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.
Abstract. The PALM 6.0 model system has been rapidly developed in the recent years with respect to its capability to simulate physical processes within urban environments. In this regard, it includes e.g. energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, as well as a plant-canopy model to consider the effects of plants on the (thermo)dynamics of the flow. This study provides a thorough evaluation of modelled meteorological, air chemistry and wall-surface quantities against dedicated in-situ measurements taken in an urban environment in Prague, Dejvice, Czech Republic. Measurements included e.g. monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared camera and monitoring of wall heat fluxes. Large-eddy simulations (LES) for multiple days within two summer and three winter episodes that are characterized by different atmospheric conditions were performed with the PALM model driven by boundary conditions obtained from a mesoscale model. For the simulated episodes, the resulting temperature, wind speed and concentrations of chemical compounds within street canyons agreed well with the observations, except the LES did not adequately capture nighttime cooling near the surface at certain meteorological conditions. In some situations, less turbulent mixing was modelled resulting in higher near-surface concentrations. At most of the surface evaluation points the simulated wall-surface temperature agreed fairly well with the observed one regarding its absolute value as well as daily amplitude. However, especially for the winter episodes and for modern buildings with multi-layer walls, the heat transfer through the wall is partly not well captured leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, we show that model results depend on the accuracy of the input data, particularly the temperatures of surfaces affected by nearby trees strongly depend on the spatial distribution of the leaf area density, land-surface temperatures at grass surfaces strongly depend on the initial soil moisture, or wall-surface temperatures depend on the correct prescription of wall material parameters, though these parameters are often not available with sufficient accuracy. Moreover, we also point out current model limitations, here we particularly focus on implications with respect to the discrete representation of topography on a Cartesian grid, complex heterogeneous facades, as well as glass facades that are not well represented in terms of radiative processes. With these findings presented, we aim to validate the representation of physical processes in PALM as well as to point out specific shortcomings. This will help to build a baseline for future developments of the model and for improvements of simulations of physical processes in an urban environment.
SUMMARYAn air-quality forecasting system based on the pair 'NWP model MM5-chemistry transport model CAMx' is proposed. A version of the ensemble Kalman Filter has been developed. The model-error covariance matrix is parametrized with the help of a covariance function and represented by an ensemble formed as a random selection from leading eigenvectors. The performance of the system is tested on the case of an ozone episode in June 2001. As a source of observations, the AirBase database has been used. Starting the forecast from analysed concentration fields improves the quality of forecast of the next day's ozone concentration maxima.
The authors present the results of a comparison of wind parameters and heat flux inferred from Doppler SODAR (Sensitron/Sweden) with direct measurements using an acoustic anemometer (Kaijo-Denki, DAT 300) and a platinum wire thermometer. Rather important are the results of a calibration method for C', from measurements of temperature standard deviation, and of an underestimation of the wind speed by Doppler SODAR. An operational means to calculate the flux of sensible heat on the basis of SODAR measurements is studied.
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.
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