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

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, <i>E</i>_S. In the most widely employed plant isoprenoid emission models, the algorithms developed by Guenther and colleagues (1991, 1993), instantaneous variation of the steady-state emission rate is described as the product of <i>E</i>_S and light and temperature response functions. When these models are employed in the atmospheric chemistry modeling community, species-specific <i>E</i>_S values and parameter values defining the instantaneous response curves are often taken as initially defined. In the current review, we argue that <i>E</i>_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 <i>E</i>_S determinations. In particular, there is now increasing consensus that in addition to variations in light and temperature, alterations in atmospheric and/or within-leaf CO₂ 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 <i>E</i>_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 <i>E</i>_S also varies depending on the degree of aggregation of <i>E</i>_S values in different parameterization schemes (leaf- vs. canopy- or region-scale, species vs. plant functional type levels) and various aggregated <i>E</i>_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 <i>E</i>_S within the proper context of model structure and spatial and temporal resolution.