The leaf-level emission factor of volatile isoprenoids: caveats, model algorithms, response shapes and scaling

Abstract

Abstract. In models of plant volatile isoprenoid emissions, the instantaneous compound emission rate typically scales with the plant's emission potential under specified environmental conditions, also called as the emission factor, E S . In the most widely employed plant isoprenoid emission models, the algorithms developed by colleagues (1991, 1993), instantaneous variation of the steady-state emission rate is described as the product of E S and light and temperature response functions. When these models are employed in the atmospheric chemistry modeling community, speciesspecific E S values and parameter values defining the instantaneous response curves are often taken as initially defined. In the current review, we argue that E S as a characteristic used in the models importantly depends on our understanding of which environmental factors affect isoprenoid emissions, and consequently need standardization during experimental E S determinations. In particular, there is now increasing consensus that in addition to variations in light and temperature, Correspondence to:Ü. Niinemets (ylo.niinemets@emu.ee) alterations in atmospheric and/or within-leaf CO 2 concentrations may need to be included in the emission models. Furthermore, we demonstrate that for less volatile isoprenoids, mono-and sesquiterpenes, the emissions are often jointly controlled by the compound synthesis and volatility. Because of these combined biochemical and physico-chemical drivers, specification of E S as a constant value is incapable of describing instantaneous emissions within the sole assumptions of fluctuating light and temperature as used in the standard algorithms. The definition of E S also varies depending on the degree of aggregation of E S values in different parameterization schemes (leaf-vs. canopy-or region-scale, species vs. plant functional type levels) and various aggregated E S schemes are not compatible for different integration models. The summarized information collectively emphasizes the need to update model algorithms by including missing environmental and physico-chemical controls, and always to define E S within the proper context of model structure and spatial and temporal resolution.

Global terrestrial isoprene emission models: sensitivity to variability in climate and vegetation

“…In fact, applying canopy-based emission factors that were calculated with a given canopy model using a prescribed vegetation product to models that use different canopy transfer and vegetation models would be, strictly speaking, incorrect, and introduces a large source of uncertainty. A similar argument applies when using leaf-level emission factors together with different leaf emission algorithms if the values of the emission factors are based on measurements that were performed under non-standard conditions (Niinemets et al, 2010b).…”

Chemodiversity of a Scots pine stand and implications for terpene air concentrations

“…Many caveats have lately been presented towards the original empirical algorithm approach (Niinemets et al, 2010a, b). The compound-specific physico-chemical properties are very variable (Copolovici and Niinemets, 2005) and may influence the EFs (Niinemets et al, 2010a), and since plant emissions are almost always composed of several compounds, the use of a summed emission strength is not sufficient for detailed air chemistry calculations. In longer term, both the quantity and quality of emitted compounds varies diurnally, within the season and along with environmental stressors (e.g.…”

Quantifying the uncertainty in simulating global tropospheric composition due to the variability in global emission estimates of Biogenic Volatile Organic Compounds

“…The long term ground based flask measurements performed by the NOAA Earth System Research Laboratory (ESRL) Global Monitoring Division (GMD) provides a valuable record of changes in abundant long-lived trace gas species such as CO and CH 4 (Novelli et al, 1998(Novelli et al, , 2003. The measurement sites are situated at many different locations, usually well away from strong local anthropogenic emission sources.…”

“…Sensitivity studies have shown that the resulting biogenic emission fluxes calculated online are fairly sensitive to the update frequency at which the meteorological input fields are applied (Ashworth et al, 2010) and to assumptions regarding the other variables used to calculate the emission flux online . Moreover, algorithms designed to relate the release of isoprene towards physical environmental variables, such as temperature, still do not account for the feedback of the efficiency of the emission of the terpenes towards changing atmospheric levels of carbon dioxide, which is thought to be important (Niinemets et al, 2010). However, one drawback of adopting an online method for calculating BVOC emission fluxes is that the implementation often does not cover all of the BVOC species released for which regional emission fluxes from biogenic sources dominate e.g.…”