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Adapting building operation during the COVID-19 pandemic to improve indoor air quality (IAQ) while ensuring sustainable solutions in terms of costs and CO2 emissions is challenging and limited in literature. Our previous study investigated different HVAC operation strategies, including increased filtration using MERV 10, MERV 13, or HEPA filters, as well as supplying 100% outdoor air into buildings for a system initially sized for MERV 10 filtration. This paper significantly extends that research by systematically analyzing the potential financial and environmental impact for different locations in the US. The previous medium office building system model is improved. 2022. "Tradeoffs among indoor air quality, financial costs, and CO2 emissions for HVAC operation strategies to mitigate indoor virus in U.S. office buildings," Building and Environment, 221, pp. 109282, to account for operation in different climates. New evaluation metrics are created to consider the comprehensive impact of improving IAQ on costs and CO2 emissions, using dynamic emission factors for electricity generation depending on the location. HVAC operation strategies are studied in five different locations across the United States, with distinct climates and electricity sources. In four of the five locations, MERV 13 filtration offers the best improvement in IAQ per increase in costs and emissions relative to MERV 10. The exception is the mildest climate of San Diego, where use of 100% outdoor air provides the best IAQ with a limited increase in costs and emissions. A system not sized for HEPA filtration can lead to increased costs and emissions without much improvement in IAQ.
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Adapting building operation during the COVID-19 pandemic to improve
indoor air quality (IAQ) while ensuring sustainable solutions in terms of costs
and CO2emissions is challenging and limited in literature. Our previous
study investigated different HVAC operation strategies, including increased
filtration using MERV 10, MERV 13, or HEPA filters, as well as supplying
100% outdoor air into buildings for a system initially sized for MERV 10
filtration. This paper significantly extends that research by systematically
analyzing the potential financial and environmental impact for different locations
in the US. The previous medium office building system model is improved
Preprint submitted to Building and Environment June 1, 2022
C. A. Faulkner, J. E. Castellini, Y. Lou, W. Zuo, D. M. Lorenzetti, M. D. Sohn. 2022.
"Tradeoffs Among Indoor Air Quality, Financial Costs, and CO2 Emissions for HVAC
Operation Strategies to Mitigate Indoor Virus in U.S. Office Buildings," Building and
Environment, 221, pp. 109282,
Tradeoffs Among Indoor Air Quality, Financial Costs,
and CO2 Emissions for HVAC Operation Strategies to
Mitigate Indoor Virus in U.S. Office Buildings
Cary A. Faulknera, John E. Castellini Jr.a, Yingli Loub, Wangda Zuoc,d,
David M. Lorenzettie, Michael D. Sohne
aDepartment of Mechanical Engineering, University of Colorado Boulder, UCB
427, Boulder, 80309, CO, U.S.A.
bDepartment of Civil, Environmental and Architectural Engineering, University of
Colorado Boulder, UCB 428, Boulder, 80309, CO, U.S.A.
cDepartment of Architectural Engineering, Pennsylvania State University, 104
Engineering Unit A, University Park, 16802, PA, U.S.A.
dNational Renewable Energy National Laboratory, Golden, 80401, CO, U.S.A.
eEnergy Analysis and Environmental Impacts Division, Lawrence Berkeley National
Laboratory, 1 Cyclotron Road, Berkeley, 94720, CA, U.S.A.
to account for operation in different climates. New evaluation metrics are
created to consider the comprehensive impact of improving IAQ on costs
and CO2emissions, using dynamic emission factors for electricity generation
depending on the location. HVAC operation strategies are studied in five
different locations across the United States, with distinct climates and electricity
sources. In four of the five locations, MERV 13 filtration offers the best
improvement in IAQ per increase in costs and emissions relative to MERV 10.
The exception is the mildest climate of San Diego, where use of 100% outdoor
air provides the best IAQ with a limited increase in costs and emissions. A
system not sized for HEPA filtration can lead to increased costs and emissions
without much improvement in IAQ.
Keywords: Indoor air quality, financial cost, CO2emissions, COVID-19
pandemic, climate change.
1. Introduction1
Sustainably operating buildings to improve indoor air quality (IAQ) is2
critical during both a global pandemic and rapid climate change. The United3
States (U.S.) is the second highest contributor to global greenhouse gas4
emissions [1] and buildings account for about 36% of energy-related CO2
emissions in the U.S. [2]. Building operation during the COVID-19 pandemic6
is crucial, as studies have shown that the risk of infection indoors caused by7
airborne transmission is significant [3, 4, 5]. Strategically operating building8
heating, ventilation, and air-conditioning (HVAC) systems can improve IAQ9
and reduce the risk of infection from airborne viral particles [6, 7, 8, 9],10
but can also result in increased energy consumption [10, 11]. This can be11
caused by increased fan energy to overcome the additional pressure drop12
of more efficient filters, or increased heating and/or cooling energy due to13
higher outdoor air ventilation rates, for example. Balancing both IAQ and14
sustainability is a challenge that depends on many factors such as mitigation15
strategy, climate, energy sources, etc.16
Previous research has attempted to study the tradeoffs between IAQ17
and sustainability for various mitigation strategies and climates. Schibuola18
and Tambani [12] studied using increased mechanical ventilation with high19
efficiency air handling units to reduce the risk of infection of COVID-1920
and improve energy efficiency in Italian secondary schools. They found21
increasing mechanical ventilation can significantly reduce infection risks, and22
the increased energy can be offset via the installation of high efficiency air23
handling units. Sha et al. [13] investigated increasing building ventilation24
while reducing energy consumption via direct cooling with outdoor air in25
high rise buildings, and found that improving the ventilation control allowed26
for around 40% reduction in energy consumption while meeting required27
ventilation rates. Zaatari et al. conducted multiple studies [14, 15] investigating28
the tradeoffs of IAQ and energy consumption for different levels of filtration29
or ventilation. They found that the best filtration or control strategy is30
dependent on building system and climate. Santos and Leal [16] studied the31
impact of ventilation rate on energy consumption in European climates and32
found increasing ventilation rate can significantly increase energy consumption.33
Ben-David and Waring [17] compared the associated costs for different levels34
of filtration and ventilation for office buildings in different climates. The35
results showed that improving filtration and increasing ventilation rate complement36
each other, and improving filtration tended to have a greater impact on the37
cost function. Our previous work [10] created new component models for38
HVAC filters and viral transmission and implemented them in a dynamic39
system model using Modelica language. The new models were used to analyze40
indoor virus concentration, predicted number of infections, and energy consumption41
for different mitigation strategies, including use of 100% outdoor air and42
MERV 10, MERV 13, and HEPA filtration.43
Although significant progress has been made, further analysis can be44
performed to understand the tradeoffs between IAQ and sustainability as the45
pandemic enters its third year. First, some studies may investigate HVAC46
operation strategies in different climates, but do not always consider the47
differences in operation based on climate. For example, buildings in humid48
climates operate their systems differently in unoccupied hours to avoid build49
up of mold. Furthermore, studies often assume constant outdoor airflow50
rates and do not account for dynamic outdoor airflow rates based on the51
control of the airside economizer. The amount of free cooling provided by52
the airside economizer impacts both IAQ and energy consumption and varies53
among climates. Also, studies often quantify sustainability in terms of energy54
consumption or cost, but greenhouse gas emissions are not always considered.55
This becomes especially important in the age of rapid climate change, since56
building operators may prioritize minimizing greenhouse gas emissions over57
IAQ or energy costs. New policies may also incentivize limiting greenhouse58
gas emissions by placing a tax on these emissions. Furthermore, new metrics59
are needed to quantify the tradeoffs among IAQ, costs, and emissions.60
To address this research gap, we propose a study to analyze the tradeoffs61
among IAQ, financial costs, and CO2emissions of four mitigation strategies in62
five unique geographic locations with distinct climates and electricity sources63
across the U.S. Five of the 17 sustainable development goals outlined by the64
United Nations [18] are targeted in this paper: 3) good health and well-being,65
7) affordable and clean energy, 9) industry, innovation, and infrastructure,66
11) sustainable cities and communities, and 13) climate action. The studied67
mitigation strategies include different levels of filtration, such as MERV 10,68
MERV 13, and HEPA filtration, as well as supplying 100% outdoor air69
with MERV 10 filtration. We simulate the scenarios using detailed system70
modeling of a prototype medium office building initially sized for MERV 1071
filtration based on the Modelica Buildings library [19, 20]. Our scientific72
contributions in this paper include: 1) developed detailed system models73
to account for the dynamics of the HVAC system to simulate mitigation74
strategies in different locations with distinct climates, 2) proposed novel75
comprehensive evaluation metrics which consider the effectiveness of mitigation76
strategies in terms of IAQ, financial costs, and CO2emissions, including using77
newly available dynamic CO2emission factors dependent on location, and 3)78
identified mitigation strategies in each location that improve IAQ by 6-16%79
with limited increases in costs and emissions.80
The remainder of this paper is organized as follows. We introduce the81
building system model and improvement to account for operation in different82
climates in Section 2. Next, methods to evaluate and compare the mitigation83
strategies are detailed in Section 3. The scope of analysis for this study84
including the four mitigation strategies and five locations is described in85
Section 4. The results in terms of IAQ, costs, and CO2emissions are presented86
in Section 5. Finally, conclusions are drawn in Section 6.87
2. Building System Modeling88
We first introduce the medium office building system studied in this89
paper. The system modeling for the different climates is then detailed.90
2.1. Building System91
The studied building is based on the DOE commercial reference medium92
office building [21], with a focus on the bottom floor based on an existing93
model [22]. The schematic for this system is shown in Figure 1. The floor94
consists of five zones, including a core zone and four perimeter zones. A95
central air handling unit with heating and cooling coils services this floor,96
with VAV terminal boxes containing reheat coils for each zone. An outdoor97
air economizer is used to supply the minimum outdoor airflow based on98
ASHRAE standards [23] as well as provide free cooling. Natural gas is used to99
provide heating, while electricity is used to provide cooling and power the fan.100
The HVAC system is controlled based on the VAV 2A2-21232 sequence from101
the Sequences of Operation for Common HVAC Systems described in [24].102
Figure 1: Schematic of VAV system servicing the bottom floor of the five zone medium
office building.
2.2. System Modeling103
The five zone, medium office building system model is developed using the104
Modelica Buildings library for this study. The HVAC system is sized for each105
climate using EnergyPlusTM and the fan is assumed to be sized for MERV106
10 filtration. We use typical meteorological year data for each location [25].107
More about the original building system model can be found in [10].108
The previous model was designed for a cold and dry climate, so the109
air-conditioning (AC) system can be turned off when there are no occupants.110
However, when the system is used in a humid climate (e.g., Tampa), the111
AC has to run at all times to avoid development of mold due to the high112
humidity. For the system located in Tampa in this study, the model is113
adapted to supply air through the building at all times, including unoccupied114
hours. The outdoor air damper is closed during unoccupied hours and only115
recirculated air is supplied to the building (including for the 100% outdoor116
air case). For cooling scenarios, the supply air temperature setpoint is reset117
from 12 C to 27 C and the zone temperatures are reset from 24 C to 30 C118
in unoccupied hours. For heating scenarios, the zone temperatures are reset119
from 20 C to 12 C in unoccupied hours. This allows for the system to run120
and prevent buildup of mold, while limiting the increase in energy during the121
unoccupied hours.122
The dew point temperature in the core zone for the system in Tampa when123
the system is always running compared to when the system turns off during124
unoccupied hours is shown in Figure 2. The two days shown are Sunday and125
Monday, August 25 and 26. When the system does not run on Sunday, the126
dew point temperature in this zone increases above the acceptable limit of127
15 C (according to ASHRAE Standard 62.1 [23]) for over 8 hours due to128
infiltration of humid air in the building. After the system turns on Monday129
morning, the dew point temperature drops back to an acceptable range.130
On the other hand, the dew point temperature in this zone remains in an131
acceptable range during this time when the system runs 24/7.132
Figure 2: Dew point temperature in the core zone for the system in Tampa on August
3. Methods to Compare Mitigation Strategies133
The methods to compare the mitigation strategies in terms of IAQ, financial134
costs, and CO2emissions are detailed in this section.135
3.1. Indoor Air Quality Calculation136
Indoor air quality can consider several factors, such as chemical and137
biological compounds, particulates, and gases [26]. To narrow the scope,138
this study focuses on indoor biological compounds, using the COVID-19139
pandemic as a scenario for analysis. Thus, IAQ is represented by the building140
level concentration of COVID-19 virus in this study. The sick people generate141
viral particles directly into each well-mixed zone at a constant generation142
rate. The balance of concentration in a zone can be described as:143
dt = (1/mair,zone)[Σ( ˙mc)in Σ( ˙mc)out] + ˙cgen,zone ˙cdecay ,zone,(1)
where dczone
dt is the rate of change of virus concentration in the zone with144
respect to time, mair,zone is the mass of air in the zone, Σ( ˙mc)in is the145
sum of the virus concentration flowrates into the zone, Σ( ˙mc)out is the sum146
of the virus concentration flowrates out of the zone, ˙cgen,z one is the virus147
concentration generation rate within the zone, and ˙cdecay,zone is the rate of148
viral decay in the zone, which is modeled based on a first order method:149
˙cdecay,zone =kdecay czone,(2)
where kdecay is a defined constant rate of viral decay, and czone is the virus150
concentration in the zone.151
We simulate the presence of one sick person in each zone within the152
building from 9:00 AM - 5:00 PM, Monday through Friday throughout the153
year. This allows for the evaluation of the mitigation strategies during154
different conditions, such as weather, throughout the year. We select a typical155
virus generation rate of 25 quanta/hr [27, 28] and a viral decay rate of 0.48156
hr1[6] based on data from the literature. The final results for IAQ presented157
in Section 5 are calculated based on the average virus concentration in all158
the zones, averaged over the year during occupied hours.159
3.2. Financial Cost Calculation160
The annual financial costs for the different mitigation strategies are calculated161
based on the following equation:162
Jtotal =Jfilter +Jelec +Jgas,(3)
where Jtotal is the total annual costs, Jfilter are the costs associated with163
filtration, Jelec are the electricity costs to run the HVAC system, and Jgas
are the costs for natural gas heating. The costs associated with filtration165
include purchase costs and labor costs for replacing the filters throughout166
the year based on their expected life. The electricity costs to run the HVAC167
system come from fan and cooling power. Finally, the natural gas costs are168
calculated based on the heat supplied in the HVAC system from natural gas.169
3.3. CO2Emissions Calculation170
The annual CO2emissions for the mitigation strategies are determined171
based on emissions associated with natural gas heating and electricity consumed172
by the HVAC system, using the method adopted in [29, 30]. The emission173
factor for natural gas heating is constant and independent of location. However,174
the emission factor for electricity is dynamic and depends on the electricity175
sources of the location. Different locations use various portions of renewable,176
nuclear, or fossil fuel energy. The electricity sources vary based on the time177
of day as well as season, for example depending on the availability of solar178
or wind energy. The emission factor data comes from the Cambium project179
lead by the National Renewable Energy Laboratory [31].180
Figure 3 shows an example of how CO2emissions are calculated for a181
sample day based on the natural gas and electricity usage. Figure 3a shows182
the energy consumption for this heating day in Denver. We see the natural183
gas usage varies based on the heating demand, while the electricity remains184
constant since only fan power is needed. The emission factor of electricity185
in Figure 3b varies during the day based on the availability of renewable186
energy, while the emission factor of natural gas heating remains constant.187
Finally, Figure 3c shows the hourly CO2emissions are the product of the188
hourly energy usage and emission factor.189
(a) Hourly energy consumption. (b) Hourly emission factors.
(c) Hourly CO2emissions.
Figure 3: Calculation of CO2emissions based on electricity and natural gas usage for Feb
20, 2020 in Denver.
3.4. Analysis of Combined Metrics190
To evaluate the performance of the different strategies relative to MERV191
10, we define a series of metrics by considering the IAQ, costs and/or CO2
emissions. These are relative metrics, since they are calculated for the193
strategies relative to MERV 10. First, we calculate the percent increase194
in costs or CO2emissions relative to MERV 10. This is described as:195
Ji=Ji/JM10 1,(4)
where Jiis the percent increase in costs/emissions associated with a strategy196
irelative to MERV 10, Jiis the costs/emissions for strategy i, and JM10 is197
the costs/emissions for MERV 10 in that location.198
The percent improvement in IAQ relative to the percent increase in199
costs/emissions can then be calculated as:200
IAQ/Ji= (1 I AQi/I AQM10)/Ji,(5)
where IAQ/Jiis the marginal improvement in IAQ per increase in cost/emissions201
for a strategy irelative to MERV 10, IAQiis the IAQ metric for a strategy202
i, and IAQM10 is the IAQ metric for the MERV 10 strategy.203
We then compare the marginal improvements in IAQ relative to both204
costs and emissions by applying a price to CO2emissions. We use a cost205
of $12 (USD) per ton of CO2emissions based on average prices in the206
U.S. described by the Regional Greenhouse Gas Initiative and California207
Cap-and-Trade Program [32]. By converting CO2emissions to costs, the208
marginal improvements in IAQ relative to both costs and emissions can be209
calculated based on Equation 5.210
4. Scope of Analysis211
We describe the scope of our analysis in this section, including the selected212
mitigation strategies, summary of the chosen geographic locations, and list213
of assumptions.214
4.1. Mitigation Strategies215
Four mitigation strategies are chosen for this study, including use of216
MERV 10, MERV 13, or HEPA filtration, or supply of 100% outdoor air into217
the building with MERV 10 filtration. The 100% outdoor air strategy also218
uses MERV 10 filtration, since filtration is needed for outdoor contaminants219
as well. For brevity, this strategy is referred to simply as “100% outdoor220
air” in the remainder of this paper. For the cases other than the 100%221
outdoor air case, the minimum outdoor airflow during occupied hours is222
defined based on a minimum volumetric outdoor airflow rate, rather than223
an outdoor air fraction. The outdoor airflow can also increase above the224
minimum value to provide free cooling based on the outdoor air economizer225
control. For all cases, including the 100% outdoor air case, the outdoor226
airflow will only decrease below the minimum value to prevent freezing of227
the heating/cooling coils. The simulated static pressure drop caused by the228
HVAC filter varies quadratically with the mass flowrate, as described in [10].229
It should be noted the pressure drop across the filter can increase over time230
as the filter accumulates particles [33] and the pressure drop can vary for231
filters with the same rating, depending on the depth or type of filter [17].232
For simplicity, a constant nominal pressure drop for each filter is chosen233
based on the average of the typical initial and final pressure drops. Similarly,234
the filter particle removal efficiency is dependent on many aspects, such as235
the size of the particles, loading of filters, and duct leakage [34]. This study236
assumes the viral particles have diameters between 1-3 µm, and a constant,237
typical removal efficiency is chosen based on filter data for particles of this238
size. Table 1 shows the settings for the HVAC filters used in the simulations.239
The filtration efficiencies come from ASHRAE technical resources [35] and240
the pressure drop values come from data for MERV 10 [36], MERV 13 [37],241
and HEPA [38] filters.242
Filter Nominal Pressure Drop (Pa) Filtration Efficiency
MERV 10 143 50%
MERV 13 162 85%
HEPA 373 99.97%
Table 1: HVAC filter simulation settings.
The costs of the HVAC filters, which are obtained from [38], are shown243
in Table 2. The total annual costs are determined by the purchase and labor244
costs throughout the year based on the expected life of the filters.245
Filter Purchase
Cost (USD)
Costs per
Expected Life Total Annual
MERV 10 $7$17 4 months $72
MERV 13 $11 $17 4 months $84
HEPA $150 $17 12 months $167
Table 2: HVAC filter costs.
4.2. Geographic Locations and Climates246
Five unique geographic locations with distinct climates across the United247
States are selected based on related work [29, 30] to provide a diversity248
of climates and electricity sources. A summary of the climates, electricity249
sources, energy prices, and average emission factors from electricity generation250
is shown in Figure 4. The climates vary from the very cold climate of251
International Falls, Minnesota to the hot and humid climate of Tampa,252
Florida. The breakdown of electricity sources in the year 2020 for the five253
locations [31] are also shown. The average emission factors from electricity254
generation for each location are included to understand the impact of the255
electricity sources on CO2emissions. Great Falls has the lowest average256
emission factor since it uses mostly renewable energy from hydropower. San257
Diego has the second lowest average emission factor, due to utilizing significant258
renewable energy, such as solar power, and limiting its fossil fuel usage.259
International Falls, Tampa, and Denver have the highest average emission260
factors. While Denver and International Falls utilize zero emission sources261
like wind and nuclear energy, they still rely significantly on fossil fuels like262
coal and natural gas for electricity. Tampa also heavily relies on fossil fuels,263
since over 75% of Tampa’s electricity comes from natural gas. It should264
be noted that electricity sources such as wind and nuclear power have zero265
direct emissions, but include emissions when considering the entire life cycle266
of production [39, 40]. This study only incorporates direct emissions and not267
full life cycle emissions in order to focus on the emissions directly associated268
with building operation. The electricity [41] and natural gas [42] prices for269
each location are also included. The natural gas price is based on the total270
price paid by end-users per thousand cubic feet of natural gas, and is inclusive271
of all taxes and other fees.272
Figure 4: Summary of climate, electricity sources, energy prices, and average emission
factor from electricity generation for the five studied locations.
4.3. Assumptions273
The following assumptions are used for this study. First, we assume274
constant virus generation rates from the sick people and a constant first275
order viral decay rate value for COVID-19 virus in this work. We assume276
one sick person per zone working from 9:00 AM to 5:00 PM, Monday through277
Friday during the entire year. The air in each zone of the office building is278
also assumed to be well-mixed. We assume constant nominal pressure drop279
values for each filter, although the actual pressure drop varies based on the280
airflow rate. The removal efficiencies of the filters are also assumed to be281
constant. We assume the fan is sized for an existing HVAC system with282
MERV 10 filtration in all cases. The individual electricity and natural gas283
prices for each location are constant throughout the year. We use hourly284
weather data and CO2emission data for each location based on the year285
5. Results and Discussion287
We first show an overview of the results for the four mitigation strategies288
in the five locations in terms of IAQ, financial costs, and CO2emissions.289
We then analyze the results based on the impacts of climate and electricity290
sources. Finally, we discuss the results based on the tradeoffs among different291
user priorities.292
5.1. Overview of Results293
The annual results for IAQ, costs, and CO2emissions are shown in Figure294
5. The virus concentrations are normalized by the annual average virus295
concentration for the MERV 10 case in International Falls (0.011 quanta/m3).296
One general result is that HEPA filtration never provides the best IAQ for297
a given location, and is also always worse than the less efficient MERV298
13 filtration. In the five locations, MERV 13 filtration improves the IAQ299
by 5.4-10.6% compared to HEPA filtration. This is because the system is300
not sized for the additional pressure drop caused by HEPA filtration, which301
results in reduced overall system flowrates and lower virus removal rates.302
(a) Annual CO2emissions vs cost.
(b) Average virus concentration vs annual
(c) Average virus concentration vs annual
Figure 5: Results for average virus concentration, annual cost, and annual CO2emissions
for the four mitigation strategies and five locations.
The annual results show dependencies on climate and electricity sources.303
This can especially be seen in Figure 5a, where the colder climates have304
lower annual costs compared to the warmer climates, and there is also a305
clear divide between the locations with higher or lower CO2emissions from306
electricity generation. Figures 5b and 5c similarly show these divides based307
on climate and electricity sources, as well as the IAQ trends for the different308
mitigation strategies. The 100% outdoor air strategy usually provides the309
best IAQ, but can lead to significant increases in costs and CO2emissions.310
MERV 10 filtration is typically the cheapest and lowest emission strategy,311
but also usually provides the worst IAQ. MERV 13 filtration improves the312
IAQ relative to MERV 10 filtration, but with moderate increases in costs313
and emissions. Finally, HEPA filtration often improves the IAQ relative to314
MERV 10 filtration, but not compared to MERV 13 filtration or use of 100%315
outdoor air. It also can lead to significant increases in costs and emissions.316
Based on these findings, we analyze the impacts of climate and electricity317
sources in the following subsections.318
5.2. Impact of Climate319
We discuss the results for the four mitigation strategies in this section320
based on colder and warmer climates. The colder climates are International321
Falls, Great Falls, and Denver, while the warmer climates are San Diego and322
5.2.1. Colder Climates324
There are several common trends among the colder climates. International325
Falls is used as an example in this section, and the breakdown of the results326
in this location is shown in Figure 6. The key feature of the colder climates327
is the dominant energy consumption of natural gas for heating. Figure 6a328
shows, for most cases, the majority of annual energy comes from natural gas329
heating, especially for the 100% outdoor air case. Despite the significant330
natural gas usage, Figure 6b shows the costs from natural gas are relatively331
small compared to those from electricity (used for cooling and fan energy).332
The percentage of costs associated with natural gas heating range from333
14-33% for the four cases in this location. This is because natural gas is334
significantly cheaper than electricity, which is true in all the studied locations.335
The majority of emissions comes from electricity usage for most of the cases336
in this location, as shown in Figure 6c. The exception is the 100% outdoor337
air case, which results in 56% of emissions from natural gas heating due to338
the energy needed to heat the cold outdoor air.339
(a) Breakdown of annual energy consumption. (b) Breakdown of annual cost.
(c) Breakdown of annual CO2emissions.
Figure 6: Annual energy, cost, and CO2emission results for International Falls.
There is also a tradeoff between heating and fan energy for the more340
efficient filter cases. The higher pressure drop filters require more fan power341
to supply airflow, which results in the fan dissipating more heat to the airflow342
as it works harder. This causes the more efficient filter cases to save on some343
heating energy, which is especially seen by the HEPA case in Figure 6a. For344
the colder climates, the additional heat produced by the fan can be beneficial345
to efficiently add heat to the system, while not requiring much more cooling346
energy, since these climates do not require significant cooling. However,347
this increase in electrical heating leads to higher costs due to the relative348
price of electricity compared to natural gas heating. It can also increase or349
reduce emissions depending on the electricity sources in a particular location.350
Since International Falls uses significant fossil fuel energy in their electricity351
generation, the more efficient filter cases lead to higher emissions relative to352
the MERV 10 case.353
The very cold climate also affects the control of the outdoor air economizer.354
For the 100% outdoor air case, the economizer will always supply 100%355
outdoor air (or at least the minimum outdoor airflow for the other cases),356
except when the outdoor air needs to be reduced to prevent freezing of the357
coils in the air handling unit. This becomes noticeable for the colder climates.358
For example, Figure 5c shows that MERV 13 filtration provides better IAQ359
compared to supply of 100% outdoor air for International Falls, which is360
not the case for the other locations. This is because the outdoor airflow361
needs to be reduced often throughout the year to prevent freezing, so MERV362
13 filtration becomes more effective. Figure 7 shows the dynamic usage of363
outdoor air throughout the year in International Falls for the 100% outdoor364
air case. We see this strategy can supply 100% outdoor air in the warmer365
months, but often has to reduce the outdoor airflow in the winter and colder366
mornings. As a result, 100% outdoor air is only supplied about 55% of the367
time during occupied hours.368
Figure 7: Dynamic usage of outdoor air in International Falls for the 100% outdoor air
5.2.2. Warmer Climates369
Next, there are some typical trends in the warmer climates. Compared370
to the colder climates, which use a lot of natural gas for heating, the warmer371
climates rely heavily on electricity for cooling and use very little natural gas.372
As an example of a warmer climate, Figure 8 shows the results for Tampa,373
which is considered a hot and humid climate by ASHRAE. The low usage374
of natural gas heating leads to much lower costs and emissions from natural375
gas compared to higher costs and emissions from electricity. Less than 3%376
of the costs and 4% of the emissions come from natural gas heating for the377
four strategies in this location. The relative price of electricity compared to378
natural gas and reliance on electricity in warmer climates is the reason for379
the higher annual costs in the warmer climates, as seen in Figure 5a.380
(a) Breakdown of annual energy consumption.
(b) Breakdown of annual cost. (c) Breakdown of annual CO2emissions.
Figure 8: Annual energy, cost and CO2emission results for Tampa.
For Tampa, use of 100% outdoor air leads to a 33% increase in cooling381
energy (including dehumidification) relative to MERV 10 filtration because of382
both the heat and humidity in this climate. This also leads to large increases383
in costs and emissions. In San Diego, however, supplying 100% outdoor air384
does not increase the costs and emissions as much, as seen in Figure 9. This is385
due to the relatively milder weather and lower humidity compared to Tampa.386
(a) Breakdown of annual energy consumption.
(b) Breakdown of annual cost. (c) Breakdown of annual CO2emissions.
Figure 9: Annual energy, cost and CO2emission results for San Diego.
This weather in San Diego also allows for more outdoor air use for the387
filter cases using the airside economizer throughout the year, which affects388
the virus concentration results shown in Figure 5b. There are relatively389
smaller differences among the virus concentrations for the MERV 10, MERV390
13, and 100% outdoor air cases due to the high outdoor air usage in San391
Diego. MERV 10 filtration even improves the IAQ by 6% compared to HEPA392
filtration due to the significant amount of outdoor air supplied for this climate393
and the reduced flowrates caused by the high pressure drop of the HEPA394
filter. Figure 10 shows the dynamic outdoor air usage throughout the year395
for the MERV 10 cases in San Diego and Tampa. This shows the high usage of396
outdoor air in San Diego due to its milder weather, although less outdoor air397
is used during the hotter months from July through October. For reference,398
the monthly average outdoor temperatures for these two locations are shown399
in Figure 11. In comparison, not much outdoor air is used for the filter400
cases in Tampa due to the heat and high humidity, as shown in Figure 10b.401
This leads to larger differences in virus concentrations among the MERV 10,402
MERV 13, and 100% outdoor air cases for Tampa as seen in Figure 5b.403
(a) San Diego (warm and marine).
(b) Tampa (hot and humid).
Figure 10: Dynamic usage of outdoor air using MERV 10 filtration in San Diego and
Figure 11: Average monthly temperatures in Tampa and San Diego.
Finally, the increased heat dissipated by the fan for the more efficient404
filter cases is more penalizing for the warmer climates. Compared to the405
colder climates, the additional heat from the fan is not typically needed and406
rather requires the system to provide more cooling. This leads to higher costs407
and emissions for the more efficient filter cases relative to MERV 10, as seen408
in Figures 8 and 9.409
5.3. Impact of Electricity Sources410
Next, the impact of electricity sources on the results are analyzed in this411
section. Great Falls and San Diego are the locations with lower CO2emissions412
from electricity, while International Falls, Denver, and Tampa have higher413
CO2emissions from electricity. About 96% of the electricity generation in414
Great Falls comes from the renewable sources of hydro and wind power,415
making it the lowest emissions from electricity location in this study. San416
Diego limits its fossil fuel usage while utilizing significant renewable energy.417
International Falls, Denver, and Tampa rely heavily on fossil fuels like coal418
and natural gas for electricity generation.419
5.3.1. Locations with Low CO2Emissions from Electricity Generation420
First, we present results for the cleaner electricity locations, using Great421
Falls as an example. The dynamic CO2emission factor from electricity422
throughout the year for Great Falls is shown in Figure 12. The emission423
factor for electricity exceeds the emission factor for natural gas heating424
(180 kg/MWhr) during only about 11% of the year. It often utilizes 100%425
renewable energy for electricity resulting in an emission factor of zero, and426
has an average emission factor throughout the year of about 39 kg/MWhr.427
Figure 12: Dynamic CO2emission factor from electricity in Great Falls.
Figure 13 shows the breakdown of energy consumption and CO2emissions428
for this location. Unlike the similarly cold climate of International Falls, its429
electricity largely comes from clean hydropower. Thus, its emissions mainly430
come from natural gas heating rather than electricity. In this case, even for431
the highest emission scenario of using 100% outdoor air, a building in Great432
Falls will produce less emissions than one in the other studied cold climates.433
For example, use of 100% outdoor air in Great Falls produces about 32% less434
emissions than MERV 10 filtration in Denver.435
(a) Breakdown of annual energy consumption. (b) Breakdown of annual CO2emissions.
Figure 13: Results for Great Falls.
Furthermore, the additional electrical heating dissipated by the fan in the436
efficient filter cases leads to a further reduction in emissions for these cases437
when the electricity is coming from low emissions sources, as seen in Figure438
13b. This is because the small increase in emissions from electricity to power439
the fan for these cases is offset by the reduction in emissions from natural440
gas heating due to the heat added by the fan. Thus, HEPA filtration has441
the lowest emissions in this location, when it typically has one of the highest442
emissions in other locations.443
5.3.2. Locations with High CO2Emissions from Electricity Generation444
Next are the results for the high CO2emissions from electricity locations.445
The results for energy consumption and CO2emissions in Denver are shown446
as an example in Figure 14. Despite a significant portion of energy consumption447
from natural gas heating, especially with the 100% outdoor air case, Figure448
14a shows the majority of emissions comes from electricity.449
(a) Breakdown of annual energy consumption. (b) Breakdown of annual CO2emissions.
Figure 14: Results for Denver.
The high emissions from electricity is because the electricity generation450
in Denver mainly comes from burning fossil fuels such as coal and natural451
gas. Thus, despite the 100% outdoor air case using more energy than the452
HEPA case, the HEPA case results in more emissions due to the electricity453
usage over natural gas. The dynamic CO2emission factor from electricity454
throughout the year in Denver is shown in Figure 15. The emission factor455
from electricity exceeds that from natural gas heating about 99% of the time456
in Denver. Because of this, the increase in electricity and decrease in heating457
caused by the higher fan power for the more efficient filter cases further458
increases the emissions for these cases, as shown in Figure 14.459
Figure 15: Dynamic CO2emission factor from electricity in Denver.
5.4. Findings Based on Priority460
The results based on user priority are summarized in this section. For461
each climate, the strategies can be compared relative to MERV 10 filtration462
based on the metrics of IAQ, costs, and CO2emissions, or any combination463
of these metrics. We first present the results based on a single priority, then464
analyze the results with a combination of priorities.465
5.4.1. Results for Individual Priorities466
For each strategy, the results for IAQ, costs, and CO2emissions are467
normalized by the results using MERV 10 filtration in that location. Thus,468
the MERV 10 results are always equal to one since they are normalized by469
themselves. A number less than one represents an improvement relative470
to MERV 10, signifying a reduction in indoor virus concentration, costs,471
or emissions. Conversely, a number greater than one represents a worse472
performance relative to MERV 10, such as an increase in indoor virus concentration,473
costs, or emissions. The results relative to MERV 10 filtration are shown for474
International Falls in Table 3, and similar tables for the remaining locations475
are included in the appendix.476
Strategy IAQ Cost CO2
MERV 10 1 1 1
100% OA 0.89 1.17 1.31
MERV 13 0.89 1.07 1.03
HEPA 0.97 1.21 1.07
Table 3: Results for the strategies relative to MERV 10 for the individual metrics in
International Falls.
There are trends for the best strategy based on a single priority for the477
different locations. In four of the five locations, supply of 100% outdoor air478
provides the best IAQ. The exception occurs in International Falls, whose479
very cold climate prevents the use of 100% outdoor air during the coldest480
times of the year to avoid freezing of the coils in the air handling unit.481
MERV 13 filtration provides the second best IAQ in all locations, except482
International Falls, where it has slightly better IAQ compared to 100%483
outdoor air. HEPA filtration is usually third best for IAQ due to the reduced484
flowrates caused by the high pressure drop of the filter, although its high485
particle removal efficiency usually allows it to outperform MERV 10 filtration.486
MERV 10 filtration provides the worst IAQ in all locations except San Diego,487
where the high outdoor air usage allows it to outperform HEPA filtration.488
Based on these results, there are tradeoffs between filter efficiency and pressure489
drop (and resulting airflow rate). There should be a theoretical ideal balance490
between filter efficiency and pressure drop, which would likely be dependent491
on many factors including climate. In this study, the differences in airflow492
rates become very important for the efficient filters and our findings show a493
slightly less efficient filter with significantly lower pressure drop is preferable.494
MERV 10 filtration has the lowest costs in all five locations due to its low495
energy usage compared to the other cases. In four of the five locations, MERV496
13 filtration has the second lowest costs. The exception is in San Diego,497
where 100% outdoor air has lower costs since the milder weather causes a498
smaller increase in heating/cooling energy for 100% outdoor air relative to499
the increase in electricity to power the fan for the MERV 13 case. Use of500
100% outdoor air in Tampa, Great Falls, and International Falls leads to the501
highest costs in these locations due to the more extreme weather. Finally,502
use of HEPA filtration leads to the highest costs in Denver and San Diego,503
where the costs from the increased fan power for the HEPA case outweighs504
the increase in costs for 100% outdoor air. These two locations also have505
relatively milder weather compared to the other locations, which explains506
why the increase in costs from 100% outdoor air is less significant.507
MERV 10 filtration also has the lowest CO2emissions in four of the508
five locations. Similar to having the lowest costs, this is because MERV509
10 filtration tends to use the least energy. The exception is in Great Falls,510
where the reduced natural gas heating for the efficient filter cases caused by511
the increased heat dissipated by the fan leads to lower overall emissions. This512
is because of the high use of renewable energy in Great Falls, so the small513
increase in emissions from electricity are offset by the reduction in emissions514
from natural gas heating for the efficient filter cases. For Great Falls, the515
rank of CO2emissions from lowest to highest is: 1) HEPA, 2) MERV 13, 3)516
MERV 10, and 4) 100% outdoor air. The 100% outdoor air strategy has the517
highest CO2emissions in International Falls, Great Falls, and Tampa. These518
are the climates with the most extreme weather, so use of 100% outdoor air519
results in higher emissions from increased heating/cooling. HEPA filtration520
results in the highest emissions in Denver and San Diego due to the increase521
in electricity consumption. The weather in these climates is milder compared522
to the others, so use of 100% outdoor does not result in as high emissions523
compared to HEPA filtration. Finally, MERV 13 filtration typically has the524
second or third lowest CO2emissions due to its moderate energy usage.525
5.4.2. Combination of Priorities526
An optimal strategy can be selected for user’s with a combination of527
priorities as well. Figure 16 shows the comparison of the marginal improvement528
in IAQ per increase in emissions vs the marginal improvement in IAQ per529
increase in costs for the different strategies relative to MERV 10 in the five530
Figure 16: Marginal improvement in IAQ relative to costs and CO2emissions for the five
Based on the method to calculate these metrics (described in Section532
3.4), a higher positive number for these metrics means the strategy is more533
beneficial. For example, it represents a greater improvement in IAQ with a534
smaller increase in costs or emissions relative to MERV 10. Thus, the markers535
in the upper right hand corner perform the best in terms of improvement in536
IAQ relative to both costs and emissions. MERV 13 filtration in International537
Falls and Tampa are the best examples for this, since they can greatly538
improve the IAQ with limited increases in costs and emissions in these539
locations. The more extreme weather in these climates means the MERV540
10 cases use less outdoor air throughout the year, and the 100% outdoor541
air cases result in more significant penalties in terms of costs and emissions,542
making MERV 13 filtration a good option. MERV 13 filtration also performs543
the best for Denver, although its improvement relative to 100% outdoor air is544
not as significant as the previously mentioned locations. Use of 100% outdoor545
air performs the best for San Diego because of its milder weather, resulting546
in less of a penalty in terms of costs and emissions for this case.547
While both these metrics are usually positive, there are three cases where548
they become negative, two of which occur in Great Falls. The metrics549
are typically positive due to the sign convention of the calculations: an550
improvement in IAQ relative to MERV 10 is positive and and increase in551
costs/emissions relative to MERV 10 is positive. However, the reduction in552
emissions for the MERV 13 and HEPA cases relative to MERV 10 in Great553
Falls causes IAQ/Eto be negative for these cases. In this case, the554
negative sign represents a more beneficial strategy, for example MERV 13555
filtration in Great Falls results in a significant improvement in IAQ with a556
small improvement in emissions relative to MERV 10. Similarly, the HEPA557
case sees a small improvement in IAQ with a more significant reduction in558
emissions relative to MERV 10. The final case with negative values is the559
HEPA case in San Diego. HEPA filtration results in worse IAQ relative to560
MERV 10 in San Diego because of the high outdoor air usage for MERV 10561
in this climate and reduced flowrates for the HEPA filter case. In this case,562
the negative sign represents a non-beneficial strategy, because it worsened563
the IAQ and increased the costs and emissions relative to MERV 10.564
Finally, associating a cost with CO2emissions allows us to directly compare565
the marginal improvement in IAQ to both these metrics simultaneously. This566
is shown for the three strategies relative to MERV 10 in the five locations in567
Figure 17.568
Figure 17: Marginal improvement in IAQ relative to costs including the cost of CO2
emissions for the five locations.
MERV 13 filtration appears to be the most beneficial strategy in four of569
the five locations. As seen before, 100% outdoor air is able to outperform570
MERV 13 filtration in San Diego due to the milder weather. MERV 13571
filtration shows the greatest improvement in Tampa due to the limited outdoor572
air usage for the MERV 10 case and the significant penalty in costs for the573
100% outdoor air case. HEPA filtration is the least beneficial strategy for574
all the climates due to the small increase in IAQ relative to high increases575
in costs. For this metric, the only negative number occurs for the HEPA576
case in San Diego, since HEPA filtration worsens the IAQ relative to MERV577
10. We do not see the negative numbers for the Great Falls cases since the578
reduction in emissions is offset by the increase in other costs for the MERV579
13 and HEPA cases.580
6. Conclusion581
The tradeoffs among IAQ, financial costs, and CO2emissions for four582
strategies to mitigate indoor virus are compared for five locations across the583
United States. The mitigation strategies include different levels of filtration,584
such as MERV 10, MERV 13, or HEPA filtration, as well as supply of 100%585
outdoor air into the building. The locations have a variety of climates586
ranging from very cold to hot and humid. Their electricity profiles are587
also comprised differently, with varying portions of renewable energies and588
fossil fuels for generating electricity. The strategies are evaluated using589
a prototypical medium office building model initially sized for MERV 10590
filtration, developed using the Modelica Buildings library.591
The results show the best solution is dependent on climate, electricity592
profile, and user priority. MERV 10 filtration is often the best option when593
the user cares most about costs and/or CO2emissions, since this strategy594
tends to use the least energy. Use of 100% outdoor air usually provides the595
best IAQ, although often significantly increases costs and CO2emissions.596
The results show this can be a good option in the relatively milder climate597
of San Diego, where the increase in costs and emissions is limited. MERV 13598
filtration can provide a nice balance of the three metrics in most locations599
due to its virus filtration efficiency and relatively smaller increases in energy600
consumption. This strategy outperforms 100% outdoor air in the locations601
with more extreme weather, since it avoids the significant increase in heating/cooling602
outdoor air in these locations. Finally, HEPA filtration should be avoided603
for this system, and similar systems that are not sized to overcome the high604
pressure drops of these filters. This leads to large increases in fan power and605
reductions in system flowrates, leading to high costs and emissions with little606
improvement in IAQ.607
Future studies can be conducted based on the work in this paper. The608
models we used in this study can be applied to other contaminant scenarios,609
for example PM2.5which can infiltrate the building from outdoor air. Other610
indoor contaminants can be considered as well, such as CO2, which can611
affect worker productivity [43] and quality of sleep [44]. They can also612
be used to evaluate advanced control strategies to improve IAQ, such as613
occupant-based strategies. We can also study tradeoffs among energy, costs,614
and CO2emissions for other indoor virus mitigation strategies, such as use of615
portable air cleaners, which have been shown to be effective at reducing virus616
concentrations within rooms [45]. Finally, this study focuses on applying617
mitigation strategies to an existing building, since redesigning an HVAC618
system is costly. However, the models can be used to evaluate HVAC system619
designs for new buildings, for example to study a system designed for HEPA620
This research was supported in part by the U.S. Defense Threat Reduction623
Agency and performed under U.S. Department of Energy Contract No.624
DE-AC02-05CH11231. This work emerged from the IBPSA Project 1, an625
international project conducted under the umbrella of the International Building626
Performance Simulation Association (IBPSA). Project 1 will develop and627
demonstrate a BIM/GIS and Modelica Framework for building and community628
energy system design and operation. This research was supported by the629
National Science Foundation under Awards No. CBET-2217410.630
Appendix A631
Location Strategy Normalized IAQ Costs (USD) CO2Emissions
(kg CO2)
International Falls
MERV 10 1.00 6820 29500
100% OA 0.89 7950 38500
MERV 13 0.89 7270 30500
HEPA 0.97 8270 31600
Great Falls
MERV 10 0.96 6201 11242
100% OA 0.84 7365 19528
MERV 13 0.85 6632 10896
HEPA 0.95 6962 8717
MERV 10 1.04 5856 28555
100% OA 0.91 6654 34943
MERV 13 0.93 6290 30314
HEPA 0.98 8113 37235
San Diego
MERV 10 0.94 12041 11825
100% OA 0.88 12597 12493
MERV 13 0.89 13061 12823
HEPA 1.00 15902 15473
MERV 10 1.09 17928 60829
100% OA 0.87 20224 69007
MERV 13 0.91 18548 62861
HEPA 1.01 19054 63919
Table 4: Results for the four strategies in all five climates for IAQ, costs, and CO2
emissions. 50
Appendix B632
Strategy IAQ Cost CO2
MERV 10 1 1 1
100% OA 0.88 1.19 1.74
MERV 13 0.89 1.07 0.97
HEPA 0.99 1.12 0.78
Table 5: Results for the strategies relative to MERV 10 for the individual metrics in Great
Strategy IAQ Cost CO2
MERV 10 1 1 1
100% OA 0.88 1.14 1.22
MERV 13 0.89 1.07 1.06
HEPA 0.95 1.39 1.30
Table 6: Results for the strategies relative to MERV 10 for the individual metrics in
Strategy IAQ Cost CO2
MERV 10 1 1 1
100% OA 0.94 1.05 1.06
MERV 13 0.95 1.08 1.08
HEPA 1.06 1.32 1.31
Table 7: Results for the strategies relative to MERV 10 for the individual metrics in San
Strategy IAQ Cost CO2
MERV 10 1 1 1
100% OA 0.80 1.13 1.13
MERV 13 0.84 1.03 1.03
HEPA 0.92 1.06 1.05
Table 8: Results for the strategies relative to MERV 10 for the individual metrics in
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Building and Environment 207 (2022) 108441.776
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This article presents results from an experimental study to ascertain the transmissibility of the SARS-CoV-2 virus between rooms in a building that are connected by a central ventilation system. Respiratory droplet surrogates made of mucus and virus mimics were released in one room in a test building, and measurements of concentration levels were made in other rooms connected via the ventilation system. The paper presents experimental results for different ventilation system configurations, including ventilation rate, filtration level (up to MERV-13), and fractional outdoor air intake. The most important finding is that respiratory droplets can and do transit through central ventilation systems, suggesting a mechanism for viral transmission (and COVID-19 specifically) within the built environment in reasonable agreement with well-mixed models. We also find the deposition of small droplets (0.5-4 μm) on room walls to be negligibly small.
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Buildings account for approximately 36% of the United States’ total carbon emissions and building retrofits have great potential to reduce carbon emissions. Current research adopts a constant electricity emission factor although it changes over time due to the increase of renewable energy generation. To accurately predict emission reduction potential of building retrofits, this study develops a novel method by using dynamically changing electricity emission factors. Using medium office buildings as an example, we predicted emission reduction of eight building retrofit measures from 2020 to 2050 in five locations in the U.S. with distinct climates and renewable adoption rates. To evaluate emission reduction potential sensitivity to the compositions of electricity generation, five scenarios for renewable energy adoptions are investigated. The results reveal several new phenomena on emission reduction potential of building retrofits for medium offices in the U.S.: (1) it decreases from 2026 to 2050; (2) it has the same trend with coal usage; and (3) it reaches the maximum under the high renewable cost scenario. Based on the results, it is recommended that building retrofits should focus on 1) improving lighting and equipment efficiency; 2) locations with higher coal usage rate, and 3) buildings under the high renewable cost scenario. The new method can also be used for predicting emission reduction potential of the building sector in the U.S. by applying to other building types and regions.
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To minimize the indoor transmission of contaminants, such as the virus that can lead to COVID-19, buildings must provide the best indoor air quality possible. Improving indoor air quality can be achieved through the building’s HVAC system to decrease any concentration of indoor contaminants by dilution and/or by source removal. However, doing so has practical downsides on the HVAC operation that are not always quantified in the literature. This paper develops a temporal simulation capability that is used to investigate the indoor virus concentration and operational cost of an HVAC system for two mitigation strategies: (1) supplying 100% outdoor air into the building and (2) using different HVAC filters, including MERV 10, MERV 13, and HEPA filters. These strategies are applied to a hypothetical medium office building consisting of five occupied zones and located in a cold and dry climate. We modeled the building using the Modelica Buildings library and developed new models for HVAC filtration and virus transmission to evaluate COVID-19 scenarios. We show that the ASHRAE-recommended MERV 13 filtration reduces the average virus concentration by about 10% when compared to MERV 10 filtration, with an increase in site energy consumption of about 3%. In contrast, the use of 100% outdoor air reduces the average indoor concentration by about an additional 1% compared to MERV 13 filtration, but significantly increases heating energy consumption. Use of HEPA filtration increases the average indoor concentration and energy consumption compared to MERV 13 filtration due to the high resistance of the HEPA filter.
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The COVID-19 pandemic has highlighted the need for strategies that mitigate the risk of aerosol disease transmission in indoor environments with different ventilation strategies. It is necessary for building operators to be able to estimate and compare the relative impacts of different mitigation strategies to determine suitable strategies for a particular situation. Using a validated CFD model, this study simulates the dispersion of exhaled contaminants in a thermally stratified conference room with overhead heating. The impacts of portable air-cleaners (PACs) on the room airflow and contaminant distribution were evaluated for different PAC locations and flow rates, as well as for different room setups (socially distanced or fully occupied). To obtain a holistic view of a strategy’s impacts under different release scenarios, we simultaneously model the steady-state distribution of aerosolized virus contaminants from eight distinct sources in 18 cases for a total of 144 release scenarios. The simulations show that the location of the source, the PAC settings, and the room set-up can impact the average exposure and PAC effectiveness. For this studied case, the PACs reduced the room average exposure by 31%–66% relative to the baseline case. Some occupant locations were shown to have a higher-than-average exposure, particularly those seated near the airflow outlet, and occupants closest to sources tended to see the highest exposure from said source. We found that these PACs were effective at reducing the stratification caused by overhead heating, and also identified at least one sub-optimal location for placing a PAC in this space.
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Building retrofits have great potential to reduce CO2 emissions since buildings are responsible for 36% of emissions in the United States. Several existing studies have examined the effect of building retrofit measures on CO2 emission reduction. However, these studies oversimplified emission factors of electricity by adopting constant annual emission factors. This study uses hourly emission factors of electricity to analyze the effect of building retrofit measures on emission reduction using U.S. medium office buildings as an example. We analyzed the CO2 emission reduction effects of eight building retrofit measures that related to envelope and mechanical systems in five locations: Tampa, San Diego, Denver, Great Falls, and International Falls. The main findings are: (1) estimating CO2 emission reduction with constant emission factors overestimates the emission reduction for most measures in San Diego, while it underestimates the emission reduction for most measures in Denver and International Falls; (2) The same retrofit measure may have different effects on CO2 emission reduction depending on the climate. For instance, improving lighting efficiency and improving equipment efficiency have less impact in emission reduction in cold climates than hot climates; and (3) The most energy efficient measure may not be the most efficient emission measure. For example, in Great Falls, the most energy efficient measure is improving equipment efficiency, but the most efficient emission measure is improving heating efficiency.
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The COVID-19 pandemic, through governmental stay-at-home orders, forced rapid changes to social human behavior and interrelations, targeting the work environments to protect workers and users. Rapidly, global organizations, US associations, and professionals stepped in to mitigate the virus's spread in buildings' living and work environments. The institutions proposed new air system HVAC settings without efficiency concerns, such as improved flow rates and filtering for irradiation, humidity, and temperature. Current literature consensually predicted an increase in energy consumption due to new measures to control the SARS-CoV-2 spread. The research team assumed the effort of validating the prior published outcomes, applied to US standardized high-rise office buildings, as defined and set by the key entities in the field, by resorting to a methodology based on software energy analysis. The study compares a standard high-rise office building energy consumption, and CO2 emissions and operations costs in nine US climate zones — from 0 to 8, south to north latitudes, respectively —, assessed in specifically the most populated cities, between the previous and post COVID-19 scenarios. The outcomes clarify the gathered knowledge, explaining that climate zones above mixed-humid type (4) tend to increase relative energy use intensity by 21.72%, but below that threshold the zones decrease relative energy use intensity by 11.92%.
The Indoor Air Quality (Indoor Air Quality (IAQ)) of the bedroom environment has recently garnered attention since air pollution can affect sleep. Previous studies investigated IAQ and sleep quality in controlled environments which impacts both self-reported and measured sleep quality. Studies within a participant’s home environment are ecologically valid and reduce participant bias. Here, we study 20 participants over 2.5 months in Austin, TX. We monitored five components of IAQ using the BEVO Beacon, a calibrated purpose-built environmental monitor, and measured participant sleep quality through wearable activity trackers and 4-question surveys sent four times a week. We found significant decreases in sleep quality during nights with elevated CO, CO2, and temperature. Elevated CO was associated with a mean increase in 0.9 self-reported awakenings and decreases in device-measured sleep time of 21.6 min and sleep efficiency of 0.6%. Increased CO2 and temperature were associated with decreases in device-measured sleep time of 17.5 and 15.2 min, respectively. Elevated PM2.5 and TVOCs concentrations were associated with overall improvements in sleep quality. Participants reported a mean of 4.4 fewer awakenings and had a 1.1% increased in measured sleep efficiency for nights with elevated PM2.5. Elevated TVOCs were associated with an increase in sleep time of 14.5 min. These findings indicate a need to study the relationship between these aggregate IAQ measures and sleep quality more closely. Our results also indicate that pollutants can independently affect sleep quality regardless of the CO2 measurements. Compared to literature, our study is the longest and includes the most IAQ parameters.
Here we evaluate the transport of respiratory droplets that carry SARS-CoV-2 through central air handling systems in multiroom buildings. Respiratory droplet size modes arise from the bronchioles representing the lungs and lower respiratory tract, the larynx representing the upper respiratory tract including vocal cords, or the oral cavity. The size distribution of each mode remains largely conserved, although the magnitude of each droplet mode changes as infected individuals breathe, speak, sing, laugh, cough, and sneeze. Here we evaluate how each type of respiratory droplet transits central ventilation systems and the implications thereof for infectivity of COVID-19. We find that while larger oral droplets can transmit through the air handling systems, their size and concentration are greatly reduced with but few oral droplets leaving the source room. In contrast, the smaller droplets that originate from the bronchioles and larynx are much more effective in transiting through the air handling system into connected rooms. This suggests that ratio of lower respiratory or deep lung infections increases relative to upper respiratory infections in rooms connected by central air handling systems. Also, increasing the temperature and humidity in the range considered after the droplets have achieved an “equilibrium” size reduces the probability of infection.
As suggested by many guidelines, a high ventilation rate is required to dilute the indoor virus particles and reduce the airborne transmission risk, i.e., dilution ventilation (DV). However, high ventilation rates may result in high energy costs. Ventilative cooling (VC), which requires high ventilation rates like DV, is an option to reduce the cooling energy consumption. By combining DV and VC, this paper investigated the operation of the mechanical ventilation system in high-rise buildings during the COVID-19 pandemic, aiming to minimizing the cooling related energy consumption and reducing COVID-19 transmission. First, a modified Wells-Riley model was proposed to calculate DV rates. The ventilation rate required to achieve VC was also introduced. Then, a new ventilation control strategy was proposed for achieving DV and VC. Finally, a case study was conducted on a real high-rise building, where the required DV rate and the impact of the settings of the mechanical ventilation on the energy savings were evaluated. The results indicate that the required ventilation rates vary from 36 m³/s to 3306 m³/s depending on the protective measures. When the occupants follow the protective measures, the proper settings of the mechanical ventilation system can reduce energy consumption by around 40%.
The unprecedented coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made more than 125 million people infected and more than 2.7 million people dead globally. Airborne transmission has been recognized as one of the major transmission routes for SARS-CoV-2. This paper presents a systematic approach for evaluating the effectiveness of multi-scale IAQ control strategies in mitigating the infection risk in different scenarios. The IAQ control strategies across multiple scales from a whole building to rooms, and to cubical and personal microenvironments and breathing zone, are introduced, including elevated outdoor airflow rates, high-efficiency filters, advanced air distribution strategies, standalone air cleaning technologies, personal ventilation and face masks. The effectiveness of these strategies for reducing the risk of COVID-19 infection are evaluated for specific indoor spaces, including long-term care facility, school and college, meat plant, retail stores, hospital, office, correctional facility, hotel, restaurant, casino and transportation spaces like airplane, cruise ship, subway, bus and taxi, where airborne transmission are more likely to occur due to high occupancy densities. The baseline cases of these spaces are established according to the existing standards, guidelines or practices. Several integrated mitigation strategies are recommended and classified based on their relative cost and effort of implementation for each indoor space. They can be applied to help meet the current challenge of ongoing COVID-19, and provide better preparation for other possible epidemics and pandemics of airborne infectious diseases in the future.