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.
Global and regional impacts of land cover changes on isoprene
emissions derived from spaceborne data and the MEGAN model
