People spend the majority of their time in residences and the health burden of indoor air is significant. However, the definitions of "acceptable" and “good” indoor air quality (IAQ), and the most effective, energy efficient methods for achieving various levels of IAQ are still matters of research and debate. Current ventilation standards focus on minimum requirements for overall and mechanically provided ventilation rates, and vented combustion equipment, and require only the installation of kitchen and bath exhaust fans for source control. These standards generally are regarded as health protective, yet they are based only on expert judgment with minimal rigorous scientific justification. The goal of this presentation is to describe work that has been done at LBNL to develop a data-driven, physics-based modeling approach to assess energy and indoor air quality health impacts across the U.S. population for both new and retrofitted homes. The goal of the modeling framework is to develop a computationally efficient modeling platform to determine IAQ and energy impact of changes in residences such as ventilation changes, filtration, and air cleaning. This framework will allow us to determine the population wide impact of widespread implementation of various standards on health and energy demand. The presentation will focus on describing work that has been done to fill critical gaps in developing this framework including identification of priority pollutants, development of a health impact assessment methodology, development of an incremental ventilation energy model, and efforts to fulfill key data needs.