Based on its geographic similarity and nested structure, a chemical transport and transformation model developed in The Netherlands was adopted to a nine-parish, 5,400-km2 area in southern Louisiana, USA, and tested for its ability to predict concentrations in the environment. SimpleBox 2.0 represents a class of models that compartmentalize the air, water, soil, sediment, and plants into boxes while maintaining a high degree of detail for processes within and between boxes. Past use has been in the evaluative mode, primarily where qualitative predictions of chemical behavior and distribution are made. Limited testing of model-predicted versus measured concentrations have been attempted. In recent years, quality and quantity of emission and monitoring data have improved dramatically. Such information was used in calibration and validation exercises with eight chemicals in the Louisiana chemical corridor, which receives inputs from urban, industrial, and agricultural sources. Geographically, the corridor was nested within the state of Louisiana, which was in turn nested within the continental United States. Parameter sensitivity studies, including transport coefficients, temperature, and degradation half-life revealed that the latter produces the largest range of variation in predicted concentrations. Published half-life data were used with benzene, vinyl chloride, 1,1,1-trichloethane, and atrazine in a calibration phase with 1995 monitoring data at steady state; this allowed selection of the appropriate emission database. A validation exercise was performed with toluene, styrene, trichloroethylene, and metribuzin. Predictions were compared to average measured concentrations. Atrazine and metribuzin reside primarily in the water; the others reside in the air. The predicted concentrations for benzene, metribuzin, and trichloroethylene were low by a factor of less than two. Vinylchloride, toluene, and 1,1,1-trichloroethane were low by factors between 3 and 10. Styrene and atrazine were low by factors of 45 and 65, respectively.