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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10440851" target="_blank" >RIV/00216208:11320/21:10440851 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DhrY5P9ZR_" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DhrY5P9ZR_</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5194/acp-21-8413-2021" target="_blank" >10.5194/acp-21-8413-2021</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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 x 10(6) km(2), 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 &gt; 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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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 x 10(6) km(2), 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 &gt; 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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Atmospheric Chemistry and Physics

ISSN

1680-7316

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

24

Strana od-do

8413-8436

Kód UT WoS článku

000660584300001

EID výsledku v databázi Scopus

—