EGU24-10961, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-10961
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Analysis of tropospheric ozone predictors and their relationship with the occurrence of fires in mainland Portugal

Catarina Alonso1,2, João A. Santos2, and Célia Gouveia1,3
Catarina Alonso et al.
  • 1Instituto Português do Mar e da Atmosfera (IPMA), 1749-077 Lisboa, Portugal (catarina.alonso@ipma.pt)
  • 2Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB)—Department of Physics, Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
  • 3Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal

The World Health Organization (WHO) estimates that air pollution is responsible for more than seven million premature deaths every year around the world. Above background concentrations, tropospheric ozone (O3) exerts negative effects on human health and vegetation. High ozone production occurs in conditions of strong sunlight and high temperature, as the acceleration of ozone formation is associated with high temperatures and photolysis. Therefore, it is a secondary pollutant that results from the reaction between nitrogen oxides (NOx) and volatile organic compounds (VOCs) released into the atmosphere from natural or anthropogenic activities. The combination of sunlight with non-methane hydrocarbons (NMHCs) and NOx (NO + NO2) from biomass burning can also contribute to an increase in tropospheric ozoneconcentration values. The main objective of this research is to study the tropospheric ozoneconcentration through the analysis of some precursors, between 2004 and 2022, over Portugal's mainland. In the present analysis, several predictors were selected, such as Surface Solar Radiation Downwards (SSRD), Fire Radiative Power (FRP), Temperature, Nitrogen Dioxide (NO2), and Time of the Year (TOY). The FRP data used has been delivered in near real-time, since 2004, by the EUMETSAT Land Surface Analysis Satellite Applications Facility (LSA-SAF). The SSRD, ozone concentration and the remaining variables were collected from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. The SSRD data is obtained from the ERA5 database, while the other variables are from the EAC4 database. A stepwise regression was applied to selected predictors used to evaluate the influence of each on ozone concentration and two models to estimate mean and maximum ozone tropospheric concentration were proposed. To understand the synoptic atmospheric patterns linked to tropospheric ozone concentration, spatial patterns of geopotential 850 mb, sea mean level pressure, vertical velocity, air temperature, and wind speed were analyzed during days characterized by high and low ozone concentrations. The regression models proposed have been tested using the Monte Carlo procedure and both models show high accuracy and robustness. Results also show a relevant contribution of FRP to mean and maximum ozone concentrations, namely for the composite of days characterized by high ozone concentration. In the present context of climate change and considering the foreseen increase of fire activity and severity, the proposed models revealed to be a useful tool for estimating tropospheric ozone concentration during the recent extreme fire events and also for analyzing the potential impacts of those concentrations on health and ecosystems. 

 

Acknowledgements:

This study is partially supported by the European Union’s Horizon 2020 research project FirEUrisk (Grant Agreement no. 101003890), by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020- IDL,  DHEFEUS - 2022.09185.PTDC and by European Investment Funds by FEDER/COMPETE/POCI– Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033/2020.

How to cite: Alonso, C., A. Santos, J., and Gouveia, C.: Analysis of tropospheric ozone predictors and their relationship with the occurrence of fires in mainland Portugal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10961, https://doi.org/10.5194/egusphere-egu24-10961, 2024.