Global climate change is one of the most important scientific, societal and economic contemporary challenges. Fundamental understanding of the major processes driving climate change is the key problem which is to be solved not only on a global but also on a regional scale. The accuracy of regional climate modelling depends on a number of factors. One of these factors is the adequate and comprehensive information on the anthropogenic impact which is highest in industrial regions and areas with dense population – modern megacities. Megacities are not only “heat islands”, but also significant sources of emissions of various substances into the atmosphere, including greenhouse and reactive gases. In 2019, the mobile experiment EMME (Emission Monitoring Mobile Experiment) was conducted within the St. Petersburg agglomeration (Russia) aiming to estimate the emission intensity of greenhouse (CO₂, CH₄) and reactive (CO, NO_x) gases for St. Petersburg, which is the largest northern megacity. St. Petersburg State University (Russia), Karlsruhe Institute of Technology (Germany) and the University of Bremen (Germany) jointly ran this experiment. The core instruments of the campaign were two portable Bruker EM27/SUN Fourier transform infrared (FTIR) spectrometers which were used for ground-based remote sensing measurements of the total column amount of CO₂, CH₄ and CO at upwind and downwind locations on opposite sides of the city. The NO₂ tropospheric column amount was observed along a circular highway around the city by continuous mobile measurements of scattered solar visible radiation with an OceanOptics HR4000 spectrometer using the differential optical absorption spectroscopy (DOAS) technique. Simultaneously, air samples were collected in air bags for subsequent laboratory analysis. The air samples were taken at the locations of FTIR observations at the ground level and also at altitudes of about 100 m when air bags were lifted by a kite (in case of suitable landscape and favourable wind conditions). The entire campaign consisted of 11 mostly cloudless days of measurements in March–April 2019. Planning of measurements for each day included the determination of optimal location for FTIR spectrometers based on weather forecasts, combined with the numerical modelling of the pollution transport in the megacity area. The real-time corrections of the FTIR operation sites were performed depending on the actual evolution of the megacity NO_x plume as detected by the mobile DOAS observations. The estimates of the St. Petersburg emission intensities for the considered greenhouse and reactive gases were obtained by coupling a box model and the results of the EMME observational campaign using the mass balance approach. The CO₂ emission flux for St. Petersburg as an area source was estimated to be 89 ± 28 $\mathrm{kt}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ , which is 2 times higher than the corresponding value in the EDGAR database. The experiment revealed the CH₄ emission flux of 135 ± 68 $\mathrm{t}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ , which is about 1 order of magnitude greater than the value reported by the official inventories of St. Petersburg emissions (∼ 25 $\mathrm{t}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ for 2017). At the same time, for the urban territory of St. Petersburg, both the EMME experiment and the official inventories for 2017 give similar results for the CO anthropogenic flux (251 ± 104 $\mathrm{t}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ vs. 410 $\mathrm{t}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ ) and for the NO_x anthropogenic flux (66 ± 28 $\mathrm{t}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ vs. 69 $\mathrm{t}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ ).

The observed ozone layer depletion is influenced by continuous anthropogenic activity. This fact enforced the regular ozone monitoring globally. Information on spatial-temporal variations in total ozone columns (TOCs) derived by various observational methods and models can differ significantly due to measurement and modelling errors, differences in ozone retrieval algorithms, etc. Therefore, TOC data derived by different means should be validated regularly. In the current study, we compare TOC variations observed by ground-based (Bruker IFS 125 HR, Dobson, and M-124) and satellite (OMI, TROPOMI, and IKFS-2) instruments and simulated by models (ERA5 and EAC4 re-analysis, EMAC and INM RAS—RSHU models) near St. Petersburg (Russia) between 2009 and 2020. We demonstrate that TOC variations near St. Petersburg measured by different methods are in good agreement (with correlation coefficients of 0.95–0.99). Mean differences (MDs) and standard deviations of differences (SDDs) with respect to Dobson measurements constitute 0.0–3.9% and 2.3–3.7%, respectively, which is close to the actual requirements of the quality of TOC measurements. The largest bias is observed for Bruker 125 HR (3.9%) and IKFS-2 (−2.4%) measurements, whereas M-124 filter ozonometer shows no bias. The largest SDDs are observed for satellite measurements (3.3–3.7%), the smallest—for ground-based data (2.3–2.8%). The differences between simulated and Dobson data vary significantly. ERA5 and EAC4 re-analysis data show slight negative bias (0.1–0.2%) with SDDs of 3.7–3.9%. EMAC model overestimates Dobson TOCs by 4.5% with 4.5% SDDs, whereas INM RAS-RSHU model underestimates Dobson by 1.4% with 8.6% SDDs. All datasets demonstrate the pronounced TOC seasonal cycle with the maximum in spring and minimum in autumn. Finally, for 2004–2021 period, we derived a significant positive TOC trend near St. Petersburg (~0.4 ± 0.1 DU per year) from all datasets considered.

Monitoring atmospheric anthropogenic halocarbons plays an important role in tracking their atmospheric concentrations in accordance with international agreements on emissions of ozone-depleting substances and, thus, in estimating the ozone layer recovery. Within the Network for the Detection of Atmospheric Composition Change (NDACC), regular Fourier transform infrared (FTIR) measurements can provide information on the abundancies of halocarbons on a global scale. We improved retrieval strategies for deriving the CFC-11 (CCl₃F), CFC-12 (CCl₂F₂), and HCFC-22 (CHClF₂) atmospheric columns from IR solar radiation spectra measured by the Bruker IFS125HR spectrometer at the St. Petersburg site (Russia). We used the Tikhonov–Phillips regularization approach for solving the inverse problem with optimized values of regularization parameters. We tested the strategies developed by comparison of the FTIR measurements with independent data. The analysis of the time series of column-averaged dry air mole fractions (Xgas) measured in 2009–2019 gives mean values of 225 pptv (parts per trillion by volume; CFC-11), 493 pptv (CFC-12), and 238 pptv (HCFC-22). Trend values total −0.40 % yr⁻¹ (CFC-11), −0.49 % yr⁻¹ (CFC-12), and 2.12 % yr⁻¹ (HCFC-22). We compared the means, trends, and seasonal variability in X_CFC-11, X_CFC-12, and X_HCFC-22 to that of (1) near-ground volume mixing ratios (VMRs), measured at the observational site Mace Head, Ireland (GVMR), (2) the mean in the 8–12 km layer VMRs, measured by ACE-FTS and averaged over 55–65^∘ N latitudes (SVMR), and (3) Xgas values of the Whole Atmosphere Community Climate Model (WACCM) for the St. Petersburg site (WXgas). In general, the comparison of Xgas with the independent data showed a good agreement of their means within the systematic errors of the measurements considered. The trends observed over the St. Petersburg site demonstrate the smaller decrease rates for X_CFC-11 and X_CFC-12 than that of the independent data and the same increase rate for X_HCFC-22. As a whole, Xgas, SVMR, and WXgas showed qualitatively similar seasonal variations, while the GVMR variability is significantly less, and only the WX_HCFC-22 variations are essentially smaller than that of X_HCFC-22 and SVMR_HCFC-22.