The trend towards episodic modeling of environmentally-dependent emissions is increasing, with models available or under development for dust, ammonia, biogenic volatile organic compounds, soil nitrous oxide, pesticides, sea salt and chloride, mercury, and wild fire emissions. These emissions are estimated as hourly values using numerical modeling from physical principles, resulting in more realistic values than the historical approach of using national annual air quality inventories with temporal and spatial disaggregation factors. The basis of many of these new modeling tools is a surface flux model, either one-way or bi-directional, underpinned by similar surface boundary physics, with modifications or parameters to treat the flux of a specific emission compound or class of emissions. These developments will result in closely-related emission modeling tools with overlapping input data requirements. The emission flux models will need to be installed in or coupled to an emission modeling system, such as the Sparse Matrix Operator Kernel Emission (SMOKE) system. To maintain a unified one-atmosphere approach to air quality modeling, and to ensure a consistent scientific basis and computational efficiency, a unified emission flux modeling approach capable of estimating all or most of the environmentally-dependent emissions is recommended.. This can be accomplished by establishing a model platform containing representations of the basic chemical and physical mechanisms for mass fluxes of gaseous and particulate emissions. The modeled emissions will be merged by SMOKE with reported emission data from an inventory and supplied to the Community Multiscale Air Quality (CMAQ) model, a regional Eulerian grid model. In some instances, modeling of bi-directional fluxes will be necessary, which may require a closer coupling with CMAQ to accommodate reinitialization of the concentration field at each time step.