Causes of Haze Assessment (COHA) Update

Current and near-future Major Tasks

• Visibility trends analysis

• Assess meteorological representativeness of 2002 (modeling base year)

• PMF modeling and case study

• Evaluate winds used in back-trajectory analysis

Trends Analysis Pages - Done

Are there any statistically significant multi year trends in the haze levels and causes of haze?

http://coha.dri.edu/web/general/tools_trendanaly.html

• National maps and tables• Individual site analysis

Trends Analysis for Aerosol Light Extinction Coefficients (1/Mm) in 20% Worst Days

Note:: ncrease Trend : Decrease Trend The size of the arrow is related to the slope (1/Mm/Year). Red: P Value <= 0.05 Yellow: 0.05 < P Value <= 0.1 Light Blue: 0.1 < P Value <= 0.2 Dark Blue: P Value > 0.2

Meteorological Representativeness of 2002- Backtrajectory Analysis

• Generate 8-day back-trajectories of all WRAP IMPROVE aerosol monitoring sites (every 3 hrs, from 3 starting heights) for 2003 and 2004 to give 5 years of trajectories - 80% Done, will be done by October.

• Produce residence time maps for 2002 and the 5-year period (2000 – 2004), plus maps of ratios and of differences of 2002 and the 5-year period for each site. Interpret the maps for each monitoring site and document on the COHA web site – Will be done by November

GRCA2 difference and ratio in residence time between 2002 and the 5-yr period 2000 to 2004

Difference Map

Ratio Map

Receptor Modeling - Positive Matrix Factorization (PMF) and Chemical Mass Balance (CMB)

• Mathematical technique for determining the contributions of various sources to a given sample of air

jijii

j

j

i I

II

SPSPSP

SPSPSPSPSPSP

C

CC

2

1

21

22221

11211

2

1

SPij – Source Profile: Emissions of compound i from source j (100%).

Ij – Contribution of source j (g/m3).

Ci – Concentration of compound i (g/m3).

CMB PMF

Input Both C and SP Only C

Output Only I Both SP and I

Receptor Modeling - Positive Matrix Factorization (PMF) and Chemical Mass Balance (CMB) (Cont.)

CMB PMF

Assumptions Composition of source emissions is relatively constantEmissions do not react or selectively deposit between source and receptor (mass is conserved)Source profiles are linearly independentFor CMB, all major sources should be included in the model

Limitations Reactive compoundsOnly identifies categories of sources, not individual sourcesIdentifies only relative contributions, not mass emission rates

Limitations Must know source profilesHigh sensitivity to uncertainty / error in source profilesOmission of a source can lead to large errors

Pure statistical modellarge number of samples (100+) are neededNeed to make arbitrary decision of the number of sources (factors)

Positive Matrix Factorization for Groups of Sites Using 2000 – 2004 Aerosol Data

Grouping of Class I areas by TSSA source region attribution of sulfate and nitrate – 22 groups including Hawaii and Alaska

Ready to go. Waiting for 2004 aerosol data, will be finished in ~1 month once data are available

PMF Running Parameters• Running Mode: Robust Mode, the value of outlier

threshold distance = 4.0 (i.e. if the residue exceeds 4 times of the standard deviation, a measured value is considered outlier).

• Error Mode (decides the standard deviation of the data):EM = -12 (based on observed value)

• FPEAK and FKEY Matrix (controls the rotation) – default: 0 (central), may try different numbers

PMF Input Data – Data Value and Uncertainty

• 2000 -2004 aerosol PM10 and PM2.5 mass and chemical speciation data from the VIEWS web site (Al data are excluded due to the large uncertainties in measurements).

• Data are screened to remove the days when either PM10 or PM2.5 mass concentration is missing.

• Data value and associated uncertainty

If data is missing Thendata value = geometric mean of the measured valuesuncertainty = 4 * geometric mean of the measured values

Else if data bellows detection limitdata value = 1/2 * detection limituncertainty = 5/6 * detection limit

Elsedata value = measured datauncertainty = analytical uncertainty + 1/3 * detection limit

PMF Output• Source profiles

PMF Output (Cont.)

• Contributions of each source to aerosol mass and light extinction for each sampling day

0

0.5

1

1.5

2

2.5

1/3/03

2/2/03

3/4/03

4/3/03

5/3/03

6/2/03

7/2/03

8/1/03

8/31/0

3

9/30/0

3

10/30

/03

11/29

/03

12/29

/03

BRCA1ZION1ZICA1CAPI1

g/m3

Other Planned Work (FY06)

1.Case study for selected sites: PMF modeling for individual sites

2.Compare PMF results for the selected sites based on group modeling and individual modeling

3.Compare PMF smoke factor contribution with 2002 fire emissions inventory and DRI fire database

4.Combine PMF modeling results with the backtrajectories and emission inventories to investigate the major source regions of certain aerosol sources (e.g. smoke) for each site

5.Episode analysis based on PMF results

Other Planned Work (FY06) cont.

6. Redo aerosol composition statistics using 2000-2004 baseline period?

7. Evaluate winds used in back-trajectory calculations- Measurement data for evaluation collected- Evaluation done by December or so

8. Prepare overview page for each site: list of products available for the site

Comparison of Source Factors Based on PMF Modeling for AGTI1 and Group 6 (AGTI1, JOSH1, PINN1, PORE1, RAFA1, SAGA1, SAGO1)

0.0001

0.001

0.01

0.1

1

AS BR CA EC1 EC2 EC3 OC1 OC2 OC3 OC4 OP CL CR CU H FE PB MG MN NI NO3 P K RB SE SI NA SR S TI V ZN ZR

AGTI1 Group6

0.0001

0.001

0.01

0.1

1

AS BR CA EC1 EC2 EC3 OC1 OC2 OC3 OC4 OP CL CR CU H FE PB MG MN NI NO3 P K RB SE SI NA SR S TI V ZN ZR

0.0001

0.001

0.01

0.1

1

AS BR CA EC1 EC2 EC3 OC1 OC2 OC3 OC4 OP CL CR CU H FE PB MG MN NI NO3 P K RB SE SI NA SR S TI V ZN ZR

0.0001

0.001

0.01

0.1

1

10

AS BR CA EC1 EC2 EC3 OC1 OC2 OC3 OC4 OP CL CR CU H FE PB MG MN NI NO3 P K RB SE SI NA SR S TI V ZN ZR

0.0001

0.001

0.01

0.1

1

AS BR CA EC1 EC2 EC3 OC1 OC2 OC3 OC4 OP CL CR CU H FE PB MG MN NI NO3 P K RB SE SI NA SR S TI V ZN ZR

Comparison of Factor Contributions to AGTI1 PM2.5 Based on PMF Individual and Group Modeling

0

0.5

1

1.5

2

2.5

SecondarySulfate

Aged SeaSalt

Dust SecondaryNitrate

Smoke

Individual Modeling

Group Modeling

g/m3

Backtrajectory Analysis for PMF Factor - Example

Backtrajectory analysis for PMF modeled factor 5 (BWS5) (Weighted – Unweighted). This serves to confirm that the factor 5 is in actual fact a “vegetative burn” factor from wildfires to the northwest of Boundary Waters Canoe Area IMPROVE site (Engelbrecht et al., 2004).

Causes of haze questions-

1. What are the aerosol components responsible for haze? – Aerosol summary for 5 baseline period

2. What is the role of meteorology in the causes of haze? – Baktrajectory analysis of transport, difference of 2002 from 2000-2004 average, episode analysis

3. What are the emissions sources responsible for haze? – PMF analysis, off-shore shipping analysis, dust analysis, fire analysis, EI data comparison

4. Are there any detectable and/or statistically significant multi-year trends in the causes of haze? – Trend analysis already completed