1. Air Quality Emission inventories

2. What is an Emission Inventory?
Atmospheric emissions inventory is a compilation of all sources of air pollution within an area

3. Why Emission Inventory?
Air quality assessment
Evaluating the sources
Air Quality Management
Abatement strategy
Measure trends over time

4. Detailed description of an inventory:
Geographic area (geographic domain for the inventory)
Pollutants (purpose the inventory)
Source Categories (Anthropogenic/Natural sources)
Modelling (Geographically/time resolution, Pollutant species)
Spatial resolutions
Temporal resolution (variability of emissions over time)
Speciation (Disaggregates into indiv. chemical comp.or groups)
Base year (reference year)

5. Two different approaches: a) top-down inventory
Activity statistics (consumption,production,vehicle type etc)
Population statistics, land-use and emission factors
Detailed information about
location not required

6. Two different approaches: b) bottom-up inventory
Detailed knowledge of source types and locations
Specific emissions for individual sources
Consumption and or production
data using emission factors

7. Emission Inventory Module
Geographical Information System (GIS)
Calculation of Emission
Modeling
Point Sources
Line Sources
Area sources
Industry
Stacks
Consumption
Emission
Emission factors
Time variation
Static road data
(Geography, road classification)
Dynamic traffic data
Emission factors
Time variation
Consumption
Emission
Source sector
Fuel
Emission factors
Time variation

8. Emission Inventory Features
Emission inventory Lookups
Point emission
Line emission
Area emission

9. Emission inventory lookup data
Fuels
Source sectors
Time variations

10. Cleaning Device and cleaning efficiency Process data
Point Source data
Owners
Industries
Stack data
Cleaning Device and cleaning efficiency
Process data
Process emission data
Process consumption and emission factor data

11. Concept of the Point Source
Industry
Stack
Stack
Cleaning
device
Cleaning
device
Process
Process

12. Point Sources - Input Data
Industries
Stacks
Cleaning devices
Processes
Processes emission/consumption data
Fuels
Time variations
Source sectors
Emission factors

13. Line Sources
Vehicle emissions from road transport are provided for sections along the line of the road

14. Line source data Traffic lookup data Road node definition Static data
Vehicle classes
Road classes
Time variation
Road node definition
Static data
Dynamic data
Road link vehicle distribution
Traffic emission factors

15. Concept of Line Sources
ROAD LINK DATA: ID
NAME
GRADIENT (%)
LENGTH
DIRECTION
LANE WIDTH
ROAD CLASS
ADT
SPEED
Lane 2
Width
ADT
Speed
End node
Sub nodes
Lane 1
Width
ADT
Speed
Lane direction 1
(start to end)
Start node

16. Line Sources - Input Data
Traffic look up data
Road classes
Vehicle classes
Geography
Road nodes
Sub nodes
Static traffic data
Road links description
Dynamic traffic data
Speed
Annual daily traffic
Emission factors/dependencies

17. Traffic Emission Factors
Select the factor set year
Emission calculation vehicle classes (ECVC)
Emission calculation vehicle classes – Registration vehicle class Distribution
Average fuel consumption
Basic and averaging factors
Speed dependency factors
Road gradient factors
NO2 percentage of NOx
PM10 data

18. Area Sources
Smaller or more diffuse sources of pollution (home heating, public services etc.) are provided on an area basis either for administrative areas, such as counties, municipality etc, or for regular grids.

19. Concept of Area Sources
Area sources
Regions ID
Emission/Consumption Value
Emission factors

20. Area Sources Stationary combustion Process emissions and evaporation:
Consumption dataset for combinations of source sectors and fuel
Emission factors for different components for the same combinations
Process emissions and evaporation:
Emission dataset for combinations of source sectors and components

21. Regions (polygons) and grids Fuels/components Source sectors
Area Sources -Input
Regions (polygons) and grids
Fuels/components
Source sectors
Time Variations
Consumption or emission data
Emission factors

22. Exercises

23. Build Emission Inventory Database Exercise
Check that all the components needed are predefined. If not, import missing components.
Import following data
Source sectors
Time variations

24. Time Variations
Factors for scaling annual emissions/consumptions to weekly, daily,hourly or half hourly emissions
Hierarchical structure (sub-time variations)
Specific validity period (1995, w1-w52 etc)
Sum of factors for all time steps is 1.0
Sub-factors are multiplied to find the most detailed factor

25. Point source emission:
Import Owner and Address register
Import Industry register
Import Stack data
Import Process Data
Import Process Consumption and Emission

26. Emission Inventory Exercise
How many industries are located in ”KPIZ”?
How many processes have source sector 1102, what it is?
Is there any cleaning devices in the project?
How many stacks is connected to the industry , EMAL?
How many processes are connected to stack ?
What type of data are connected to the processes? Which components or fuels is used?
Is there any emission factors for these processes?

27. Emission Inventory Exercise
Create a new industry and a stack for the industry.
Add physical parameters for the stack.
The data provided by the industry is consumption of ton/year oil for a boiler.
Consumption emission factor for the boiler is 10 kg SO2 pr ton coal.

28. Area source emission:
Import area source datasets for gridded emissions
Import gridded emission data

29. Check the imported data by:
Number rows imported
Random sample test
Total amount of emissions, if number and locations are correct

30. Traffic source emission:
Import Time variation
Import Road class
Import vehicle class
Import road notes
Import static traffic data
Import dynamic traffic data
Import vehicle distribution
Import traffic emission factors

31. Check the imported data by:
Number rows imported
Random sample test
Road note and road links on GIS