table\u0026nbsp;4). CTT has the highest concentration among all the polymers in each PM size fraction, and TTT makes a lower but significant contribution to TWPs. The high concentration of TWPs highlights the important contribution of vehicular traffic to airborne MNPs (Supplementary Table\u0026nbsp;4), attributing their prevalence to tire abrasion influenced by traffic density, driving patterns, and road conditions\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Following TWPs, polymers such as C-PVC*, C-PE, and C-PET were consistently dominant across PM size fractions (Supplementary Table\u0026nbsp;4). Compared to the current study, Chen et al.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e observed elevated levels of PVC (0.5 \u0026micro;g/m\u0026sup3;) and PE (0.6 \u0026micro;g/m\u0026sup3;) in PM\u003csub\u003e2.5\u003c/sub\u003e at urban sites in Shanghai, China. Similarly, Kyoto, Japan, also reported higher levels of PE (230 ng/m\u003csup\u003e3\u003c/sup\u003e), PET (39 ng/m\u003csup\u003e3\u003c/sup\u003e) in particle size of 0.43\u0026ndash;2.1\u0026micro;m and PS (4 ng/m\u003csup\u003e3\u003c/sup\u003e) in particle size of 7.0 to 11.0\u0026micro;m\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Graz, Austria, showed moderate median PM\u003csub\u003e2.5\u003c/sub\u003e concentrations of PET (up to 180 ng/m\u0026sup3;), PP (up to 40.5 ng/m\u0026sup3;), and PE (up to 33.3 ng/m\u0026sup3;) in different classes of region, while high alpine sites, Kau et al.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e reported variable PET concentrations (4.1\u0026ndash;29.5 ng/m\u0026sup3; in PM\u003csub\u003e1\u003c/sub\u003e; 0.53\u0026ndash;35.6 ng/m\u0026sup3; in PM\u003csub\u003e10\u003c/sub\u003e). In another urban study in China, Luo et al.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e noted significantly lower PE levels (5.0\u0026ndash;10.2 pg/m\u0026sup3;), possibly due to the selection of a different quantifier during the analysis. However, variations in methods for identifying and quantifying MNPs can lead to differing results. A study at Tokushima University, Japan, Mizuguchi et al.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e detected lower PP (\u0026lt;\u0026thinsp;LOD to 3.5 ng/m\u0026sup3;) and PS (0.25\u0026ndash;0.76 ng/m\u0026sup3;) concentrations in PM\u003csub\u003e10\u003c/sub\u003e samples. A comparative overview of reported mass concentrations of MNPs in different PM size fractions across various global locations is given in supplementary information (Supplementary Table\u0026nbsp;5), emphasizing the variability in urban airborne MNPs pollution and the urgent necessity of standardized analytical methods for consistent and meaningful data and derived health risk evaluation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003e2.1.2 Size-fraction dependent polymer composition\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eWithin the present study, TWPs accounted for 60–65% of the three PM size fractions (Fig. 2), which aligns with European reports\u003csup\u003e54\u003c/sup\u003e, attributing 64% of microplastic emissions to tire wear. According to Kraftfahrt Bundesamt\u003csup\u003e55\u003c/sup\u003e, in 2022, Saxony had 2,185,262 cars and 223,906 registered trucks and buses, reflecting on our findings that CTT emissions are over ten times higher than TTT (Supplementary Table\u0026nbsp;4). TWPs in the air were not limited to urban areas\u003csup\u003e36,56,57\u003c/sup\u003e but can also transported via wind to the open ocean\u003csup\u003e19,45\u003c/sup\u003e and high alpine sites\u003csup\u003e40,58\u003c/sup\u003e, highlighting their widespread dominance among polymers. Our study results observed that the following TWPs, C-PE (12–17%), C-PVC* (12–14%) and C-PET (4–7%), are the most prominent polymers existing in all size fractions (Fig. 2a to c). These polymers were also generally reported in a variety of environmental matrices due to their significant production in Europe\u003csup\u003e59\u003c/sup\u003e and consumption\u003csup\u003e60,61\u003c/sup\u003e. An urban area study in Oldenburg, Germany, Goßmann et al.\u003csup\u003e36\u003c/sup\u003e, also observed a similar trend in polymer composition from roadside spider web samples. Although C-PS, C-PP, and C-PC have significantly less contribution (0.1–0.6%) in all size fractions (Fig. 2a to c), aligning with the previous polymer analysis studies\u003csup\u003e36,46,62\u003c/sup\u003e, indicates their presence is still important for studying the dynamics of MNPs. Moreover, our study revealed the predominance of C-PVC*, C-PC, C-PMMA, and TTT in FMPs, while C-PP, C-PE, C-PET, and C-PS are more prevalent in CMPs. This distinction forms two different polymer groups based on size fractions, which is consistent with the discussion in section 2.1.1.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003e2.1.3 Relative polymer contribution\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe present study found that PM\u003csub\u003e10\u003c/sub\u003eMNPs contributed 3.6% to PM\u003csub\u003e10\u003c/sub\u003e, FMPs contributed 2.8% to PM\u003csub\u003e2.5\u003c/sub\u003e, and CMPs contributed 5.2% to PM\u003csub\u003e10-2.5\u003c/sub\u003e mass loads (Fig. 3). A few urban environmental studies reported 13.2% in Shanghai, China\u003csup\u003e39\u003c/sup\u003e, 0.67% in Graz, Austria\u003csup\u003e31\u003c/sup\u003e and 0.2% in Taiwan\u003csup\u003e63\u003c/sup\u003e contributions as FMPs in total PM\u003csub\u003e2.5\u003c/sub\u003e mass load. The German Environment Agency (UBA) report\u003csup\u003e64\u003c/sup\u003e indicated that TWPs contributed 3.1% and 4.6% of total PM\u003csub\u003e10\u003c/sub\u003e and PM\u003csub\u003e2.5\u003c/sub\u003e mass load, respectively. A study in Hamburg, Germany, Samland et al.\u003csup\u003e65\u003c/sup\u003e reported that 12% of PM\u003csub\u003e10\u003c/sub\u003e and PM\u003csub\u003e2.5\u003c/sub\u003e mass on major roads consists of TWPs and BWPs. In another study from Stockholm, Sweden, TWPs accounted for approximately 4–6% of total PM\u003csub\u003e10\u003c/sub\u003e concentrations\u003csup\u003e66\u003c/sup\u003e. In this study, TWPs accounted for 2.3% of PM\u003csub\u003e10\u003c/sub\u003e and 1.9% of PM\u003csub\u003e2.5\u003c/sub\u003e mass loads, respectively. Even though the contribution of MNPs to the total PM mass is below 10% compared to other chemical constituents (such as organic and inorganic)\u003csup\u003e67\u003c/sup\u003e, their abundance reflects the presence of an omnipresent and relevant pollutant class in the atmospheric environment. Understanding these contributions is essential for developing mitigation strategies and assessing potential health risks of MNPs.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003e2.2 Inter-polymer and carbon sum parameters associations\u003c/h2\u003e\n \u003cp\u003eUnderstanding interrelations between carbonaceous parameters and polymers is crucial for identifying sources and transformations in the atmosphere. Limited studies have explored inter-relationships among polymers and their association with other urban pollutants, significantly influencing their environmental fate and transport mechanisms\u003csup\u003e68\u003c/sup\u003e. This highlights the need for further research and data dissemination on the extent of MNPs pollution\u003csup\u003e69\u003c/sup\u003e. The correlation table (Supplementary Table\u0026nbsp;6a to c) shows the interaction between the detected polymers and carbon sum parameters in their respective size fractions.\u003c/p\u003e\n \u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e2.2.1 Inter-polymer associations\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eIn the present study, C-PMMA showed better correlations with C-PE (R = 0.76) and C-PP (R = 0.56) in FMPs (Supplementary Table\u0026nbsp;6b), suggesting common sources such as cosmetics and personal care products\u003csup\u003e70\u003c/sup\u003e, with TTT (R = 0.61) and C-PS (R = 0.57) indicating emissions associated with TWPs and construction materials, respectively\u003csup\u003e47,62,71\u003c/sup\u003e. C-PVC*/C-PP (R = 0.60) and C-PP/C-PE (R = 0.61) (Supplementary Table\u0026nbsp;6b) indicated a similar fragmentation process\u003csup\u003e72\u003c/sup\u003e. Other correlating polymers, such as C-PE, C-PET and C-PS (R = 0.55), reflect their widespread use in single-use plastic bags, containers, construction materials, textiles, and other common sources\u003csup\u003e47,62\u003c/sup\u003e. A study from China\u003csup\u003e39\u003c/sup\u003e reported significant correlations between PS, PVC, and PE (R = 0.68–0.82), suggesting a shared emission source and such relationships were not observed in our study (Supplementary Table 6b) except for PM\u003csub\u003e10\u003c/sub\u003eMNPs C-PVC*/C-PE (R = 0.81) (Supplementary Table\u0026nbsp;6a). This underlines that the composition and emissions of MNPs can vary depending on study location, population density, and topography, even in urban areas. In this study, overall CMPs show weaker correlations than FMPs (Supplementary Table\u0026nbsp;6c), likely due to differences in degradation, transport, or sources\u003csup\u003e73\u003c/sup\u003e, with a notable CTT/C-PS correlation (R = 0.60) suggesting co-emissions from tire wear and road markings\u003csup\u003e74\u003c/sup\u003e. TWPs have strong correlations (R = 0.95, 0.93, and 0.96 in ∑PM\u003csub\u003e10\u003c/sub\u003eMNPs, ∑FMPs, and ∑CMPs, respectively). This finding highlights their substantial contribution to atmospheric MNPs loading, primarily from tire wear, representing primary MNPs\u003csup\u003e75\u003c/sup\u003e generated through road surface abrasion\u003csup\u003e50,76\u003c/sup\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e2.2.2 Relationship between MNPs and carbon sum parameters\u003c/h2\u003e\n \u003cp\u003eIndividual concentrations of all the carbon sum parameters and their relative PM ratios, are shown in Supplementary Table\u0026nbsp;4. Similar to inter-polymer associations, correlations in FMPs with carbon sum parameters are stronger compared to PM\u003csub\u003e10\u003c/sub\u003eMNPs and CMPs (Supplementary Table\u0026nbsp;6a to c), reflecting that fine particles offer a clearer representation of MNPs associations and possess greater sorption capacity for organic contaminants\u003csup\u003e77\u003c/sup\u003e. A strong correlation (R = 1.0) between TC/OC in all PM size fractions indicated that the organic fraction of carbon is dominant over the total. Additionally, the correlation value of OC/POC (R = 0.72) and OC/SOC (R = 0.91) in FMPs showed a significant existence of primary and secondary carbon in the organic fraction. In contrast, CMPs only observed their dominance as secondary rather than primary carbon (Supplementary Table\u0026nbsp;6a-c). Similarly, the correlation between POC and EC (R = 1.0) across all PM size fractions suggested a common origin, likely from incomplete combustion sources, such as diesel exhaust and biomass burning\u003csup\u003e78\u003c/sup\u003e. In our study, only C-PMMA, C-PVC*, and C-PE in PM\u003csub\u003e10\u003c/sub\u003eMNPs exhibit good correlations with all carbon parameters (R = 0.53 to 0.94), suggesting their coexistence as both POC and SOC constituents, particularly in POM form emissions (Supplementary Table\u0026nbsp;6a). The correlation of C-PET with POM (R = 0.40) and EC (R = 0.44), which is lower than the correlations observed at a high alpine site in Sonnblick, Austria\u003csup\u003e40\u003c/sup\u003e, is attributed to differences in source contributions and atmospheric processes. Except for SOC, ∑FMPs are strongly correlated with EC, OC, TC, POC, and POM (R = 0.67–0.80), suggesting that a significant portion of these MNPs likely originate as POM from primary sources like TWPs (Supplementary Table\u0026nbsp;6b). In comparison to our study, a weaker correlation was observed in Austria\u003csup\u003e31\u003c/sup\u003e between ∑MNPs and OM (R = 0.46) and EC (R = 0.51). Notably, individual polymers such as C-PET, C-PS, and C-PE showed strong correlations with OC, SOC, and POM (R = 0.51–0.80) (Supplementary Table 6b), which are in agreement with the previous results in urban samples\u003csup\u003e31\u003c/sup\u003e. These polymers can release volatile organic compounds (VOCs), e.g. monomers, oligomers and additives during their degradation or processing, which may undergo atmospheric reactions leading to the formation of SOA\u003csup\u003e79\u003c/sup\u003e. However, polymers like C-PC, CTT, TTT, and TWPs correlated strongly with EC and POC (R = 0.59–0.79), indicating their primary origin from traffic emissions such as vehicle components, tire treads and surface abrasion (Supplementary Table\u0026nbsp;6b). Since refractory polymeric carbon such as black carbon, but also PVC, is part of the C-PVC* cluster (section 2.1), its correlation with the various carbon parameters is not very conclusive. Contrary to ∑FMPs, ∑CMPs correlated poorly with OC but significantly with SOC rather than POC, suggesting SOA formation during secondary processes, particularly in C-PS and TWPs (Supplementary Table\u0026nbsp;6c). These results demonstrate that MNPs are closely associated with carbonaceous particles in the atmosphere, reflecting their role as adsorbers that influence the transport, transformation, and reactivity of airborne pollutants.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3 Estimated MNPs intake, exposure and their toxicity on humans","content":"\u003cp\u003eInhalation of airborne MNPs is increasingly recognized as a potential exposure pathway, though their health impacts are not fully understood. This section presents exposure estimates based on measured concentrations; however, where potential effects are discussed, they remain largely hypothetical. Targeted studies are needed to address current knowledge gaps and verify these assumptions. In order to observe outdoor inhalation exposure, from measured \u0026sum;MNPs concentration in ambient air, we have calculated the amount of MNPs that can enter the body (ages 20\u0026ndash;59) through outdoor inhalation (refer section 5.5.3 and Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e7\u003c/span\u003e for more details ). The study estimated a daily inhalation of 2.1 \u0026micro;g of PM\u003csub\u003e10\u003c/sub\u003eMNPs, which includes 1.1 \u0026micro;g of FMPs and 0.94 \u0026micro;g of CMPs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Upscaling current inhalation exposure estimates for airborne MNPs, translating to annual intakes of 0.7 mg, 0.4 mg, and 0.3 mg, respectively, is essential for assessing long-term health risks and ensuring lab findings reflect real-world conditions for meaningful dose-response insights. These estimated annual intakes are comparable to those reported in an Australian indoor house dust study in Sydney\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e, which estimated inhalation exposure at 0.2 mg/kg-body weight/year, as well as ten times lower than European estimates, indicating an intake of approximately 2 mg/year of nanoplastics through seafood consumption\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. According to the WHO, mass concentration is a crucial parameter for evaluating air pollution exposure and its health effects, along with developing legislation to address public exposure to MNPs\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. An estimated daily intake of PE bound to PM₂.₅ study reported approximately 34 pg/day in Taiyuan, China\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Surprisingly, in Mumbai, India, a broader range of MNPs intake, from 61.85 to 102.59 \u0026micro;g/day was observed\u003csup\u003e\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. As the analytical methods used are neither quality-assured nor harmonized, it is currently difficult to evaluate these differences have been highlighted in section 2.1.1. Using model approaches\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, reported estimations of daily MNPs intake via air, reported 8.23x10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e \u0026micro;g/day and 1.07 x10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e mg/capita/day, respectively. Based on these findings, it appears that airborne MNPs intake may be higher than previously estimated, emphasizing the value of analytical measurements to complement model-based exposure assessments.\u003c/p\u003e \u003cp\u003eMoreover, a statistical analysis by Kernel Density Estimation (KDE) using the Kolmogorov-Smirnov test\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e assessed the probabilistic density of MNPs intake across different particle sizes. The test shows that a peak in FMPs intake highlights a consistent and widespread exposure level across the population (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) compared to PM\u003csub\u003e10\u003c/sub\u003eMNPs and CMPs. Due to the small size of FMPs, they can penetrate deeper into the respiratory tract, highlighting a higher potential for long-term retention and systemic exposure\u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e. Based on this assumption and to explore potential health impacts, this study calculated relative risk (RR) and attributable fraction (AF) for FMPs exposure (equations \u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e9\u003c/span\u003e) on the basis of existing epidemiological models to estimate environmental burden of disease\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e (Supplementary Table\u0026nbsp;8). This study found indications for potential increased mortality risks of 5\u0026ndash;9% for cardiopulmonary (RR: 1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01; CI: 1.06\u0026ndash;1.10) and 8\u0026ndash;13% for lung cancer (RR: 1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02; CI: 1.09\u0026ndash;1.15) compared to the threshold level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec; Supplementary Table\u0026nbsp;8). Although RR remained consistently higher than the threshold throughout the study period, it is closely aligned with findings from Colombia\u0026rsquo;s northern Caribbean region\u003csup\u003e\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e, which reported RR values of 1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001 for cardiopulmonary disease and 1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 for lung cancer. However, the risks observed in the present study are lower than those reported for Taiwan\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e (AF: 26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.6% for cardiopulmonary and 26.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.9% for lung cancer) and Romania\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e (AF: 17.5\u0026ndash;24.6% for cardiopulmonary and 25.0\u0026ndash;34.4% for lung cancer) but notably higher than those reported in a European meta-analysis, which found PM\u003csub\u003e2.5\u003c/sub\u003e-associated RR of 1.03 for lung cancer incidence and 1.05 for mortality\u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e. These observations suggest that, despite their small mass, prolonged exposure to airborne MNPs may pose health risks over time. The elevated RR for lung and cardiopulmonary mortality, which could be derived from the comparative assessments of this study, may be influenced by a possible polymer-specific toxicity of particulate matter\u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e. Studies suspect this is in connection with lung deposition of PE, PET, PP\u003csup\u003e\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e, which have also been detected in placental\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e and liver\u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e tissue, and are possibly related to respiratory, fetal development and hepatic function issues. These specific polymers have been categorized as IV, III, and I, respectively, with Polymer Hazard Index (PHI) shown in Supplementary Table\u0026nbsp;7 indicating C-PE is more hazardous compared to the other polymers (C-PET and C-PP) and can cross the blood-brain barrier, potentially leading to neurotoxic effects and neurodegenerative diseases\u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e,\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e. We detected substantial TWPs (Hazard Category V for CTT and TTT), which are known to carry a cocktail of harmful chemicals such as benzothiazoles and 6-phenyl-1,2,3,4-tetrahydroquinoline quinone (6-PPDQ), contributing to acute toxicity, oxidative stress, and chronic respiratory and cardiovascular issues\u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e,\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e. C-PVC*, notably abundant in fine particles and having the highest PHI after TWPs are categorized as the most hazardous (Hazard Category V) polymer that can induce arterial plaque formation and systemic inflammation, increasing cardiovascular risks\u003csup\u003e\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u003c/sup\u003e. PVC as part of C-PVC* is produced from vinyl chloride monomer compound classified as a Group 1 carcinogen, and was assigned one of the highest hazard scores due to its strong associations with carcinogenicity and mutagenicity\u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e. Complementing this, it was found that PVC is dominant in human lung tissue\u003csup\u003e\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e but also and accounts as C-PVC* for over 97% of the total PHI, indicating its overwhelming contribution to health risks from inhaled microplastics. These calculations are based on the C-PVC* data, which do not allow any analytical differentiation between PVC and soot/BC. Since black carbon is also a highly toxicologically relevant polymer, the derived data remain highly relevant. C-PS, although less abundant, falls under Hazard Category II (Supplementary Table\u0026nbsp;7) and, according to previous experimental studies, it has the potential to induce cellular apoptosis, disrupt cellular integrity, and has been linked to reproductive toxicity and hormonal disruptions, including impacts on testicular functions\u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e. C-PC exposure (Hazard Category IV) is associated with tissue damage, redox homeostasis in the liver and imbalance of various metabolic pathways in the human body\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e. The consistency between our risk estimates (RR, AF and PHI) and an increasingly evident polymer-specific toxicity strengthens the case that MNPs inhalation represents a genuine public health concern. It is important to emphasize that while these risk values provide insight into potential health concerns, they are based on associations and modelled estimates rather than direct causality.\u003c/p\u003e "},{"header":"4 Conclusions","content":"\u003cp\u003eThe present study offers a detailed characterisation of airborne MNPs in an urban environment, revealing their significant presence across PM size fractions and highlighting TWPs as the dominant source,P followed by C-PVC*, C-PE, and C-PET. FMPs enriched with hazardous polymers, such as C-PVC* and TWPs, pose greater inhalation risks due to their potential for deep lung deposition and interaction with carbon sum parameters. Our findings estimated a daily as well as annual inhalation intake of MNPs and identified elevated mortality risks for cardiopulmonary and lung cancer outcomes, which underscores the need for regulatory attention. Importantly, while this study is geographically localized, the implications are far-reaching as regional studies like this are essential to inform global exposure baselines and guide science-driven policy. Addressing MNPs pollution is critical to achieving Sustainable Development Goal (SDG) 3 (Good Health and Well-being) by reducing human exposure, SDG 11 (Sustainable Cities and Communities) by integrating air quality management into urban planning, and SDG 13 (Climate Action) by mitigating the atmospheric impact of MNPs emissions. In summary, while current evidence increasingly suggests that inhalation of MNPs, particularly FMPs, could have health implications, more longitudinal and mechanistic studies are required to confirm polymer-specific toxicities, establish safe exposure thresholds, and inform regulatory standards. Until then, our findings underscore the importance of monitoring airborne MNPs as emerging pollutants and continuing to refine health risk assessment methods.\u003c/p\u003e"},{"header":"5 Materials and methodology","content":"\u003cp\u003e\u003cspan\u003e\u003cem\u003e5.1 Reference standards and chemicals\u003c/em\u003e\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCommercially available pure polymers were used as standards. In total, eleven polymers were selected to quantify MNPs in air. The analyzed polymers \u0026mdash; C-PE, C-PP, C-PVC*, C-PET, C-PS, C-PMMA, C-PC, C-PA6, MDI-PUR, CTT, and TTT\u0026mdash;along with detailed information on their standards and suppliers, are listed in Supplementary Table\u0026nbsp;1. Ethanol and Dichloromethane (DCM) was taken from Carl von Ossietzky University of Oldenburg laboratory supply store, partly further distilled to residue grade, Hexafluoro isopropanol (Sigma Aldrich, Germany), Acetone, Tetrahydrofuran and Tetra methyl ammonium hydroxide (TMAH, 25% in methanol (MeOH), Sigma-Aldrich, Germany), deuterated polystyrene solution (dPS, Sigma Aldrich, Germany). All solvents are filtered through glass fibre filter of 0.3 \u0026micro;m pore size (Whatman, Altmann Analytical, Germany; pretreated at 500\u0026deg;C/4h).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Instrumentation and calibration\u003c/h2\u003e \u003cp\u003eMNPs analysis was performed as outlined in published literature\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e by using Py-GC-MS. The instrument set-up consisted of a micro furnace pyrolyzer (EGA/Py-3030D; FrontierLabs, Japan) with an auto-shot sampler (AS1020E; FrontierLabs, Japan), which was coupled with a GC-MS (6890N-5973MSD; Agilent Technologies). The measurement was performed in Single Ion Monitoring (SIM) mode to enhance overall sensitivity. A detailed description of the instrument settings and procedural parameters can be found in the supplementary information (Supplementary Table\u0026nbsp;2). The external calibration of the device was carried out using both liquid and solid standards (Supplementary Fig.\u0026nbsp;1). For the calibration, C-PS, C-PMMA, C-PVC*, C-PC, C-PET and C-PA6 polymers standards (0.01-1.0 \u0026micro;g) were prepared in organic solvent according to their solubility\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e and C-PE, C-PP, CTT, TTT and PUR were weighed as solid standards (1.0\u0026ndash;16 \u0026micro;g) in pyrolysis cups. One-point calibration was used to calculate the concentration of C-PP and C-PE due to their low concentration (\u0026lt;\u0026thinsp;1 \u0026micro;g) in aerosol samples by following the published procedure\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. The current study used deuterated PS (d\u003csub\u003e8\u003c/sub\u003e-PS) in dichloromethane as an internal standard with 20 \u0026micro;L of 125 \u0026micro;g mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of solution injected (equivalent to 2.5 \u0026micro;g per cup) into pyrolysis cups along with analytes. For quantification, the ratio of peak areas of the respective selected marker compounds (supplementary table 3) to the peak areas of the internal standard (here m/z 98 from styrene trimer) was plotted against the mass of polymer used to get the calibration curve\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e. Each curve was plotted with 95% confidence and prediction bands, and the calibration linearity for each polymer was calculated as the determination coefficient (r\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e) value using Origin 2023 (Supplementary Fig.\u0026nbsp;1). 20 \u0026micro;L of TMAH solution (12.5% in methanol, Sigma Aldrich, Germany) was added to each pyrolysis cup for online derivatization and thermochemolysis to enhance the signal sensitivity for C-PET and C-PC\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. The marker compounds for C-PP, C-PE, C-PVC*, CTT and TTT were not affected by TMAH addition to the pyrolysis cups\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e,\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e. A summary of marker compounds, quantifier ions, linear equation, R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e value, Limit of Detection (LOD) and Limit of Quantification (LOQ) is highlighted in the supplementary material (Supplementary Table\u0026nbsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e5.3 MNPs collection and analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eParticulate matter (PM) samples (PM\u003csub\u003e10\u003c/sub\u003e and PM\u003csub\u003e2.5\u003c/sub\u003e fractions simultaneously) were collected at Torguer Stra\u0026szlig;e, Leipzig, Germany (51.35\u0026deg; N, 12.42\u0026deg; E) using DIGITEL (DHA-80) high-volume samplers. The site was selected for its high traffic density, representing urban conditions (Supplementary Fig.\u0026nbsp;2). Samples were collected for two weeks, from 01 September 2022 to 14 September 2022. The sampler was operated at a flow rate of 500 L min\u003csup\u003e-\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e for 24 hours, following Ambient air- European Standards\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e,\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e. For the collection of airborne particles, the samplers were equipped with quartz fibre filters (Munktell MK 360; \u0026Oslash;=150mm). There are fine and coarse fractions of particulate matter in PM\u003csub\u003e10\u003c/sub\u003e samples, but PM\u003csub\u003e2.5\u003c/sub\u003e samples only contain fine fractions. We calculated the PM\u003csub\u003e10-2.5\u003c/sub\u003e, a coarse fraction of particulate matter, by subtracting the PM\u003csub\u003e2.5\u003c/sub\u003e concentration from the PM\u003csub\u003e10\u003c/sub\u003e concentration.\u003c/p\u003e \u003cp\u003eAn 18 mm punch (~\u0026thinsp;254 mm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e of area) from the sampled filter was placed into a pyrolytic cup along with an internal standard and TMAH for analysis. The direct sample introduction without any pretreatment, as used in previous studies \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e,\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e is ideal for saving time and avoiding sample manipulations.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Analysis of carbonaceous constituents in PM samples\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe carbonaceous aerosol fractions, Elemental carbon (EC) and Organic carbon (OC), were analysed using a thermo-optical instrument ( EC/OC analyser: Sunset Laboratory Inc., USA) in accordance with EUSAAR2\u003csup\u003e107\u003c/sup\u003e. A filter punch (1.41 cm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e) from the sampled filter area was taken and analysed for carbon parameters using an EC/OC analyser.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e5.5 Calculations and statistical analysis\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e5.5.1 Detection and Quantification limits of the instrument\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe LOD and LOQ in absolute mass (\u0026micro;g) for each polymer as absolute mass were calculated using:\u003c/p\u003e \u003cp\u003e \u003cem\u003eLOD\u0026thinsp;=\u0026thinsp;3.3σ/s (1)\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eLOQ\u0026thinsp;=\u0026thinsp;10σ/s\u003c/em\u003e (2)\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eσ\u003c/em\u003e denotes the standard deviation of the peak area of the lowest standard concentration, and \u003cem\u003es\u003c/em\u003e denotes the slope of the calibration curve\u003csup\u003e\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e5.5.2 Carbon sum parameters\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCalculated carbon sum parameters are mentioned below using the following equations:\u003c/p\u003e \u003cp\u003eTotal carbon (TC)\u0026thinsp;=\u0026thinsp;EC\u0026thinsp;+\u0026thinsp;OC (3) Primary organic carbon (POC) = (OC/EC) \u003csub\u003emin\u003c/sub\u003e x EC\u003csup\u003e\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e (4)\u003c/p\u003e \u003cp\u003eSecondary organic carbon (SOC)\u0026thinsp;=\u0026thinsp;OC \u0026ndash; POC\u003csup\u003e\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e (5)\u003c/p\u003e \u003cp\u003eParticulate organic matter (POM)\u0026thinsp;=\u0026thinsp;1.6 x OC\u003csup\u003e\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e (6)\u003c/p\u003e \u003cp\u003eThe term (OC/EC) \u003csub\u003emin\u003c/sub\u003e is the minimum OC/EC ratio, and 1.6 is the factor which is used to calculate the particulate fraction of organic matter from OC in urban aerosol samples.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e5.5.3 MNPs inhalation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the present study, we calculated the amount of MNPs that have the potential to enter the human body (Age group\u0026thinsp;=\u0026thinsp;20 to 59 years) through inhalation in the outdoor environment with the following equation:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ1\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\text{M}\\text{N}\\text{P}\\text{s}\\:\\text{i}\\text{n}\\text{t}\\text{a}\\text{k}\\text{e}\\:({\\mu\\:}g/day)\\:=IR\\:\\times\\:\\:T\\:\\times\\:\\:C\\:$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWhere IR represents the average inhalation rate (0.83 m\u003csup\u003e3\u003c/sup\u003e/hour), T represents outdoor exposure time (4 hours/day), and C represents the daily average concentration of \u0026sum;MNPs\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e5.5.4 Probability density estimation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the present study, a probability density function test was performed as per Chen et al.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. From the daily intake of MNPs dataset, a statistical analysis from Kernel Density Estimation (KDE) was applied to analyze MNPs exposure distributions, providing a smooth probability density function without arbitrary binning. It helped to identify dominant inhalation exposure levels across PM\u003csub\u003e10\u003c/sub\u003e, PM\u003csub\u003e2.5\u003c/sub\u003e, and PM\u003csub\u003e10-2.5\u003c/sub\u003e. The Kolmogorov-Smirnov test was used to evaluate the data distribution and goodness of fit. By smoothing the data, KDE improves exposure risk characterization and supports daily intake estimates. This method enhances statistical reliability, enabling a more precise evaluation of high-risk exposure zones in urban air and strengthening the study\u0026rsquo;s microplastic inhalation risk assessment.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e5.5.5 Health risk assessments and polymer-specific toxicity\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe Relative Risk (RR) associated with exposure to FMPs was estimated using a log-linear exposure-response model widely utilized in environmental epidemiology to quantify the health burden attributable to air pollutants. The following equation was applied:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ2\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:RR={\\left(\\frac{X+\\:1}{Xo+1}\\right)}^{\\beta\\:}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWhere X is the measured FMPs concentration, X₀ is the background concentration of PM₂.₅ (set at 3 \u0026micro;g/m\u0026sup3;)\u003csup\u003e63\u003c/sup\u003e, β is the risk coefficient, taken as 0.15 for cardiopulmonary mortality and 0.23 for lung cancer mortality, following WHO guidelines\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo quantify the proportion of mortality attributable to FMPs exposure, the Attributable Fraction (AF) was calculated using\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e,\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ3\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:AF=\\frac{\\text{R}\\text{R}-1}{\\text{R}\\text{R}}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e9\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWhere RR is calculated from Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This helps to estimate the proportion of disease burden that could be prevented if PM\u003csub\u003e2.5\u003c/sub\u003e concentrations were reduced to background levels.\u003c/p\u003e \u003cp\u003eThe chemical toxicity associated with distinct polymer types is a key factor in assessing the ecological risks of MNPs. The potential hazards associated with each polymer were assessed since PM10MNPs represent the highest contribution of each polymer in this study. Based on this, the Polymer Hazard Index (PHI) was calculated specifically for PM\u003csub\u003e10\u003c/sub\u003eMNPs using the following Eq.\u0026nbsp;9\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ4\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:PHI=\\:\\sum\\:({S}_{n}\\:\\times\\:\\:{P}_{n})$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e10\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWhere Sₙ is the hazard score assigned to each polymer type based on its toxicological properties\u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e, Pₙ is the proportion of that polymer within the PM\u003csub\u003e10\u003c/sub\u003eMNPs.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.6 Quality control (QC) and quality assurance (QA)\u003c/h2\u003e \u003cp\u003eQC and QA measures have been implemented during the whole sampling, preparation, and analysis to ensure the accuracy and reliability of data while minimizing contamination risks. All laboratory apparatus, including glassware and steel ware, was cleaned with ultrapure water and pure ethanol before use and then dried in a fume hood to prevent contamination. The chemicals used in this study were filtered with a 0.3 \u0026micro;m pore-sized glass fibre filter and stored in a pre-cleaned glass bottle. During all the analytical steps, no plastic material was used, a cotton laboratory coat and nitrile gloves were worn, and a clean laminar flow bench was used to process all the samples and standard preparation procedures. To ensure accurate measurements, solid standards were weighed in pyrolysis cups (Eco Cups 80 LF, Frontier Labs, Japan), which were pre-cleaned to avoid contamination with a precision microbalance (Sartorius Cubis MSE2.7S-000-DM). Variabilities in the preparation of calibrants, samples and with the instrument were corrected using internal standards\u003csup\u003e\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e\u003c/sup\u003e. Quartz fibre filters were heated at 850℃ for 3 hours before collecting the PM\u003csub\u003e10\u003c/sub\u003e and PM\u003csub\u003e2.5\u003c/sub\u003e samples. To preserve the integrity of the collected samples, they were stored at -20\u0026deg;C until analysis. Additionally, field blanks were placed during sample collection procedures, which were processed similarly to routine laboratory sample preparation procedures. The final concentration of the samples in this study is reported after the blank subtraction. During the analysis of samples by Py-GC-MS, blank cups were also placed to check any carryover signals and cross-contamination from the previous sample analyzed. The reproducibility of the instrument was thoroughly checked throughout the sequence by evaluating the d\u003csub\u003e8\u003c/sub\u003e-PS signals. During pyrolysis, the system is frequently cleaned by measuring multiple instrument blanks (GC runs without injections) to ensure accurate analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowlegements\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Leibniz Association (Berlin, Germany) under the Leibniz Collaborative Excellence Programme, project \u0026apos;AirPlast\u0026apos; (Grant: K389/2021).\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eH.H. and A.K. conceptualized the study. A.K. conducted sampling, Py-GC-MS measurements, data analysis, and wrote the main manuscript, including preparation of figures, tables, and supplementary material. A.E.P. and M.v.P. contributed to data interpretation, scientific guidance, and manuscript refinement. B.S.-B. provided instrumentation, methodological support, and scientific input. H.H. supervised the project and provided critical feedback. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHartmann, N. B. \u003cem\u003eet al.\u003c/em\u003e Are We Speaking the Same Language? Recommendations for a Definition and Categorization Framework for Plastic Debris. \u003cem\u003eEnviron. Sci. Technol.\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, 1039\u0026ndash;1047 (2019).\u003c/li\u003e\n\u003cli\u003eEberhard, T., Casillas, G., Zarus, G. M. \u0026amp; Barr, D. B. 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Species Contributions to PM2.5 Mass Concentrations: Revisiting Common Assumptions for Estimating Organic Mass. \u003cem\u003eAerosol Science and Technology\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 602\u0026ndash;610 (2001).\u003c/li\u003e\n\u003cli\u003eUSEPA. \u003cem\u003eRisk Assessment Guidance for Superfund. Human Health Evaluation Manual (Part A)\u003c/em\u003e. https://www.epa.gov/sites/default/files/2015-09/documents/rags_a.pdf (1989).\u003c/li\u003e\n\u003cli\u003eOstro, B. Assessing the environmental burden of disease at national and local levels. (2004).\u003c/li\u003e\n\u003cli\u003eWHO. \u003cem\u003eWHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide\u003c/em\u003e. (2021).\u003c/li\u003e\n\u003cli\u003eSeeley, M. E. \u0026amp; Lynch, J. M. Previous successes and untapped potential of pyrolysis\u0026ndash;GC/MS for the analysis of plastic pollution. \u003cem\u003eAnal Bioanal Chem\u003c/em\u003e (2023) doi:10.1007/s00216-023-04671-1.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Micro- and nano-plastics (MNPs), urban air, polymer composition, tire wear particles, inhalation exposure","lastPublishedDoi":"10.21203/rs.3.rs-6790463/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6790463/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAirborne micro- and nano-plastics (MNPs) represent a long-time underestimated threat to the urban environment, directly challenging Sustainable Development Goal 3 (Good Health and Well-Being). This study characterizes the concentration and polymer composition of atmospheric MNPs in urban air by analyzing size-fractionated aerosol samples using Pyrolysis-Gas Chromatography-Mass Spectrometry. Total PM\u003csub\u003e10\u003c/sub\u003eMNPs concentrations averaged 0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, with fine microplastics and coarse microplastics contributing equally. Tire wear particles were dominant, constituting approximately 65% of total MNPs, and car tire tread particles were consistently abundant across all studied size fractions. The identified polymers were strongly correlated with carbonaceous aerosol markers, indicating complex atmospheric interactions. An estimated inhalation of 2.1 \u0026micro;g/day of airborne MNPs, combined with polymer-specific hazard index, may increase the relative risk of cardiopulmonary mortality by up to 9% and lung cancer-related mortality by up to 13%. By integrating exposure, risk assessment, and analytical data, these findings highlight the need for global policy action, emphasizing the value of region-specific research for air quality and public health initiatives.\u003c/p\u003e","manuscriptTitle":"Micro- and nano-plastics (MNPs) in urban air: polymer composition, interactions and inhalation risk","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-16 15:33:16","doi":"10.21203/rs.3.rs-6790463/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-earth-and-environment","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsenv","sideBox":"Learn more about [Communications Earth and Environment](https://www.nature.com/commsenv/)","snPcode":"","submissionUrl":"","title":"Communications Earth \u0026 Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"26ecb1f7-21a8-4139-b825-5e2ff43a1430","owner":[],"postedDate":"June 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49937986,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry/Atmospheric chemistry"},{"id":49937987,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"}],"tags":[],"updatedAt":"2025-12-02T08:10:58+00:00","versionOfRecord":{"articleIdentity":"rs-6790463","link":"https://doi.org/10.1038/s43247-025-02980-0","journal":{"identity":"communications-earth-and-environment","isVorOnly":false,"title":"Communications Earth \u0026 Environment"},"publishedOn":"2025-12-01 05:00:00","publishedOnDateReadable":"December 1st, 2025"},"versionCreatedAt":"2025-06-16 15:33:16","video":"","vorDoi":"10.1038/s43247-025-02980-0","vorDoiUrl":"https://doi.org/10.1038/s43247-025-02980-0","workflowStages":[]},"version":"v1","identity":"rs-6790463","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6790463","identity":"rs-6790463","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}