1



### Regional Air Quality Analyses for Ozone, PM 2.5 

### , and Regional Haze: Base C Emissions Inventory ( September 12 , 2011)

The Lake Michigan Air Directo r s Consortium, in conjunction with its member states, are conducting a ir quality modeling for ozone and fine particles (PM 2. 5 ) in preparation for future State Implementation Plan (SIP) work. The modeling analyses are focused on examining model performance (by comparing base year modeled and mo nitored concentrations) and providing
strategy

- relevant information (through a series of model sensitivity runs). This document describes the develop ment of the latest base year emissions inventor y (Base C v 7)

. I mprovements to the base year inventory are summarized in the table below.

Table 1. Summary of Base C Inventory Improvements

Sector Activity

Point Update d State data (Indiana, Iowa, Minnesota, Ohio, Wisconsin)

Updated EGU

- nonEGU splitting

Area Update d State data (Indiana, Iowa, Minnesota, Ohio, Wisconsin)

Improved PM speciation profiles

Revised woodburning emissions

Nonroad Incorporate d ERTAC rail data

Other Review ed and identified appropriate speciation profiles

Overview

T he primary base year selected for initial modeling is 2007. 1 Meteorology was developed for using MM5 and WRF . (Note: WRF meteorology is being used in the latest base year modeling.)

The base year inventory w as developed in phases , as summarized in Table 2.

Outstanding emissions inventory issues include:

 Reliability of the MOVES

- based on

- road emission estimates. (Note, a separate effort is underway to do a top

- down evaluation of these emissions using ambient monitoring data. )

 Reliability of new MEGAN biogenic emission estimates

 Development of improved agricultural ammonia emission estimate s

 Use of i mproved PM and VOC speciation profiles

 Appropriateness of assumed transportable dust fraction (i.e., 9 0 %)

 Inclusion of both PM

- filterable and PM

- con densible emissions

 Inclusion of fire emissions

1 Limited modeling was also performed for a 2008 base year, but a decision was made to focus on 2007 because of generally higher air quality concentrations in that y ear. In addition, the LADCO States recently decided to update the modeling base year to 201 1 . Work is underway to prepare emissions and meteorology for this year. Until the new inventory and meteorology are ready, LADCO will continue to

use the 2007 bas e year data in its regional modeling analyses.2 Table 2. Contents of Basecase Inventory

Sector Base B Base Cv2 Base Cv4 Base Cv 7

EGU Point 2007 CEM data (annualized w/

2005

- 2007 temporal) 2007 CEM data (annualized w/ updated temporal) (updated EGU

- nonEGU splitting) I m p r o v e d T r a n s l a t i o n f r o m S t a g i n g t a b l e s t o N I F ( I L

, O H )

Non

- EGU Point 2008 State data 2008 State data (updated EGU

- nonEGU splitting and

PM

- condensibles) Updated State data I m p r o v e d T r a n s l a t i o n f r o m S t a g i n g t a b l e s t o N I F ( I L

, O H )

Area 2008 State data Improved PM speciation profiles Updated State data Modified woodburning emissions

Nonroad 2007 NONROAD2008

MAR Base M Rail

– ERTAC

Marine

– Base M (w/ 2 0 0 5 S i p

i n v e n t o r y growth )

Aircraft

– 2008 State date

Agricultural Ammonia Base M

Biogenics MEGAN

On

- road Base M (new grid)

B+: initial MOVES emissions MOVES w/ nat’l ldefaults (MW states only) MOVES w/ nat’l defaults (all states)

Fires (not included) (not included) (not included)

Non

- LADCO Region Base M

Note: The other versions of Base C (Cv3, Cv5, Cv6) reflected minor corrections to individual sectors.3

Summary of Base Year Emissions The emissions base year for the current regional modeling is 2 0 0 8

. 2008 emissions w ere provided for EGU point, no nroad, on

- road, and biogenics , and 2008 emissions (only) w ere provided for the other sectors (non

- EGU point and area). Based on consultation with the States and examination of various emission surrogates (e.g., population, employment, and VMT), 2008

emiss ions for these sectors were used “as is” to repres ent 2007 emissions

.

For on

- road, off

- road, ammonia, and biogenic sources, emissions w ere estimated using

emission models. Three other off

- road categories are not accounted for by the NONROAD emissions model: commercial marine, aircraft, and rail. Marine emissions will continue to be based on LADCO’s Base M (2005) inventory. Aircraft emissions for 2008 w ere provided by the

S tates. Rail emissions w ere based on the new 2008 inventory prepared by ERTAC. For point

and area sources , emissions w ere prepared using data supplied by the S tates. Further discussion is provided below for each source sector in the LADCO region. For th e rest of the modeling domain, Base M inventories will b e used u ntil more recent inventories are available

fro m other regional organizations.

A su mmary of annual emissions by pollutant and source sector is provided in Figure 1. A more complete emissions summary is provided in Attachment 1.

F igure 1. Annual emissions summary by pollutant and source sector 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000

NOX ROG SO2 PM2.5 area

on

- road

MAR

nonroad

nonEGU

EGU

0% 20% 40% 60% 80% 100%

NOX ROG SO2 PM2.5 area

on

- road

MAR

nonroad

nonEGU

EGU4

On

- Road Sources: Emission estimates were derived using EPA’s new MOVES2010 a model for

on

- road motor vehicles. MOVES20 10 a was developed for s tate/local air quality and transportation agencies to use in preparing on

- road inventories for SIPs and transportation conformity. MOVES2010 replaced the previous model for estimating on

- road mobile source emissions, MOBILE6.2. EPA guidance is for states to use MOVES2010 a “in ozone, CO, PM, and NO2 SIP development as expeditiously as practicable.”

MOVES2010 a was developed principally to be run in an “inventory” mode (i.e., monthly
average, county

- level emission estimates), which is what state/local agen cies need for their SIP inventories and conformity demonstrations. For photochemical modeling, however, more refined temporal and spatial information is desired. Two options exist for providing this more refined information: (1) running MOVES2010 a for ea ch hour (using concurrent meteorological conditions) to provide the appropriate emission factor, or (2) developing MOVES2010 a “look

- up” tables which cover the expected ranges of key meteorological variables and then using the tables to provide the emission factor for each hour based on the concurrent meteorological

conditions. Initial PC

- based modeling showed that the first option was prohibitive

. Subsequent

Linux

- based modeling produced a factor of 2 decrease in model run times, but still suggested

that the look

- up table option was preferable.

Using a Linux

- based version of MOVES2010 a created by W isconsin DNR, on

- road motor

vehicle inventories w ere prepared based on a multi

- step process :

Step 1: A state

- level run was conducted to produce te mporal profile s for each state for weekday and weekend emissions as a function of pollutant, emission type (exhaust and evaporative), and vehicle type (gasoline and diesel).

Step 2: A county

- level run w as conducted for each representative county for January and July to produce a weekday and weekend emission estimate for these two months.

Step 3: The monthly profiles were applied to the rep resentative county results to generate a weekday and weekend emission estimate for all months.

For Base Cv4, national defau lts were used in the MOVES runs. State

- specific inputs were supplied by most LADCO States, but were not used to produce a modeling inventory. 2 The resulting county

- level weekday and weekend emission estimates for each month were then

modeled as an area source in EMS. Emission processing assumptions include:

Temporal: Weekday emissions assigned to Monday

- Friday, and weekend emissions assigned to Saturday

- Sunday. It should be noted that the emission file s already reflect hourly values.

Spatial: Applied 2002 surrogates based on roadway type.

Speciation: Exhaust and evaporative emissions by vehicle type (gasoline and diesel) were speciated separately.

2 Preliminary MOVES runs for a few cities (Cleveland, Milwaukee, and E.St.Louis) indicate that the

emission estimates are about 8

- 10% higher using state

- specific inputs.5

Off

- R oad Sources: NMIM2008 w as run (using default monthly temperatures) by Wisconsin

DNR for the 2007 and 2008 for the five LADCO States plus MN, IA, and MO

. Local data for agricultural equipment, construction equipment, commercial marine, recreational marine, and railroads were prepared previously by contractors (Environ, 2004, E.H. Pechan, 2004 , and
Environ, 2007 a , 2007 b ).

Three other off

- road categories are not accounted for by the NMIM emissions model: commercial marine, aircraft, and rail. Marine emissions will continue to be based on LADCO’s Base M (2005) inventory (Environ, 2007a)

. A summary of the annual emissions by vessel type

for the 5

- state LADCO region are provided in Table 3.

Table 3. Annual Commercial Marine Emissions for 2005 (LADCO Region)

Aircraft emissions for 2008 w ere provided by the States.

Rail emissions w ere based on the new 2008 inventory prepared by ERTAC. Emissions data were developed for rail yards and line haul operations. Documentation for the rail emissions is

available at http://www.ertac.us/rail/ind ex.html

Area and Point Sources: EMS w as run by LADCO using data supplied by the LADCO States

and Minnesota to produce weekday, Saturday, and Sunday emissi ons for each month. The

ERTAC recommendations on area sources w ere followed in preparing these data

.

Two significant area source improvements were made in developing Base Cv4 : application of appropriate PM speciation profiles, and adjustment of r esidential wood combustion (RWC)

emissions

. First, several PM area source categories , which were using the default speciation profile, were assigned SCC

- specific profiles based on several recent references (CMU, 2004, EC/R, 2005, and Turner, 2010). This resulted in significantly more primary OC and EC

emissions.

S econd , Michigan DEQ adjusted EPA’s RWC tool to reallocate the indoor furnaces and outdoor hydronic heaters (*8510 and *8610, respectively) to nonMSA counties. Counties that are part of an MSA, were assigned zero appliances for both categories. Additionally, an issue with double counting some county a ctivity data in WI and MI was addressed. Table 4 show s the statewide changes in emissions from the standard tool to the revised tool. These changes resulted in a shift in the spatial distribution of emissions, and (due to the double counting) a reduction in

statewide emissions in some states.6 Table 4. Standard and Adjusted Residential Wood Combustion Emissions

Standard

RWC Tool Adjusted

RWC Tool Adjusted

RWC Tool Adjusted

RWC Tool Adjusted

RWC Tool Adjusted

RWC Tool

State Pollutant Emissions Emissions 2104008400 2104008510 2104008610 sum

17 Primary PM10 13,880 14,012 51 4,570 2,454 7,075

18 Primary PM10 11,729 11,724 37 3,762 3,274 7,073

26 Primary PM10 35,143 27,255 91 4,537 6,630 11,257

27 Primary PM10 17,741 17,741 45 879 3,860 4,784

39 Primary PM10 25,703 23,332 80 7,919 5,890 13,889

55 Primary PM10 23,407 20,311 53 2,887 6,156 9,096

For EGU point source s, the annual and summer season emissions w ere temporalized for modeling purposes using profiles prepared by Scott Edick (Michigan DEQ) based on CEM data

. Figure 3 shows the location (and magnitude) of non

- EGU and EGU point sources.

Figure 3. Spatial plot of non

- EGU (left) and EGU (right) sources7

Biogenics: Environ, under contract to the Midwest Ozone Group, produced day

- specific biogenic emissions for the full modeling domain using the CONCEPT/MEGAN biogenics model for 2007 and 2008 (Guenther, et al, 2006, and Sakulyanontvittaya , et al, 2008). MEGAN2.03a

wa s used, which is a modified version of MEGANv2.03 available from http://acd.ucar.edu/~guenther/MEGAN/MEGAN.htm

. The improvements for the modified

version include:

 Enabling input of temperature a nd solar radiation data from various sources. Previous versions of MEGAN obtained these data only from MCIP model outputs.

E nviron developed code to allow input of solar radiation from satellite data and temperature from MM5 and MM5CAMX models.

 Pre

- proces sors were developed to allow the use of alternative modeling grids developed in ArcGIS.

 The MEGAN code is currently capable of outputting model

- ready data for CMAQ.

The MEGAN code w as m odified to include outputting of CAMx model

- ready data.

 Modification of the MEGAN FORTRAN code that runs on Linux to accept observed temperature data and satellite radiation data and generate emissions for grid

definitions that are developed using ArcGIS.

Figure 4 compares the biogenic isoprene and NO emission estimates for 2007 with those for 2005 (Base M).

Figure 4 . Biogenic emissions: isoprene (left column) and NO (right column) for 2005 (top) and 2007 (bottom)8

Ammonia: The ag ricultural ammonia emissions were based on C arnegie Mellon University’s

Ammonia Emission Inventory for the Continental United States ( http://www.cmu.edu/ammonia ).

Specifically, the CMU annual emissions for 2002 were first grown to reflect 2007 conditions

based on t h e methodology u s e t o c r e a t e t h e 2 0 0 5 L A D C O S I P i n v e n t o r i e s . A new process

based ammonia emissions model developed for LADCO (see Zhang, et al, 2005, and Mansell, et al, 2005) was then used to develop temporal factors

– i.e., month of year, and hour of day t o

r e f l e c t t h e i m p a c t o f a v e r a g e m e t e o r o l o g y o n l i v e s t o c k e m i s s i o n s

.

E missions T

ile plo t for L i v

e s t o c k A m m o n i

a i n t h e U p p e r M i d w e s t a n d M

i d A t l a n t i c S t a t e s

.

Canadian Emissions: Scott Edick (Michigan DEQ) processed the 2005 Canadian National Pollutant Release Inventory, Version 1.0 (NPRI). A subset of the NPRI data (emissions and stack parameters) relevant to the air quality modeling were reformatted an d used in the regional modeling.

References Carnegie Mellon University, Spreadsheet: emission.profiles,v2.xls, February 17, 2004

EC/R, Incorporated, 2005, “ Improving Modeling Inventory Data: Speciation Profiles ”, Draft Technical Report

, February 17, 20059

E.H. Pechan, 2004, “LADCO Nonroad Emissions Inventory Project

– Development of Local Data for Construction and Agricultural Equipment”, Final Report, September 10, 2004

Environ, 2004, “LADCO Nonroad Emissions Inventory Project for Locomotive, Commercial

M arine, and Recreational Marine Emission Sources, Final Report, December 2004.

Environ, 2007 a , “LADCO 2005 Locomotive Emissions”, Draft, February 2007.

Environ, 2007 b , “LADCO 2005 Commercial Marine Emissions”, Draft, March 2, 2007.

Guenther, A., T. Karl, P. Harley, C. Wiedinmyer, P. Palmer, and C. Geron, Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem Phys., 6, 3181

- 3210, 2006.

Mansell, G, Z. Wang, R . Zhang, J. Fadel, T. Ramsey, H. Xin, Y. Liang, and J. Arogo, 2005, “An Improved Process

- Based Ammonia Emissions Model for Agricultural Sources

– Emission

Estimates”

Sakulyanontvittaya, T., Duhl, T., Wiedinmyer, C., Helmig, D., Matsunaga, S., Potosnak , M., Milford, J., and Guenther, A. Monoterpene and Sesquiterpene Emission Estimates for the United States, Environ. Sci. Technol., 2008, 42, p. 1623

- 1629. Turner, Jay, Spreadsheet: WUSTL

- LADCO_SourceProfiles_v3.xlsx , and Metadata for Source

Profiles for C MB Modeling of Midwest U.S. Urban Areas Version 3 (August 24, 2010)

, Wa shington University in St. Louis, jrturner@wustl.edu

Zhang, R, T. Ramsey, J. Fadel, J. Arogo, Z. Wang, G. Mansell, and H. Xin, 20 05, “An Improve d

Process

- Based Ammonia Emissions Model for Agricultural Sources

– Model Development”