In this article, we present a model order reduction method based on time-sc
ale analysis for chemical reaction systems. The method can be applied to an
y reaction system exhibiting multiple time scales and described by the set
of differential equations dc/dt = f(c), where c (dimension n) is the vector
of chemical species and f is the operator describing the kinetics. From th
e Jacobian of the kinetic operator and its eigenvalues, regions which exhib
it different timescale behavior are identified. Within each region, the set
of fast variables (dimension nf) is identified and these are linearly lump
ed into a smaller set of pseudo species. The fast and slow time scales can
be separated, and the concentrations of the fast species can then be approx
imated by explicit algebraic expressions. Thus, the dynamics of the reactio
n system can be simulated by a smaller set of variables (dimension n-n(f))
characteristic of each region. The generated reduced models are non-stiff,
computationally efficient, and valid over a range of initial conditions. Th
e use of the method is illustrated by simplifying a description of cyclohex
ane oxidation.