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PM2.5 Concentrations in Residential Outdoor Air Near OWBs

Agnes N Mukasa1, Emily J Shusas2, Kimberly A Mazor1, Judith A Abbott

1

, Gerald J McDonald1, Kevin M Malone

1, and Stephen J Shost1

.

1 New York State Department of Health, Troy, NY; 2 New York State Energy Research & Development Authority, Albany, NY

SUMMARY RESULTS – WIND SPEED & DIRECTION

CONCLUSIONS

RESULTS – PM2.5 POLLUTION EVENTS

Although these investigations considered only six residential locations near 

OWBs, study results indicated that OWBs can significantly increase PM2.5

concentrations in outdoor air at nearby residences. The study did not 

employ regulatory air monitors, so measured PM2.5levels were not 

compared to air quality standards. None the less, the severity of adverse 

health effects associated with even short-duration elevated PM2.5air 

concentrations, along with the demonstrated importance of OWBs as 

sources of wood smoke and PM2.5in some residential settings, indicate 

that further efforts to reduce exposures to OWB-derived wood smoke and 

PM2.5are warranted.

Geometric mean (GM) 5- or 10-minute average fine particulate (PM2.5) 

concentrations were statistically significantly elevated at 5 of 6 nearfield 

monitors, located 150 to 1,270 feet distant from the nearest Outdoor 

Wood-Fired Boiler (OWB), compared with paired reference monitors 

located in the same general area -- but at least 2,500 feet distant from the 

nearest OWB (p = <0.0001 – 0.01). GM PM2.5 level increases of 15, 17, 

46, 74 and 187 percent were calculated. Relative odds of observing an 

extreme (>95th percentile) PM2.5 concentration were 1.8- to 4.3-fold higher 

at the 5 nearfield monitors, and increases were statistically significant (p = 

<0.0001 – 0.043). Calm (0 m.p.h.) winds were statistically significantly 

associated with increased relative odds of observing an extreme PM2.5

concentration difference (nearfield PM2.5 minus reference PM2.5) at four of 

the five sites. Downwind status was statistically significantly associated 

with increased relative odds of observing an extreme PM2.5 concentration 

difference at 3 of the 5 sites. In summary, residence near OWBs was 

associated with substantially increased GM PM2.5 levels and numbers of 

PM2.5 pollution events. PM2.5 pollution episodes at a residence near an 

OWB can be associated with calm periods, downwind status, or both.

OWBs (Fig. 1) can be substantial sources of wood smoke and associated 

PM2.5. A 2006 report issued by the Northeast States for Coordinated Air 

Use Management indicated that average PM2.5 emissions (grams per 

hour) from one OWB are equivalent to the emissions from 22 US EPAcertified wood stoves, 205 oil furnaces, or as many as 8,000 natural gas 

furnaces. 

During the 2007 and 2008 heating seasons, New York State Department 

of Health (NYS DOH) investigators conducted an air monitoring study to 

evaluate the potential for smoke from OWBs to increase outdoor air PM2.5

levels in residential neighborhoods. This was accomplished by 

comparing PM2.5 concentrations in air at residences near OWBs to levels 

in air at residences distant from OWBs, and then by determining if 

unusually elevated PM2.5 concentrations reported in air at residences near 

BACKGROUND

As indicated in Table 2, calm winds were common at the 5 study sites 

reporting wind speed and direction data, but 2 nearfield monitors were only 

rarely downwind of nearby OWBs. 

RESULTS – TIME CALM & DOWNWIND

Monitor 

Pair

Instrument

Pair Monitoring Period

Distance Between

Nearfield Monitor 

& OWB(s) (ft)

PM2.5 Data

Log Intervals 

(min)

OWB Status

N1/R1 DR2/DR1 02/19/08 - 03/04/08 390, 500, 580, 

1420 10 non-permitted/no complaints

N2/R2 DR1/DR2 03/12/07 - 03/26/07 260 5 permitted/no complaints

N3/R3 DR1/DR2 03/20/08 - 04/10/08 680 10 non-permitted/no 

complaints

N4/R4 DR2/DR1 03/30/07 - 04/20/07 1270 5 permitted/no complaints

N5/R5 DR1/DR2 01/07/08 - 01/28/08 350, 1180 10 permitted/no complaints

N6/R6 DR2/DR1 03/06/08 - 03/13/08 150 10 non-permitted/complaints

Table 1. Summary of air monitor deployments.

Monitor 

Pair

Time-Matched 

PM2.5

Concentrations 

(n)

Time-Matched PM2.5

Concentrations with 

Time-Matched 

Meteorological Data (n)

Percent of 

Monitoring 

Time 

Downwind

(Nearfield)

Percent of 

Monitoring 

Time Winds 

Calm 

(Nearfield)

N1/R1 1,914 1,802 13.3 % 54.3 %

N2/R2 3,373 3,344 17.7 % 20.5 %

N3/R3 2,689 2,685 1.9 % 28.3 %

N4/R4 4,004 0 -- --

N5/R5 3,001 2,687 4.1 % 33.8 %

N6/R6 970 820 28.1% 24.8%

Table 2. Summary of time-matched PM2.5 monitoring data.

Figure 3 Boxplots of time-matched PM2.5concentrations.

Monitor

Pair

Nearfield Monitor 

Geometric Mean PM2.5

Concentration (μg/m3)

Reference Monitor 

Geometric Mean 

PM2.5

Concentration 

(μg/m3)

Mean Paired 

PM2.5

Concentration 

Difference 

(μg/m3)

Student's 

p

N1/R1 11.5 9.8 4.3 0.01

N2/R2 15.8 9.1 6.6 <0.0001

N3/R3 6.6 2.3 5.4 <0.0001

N4/R4 3.2 4.4 0.2 0.59

N5/R5 9.8 8.5 2.0 <0.0001

N6/R6 13.3 9.1 5.2 <0.0001

Table 3. Comparisons of PM2.5concentrations at 

nearfield monitors and corresponding reference monitors.

Table 4. Relative odds of observing a 95th percentile or greater PM2.5

concentration (PM2.5pollution event) at each nearfield monitor compared 

with its corresponding reference monitor, with 95% confidence intervals and 

regression p-values

.

Site

95th Percentile PM2.5

Concentration 

Cutpoint (μg/m3)

Odds Ratio

95% Confidence 

Interval

logit p

NEARFIELD

1 56.3 1.9 1.1, 3.1 0.016

2 46.9 1.8 1.2, 2.6 0.004

3 15.6 4.3 2.6, 7.1 <0.0001

4 13.5 0.8 0.5, 1.2 0.22

5 26.2 1.8 1.3, 2.5 0.0001

6 37.8 2.0 1.02, 3.8 0.043

Site

CALM(2)

Odds Ratio 

(95% CI)

CALM(2)

logit

p

DOWNWIND(3) 

Odds Ratio

(95% CI)

DOWNWIND(3)

logit

p

1 21.0 (2.8, 155.4) 0.003 0.24 (0.03, 1.8) 0.17

2 2.1 (1.4, 3.1) 0.0002 1.7 (1.1, 2.6) 0.009

3 2.7 (1.7, 4.3) <0.0001 2.0 (0.7, 5.3) 0.17

5 4.5 (2.9, 7.0) <0.0001 4.0 (2.2, 7.1) <0.0001

6 0.8 (0.3, 2.1) 0.69 5.9 (2.6, 13.6) <0.0001

Table 5. Relative odds of observing a 95th percentile or greater paired 

PM2.5concentration difference at each study site that provided timematched meteorological data, with 95% confidence intervals and logistic 

regression p-values

(1)

.

Figure 2. DataRAM and Dustscan

monitors ready for deployment.

Note: The study employed only DataRAM data. 

Fig. 3 & Table 3 indicate that at five of six deployments, GM PM2.5levels 

were higher at residences near OWBs than at more distant residences. 

Table 3 indicates that the increases were statistically significant.

The possibility that local roads and homes contributed to elevated PM2.5

levels observed around study OWBs cannot be ruled out, although there is 

evidence that such contributions were negligible. Specifically, other studies 

have determined that PM2.5emissions from vehicles, and primary home 

heating systems common in rural NYS, are considerably lower than 

emissions from OWBs (Gillies et al., 2001; NESCAUM, 2006). In as much as 

OWBs are often employed as primary home heating sources, home heating 

system flues at OWB owners' residences probably emitted minimal, if any, 

PM2.5. With regard to fireplace emissions, no chimney smoke was observed 

at any OWB owner's home, nearfield monitor location, or reference monitor 

location over the course of the study, despite frequent site visits. 

METHODS (CONTD.)

Table 5 indicates that at 4 sites, calm winds were associated with 

statistically significant 2.1- to 21-fold increased relative odds of observing 

an extreme (>95

th percentile) PM2.5

difference. As expected, calm winds 

often occurred at night, so that at 4 sites the relative odds of observing an 

extreme PM2.5concentration were elevated at night (data not shown). At 

3 sites, downwind status was associated with statistically significant 1.7- to 

5.9-fold increased relative odds of observing an extreme (>95

th percentile) 

difference. 

Notes: 

(1) Odds ratios, confidence intervals and p-values were adjusted for autocorrelation.

(2) “CALM” indicates that the mean nearfield wind speed was 0 mph 

(3) “DOWNWIND” indicates that the nearfield monitor was approximately downwind 

of a nearby outdoor wood-fired boiler. 

ALTERNATIVE PM2.5 SOURCES

Table 4 indicates that at the 5 sites where nearfield GM PM2.5levels were 

statistically significantly elevated, proximity to one or more OWBs was 

associated with a statistically significant 1.8 to 4.3-fold increased relative 

odds of observing a PM2.5pollution event. 

RESULTS – PM2.5 LEVELS COMPARED 

METHODS

Figure 1. A study OWB 

in operation.

OWBs coincided with wind conditions favoring local accumulation of OWB 

smoke (e.g., calm winds), or transport of OWB smoke towards the monitors.

NYS DOH staff deployed DataRAM Model 4000 air monitors (Fig. 2) to 

record 5- or 10-minute average PM2.5 concentrations at several residential 

properties near operational OWBs. Two nearfield monitors were deployed 

within 1,500 feet of multiple OWBs (Table 1). Deployments lasted for one to 

three weeks per study site. Student’s t-test was employed to evaluate GM 

differences, and logistic regression (logit) was used to evaluate pollution 

episodes. Statistical tests adjusted for autocorrelation and employed an α of 

0.05.