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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><sub>S</sub>. 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><sub>S</sub> and light and temperature response functions. When these models are employed in the atmospheric chemistry modeling community, species-specific <i>E</i><sub>S</sub> 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><sub>S</sub> 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><sub>S</sub> determinations. In particular, there is now increasing consensus that in addition to variations in light and temperature, alterations in atmospheric and/or within-leaf CO<sub>2</sub> 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><sub>S</sub> 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><sub>S</sub> also varies depending on the degree of aggregation of <i>E</i><sub>S</sub> values in different parameterization schemes (leaf- vs. canopy- or region-scale, species vs. plant functional type levels) and various aggregated <i>E</i><sub>S</sub> 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><sub>S</sub> within the proper context of model structure and spatial and temporal resolution.