AQ Data Systems and Processing Centers
Back to <Data Summit Workspace
Back to <Community Air Quality Data System Workspace
Note: This page was originally produced for the EPA data summit in RTP, Feb 12 & 13 2008.
The version existing at the time of the AQ data summit can be viewed via the history tab.
- Add New Data System Profile or Submit Word Doc
- Data System Profile Development
- Data System Connectivity Matrix
- CUAHSI Hydrologic Data System; Observational Data Model
Data System Profiles
Individual data system descriptions are editable via their individual pages; click the link in the left column to access those pages.
| Data System Abbr | Data System Name | Organizations | Description |
|---|---|---|---|
| 3D-AQS | Three Dimensional Air Quality System (3D-AQS) | University of Maryland, Baltimore County. Partners include Battelle Memorial Institute, University of Wisconsin, NASA, EPA, NOAA, and CDC. | The 3D-AQS project is using a range of remote sensing instruments to expand EPA’s AQS into a three-dimensional system of nation-wide coverage, with the goal of providing information on the vertical and horizontal distribution of pollutants, particularly aerosols and particulates. The 3D-AQS project has three key initiatives. First, the project is improving existing data and visualization methods by developing finer resolution products, quantitative analysis of the satellite data with ground-based data, and creating new visualizations of 3D air quality information. Second, the project integrates satellite and lidar data into EPA’s AirQuest system, a database that merges AQS and AIRNow data with other monitor, model, and socioeconomic data, making the NASA data easily accessible. Third, the Integrating satellite Data from Environmental Applications (IDEA) product, which unites a range of satellite data in near real time, is bing migrated to an operational environment within NOAA’s National Environmental Satellite, Data, and Information Service (NESDIS). IDEA is being enhanced to include data from GASP and the ground-based LIDAR sensors. An end user advisory committee comprised of air quality forecasters and analysts is providing input and advice at each stage of the project. |
| AERONETd | No Distributor | ||
| AIRNOW | No Distributor | ||
| AIRNow | AIRNow | EPA, National, State and Local Partners | |
| AMAP G | No Distributor | ||
| AQS d | No Distributor | ||
| AQS h | No Distributor | ||
| ASOS STI | No Distributor | ||
| ASTR FIREd | No Distributor | ||
| ASTR FIREm | No Distributor | ||
| ATADV | No Distributor | ||
| AVHRR | No Distributor | ||
| Africa Dust | No Distributor | ||
| Astrophoto | No Distributor | ||
| CALIPSO | No Distributor | ||
| CASTNET | CASTNET | EPA, NADP/NTN, CAPMoN | The Clean Air Status & Trends Network (CASTNET) is a rural, regional monitoring network designed primarily to measure seasonal and annual average concentrations and depositions over many years. CASTNET measurements are used to track long-term temporal and spatial trends due to changes in air quality. Data is used to assess the environmental impacts as a result of the U.S. EPA’s emission reduction programs (in particular, the Acid Rain Program (ARP) and the NOx Budget Trading Program (NBP)). In the future, CASTNET is expected to serve as an assessment tool for the Clean Air Interstate Rule (CAIR). Data measured from the CASTNET network is used by universities, ecologists, tribes, as well as federal regulators, as it is the only national long-term, regional, rural monitoring network. |
| CIESIN GPW | No Distributor | ||
| CIESIN POP | No Distributor | ||
| CMAQ | Community Multi-scale Air Quality Model (CMAQ) | EPA | The CMAQ model is a comprehensive, three-dimensional, grid-based Eulerian air quality model designed to estimate ozone and particulate concentrations and deposition over a broad range of temporal and spatial scales. CMAQ, which is a publically available, peer-reviewed, state-of-the-science model, consists of a number of science attributes that are critical for simulating the oxidant precursors and non-linear organic and inorganic chemical relationships associated with the formation of ozone and sulfate, nitrate, and organic aerosols. CMAQ also simulates the transport and removal of directly emitted particles which are speciated as elemental carbon, crustal material, nitrate, sulfate, and organic aerosols. Additionally, the multi-pollutant version of CMAQ simulates mercury and over 30 toxic volatile organic compounds and metals.
CMAQ is being used by the US EPA, State and Regional environmental organizations, universities, and independent research organizations to provide data in support of a wide range of analyses linked to understanding the spatial and temporal patterns of pollutant concentrations and deposition in relation to emissions and meteorology and as part of regulatory programs for evaluating the effectiveness of emissions control strategies for attainment of National Ambient Air Quality Standards. The US EPA’s Office of Air Quality Planning and Standards in collaboration with the Office of Research and Development have recently run CMAQ for the full year of 2002 using a 2002-based air quality modeling platform. |
| CMAQ Baron G | No Distributor | ||
| DataFed | DataFed | Washington University | DataFed is Web services-based software that non-intrusively mediates between autonomous, distributed data providers and users. DataFed is designed in accordance with the GEOSS architecture; It provides standard interfaces to heterogeneous distributed data, fosters data integration and use with processing web services and tools, and collects metadata and user-feedback on datasets. DataFed also provides standards-based data feeds to the NASA Giovanni System. |
| EDGAR | No Distributor | ||
| EDGAR WCS | No Distributor | ||
| EMF | Emissions Modeling Framework | EPA | Emissions Modeling Framework (EMF) is an “expert system” software tool for EPA staff and contractors involved in emissions modeling. “Emissions modeling” is process of converting emission inventory data from its raw form to the forms needed by air quality models used to predict ozone, particulate matter, and hazardous air pollutants in the ambient air. This software is needed to improve efficiency and quality control of in-house and contractor emissions modeling and to provide transparency and data access to those who need information about the work of those modelers. Additionally, we anticipate making this software available to those outside of EPA so that they can have a copy of this same tool; these users would not interact with the EPA system, but rather have their own system installed at their location.
The software is a client-server application based on a three-tier architecture (see http://www.sei.cmu.edu/str/descriptions/clientserver.html). The three tiers are (1) the user interface client, (2) a database management layer, and (3) a middleware layer between the other two tiers that is used to implement the business logic of the software application. This architecture is needed to support the requirement that both data and a set of compute servers be shared among a set of users. The EPA installation of the software has user access only from inside the EPA/RTP firewall. The EMF provides integrated quality control processes to foster high quality of emissions results, data handling, organization of data in a central database server, tracking of emissions modeling efforts, and real-time accessibility of information. A user interface will allow non-experts to access emission modeling capabilities. The interface will be able to facilitate various activities related to emissions modeling in addition the computation of emission inputs for air quality models. Such activities include 1) the acceptance of new EPA-provided data into the system with appropriate quality control and tracking; 2) set-up and execution of emissions modeling for air quality modeling applications; 3) quality assurance of emissions modeling results; 4) reporting and archiving of reports of emission inventory data; and 5) accessing projection and control information that is used for creating future-year emissions estimates. |
| EPA AIRQuest Data Warehouse | EPA AIRQuest Data Warehouse | EPA | The audience, at present, is INTERNAL EPA analysts, application builders, and data integrators. AIRQuest was constructed as a true data warehouse, built to integrate data from various source data systems, to enable complete air quality analyses from a single system. AIRQuest harvests data from AQS, NEI, and AIRNow, integrating that data spatially and temporally. It also features datasets outside of EPA that are useful for analysis -- meteorological, census, etc. |
| EPA AQS | Air Quality System (AQS) | State, local, tribal, and other federal agencies submit and own the data in AQS. | AQS is the national repository for ambient air quality data. It is intended primarily or State, Local, and Tribal organizations to supply their data to the USEPA. However, the system does allow for the extraction of data through standardized reports and on-line forms to view the data. |
| EPA AirMarkets | No Distributor | ||
| ESIP | ESIP | NASA, NOAA, EPA are strategic partners | |
| GASP | No Distributor | ||
| GASP tiff | No Distributor | ||
| GDSG Fire | No Distributor | ||
| GFED WCS | No Distributor | ||
| GFED8day | No Distributor | ||
| GIOVANNI | GIOVANNI | NASA | The Goddard Online Interactive Visualization ANd aNalysis Infrastructure or "Giovanni" is an online tool allowing researchers, students, and application users to easily explore, inter-compare, and analyze remote sensing data using only a Web browser. |
| GOCART G OL | No Distributor | ||
| GOES | No Distributor | ||
| GOES 12 | No Distributor | ||
| GOMEm | No Distributor | ||
| GSFC NO2 OL | No Distributor | ||
| GeoWeb | Environmental Geoweb Service (GeoWeb) | EPA | The Environmental Geoweb Service (Geoweb) is a service that locates, indexes, and presents geographically-referenced scientific data so that EPA scientists can perform cross-disciplinary searches for data of relevance to their work, and can publish data from their research that might benefit other scientists. The Geoweb Service has been designed and developed within the EPA and is currently in an early stage of production use.
The Geoweb Server searches for and indexes geographically-referenced scientific data made public on the servers of organizations outside of the EPA, or on selected data servers within the EPA network. The outside sources are currently concentrated at NASA, NOAA, and the Center for Ocean-Land-Atmosphere. The inside sources include Community Mesoscale Air Quality data. The Geoweb Service has the potential to index any geographically-referenced data published on servers inside or outside of the EPA. User connection to search the index is only available from workstations on the EPA internal network. The Geoweb Server normally performs its dataset indexing at a weekly interval. The Server is instructed to web-crawl an adjustable list of scientific data servers. Metadata about the files found on the indexed servers is brought back to EPA’s Geoweb Server and assembled into an xml database. This database contains all computer-obtainable metadata about each indexed file, and the location of the file on the Internet. The data files themselves remain on the servers where originally published. Currently, about 700,000 scientific files are indexed. Users of the Geoweb Service connect to it at http://gds.rtpnc.epa.gov. They can follow links to specific data sources found on the home page, or perform searches for data by providing search terms. The searches execute quickly because the metadata being searched is all local to the Geoweb Server. The user is presented with a search results list, similar to Google or Yahoo search results. The user can then view the metadata associated with each dataset, or initiate a visualization of the data contents. The visualizations are performed using the World Wind Geo tool, based on NASA’s World Wind, and developed here at EPA; or by using Google Earth, NASA’s World Wind, or ArcGIS Explorer. The reading of metadata and the visualization of the data correctly referenced to the World Wind, Google Earth, or ArcGIS globe is supported for all data set types. Data served from OPeNDAP servers can also be subsetted by geographic bounding boxes, date, or time and the data subset can then be downloaded across the Internet to the user’s workstation. |
| HEI | HEI Air Quality Database | Health Effects Institute | The HEI Air Quality Database focuses on levels of PM2.5 components and gaseous pollutants at and near sites in the EPA's PM2.5 Chemical Speciation Trends Network (STN) and State, Local and Tribal air monitoring stations (SLAMS). The Database was originally made available in association with HEI's Request for Applications 05-1, Studies to Compare Components and Characteristics of Particulate Matter Associated with Health Effects, which was issued in the summer of 2005. The Database is now available to investigators interested in using the information for studies on air quality and health. Currently, the Database contains information on speciated PM components and gaseous pollutants at these sites for the years 2000-2006 and it is anticipated that the information will be updated regularly for the next 2-3 years. |
| MNEI Area | No Distributor | ||
| MNEI Mobile | No Distributor | ||
| MNEI NonRoad | No Distributor | ||
| MNEI Point | No Distributor | ||
| MODIS FIRE | No Distributor | ||
| MODIS IMG | No Distributor | ||
| MODISd G | No Distributor | ||
| MODISm G | No Distributor | ||
| MOPITT Day | No Distributor |
