# IMPROVE PMF Factor Identification notes 

# Positive Matrix Factorization Analysis of HALE1 & HAVO1 IMPROVE data sets Regional Haze Program Visibility Assessment

4/20/2012 State of Hawaii, Department of Health, Clean Air Branch

# IMPROVE PMF Factor Identification notes Positive Matrix Factorization Analysis of HALE1 & HAVO1

IMPROVE data sets

• Signal to Noise: Assessment of IMPROVE Data and Uncertainty
• Coefficient of determination: Assessment of PMF results
• PMF factor profiles and identification discussion

# IMPROVE Data Signal to Noise

• IMPROVE data from Scott Copeland (CIRA) was used for the PMF analysis

– Data set validation and data units verification were accomplished through calculation of mass densities and visibility impacts associated with the HAVO1 and HALE1 Hawaii National Parks for the years 2001
- 2004 for the Worst 20% and Best 20% days; results were compared to WRAP TSS 2000
- 2004 Emission Scenarios and matched very well.


## • Concentration (x) and uncertainty (s) data sets were prepared

– Values were unchanged from those given in the data set except for
• Elemental/molecular species blank values, which were replaced with annual statistical means
• Uncertainties for “Visibility Impacting” mass densities (ex. Ammonium sulfate), not included in the data set, were set proportional to concentration values to achieve an arbitrary, but low, signal to noise of 3.0. (see PMF analysis section for additional discussion)


## • Signal to noise was calculate using Equation 1 in the EPA PMF v3.0 Fundamentals & User Guide (Norris et al, 2008)

# IMPROVE Data Signal to Noise: HALE1 - 2005

# IMPROVE Data Signal to Noise: HALE1 - 2003 - 8

# IMPROVE Data Signal to Noise: HAVO1 - 2005

# IMPROVE Data Signal to Noise: HAVO1 - 2003 - 8

# PMF 3.0 Species r^2: Definition of r

The “EPA PMF 3.0 User Guide” states that the “coefficient of determination (r 2 

### )” is included in the output statistics. While not stated explicitly in the guide, “r” is computed using the Pearson correlation coefficient; where X, Y, and n are the IMPROVE data set, post PMF reconstructed data set, and number of elements in the data set.

Note that EPA PMF 3.0 output, in addition to r 2 

### , includes linear regression slope and intercept values for each species being evaluated. This augments the information provided by the “r” which is invariant to location (“a” and “c” in the equation below) and scale (“b” and “d” in the equation below) changes that apply to all elements in a data set (as discussed in http://en.wikipedia.org/wiki/Correlation_and_dependence#Pearson.27s_p 

### roduct
- moment_coefficient )

# PMF 3.0 Species r^2: Results

# Volcano Profiles

• HAVO1 (both 2005 and 2003
- 8) has 3 Volcano profiles. They have very similar time histories, but different speciation.

– Volcano #1 (Metals with high Selenium):

– Volcano #2 (Low Metals)

– Volcano #3 (Metals with high Potassium, Sodium & Strontium) 

### • HALE1 (both 2005 and 2003
- 8) has one Volcano profile.

– Volcano #1 (Metals with high Selenium) 

### • Volcano profiles are all high in sulfate and low in nitrate.

– Note that it while a relatively significant percentage of the HAVO1 nitrate is attributed to Volcano #2 & Volcano #3 factors, the absolute magnitude is very small; 0.00 to 0.01 micrograms/m^3. 

### • Volcano profiles represent the vast majority of sulfate content at HAVO1. This is consistent with the fact that the Kilauea volcano emits more SO2 than the combined output of the top 10 dirtiest power plants in the USA.


### • The time histories associated with the 2005 data sets for HAVO1 and HALE1 both appear similar to the Trajectory Distance Data Distribution plots (see Appendix B).

– The time histories associated with the 2005 data sets for HAVO1 and HALE1 both appear similar to the Trajectory Distance Data Distribution plots calculated from Alpine MM5 data using HYSPLIT.

– Trajectories are started hourly at the Hawaii volcano summit (trajectory #1) and rift zone (trajectory #2) and shown in 24 hour time bins. Time bins begin at 1000 UTM to match 10 hour Hawaii time difference from UTM.

# Volcano #1 (Metals with high Selenium): 2005 - HALE1

# Volcano #1 (Metals with high Selenium): 2003 - 8 - HALE1

# Volcano #1 (Metals with high Selenium): 2005 - HAVO1

# Volcano #1 (Metals with high Selenium): 2003 - 8 - HAVO1

# Volcano #2 (Low Metals): 2005 - HAVO1

# Volcano #2 (Low Metals): 2003 - 8 - HAVO1

## Volcano #3 (Metals with high Potassium, Sodium & Strontium): 2005 - HAVO1

## Volcano #3 (Metals with high Potassium, Sodium & Strontium): 2003 - 8 - HAVO1

## Additional Information: Volcano #1 (HALE1 & HAVO1), #2 & #3 (HAVO1)

• ANNETTE T. HOLLINGSHEAD, STEVEN BUSINGER, ROLAND DRAXLER, JOHN PORTER and DUANE STEVENS, ” DISPERSION MODELLING OF THE KILAUEA PLUME”, Boundary
- Layer Meteorology 108: 121 – 144, 2003.
• “The volcanic aerosol plume is composed mainly of water vapour , SO2, and sulfate particulates. As mentioned previously, SO2 rapidly converts to sulfate particulates in the high relative humidity conditions near the main vent.”
• “Once sulfuric acid aerosols are formed, the addition of naturally existing ammonia can partially neutralize the aerosol to form ammonium bisulfate, (NH4)HSO4, or totally neutralize the aerosol to form ammonium sulfate, (NH4)2SO4. However, volatility measurements in the volcano plume show that the aerosols remain highly acidic, with very little neutralization even after being advected more than 1,600 km downwind (Clarke and Porter, 1991).”

• USGS, Hawaiian Volcano Observatory, Volcano Watch: June 5, 2008 – “What to worry about in Kilauea volcanic emissions?” ( http://hvo.wr.usgs.gov/volcanowatch/2008/08_06_05.html )
• “Kilauea is currently producing up to 4,000 tonnes /day of SO 2 , resulting in concentrations in air greater than 5 parts per million ( ppm ) in downwind communities within 50 km (31 miles). Sustained concentrations greater than 0.3 ppm are considered unhealthy. During its journey through the air, the SO 2 reacts with oxygen, sunlight, and water to form vog , a mixture of gas and tiny sulfuric acid aerosol droplets.”
• “Water, SO2, and CO2 comprise about 99 percent of Kilauea's emissions. All the other constituents together account for the remaining 1 percent and there are many of them. Hydrogen (H2), Hydrogen Chloride ( HCl ), Hydrogen Fluoride (HF), and Carbon Monoxide (CO) are the principal minor constituents. Of these, H2 and CO are already in the atmosphere at trace levels.”
• “About one tonne

/day, combined, of various metals, such as lead, copper, gold, silver, zinc, bismuth, and mercury are emitted by Kilauea. There are many more components present in trace amounts - in fact, it's probably easier to name elements that are not present in Kilauea emissions than to list all the ones that are.”

## Additional Information: Volcano#1 (Metals with high Selenium ) 

## HALE1 & HAVO1

• USGS, Hawaiian Volcano Observatory, Volcano Watch: July 27, 2006 – “Volcanic selenium and sulfur
- a delicate balance” ( http://hvo.wr.usgs.gov/volcanowatch/2006/06_07_27.html )
• “Both natural and man
- made sources contribute selenium to the environment. Primary anthropogenic sources include copper production and coal and oil combustion. Since there is a narrow range between safe and dangerous levels of selenium, areas with excess selenium due to man
- made pollution are of concern.”
• “While natural sources of selenium include soil, plants, microorganisms, animals, and sea salt, volcanoes also comprise a significant source of selenium . In 1986, the annual selenium emissions from Kilauea were estimated at eight tons. This is roughly eight times more selenium than that emitted as manmade pollution in Los Angeles County and 900 times more than that from manmade sources on the Big Island.”

## Additional Information: Volcano#1 (Metals with high Selenium) - 

## HALE1 & HAVO1

• PMF analysis for HALE1 (2005) on Worst 20% days:
• 33.4% of copper is associated with this factor(r^2=0.01)
• 56.5% of hydrogen is associated with this factor (r^2=0.95)
• 29.0% of lead is associated with this factor (r^2=0.58)
• 0.0% of nitrate is associated with this factor (r^2=0.97)
• 64.6% of selenium is associated with this factor (r^2 = 0.29)
• 67.2% of sulfur is associated with this factor (r^2=0.96)
• PMF analysis for HALE1 (2003
- 2008) on Worst 20% days:
• 28.2% of copper is associated with this factor(r^2=0.11)
• 66.3% of hydrogen is associated with this factor (r^2=0.96)
• 27.1% of lead is associated with this factor (r^2=0.47)
• 0.7% of nitrate is associated with this factor (r^2=0.93)
• 75.2% of selenium is associated with this factor (r^2 = 0.60)
• 76.7% of sulfur is associated with this factor (r^2=0.98)
• PMF analysis for HAVO1 (2005) on Worst 20% days:
• 67.9% of copper is associated with this factor(r^2=0.80)
• 29.3% of hydrogen is associated with this factor (r^2=0.83)
• 74.8% of lead is associated with this factor (r^2=0.97)
• 0.0% of nitrate is associated with this factor (r^2=0.63)
• 93.1% of selenium is associated with this factor (r^2 = 1.00)
• 49.9% of sulfur is associated with this factor (r^2=0.97)
• PMF analysis for HAVO1 (2003
- 2008) on Worst 20% days:
• 65.6% of copper is associated with this factor(r^2=0.60)
• 16.4% of hydrogen is associated with this factor (r^2=0.66)
• 84.5% of lead is associated with this factor (r^2=0.99)
• 0.0% of nitrate is associated with this factor (r^2=0.76)
• 64.6% of selenium is associated with this factor (r^2 = 0.90)
• 85.4% of sulfur is associated with this factor (r^2=0.95) • These PMF factors have high percentages of the IMPROVE total sulfur, hydrogen, selenium and other metals.
• They also have low percentages of nitrate.
• This is the only Volcano factor associated with HALE1.
• Note that useful information can be gained from considering the factor mass percentage, mass density, and r^2 associated with a given atomic/molecular species.

• For these factors, even though the r^2 associated with the metals were not very high, the combination of the high sulfur and low nitrate

# Asian Dust

• Asian dust profiles have the following distinguishing characteristics

– Fine soil (Al, Ca, Fe, Si, Ti) metals



### – Significant percentage of the total Manganese mass density

• Mn is a recognized trace constituent of Asian dust; http://karws.gso.uri.edu/DustClub/Articles/Lee%202004%20Dust%20Ulsan.pdf



### – Similar factor time histories for both HALE1 and HAVO1

• 2005 data set profiles
• 2003
- 2008 data set profiles
• 2005 data sets have similar features to those found in 2003
- 2008 data set profiles

# Dust (Asian): 2005 - HALE1

# Dust (Asian): 2003 - 8 - HALE1

# Dust (Asian): 2005 - HAVO1

# Dust (Asian): 2003 - 8 - HAVO1

## Nitrate/Sulfate - Rich - Secondary(Iron)



# • Factors present only at HALE1

– These factors were similar to COHA “Nitrate
- rich Secondary (Iron)” for 

## Hawaii. Note that the COHA factor also had sulfate.

– 2005 data set: 1 of the 8 factors were characterized by relatively high nitrate, sulfate, and iron

– 2003
- 2008 data set: 2 of the 8 factors were characterized by relatively 

## high nitrate, sulfate, and iron

# Nitrate/Sulfate - Rich Secondary (Iron): 2005 - HALE1

# Nitrate/Sulfate - Rich - Secondary(Iron): 2003 - 8 - HALE1::factor 3

# Nitrate/Sulfate - Rich Secondary (Iron): 2003 - 8 - HALE1::factor 4

# Smoke (Bromine)

• These factors are characterized by the high percentage of total Bromine mass density
• The broad term “Smoke (Bromine)” is meant to be associated with a broad range of man
- made sources that
• The COHA PMF analysis ( http://www.coha.dri.edu/web/general/tools_PMFModeling.html ) identified similar factors as

– Secondary (Alaska)

– Urban/Diesel (Colorado Plateau)



### – Smoke (Death Valley)

– Mobile (Columbia River Gorge)


## • The EPA “Multivariate Receptor Modeling Workbook” (Sept 2005) identifies Bromine as a “Key Species” for “Vehicle Exhaust”

– http://www.sonomatechdata.com/sti_workbooks/#MVRMWB

# Smoke (Bromine): 2005 - HALE1

# Smoke (Bromine): 2003 - 8 - HALE1

# Smoke (Bromine): 2005 - HAVO1

# Smoke (Bromine): 2003 - 8 - HAVO1

# Oil Combustion (Nickel & Vanadium)

• These factors are characterized by the high percentage of total Nickel and Vanadium, mass density
• The COHA PMF analysis ( http://www.coha.dri.edu/web/general/tools_PMFModeling.html ) identified similar factors as

– Sulfate
- rich Secondary/Oil Combustion (California Coast)

– Oil Combustion (Northwest)

– Urban/Diesel (Colorado Plateau)

– Smoke (Death Valley)



### – Mobile (Columbia River Gorge)


## • The EPA “Multivariate Receptor Modeling Workbook” (Sept 2005) identifies Nickel and Vanadium as a “Key Species” for “Residual Oil Combustion”

– http://www.sonomatechdata.com/sti_workbooks/#MVRMWB

# Oil Combustion (Nickel & Vanadium): 2005 - HALE1

# Oil Combustion (Nickel & Vanadium): 2003 - 8 - HALE1

# Oil Combustion (Nickel & Vanadium): 2005 - HAVO1

# Oil Combustion (Nickel & Vanadium): 2003 - 8 - HAVO1

# Sea Salt/Nitrate - Rich - Secondary

• These factors are characterized by the high percentage of total Chlorine (CL) & Chloride (CHL) mass density.
• The COHA PMF analysis ( http://www.coha.dri.edu/web/general/tools_PMFModeling.html ) 

## identified similar factors as

– Sea Salt (Hawaii)


## • The EPA “Multivariate Receptor Modeling Workbook” (Sept 2005) identifies Chloride as a “Key Species” for “Sea Water”

– http://www.sonomatechdata.com/sti_workbooks/#MVRMWB

# Sea Salt/Nitrate - Rich - Secondary: 2005 - HALE1

# Sea Salt/Nitrate - Rich - Secondary: 2003 - 8 - HALE1

# Sea Salt/Nitrate - Rich - Secondary:2005 - HAVO1

# Sea Salt/Nitrate - Rich - Secondary: 2003 - 8 - HAVO1

# Shipping (Zinc)

• These factors are characterized by the high percentage of total Zinc mass density. “Shipping” was selected since it best matched with the Hawaii COHA 

### results and would be expected to be most applicable.
• The COHA PMF analysis ( http://www.coha.dri.edu/web/general/tools_PMFModeling.html ) identified similar factors as

– Aged Sea Salt (Alaska)

– Mobile (Central Rockies)

– Nitrate
- rich Secondary (Colorado Plateau)

– Mobile (Columbia River Gorge)

– Mobile/Others (Death Valley)



### – Diesel (Great Basin)

– Shipping (Hawaii)

– Nitrate
- rich Secondary/Mobile (Hells Canyon)


### • The EPA “Multivariate Receptor Modeling Workbook” (Sept 2005) identifies 

### Chloride as a “Key Species” for “Municipal incinerator; also smelters, zinc oxide kiln”

– http://www.sonomatechdata.com/sti_workbooks/#MVRMWB

# Shipping (Zinc): 2005 - HALE1

# Shipping (Zinc): 2003 - 8 - HALE1

# Shipping (Zinc): 2005 - HAVO1

# Shipping (Zinc): 2003 - 8 - HAVO1

# Major Ports in Asia

# Major Port in Western 

# Pacific

## World Port Ranking, 2005

• “The American Association of Port Authorities (AAPA) ranks the world's ports annually according to their volume capacity, container traffic, number of cruise passengers, revenues, and storage capacity, among other criteria.”
• http://www.infoplease.com/business/world

- port - ranking
- 2005.html
• Top 10 Ports within Pacific Region for both Total Cargo Volume (metric tons) and Container Traffic ( Twenty
- foot Equivalent Units
- TEU)
• Port Total Cargo Volume Container Traffic
• Shanghai #1 #3
• Singapore #2 #1
• Ningbo #4 #15
• Tianjin #5 #16
• Guangzhou #6 #18
• Hong Kong #7 #2
• Busan #8 #5
• Shenzhen N/A #4
• Kaohsiung #20 #6
• Los Angeles N/A #10

# Assessment of PMF shipping factors

• Results & Discussion

– The factors identified with shipping (tagged with blue arrows on the “Identification of Shipping” page) were originally selected based on their high Zinc content. This appeared consistent with the COHA analysis results.

– While Zinc is a documented component in shipping emissions, it does not appear to be as significant a component as Vanadium or Nickel in near
- field emission collections.

• Additional investigation is needed to find any references pertaining to characteristics of long range transport.



### – The shipping related factors for HALE1(2005) and HALE1(2003
- 2008) appear to be good matches for shipping based on the V/Ni and V/EC ratios.



### – The shipping related factors for HAVO1(2005) and HAVO1(2003
- 2008), while not appearing to be good matches based on the V/Ni and V/EC ratios, at present appear to be the best choices. Other candidate factors have characteristics that would seem to make them poor choices.

• Time
- histories and the quantities of each factors key pollutants were considered.
• When assessing PMF results, the quality of the numerical results for each species was considered. The r^2 value (r=Pearson correlation coefficient), included in the attached data, was used.

# Shipping References

• V/Ni & V/EC are recommended as possible screening parameters (Reference I1)
• Zinc content of heavy fuel oil does not appear consistent with PMF results for the factors currently identified with shipping (Reference I2)
• Reference I1: “ valid tracers of commercial shipping emissions were V/Ni = 4 - 5 and V/EC < 2 , whereas V/EC > 8 excluded the influence of shipping emissions”; Mar Viana , et.al., “Chemical Tracers of Particulate Emissions from Commercial Shipping”, Environ. Sci. Technol. 2009, 43, 7472
- 7477.

– Units: V ( ng /m^3), Ni ( ng /m^3), EC ( microg /m^3), V/Ni (1), V/EC (1/1000)

– “The monitoring station was an urban background station located approximately 150 m from the harbor and, thus, was strongly influenced by the emissions from docking ships, incoming and outgoing ships in the harbor itself, and ship traffic a cro ss the Gibraltar Strait”

– “It is important to highlight that the remaining ratios (V/S, La/ Ce , Zn/Ni, Pb /Zn, OC/EC) were tested but did not show correlations with shipping emissions and, thus, could not be considered as tracers, at this Mediterranean harbor”

– “However, due to the varying composition of particulates from shipping emissions around the world, certain of these tracers might be valid for other harbors” • Reference I2: “Composition of exhaust from a ship diesel engine using heavy fuel oil (HFO) was investigated onboard a large cargo vessel”; Jana Moldanova , et.al, “ Characterisation of particulate matter and gaseous emissions from a large ship diesel engine”, Atmospheric Environment 43 (2009) 2632
- 2641)

– Fuel Sample Characterization (mg/kg): V (107), Na (17), Al (3), Si (5), Fe (13), Ni (35), Ca (3), Mg (<1), Pb (<1), Zn (<1), P (<1), K (1)

– “EDS analyses of chemical composition of soot particles in MH and MC samples show mainly carbon with small amounts of oxygen and of vanadium, nickel, sulphur and silicon, likely originating from the HFO”; Energy Dispersive Spectrometer (EDS); MH samples are extracted in the hot exhaust, while MC samples are extracted after the particulate matter has been cooled; EDS results (weight percent) are below; “ n.d .” stands for “not detected”.

– Soot
- type particles: C (94.4%), O (0.7%), S (0.3%), V (2.7%), Ni (1.8%), Si (0.1%), Ca ( n.d .)

– Char particle: C (93.1%), O ( n.d .), S (2.1), V (3.8%), Ni (0.9%), Si ( n.d .), Ca (0.1)

– Char
- mineral particle: C (53.5%), O (3.8%), S (7.5%), V (17.6%), Ni (8.6%), Si ( n.d .), Ca (9.0%)

– Mineral/ash Particle: C (11.1%), O (5.7%), S (4.9%), V (30.7%), Ni (20.9%), Si ( n.d .), Ca (26.7)

– OC
- type particles: C (79.9%), O (5.1%), S (3.6%), V (11.2%), Ni ( n.d .), Si (0.2%), Ca ( n.d .)

# Identification of Shipping

HAVO1(2005) • The factors identified with shipping (tagged with blue arrows) were originally selected based on their high Zinc content. Thi s appeared consistent with the COHA analysis results.
• While Zinc is a documented component in shipping emissions, it does not appear to be as significant a component as Vanadium or Nickel in near
- field emission collections.
• The shipping related factors for HALE1(2005) and HALE1(2003
- 2008) appear to be good matches for shipping based on the V/Ni and V/EC ratios.

• While the V/Ni ratio for HAVO1(2005) Factor#2 would appear to be a better match for shipping, the fact that it represents suc h a large percentage of the total NO3 appears consistent with a local source.
• While the V/Ni ratio for HAVO1(2005) Factor#4 would appear to be a better match for shipping, its time

- history and species make
- up appear much more consistent with Asian Dust.
• While the V/Ni ratio for HAVO1(2003

- 2008) Factor#4 would appear to be consistent with shipping, the fact that it represents such a large percentage of the total NO3 appears consistent with a local source. HALE1(2005)

HALE1(2003 - 2008) HAVO1(2003 - 2008)

# HALE1 (2005): PMF Results

# HALE1 (2005): IMPROVE results

# HALE1 (2003 - 2008): PMF Results

# HALE1 (2003 - 2008): IMPROVE results

# HAVO1 (2005): PMF Results

# HAVO1 (2005): IMPROVE results

# HAVO1 (2003 - 2008): PMF Results

# HAVO1 (2003 - 2008): IMPROVE results

# Brush Fire/Burning Vegetation

• This factor is characterized its short duration (2 adjacent measurements), high percentage of Phosphorus and Potassium total mass densities, and low NO3 and Sulfur mass densities.
• The COHA PMF analysis 

## ( http://www.coha.dri.edu/web/general/tools_PMFModeling.html ) did not have a similar factor.
• The EPA “Multivariate Receptor Modeling Workbook” (Sept 2005) identifies ( http://www.sonomatechdata.com/sti_workbooks/#MVRMWB )

– Potassium as a “Key Species” for “Vegetative Burning, soil”

– NOTE: While Phosphorus is a “Key Species” for “Fuel Combustion”, the PMF r^2 for Phosphorus is approximately zero in most cases. The apparent presence of Phosphorus is thus not felt to be a reliable indicator of a man - made source.

# Brush Fire/Burning Vegetation: 2005 - HALE1