Abstract. 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.
Abstract. 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 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 MEGAN model coupled with the canopy model MOHYCAN 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, MODIS, ESA CCI-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 Mkm2, with trends spanning from −0.26 % yr−1 to +0.03 % yr−1 between 2001 and 2016. At 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. 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 and temporal variability of isoprene associated to remotely-sensed LULC datasets. The interannual variability of 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 of HCHO columns in most forested regions. The implementation of LULC change has little impact on this correlation, due to the dominance of meteorology as 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 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.
No abstract
<p>Nitrogen oxides (NO<sub>x </sub>= NO + NO<sub>2</sub>) play a major role in tropospheric chemistry through their impact on ozone and hydroxyl radical (OH) distributions, and therefore on the oxidizing capacity of the atmosphere. Whereas anthropogenic NO<sub>x</sub> emissions are dominant globally, natural sources are responsible for ca. 30 % of the total emissions into the atmosphere. These sources include soil emissions (due to microbial nitrification and denitrification) and lightning (due to thermal dissociation of O<sub>2</sub> followed by recombination with N<sub>2</sub>). Chemistry-transport models (CTMs) rely on bottom-up (BU) inventories, the uncertainty of which is acknowledged, especially for natural sources. Soil NO<sub>x</sub> is mainly emitted as nitric oxide (NO) and current global BU estimates range from 4 to 15 Tg N yr<sup>-1</sup> with nearly 70% occurring in the tropics. Satellite retrievals of tropospheric NO<sub>2</sub> columns are used as top-down constraints in CTMs to derive NO<sub>x</sub> emissions from various sources (anthropogenic, biomass burning, soil, lightning) such as illustrated in Martin et al. (2003), Jaegl&#233; et al. (2005), M&#252;ller et Stavrakou (2005), Stavrakou et al. (2008) or Vinken et al. (2014). This is realized through the method of source inverse modelling, which consists in the optimization of emissions in a CTM in order to minimize the discrepancy between observed and simulated NO<sub>2</sub> columns.</p><p>In this study, we present top-down monthly soil NO<sub></sub>emissions at 0.5&#176; resolution over Africa and South America for 2019 based on spaceborne tropospheric NO<sub>2</sub> columns from the TROPOspheric Monitoring Instrument (TROPOMI). In a first step, we evaluate three global BU inventories against each other and against flux observations over the Tropics. The following BU estimates are considered: (1) YL-MAG, based on the Yienger and Levy parameterization (1995), (2) CAMS, provided by the Copernicus Atmosphere Monitoring Service (Granier et al., 2019; Simpson and Darras, 2021), and (3) HEMCO, calculated using Harvard&#8211;NASA Emission Component software (Weng et al., 2020). The last two estimates rely on the parameterization of Hudman et al. (2012). We assess YL-MAG, CAMS and HEMCO inventories against in situ measurements of biogenic soil NO fluxes compiled from literature distinguishing between seasons (dry/wet) and biomes. Based on this evaluation, the best BU inventory is selected and further used as a priori information in the regional MAGRITTE CTM (M&#252;ller et al., 2019) run at 0.5&#176;&#215;0.5&#176; resolution for the year 2019. Monthly top-down NO<sub>x</sub> fluxes (from the anthropogenic, biomass burning, soil and lightning categories) are inferred from TROPOMI NO<sub>2</sub> columns using an inversion framework based on the adjoint of MAGRITTE. The top-down soil NO fluxes and NO<sub>x</sub> abundances are subsequently validated against in situ measurements over the two tropical regions.</p>
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