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Air Quality, Atmosphere & Health

, Volume 12, Issue 7, pp 837–846 | Cite as

Passive sampling as a feasible tool for mapping and model evaluation of the spatial distribution of nitrogen oxides in the city of Curitiba, Brazil

  • Erika FelixEmail author
  • Lars Gidhagen
  • Marcelo F. Alonso
  • Everaldo P. Nahirny
  • Bruno L. Alves
  • David Segersson
  • Jorge H. Amorim
Article
  • 144 Downloads

Abstract

Nitrogen oxides (NOx) are important pollutants that affect air quality in urban areas and are associated with harmful effects in human health. These compounds are emitted by combustion process especially vehicles. The main aim of this paper is to assess the concentrations of NOx in the atmosphere of Curitiba by using Ogawa samplers and dispersion models. The determination of compounds in 11 places was performed by using a simple colorimetric reaction and spectrophotometry. A comparison between the Ogawa samplers and the reference chemiluminescence analyzer showed good agreement and repeatability of the method used. Two-week sampling campaigns were performed at 11 stations from July 29 to August 12, and from August 15 to 29, 2016. The results showed the highest concentrations in places with high traffic vehicular and at street level (121 μg m−3 for NOx, 47.9 μg m−3 for NO2, and 48 μg m−3 for NO) as compared to the roof level that can be attributed to the impact of local traffic passing the street canyon. The similarity of monitored and modeled NOx concentrations (17 out of 26 pointwise comparisons within ± 25%) gives confidence in the emission inventory and the model simulations, allowing a conclusion of the source contributions.

Keywords

Nitrogen oxides Atmosphere Passive sampler Spectrophotometry Modeling 

Notes

Acknowledgments

This study has been supported on the Swedish side by the Swedish Ministry of Environment and Energy, and on the Brazilian counterpart by the Federal University of Paraná, the Federal University of Technology of Paraná, the Federal University of Pelotas, and the Municipality of Curitiba. The authors thank the data provided by the Instituto Ambiental do Paraná (IAP), especially Dirlene Cavalcanti e Silva and João Carlos de Oliveira.

Compliance with ethical standards

Interest statement

The authors declare that there is no conflict of interest.

References

  1. AEA Energy & Environment (2008). Diffusion tubes for ambient NO2 monitoring: practical guidance. https://laqm.defra.gov.uk/documents/0802141004_NO2_WG_PracticalGuidance_Issue1a.pdf. Accessed April 2019
  2. Afif C, Dutot AL, Jambert C, Abboud M, Adjizian-Gérard J, Farah W, Perros PE, Rizk T (2009) Statistical approach for the characterization of NO2 concentrations in Beirut. Air Qual Atmos Health 2:57–67.  https://doi.org/10.1007/s11869-009-0034-2 CrossRefGoogle Scholar
  3. AIRVIRO. Air Quality Management. https://www.airviro.com/airviro/. Accessed April 2019
  4. Alonso MF, Longo K, Freitas S, Fonseca R, Marécal V, Pirre M, Klenner L (2010) An urban emissions inventory for South America and its application in numerical modeling of atmospheric chemical composition at local and regional scales. Atmos Environ 44:5072–5083.  https://doi.org/10.1016/j.atmosenv.2010.09.013 CrossRefGoogle Scholar
  5. Bahino J, Yoboué V, Galy-Lacaux C, Adon M, Akpo A, Keital S, Liousse C, Gardrat E, Chiron C, Ossohou M, Gnamien S, Djossou J (2018) A pilot study of gaseous pollutants’ measurement (NO2, SO2, NH3, HNO3 and O3) in Abidjan, Côte d’Ivoire: contribution to an overview of gaseous pollution in African cities. Atmos Chem Phys 18:5173–5198.  https://doi.org/10.5194/acp-18-5173-2018 CrossRefGoogle Scholar
  6. Baird C, Cann M (2012) Environmental chemistry, 5th edn. W. H. Freeman and Company, New YorkGoogle Scholar
  7. Bashtani J, Seddighi S, Bahrabadi-Jovein I (2018) Control of nitrogen oxide formation in power generation using modified reaction kinetics and mixing. Energy 145:567–581.  https://doi.org/10.1016/j.energy.2017.12.143 CrossRefGoogle Scholar
  8. Bush T, Smith S, Stevenson K, Moorcroft S (2001) Validation of nitrogen dioxide diffusion tube methodology in the UK. Atmos Environ 35:289–296CrossRefGoogle Scholar
  9. Caballero S, Esclapez R, Galindo N, Mantilla E, Crespo J (2012) Use of a passive sampling network for the determination of urban NO2 spatiotemporal variations. Atmos Environ 63:148–155.  https://doi.org/10.1016/j.atmosenv.2012.08.071 CrossRefGoogle Scholar
  10. Castelhano FJ, Roseghini WFF (2011) A utilização de policloreto de vinila (PVC) na construção de miniabrigos meteorológicos para aplicação em campo. Revista Brasileira de Climatologia 9:48–55CrossRefGoogle Scholar
  11. Danard M (1977) A simple model for mesoscale effects of topography on surface winds. Mon Weather Rev 105:572–581.  https://doi.org/10.1175/1520-0493(1977)105%3C0572:ASMFME%3E2.0.CO;2 CrossRefGoogle Scholar
  12. Dari-Salisburgo C, Di Carlo P, Giammaria F, Kajii Y, D’Altorio A (2009) Laser induced fluorescence instrument for NO2 measurements: observations at a Central Italy background site. Atmos Environ 43:970–977.  https://doi.org/10.1016/j.atmosenv.2008.10.037 CrossRefGoogle Scholar
  13. EEA (2016) EMEP/EEA air pollutant emission inventory guidebook 2016 – category code 1. A 3b Road transport, Update Dec. 2016. https://www.eea.europa.eu/publications/emep-eea-guidebook-2016/part-b-sectoral-guidance-chapters/1-energy/1-a-combustion/1-a-3-b-i/view, Last accessed: June 14, 2018
  14. Freitas SR, Longo KM, Alonso MF, Pirre M, Marecal V, Grell G, Stockler R, Mello RF, Sánchez Gácita M (2011) PREP-CHEM-SRC – 1.0: a preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models. Geosci Model Dev 4:419–433.  https://doi.org/10.5194/gmd-4-419-2011
  15. Freitas SR, Panetta J, Longo KM, Rodrigues LF, Moreira DS, Rosário NE, Silva Dias PL, Silva Dias MAF, Souza EP, Freitas ED, Longo M, Frassoni A, Fazenda AL, Santos e Silva CM, Pavani CAB, Eiras D, França DA, Massaru D, Silva FB, Santos FC, Pereira G, Camponogara G, Ferrada GA, Campos Velho HF, Menezes I, Freire JL, Alonso MF, Gácita MS, Zarzur M, Fonseca RM, Lima RS, Siqueira RA, Braz R, Tomita S, Oliveira V, Martins LD (2017) The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas. Geosci Model Dev 10:189–222.  https://doi.org/10.5194/gmd-10-189-2017 CrossRefGoogle Scholar
  16. Gaffin JM, Hauptman M, Petty CR, Sheehan WJ, Lai PS, Wolfson JM, Gold DR, Coull BA, Koutrakis P, Phipatanakul W (2018) Nitrogen dioxide exposure in school classrooms of inner-city children with asthma. J Allerg Clin Immunol 141:2249–2255.  https://doi.org/10.1016/j.jaci.2017.08.028 CrossRefGoogle Scholar
  17. Gidhagen L, Johansson H, Omstedt G (2009) SIMAIR – evaluation tool for meeting the EU directive on air pollution limits. Atmos Environ 43:1029–1036.  https://doi.org/10.1016/j.atmosenv.2008.01.056 CrossRefGoogle Scholar
  18. Glarborg P, Miller JA, Ruscic B, Klippenstein SJ (2018) Modeling nitrogen chemistry in combustion. Prog Energy Combust Sci 67:31–68.  https://doi.org/10.1016/j.pecs.2018.01.002 CrossRefGoogle Scholar
  19. Guenther AB, Jiang X, Heald CL, Sakulyanontvittaya T, Duhl T, Emmons LK, Wang X (2012) The model of emissions of gases and aerosols from nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions. Geosci Model Dev 5(6):1471–1492.  https://doi.org/10.5194/gmd-5-1471-2012 CrossRefGoogle Scholar
  20. Hagenbjörk A, Malmqvist E, Mattisson K, Sommar NJ, Modig L (2017) The spatial variation of O3, NO, NO2 and NOx and the relation between them in two Swedish cities. Environ Monit Assess 189:161.  https://doi.org/10.1007/s10661-017-5872-z CrossRefGoogle Scholar
  21. Hagenbjörk-Gustafsson A, Tornevi A, Forsberga B, Eriksson K (2010) Field validation of the Ogawa diffusive sampler for NO2 and NOx in a cold climate. J Environ Monit 12:1315–1324.  https://doi.org/10.1039/b924615k CrossRefGoogle Scholar
  22. Heal MR, O’Donoghue MA, Cape JN (1999) Overestimation of urban nitrogen dioxide by passive diffusion tubes: a comparative exposure and model study. Atmos Environ 33:513–524CrossRefGoogle Scholar
  23. Ho Yu C, Morandi MT, Weisel CP (2008) Passive dosimeters for nitrogen dioxide in personal/indoor air sampling: a review. J Expo Sci Environ Epidemiol 18:441–451.  https://doi.org/10.1038/jes.2008.22 CrossRefGoogle Scholar
  24. Huang YK, Luvsan ME, Gombojav E, Ochir C, Bulgan J, Chan CC (2013) Land use patterns and SO2 and NO2 pollution in Ulaanbaatar, Mongolia. Environ Res 124:1–6.  https://doi.org/10.1016/j.envres.2013.02.006 CrossRefGoogle Scholar
  25. Huang Y, Shi W, Zhang C, Li L, Wen H (2016) Diazo-coupling spectrophotometric determination of nitrogen oxides in the air. Atmos Pollut Res 7:333–338.  https://doi.org/10.1016/j.apr.2015.10.011 CrossRefGoogle Scholar
  26. Huang Y, Shi W, Zhang C, Wen H (2017) Spectrophotometric determination of nitrogen oxides in the air with 2-N-ethyl-5-naphthol-7-sulfonic acid. J Appl Spectrosc 84:639–645.  https://doi.org/10.1007/s10812-017-0522-3 CrossRefGoogle Scholar
  27. INFRAS (2017) HBEFA version 3.3 – background documentation. Available 14th June 2018 at: http://www.hbefa.net/e/documents/HBEFA33_Documentation_20170425.pdf. Aceessed April 2019
  28. Instituto de Nacional de Pesquisas Espaciais (INPE). Centro de Previsão de Tempo e Estudos climáticos (CPTEC). http://meioambiente.cptec.inpe.br/index.php?lang=en. Accessed April 2019
  29. Jiménez AS, Heal MR, Beverland IJ (2011) Intercomparison study of NOx passive diffusion tubes with chemiluminescence analysers and evaluation of bias factors. Atmos Environ 45:3062–3068.  https://doi.org/10.1016/j.atmosenv.2011.03.011 CrossRefGoogle Scholar
  30. Kenkel JA, Sisk TD, Hultine KR, Sesnie SE, Bowker MA, Johnson NC (2016) Indicators of vehicular emission inputs into semi-arid roadside ecosystems. J Arid Environ 134:150–159.  https://doi.org/10.1016/j.jaridenv.2016.06.007 CrossRefGoogle Scholar
  31. Lanzafame R, Monforte P, Scandura PF (2016) Comparative analyses of urban air quality monitoring systems: passive sampling and continuous monitoring stations. Energy Procedia 101:321–328.  https://doi.org/10.1016/j.egypro.2016.11.041 CrossRefGoogle Scholar
  32. Liu F, Van der RJ, Eskes H, Ding J, Mijling B (2018) Evaluation of modeling NO2 concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China. Atmos Chem Phys 18:4171–4186.  https://doi.org/10.5194/acp-18-4171-2018 CrossRefGoogle Scholar
  33. Lodge JP Jr (1989) Methods of air sampling and analysis. Lewis, MichiganGoogle Scholar
  34. Longo KM, Freitas SR, Andreae MO, Setzer A, Prins E, Artaxo P (2010) The coupled aerosol and tracer transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) – part 2: model sensitivity to the biomass burning inventories. Atmos Chem Phys 10:5785–5795.  https://doi.org/10.5194/acp-10-5785-2010 CrossRefGoogle Scholar
  35. Lozano A, Usero J, Vanderlinden E, Raez J, Contreras J, Navarrete B, Bakouri HE (2010) Optimization of the design of air quality monitoring networks and its application to NO2 and O3 in Jaen, Spain. Microchem J 96:406–411.  https://doi.org/10.1016/j.microc.2010.07.002 CrossRefGoogle Scholar
  36. Masey N, Gillespie J, Heal MR, Hamilton S, Beverland IJ (2017) Influence of wind-speed on short-duration NO2 measurements using Palmes and Ogawa passive diffusion samplers. Atmos Environ 160:70–76.  https://doi.org/10.1016/j.atmosenv.2017.04.008 CrossRefGoogle Scholar
  37. Moreira DS, Freitas SR, Bonatti JP, Mercado LM, Rosário NME, Longo KM, Miller JB, Gloor M, Gatti LV (2013) Coupling between the JULES land-surface scheme and the CCATT-BRAMS atmospheric chemistry model (JULESCCATT-BRAMS1.0): applications to numerical weather forecasting and the CO2 budget in South America. Geosci Model Dev 6:1243–1259.  https://doi.org/10.5194/gmd-6-1243-2013 CrossRefGoogle Scholar
  38. Ng NL, Brown SS, Archibald AT, Atlas E, Cohen RC, Crowley JN, Day DA, Donahue NM, Fry JL, Fuchs H, Griffin RJ, Guzman MI, Herrmann H, Hodzic A, Iinuma Y, Jimenez JL, Kiendler-Scharr A, Lee BH, Luecken DJ, Mao J, McLaren R, Mutzel A, Osthoff HD, Ouyang B, Picquet-Varrault B, Platt U, Pye HOT, Rudich Y, Schwantes RH, Shiraiwa M, Stutz J, Thornton JA, Tilgner A, Williams BJ, Zaveri RA (2017) Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol. Atmos Chem Phys 17:2103–2162.  https://doi.org/10.5194/acp-17-2103-2017 CrossRefGoogle Scholar
  39. Omstedt G, Andersson S, Gidhagen L, Robertson L (2011) New model tools for meeting the targets of the EU Air Quality Directive: description, validation and evaluation of local air quality improvement due to reduction of studded tyre use on Swedish roads. Int J Environ Pollut 47:79–96.  https://doi.org/10.1504/IJEP.2011.047328 CrossRefGoogle Scholar
  40. Özel MZ, Ward MW, Hamilton JF, Lewis AC, Raventós-Duran T, Harrison RM (2009) Analysis of organic nitrogen compounds in urban aerosol samples using GCxGC-TOF/MS. Aerosol Sci Technol 44:109–116.  https://doi.org/10.1080/02786820903410105 CrossRefGoogle Scholar
  41. Richmond-Bryant J, Owen RC, Graham S, Snyder M, McDow S, Oakes M, Kimbrough S (2017) Estimation of on-road NO2 concentrations, NO2/NOX ratios, and related roadway gradients from near-road monitoring data. Air Qual Atmos Health 10:611–625.  https://doi.org/10.1007/s11869-016-0455-7 CrossRefGoogle Scholar
  42. Salem AA, Soliman AA, El-Haty IA (2009) Determination of nitrogen dioxide, sulfur dioxide, ozone, and ammonia in ambient air using the passive sampling method associated with ion chromatographic and potentiometric analyses. Air Qual Atmos Health 2:133–145.  https://doi.org/10.1007/s11869-009-0040-4 CrossRefGoogle Scholar
  43. Salmón P, Stroh E, Herrera-Dueñas A, von Post M, Isaksson C (2018) Oxidative stress in birds along a NOx and urbanisation gradient: an interspecific approach. Sci Total Environ 622-623:635–643.  https://doi.org/10.1016/j.scitotenv.2017.11.354 CrossRefGoogle Scholar
  44. Saltzman BE (1954) Colorimetric microdetermination of nitrogen dioxide in the atmosphere. Anal Chem 26:1949–1955CrossRefGoogle Scholar
  45. Sampling Protocol Using the Ogawa Sampler, version 6, http://www.ogawausa.com/protocols. Accessed April 2019
  46. Suzuki H, Miyao Y, Nakayama T, Pearce JK, Matsumi Y, Takahashi K, Kita K, Tonokura K (2011) Comparison of laser-induced fluorescence and chemiluminescence measurements of NO2 at an urban site. Atmos Environ 45:6233–6240.  https://doi.org/10.1016/j.atmosenv.2011.07.065 CrossRefGoogle Scholar
  47. Thunis P, Miranda A, Baldasano JM, Blond N, Douros J, Graff A, Janssen S, Uda-Rezler K, Karvosenoja N, Maffeis G, Martilli A, Rasoloharimahefa M, Real E, Viaene P, Volta M, White L (2016) Overview of current regional and local scale air quality modelling practices: assessment and planning tools in the EU. Environ Sci Pol 65:13–21.  https://doi.org/10.1016/j.envsci.2016.03.013 CrossRefGoogle Scholar
  48. Vardoulakis S, Lumbreras J, Solazzo E (2009) Comparative evaluation of nitrogen oxides and ozone passive diffusion tubes for exposure studies. Atmos Environ 43:2509–2517.  https://doi.org/10.1016/j.atmosenv.2009.02.048 CrossRefGoogle Scholar
  49. Veremchuk LV, Tsarouhas K, Vitkina TI, Mineeva EE, Gvozdenko TA, Antonyuk MV, Rakitskii VN, Sidletskaya KA, Tsatsakis AM, Golokhvast KS (2018) Impact evaluation of environmental factors on respiratory function of asthma patients living in urban territory. Environ Pollut 235:489–496.  https://doi.org/10.1016/j.envpol.2017.12.122 CrossRefGoogle Scholar
  50. Wang Y, Fan SH, Wang SL (2005) Chemiluminescence determination of nitrogen oxide in air with a sequential injection method. Anal Chim Acta 541:131–136.  https://doi.org/10.1016/j.aca.2004.11.072 CrossRefGoogle Scholar
  51. Wilhelm M, Qianc L, Ritz B (2009) Outdoor air pollution, family and neighborhood environment, and asthma in LA FANS children. Health Place 15:25–36.  https://doi.org/10.1016/j.healthplace.2008.02.002 CrossRefGoogle Scholar
  52. Xu W, Sun Y, Wang Q, Du W, Zhao J, Ge X, Han T, Zhang Y, Zhou W, Li J, Fu P, Wang Z, Worsnop DR (2017) Seasonal characterization of organic nitrogen in atmospheric aerosols using high resolution aerosol mass spectrometry in Beijing, China. Earth Space Chem 1:673–682.  https://doi.org/10.1021/acsearthspacechem.7b00106 CrossRefGoogle Scholar
  53. Yang BY, Qian Z, Howard SW, Vaughn MG, Fan SJ, Liu KK, Dong GH (2018) Global association between ambient air pollution and blood pressure: a systematic review and meta-analysis. Environ Pollut 235:576–588.  https://doi.org/10.1016/j.envpol.2018.01.001 CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Erika Felix
    • 1
    Email author
  • Lars Gidhagen
    • 2
  • Marcelo F. Alonso
    • 3
  • Everaldo P. Nahirny
    • 4
  • Bruno L. Alves
    • 1
  • David Segersson
    • 2
  • Jorge H. Amorim
    • 2
  1. 1.Department of Chemistry and BiologyFederal Technological University of Parana (UTFPR)CuritibaBrazil
  2. 2.Swedish Meteorological and Hydrological InstituteNorrköpingSweden
  3. 3.Federal University of PelotasPelotasBrazil
  4. 4.Department of ChemistryFederal University of Parana (UFPR), Centro PolitécnicoCuritibaBrazil

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