GEOS-Chem-hyd: enabling source-oriented sensitivity analysis with GEOS-Chem

Abstract. Effective environmental policymaking requires accurate quantification of the impacts on air quality of changes in emissions. Chemical transport models, such as GEOS-Chem, are widely used for such analysis. Traditional methods to compute the relative influence of a change in emissions, or the sensitivity of pollutant concentrations to a change in emissions, with these models often suffer from numerical inaccuracies, especially when evaluating nonlinear atmospheric processes. To overcome these limitations, we integrated a novel sensitivity analysis approach leveraging hyperdual numbers into GEOS-Chem, making GEOS-Chem-hyd. The hyperdual step method accurately calculates first- and second-order sensitivities simultaneously and avoids common numerical errors associated with traditional finite difference methods. The real concentrations as well as first- and second-order sensitivities with respect to emissions calculated with GEOS-Chem-hyd align with the values calculated with GEOS-Chem version 14.0.0 within expected error. Applying GEOS-Chem-hyd to assess how changes in emissions of oxides of nitrogen could be expected to alter ozone, particulate matter, ammonium, and biogenic organic aerosol concentrations demonstrated regional differences and nonlinear influences. As an example of regional variations, the emissions of oxides of nitrogen were shown to decrease biogenic organic aerosol in most areas, except in portions of the boreal forests in Siberia. The nonlinear influence of emissions of oxides of nitrogen on ozone, ammonium, and biogenic organic aerosol was evidenced by second-order sensitivities on the same order of magnitude as the first-order sensitivities. GEOS-Chem-hyd incurs approximately four times greater computational costs than GEOS-Chem, which is competitive with the three GEOS-Chem model executions required for less accurate second-order sensitivities using the central finite difference method. GEOS-Chem-hyd provides a framework for efficient assessment of the influence of new scientific modules, which are easily incorporated into the sensitivity analysis framework, and supports informed emission control policy development through accurate, source-oriented sensitivity analysis.