| Abstract: | Optimization models for the design of regional air quality control strategies have been developed under the assumption that the annual frequencies of the different meteorological conditions remain constant from year to year. This paper demonstrates empirically that this assumption is not correct, and that the solutions of such models lead either to violation of the annual air quality standard or to unnecessarily high costs for pollution abatement. A chance-constrained, geographically based approach is formulated to account for the interannual randomness of the meteorological conditions and for the locations of pollution sources and receptors and is applied with different approximation methods. The policy implications of the results in terms of optimal standard selection and implementation of the optimal chance-constrained pollution abatement plan through decentralized decision-making by individual pollution sources are assessed. |
