The impact of vehicle emissions on the global climate has drawn increasing concern in the past few decades. Patterns of housing development determine travel behaviors, thus affecting transport-related greenhouse gas emissions. Here, a bi-level model is established to describe the relationships among housing allocation, traffic volume, and CO_(2) emissions using a continuum modeling approach. The user-equilibrium condition is achieved in the lower-level, and the minimum CO_(2) emissions are obtained by optimization the housing allocation in the upper-level. A hypothetical city is considered with one central business district (CBD) and a road network that is densely distributed outside of the CBD. Several commuter classes with different values of time are considered. The finite element method, the Newton-Raphson algorithm, and the convex combination approach are applied to solve the constrained optimization problem established in the bi-level model. A numerical example is given to demonstrate the effectiveness of the method.
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