Causes of Haze Assessment Dave DuBois Desert Research Institute Presented at the RPO National...
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![Page 1: Causes of Haze Assessment Dave DuBois Desert Research Institute Presented at the RPO National Technical Workgroup Meeting November 5, 2003.](https://reader036.fdocuments.us/reader036/viewer/2022062409/56649ef15503460f94c02a24/html5/thumbnails/1.jpg)
Causes of Haze Assessment
Dave DuBois
Desert Research Institute
Presented at the RPO National Technical Workgroup Meeting
November 5, 2003
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Acknowledgements• WRAP Air Monitoring & Reporting Forum Chair
– Marc Pitchford
• DRI Faculty– Mark Green, Principal Investigator– Jin Xu– Dan Freeman– Vic Etyemezian
• DRI students and hourly employees– Aleksandra Nikolic– Karl Graham– Anthony Deleon– Eric Peters
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COHA Status Report
• Review goals and objectives• COHA approach• Virtual report• Aerosol descriptions• Meteorological descriptions• Emissions descriptions• Trajectory analysis• Episode analysis
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Goals & Objectives
• Assess causes of haze for all study sites• Systematic study of 128 Class I areas, 8 tribal sites and
10 CENRAP sites• Encourage broad-based stakeholder participation
throughout the assessment process• Enhance the utility and accessibility of the results for:
– SIP & TIP development, – Regional air quality model evaluation & interpretation,– Identification of monitoring gaps,– Improved methodology for setting natural haze levels,– Tracking effectiveness of emission control programs
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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
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COHA ApproachDetermine causes of haze at WRAP and CENRAP Class I areas, tribal and selected CENRAP IMPROVE protocol sites
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COHA Approach
• Systematic study—many sites, many questions to answer
• Processing reports in batch mode to facilitate timely completion
• Give each site individual attention once batch processing is completed
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COHA Approach
• Virtual report—no paper report
• A virtual report designed as a tool to:– guide us in the causes of haze
– communicate results
– help users to interpret causes of haze
• Virtual report gives us the ability to mix text, graphics, animations and links to external web sites in addition to timely updates
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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
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View reportsby state, area, tribal area orprotocol site
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View animationsof IMPROVEmeasurements
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Aerosol Descriptive Analysis
• For the years 1997-2001, 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?
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Provides answers to the questions:
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Aerosol Descriptive Analysis
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BIBE1, Big Bend National Park, TX BOWA1, Boundary Waters Canoe Area, MNDENA1, Denali National Park, AKGRCA2 , Hance Camp at Grand Canyon NP, AZHAVO1, Hawaii Volcanoes National Park, HIJARB1, Jarbidge Wilderness, NVMORA1, Mount Rainier National Park, WASAGO1, San Gorgonio Wilderness, CASAGU1, Saguaro National Monument, AZ UPBU1, Upper Buffalo Wilderness, AR
Aerosol descriptions available on web page now:
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Aerosol Descriptive Analysis
Pages designed for users to copy and paste text and figuresinto their own reports
Example: San GorgonioWilderness Area, California
Both charts and text to describe the 20% best, worst and middle 60%
Printer friendly and black &white versions of pages
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Meteorological & Emissions Descriptive Analysis
• Archived monitoring network locations, climate, emissions, wildfires, census, political, physical, and image databases
• Databases will help 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
• Over 120 GB of data archived at DRI
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Descriptive Analysis Map Progress
• Standard maps to support descriptive analysis text– Terrain (labels on rivers, lakes, major features, peaks)– Nearby met/air quality networks– Urban boundaries, roads, landmarks– Landuse map– Landsat image (qualitative landuse, with some features
labeled)– Emissions map (fires, WRAP point inventory, urban
areas, roads)
• Specialized maps (as needed basis)– 3D terrain map– Meteorological flow map to illustrate transport
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Maps for web siteApprox. percent completed
9080
7525
Hawaii: 0, Alaska: 0
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80
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50 50
25
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75
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Standard Analysis Map Progress
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Example “20 km” terrain mapCucamonga Wilderness Area
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Example “2 km” terrain map
Cucamonga Wilderness Area
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Meteorological Description Update
• Describe meteorological influences by defining regions:– Hawaii and So. Calif. Coastal are posted on web
• Detailed meteorological descriptions:– San Gorgonio and Jarbidge are posted on web
• Terrain description– Access database tool developed to assist descriptive text
• Identify nearby meteorological measurements for use in interpreting aerosol data
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Example “20 km” met/air quality network map
Cucamonga Wilderness Area
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Trajectory Analysis Status
• Three years (2000-2001), three heights (10, 500, 1500m), every three hours
• EDAS for continental sites and FNL for Hawaii and Alaska
• HYSPLIT v4.6 model calculations done for all sites• Trajectory output being processed and stored in
database • Trajectory tool being developed to produce ASCII
summary files and convert trajectories into shapefiles• Generate summary maps
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Emissions Description Status
• Developing standard template for web site
• Creating maps of emissions surrounding each site at two scales: 2 km and 20 km
• Include table of surrounding point sources ranked by distance and emission rate
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“20 km” emissions map
Cucamonga Wilderness Area
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Episode Analysis
• Use combination of backtrajectory, 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
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Episode Analysis• Created animated maps of IMPROVE and protocol
measurements for entire network• Choose episodes base on sites classified with 20%
worst light extinction• Noting duration, frequency, regional extent, season
and components that contributed to light extinction• Assemble case studies and classify into episode
types• Create database of these episodes• Combine results of episode analysis with cluster
analysis to develop conceptual models
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Example Episode Analysis Map
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Asiandustepisode