Causes of Haze Assessment Mark Green, Dave DuBois, Jin Xiu, and Dan Freeman Desert Research Institute Marc Pitchford, NOAA and WRAP Monitoring Forum Chair Presented at the WRAP Technical Summit Meeting Tempe, AZ January 27, 2004

COHA Status Report Review goals and objectives COHA approach Virtual report Aerosol descriptions Meteorological descriptions Emissions descriptions Trajectory analysis Episode analysis 2

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 4

COHA Approach Determine causes of haze at WRAP and CENRAP Class I areas, tribal and selected CENRAP IMPROVE protocol sites 5

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 7

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,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 a DRAFT, password protected form: Username: dri-coha Password: hazeyweb 8 Much of the web site is a shell ready to receive data and causes of haze information that we generate

View reports by state, area, tribal area or protocol site 9 View animations of IMPROVE measurements This interface is under construction and may change

Aerosol Descriptive Analysis For the years , 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? 10 Provides answers to the questions:

Aerosol Descriptive Analysis Pages designed for users to copy and paste text and figures into their own reports Example: Upper Buffalo Wilderness Area, Arkansas Both charts and text to describe the 20% best, worst and middle 60% Printer friendly and black & white versions of pages 12

% of sample days each month in worst 20 percentile Aerosol components responsible for haze worst days, by month

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 Graphs in this page have both color and B&W versions, and links to the data table associated with it. Click on the bars in the bar chart will bring up pie charts with percentage numbers. Click on the text or numbers with hyperlinks will bring up the explanation page or associated data table or graph. It also includes links to a color and a B&W print- friendly page.

Sample Links From the Main Page Light extinction of the major chemical components in each month from Percentage contributions of the major chemical components to haze in 20% worst, middle 60% and 20% best days in each month of the year Mean percentage contributions of the major chemical components to aerosol light extinction in 20% worst, middle 60% and 20% best days

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 13

2 Km terrain

20 Km terrain

20 Km Emissions

Nearby networks

2 Km urban

20 Km urban

2 Km land use

20 Km land use

20 Km Landsat

Meteorological description of sites Describe regional and local scale settings Terrain maps and discussion Representativeness of site Nearby population /industrial centers Nearby AQ/met sites Wind patterns surface and upper air Stability/mixing Meteorological factors regarding AQ Big Bend NP annual wind rose

Representativeness 1.ZION1 monitoring site is close to the Interstate 15 corridor. 2.Canyons of Zion National Park are generally steep and constricted, hence susceptible to trapping inversions. In these situations, ZION1 measurements will be more representative of the Kolob Canyon section of the Park than of the Zion Canyon section, being influenced more by trapped pollutants in the basins and valleys in the New Harmony and Cedar City areas. 3.During large scale inversions, such as subsidence inversions associated with buildup and stagnation of synoptic high-pressure ridges over periods of a few days or longer, conditions may be more uniform within the Park. These are most likely to occur during the summer (July – September), when pressure and temperature gradients in the region are weakest, and wind circulations therefore weaker.

Wind Patterns August December Wind roses from the Cedar City NWS site (~ 30 km north of the monitoring site) show the preponderance of southerly flow, especially in the summer, with significant frequencies of northerly wind directions in other seasons. April

Zion National Park (ZION1) (Based on aerosol data from March 2000 to December 2002) On average, sulfate is the largest aerosol contributor to haze. Nitrate is the largest contributor to aerosol light extinction in the 20% worst days, with a contribution of 26%. Sulfate, OMC and CM each contributes about 20% to the aerosol light extinction in the 20% worst days.

1. Higher occurrence of the 20% worst days happened in the summer and winter. 2. OMC is the largest aerosol contributor to haze in the 20% worst days in the summer. 3. Nitrate is the largest aerosol contributor in the winter, with a contribution of % in the worst days. 4. CM contributes about 20% - 25% to haze from April to September. 5. The contribution of sulfate is pretty constant throughout the year. Aerosol Properties

Trajectory Analysis Status Three years ( ), 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 Febrruary 20

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 23

Normalized Residence Time in January

Normalized Residence Time in August

Normalized Residence Time for 20% Worst Days

Normalized Residence Time for 20% Best Days

Normalized Residence Time for 20% Worst Nitrate Days

Episode Analysis Created animated maps of IMPROVE and protocol measurements for entire network Choose episodes based on sites classified with 20% worst light extinction Note 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 other analyses to develop conceptual models 24

“Hazagon” Analysis The hazagon provides a way to visualize speciated extinction for those sites in the 20% worst category 25

Example Episodes Intermountain West Nitrate Central US nitrate December 2002 April 16, 2001 Asian Dust over Western US August 2001 wildfires October 16, 2001 Arizona dust September 3, 1997 Eastern sulfate transport to Colorado Plateau 27

Nitrate Episodes

Example surface map- High pressure over area entire period

4/16/01 Asian Dust Episode 28

GOES View of the Dust Streak Across North America, April 17 GOES10 view of dust streak on the morning of April 17 GOES8 view of dust streak on the evening of April 17 29

Transport of the Asian dust to the United States The common weather conditions are usually associated with the upper low pressure trough / cut-ff low and surface low pressure system (low formed by a strong cyclonic vortex) over northeast China and north Korea [Kim et al., 2002]. Under this weather conditions, Asian dust can move fast along the zonal wind distribution due to the jet streak [Kim et al., 2002]. 30

Large Area Regional Haze on April 16, of the 68 WRAP IMPROVE monitoring sites were in 20% worst case days of the year For the sites that were 20% worst case days, the average contribution of fine soil to PM 2.5 is ~60% (with a standard deviation of 13%), and dusts (fine soil and coarse mass) contributed in average ~ 46% (S.D. 13%) to the aerosol light extinction. The average contribution of fine soil to PM 2.5 is ~54%, and to aerosol light extinction is ~41% for all WRAP sites on April 16,

Asian Dust Signature Asian dust may cause haze in a large area and last several days depending on the regional and local weather conditions in the United States. Usually, dust elements dominate the aerosol light extinction in the whole western United States during the Asian dust episode. The dust cloud may also move to the Eastern U.S. and influence some of the eastern sites, although the influence is usually much smaller in both spatial scale and loading. Most of the Asian dust episodes happen in the spring during the Month of March to May. 32

Asian Source Attribution Evidence The desert regions in Mongolia and China, especially Gobi desert in Northwest China, are important sources of mineral aerosols. Given suitable weather conditions, dust can be lifted from the dry surface of the Asian Gobi desert region and transported to the United States in about 7-10 days. Extremely high aerosol loadings dominated by dust components are observed in Northern China and Korea during the episode. 33

Origin of the Asian Dust Strong low pressure system sitting in northeast Mongolia caused surface wind speeds to be as high as ~30 m/s 34

The August 2001 Western US Wildfire Episode 44 sites in the WRAP region experienced the worst 20% day on August 17. Most of August experienced heavy OC in the west. 3 sites had this day as worst Bext: CABI1, Cabinet Mountains, MT NOCA1, North Cascades, WA PASA1, Pasayten, WA 35

The August 2001 Western US Wildfire Episode: August Fires started early in August and lasted all month was not a particularly bad fire year in terms of number of acres burned 36

Databases available IMPROVE data Text, photos and maps on fires from NIFC, USFS, newspapers Text on meteorology from NWS, NCDC Weather maps from CDC, NCEP, WXP MODIS satellite images from UWisc, USFS Coarse fire locations fron MODIS, AVHRR 37

Large Fire Locations Typical of late season fires, most of the fires are in the northwest and northern Great Basin 38

August 15 Terra MODIS at 18:38 UTC shows transport of regional smoke plumes 39

August 17 Terra MODIS at 18:38 UTC Can see thick smoke in NW and coastal areas The Moose Incident was one of the largest fires of the 2001 season. This lightning caused fire occurred August16th on the Flathead National Forest. The Moose fire ultimately burned approximately 71,000 acres before it was controlled. 40

Conditions According to NIFC National Fire News the national level of preparedness increased to the highest point on the 16th, as more than one half million acres are burning in 42 large fires across the United States. Nearly 21,000 firefighters are working on the fire lines. Record high temperatures in Oregon, Washington, and Idaho may increase large fire activity. Predicted strong winds will challenge firefighters on the 17th. Media reports on the 16th indicate federal troops will join the 21,000 firefighters. Fire activity as of mid-August was near to or slightly above the 10- year average. 41

Drought 42

Morning surface weather 17 August (12:00 UTC) Notice radar echos (see end of presentation) 43

5 day backtrajectories from morning of 17 Aug Fires Possible Canadian influence on Montana sites NM sites point toward regional fires in Northwest and upper Great Basin 44

Arizona Local (Regional) Dust Episode 45

Annual Percentile of Bext, OC, FS and CM on 10/16/

Surface Weather Map Before the Sampling Day 47

Surface Weather Map Midnight October 16,

Case study for September 3, 1997-Eastern US sulfate transport to Colorado Plateau 12 spatially coherent sites in TX, NM, AZ, CO 20% worst haze,with sulfate dominant 52

Highest S for all 1997 at Arizona, New Mexico sites and Mesa Verde, percentile other sites 53

2 days prior to event, flow was light from the east to southeast upwind of sites. Haze reported at many eastern US NWS stations 54

Weak cold front passes- stronger flow accelerates westward movement of hazy airmass? Flow in response to high pressure system along Canadian border 55

Bandalier, Big Bend 315 hour backtrajectories from noon local time Sep 3 BAND BIBE 56

TONT Tonto, Grand Canyon 315 hour backtrajectories from noon local time Sep 3 57 GRCA

Mt. Zirkel, Great Sand Dunes, 315 hour backtrajectories from noon local time Sep 3 MOZI GRSA 58

Conceptual model of event Highest S day for 1998 for Arizona and New Mexico sites long-range transport from eastern US Specific source areas in eastern US, unknown, could be large hazy blob and many source areas included from southeast to possibly Ohio River Valley Initial inspection of aerosol maps indicates rare to get this far west- but not unusual to reach Big Bend (from BRAVO study analyses) Movement of large early autumn high pressure west to east along Canadian border associated with this pattern and other cases of eastern US transport to Big Bend Need to document frequency of occurrence, by site of S transport from east of CENRAP, WRAP 59

Status and Schedule Aerosol descriptions done Emissions, terrain, land use, etc maps early February Backtrajectory maps – late February Meteorological site descriptions – 30 done, 10 per week progress Episode analyses- about10 done- will be ongoing for some time Conceptual model development- initial conceptual models expected by late Summer 2004 – incrementally before then

Future Phases Evaluation of EDAS wind field used for backtrajectory 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 settting affected by mesoscale source areas Triangulation of backtrajectories for worst case days to better identify source areas Regression analysis of backtrajectories, aerosol data for quantitative attribution to regions- Trajectory Mass Balance Regression Refinement of conceptual models