Effect of the COVID-19 Lockdown on Air Pollution in the Ostrava Region.

A proper estimation of anti-epidemic measures related to the influence of the COVID-19 outbreak on air quality has to deal with filtering out the weather influence on pollution concentrations. The goal of this study was to estimate the effect of anti-epidemic measures at three pollution monitoring stations in the Ostrava region. Meteorological data were clustered into groups with a similar weather pattern, and pollution data were divided into subsets according to weather patterns. Then each subset was evaluated separately. Our estimates showed a 4.1-5.7% decrease in NOx concentrations attributed to lower traffic intensity during the lockdown. The decrease of PM2.5 varied more significantly between monitoring stations. The highest decrease (4.7%) was detected at the traffic monitoring station, while there was no decrease detected at the rural monitoring station, which focuses mainly on domestic heating pollution. The key result of the study was the development of an analytical method that is able to take into account the effect of meteorological conditions. The method is much simpler and easy to replicate as an alternative to other published methods.

Moss biomonitoring and air pollution modelling on a regional scale: delayed reflection of industrial pollution in moss in a heavily polluted region?

A passive biomonitoring survey using terrestrial mosses was performed in a heavily polluted industrial region on the border between Czechia and Poland in a regular grid of 41 sampling points. The concentrations of 38 elements were determined in the moss samples, using Neutron Activation Analysis (NAA). Simultaneously, air pollution modelling was performed using the Czech reference methodology Symos'97 for the year of the sampling (2015) and 3 years prior (2012) in order to compare the results of both the approaches and evaluate the credibility of the moss biomonitoring method. The NAA results were transformed according to the principles of compositional data analysis and assessed using hierarchical clustering on principal components. The resulting clusters were compared with the results of air pollution modelling using one-way analysis of variance. The association of determined clusters with the pollution from industrial sources was confirmed only for the results of the 2012 modelling. This validates the complementarity of the air pollution modelling and the moss biomonitoring, ascertains the moss biomonitoring as a valid method for long-term pollution assessment and confirms one of the fundamentals of moss biomonitoring, the reflection of the atmospheric conditions prevailing in the period before the sampling.