WRAP 2004 Technical Work Elements

Tom Moore

March 24, 2004

Air Managers’ Committee

§308/§309(g) Implementation Workgroup

2004 WRAP Technical Work Elements

Topics Today Attribution of Haze Project

TOC-sponsored

Emissions Inventories EDMS collaborative effort – Emissions\Fire\Dust Forums Emissions Inventories’ Status – focus on fire EIs

Regional Modeling Center Source Apportionment based on “interim” 2002 EIs AQ Modeling Forum-sponsored

Causes of Haze Assessment Ambient Monitoring Forum-sponsored

2004 WRAP Technical Work Elements

Start of technical and policy analysis path to Regional Haze Plans due by end of 2007

Technical analyses to understand: 2000-04 Baseline and 2064 natural conditions Reasonable Progress to national visibility goal Emissions reductions needed to achieve RP to 2018

Technical Activities - what is going on now?

2004 AoH Project Data Sources

Source apportionment modeling simulations from the Regional Modeling Center

Receptor-oriented source contribution analyses of aerosol and meteorological monitoring data from the Causes of Haze Assessment project

Existing and refined emissions inventories from the Dust, Emissions, and Fire Forums

Special-purpose source attribution studies such as BRAVO, et cetera

EPA technical guidance documents and analyses Journal publications, and workshop/conference reports

addressing emissions and visibility impairment

2004 AoH Project Deliverables

Identify: Geographic source areas of emissions that

contribute to impairment at each mandatory federal and tribal Class I area

Mass and species distributions of emissions by source categories within each contributing geographic source area

The amount of natural and manmade emissions affecting each Class I area

2004 AoH Project Deliverables

Provide: Documentation of the assumptions,

methods, and uncertainties used in the integrated analyses of modeling, monitoring, and emissions data.

Succinct, clear summaries for policymakers, of the estimated areas and sources of impairment for each Class I area, including the associated uncertainty

AoH Project Schedule January – March

Organizational meeting – March 29-30 – workgroup page on WRAP website

Develop scope of work for contractor support + hire

April – June Review/discuss existing source attribution studies

(BRAVO, et cetera) Contractor to identify data available for AoH project

July – September Review/discuss work products from RMC, CoHA,

and EIs Assign expert review topics

AoH Project Schedule

October – December Continue review/discussion of work products from

RMC, CoHA, and EIs Review/discuss draft reports from expert reviewers Review first draft of AoH report prepared by

contractor

January 2005 Publish final 2004 AoH report Make plan for subsequent workgroup activities

Emissions Data Management System

Regional data center to identify existing, projected, and future control levels of emissions (more detail later this morning) Provide a “bucket” to store state and tribal

EIs, as basis of Regional Haze Plans Complete EI for WRAP region Provide modeling input files Under construction now, on-line late 2004 www.pechan.com/edms

EDMS Project – 2004 - Phase 1

Purpose

Regional Haze Rule Implementation Performance Monitoring

Region-Wide Emission Inventory Analysis of Collected Data Emissions Comparisons Emissions Trends Analysis

EDMS Project – 2004 - Phase 1

Concepts GIS/Layers

Need to add to map

2002 “Interim” Emissions Inventories Existing EI Data from §309 work

Mobile (on-road and non-road) Road Dust (paved and unpaved)

Improved EI Data Point and Area from 1999 NEI (CENRAP + WRAP) Ammonia Biogenics Windblown Dust

EI Development Work Fire Mexico/Canada

Fire EI Tasks (task notes on following slides, resulting from discussions at 12/19/02 FEJF meeting)

Task 1 Task 2 Task 3 Task 4

Due Date 4/04 8/04 1/05 5/05

Purpose 1) Model Evaluation

2) Test Apportionment

WRAP Strategic Plan Phase I Apportionment

Baseline Planning Apportionment

2018 Planning Apportionment

Product 2002 Wx

2002 Rx

2018 Ag BSM

Final 2002 Wx

Final 2002 Rx

Final 2002 Ag

2000-04 Representative EI for all fire types

2018 Representative EI(s) for all fire types

Task 1Modeling Evaluation EI - Fire

2002 actual Wildfire EI – by April 2004 2002 actual Rx fire EI (using NIFC and other state

electronic data to supplement emissions estimates) – April 2004

2002 actual Ag fire EI (may use 2018 BSM for now) Used for model performance evaluation – ambient monitoring data

compared to model results Provides confidence in using model to characterize current and future

years’ planning EIs Used to test geographic source apportionment – effects at each

Class I area, tribal reservation, or other geographic area Provides modeling estimate of contributions from each upwind source

jurisdiction

Task 2Initial Modeling Apportionment EI - Fire

Start with Phase I 2002 actual EI(s) 2002 actual Wildfire EI - 8/2004 2002 actual Rx fire EI - 8/2004 (split natural versus

anthropogenic) 2002 actual Ag fire EI - 8/2004 For all 3 types of fire:

Used to complete Strategic Plan 2004 deliverable (geographic source apportionment) for TOC Attribution of Haze project

Effects at each Class I area, tribal reservation, or other geographic area

Modeling analysis of natural versus anthropogenic

Task 3Planning Baseline Period EI - Fire

Start/stay with Task 2 2002 EI format for consistency Use at least 2000-04 data, could be longer period, must

be representative of regional haze baseline period Wildfire EI - 1/2005 Rx fire EI - 1/2005 Ag fire EI - 1/2005 To construct these EIs:

Consult with states & tribes on smoke management programs Other considerations?

Task 4Planning 2018 Projection Year EI - Fire

Stay with Task 3 Baseline Planning 2002 EI format for consistency

Base projections on predictable variables, may only provide ranges or scenarios of emissions

Wildfire EI - 5/2005 Rx fire EI - 5/2005 Ag fire EI - 5/2005 To construct these EIs:

Consult with states & tribes on smoke management programs

Other considerations?

2004 Regional Modeling Center Workplan

The Air Quality Modeling Forum has two major areas of activity planned for 2004: The Regional Modeling Center (RMC) will

continue to operate and will implement many of the tools and improvements developed in 2003.

The RMC will use the same team of contractors (UCR, ENVIRON, CEP) that have been used for the past 2 years

The final work plan is being amended into the existing RMC contract.

The second major area of activity is to initiate modeling for Class I areas in Alaska.

2004 Regional Modeling Center WorkplanMajor Elements

1. Project Administration2. 2002 year MM5 Modeling data – for now and later3. 2002 “Interim” Base Emissions Inventory processing4. CMAQ Runs & Evaluation – based on modeling protocol5. Source Apportionment (described later)6. Natural vs. Anthropogenic Analysis7. Windblown Fugitive Dust Model8. Fire Sensitivity9. Fire De Minimus10. Alaska Modeling

Lesser Elements1. Emissions Speciation2. Model Performance Software3. Comparison of Alternate Models (AQ & meteorology)

As needed:1. Training

Gridded Dispersion Modeling - Source Apportionment

Project Manager - Gail Tonnesen, University of California, Riverside

Regional Modeling Center Team University of California, Riverside ENVIRON Corporation Carolina Environmental Programs at University of

North Carolina http://pah.cert.ucr.edu/rmc/

Motivation

Need to understand which emissions sources contribute to haze and other pollutants.

Europeans call these “Blame Matrices” Use this information to assist in

developing control strategies.

Modeling Approaches

Sensitivity Studies: Brute Force: Zero-in or Zero-out a single source. DDM Sensitivity – efficient but non-linear.

Use tracers or “tagged species” to track mass from a source type: UCR and ENVIRON are implementing similar

tracer algorithms in CMAQ and CAMx. Modeling back-trajectories. Chemical Mass Balance (CMB). Hybrid Approaches: OSAT

Uses tracers to track O3 formation that was sensitive to VOC or NOx.

Tagged Species Approach Use “Tagged Species” tracers to track

chemical transformations and the movement and chemical conversion of mass across domain.

Add source type tracers for key species and for defined regions and source categories.

Outputs 3-D fields showing transport of secondary species.

Also outputs bar plots showing contributions at each receptor site.

Chemical Transformations

Emissions are as NOx = NO + NO2 Use integrated reaction rates at each time

step to update the tagged species: NOX PAN NOX Organic NO3 NOX HNO3 HNO3 Aerosol NO3

Tagged Species for Nitrates

NOX = reactive N family.

= { NO, NO2, NO3, 2*N2O5, HONO, PNA} HNO3 PAN Organic NO3 Aerosol NO3

Traced Area: WRAP Modeling Domain0 0 0 0 0 0 0 0 0 0 0 0 0 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91

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9 9 9 9 9 9 9 9 9 9 9 9 9 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 75 75 75 75 75 75 75 75 75 75

9 9 9 9 9 9 9 9 9 9 9 9 9 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 75 75 75 75 75 75 75 75 75 75

8 8 8 8 8 9 9 9 9 9 9 9 9 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 75 75 75 75 75 75 75 75 75 75

8 8 8 8 8 8 8 8 8 8 8 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 75 75 75 75 75 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 60 60 60 60 60 20 20 20 20 20 20 20 20 20 20 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 80 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 80 80 80 80 80 80 80 80

8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70 70 70

8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70 70 70

8 8 8 8 8 8 8 8 8 8 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70 70 70

8 60 60 60 8 8 8 8 8 8 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70 70 99

92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70 99

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92 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 0 70 70 70 70 0

92 92 92 92 92 92 60 60 60 60 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0

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92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

91 91 91

0 0 0

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44 0 0

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33 33 33

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33 33 33

33 33 33

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

59 59 59

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59 59 59

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80 65 65

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99 99 99

99 99 99

99 99 99

99 99 99

99 99 99

99 99 99

99 99 99

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99 99 99

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Source Area Mapping File: Each state is distinguished by a unique number

Transport & Loss Terms

Use CMAQ transport solvers for advection and dispersion of each tracer.

Also update for mass export in cloud and aqueous chemistry algorithms.

Update tagged species for emissions and deposition terms.

Check for mass conservation at each step and adjust mass if needed. Halt if large errors.

Traced Source TagsTypes Source

CategoryNotes

ICON ICON Initial Concentration

BCON BCON Boundary Concentration

Emissions MV_* Mobile sources from any state (on-road)

BG_* Biogenic sources from any state

RD_* Paved + unpaved road dust from any state

NR_* Non-road sources from any state

PN_* Point sources from any state

AR_* Area sources from any state

WF_* Wildland fire from any state

AG_* Agricultural fire from any state

RX_* Prescribed fire from any state

ET_* Total emissions from any state

*_WRAP Any type of source category emissions from WRAP domain

Others OTHERS Any sources other than all of the above

Contributions to Aerosol NO3 at Yosemite

Causes of Haze Assessment Project

Project Manager – Mark Green, Desert Research Institute

4-year project – 2004 is year 2 CoHA Team – DRI + other analysts http://coha.dri.edu

Userid = dri-coha Password = hazeyweb

CoHA Approach

Determine causes of haze at WRAP and CENRAP Class I areas, tribal and selected CENRAP IMPROVE protocol sites

5

CoHA Study Data

Began analysis of 1997 to 2002 IMPROVE and protocol database

Primarily using IMPROVE and protocol sites with full speciation data in the study region (118 sites by December 2002)

Using nationwide network of 158 sites (end of 2002) to establish continental and regional setting

CoHA not just computing statistics, but forming conclusions regarding the causes of the haze

First complete a set of descriptive analyses, maps, and other graphics for aerosol composition, spatial and temporal variation, emissions, land use, topographic effects, transport patterns, local wind patterns etc

Do episode analyses to determine likely causes of haze for various commonly and uncommonly occurring conditions

Using above resources form conceptual models of causes of haze and assign quantitative number based on frequency of occurrence of conditions

Causes of Haze likely to be segregated by compound of interest, e.g. sulfate and by geographic area - by source type as possible

Example: Sulfate causes 50% of aerosol haze at Area A -

60% of which is generated within the WRAP area, mainly in the states of B,C,and D, 20% is transported into the RPO from states to the east of WRAP and mainly in summer, and 20% from other countries (mostly Country F). Based upon emissions inventory, it is estimated that 80% of the sulfate haze is due to source type G.

Nitrate is X % of the haze, 50% of which … Carbon, coarse mass - probably more difficult

The Causes of Haze web site is online now in aDRAFT, passwordprotected form:http://coha.dri.edu

Username: dri-cohaPassword: hazeyweb

8

Much of the web site is a shell ready to receive data and causes of haze information that we generate

Aerosol Descriptive Analysis Provides answers to the questions:

For the years 1997-2002, how many measurements are available for the site in each month of each year, and what are the contributions of the major aerosol components to light extinction in each month of each year?

What is the overall average light extinction at the site, and what are the contributions of the major aerosol components to the light extinction?

What are the light extinction contributions by the major aerosol components for best, worst and average days and how do they compare?

What percentage of the sampling days are the worst days in each month & how variable are the chemical components?

Sample Aerosol Description Page

Overall average light extinction and contributions of major aerosol chemical components to light extinction

Average contributions of major aerosol chemical components to light extinction in 20% best, middle 60% and 20% worst days

Percentage of sampling days that are 20% worst days in each month

Average contributions of major aerosol chemical components to light extinction during 20% worst days in each month

Meteorological & Emissions Descriptive Analysis

Archived monitoring network locations, climate, emissions, wildfires, census, political, physical, and image databases

Information from these databases are helping us build conceptual models and answer descriptive analysis questions by visualizing data (e.g. map emissions densities)

Assist us in the general and detailed description of the meteorological setting of each site

Creating maps of emissions surrounding each site at two scales: 2 km and 20 km- Regional emission maps to be added

Include table of surrounding point sources ranked by distance and emission rate

20 Km terrain

2 Km terrain

Three years (2000-2002), three heights (10, 500, 1500m), every three hours, 8 days back

HYSPLIT v4.6 model calculations done for all sites Trajectory output processed and stored in database Trajectory tool developed to produce ASCII

summary files and convert trajectories into shape files

Generate summary maps Generate monthly and annual residence time maps,

20% best, 20% worst extinction, conditional probability

Finalizing process to generate all maps, all sites in one batch- should be done late February

Trajectory Analysis Status

Episode Analysis

Use combination of back trajectory, synoptic, mesoscale meteorological analysis, aerosol and emissions data to conceptually understand single site and regional or sub-regional episodes of high aerosol component concentrations

Systematic survey of episodes from the 1997 to 2002 IMPROVE database

“Hazagon” Analysis The hazagon provides a way to visualize speciated

extinction for those sites in the 20% worst category

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Future Phases Evaluation of EDAS wind field used for back

trajectory analysis – when adequate, when misleading- possible use of MM5 or diagnostic wind fields for trajectory analysis for some sites

Mesoscale meteorological analysis – trajectory analysis? Needed for sites in complex/coastal setting affected by mesoscale source areas

Triangulation of back trajectories for worst case days to better identify source areas

Regression analysis of back trajectories, aerosol data for quantitative attribution to regions- Trajectory Mass Balance Regression

Refinement of conceptual models