Application of the Principal Component Analysis (PCA) Method to Assess the Impact of Meteorological Elements on Concentrations of Particulate Matter (PM10): A Case Study of the Mountain Valley (the Sącz Basin, Poland)

Abstract

The aim of this study was to determine, by use PCA analysis, the impact of meteorological elements on the PM10 concentration on the example of the mountain valley. Daily values of selected meteorological elements, measured during a ten-year period in the spring, summer, autumn and winter, obtained from the meteorological station in Nowy Sącz, were adopted as variables explaining PM10 concentration. The level of PM10 was significantly affected by the maximum, minimum and average temperature in autumn, winter and spring. In summer the average and maximum temperature was significant. In winter, the first principle component mainly consisted of the combination of the average and maximum wind speed. The second principal component in spring, summer and autumn was the combination of the wind speed (average and maximum), but in winter humidity and atmospheric pressure seemed to be significant. The third principal component, in terms of strength of impact, was humidity in spring, the combination of humidity and minimum temperature in summer, and precipitation in autumn. In winter, the highest PM10 concentrations were observed during the non-directional, anticyclonic wedge conditions. Three principal components were distinguished in this situation: temperature (average, maximum and minimum); the combination of humidity and wind speed and precipitation.

Variability and selection among mutant families of wheat for biomass allocation, yield and yield‐related traits under drought‐stressed and non‐stressed conditions

“…Traits with high loading on the first and second PCs are important for selection as they are able to discriminate the genotypes more effectively compared to traits with less contributions (Shlens, 2014;Zhang & Castelló, 2017;Zuśka et al, 2019). The differences in trait contributions to the total variation observed among the genotypes under different water regimes were in line with findings from Mwadzingeni et al (2016) and Mathew et al (2019).…”

“…Under water‐stressed condition, the high positive loadings of productive tiller number, shoot biomass, total biomass, root biomass, root–shoot ratio and grain yield on the first two PC axes indicate the importance of selecting families based on these traits for drought tolerance and increased biomass (Table 5). Traits with high loading on the first and second PCs are important for selection as they are able to discriminate the genotypes more effectively compared to traits with less contributions (Shlens, 2014; Zhang & Castelló, 2017; Zuśka et al., 2019). The differences in trait contributions to the total variation observed among the genotypes under different water regimes were in line with findings from Mwadzingeni et al.…”

The Condition of Air Pollution in Kraków, Poland, in 2005–2020, with Health Risk Assessment

“…Specific attention was lately paid to particulate matter (PM). PM particles can adsorb other harmful substances on their surfaces [ 31 ], and consequently, they can cause additional adverse health effects after entering human bodies [ 32 ]. Street dust was described as the most effective and sensitive indicator of urban environment pollution, especially by heavy metals [ 33 ].…”

Hydrobiochemical balance of total mercury in a forest catchment area at former cinnabar mining locality

“…Among the most polluted places are those located in mountain valleys. Research on the impact of meteorological conditions on particulate concentrations in the air has shown a clear relationship between elevated concentrations and thermal inversion mainly in winter season (Zuśka et al, 2019).…”