Time-varying relationship between SO42-, NO3-, NH4+ concentrations in cumulative precipitation samples and gaseous pollutants

In this work we are expanding upon our previous statistical modeling methodology for reconstruction of daily courses of SO42-, NO3- and NH4+ concentrations in cumulative precipitation samples (Hunova et al 2022, Hunova et al 2024). Here, we investigate relationship between the wet concentrations and concentrations of gaseous pollutants (NOx, SO2, NH3) in a detailed way from several viewpoints using modern and highly flexible statistical approach based on GAM (Generalzied Additive Model) with complexity-penalized spline components. This framework allows for decomposition of influences upon wet concentration into several easily interpretable components as well as for the nonlinearity dictated by basic physical consideration (such as saturation phenomena). The GAM model is formulated in such a way that it deals appropriately with the time-aggregated collections whose length changed historically (from 7 days to 1 day). Since it is quite obvious that the wet concentration in a spatial point sample is related to the gas concentration in a much broader area, we work not only with gaseous concentrations measured at the wet-sample-collection location, but also with numerical air pollution model (CAMx) aerial average estimates in our simultaneous models. Here, it is not clear a priori, how large neighborhood we should take for the most informative CAMx output spatial average and similarly whether it is more natural to take CAMx concentrations at surface or in 50 m. Therefore, we assess both of these features in a formalized way (via AIC model comparison).  The modelling approach is illustrated at four professional Czech Hydrometeorological Institute (CHMI) stations (ALIB, JKOS, PPRM, TBKR) with long-term data (2016-2021). There, it turns out that both local measurement and relatively large area CAMx gaseous concentration averages influence water sample ion concentrations significantly. Hight and spatial aggregation differs for different ions. Further analysis using time-varying (TVAR) framework then shows that the influence of the concentration measurements is highly seasonal (local slope changes smoothly but very substantially, favoring spring to summer influences). The work has been done in cooperation with the CHMI and is related to the Technology Agency Czech Republic project ARAMIS, SS02030031).

 

References:
Hunova,I.-Brabec,M.-Maly,M. (2024): Major ions in Central European precipitation – insight into changes in NO3-/SO42-, NH4+/NO3- and NH4+/SO42- ratios over the last four decades. Chemosphere 349 (2024) 140986
Hunova,I.-Brabec,M.-Maly,M.-Skachova,H. (2022): Reconstruction of daily courses of SO42-, NO3-, NH4+ concentrations in precipitation from cumulative samples. Atmosphere 2022, 13, 1049. https://doi.org/10.3390/atmos13071049