[1] We present the first estimate of the global distribution of CO₂surface fluxes from 14 stations of the Total Carbon Column Observing Network (TCCON). The evaluation of this inversion is based on 1) comparison with the fluxes from a classical inversion of surface air‐sample‐measurements, and 2) comparison of CO₂mixing ratios calculated from the inverted fluxes with independent aircraft measurements made during the two years analyzed here, 2009 and 2010. The former test shows similar seasonal cycles in the northern hemisphere and consistent regional carbon budgets between inversions from the two datasets, even though the TCCON inversion appears to be less precise than the classical inversion. The latter test confirms that the TCCON inversion has improved the quality (i.e., reduced the uncertainty) of the surface fluxes compared to the assumed or prior fluxes. The consistency between the surface‐air‐sample‐based and the TCCON‐based inversions despite remaining flaws in transport models opens the possibility of increased accuracy and robustness of flux inversions based on the combination of both data sources and confirms the usefulness of space‐borne monitoring of the CO₂ column.

Kraków is routinely affected by very high air pollution levels, especially during the winter months. Although a lot of effort has been made to characterize ambient aerosol, there is a lack of online and long-term measurements of non-refractory aerosol. Our measurements at the AGH University of Science and Technology provide the online long-term chemical composition of ambient submicron particulate matter (PM₁) between January 2018 and April 2019. Here we report the chemical characterization of non-refractory submicron aerosol and source apportionment of the organic fraction by positive matrix factorization (PMF). In contrast to other long-term source apportionment studies, we let a small PMF window roll over the dataset instead of performing PMF over the full dataset or on separate seasons. In this way, the seasonal variation in the source profiles can be captured. The uncertainties in the PMF solutions are addressed by the bootstrap resampling strategy and the random a-value approach for constrained factors. We observe clear seasonal patterns in the concentration and composition of PM₁, with high concentrations during the winter months and lower concentrations during the summer months. Organics are the dominant species throughout the campaign. Five organic aerosol (OA) factors are resolved, of which three are of a primary nature (hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and coal combustion OA (CCOA)) and two are of a secondary nature (more oxidized oxygenated OA (MO-OOA) and less oxidized oxygenated OA (LO-OOA)). While HOA contributes on average 8.6 % ± 2.3 % throughout the campaign, the solid-fuel-combustion-related BBOA and CCOA show a clear seasonal trend with average contributions of 10.4 % ± 2.7 % and 14.1 %, ±2.1 %, respectively. Not only BBOA but also CCOA is associated with residential heating because of the pronounced yearly cycle where the highest contributions are observed during wintertime. Throughout the campaign, the OOA can be separated into MO-OOA and LO-OOA with average contributions of 38.4 % ± 8.4 % and 28.5 % ± 11.2 %, respectively.

Currently, the atmospheric methane burden is rising rapidly, but the extent to which shifts in coal production contribute to this rise is not known. Coalbed methane emissions into the atmosphere are poorly characterised, and this study provides representative δ¹³CCH₄ signatures of methane emissions from specific coalfields. Integrated methane emissions from both underground and opencast coal mines in the UK, Australia and Poland were sampled and isotopically characterised. Progression in coal rank and secondary biogenic production of methane due to incursion of water are suggested as the processes affecting the isotopic composition of coal-derived methane. An averaged value of −65 ‰ has been assigned to bituminous coal exploited in open cast mines and of −55 ‰ in deep mines, whereas values of −40 and −30 ‰ can be allocated to anthracite opencast and deep mines respectively. However, the isotopic signatures that are included in global atmospheric modelling of coal emissions should be region- or nation-specific, as greater detail is needed, given the wide global variation in coal type.

The paper shows wind shear impact on PM₁₀ vertical profiles in Kraków, southern Poland. The data used consist of background data for two cold seasons (September 2018 to April 2019 and September 2019 to April 2020) and data for several case studies from November 2019 to March 2020. The data are composed of PM₁₀ measurements, model data, and wind speed and direction data. The background model data come from operational forecast results of the AROME model. PM₁₀ concentration in the vertical profile was measured with a sightseeing balloon. Significant spatial variability of the wind field was found. The case studies represent the conditions with much lower wind speed and a much higher PM₁₀ level than the seasonal average. The inversions were much more frequent than on average too. Wind shear turned out to be the important factor in terms of PM₁₀ vertical profile modification. It is generated due to the relief impact, i.e. the presence of a large valley, blocked on one side with the hills. The analysis of PM₁₀ profiles from all flights allows us to distinguish three vertical zones of potential air pollution hazards within the valley (about 100 m deep) and the city of Kraków: (1) up to about 60 m a.g.l. – the zone where during periods of low wind speed, air pollution is potentially the highest and the duration of such high levels is the longest, i.e. the zone with the worst aerosanitary conditions; (2) about 60–100 m a.g.l. – transitional zone where the large decrease in PM₁₀ levels with height is observed; (3) above 100–120 m a.g.l. – the zone where air quality is significantly better than in zone 1, either due to the increase in the wind speed or due to the wind direction change and advection of different, clean air masses.