Summer scenarios simulating impurity transport in the Baikal region are considered. The tracers’ distribution from the locations of forest wildfires in July-August 2019 is calculated with the ICM&MG SB RAS mesoscale model of atmospheric dynamics and admixture transport. The same meteorological scenarios are used to estimate the distribution of pollutants from emissions of boiler houses and thermal power plants in the region. The results demonstrate that smog from forest fires and industrial sources lead to the significant load on the atmosphere of the region.
The algorithm for source identification and concentration field reconstruction problems for an atmospheric chemistry transport and transformation model is tested with combined in situ and remote sensing data. It is based on the ensembles of the adjoint problem solutions and the sensitivity operators. Novosibirsk city traffic emissions inverse modeling scenario is used to test the algorithm.
The paper presents some results of a numerical scenario on pollutants dispersion in the south of the Lake Baikal region. We used the scenario approach and simulated the case corresponding to the late fall or early winter. At this time, in Eastern Siberia, low temperatures are established in the atmosphere and on the ground. However, Lake Baikal is not yet covered with ice: according to climatic data, ice cover appears only in January. Therefore, a situation arises when large temperature gradients between land and lake form in vast areas of the region. Under such conditions, we examined the formation of atmospheric circulation in the Baikal region. To describe the meteorological processes, we use a mesoscale model for the dynamics of the atmosphere, developed in ICMMG SB RAS. Performing the scenario, we use the results of the COSMO-SIB6 predictive mesoscale model to specify the initial distributions of meteorological fields. Based on hydrodynamic processes, we also simulated the processes of impurity propagation from the sources of the Irkutsk-Cheremkhovo industrial hub and other major industrial centers in the region. Under the conditions of the considered winter scenario with north-west background flow, the calculation results showed that the lightweight impurities from high sources at the enterprises of the region not only from Irkutsk, but also from more distant enterprises of the Angarsk complex can reach the water area of Lake Baikal.
KEYWORDS: In situ metrology, Remote sensing, Air contamination, Data modeling, Inverse problems, Atmospheric modeling, Atmospheric chemistry, Systems modeling, Chemical analysis
The results of the inverse source problem solution for an atmospheric chemistry transport and transformation model for in situ and remote sensing measurement data are compared. The algorithm based on the ensembles of the adjoint problem solutions is applied to solve the inverse problem. The solutions are compared in the Novosibirsk city inverse modeling scenario.
The work is focused on studying the features of local circulation formation and impurity transport processes in the Baikal region. To carry out the research, we use the basic numerical mesoscale model of the atmospheric dynamics and impurity transport in regions with complex relief, developed at the ICMMG SB RAS. On its basis, we created a special version of the model adapted to the climatic and orographic conditions of the region. The results of a numerical experiment on modeling the transport of a smoke tracer under the conditions of a summer meteorological scenario are presented.
The efficiency of the variational chemical data assimilation algorithm is evaluated in a scenario for the city of Novosibirsk. In the algorithm the data assimilation is carried out quasi-independently on the different stages of the splitting scheme of the chemical transport model. RADM2 chemical reaction scheme is selected as the atmospheric chemistry reaction mechanism. Monitoring data is available in the limited number of the monitoring sites and for the limited number of species.
The verification of the results of numerical simulation of the distribution of anthropogenic emissions of the Norilsk industrial zone using the WRF-CHEM model using airborne sounding data carried out in 13 August 2004 was carried out. The results of numerical modelling of the distribution of the concentration of sulphur dioxide, ozone and mass concentration of aerosol reproduce qualitatively the distributions obtained during airborne sounding. Quantitative estimates showed that the root-mean-square error for sulphur dioxide, the mass concentration of aerosol PM2.5 and ozone, calculated for all three flights, was 36 ppb, 3.4 μg/m3, 7.7 ppb, respectively.
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