Integrated assessment models for air quality control at local level

Poor air quality is dangerous for health, the environment and many industrial activities; recently, it has been correlated to the pace of coronavirus outbreak in some areas. From an environmental regulatory perspective it is a challenging problem, since regulators seem to be missing decision support systems to tackle the issue and come up with balanced policies. We advocate the use of integrated assessment modelling (IAM) as a tool of decision support system for regulators that are in charge of air quality control. Since pollutants in the atmosphere depend on multiple sources of emission and some of them have non-linear reactions when in contact with other substances, traditional models of response for air quality pollution do not perform well. IAMs allow for multi-objective optimization, also taking into account the costs and benefits of emission reduction in a Pareto-optimality framework of analysis.