This threaded discussion forum is intended for general OTAG topics that are not covered by the discussions on other pages dealing with specific topics.
Abstracts due: Sept 23, 97
Acceptance by: Dec 5, 97
Manuscript due: Feb 1, 98
Meeting: June 14-19,98
I am proposing that
- you all have a good look at your own backlog of unpublished work
- examine the AWMA program
- submit your abstracts to AWMA
- submit your abstracts to this OTAG AQA website - We will have separate page for those
Considering the completeness of much of the material, I feel that this will not prevent us from proceeding with new work between now and Feb 1, 98 whae the manuscripts are due. As always, the papers can and should be 'as short as possible but not shorter'. So, the publication effort should be an excercise in filtering, aggregating and integrating the existing material with an eye on high info density, complementarity of content minimum redundancy.
This is good place to state your respones and/or questions.
EPA's proposed SIP call includes a paper by Rao( 10:Porter, P.S., S.T. Rao, E. Zalewsky, I Zurbenko, R.F. Henry, and J.Y. Ku, "Statistical Characteristics of Spectrally-Decomposed Ambient Ozone Time Series Data," Report to the Ozone Transport Assessment Group, 1996.) in their weight of evidence; I would like to review in detail. is it avaialble? Could not find in technical papers on AQA website. on 2/5/98
EPA's proposed SIP call includes a paper by Rao( 10:Porter, P.S., S.T. Rao, E. Zalewsky, I Zurbenko, R.F. Henry, and J.Y. Ku, "Statistical Characteristics of Spectrally-Decomposed Ambient Ozone Time Series Data," Report to the Ozone Transport Assessment Group, 1996.) in their weight of evidence; I would like to review in detail. is it avaialble? Could not find in technical papers on AQA website. on 2/5/98
An appreciation of the strengths of both models and observations can assist the understanding of current analyses and lead to improved techniques. A model's strength is its ability to (1) integrate an enormous spectrum of data (e.g., emissions and meterological variables) and process understandings (e.g., chemical mechanisms and flow phenomena), and (2) serve as an exceptional space and time mapping tool. This latter attribute reflects the model's unique ability to predict into the future and to supplemant (or fill in) present gaps in observed data. The process formulations imbedded in models enable the addressing of so many "what if" questions related to emissions control. However, models are engineering tools that invoke substantial approximations of scientific understandings of natural phenomena, and both their formulations and application methods reflect engineering principles more than fundamental science. Observations, on the other hand, provide a basis for testing and diagnosing models, but in some instances can capture process-type relationships all by themselves (e.g., the emergence of observational-based models for defining NOx and VOC control preferences). Applied in isolation, the use of models or observations is not acceptable. Space and time constraints often bias the interpretation of observational analyses (i.e., analysis results reflect time and space of monitors which may or may not be reflecting the scales of concern). Models suffer from a very large spectrum of weaknesses, because they attempt to portray so many phenomena. Most critical though is the risk of using a potentially-biased model that is assumed to be bias-free. The integrated use of observations and models mitigates the individual weaknesses of both approaches and produces a powerful air quality management tool.
Reference:
National Research Council, "Rethinking the Ozone Problem in Urban and Regional Air Pollution," National Academy Press, 1991.
| Location Name | Latitude | Longitude | Elev. (m) |
| New England; Whiteface Mt, NY: | 44.365 | 73.902 | 1480 |
| Southeast; Great Smokey Mt, TN: | 35.631 | 83.944 | 793 |
| Midwest; Boston Mt, AK: | 35.8 | 93.2 |
| In order to add a new entry to this list, you must be registered with the OTAG/AQA Peoples Page. |