indoor environmental quality and health michael apte indoor environment department philipsvisit...
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Indoor Environmental Quality and Health
Michael ApteIndoor Environment Department
PhilipsVisitApril 2 2007
Indoor Environment Department Mission
• Excellent R&D leading to better understood and reduced pollutant exposures and associated health effects– While maintaining or reducing energy use– With emphasis on the Indoor Environment
Indoors86%
Vehicles6%
Outdoors8%
Why Indoor Environments Are Important
People indoors 90% of timePollutant exposures increase
1000 fold with indoor releaseFor many pollutants, indoor
concentration >> outdoor conc. Very large population affected
frequently by indoor exposuresLarge potential economic
benefits of improved Indoor Environmental Quality (IEQ)
IEQ control has implications for energy consumption
Indoor Environment DepartmentResearch Domain
Energy useEnergy use
ExposuresExposuresHealth effectsHealth effects
Building Design and Operation
Building Design and Operation
ProductivityProductivityOutdoor Air QualityOutdoor Air Quality
Effectiveness of
Control Measures
Effectiveness of
Control Measures
Building Science and Engineering
Physics and Chemistry
Fluid dynamics
Building Science and Engineering
Physics and Chemistry
Fluid dynamics
Pollutant Sources
Pollutant Sources
Research Products: Technologies, Models, Measurement methods, Guidelines, Standards, Information
Research Products: Technologies, Models, Measurement methods, Guidelines, Standards, Information
CostsCostsActivitiesActivities
ConcentrationsConcentrations
ClimateClimate
Statistics
Exposure and risk assessment
Epidemiology
Computing
Statistics
Exposure and risk assessment
Epidemiology
Computing
Research Methods• Laboratory experiments
• Field studies in real buildings– Pollutant source characterization
– Air and pollutant transport measurements
– Exposure characterization
– Evaluate IAQ control measures
– Health and productivity assessments
• Multivariate statistical analyses of data
• Air and pollutant transport modeling
• Modeling of exposures
• Critical reviews
• Input for standards
Recent Research Highlights
Air freshener
Product use in the presence of ozone
Pine oil -based cleaner
Orange oil -based cleaner
Indoor Air Chemistry: Cleaning Agents, Ozone and Toxic Air Contaminants
Motivation • Potential for substantial toxic emissions from cleaning products and
air fresheners, and for reactions of primary emissions with ozone• Poor understanding of primary emissions and reactionsApproach • Measurement of primary VOC emissions plus bench and room-scale
studies of ozone reactive chemistry
Key results • 2-butoxyethanol exposure
may approach or exceed California’s reference level
• Terpenes + ozone can yield high levels of formaldehyde and ultrafine aerosol particles
Significance• Implications for product
selection and formulation
Indoor Particle Tracking & Resuspension
MOTIVATION
• Tracking & resuspension affect exposures.
• Magnitudes not quantified and physical processes not understood.
TRACKING BY FOOT TRAFFIC
RECENT PROGRESS
• Measured size-resolved particle tracking by foot steps for several surfaces and stepping sequences.
• Measured, in real time, size-resolved particle resuspension from clothing for different clothing material and activities.
KEY FINDINGS
• Shoe-to-floor and floor-to-shoe mass transfer is 2-25% for a single step.
• Shoe-to-floor and floor-to-shoe mass transfer decreases with multiple steps.
• 4-11% of particle mass on clothing was resuspended during 30 minutes of walking in place.
Step number on clean floor
0 2 4 6 8 10 12
Fra
cti
on
tra
nsf
erre
d f
rom
sh
oe
To
cle
an f
loo
r in
a s
ing
le s
tep
0.00
0.05
0.10
0.15
0.20
Cu
mu
lative fraction
tran
sferred
0.00
0.15
0.30
0.45
0.60
Single-step fraction transferred
Cumulative fraction transferred
MOTIVATION
• What types of sensors should be used to detect and locate an unknown indoor release? Where should they be placed?
• Needed algorithm to “fuse” multiple streams of data from disparate sensors, in real time, for event reconstruction.
Optimal Sensor Networks for Rapid Response to Toxic Pollutant Releases in Buildings
RECENT PROGRESS
• Bayesian probabilistic algorithm that updates model predictions rapidly, using any type of sensor data.
• In FY06, (1) developed statistics to interpret data from threshold-type sensors; (2) tested algorithm against data from a real building; (3) evaluated performance of monitoring networks for a variety of sensor performance characteristics.
Three-Floor Building
0
2
4
6
20 60 120 180
Sensor Cycle Time (sec)T
ime
to
loca
te s
ou
rce
(m
in)
Sensor detection limit = 20 mg/m3
SIGNIFICANT RESULTS
• To locate source, sensor cycle (reset) time is often more critical than sensor detection limit.
• Slower but more accurate sensors are often better than faster but less accurate sensors.
Indoor Residential Chemical Emissions as Risk Factors for Children’s Respiratory Health
• Motivation– Unexplained increase in asthma/allergies worldwide in recent decades – Influence of indoor chemical emissions on allergies and asthma largely
unrecognized
• Approach – critical review of scientific literature
• Results – many common indoor chemicals or sources associated with large increase in respiratory or allergic effects in children, most consistently for formaldehyde, plastics
• Significance – findings provide justification for preventive actions for formaldehyde exposures, and document need to confirm the many other reported relationships with adverse health effects in children
Formaldehyde or particleboard
20– 700 % increase (12 findings)
20, 30, 30, 40, 40, 40, 40, 60, 70, 80, 100, 700 %
Plasticizers or plastics
0 – 1,170 % increase
(12 findings)0, 10, 40, 40, 50, 90, 90, 140, 190, 190, 240, 1169 %
Increased asthma-related effects in children
Impact of Temp. and Ventilation on Work Performance
Motivation• Economics drives decisions
about building design and operation
• IEQ-productivity research data not readily usable for cost-benefit assessments
Approach• Synthesize and statistically fit
research data relating objective measures of work performance with temperature and ventilation
Results• Best estimates of quantitative
relationships to aid decision making
-10
010
20
15 20 25 30 35
Temperature (oC)
reported in each study
composite weighted
90% CI of composite weighted
sample size weighted
unweighted
P p
er o C
.8.8
5.9
.95
1R
ela
tiv
e P
erfo
rman
ce
15 20 25 30 35Temperature (°C)
Measurement of Outdoor Air (OA) Flows into HVAC SystemsMotivation
• OA supply affects health & energy
• OA supply rarely measured and poorly controlled
• Measurement of OA intake rate is technically challenging
Approach• Lab & field testing of
emerging real-time OA measurement technologies
• Experiments identified causes of and cures for measurement errors
Return air damper
Return air damper
Intake louverIntake louver
Return AirReturn Air
OAOA
OA damperOA damper
Supply air
Supply air
OA Meas. System
Location
OA Meas. System
Location
Findings• 3 of 4 technologies tested can work well –
If used with proper system of louvers, dampers, P transducers
• Most accurate system measures velocities inside OA intake louver, not downstream
DeltaQ Method of Measuring Air Leakage in Residential Ducts
Motivation• 20-40% of HVAC energy is wasted through duct leaks• No practical and accurate leakage test methods existed
-1000
-500
0
500
1000
1500
-30 -20 -10 0 10 20 30
Pressure Difference, Pa
Air
Flo
w, c
fm
-80
-60
-40
-20
0
20
40
60
80
100
120
Del
taQ
Flo
w, c
fm
Air Handler OffAir Handler OnDeltaQ
Approach• Measure flow through
building envelope vs. P with and without air handler operation
• Data analyses gives leakage to outdoors
Results• New test method works.
Has been included in ASTM Test Method
Efficacy of Intermittent VentilationMotivation• Want to be able to ventilate buildings at time-varying rates for peak
power control, or to reduce exposures to outdoor pollutants
Efficacy Contours
0
1
2
3
4
5
0 0.2 0.4 0.6 0.8
Under-ventilation Fraction (-)
Nom
inal
Tur
n-ov
er, N
(air
chan
ges)
10% Efficacy
30% Efficacy
50% Efficacy
70% Efficacy
90% Efficacy
Approach• Use equivalent air pollutant
dose as metric
• simplified physical modeling
Results• Ventilation efficacy
determined as function of ventilation turn-over (N) & under-ventilation fraction
• Being incorporated into standards
))((5.0 ttACHACH lowhighloweqN
Miniature Particle Matter (PM) Monitor• Problem: PM monitors costly, bulky,
poor for population-based exposure assessment & epidemiology
• Collaboration: EETD, ED, UC BSAC• Approach: MEMs PM sensor array chip• PM collection: Thermophoresis• Mass Detection: Film Bulk Acoustic
Resonator (FBAR) array chip• Source Characterization: UV and NIR
Absorbance (not fully completed)• Status: Completed prototype,
Validated in lab and field, final report, Patented, LOD 18 g m-3
• Vision: PM sensors embedded in cell phone, GPS, high density data networksFunding: CARB
Staff:Apte, Gundel, Black
Improving Ventilation and Saving Energy In Relocatable Classrooms (RCs)
• Problem: About 600,000 RCs in U.S. -> 16M Students– HVAC noise, poor ventilation, inefficient heat pumps
– Cannot meet State and ASHRAE Standards (T24, 62.1)
• Collaboration: EETD, Bard Mfg., Geary Pacific Corp
• Approach: Specify, develop, lab & field validate, bring new HVAC product to market
– Noise: 55 dB(A) -> 35-45 dB(A)
– Efficiency improvement: Cooling +38% Heating +44%
– Ventilation: continuous @ 15 CFM/occupant (meets T24)
– Refrigerant: R410A (non CFC)
• Status: Validated in Lab and Field
Commercialized
• Specification: CHPS RC standard10
SE
ER
IHP
AC
Daily average CO2 (ppm)
North CA South CA
5000
3750
2500
1250
0
ASH
RA
E 62.1 >
Bard Quiet Climate II
Ambient Ozone and Building-Related Symptoms
• Problem: Identify cause of building related symptoms (BRS)
• Data: USEPA BASE Study from 100 Blds., ambient ozone
• Hypothesis: Ozone mediated indoor chemistry -> Toxic and irritating reaction products
• Multivariate* association (p<0.05) between ambient ozone and BRS
• Ozone mitigating HVAC strategies crucial
for remediation
0%5%
10%15%20%25%30%35%40%45%50%
Upper Respiratory Dry Eyes Neurological Headache
BRS Prevalence Reduction Potential
Max -> Median Max-> Min
Compound R C=O benzene -0.29* n ethylbenzene -0.19 n o-xylene -0.12 n d-limonene 0.11 n naphthalene 0.13 n phenol 0.26 n ethyl acetate 0.12 y formaldehyde 0.18+ y TXIB 0.19 y acetaldehyde 0.28* y texanol 1&3 0.32* y hexanal 0.38* y pentanal 0.40* y
Un
sa
tura
ted
nonanal 0.60** y n-undecane 0.11 n chloromethane 0.24* n 2-ethylhexanol 0.25 n 2-butoxyethanol 0.32* n 1-butanol 0.38* n S
atu
rate
d
ethanol 0.49+ n
*Adjusted for sex, environmental sensitivities, age,smoking status, thermal exposure, dCO2, RH, 1,2,4TMB, HDD and CDD, and season