The Tropospheric Ozone Assessment Report (TOAR) is an activity of the International Global Atmospheric Chemistry Project. This paper is a component of the report, focusing on the present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation. Utilizing the TOAR surface ozone database, several figures present the global distribution and trends of daytime average ozone at 2702 non-urban monitoring sites, highlighting the regions and seasons of the world with the greatest ozone levels. Similarly, ozonesonde and commercial aircraft observations reveal ozone’s distribution throughout the depth of the free troposphere. Long-term surface observations are limited in their global spatial coverage, but data from remote locations indicate that ozone in the 21st century is greater than during the 1970s and 1980s. While some remote sites and many sites in the heavily polluted regions of East Asia show ozone increases since 2000, many others show decreases and there is no clear global pattern for surface ozone changes since 2000. Two new satellite products provide detailed views of ozone in the lower troposphere across East Asia and Europe, revealing the full spatial extent of the spring and summer ozone enhancements across eastern China that cannot be assessed from limited surface observations. Sufficient data are now available (ozonesondes, satellite, aircraft) across the tropics from South America eastwards to the western Pacific Ocean, to indicate a likely tropospheric column ozone increase since the 1990s. The 2014–2016 mean tropospheric ozone burden (TOB) between 60°N–60°S from five satellite products is 300 Tg ± 4%. While this agreement is excellent, the products differ in their quantification of TOB trends and further work is required to reconcile the differences. Satellites can now estimate ozone’s global long-wave radiative effect, but evaluation is difficult due to limited in situ observations where the radiative effect is greatest.

From the earliest observations of ozone in the lower atmosphere in the 19th century, both measurement methods and the portion of the globe observed have evolved and changed. These methods have different uncertainties and biases, and the data records differ with respect to coverage (space and time), information content, and representativeness. In this study, various ozone measurement methods and ozone datasets are reviewed and selected for inclusion in the historical record of background ozone levels, based on relationship of the measurement technique to the modern UV absorption standard, absence of interfering pollutants, representativeness of the well-mixed boundary layer and expert judgement of their credibility. There are significant uncertainties with the 19th and early 20th-century measurements related to interference of other gases. Spectroscopic methods applied before 1960 have likely underestimated ozone by as much as 11% at the surface and by about 24% in the free troposphere, due to the use of differing ozone absorption coefficients.There is no unambiguous evidence in the measurement record back to 1896 that typical mid-latitude background surface ozone values were below about 20 nmol mol–1, but there is robust evidence for increases in the temperate and polar regions of the northern hemisphere of 30–70%, with large uncertainty, between the period of historic observations, 1896–1975, and the modern period (1990–2014). Independent historical observations from balloons and aircraft indicate similar changes in the free troposphere. Changes in the southern hemisphere are much less. Regional representativeness of the available observations remains a potential source of large errors, which are difficult to quantify.The great majority of validation and intercomparison studies of free tropospheric ozone measurement methods use ECC ozonesondes as reference. Compared to UV-absorption measurements they show a modest (~1–5% ±5%) high bias in the troposphere, but no evidence of a change with time. Umkehr, lidar, and FTIR methods all show modest low biases relative to ECCs, and so, using ECC sondes as a transfer standard, all appear to agree to within one standard deviation with the modern UV-absorption standard. Other sonde types show an increase of 5–20% in sensitivity to tropospheric ozone from 1970–1995.Biases and standard deviations of satellite retrieval comparisons are often 2–3 times larger than those of other free tropospheric measurements. The lack of information on temporal changes of bias for satellite measurements of tropospheric ozone is an area of concern for long-term trend studies.

Perilipin is the most abundant adipocyte-specific protein that coats lipid droplets, and it is required for optimal lipid incorporation and release from the droplet. We identified two heterozygous frameshift mutations in the perilipin gene (PLIN1) in three families with partial lipodystrophy, severe dyslipidemia, and insulin-resistant diabetes. Subcutaneous fat from the patients was characterized by smaller-than-normal adipocytes, macrophage infiltration, and fibrosis. In contrast to wild-type perilipin, mutant forms of the protein failed to increase triglyceride accumulation when expressed heterologously in preadipocytes. These findings define a novel dominant form of inherited lipodystrophy and highlight the serious metabolic consequences of a primary defect in the formation of lipid droplets in adipose tissue.

TROPOMI (the TROPOspheric Monitoring Instrument), on board the Sentinel-5 Precursor (S5P) satellite, has been monitoring the Earth's atmosphere since October 2017 with an unprecedented horizontal resolution (initially 7 km²×3.5 km², upgraded to 5.5 km²×3.5 km² in August 2019). Monitoring air quality is one of the main objectives of TROPOMI; it obtains measurements of important pollutants such as nitrogen dioxide, carbon monoxide, and formaldehyde (HCHO). In this paper we assess the quality of the latest HCHO TROPOMI products versions 1.1.(5-7), using ground-based solar-absorption FTIR (Fourier-transform infrared) measurements of HCHO from 25 stations around the world, including high-, mid-, and low-latitude sites. Most of these stations are part of the Network for the Detection of Atmospheric Composition Change (NDACC), and they provide a wide range of observation conditions, from very clean remote sites to those with high HCHO levels from anthropogenic or biogenic emissions. The ground-based HCHO retrieval settings have been optimized and harmonized at all the stations, ensuring a consistent validation among the sites. In this validation work, we first assess the accuracy of TROPOMI HCHO tropospheric columns using the median of the relative differences between TROPOMI and FTIR ground-based data (BIAS). The pre-launch accuracy requirements of TROPOMI HCHO are 40 %–80 %. We observe that these requirements are well reached, with the BIAS found below 80 % at all the sites and below 40 % at 20 of the 25 sites. The provided TROPOMI systematic uncertainties are well in agreement with the observed biases at most of the stations except for the highest-HCHO-level site, where it is found to be underestimated. We find that while the BIAS has no latitudinal dependence, it is dependent on the HCHO concentration levels: an overestimation ($+\mathrm{26}\pm \mathrm{5}$ %) of TROPOMI is observed for very low HCHO levels ($<\mathrm{2.5}\times {\mathrm{10}}^{\mathrm{15}}$ molec. cm⁻²), while an underestimation ($-\mathrm{30.8}\mathit{\%}\pm \mathrm{1.4}$ %) is found for high HCHO levels ($>\mathrm{8.0}\times {\mathrm{10}}^{\mathrm{15}}$ molec. cm⁻²). This demonstrates the great value of such a harmonized network covering a wide range of concentration levels, the sites with high HCHO concentrations being crucial for the determination of the satellite bias in the regions of emissions and the clean sites allowing a small TROPOMI offset to be determined. The wide range of sampled HCHO levels within the network allows the robust determination of the significant constant and proportional TROPOMI HCHO biases (TROPOMI $=+\mathrm{1.10}\pm \mathrm{0.05}$ $\times {\mathrm{10}}^{\mathrm{15}}+\mathrm{0.64}\pm \mathrm{0.03}$ × FTIR; in molecules per square centimetre). Second, the precision of TROPOMI HCHO data is estimated by the median absolute deviation (MAD) of the relative differences between TROPOMI and FTIR ground-based data. The clean sites are especially useful for minimizing a possible additional collocation error. The precision requirement of 1.2×10¹⁶ molec. cm⁻² for a single pixel is reached at most of the clean sites, where it is found that the TROPOMI precision can even be 2 times better (0.5–0.8×10¹⁵ molec. cm⁻² for a single pixel). However, we find that the provided TROPOMI random uncertainties may be underestimated by a factor of 1.6 (for clean sites) to 2.3 (for high HCHO levels). The correlation is very good between TROPOMI and FTIR data (R=0.88 for 3 h mean coincidences; R=0.91 for monthly means coincidences). Using about 17 months of data (from May 2018 to September 2019), we show that the TROPOMI seasonal variability is in very good agreement at all of the FTIR sites. The FTIR network demonstrates the very good quality of the TROPOMI HCHO products, which is well within the pre-launch requirements for both accuracy and precision. This paper makes suggestions for the refinement of the TROPOMI random uncertainty budget and TROPOMI quality assurance values for a better filtering of the remaining outliers.

Within the European project UFTIR (Time series of Upper Free Troposphere observations from an European ground-based FTIR network), six ground-based stations in Western Europe, from 79° N to 28° N, all equipped with Fourier Transform infrared (FTIR) instruments and part of the Network for the Detection of Atmospheric Composition Change (NDACC), have joined their efforts to evaluate the trends of several direct and indirect greenhouse gases over the period 1995–2004. The retrievals of CO, CH₄, C₂H₆, N₂O, CHClF₂, and O₃ have been optimized. Using the optimal estimation method, some vertical information can be obtained in addition to total column amounts. A bootstrap resampling method has been implemented to determine annual partial and total column trends for the target gases. The present work focuses on the ozone results. The retrieved time series of partial and total ozone columns are validated with ground-based correlative data (Brewer, Dobson, UV-Vis, ozonesondes, and Lidar). The observed total column ozone trends are in agreement with previous studies: 1) no total column ozone trend is seen at the lowest latitude station Izaña (28° N); 2) slightly positive total column trends are seen at the two mid-latitude stations Zugspitze and Jungfraujoch (47° N), only one of them being significant; 3) the highest latitude stations Harestua (60° N), Kiruna (68° N) and Ny-Ålesund (79° N) show significant positive total column trends. Following the vertical information contained in the ozone FTIR retrievals, we provide partial columns trends for the layers: ground-10 km, 10–18 km, 18–27 km, and 27–42 km, which helps to distinguish the contributions from dynamical and chemical changes on the total column ozone trends. We obtain no statistically significant trends in the ground-10 km layer for five out of the six ground-based stations. We find significant positive trends for the lowermost stratosphere at the two mid-latitude stations, and at Ny-Ålesund. We find smaller, but significant trends for the 18–27 km layer at Kiruna, Harestua, Jungfraujoch, and Izaña. The results for the upper layer are quite contrasted: we find significant positive trends at Kiruna, Harestua, and Jungfraujoch, and significant negative trends at Zugspitze and Izaña. These ozone partial columns trends are discussed and compared with previous studies.

Formaldehyde (HCHO) columns have been retrieved from ground-based Fourier transform infrared (FTIR) campaign measurements in 2004 and 2007 and from UV-Visible MAX-DOAS measurements in 2004–2005 at the NDACC site of Réunion Island (21° S, 55° E). The FTIR and MAX-DOAS daily mean formaldehyde total columns are intercompared in their common measurement period, from August to October 2004. The ground-based data are also compared to correlative SCIAMACHY data. The comparisons account for the vertical sensitivity differences of the data sets, by including their respective averaging kernels. Complete error budgets are also presented. The FTIR and MAX-DOAS daily mean total columns agree very well: no significant bias is observed and the standard deviation of the comparisons is only 8%. Both FTIR and MAX-DOAS HCHO total columns are in good agreement with SCIAMACHY values in the 2004–2005 period, with standard deviations of 21% and 31%, respectively. The same seasonal cycle is observed by the different instruments, with a minimum in austral winter and a maximum in February–March. The FTIR and MAX-DOAS data are confronted with HCHO columns calculated by a global CTM, the IMAGES model. The model underestimates the HCHO columns by 23–29% in comparison with FTIR, and by 15% in comparison with DOAS. This bias might have multiple causes, including an underestimation of OH concentrations in the model (as indicated by a sensitivity study using prescribed OH fields) and/or an underestimated contribution of large-scale transport of HCHO precursors from Madagascar. The latter hypothesis is comforted by the large observed day-to-day variability of HCHO columns, and by the observation that the peak values of FTIR columns can often be associated with free tropospheric transport patterns from source regions over Madagascar to Réunion Island, according to simulations performed with the Lagrangian particle dispersion model FLEXPART.