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Among the biogenic volatile organic compounds (BVOCs) emitted by plant foliage, isoprene is by far the most important in terms of both global emission and atmospheric impact. It is highly reactive in the air, and its degradation favours the generation of ozone (in the presence of NOx) and secondary organic aerosols. A critical aspect of BVOC emission modelling is the representation of land use and land cover (LULC). The current emission inventories are usually based on land cover maps that are either modelled and dynamic or satellite-based and static. In this study, we use the state-of-the-art Model of Emissions of Gases and Aerosols from Nature (MEGAN) model coupled with the canopy model MOHYCAN (Model for Hydrocarbon emissions by the CANopy) to generate and evaluate emission inventories relying on satellite-based LULC maps at annual time steps. To this purpose, we first intercompare the distribution and evolution (2001–2016) of tree coverage from three global satellite-based datasets, MODerate resolution Imaging Spectroradiometer (MODIS), ESA Climate Change Initiative Land Cover (ESA CCI-LC), and the Global Forest Watch (GFW), and from national inventories. Substantial differences are found between the datasets; e.g. the global areal coverage of trees ranges from 30 to 50×106 km2, with trends spanning from −0.26 to +0.03 % yr−1 between 2001 and 2016. At the national level, the increasing trends in forest cover reported by some national inventories (in particular for the US) are contradicted by all remotely sensed datasets. To a great extent, these discrepancies stem from the plurality of definitions of forest used. According to some local censuses, clear cut areas and seedling or young trees are classified as forest, while satellite-based mappings of trees rely on a minimum height. Three inventories of isoprene emissions are generated, differing only in their LULC datasets used as input: (i) the static distribution of the stand-alone version of MEGAN, (ii) the time-dependent MODIS land cover dataset, and (iii) the MODIS dataset modified to match the tree cover distribution from the GFW database. The mean annual isoprene emissions (350–520 Tg yr−1) span a wide range due to differences in tree distributions, especially in isoprene-rich regions. The impact of LULC changes is a mitigating effect ranging from 0.04 to 0.33 % yr−1 on the positive trends (0.94 % yr−1) mainly driven by temperature and solar radiation. This study highlights the uncertainty in spatial distributions of and temporal variability in isoprene associated with remotely sensed LULC datasets. The interannual variability in the emissions is evaluated against spaceborne observations of formaldehyde (HCHO), a major isoprene oxidation product, through simulations using the global chemistry transport model (CTM) IMAGESv2. A high correlation (R > 0.8) is found between the observed and simulated interannual variability in HCHO columns in most forested regions. The implementation of LULC change has little impact on this correlation due to the dominance of meteorology as a driver of short-term interannual variability. Nevertheless, the simulation accounting for the large tree cover declines of the GFW database over several regions, notably Indonesia and Mato Grosso in Brazil, provides the best agreement with the HCHO column trends observed by the Ozone Monitoring Instrument (OMI). Overall, our study indicates that the continuous tree cover fields at fine resolution provided by the GFW database are our preferred choice for constraining LULC (in combination with discrete LULC maps such as those of MODIS) in biogenic isoprene emission models.

Biogenic volatile organic compounds (BVOCs), primarily emitted by terrestrial vegetation, are highly reactive and have large effects on the oxidizing potential of the troposphere, air quality and climate. In terms of global emissions, isoprene is the most important BVOC. Droughts bring about changes in the surface emission of biogenic hydrocarbons mainly because plants suffer water stress. Past studies report that the current parameterization in the state-of-the-art Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1, which is a function of the soil water content and the permanent wilting point, fails at representing the strong reduction in isoprene emissions observed in field measurements conducted during a severe drought. Since the current algorithm was originally developed based on potted plants, in this study, we update the parameterization in the light of recent ecosystem-scale measurements of isoprene conducted during natural droughts in the central U.S. at the Missouri Ozarks AmeriFlux (MOFLUX) site. The updated parameterization results in stronger reductions in isoprene emissions. Evaluation using satellite formaldehyde (HCHO), a proxy for BVOC emissions, and a chemical-transport model, shows that the adjusted parameterization provides a better agreement between the modelled and observed HCHO temporal variability at local and regional scales in 2011–2012, even if it worsens the model agreement in a global, long-term evaluation. We discuss the limitations of the current parameterization, a function of highly uncertain soil properties such as porosity.

Natural emissions (vegetation, soil, and lightning) are the dominant sources of non-methane biogenic volatile organic compounds (BVOCs) and nitrogen oxides (NO.sub.x â¡ NO + NO.sub.2) released into the atmosphere over Africa. BVOCs and NO.sub.x interact with each other and strongly impact their own chemical lifetimes and degradation pathways, in particular through their influence on hydroxyl radical levels. To account for this intricate interplay between NO.sub.x and VOCs, we design and apply a novel inversion setup aiming at simultaneous optimization of monthly VOC and NO.sub.x emissions in 2019 in a regional chemistry-transport model, based on Tropospheric Ozone Monitoring Instrument (TROPOMI) HCHO and NO.sub.2 satellite observations. The TROPOMI-based inversions suggest substantial underestimations of natural NO.sub.x and VOC emissions used as a priori in the model. The annual flux over Africa increases from 125 to 165 Tg yr.sup.-1 for isoprene, from 1.9 to 2.4 TgN yr.sup.-1 for soil NO emissions, and from 0.5 to 2.0 TgN yr.sup.-1 for lightning NO emissions. Despite the NO.sub.x emission increase, evaluation against in situ NO.sub.2 measurements at seven rural sites in western Africa displays significant model underestimations after optimization. The large increases in lightning emissions are supported by comparisons with TROPOMI cloud-sliced upper-tropospheric NO.sub.2 volume mixing ratios, which remain underestimated by the model even after optimization. Our study strongly supports the application of a bias correction to the TROPOMI HCHO data and the use of a two-species constraint (vs. single-species inversion), based on comparisons with isoprene columns retrieved from the Cross-track Infrared Sensor (CrIS).

Natural emissions (vegetation, soil, and lightning) are the dominant sources of non-methane biogenic volatile organic compounds (BVOCs) and nitrogen oxides (NOx≡ NO + NO2) released into the atmosphere over Africa. BVOCs and NOx interact with each other and strongly impact their own chemical lifetimes and degradation pathways, in particular through their influence on hydroxyl radical levels. To account for this intricate interplay between NOx and VOCs, we design and apply a novel inversion setup aiming at simultaneous optimization of monthly VOC and NOx emissions in 2019 in a regional chemistry-transport model, based on Tropospheric Ozone Monitoring Instrument (TROPOMI) HCHO and NO2 satellite observations. The TROPOMI-based inversions suggest substantial underestimations of natural NOx and VOC emissions used as a priori in the model. The annual flux over Africa increases from 125 to 165 Tg yr−1 for isoprene, from 1.9 to 2.4 TgN yr−1 for soil NO emissions, and from 0.5 to 2.0 TgN yr−1 for lightning NO emissions. Despite the NOx emission increase, evaluation against in situ NO2 measurements at seven rural sites in western Africa displays significant model underestimations after optimization. The large increases in lightning emissions are supported by comparisons with TROPOMI cloud-sliced upper-tropospheric NO2 volume mixing ratios, which remain underestimated by the model even after optimization. Our study strongly supports the application of a bias correction to the TROPOMI HCHO data and the use of a two-species constraint (vs. single-species inversion), based on comparisons with isoprene columns retrieved from the Cross-track Infrared Sensor (CrIS).

Volatile organic compounds (VOCs) are key precursors of tropospheric ozone and secondary organic aerosols, a major component of PM2.5, and several aromatic VOCs are toxic. Glyoxal is a short-lived oxidation product of many VOCs, yet global models consistently underestimate its abundance, indicating a substantial missing source. Here, we derive improved estimates of global biogenic, pyrogenic, and anthropogenic VOC emissions and new constraints on the atmospheric glyoxal budget, based on the first joint inversion of TROPOMI formaldehyde and glyoxal columns using the adjoint of the MAGRITTEv1.2 chemical transport model. For 2021, the global NMVOC flux is estimated at 1070 Tg yr−1, 19 % above bottom-up estimates, partitioned into 749 Tg from vegetation, 102 Tg from biomass burning, and 219 Tg from anthropogenic activity. Emissions of anthropogenic glyoxal precursors are 43 % higher globally when constrained by satellite data compared with inventory-based simulations, with large underestimations in India, China, and Africa. The total glyoxal source is estimated at 100 Tg yr−1, of which 41 % originates from unidentified VOCs, predominantly biogenic and concentrated in the Tropics. Likely contributors include poorly represented formation pathway in isoprene oxidation under low-NOx conditions and an underestimated contribution of monoterpenes. Validation against Pandonia Global Network, in situ, and MAX-DOAS datasets confirms improved agreement of the satellite-constrained model relative to the model based on inventory data alone.

Natural emissions (vegetation, soil, and lightning) are the dominant sources of non-methane biogenic volatile organic compounds (BVOCs) and nitrogen oxides (NOx≡ NO + NO2) released into the atmosphere over Africa. BVOCs and NOx interact with each other and strongly impact their own chemical lifetimes and degradation pathways, in particular through their influence on hydroxyl radical levels. To account for this intricate interplay between NOx and VOCs, we design and apply a novel inversion setup aiming at simultaneous optimization of monthly VOC and NOx emissions in 2019 in a regional chemistry-transport model, based on Tropospheric Ozone Monitoring Instrument (TROPOMI) HCHO and NO2 satellite observations. The TROPOMI-based inversions suggest substantial underestimations of natural NOx and VOC emissions used as a priori in the model. The annual flux over Africa increases from 125 to 165 Tg yr−1 for isoprene, from 1.9 to 2.4 TgN yr−1 for soil NO emissions, and from 0.5 to 2.0 TgN yr−1 for lightning NO emissions. Despite the NOx emission increase, evaluation against in situ NO2 measurements at seven rural sites in western Africa displays significant model underestimations after optimization. The large increases in lightning emissions are supported by comparisons with TROPOMI cloud-sliced upper-tropospheric NO2 volume mixing ratios, which remain underestimated by the model even after optimization. Our study strongly supports the application of a bias correction to the TROPOMI HCHO data and the use of a two-species constraint (vs. single-species inversion), based on comparisons with isoprene columns retrieved from the Cross-track Infrared Sensor (CrIS).

Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimations of NMVOC emissions in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) is evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide and (2) aircraft in situ HCHO concentration measurements from campaigns conducted over the USA during 2012–2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives ΩOMI=0.651Ωairc+2.95×1015 molec.cm-2, with ΩOMI and Ωairc the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data gives ΩOMI=0.659ΩFTIR+2.02×1015 molec.cm-2. Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions (∼445Tgyr-1) are 25 % higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over the southeastern USA remains imperfectly elucidated.