http://capitawiki.wustl.edu/index.php/20050605_DataFed_and_FASTNET_Tools_for_Agile_Air_Quality_Analysis

1. DataFed and FASTNET Tools for Agile Air Quality Analysis Husar & Poirot

5. Current Data Connectivity Currently, most of the data used in the PM management process are housed in the central AIRS database, populated by mandated data submissions by the states. AIRS has provisions for ‘pre-packaged’ reports, mostly reporting summaries pertinent to regulatory process, but it does not have facilities to perform detailed specialized analysis of the raw data. For this reason, past projects at the Center for Air Pollution Impact and Trend Analysis (CAPITA) at Washington University with the EPA provided access to the raw AIRS data, converted data into a uniform “Voyager” format, and distribute to states and other agencies. Similar data access and delivery systems were built by CAPITA for individual states, including California. AirNOW is the EPA’s database for collecting near real time air quality monitoring data from the states. It is currently centralized and focused on ozone and particulate matter (PM) but contains limited contextual information because it is not linked to other systems such as satellite data, weather or model forecasts. The addition of satellite imagery could provide valuable context for the interpretation of the surface air quality data in AirNOW. In 1999, the U.S. Environmental Protection Agency announced a major initiative to improve visibility in national parks and wilderness areas by reducing regional haze. In support of the resulting Regional Haze Rule, the EPA and five Regional Planning Organizations (RPOs) have established the Visibility Information Exchange Web System (VIEWS, 2002) to facilitate the exchange of data. VIEWS is an important resource for inclusion in a federated PM network. It should be noted that the PM air quality management process does not use dedicated, ‘hard-wired’ Decision Support Systems (DSS). The management decisions are built mostly on human decision hierarchy. Human decisions makers rely on expert judgment and on the richness and diversity of environmental data. The required data for an AQ decision support system come from many disparate sources, e.g. point and area source data, air quality monitoring by many sensor types, weather data, as well as data on effects, e.g. visibility degradation. The existing centralized federal data management system may be appropriate for enforcement. However, for SIP’s and other analyses it is too rigid, and insufficient in content. Hence, the development and implementation of an agile federated information system is an attractive architecture for AQ decision support.