Skip to main content

Advertisement

Log in

Influence of vehicular emissions on the levels of polycyclic aromatic hydrocarbons (PAHs) in urban and industrial areas of La Plata, Argentina

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Polycyclic aromatic hydrocarbons (PAHs) are considered potentially toxic, even carcinogenic, because of their affection to public health and the environment. It is necessary to know their ambient levels and the origin of these pollutants in order to mitigate them. A concerning scenario is the one in which commercial/administrative, industrial, and residential activities coexist. In this context, Gran La Plata (Argentina) presents such characteristics, in addition to the presence of one of the most important petrochemical complexes in the country and intense vehicular traffic. The source apportionment of PAH emission in the region, associated to 10-µm and 2.5-µm particulate matter fractions, was studied. First, different missing value imputation methods were evaluated for PAH databases. GSimp presented a better performance, with mean concentrations of ∑PAHs of 65.8 ± 40.2 ng m−3 in PM10 and 39.5 ± 18.0 ng m−3 in PM2.5. For both fractions, it was found that the highest contribution was associated with low molecular weight PAHs (3 rings), with higher concentrations of anthracene. Emission sources were identified by using principal component analysis (PCA) together with multiple linear regression (MLR) and diagnostic ratios of PAHs. The results showed that the main emission source is associated with vehicular traffic in both fractions. Classification by discriminant analysis showed that emissions can be identified by region and that fluoranthene, benzo(a)anthracene, and anthracene in PM10 and anthracene and phenanthrene in PM2.5 are a characteristic of emissions from the petrochemical complex.

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

Access this article

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
Fig. 6
Fig. 7

Similar content being viewed by others

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Not applicable.

References

  • Abbasi, S., & Keshavarzi, B. (2019). Source identification of total petroleum hydrocarbons and polycyclic aromatic hydrocarbons in PM10 and street dust of a hot spot for petrochemical production: Asaluyeh County, Iran. Sustainable Cities and Society, 45, 214–230.

  • Behrentz Valencia, E., Sánchez Morcote, N., & Rivera Contreras, A. J. (2009). Parte 1: Caracterización de Material Particulado y Modelos Receptores. Elementos técnicos del Plan decenal de descontaminación de Bogotá.

  • Belis, C. A., Larsen, B. R., Amato, F., El Haddad, I., Favez, O., Harrison, R. M., ... & Viana, M. (2014). European guide on air pollution source apportionment with receptor models. JRC reference reports EUR26080 EN.

  • Bolks, A., DeWire, A., & Harcum, J. B. (2014). Baseline assessment of left-censored environmental data using R. Tech Notes, 10, 28.

    Google Scholar 

  • Buzcu, B., & Fraser, M. P. (2006). Source identification and apportionment of volatile organic compounds in Houston, TX. Atmospheric Environment, 40(13), 2385–2400.

  • Carreras, H. A., Calderón-Segura, M. E., Gómez-Arroyo, S., Murillo-Tovar, M. A., & Amador-Muñoz, O. (2013). Composition and mutagenicity of PAHs associated with urban airborne particles in Córdoba, Argentina. Environmental Pollution, 178, 403–410.

    Article  CAS  Google Scholar 

  • Chen, S. C., & Liao, C. M. (2006). Health risk assessment on human exposed to environmental polycyclic aromatic hydrocarbons pollution sources. Science of the Total Environment, 366(1), 112–123.

    Article  CAS  Google Scholar 

  • Cheruiyot, N. K., Lee, W. J., Mwangi, J. K., Wang, L. C., Lin, N. H., Lin, Y. C., & Chang-Chien, G. P. (2015). An overview: Polycyclic aromatic hydrocarbon emissions from the stationary and mobile sources and in the ambient air. Aerosol and Air Quality Research, 15(7), 2730–2762.

    Article  CAS  Google Scholar 

  • Colman Lerner, J. E. (2013). Contaminación ambiental: análisis y mitigación/remoción de material particulado (MP) y compuestos orgánicos volátiles (COVs) y semivolátiles (COSVs) (Doctoral dissertation, Universidad Nacional de La Plata).

  • Comero, S., Capitani, L., & Gawlik, B. M. (2009). Positive matrix factorisation (PMF)–An introduction to the chemometric evaluation of environmental monitoring data using PMF (p. 59). Office for Official Publications of the European Communities.

    Google Scholar 

  • de Paula, P. H. M., Mateus, V. L., Araripe, D. R., Duyck, C. B., & Saint’Pierre, T. D., & Gioda, A. (2015). Biomonitoring of metals for air pollution assessment using a hemiepiphyte herb (Struthanthus flexicaulis). Chemosphere, 138, 429–437.

    Article  Google Scholar 

  • Dotse, S. Q., Asane, J. K., & Ofosu, F. G. (2012). Particulate matter and black carbon concentration levels in Ashaiman, a semi-urban area of Ghana, 2008. Regression and Multilevel/Hierarchical Models, 389–390.

  • Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.

  • Geng, F., Cai, C., Tie, X., Yu, Q., An, J., Peng, L., & Xu, J. (2009). Analysis of VOC emissions using PCA/APCS receptor model at city of Shanghai, China. Journal of Atmospheric Chemistry, 62(3), 229–247.

  • Giuliani, D., Colman Lerner, J. E., & Porta, A. (2021). Human health risk associated to particulate matter and polycyclic aromatic hydrocarbon levels and their relation with preponderant sources in Gran La Plata, Argentina. Environmental Science and Pollution Research, 1–16.

  • Gogou, A., Stratigakis, N., Kanakidou, M., & Stephanou, E. G. (1996). Organic aerosols in Eastern Mediterranean: Components source reconciliation by using molecular markers and atmospheric back trajectories. Organic Geochemistry, 25(1–2), 79–96.

    Article  CAS  Google Scholar 

  • Gutiérrez, M. D. L. A., Palmieri, M. A., Giuliani, D. S., Colman Lerner, J. E., Maglione, G., Andrinolo, D., & Tasat, D. R. (2020). Monitoring human genotoxicity risk associated to urban and industrial Buenos Aires air pollution exposure. Environmental Science and Pollution Research, 1–12.

  • Hayakawa, K. (2018). Chemistry of polycyclic aromatic hydrocarbons (PAHs), nitropolycyclic aromatic hydrocarbons (NPAHs) and other oxidative derivatives of PAHs. In Polycyclic aromatic hydrocarbons (pp. 3–10). Springer, Singapore.

  • Helsel, D. R. (2012). Statistics for censored environmental data using Minitab and R. John Wiley & Sons.

    Google Scholar 

  • Hopke, P. K. (1985). Receptor modeling in environmental chemistry. John Wiley & Sons.

    Google Scholar 

  • Hopke, P. K. (2016). Review of receptor modeling methods for source apportionment. Journal of the Air & Waste Management Association, 66(3), 237–259.

    Article  Google Scholar 

  • Hui, L., Liu, X., Tan, Q., Feng, M., An, J., Qu, Y., & Jiang, M. (2018). Characteristics, source apportionment and contribution of VOCs to ozone formation in Wuhan, Central China. Atmospheric Environment, 192, 55–71.

    Article  CAS  Google Scholar 

  • International Agency for Research on Cancer (IARC). (2016). Outdoor air pollution, Vol. 109. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans. Lyon: IARC.

  • Jia, C., & Fu, X. (2020). Characterizing community exposure to atmospheric polycyclic aromatic hydrocarbons (PAHs) in the Memphis Tri-State Area.

  • Kaiser, H. F. (1958). The varimax criterion for analytic rotation in factor analysis. Psychometrika, 23(3), 187–200.

    Article  Google Scholar 

  • Karavalakis, G., Poulopoulos, S., & Zervas, E. (2012). Impact of diesel fuels on the emissions of non-regulated pollutants. Fuel, 102, 85–91.

    Article  CAS  Google Scholar 

  • Katsoyiannis, A., Sweetman, A. J., & Jones, K. C. (2011). PAH molecular diagnostic ratios applied to atmospheric sources: A critical evaluation using two decades of source inventory and air concentration data from the UK. Environmental Science & Technology, 45(20), 8897–8906.

    Article  CAS  Google Scholar 

  • Kavouras, I. G., Koutrakis, P., Tsapakis, M., Lagoudaki, E., Stephanou, E. G., Von Baer, D., & Oyola, P. (2001). Source apportionment of urban particulate aliphatic and polynuclear aromatic hydrocarbons (PAHs) using multivariate methods. Environmental Science & Technology, 35(11), 2288–2294.

    Article  CAS  Google Scholar 

  • Lammel, G. (2015). Polycyclic aromatic compounds in the atmosphere–A review identifying research needs. Polycyclic Aromatic Compounds, 35(2–4), 316–329.

    Article  CAS  Google Scholar 

  • Lan, S. H., Lan, H. X., Yang, D., & Wu, X. W. (2014). Study of nitro-polycyclic aromatic hydrocarbons in particulate matter in Dongguan. Environmental Science and Pollution Research, 21(12), 7390–7399.

    Article  CAS  Google Scholar 

  • Lanzaco, B. L., López, M. L., Olcese, L. E., & Toselli, B. M. (2019). Elemental composition of PM0.25 collected in an urban site of Argentina: A first case study. Spectrochimica Acta Part B: Atomic Spectroscopy, 161, 105712.

  • Li, J., Zhang, G., Li, X. D., Qi, S. H., Liu, G. Q., & Peng, X. Z. (2006). Source seasonality of polycyclic aromatic hydrocarbons (PAHs) in a subtropical city, Guangzhou, South China. Science of the Total Environment, 355(1–3), 145–155.

    Article  CAS  Google Scholar 

  • Li, W., Peng, Y., Shi, J., Qiu, W., Wang, J., & Bai, Z. (2011). Particulate polycyclic aromatic hydrocarbons in the urban northeast region of China: Profiles, distributions and sources. Atmospheric Environment, 45(40), 7664–7671.

    Article  CAS  Google Scholar 

  • Little, R. J., & Rubin, D. B. (2019). Statistical analysis with missing data (Vol. 793). John Wiley & Sons.

  • Liu, W., Xu, Y., Zhao, Y., Liu, Q., Yu, S., Liu, Y., & Liu, W. (2019). Occurrence, source, and risk assessment of atmospheric parent polycyclic aromatic hydrocarbons in the coastal cities of the Bohai and Yellow Seas. China. Environmental Pollution, 254, 113046.

    Article  CAS  Google Scholar 

  • Liu, H., Li, B., Qi, H., Ma, L., Xu, J., Wang, M., & Tian, C. (2021). Source apportionment and toxic potency of polycyclic aromatic hydrocarbons (PAHs) in the air of Harbin, a cold city in Northern China. Atmosphere, 12(3), 297.

    Article  CAS  Google Scholar 

  • López-Noreña, A. I., Berná, L., Tames, M. F., Millán, E. N., Puliafito, S. E., & Fernandez, R. P. (2021). Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem. Atmospheric Environment, 118839.

  • Manoli, E., Kouras, A., Karagkiozidou, O., Argyropoulos, G., Voutsa, D., & Samara, C. (2016). Polycyclic aromatic hydrocarbons (PAHs) at traffic and urban background sites of northern Greece: Source apportionment of ambient PAH levels and PAH-induced lung cancer risk. Environmental Science and Pollution Research, 23(4), 3556–3568.

    Article  CAS  Google Scholar 

  • Mellado, D., Gutierrez, M. A., Lerner, J. E. C., Demetrio, P. M., Porta, A. A., Jacovkis, P. M., & Sanchez, E. Y. (2020). Location of areas of emission of pollutants when poor urban air quality is detected. International Journal of Environment and Health, 10(2), 93–106.

    Article  Google Scholar 

  • Meyers, L. S., Gamst, G., & Guarino, A. J. (2016). Applied multivariate research: Design and interpretation. Sage Publications.

  • Nagato, E. G. (2018). PAHs and NPAHs in airborne particulate matter: Initial formation and atmospheric transformations. In Polycyclic aromatic hydrocarbons (pp. 11–25). Springer, Singapore.

  • Nagendra, S. S., Schlink, U., Müller, A., & Khare, M. (2020). Urban air quality monitoring, modelling and human exposure assessment. Springer Singapore Pte. Limited.

  • Norris, G. A., Duvall, R., Brown, S. G., & Bai, S. (2014). Positive matrix factorization (PMF) 5.0 fundamentals and user guide prepared for the US Environmental Protection Agency. USEPA, Office Res Dev, Washington, DC.

  • Orazi, M. M., Arias, A. H., Oliva, A. L., Ronda, A. C., & Marcovecchio, J. E. (2020). Characterization of atmospheric and soil polycyclic aromatic hydrocarbons and evaluation of air-soil relationship in the southwest of Buenos Aires province (Argentina). Chemosphere, 240, 124847.

    Article  CAS  Google Scholar 

  • Puliafito, S. E., Bolaño-Ortiz, T. R., Peña, L. L. B., & Pascual-Flores, R. M. (2020). Dataset supporting the estimation and analysis of high spatial resolution inventories of atmospheric emissions from several sectors in Argentina. Data in brief, 29.

  • Quiterio, S. L., Arbilla, G., Bauerfeldt, G. F., & Moreira, J. C. (2006). Polycyclic aromatic hydrocarbons and their molecular diagnostic ratios in airborne particles (PM10) collected in Rio de Janeiro, Brazil. Water, Air, and Soil Pollution, 179(1), 79–92.

    Google Scholar 

  • Rashid, M., Yunus, S., Mat, R., Baharun, S., & Lestari, P. (2014). PM10 black carbon and ionic species concentration of urban atmosphere in Makassar of South Sulawesi Province. Indonesia. Atmospheric Pollution Research, 5(4), 610–615.

    Article  Google Scholar 

  • Ravindra, K., Sokhi, R., & Van Grieken, R. (2008). Atmospheric polycyclic aromatic hydrocarbons: Source attribution, emission factors and regulation. Atmospheric Environment, 42(13), 2895–2921.

    Article  CAS  Google Scholar 

  • Red de Seguridad Alimentaria - Conicet (RSA). (2021). Polvo de Carbón en la región del Gran La Plata, Provincia de Buenos Aires. https://rsa.conicet.gov.ar/wp-content/uploads/2021/03/Informe-Polvo-de-carbon-en-la-region-del-Gran-La-Plata-RSAAC.pdf

  • R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/

  • Rovira, J., Nadal, M., Schuhmacher, M., & Domingo, J. L. (2021). Environmental impact and human health risks of air pollutants near a large chemical/petrochemical complex: Case study in Tarragona, Spain. Science of the Total Environment, 787, 147550.

  • Sienra, M. del R., Rosazza, N. G., & Préndez, M. (2005). Polycyclic aromatic hydrocarbons and their molecular diagnostic ratios in urban atmospheric respirable particulate matter. Atmospheric Research, 75(4), 267–281.

  • Simier, M., Thioulouse, J., & Olivier, J. M. (1998). ADE-4 software: A tool for multivariate analysis and graphical display. Oceanis, 24(4), 393–416.

    Google Scholar 

  • Singh, A., & Singh, A. K. (2013). ProUCL version 5.0. Technical guide-Statistical software for environmental applications for data sets with and without nondetect observations. EPA: Washington, WA, USA.

  • Song, Y., Shao, M., Liu, Y., Lu, S., Kuster, W., Goldan, P., & Xie, S. (2007). Source apportionment of ambient volatile organic compounds in Beijing. Environmental Science & Technology, 41(12), 4348–4353.

    Article  CAS  Google Scholar 

  • Thurston, G. D., & Spengler, J. D. (1985). A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston. Atmospheric Environment (1967), 19(1), 9–25.

  • Tobiszewski, M., & Namieśnik, J. (2012). PAH diagnostic ratios for the identification of pollution emission sources. Environmental Pollution, 162, 110–119.

    Article  CAS  Google Scholar 

  • Viana, M., Pandolfi, M., Minguillón, M. C., Querol, X., Alastuey, A., Monfort, E., & Celades, I. (2008). Inter-comparison of receptor models for PM source apportionment: Case study in an industrial area. Atmospheric Environment, 42(16), 3820–3832.

    Article  CAS  Google Scholar 

  • Wang, X., Zong, Z., Tian, C., Chen, Y., Luo, C., Tang, J., & Zhang, G. (2018). Assessing on toxic potency of PM 2.5-bound polycyclic aromatic hydrocarbons at a national atmospheric background site in North China. Science of the Total Environment, 612, 330–338.

    Article  CAS  Google Scholar 

  • Wei, R., Wang, J., Su, M., Jia, E., Chen, S., Chen, T., & Ni, Y. (2018a). Missing value imputation approach for mass spectrometry-based metabolomics data. Scientific Reports, 8(1), 1–10.

    Google Scholar 

  • Wei, R., Wang, J., Jia, E., Chen, T., Ni, Y., & Jia, W. (2018b). GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies. PLoS Computational Biology, 14(1), e1005973. https://doi.org/10.1371/journal.pcbi.1005973

    Article  CAS  Google Scholar 

  • World Health Organization (WHO). (2006). Air quality guidelines: Global update 2005: Particulate matter, ozone, nitrogen dioxide, and sulfur dioxide. World Health Organization.

  • Wu, D., Wang, Z., Chen, J., Kong, S., Fu, X., Deng, H., & Wu, G. (2014). Polycyclic aromatic hydrocarbons (PAHs) in atmospheric PM2.5 and PM10 at a coal-based industrial city: Implication for PAH control at industrial agglomeration regions. China. Atmospheric Research, 149, 217–229.

    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. Atmospheric Environment, 44(15), 1919–1926.

    Article  CAS  Google Scholar 

  • Yunker, M. B., Macdonald, R. W., Vingarzan, R., Mitchell, R. H., Goyette, D., & Sylvestre, S. (2002). PAHs in the Fraser River basin: A critical appraisal of PAH ratios as indicators of PAH source and composition. Organic Geochemistry, 33(4), 489–515.

    Article  CAS  Google Scholar 

  • Zhao, B., Zhang, S., Zhou, Y., He, D., Li, Y., Ren, M., & Fang, J. (2015). Characterization and quantification of PAH atmospheric pollution from a large petrochemical complex in Guangzhou: GC–MS/MS analysis. Microchemical Journal, 119, 140–144.

    Article  CAS  Google Scholar 

  • Zhao, T., Yang, L., Huang, Q., Zhang, Y., Bie, S., Li, J., ... & Wang, W. (2020). PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) and their derivatives (nitrated-PAHs and oxygenated-PAHs) in a road tunnel located in Qingdao, China: Characteristics, sources and emission factors. Science of the Total Environment, 720, 137521.

Download references

Acknowledgements

The authors would like to thank the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), the Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CIC PBA), and Universidad Nacional de La Plata (UNLP) for their support to the present study.

Funding

This research is supported by the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), the Ministerio de Ciencia, Tecnología e Innovación (MINCyT), the Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CIC PBA), and the Universidad Nacional de La Plata (UNLP).

Author information

Authors and Affiliations

Authors

Contributions

D. Mellado, D. Giuliani, P.M. Demetrio, E.Y. Sanchez, A. Porta, and J.E. Colman Lerner were major contributors in writing the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Daniela Giuliani.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

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.

Rights and permissions

Springer Nature or its licensor 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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mellado, D., Giuliani, D., Demetrio, P.M. et al. Influence of vehicular emissions on the levels of polycyclic aromatic hydrocarbons (PAHs) in urban and industrial areas of La Plata, Argentina. Environ Monit Assess 194, 822 (2022). https://doi.org/10.1007/s10661-022-10496-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-022-10496-9

Keywords

Navigation