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Integration of air pollution data collected by mobile measurement to derive a preliminary spatiotemporal air pollution pro file from two neighboring German-Czech border villages

Publikace na Přírodovědecká fakulta |
2020

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

Generally, there are only a few fixed air quality monitoring stations installed in villages or rural areas and only a few studies on small-scale variations in air pollution have been described in detail, which make it difficult to estimate human exposure in such environments and related adverse health effects. Moreover, biomass combustion can be an important source of air pollution in rural areas, comparable to vehicle and industrial emissions in urban planning.

And their air pollutants are mainly affected by local sources. For this reason, a survey on rural air pollution was carried out in this study.

Therefore, portable, battery-powered monitoring devices were used to measure particulate matter (PM10, PM2.5, PM1, particle number concentration, and black carbon) in order to study air quality in rural communities. The focus of the investigations was to explore the application of mobile monitoring equipment in small-scale environments, compare the differences in rural air pollutants between two neighboring villages in two countries, and the identification of pollution hotspots.

The measurements were carried out in November 2018 in two villages on the German-Czech border. Over a period of four days, 21 mobile measurements along fixed routes were carried out simultaneously at both locations.

The analysis of the data revealed significant differences in PN and PM concentrations in rural air pollutants between the two countries. The spatial and temporal distribution of air pollution hotspots in the Czech village was higher than that in the German village.

The relationships between the measurement parameters were weak but highly significant and the meteorological parameters can effect air pollution. Overall, the results of this study show that mobile measurements are suitable for effectively recording and distinguishing spatial and temporal characteristics of air quality. (C) 2020 Elsevier B.V.

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