Atmospheric Cluster Dynamics Code: a flexible method for solution of the birth-death equations

TLDR: The Atmospheric Cluster Dynamics Code (ACDC) as mentioned in this paper was created to study the first steps of atmospheric new particle formation by examining the formation of molecular clusters from atmospherically relevant molecules.

Abstract: . The Atmospheric Cluster Dynamics Code (ACDC) is presented and explored. This program was created to study the first steps of atmospheric new particle formation by examining the formation of molecular clusters from atmospherically relevant molecules. The program models the cluster kinetics by explicit solution of the birth–death equations, using an efficient computer script for their generation and the MATLAB ode15s routine for their solution. Through the use of evaporation rate coefficients derived from formation free energies calculated by quantum chemical methods for clusters containing dimethylamine or ammonia and sulphuric acid, we have explored the effect of changing various parameters at atmospherically relevant monomer concentrations. We have included in our model clusters with 0–4 base molecules and 0–4 sulfuric acid molecules for which we have commensurable quantum chemical data. The tests demonstrate that large effects can be seen for even small changes in different parameters, due to the non-linearity of the system. In particular, changing the temperature had a significant impact on the steady-state concentrations of all clusters, while the boundary effects (allowing clusters to grow to sizes beyond the largest cluster that the code keeps track of, or forbidding such processes), coagulation sink terms, non-monomer collisions, sticking probabilities and monomer concentrations did not show as large effects under the conditions studied. Removal of coagulation sink terms prevented the system from reaching the steady state when all the initial cluster concentrations were set to the default value of 1 m−3, which is probably an effect caused by studying only relatively small cluster sizes.