RESUMO
In this paper we present a technique for estimating optical backscatter and extinction profiles using lidar, which exploits the difference between the observed linear volume depolarization ratio at 355 nm and the corresponding expected aerosol-only depolarization ratio. The technique is specific to situations where a single strongly depolarizing species is present and the associated linear particulate depolarization ratio may be presumed to be known to within a reasonable degree of accuracy (on the order of 10%). The basic principle of the technique is extended to deal with situations where a depolarizing fraction is mixed with nondepolarizing aerosol. In general, since the relative depolarization interchannel calibration is much more stable than the absolute system calibration, the depolarization-based technique is easier to implement than conventional techniques that require a profile-by-profile calibration or, equivalently, an identification of aerosol-free altitude intervals. This in particular allows for unattended data analysis and makes the technique well-suited to be part of a broader (volcanic ash) surveillance system. The technique is demonstrated by applying it to the analysis of aerosol layers resulting from the 2010 eruptions of the Eyjafjallajökull volcano in Iceland. The measurements were made at the Cabauw remote-sensing site in the central Netherlands. By comparing the results of the depolarization-based inversion with a more conventional manual inversion procedure as well as Raman lidar results, it is demonstrated that the technique can be successfully applied to the particular case of 355 nm depolarization lidar volcanic ash soundings, including cases in which the ash is mixed with nondepolarizing aerosol.
RESUMO
A method is introduced to derive integral properties of the aerosol size distribution, e.g., aerosol mass, from tropospheric multiwavelength Raman lidar aerosol extinction and backscatter data, using an adapted form of the principal component analysis (PCA) technique. Since the refractive index of general tropospheric aerosols is variable and aerosol types can vary within one profile, an inversion technique applied in the troposphere should account for varying aerosol refractive indices. Using PCA, if a sufficiently complete set of appropriate refractive index dependent kernels is used, no a priori information about the aerosol type is necessary for the inversion of integral properties. In principle, the refractive index itself can be retrieved, but this quantity is more sensitive to measurement errors than the various integral properties of the aerosol size distribution. Here, the PCA technique adapted for use in the troposphere is introduced, the refractive index information content of the kernel sets is investigated, and error analyses are presented. The technique is then applied to actual tropospheric Raman lidar measurements.
RESUMO
In April 2020, several wildfires took place in and around the Chernobyl exclusion zone. These fires reintroduced radioactive particles deposited during the 1986 Chernobyl disaster into the atmosphere, causing concern about a possible radiation hazard. Several countries and several stations of the International Monitoring System measured increased Cs137 levels. This study presents the analyses made by RIVM and SCK CEN/RMI during the April 2020 wildfires. Furthermore, more in-depth research was performed after the wildfires. A statistical analysis of Cs137 detections is presented, comparing the April 2020 detections with historical detections. Inverse atmospheric transport modelling is applied to infer the total released Cs137 during the wildfires. Finally, it is assessed whether the Cs137 detections in Belgium and the Netherlands can be attributed to the wildfires.