The regularization term, λ in Equation , imposes a cost on the departure of the posterior emissions from the prior emissions. In this work, we chose a value of 25 because it balances the desire to maximize the improvements in the model (lower grid residuals) while minimizing the departure from the prior (lower emission residuals). By selecting this value, we achieve most of the improvements in the correlation coefficient of the model without ending up with unrealistic scaling factors. The algorithm then balances the cost in the change of the emissions with the cost of the mismatch between the GCAS retrievals and the sum of the scaled fields from the source apportionment simulations. We assume as a prior that all scaling factors are 1.