Abstract
Air quality managers have traditionally relied on deterministic and statistical approaches for forecasting concentrations. In some parts of the world, concentration forecasts are used to trigger urgent and sometimes drastic preventative measures in the hope that severe pollution episodes are alleviated or avoided altogether. These preventative measures, however, are often applied rather indiscriminately to all emission sources without accounting for specific influence of each individual source on the forecast outcome. This blanket approach fails to improve air quality in a cost-effective manner. Adjoint sensitivity analysis approach provides a unique framework for efficient forecast of the impact of individual sources on short-term air quality. We demonstrate how this method can be used for short-term emission behavior modification resulting in amelioration of pollution episodes.
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Questioner Name: Henk Eskes
Q: Canada has a health index which is based on O3 and NO2, while the US and Europe look only at O3. This makes a significant difference as considering only O3 could result in increased concentrations due to reduced NOx emissions. Should Europe and the US include NO2?
A: Inclusion of NO2 in the Canadian health index is due to an observed association between NO2 and health outcomes (i.e., mortality) in Canadian time series studies. Health Canada maintains that this association is not explained by other species, and therefore, that inclusion of NO2 is not only justified but also necessary. They agree, however, that the observed association does not imply causality and that NO2 may be a proxy for some other pollutants. This lack of causality implies that reductions in NOx emissions may not result in reduction in the associated health outcomes. Therefore, there are good arguments for and against inclusion of NO2 in policy-relevant air quality metrics.
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Russell, M., Hakami, A. (2014). Forecasting Sensitivities: Is Adaptive, Short-Term Air Quality Management a Viable Option?. In: Steyn, D., Builtjes, P., Timmermans, R. (eds) Air Pollution Modeling and its Application XXII. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5577-2_33
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DOI: https://doi.org/10.1007/978-94-007-5577-2_33
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