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Air Toxic Emissions Inventory


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Benzo(a)pyrene Emissions Assessment (2002)

2002 Inventory of Toxic Air Emissions

2001 Inventory of Toxic Air Emissions

1999 Inventory of Toxic Air Emissions

1998 Inventory of Toxic Air Emissions

1997 Inventory of Toxic Air Emissions

1996 Inventory of Toxic Air Emissions

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Air Toxics Emission Protocol for the Great Lakes States

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Comments or questions about the Commission's air quality initiatives? Contact Jon Dettling at dettling@glc.org


The RAPIDS Data Model

The RAPIDS data model is the cornerstone of the RAPIDS system. It consists of a core data model that includes entities that are shared by most mission critical applications, such as emission inventory, permitting, compliance. As more applications are added to the RAPIDS system, the core data model will be extended to include the additional entities/attributes needed to support these new applications. As such, the core data model is the foundation upon which the enterprise is built. The stronger the foundation, the more robust the enterprise.

The RAPIDS core data model consists of seven modules: Geographic, Legal, Source, Device, Process, Stream and Emission Estimation. RAPIDS is geo-referenced and locations can be entered as either points, lines, or polygons.

The data flow in RAPIDS is illustrated below. RAPIDS follows a geographic-source-device-process-stream hierarchy. At the geographic-source-device levels, physical/locational information are stored and managed. Every source type has a process, every process is located at a device and every device is located at a source. Processes are associated with input and output streams that transfer energy and material into and out of the process. Output streams transport air pollutant emissions (gaseous streams), water contaminants (liquid streams), solid and hazardous waste materials (solid streams), and products (product streams) generated by a process. Input streams/materials feed device/process combinations and are transformed into output streams/materials.

Both physical connectivity between devices and logical connectivity for various device/process combinations are tracked. Logical connectivity allows us to properly track streams for different device/process combinations when the pathway is process-specific. For example, a boiler burning oil might have different controls than when the same unit is burning gas. In RAPIDS, that situation would be represented by two separate processes and the logical connectivity would allow the user to track the associated streams through different pieces of control equipment.

The following features of the RAPIDS data model provide the flexibility needed to handle multimedia environmental data management needs, as well as complexity of device and process connections:

  • There are a relatively small number of tables required to quantify and characterize sources of emissions. This is achieved by a design that is highly table-driven.


  • A full record, rather than a single field, is used to store information on a data item. This allows a means of providing complete information on the data item of interest, including the context (when, where, and subject material), confidentiality, and reference information (other documents, who and when the data were entered). This is referred to as a "flexible attribute" format which contrasts with the fixed attributes used in most other data models (see discussion below on the Activity record structure).


  • Only a single source table, a single device table, and a single process table is needed to contain data on all types of sources, devices, and processes, including both point and area sources.


  • Entities can be grouped as needed and Activity records can be associated with such groups (e.g., a group of related processes in use during an operating scenario).

The RAPIDS data model provides maximum flexibility in the types and volume of data that can be stored. The RAPIDS data model:

  • Is based upon conventional and not regulatory principles. In this way, as regulations change, your database can change with them without requiring a major restructuring of the database.


  • Is applicable to both public agencies and private industry. The core entities and relationships are defined for the proper management of environmental data by national, state, and regional/local agencies. The model is also defined for the comprehensive management of environmental and process data by individual facilities. In this way, agencies and industry are able to communicate information in a consistent and understandable way.


  • Is able to manage data from any media ( e.g. air, water, waste). The model supports processes with input and output streams of any media covering both environmental developing integrated applications such as inventory, monitoring, process optimization, environmental permitting, reporting, and compliance.


  • Represents both the physical and logical structures of a source. Sources and devices have physical locations. Devices are physically linked via connections. Processes operate at or within a device and physical streams enter and leave the processes. However, the model also allows you to group sources, devices, processes, and streams for representing logical associations (e.g. area sources, process units, and operating scenarios).


  • Integrates the management of point and area sources. The key entities and relationships describing point sources are applicable to area sources. Area sources are viewed as source groups, optional consisting of individual sources (such as large dry cleaners). The benefit is that the data storage, estimation, and reporting functions can done uniformly for both types of sources.


  • Is upwardly compatible with existing systems. Most current data models for environmental facility data use a facility/point/segment/emittant hierarchy. The RAPIDS data model uses a source/device/process/stream/material hierarchy and is therefore, consistent with this hierarchy.


  • Is flexible. The core entities and relationships as well as the reference tables have been designed so that new attributes and associations can be accommodated in most cases without a change in the data model. Instead, the system is data-driven modification of reference table data enables you to change the operation of the system to meet new requirements.




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