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Atmospheric nitric acid (HNO3) has a significant impact on the formation of the ozone layer; therefore, its content is regularly monitored using various local and remote-sensing methods. We used ground-based measurements of solar IR spectra with a Bruker 125HR Fourier spectrometer to derive information on the HNO3 content at the St.Petersburg observational NDACC site in Peterhof. The HNO3 time series obtained showed a pronounced seasonal cycle with a maximum in winter and early spring and a minimum in summer and early autumn. The averaged seasonal variations in nitric acid varied from –30 to +60% for the 0–15 km layer, from –25 to +25% for the 15–50 km layer, and from –25 to +30% for total columns. For 2009–2022 measurement period, no statistically significant trend was found in the time series considered. Comparison of HNO3 stratospheric columns with independent satellite measurements by the MLS and ACE-FTS instruments showed their qualitative and quantitative agreement; the correlation coefficient between ground-based and satellite measurements totals 0.88–0.93. Time series on the vertical structure of the atmospheric nitric acid measured at the St.Petersburg site can be used both to analyze the state of the ozonosphere and to validate satellite measurements and refine the parameters of atmospheric models.

Due to the increase in CO2 content in the Earth's atmosphere, which is highly dependent on anthropogenic emissions of CO2, quality of emission estimation should be improved. Advanced experiment-based methods of the CO2 anthropogenic emission estimation are built on solution of an inverse problem using highly-accurate measurements of CO2 content and numerical models of transport and chemistry in the atmosphere. The accuracy of such models greatly determines errors of the emission estimations. In a current study temporal variations of column-average CO2 content in an atmospheric layer from surface to the height of ~70–75 km (XCO2) in the Russian megapolis of St. Petersburg during Jan 2019–Mar 2020 simulated by WRF-Chem model and measured by IR Fourier-transform spectrometer Bruker EM27/SUN are compared. The research has demonstrated that the WRF-Chem model simulates well the observed temporal variation of XCO2 in the area of St. Petersburg (correlation coefficient of ~0.95). However, using CarbonTracker v2022-1 data as chemical boundary conditions, the model overestimates XCO2 relative to the observations significantly during almost the whole period of investigation – systematic difference and standard deviation of the difference are 4.2 and 1.9 ppm (1 and 0.5%). A correction of the chemical boundary conditions which is based on analysis of a relation between near-surface wind direction and XCO2 variation notably decreases the systematic difference between the modelled and observed data (almost by a factor of 2). The XCO2 variation by the observations and modelling with uncorrected chemical boundary conditions are in a better agreement during vegetation season. Probably this is related to the compensation of the systematic difference by inaccuracies in estimated biogenic contribution. Hence, the reason of the still existing mean difference between the modelled and observed data can be inaccuracies in setting chemical boundary conditions for upper troposphere and in estimating how biosphere influences CO2 content.

The results of studying spatial-temporal CO2 variations near St. Petersburg during 2014–2017 based on satellite measurements (OSO-2 satellite), ground-based spectroscopic and local measurements are presented. According to satellite data the full amplitude of the spatial-temporal variations for the average CO2 mixing ratio (XCO2) amounted to 57.7 ppm (over 14%). The maximal XCO2 spatial variations during one day of observations (17.03.2015) were 46.8 ppm (more than 10%). Comparison of CO2 satellite and ground-based spectroscopic measurements has shown that ground-based measurements in the NDACC observing system after correction of systematic differences from the TCCON system can be used for validation of satellite measurements. Ground-based local measurements of the near-surface CO2 mixing ratio at Peterhof do not correlate with either spectroscopic ground-based or satellite measurements due to both mesoscale CO2 variations and significantly different spatial averaging kernels of direct and remote measurements.