The representativeness of ambient air quality of an in situ measurement is key in the use and correct interpretation of the measured concentration values. Though the horizontal representativeness ...aspect is generally not neglected in air pollution studies, a detailed, high-resolution vertical distribution of ambient air pollutant concentrations is rarely addressed. The aim of this study is twofold: (i) to explore the vertical distribution of ground-level ozone (O
3
) concentrations measured at four heights above the ground—namely at 2, 8, 50, and 230 m—and (ii) to examine in detail the vertical O
3
concentration gradient in air columns between 2 and 8, 8 and 50, and 50 and 230 m above the ground. We use the daily mean O
3
concentrations measured continuously at the Košetice station, representing the rural Central European background ambient air quality observed during 2015–2021. We use the semiparametric GAM (generalised additive model) approach (with complexity or roughness-penalised splines implementation) to analyse the data with sufficient flexibility. Our models for both O
3
concentrations and O
3
gradients use (additive) decomposition into annual trend and seasonality (plus an overall intercept). The seasonal and year-to-year patterns of the modelled O
3
concentrations look very similar at first glance. Nevertheless, a more detailed look through O
3
gradients shows that they differ substantially with respect to their seasonal and long-term dynamics. The vertical O
3
concentration gradient in 2–230 m is not uniform but changes substantially with increasing height and shows by far the highest dynamics near the ground between 2 and 8 m, differing in both the seasonal and annual aspects for all the air columns inspected. We speculate that non-linear changes of both seasonal and annual components of vertical O
3
gradients are due to atmospheric-terrestrial interactions and to meteorological factors, which we will explore in a future study.
For the proper diagnosis of toxoplasmosis it is essential to determine the stage of the infection, for which the most preferred method is IgG avidity test. The avidity index (AI) should initially be ...low (AI≤0.3) in the acute phase and increase during the infection. However, persistent low avidity can occur in patients with latent toxoplasmosis, which can complicate the interpretation of the results. The aim of the study is to explain the causes of this phenomenon.
A retrospective study was carried out with 717 serum samples collected from 442 patients from the categories of pregnant and non-pregnant women, men, and newborns + infants (age < 0.5 year). The trends of AI kinetics were evaluated in repeatedly examined patients. The frequency of cases with low avidity was compared in individual categories of patients and in groups of people with acute and non-acute toxoplasmosis.
The proportion of patients with initially low avidity was 42.1% in the acute toxoplasmosis group while it was 13.0% in the non-acute groups. In uninfected newborns with anti-Toxoplasma antibodies transmitted from the mother, a decrease in IgG avidity levels over time was observed, resulting in 29.2% of samples showing low (improper) avidity. While the dynamics of IgG avidity and the frequency of cases of improperly low avidity were similar in men and pregnant and non-pregnant women, the category of newborns and infants differed substantially for these indicators.
Due to acceptable specificity and negative predictive value, high avidity can rule out acute toxoplasmosis, but moderate sensitivity complicates the possibility of its confirmation. The results of the avidity test must be interpreted in the context of the results of other methods.
Fog is a very complex phenomenon, relevant to both atmospheric physics and chemistry, contributing to the atmospheric inputs of both nutrients and pollutants to the environment. Fog occurrence is ...affected by numerous factors. The aim of this study is to examine the effects of terrain on fog occurrence. Namely, we studied in detail how altitude, slope and landform influence the probability of fog occurrence using the generalized additive model. In particular, we investigated how different explanatory variables might modify (deform) the trend and the seasonal component of the probability of fog occurrence. We used long-term records of daily fog occurrence measured in 1981–2017 at 56 professional meteorological stations in Romania, reflecting different environments and geographical areas. The altitude of the sites under review ranged between 13 and 2504 m above sea level, the coverage of localities at different altitudes being highly uneven. Out of the terrain variables considered, the most decisive influence was found to be altitude. We have included information on slope and landform, which refined and bettered the basic model. Our model results indicated a significant decrease in the probability of fog occurrence over the examined period. The behaviour of fog differed according to the altitude, the most profound effects being observed for ground-level fog and fog above flat terrain. The probability of fog occurrence at different altitudes varied mostly in summer and autumn, whereas it was very similar in winter.
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•Effects of terrain on fog incidence at 56 Romanian sites in 1981–2017 analysed by GAM.•Details of decreasing fog trends and seasonality were explored.•Non-linear behaviour for both year-to-year trends and annual seasonality confirmed.•Of variables examined, the altitude showed the most decisive effect on fog occurrence.•Inclusion of slope and landform enhanced the GAM model used.
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•Long- term trends in fog occurrence at 12 Czech sites in 1961–2018 analysed using GAM.•Non-linear behaviour for both year-to-year trends and annual seasonality confirmed.•Significant ...decreasing trends detected though pattern differed among individual sites.•Significant seasonality in fog occurrence though pattern differed among individual sites.•Fog’s seasonal profile at some sites has deformed substantially over the long term.
Fog is a very important and complex atmospheric phenomenon of the utmost importance for the environment and for human society. For practical reasons, fog occurrence is observed regularly at meteorological stations worldwide. Decreasing trends in fog frequency reported from numerous regions have been often associated with either decreasing pollution or climate change, including increasing temperature and changes in atmospheric circulation.
We have examined the data on fog occurrence from twelve Czech sites representing different environments (urban, rural, mountain), geographical areas, and altitudes across the country. For our analysis we used long-term records from the time period of 1961–2018, covering both the ambient air’s heavily polluted periods of the 1970s and 1980s and the cleaner period, following the adoption of new, more stringent legislation and effective countermeasures after the 1990s. We applied a generalised additive model (GAM) framework as a flexible, semiparametric regression approach to address nonlinear trend shapes in a formalised and unified way. In particular, we employed a penalised spline approach with cross-validated penalty coefficient estimation.
Our study confirmed non-linear behaviour for both year-to-year trends and annual seasonality. Our results showed further that over the analysed, almost sixty-year period, fog occurrence has decreased significantly at all the examined sites, though the pattern of the long-term change differed among individual sites. Moreover, we have found significant seasonality in fog occurrence, though it is different at individual sites. Furthermore, apart from the overall annual fog probability change over the years, at some sites the fog’s seasonal profile has also deformed substantially over the long term.
Fog is influenced by numerous factors, including forests. The aim of our study was to examine in detail the extent to which forests affect fog. We hypothesised that: (i) fog incidence is affected by ...forests, (ii) the forested area in the station's neighbourhood is a factor influencing fog incidence, (iii) the influence on fog differs between coniferous and broad-leaved forests and (iv) the effect of forests on fog occurrence differs with altitude. For this, we used long-term records of fog incidence measured in 1981–2017 at 56 professional meteorological stations in Romania, GIS-derived information on forested areas in the neighbourhood of these stations, and land-use data on the types of these forests. The analyses are based on a semiparametric generalised additive logistic model for the probability of fog occurrence with potentially nonlinear, smooth effects modelled via penalised splines. Our results indicated that forests do affect fog incidence significantly, though their effect is considerably lower than the effect of dominant factors we studied previously, such as seasonality and altitude. It was indicated that forested areas in the neighbourhood of these stations are a factor significantly influencing fog incidence, even when forest is not the dominant land-use factor. In this respect, a radius of 3 km was the most effective when considering the forested area in a circle around the meteorological station. Our model showed that the influence on fog occurrence differs between coniferous and broad-leaved forests, and the effect of forests on fog occurrence is modified by altitude. The hypotheses propounded were confirmed and the hypothesised effects were quantified. Our findings, relevant at least for temperate forests, will enhance further considerations related to fog formation and wet atmospheric deposition. Moreover, our study opens a new challenge for further research of water balance as related to deforestation in catchment areas.
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•Semiparametric GAM analysis of forest effects on fog seasonality presented.•Forests affect fog incidence significantly.•Forested area within a 3 km radius from a station proved to be the most influential.•Influence on fog occurrence differs between coniferous and broad-leaved forests.•Effect of forest on fog occurrence strongly depends on altitude.
Fog is an important atmospheric phenomenon highly relevant to ecosystems and/or the environment. Two essential prerequisites of fog formation are the presence of fog condensation nuclei and water in ...the atmosphere. The aim of our study was to examine in detail how fog occurrence is influenced by water areas in the immediate vicinity of the fog observation site. We have used as input data long-term observations on fog occurrence measured at 56 professional meteorological stations in Romania in 1981–2017 and GIS-derived information on water areas and on two topographical indices, TWI and TPI, in the neighbourhood of these stations. We formulated three alternative models of different complexity based on a semiparametric generalised additive logistic model for the probability of fog occurrence with potentially nonlinear, smooth effects modelled via penalised splines. A radius of 9 km appeared to be the most influential when considering the water area in a circle around the fog observation station. Based on our results, we concluded that (i) the water area in the vicinity of the station is a factor influencing fog occurrence, (ii) the water's effect differs according to water type (freshwater or seawater proximity), and (iii) GIS-derived topographical indices are informative for the explanation of fog occurrence and their inclusion enhanced the fit of the models substantially. Our findings, based on a reliable long-term data set of fog occurrence and recent GIS-derived data, explored by a relevant statistical approach will enhance further considerations related to fog formation and its environmental consequences.
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•Effect of water on fog incidence at 56 Romanian sites in 1981–2017 analysed by GAM•Water area round station affects fog occurrence but less than altitude or seasonality.•The radius of 9 km round the fog observation station appeared as the most influential.•Seasonal profile and frequency of fog vary due to freshwater or seawater proximity.•GIS-derived topographical indices informative for the explanation of fog occurrence.
We examined observation-based fog occurrence at three Czech monitoring sites: Praha 4 - Libuš, Košetice and Churáňov, representing different environments - urban, rural and mountain - over a time ...span of 27 years (1989–2015). We searched for a simple model describing fog occurrence fitting the observed air pollution and meteorological data. For our analysis we used a generalized additive model, GAM, with (penalized) spline components to capture possible nonlinear and a priori unknown functional relationships. In order to cope with the binary nature of the data (indicators of fog presence on individual days), we employed a logistic regression GAM model fitted by a maximizing penalized likelihood (where the penalty coefficients were estimated via cross-validation). After testing several physically motivated models, being guided by AIC and physical interpretation of the components, we arrived at a model which uses the following explanatory variables: relative humidity, ambient SO2 concentrations, ambient NOx concentrations, air temperature and seasonality. All associations between the response and the analysed explanatory variables were highly significant. According to our results, the most important explanatory variables modelling the fog probability were relative humidity and air pollutants. Interestingly, we observed an increasing trend in fog occurrence at all three sites under review starting around the mid 2000s.
The most important explanatory variables modelling the fog probability at three Central European sites were humidity, SO2 and NOx. An increasing trend in fog occurrence has been observed since the mid 2000s.
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•Fog occurrence at three Czech sites over 27 years (1989–2015) was studied.•A logistic regression GAM model fitted by a maximizing penalized likelihood employed.•Explanatory variables: relative humidity, SO2, NOx, air temperature, seasonality.•Humidity, SO2, NOx are the most important explanatory variables for fog probability.•Increasing trend recorded in fog occurrence since the mid 2000s.
The aim of our study was to identify the factors substantially affecting day-to-day variability in O3 concentrations in Czech mountain forests and to describe their influence in detailed, ...quantitative way. We examined the effects of meteorology and ambient NOx recorded in regular long-term continuous monitoring at five mountain forest sites representing different regions, covering both polluted and relatively unpolluted areas over the time period of 1992–2018. To investigate the association between ambient O3 concentrations on one hand, and precursor NOx concentrations, and meteorology on the other hand, we used a generalized additive model, GAM, with semiparametric (penalized-spline-based) components to capture properly the possible departures from linearity that is not captured by traditional linear regression approaches. Our results revealed that the O3 concentrations showed significant associations with all selected explanatory variables, i.e., air temperature, global solar radiation (GLRD), relative humidity, and NOx. Apparently, both meteorology and air pollution are highly important for day-to-day O3 concentrations, and this finding is consistent for all five rural sites, representing middle-elevated forested mountain areas in Central Europe. In addition to individual variables, we were able to detect interactions between three pairs of explanatory variables, namely temperature*GLRD, temperature*relative humidity, and GLRD*relative humidity. Moreover, we confirmed non-linear O3 behavior toward all individual explanatory variables.
It is important to study precipitation chemistry to comprehend both atmospheric and environmental processes. The aim of this study was the reconstruction of daily concentration patterns of major ions ...in precipitation from samples exposed for longer and differing time periods. We explored sulphates (SO42−), nitrates (NO3−) and ammonium (NH4+) ions measured in precipitation within a nation-wide atmospheric deposition monitoring network in the Czech Republic during 1980–2020. We visualised the long-term trends at selected individual years for four stations, Praha 4-Libuš (LIB), Svratouch (SVR), Rudolice v Horách (RUD) and Souš (SOU), differing in geographical location and reflecting different environments. We found anticipated time trends reflecting the emission patterns of the precursors, i.e., sharp decreases in SO42−, milder decreases in NO3− and steady states in NH4+ concentrations in precipitation. Statistically significant decreasing time trends in SO42− and NO3− concentrations in precipitation between 1990 and 2015 were revealed for the LIB and SVR sites. Spring maxima in April were found for all major ions at the LIB site and for NO3− for the SVR site, for both past and current samples, whereas no distinct seasonal behaviour was recorded for NH4+ at the RUD and SO42− at the SVR sites. By applying Bayesian modelling and the Integrated Nested Laplace Approximation approach, we were able to reconstruct the daily patterns of SO42−, NO3− and NH4+ concentrations in precipitation, which might be further utilised for a wide range of tasks, including comparison of magnitudes and shapes between stations, grouping the decomposed daily data into the ecologically motivated time periods, as well as for logical checks of sampling and measurement reliability.
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