Abstract. Methane (CH4) emissions from coal production amount to roughly one-third of European anthropogenic CH4 emissions in the atmosphere. Poland is the largest hard coal producer in the European Union with the Polish side of the Upper Silesian Coal Basin (USCB) as the main part of it. Emission estimates for CH4 from the USCB for individual coal mine ventilation shafts range between 0.03 and 20 kt a−1, amounting to a basin total of roughly 440 kt a−1 according to the European Pollutant Release and Transfer Register (E-PRTR, http://prtr.ec.europa.eu/, 2014). We mounted a ground-based, portable, sun-viewing FTS (Fourier transform spectrometer) on a truck for sampling coal mine ventilation plumes by driving cross-sectional stop-and-go patterns at 1 to 3 km from the exhaust shafts. Several of these transects allowed for estimation of CH4 emissions based on the observed enhancements of the column-averaged dry-air mole fractions of methane (XCH4) using a mass balance approach. Our resulting emission estimates range from 6±1 kt a−1 for a single shaft up to 109±33 kt a−1 for a subregion of the USCB, which is in broad agreement with the E-PRTR reports. Three wind lidars were deployed in the larger USCB region providing ancillary information about spatial and temporal variability of wind and turbulence in the atmospheric boundary layer. Sensitivity studies show that, despite drawing from the three wind lidars, the uncertainty of the local wind dominates the uncertainty of the emission estimates, by far exceeding errors related to the XCH4 measurements themselves. Wind-related relative errors on the emission estimates typically amount to 20 %.

Abstract. We present lower/middle tropospheric columnaveraged CH 4 mole fraction time series measured by nine globally distributed ground-based FTIR (Fourier transform infrared) remote sensing experiments of the Network for the Detection of Atmospheric Composition Change (NDACC). We show that these data are well representative of the tropospheric regional-scale CH 4 signal, largely independent of the local surface small-scale signals, and only weakly dependent on upper tropospheric/lower stratospheric (UTLS) CH 4 variations. In order to achieve the weak dependency on the UTLS, we use an a posteriori correction method. We estimate a typical precision for daily mean values of about 0.5 % and a systematic error of about 2.5 %. The theoretical assessments are complemented by an extensive empirical study. For this purpose, we use surface in situ CH 4 measurements made within the Global Atmosphere Watch (GAW) network and compare them to the remote sensing data. We briefly discuss different filter methods for removing the local small-scale signals from the surface in situ data sets in order to obtain the in situ regional-scale signals. We find good agreement between the filtered in situ and the remote sensing data. The agreement is consistent for a variety of timescales that are interesting for CH 4 source/sink research: day-to-day, monthly, and inter-annual. The comparison study confirms our theoretical estimations and proves that the NDACC FTIR measurements can provide valuable data for investigating the cycle of CH 4 .Published by Copernicus Publications on behalf of the European Geosciences Union. E. Sepúlveda et al.: NDACC FTIR and GAW surface in situ tropospheric CH 4

Abstract. We report on the ground-based FTIR (Fourier transform infrared) tropospheric water vapour isotopologue remote sensing data that have been recently made available via the database of NDACC (Network for the Detection of Atmospheric Composition Change; ftp://ftp.cpc.ncep.noaa.gov/ndacc/MUSICA/) and via doi:10.5281/zenodo.48902. Currently, data are available for 12 globally distributed stations. They have been centrally retrieved and quality-filtered in the framework of the MUSICA project (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). We explain particularities of retrieving the water vapour isotopologue state (vertical distribution of H 16 2 O, H 18 2 O, and HD 16 O) and reveal the need for a new metadata template for archiving FTIR isotopologue data. We describe the format of different data components and give recommendations for correct data usage. Data are provided as two data types. The first type is best-suited for tropospheric water vapour distribution studies disregarding different isotopologues (comparison with radiosonde data, analyses of water vapour variability and trends, etc.). The second type is needed for analysing moisture pathways by means of {H 2 O, δD}-pair distributions.

Abstract. The thermal infrared nadir spectra of IASI (Infrared Atmospheric Sounding Interferometer) are successfully used for retrievals of different atmospheric trace gas profiles. However, these retrievals offer generally reduced information about the lowermost tropospheric layer due to the lack of thermal contrast close to the surface. Spectra of scattered solar radiation observed in the near and/or short wave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument) offer higher sensitivity near ground and are used for the retrieval of total column averaged mixing ratios of a variety of atmospheric trace gases. Here we present a method for the synergetic use of IASI profile and TROPOMI total column data. Our method uses the output of the individual retrievals and consists of linear algebra a posteriori calculations (i.e. calculation after the individual retrievals). We show that this approach is largely equivalent to applying the spectra of the different sensors together in a single retrieval procedure, but with the substantial advantage of being applicable to data generated with different individual retrieval processors, of being very time efficient, and of directly benefiting from the high quality and most recent improvements of the individual retrieval processors. We demonstrate the method exemplarily for atmospheric methane (CH4). We perform a theoretical evaluation and show that the a posteriori combination method yields a total column averaged CH4 product (XCH4) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the upper tropospheric and lower stratospheric (UTLS) CH4 partial column information of the corresponding IASI product. As consequence, the combined product offers in addition sensitivity for the tropospheric CH4 partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effects are verified by comparisons to CH4 reference data obtained from collocated XCH4 measurements at six globally distributed TCCON (Total Carbon Column Observing Network) stations, CH4 profile measurements made by 24 individual AirCore soundings, and lower tropospheric CH4 data derived from continuous ground-based in-situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. The comparisons clearly demonstrate that the combined product can reliably detect XCH4 signals and allows to distinguish between tropospheric and UTLS CH4 partial column averaged mixing ratios, which is not possible by the individual TROPOMI and IASI products. We find indications of a weak positive bias of about +1 % of the combined lower tropospheric data product with respect to the references. For the UTLS CH4 partial columns we find no significant bias.

Abstract. The objective of this study is to derive methane (CH4) emissions from three landfills, which are found to be the most significant CH4 sources in the metropolitan area of Madrid in Spain. We derive CH4 emissions from the CH4 enhancements observed by spaceborne and ground-based instruments. We apply satellite-based measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and the Infrared Atmospheric Sounding Interferometer (IASI) together with measurements from the ground-based COllaborative Carbon Column Observing Network (COCCON) instruments. In 2018, a 2-week field campaign for measuring the atmospheric concentrations of greenhouse gases was performed in Madrid in the framework of Monitoring of the Greenhouse Gases Concentrations in Madrid (MEGEI-MAD) project. Five COCCON instruments were deployed at different locations around the Madrid city center, enabling the observation of total column-averaged CH4 mixing ratios (XCH4). Considering the prevalent wind regimes, we calculate the wind-assigned XCH4 anomalies for two opposite wind directions. Pronounced bipolar plumes are found when applying the method to NO2, which implies that our method of wind-assigned anomaly is suitable to estimate enhancements of trace gases at the urban level from satellite-based measurements. For quantifying the CH4 emissions, the wind-assigned plume method is applied to the TROPOMI XCH4 and to the lower tropospheric CH4 / dry-air column ratio (TXCH4) of the combined TROPOMI+IASI product. As CH4 emission strength we estimate 7.4 × 1025 ± 6.4 × 1024 molec. s−1 from the TROPOMI XCH4 data and 7.1 × 1025 ± 1.0 × 1025 molec. s−1 from the TROPOMI+IASI merged TXCH4 data. We use COCCON observations to estimate the local source strength as an independent method. COCCON observations indicate a weaker CH4 emission strength of 3.7 × 1025 molec. s−1 from a local source (the Valdemingómez waste plant) based on observations from a single day. This strength is lower than the one derived from the satellite observations, and it is a plausible result. This is because the analysis of the satellite data refers to a larger area, covering further emission sources in the study region, whereas the signal observed by COCCON is generated by a nearby local source. All emission rates estimated from the different observations are significantly larger than the emission rates provided via the official Spanish Register of Emissions and Pollutant Sources.