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Assessment of ozone concentration data from the northern Zagreb area, Croatia, for the period from 2003 to 2016.

Brunislav MatasovićGordana PehnecIvan BešlićSilvije DavilaDinko Babić
Published in: Environmental science and pollution research international (2021)
A measurement station located in an urban area on the southern slope of the Medvednica Mountain (120 m a.s.l.), close to the Croatian capital Zagreb, provided data for an analysis of the photosmog in the city of Zagreb. Data for the period 2003-2016 obtained from this station and analysed in this work can also be compared with the nearby Puntijarka station (980 m a.s.l.) for which a similar analysis has already been carried out. In Puntijarka station analysis, it has been shown that there is most probably no significant change in ozone concentrations during the observed period. In this study the mean value of the annual ozone volume fractions showed a linear trend of 0.23 ppb yr-1, a growth that is in the worst case scenario among the lowest global prediction, while the seasonal (April-to-September) mean values had a trend of 0.32 ppb yr-1, which is a certain clearly observable growth. The 95-percentile values had trends of 0.009 ppb yr-1 (annual data) and -0.072 ppb yr-1 (seasonal data), respectively. Both of these values show very small changes if any at all. By using FT analysis, with the calculation of uncertainties, we have observed three prominent cycles of 169 ± 4 h (weekly cycle), 24 ± 1 h and 12 ± 1 h (diurnal cycles). Uncertainties were low which strongly indicate that the cycles are present. However, since high concentrations of ozone were observed only sporadically, ozone pollution in the northern part of Zagreb is at the present rather low. A Fourier transformation was used to analyse the data for periodic behaviour, which revealed the existence of diurnal and weekly modulations. Nevertheless, constant monitoring is important and will continue in the future as part of continuous monitoring of the ozone levels in the area.
Keyphrases
  • electronic health record
  • particulate matter
  • big data
  • hydrogen peroxide
  • artificial intelligence
  • climate change
  • single cell
  • health risk assessment