Estimating Emissions from Sources of Air Pollution
6.1 Development of an Emissions Inventory
6.1.8 Compiling an Emissions Inventory
The development of an emission inventory is a multi-step process as discussed below. It consists of:
1. Data collection
Data must first be collected. Decisions must be made concerning the relevant emission sources to be included in the inventory. Determinations must also be made as to when emission factors will be used, when emission models will be used, and when emission measurements need to be made. The best sources of data must be identified, and then all relevant data must be collected. In some cases, relevant emissions data will be considered to be confidential. Steps must be taken to collect this data in a form that meets the confidentiality requirements and still allows an adequate assessment of the data. This can be a challenging process at times. In other cases, the data collected is highly uncertain or must be extrapolated to areas where data is scarce. As discussed in Step 2, the uncertainty involved in this data must be estimated and noted.
2. Uncertainty Assessment
The uncertainty in the emission estimates for the various sources must be determined. Otherwise, the policy makers or other users of the inventory can be given a false assessment of the meaning of the inventory and how much it can be relied upon. All emission inventories involve uncertainties. The inventory developers must assess those uncertainties and make that information available along with the inventory information.
3. Definition of key emission categories
As the inventory data is brought together, it normally becomes apparent that there are clear breakdowns of the data that allow the proper grouping of the emission sources into relevant categories. Common emission source categories were discussed in sub-section 6.1.4.
4. Time series consistency
Inventories are often use to determine progress in meeting emission reduction goals. Thus, inventories compiled for different years are compared to see how emissions are changing. If inconsistent processes are used to build inventories for different years, then the inventories cannot be compared. In cases where inventories will be compared over different years, then care must be taken to ensure that similar approaches are used to build the inventories. Even in cases of emission uncertainties, inventories for different years that are developed using consistent approaches can provide meaningful indications of emission trends.
5. Quality Assurance
While emission inventories are always uncertain, efforts must be made to insure the best possible emission values. All emission inventory development process must contain a quality assurance element to minimize errors and to ensure consistency.
6. Reporting
Inventories are only worthwhile if they are summarized in formats that can be adequately used by the persons for which the inventory was developed. Care must be taken to present inventory data in a consistent and meaningful way.
1. Data collection
Data must first be collected. Decisions must be made concerning the relevant emission sources to be included in the inventory. Determinations must also be made as to when emission factors will be used, when emission models will be used, and when emission measurements need to be made. The best sources of data must be identified, and then all relevant data must be collected. In some cases, relevant emissions data will be considered to be confidential. Steps must be taken to collect this data in a form that meets the confidentiality requirements and still allows an adequate assessment of the data. This can be a challenging process at times. In other cases, the data collected is highly uncertain or must be extrapolated to areas where data is scarce. As discussed in Step 2, the uncertainty involved in this data must be estimated and noted.
2. Uncertainty Assessment
The uncertainty in the emission estimates for the various sources must be determined. Otherwise, the policy makers or other users of the inventory can be given a false assessment of the meaning of the inventory and how much it can be relied upon. All emission inventories involve uncertainties. The inventory developers must assess those uncertainties and make that information available along with the inventory information.
3. Definition of key emission categories
As the inventory data is brought together, it normally becomes apparent that there are clear breakdowns of the data that allow the proper grouping of the emission sources into relevant categories. Common emission source categories were discussed in sub-section 6.1.4.
4. Time series consistency
Inventories are often use to determine progress in meeting emission reduction goals. Thus, inventories compiled for different years are compared to see how emissions are changing. If inconsistent processes are used to build inventories for different years, then the inventories cannot be compared. In cases where inventories will be compared over different years, then care must be taken to ensure that similar approaches are used to build the inventories. Even in cases of emission uncertainties, inventories for different years that are developed using consistent approaches can provide meaningful indications of emission trends.
5. Quality Assurance
While emission inventories are always uncertain, efforts must be made to insure the best possible emission values. All emission inventory development process must contain a quality assurance element to minimize errors and to ensure consistency.
6. Reporting
Inventories are only worthwhile if they are summarized in formats that can be adequately used by the persons for which the inventory was developed. Care must be taken to present inventory data in a consistent and meaningful way.
