Annex F. Source Apportionment Studies 

Table F-1. Epidemiologic studies of ambient PM sources, factors, or constituents 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 31 

Grouping 

method: PCA + 

PMF/CMB hybrid 

(COPREM) 

# of groups: 12, 

but only 6 used in 

relating to health 

effects, and CO, 

NO2

Groups/Factors/ Sources:

Road, vehicle, salt, 

biomass, oil, coal, rock, 

lime, NaNO3, NH4NO3, 

(NH4)2SO3, (NH4SO4) 

PM variables used:

Mass contribution of 

sources 

Reference: Andersen et 

al. (2007, 093201) 

Location: 1 monitor in 

Copenhagen, Denmark/ 

6 yr, but apportionment 

done for 1.5 yr only 

(2002-2003) 

Particle Size: PM10

Results: Single pollutant models: Biomass, secondary compounds, oil, and crustal significantly associated with CVD HA 

(4-day ma). Biomass and secondary components significantly associated with respiratory HA (5-day ma). No significant effects 

for asthma HA in children (6-day ma). 

Two pollutant models: Crustal effect for CVD admissions remained robust. Biomass effect for respiratory admissions was 

highest. Effect of vehicle source remained robust for asthma admissions in children in presence of other PM10 sources. 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 16 

elements + NO3, 

SO4, EC, OC 

Grouping 

method: NR 

# of groups: NR 

Groups/Factors/ Sources:

NR 

PM variables used:

Every component (16 

elements + NO3, 

SO4,EC, OC) 

Reference: Bell et al. (Bell 

et al., 2009, 191007) 

Location: PM2.5: 

2000-2005 (6 yr)/106 US 

counties/EPA composition 

data 

PM10: 1987-2000/100 

counties/EPA composition 

data 

Particle Size: PM10, PM2.5

Results: Mortality: Ni significantly increased PM10 mortality risks. However, effect of Ni was not significant when New York City 

was removed, in a sensitivity analysis conducted by selectively removing cities from the overall estimate. 

Hospital Admissions: CVD and respiratory HAs higher in counties with higher EC, Ni, and V PM2.5. In CVD association 

between PM2.5, RR and V robust to inclusion of EC or V, and V robust to inclusion of EC. 

Subjects: NR 

Exposure:

1998-2009 

(8.3 yr) 

N: NR Number of 

Constituents 

considered for 

grouping: 16 

elements + CO, 

NO2, SO2, EC, 

OC 

Grouping 

method: PCA 

# of groups: 4 

Groups/Factors/ Sources:

Vehicle (CO, NO2, EC, OC), 

Soil (Al, Ca, Fe, Si), 

Combustion (Cr, Cu, Fe, 

Mn, Zn), Factor 4 (Br, Cl, 

Pb) 

PM variables used:

individual components, 

then groupings 

Reference: Cakmak et al. 

(2009, 191995) 

Location: 1 monitor in 

Santiago, Chile 

Particle Size: PM2.5

Results: Individual components: EC, OC only stat. sign. risk estimates for total, cardiac, and respiratory mortality for 1-day lag 

after adjustment for other elements. 

Groupings: Lag 1. Vehicle factor: Increased total mortality, cardiac mortality, and respiratory mortality. Soil factor: increased 

cardiac mortality and respiratory mortality (but smaller than vehicle factor RRs). Combustion factor: greatest RR for respiratory 

mortality, but significant for total and cardiac mortality. Factor 4: increased total, cardiac, and respiratory mortality. Point 

estimates for Factor 1 significantly different from Factors 3 and 4. Elderly had higher risk estimates for combustion and soil 

sources. No significant effect modification by gender or season. 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 15 

elements + EC, 

OC, NO3

Grouping 

method: NR 

# of groups: NR 

Groups/Factors/ Sources:

NR 

PM variables used:

Every component 

Reference: Franklin et al. 

(2008, 097426) 

Location: STN/25 

communities/2000-2005 

(6 yr) 

Particle Size: PM2.5 Results: The PM2.5-mortality association was significantly modified by Al, As, Sulfate, Ni, and Si. When including a combination 

of species proportions and using backwards elimination Al, sulfate, and Ni remained significant. Al and Ni explained most of the 

residual heterogeneity. 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database (Health and 

Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used by U.S. EPA in the process of 

developing science assessments such as the Integrated Science Assessments (ISA) and the Integrated Risk Information System (IRIS). 

December 2009 F-1 
Subjects:

Children with 

physician 

diagnosed 

asthma and 

symptoms or 

medication use 

in previous 12 

mo, and resided 

within 30km of 

New Haven 

county monitor 

Exposure: NR 

N: 149 

children 

Number of 

Constituents 

considered for 

grouping: 17 

elements + EC 

Grouping 

method: PCA 

# of groups: 6 

Groups/Factors/ Sources:

Vehicle (EC, Zn, Pb, Cu, 

Se), road dust (Si, Fe, Al, 

Ca, Ba, Ti), sulfur (S, P), 

biomass burning, (K) oil (V, 

Ni), sea salt (Na, Cl) 

In addition, effects of NO2, CO, SO2, and O3 were 

included in the health 

outcomes model 

PM variables used:

Groupings and 

individual elements 

Reference: Gent et al. 

(2009, 180399) 

Location: 2 monitors in 

New Haven, CT/ 3.5 yr 

Particle Size: PM2.5

Results: Overall: Trace elements originating from motor vehicle, road dust, biomass burning, and oil sources associated with 

symptoms and/or medication use. No associations with S or sea salt. 

Specific Results: PM2.5 mass from motor vehicle or road dust associated with increased odds of respiratory symptoms or 

inhaler use. Reduced odds of wheeze or inhaler use with same day S. Significant reductions odds of wheeze with biomass 

burning. 

Co-pollutant: Positive effects of motor vehicles and road dust on wheeze were robust to the inclusion of gaseous copollutants. 

However, NO2 increases association with wheeze. 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: NR 

Grouping 

method:

Comparison of: 

PMF; (absolute) 

PCA; UNMIX 

# of groups: 6-10 

Groups/ Factors/ 

Sources: Different 

research groups 

gave different 

names to sources 

Sources for which 

association with health 

was analyzed: Soil, traffic, 

Secondary SO4, NO3

(Washington, DC only), 

residual oil (Washington, 

DC only), Wood smoke/ 

biomass combustion, Sea 

salt, incinerator 

(Washington, DC only), 

primary coal (Washington, 

DC only), Cu smelter 

(Phoenix only) 

PM variables used:

Mass contribution of 

sources 

Reference: Ito et al. 

(2006, 088391) 

Location: Washington, 

DC 

Particle Size: PM2.5

Results: Overall, PM2.5 effects observed at lag 3. Lag structure of association varied across source types, but consistent 

across investigators for total (nonaccidental mortality): soil factor - mostly positive at various lags (not significant); secondary 

sulfate - strongest association at lag 3; nitrate - mostly negative except at lag 3; residual oil - strongest association at lag 2 (not 

significant); wood-burning - increasing association as lag increases (not significant); incinerator - significant negative 

associations at lag 0; primary coal - significant association at lag 3. 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 15 

elements 

Grouping 

method: PCA 

# of groups: 8 

Groups/ Factors/ Sources:

Soil/crustal (PM fine), 

mobile vehicle exhaust (PM 

fine), coal (PM fine), fuel oil; 

metals, salt manganese, 

residual 

PM variables used:

Tracers: Si, V, Cl, Pb, 

Se 

Reference: Laden et al. 

(2000, 012102) 

Location: Monitors in 6 

Eastern US cities (Harvard 

Six Cities Study) 

Particle Size: NR Results: Lag 0-1 avg for all results. Overall 6 cities, mobile source factor (using Pb as tracer) had greatest association with 

daily mortality (3.4%) with 10 μg/m3 increase. The greatest effects for mortality due to mobile sources were observed in 

Madison (Portage), Knoxville (Kingston-Harriman), and St. Louis, although the Madison results were not statistically significant. 

The coal source factor was only significant in Boston (Watertown) - 2.8% increase in mortality and the overall percent increase

was also significant (1.1%). Deaths from pneumonia attributable to coal combustion sources was 7.9% (CI 3.1-12.7%) and 

statistically significant. The crustal factor was not associated with mortality in any city, although this factor was not a significant 

predictor in the regression model for Boston (Watertown) due to its low contribution to PM2.5 mass. For specific elements 

included simultaneously, S, Pb, and Ni were significantly associated with overall mortality (3.0, 1.6, 1.5%, respectively). Boston 

had the greatest percent increase in mortality for S (7.9%), Knoxville for Pb (15.0%), and Steubenville for Ni (8.2%), although

the CIs are all quite large. 

Reanalysis results: (Schwartz, 2003, 042811) Effects changed slightly. New percent increases in mortality for combined cities 

are 3.5 and 0.79 for traffic and coal, respectively. The coal factor in Boston decreased to 2.1% increased mortality. A residual 

oil factor in Boston and Steubenville resulted in at 22.9% increase in daily deaths (but was not significant in the original 

analysis). 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 13 

elements 

Grouping 

method: Absolute 

PCA 

# of groups: 5 

Groups/ Factors/ Sources:

Crustal; long range 

transported; oil combustion; 

soil; traffic 

PM variables used:

Tracers: Si (crustal); S 

(long-range transport); 

Ni (oil combustion); Cl 

(salt); ABS (local 

traffic). 

Reference: Lanki et al. 

(2006, 088412) 

Location: Monitors in 

Helsinki, Finland, 

Amsterdam,The 

Netherlands and Erfurt, 

Germany 

Particle Size: UF/PM2.5

Results: Highest observed effects were for crustal sources and salt at lag 3 (when analyzing sources), but not consistent or 

significant. In multipollutant models only ABS associated with ST-segment depression, but wide CIs. When examining indicator 

elements of a source, local traffic found to be the most toxic, but when examined per IQR long-range transport and traffic had 

similar effects. 

December 2009 F-2 
Results: All had significant associations with mortality. Traffic density and EC had the largest effects. 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: NR 

Grouping 

method: No 

grouping was 

performed 

# of groups: NR 

Groups/ Factors/ Sources:

NR 

PM variables used:

Mass contribution of 

16 constituents 

Reference: Lippmann et 

al. (2006, 091165) 

Location: U.S. 

Particle Size: PM10 for risk 

estimates, PM2.5 for 

speciation data Results: The strongest predictions of the variation in PM10 risk estimates across the 90 NMMAPs MSAs was for Ni and V. 

Elevated, but nonsignificant increases were associated with EC, Zn, SO42-, Cu, Pb, and OC. Al and Si had the lowest values. 

Subjects:

Elderly only 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 10 

elements, OC, 

EC, CO, NO2; 

SO2

Grouping 

method:

Unspecified type of 

factor analysis 

# of groups: 3 or 5

Groups/ Factors/ Sources:

Motor exhaust/road dust, 

soil, vegetative burning, 

local SO2, regional SO4

PM variables used:

First used individual 

constituents: S, Zn, 

Pb, K, OC, EC, TC 

(AL+Si+Ca+Fe+Ti), 

then factor scores 

Reference: Mar et al. 

(2000, 001760) 

Location: 1 monitor in 

Phoenix, AZ 

Particle Size: NR 

Results: Cardiovascular mortality associated with PM2.5 mass on lag 1 and 4 (6 and 4%, respectively). EC and TC associated 

with CV mortality for lag 1 (RR = 1.05); OC was weakly associated with CV mortality for lags 1 and 3. For total mortality, 

regional sulfate was positively associated at lag 0, but negatively associated at lag 3. The local SO2 and the soil factors were 

negatively associated with total mortality. For CV mortality, secondary sulfate was positively associated at lag 0, motor vehicle 

at lag 1, and vegetative burning at lag 3. 

Reanalysis results (Mar, 2003): Similar associations were observed. 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: NR 

Grouping 

method:

Comparison of: 

PMF (absolute); 

PCA; UNMIX 

# of groups: 6-10 

Groups/ Factors/ 

Sources: Different 

labs gave different 

names to sources 

(see Hopke et al, 

table 2) 

Sources for which 

association with health was 

analyzed: Soil, Traffic, 

secondary SO4, NO3, 

(Washington, DC only), 

residual oil (Washington, 

DC only), woodsmoke/ 

biomass combustion, sea 

salt, incinerator 

(Washington, DC only); 

primary coal (Washington, 

DC only); Cu smelter 

(Phoenix only) 

PM variables used:

Mass contribution of 

sources 

Reference: Mar et al. 

(2006, 086143) 

Location: Phoenix, AZ 

Particle Size: PM2.5

Results: Using daily PM2.5 data found the following associations with cardiovascular mortality: Secondary sulfate - greatest 

effect observed for all sources and at lag 0; traffic - associated at lag 1; copper smelter associated at lag 0; sea salt - had the 

greatest statistical significance and observed at lag 5; biomass/wood burning - less consistent lag structure but greatest 

association at lag 3; soil - did not show an association or consistent lag structure. For total (nonaccidental) mortality 

associations were weaker and consistently observed for only: copper smelter - lag 0; sea salt - lag 5. 

Subjects NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 15 

elements, EC, 

OC; NO3; SO4, 

PM2.5 mass 

Grouping 

method: No 

grouping was 

performed 

# of groups: NA 

Groups/ Factors/ Sources:

NR 

PM variables used:

Mass contribution of 

every constituent 

Reference: Ostro et al. 

(2007, 091354) 

Location: Monitors in 6 

CA counties, some with 2 

monitors, for 4 yr 

Particle Size: PM2.5

Results: Effects were greater during the winter months. In the all year analysis, at 3-day lag associations observed for EC, OC, 

NO3 and Zn. During winter months (Oct -March) effects observed for most species for both all-cause and cardiovascular 

mortality at lag 3 (EC, OC, SO4, Ca, Fe, K, Mn, Pb, S, Si, Ti, Zn) and (OC, NO3, SO4, Fe, Mn, S, V, Zn), respectively. 

Subjects NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 9 

elements,EC, OC, 

PM2.5 mass, SO4, 

NO3

Grouping 

method: No 

grouping was 

performed 

# of groups: NA 

Groups/ Factors/ Sources:

NR 

PM variables used:

Mass contribution of 

every constituent 

Reference: Ostro et al. 

(2009, 191971) 

Location: Monitors in 6 

CA counties, some with 2 

monitors/4 yr 

Particle Size: PM2.5

Results: The following associations were observed with cardiovascular mortality: PM2.5 (lag 3); EC (lag 2); NO3 (lag 3); SO4

(lag 3); Fe (lag 2); K (lag 2); S (lag 3); Ti (lag 2); Zn (lag 3). 

December 2009 F-3 
Subjects:

Medicare 

enrollees 65 or 

older 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: SO4, 

NO3, Si, EC, 

OCM, Na, NH4

Grouping 

method: NR 

# of groups: NR 

Groups/Factors/ Sources:

Only suggested in 

discussion 

PM variables used:

Tracers 

Reference: Peng et al. 

(2009, 191998) 

Location: 119 urban 

communities STN 

data/2000-2006 

Particle Size: PM2.5 Results: CVD HAs: EC associated with same-day CVD HAs in single and multi-pollutant models. In single pollutant models 

associations also observed for sulfate, nitrate, OCM, and ammonium. However, the sulfate, nitrate, OCM, and ammonium 

associations were reduced in the multi-pollutant models. 

Respiratory HAs: OCM associated with same-day respiratory HAs in single and multi-pollutant models. Some evidence for 

sulfate associations at one and two-day lag. 

Subjects: Adult 

asthma subjects, 

max 2 km from 

single monitor 

Exposure: NR 

N: 78 Number of 

Constituents 

considered for 

grouping:

Unknown 

Grouping 

method: PCA 

# of groups: 6 

Groups/Factors/ Sources:

Long range (PM mass, S, 

K, Zn), local 

combustion-traffic (Cu, Zn, 

Mn, Fe), soil (Si, Al, Ca, Fe, 

Mn), oil (V, Ni), salt (Na, Cl), 

unidentified 

PM variables used:

every component 

individually, then 

groupings 

Reference: Penttinen et 

al. (2006, 087988) 

Location: Helsinki 

1996-1997 (7 mo) 

Particle Size: PM2.5

Results: Long range PM2.5 associated with decreased mean PEF in the morning at lag 1. Local combustion PM2.5 associated 

with decreased mean PEF in the evening for lag 1. Local combustion PM2.5 associated with decreased mean PEF in the 

afternoon and evening for 5-day mean lag. Negative significant association between long-range PM2.5 and asthma symptom 

prevalence at lag 3. Sea-salt PM2.5 negatively associated with bronchodilator use at lag 3 and 5-day mean lag. Sea-salt PM2.5

negatively associated with corticosteroid use for 5-day mean lag. Unidentified PM2.5 negatively associated with corticosteroid 

use at lag 1. Most consistent negative responses for local combustion, although not always significant. No consistent or 

significant associations between 5-day avg concentrations of elements and PEF, cough, asthma symptoms, or medication use. 

Subjects:

Healthy male 

young police 

officers 

Exposure: 4 

consecutive days 

N: 9 Number of 

Constituents 

considered for 

grouping: 10 

elements; 3 

gaseous 

pollutants; 2 

physical variables

Grouping 

method: PCA 

# of groups: 4 

when 13+2 

constituents 

included; 3 when 

only 9 

“PM-associated” 

constituents 

included 

Groups/ Factors/ Sources:

Soil; automotive steel wear; 

gasoline combustion; 

speed-changing traffic 

PM variables used:

Mass contribution or 

score of sources 

Reference: Riediker et al. 

(2004, 091261) 

Location: Inside 9 state 

police patrol cars 

Particle Size: PM2.5

Results: Using two different factor analysis models found most significant effects (MCL, SDNN, PNN50, supraventricular 

ectopic beats, % neutrophils, % lymphocytes, MCV, von Willebrand Factor, and protein C) were for “speed-change factor” (i.e., 

Cu, S, aldehydes). Some associations observed for “crustal” and none for “steel wear” and “gasoline.” 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: NR 

Grouping 

method:

Comparison of: 

PMF, CMB-LGO, “a 

priori decision” 

# of groups: 9,11 

(6 of them common 

between methods) 

Groups/ Factors/ Sources:

gasoline, diesel, wood 

smoke/ biomass burning, 

soil, secondary 

SO4/ammonium sulfate, 

secondary nitrate/ 

ammonium nitrate, metal 

processing, railroad, bus 

and highway, cement kiln, 

power plants, other OC, 

ammonium bisulfate 

PM variables used:

Mass contribution or 

score of sources, and 

tracers 

Reference: Sarnat et al. 

(2008, 097972) 

Location: 1monitor in 

Atlanta. GA for 2 yr 

Particle Size: PM2.5

Results: Sulfate secondary associated with 1.2-2.0% increase in RD visits, significant negative association RD visits and 

primary emissions from coal-fired power plants. CVD significantly associated with other OC (1.014), biomass (1.033), diesel 

and gas for CMB-LGO. For PMF and CVD visits: diesel (1.025), gas, wood smoke, metal processing (1.013). Year-long 

associations: PMF diesel, EC, CMB-LGO gas, Zn and biomass combustion sources (CMB-LGO biomass burning, PMF wood 

smoke, and K). Diesel and gas sources association with RD in the warm season (1.2-2.1% per IQR). 

Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 11 

elements, TC, 

NO3

Grouping 

method:

Comparison of: 

PMF, UNMIX, 

Multilinear Engine 

# of groups: 8 

Groups/ Factors/ Sources:

Vegetative burning; As-rich 

Vehicle; SO4; NO3; Soil; 

Cu-rich; Marine 

PM variables used:

Tracers: TC 

(vegetative burning); 

As (As-rich); Zn 

(vehicle); Si (soil) 

Reference: Schreuder et 

al. (2006, 097959) 

Location: 1monitor in 

Spokane, WA for 7 yr 

Particle Size: PM2.5

Results: Si, As, and Zn were not associated with any health outcomes; while an IQR increase in TC (vegetative burning) was 

associated with a 2% increase in respiratory ED visits. 

December 2009 F-4 
Subjects: NR 

Exposure: NR 

N: NR Number of 

Constituents 

considered for 

grouping: 8 

metals, IPM, 

FPM, SO4, CX, 

DCM, ACE, CO 

Grouping 

method:

Unspecified type of 

factor analysis 

# of groups: 5 

Groups/ Factors/ Sources:

Oil burning, motor 

emissions, resuspended 

dust, secondary aerosol, 

industrial sources 

PM variables used:

individual constituents, 

then factor scores, 

then tracers 

Reference: Tsai et al. 

(2000, 006251) 

Location: 3 NJ sites for 2 

summers (ATEOS study) 

Particle Size: NR 

Results: RR associated with 10 μg/m3 increases: Newark - 1.03 for industrial and total daily deaths; 1.02 for sulfate and total 

daily deaths; 1.04 for sulfate and cardiopulmonary deaths. Camden - 1.11 for oil burning sources and total daily deaths; 1.10 

industrial and total daily deaths; 1.12 for oil burning sources and cardiopulmonary daily deaths; 1.02 for sulfate and 

cardiopulmonary daily deaths 

Subjects: Adult 

males 

Exposure: CAD 

n: 56, data 

collected 12 

times over 6 

mo for every 

subject, but 

extended 

period of 

missing PM 

data 

Number of 

Constituents 

considered for 

grouping:

Apportionment 

based on particle 

size distribution. 

Grouping 

method: PMF 

# of groups: 5 

Groups/ Factors/ Sources:

Airborne soil, local traffic, 

local fuel combustion, 

remote traffic (diesel), 

secondary aerosols 

PM variables used:

Mass contribution or 

score of sources 

Reference: Yue et al. 

(2007, 097968) 

Location: 1monitor in 

German city, 30.000 

samples 

Particle Size: UF/PM2.5

Results: Overall, repolarization parameters influenced by traffic-related particles; vWF increased in response to traffic-related 

particles and combustion-generated aerosols. All source factors contributed to increasing CRP levels. 

December 2009 F-5 
Table F-2. Human clinical studies of ambient PM sources, factors, or constituents 

Subjects: Adult 

18-45, healthy vs. 

asthmatic 

Exposure: CAPs, 

healthy and 

asthmatic subjects 

exposed at different 

times 

N: 12 healthy, 12 

asthmatic 

Constituents 

considered for 

grouping: 7 

elements, EC, NO3, 

SO4

Grouping method:

PCA 

# of groups: 4 

(note: OC data was 

unavailable) 

Groups/ Factors/ 

Sources: Crustal (Al 

Si CA K Fe),S (2 

metrics of SO4 + 

elemental S), Total 

Mass+NO3, EC 

PM variables used:

Total mass, then 

tracers: SO4, EC, Fe

Study: Gong et al. 

(2003, 042106) 

Location: Los 

Angeles, CA 

Particle Size: PM2.5

Results: Fe and EC associated with a decrease in ST-segment voltage 2 days post-exposure. EC associated with an increase in 

ST-segment voltage immediately following exposure. Sulfate content associated with a decrease in systolic BP 4 h post-exposure.

Subjects: Elderly, 

COPD vs. healthy/ 

CAPs 

Exposure: NO2 (full 

factorial) 

N: 6 healthy, 18 

COPD 

Constituents 

considered for 

grouping: 7 

elements 

+ EC 

Grouping method:

PCA 

# of groups: 3 

(note: OC was 

unavailable) 

Groups/ Factors/ 

Sources: Crustal (Al 

Si CA K Fe), 

S (= SO4),Na 

PM variables used:

Total mass, then 

tracers:, SO4, Si, Fe, 

EC 

Study: Gong et al. 

(2005, 087921) 

Location: Los 

Angeles, CA 

Particle Size: PM2.5

Results: Mass concentration of CAPs not observed to significantly affect lung function. However, sulfate content was associated with 

a decrease lung function (FEV1 and FVC), which was enhanced by coexposure to NO2. 

Subjects: Healthy 

adults 

Exposure: CAPs 

N: 35 male; 2 female Constituents 

considered for 

grouping: 8 

elements and SO4

Grouping method:

PCA 

# of groups: 2 

Groups/ Factors/ 

Sources:

Fe/SO4/Se/V/Zn/Cu 

PM variables used:

Factor scores, then 

mass contribution of 

all 9 constituents 

Reference: Huang 

et al. (2003, 

087377) 

Location: Chapel 

Hill, NC 

Particle Size: PM2.5 Results: Associations observed between sulfate,Zn, and Se content and increases in BAL neutrophils. Increases in fibrinogen 

associated with Cu, Zn, and V content. 

Subjects: Healthy 

adults 

19-50 yr/CAPs 

Exposure: O3

N: 23 Constituents 

considered for 

grouping: unknown 

Grouping method:

No grouping was 

performed 

# of groups: NA 

Groups/ Factors/ 

Sources: NR 

PM variables used:

Every constituent in 

univariate analysis, 

then OC and SO4 in 

multivariate analysis 

Reference: Urch et 

al. (2004, 055629) 

Location: Toronto, 

Canada 

Particle Size: PM2.5

Results: CAPs-induced increase in diastolic BP significantly associated with carbon content of the particles. 

Subjects: Healthy 

adults/CAPs 

Exposure: O3

N: 24 Constituents 

considered for 

grouping: 14 

elements, EC, OC 

Grouping method:

No grouping was 

performed 

# of groups: NA 

Groups/ Factors/ 

Sources: NR 

PM variables used:

Every constituent in 

univariate analysis, 

then OC and SO4 in 

multivariate analysis 

Reference: Urch et 

al. (2004, 055629) 

Location: Toronto, 

Canada 

Particle Size: PM2.5 Results: Both organic and EC content of CAPs associated with an increase in brachial artery vasoconstriction. 

December 2009 F-6 
Table F-3. Toxicological studies of ambient PM sources, factors, or constituents 

Subjects: Rats 

Exposure: CAPs 

(3-day mean CAPs 

concentration range: 

126.1-481.0 μg/m3) 

CAPs (3-day mean 

CAPs concentration 

range: 

126.1-481.0 μg/m3) 

N: 7-10 rats × 

2 levels CAPs 

× 2 levels SO2

× 6 runs in 

different 

seasons 

Constituents 

considered for 

grouping: 20 

elements; OC; EC 

Grouping 

method:

Previous study 

in same city 

(Clarke et al., 

2000, 013252) 

and PCA of this 

experiment’s 

data 

# of groups: 4 

Groups/ Factors/ Sources: V/Ni, 

S, Al/Si, Br/Pb 

PM variables 

used: 4 tracers (Si, 

SO4, V, Pb) and 

EC, OC in 

univariate step. 4 

tracers (Si, SO4, V, 

Pb) in multivariate 

step 

Reference:

Batalha et al. 

(2002, 088109) 

Location:

Boston, MA 

Particle Size:

PM2.5

Results: Univariate analyses for first day not significant for L/W ratio. Univariate analyses for second and third day and second+third day 

mean were similar. Presented second+third day mean regression data. CAPs mass, Si, Pb, SO4, EC, OC significant for decreased L/W 

ratio in normal+CB rats exposed to CAPs. Si, SO4 significant for decreased L/W ratio in normal rats. Si, OC significant for decreased L/W 

ratio in CB rats. Multivariate analysis using normal+CB rats for Si, SO4, V, Pb - only Si remained significant with decreased L/W ratio. 

Subjects: Normal 

human bronchial 

epithelial and human 

AM 

Exposure: (2-3X105 

cells/mL; 11 or 50 

μg/mL) 

N: NR Constituents 

considered for 

grouping: 12 

elements 

Grouping 

method: PCA 

# of groups: 2 

Groups/ Factors/ Sources:

Cr/Al/Si/Ti/Fe/Cu (“crustal”), 

Zn/As/V/Ni/Pb/ 

Se 

PM variables 

used: NR 

Reference:

Becker et al. 

(2005, 088590) 

Location:

Chapel Hill, NC; 

repeated 

sampling for 1 yr 

Particle Size:

PM10

Results: Cr/Al/Si/Ti/Fe/Cu associated with IL-8 release in normal human bronchial epithelial cells and IL-6 release in AM. 

Zn/As/V/Ni/Pb/Se not associated with any endpoints. Stepwise linear regression with individual constituents Fe and Si associated with 

IL-6 release in AM. Cr associated with IL-8 release in NHBE cells. 

Subjects: Dogs 

Exposure: CAPs (avg 

for all studies, paired: 

203.4, crossover: 

360.8 μg/m3) repeated 

exposure with several 

weeks in between 

N: 10 dogs, 20 

paired 

exposures, 24 

crossover 

Constituents 

considered for 

grouping: 19 

elements, black C 

Grouping 

method: PCA 

# of groups: 4 

for exposure in 

paired runs,6 for 

exposure in 

crossover runs 

Groups/ Factors/ Sources: V/Ni, 

S, Al/Si, Br/Pb, S, Na/Cl, Cr 

PM variables 

used: All elements, 

then factor scores 

Reference:

Clarke et al. 

(2000, 013252) 

Location:

Boston, MA 

Particle Size:

PM2.5

Results: No significant differences between baseline, sham, or CAPs group for BAL cell differential percentages. Total BAL protein 

increased with CAPs compared to sham. No significant hematological effects with CAPs exposure. Mixed linear regression analyses

(statistics not provided): Al and Ti (3-day avg. concentrations) associated with dose-dependent decreases in BAL AM and increases in 

BAL PMN percentages. Sulfate associated with increased WBC. BC, Al, Mn, Si, Zn, Ti, V, Fe, Ni associated with increased blood PMN. 

Na associated with increased blood lymphocytes. Al, Mn, Si associated with decreased blood lymphocytes. CAPs mass and BC 

associated with decreased blood eosinophils. CAPs mass associated with decreased platelet count. Regression using results of factor 

analysis: None for 3-day avg. concentration for BAL parameters. V/Ni for increased AM percentage and Br/Pb for increased PMN 

percentage for 3rd-day only concentration. V/Ni and Al/Si for increased blood PMN percentage and decreased blood lymphocyte 

percentage. Al/Si also for increased WBC counts. Na/Cl for increased blood lymphocyte percentage. S for decreased RBC and 

hemoglobin. 

Subjects Primary 

human airway 

epithelial cells 

(100,000 cells/mL; 

dose not provided) 

Exposure: NR 

N: NR Constituents 

considered for 

grouping: NR 

Grouping 

method: CMB, 

but not on 

coarse and 

ultrafine 

# of groups: 6 

or 7 

Groups/ Factors/ Sources:

Mobile, residual, oil, wood, soil, 

secondary SO4, secondary NO3

PM variables 

used: Mass 

contribution of 

constituents, then 

mass contribution 

of sources 

Reference:

Duvall et al. 

(2008, 097969) 

Location: 5 US 

cities 

Particle Size:

PM2.5

Results: Linear regression with individual constituents: Sulfate associated with increased IL-8 mRNA expression. Sr associated with 

increased COX-2 and decreased HO-1 mRNA expressions. K associated with decreased HO-1 mRNA expression. 

Linear regression with sources: Significance levels not provided. 

December 2009 F-7 
 

Subjects: Rats 

Exposure: CAPs 

(3-day mean CAPs 

concentration range: 

126.1-481.0 μg/m3) 

N: 7-10 rats × 

2 levels CAPs 

× 2 levels SO2

× 6 runs in 

different 

seasons 

Constituents 

considered for 

grouping: 20 

elements, OC, EC 

Grouping 

method:

Previous study 

in same city 

(Clarke et al.), 

and PCA of this 

experiment’s 

data 

# of groups: 4 

Groups/ Factors/ Sources: V/Ni, 

S, Al/Si/Ca, Br/Pb 

PM variables 

used: 4 tracers (I, 

SO4,V, Pb) and EC, 

OC 

Reference:

Godleski et al. 

(2002, 156478) 

Location:

Boston, MA 

Particle Size:

NR 

Results: Increased percent of PMNs in BALF in CAPs-exposed rats at 24 h. CAPs affected lung tissue mRNA involved in 

pro-inflammation, immune, and vascular endothelial responses. Linear regression: Increased PMN associated with CAPs mass, Br, Pb, 

SO4, EC, and OC. 

Subjects Rats 

(Sprague Dawley) 

Exposure: CAPs (avg. 

mass concentration 

600 μg/m3); also 

carbon black and 

ROFA 

N: 13 

experiments 

(1 rat/group at 

each time 

point) 

Constituents 

considered for 

grouping: 20 

elements 

Grouping 

method: No 

grouping was 

performed 

# of groups: NA

Groups/ Factors/ Sources: NR PM variables 

used: Mass 

contribution of 

every constituent 

Reference:

Gurgueira et al. 

(2002, 036535) 

Location:

Boston, MA 

Particle Size:

PM2.5

Results: Increased oxidative stress in heart and lungs following CAPs exposure (and ROFA exposure). 

Univariate regression: Mn, Zn, Fe, Cu, and Ca most significant responses for lung (r2

>0.40). Al, Si, Ti, Fe, and total mass most significant 

response for heart (r2

>0.49). 

Subjects Rats (SH and 

WKY) 

Exposure: CAPs 

(144-2758 μg/m3) 

N: 6 1-day , 

1-strain runs, 

7 2-day, 

2-strain runs, 

4-9 rats per 

run. 

Constituents 

considered for 

grouping: NR 

Grouping 

method: No 

grouping was 

performed 

# of groups: NA

Groups/ Factors/ Sources: NR PM variables 

used: Mass 

contribution of 

every constituent 

Reference:

Kodavanti et al. 

(2005, 087946) 

Location: RTP, 

NC 

Particle Size:

PM2.5

Results: No significant correlations between biologic responses and exposure variables (i.e., CAP mass, OC, inorganic C, sulfate, and 

other major elemental constituents). Al, Cu, Zn correlated with biologic responses when constituents normalized per unit mass of CAP 

(μg/mg). Zn correlated with plasma fibrinogen in SH rats (p = 0.0023). 

Subjects: Mice (C57 

and ApoE) 

Exposure: CAPs (avg. 

mass concentration 

113 μg/m3

) 

N: C57: 3-6 

mice/group 

ApoE-/-: 9-10 

mice/group 

Constituents 

considered for 

grouping: 19 

elements + OC, EC, 

NO3

Grouping 

method:

(Absolute) PCA 

# of groups: 4 

Groups/ Factors/ Sources:

Regional SO4 (S/Si/OC); 

Resuspended soil 

(CA/Fe/Al/Si);RO power plants 

(V/Ni/Se); 

traffic and unknown 

PM variables 

used: Mass 

contribution of 

sources 

Reference:

Lippmann et al. 

(2005, 087453) 

Location: Rural 

location upwind 

from New York 

City 

Particle Size:

PM2.5

Results: ApoE null mice: Resuspended soil associated with decreased HR during exposure, but increased HR after exposure. 

Secondary sulfate associated with decreased HR after exposure. Residual oil associated with increased RMSSD and SDNN in afternoon 

following exposure. Secondary sulfate associated with decreased RMSSD and SDNN in night following exposure. Resuspended soil 

associated with increased RMSSD at night following exposure. PM mass associated with decreased HR during exposure and decreased

RMSSD at night following exposure. 

C57 mice: Motor vehicle/other source category associated with decrease in RMSSD in afternoon following exposure 

Subjects: Mice 

(ApoE-/-) 

Exposure: CAPs (avg. 

mass concentration 

85.6 μg/m3

) 

N: 12 ApoE-/-

mice (6/group)

Number of 

Constituents 

considered for 

grouping: NR 

Grouping 

method: No 

grouping was 

performed 

# of groups: NR

Groups/ Factors/ Sources: NR PM variables 

used: Mass 

contribution of 

every constituent in 

CAPs portion of 

study, contribution 

of 16 constituents 

in epi portion 

Reference:

Lippmann et al. 

(2006, 091165) 

Location: Rural 

location upwind 

from New York 

City 

Particle Size:

PM2.5

Results: Lag for HR elevations on 14 days with wind from NW was same day. Lag for SDNN reduction on 14 days with wind from NW 

was 0, 1 and 2. 

GAM analysis: Β coefficient significant for Ni and HR (but not V, Cr, or Fe). Β coefficient significant for Ni and log SDNN (but not V, Cr, or 

Fe). 

December 2009 F-8 
 

Subjects: NR 

Exposure: CAPs 

(90,000/well; 300 

μg/mL) 

N: 110 

samples 

Constituents 

considered for 

grouping: 19 

elements + OC, EC, 

NO3

Grouping 

method:

(Absolute) PCA 

# of groups: 4 

Groups/ Factors/ Sources:

Regional SO4

soil; unknown 

oil combustion 

PM variables 

used: Mass 

contribution of 

sources 

Reference:

Maciejczyk and 

Chen (2005, 

087456) 

Location: Rural; 

upwind from New 

York City 

Particle Size:

PM2.5

Results: Correlation: V and Ni positively correlated with NF-κB. Oil combustion correlated the greatest with NF-κB (0.316). Significance 

not provided. Only 2% of mass contribution originates from this source. 

Subjects: Dogs 

Exposure: 

N: 8 dogs, 24 

exposure-days 

in 1997-98; 4 

dogs, 21 

exposure-days 

in 2001-2002 

Constituents 

considered for 

grouping: 13 

elements, BC, EC, 

OC 

Grouping 

method:

Compared 3 

factor-analytic 

models within a 

SEM model 

# of groups: 4 

Groups/ Factors/ Sources: Oil 

Combustion V/Ni; power plants 

S ;road dust Al/Si ;motor vehicles 

BC/OC/EC 

PM variables 

used: Mass 

contribution of 

every constituent 

Reference:

Nikolov et al. 

(2008, 156808) 

Location:

Boston, MA 

Particle Size:

NR 

Results: Univariate response for respiratory outcomes: road dust and oil combustion associated with decreased respiratory frequency; 

motor vehicles associated with increased respiratory frequency; motor vehicles associated with increased PEF; road dust associated 

with decreased penh and motor vehicles associated with increased penh. 

Multivariate responses for respiratory outcome: Road dust associated with decreased respiratory rate; Motor vehicles associated 

with increased airway irritation. 

Subjects: Rats 

(Sprague-Dawley) 

Exposure: CAPs (avg. 

mass concentration 

range 150-2520 

μg/m3) acetylcysteine 

full factorial 

N: 4-8 rats 

(1-2 per group 

- sham, CAPs, 

sham/NAC, 

CAP/NAC) 

10 exposures 

Constituents 

considered for 

grouping: 20 

elements 

Grouping 

method: No 

grouping was 

performed 

# of groups: NA

Groups/ Factors/ Sources: NR PM variables 

used: Mass 

contribution of 

every constituent 

Reference:

Rhoden et al. 

(2004, 087969) 

Location:

Boston, MA 

Particle Size:

PM2.5

Results: Increased oxidative stress and inflammation in lungs of CAPs animals that was attenuated with NAC. 

Univariate regression: Al, Si, Fe, K, Pb, and Cu most significantly correlated with lung TBARS. No significant correlations for lung 

carbonyls or lung PMN. 

Subjects: Rats 

(Sprague-Dawley 

Exposure: CAPs 

(3-day avg. mass 

concentration range 

126.1-481 μg/m3) 

N: 7-10 

rats/group 

(air/sham, 

SO2/sham, 

air/CAP, 

SO2/CAP) × 6 

runs in 

different 

seasons 

Constituents 

considered for 

grouping: 15 

elements (used 

Clarke 2000 to 

select tracers) 

Grouping 

method:

Previous study 

in same city 

(Clarke et al. 

2000) 

# of groups: 6 

Groups/ Factors/ Sources: V/Ni 

S 

Al/Si 

Br/Pb 

______ 

Na/Cl 

Cr 

PM variables 

used: Mass 

contribution of 8 

elements in 

univariate step. 

Tracers (Si, SO4, V, 

Pb, Br, Cl) and EC, 

OC in multivariate 

step. 

Reference:

Saldiva et al. 

(2002, 025988) 

Location:

Boston, MA 

Particle Size:

PM2.5

Results: Increased percent and number of PMN in majority of air and SO2 rats exposed to CAPs, but significance levels not provided. 

Other responses (protein, LDH, NAG) were variable and depended upon the CAPs exposure. No CAPs effect on histopathology. 

Linear regression: V, Br, Pb, SO4, EC, OC, Si, CAP mass associated with increased PMN and lymphocytes for normal+CB rats. Only V 

not associated with PMN in normal rats. Lymphocyte response due to CB rats, but not observed for SO4 , Si, or mass in this group. Br, 

Pb, SO4, EC, OC, Si associated with increased total protein in CB rats. Cl and V associated with decreased LDH in CB rats. No BAL 

effects in normal rats exposed to CAPs. V, Br, Pb, EC, OC, and Cl associated with increased neutrophil density in lungs of normal rats. 

Subjects Rats (Fisher 

344) 

Exposure: 0.75, 1.5 

and 3 mg/rat via 

intratracheal instillation 

N: 5 rats/dose Constituents 

considered for 

grouping: NR 

Grouping 

method: CMB 

# of groups: 13 

Groups/ Factors/ Sources:

secondary NO3; secondary NH4; 

secondary SO4; coke production; 

vegetative detritus; natural gas 

combust; road dust; wood 

combust; meat cooking gasoline; 

diesel other OM; other mass 

PM variables 

used: Mass 

contribution of 

every constituent, 

then mass 

contribution of 

sources 

Reference:

Seagrave et al. 

(2006, 091291) 

Location: 4 SE 

US sites for 2 

seasons 

Particle Size:

PM2.5

Results: Potency depended upon season and site of sample collection. In general, effects were greater in the winter. 

PLS analysis: 2 major constituents identified (OC, Pb, hopanes/steranes, nitrate, As for first and major metal oxides for the second), 

gasoline most important predictor for both constituents, with diesel influencing second constituent and nitrate influencing first constituent. 

First constituent affected cytotoxic responses, second constituent affected inflammatory responses. 

December 2009 F-9 
 

Subjects: BEAS-2B 

cells (35000 cells/cm2; 

10, 20, 40, 80 μg/cm2) 

Exposure: Loose 

surface soil sweepings 

through mechanical 

tumbler and cascade 

impactor 

N: 6; 16 runs 

over 6 mo 

Constituents 

considered for 

grouping: 13 

elements, TC, 5 OC 

variables, 4 EC 

variables, 2 ions, 

EU, one ratio (Ca: 

Al), OP, CO3

Grouping 

method: PLS 

# of groups: NR

Groups/ Factors/ Sources: NR PM variables 

used: Mass 

contribution every 

constituent (?) 

Reference:

Veranth et al. 

(2006, 087479) 

Location: 8 sites 

in the western 

US 

Particle Size:

PM2.5

Results: Dose-related increase in IL-6 and decreases in cell viability for all soil types. IL-8 responses more variable and dependent upon 

soil type. Univariate correlations. Low correlations for all constituents tested with IL-6. Highest correlations for EC1 (R2

 = 0.50) and 

pyrolyzed OC (R2 = 0.46), then Ca/Al (R2 = 0.21). Carbonate carbon, EC3, and Sr correlated with IL-8 (R2 = 0.27, 0.13, and 0.25, 

respectively). EC and Ni correlated with IL-8 trend over the range of 10-80 μg/cm2 (R2 = 0.39 and 0.27, respectively). Multivariate 

redundancy analysis OC1, OC3, OC2, EC2, Br, EC1, Ni correlated with IL-8 release, decreased viability, and decreased IL-6 at low and 

high doses. Ni, EC1, and EC2 correlated with IL-6 release at the high dose, decreased IL-6 at the low dose, decreased IL-8 release, and 

decreased viability. Br was negatively associated. 

Subjects: Dogs 

Exposure: CAPs (avg. 

mass concentration 

range 161.3-957.3 

μg/m3

) repeated 

exposure with several 

weeks in between 

N: 6 dogs, 20 

exposures 

Constituents 

considered for 

grouping: 15 

elements (+EC 

OC?) (used Clarke 

et al. 2000) 

Grouping 

method:

Previous study 

in same city 

(Clarke et al. 

2000) 

# of groups: 6 

(but did not use 

all in analysis of 

health effects) 

Groups/ Factors/ Sources: V/Ni 

S 

Al/Si 

Br/Pb 

Na/Cl 

Cr 

PM variables 

used: Univariate: 

Mass 

Number 

Ni, S, Si, BC 

Multivariate: Ni, S, 

Si , BC 

Reference:

Wellenius et al. 

(2003, 055691) 

Location:

Boston, MA 

Particle Size:

PM2.5

Results: ST-segment elevation increased with CAPs. 

Univariate regression: Si and Pb associated with peak ST-segment elevation and integrated ST-segment change.CAPs mass or 

number concentration were not associated with any change. 

Multivariate regression: Si associated with peak ST-segment elevation and integrated ST-segment change. 

Subjects: Alveolar 

macrophage cell line 

(NR8383); 1 ×106 

cells/ml 

Exposure: Soluble 

components exposure 

concentration range 

from 20-200 pg of 

PM/cell 

N: 45 PM 

samples, 3 

runs 

Constituents 

considered for 

grouping: 43 + EC, 

OC 

Grouping 

method: PMF 

# of groups: 9 

Groups/Factors/ Sources:

Mobile, water soluble carbon, 

sulfate, soil, iron, Cd and Zn point 

source, Pb, pyrotechnics, 

platinum 

PM variables 

used: Mass 

contribution of 

sources 

Reference:

Zhang et al. 

(2008, 192008) 

Location: Metro 

area of Denver, 

CO/ 45 samples 

through 1 yr 

Particle Size:

2.5; filtered to 

0.22 um Results: Started with regression on 9 sources, then 3 (water-soluble carbon factor, soil dust source, iron source). Soil dust source was 

not significant. Final regression model excluded 3 days of outliers (Fe source most significant, then water-soluble carbon factor, then soil 

dust source) for ROS effects, with adjusted R2 of 0.774. Fe source likely associated with industrial source and includes high loadings of 

water-soluble Fe and Ti (not identified); water-soluble C factor derived from both secondary organic aerosol and biomass smoke (largely 

consists of polar organic compounds); soil dust source identified by water-soluble resuspended dust elements and contains Mg and Ca. 

December 2009 F-10 
Annex F References 

Andersen ZJ; Wahlin P; Raaschou-Nielsen O; Scheike T; Loft S (2007). Ambient particle source apportionment and daily 

hospital admissions among children and elderly in Copenhagen. J Expo Sci Environ Epidemiol, 17: 625-636. 

093201

Batalha JR; Saldiva P H; Clarke RW; Coull BA; Stearns RC; Lawrence J; Murthy GG; Koutrakis P; Godleski JJ (2002). 

Concentrated ambient air particles induce vasoconstriction of small pulmonary arteries in rats. Environ Health 

Perspect, 110: 1191-1197. 088109

Becker S; Mundandhara S; Devlin RB; Madden M (2005). Regulation of cytokine production in human alveolar 

macrophages and airway epithelial cells in response to ambient air pollution particles: further mechanistic studies. 

Toxicol Appl Pharmacol, 207: 269-275. 088590

Bell ML; Ebisu K; Peng RD; Dominici F (2009). Adverse health effects of particulate air pollution: modification by air 

conditioning. Epidemiology, 20: 682-686. 191007

Cakmak S; Dales RE; Vida CB (2009). Components of particulate air pollution and mortality in Chile. Int J Occup Environ 

Health, 15: 152-158. 191995

Clarke RW; Coull B; Reinisch U; Catalano P; Killingsworth CR; Koutrakis P; Kavouras I; Murthy GGK; Lawrence J; 

Lovett E; Wolfson JM; Verrier RL; Godleski JJ (2000). Inhaled concentrated ambient particles are associated with 

hematologic and bronchoalveolar lavage changes in canines. Environ Health Perspect, 108: 1179-1187. 013252

Duvall RM; Norris GA; Dailey LA; Burke JM; McGee JK; Gilmour MI; Gordon T; Devlin RB (2008). Source 

apportionment of particulate matter in the US and associations with lung inflammatory markers. Inhal Toxicol, 20: 

671-683. 097969

Franklin M; Koutrakis P; Schwartz J (2008). The role of particle composition on the association between PM2.5 and 

mortality. Epidemiology, 19: 680-689. 097426

Gent JF; Koutrakis P; Belanger K; Triche E; Holford TR; Bracken MB; Leaderer BP (2009). Symptoms and medication use 

in children with asthma and traffic-related sources of fine particle pollution. Environ Health Perspect, 117: 1168-

1174. 180399

Godleski JJ; Clarke RW; Coull BA; Saldiva PHN; Jiang NF; Lawrence J; Koutrakis P (2002). Composition of inhaled 

urban air particles determines acute pulmonary responses. Ann Occup Hyg, 46: 419-424. 156478

Gong H Jr; Linn WS; Clark KW; Anderson KR; Geller MD; Sioutas C (2005). Respiratory responses to exposures with 

fine particulates and nitrogen dioxide in the elderly with and without COPD. Inhal Toxicol, 17: 123-132. 087921

Gong H Jr; Linn WS; Sioutas C; Terrell SL; Clark KW; Anderson KR; Terrell LL (2003). Controlled exposures of healthy 

and asthmatic volunteers to concentrated ambient fine particles in Los Angeles. Inhal Toxicol, 15: 305-325. 042106

Gurgueira SA; Lawrence J; Coull B; Murthy GGK; Gonzalez-Flecha B (2002). Rapid increases in the steady-state 

concentration of reactive oxygen species in the lungs and heart after particulate air pollution inhalation. Environ 

Health Perspect, 110: 749-755. 036535

Huang Y-CT; Ghio AJ; Stonehuerner J; McGee J; Carter JD; Grambow SC; Devlin RB (2003). The role of soluble 

components in ambient fine particles-induced changes in human lungs and blood. Inhal Toxicol, 15: 327-342. 

087377

Ito K; Christensen WF; Eatough DJ; Henry RC; Kim E; Laden F; Lall R; Larson TV; Neas L; Hopke PK; Thurston GD 

(2006). PM source apportionment and health effects: 2 An investigation of intermethod variability in associations 

between source-apportioned fine particle mass and daily mortality in Washington, DC. J Expo Sci Environ 

Epidemiol, 16: 300-310. 088391

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database (Health and 

Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used by U.S. EPA in the process of 

developing science assessments such as the Integrated Science Assessments (ISA) and the Integrated Risk Information System (IRIS). 

December 2009 F-11 
Kodavanti UP; Schladweiler MC; Ledbetter AD; McGee JK; Walsh L; Gilmour PS; Highfill JW; Davies D; Pinkerton KE; 

Richards JH; Crissman K; Andrews D; Costa DL (2005). Consistent pulmonary and systemic responses from 

inhalation of fine concentrated ambient particles: roles of rat strains used and physicochemical properties. Environ 

Health Perspect, 113: 1561-1568. 087946

Laden F; Neas LM; Dockery DW; Schwartz J (2000). Association of fine particulate matter from different sources with 

daily mortality in six US cities. Environ Health Perspect, 108: 941-947. 012102

Lanki T; De Hartog JJ; Heinrich J; Hoek G; Janssen NAH; Peters A; Stolzel M; Timonen KL; Vallius M; Vanninen E; 

Pekkanen J (2006). Can we identify sources of fine particles responsible for exercise-induced ischemia on days 

with elevated air pollution? The ULTRA study. Environ Health Perspect, 114: 655-660. 088412

Lippmann M; Hwang J; Maclejczyk P; Chen L (2005). PM source apportionment for short-term cardiac function changes 

in ApoE-/- mice. Environ Health Perspect, 113: 1575-1579. 087453

Lippmann M; Ito K; Hwang JS; Maciejczyk P; Chen LC (2006). Cardiovascular effects of nickel in ambient air. Environ 

Health Perspect, 114: 1662-1669. 091165

Maciejczyk P; Chen LC (2005). Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice: VIII 

source-related daily variations in in vitro responses to CAPs. Inhal Toxicol, 17: 243-253. 087456

Mar TF; Ito K; Koenig JQ; Larson TV; Eatough DJ; Henry RC; Kim E; Laden F; Lall R; Neas L; Stolzel M; Paatero P; 

Hopke PK; Thurston GD (2006). PM source apportionment and health effects: 3 Investigation of inter-method 

variations in associations between estimated source contributions of PM25 and daily mortality in Phoenix, AZ. J 

Expo Sci Environ Epidemiol, 16: 311-320. 086143

Mar TF; Norris GA; Koenig JQ; Larson TV (2000). Associations between air pollution and mortality in Phoenix, 1995-

1997. Environ Health Perspect, 108: 347-353. 001760

Nikolov MC; Coull BA; Catalano PJ; Diaz E; Godleski JJ (2008). Statistical methods to evaluate health effects associated 

with major sources of air pollution: a case-study of breathing patterns during exposure to concentrated Boston air 

particles. J Roy Stat Soc C Appl Stat, 57: 357-378. 156808

Ostro B; Feng W-Y; Broadwin R; Green S; Lipsett M (2007). The effects of components of fine particulate air pollution on 

mortality in California: results from CALFINE. Environ Health Perspect, 115: 13-19. 091354

Ostro B; Roth L; Malig B; Marty M (2009). The effects of fine particle components on respiratory hospital admissions in 

children. Environ Health Perspect, 117: 475–480. 191971

Peng R; Bell M; Geyh A; McDermott A; Zeger S; Samet J; Dominici F (2009). Emergency admissions for cardiovascular 

and respiratory diseases and the chemical composition of fine particle air pollution. Environ Health Perspect, 117: 

957-963. 191998

Penttinen P; Vallius M; Tiittanen P; Ruuskanen J; Pekkanen J (2006). Source-specific fine particles in urban air and 

respiratory function among adult asthmatics. Inhal Toxicol, 18: 191-198. 087988

Rhoden CR; Lawrence J; Godleski JJ; Gonzalez-Flecha B (2004). N-acetylcysteine prevents lung inflammation after shortterm inhalation exposure to concentrated ambient particles. Toxicol Sci, 79: 296-303. 087969

Riediker M; Devlin RB; Griggs TR; Herbst MC; Bromberg PA; Williams RW; Cascio WE (2004). Cardiovascular effects in 

patrol officers are associated with fine particulate matter from brake wear and engine emissions. Part Fibre Toxicol, 

1: 2. 091261

Saldiva PHN; Clarke RW; Coull BA; Stearns RC; Lawrence J; Krishna-Murthy GG; Diaz E; Koutrakis P; Suh H; Tsuda A; 

Godleski JJ (2002). Lung inflammation induced by concentrated ambient air particles is related to particle 

composition. Am J Respir Crit Care Med, 165: 1610-1617. 025988

Sarnat JA; Marmur A; Klein M; Kim E; Russell AG; Sarnat SE; Mulholland JA; Hopke PK; Tolbert PE (2008). Fine 

particle sources and cardiorespiratory morbidity: An application of chemical mass balance and factor analytical 

source-apportionment methods. Environ Health Perspect, 116: 459-466. 097972

Schreuder AB; Larson TV; Sheppard L; Claiborn CS (2006). Ambient woodsmoke and associated respiratory emergency 

department visits in Spokane, Washington. Int J Occup Environ Health, 12: 147-153. 097959

Schwartz J (2003). Daily deaths associated with air pollution in six US cities and short-term mortality displacement in 

Boston. 042811

December 2009 F-12 
December 2009 F-13 

Seagrave JC; McDonald JD; Bedrick E; Edgerton ES; Gigliotti AP; Jansen JJ; Ke L; Naeher LP; Seilkop SK; Zheng M; 

Mauderley JL (2006). Lung toxicity of ambient particulate matter from southeastern US sites with different 

contributing sources: relationships between composition and effects. Environ Health Perspect, 114: 1387-93. 

091291

Tsai FC; Apte MG; Daisey JM (2000). An exploratory analysis of the relationship between mortality and the chemical 

composition of airborne particulate matter. Inhal Toxicol, 12: 121-135. 006251

Urch B; Brook JR; Wasserstein D; Brook RD; Rajagopalan S; Corey P; Silverman F (2004). Relative contributions of 

PM2.5 chemical constituents to acute arterial vasoconstriction in humans. Inhal Toxicol, 16: 345-352. 055629

Veranth JM; Moss TA; Chow JC; Labban R; Nichols WK; Walton JC; Walton JG; Yost GS (2006). Correlation of in vitro 

cytokine responses with the chemical composition of soil-derived particulate matter. Environ Health Perspect, 114: 

341-349. 087479

Wellenius GA; Coull BA; Godleski JJ; Koutrakis P; Okabe K; Savage ST (2003). Inhalation of concentrated ambient air 

particles exacerbates myocardial ischemia in conscious dogs. Environ Health Perspect, 111: 402-408. 055691

Yue W; Schneider A; Stolzel M; Ruckerl R; Cyrys J; Pan X; Zareba W; Koenig W; Wichmann HE; Peters A (2007). 

Ambient source-specific particles are associated with prolonged repolarization and increased levels of inflammation 

in male coronary artery disease patients. Mutat Res Fund Mol Mech Mutagen, 621: 50-60. 097968

Zhang Y; Schauer JJ; Shafer MM; Hannigan MP; Dutton SJ (2008). Source apportionment of in vitro reactive oxygen 

species bioassay activity from atmospheric particulate matter. Environ Sci Technol, 42: 7502-7509. 192008