Abstract
Background
Traffic-related air pollution (TRAP) poses significant risks to human health, particularly in urban areas with high traffic volumes. Intake fraction (iF) quantifies the relationship between emissions and exposure, defined as the ratio of the total inhalation increment of all exposed individuals in a target population to the emissions from specific pollution sources over a certain period.
Objective
The overarching objective of this study is to unravel the underlying value and significance of the iF method in evaluating TRAP exposure risks, while also exploring its future development trajectories and potential avenues for application.
Methods
We conducted a comprehensive review of iF to assess TRAP exposure. We employed a search strategy to identify and analyze literature on iF methods related to TRAP exposure across academic databases covering the period from 2002 to 2024. After deduplication, title and abstract screening, and full-text review, we ultimately included 25 studies on iF related to TRAP.
Results
We classified the measurement methods of iF into four types: simple estimation method, dispersion simulation method, numerical simulation method, and exposure monitoring method. We found orders of magnitude of differences in iF among studies. Population density, pollutant concentration, and breathing rate explain a significant portion of the variations. iF values of nitrogen oxides (NOx), carbon monoxide (CO), and fine particulate matter (PM2.5) are higher than those of diesel particulate matter (DPM), ultrafine particles (UFP), and benzene. Compared to power plants, TRAP has higher iF values, emphasizing the control priority of TRAP. Future research should expand to under-researched regions, strengthen investigations on UFP and secondary pollutants, and refine iF calculation methods using high-resolution and mobility data.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 6 print issues and online access
$259.00 per year
only $43.17 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout




Similar content being viewed by others
Data availability
The data that support the findings of this study are available from the corresponding author, (XD), upon reasonable request.
References
Al Otary L, Abou-Zeid M, Kaysi I. Modeling car ownership and use in a developing country context with informal public transportation. Transportation. 2022;49:1–36.
Hou LC, Wang YP, Zheng YH, Zhang AM. The impact of vehicle ownership on carbon emissions in the transportation sector. Sustainability. 2022;14:23.
Guo D, Wang J, Zhao JB, Sun F, Gao S, Li CD, et al. A vehicle path planning method based on a dynamic traffic network that considers fuel consumption and emissions. Sci Total Environ. 2019;663:935–43.
Yang HH, Dhital NB, Lai YH, Chan TY. Intermodal comparison of commuters’ exposure to VOCs between public, private, and active transportation. Environ Monit Assess. 2023;195:14.
Kwan SC, Zakaria SB, Ibrahim MF, Mahiyuddin WRW, Sofwan NM, Wahab MIA, et al. Health impacts from TRAPs and carbon emissions in the projected electric vehicle growth and energy generation mix scenarios in Malaysia. Environ Res. 2023;216:10.
Hu YH, Chavez T, Eckel SP, Yang TY, Chen XC, Vigil M, et al. Joint effects of traffic-related air pollution and hypertensive disorders of pregnancy on maternal postpartum depressive and anxiety symptoms. J Expo Sci Environ Epidemiol. 2025;35:278–87.
Li QM, Liang J, Wang Q, Chen YT, Yang HY, Ling H, et al. 2022. Numerical Investigations of urban pollutant dispersion and building intake fraction with various 3D building configurations and tree plantings. Int J Environ Res Public Health. 2022;19:3524.
Requia WJ, Dalumpines R, Adams MD, Arain A, Ferguson M, Koutrakis P. Modeling spatial patterns of link-based PM2.5 emissions and subsequent human exposure in a large Canadian metropolitan area. Atmos Environ. 2017;158:172–80.
Wei P, Brimblecombe P, Yang FH, Anand A, Xing Y, Sun L, et al. Determination of local traffic emission and non-local background source contribution to on-road air pollution using fixed-route mobile air sensor network. Environ Pollut. 2021;290:12.
Ramacher MOP, Karl M. Integrating modes of transport in a dynamic modelling approach to evaluate population exposure to ambient NO2 and PM2.5 pollution in urban areas. Int J Environ Res Public Health. 2020;17:35.
Boogaard H, Patton AP, Atkinson RW, Brook JR, Chang H, Crouse DL, et al. Long-term exposure to traffic-related air pollution and selected health outcomes: a systematic review and meta-analysis. Environ Int. 2022;164:6.
Matz CJ, Egyed M, Hocking R, Seenundun S, Charman N, Edmonds N. Human health effects of traffic-related air pollution (TRAP): a scoping review protocol. Syst Rev. 2019;8:5.
Bennett DH, McKone TE, Evans JS, Nazaroff WW, Margni MD, Jolliet O, et al. Defining intake fraction. Environ Sci Technol. 2002;36:206A–211A.
Marshall JD, Nazaroff WW. Exposure Analysis (Chapter 10: Intake Fraction). In University of British Columbia. 2006, pp. 237–251. Retrieved from https://depts.washington.edu/airqual/reports/Intake%20Fraction%20--%20proofs.pdf.
Habilomatis G, Chaloulakou A. A CFD modeling study in an urban street canyon for ultrafine particles and population exposure: the intake fraction approach. Sci Total Environ. 2015;530:227–32.
Hang J, Luo Z, Wang X, He L, Wang B, Zhu W. The influence of street layouts and viaduct settings on daily carbon monoxide exposure and intake fraction in idealized urban canyons. Environ Pollut. 2017;220:72–86.
Sha CY, Wang XM, Lin YY, Fan YF, Chen X, Hang J. The impact of urban open space and ‘lift-up’ building design on building intake fraction and daily pollutant exposure in idealized urban models. Sci Total Environ. 2018;633:1314–28.
Shi TH, Ming TZ, Wu YJ, Peng C, Fang YP, de_Richter R. The effect of exhaust emissions from a group of moving vehicles on pollutant dispersion in the street canyons. Build Environ. 2020;181:107120.
Xu J, Jin TS, Miao YN, Han B, Gao JJ, Bai ZP, et al. Individual and population intake fractions of diesel particulate matter (DPM) in bus stop microenvironments. Environ Pollut. 2015;207:161–7.
Li ZT, Zhang H, Wen CY, Yang AS, Juan YH. The effects of lateral entrainment on pollutant dispersion inside a street canyon and the corresponding optimal urban design strategies. Build Environ. 2021;195:107740.
Lin YY, Chen GW, Chen TH, Luo ZW, Yuan C, Gao P, et al. The influence of advertisement boards, street and source layouts on CO dispersion and building intake fraction in three-dimensional urban-like models. Build Environ. 2019;150:297–321.
Heath GA, Granvold PW, Hoats AS, Nazaroff WW. Intake fraction assessment of the air pollutant exposure implications of a shift toward distributed electricity generation. Atmos Environ. 2006;40:7164–77.
Heath GA, Nazaroff WW. Intake-to-delivered-energy ratios for central station and distributed electricity generation in California. Atmos Environ. 2007;41:9159–72.
Parvez F, Lamancusa C, Wagstrom K. Primary and secondary particulate matter intake fraction from different height emission sources. Atmos Environ. 2017;165:1–11.
Wang SX, Hao JM, Ho MS, Li J, Lu YQ. Intake fractions of industrial air pollutants in China: estimation and application. Sci Total Environ. 2006;354:127–41.
Zhou Y, Levy JI, Hammitt JK, Evans JS. Estimating population exposure to power plant emissions using CALPUFF: a case study in Beijing, China. Atmos Environ. 2003;37:815–26.
Bennett DH, Margni MD, McKone TE, Jolliet O. Intake fraction for multimedia pollutants: a tool for life cycle analysis and comparative risk assessment. Risk Anal. 2002;22:905–18.
Fantke P, Jolliet O, Apte JS, Hodas N, Evans J, Weschler CJ, et al. Characterizing Aggregated Exposure to Primary Particulate Matter: Recommended Intake Fractions for Indoor and Outdoor Sources. Environ Sci Technol. 2017;51:9089–100.
Hirai Y, Sakai S, Watanabe N, Takatsuki H. Congener-specific intake fractions for PCDDs/DFs and Co-PCBs: modeling and validation. Chemosphere. 2004;54:1383–1400.
Huijbregts MA, Struijs J, Goedkoop M, Heijungs R, Jan Hendriks A, van de Meent D. Human population intake fractions and environmental fate factors of toxic pollutants in life cycle impact assessment. Chemosphere. 2005;61:1495–504.
Humbert S, Marshall JD, Shaked S, Spadaro JV, Nishioka Y, Preiss P, et al. Intake fraction for particulate matter: recommendations for life cycle impact assessment. Environ Sci Technol. 2011;45:4808–16.
Levy JL, Wolff SK, Evans JS. A regression-based approach for estimating primary and secondary particulate matter intake fractions. Risk Anal. 2002;22:895–904.
Shin HM, McKone TE, Bennett DH. Intake fraction for the indoor environment: a tool for prioritizing indoor chemical sources. Environ Sci Technol. 2012;46:10063–72.
Arnot JA, Mackay D, Parkerton TF, Zaleski RT, Warren CS. Multimedia modeling of human exposure to chemical substances: the roles of food web biomagnification and biotransformation. Environ Toxicol Chem. 2010;29:45–55.
Hodas N, Loh M, Shin HM, Li D, Bennett D, McKone TE, et al. Indoor inhalation intake fractions of fine particulate matter: review of influencing factors. Indoor Air. 2016;26:836–56.
Huijbregts MAJ, Geelen LMJ, Hertwich EG, McKone TE, Van De Meent D. A comparison between the multimedia fate and exposure models CalTOX and uniform system for evaluation of substances adapted for life-cycle assessment based on the population intake fraction of toxic pollutants. Environ Toxicol Chem. 2005;24:486–93.
Navarro KM, Cisneros R, O’Neill SM, Schweizer D, Larkin NK, Balmes JR. Air-quality impacts and intake fraction of PM2.5 during the 2013 Rim megafire. Environ Sci Technol. 2016;50:11965–73.
Russo JS, Khalifa HE. CFD assessment of intake fraction in the indoor environment. Build Environ. 2010;45:1968–75.
Tainio M, Holnicki P, Loh MM, Nahorski Z. Intake fraction variability between air pollution emission sources inside an urban area. Risk Anal. 2014;34:2021–34.
Apte JS, Bombrun E, Marshall JD, Nazaroff WW. Global intraurban intake fractions for primary air pollutants from vehicles and other distributed sources. Environ Sci Technol. 2012;46:3415–23.
Loh MM, Soares J, Karppinen A, Kukkonen J, Kangas L, Riikonen K, et al. Intake fraction distributions for benzene from vehicles in the Helsinki metropolitan area. Atmos Environ. 2009;43:301–10.
Requia WJ, Adams MD, Arain A, Ferguson M. Particulate matter intake fractions for vehicular emissions at elementary schools in Hamilton, Canada: an assessment of outdoor and indoor exposure. Air Qual Atmos Health. 2017;10:1259–67.
Stevens G, de Foy B, West JJ, Levy JI. Developing intake fraction estimates with limited data: comparison of methods in Mexico City. Atmos Environ. 2007;41:3672–83.
Marshall JD, Teoh SK, Nazaroff WW. Intake fraction of nonreactive vehicle emissions in US urban areas. Atmos Environ. 2005;39:1363–71.
Marshall JD, Behrentz E. Vehicle self-pollution intake fraction: children’s exposure to school bus emissions. Environ Sci Technol. 2005;39:2559–63.
Briant R, Seigneur C, Gadrat M, Bugajny C. Evaluation of roadway Gaussian plume models with large-scale measurement campaigns. Geosci Model Dev. 2013;6:445–56.
Taimisto P, Tainio M, Karvosenoja N, Kupiainen K, Porvari P, Karppinen A, et al. Evaluation of intake fractions for different subpopulations due to primary fine particulate matter (PM2.5) emitted from domestic wood combustion and traffic in Finland. Air Qual Atmos Health. 2011;4:199–209.
Lobscheid AB, Nazaroff WW, Spears M, Horvath A, McKone TE. Intake fractions of primary conserved air pollutants emitted from on-road vehicles in the United States. Atmos Environ. 2012;63:298–305.
Greco SL, Wilson AM, Spengler JD, Levy JI. Spatial patterns of mobile source particulate matter emissions-to-exposure relationships across the United States. Atmos Environ. 2007;41:1011–25.
Bastos J, Milando C, Freire F, Batterman S. Intake fraction estimates for on-road fine particulate matter (PM2.5) emissions: exploring spatial variation of emissions and population distribution in Lisbon, Portugal. Atmos Environ. 2018;190:284–93.
Carella B, Mudu P. Exposure to air pollution: an intake fraction application in Turin province. Arch Environ Occup Health. 2009;64:156–63.
Requia WJ, Adams MD, Arain A, Koutrakis P, Lee WC, Ferguson M. Spatio-temporal analysis of particulate matter intake fractions for vehicular emissions: hourly variation by micro-environments in the Greater Toronto and Hamilton Area, Canada. Sci Total Environ. 2017;599-600:1813–22.
Yuan Y, Zhu Y, Wu J. Modeling traffic-emitted ultrafine particle concentration and intake fraction in Corpus Christi, Texas. Chem Prod Process Model. 2011;6:8.
Zhou Y, Levy JI. The impact of urban street canyons on population exposure to traffic-related primary pollutants. Atmos Environ. 2008;42:3087–98.
Song XC, Zhao Y. Numerical investigation of airflow patterns and pollutant dispersions induced by a fleet of vehicles inside road tunnels using dynamic mesh Part II: Pollutant dispersion and exposure levels. Atmos Environ. 2019;210:198–210.
Wang BQ, Li YN, Tang ZN, Cai NN, Niu HH. Effects of vehicle emissions on the PM2.5 dispersion and intake fraction in urban street canyons. J Clean Prod. 2021;324:129212.
Zhang K, Chen GW, Wang XM, Liu SH, Mak CM, Fan YF, et al. Numerical evaluations of urban design technique to reduce vehicular personal intake fraction in deep street canyons. Sci Total Environ. 2019;653:968–94.
Zhang K, Chen GW, Zhang Y, Liu SH, Wang XM, Wang BM, et al. Integrated impacts of turbulent mixing and NOX-O3 photochemistry on reactive pollutant dispersion and intake fraction in shallow and deep street canyons. Sci Total Environ. 2020;712:135553.
Du X, Wu Y, Fu LX, Wang SX, Zhang SJ, Hao JM. Intake fraction of PM2.5 and NOx from vehicle emissions in Beijing based on personal exposure data. Atmos Environ. 2012;57:233–43.
Luo ZW, Li YG, Nazaroff WW. Intake fraction of nonreactive motor vehicle exhaust in Hong Kong. Atmos Environ. 2010;44:1913–8.
Marshall JD, Riley WJ, McKone TE, Nazaroff WW. Intake fraction of primary pollutants: motor vehicle emissions in the South Coast Air Basin. Atmos Environ. 2003;37:3455–68.
Meng C, Cheng TH, Gu XF, Shi SY, Wang WN, Wu Y, et al. Contribution of meteorological factors to particulate pollution during winters in Beijing. Sci Total Environ. 2019;656:977–85.
Nauth D, Loughner CP, Tzortziou M. The influence of synoptic-scale wind patterns on column-integrated nitrogen dioxide, ground-level ozone, and the development of sea-breeze circulations in the New York City metropolitan area. J Appl Meteorol Climatol. 2023;62:645–55.
Sokolowski MM. Burning out coal power plants with the Industrial Emissions Directive. J World Energy Law Bus. 2018;11:260–9.
Yuan M, Barron AR, Selin NE, Picciano PD, Metz LE, Reilly JM, et al. Meeting US greenhouse gas emissions goals with the international air pollution provision of the clean air act. Environ Res Lett. 2022;17:20.
Deng W. Comparative study on flue gas emission rules of thermal power plants in EU and China. Electric Power. 2015;48:156–60.
Anenberg SC, Miller J, Injares RM, Du L, Henze DK, Lacey F, et al. Impacts and mitigation of excess diesel-related NOx emissions in 11 major vehicle markets. Nature. 2017;545:467.
Vijayaraghavan K, Lindhjem C, Koo B, DenBleyker A, Tai E, Shah T, et al. Source apportionment of emissions from light-duty gasoline vehicles and other sources in the United States for ozone and particulate matter. J Air Waste Manag Assoc. 2016;66:98–119.
Zheng XQ, Chai QM, Chen Y, Li XM. Assessing the GHG mitigation effect of the National VI Emissions Standard for light duty vehicles in China. Environ Sci Pollut Res. 2023;30:36–43.
Shen Y, Wu TR, Lian AP, Gao J, Peng F, Song GH, et al. Dynamic emission characteristics and control strategies of air pollutants from motor vehicles in downtown Beijing, China. J Environ Sci. 2024;136:637–46.
Stevenson M, Thompson J, de Sá TH, Ewing R, Mohan D, McClure R, et al. Land use, transport, and population health: estimating the health benefits of compact cities. Lancet. 2016;388:2925–35.
Bai X, Chen H, Oliver BG. The health effects of traffic-related air pollution: a review focused the health effects of going green. Chemosphere. 2022;289:9.
Bhardawaj A, Habib G, Kumar A, Singh S, Nema AK. A review of ultrafine particle-related pollution during vehicular motion, health effects and control. J Environ Sci Public Health. 2017;01:268–88.
Groma V, Alföldy B, Börcsök E, Czömpöly O, Füri P, Horváthné Kéri A, et al. Sources and health effects of fine and ultrafine aerosol particles in an urban environment. Atmos Pollut Res. 2022;13:101302.
Vallabani NVS, Gruzieva O, Elihn K, Juárez-Facio AT, Steimer SS, Kuhn J, et al. Toxicity and health effects of ultrafine particles: Towards an understanding of the relative impacts of different transport modes. Environ Res. 2023;231:116186.
Damayanti S, Harrison RM, Pope F, Beddows DCS. Limited impact of diesel particle filters on road traffic emissions of ultrafine particles. Environ Int. 2023;174:7.
He Y, Lan XY, Zhu LY. Effect of urban green infrastructure on pedestrian exposure to ultrafine particles: A case study of Guangzhou, China. Urban CLim. 2023;49:13.
Jung CR, Chen WT, Young L, Hsiao TC. A hybrid model for estimating the number concentration of ultrafine particles based on machine learning algorithms in central Taiwan. Environ Int. 2023;175:12.
Lauenburg M, Karl M, Matthias V, Quante M, Ramacher MO. City scale modeling of ultrafine particles in urban areas with special focus on passenger ferryboat emission impact. Toxics. 2022;10:30.
Ge YH, Fu QY, Yi M, Chao Y, Lei XN, Xu XY, et al. High spatial resolution land-use regression model for urban ultrafine particle exposure assessment in Shanghai, China. Sci Total Environ. 2022;816:151633.
Requia WJ, de Melo HFA. Effectiveness of public policies related to traffic emissions in improving air quality in Brazil: a causal inference study using Bayesian structural time-series models. Atmos Environ. 2024;319:9.
Ajayi SA, Adams CA, Dumedah G, Adebanji OA, Ababio-Donkor A, Ackaah W, et al. Public perceptions of vehicular traffic emissions on health risk in Lagos metropolis Nigeria: a critical survey. Heliyon. 2023;9:19.
Soleimani M, Akbari N, Saffari B, Haghshenas H. Health effect assessment of PM2.5 pollution due to vehicular traffic (case study: Isfahan). J Transp Health. 2022;24:22.
Gupta V, Choudhary R, Agarwal A. Integrating land use and traffic to spatial prediction of particulate matter. Urban CLim. 2024;54:20.
Ratanavalachai T, Trivitayanurak W. Application of a PM2.5 dispersion model in the Bangkok central business district for air quality management. Front Environ Sci. 2023;11:12.
Alvarado-Molina M, Curto A, Wheeler AJ, Tham R, Cerin E, Nieuwenhuijsen M, et al. Improving traffic-related air pollution estimates by modelling minor road traffic volumes. Environ Pollut. 2023;338:10.
Li JY, Zhang NY, Tian PF, Zhang M, Shi JS, Chang Y, et al. Significant roles of aged dust aerosols on rapid nitrate formation under dry conditions in a semi-arid city. Environ Pollut. 2023;336:8.
van Drooge BL, Fontal M, Fernández P, Fernández MA, Muñoz-Arnanz J, Jiménez B, et al. Organic molecular tracers in atmospheric PM1 at urban intensive traffic and background sites in two high-insolation European cities. Atmos Environ. 2018;188:71–81.
Zhang ZH, Li HW, Ho WK, Cui L, Men Q, Cao L, et al. Critical roles of surface-enhanced heterogeneous oxidation of SO2 in haze chemistry: review of extended pathways for complex air pollution. Curr Pollut Rep. 2024;10:70–86.
Bowman H, Turnock S, Bauer SE, Tsigaridis K, Deushi M, Oshima N, et al. Changes in anthropogenic precursor emissions drive shifts in the ozone seasonal cycle throughout the northern midlatitude troposphere. Atmos Chem Phys. 2022;22:3507–24.
Cheng F, Li ZQ, Yang ZY, Li RH, Wang DD, Jia AL, et al. First retrieval of 24-hourly 1-km-resolution gapless surface ozone (O3) from space in China using artificial intelligence: diurnal variations and implications for air quality and phytotoxicity. Remote Sens Environ. 2025;316:16.
Li YF, Huang YQ, Li R, Zhang K. Historical redlining and park use during the COVID-19 pandemic: evidence from big mobility data. J Expo Sci Environ Epidemiol. 2024;34:399–406.
Xu R, Huang X, Zhang K, Lyu WX, Ghosh D, Li ZL, et al. Integrating human activity into food environments can better predict cardiometabolic diseases in the United States. Nat Commun. 2023;14:9.
Funding
This work was supported by the National Key Research and Development Program of China (grant number 2022YFC3702604).
Author information
Authors and Affiliations
Contributions
SM: Methodology, formal analysis, investigation, writing—original draft. LQ: Methodology, investigation, writing—review & editing. PW: Writing—review & editing. SC: Writing—review & editing. KZ: Methodology, writing—review & editing. ZW: Writing—review & editing. XD: Conceptualization, methodology, writing—review & editing, resources.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Meng, S., Qi, L., Wu, P. et al. Comprehensive review of intake fraction methods for assessing traffic-related air pollution exposure: insights, variations, and future directions. J Expo Sci Environ Epidemiol (2025). https://doi.org/10.1038/s41370-025-00775-1
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41370-025-00775-1