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
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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 92 92 92 0 0 0 0 0 0 0 92 92 92
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
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
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 60 60 60 60 70 70 70 70 70 70 70
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 60 60 60 60 70 70 70 70 70 70
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 60 60 60 70 70 70 70 70 70
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 60 60 70 70 70 70 70 70
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 60 70 70 70 70 70 70 70
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
92 92 92 92 92 92 92 92 60 60 92 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 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 60 60 60 60 60 60 60 60 60 60 60 60 60 60 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 60 60 60 60 60 60 60 60 60 60 60 60 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 60 60 60 60 60 60 60 60 60 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 60 60 60 60 60 60 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 60 60 60 60 60 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 60 60 60 60 60 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 60 60 60 60 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 60 60 60 60 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 60 60 60 60 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 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
0 0 0
0 0 0
0 0 0
44 0 0
44 44 0
44 44 44
44 44 44
33 44 44
33 33 44
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
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
59 59 59
59 59 59
59 59 59
59 59 59
75 59 59
75 75 59
75 75 59
75 75 75
75 75 75
80 75 65
80 75 65
80 80 65
80 65 65
80 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
70 70 70
70 70 70
70 70 70
70 70 70
70 70 70
70 70 70
0 70 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
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
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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
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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