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Traffic-related particle emissions and exposure on an urban road

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Emisja cząstek ze źródeł komunikacyjnych w mieście
Języki publikacji
EN
Abstrakty
EN
Extensive aerosol particle concentrations are one of the factors contributing to poor air quality in cities. The aim of this study is to assess particle number and mass concentrations on a road in Lublin, Poland, in peak and off-peak traffic hours and its impact on the particle exposure for commuters and pedestrians. Mobile monitoring and fixed-site measurements on the sidewalk along the established 2.1 km long route were conducted with the use of Mobile Air Pollution Analytic Laboratory equipped, among other things, with instruments measuring the real-time number and mass concentrations of particles with size range from 10 nm to 32 μm. The highest average concentrations of ultrafine particle number PN0.1 (25.4 ±11×103 pt/cm3; mean ± standard deviation), total particle number PN (29.2 ±12×103 pt/cm3) as well as mass concentrations of PM2.5 (29.1 ±7.6 μg/m3) and PM10 (45.4 ±10.3 μg/m3) were obtained in peak traffic hours for the part of the route with the most intensive traffic. The average particle number concentrations for the entire route and the part of route with the most intensive traffic in peak times were found to be about 3 to 4 times higher than in off-peak times. The average particle mass concentrations were about twice as high. Furthermore, the average values of the examined particle number and mass concentrations were higher for the on-road measurements than for fixed-site measurements. Moreover, a greater percentage of ultrafine particles was observed during mobile monitoring than in the fixed-site measurement points. It was established that a greater number and mass of particles, irrespectively of their size range, is deposited in the respiratory tract of commuters and pedestrians in peak hours than in off-peak hours. In peak times the average particle doses received by commuters and pedestrians equaled 4.8 ±2.4×109 pt/h or 29.6 ±10.7 μg/h (PM10) and 4.2 ±2.3×109 pt/h or 29.6 ±8.6 μg/h (PM10), respectively. Additionally, in both peak and off-peak hours greater particle doses were determined in the considered part of the route with the most intensive traffic; however, in off-peak traffic times pedestrians are more exposed to traffic-related pollutants than commuters. Overall, the obtained results reflect the importance of traffic-related particle emission measurements for exposure evaluations and the need of taking the actions aimed at decreasing it.
PL
Celem pracy było określenie stężenia liczbowego i masowego cząstek na wybranych ulicach Lublina w godzinach szczytu oraz poza szczytem, a także ocena narażenia kierowców i pieszych na ich oddziaływanie. W ramach badań przeprowadzono zarówno pomiary mobilne, jak i stacjonarne w określonych punktach pomiarowych na trasie o długości 2,1 km. Mierzono w czasie rzeczywistym między innymi stężenia liczbowe i masowe cząstek o rozmiarach w zakresie od 10 nm do 32 μm. Najwyższe średnie koncentracje ultradrobnych cząstek PN0.1 (25,4 ±11×103 #/cm3) oraz koncentracje całkowitej liczby cząstek PN (29,2 ±12×103 #/cm3), a także stężenia masowe PM2.5 (29,1 ±7,6 μg/m3) oraz PM10 (45,4 ±10,3 μg/m3) rejestrowano w godzinach szczytu na wydzielonym odcinku trasy o największej intensywności ruchu. Średnie koncentracje cząstek mierzone w godzinach szczytu dla całej trasy oraz dla wydzielonego odcinka były, w zależności od wielkości cząstek, ok. 3-4 razy większe w porównaniu do wyników pomiarów dla godzin pozaszczytowych. Z kolei średnie stężenia masowe cząstek były około dwa razy większe. Ponadto, większe średnie stężenia liczbowe i masowe cząstek odnotowano dla pomiarów mobilnych niż dla stacjonarnych. Wyznaczone dawki dotyczące liczby i masy cząstek deponowanych w drogach oddechowych kierowców w godzinach szczytu wynosiły odpowiednio 4,8 ±2,4×109 #/h i 29,6 ±10,7 μg/h (PM10). Zarówno dla godzin szczytu, jak i poza szczytem, większe dawki deponowanych cząstek uzyskano dla wydzielonego odcinka trasy o największej intensywności ruchu. Podsumowując, otrzymane wyniki wskazują na istotność pomiarów cząstek emitowanych ze źródeł komunikacyjnych, szczególnie w kontekście narażenia uczestników ruchu drogowego na te cząstki.
Rocznik
Strony
83--93
Opis fizyczny
Bibliogr. 38 poz., tab., wykr.
Twórcy
autor
  • Lublin University of Technology, Poland
  • Lublin University of Technology, Poland
  • Lublin University of Technology, Poland
autor
  • Lublin University of Technology, Poland
Bibliografia
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  • 3. Caban, J., Drozdziel, P., Vrabel, J., Sarkan, B., Marczuk, A., Krzywonos, L. & Rybicka, I. (2016). The research on ageing of glycol-based brake fluids of vehicles in operation, Advances in Science and Technology, 10, 32, pp. 9–16.
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  • 5. Cheng, Y.H. (2008). Comparison of the TSI model 8520 and GRIMM series 1.108 portable aerosol instrument used to monitor particulate matter in an iron foundry, Journal of Occupational and Environmental Hygiene, 5, 3, pp. 157–168.
  • 6. Dons, E., Int Panis, L., Van Poppel, M., Theunis, J. & Wets, G. (2012). Personal exposure to Black Carbon in transport microenvironments, Atmospheric Environment, 55, pp. 392–398.
  • 7. Drozdziel, P., Rybicka, I., Madleňák, R., Andrusiuk, A. & Siłuch, D. (2017a). The engine set damage assessment in the public transport vehicles, Advances in Science and Technology, 11, 1, pp. 117–127.
  • 8. Drozdziel, P., Wińska, M., Madleňák, R. & Szumski, P. (2017b). Optimization of the Post Logistics Network and Location of the Local Distribution Center in Selected Area of the Lublin Province, Procedia Engineering, 192, pp. 130–135.
  • 9. EEA, European Environment Agency (2017). Air quality in Europe – 2017 report, (http://www.eea.europa.eu/publications/air-qualityin-europe-2017 (21.11.2017)).
  • 10. Fruin, S., Westerdahl, D., Sax, T., Sioutas, C. & Fine, P.M. (2008). Measurements and predictors of on-road ultrafine particle concentrations and associated pollutants in Los Angeles, Atmospheric Environment, 42, pp. 207–219.
  • 11. Goel, A. & Kumar, P. (2015). Characterisation of nanoparticle emissions and exposure at traffic intersections through fast-response mobile and sequential measurements, Atmospheric Environment, 107, pp. 374–390.
  • 12. Grynkiewicz-Bylina, B., Rakwic, B. & Pastuszka, J.S. (2005). Assessment of exposure to traffic-related aerosol and to particle-associated PAHs in Gliwice, Poland, Polish Journal of Environmental Studies, 14, 1, pp. 117–123.
  • 13. Holnicki, P., Kałuszko, A., Nahorski, Z., Stankiewicz, K. & Trapp, W. (2017). Air quality modeling for Warsaw agglomeration, Archives of Environmental Protection, 43, 1, pp. 48–64.
  • 14. Joodatnia, P., Kumar, P. & Robins, A. (2013). The behaviour of traffic produced nanoparticles in a car cabin and resulting exposure rates, Atmospheric Environment, 65, pp. 40–51.
  • 15. Karagulian, F., Belis, C.A., Dora, C.F., Prüss-Ustün, A.M., Bonjour, S., Adair-Rohani, H. & Amann, M. (2015). Contributions to cities’ ambient particulate matter (PM): A systematic review of local source contributions at global level, Atmospheric Environment, 120, pp. 475–483.
  • 16. Kaur, S., Nieuwenhuijsen, M. & Colvile, R. (2005). Personal exposure of street canyon intersection users to PM2.5, ultrafine particle counts and carbon monoxide in Central London, UK, Atmospheric Environment, 39, pp. 3629–3641.
  • 17. Klejnowski, K., Kozielska, B., Krasa, A. & Rogula-Kozłowska, W. (2010). Polycyclic aromatic hydrocarbons in PM1, PM2.5, PM10 and TSP in the Upper Silesian agglomeration, Poland, Archives of Environmental Protection, 36, 2, pp. 65–72.
  • 18. Knibbs, L.D., Cole-Hunter, T. & Morawska, L. (2011). A review of commuter exposure to ultrafine particles and its health effects, Atmospheric Environment, 45, pp. 2611–2622.
  • 19. Kozawa, K.H., Winer, A.M. & Fruin, S.A. (2012). Ultrafine particle size distributions near freeways: Effects of differing wind directions on exposure, Atmospheric Environment, 63, pp. 250–260.
  • 20. Kuhlbusch, T., John, A., Fissan, H., Schmidt, K.-G., Schmidt, F., Pfeffer, H.-U. & Gladtke, D. (1998). Diurnal variations of particle number concentrations – influencing factors and possible implications for climate and epidemiological studies, Journal of Aerosol Science, 29, pp. 213–214.
  • 21. Kumar, P. & Goel, A. (2016). Concentration dynamics of coarse and fi ne particulate matter at and around the signalised traffic intersections, Environmental Science: Processes & Impacts, 18, pp. 1220–1235.
  • 22. Kumar, P., Morawska, L., Birmili, W., Paasonen, P., Hu, M., Kulmala, M., Harrison, R.M., Norford, L. & Britter, R. (2014). Ultrafine particles in cities, Environment International, 66, pp. 1–10.
  • 23. Olszowski, T. & Bożym, M. (2014). Pilot study on using an alternative method of estimating emission of heavy metals from wood combustion, Atmospheric Environment, 94, pp. 22–27.
  • 24. Oleniacz, R., Bogacki, M., Szulecka, A., Rzeszutek, M. & Mazur, M. (2016). Assessing the impact of wind speed and mixing-layer height on air quality in Krakow (Poland) in the years 2014–2015, Journal of Civil Engineering, Environment and Architecture, 63, pp. 315–342.
  • 25. Polednik, B. (2013a). Particulate matter and student exposure in school classrooms in Lublin, Poland, Environmental Research, 120, pp. 134–139.
  • 26. Polednik, B. (2013b). Particle exposure in a baroque church during sunday masses, Environmental Research, 126, pp. 215–220.
  • 27. Rogula-Kozłowska, W., Pastuszka, J.S. & Talik, E. (2008). Influence of vehicular traffic on concentration and particle surface composition of PM10 and PM2.5 in Zabrze, Poland, Polish Journal of Environmental Studies, 17, 4, pp. 539–548.
  • 28. Sabaliauskas, K., Jeong, C.-H., Yao, X., Jun, Y.-S., Jadidian, P. & Evans, G.J. (2012). Five-year roadside measurements of ultrafine particles in a major Canadian city, Atmospheric Environment, 49, pp. 245–256.
  • 29. Sartini, C., Zauli Sajani, S., Ricciardelli, I., Delgado-Saborit, J.M., Scotto, F., Trentini, A., Ferrari, S. & Poluzzi, V. (2013). Ultrafine particle concentrations in the surroundings of an urban area: comparing downwind to upwind conditions using Generalized Additive Models (GAMs), Environmental Science: Processes & Impacts, 11, pp. 2087–2095.
  • 30. Szczygłowski, P. & Mazur, M. (2008). Application of BOOT statistical package in calculating pollutant spreading in air, Environment Protection Engineering, 34, 4, pp. 151–156.
  • 31. Skubacz, K. (2009). Measurements of aerosol size distribution in urban areas of Upper Silesia, Archives of Environmental Protection, 35, 4, pp. 23–34.
  • 32. Sturm, R. (2016). Local lung deposition of ultrafine particles in healthy adults: experimental results and theoretical predictions, Annals of Translational Medicine, 4, 21, pp. 420.
  • 33. TomTom, TomTom Traffic Index (2017). (http://www.tomtom.com/trafficindex (25.07.2017)).
  • 34. WIOP, Wojewódzki Inspektorat Ochrony Powietrza w Lublinie (2017). Air Quality Monitoring System, (http://envir.wios.lublin.pl (08.08.2017)). (in Polish)
  • 35. WIOŚ, Wojewódzki Inspektorat Ochrony Środowiska w Lublinie (2016), Lublin Voivodeship Environment analysis report in years 2013–2015, (http://envir.wios.lublin.pl (08.08.2017)). (in Polish)
  • 36. Wróbel, A., Rokita, E. & Maenhaut, W. (2000). Transport of traffic-related aerosols in urban areas, Science of The Total Environment, 257, 2–3, pp. 199–211.
  • 37. 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, Journal of Environmental Science and Health, 26, pp. 339–362.
  • 38. Zhao, H., Che, H., Ma, Y., Wang, Y., Yang, H., Liu, Y., Wang, Y., Wang, H. & Zhang, X. (2017). The Relationship of PM Variation with Visibility and Mixing-Layer Height under Hazy/Foggy Conditions in the Multi-Cities of Northeast China, International Journal of Environmental Research and Public Health, 14, 5, 471.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-695234a6-101d-4090-88af-1868b67384e8
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