GIS Assisted Emission Inventory Development for Variable ... · Methodological framework ... Mobile emissions GIS compatible Database Preparation. Spatial Analyst Feature locations

GIS assisted Emission inventory Development for Variable grid Emission

database for Mississippi region

Yerramilli Anjaneyulu,

AgendaMicro scale – Mesoscale ModelingVariable grid emission inventory development requirements Methodological framework GIS layer developmentCalculation and Querying in GIS Output map generation Future scope of the work

Microscale – mesoscale Modeling

This is a study of atmospheric dispersion in the coastal zone using regional ensemble models and multi-model ensemble systems to develop the meteorological fields necessary to predict the movement and dispersal of pollutant plumes in the coastal environment.

The goal of the project is to construct a dispersion forecasting capability tailored for application in the Gulf Coast region.

Microscale – Mesoscale modeling domain

Microscale Modeling domain

Grid of DEM & LIDAR data of the study area

CMAQ Hysplit

Problem Identified..

Chemical simulations in most of the models require surface emissions in a grided formatSimple interpolation of broader level emissions to obtain gridded data lead to erroneous results A GIS based methodology for distributing emissions from broader level inventory to finely grided emissions values is developed. Local micro-scale features such as activity and grid size is considered for modeling

Emission estimation using GIS

Sources of pollution and activity are generated as a thematic layers in GIS The sources are linked to attribute database and emission factors using SCC codeThe emission levels are calculated using activity and emission rate equation mentioned above Statistical local interpolation – Natural neighbor local interpolation technique has been used to generate emission prediction in local scales for which data is not available.Grided emission database of selected area is selected using Raster overlay method

Maps

GIS

Point

Mobile

Area

Mobile6

Non-road

urban

rural

Methodological Framework

Database structurePoint

NEI/NIF2.0 Point

Area

NE/NIF2.0I Point

Mobile

NE/NIF2.0 Mobile Non road

Mobile data

Emission calculation

Area type emissions

Mobile emissions

GIS compatible Database

Preparation

Spatial Analyst

Feature locations

Relational Join

Emission calculation codes (AP42)

Grided Emissions

Importing Emission database and AP42 factors into GIS

Attribute information for the feature class

Attributes are the building blocks for computing emissions Each facility whether line, point, polygon are associated with descriptive attribute information namely facility type, SCC code, emission rate etc. It will also have control factor option for manipulating the emission levels

Linkage between feature class and emission factor

Source Classification Codes (SCC) are used to develop linkage between feature class and facility It is used to allocate the emissions

General querying and mathematical tools are used to compute emissions

Emission Inventory Sources

Coarse Grid of 36km

Coarse Grid of 12km

Coarse Grid of 4km

To start with actual 2002 data developed by the RPOs for the U.S., version 2 of the year 2000 were used in the present study. Latest point emission data from MSDEQ is used to calculate gridded point emission database

Calculation methodology

AP42 / FIRE database

The general equation for emissions estimation is: E = A x EF x (1-ER/100)where:E = emissions; A = activity rate; EF = emission factor, and ER =overall emission reduction

efficiency, %

ActivityProcesses that cause emissions to be released Calculated using emission factor and measurable value Number of people per household

Road network ( number of lanes and vehicular number) Number of people in a given location

Attribute database is created in GIS as a number of layers

Infrastructural mapping of the study area

Infrastructural facilities namely Electricity generating units, Industrial locations, live stock facilities Political units namely counties, municipalities, census tracts, province Land use, demographic profiles of the study area Transportation facilities etc Infrastructural data is important for manipulating and developing the emission database

EPA FIPS code

Gas based power plantsElectric generating plants

Cities

Population size in the study area

Gulf coast counties

Calculation example Emissions from Utilities

Total area based CO emissions in the study area (%)

0

2.543

5.109

2478.02

5470.19

7238.8

240.22

606.13

96.01

7.66

40.89

4518.14

92.29

35.491336.4

426.48 0.0216.58740558

Fuel Comb. Industrial

Fuel Comb. Other

Fuel Comb. Other

Fuel Comb. Other

Fuel Comb. Other

Other Industrial Processes

Waste Disposal & Recycling

Highw ay Vehicles

Highw ay Vehicles

Highw ay Vehicles

Highw ay Vehicles

Off-Highw ay

Off-Highw ay

Off-Highw ay

Off-Highw ay

Off-Highw ay

Off-Highw ay

Miscellaneous

Point sources of sulfur dioxide in the study area

74%

4%

1%

0%

0%

0%

0%

5%

17%

0%0%0%0%0%0%0%

0%

Internal Combustion

Oil

Gas

Other

Commercial/Institutional Gas

Commercial/Institutional Oil

Residential Other

Misc. Fuel Comb. (Except Residential)

Organic Chemical Mfg

Open Burning

Heavy-Duty Gas Vehicles

Light-Duty Gas Vehicles & Motorcycles

Diesels

Light-Duty Gas Trucks

Other

Non-Road Gasoline

Aircraft

Area based sulfur dioxide in the study area

0%1% 0%

17%

12%

12%

0%

3%0%

20%

8%

17%

6%

1% 1% 2%



Residential Wood

Residential Other

Open Burning



Diesels


Other

Non-Road Gasoline

Aircraft

Non-Road Diesel

Marine Vessels

Railroads

Other Combustion

Area based Oxides of the study area

0%

91%

0%3%

0%0%0%0%0%0%0%0%0%0%

0% 0%

4%1%

Internal Combustion

Internal Combustion

Oil

Gas

Other



Residential Wood

Residential Other

Misc. Fuel Comb. (Except Residential)

Organic Chemical Mfg

Oil & Gas Production

Open Burning



Diesels


Other

Output Map generation

Grided emissions of

Oxides of Nitrogen

Mississippi

ArcGIS 9 Development TeamSeptember 2003 Source: ESRI Data & Maps CDCreated in ArcGIS 9 using ArcMap

Southern United States0 2 4 61

Miles

0

0

181472

991

239.25

18441

9816.68

1230.684246.63

3015.95

11288.66

0

18

0

Mississippi

Louisiana

Alabama

-90°

Central Mer idian: -961st Std Par allel: 202nd Std Parallel: 60Latitude of Or igin: 40

Albers Projection

Legend

Outer_Grids<all other va lues>

link.NOX<Null>0

18239.25

991

1230.681472

3015.95

4246.639816.68

11288.6618441

[_ Capital Cities

Interstate HighwaysRivers

Lakes

State Boundaries

Grided emissions of Sulfur dioxide

Mississippi

0.69

0.54

2.7

20

Source: EPA



Miles

0

0

0

1

58

2204

58.1558.42

0.27

46606

24368.8

1

26573.26

00

Mississippi

Louisiana

Alabama

-90°


Albers Projection

Legend

Outer_Grids<all other values>

link.SO24660626573.26

24368.8

220458.42

58.15

581

0.27

0<Null>

[_ Capital Cities

Interstate HighwaysRivers

Lakes

State Boundaries

Sulfur dioxide Emission database

Carbon monoxideMississippi

9.9 to 21

51 – 130 >130

Total Carbon Monoxide emissions ( Tons per SqMi)

ArcGIS 9 Development TeamSeptember 2003 Source : ESRI Data & Maps CDCreated in ArcGIS 9 using ArcMap


Miles

0

0321

735

10

43.63

1474

2493.27

1518.121918.02

399.9

2813.99

0

10

0

Mississippi

Louisiana

Alabama

-90°


Albers Projection

Legend


link.CO010

43.63321

399.9735

14741518.121918.02

2493.272813.99

[_ Capital C itiesInterstate Highways

RiversLakesState Boundaries

Carbon monoxide emission database

Particulate Matter PM10

MississippiArcGIS 9 Development TeamSeptember 2003 Source: ESRI Data & Maps CDCreated in ArcGIS 9 using ArcMap


Miles

0

0

0

13

49

26220

48.5248.52

1446

297.65

572.83

20

7.37.3

Mississippi

Louisiana

Alabama

-90°


Albers Projection

Legend


link.PM_CON0

7.3

13

20

48.52

49

262

297.65

572.83

[_ Capital Cities

Inte rstate Highways

Rivers

Lakes

Sta te Boundaries

Sulfur dioxide emission quantities from Point source

Emission estimation

Currently no elements are developed for automated emission estimation Manual commands based emission estimation algorithm is developed Emission levels are shown in Map as a chloropleth map. Feature output can be saved as dbf format for converting to other formats


Southern United States0 5 10 152.5

Miles

[_

[_Jackson

Montgomery

Alabama

Mississippi

Florida

Louisiana

-90°

-90°

30°

30°


Albers Proj ection

Legend

[_ Capital Cities

State BoundariesInterstate HighwaysRiversLakes

C3_LayerV

-6.732930 - -5.405770-5.405769 - -4.017580-4.017579 - -2.471370

-2.471369 - -0.917947-0.917946 - 1.006360

WRF output

Model output

Future ScopeUse high resolution satellite products to correlate the emission sources and developing emission inventory

Develop GIS assisted emission inventory preparation and processing system for directly coupling to Mesoscale models (Implementing Sparse matrix algorithms into GIS)

Incorporate Biogenic emission inventory into the model and use Satellite derived products

Acknowledgements

Thanks for the support of the Atmospheric Dispersion Project (ADP) funded by the National Oceanic and Atmospheric Administration through the U.S. Department of Commerce (Silver Springs, MD); Contract #NA06OAR4600192.

THANK YOUJ. Indracanti, V. S. Challa, R. L. Hughes, J. M. Baham, C. Patrick, M. Rabarison, J. Young, and Y. Anjaneyulu, Trent Lott Geospatial and Visualization Center; S. Swanier, Office of Strategic Initiatives, Jackson State University

Documents

GIS Assisted Emission Inventory Development for Variable ... · Methodological framework ... Mobile emissions GIS compatible Database Preparation. Spatial Analyst Feature locations