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Starting in 1969 and comprising three launches a week, the Uccle (Brussels, Belgium) ozonesonde dataset is one of longest and densest in the world. Moreover, as the only major change was the switch from Brewer-Mast (BM) to electrochemical concentration cell (ECC) ozonesonde types in 1997 (when the emissions of ozone-depleting substances peaked), the Uccle time series is very homogenous. In this paper, we briefly describe the efforts that were undertaken during the first 3 decades of the 50 years of ozonesonde observations to guarantee the homogeneity between ascent and descent profiles, under changing environmental conditions (e.g. SO2), and between the different ozonesonde types. This paper focuses on the 50-year-long Uccle ozonesonde dataset and aims to demonstrate its past, present, and future relevance to ozone research in two application areas: (i) the assessment of the temporal evolution of ozone from the surface to the (middle) stratosphere, and (ii) as the backbone for validation and stability analysis of both stratospheric and tropospheric satellite ozone retrievals. Using the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) multiple linear regression model (SPARC/IO3C/GAW, 2019), we found that the stratospheric ozone concentrations at Uccle have declined at a significant rate of around 2 % per decade since 1969, which is also rather consistent over the different stratospheric levels. This overall decrease can mainly be assigned to the 1969–1996 period with a rather consistent rate of decrease of around −4 % per decade. Since 2000, a recovery of between +1 % per decade and +3 % per decade of the stratospheric ozone levels above Uccle has been observed, although it is not significant and is not seen for the upper stratospheric levels measured by ozonesondes. Throughout the entire free troposphere, a very consistent increase in the ozone concentrations of 2 % per decade to 3 % per decade has been measured since both 1969 and 1995, with the trend since 1995 being in almost perfect agreement with the trends derived from the In-service Aircraft for a Global Observing System (IAGOS) ascent/descent profiles at Frankfurt. As the number of tropopause folding events in the Uccle time series has increased significantly over time, increased stratosphere-to-troposphere transport of recovering stratospheric ozone might partly explain these increasing tropospheric ozone concentrations, despite the levelling-off of (tropospheric) ozone precursor emissions and notwithstanding the continued increase in mean surface ozone concentrations. Furthermore, we illustrate the crucial role of ozonesonde measurements for the validation of satellite ozone profile retrievals. With the operational validation of the Global Ozone Monitoring Experiment-2 (GOME-2), we show how the Uccle dataset can be used to evaluate the performance of a degradation correction for the MetOp-A/GOME-2 UV (ultraviolet) sensors. In another example, we illustrate that the Microwave Limb Sounder (MLS) overpass ozone profiles in the stratosphere agree within ±5 % with the Uccle ozone profiles between 10 and 70 hPa. Another instrument on the same Aura satellite platform, the Tropospheric Emission Spectrometer (TES), is generally positively biased with respect to the Uccle ozonesondes in the troposphere by up to ∼ 10 ppbv, corresponding to relative differences of up to ∼ 15 %. Using the Uccle ozonesonde time series as a reference, we also demonstrate that the temporal stability of those last two satellite retrievals is excellent.

Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of aerosols and tropospheric nitrogen dioxide (NO2) were carried out in Uccle (50.8° N, 4.35° E), Brussels, during 1 year from March 2018 until March 2019. The instrument was operated in both the UV and visible wavelength ranges in a dual-scan configuration consisting of two sub-modes: (1) an elevation scan in a fixed viewing azimuthal direction (the so-called main azimuthal direction) pointing to the northeast and (2) an azimuthal scan in a fixed low elevation angle (2°). By applying a vertical profile inversion algorithm in the main azimuthal direction and a parameterization technique in the other azimuthal directions, near-surface NO2volume mixing ratios (VMRs) and vertical column densities (VCDs) were retrieved in 10 different azimuthal directions. The dualscan MAX-DOAS dataset allows for partly resolving the horizontal distribution of NO2around the measurement site and studying its seasonal variations. Furthermore, we show that measuring the tropospheric NO2VCDs in different azimuthal directions improves the spatial colocation with measurements from the Sentinel-5 Precursor (S5P), leading to a reduction of the spread in validation results. By using NO2vertical profile information derived from the MAX-DOAS measurements, we also resolve a systematic underestimation in S5P NO2data due to the use of inadequate a priori NO2profile shape data in the satellite retrieval., SCOPUS: ar.j, info:eu-repo/semantics/published

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar–Ball–Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64–96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr−1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

This study investigated the impact of diffuse light on canopy scale emission of isoprene and monoterpenes measured continuously above a mixed temperate forest, using the disjunct eddy-covariance by mass scanning technique with a proton transfer reaction-mass spectrometer (PTR-MS) instrument. To assess this impact, the relationship between emissions/radiation and emissions/gross primary production (GPP) under clear sky and cloudy conditions were analysed. Under cloudy conditions (high proportion of diffuse radiation), the isoprene and monoterpene fluxes were enhanced compared to clear sky conditions (low proportion of diffuse radiation) at equivalent temperature and above-canopy total radiation. The whole-canopy enzymatic activity of the metabolic isoprene production pathway, however, was suggested to be lower under cloudy conditions than under clear sky conditions at equivalent temperature. The mechanisms behind these observations are probably linked to the better penetration of diffuse radiation in the canopy. Shade leaves/needles receive more radiation in cloudy conditions than in clear sky conditions, thereby inducing the observed effects.

Direct plant stress sensing is the key for a quantitative understanding of drought stress effects on biogenic volatile organic compound (BVOC) emissions. A given level of drought stress might have a fundamentally different effect on the BVOC emissions of different plants. For the first time, we continuously quantified the level of drought stress in a young potted beech (Fagus sylvatica L.) with a linear variable displacement transducer (LVDT) installed at stem level in combination with simultaneous measurements of BVOC emissions and photosynthesis rates at leaf level. This continuous set of measurements allowed us to examine how beech alters its pattern of photosynthesis and carbon allocation to BVOC emissions (mainly monoterpenes, MTs) and radial stem growth during the development of drought stress. We observed an increasing-decreasing trend in the MT emissions as well as in the fraction of assimilated carbon re-emitted back into the atmosphere (ranging between 0.14 and 0.01%). We were able to link these dynamics to pronounced changes in radial stem growth, which served as a direct plant stress indicator. Interestingly, we detected a sudden burst in emission of a non-identified, non-MT BVOC species when drought stress was acute (i.e. pronounced negative stem growth). This burst might have been caused by a certain stress-related green leaf volatile, which disappeared immediately upon re-watering and thus the alleviation of drought stress. These results highlight that direct plant stress sensing creates opportunities to understand the overall complexity of stress-related BVOC emissions.

We measured the isoprene and monoterpene fluxes continuously above a mixed forest site at Vielsalm in the eastern part of Belgium, using the disjunct eddy covariance technique with proton transfer reaction-mass spectrometry. Simultaneously, we also measured the carbon dioxide fluxes in order to deduce the gross primary production. The measurements were conducted from July to September 2009. During the day, the seasonal evolution of the isoprene/monoterpene emissions was studied using a monthly temperature and light dependence function deduced from our results to standardize the fluxes. A seasonal decrease in the standard emission factors was observed, probably linked to acclimation or senescence. The standard emission factor for isoprene fluxes (30 °C, 1000 μmol m −2 s −1 ) fell from 0.91 ± 0.01 to 0.56 ± 0.02 μg m −2 s −1 and for monoterpene fluxes from 0.74 ± 0.03 to 0.27 ± 0.03 μg m −2 s −1 . During the night, a slight positive flux of monoterpenes was observed that seemed to be driven by air temperature. The standard emission factor (30°C) for nighttime monoterpene fluxes was equal to 0.093 ± 0.019 μg m −2 s −1 . Finally, we studied the seasonal evolution of the relationship between the gross primary production and the isoprene/monoterpenes fluxes. A linear relationship was observed, highlighting the strong link between carbon assimilation and isoprene/monoterpene emissions.

Methanol is the second most abundant volatile organic compound in the troposphere and plays a significant role in atmospheric chemistry. While there is consensus about the dominant role of living plants as the major source and the reaction with OH as the major sink of methanol, global methanol budgets diverge considerably in terms of source/sink estimates, reflecting uncertainties in the approaches used to model and the empirical data used to separately constrain these terms. Here we compiled micrometeorological methanol flux data from eight different study sites and reviewed the corresponding literature in order to provide a first cross-site synthesis of the terrestrial ecosystem-scale methanol exchange and present an independent data-driven view of the land–atmosphere methanol exchange. Our study shows that the controls of plant growth on production, and thus the methanol emission magnitude, as well as stomatal conductance on the hourly methanol emission variability, established at the leaf level, hold across sites at the ecosystem level. Unequivocal evidence for bi-directional methanol exchange at the ecosystem scale is presented. Deposition, which at some sites even exceeds methanol emissions, represents an emerging feature of ecosystem-scale measurements and is likely related to environmental factors favouring the formation of surface wetness. Methanol may adsorb to or dissolve in this surface water and eventually be chemically or biologically removed from it. Management activities in agriculture and forestry are shown to increase local methanol emission by orders of magnitude; however, they are neglected at present in global budgets. While contemporary net land methanol budgets are overall consistent with the grand mean of the micrometeorological methanol flux measurements, we caution that the present approach of simulating methanol emission and deposition separately is prone to opposing systematic errors and does not allow for full advantage to be taken of the rich information content of micrometeorological flux measurements.

This study provides improved methanol emission estimates on the global scale, in particular for the largest methanol source, the terrestrial biosphere, and for biomass burning. To this purpose, one complete year of spaceborne measurements of tropospheric methanol columns retrieved for the first time by the thermal infrared sensor IASI aboard the MetOp satellite are compared with distributions calculated by the IMAGESv2 global chemistry-transport model. Two model simulations are performed using a priori biogenic methanol emissions either from the new MEGANv2.1 emission model, which is fully described in this work and is based on net ecosystem flux measurements, or from a previous parameterization based on net primary production by Jacob et al. (2005). A significantly better model performance in terms of both amplitude and seasonality is achieved through the use of MEGANv2.1 in most world regions, with respect to IASI data, and to surface- and air-based methanol measurements, even though important discrepancies over several regions are still present. As a second step of this study, we combine the MEGANv2.1 and the IASI column abundances over continents in an inverse modelling scheme based on the adjoint of the IMAGESv2 model to generate an improved global methanol emission source. The global optimized source totals 187 Tg yr(-1) with a contribution of 100 Tg yr(-1) from plants, only slightly lower than the a priori MEGANv2.1 value of 105 Tg yr(-1). Large decreases with respect to the MEGANv2.1 biogenic source are inferred over Amazonia (up to 55 %) and Indonesia (up to 58 %), whereas more moderate reductions are recorded in the Eastern US (20-25 %) and Central Africa (25-35 %). On the other hand, the biogenic source is found to strongly increase in the arid and semi-arid regions of Central Asia (up to a factor of 5) and Western US (factor of 2), probably due to a source of methanol specific to these ecosystems which is unaccounted for in the MEGANv2.1 inventory. The most significant error reductions achieved by the optimization concern the derived biogenic emissions over the Amazon and over the Former Soviet Union. The robustness of the derived fluxes to changes in convective updraft fluxes, in methanol removal processes, and in the choice of the biogenic a priori inventory is assessed through sensitivity inversions. Detailed comparisons of the model with a number of aircraft and surface observations of methanol, as well as new methanol measurements in Europe and in the Reunion Island show that the satellite-derived methanol emissions improve significantly the agreement with the independent data, giving thus credence to the IASI dataset., SCOPUS: ar.j, info:eu-repo/semantics/published

Radiation fog occurs over many locations around the world in stable atmospheric conditions. Air traffic at busy airports can be significantly disrupted because low visibility at the ground makes it unsafe to take off, land and taxi on the ground. Current numerical weather prediction forecasts are able to predict general conditions favorable for fog formation, but not the exact time or location of fog occurrence. A selected set of observations available in near-real time at strategic locations could also be useful to track the evolution of key processes and key parameters that drive fog formation. Such observations could complement the information predicted by numerical weather prediction (NWP) models that is made available to airport forecasters in support of their fog forecast. This paper presents an experimental setup based on collocated automatic lidar and ceilometer measurements, relative humidity measurements and horizontal visibility measurements to study hygroscopic growth of fog condensation nuclei. This process can take several minutes to hours, and can be tracked using lidar- or ceilometer-attenuated backscatter profiles. Based on hygroscopic growth laws we derive a set of parameters that can be used to provide alerts minutes to hours prior to formation of radiation fog. We present an algorithm that uses the temporal evolution of attenuated backscatter measurements to derive pre-fog formation alerts. The performance of the algorithm is tested on 45 independent pre-fog situations at two locations (near Paris, France, and Brussels, Belgium). We find that an alert for pre-fog conditions predominantly occurs 10–50 min prior to fog formation at an altitude ranging 0 to 100 m above ground. In a few cases, alerts can occur up to 100 min prior to fog formation. Alert durations are found to be sensitive to the relative humidity conditions found a few hours prior to the fog.