Comparison of concentrations of chemical species and emission sources PM2.5 before pandemic and during pandemic in Krakow, Poland

Estimation of public exposure to PAH and environmental risks via wastewater-based epidemiology

The wastewater-based epidemiology (WBE) has the potential to monitor public health emergencies via the analysis of human urinary biomarkers in wastewater. This work proposes a novel approach utilizing WBE for the spatial and temporal evaluation of PAHs exposure using hydroxyl derivatives of PAHs. These are 1-hydroxynaphthalene, 2-hydroxynaphthalene, 2-hydroxyfluorene, 9-hydroxyfluorene, 9-hydroxyphenanthrene, 1-hydroxypyrene and 3-hydroxybenzo(a)pyrene. Most target markers were found at quantifiable concentrations in raw and treated wastewater. The total loads identified in raw sewage ranged from 88.33 g/day to 154.77 g/day during the summer period and from 137.66 g/day to 283.78 2 g/day during the winter period. The obtained results for the removal efficiencies of OH-PAHs indicate a seasonal dependency in their degradation. Removal efficiencies were higher in January compared to August. The results of the back calculations allowed to estimate that during the summer, on average, a resident of Krakow could absorb approximately 2.1 µg of the assessed OH-PAHs per day, while in winter, this value increased to 4.1 µg. This is close to the reported in the literature value that the total daily exposure to OH-PAHs is estimated at 3 µg/day. Moreover, the risk quotation (RQ) values on the base of acute and chronic data base for compounds present in effluents were calculated. The RQ values in January were relatively low, but in August the RQ values were higher, indicating a high concentration of effluent and nitrogen in summer as these compounds were removed in winter and summer. To the authors' knowledge, this is the first time wastewater profiling of OH-PAHs in wastewater for the evaluation of exposure to PAHs have been used, also their removal as well emission with effluent were determined.

Chemical composition and source apportionment of ambient PM2.5 in a coastal urban area, Northern Poland

Coastal urban areas impact atmospheric chemistry and air quality through various sources, interactions, and processes. This study examines the mass concentrations of fine mode (PM2.5) aerosol and its major and trace components (Al, As, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mo, Mn, Na, Ni, Pb, Sb, Se, Sr, Te, Ti, Tl, V, Zn). The comprehensive field measurements were conducted in Poland between September 2019 and May 2020. Seasonal distribution and drivers of these pollutants showed considerable variability. In winter, higher concentrations were observed for Pb, Co, and As due to the higher contribution of pyrogenic emission. The Principal Component Analysis provided evidence of anthropogenic sources of trace species associated with coal combustion by industry/power plants, brake wear-related emissions, vehicle emissions, shipping activities, road-resuspended dust, and urban construction activities. These results showed that major chemical elements (Ca, Na, Fe, Mg, Al, and K) contributed to 4.07-34.0% of all components. Se, Zn, and Br contributed 1.29%, 1.25%, and 1.04%, respectively, while other tracers ranged between 0.07% and 0.95%. The diagnostic ratio of V/Ni remained stable between 0.45 and 0.46 during the cold season, then increased in spring, indicating that ship emissions were an important source of these metals during the warm season.

Air pollution seasons in urban moderate climate areas through big data analytics

High particulate matter (PM) concentrations have a negative impact on the overall quality of life and health. The annual trends of PM can vary greatly depending on factors such as a country's energy mix, development level, and climatic zone. In this study, we aimed to understand the annual cycle of PM concentrations in a moderate climate zone using a dense grid of low-cost sensors located in central Europe (Krakow). Over one million unique records of PM, temperature, humidity, pressure and wind speed observations were analyzed to gain a detailed, high-resolution understanding of yearly fluctuations. The comprehensive big-data workflow was presented with the statistical analysis of the meteorological factors. A big data-driven approach revealed the existence of two main PM seasons (warm and cold) in Europe's moderate climate zone, which do not correspond directly with the traditional four main seasons (Autumn, Winter, Spring, and Summer) with two side periods (early spring and early winter). Our findings also highlighted the importance of high-resolution time and space data for sustainable spatial planning. The observations allowed for distinguishing whether the source of air pollution is related to coal burning for heating in cold period or to agricultural lands burning during the warm period.