A process-based model to predict the effects of climatic change on leaf isoprene emission rates

Martin, Marion; Stirling, Clare M.; Humphries, Steven W.; Long, S. P.

doi:10.1016/s0304-3800(00)00258-1

Cited by 60 publications

(84 citation statements)

References 31 publications

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“…Current model development efforts are focused on the improvement of simple empirical algorithms and the development of more process-based emission models (Arneth et al, 2006;Back et al, 2005;Grote et al, 2006;Niinemets et al, 2002a;Martin et al, 2000;Niinemets et al, 1999;Zimmer et al, 2000). Each approach lends itself more easily to different applications, such as the easy implication of simple empirical models in atmospheric chemistry models (e.g., Guenther et al, 2006), or the detailed study allowed for by the more intricate models (e.g., Grote et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

“…Thus, the emissions are linked to the photosynthetic activity of the leaf with the use of only one single leaf dependent parameter, the fractional allocation of electron transport to synthase activity. Martin et al (2000) developed a process based approach for isoprene emissions using the knowledge of the biochemical pathway of isoprene synthesis, thus providing a highly mechanistic model.…”

Section: The Niinemets Et Al Modelmentioning

confidence: 99%

“…The model applied here is a slight modification (following Arneth et al, 2007) of the original version used by Martin et al (2000) in order to assure compatibility with the analogous expression in the model of Niinemets et al The rate of isoprene synthesis is thus proposed to be highly dependent on the rate of supply of carbon in the form of phosphoglyceric acid (PGA) or pyruvate (from photosynthesis or photorespiration), the rate of phosphorylation to supply the ATP T. Keenan et al: Process based inventory of isoprenoid emissions needed for the conversion of PGA/pyruvate to DMAPP and the amount and in vivo activity of the isoprene synthase enzyme (Lehning et al, 1999;Loreto and Sharkey, 1993;Monson et al, 1992), following the suggestion that Pyruvate is formed from Rubisco carboxylation about 1% of the time (Andrews and Kane, 1991).…”

Section: The Martin Et Al Modelmentioning

confidence: 99%

“…These have shown to have high predictive power in some, but not in all situations (e.g., Arneth et al, 2007;Bai et al, 2006;Geron et al, 2002;Otter et al, 2002Otter et al, , 2003Wang et al, 2007). With an improved understanding of the biochemical reaction pathways for the formation of various plant volatiles, more mechanistic models have evolved (Bäck et al, 2005;Martin et al, 2000;Niinemets et al, 1999;Niinemets and Reichstein, 2003;Zimmer et al, 2000). In these process based models, responses of key enzymatic activities to environmental variables set the internal biochemical conditions, which finally determines the emission rates.…”

Section: Introductionmentioning

confidence: 99%

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Process based inventory of isoprenoid emissions from European forests: model comparisons, current knowledge and uncertainties

et al. 2009

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Abstract. Large uncertainties exist in our knowledge of regional emissions of non-methane biogenic volatile organic compounds (BVOC). We address these uncertainties through a two-pronged approach by compiling a state of the art database of the emissions potentials for 80 European forest species, and by a model assessment and inter-comparison, both at the local and regional scale, under present and projected future climatic conditions. We coupled three contrasting isoprenoid models with the ecophysiological forest model GOTILWA+ to evaluate leaf and ecosystem isoprenoid emissions, build an emissions inventory for European forests, and to consider model behaviour in present climate and under projected future climate change conditions. Hourly, daily and annual isoprene emissions as simulated by the models were evaluated against flux measurements. The validation highlighted a general model capacity to capture gross fluxes but inefficiencies in capturing short term variability. A regional inventory of isoprenoid emissions for European forests was created using each of the three modelling approaches. The models agreed on an average European emissions budget of 1.03 TgC a −1 for isoprene and 0.97 TgC a −1 for monoterpenes for the period 1960-1990, which was dominated by a few species with largest aerial coverage. Species contribution to total emissions depended both on species emission potential and geographical distribution. For projected future climate conditions, however, emissions budgets proved highly model dependent, illustrating the current uncertainty associated with isoprenoid emissions responses to potential future conditions.Correspondence to: T. Keenan (t.keenan@creaf.uab.es) These results suggest that current model estimates of isoprenoid emissions concur well, but future estimates are highly uncertain. We conclude that development of reliable models is highly urgent, but for the time being, future BVOC emission scenario estimates should consider results from an ensemble of available emission models.

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Section: Discussionmentioning

confidence: 99%

Section: The Niinemets Et Al Modelmentioning

confidence: 99%

Section: The Martin Et Al Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Process based inventory of isoprenoid emissions from European forests: model comparisons, current knowledge and uncertainties

et al. 2009

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“…Although our understanding of why plants emit isoprene is still incomplete (Laothawornkitkul et al, 2009), robust relationships between isoprene emissions and the photosynthetic photon flux density (PPFD) and ambient temperature have been identified and form the basis of some of the most widely used algorithms used to predict its emissions from the biosphere (Guenther et al, 1991(Guenther et al, , 1993(Guenther et al, , 2006(Guenther et al, , 2012. Although the algorithms of Guenther are perhaps the most widely used and highly cited, numerous other models exist which are formulated on a partial understanding of the underlying metabolic processes that determine production rates of isoprene synthase such as photosynthesis (Arneth et al, 2007;Niinemets et al, 1999;Martin et al, 2000;Zimmer et al, 2000;Bäck et al, 2005;Pacifico et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Isoprene emission potentials from European oak forests derived from canopy flux measurements: an assessment of uncertainties and inter-algorithm variability

et al. 2017

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Abstract. Biogenic emission algorithms predict that oak forests account for ∼ 70 % of the total European isoprene budget. Yet the isoprene emission potentials (IEPs) that underpin these model estimates are calculated from a very limited number of leaf-level observations and hence are highly uncertain. Increasingly, micrometeorological techniques such as eddy covariance are used to measure whole-canopy fluxes directly, from which isoprene emission potentials can be calculated. Here, we review five observational datasets of isoprene fluxes from a range of oak forests in the UK, Italy and France. We outline procedures to correct the measured net fluxes for losses from deposition and chemical flux divergence, which were found to be on the order of 5-8 and 4-5 %, respectively. The corrected observational data were used to derive isoprene emission potentials at each site in a two-step process. Firstly, six commonly used emission algorithms were inverted to back out time series of isoprene emission potential, and then an "average" isoprene emission potential was calculated for each site with an associated uncertainty. We used these data to assess how the derived emission potentials change depending upon the specific emission algorithm used and, importantly, on the particular approach adopted to derive an average site-specific emission potential. Our results show that isoprene emission potentials can vary by up to a factor of 4 depending on the specific algorithm used and whether or not it is used in a "big-leaf" or "canopy environment (CE) model" format. When using the same algorithm, the calculated average isoprene emission potential was found to vary by as much as 34 % depending on how the average was derived. Using a consistent approach with version 2.1 of the Model for Emissions of Gases and Aerosols from Nature (MEGAN), we derive new ecosystemscale isoprene emission potentials for the five measurement sites: Alice Holt, UK (10 500 ± 2500 µg m −2 h −1 ); Bosco Fontana, Italy (1610 ± 420 µg m −2 h −1 ); CastelPublished by Copernicus Publications on behalf of the European Geosciences Union. B. Langford et al.: Isoprene emission potentials from European oak forestsporziano, Italy (121 ± 15 µg m −2 h −1 ); Ispra, Italy (7590 ± 1070 µg m −2 h −1 ); and the Observatoire de Haute Provence, France (7990 ± 1010 µg m −2 h −1 ). Ecosystemscale isoprene emission potentials were then extrapolated to the leaf-level and compared to previous leaf-level measurements for Quercus robur and Quercus pubescens, two species thought to account for 50 % of the total European isoprene budget. The literature values agreed closely with emission potentials calculated using the G93 algorithm, which were 85 ± 75 and 78 ± 25 µg g −1 h −1 for Q. robur and Q. pubescens, respectively. By contrast, emission potentials calculated using the G06 algorithm, the same algorithm used in a previous study to derive the European budget, were significantly lower, which we attribute to the influence of past light and temperature conditions. Adopting these new G0...

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Biogenic VOCs

Steiner¹,

Goldstein²

2007

Volatile Organic Compounds in the Atmosphere

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A process-based model to predict the effects of climatic change on leaf isoprene emission rates

Cited by 60 publications

References 31 publications

Process based inventory of isoprenoid emissions from European forests: model comparisons, current knowledge and uncertainties

Process based inventory of isoprenoid emissions from European forests: model comparisons, current knowledge and uncertainties

Isoprene emission potentials from European oak forests derived from canopy flux measurements: an assessment of uncertainties and inter-algorithm variability

Biogenic VOCs

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