Abstract

Abstract. The Rapid Adaptive Optimization Model for Atmospheric Chemistry (ROMAC) is a flexible and computationally efficient photochemical box model. Its unique adaptive dynamic optimization module allows for the dynamic and rapid estimation of the impact of chemical and physical processes on pollutant concentration. ROMAC outperforms traditional box models in evaluating the influence of physical processes on pollutant concentrations. Its ability to quantify the effects of chemical and physical processes on pollutant concentrations has been confirmed through chamber and field observation cases. Since the development of a variable-step and variable-order numerical solver that eliminates the need for Jacobian matrix processing, the computational efficiency of ROMAC has seen a marked improvement with only a marginal increase in error. Specifically, the computational efficiency has improved by 96 % when compared to several established box models, such as F0AM and AtChem. Moreover, the solver maintains a discrepancy of less than 0.1 % when its results are compared with those obtained from a high-precision solver in AtChem.

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