Skip to main content
SpringerLink
Log in

Students exposure assessment towards PM number concentration while commuting from different transport modes during school timings

  • Original Paper
  • Published:
Stochastic Environmental Research and Risk Assessment Aims and scope Submit manuscript

Abstract

Among the various daily activities, commuting to school is considered as an important activity for the students. While commute, students are exposed to elevated particle concentrations that make significant contributions to their daily personal exposures. Present study compares the student exposure towards particle number concentration (PNC) and inhaled doses while commuting from different transports during morning (MT) and afternoon (AT) trips. PNC was measured from four different transport modes: two-wheeler (2W), three-wheeler (3W), passenger car (PC) and school bus (SB) during summer and winter seasons. In summer season, average total PNC was highest for 3W and SB during MT (5.53E+07 # m−3) and AT (5.29E+07 # m−3) trips respectively. However, in winter season, 3W has the highest average total PNC during MT (1.04E+08 # m−3) and AT (7.92E+07 # m−3) trips. Ventilation settings greatly influence the in-cabin PNC and found to be highest under window open (WO) scenario for PC and least under WO and window closed scenarios for SB during MT and AT trips respectively. The PNC exposure varies significantly with student seating positions inside SB and followed different trends during MT (front > middle > rear) and AT (rear > front > middle) trips. The mixed-effect multivariate linear regression model was used to estimate the effects of multiple predictor variables that influence the PNC measured from different transport modes while commuting. Background concentration (PNC) and meteorological variables (wind speed, ambient temperature and relative humidity) were important predictors of PNC measured while commuting and explained the variability between 0.04–27.31%.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

PM:

Particulate matter (aerodynamic diameter ≤ 2.5 μm, PM2.5)

O-D:

Origin–Destination

MEs:

Microenvironments

2W:

Two-wheeler

3W:

Three-wheeler

PC:

Passenger car

SB:

School bus

AERs:

Air exchange rates

PNC:

Particle number concentration

MT:

Morning timing

AT:

Afternoon timing

WO:

Windows open

WC:

Windows closed

References

  • Adak P, Sahu R, Elumalai SP (2016) Development of emission factors for motorcycles and shared auto-rickshaws using real-world driving cycle for a typical Indian city. Sci Total Environ 544:299–308

    CAS  Google Scholar 

  • Adams HS, Nieuwenhuijsen MJ, Colvile RN, mcmullen MAS, Khandelwal P, (2001) Fine particle personal exposure levels in transport microenvironments, London UK. Sci Total Environ 279(1–3):29–44

    CAS  Google Scholar 

  • Adar SD, Davey M, Sullivan JR, Compher M, Szpiro A, Liu LJ (2008) Predicting airborne particle levels aboard Washington State school buses. Atmos Environ 42:7590–7599

    CAS  Google Scholar 

  • Adar SD, Gold DR, Coull BA, Schwartz J, Stone PH, Suh H (2007) Focused exposures to airborne traffic particles and heart rate variability in the elderly. Epidemiology 18:95–103

    Google Scholar 

  • Ai ZT, Mak CM (2015) From street canyon microclimate to indoor environmental quality in naturally ventilated urban buildings: issues and possibilities for improvement. Build Environ 94:489–503

    CAS  Google Scholar 

  • Air Quality in Europe d (2017) Report. Publications Office of the European Union, Luxembourg.

  • Alameddine I, Abi Esber L, Bou Zeid E, Hatzopoulou M, El-Fadel M (2016) Operational and environmental determinants of in-vehicle CO and PM2.5 exposure. Sci Total Environ 551:42–50

    Google Scholar 

  • Almeida SM, Silva AV, Sarmento S (2014) Effects of exposure to particles and ozone on hospital admissions for cardiorespiratory diseases in setúbal, Portugal. J Toxicol Environ Health Part A 77:837–848

    CAS  Google Scholar 

  • Apte JS, Kirchstetter TW, Reich AH, Deshpande SJ, Kaushik G, Chel A, Marshall JD, Nazaroff WW (2011) Concentrations of fine, ultrafine, and black carbon particles in auto-rickshaws in New Delhi. India Atmos Environ 45(26):4470–4480

    CAS  Google Scholar 

  • Asmi E, Antola M, Yli-Tuomi T, Jantunen M, Aarnio P, Makela T, Hillamo R, Hameri K (2009) Driver and passenger exposure to aerosol particles in buses and trams in Helsinki. Finland Sci Total Environ 407(8):2860–2867

    CAS  Google Scholar 

  • Beddows DCS, Harrison RM, Green DC, Fuller GW (2015) Receptor modelling of both particle composition and size distribution from a background site in London, UK. Atmos Chem Phys 15:10107–10125

    CAS  Google Scholar 

  • Behrentz E, Fitz DR, Pankratz DV, Sabin LD, Colome S, Fruin SA, Winer AM (2004) Measuring self-pollution in school buses using a tracer gas technique. Atmos Environ 38:3735–3746

    CAS  Google Scholar 

  • Bigazzi AY, Figliozzi MA (2014) Review of urban bicyclists’ intake and uptake of traffic-related air pollution. Transp Rev 34:221–245

    Google Scholar 

  • Buonanno G, Giovinco G, Morawska L, Stabile L (2011) Tracheobronchial and alveolar dose of submicrometer particles for different population age groups in Italy. Atmos Environ 45(34):6216–6224

    CAS  Google Scholar 

  • Cepeda M, Schoufour J, Freak-Poli R, Koolhaas CM, Dhana K, Bramer WM, Franco OH (2017) Levels of ambient air pollution according to mode of transport: a systematic review. Lancet Public Health 2(1):23–34

    Google Scholar 

  • Charron A, Harrison RM (2003) Primary particle formation from vehicle emissions during exhaust dilution in the roadside atmosphere. Atmos Environ 37(29):4109–4119

    CAS  Google Scholar 

  • Charron A, Harrison RM (2005) Fine (PM2.5) and coarse (PM2.5-10) particulate matter on a heavily trafficked London highway: sources and processes. Environ Sci Technol 39:7768–7776

    CAS  Google Scholar 

  • Choi W, Ranasinghe D, Bunavage K, deshazo JR, Wu L, Seguel R, Winer AM, Paulson SE, (2016) The effects of the built environment, traffic patterns, and micrometeorology on street level ultrafine particle concentrations at a block scale: results from multiple urban sites. Sci Total Environ 553:474–485

    CAS  Google Scholar 

  • Clifford S, Mazaheri M, Salimi F, Ezz WN, Yeganeh B, Low-Choy S, Walker K, Mengersen K, Marks GB, Morawska L (2018) Effects of exposure to ambient ultrafine particles on respiratory health and systemic inflammation in children. Environ Int 114:167–180

    CAS  Google Scholar 

  • Correia C, Martins V, Cunha-Lopes I, Faria T, Diapouli E, Eleftheriadis K, Almeida SM (2020) Particle exposure and inhaled dose while commuting in Lisbon. Environ Pollut 257:113–547

    Google Scholar 

  • De Nazelle A, Bode O, Orjuela JP (2017) Comparison of air pollution exposures in active vs. Passive travel modes in Europe: a quantitative review. Environ Int 99:151–160

    Google Scholar 

  • De Nazelle A, Fruin S, Westerdahl D, Martinez D, Ripoll A, Kubesch N, Nieuwenhuijsen M (2012) A travel mode comparison of commuters’ exposures to air pollutants in Barcelona. Atmos Environ 59:151–159

    Google Scholar 

  • Delfino RJ, Gillen DJ, Tjoa T, Staimer N, Polidori A, Arhami M, Sioutas C, Longhurst J (2011) Electrocardiograhic ST-segment depression and exposure to traffic-related aerosols in elderly subjects with coronary artery disease. Environ Health Perspect 119:196–202

    CAS  Google Scholar 

  • Fan ZT, Meng Q, Weisel C, Laumbach R, Ohman-Strickland P, Hernandez MZ (2009) Acute exposure to elevated PM2.5 generated by traffic and cardiopulmonary health effect in healthy older adults. J Eposure Sci Environ Epidemiol 19:525–533

    CAS  Google Scholar 

  • Fruin SA, Hudda N, Sioutas C, Delfino RJ (2011) Predictive model for vehicle air exchange rates based on a large. Represent sample Environ Sci Technol 45(8):3569–3575

    CAS  Google Scholar 

  • Goel A, Kumar P (2016) Vertical and horizontal variability in airborne nanoparticles and their exposure around signalised traffic intersections. Environ Pollut 214:54–69

    CAS  Google Scholar 

  • Goel R, Gani S, Guttikunda SK, Wilson D, Tiwari G (2015) On-road PM2.5 pollution exposure in multiple transport microenvironments in Delhi. Atmos Environ 123:129–138

    CAS  Google Scholar 

  • Government of India (2011) Dhanbad city census 2011 data. https://www.census2011.co.in/. Accessed 15 Feb 2020.

  • Ham W, Vijayan A, Schulte N, Herner JD (2017) Commuter exposure to PM2.5, BC, and UFP in six common transport microenvironments in Sacramento. California Atmos environ 167:335–345

    CAS  Google Scholar 

  • Hammond D, Jones S, Lalor M (2006) In-vehicle measurement of ultrafine particles on compressed natural gas, conventional diesel, and oxidation-catalyst diesel heavy-duty transit buses. Environ Monit Assess 125(1–3):239–246

    Google Scholar 

  • Han X, Naeher LP (2006) A review of traffic-related air pollution exposure assessment studies in the developing world. Environ Int 32:106–120

    CAS  Google Scholar 

  • Health Effects Institute (2010) In: Traffic-Related Air Pollution: a Critical Review of the Literature on Emissions, Exposure and Health Effects. Health Effects Institute Special Report No.17.

  • Health effects of transport-related air pollution (2005) Copenhagen: WHO Regional Office for Europe.

  • Heinzerling A, Hsu J, Yip F (2016) Respiratory health effects of ultrafine particles in children: a literature review. Water Air Soil Pollut 227(1):32

    Google Scholar 

  • Hinds WC (1999) Aerosol Technology: Properties, Behavior, and Measurement of Airborne Particles. Wiley, New York

    Google Scholar 

  • Hofman J, Samson R, Joosen S, Blust R, Lenaerts S (2018) Cyclist exposure to black carbon, ultrafine particles and heavy metals: an experimental study along two commuting routes near Antwerp, Belgium. Environ Res 164:530–538

    CAS  Google Scholar 

  • Huang J, Deng F, Wu S, Guo X (2012) Comparisons of personal exposure to PM2.5 and CO by different commuting modes in Beijing. China Sci Total Environ 425:52–59

    CAS  Google Scholar 

  • Hussein T, Juwhari H, Al Kuisi M, Alkattan H, Lahlouh B, Al-Hunaiti A (2018) Accumulation and coarse mode aerosol concentrations and carbonaceous contents in the urban background atmosphere in Amman. Jordan Arabian J Geosci 11(20):617

    Google Scholar 

  • Hussein T, Kukkonen J, Korhonen H, Pohjola M, Pirjola L, Wraith D, Härkönen J, Teinilä K, Koponen IK, Karppinen A, Hillamo R, Kulmala M (2007) Evaluation and modeling of the size fractionated aerosol particle number concentration measurements nearby a major road in Helsinki – part II: aerosol measurements within the SAPPHIRE project. Atmos Chem Phys 7:4081–4094

    CAS  Google Scholar 

  • Jacob DC (1999) Introduction to Atmospheric Chemistry Princeton. University Press, Princeton, New Jersey

    Google Scholar 

  • Jeong H, Park D (2017) Contribution of time-activity pattern and microenvironment to black carbon (BC) inhalation exposure and potential internal dose among elementary school children. Atmos Environ 164:270–279

    CAS  Google Scholar 

  • Karanasiou A, Viana M, Querol X, Moreno T, de Leeuw F (2014) Assessment of personal exposure to particulate air pollution during commuting in European cities-recommendations and policy implications. Sci Total Environ 490:785–797

    CAS  Google Scholar 

  • Kaur S, Nieuwenhuijsen MJ (2009) Determinants of personal exposure to PM2.5, ultrafine particle counts, and CO in a transport microenvironment. Environ Sci Technol 43:4737–4743

    CAS  Google Scholar 

  • Kaur S, Nieuwenhuijsen MJ, Colvile RN (2007) Fine particulate matter and carbon monoxide exposure concentrations in urban street transport microenvironments. Atmos Environ 41(23):4781–4810

    CAS  Google Scholar 

  • Knibbs LD, Cole-Hunter T, Morawska L (2011) A review of commuter exposure to ultrafine particles and its health effects. Atmos Environ 45(16):2611–2622

    CAS  Google Scholar 

  • Knibbs LD, de Dear RJ, Atkinson SE (2009) Field study of air change and flow rate in six automobiles. Indoor Air 19:303–313

    CAS  Google Scholar 

  • Kolluru SSR, Patra AK, Dubey RS (2019) In-vehicle PM2.5 personal concentrations in winter during long distance road travel in India. Sci Total Environ 684:207–220

    CAS  Google Scholar 

  • Kulshrestha A, Satsangi PG, Masih J, Taneja A (2009) Metal concentration of PM2.5 and PM10 particles and seasonal variations in urban and rural environment of Agra India. Sci Total Environ 407:6196–6204

    CAS  Google Scholar 

  • Kumar A, Elumalai SP (2020) On-site and off-site material preparation pavement approaches on particle emission and associated health impacts on workers. Stoch Env Res Risk Assess 34:183–199

    Google Scholar 

  • Kumar P, Patton AP, Durant JL, Frey HC (2018) A review of factors impacting exposure to PM2.5, ultrafine particles and black carbon in Asian transport microenvironments. Atmos Environ 187:301–316

    CAS  Google Scholar 

  • Leavey A, Reed N, Pate S, Bradley K, Kulkarni P, Biswas P (2017) Comparing onroad real-time simultaneous in-cabin and outdoor particulate and gaseous concentrations for a range of ventilation scenarios. Atmos Environ 166:130–141

    CAS  Google Scholar 

  • Lee ES, Stenstrom MK, Zhu Y (2015) Ultrafine particle infiltration into passenger vehicles. Part I: Experimental evidence. Transp Res Part D: Trans Environ 38:156–165

    Google Scholar 

  • Li B, Lei X, Xiu G, Gao C, Gao S, Qian N (2015a) Personal exposure to black carbon during commuting in peak and off-peak hours in Shanghai. Sci Total Environ 525:237–245

    Google Scholar 

  • Li F, Lee ES, Liu J, Zhu Y (2015b) Predicting self-pollution inside school buses using a CFD and multi-zone coupled model. Atmos Environ 107:16–23

    Google Scholar 

  • Li X, Wang J, Tu XD, Liu W, Huang Z (2007) Vertical variations of particle number concentration and size distribution in a street canyon in Shanghai. China Sci total environ 378(3):306–316

    CAS  Google Scholar 

  • Morales Betancourt R, Galvis B, Balachandran S, Ramos-Bonilla JP, Sarmiento OL, Gallo-Murcia SM, Contreras Y (2017) Exposure to fine particulate, black carbon, and particle number concentration in transportation microenvironments. Atmos Environ 157:135–145

    CAS  Google Scholar 

  • Moreno T, Querol X, Alastuey A, Viana M, Gibbons W (2009) Profiling transient daytime peaks in urban air pollutants: city centre traffic hotspot versus urban background concentrations. J Environ Monit 11:1535–1542

    CAS  Google Scholar 

  • Onat B, Şahin ÜA, Uzun B, Akın Ö, Özkaya F, Ayvaz C (2019) Determinants of exposure to ultrafine particulate matter, black carbon, and PM2.5 in common travel modes in Istanbul. Atmos Environ 206:258–270

    CAS  Google Scholar 

  • Ott W, Klepeis N, Switzer P (2008) Air change rates of motor vehicles and in-vehicle pollutant concentrations from secondhand smoke. J Eposure Sci Environ Epidemiol 18(3):312–325

    CAS  Google Scholar 

  • Pant P, Habib G, Marshall JD, Peltier RE (2017) PM2.5 exposure in highly polluted cities: a case study from New Delhi. India Environmental research 156:167–174

    CAS  Google Scholar 

  • Pérez N, Pey J, Cusack M, Reche C, Querol X, Alastuey A, Viana M (2010) Variability of particle number, black carbon, and PM10, PM2.5, and PM1 levels and speciation influence of road traffic emissions on urban air quality. Aerosol Sci Technol 44(7):487–499

    Google Scholar 

  • Qiu Z, Lv H, Zhang F, Wang W, Hao Y (2019) Pedestrian exposure to PM2.5, BC and UFP of adults and teens: a case study in Xi’an. China Sustain Cities Soc 51:101–774

    Google Scholar 

  • Ragettli MS, Corradi E, Braun-Fahrländer C, Schindler C, de Nazelle A, Jerrett M, Ducret-Stich RE, Kunzil N, Phuleria HC (2013) Commuter exposure to ultrafine particles in different urban locations, transportation modes and routes. Atmos Environ 77:376–384

    CAS  Google Scholar 

  • Ramos CA, Wolterbeek HT, Almeida SM (2016) Air pollutant exposure and inhaled dose during urban commuting: a comparison between cycling and motorized modes. Air Qual Atmos Health 9(8):867–879

    CAS  Google Scholar 

  • Ramos MJ, Vasconcelos A, Faria M (2015) Comparison of particulate matter inhalation for users of different transport modes in Lisbon. Transp Res Procedia 10:433–442

    Google Scholar 

  • Riediker M, Cascio WE, Griggs TR, Herbst MC, Bromberg PA, Neas L, Willams RW, Devlin RB (2004) Particulate matter exposure in cars is associated with cardiovascular effects in healthy young men. Am J Respir Crit Care Med 169(8):934–940

    Google Scholar 

  • Rivas I, Kumar P, Hagen-Zanker A (2017) Exposure to air pollutants during commuting in London: are there inequalities among different socio-economic groups. Environ Int 101:143–157

    CAS  Google Scholar 

  • Sabapathy A, Santhosh Ragavan V, K, Saksena S, (2012) An assessment of two-wheeler CO and PM10 exposures along arterial main roads in Bangalore city, India. Open Atmos Sci J. https://doi.org/10.2174/1874282301206010071

    Article  Google Scholar 

  • Schneider IL, Teixeira EC, Oliveira LFS, Wiegand F (2015) Atmospheric particle number concentration and size distribution in a traffic –impacted area. Atmos Pollut Res 6(5):877–885

    CAS  Google Scholar 

  • Seinfeld JH, Pandis SN (1998) Atmospheric chemistry and physics of air pollution New York. John Wiley and Sons Inc, USA

    Google Scholar 

  • Shen J, Gao Z (2019) Commuter exposure to particulate matters in four common transportation modes in Nanjing. Build Environ 156:156–170

    Google Scholar 

  • Singh N, Vasudevan V (2018) Understanding school trip mode choice – The case of Kanpur (India). J Transp Geogr 66:283–290

    Google Scholar 

  • Singh S, Elumalai SP, Pal AK (2016) Rain ph estimation based on the particulate matter pollutants and wet deposition study. Sci Total Environ 563:293–301

    Google Scholar 

  • U.S. Environmental Protection Agency, (2009) Metabolically Derived Human Ventilation Rates: A Revised Approach based upon Oxygen Consumption Rates. National Center for Environmental Assessment, Office of Research and Development

    Google Scholar 

  • Valavanidis A, Fiotakis K, Vlachogianni T (2008) Airborne particulate matter and human health: toxicological assessment and importance of size and composition of particles for oxidative damage and carcinogenic mechanisms. J Environ Sci Health Part C 26(4):339–362

    CAS  Google Scholar 

  • Vinicius M, Rodrigues C, Moreira M, Paula MD (2016) Hotspots of black carbon and PM 2.5 in an urban area and relationships to traffic characteristics. Environ Pollut 218:475–486

    Google Scholar 

  • Wang G, Jiang R, Zhao Z, Song W (2013) Effects of ozone and fine particulate matter (PM2.5) on rat system in flammation and cardiac function. Toxicol Lett 217:23–33

    CAS  Google Scholar 

  • Wang X, Westerdahl D, Wu Y, Pan X, Zhang KM (2011) On-road emission factor distributions of individual diesel vehicles in and around Beijing. China Atmos Environ 45(2):503–513

    CAS  Google Scholar 

  • Watson JR, Stock CA, Sarmiento JL (2015) Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic–size-based ecosystem model. Prog Oceanogr 138:521–532

    Google Scholar 

  • Weichenthal S, Dufresne A, Infante-Rivard C, Joseph L (2008) Determinants of ultrafine particle exposures in transportation environments: findings of an 8-month survey conducted in Montreal, Canada. J Eposure Sci Environ Epidemiol 18:551–563

    CAS  Google Scholar 

  • Wu S, Deng F, Niu J, Huang Q, Liu Y, Guo X (2010) Association of heart rate variability in taxi drivers with marked changes in particulate air pollution in Beijing in 2008. Environ Health Perspect 118:87–91

    CAS  Google Scholar 

Download references

Acknowledgement

We express our sincere gratitude to student, driver and attendant for participating in present study. Also, we would like to thank the school administration for giving their permission to conduct measurements inside school premises and transport modes. We also express our gratitude towards IIT(ISM), Dhanbad for providing financial support (FRS project: FRS (40)/2012-2013/ESE) entitled “Physical and chemical characterization of PM for Dhanbad city to identify the contribution from traffic sources” to carry out this work.

Author information

Authors and Affiliations

  1. Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, 826004, India

    Sandeep Kumar Chaudhry & Suresh Pandian Elumalai

Authors
  1. Sandeep Kumar Chaudhry
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Suresh Pandian Elumalai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Suresh Pandian Elumalai.

Ethics declarations

Conflict of interest

The authors declare that they have no Conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 2886 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chaudhry, S.K., Elumalai, S.P. Students exposure assessment towards PM number concentration while commuting from different transport modes during school timings. Stoch Environ Res Risk Assess 35, 371–388 (2021). https://doi.org/10.1007/s00477-020-01902-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00477-020-01902-0

Keywords

Search

Navigation