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The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is employed as an intercomparison tool for validating TROPOspheric Monitoring Instrument (TROPOMI) satellite NO2 retrievals against high-resolution Airborne Prism EXperiment (APEX) remote sensing observations performed in June 2019 in the region of Antwerp, a major hotspot of NO2 pollution in Europe. The model is first evaluated using meteorological and chemical observations in this area. Sensitivity simulations varying the model planetary layer boundary (PBL) parameterization were conducted for a 3 d period in June 2019, indicating a generally good performance of most parameterizations against meteorological data (namely ceilometer, surface meteorology, and balloon measurements), except for a moderate overestimation (∼ 1 m s−1) of near-surface wind speed. On average, all but one of the PBL schemes reproduce the surface NO2 measurements at stations of the Belgian Interregional Environmental Agency fairly well, although surface NO2 is generally underestimated during the day (between −4.3 % and −25.1 % on average) and overestimated at night (8.2 %–77.3 %). This discrepancy in the diurnal evolution arises despite (1) implementing a detailed representation of the diurnal cycle of emissions (Crippa et al., 2020) and (2) correcting the modeled concentrations to account for measurement interferences due to NOy reservoir species, which increases NO2 concentrations by about 20 % during the day. The model is further evaluated by comparing a 15 d simulation with surface NO2, NO, CO, and O3 data in the Antwerp region. The modeled daytime NO2 concentrations are more negatively biased during weekdays than during weekends, indicating a misrepresentation of the weekly temporal profile applied to the emissions obtained from Crippa et al. (2020). Using a mass balance approach, we determined a new weekly profile of NOx emissions, leading to a homogenization of the relative bias among the different weekdays. The ratio of weekend to weekday emissions is significantly lower in this updated profile (0.6) than in the profile based on Crippa et al. (2020; 0.84). Comparisons with remote sensing observations generally show a good reproduction of the spatial patterns of NO2 columns by the model. The model underestimated both APEX (by ca. −37 %) and TROPOMI columns (ca. −25 %) on 27 June, whereas no significant bias is found on 29 June. The two datasets are intercompared by using the model as an intermediate platform to account for differences in vertical sensitivity through the application of averaging kernels. The derived bias of TROPOMI v1.3.1 NO2 with respect to APEX is about −10 % for columns between (6–12) × 1015 molec. cm−2. The obtained bias for TROPOMI v1.3.1 increases with the NO2 column, following CAPEX=1.217Cv1.3-0.783 × 1015 molec. cm−2, in line with previous validation campaigns. The bias is slightly lower for the reprocessed TROPOMI v2.3.1, with CAPEX=1.055CPAL-0.437 × 1015 molec. cm−2 (PAL). Finally, a mass balance approach was used to perform a crude inversion of NOx emissions based on 15 d averaged TROPOMI columns. The emission correction is conducted only in regions with high columns and high sensitivity to emission changes in order to minimize the errors due to wind transport. The results suggest that emissions increase over Brussels–Antwerp (+20 %), the Ruhr Valley (13 %), and especially Paris (+39 %), and emissions decrease above a cluster of power plants in western Germany.

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.

The Royal Meteorological Institute of Belgium (RMI) gathered ambient aerosol data in Brussels with a 7-wavelengths aethalometer and a 3 wavelengths integrating nephelometer. The amount of light-absorbing particles showed a clear daily and weekly cycle, with a sharp peak in the morning rush hour time and a broader peak in the evening. During weekends, the rush hour peak diminished. The spectral dependency of the absorption coefficient revealed peak contributions of traffic emissions to the amount of light-absorbing particles of up to 90%. Other sources (like wood burning from households) showed peak contributions of up to 35%. These percentages showed in addition a clear daily, weekly and seasonal cycle, with higher contributions of these other sources during night time, weekends and summer.

Starting in 1969, and with three launches a week, the Uccle (Brussels, Belgium) ozonesonde dataset is one of longest and densest of the world. Moreover, as the only major change was the switch from Brewer-Mast 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 which efforts have been taken during the first three 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 years 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 backbone for validation and stability analysis of both stratospheric as well as 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 declined at a significant rate of around 2 %/decade since 1969, rather consistently over the different stratospheric levels. This overall decrease can mainly be assigned to the 1969–1996 period with a rather consistent decline rate around −4 %/decade. Since 2000, a recovery between +1 to +3 %/decade of the stratospheric ozone levels above Uccle is observed, although not significant and not for the upper stratospheric levels measured by ozonesondes. Throughout the entire free troposphere, a very consistent increase of the ozone concentrations at 2 to 3 %/decade is measured since both 1969 and 1995, the latter trend 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 amount of tropopause folding events in the Uccle time series 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 in (tropospheric) ozone precursor emissions and notwithstanding the continued increase of mean surface ozone concentrations. Furthermore, we illustrate the crucial role of ozonesonde measurements for validation of satellite ozone profile retrievals. With the operational validation of Global Ozone Monitoring Experiment 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 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, 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 up to ~15 %. Using the Uccle ozonesonde time series as 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

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 one year from March 2018 until March 2019. The instrument was operated in both UV and visible (Vis) 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 NO2 concentrations (VMRs) and vertical column densities (VCDs) were retrieved in ten different azimuthal directions. The dual-scan MAX-DOAS dataset allows partly resolving the horizontal distribution of NO2 around the measurement site and studying its seasonal variations. Furthermore, we show that measuring the tropospheric NO2 VCDs 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 NO2 vertical profile information derived from the MAX-DOAS measurements, we also resolve a systematic underestimation in S5P NO2 data due to the use of inadequate a-priori NO2 profile shape data in the satellite retrieval.

Isoprene is a highly reactive volatile organic compound emitted by vegetation, known to be a precursor of secondary organic aerosols and to enhance tropospheric ozone formation under polluted conditions. Isoprene emissions respond strongly to changes in meteorological parameters such as temperature and solar radiation. In addition, the increasing CO2 concentration has a dual effect, as it causes both a direct emission inhibition as well as an increase in biomass through fertilization. In this study we used the MEGAN (Model of Emissions of Gases and Aerosols from Nature) emission model coupled with the MOHYCAN (Model of HYdrocarbon emissions by the CANopy) canopy model to calculate the isoprene fluxes emitted by vegetation in the recent past (1979–2014) and in the future (2070–2099) over Europe at a resolution of 0.1∘×0.1∘. As a result of the changing climate, modeled isoprene fluxes increased by 1.1 % yr−1 on average in Europe over 1979–2014, with the strongest trends found over eastern Europe and European Russia, whereas accounting for the CO2 inhibition effect led to reduced emission trends (0.76 % yr−1). Comparisons with field campaign measurements at seven European sites suggest that the MEGAN–MOHYCAN model provides a reliable representation of the temporal variability of the isoprene fluxes over timescales between 1 h and several months. For the 1979–2014 period the model was driven by the ECMWF ERA-Interim reanalysis fields, whereas for the comparison of current with projected future emissions, we used meteorology simulated with the ALARO regional climate model. Depending on the representative concentration pathway (RCP) scenarios for greenhouse gas concentration trajectories driving the climate projections, isoprene emissions were found to increase by +7 % (RCP2.6), +33 % (RCP4.5), and +83 % (RCP8.5), compared to the control simulation, and even stronger increases were found when considering the potential impact of CO2 fertilization: +15 % (RCP2.6), +52 % (RCP4.5), and +141 % (RCP8.5). However, the inhibitory CO2 effect goes a long way towards canceling these increases. Based on two distinct parameterizations, representing strong or moderate inhibition, the projected emissions accounting for all effects were estimated to be 0–17 % (strong inhibition) and 11–65 % (moderate inhibition) higher than in the control simulation. The difference obtained using the two CO2 parameterizations underscores the large uncertainty associated to this effect.

Local surface mass balance (SMB) measurements are crucial for understanding changes in the total mass of the Antarctic Ice Sheet, including its contribution to sea level rise. Despite continuous attempts to decipher mechanisms controlling the local and regional SMB, a clear understanding of the separate components is still lacking, while snowfall measurements are almost absent. In this study, the different terms of the SMB are quantified at the Princess Elisabeth (PE) station in Dronning Maud Land, East Antarctica. Furthermore, the relationship between snowfall and accumulation at the surface is investigated. To achieve this, a unique collocated set of ground-based and in situ remote sensing instrumentation (Micro Rain Radar, ceilometer, automatic weather station, among others) was set up and operated for a time period of 37 months. Snowfall originates mainly from moist and warm air advected from lower latitudes associated with cyclone activity. However, snowfall events are not always associated with accumulation. During 38 % of the observed snowfall cases, the freshly fallen snow is ablated by the wind during the course of the event. Generally, snow storms of longer duration and larger spatial extent have a higher chance of resulting in accumulation on a local scale, while shorter events usually result in ablation (on average 17 and 12 h respectively). A large part of the accumulation at the station takes place when preceding snowfall events were occurring in synoptic upstream areas. This fresh snow is easily picked up and transported in shallow drifting snow layers over tens of kilometres, even when wind speeds are relatively low (< 7 ms−1). Ablation events are mainly related to katabatic winds originating from the Antarctic plateau and the mountain ranges in the south. These dry winds are able to remove snow and lead to a decrease in the local SMB. This work highlights that the local SMB is strongly influenced by synoptic upstream conditions.

For three austral summer seasons (2013–2016, each from December to February) aerosol particles arriving at the Belgian Antarctic research station Princess Elisabeth (PE), in Dronning Maud Land in East Antarctica were characterized in terms of number concentrations of total aerosol particles (NCN) and cloud condensation nuclei (NCCN), the particle number size distribution (PNSD), the aerosol particle hygroscopicity and the influence of the air mass origin on NCN and NCCN. In general NCN was found to range from 40 to 6700 cm−3 with a median of 333 cm−3, while NCCN was found to cover a range between less than 10 and 1300 cm−3 for supersaturations (SS) between 0.1 and 0.7 %. It is shown that the aerosol is Aitken mode dominated and is characterized by a significant amount of freshly, secondarily formed aerosol particles, with 94 % and 36 % of the aerosol particles are smaller than 90 nm and &approx; 35 nm, respectively. Measurements of the basic meteorological parameters as well as the history of the air masses arriving at the measurement station indicate that the station is influenced by both, continental air masses originating from the Antarctic inland ice sheet (continental events – CE) and marine air masses originating from the Southern Ocean (marine events – ME). CEs came along with rather constant NCN and NCCN values, which we denote to be Antarctic continental background concentrations. MEs however cause large fluctuations in NCN and NCCN caused by scavenging due to precipitation or new particle formation based on marine precursors. The application of Hysplit back trajectories in form of the potential source contribution function (PSCF) analysis indicate, that the region of the Southern Ocean is a potential source of Aitken mode particles. For particles larger than &approx; 110 nm (CCN measured at SS of 0.1 %) the Antarctic ice shelf regions were found to be a potential source region, most likely due to the emission of sea salt aerosol particles, released from snow particles from surface snow layers by sublimation, e.g., during periods of high wind speed, leading to drifting or blowing snow. On the basis of the PNSDs and NCCN, the critical diameter for cloud droplet activation and the aerosol particle hygroscopicity parameter κ were determined to be 110 nm and 1, respectively, for a SS of 0.1 %. The region of the Antarctic inland plateau however was not found to feature a significant source region for CN and CCN measured at the PE station in austral summer.

Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the strongest events are considered. Here, we develop a blowing snow detection (BSD) algorithm for ground-based remote-sensing ceilometers in polar regions and apply it to ceilometers at Neumayer III and Princess Elisabeth (PE) stations, East Antarctica. The algorithm is able to detect (heavy) blowing snow layers reaching 30m height. Results show that 78% of the detected events are in agreement with visual observations at Neumayer III station. The BSD algorithm detects heavy blowing snow 36% of the time at Neumayer (2011-2015) and 13% at PE station (20102016). Blowing snow occurrence peaks during the austral winter and shows around 5% interannual variability. The BSD algorithm is capable of detecting blowing snow both lifted from the ground and occurring during precipitation, which is an added value since results indicate that 92% of the blowing snow is during synoptic events, often combined with precipitation. Analysis of atmospheric meteorological variables shows that blowing snow occurrence strongly depends on fresh snow availability in addition to wind speed. This finding challenges the commonly used parametrizations, where the threshold for snow particles to be lifted is a function of wind speed only. Blowing snow occurs predominantly during storms and overcast conditions, shortly after precipitation events, and can reach up to 1300ma:g:l: in the case of heavy mixed events (precipitation and blowing snow together). These results suggest that synoptic conditions play an important role in generating blowing snow events and that fresh snow availability should be considered in determining the blowing snow onset. ispartof: Cryosphere vol:11 issue:6 pages:2755-2772 status: 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 underestimation acts as a selective systematic error (Moncrieff et al. 1996) and could lead to a strong overestimation of net ecosystem exchange

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.