With attention increasing regarding the level of air pollution in different metropolitan and industrial areas worldwide, interest in expanding the monitoring networks by low-cost air quality sensors is also increasing. Although the role of these small and affordable sensors is rather supplementary, determination of the measurement uncertainty is one of the main questions of their applicability because there is no certificate for quality assurance of these non-reference technologies. This paper presents the results of almost one-year field testing measurements, when the data from different low-cost sensors (for SO2, NO2, O3, and CO: Cairclip, Envea, FR; for PM1, PM2.5, and PM10: PMS7003, Plantower, CHN, and OPC-N2, Alphasense, UK) were compared with co-located reference monitors used within the Czech national ambient air quality monitoring network. The results showed that in addition to the given reduced measurement accuracy of the sensors, the data quality depends on the early detection of defective units and changes caused by the effect of meteorological conditions (effect of air temperature and humidity on gas sensors and effect of air humidity with condensation conditions on particle counters), or by the interference of different pollutants (especially in gas sensors). Comparative measurement is necessary prior to each sensor’s field applications.

Use of small air quality sensors is very popular during last few years not only in research but also in public sector. From scientific point of view there are possibilities to cover larger area in air quality monitoring by adding small and easy affordable sensors into the reference measurement networks. Such an application of sensors can be very useful for identifying new hotspots or for development of finescale air quality modelling. Nevertheless, there are some limits for real-time outdoor monitoring that must be considered-higher detection limits and weak possibility to deal with non-standard conditions (low temperatures or high air humidity). Therefore, it is very important to be careful with data postprocessing and data interpretation to not get misleading air quality information. Despite a few independent studies and tests of different types of small sensors have been already done (by universities, companies and also by EU Reference Laboratories), the standardized procedure for testing and verifying the data quality has not yet been developed. Sharing the field-measurement experience with different sensors and the data correction methods is therefore crucial. Here we provide results from test measurement of set of electrochemical Cairclip sensors (Cairpol, FR) for SO2, NO2, O3/NO2 and CO during summer (in year 2015) and winter period (2017/2018). The best performance both in comparison between pairs and also between sensors and reference monitors (RM) was found out in combined O3/NO2 Cairclip sensor. Nevertheless, the association of sensor's measured data with sum of O3 and NO2 measured by RM was much better in summer (R2 = 0.88) than in winter period (R2 = 0.31). Based on the known effect of air temperature and humidity on sensors data quality, we further applied some corrections based on dew point deficit (Td deficit). In this way verified data showed significant improvement in relationship with RM data (R2 = 0.88 with improved slope in summer and R2 = 0.58 in winter). Although the quality of sensor's measurement can be influenced by many factors at once and further research is needed to resolve all uncertainties, the simple corrections based on the most critical meteorological factors can be very effective.

Understanding how natural processes arise from complex interactions between particular processes at small spatiotemporal scales and in turn how these processes form patterns at large spatiotemporal scales is one of the current principal questions in environmental science. The problem is very complicated, as in many cases, key processes are often studied by researchers in separate disciplines such as ecology, soil science or hydrology. One of the major obstacles is that the processes at a landscape scale are difficult to manipulate and, in many cases, even measure. In particular, the belowground processes are in many cases overlooked or at least understudied. Here we briefly describe a methodological solution used to cope with this problem and describe artificial catchments designed for experimental manipulation at the level of a landscape, called FALCON. This array has two treatments: one mimics a site reclaimed using an alder plantation and the other was left to unassisted primary succession. For each treatment, there were two replicates in four similar catchments. Individual catchments are hydrologically isolated from the environment and equipped with instruments, so that all the main processes and all significant flows of substances and energy in the ecosystem can be monitored, including the cycling of water, nutrients and gas between the ecosystem and the atmosphere. In addition, in each catchment there are sets of lysimeters, which allow the study of small-scale processes and how these can be extrapolated to the catchment scale. In addition, two lysimetric fields exist alongside the catchments for monitoring the effects of the experimental manipulation.