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Inverse modeling is a widely used top-down method to infer greenhouse gas (GHG) emissions and their spatial distribution based on atmospheric observations. The errors associated with inverse modeling have multiple sources, such as observations and a-priori emission estimates, but they are often dominated by the transport model error. Here, we utilize the Lagrangian Particle Dispersion Model (LPDM) FLEXPART, driven by the meteorological fields of the regional numerical weather prediction model COSMO. The main source of errors in LPDMs is the turbulence diffusion parameterization and the meteorological fields. The latter are outputs of an Eulerian model. Recently, we introduced an improved parameterization scheme of the turbulence diffusion in FLEXPART, which significantly improves FLEXPART-COSMO simulations at 1 km resolution. We exploit F-gases measurements from two extended field campaigns on the Swiss Plateau (in Beromünster and Sottens) and we conduct both high- (1 km) and low-resolution (7 km) FLEXPART transport simulations that are then used in a Bayesian analytical inversion to estimate spatial emission distributions. Our results for four F-gases (HFC-134a, HFC-125, HFC-32, SF6) indicate that both high-resolution inversions and a dense measurement network significantly improve the ability to estimate the spatial distribution of emissions. Furthermore, the total emission estimates from the high-resolution inversions (351±44 Mg yr−1 for HFC-134a, 101±21 Mg yr−1 for HFC-125, 50±8 Mg yr−1 for HFC-32, 9.0±1.1 Mg yr−1 for SF6) are significantly higher compared to the low-resolution inversions (20–40 % increase) and result in total a-posteriori emission estimates that are closer to national inventory values as reported to the UNFCCC (10–20 % difference between high-resolution inversion estimates and inventory values compared to 30–40 % difference between the low-resolution inversion estimates and inventory values). Specifically, we attribute these improvements to a better representation of the atmospheric flow in complex terrain in the high-resolution model, partly induced by the more realistic topography. We further conduct numerous sensitivity inversions, varying different parameters and variables of our Bayesian inversion framework to explore the whole range of uncertainty in the inversion errors (e.g., inversion grid, spatial distribution of a-priori emissions, covariance parameters like baseline uncertainty and spatial correlation length, temporal resolution of the assimilated observations, observation network, seasonality of emissions). From the above-mentioned parameters, we find that the uncertainty of the mole fraction baseline and the spatial distribution of the a-priori emissions have the largest impact on the a-posteriori total emission estimates and their spatial distribution. This study is a step towards mitigating the errors associated with the transport models and better characterizing the uncertainty inherent in the inversion error. Improvements in the latter will facilitate the validation and standardization of the national GHG emission inventories and support policymakers.

Human-made halocarbons contribute about 11 % of the anthropogenically caused radiative forcing by long-lived greenhouse gases. Moreover, chlorinated or brominated halocarbons cause stratospheric ozone depletion. Synthetic halocarbons are emitted to the atmosphere by a wide range of production or consumption-related activities, being used as foam blowing, cooling, or fire extinguishing agents for example. To derive observation-based estimates of halocarbon emissions so-called "top-down" inverse modeling methods have been developed. These methods rely on global atmospheric observations from long-term halocarbon measurement networks such as the Advanced Global Atmospheric Gases Experiment (AGAGE) and the National Oceanic and Atmospheric Administration (NOAA). However, to assess halocarbon emissions on a country to regional level and to complement national emission inventories by top-down methods, measurements are required, which capture regional pollution events.We present 18 months of continuous, high-frequency, high-precision halocarbon measurements from the Beromünster and Sottens tall towers (Swiss Plateau). Together, the two sites are sensitive to the most densely populated and industrialized region of Switzerland and parts of southeastern France. For analysis, hourly two-liter air samples were pre-concentrated at low temperatures (down to -165 oC), before the analytes were separated by gas chromatography and detected by quadrupole mass spectrometry (GC-MS).Based on the measured concentration records, we assessed Swiss emissions and source regions of 28 halocarbons, covering the halocarbons of the Montreal and Kyoto Protocols. This includes the banned chlorofluorocarbons (CFCs) and halons, the regulated hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs), as well as the recently introduced unregulated hydrofluoroolefins (HFOs). The emissions were quantified using two independent top-down methods: a tracer ratio method and a Bayesian inversion based on regional atmospheric transport modeling.We found good agreement between our top-down results and the emissions reported in the Swiss national greenhouse gas inventory for the major HFCs, HFC-125 and HFC-32, for which we calculated emissions of 100 Mg yr-1 and 45 Mg yr-1, respectively. For HFC-134a, our calculated emissions of 280 Mg yr-1 hint at an overestimation of the Swiss national inventory. For the CFCs and HCFCs, we observed moderately elevated atmospheric concentrations with the corresponding emissions likely being related to the ongoing outgassing from existing banks. For the recently phased-in HFOs HFO-1234yf, HFO-1234ze(E), and HCFO-1233zd(E), we report the first national emission numbers, totaling to 56 Mg yr-1. In addition, we present the first quantitative atmospheric measurements of the newly marketed HFO-1336mzz(Z), belonging to the group of emerging unsaturated halocarbons, of which the future environmental impacts are yet unclear.To continue resolving the picture for Europe, another 6 months (December 2021 to May 2022) measurement campaign is currently being conducted in the Netherlands. The aim is to investigate local halocarbon emissions and locate regional emission sources with the above-described methods.

Atmospheric inverse modelling is a ’top-down’ emission estimation method, which utilises numerical models to estimate emissions from observed and simulated concentrations of atmospheric compounds. Inverse emission modelling can be applied for the support of emission inventories and emission reporting, which are usually based on ’bottom-up’ methods. The latter employ activity data and emission factors for the relevant processes. Depending on the emitting process, both may be afflicted by large uncertainties, especially when spatially-resolved emissions are considered on sub-national scales. Inverse modelling offers an alternative tool to emission estimation, validation and optimization of emission inventories. It is widely used by the scientific community for different atmospheric compounds and from global to the facility scale.Atmospheric inversions can be carried out by combining source sensitivities simulated by atmospheric transport models, observations, and an inversion framework. Here, we focus on emissions of synthetic greenhouse gases (GHG) in the Swiss domain. 'Bottom-up' estimates of these emissions are connected to large uncertainties in the leakage rates of these compounds from various applications (e.g., refrigeration, foam blowing). Globally, synthetic GHGs account for a considerable fraction of the total anthropogenic radiative forcing (~10%), and their future environmental impact depends on the replacement of compounds with long lifetimes by compounds with short lifetimes and minimal global warming potential (GWP). In Switzerland, synthetic GHGs contribute about 3.5% to national total GHG emissions according to bottom-up reporting.Newly available synthetic gases observations, collected as part of the Swiss project IHALOME (Innovation in Halocarbon Measurements and Emission Validation), from the Swiss Plateau at the Beromünster and Sottens tall towers, allow us to localise and quantify the emissions in Switzerland and in the neighboring countries. We apply the Lagrangian Particle Dispersion Model (LPDM) FLEXPART, driven by meteorological fields of the Numerical Weather Prediction (NWP) model COSMO, at two different spatial resolutions (7 km x 7 km and 1 km x 1 km). During the last decade, FLEXPART-COSMO was successfully operated at 7 km x 7 km spatial resolution to estimate Swiss emissions of methane and nitrous oxide. Reliable simulations at 1 km x 1 km resolution were recently established and required an update of FLEXPART-COSMO's turbulence scheme.Inversion results for the most important (by emissions) synthetic GHGs (HFCs and SF6) are presented. Special attention is given to comparisons between inversions for different transport model resolutions and the question if the high resolution simulations are able to enhance the capability of the inversion method to localise emissions. Additionally, the sensitivity of the inversions to different a priori emission fields is presented. Finally, the sensitivity of the inversion towards covariance parameters, either obtained from maximum likelihood optimisation or from expert judgment, is examined. Inversions with the high resolution model amplify the emission differences between the Swiss Plateau and the high altitude regions in the Alps by both increasing the emissions in the big cities and decreasing the emissions in the high altitude regions. At the same time, no significant difference in total national emissions is observed between high and low resolution model inversions.

Halocarbons are emitted by various anthropogenic activities to the atmosphere, where they contribute to global warming and stratospheric ozone-depletion. To determine national halocarbon emissions, the so-called "top-down" approach relies on atmospheric observations, at sites that reflect emissions on a country level, and com-bines these observations with inverse modelling methods. In this study, we present 12 months (September 2019 to September 2020) of continuous atmospheric observations of 28 halocarbons from a measurement campaign at the Beromünster tall tower in Switzerland. The site is sensitive to the most densely populated area of Switzer-land, the Swiss Plateau, thus the measurements were well suited to derive Swiss halocarbon emissions. Emissions were calculated by two different top-down methods, a tracer-ratio method (TRM) with carbon monoxide (CO) as the independent tracer, and a Bayesian inversion (BI), based on atmospheric transport simulations using FLEXPART–COSMO. The results were compared to previously reported top-down emission estimates, based on measurements at the high-Alpine site Jungfraujoch, and to the "bottom-up" Swiss national greenhouse gas (GHG) inventory, as annually reported to the United Nations Framework Convention on Climate Change (UN-FCCC). We observed ongoing outgassing from existing foams and refrigerators for the ozone-depleting, banned chlorofluorocarbons (CFCs) and the regulated hydrochlorofluorocarbons (HCFCs), confirming their large historical use. For the major hydrofluorocarbons (HFCs) HFC-125 (CHF2CF3) and HFC-32 (CH2F2), our calcu-lated emissions of 99 ± 29 Mg yr−1 and 46 ± 13 Mg yr−1 were in good agreement with the national Swiss inventory values, whereas for HFC 134a (CH2FCF3) our result of 300 ± 85 Mg yr−1 was about 30 % lower than the UNFCCC reported value. For the other investigated HFCs, perfluorocarbons (PFCs), SF6 and NF3, emissions were small and in agreement with the inventory. Finally, we report the first country-based emission estimates of a total of 50 Mg yr−1 for three recently phased-in, unregulated hydrofluoroolefins (HFOs), HFO 1234yf (CF3CF=CH2), HFO-1234ze(E) ((E)-CF3CH=CHF) and HCFO-1233zd(E) ((E) CF3CH=CHCl).

Synthetic halocarbons reach the atmosphere due to a wide range of anthropogenic activities. They are, for example, used as propellants in foam blowing or as cooling agents in refrigeration and air conditioning. Long-lived halocarbons act as strong greenhouse gases. They are responsible for about 11% of the radiative forcing by long-lived greenhouse gases (LLGHGs). In addition, chlorinated or brominated halocarbons contribute to stratospheric ozone depletion. There are only two in situ long-term measurement programs, operated by the Advanced Global Atmospheric Gases Experiment (AGAGE) and the National Oceanic and Atmospheric Administration (NOAA) that monitor the worldwide abundance of halocarbons in the atmosphere. Based on these observations, halocarbon emissions are estimated by top-down box- or inverse modelling approaches on a global to transnational scale. However, to capture regional pollution sources and to validate country-specific bottom-up emission estimates by top-down methods, additional regional-scale measurements are required.We present the first continuous halocarbon measurements at the Beromünster tall tower, representing the most industrialized and densely populated area of Switzerland, the Swiss Plateau. During one year, high precision, high accuracy atmospheric measurements were performed with the analytical setup of the global AGAGE network. This involves sample pre-concentration at low temperatures (down to -180 oC), and analyte separation and detection by gas chromatography and quadrupole mass spectrometry. All halocarbon compound classes of the Montreal and Kyoto Protocols are covered by our measurements. This includes the banned chlorofluorocarbons (CFCs) and halons, the regulated hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs), as well as the recently introduced unregulated hydrochfluoroolefins (HFOs). The results improve our understanding of important source areas in Switzerland, and, for the first time offer the possibility to robustly quantify Swiss national halocarbon emissions with observation-based top-down methods, i.e. the tracer ratio method and Bayesian inverse modeling.

Synthetic greenhouse gases contribute currently about 10% to anthropogenic radiative forcing, and their future impact depends on the replacement of compounds with long lifetimes by compounds with short lifetimes and negligible global warming potential (GWP). Furthermore, chlorine and bromine-containing synthetic gases are the drivers of stratospheric ozone destruction. Therefore, observing the atmospheric abundance of synthetic gases and quantifying their emission sources is critical for predicting their related future impacts and assuring successful regulation.Regional-scale atmospheric inverse modeling can provide observation-based estimates of greenhouse gas emissions at a country and continental scale and, consequently, support the process of forecasting and regulation. Inverse modeling is based on three main components: Source sensitivities derived from atmospheric transport models, observations, and an inversion framework. Within the Swiss National Science Foundation project IHALOME (Innovation in Halocarbon Measurements and Emission Validation) we increase the spatial resolution of the Lagrangian particle dispersion model FLEXPART-COSMO from 7 km to 1 km in order to enhance localization of Swiss halocarbon emissions based on newly available observations from the Swiss Plateau at the Beromünster tall tower. The transport model is driven by the meteorological fields of the regional numerical weather prediction model (NWP) COSMO run at MeteoSwiss.The higher-resolution model exhibits increased three-dimensional dispersion, and as a result, is unable to reproduce the variability seen in the observations and in the 7 km model at the tall tower site Beromünster for a well-studied validation tracer (methane). Because the TKE (Turbulent Kinetic Energy) values do not differ significantly between the two model versions, head-to-head comparisons of parameterized turbulence cannot fully explain the concentration discrepancies. Comparisons of wind fluctuations resolved on the grid-scale suggest that the dispersion differences may originate from a duplication of turbulent transport, on the one hand, covered by the high-resolution grid of the Eulerian model and, on the other hand diagnosed by FLEXPART's turbulence scheme. In an attempt to tune FLEXPART-COSMO’s turbulence scheme at high resolution, we scale FLEXPART's parameterized turbulence so it matches the TKE computed in COSMO. Test simulations with the scaled FLEXPART turbulence show remarkable improvements in the high-resolution model's ability to predict the observed tracer variability and concentration at the Beromünster tall tower. We further introduce new equations in FLEXPART's turbulence scheme for each component of the variations of the winds in order to mimic the TKE produced by the turbulence scheme of COSMO and hence resolve the part of the turbulence spectrum which is unresolved by the high-resolution model. Compared to the coarse resolution simulations, simulations with scaled turbulence result in a more realistic and pronounced diurnal cycle of the tracer and overall improved correlation with observations.Concluding, the increasing resolution of NWP models may lead to the representation of the part of the turbulence spectrum by the models themselves. In these models, big eddies (most likely related to convection) are partly resolved and do not require additional parameterization. The turbulence schemes of the past, developed for coarse resolution models, should be revisited to include this effect.

Climate change is one of the biggest challenges of the modern era. Halocarbons contribute already about 14% to current anthropogenic radiative forcing, and their future impact may become significantly larger due to their long atmospheric lifetimes and continued and increasing usage. In addition to their influence on climate change, chlorine and bromine-containing halocarbons are the main drivers of the destruction of the stratospheric ozone layer. Therefore, observing their atmospheric abundance and quantifying their sources is critical for predicting the related future impact on climate change and on the recovery of the stratospheric ozone layer.Regional scale atmospheric inverse modelling can provide observation-based estimates of greenhouse gas emissions at a country scale and, hence, makes valuable information available to policy makers when reviewing emission mitigation strategies and confirming the countries' pledges for emission reduction. Considering that inverse modelling relies on accurate atmospheric transport modelling any advances to the latter are of key importance. The main objective of this work is to characterize and improve the Lagrangian particle dispersion model (LPDM) FLEXPART-COSMO at kilometer-scale resolution and to provide estimates of Swiss halocarbon emissions by integrating newly available halocarbon observations from the Swiss Plateau at the Beromünster tall tower. The transport model is offline coupled with the regional numerical weather prediction model (NWP) COSMO. Previous inverse modelling results for Swiss greenhouse gases are based on a model resolution of 7 km x 7 km. Here, we utilize higher resolution (1 km x 1 km) operational COSMO analysis fields to drive FLEXPART and compare these to the previous results.The higher resolution simulations exhibit increased three-dimensional dispersion, leading to a general underestimation of observed tracer concentration at the receptor location and when compared to the coarse model results. The concentration discrepancies due to dispersion between the two model versions cannot be explained by the parameters utilized in FLEPXART’s turbulence parameterization, (Obhukov length, surface momentum and heat fluxes, atmospheric boundary layer heights, and horizontal and vertical wind speeds), since a direct comparison of these parameters between the different model versions showed no significant differences. The latter suggests that the dispersion differences may originate from a duplication of turbulent transport, on the one hand, covered by the high resolution grid of the Eulerian model and, on the other hand, diagnosed by FLEXPART's turbulence scheme. In an attempt to reconcile FLEXPART-COSMO’s turbulence scheme at high resolution, we introduced additional scaling parameters based on analysis of simulated mole fraction deviations depending on stability regime. In addition, we used FLEXPART-COSMO source sensitivities in a Bayesian inversion to obtain optimized emission estimates. Inversions for both the high and low resolution models were carried out in order to quantify the impact of model resolution on posterior emissions and estimate about the uncertainties of these emissions.