Characterization of indoor and outdoor sub-micron particles (PM1) in Edmonton homes

AWMA CPANS Edmonton LuncheonUniversity of Alberta Faculty Club, Edmonton, AB

April 1, 2016

Md. Aynul Bari, Dr.-Ing.School of Public Health, University of Alberta           

Edmonton, AB

2

Levels of air pollution exposure measurement

(Ambient)

Street Level Backyard

(Indoor)

(Personal)

IV III II I

(Near-field outdoor)

3Background

Indoor air quality is an important determinant of health.

Several studies have been conducted across Canada (e.g., Quebec City, Windsor, Regina, Halifax etc.) in order to compare baseline data and upgrade Health Canada’s Indoor Air Quality Guidelines.

Most epidemiological studies assume outdoor air as a risk factor and are not free from bias because they ignore exposure from indoor air quality.

4Indoor Environment and Time-Activity –Mean Amounts of Time Spent in Various

Microenvironments for North American Adults

87% total time indoors69% time at home

88% total time indoors64% time at home

Leech et al. 2002. J. Exp. Anal. Environ. Epidemiol., 12, 427-432

5Emission sources of sub-micron particles

Biomass burning (wood stoves/fireplaces)

Particle diameter (µm)

0

20

40

60

80

100

Par

ticle

mas

s (%

)

<0.50.5–0.6

0.6–1.01.0–2.1

2.1–3.33.3–4.8

4.8–7.17.1–11.4

>11.4

Manually-fed chimney stovePM: 284 – 338 mg/m³

Modern pellet stove, PM: 17 mg/m³

More than 80% of emitted PM has a size fraction of < 1 µm

Bari et al., 2011. Atmospheric Environment 45, 7627-7634

Vehicle emissions

6

Objective

Characterize indoor and outdoor levels and sources of

sub-micron particles (PM1) at Edmonton homes.

7

Bari et al., 2015. Environmental Science & Technology 49, 6419–6429

8

National Pollutant Release Inventory, 2015 (http://www.ec.gc.ca/inrp-npri/)

Industrial sources reporting to Environment Canada’sNational Pollutant Release Inventory (NPRI)–

Edmonton and Surrounding Region

Google Earth (Image IBCAO © 2013 Google)

Wabamun Lake

Fort Saskatchewan

Edmonton

Lehigh cement plant

Imperial oil

SUNCOR

Industrial Heartland of Alberta

Coal combustion sources related to power generation

Generating Plants

9Methodology: Indoor/outdoor sampling

Winter: Jan–Apr (n =50) Summer: Jul – Aug (n = 50) 74 non-smoking homes

Nine consecutive 7-day sampling period per season (5-6 homes per period).

OX- Oxford

WM-Westmount

SA-Spruce Avenue

PD-Parkdale

TC-Thorncliff

GB-Gold Bar

OT-Ottewell

ST-Strathearn

FH-Falconer Heights

TT-Terwillegar Towne

TS-Terwillegar South

Homes sampled were stratified by age – residences grouped into five construction year strata.

≤ 19461946 – 1960 1961 – 1980 1981 – 2000 ≥ 2001

NAPS: National Air Pollution Surveillance

OX

TC

FH

TS

TT

PDSAWM

ST OT

GB

Winter

NAPS

2010

10

Baseline Questionnaire data:• Year of construction.• Heating and cooking systems.• Attached or detached garage.• Supplemental heating-wood stoves/fireplace.• Carpets in bed rooms and living rooms.• Nearby outdoor sources.

Daily Diary Questionnaire data:• Environmental Tobacco Smoke (ETS); burning of candles,

incense.• Window opening and air conditioner use • Any cleaning activities e.g., vacuuming, dusting, sweeping.• Car idling in the garage.• Cooking (type, duration) and use of exhaust fan.• Barbeque use.• Use of stoves to fry, grill, burn foods.

Methodology – Questionnaires

11

Seven consecutive 24 h PM sampling (PM1, PM1-2.5, M10-2.5) using Harvard coarse mode impactor (HCI)

Outdoor

Methodology – PM1 sampling and analysis

Chemical analysis

34 heavy and trace metals

Energy dispersive X-ray fluorescence (ED-XRF)

Inductively coupled plasma mass spectrometry (ICP-MS)

Indoor/outdoor sampling

Harvard coarse impactor

12Results: Data quality

Winter SummerN = 27 Indoor Outdoor Indoor Outdoor

BDL (%) BDL (%) BDL (%) BDL (%)PM1 8 4 20 10

Silver (Ag) 0 12 5 24Aluminum (Al) 19 17 13 11Arsenic (As) 3 1 0 0

Boron (B) 27 19 0 0Barium (Ba) 11 7 14 8Bismuth (Bi) 17 8 27 27Calcium (Ca) 5 4 19 27

Cadmium (Cd) 39 34 19 12Chlorine (Cl) 36 26 29 18Cobalt (Co) 19 11 41 40

Chromium (Cr) 47 66 41 47Copper (Cu) 40 50 18 19

Iron (Fe) 0 0 6 4Potassium (K) 7 1 7 4

Magnesium (Mg) 2 1 22 24Manganese (Mn) 0 0 0 0

Molybdenum (Mo) 19 7 5 3Sodium (Na) 12 17 46 50Nickel (Ni) 60 70 48 46Lead (Pb) 24 4 14 8Sulfur (S) 0 0 0 0

Antimony (Sb) 1 1 0 0Silicon (Si) 9 2 14 29

Tin (Sn) 22 61 2 58Thallium (Tl) 23 6 24 16Vanadium (V) 7 1 3 1

Zinc (Zn) 7 2 16 8

No blank correction (>50% of blanks are below detection limit (BDL).

First four 7-day sampling periods in winter were invalid and excluded.

13Results – Data quality (precision)

y = 0.997x + 0.09R² = 0.9917

0

25

50

75

100

0 25 50 75 100N

APS

2 co

ncen

trat

ion

(µg/

m3 )

NAPS1 concentration (µg/m3)

Summer (n =60)

y = 0.854x + 0.67R² = 0.8863

0

10

20

30

40

50

0 10 20 30 40 50

NA

PS2

conc

entr

atio

n (µ

g/m

3 )

NAPS1 concentration (µg/m3)

Winter (n = 33)

% difference: Median 14.7 (IQR: 6.8, 49.0)

% difference: Median 15.4 (IQR: 4.4, 38.2)

• Duplicate sampling (~10% of total sampling) at NAPS station.

14Home characteristics

Characteristics Winter (n = 26)

Summer (n = 50)

Attached home 3 (12%) 3 (6%)

Attached garage with connecting door to home 8 (32%) 17 (34%)

Detached garage 17 (65%) 32 (64%)

Air conditioning operation – 13 (26%)

Carpet in home 25 (100%) 46 (98%)

Windows open at least one day during monitoring 23 (88%) 50 (100%)Visitor smoking at home at least one day during monitoring 3 (12%) 1 (2%)Visitor smoking outside home at least one day during monitoring 8 (32%) 9 (18%)Barbeque use – 31 (62%)Anyone left cars idling at least one day during monitoring 6 (24%) 9 (18%)Electric cooking stove use 22 (88%) 41 (42%)Anyone used stove to sauté, fry or grill 23 (88%) 45 (90%)Anyone burned food at least one day during monitoring 7 (27%) 14 (28%)

15

Characterization of PM1

16Results – PM1 levels-Box Plot

0.1

1

10

100

PM1

(µg/

m3 )

Indoor(n = 173)

Indoor(n = 329)

Outdoor (n = 319)

Outdoor(n = 177)

Maximum

75th percentile

Median

25th percentile

Minimum

Winter SummerPM1 2010

17Temporal profiles of indoor and outdoor PM1

05-A

ug

25-F

eb

09-M

ar

20-M

ar

31-M

ar

09-A

pr

03-J

un

24-J

un

14-J

un

05-J

ul

16-J

ul

26-J

ul

17-A

ug

26-A

ug

0.1

1

10

100

1000

PM1

(µg/

m3 )

Outdoor Indoor2010 PM1SummerWinter

Maximum

75th percentile

Median

25th percentile

Minimum

Geometric mean

18

0

50

100

150

200

24h

conc

entr

atio

n (µ

g/m

3 )

PM1OutdoorIndoor 2010 IAQ study

Influence of wildfires smoke on indoor and outdoor air quality in Edmonton

Edmonton, August 19, 2010, 2:16 pm

Edmonton, March 12, 2010

BC wildfiresAugust 18, 2010

19Variability in indoor/outdoor (I/O) ratios by home

0.01

0.1

1

10

100

1000

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Dai

ly I/

O ra

tio

Home ID

0.01

0.1

1

10

100

1000

19 49 51 5 34 31 11 21 10 43 52 53 55 57 56 54 33 7 4 6 25 20 58 59 40 15 27 28 37 36 30 63 61 62 65 64 66 23 50 69 42 68 70 18 67 71 73 74 72

Dai

ly I/

O ra

tio

Home ID

February

Summer

March April

Winter

June March April

Median = 0.62

Median = 1.24

20Influence of particle infiltration

0.0

0.5

1.0

1.5

2.0

2.5

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 46 48 49 50

F inf

Home

0.0

0.5

1.0

1.5

2.0

2.5

4 5 6 7 10 11 15 18 19 20 21 23 25 27 28 30 31 33 34 36 37 40 42 43 49 50 51 53 55 56 58 59 61 63 65 66 67 68 69 71 72 73

F inf

Home

SummerMedian = 0.78

WinterMedian = 0.45

Infiltration factor, Finf P = particle penetration coefficienta = air exchange rate (per hour) k = particle loss rate (per hour)

Estimates of FinfTracer-based method (e.g., using sulfur ratio)

21

Source apportionment of PM1 elements

22Analytical Approach for PM1 Source

Identification/Verification

Source Identification: multivariate analysis…US EPA positive matrix factorization (PMF)

Source Verification: ‘local’ source influence…conditional probability function (CPF) plots

‘regional’ source influence…air parcel backward trajectories w/NOAA HYSPLIT[potential source contribution function (PSCF) plots]

statistical correlation w/measured air pollutants…Pearson correlations

23

Source-compositions

Source-impacts

Receptor Model(e.g., PMF, PCA, CMB)

Receptor (monitor)

Multivariate analysis: Receptor modeling

U.S. EPA Positive matrix

factorization (EPA PMF3.0).

based on analysis on correlation between measured chemical species in a number of samples (n >100).

oPCA: Principal component analysis

oPMF: Positive matrix factorization

CMB: Chemical mass balance

Edmonton IAQ study: Indoors (n = 254) Outdoors (n = 275) Pooled (n = 529) No. of elements: 27

Source Identification

24

Sources Outdoor contributions

Factor 1 Secondary sulfate 42.8%

Factor 2 Soil 18.7%

Factor 3 Biomass smoke & ETS 17.1%

Factor 4 Traffic 4.3%

Factor 5 Settled and mixed dust 3.7%

Factor 6 Coal combustion 3.6%

Factor 7 Oil and gas industry 2.4%

Factor 8 Road salt/ road dust 2.6%

Factor 9 Urban mixture 5.0%

Sources of elements in PM1 mass in Edmonton homes

Indoor contributions

43.9%

15.8%

17.8%

2.9%

3.9%

2.7%

2.1%

1.2%

2.0%

Factor 10 Carpet dust Indoor

Factor 11 Cu-factor Indoor

Factor 12 Ag-factor Indoor

4.3%

1.7%

1.6%

Outdoor model Pooled indoor/outdoor model

Source Identification

25

Con

cent

ratio

ns o

f spe

cies

app

ortio

ned

to fa

ctor

% o

f spe

cies

app

ortio

ned

to fa

ctor

PMF-derived source profile

Secondary sulfate

0

40

80

0.00010.0010.010.1

1EM

-PM

1A

g Al

As B Ba Bi

Ca

Cd Cl

Co Cr

Cu Fe K

Mg

Mn

Mo Na Ni

Pb S Sb Si Sn Tl V Zn

Indoor concentration of species Outdoor concentration of speciesindoor % of species Outdoor % of species

0

40

80

0.0001

0.001

0.01

0.1

1

EM-P

M1

Ag Al

As B Ba Bi

Ca

Cd Cl

Co Cr

Cu Fe K

Mg

Mn

Mo Na Ni

Pb S Sb Si Sn Tl V Zn

Secondary sulfate

Oil and gas industry

0

40

80

0.00010.001

0.010.1

1

EM-P

M1

Ag Al

As B Ba Bi

Ca

Cd Cl

Co Cr

Cu Fe K

Mg

Mn

Mo Na Ni

Pb S Sb Si Sn Tl V Zn

Cu-factor

Source Identification

26Performance of PMF model

y = 0.72x + 0.08R² = 0.82p = 0.03

0

0.5

1

1.5

2

2.5

0 0.5 1 1.5 2 2.5

Mod

eled

tota

l PM

1 el

emen

ts (µ

g/m

3 )

Measured total PM1 elements (µg/m3)

Indoor

y = 0.82x + 0.08R² = 0.87p = 0.04

0

0.5

1

1.5

2

2.5

0 0.5 1 1.5 2

Mod

eled

tota

l PM

1 el

emen

ts (µ

g/m

3 )

Measured total PM1 elements (µg/m3)

Outdoor

Source Identification

27

Local sources are likely to be located in the directions that have high conditional probability values.

Local source identification: Conditional probability function (CPF)

Uses hourly wind direction data along with daily averaged source contributions to identify the likely sources contributing to a given factor.

Edmonton

Wind rose

0.10.2

0.30.4

0.50.6

probability

CPF

Wind directions corresponding to the highest source contributions.

Threshold criterion: highest 25% (i.e, 75th percentile) of the contributions.

Source Verification

28

Secondary nitrate

Example of analysis for local source identificationConditional probability function (CPF)Industrial Heartland of Alberta

Oil and gas industryTraffic

Edmonton

Imperial oil

SUNCOR

Source Verification

29

Backward trajectoryNational Oceanic and Atmospheric Administration (NOAA) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT)48 to 96-hr backward trajectories

Potential Source Contribution Function (PSCF)

0.5˚ x 0.5˚ latitude and longitude

72-hr backward trajectories

Threshold criterion: 75th percentile (highest 25%) of the contributions

Example of analysis for potential long-range sourcesSource Verification

30Example of analysis for long-range sourcesBackward trajectory

Biomass smoke & ETS

Williams Lake, BCAugust 18-22, 2010

PSCF

Edmonton

BC wildfiresAugust 18, 2010

Source Verification

31Correlation (Pearson coefficient) of outdoor sourceswith other pollutants and meteorological parameters

Possible sources OC EC NO2 SO2 Benzene Toluene Acetaldehyde Temperature

Secondary sulfate 0.06 0.06 0.05 0.03 0.05 -0.08 -0.08 -0.13*

Soil -0.23* -0.18** 0.40** 0.08 0.006 -0.01 -0.19** -0.40**

Biomass smoke & ETS 0.73** 0.71** -0.26** -0.26** 0.51** 0.001 0.29** 0.58**

Traffic 0.16* 0.05 0.47** 0.01 0.40** 0.15* -0.06 -0.11

Settled and mixed dust -0.08 -0.08 -0.05 -0.06 -0.08 -0.02 -0.03 0.05

Coal combustion 0.001 0.08 0.26** -0.001 0.28** 0.05 0.07 0.05

Oil and gas industry -0.01 -0.04 0.04 0.16** -0.02 -0.02 0.06 0.08

Road salt/road dust -0.1 -0.10 0.79** 0.08 0.34** 0.08 -0.16** -0.40**

Urban mixture 0.76** 0.79** 0.28** -0.18** 0.74** 0.07 -0.09 -0.15*

**Correlation significant at p = 0.01 *correlation significant at p = 0.05

Source Verification

32Influence of particle infiltration (slopes)

y = 0.44x - 0.01R² = 0.72

y = 0.70x - 0.06R² = 0.58

0

1

2

3

4

5

0 1 2 3 4 5

Secondary sulfate

winter summer

y = 1.06x + 0.23R² = 0.05

y = 1.9x - 0.07R² = 0.63

0

5

10

15

20

25

0 5 10 15 20 25

Biomass smoke and ETS

y = 0.24x + 0.13R² = 0.79

y = 0.69x + 0.01R² = 0.79

0

5

10

15

0 5 10 15

Traffic

y = 0.40x + 0.001R² = 0.92

y = 0.45x + 0.17R² = 0.84

0

5

10

15

20

25

0 5 10 15 20 25

Oil and gas industry

Indo

or c

ontri

butio

ns (µ

g/m

3 )

Outdoor contributions (µg/m3)

33Variability in outdoor sources across different neighborhoods

(p-values, one-way Wilcoxon score)Secondary sulfate Biomass smoke & ETS

TS' WM SA' ST GB' OX TS' WM SA' ST GB' OXTC 0.53 0.27 0.13 0.93 0.93 0.25 0.07 0.38 0.98 0.29 <0.01 0.14TS' 0.64 0.06 0.15 0.30 0.12 <0.01 <0.01 0.22 <0.01 <0.01WM 0.03 0.84 0.15 0.08 0.69 0.07 0.04 0.20SA' 0.02 0.36 0.70 0.27 0.01 0.03ST 0.73 0.25 <0.01 0.06GB' 0.59 0.81

Traffic Oil and gas industryTS' WM SA' ST GB' OX TS' WM SA' ST GB' OX

TC 0.84 <0.01 <0.01 <0.01 0.99 0.91 0.48 0.56 0.12 0.59 0.40TS' 0.96 0.02 <0.01 <0.01 0.70 0.50 0.41 0.23 0.48 0.33WM <0.01 <0.01 <0.01 0.35 0.77 0.13 0.21 0.14SA' 0.34 0.42 <0.01 0.20 0.59 0.85ST 0.70 <0.01 0.30 0.35GB' <0.01 0.61

OX- Oxford

WM-Westmount

SA-Spruce Avenue

OT-Ottewell

FH-Falconer Heights

TT-Terwillegar Towne

TS-Terwillegar South

PD-Parkdale

TC-Thorncliff

GB-Gold Bar

ST-Strathearn

Significant variation, p < 0.01

34Summary

The major sources of PM1 elements (more than two-third) were made up of secondary sulfate, soil and biomass smoke & ETS.

Secondary sulfate signal is multi-component.

Other minor outdoor sources contributed to one-quarter of elemental PM1 mass. These include: traffic, mixed dust, oil and gas industry, coal combustion, road-salt, and urban mixture.

Indoor-generated sources of PM1 elements: carpet dust, Cu-rich, Ag-rich.

Larger particle infiltration was observed during summer than winter.

35SPECIAL THANKS

University of Alberta Dr. Warren Kindzierski

Alberta Innovates-Technology Transfer (AITF)

Dr. Lance Wallace, Consultant, Santa Rosa, CA, USA

Thank You for your kind attention!

Health CanadaMarie-Ève HérouxDr. Amanda A. J. Wheeler Morgan MacNeillKeith Van RyswykMélissa St-JeanTae Maen Shin

36

Questions?