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Characterizing urban pollution variability in Central Poland using radon-222

Treść / Zawartość
Identyfikatory
Warianty tytułu
Konferencja
III International Conference „Radon in the Environment” (3 ; 27-31 May 2019 ; Krakow, Poland)
Języki publikacji
EN
Abstrakty
EN
Four years of observations of radon, meteorology and atmospheric pollution was used to demonstrate the efficacy of combined diurnal and synoptic timescale radon-based stability classification schemes in relating atmospheric mixing state to urban air quality in Zgierz, Central Poland. Nocturnal radon measurements were used to identify and remove periods of non-stationary synoptic behaviour (13–18% of each season) and classify the remaining data into five mixing states, including persistent temperature inversion (PTI) conditions, and non-PTI conditions with nocturnal conditions ranging from well mixed to stable. Mixing state classifications were performed completely independently of site meteorological measurements. World Health Organization guideline values for daily PM2.5/PM10 were exceeded only under strong PTI conditions (3–15% of non-summer months) or often under non-PTI stable nocturnal conditions (14–20% of all months), when minimum nocturnal mean wind speeds were also recorded. In non-summer months, diurnal amplitudes of NO (CO) increased by the factors of 2–12 (3–7) from well-mixed nocturnal conditions to PTI conditions, with peak concentrations occurring in the morning/evening commuting periods. Analysis of observations within radon-derived atmospheric mixing ‘class types’ was carried out to substantially clarify relationships between meteorological and air quality parameters (e.g. wind speed vs. PM2.5 concentration, and atmospheric mixing depth vs. PM10 concentration).
Słowa kluczowe
Czasopismo
Rocznik
Strony
59--65
Opis fizyczny
Bibliogr. 19 poz., rys.
Twórcy
  • Environmental Research, ANSTO Locked Bag 2001, Kirrawee DC, NSW 2232, Australia
  • Faculty of Geographical Sciences Department of Meteorology and Climatology University of Lodz Narutowicza 88 St., 90-139 Łódź, Poland
Bibliografia
  • 1. Apte, J. S., Brauer, M., Cohen, A. J., Ezzati, M., & Pope III, C. A. (2018). Ambient PM2.5 reduces global and regional life expectancy. Environ. Sci. Technol. Lett., 5(9), 546–551.
  • 2. Lelieveld, J., Klingmuller, K., Pozzer, A., Pöschl, U., Fnais, M., Daiber, A., & Münzel, T. (2019). Cardiovascular disease burden from ambient air pollution in Europe reassessed using novel hazard ratio functions. Eur. Heart J., 40(20), 1590–1596. https://doi.org/10.1093/eurheartj/ehz135.
  • 3. Ayers, G. P., Bigg, E. K., Turvey, D. E., & Manton, M. J. (1982). Urban influence on condensation nuclei over a continent. Atmos. Environ., 16, 951–954.
  • 4. Chambers, S. D., Guérette, E. -A., Monk, K., Griffiths, A. D., Zhang, Y., Duc, H., Cope, M., Emmerson, K. M., Chang, L. T., Silver, J. D., Utembe, S., Crawford, J., Williams, A. G., & Keywood, M. (2019a). Skilltesting chemical transport models across contrasting atmospheric mixing states using Radon-222. Atmosphere, 10(1), 25. https://doi.org/10.3390/atmos10010025.
  • 5. Chambers, S. D., Podstawczyńska, A., Pawlak, W., Fortuniak, K., Wiliams, A. G., & Griffiths, A. D.(2019b). Characterising the state of the urban surface layer using radon-222. J. Geophys. Res. Atmos., 124(2), 770–788.
  • 6. Chambers, S. D., Williams, A. G., Crawford, J., & Griffi ths, A. D. (2015). On the use of radon for quantifying the effects of atmospheric stability on urban emissions. Atmos. Chem. Phys., 15, 1175–1190.
  • 7. Kikaj, D., Vaupotič, J., & Chambers, S. D. (2019a). Identifying “persistent temperature inversion” events in a sub-Alpine Basin using Radon-222. Atmos. Meas. Tech., 12, 4455–4477. https://doi.org/10.5194/amt12-4455-2019.
  • 8. Kikaj, D., Chambers, S. D., & Vaupotič, J. (2019b). Radon-based atmospheric stability classifycation in contrasting sub-Alpine and sub-Mediterranean environments. J. Environ. Radioact., 203, 125–134. DOI: 10.1016/j.jenvrad.2019.03.010.
  • 9. Moses, H., Stehney, A. F., & Lucas, H. J. (1960). The effect of meteorological variables upon the vertical and temporal distributions of atmospheric radon. J. Geophys. Res., 65, 1223–1238.
  • 10. Perrino, C., Pietrodangelo, A., & Febo, A. (2001). An atmospheric stability index based on radon progeny measurements for the evaluation of primary urban pollution. Atmos. Environ., 35, 5235–5244.
  • 11. Williams, A. G., Chambers, S. D., & Griffi ths, A. D. (2013). Bulk mixing and decoupling of the nocturnal stable boundary layer characterized using a ubiquitous natural tracer. Bound. Layer Meteorol., 20(149), 381–402.
  • 12. Williams, A. G., Chambers, S. D., Conen, F., Reimann, S., Hill, M., Griffi ths, A. D., & Crawford, J. (2016). Radon as a tracer of atmospheric influences on traffic-related air pollution in a small inland city. Tellus B, 68, 30967. http://dx.doi.org/10.3402/tellusb.v68.30967.
  • 13. Podstawczyńska, A., & Chambers, S. D. (2019). Improved method for characterising temporal variability in urban air quality Part I: Traffic emissions in Central Poland. Atmos. Environ., 219, 117038. https://doi.org/10.1016/j.atmosenv.2019.117038.
  • 14. Chambers, S. D., & Podstawczyńska, A. (2019). Improved method for characterising temporal variability in urban air quality Part II: particulate matter and precursors in central Poland. Atmos. Environ., 219, 117040. https://doi.org/10.1016/j.atmosenv.2019.117040.
  • 15. Grossi, C., Arnold, D., Adame, A. J., Lopez-Colo, L., Bolivar, J. P., de la Morena, B. A., & Vargas, A. (2012). Atmospheric 222Rn concentration and source term at El Arenosillo 100m meteorological tower in southwest, Spain. Radiat. Meas., 47, 149–162.
  • 16. Schmithüsen, D., Chambers, S. D., Fischer, B., Gilge, S., Hatakka, J., Kazan, V., Neubert, R., Paatero, J.,Ramonet, M., Schlosser, C., Schmid, S., Vermeulen, A., & Levinet, I. (2017). A European wide 222Radon and 222Radon progeny comparison study. Atmos. Meas. Tech., 10, 1299–1312.
  • 17. Williams, A. G., & Chambers, S. D. (2016). A history of radon measurements at Cape Grim. In N. Derek, P. B. Krummel & S. J. Cleland (Eds.), Baseline Atmospheric Program (Australia) History and Recollections (40th Anniversary Special ed.) (pp. 131–146).Australia: Burreau of Metrology/CSIRO Oceans and Atmosphere.
  • 18. Jędruszkiewicz, J., Czernecki, B., & Marosz, M.(2017). The variability of PM10 and PM2.5 concentrations in selected Polish agglomerations: the role of meteorological conditions, 2006–2016. Int. J. Environ. Health, 27, 441–462.
  • 19. Draxler, R. R., & Rolph, G. D. (2003). Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Retrieved July 31, 2019, from http://www.arl.noaa.gov/ready/hysplit4.html.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fca5e82e-2ca8-4d9c-a8dd-cd9d3391d69d
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