Operation

An important supplement to stationary measurements can be mobile measurements of atmospheric environment parameters (e.g. air pollution, meteorological and biometeorological parameters, etc.). Such measurements can be performed using drones, car platforms, bicycles and other similar vehicles, as well as on foot. The experience of the team of the WOPAS indicates that the results of such measurements can be used, among others, for recognition of spatial variability of measured parameters on a local and micro scale, recognition of variability of measured parameters outside the area covered by stationary measurements, indication of areas particularly exposed to hazards related to the atmospheric environment.

Within these services, the WOPAS team offers both urban oriented measurements and measurements in mountain areas. Moreover during campaigns the usefulness of sensors can be tested. Mobile measurements provide unique insights into spatial and temporal variability of atmospheric parameters, identifying hotspots and supporting tailored mitigation strategies in both urban and challenging mountainous environments.

Measurement campaigns aim to analyze the variability of plant pollen in the urban atmosphere and its coexistence with air pollutants to determine potential adverse health effects. The planned measurements will include in-situ observations (using the Swissens Poleno Jupiter automatic pollen analyzer and the Burkard-type manual pollen trap) as well as lidar measurements utilizing the fluorescence channel.

Intercomparison campaigns. Comparison, testing, exploitation of any measurement devices with WOPAS instruments that follow ACTRIS protocols (both in-situ and remote-sensing aerosols measurements)  or meteorological equipment. Campaigns can include the testing of usefulness for mobile measurements. These campaigns help users ensure compliance with measuring standards, improve device calibration, and build capacity through hands-on experience.

The atmospheric boundary layer (ABL) is one of the fundamental part of the atmosphere influencing e.g. air quality, substance transport, etc. In middle latitudes, during radiative weather conditions, it is characterized by typical variability resulting from changes in the radiative balance. Despite the importance of proper parameterization of the boundary layer, particularly in determining the depth of the mixing layer, errors generated by meteorological models can reach up to 100%. Therefore, it is especially crucial to develop an appropriate methodology to fully describe the dynamics of the ABL.

The goal of the measurement experiment is to integrate lidar, sodar, drone, and ground-based measurements to verify assumptions regarding the depth of the mixing height and validate results from atmospheric models. At WOPAS, continuous measurements are conducted using high-power aerosol lidar, monostatic Doppler minisodar, vertical profile measurements with a prototype measurement head installed on a drone, and comprehensive meteorological observations. The integration of multiple measurement methods ensures a robust understanding of ABL dynamics, aiding in the refinement of meteorological models and their outputs, particularly in urban and rural settings

Measurement campaigns enabling the determination of atmospheric aerosol properties using in situ measurements (aethalometer, nephelometer, ultrafine and fine particle distribution spectrometers) and remote sensing techniques (high-power aerosol lidar, photometers) allow for the characterization of aerosol properties. These measurements will be supplemented with data on the concentrations of gaseous pollutants, such as NOx (NO, NO2), ozone, suspended particulate matter (PM10, PM2.5), and aerosol chemical composition analysis based on gravimetric measurements.

At the WOPAS platform, comprehensive meteorological measurements are conducted, including the radiation balance in the longwave and shortwave ranges, precipitation intensity and type using an optical disdrometer, wind speed and direction, and temperature gradient measurements up to 14 m above ground level on a meteorological tower. Additionally, the structure of the lower part of the boundary layer is studied using SODAR.

Furthermore, the WOPAS team has extensive experience in modeling atmospheric processes using models such as WRF, WRF-Chem, EMEP, u_EMEP, and ADMS. Methods for applying machine learning in air quality modeling are also being developed.

The campaigns provide data for urban air quality assessments, enabling evidence-based decisions for e.g. health impact assessment, air quality management, and deeper insight into processes favoring haze events.

Provision of lidar products in a near real-time window (e.g. within 3 hrs from measurement time) to a repository for use in model applications (e.g. Copernicus Atmosphere Monitoring Service). 

The service includes:

• Data analysis of the PANGEA lidar measurements in near real-time

• Data provision in near real-time to an online repository to be used as input in model applications (e.g. CAMS)

Short and long-term experimental Cal/Val campaigns at PANGEA premises, using PANGEA’s infrastructure and user’s own instrumentation. The infrastructure at PANGEA includes ACTRIS compliant aerosol and cloud remote sensing instrumentation, along with complementary measurements for meteorological parameters and radiation. Additional instruments from the users can be also accommodated indoor or outdoor, as needed.

The service includes:

• Data collection and data analysis of the PANGEA instrumentation

• Administrative and technical support on the (de)mobilization, installation, and operation of the user’s instrumentation

• Support from the scientific staff to collect, process and analyze the data.

• Support from the scientific staff to set the measurements schedule coincident with satellite overpasses

Application, testing, and validation of the user’s custom algorithm for lidar data processing and product retrievals based on lidar measurements from PANGEA instrumentation. The possibility to include testing of the algorithm based on simulated lidar signals (e.g. from an EARLINET algorithm intercomparison exercise) is also provided. 

The service includes:

• Provision of lidar measurements from PANGEA station

• Support in the processing and analysis of raw lidar data from the PANGEA instrumentation 

• Support in the algorithm testing/validation using simulated lidar signals