1. Impact of High Efficiency Filtration Combined with High Ventilation Rates on Indoor Particle Concentrations and Energy Usage in Office Buildings
Michael Waring, PhD
Drexel University

2. Impact of High-Efficiency Filtration Combined with High Ventilation Rates on Indoor Particle Concentrations and Energy Usage in Office Buildings
NAFA Technical Seminar 2016
Phoenix, AZ
April 7, 2016
Michael S. WARING*, Tom Ben-David, Sheng Wang
*Associate Professor
Civil, Architectural and Environmental Engineering
Drexel University, Philadelphia, PA
Indoor Environment Research Group (
Drexel Air Resources Research Laboratory (DARRL)
Building Science & Engineering Group (BSEG)

3. Introduction IAQ, building energy, and ventilation
People spend 87% of time indoors
Indoor exposure to air pollutants is critical
Buildings consume ~40% of energy in the U.S.
44% more than transportation
36% more than industry
Office stock is a subsector that consumes much energy
Higher ventilation rates increase productivity and reduce absenteeism and sick building syndrome in offices
However, higher ventilation rates may introduce more PM and ozone, which have health impacts due to exposure
Filters may be an effective way to manage PM at higher ventilation
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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4. Introduction Cost and benefits of filtration
Studies estimate the cost of filtration to be $2.5~$15 /occ/year
Depending on filter type and MERV
Studies suggest that the cost of filtration outweighs its cost
E.g. Azimi & Stephens, 2013; Bekö et al., 2008; Hänninen et al., 2005; Montgomery at al., 2015; Quang et al., 2013
Significant reduction in morbidity and mortality
Monetized benefits are estimated $20~$150 /occ/year
Interplay of ventilation and filtration affects indoor air quality and building energy consumption
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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5. Research Overview NAFA funded research project
Question: Can filters protect occupants at high air exchange rates? And is this protection cost efficient?
Measurements: Measuring Impacts in Drexel Building
Vary filters (MERV 8, 14, 15) and air exchange rates (~1, 2, 3 h-1)
Sample outdoor air, supply air, and return air (6 min cycle; 2 min each)
PM2.5, ozone (O3), carbon dioxide (CO2), sometimes PM size distributions
Determine indoor/outdoor (I/O) ratios of pollutants
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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6. Results Experiments: PM2.5 I/O ratios
4 experiments: MERV 8 and 14 each at AER of 1.2 and 2.2 h-1
MERV 8
AER = 2.2 h-1
0.35 (0.089)
MERV 8
AER = 1.2 h-1
0.24 (0.04)
MERV 14
AER = 1.2 h-1
0.02 (0.03)
MERV 14
AER = 2.2 h-1
0.08 (0.18)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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7. Results Experiments: PM number I/O ratios
4 experiments: MERV 8 and 14 each at AER of 1.2 and 2.2 h-1
MERV 8
AER = 2.2 h-1
1.4 (0.58)
MERV 14
AER = 2.2 h-1
0.81 (0.44)
MERV 8
AER = 1.2 h-1
1.0 (0.33)
MERV 14
AER = 1.2 h-1
0.71 (0.31)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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8. Results Experiments: PM2.5 and PM number shown
4 experiments: MERV 8 and 14 each at AER of 1.2 and 2.2 h-1
MERV 8, 2.2 h-1
MERV 8, 1.2 h-1
MERV 14, 2.2 h-1
MERV 14, 1.2 h-1
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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9. Research Overview NAFA funded research project
Question: Can filters protect occupants at high air exchange rates? And is this protection cost efficient?
Modeling: Impact Ventilation and Filtration have on Building Energy Consumption and Monetized IAQ Exposure in U.S. Offices
Model an office in 15 cities in different climate zones across U.S.
Vary ventilation rates and filters in the modeled building
Monetize costs and assess tradeoffs (i.e., filter cost vs. IAQ protection)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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10. Methodology Modeling: Building simulations
Energy simulations using EnergyPlus
15 different cities in the contiguous U.S.
Average cost of utilities in each state (2013)
Office parameters (1,500 m2)
Ventilation at 0, 8.5, 17, 25.5 L/s/person
0, 0.38, 0.77, and 1.2 h-1
Typical construction, occupancy, power density, etc.
ASHRAE Standards 62.1, 90.1, 189.1
Constant Air Volume (CAV) system
Chiller COP = 3.2
Natural gas boiler efficiency = 0.80
Fan efficiency = 0.70; fan motor efficiency = 0.65
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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11. Methodology Modeling: Air filters
MERV 8, 10, 12, 14, 16, and HEPA filters modeled
Median efficiency reported in literature (26.0%−99.7%)
Azimi et al., 2013
Varied in pressure drop (111−374 Pa)
Pressure drop across filter was added to pressure rise by the supply air fan (600 Pa with no filter)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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12. Methodology Modeling: IAQ model Mass balance semi-transient IAQ model
Nazaroff and Cass, 1986; Rackes and Waring, 2013; Riley et al., 2012
Only pollutants of outdoor origin
Quantify the positive effect filtration has on IAQ
Assess how filtration can mitigate negative effects of ventilation
Pollutants include: Carbon monoxide (CO); Nitrogen dioxide (NO2); Ozone (O3); Fine particles (PM2.5)
Taken from EPA monitoring stations for 6 years
Differential model:
Iterative solution:
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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13. Methodology Modeling: Cost and benefits of filtration
What affects the cost and benefits of filtration?
Nominal cost
Lifespan
Installation cost
Pressure drop
Removal efficiency
Affecting filter cost (Jfilter)
Affecting energy consumption cost (JE)
Affecting IAQ exposure outcomes (JIAQ)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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14. Methodology Modeling: Cost function
Cost function includes these costs and benefits of filtration:
Total cost
Energy cost
Filter cost
Monetized IAQ exposure
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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15. Methodology Modeling: Cost function
For a particular building in a particular climate, the function depends on two variables: Ventilation and Filtration
Assess the effect of ventilation on total cost function:
Assess the effect of filtration on total cost function:
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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16. Methodology Modeling: Energy Cost (JE)
Increases in ventilation rate and pressure drop require more energy
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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17. Methodology Modeling: IAQ monetization (JIAQ)
Morbidity and mortality relating to acute and chronic effects
Exposure to CO and NO2 reported to cause acute morbific symptoms
Exposure to O3 and PM2.5 reported to cause both acute and chronic morbific and mortal symptoms
Exponential C-R function to quantify incidences due to exposure
Outcomes include mostly cardiopulmonary diseases
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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18. Methodology Modeling: IAQ monetization (JIAQ)
Quantification of mortality and morbidity
Guidelines provided by the EPA
Based on either cost of illness (COI) for most acute health effects or willingness to pay (WTP) for most chronic health effects and mortality
Outcome
Cost per incidence (2013$)
Mortality
$8,620,400
Chronic bronchitis
$462,929
Chronic asthma
$52,953
Asthma attack
$44
Minor restricted activity days
$69
Hospital admission (any reason)
$31,640
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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19. Results Modeling: Filter costs (Jfilter) The cost of the filter itself
Includes purchase, replacement, and installation
$0.5~$8.50 per person per year for MERV 8-16
Up to ~$18 per person per year for HEPA
Other studies report similar values (e.g. Azimi & Stephens, 2013)
This cost must assessed for each case among filters
Highly dependent on manufacturer and type of filter
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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20. Results Modeling: IAQ results Pollutant concentrations:
NO2 O3
Pollutant concentrations:
CO not affected by increasing ventilation
NO2 and O3 increase as ventilation rate increases
PM2.5 varies with filtration more than with ventilation
Absolute concentrations correspond to other studies CO
MERV MERV MERV 12 (#1) MERV 12 (#2) MERV MERV HEPA
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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21. Results Modeling: IAQ results Monetized results:
CO and NO2 have negligible effects, but O3 increases
Effects of PM2.5 is highly influenced by filtration
CO NO O3
MERV MERV MERV 12 (#1) MERV 12 (#2) MERV MERV HEPA
PM2.5
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22. Results Modeling: Combined energy and IAQ results
Cost difference compared to BL (0 L/s/occ + MERV 8):
Baseline: no ventilation, MERV 8
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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23. Results Modeling: Combined energy and IAQ results
IAQ effects are much more expensive than energy cost
JIAQ ≈ 5 × JE at low ηPM2.5
Filtration affects total cost function more than ventilation
PM2.5 concentration is dominant parameter
Cost difference compared to BL (0 L/s/occ + MERV 8):
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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24. Results Modeling: Empirical cost function: Energy cost
Empirical energy cost function (occupant normalized):
Energy cost (US$/occ)
Filter pressure drop (Pa)
Base energy cost (US$/occ)
Ventilation rate (l/s/occ)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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25. Results Modeling: Empirical cost function: Energy cost
Empirical energy cost function (occupant normalized):
Annual and monthly fits in each location
Mean R2 = 0.952
Mean NRMSE = 7.73%
Ventilation slope (JE,N /Qv,N)
Pressure slope (JE,N /Δpf)
Annual JE,0 = 52.2 ~ 85.4 $US/occ
Annual mv = 0.64 ~ 2.07 ($US/occ)/(l/s/occ)
Annual mf = 2.1×10−2 ~ 4.2×10−2 $US/occ/Pa
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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26. Results Modeling: Empirical cost function: Monetized IAQ
Empirical IAQ exposure cost function (occupant normalized):
IAQ cost (US$/occ)
Base IAQ cost (US$/occ)
Filter removal efficiency (−)
Ventilation rate (l/s/occ)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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27. Results Modeling: Empirical cost function: Monetized IAQ
Empirical IAQ exposure cost function (occupant normalized):
Annual and monthly fits in each location
Mean R2 = 0.987
Mean NRMSE = 4.00%
aIAQ, bIAQ, cIAQ are constant model coefficients
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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28. Results Modeling: Empirical cost function: Monetized IAQ
Empirical IAQ exposure cost function (occupant normalized):
Epidemiological uncertainty
All parameters were calculated with a confidence interval
At the mean of the function:
JIAQ,0 = 311 ~ 681 $US/occ
aIAQ = 57.5 ~ 143 ($US/occ)/(l/s/occ)1/2
bIAQ = 191 ~ 437 $US/occ
cIAQ = 46.9 ~ 94.4 ($US/occ)/(l/s/occ)1/2
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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29. Results Modeling: Effect of ventilation changes
Ventilation derivative ($/occ per L/s/occ)
A function of both ηPM2.5 and Qv
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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30. Results Modeling: Effect of ventilation changes Ventilation derivative
($/occ per L/s/occ)
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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31. Results Modeling: Effect of filtration changes J/Δpf is constant
Filtration derivative split into two:
Pressure drop derivative ($/occ per Pa):
Filter efficiency derivative ($/occ per eff):
J/Δpf is constant
Increasing pressure drop is always unfavorable
Maximum potential cost increase: ~$1.0/occ/yr
J/ΔηPM2.5 is a function of ventilation, always negative
Increasing ηPM2.5 is always favorable
Increasing ventilation will increase filtration efficacy
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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32. Results Modeling: Effect of filtration Filter efficiency derivative:
Compared with
VR = 8.5 l/s/occ,
filtration is:
~1.20 times more efficacious at 17 l/s/occ and
~1.35 times more efficacious at 25.5 l/s/occ
More favorable
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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33. Conclusions Ventilation – filtration interaction
Coupling high filter efficiency with a high ventilation rate can improve IAQ
Benefits of high efficiency filtration significantly outweigh its cost
At high filter efficiency, increasing ventilation is favorable
At high ventilation rates, filtration is more efficacious
The effects of filtration and ventilation can be predicted empirically
The framework of this study can aid in determining desirable ventilation- filtration couples
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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34. Conclusions Modeling: Limitations and future work Limitations
Epidemiological C-R and illness valuation bear large uncertainties
Model coefficients are highly variable between different locations and need to be properly characterized
Additional effects of ventilation such as productivity increase and SBS are not considered in this study
Future work
Finish experimental characterizations
Fully characterize model parameters
Improve framework for minimum filtration recommendations
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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35. Acknowledgment Coauthors and special thanks Co-authors for project:
Sheng Wang (experiments)
Tom Ben-David (modeling)
Funding: National Air Filtration Association
How well can higher efficiency filtration control particles at high ventilation rates in offices?
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36. Thank you to our sponsors!
Timmy Lott to thank