Skip to main content
SpringerLink
Log in

Source apportionment of BTEX compounds in Tehran, Iran using UNMIX receptor model

  • Published:
Air Quality, Atmosphere & Health Aims and scope Submit manuscript

Abstract

Understanding the distribution levels and sources of volatile organic compounds (VOC), mainly benzene, toluene, ethyl benzene and xylenes (BTEX), in the ambient atmosphere is important for efficiently managing and implementing the associated control strategies. We measured BTEX compounds at an industrial location in the west Tehran city (Iran), which is highly influenced by industrial activities and traffic during the winter and spring seasons during 2014–2015. A multivariate receptor model, UNMIX, was applied on the measured data for the identification of the sources and their contributions to BTEX compounds in a highly industrialised and trafficked atmospheric environment of Tehran city. Three main groups of sources were identified. These included solvent and painting sources (e.g. vehicle manufacturing), motorised road vehicles and mixed origin sources. Whilst the solvent and painting sources and vehicle exhaust emissions contributed to about 5 and 29 % of total BTEX mass, respectively, the mixed origin source contributed to about two third (∼66 %) of the remaining mass. These mixed origin sources included rubber and plastic manufacturing (39 %), leather industries (28 %) and the unknown sources (33 %). The mean concentrations of benzene, toluene, ethyl benzene and average xylene (o, p.m.) compounds were measured as 28.96 ± 9.12 μg m−3, 29.55 ± 9.73 μg m−3, 28.61 ± 12.2 μg/m−3 and 25.68 ± 10.58 μg m−3, respectively. A high correlation coefficient (R 2 > 0.94) was also found between predicted (modelled) and measured concentrations for each sample. Further analyses from UNMIX receptor model showed that the average weekday contributions of BTEX compounds were significantly higher during winter compared with those during spring. This higher concentration during winter may be attributed to calm wind conditions and high stability of the atmosphere, along with the after effect of government policies on the use of cleaner fuel in refineries that became operational in winter 2014.

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.

Institutional subscriptions

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

Similar content being viewed by others

References

  • Al-Dabbous AN, Kumar P (2014) Number and size distribution of airborne nanoparticles during summertime in Kuwait: first observations from the Middle East. Environ Sc Technol 48:13634–13643. doi:10.1021/es505175u

    Article  CAS  Google Scholar 

  • Al-Dabbous AN, Kumar P (2015) Source apportionment of airborne nanoparticles in a Middle Eastern city using positive matrix factorization. Environ Sci 17:802–812

    CAS  Google Scholar 

  • Berglund B, Brunekreef B, Knöppe H, Lindvall T, Maroni M, Mølhave L, Skov P (1992) Effects of indoor air pollution on human health. Indoor Air 2:2–25

    Article  Google Scholar 

  • Blifford IH, Meeker GO (1967) A factor analysis model of large scale pollution (1967). Atmos Environ 1:147–157

    Article  CAS  Google Scholar 

  • Chan DW, Tam CS, Jones A (2007) An inter-comparison of VOC types and distribution in different indoor environments in a university campus. Indoor Built Environ 16:376–382

    Article  CAS  Google Scholar 

  • Chan LY et al. (2006) Characteristics of nonmethane hydrocarbons (NMHCs) in industrial, industrial-urban, and industrial-suburban atmospheres of the Pearl River Delta (PRD) region of south China Journal of Geophysical Research: Atmospheres (1984–2012) 111

  • Chow J, Egami R, Watson J, DeLong T (1990) Applying the air quality source apportionments to geothermal power plant emissions. Bull Geothermal Res Counc 19:208–213

    CAS  Google Scholar 

  • Chow JC, Spengler JD (1986) A method of combining dispersion models and trajectory models with principal component analysis and chemical mass balance receptor models Transactions, Receptor Methods for Source Apportionment: Real World Issues and Applications, TG Pace, ed Air Pollut Control Assoc, Pittsburgh, PA:194

  • Cleland J, Kingsbury G, Mixon P (2002) United States Environmental Protection Agency

    Google Scholar 

  • Cockerham LG, Shane BS (1993) Basic environmental toxicology. CRC Press

  • Crump KS (1994) Risk of benzene-induced leukemia: a sensitivity analysis of the pliofilm cohort with additional follow-up and new exposure estimates. J Toxicol Environ Health 42:219–242

    Article  CAS  Google Scholar 

  • Dutta C, Som D, Chatterjee A, Mukherjee A, Jana T, Sen S (2009) Mixing ratios of carbonyls and BTEX in ambient air of Kolkata, India and their associated health risk. Environ Monit Assess 148:97–107

    Article  CAS  Google Scholar 

  • Gee IL, Sollars CJ (1998) Ambient air levels of volatile organic compounds in Latin American and Asian cities. Chemosphere 36:2497–2506

    Article  CAS  Google Scholar 

  • Helmes C et al (1982) Evaluation and classification of the potential carcinogenicity of organic air pollutants. J Environ Sci Health Part A 17:321–389

    Article  Google Scholar 

  • Henry RC (1994) Vehicle-related hydrocarbon source compositions from ambient data: the GRACE/SAFER method. Environ Sci Technol 37, 37–42

  • Henry RC (1997) History and fundamentals of multivariate air quality receptor models. Chemometrics Intell Lab Syst 37:37–42

    Article  CAS  Google Scholar 

  • Henry RC (2000) UNMIX Version 2 Manual Prepared for the US Environmental Protection Agency

    Google Scholar 

  • Hester RE, Harrison RM (1995) Volatile organic compounds in the atmosphere. vol 4. Royal Society of Chemistry

  • Hong Y-J, Jeng HA, Gau Y-Y, Lin C, Lee I-L (2006) Distribution of volatile organic compounds in ambient air of Kaohsiung. Taiwan Environ Monit Assess 119:43–56

    Article  CAS  Google Scholar 

  • Hopke PK (2003) Recent developments in receptor modeling. J Chemometr 17:255–265

    Article  CAS  Google Scholar 

  • Hoque RR, Khillare P, Agarwal T, Shridhar V, Balachandran S (2008) Spatial and temporal variation of BTEX in the urban atmosphere of Delhi. India Sci Total Environ 392:30–40

    Article  CAS  Google Scholar 

  • Ilgen E, Levsen K, Angerer J, Schneider P, Heinrich J, Wichmann H-E (2001) Aromatic hydrocarbons in the atmospheric environment. Part III: personal monitoring. Atmos Environ 35:1265–1279

    Article  CAS  Google Scholar 

  • Iran SCo (2015) The estimated population of the Tehran city (http://www.amarorgir/Defaultaspx?tabid=2091)

  • Jia C, Batterman S, Godwin C (2008) VOCs in industrial, urban and suburban neighborhoods, Part 1: indoor and outdoor concentrations, variation, and risk drivers. Atmos Environ 42:2083–2100

    Article  CAS  Google Scholar 

  • Khoder MI (2007) Ambient levels of volatile organic compounds in the atmosphere of Greater Cairo. Atmos Environ 41:554–566

    Article  CAS  Google Scholar 

  • Kim H, Bernstein JA (2009) Air pollution and allergic disease. Curr Allergy Asthma Rep 9:128–133

    Article  CAS  Google Scholar 

  • Kumar P, Fennell P, Britter R (2008) Measurements of particles in the 5–1000 nm range close to road level in an urban street canyon. Sci Total Environ 390:437–447

    Article  CAS  Google Scholar 

  • Kumar P, Ketzel M, Vardoulakis S, Pirjola L, Britter R (2011) Dynamics and dispersion modelling of nanoparticles from road traffic in the urban atmospheric environment. Rev J Aerosol Sci 42:580–603. doi:10.1016/j.jaerosci.2011.06.001

    Article  CAS  Google Scholar 

  • Kumar P et al (2014) Ultrafine particles in cities. Environ Int 66:1–10

    Article  CAS  Google Scholar 

  • Kumar P, Pirjola L, Ketzel M, Harrison RM (2013) Nanoparticle emissions from 11 non-vehicle exhaust sources. Rev Atmos Environ 67:252–277

    Article  CAS  Google Scholar 

  • Larsen RK, Baker JE (2003) Source apportionment of polycyclic aromatic hydrocarbons in the urban atmosphere: a comparison of three methods. Environ Sci Technol 37:1873–1881

    Article  CAS  Google Scholar 

  • Lu J, Bzdusek PA, Christensen ER, Arora S (2005) Estimating sources of PAHs in sediments of the Sheboygan River, Wisconsin, by a chemical mass balance model. J Great Lakes Res 31:456–465

    Article  CAS  Google Scholar 

  • Mansha M, Saleemi AR, Naqvi JH (2011) Status and spatial visualization of toxic pollutants (BTEX) in urban atmosphere advances in chemical. Eng Sci 1:231

    CAS  Google Scholar 

  • Marć M, Namieśnik J, Zabiegała B (2014) BTEX concentration levels in urban air in the area of the Tri-City agglomeration (Gdansk, Gdynia, Sopot), Poland Air Quality. Atmos Health 7:489–504

    Article  Google Scholar 

  • Monod A, Sive BC, Avino P, Chen T, Blake DR, Rowland FS (2001) Monoaromatic compounds in ambient air of various cities: a focus on correlations between the xylenes and ethylbenzene. Atmos Environ 35:135–149

    Article  CAS  Google Scholar 

  • Mouzourides P, Kumar P, Neophytou MKA (2015) Assessment of long-term measurements of particulate matter and gaseous pollutants in South-East Mediterranean Atmos Environ 107:148-165 doi:http://dx.doi.org/10.1016/j.atmosenv.2015.02.031

  • Mukerjee S et al (2004) Field method comparison between passive air samplers and continuous monitors for VOCs and NO in El Paso, Texas. Air and Waste Manage 54:307–319

  • Muezzinoglu A, Odabasi M, Onat L (2001) Volatile organic compounds in the air of Izmir. Turkey Atmos Environ 35:753–760

    Article  CAS  Google Scholar 

  • Paatero P, Tapper U (1994) Positive matrix factorization: a non‐negative factor model with optimal utilization of error estimates of data values. Environmetrics 5:111–126

    Article  Google Scholar 

  • Park SS, Kim YJ, Kang CH (2002) Atmospheric polycyclic aromatic hydrocarbons in Seoul. Korea Atmos Environ 36:2917–2924

    Article  CAS  Google Scholar 

  • Possanzini M, Di Palo V, Gigliucci P, Scianò MCT, Cecinato A (2004) Determination of phase-distributed PAH in Rome ambient air by denuder/GC-MS method. Atmos Environ 38:1727–1734

    Article  CAS  Google Scholar 

  • Rad HD, Babaei AA, Goudarzi G, Angali KA, Ramezani Z, Mohammadi MM (2014) Levels and sources of BTEX in ambient air of Ahvaz metropolitan city air quality. Atmos Health 7:515–524

    Article  CAS  Google Scholar 

  • Samek L, Stegowski Z, Furman L, Fiedor J (2016) Chemical content and estimated sources of fine fraction of particulate matter collected in Krakow Air Quality, Atmosphere & Health:1-6

  • Sarkhosh M, Mahvi AH, Yunesian M, Nabizadeh R, Borji SH, Bajgirani AG (2013) Source apportionment of volatile organic compounds in Tehran. Iran Bull Environ Contam Toxicol 90:440–445

    Article  CAS  Google Scholar 

  • Shraim AM, Alenazi DA, Abdel-Salam A-SG, Kumar P (2016) Loading Rates of Dust and Metals in Residential Houses of Arid and Dry Climatic Regions Aerosol and Air Quality Research

    Google Scholar 

  • Wallace LA (2001) Human exposure to volatile organic pollutants: implications for indoor air studies. Ann Rev Energy Environ 26:269–301

    Article  Google Scholar 

  • Yang B et al (2013) Source apportionment of polycyclic aromatic hydrocarbons in soils of Huanghuai Plain, China: comparison of three receptor models. Sci Total Environ 443:31–39

    Article  CAS  Google Scholar 

  • Yuan B, Shao M, Lu S, Wang B (2010) Source profiles of volatile organic compounds associated with solvent use in Beijing. China Atmos Environ 44:1919–1926

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This research has been supported by the Tehran University of Medical Sciences, Institute for Environmental research, Center for Air Pollution Research (grant number 24577-46-03-92). The authors also would like to acknowledge and thank Loghman Barzegar and Arsalan Yousefzadeh at the Occupational Health School at Tehran University of Medical Science for their help in the synthetic dataset tests and the software development.

Author information

Authors and Affiliations

  1. Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran

    Mohammad Hadi Dehghani, Daryoush Sanaei, Ramin Nabizadeh & Shahrokh Nazmara

  2. Institute for Environmental Research, Center for Solid Waste Research, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran

    Mohammad Hadi Dehghani

  3. Center for Air Pollution Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran

    Daryoush Sanaei & Ramin Nabizadeh

  4. Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH, UK

    Prashant Kumar

  5. Environmental Flow (EnFlo) Research Centre, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH, UK

    Prashant Kumar

Authors
  1. Mohammad Hadi Dehghani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daryoush Sanaei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramin Nabizadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shahrokh Nazmara
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Prashant Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Mohammad Hadi Dehghani or Daryoush Sanaei.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dehghani, M.H., Sanaei, D., Nabizadeh, R. et al. Source apportionment of BTEX compounds in Tehran, Iran using UNMIX receptor model. Air Qual Atmos Health 10, 225–234 (2017). https://doi.org/10.1007/s11869-016-0425-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11869-016-0425-0

Keywords

Search

Navigation