Air Quality Response Modeling for Decision Support
AbstractAir quality management relies on photochemical models to predict the responses of pollutant concentrations to changes in emissions. Such modeling is especially important for secondary pollutants such as ozone and fine particulate matter which vary nonlinearly with changes in emissions. Numerous techniques for probing pollutant-emission relationships within photochemical models have been developed and deployed for a variety of decision support applications. However, atmospheric response modeling remains complicated by the challenge of validating sensitivity results against observable data. This manuscript reviews the state of the science of atmospheric response modeling as well as efforts to characterize the accuracy and uncertainty of sensitivity results.
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Cohan, D.S.; Napelenok, S.L. Air Quality Response Modeling for Decision Support. Atmosphere 2011, 2, 407-425.
Cohan DS, Napelenok SL. Air Quality Response Modeling for Decision Support. Atmosphere. 2011; 2(3):407-425.Chicago/Turabian Style
Cohan, Daniel S.; Napelenok, Sergey L. 2011. "Air Quality Response Modeling for Decision Support." Atmosphere 2, no. 3: 407-425.