State-of-the-Art Review of CO2

Demand Controlled Ventilation

Technology and Application

Steven J. Emmerich

Andrew K. Persily

NISTIR 6729
NISTIR 6729

March 2001

U.S. Department of Commerce

Donald L. Evans, Secretary

National Institute of Standards and Technology

Karen H. Brown, Acting Director

State-of-the-Art Review of CO2

Demand Controlled Ventilation

Technology and Application

Steven J. Emmerich

Andrew K. Persily

Building and Fire Research Laboratory

Prepared for:

Architectural Energy Corporation

Boulder, Colorado
i

ABSTRACT

The control of outdoor air intake rates in mechanically ventilated buildings based on indoor

carbon dioxide (CO2) levels, often referred to as CO2 demand controlled ventilation (DCV), has

the potential for reducing the energy consumption associated with building ventilation in some

commercial and institutional buildings. Carbon dioxide DCV has been discussed, promoted,

studied and demonstrated for about twenty years, but questions still remain regarding the actual

energy savings potential as a function of climate, ventilation system features, and building

occupancy. In addition, questions exist as to the indoor air quality (IAQ) impacts of the approach

and the best way to implement CO2 DCV in general and in a given building. This report presents

a state-of-the-art review of CO2 DCV technology and application including discussion of the

concept and its application, and a literature review. In addition the regulatory and standard

requirements impacting CO2 DCV are also examined.

Keywords: carbon dioxide, control, energy efficiency, indoor air quality, ventilation
iii

TABLE OF CONTENTS

Abstract i

1. INTRODUCTION 1

2. TECHNICAL BACKGROUND: CARBON DIOXIDE IN BUILDINGS 2

2.1 Carbon Dioxide Generation Rates 2

2.2 Carbon Dioxide, Indoor Air Quality and Ventilation 4

3. LITERATURE REVIEW 11

3.1 Case Studies – Field Tests 11

3.2 Case Studies – Simulations 14

3.3 Sensor Performance and Location 20

3.4 Application 23

3.5 Summary and Conclusions 25

4. TECHNOLOGY UPDATE: SENSORS 28

5. STANDARDS AND REGULATORY CONTEXT 29

6. SUMMARY 31

7. ACKNOWLEDGEMENTS 32

8. REFERENCES 33

Appendix A: CEC RFP Issues 39

Appendix B: Preliminary Application Guidance and Issues 41

THIS REPORT WAS PREPARED AS A RESULT OF WORK SPONSORED BY THE

CALIFORNIA ENERGY COMMISSION (COMMISSION). IT DOES NOT NECESSARILY

REPRESENT THE VIEWS OF THE COMMISSION, ITS EMPLOYEES, OR THE STATE OF

CALIFORNIA. THE COMMISSION, THE STATE OF CALIFORNIA, ITS EMPLOYEES,

CONTRACTORS, AND SUBCONTRACTORS MAKE NO WARRANTY, EXPRESS OR

IMPLIED, AND ASSUME NO LEGAL LIABILITY FOR THE INFORMATION IN THIS

REPORT; NOR DOES ANY PARTY REPRESENT THAT THE USE OF THIS INFORMATION

WILL NOT INFRINGE UPON PRIVATELY OWNED RIGHTS. THIS REPORT HAS NOT

BEEN APPROVED OR DISAPPROVED BY THE COMMISSION NOR HAS THE

COMMISSION PASSED UPON THE ACCURACY OR ADEQUACY OF THE INFORMATION

IN THIS REPORT.
1

1. INTRODUCTION

Many ventilation requirements and recommendations, e.g., ASHRAE Standard 62-1999, are in

the form of outdoor airflow rates per person expressed as L/s or cfm per person. Mechanical

ventilation systems are therefore designed to provide a minimum level of outdoor air based on

the designed occupancy level multiplied by the per-person ventilation requirement. However, a

space that is occupied at less than its design level may still be ventilated at this design minimum

rate, often resulting in increased energy consumption beyond that which would be required based

on the actual occupancy. Furthermore, early during a given day of building occupancy,

contaminants generated by people and their activities will not yet have reached their ultimate

levels based on the transient nature of the situation. As a result, it is sometimes possible to delay

or lag the onset of the design ventilation rate to take credit for this transient effect. A number of

approaches have been proposed to account for actual occupancy levels and to provide the

ventilation rate corresponding to the actual rather than design occupancy. These include timebased scheduling when the occupancy patterns are well known and predictable, occupancy

sensors to determine when people have entered a space (though not necessarily how many) and

CO2 sensing and control as a means of estimating the number of people in a space or at least the

strength of occupant-related contaminant sources.

Controlling outdoor air intake rates using CO2 demand controlled ventilation (DCV) offers the

possibility of reducing the energy penalty of over-ventilation during periods of low occupancy,

while still ensuring adequate levels of outdoor air ventilation. As discussed later in this report,

depending on climate and occupancy patterns, CO2 DCV may provide significant energy savings

in commercial and institutional buildings. While a number of studies have suggested the extent

of such savings via field studies and computer simulations, additional work is needed to better

define the magnitude of energy savings possible and the dependence of these savings on climate,

building and system type, control approach, and occupancy patterns. In addition, important

issues remain to be resolved in the application of CO2 DCV including how best to apply the

control approach, including issues such as which control approach to use in a given building,

sensor location, sensor maintenance and calibration, and the amount of baseline ventilation

required to control contaminant sources that don’t depend on the number of occupants.

This report presents a state-of-the-art review of CO2 DCV technology and its application in

commercial and institutional buildings. Following this introduction, the next section presents the

theoretical background of CO2 DCV including discussions of CO2 generation rates by people, the

relationship of indoor CO2 to building ventilation rates, and the basic concept of controlling

ventilation based on indoor CO2 levels. The third section of the report is a literature review of

previous research on CO2 DCV, including field demonstration projects, computer simulation

studies, studies of sensor performance and location, and discussions of the application of the

approach. The next section of the report contains an update on CO2 sensor technology as it

applies to DCV. The manner in which CO2 DCV is addressed in standards and other regulations,

including California’s Energy Efficiency Standards (often referred to as Title 24), is presented in

section five of this report. The report also contains two appendices. The first appendix discusses

how CO2 DCV relates to the four issues identified by the California Energy Commission Public

Interest Energy Research Request for Proposal #400-99-401 that resulted in this project. The

second appendix summarizes preliminary guidance on the application of CO2 DCV based on the

material reviewed in preparing this report. While future phases of this effort are intended to

develop more definitive guidance, this appendix attempts to capture some of the guidance that

has been developed to date while identifying some issues that remain to be resolved.
2

2. TECHNICAL BACKGROUND: CARBON DIOXIDE IN BUILDINGS

In order to evaluate the possibilities and application of CO2 DCV, it is important to understand

the dynamics of indoor CO2. This section discusses these dynamics, including indoor CO2

generation rates, how indoor CO2 levels relate to ventilation, and how CO2 can be used to control

ventilation. Much of this material is based on an earlier publication by Persily (1997). This

discussion does not cover the issue of using indoor CO2 to measure or estimate building

ventilation rates, but rather is focused on issues related to ventilation rate control based on indoor

CO2 levels. Persily (1997) contains a discussion of the measurement issue, as does ASTM

Standard D6245 (1998).

2.1 Carbon Dioxide Generation Rates

While it is not critical to the application of CO2 DCV, the emission rate of occupant generated

CO2 is certainly a relevant issue in this discussion. This section discusses the rate at which

people generate CO2.

People generate CO2, and consume oxygen, at a rate that depends primarily on their body size

and their level of physical activity. The relationship between activity level and the rates of

carbon dioxide generation and oxygen consumption is discussed in the ASHRAE Fundamentals

Handbook (ASHRAE 1997). The rate of oxygen consumption VO2, in L/s, of a person is given

by the following equation

VO2 =

0.00276ADM

(0.23RQ + 0.77)

(1)

When using inch-pound units, VO2 is expressed in cfm and Equation (1) takes the form

VO2 =

0.000543ADM

(0.23RQ + 0.77)

(2)

where RQ is the respiratory quotient, i.e., the relative volumetric rates of carbon dioxide

produced to oxygen consumed. M is the level of physical activity, or the metabolic rate per unit

of surface area, in mets (1 met = 58.2 W/m

2

= 18.5 Btu/h·ft

2

). AD is the DuBois surface area in

m

2

, which can be estimated by the following equation

AD = 0.203H

0.725W0.425

(3)

where H is the body height in m and W is the body mass in kg. When using inch-pound units, AD

is in ft

2

, 0.203 is replaced with 0.660, H is in ft and W is in lb. For an average size adult, AD

equals about 1.8 m

2

(19 ft

2

). Additional information on body surface area is available in the EPA

Exposure Factors Handbook (EPA 1999). The value of RQ depends on diet, the level of physical

activity and the physical condition of the person. It is equal to 0.83 for an average size adult

engaged in light or sedentary activities. RQ increases to a value of about 1 for heavy physical

activity, about 5 met. Given the expected range of RQ, it has only a secondary effect on carbon

dioxide generation rates.

The carbon dioxide generation rate of an individual is therefore equal to VO2 multiplied by RQ.

Figure 1 shows oxygen consumption and carbon dioxide generation rates as a function of

physical activity for an average sized adult with a surface area of 1.8 m

2

(19 ft

2

) and RQ = 0.83.

Based on Equation 1, the carbon dioxide generation rate corresponding to an average size adult

engaged in office work (1.2 met) is about 0.0052 L/s (0.011 cfm). However, the generation rate

depends strongly on activity level and can cover a range from less than 0.0050 L/s (0.011 cfm) at

1 met to as high as 0.010 L/s (0.021 cfm) at about 2 met for the occupants of an office building.
3

The carbon dioxide generation rate for a child with AD = 1 m

2

(11 ft

2

) and a physical activity

level of 1.2 met is equal to 0.0029 L/s (0.0061 cfm). When making calculations that use the

carbon dioxide generation rate in a building, one must consider the level of physical activity and

the size of the building occupants. Chapter 8 of the ASHRAE Fundamentals Handbook, Thermal

Comfort, (ASHRAE 1997) contains typical met levels for a variety of activities. Some of these

values are reproduced in Table 1.

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0 1 2 3 4 5

Physical activity (met)

0.00

0.01

0.02

0.03

0.04

0.05

0.06

(cfm)

Oxygen

consumption

Carbon dioxide

generation (RQ = 0.83)

Figure 1 CO2 generation and O2 consumption as a function of physical activity (for an average

size adult)

Oxygen depletion is sometimes cited as a cause of indoor air quality complaints in buildings.

Based on the oxygen consumption rates determined with Equation 1, O2 depletion due to low

ventilation rates is almost never an issue. Given an activity level corresponding to office work,

about 1.2 met, the oxygen consumption rate of an individual equals 0.006 L/s (0.013 cfm). At an

outdoor air ventilation rate of 7.5 L/s (16 cfm) per person, the steady-state indoor oxygen

concentration is reduced from its typical outdoor level of 21 % to 20.9 %. At 2.5 L/s (5.3 cfm),

the indoor oxygen concentration is reduced to 20.8 %. Reduced oxygen concentrations do not

affect human health or comfort until oxygen levels decrease below 19.5 % (NIOSH 1987), which

corresponds to an outdoor air ventilation rate of 0.4 L/s (0.8 cfm) per person. Such low oxygen

concentrations are not typically encountered indoors, except in confined spaces where another

gas is displacing oxygen or during fires.
4

Activity Met

Seated, quiet 1.0

Reading and writing, seated 1.0

Typing 1.1

Filing, seated 1.2

Filing, standing 1.4

Walking at 0.9 m/s (2 mph) 2.0

House cleaning 2.0-3.4

Exercise 3.0-4.0

Table 1 Typical Met Levels for Various Activities (ASHRE 1997)

2.2 Carbon Dioxide, Indoor Air Quality and Ventilation

There has been a great deal of confusion over the years with respect to the relationship of indoor

CO2 levels, indoor air quality and ventilation (Persily 1993 and 1997), much of which has carried

over into the discussion of demand controlled ventilation. One of the primary issues has been the

significance of indoor CO2 levels as an indicator of indoor air quality and the ability to maintain

acceptable indoor air quality based on the control of indoor CO2 levels. This section discusses

the significance of indoor CO2 levels in the context of indoor air quality and ventilation.

Indoor CO2 concentrations have been referred to as an indicator of indoor air quality, often

without describing the specific association between carbon dioxide and indoor air quality that is

being indicated. There are a number of relationships that could be implied in discussing carbon

dioxide and indoor air quality including the relationship between carbon dioxide concentrations

and occupant perceptions of the indoor environment, the relationship between carbon dioxide

concentrations and the concentrations of other indoor contaminants, and the relationship between

carbon dioxide and outdoor air ventilation rates. While some of these relationships are relatively

well understood, and in some cases well founded, others have not been documented

experimentally or theoretically. In other words, indoor carbon dioxide concentrations can be used

to indicate specific and limited aspects of indoor air quality, but do not provide an overall

indication of the quality of indoor air. However, this relationship is almost an entirely different

issue from that of controlling outdoor air intake rates based on CO2 levels as discussed below.

Carbon Dioxide and Indoor Air Quality

Carbon dioxide is not generally considered to be a health concern at typical indoor

concentrations. The time-weighted average threshold limit value (8 h exposure and a 40 h work

week) for carbon dioxide is 9000 mg/m

3

(5000 ppm(v)), and the short-term exposure limit

(15 min exposure) is 54 000 mg/m

3

(30 000 ppm(v)) (ACGIH 2001). A number of studies at

elevated concentrations, about 5 % carbon dioxide in air or 90 000 mg/m

3

(50 000 ppm(v)), have

been performed, and the lowest level at which effects have been seen in humans and animals is

about 1 %, i.e., 18 000 mg/m

3

(10 000 ppm(v)) (EPA 1991). Indoor carbon dioxide

concentrations will not reach these levels unless the ventilation rate is extremely low, about 1 L/s

(2 cfm) per person for 9000 mg/m

3

(5000 ppm(v)) and less than about 0.2 L/s (0.4 cfm) per

person for 54 000 mg/m

3

(30 000 ppm(v)).

The association between carbon dioxide concentrations and occupant perceptions of the indoor

environment in terms of comfort and irritation is complex because it mixes several different

issues, including the comfort impacts of the carbon dioxide itself, associations between carbon
5

dioxide levels and the concentrations of other occupant-generated contaminants, and the

relationship between carbon dioxide and ventilation. Some indoor air quality investigators

associate indoor carbon dioxide concentrations from 1100 mg/m

3

(600 ppm(v)) to 1800 mg/m

3

(1000 ppm(v)) or higher with perceptions of stuffiness and other indicators of discomfort and

irritation (Bright et al. 1992; Rajhans 1983; Bell and Khati 1983). However, these associations

are often based on anecdotal observations of the investigator or on informal occupant surveys.

Seppanen et al. (1999) reviewed twenty-one studies, involving more than thirty thousand

subjects, of ventilation rates, indoor CO2 levels and sick building syndrome (SBS) symptoms and

found that higher CO2 levels were associated with increased symptoms in about half of the

studies. The authors do note that there were significant variations among the studies in the CO2

metric employed and a number of measurement issues. Also, they note that it is unlikely that the

symptoms were associated with exposure to CO2, but rather to other contaminants. Apte et al.

(2000) examined data from forty-one U.S. office buildings from the EPA BASE study in which

the measurement protocol was standardized and probability sampling was used to select the

buildings. Significant associations were seen between some SBS symptoms and CO2 levels,

though the authors acknowledge that CO2 is likely a surrogate for other occupant-generated

pollutants and for the ventilation rate per occupant. In other words, CO2 levels increase with

increased occupancy and decreased ventilation rate, and it may be these latter two factors that are

actually causing the symptoms. In addition, the observed associations between carbon dioxide

and occupant comfort may be due to other factors, such as thermal comfort or the concentrations

of other contaminants in the space. However, as discussed below, there is a demonstrated

correlation between indoor carbon dioxide concentrations and the level of acceptability of the

space in terms of human body odor.

The relationship between carbon dioxide concentrations and the concentrations of other indoor

contaminants depends on the characteristics of the sources of these other contaminants. As

discussed earlier, the rate at which carbon dioxide is generated in a space depends on the number

of people in the space, their size and their level of physical activity. If other contaminants are

generated at a rate that also depends on these factors, then carbon dioxide may be a good

indicator of their concentrations. However, only some indoor contaminants are generated at a

rate that depends on occupancy, and many are not a function of occupancy at all. For example,

emissions from building materials and furnishings, the intake of outdoor contaminants by the

ventilation system, and contaminants associated with some occupant activities do not depend on

the number of occupants in a space. Regardless of the indoor carbon dioxide level, the

concentration of contaminants emitted by occupant-independent sources may be high, low or in

between and the carbon dioxide concentration will not provide any information on their

concentration. This fact is one limitation on the use of carbon dioxide based demand controlled

ventilation.

Carbon Dioxide Concentrations and Body Odor Acceptability

At the same time people are generating CO2, they are also producing odor-causing bioeffluents.

Similar to carbon dioxide generation, the rate of bioeffluent generation depends on the level of

physical activity. Bioeffluent generation also depends on diet and on personal hygiene. Because

both carbon dioxide and bioeffluent generation rates depend on physical activity, the

concentrations of carbon dioxide and the odor intensity from human bioeffluents in a space

exhibit a similar dependence on the number of occupants and the outdoor air ventilation rate.

Experimental studies have been conducted in chambers and in occupied spaces, in which people

evaluated the acceptability of the air in terms of body odor (Berg-Munch et al. 1986; Cain et al.
6

1983; Fanger and Berg-Munch 1983; Fanger 1988; Iwashita et al. 1990; Rasmussen et al. 1985).

These experiments studied the relationship between outdoor air ventilation rates and odor

acceptability, and are a major consideration in developing the ventilation rate recommendations

in ventilation standards. Some of the experiments also studied the relationship between the

acceptability of the air in the space in terms of odor and carbon dioxide concentrations.

These studies have concluded that about 7 L/s (15 cfm) of outdoor air ventilation per person will

control human body odor such that roughly 80 % of unadapted persons (visitors) will find the

odor at an acceptable level. The same level of odor acceptability was found to occur at carbon

dioxide concentrations that are about 1250 mg/m

3

(700 ppm(v)) above the outdoor concentration,

which at a typical outdoor level of 630 mg/m

3

(350 ppm(v)) yields an indoor carbon dioxide

concentration of 1880 mg/m

3

(1050 ppm(v)). Based on these considerations, 1800 mg/m

3

(1000 ppm(v)) carbon dioxide is a commonly discussed guideline value (ASHRAE 1989). The

differential between indoor and outdoor levels of 1250 mg/m

3

(700 ppm(v)) is a measure of

acceptability with respect to body odor, irrespective of the outdoor carbon dioxide concentration.

Figure 2 shows the percent of unadapted persons (visitors) who are dissatisfied with the level of

body odor in a space as a function of the carbon dioxide concentration above outdoors (CEC

1992). People adapt quickly to bioeffluents. For adapted persons (occupants), the ventilation rate

per person to provide the same acceptance is approximately one third of the value for unadapted

persons (visitors) and the corresponding carbon dioxide concentrations above outdoors are three

times higher (Berg-Munch et al. 1986; Cain et al. 1983).

The relationship between percent dissatisfied and carbon dioxide concentrations for visitors

shown in Figure 2 was seen experimentally (Berg-Munch et al. 1986; Fanger and Berg-Munch

1983; Rasmussen et al. 1985), and the correlation was not strongly dependent on the level of

physical activity. In addition, the relationship did not require that the indoor carbon dioxide

concentration be at equilibrium. The relationship described in Figure 2 can also be derived based

on the experimentally-determined relationship between percent dissatisfied and outdoor air

ventilation rates in L/s (cfm) and the relationship between outdoor air ventilation rates and

equilibrium carbon dioxide concentrations that is described later in this paper.
7

Figure 2 Percent of Visitors Dissatisfied with Bioeffluents Odor as a Function of CO2

Concentration (CEC 1992)

While carbon dioxide concentrations can be an appropriate means of characterizing the

acceptability of a space in terms of body odor, as stated earlier, they do not provide information

on the control of contaminants from other pollutant sources such as building materials,

furnishings and occupant activities. And while maintaining carbon dioxide concentrations within

1250 mg/m

3

(700 ppm(v)) of outdoors should provide acceptable perceived air quality in terms

of human body odor, it does not necessarily imply adequate control of these other pollutant

sources.

Some have viewed this relationship of CO2 with bioeffluents perception as a problem with CO2

DCV, reasoning one can only control the level of odor from bioeffluents with this approach. This

conclusion is erroneous, since CO2 can also serve as an indicator of ventilation per person

independent of the relationship seen in Figure 2.

0

10

20

30

40

50

60

0 1000 2000 3000 4000 5000

CO2 concentration above outdoors (mg/m

3

)

ppm(v)

0 500 1000 1500 2000 2500 3000
8

Carbon Dioxide and Ventilation Rates

The relationship between carbon dioxide and outdoor air ventilation rates is fairly well

understood (Persily and Dols 1990; Persily 1997). All else being equal, if the ventilation rate in

an occupied space decreases then the carbon dioxide concentration will increase. However,

making quantitative estimates of building ventilation rates based on measured CO2

concentrations requires the use of a specific technique that is appropriate to the conditions that

exist in the building, and is not always as simple as has sometimes been suggested (Persily

1997). Fortunately, the use of CO2 DCV does not rely on making estimates of building

ventilation rates based on CO2 concentrations. In the context of this report, the relevant issues of

the relationship between indoor CO2 levels and ventilation include steady-state CO2

concentrations at a constant air change rate and the time it takes to achieve steady-state

conditions.

Steady-state CO2 concentrations can be determined for a given ventilation rate based on a singlezone mass balance analysis. Assuming that the CO2 concentration in the building or space of

interest can be characterized by a single value C, the mass balance of CO2 can be expressed as

follows:

V

dC

dt

= G + QCout − QC (4)

where

V = building or space volume (mass) in m

3

(mg)

C = indoor CO2 concentration in mg/m

3

(ppm(v))

Cout = outdoor CO2 concentration in mg/m

3

(ppm(v))

t = time in s

G = indoor CO2 generation rate in mg/s (m

3

/s)

Q = building or space ventilation rate in mg/s (m

3

/s)

For a constant generation rate (occupancy level) and constant ventilation rate and outdoor

concentration, the indoor concentration will eventually attain a steady state or equilibrium

concentration Css given by the following expression:

Css = Cout + G /Q (5)

If the generation rate G and the ventilation rate Q are expressed in L/s (as in Figure 1), and the

concentrations are in mg/m

3

, then Equation (5) takes the form:

Css = Cout +

1.8 ×10

6G

Q

(6)

If instead G and Q are expressed in cfm and the concentrations are in ppm(v), then Equation (5)

takes the form:

Css = Cout +

10

6

× G

Q

(7)

Therefore, as the ventilation rate increases, the steady-state CO2 concentration decreases.
9

Assuming the building or space begins the day at the outdoor CO2 concentration and is then

occupied, the indoor concentration will start to rise at a rate that depends on the building

ventilation rate Q divided by the building volume V. This quantity, Q/V, is sometimes referred to

as the outdoor air change rate of the building, while its inverse V/Q is sometimes referred to as

the time constant of the system. During this build-up, the indoor CO2 concentration is governed

by the transient solution to Equation (4):

C(t) = Cout +

G

Q

1−e

−Qt

V

















(8)

Note that as t approaches infinity, the concentration C approaches the steady-value given in

Equation (5) as expected. It is also important to note that the time required to reach steady-state

depends on the value of Q/V, with higher values (higher air change rates) corresponding to less

time required to approach steady-state. Figure 3 is a plot of the build-up in indoor CO2

concentration, calculated from Equation (8), for different air change rates. Figure 3 is based on a

generation rate of 0.0052 L/s (0.011 cfm) per person and an outdoor concentration of 630 mg/m

3

(350 ppm(v))

Figure 3 Calculated Carbon Dioxide Build-up as a Function of Air Change Rate

Figure 3 depicts the time required for indoor CO2 to reach steady-state concentration. Somehave

identified this delay as a problem with the application of CO2 demand controlled ventilation.

However, since DCV need not be based on the relationship between steady-state CO2 levels and

ventilation rates, this buildup time is not a problem.

0

500

1000

1500

2000

2500

3000

3500

4000

0 1 2 3 4 5 6 7 8 9 10

Time (h)

0

500

1000

1500

2000

2500

(p

p

m(v))

0.25 h

-1

0.50 h

-1

0.75 h

-1

1.0 h

-1

1.5 h

-1

2.0 h

-1
10

Carbon Dioxide Control versus Ventilation Control

Some discussions, and criticisms, of CO2 demand controlled ventilation are based on the

inadequacy of CO2 as an overall indicator of indoor air quality. This limitation has been noted

above and is based on many important contaminants not being generated on a per-person basis,

for example, building materials. However, the application of CO2 DCV is better understood

based on its use as an indicator of ventilation rate per person. Specifically, the control approach

is more appropriately based on the desire to maintain a specific outdoor airflow rate per person

based on a building code or ventilation standard. If the ventilation rate per person is lower than

desired, the CO2 level will build up above its setpoint, or at a rate that is recognized as high, and

the control system will need to respond by increasing the ventilation rate. If the ventilation rate is

higher than required based on the design value of outdoor air per person, the CO2 level will be

lower than the target and the control system can respond by decreasing the ventilation rate. That

decrease is the mechanism by which CO2 DCV realizes energy savings. However, the control

system need not wait for the CO2 level to reach its steady-state value to make this decision.

Control algorithms can be employed that anticipate where the CO2 level is headed and make

adjustments to the ventilation rate well in advance of steady-state conditions. Furthermore, since

other indoor contaminants buildup over time rather than instantaneously, CO2 control can be

used to take advantage of this transient effect by lagging the start of ventilation for a period of

time, thereby realizing additional energy savings. Therefore, it is important to realize that CO2

DCV uses indoor carbon dioxide to control ventilation and that the objective is not simply to

control the indoor CO2 level.
11

3. LITERATURE REVIEW

In the last fifteen years, interest in CO2-based DCV has led to a large body of literature published

in journals, conference proceedings, and other forums. An extensive literature review (Raatschen

1990) covering all aspects of demand controlled ventilation, including non-CO2-based systems,

was published at the conclusion of Annex 18, an International Energy Agency effort to develop

guidelines for DCV systems. This supercedes a more limited review published during Annex 18

by Mansson (1989). The increasing interest in DCV in the U.S. is evidenced by recent articles

published in several trade journals (Wright 1997; Di Giacomo 1999; Schell and Int-Hout 2001;

and Schell 2001). The objective of this section, which is an update of an earlier report

(Emmerich and Persily 1997), is to summarize the literature on CO2-based DCV as applied to

non-residential buildings.

Literature reports on CO2-based DCV are categorized in this paper as follows: Case StudiesField Tests; Case Studies-Simulations; Sensor Performance and Location; and Application. The

first two categories include studies of the performance of CO2-based DCV systems in real

buildings and using computer models. The various case studies that have been conducted focus

on issues including ventilation rates, energy consumption, economic impacts and the

concentrations of other indoor pollutants, though few studies address all of these issues. The

third category includes reports that address the performance of CO2 sensors and where they

should be located in a space. The fourth category discusses the application of CO2-based DCV,

from very general descriptions to detailed discussions of control algorithms.

3.1 Case Studies-Field Tests

There have been many demonstration projects in which CO2-based DCV systems were installed

in buildings and some aspects of performance were monitored. These studies vary in many

respects, including the detail with which the DCV systems are described. Some reports contain

detailed descriptions of the DCV control algorithms, while others do not even report the setpoint.

The studies also vary in the impacts that were monitored, which have included fan operation,

damper position, indoor CO2 concentrations, ventilation rates, energy consumption, the

concentrations of other pollutants, and occupant perceptions of the indoor environment. Finally,

the studies have taken place in a variety of building types including offices, schools, auditoria

and retail stores.

The application of CO2-based DCV is often discussed with reference to office buildings, and

occasionally to conference rooms within office buildings. One of the earliest studies of CO2

control in an office building took place in Helsinki (Sodergren 1982). The outdoor air control

algorithm is not described, but the CO2 setpoint was 1260 mg/m

3

(700 ppm(v)). The CO2 control

system was compared to constant outdoor air and timer-based control, and 24-h plots of CO2

concentration are presented for each system. Measured concentrations of other pollutants and

interviews with occupants did not indicate any IAQ problems.

Davidge (1991) presents a demonstration project in a 30,000 m

2

(320,000 ft

2

) Canadian office

building. In this building, the system never reduced the ventilation rate because the outdoor

temperatures in the winter were never low enough to go off free-cooling. During the summer,

damper leakage was more than enough to control CO2. Davidge also studied a boardroom, where

supplemental ventilation was controlled alternatively by a light switch, a motion sensor and a

CO2 controller. In the case of the CO2 controller, the fan came on at 1440 mg/m

3

(800 ppm(v))

and shut off at 1080 mg/m

3

(600 ppm(v)). An occupant questionnaire was administered, and it

was found that the occupants could not distinguish whether or not the fan was on in terms of air
12

quality. However, they rated the CO2 system very highly, presumably in terms of indoor air

quality though the report does not specify the survey results in any detail.

A fairly comprehensive study of CO2 control took place on two floors of an office building in

Montreal (Donnini et al. 1991, Haghighat and Donnini 1992). One floor was equipped with a

CO2 DCV system, while the other floor served as a control. The CO2 control algorithm was as

follows: the damper closed at concentrations below 1080 mg/m

3

(600 ppm(v)); as CO2 increased

above 600 ppm(v) the dampers opened with the maximum opening at 1800 mg/m

3

(1000 ppm(v)). The study lasted one year, during which indoor concentrations of CO2,

formaldehyde, volatile organic compounds and particles, ventilation system performance,

thermal comfort, and occupant perception were measured once a month. Energy demand was

monitored for the whole year. The outdoor air dampers were closed most of the year, because

there were rarely enough people to raise the indoor CO2 concentration. The indoor air quality

measurements revealed no significant contaminant concentration differences between the CO2

and the control floor. Thermal comfort was generally adequate on both floors. Annual energy

savings of 12 % were measured for the floor with DCV. Occupants of the DCV floor complained

significantly more about the indoor environment than occupants of the control floor.

Fleury (1992) reported on the performance of a CO2 controlled ventilation system in a

conference room. In this system, the fan motor speed was adjusted according to the CO2

concentration, but no information was provided on the specific control algorithm or setpoints.

The measured CO2 concentrations in the space were between 630 mg/m

3

(350 ppm(v)) to

1530 mg/m

3

(850 ppm(v)), with one peak of 1980 mg/m

3

(1100 ppm(v)). Based on occupant

questionnaires, the air quality was rated from good to excellent. Another study was undertaken in

a conference room set up to test DCV sensors, including CO2, volatile organic compounds and

humidity (Ruud et al. 1991). The CO2 setpoints were not reported, but the indoor concentration

never exceeded 1620 mg/m

3

(900 ppm(v)). Another demonstration in a conference room is

reported by Huze et al. (1994). The ventilation rate was varied proportionally to the CO2

concentration within a 900 mg/m

3

(500 ppm(v)) band centered around 2160 mg/m

3

(1200 ppm(v)). Limited results presented include a sample of the CO2 level and control signal for

one day.

One of the most frequently cited demonstration projects took place in a small bank in Pasco,

Washington (Gabel et al. 1986). This study involved the measurement of energy consumption,

contaminant levels including nitrogen dioxide, formaldehyde, carbon monoxide and particulates,

and occupant response based on a questionnaire. The study design included monitoring over the

winter, spring and summer seasons, with one week of normal operation followed by one week of

CO2 control. The system’s economizer cycle operated normally throughout the test periods. They

found that with the CO2 control system setpoint at 1800 mg/m

3

(100 ppm(v)) to 2160 mg/m

3

(1200 ppm(v)), air leakage through the closed damper provided sufficient fresh air for typical

occupancy, which was only 10 % to 15 % of design. That is, the indoor CO2 level never rose to

the control setpoints. All measured contaminants were maintained below indoor standards. Based

on a curve fit of the measured energy consumption to outdoor temperature for the two modes of

outdoor air control, average energy savings of 7.8 % for heating and cooling in six climates

typical of Oregon and Washington were calculated. Based on the questionnaires, the occupants

could not detect differences between background CO2 levels of 540 mg/m

3

(300 ppm(v)) and

1800 mg/m

3

(100 ppm(v)). The occupants reported feeling warmer during DCV control,

although the measured indoor temperatures were no different.

Another frequently-cited study took place in a Minnesota high school (Janssen et al. 1982). The

ventilation system used CO2 and temperature to control outdoor air, and had separate dampers
13

for temperature and CO2 control. Indoor contaminants, energy and subjective response of

occupants were monitored. The measured energy savings were about 20 %. The occupant

questionnaire showed that the subjects felt warmer with increased CO2 concentrations. Another

study by the same group of researchers took place in a portion of a high school, which was

retrofitted with a CO2-controlled system (Woods et al. 1982). During the early months of 1980,

the system operated under alternate periods with conventional temperature control and with CO2

control. System performance was monitored, and the subjective responses of occupants were

obtained. The system contained a set of outdoor air dampers that were controlled based on the

CO2 concentration. These dampers modulated between fully closed and fully open damper

positions, with the low setpoint at 5400 mg/m

3

(3000 ppm(v)) and the high setpoint at

9000 mg/m

3

(5000 ppm(v)). The results indicated the potential for significant energy savings.

Occupants felt warmer when CO2 control operated despite the fact that there was no measurable

temperature difference with and without CO2 control.

A study of two Finnish public buildings, one of which had CO2 controlled ventilation, included

measurements of radon, particles and CO2 (Kulmala et al. 1984). No description of the CO2

control algorithm was reported. Daily energy savings were estimated at 13 % to 20 %.

In several of the studies cited so far, the indoor CO2 concentration was often not high enough for

the CO2 control system to operate. This may be due in part to the relatively low occupant density

in office buildings. The application of CO2-based DCV is usually viewed as better suited to

spaces where occupancy is more variable and where the peaks are associated with fairly high

occupancy. Auditoria are good examples of such spaces, and there have been several case studies

in these types of spaces. One such study took place in an auditorium with CO2 and timer control

of ventilation at the Swiss Federal Institute of Technology in Zurich (Fehlmann et al. 1993). The

measurements included system run time, energy use, climatic parameters and CO2 concentrations

under winter and summer conditions. In addition, an occupant questionnaire was administered.

The ventilation system had two stages of airflow capacity, with the first stage coming on at

1080 mg/m

3

(600 ppm(v)) and the second stage at 2340 mg/m

3

(1300 ppm(v)). The second stage

would turn off at 1980 mg/m

3

(1100 ppm(v)), and the first stage at 1080 mg/m

3

(600 ppm(v)).

With ventilation controlled by CO2, run time was 67 % of the run time with timer control in

summer and 75 % in winter. Energy consumption with CO2 control was 80 % less in summer

and 30 % less in winter. Questionnaire results indicated a higher perception of odors with CO2

control, especially in the summer. It was noted that the occupancy was very low compared to

design, only about 10 % to 20 %.

Zamboni et al. (1991) reported on field measurements in auditoria in Norway and Switzerland. In

the Norwegian building, the CO2 setpoint was 1800 mg/m

3

(1000 ppm(v)), and the reported

results include indoor temperature, CO2 concentration and age of air. In the Swiss building, there

was a two-stage controller with the first setpoint at 1350 mg/m

3

(750 ppm(v)) and the second at

2340 mg/m

3

(1300 ppm(v)). The researchers monitored energy consumption and indoor climate,

and administered occupant questionnaires. Heating energy was reduced by 15 % during one

week of testing in the winter and by 75 % in the summer. With CO2 control, there was less draft

but more odor in summer.

Several demonstration projects have been conducted in so-called public spaces, including retail

stores and recreational facilities, where occupancy is expected to be more variable and less

predictable. Potter and Booth (1994) report on the performance of CO2-based DCV systems in

eight public buildings. The authors note that the results point to some potential problems with

CO2 control, but many of the results are presented simply in the form of plots of indoor CO2

concentration versus time. In an office building and a swimming pool facility, the indoor
14

concentration never reached the CO2 setpoint. Building setpoints were variable and included

2250 mg/m

3

(1250 ppm(v)), 3960 mg/m

3

(2200 ppm(v)) and 4500 mg/m

3

(2500 ppm(v)). Based

on the results, the authors identify candidate building types for CO2 control as cinemas, theatres,

bingo and snooker establishments, educational lecture theatres, teaching labs, meeting rooms,

and retail premises. They considered the issues of maintenance and reliability, noting that no

controllers in the buildings were marked for calibration due date or the date of last service.

Another study of two public spaces took place in a social club and a cinema in England (Anon

1986). The control algorithm was not described, but the CO2 setpoints were usually between

1260 mg/m

3

(700 ppm(v)) and 1800 mg/m

3

(1000 ppm(v)). The measured fuel savings were

17 % in the club and 11 % at the cinema. Warren (1982) reports on tests of energy savings with

CO2 control in a theater and a retail store. Energy and cost savings estimates are based on short

term tests in the building, and the dependence of the savings on ventilation system design

parameters is discussed. The systems in the two buildings are not described in detail.

Chan et al. (1999) address the case of a lecture theater in Hong Kong where radon is known to be

of concern. They propose a DCV system controlled by both CO2 and radon measurements to

achieve acceptable IAQ while saving energy. Few details are presented.

Finally, Strindehag et al. (1990) and Strindehag and Norell (1991) reported on a number of

examples of how outdoor air intake can be controlled by CO2 in a conference room, an

auditorium, three offices and a school. The report contains descriptions of the buildings and the

CO2 sensors, and notes that the CO2 setpoint was 1080 mg/m

3

(600 ppm(v)). However, the

control algorithms are not described, and no specific performance indicators are discussed.

Satisfactory reliability of the system in the auditorium was reported after three years of

operation.

The studies cited here show that CO2 control has been demonstrated in a wide variety of building

types including offices, schools, and public. It is apparent in examining these studies that the

CO2 control algorithm is often not described in sufficient detail to understand the system; in fact,

some of the studies did not even report CO2 setpoints. In several of the demonstration projects,

the building occupancy was insufficient to raise the indoor CO2 concentration enough to activate

the CO2 control system. Several of the studies used occupant questionnaires to evaluate

performance, with inconsistent results. In some cases, the occupants perceived the indoor

environment with CO2 control positively. In other cases, there were more complaints,

specifically with regards to odor during CO2 control. Several studies noted a feeling of increased

warmth with elevated CO2 concentration despite the fact that the measured indoor temperatures

were no higher. When considering these reports of occupant response, it must be kept in mind

that the studies employed different questionnaires.

3.2 Case Studies-Simulations

As discussed above for field tests, the reported simulation case studies vary widely in both the

description of important parameters and discussion of results. Most studies have focused on the

potential energy savings of the CO2-based DCV systems, with CO2 concentrations reported as a

measure of IAQ performance. A few studies have calculated concentrations of other pollutants.

As with the field tests, the majority of the studies have involved office buildings, with others

examining schools, retail buildings, restaurants and auditoria. Another important issue in

simulations is the treatment of infiltration and interzone airflows, with most studies using

assumed rates and a few studies employing a multizone airflow model.
15

Recently, Brandemuehl and Braun (1999) investigated the energy impact of various

combinations of six economizer and DCV strategies (no economizer, dry bulb economizer, and

enthalpy economizer – each with and without DCV) for four types of buildings (office, large

retail store, school, and sit-down restaurant) in twenty U.S. climates (including Los Angeles and

Sacramento). Additional modeling assumptions included a CO2 setpoint of 1260 mg/m

3

(700 ppm(v)) above ambient, thermostat setup or setback at night, HVAC fan shutdown during

unoccupied hours, single-zone buildings with no infiltration, ventilation effectiveness of 0.85,

and minimum ventilation flows for non-DCV cases of 9.4 L/s (20 cfm) per person, 4.7 L/s

(10 cfm) per person, 7.1 L/s (15 cfm) per person, and 9.4 L/s (20 cfm) per person for the office,

retail, school, and restaurant cases, respectively. The DCV system resulted in significant

reductions in heating energy use for all buildings and climates. Heating energy use reductions

ranged from 40 % for the office to 100 % for the retail building (i.e., the solar and internal loads

supplied all necessary heat) in Sacramento and from 75 % for the office to 100 % for the retail

building in Los Angeles. The DCV system with enthalpy economizer required the least cooling

energy use for all building types and climates. However, in some cases, much of the cooling

energy reduction was due to the economizer, and use of DCV without an economizer can

actually increase cooling energy use for dry climates. Cooling energy reductions ranged from

about 10 % to 20 % for all buildings in Sacramento and Los Angeles. The authors also note that

the savings associated with DCV are very dependent on the occupancy schedule and its

relationship to the design occupancy used to set the fixed minimum ventilation rate of the base

case. Also, for some types of buildings, additional ventilation may be required to maintain other

contaminants at acceptable levels.

In an early report of a simulation study for an office, Knoespel et al. (1991) investigated the

application of a CO2-based DCV system to a two-zone office space with both constant air

volume (CAV) and variable air volume (VAV) HVAC systems. A multiple zone pollutant

transport model was used and a ventilation airflow controller model was developed as modules

for a transient thermal system simulation program (Klein 1994). Other existing modules of the

program were used to calculate building energy consumption. Infiltration to the main zone was

assumed constant at 0.2 h

-1

and an interzone flow of 12 L/s (24 cfm) from the main office to the

conference room was included when the HVAC system was on. Knoespel compared the

performance of six ventilation strategies including constant outdoor airflow at the ASHRAE

Standard 62-1989 prescribed flow of 10 L/s (20 cfm) per person, constant outdoor airflow at a

“typical” rate of 0.7 h

-1

, minimum outdoor airflow at the typical rate with a temperature-based

economizer, DCV with a step-flow control algorithm, DCV with step-flow control and a

temperature-based economizer, and DCV with on-off control. In the step-flow control algorithm,

the fraction of outdoor air in the circulation flow was changed in 20 % steps depending on

whether the measured CO2 concentration in either zone was above or below the specified limit.

On-off control employed an algorithm in which outdoor airflow is set at 100 % if the high CO2

setpoint is exceeded and at 0 % if the CO2 concentration drops below the low setpoint. The

setpoints used were 1440 mg/m

3

(800 ppm(v)) and 1800 mg/m

3

(1000 ppm(v)). Simulations

were performed for Miami, FL and Madison, WI. In Madison, the DCV strategies provided

acceptable control of CO2 levels with coil energy savings from 9 % to 28 % for CAV systems

and from 43 % to 46 % for VAV systems compared to the Standard 62-1989 prescribed rate

strategy. The savings for Miami were of similar absolute magnitude but smaller percentages.

These results did not include fan energy use. Compared to the economizer and constant outdoor

airflow strategies at typical rates, the DCV strategies resulted in similar energy use with better

control of CO2 concentrations for both CAV and VAV systems.
16

Emmerich et al. (1994) applied the model developed by Knoespel et al. (1991) to examine the

performance of DCV systems under less favorable conditions and to study the impact on nonoccupant generated pollutants. Emmerich used the same building, Madison location, and the

HVAC systems described above but varied the simulated conditions to include a pollutant

removal effectiveness as low as 0.5 and an occupant density up to 50 % greater than design. For

all cases examined, the DCV system reduced the annual cooling and heating loads from 4 % to

41 % while maintaining acceptable CO2 concentrations. In addition to requiring more energy

use, the constant outdoor airflow strategy resulted in CO2 levels above 1080 mg/m

3

(600 ppm(v))

for more than half of occupied hours for cases with poor pollutant removal effectiveness.

Emmerich also examined the impact of DCV on non-occupant generated pollutants by modeling

a constant source of a non-reactive pollutant located in the main office zone. Four ventilation

strategies were compared including constant outdoor air at a prescribed rate based on ASHRAE

Standard 62-1989, DCV with step control and setpoints of 1440 mg/m

3

(800 ppm(v)) and

1800 mg/m

3

(1000 ppm(v)), DCV with a constant minimum outdoor airflow rate of 2.5 L/s

(5 cfm) per person calculated using the multiple space method of ASHRAE Standard 62-1989,

and DCV with scheduled purges of 100 % outdoor air from 7:30 a.m. to 8:30 a.m. and 12:30

p.m. to 1:00 p.m. The non-occupant generated pollutant source strength was specified such that

the system with constant outdoor airflow rate just met a short-term limit of 2 ppm(v) and an 8-h

average limit of 1 ppm(v). (These concentrations cannot be converted to SI units, since this

generic contaminant is not associated with any specific molecular weight.) Emmerich found that

both the straight DCV and the DCV with minimum outdoor airflow rate failed to meet the

pollutant concentration limits for both the CAV and VAV systems, but the DCV with scheduled

purge strategy successfully limited the pollutant concentrations. The purge strategy increased

building heating and cooling loads over the straight DCV strategy but still reduced the loads by

17 % (CAV) and 25 % (VAV) compared to the constant outdoor airflow case. The success of the

purge strategy was attributed partially to the ability to schedule the purges when most needed.

In another study considering the effects of poor ventilation air mixing, Haghighat et al. (1993)

simulated the performance of a CO2-based DCV system in a large office building in Montreal.

The baseline ventilation system had a flow rate of 10 L/s (20 cfm) per person, and a mixing

parameter of 0.7 was used in the model. The DCV system used a minimum ventilation rate of

2.5 L/s (5 cfm) per person, and the ventilation rate was adjusted each hour to maintain a CO2

concentration of 1440 mg/m

3

(800 ppm(v)). Infiltration was 0.4 h

-1

with the HVAC system off

and 0.04 h

-1

with it on. Four cases of occupant density were examined. The DCV system saved

from 7 % to 15 % in energy use, 2 % to 6 % in energy cost, and 7 % to 17 % in peak demand

compared to a fixed ventilation rate strategy. In a follow-up study using the same office model

with different infiltration, operating hours and other assumptions, Zmeureanu and Haghighat

(1995) found energy consumption for the DCV system ranging from a 5 % decrease to a 2 %

increase. However, because of peak demand reductions, annual energy cost savings ranging from

3 % to 26 % were found.

Sorensen (1996) also describes simulations performed for a two-zone office with a conference

room. A unique aspect of this study is its focus on examining the short term dynamics of the

system by simulating a ten hour period with one second time steps and detailed modeling of the

HVAC system. A VAV system with dual temperature and CO2 control and CAV system without

CO2 control are simulated. Because a detailed VAV system model is used, the control algorithm

is more complex than in most studies reviewed and involves both dampers and fans. When the

CO2 concentration is above an upper limit of 1620 mg/m

3

(900 ppm(v)), the damper actuator

position increases by 1 %. If the concentration remains above the upper limit, the position

continues to increase until it is fully open or until it drops below the limit. After the damper is
17

fully open, a concentration above the upper limit will increase the fan speed by 5 % until the fan

reaches maximum speed or the concentration falls below the limit. The algorithm also uses a

lower limit of 1260 mg/m

3

(700 ppm(v)) to decrease fan speed and damper position. Detailed

results are not presented, but transient CO2 concentrations and temperatures are presented and it

is stated that the VAV system used 31 % less energy than the CAV system for a cold ambient

condition.

Another recent study of office applications (Carpenter 1996 and Enermodal 1995) examined both

the energy and IAQ impacts of CO2-based DCV in a mid-sized commercial building complying

with ASHRAE Standard 90.1 in four climate zones (Chicago, Nashville, Phoenix, and Miami).

Simulations were performed using a combination of an energy analysis program (Enermodal

1990) and the multizone pollutant transport program CONTAM87 (Axley 1988). Three HVAC

systems (single-zone, multizone, and VAV) and 5 ventilation control strategies (fixed ventilation

rate, DCV with building return air controlled to 1800 mg/m

3

(1000 ppm(v))and 1440 mg/m

3

(800 ppm(v)), DCV with floor return controlled to 1000 ppm(v), and DCV with each zone

controlled to 1800 mg/m

3

(1000 ppm(v)) were analyzed. The DCV control algorithm was not

described in detail. For single-zone systems, the DCV strategy reduced heating energy by about

30 % for a setpoint of 1800 mg/m

3

(1000 ppm(v)) and by 20 % for a setpoint of 1440 mg/m

3

(800 ppm(v)). The DCV system with a setpoint of 800 ppm(v) also reduced average CO2

concentrations by 90 mg/m

3

(50 ppm(v)) to 160 mg/m

3

(90 ppm(v)) compared to the fixed

ventilation rate strategy. The DCV strategies had little effect on cooling energy, because the

DCV system tended to reduce ventilation during the cooler morning and evening hours and

increase ventilation during the warmer middle of the day. For VAV systems, the energy savings

were similar to those with single-zone systems. For multizone systems, the reduction in heating

energy was similar in absolute terms but was smaller in percent (5 % to 12 %) because of a

larger total heating load. DCV with a setpoint of 1800 mg/m

3

(1000 ppm(v)) resulted in average

CO2 concentrations 130 mg/m

3

(70 ppm(v)) to 270 mg/m

3

(150 ppm(v)) higher than the fixed

ventilation strategy, while a setpoint of 1440 mg/m

3

(800 ppm(v)) kept concentrations lower than

the fixed strategy and the maximum below 1800 mg/m

3

(1000 ppm(v)) in all zones. Providing

additional sensors in return duct of each floor had little impact on energy use and IAQ. Installing

sensors in each zone ensured that the concentration in each zone stayed below 1800 mg/m

3

(1000 ppm(v)) but at a slightly higher energy use. The performance of DCV with sensors set at

1800 mg/m

3

(1000 ppm(v)) in each zone was similar to central control with a setpoint of

1440 mg/m

3

(800 ppm(v)). Formaldehyde concentrations were also simulated to evaluate the

impact of DCV strategies on pollution from a non-occupant source. None of the DCV strategies

controlled the formaldehyde concentrations as well as the fixed ventilation strategy. It was

suggested that a morning purge should be included in a DCV strategy when non-occupant

generated pollutants are a concern, but this option was not simulated. Different DCV control

algorithms including on-off, linear proportional, proportional-integral-derivative (PID), and the

Vaculik method (discussed later in this paper) were discussed but not simulated.

Wang and Jin (1998) also simulate the performance of CO2-based DCV for an office with a

focus on describing and evaluating a control algorithm that can adjust ventilation rates based on

estimated occupancy. Three different occupancy estimation algorithms (steady state,

approximate dynamic detection, and exact dynamic detection) were compared for a single wellmixed zone with three different occupant densities and patterns. Both dynamic detection

methods detected occupancy with high accuracy and the change of occupancy with a fast

response time. Later, Wang and Jin (1999) experimentally verified the capability of the

algorithms.
18

Wang and Jin then performed simulations to compare the IAQ and energy performance of four

ventilation strategies (DCV using approximate dynamic detection algorithm, DCV with a CO2

upper limit of 1800 mg/m

3

(1000 ppm(v)), DCV with CO2 upper limit of 1800 mg/m

3

(1000 ppm(v)) upper limit and 1440 mg/m

3

(800 ppm(v)) lower limit, and constant outdoor air)

for an eight-zone open-plan office with two different occupant densities. The office had a

combination of CAV and VAV ventilation systems. Simulations were performed for single days

of summer and spring Hong Kong weather. The study found the two DCV systems based on

direct CO2 measurement were able to control CO2 levels as well as the occupancy detection

method but could not maintain constant ventilation rates per occupant. Unfortunately, the CO2

concentrations results indicate a potential major flaw in the model assumptions. At the end of the

day, the ventilation system is turned off and there is no infiltration overnight resulting in initial

CO2 concentrations of 1440 mg/m

3

(800 ppm(v)) to 1800 mg/m

3

(1000 ppm(v)). This

assumption masks likely significant differences in system performance during the morning hours

as CO2 concentration increases from background levels. Also, the authors conclude that this

would result in inadequate indoor air quality but provide no justification. Compared to the

constant ventilation strategy, all three DCV strategies were found to reduce coil loads about 8 %

for spring weather and from 12 % to 18 % for summer weather.

Meckler (1994) also simulated the application of CO2-based DCV in an office building. The

energy performance of an idealized DCV system with the ventilation rate varied to maintain

1440 mg/m

3

(800 ppm(v)) and 1660 mg/m

3

(920 ppm(v)) (i.e., no control algorithm modeled)

was compared to a baseline system with a constant ventilation rate of 10 L/s (20 cfm) per person.

The office building has ten floors with two outdoor air handling units for each floor, a central

hydronic heating and cooling plant, and an economizer. Both energy and economic impacts are

presented for five U.S. cities (Miami, Atlanta, Washington, D.C., New York, and Chicago).

Reported energy savings ranged from less than 1 % to 3 % for electricity and from 16 % to 22 %

for gas. Payback periods of 1.5 years to 2.2 years were estimated for all cities.

In a recent study with a focus on humid climates, Shirey and Rengarajan (1996) simulated the

impact of a CO2-based DCV system in a 400 m

2

(4000 ft

2

) office located in Miami, Orlando, and

Jacksonville to examine the impacts of ASHRAE Standard 62-1989 ventilation rates on indoor

humidity levels. The baseline system, a conventional direct expansion (DX) air-conditioning

system with a sensible heat ratio (SHR) of 0.78, was unable to keep the indoor humidity below

the target of 60 % relative humidity (RH) when the ventilation rate was increased from 2.5 L/s to

10 L/s (5 cfm to 20 cfm) per person. System modifications considered included a low-SHR DX

air-conditioner, a high efficiency low-SHR air-conditioner, a conventional air-conditioner with

CO2-based DCV, a conventional air-conditioner with an enthalpy recovery wheel, a heat pipe

assisted air-conditioner, and a conventional air-conditioner with a separate 100 % outdoor air DX

unit. The operation of the DCV system was simulated by matching ventilation rates to occupancy

profiles. Four alternative systems (DCV, enthalpy wheel, heat pipe, and 100 % outdoor air DX

unit) maintained acceptable humidity levels for greater than 97 % of occupied hours. Of the

systems with acceptable humidity performance, only the DCV and enthalpy wheel options did so

with less than 5 % increases in annual HVAC energy use compared to the conventional system

with a ventilation rate of 2.5 L/s (5 cfm) per person. The DCV system also significantly lowered

the peak heating demand in Orlando and Jacksonville. An economic analysis showed that the

DCV system resulted in annual HVAC operating cost increases of 7 % or less, first cost

increases of about 14 %, and life cycle cost increases of about 12 % compared to the system with

2.5 L/s (5 cfm) per person. A case with high internal loads was also examined, with the DCV and

enthalpy wheel systems again resulting in the best performance for the smallest increases in cost.
19

In a recent follow-up study, Davanagere et al. (1997) applied the same methodology with many

of the same assumptions as Shirey and Rengarajan (1996) to study HVAC system options

including CO2-based DCV in a Florida school. As in the previous study, the baseline for

comparisons was a conventional system with ventilation as required by ASHRAE Standard 62-

1981. In addition to DCV, the options simulated included the conventional system with

ASHRAE Standard 62-1989 ventilation rates and various combinations of pretreating outdoor

air, thermal energy storage, enthalpy recovery wheels, gas-fired desiccant systems, and cold air

distribution systems. Results reported included energy use, humidity levels, first costs and lifecycle costs. In general, the DCV system resulted in the smallest or close to the smallest increases

in energy costs and installed first costs compared to the baseline system. The thermal energy

storage system options generally resulted in the smallest increases (or even decreases) in peak

cooling demands and life-cycle costs. DCV was the only option that reduced peak heating

demands. Although the DCV system reduced humidity levels compared to the baseline system,

many of the other simulated options controlled humidity better.

Nakahara (1996) also discusses a simulation of DCV in a school building with an emphasis on

multiple zones and the potential benefit of zoning the ventilation system based on the level of

CO2 demand instead of based on room position. However, little detail is provided on the model,

and the baseline for the resulting potential thermal load reduction of 46 % is not clearly defined.

In addition to offices and schools, public spaces have also been the subject of DCV simulation

studies. Warren and Harper (1991) evaluated the potential heating energy savings for a CO2-

based DCV system applied to an auditorium in London. Energy simulations were performed

using a building energy analysis program (Clarke and McLean 1986) with ventilation rates

calculated separately based on occupancy profiles. Assumptions included CO2 generation of

4.7 x 10

-6 m3

/s (1.7 x 10

-4

ft

3

/s) per person, auditorium volume of 11,150 m

3

(406,000 ft

3

), high

CO2 setpoint of 1800 mg/m

3

(1000 ppm(v)), peak daily occupancy of 629, and infiltration rate of

0.4 h

-1

. Three ventilation scenarios were compared including 100 % outdoor airflow at a rate of

5,020 L/s (10,000 cfm), DCV with a minimum outdoor airflow rate of 3,770 L/s (7,500 cfm), and

DCV with no minimum. The DCV with minimum outdoor airflow rate rarely exceeded the

minimum rate to maintain CO2 concentrations below 1800 mg/m

3

(1000 ppm(v)) and saved

26.4 % in heating energy use compared to the 100 % outdoor airflow case. The DCV with no

minimum saved 53.3 %.

Ogasawara et al. (1979) evaluated the potential energy savings for a DCV system in a 30,000 m

2

(320,000 ft

2

) department store in Tokyo, Japan. Three ventilation strategies were compared

including fixed outdoor air at design rate, manual control with maximum ventilation on Sundays

(the busiest day) and half of that on weekdays, and DCV. The DCV algorithm used was

proportional control with a closed damper at 1440 mg/m

3

(800 ppm(v)) and a fully open damper

at 1800 mg/m

3

(1000 ppm(v)). Infiltration assumptions were not specified. Energy use was

calculated for 4 cooling months and 4 heating months. The DCV system reduced energy use by

40 % for the cooling season and by 30 % for the heating season. An economic analysis showed

an advantage for the DCV system.

Feher and Ambs (1997) reported a study in which measurements of CO2 concentrations in a

school building were used to estimate occupancy and to simulate operation of a DCV system.

Four independent zones of the school building, which had recently had the outdoor airflow rate

increased above design by 50 %, were included in the energy simulations. PID control was

simulated although it was concluded that there was little additional benefit compared to

proportional control. No infiltration, interzonal airflow, or air change effectiveness parameters

were included in the model. A minimum outdoor airflow of 1 h

-1

was provided. Annual HVAC
20

energy savings compared to the original design rates were estimated to range from 3 % for the

classroom zone up to 17 % for the auditorium zone depending on the control approach.

In a very unique application, Dounis et al. (1996) investigated the potential application of CO2-

based DCV to control ventilation rates for a building with natural ventilation. Simulations were

performed in which window opening was adjusted based on measured CO2 concentrations. Due

to concerns over the constant variation of natural ventilation driving forces, fuzzy logic was used

instead of conventional on-off or PID control. Carbon dioxide concentrations, window openings,

and air temperatures are presented for a simulated day. Although performance was not as good as

expected, the authors conclude that the feasibility of such a system was demonstrated.

The simulation case studies reviewed indicated energy savings for DCV systems between 4 %

and over 50 % compared to ASHRAE Standard 62-1989 or other design ventilation rates. The

energy savings varied widely depending on type of building, control algorithm, building

location, assumed occupancy and other assumptions. No parametric or sensitivity analysis has

been performed to determine which variables have the most influence on potential energy

savings. Also, energy savings are reported with respect to different baseline cases in the different

studies. A small number of the studies examined peak demand, economic impacts, humidity and

concentrations of other pollutants. These studies verified the concern for increased

concentrations of non-occupant generated pollutants, and one study examined potential solutions

including scheduled purges. Shortcomings of most of the studies included inadequate treatment

of infiltration and interzone airflows and control algorithms.

3.3 Sensor Performance and Location

The performance of a CO2-based DCV system will clearly depend on the measured CO2

concentration as reported by the system sensors. Key issues related to these sensors are their

accuracy, reliability, and location in the building. This section discusses the research that has

been done on sensor performance and location.

Sensor Performance

In the most extensive report on sensor performance, Fahlen et al. (1991 and 1992) describe an

evaluation of the performance characteristics of two CO2, nine humidity, and five mixed-gas

sensors in both lab tests and long term field tests. The lab tests consisted of both performance

and environmental tests, while the field tests consisted of a repeat of the performance tests after

the sensors had been installed in the field for 11 months. The CO2 sensors displayed acceptable

performance for control purposes with a deviation of less than 50 mg/m

3

(30 ppm(v)) at a level

of 1800 mg/m

3

(1000 ppm(v)). However, the following problems were identified: timeconsuming calibration, sensitivity to humidity, and cross-sensitivity to voltage, temperature and

tobacco smoke. Characteristic curves comparing the sensor performance before and after the

field trial are presented. At 1800 mg/m

3

(1000 ppm(v)), the deviation from the original result

was between 0 mg/m

3

(ppm(v)) and 180 mg/m

3

(100 ppm(v)).

Meier (1993) reports on the performance of two CO2 and 17 mixed-gas sensors in five different

facilities at the University of Zurich. Measurements of CO2, air quality units (AQU), and

occupancy are presented for one day in a restaurant. It is concluded that both mixed-gas and CO2

sensors are suitable for registering the occupancy level in the restaurant and can provide the

reference variable for DCV. The results of the mixed-gas sensors and CO2 sensors are compared,

but no conclusion is reached as to which sensor type is more suitable.

Recently, Okamoto et al. (1996) described the development and field testing of a CO2 sensor

employing solid-state electrolyte technology. The sensor is stated as having an accuracy of
21

± 20 % and acceptable sensitivity to temperature, humidity, and miscellaneous gases. However,

the basis of the statements (i.e., laboratory test results) is not presented. Limited field tests of the

sensors in a school and two conference rooms are described. In these tests, the sensors were used

as monitors with low, medium and high setpoints of 1260 mg/m

3

(700 ppm(v)), 2520 mg/m

3

(1400 ppm(v)), and 4500 mg/m

3

(2500 ppm(v)) but were not used to control the ventilation

system directly.

Several other reports contain more limited discussion of CO2 sensor performance. The literature

review by Raatschen (1990) describes the various types of sensors available. The CO2 sensors

discussed use infrared absorption and are available as two types - photoacoustic and photometric.

No actual performance tests were conducted, but a summary of manufacturers’ data is provided.

Houghton (1995) also describes available sensor types; manufacturer’s specifications are

presented for five sensors available in the U.S. Issues of accuracy, drift, and temperature and

pressure sensitivity are also addressed, although no independent performance tests are reported.

Helenelund (1993) also discusses the various sensor options available for DCV systems but does

not report on their performance. Based on other published reports, interviews and obtained test

results, the suitability of various sensors for different types of facilities is presented from the

point of view of both technological and economical performance. In a field test, Sodergren

(1982) reported that the sensor calibration drifted from 180 mg/m

3

(100 ppm(v)) to 270 mg/m

3

(150 ppm(v)) during the study. In another field test, Ruud et al. (1991) found that one CO2 sensor

had to be connected to the supply voltage for several days before the output signal became

stable.

Sensor Location

In an experimental study aimed at determining the proper location for DCV sensors within a

room, Stymne et al. (1990) investigated the dispersion of CO2 from simulated people in a fourroom test house. The following design factors were discussed: transfer of CO2 from the sources

to different locations (referred to as transfer probability), the expected equilibrium concentration

at a location, the rate constant of approaching equilibrium from a nonequilibrium state, and

concentration fluctuations. The total ventilation flow rate to the test house was varied between

two levels with the fraction to each room remaining constant. People were simulated by metallic

bodies heated by a 100 W lamp and emitting 0.0069 L/s (0.015 cfm) of CO2 mixed with

prewarmed air. Measurements were taken at 19 locations. Tracer gas measurements were also

performed. The measurements showed that good mixing was achieved in rooms with closed

doors, and therefore the sensor location is not critical. However, if a room is connected to other

spaces by open doors, large differences and instabilities in the CO2 concentration may occur. The

distribution pattern of the tracer gas was similarly nonuniform, indicating that the cause of the

distribution pattern is air movement through open doorways and its interaction with air

movement from the heated bodies, radiators, cold external walls, and the jet from the inlet duct.

It is recommended to place the DCV sensor at mid-height in a room and away from doorways,

radiators, windows, people and air inlet devices if possible. It is also recommended that the DCV

system have a large time constant in order not to react to the fluctuations in concentration due to

nonuniform distribution patterns.

In a follow-up study, Stymne et al. (1991) investigated the CO2 distribution pattern in an office

room with a displacement ventilation system. People were simulated by heated dummies

emitting tracer gas. Graphs of iso-concentration contours are presented for several cases. The

lack of normal disturbances such as body movements, breathing, heat sources, lighting, and solar

heat gain is mentioned as a limitation of the study. It is shown that pollutants emitted from the

‘people’ are transported to the upper mixed zone in the room and that pollutants emitted at a
22

small heat source or near the wall accumulate below the interface between the upper and lower

zones. The interface is displaced about 0.2 m (0.66 ft) upwards around the heated bodies,

ensuring the occupants better air quality than the surrounding air, even if they are above the

interface. A test with a mixing ventilation system showed a similar plume above the heated

dummies but no stratification outside the plume. It is concluded that DCV in a displacement

ventilated room is a suitable means of controlling the level of the interface between the

uncontaminated air in the upper zone and the polluted air in the lower zone. The sensors should

be located at the height of the occupants’ heads. Also, the setpoint should be lower than usual,

for example below 1440 mg/m

3

(800 ppm(v)), so that the DCV system will be activated.

A common alternative to locating DCV sensors in individual rooms is to locate them in the

ventilation system return ductwork. Reardon and Shaw (1993) and Reardon et al. (1994)

compared CO2 concentrations in the central return air shafts, individual floor return intakes, and

occupied space in a 22-story office building. Measurements showed that the individual floor

return grilles represented the spatial average concentrations in the occupied space, and that the

measurements at the top of the central return shafts represented the concentrations at the floor

return intakes. Therefore, it was concluded that the top of the return shafts is an appropriate

location for the sensors of a DCV system. However, the setpoint should be adjusted (lowered) to

account for variability in the occupied zones to avoid high local exposures.

Bearg (1994) also compares the merits of single and multiple point DCV systems. A system is

described with multiple sampling points and a single detector installed in a 5-story building. In

addition to operating the DCV system, advantages credited to the multipoint system include

identifying both leakages in the system and episodes of increased outdoor contamination such as

vehicle exhaust at a loading dock. Also, the use of a single detector ensures that differences in

measured concentrations for different sampling points are not due to calibration differences.

Such a system could also be automatically recalibrated with a known CO2 concentration.

Houghton (1995) discusses this multipoint system including its accuracy and automatic

calibration advantages. However, the system is claimed to be more costly than a system with

multiple detectors and a central computer. Some data collected by the multipoint system is

presented.

Several other reports briefly discuss sensor location issues. In another field test, Sodergren

(1982) presented graphs of the CO2 concentration at multiple locations in an office but did not

make specific recommendations on sensor location. In a test in a conference room, Ruud et al.

(1991) found that concentrations measured at the wall and in the exhaust air were nearly

identical with the wall-mounted sensor having a 2-min delay compared to the exhaust air. In a

simulation study of a DCV system applied to an office building with floors having different

occupant densities, Enermodal (1995) found that a system with sensors in the return duct of each

floor had little impact on IAQ and energy use compared to a system with a sensor in the central

return. Installing sensors in each zone ensured CO2 concentrations below 1800 mg/m

3

(1000 ppm(v)) (the setpoint) in all zones and increased energy use slightly, but at a higher

installation cost due to the additional sensors. Central control with a setpoint of 1440 mg/m

3

(800 ppm(v)) offered similar performance to individual zone control with a setpoint of 1800

mg/m

3

(1000 ppm(v)), but at a much lower installation cost.

Although many DCV studies have touched on the subjects of sensor performance and location,

only a few have examined these issues in detail. In general, sensor performance characteristics

have been found to be adequate for controlling a DCV system although concerns about

calibration and sensitivity to humidity and temperature have been expressed. Sensor calibration

concerns are being addressed by either use of a second detector tuned to a wavelength that isn’t
23

absorbed by CO2 to provide a reference value to correct for sensor drift over time or “selfcalibrating” by checking the CO2 level at night when indoor concentrations are expected to drop

to outdoor levels (Schell and Int-Hout 2001). Contradicting opinions on sensor location have

been expressed with some studies advocating a system with a single central measurement in the

HVAC return system and others preferring a system with multiple measurement points.

3.4 Application

In addition to the studies of the performance of CO2-based DCV systems, there have also been a

growing number of reports that describe how to apply these systems. These reports range from

general descriptions of CO2-based DCV to detailed descriptions of control algorithms. This

section reviews a number of these reports.

One of the earliest discussions of using CO2 to control outdoor air intake as a means of saving

energy was presented by Kusuda (1976). This paper presented some of the theoretical

background of how indoor CO2 concentrations vary as a ventilation system is turned on and off.

Sample calculations showed potential energy savings of 40 % for an office space. Another early

discussion of the energy savings potential of CO2 control was presented by Turiel et al. (1979).

This paper discussed a number of DCV control options including water vapor and concluded that

CO2 control appeared to be the most satisfactory approach.

Recently, one of the more detailed discussions of the application of DCV was reported by Schell

et al. 1998. DCV topics covered include potential energy savings with DCV, determining

locations for CO2 sensors, control strategies (including setpoint, proportional, and exponential or

PID), consideration of outdoor levels of CO2, estimation of building ventilation rates using CO2,

models for selection of DCV strategy, and benefits of DCV. Additionally, Schell et al. discuss

applying CO2-based DCV in compliance with ASHRAE Standard 62-1989 (ASHRAE 1990).

A general discussion of the principles of DCV in office buildings is presented by Davidge (1991)

and Houghton (1995). These papers discuss the circumstances under which DCV might be

expected to be most effective including the existence of unpredictable variations in occupancy, a

building and climate where heating or cooling is required for most of the year, and low pollutant

emissions from non-occupant sources. Davidge points out that when such a system is considered,

one must address the base ventilation rate that is not controlled by DCV in order to control these

non-occupant pollutant sources. The impact of free cooling on DCV systems is also discussed,

noting that long periods of free cooling will reduce the potential energy savings. The potential

for purge ventilation, both before and after occupancy, to control non-occupant sources is also

discussed.

Similar discussions of the application of CO2-based DCV are presented by Houghton (1995) and

in an application guide published by Telaire (n.d.). These publications contain background

information on CO2 control of ventilation and describe the potential energy savings benefits.

Strategies for the use of CO2-based DCV are also described including simple setpoint control

where the outdoor air intake damper is either open or closed depending on the indoor CO2

concentration, proportional control in which the intake damper or outdoor air fan flow is

proportional to the CO2 concentration, and PID (proportional-integral-derivative) control which

considers the rate of change in the CO2 concentration. Recommendations are made on the

application of these techniques based on the occupancy level.

Descriptions of specific control algorithms are presented by Vaculik and Plett (1993), Federspiel

(1996), Bjorsell (1996), and the Telaire application guide (n.d.). In their paper, Vaculik and Plett

discuss the principles of CO2-based DCV including setpoint and proportional control. They then
24

describe a control approach that accounts for differences between CO2 concentration at the

measurement location and the critical location in the building and in which the control setpoint is

adjusted to account for differences between the measured concentration and the setpoint.

Federspiel (1996) also reports on a control algorithm, referred to as On-Demand Ventilation

Control (ODVC), and presents a simple simulation to demonstrate its performance. The ODVC

strategy attempts to set the ventilation rate proportional to the occupant density even under

transient conditions by using a well-mixed single zone model to estimate the current CO2

generation rate from measured concentrations and airflows. A simple example is presented to

show the ODVC strategy controls the CO2 concentration below 1800 mg/m

3

(1000 ppm(v)) by

reacting quickly to a step change in occupancy, while a strategy of PI control of measured CO2

concentration allows CO2 to overshoot the setpoint value. Issues regarding the impact on energy

use and the potential effect of well-mixed single zone model inadequacies are not addressed. Ke

and Mumma (1997) and Wang and Jin (1998) describe similar algorithms.

Bjorsell (1996) also focuses on the description and simulation of a DCV control algorithm,

presenting a simple simulation example. The control algorithm, called Linear Quadratic, attempts

to calculate the optimal system flow to minimize a cost function that depends on concentration

and ventilation flow. However, the cost function is not specified and, although the control

method may be optimal with respect to a given cost function, it also depends on all physical data

being known and may not be practical to implement.

As mentioned earlier in the sections on field and simulation cases studies, a variety of control

setpoints have been used, and many descriptions of the application of CO2 control contain only

limited discussion of how to determine the appropriate setpoint. Schultz and Krafthefer (1993)

present a method for determining a CO2 setpoint based on the Indoor Air Quality procedure in

ASHRAE Standard 62. This method employs a two-zone model of the ventilated space and

considers the ventilation efficiency of the space. Nomographs are presented for use in

determining the CO2 setpoints.

The use of CO2 control of outdoor air is discussed relative to other approaches of outdoor air

control in papers by Elovitz (1995) and by Janu et al. (1995). Elovitz discusses various options

for controlling minimum outdoor air intake rates in VAV systems including: sequencing supply

and return fans; controlling return or relief fans based on building pressure; measuring outdoor

air intake rates directly; fan tracking; controlling the pressure in the intake plenum; outdoor air

injection fans; and, CO2 control. Advantages and disadvantages of each approach are discussed.

Elovitz points out that CO2 control does not necessarily assure satisfactory indoor air quality,

depending on the existence and strength of contaminant sources that are not proportional to the

number of occupants. Janu et al. (1995) discuss some of the same methods of outdoor airflow

control and raise the same cautions regarding CO2 control and non-occupant contaminant

sources.

In addition to a general discussion of DCV, Meier (1995) reports a sensitivity analysis on

parameters affecting the payback period for modifying a conventional ventilation system to add

DCV capability. Although few details of the calculation are presented, the total airflow rate is

reported as the most significant parameter determining payback period. However, operating

hours were also found to be significant. More recently, Meier (1998) provided estimated

potential energy-cost savings for a range of DCV applications based on case studies and

experiences of control companies. These estimates and additional ones from Mansson (1994) are

presented in Table 2. Mansson provides background information on CO2 DCV systems,

discusses strategies for base and variable ventilation rates based on application type, and presents
25

a six-step flowchart for determining the feasibility of DCV for an application. As expected, the

energy savings in Table 2 are largest for high density spaces with generally variable occupancy,

such as the various halls, theatres and cinemas. The lowest savings are seen in the office spaces,

which generally have lower occupancy densities with less variation than the other spaces.

Application Energy-cost savings range

Schools 20 % to 40 %

Day nurseries 20 % to 30 %

Restaurants, canteens 20 % to 50 %

Lecture halls 20 % to 50 %

Open-plan offices (40 % average occupancy) 20 % to 30 %

Open-plan offices (90 % average occupancy) 3 % to 5 %

Entrance halls, booking halls, airport check-in areas 20 % to 60 %

Exhibition halls, sports halls 40 % to 70 %

Assembly halls, theatres, cinemas 20 % to 60 %

Table 2 Estimated energy-cost savings from DCV (Meier 1998 and Mansson 1994)

3.5 Summary and Conclusions

This literature review has described the research into the application of CO2-based DCV. It has

covered case studies conducted in the field and through computer simulation, research on

sensors, and discussions of the application of CO2 control. This section summarizes a number of

findings of the literature review and identifies research needs. Table 3 summarizes the literature

reviewed in terms of the type of report and topics addressed.

There is fairly wide consensus on the best applications for CO2 control. Most discussions of

CO2-based DCV mention the following building types as good candidates: public buildings such

as cinemas, theaters and auditoria, educational facilities such as classrooms and lecture halls,

meeting rooms, and retail and restaurant establishments. However, it is interesting to note that

most of the case studies have investigated office buildings. As presented by Davidge (1991), the

following building features correspond to situations where CO2-based DCV are most likely to be

effective:

• the existence of unpredictable variations in occupancy

• a building and climate where heating or cooling is required for most of the year

• low pollutant emissions from non-occupant sources.

There have been a number of valuable demonstration projects in real buildings, and many of

these have shown significant energy savings through the use of CO2 control. However, several

cases exist where the indoor CO2 concentration was rarely high enough for the outdoor air intake

dampers to open, suggesting a mismatch between building occupancy, ventilation rates, and

control algorithms and setpoints. A significant shortcoming of several of the field tests, as well

as of the computer simulation studies, was the inclusion of little or no description of the CO2

sensors or control algorithm investigated in the study. These omissions make it difficult to

evaluate which approaches work best and under what circumstances.
26

While CO2 DCV can control occupant-generated contaminants effectively, it may not control

contaminants with non-occupant sources as well. The control of such non-occupant sources, such

as some building materials and outdoor air pollution, is a difficult issue because one cannot

engineer for these sources unless their source strengths and indoor concentration limits are

known. However, this information is not readily available for most contaminants and sources. A

practical solution is to maintain a base ventilation rate at all times, which can be proportional to

floor area. A morning purge with outdoor air may also be a good strategy for controlling the

buildup of these contaminants over night, and it may be equally applicable to non-DCV systems.

An outdoor air purge cycle during the day is another option for controlling non-occupant

sources.

The research on sensors indicates that currently available technology is adequate for use in these

systems. Some questions have been raised regarding calibration frequency, drift, and temperature

effects but new calibration methods have been developed to address these concerns. There is still

some debate regarding sensor location, in particular whether to use a single sensor centrally

located in the system return or multiple sensors located in the returns for whole floors or in

critical spaces, such as conference rooms. Whenever a central location is suggested, the issue of

variability among spaces is almost always mentioned. Using a lower setpoint with a central

sensor is often suggested as one means of dealing with the variability issue.

A number of needs for more research and information were identified in this literature review.

For example, more system-specific guidance on application of CO2-based DCV is needed. This

guidance should be based on system type, zoning, and expected variations in occupancy patterns

among the zones. The factors that impact energy savings and other performance issues are

becoming better understood, but more sensitivity analysis would be helpful. As mentioned in the

literature review, it would still be extremely useful to investigate more CO2-based DCV

installations and document them in terms of design and performance. Another issue meriting

attention are the positive benefits of using CO2-based DCV to maintain ventilation rates at design

levels that help to guarantee sufficient ventilation to occupants, as opposed to its use to using

CO2 control to reduce ventilation rates.
27

Field test

Simulation

Sensor performance

Sensor location

Application

Energy

IAQ

Economic

Control algorithm

Office

School

Conference room

Other

Anon. 1986 X X X

Bearg 1994 X X

Bjorsell 1996 X X

Brandemuehl and Braun 1999 X X X X X

Carpenter 1996/Enermodal 1995 X X X X X X

Chan et al. 1999 X X X

Davanagere et al. 1997 X X X X X

Davidge 1991 X X X X X

Donnini et al. 1991 and

Haghighat and Donnini 1992 X X X X X

Dounis et al. 1996 X X X

Elovitz 1995 X

Emmerich et al. 1994 X X X X X

Fahlen et al. 1991 and 1992 X X

Federspiel 1996 X X X

Feher and Ambs 1997 X X X X

Fehlmann et al. 1993 X X X X

Fleury 1992 X X X

Gabel et al. 1986 X X X X

Haghighat et al. 1993 and

Zmeureanu and Haghighat 1995 X X X X

Helenelund 1993 X

Houghton 1995 X X

Huze et al. 1994 X X

Janssen et al. 1982 and

Woods et al.1982 X X X X

Janu et al. 1995 X

Ke and Mumma 1997 X

Knoespel et al. 1991 X X X X X

Kulmala et al. 1984 X X X

Kusuda 1976 X X X X

Mansson 1994 X X

Meckler 1994 X X X X

Meier 1993 X

Meier 1995 and 1998 X X X X X X X

Nakahara 1996 X X X

Ogasawara 1979 X X X X

Okamoto et al. 1996 X

Potter and Booth 1994 X X X

Raatschen 1990 X X

Reardon and Shaw 1993 and

Reardon et al. 1994 X

Ruud et al. 1991 X X X

Schell et al. 1998 and

Schell and Int-Hout 2001 X X X X X

Schultz and Krafthefer 1993 X

Shirey and Rengarajan 1996 X X X X X

Sodergren 1982 X X X X X

Sorensen 1996 X X X X X

Strindehag et al. 1990 X X X X

Stymne et al. 1990 and

Stymne et al. 1991 X X

Telaire Systems, Inc X X

Turiel et al. 1979 X X

Vaculik and Plett 1993 X X X

Wang and Jin 1998 X X X X X X

Warren 1982 X X X

Warren and Harper 1991 X X X

Zamboni et al. 1991 X X X X

Table 3 Summary of Literature Review
28

4. TECHNOLOGY UPDATE: SENSORS

The only technologies unique to the application of carbon dioxide demand controlled ventilation

are the CO2 sensors themselves. The remaining control hardware and software (including

algorithms) are common with other HVAC control applications. This section covers only the

CO2 sensors, describing the available technology and some of the relevant performance issues.

Most major HVAC equipment manufacturers offer CO2 demand controlled ventilation as an

option, though some highlight its use more than others. However, their application literature does

not generally focus on the CO2 sensing technology. Presumably these HVAC manufacturers are

using sensors manufactured by other firms.

Sensor manufacturers are definitely promoting the use of CO2 DCV and several of them provide

a good deal of technical information on the performance and application of their products.

However, there has not been a great deal of information published on CO2 sensing for control. A

recent article by Schell and Int-Hout (2001) provides a brief description of the sensing

technology. In addition, the International Energy Agency effort (Annex 18) that studied demand

control ventilation in general did perform limited testing of CO2 sensors (Fahlen et al. 1992).

There are basically two types of CO2 sensors used for ventilation control, photometric and

photoacoustic. Photometric sensors contain a light source that emits in the infrared range and an

optical filter that ensures only wavelengths in the absorbing spectrum of CO2 enter the cell

containing the air sample. A photodetector measures the light intensity at a wavelength that is

absorbed by CO2. The higher the CO2 concentration in the sample air, the lower the measured

light intensity. Photoacoustic sensors also employ an infrared light source with an optical filter.

The CO2 molecules in the cell absorb the infrared energy, which in turn increases the molecular

vibration and generates an acoustic field. A microphone picks up this field and converts it to an

electronic signal related to the CO2 concentration.

Some of the issues affecting sensor performance include interference from other gases (e.g.

water vapor), accuracy and drift. The various sensors on the market address these issues using

different strategies. Sensor drift arises due to aging of the light source or particle/dust buildup on

the optical components. Some sensors use a second detector tuned to a wavelength that isn’t

absorbed by CO2 to provide a reference value to correct for sensor drift over time. Another

approach is to protect the sensor with a gas permeable membrane to avoid contamination by dust.

Photoacoustic sensors are not as sensitive to dirt and dust, but are still subject to aging of the

light source. Some sensors check the CO2 level at night when indoor concentrations are expected

to drop to outdoors and “self-calibrate” to account for drift.

The IEA Annex 18 sensor testing effort included testing of only two CO2 sensors, one

photometric and another photoacoustic (Fahlen et al. 1992). The testing involved sensor response

as well as the impacts of temperature, mechanical vibration and electrical noise. While the

testing was limited to only two sensors, the study concluded that these sensors showed

acceptable performance for control but noted that calibration could be a time consuming process

based on the sensor rise times of around 10 min.

Sensor manufacturers are continually working to develop cheaper, more accurate and more

stable sensors. Their cost is driven to a large degree by the number of sensors that are

manufactured and sold. In 1998, prices ranged from around $400 to $500 per sensor, but have

decreased by about 50 % based on continued use (Schell and Int-Hout 2001). This trend is likely

to continue as their use expands further.
29

5. STANDARDS AND REGULATORY CONTEXT

Carbon dioxide demand controlled ventilation clearly must be applied in a manner that is

consistent with the relevant building codes and standards. This section discusses the standards

and regulatory context relevant to CO2 DCV, specifically ASHRAE Standard 62 and the

California Energy Efficiency Standards.

ASHRAE Standard 62

Before discussing CO2 DCV in the context of Standard 62, it is appropriate to address some

confusion that exists regarding the standard and indoor CO2 levels. For example, a common

misunderstanding exists that if indoor carbon dioxide concentrations in a building are maintained

below 1800 mg/m

3

(1000 ppm(v)) or within 1260 mg/m

3

(700 ppm(v)) of outdoors, then the

building is in compliance with ASHRAE Standard 62. ASHRAE Standard 62 contains two paths

to compliance, the Ventilation Rate Procedure and the Indoor Air Quality Procedure. The

Ventilation Rate Procedure requires that one determine the design ventilation rate of a building

based on the space-use in the building, the number of occupants and the outdoor air requirements

for various space-use categories in Table 2 of the standard. The Ventilation Rate Procedure also

contains requirements for contaminant levels in the outdoor air and that no unusual contaminants

or sources exist. While compliance with the Ventilation Rate Procedure is likely to maintain

indoor carbon dioxide concentrations within 1260 mg/m

3

(700 ppm(v)) of outdoors

(corresponding to about 1800 mg/m

3

(1000 ppm(v)) for typical outdoor CO2 concentrations), the

other requirements of the procedure must also be met to achieve compliance with the entire

standard.

The Indoor Air Quality Procedure of the 1989 version of the standard contained a guideline for

indoor carbon dioxide concentrations of 1800 mg/m

3

(1000 ppm(v)), but that guideline was

removed in the 1999 version. However, complying with this guideline alone was never sufficient

for achieving compliance with the standard. In addition to this carbon dioxide guideline, the IAQ

Procedure also contained and still contains limits for four other contaminants of predominantly

outdoor origin in Table 1 of the standard and three others in Table 3. In addition, one also must

to keep all other known contaminants of concern below specific levels. The Indoor Air Quality

Procedure also contains a requirement for the subjective evaluation of the acceptability of the

level of those contaminants for which no objective measures of acceptability are available. While

it may not be clear how one identifies these contaminants of concern and the associated levels of

acceptability, it is clear that simply maintaining carbon dioxide below 1800 mg/m

3

(1000 ppm(v)) is not sufficient.

That being said, let us now review how the standard does address the issue of CO2 demand

controlled ventilation. Section 6 of this standard, Procedures, provides the means of designing

building ventilation systems for achieving acceptable indoor air quality. Two procedures exist

for doing so, the Ventilation Rate Procedure and the Indoor Air Quality (IAQ) Procedure. The

former prescribes minimum outdoor air ventilation requirements for a number of different space

types, expressed as (L/s) cfm per person, (L/s-m

2

) cfm/ft

2

of floor area or cfm (L/s) per room,

with the units depending on the space type. The standard does not specifically discuss the

application of demand-controlled ventilation, however, it is quite logical to apply this approach

to spaces where the outdoor air requirement is expressed as (L/s) cfm per person. If carbon

dioxide, or some other demand control approach, is employed as a “people counter,” then the

outdoor air could be varied in response to changes in occupancy. In fact, ASHRAE has issued

interpretation #33 of Standard 62-1999 (also referred to as interpretation #27 of Standard 62-

1989) that allows this application. The interpretation allows the use of CO2-DCV as long as other
30

provisions of the standard (specifically requirements related to intermittent occupancy) have not

been used to reduce the estimated occupancy, CO2 is not being removed by other methods such

as air cleaning, and a control algorithm is used to achieve the rates in Table 2 of the standard.

The interpretation does specifically allow for a number of different control algorithms, including

“ make or break” (on/off), proportional, proportional-integral, and proportional-integralderivative, and specifically mentions the use of the difference between indoor and outdoor CO2

levels in these controls. However, the interpretation notes “ good practice and the rationale on

which the ventilation rates in Table 2 are based, indicates the need for a non-zero base

ventilation rate to handle non-occupant sources whenever the space is occupied.” Therefore,

some residual ventilation needs to be provided to handle non-occupant contaminant sources, but

neither the standard nor the interpretation indicates how much ventilation that is.

The IAQ Procedure is a performance-based method for providing acceptable IAQ in which the

design is based on the control of certain “contaminants of concern” to specified acceptable

levels. The standard neither identifies the contaminants on which to base the design nor the

acceptable levels; that is up to the user of the standard. Carbon dioxide DCV could be one means

of implementing the IAQ Procedure, but realistically one would also need to address

contaminants that are not generated at rates associated with the number of occupants.

Another aspect of the standard that is relevant to CO2-DCV is the indoor CO2 guideline that was

in the 1989 version of the standard. Table 3 of the standard (both the 1989 and 1999 versions)

contains guidelines for selected air contaminants for potential use with the IAQ Procedure. The

1989 version of Table 3 included a limit of 1800 mg/m

3

(1000 ppm(v)) for indoor CO2, which

was the subject of much confusion. Specifically, some readers of the standard interpreted this

guideline as indicating that indoor CO2 levels about 1800 mg/m

3

(1000 ppm(v)) were a health

hazard. In fact, this guideline was based on the association with indoor CO2 levels with the level

of odor due to human bioeffluents. Since then, the approval of Addendum 62f to the standard in

1999 and its incorporation in Standard 62-1999 removed the 1800 mg/m

3

(1000 ppm(v)) CO2

guideline and replaced it with the actual contaminant of interest, i.e., human bioeffluents.

Additional changes to Appendix D of the standard explained that odor levels from human

bioeffluents were likely to be acceptable to the majority of visitors entering a space if the indoor

CO2 level were no more than 1260 mg/m

3

(700 ppm(v)) above outdoors.

California's Energy Efficiency Standards for Residential and Nonresidential Buildings

The CEC standards (1999), often referred to as Title 24, discuss demand-controlled ventilation

under Section 121 - Requirements for Ventilation. In addition to providing minimum outdoor air

ventilation rates, section 121 (c) discusses operation and control of outdoor air. An exception to

the requirement that the specified outdoor air rates shall be supplied whenever the space is

occupied states that the outdoor air rate may be reduced to 0.76 L/s-m

2

(0.15 cfm/ft

2

) if the

system is controlled by an approved demand controlled ventilation device and in the case of CO2

control, the indoor CO2 level is limited to no more than 1440 mg/m

3

(800 ppm(v)) while the

space is occupied. The basis for this limit is not provided in the document, but it should be noted

that an indoor CO2 level of 1440 mg/m

3

(800 ppm(v)) corresponds to about 11.5 L/s (23 cfm) per

person of outdoor air under steady state conditions.

These standards were revised in January 2001 in a document containing emergency regulations,

referred to as AB 970 (CEC 2001a). The requirements for CO2 demand-controlled ventilation

remained largely the same as the 1999 standards, with a few exceptions. One significant change

is that demand control ventilation is required for spaces with fixed seating and occupant densities

less than or equal to about 9 m

2

(10 ft

2

) per person and for spaces with outdoor air capacities
31

greater than or equal to 1400 L/s (3000 cfm). However, note that these requirements are for any

form of demand control that reduce outdoor air intake based on occupancy, not just those based

on CO2 sensing. While the standard is not specific, such control could be based on timers,

occupancy sensors and other approaches. When the control device is based on indoor CO2 levels,

the emergency standards still require that the indoor CO2 levels not exceed 1440 mg/m

3

(800 ppm(v)) when the space is occupied. As noted above, this CO2 level corresponds to an

outdoor air ventilation rate of 11.5 L/s (23 cfm) per person at steady-state. In addition, the 2001

standard requires a sensor in the space or in a return airstream from the space, with one sensor

for every 2300 m

2

(25,000 ft

2

) of habitable space.

Revisions to the 2001 emergency standards (CEC 2001b) were recently issued for review prior to

their adoption on April 4, 2001. These proposed revisions add an exception to the 1440 mg/m

3

(800 ppm(v)) if the ventilation rate is greater than or equal to the rate required by the standard.

The current versions of ASHRAE Standard 62-1999 and California’s Title 24 Energy Efficiency

Standards both allow the use of CO2 demand-controlled ventilation. However, neither document

provides much application guidance or specific requirements in several important areas including

sensors (number, placement, accuracy, calibration or maintenance), control algorithms and

setpoints, or base ventilation rates. To effectively realize the energy saving potential of this

technology, such guidance is definitely needed.

6. SUMMARY

Carbon dioxide demand controlled ventilation (DCV) attempts to achieve acceptable indoor air

quality (IAQ) at reduced energy cost by matching a ventilation system’s outdoor airflow rate to

the real-time occupancy as indicated by indoor CO2 levels. The potential advantages of CO2-

based DCV are increased ventilation when occupancy is high, a feedback control mechanism to

ensure acceptable IAQ and energy savings from decreased ventilation when occupancy is low.

While the energy savings potential of this approach has been highlighted in several studies, there

are still some important questions related to the implementation of CO2-based DCV. One of the

most critical issues is that low CO2 levels alone do not guarantee acceptable IAQ. For example,

the concentrations of non-occupant generated pollutants may not be well controlled by such a

system, or at least they can become elevated during periods of low occupancy due to decreased

ventilation. Also, nonuniformities in air distribution and in building occupancy can present

difficulties in locating sensors such that a representative CO2 concentration is measured. While

the potential energy savings have been identified in a number of earlier studies, additional study

is needed to help designers estimate the actual saving that can be realized in specific situations.

In addition, work remains to be done on improving CO2 sensors and in developing application

guidance. Future phases of this project will focus on increasing our understanding of the energy

savings potential and in developing improved application guidance.
32

7. ACKNOWLEDGEMENTS

This report was supported by the California Energy Commission through the Architectural

Energy Corporation. The authors acknowledge the contributions of Vern Smith of the

Architectural Energy Corporation, James Braun of Purdue University, William Healy of NIST

and Amy Musser of the University of Nebraska.
33

8. REFERENCES

ACGIH. 2001. 2001 Threshold Limit Values (TLVs) for Chemical Substances and Physical

Agents and Biological Exposure Indices (BEIs). American Conference of Governmental

Industrial Hygienists.

Anon. 1986. Ventilation Control by Measurement of Carbon Dioxide Levels in Public

Entertainment Buildings. Energy Technology Support Unit AERE Harwell, Oxfordshire.

Apte, M.G., W.J. Fisk and J.M. Daisey. 2000. Associations Between Indoor CO2 Concentrations

and Sick Building Syndrome Symptoms in US Office Buildings: An Analysis of the 1994-1996

BASE Study Data. Indoor Air 10 (4): 246-257.

ASHRAE. 1997. Fundamentals Handbook, Chapter 8 Thermal Comfort. American Society of

Heating, Refrigerating and Air-Conditioning Engineers, Inc.

ASHRAE. 1989. Standard 62-1989, Ventilation for Acceptable Indoor Air Quality. American

Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., Atlanta, GA.,

ASHRAE. 1999. Standard 62-1999, Ventilation for Acceptable Indoor Air Quality. American

Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., Atlanta, GA.,

ASTM. 1998. Standard Guide for Using Indoor Carbon Dioxide Concentrations to Evaluate

Indoor Air Quality and Ventilation. American Society for Testing and Materials, West

Conshohoken, PA, D6245-98.

Axley, J. 1988. Progress Toward a General Analytical Method for Predicting Indoor Air

Pollution in Buildings: Indoor Air Quality Modeling Phase III Report. Gaithersburg, Maryland:

National Bureau of Standards, NBSIR 88-3814.

Bearg, D.W. 1994. Second Generation Demand-Controlled Ventilation Systems. Proceedings of

ASHRAE IAQ 94: 169-174.

Bell, S.J. and B. Khati. 1983. Indoor Air Quality in Office Buildings. Occupational Health in

Ontario. 4: 103-118.

Berg-Munch, B., G. Clausen and P.O. Fanger. 1986. Ventilation Requirements for the Control of

Body Odor in Spaces Occupied by Women. Environment International 12: 195-199.

Bjorsell, N. 1996. Control Strategies for Demand Controlled Ventilating Systems. Proceedings

of Roomvent ‘96.

Brandemuehl, M.J. and J.E. Braun. 1999. The Impact of Demand-Controlled and Economizer

Ventilation Strategies on Energy Use in Buildings. ASHRAE Transactions 105 (2): 39-50.

Bright, P.D., M.J. Mader, D.R. Carpenter and I.Z. Hermon-Cruz. 1992. Guide for Indoor Air

Quality Surveys. Armstrong Laboratory, Brooks Air Force Base, Texas, AL-TR-1992-0016.

California Energy Commission. 1999. Energy Efficiency Standards for Residential and

Nonresidential Buildings, P400-98-001.

California Energy Commission. 2001a. AB970 Energy Efficiency Standards for Residential and

Nonresidential Buildings, P400-01-001.

California Energy Commission. 2001b. AB970 Energy Efficiency Standards for Residential and

Nonresidential Buildings, P400-01-009.
34

Cain, W.S., B.P. Leaderer, R. Isseroff, L.G. Berglund, R.J. Huey, E.D. Lipsitt and D. Perlman.

1983. Ventilation Requirements in Buildings - I. Control of Occupancy Odor and Tobacco

Smoke Odor. Atmosphere Environment. 17: 1183-1197.

Carpenter, S.C. 1996. Energy and IAQ Impacts of CO2-Based Demand-Controlled Ventilation.

ASHRAE Transactions 102 (2): 80-88.

CEC. 1992. Guidelines for Ventilation Requirements in buildings. Report No. 11, European

Concerted Action Indoor Air Quality & Its Impact on Man. Commission of the European

Communities, Brussels,

Chan, G.Y., C.Y. Chao, D.C. Lee, S.W. Chan, and H. Lau. 1999. Development of a Demand

Control Strategy in Buildings using Radon and Carbon Dioxide Levels. Proceedings of Indoor

Air 99 1:48-53.

Clarke, J. and D. McLean. 1986. ABACUS. E.S.P. Documentation - A Plant and Energy

Simulation System. Strathclyde University.

Davanagere, B.S., Shirey, D.B., Rengarajan, K., and F. Colacino. 1997. Mitigating the Impacts

of ASHRAE Standard 62-1989 on Florida Schools. ASHRAE Transactions 103 (1): 241-258.

Davidge, B. 1991. Demand Controlled Ventilation Systems in Office Buildings. Proceedings of

the 12th AIVC Conference Air Movement & Ventilation Control within Buildings: 157-171.

Coventry, Great Britain: Air Infiltration and Ventilation Centre.

Di Giacomo, S.M. 1999. DCV: History, Theory, Myths. Engineered Systems, February 1999.

Donnini, G., F. Haghighat, and V.H. Hguyen. 1991. Ventilation Control of Indoor Air Quality,

Thermal Comfort, and Energy Conservation by CO2 Measurement. Proceedings of the 12th

AIVC Conference Air Movement & Ventilation Control within Building: 311-331.

Dounis, A.I., M. Bruant, G. Guarracino, and P. Michel. 1996. Indoor Air-Quality Control by a

Fuzzy-Reasoning Machine in Naturally Ventilated Buildings. Applied Energy; 1:11-28.

Elovitz, D.M. 1995. Minimum Outside Air Control Methods for VAV Systems. ASHRAE

Transactions 101 (2): 613-618.

Emmerich, S.J., J.W. Mitchell, and W.A. Beckman. 1994. Demand-Controlled Ventilation in a

Multi-Zone Office Building. Indoor Environment 3: 331-340.

Emmerich, S.J. and A.K. Persily. 1997. Literature Review on CO2-Based Demand-Controlled

Ventilation. ASHRAE Transactions 103 (2): 229-243.

Enermodal. 1995. An Evaluation of the Effect of CO2-Based Demand-Controlled Ventilation

Strategies on Energy Use and Occupant-Source Contaminant Concentrations. ASHRAE

Research Project 740-TRP. Waterloo, Ontario: Enermodal Engineering Limited.

Enermodal. 1990. Enerpass Version 3.0. Waterloo, Ontario: Enermodal Engineering Limited.

EPA. 1991. Introduction to Indoor Quality. A Reference Manual. U.S. Environmental Protection

Agency, U.S. Public Health Service, National Environmental Health Association, EPA/400/3-

91/003.

EPA. 1999. Exposure Factors Handbook. U.S. Environmental Protection Agency, EPA/600/C99/001.
35

Fahlen, P., H. Andersson, and S. Ruud. 1991. Demand Controlled Ventilation - Evaluation of

Commercially Available Sensors. Proceedings in the 12th AIVC Conference Air Movement &

Ventilation Control within Buildings: 201-216.

Fahlen, P., H. Andersson and S. Ruud. 1992. Demand Controlled Ventilating Systems Sensor

Tests. Swedish National Testing and Research Institute, Boras, Sweden, SP Report 1992:13.

Fanger, P.O. and B. Berg-Munch. 1983. Ventilation and Body Odor. Engineering Foundation

Conference on Management of Atmospheres in Tightly Enclosed Spaces, Santa Barbara, CA. 45-

50.

Fanger, P.O. 1988. Introduction of the Olf and Decipol Units to Quantify Air Pollution Perceived

by Humans Indoors and Outdoors. Energy and Buildings. 12: 1-6.

Federspiel, C.C. 1996. On-Demand Ventilation Control: A New Approach to DemandControlled Ventilation. Proceedings of Indoor Air ‘96.

Feher, T.R. and L.L. Ambs. 1997. The Use of CO2 Readings with Fixed Ventilation to Predict

Energy Savings with Demand-Controlled Ventilation. Proceedings of Healthy Buildings/IAQ

’97.

Fehlmann, J., H. Wanner, and M. Zamboni. 1993. Indoor Air Quality and Energy Consumption

with Demand Controlled Ventilation in an Auditorium. Proceedings of the 6th International

Conference on Indoor Air Quality and Climate. Vol. 5: 45-50.

Fleury, B. 1992. Demand Controlled Ventilation: A Case Study. Proceedings of the 13th AIVC

Conference Ventilation for Energy Efficiency and Optimum Indoor Air Quality: 343-346.

Gabel, S. D., J.E. Janssen, J. O. Christoffel, and S. E. Scarborough. 1986. Carbon Dioxide-Based

Ventilation Control System Demonstration. U. S. Department of Energy, DE-AC79-84BP15102.

Haghighat, F. and G. Donnini. 1992. IAQ and Energy-Management by Demand Controlled

Ventilation. Environmental Technology. 13: 351-359.

Haghighat, F., R. Zmeureanu, and G. Donnini. 1993. Energy Savings in Building by Demand

Controlled Ventilation System. Proceedings of the 6th International Conference on Indoor Air

Quality and Climate. 5: 51-56.

Helenelund, C. 1993. Future of DCV - What is Economically Feasible? Proceedings of Air the

6th International Conference on Indoor Air Quality and Climate. 5: 57-62.

Houghton, D. 1995. Demand-Controlled Ventilation: Teaching Buildings to Breathe. Boulder,

CO: E. Source, Inc, TU-95-10.

Huze, M.H., Meneboo, F., and J.B. Hoffmann. 1994. Air quality sensors: a field evaluation.

Proceedings of Roomvent 94 2:491-501.

Iwashita, G., K. Kimura, S. Tanabe, S. Yoshizawa and K. Ikeda. 1990. Indoor Air Quality

Assessment Based on Human Olfactory Sensation. Journal of Architectural Planning and

Environmental Engineering. 410: 9-19.

Janssen, J. E., T.J. Hill, J.E. Woods, and E.A.B. Maldonado. 1982. Ventilation for Control of

Indoor Air Quality: A Case Study. Environment International. 8: 487-496.

Janu, G.J., J.D. Wenger, and C.G. Nesler. 1995. Strategies for Outdoor Airflow Control from a

Systems Perspective. ASHRAE Transactions 101 (2): 631-643.
36

Ke, Y.-P. and S.A. Mumma. 1997. Using Carbon Dioxide Measurements to Determine

Occupancy for Ventilation Controls. ASHRAE Transactions 103 (2): 365-374.

Klein S. 1994. TRNSYS, A Transient System Simulation Program, Version 14.1 Users Manual.

University of Wisconsin-Madison: Solar Energy Laboratory.

Knoespel P, J. Mitchell, and W. Beckman. 1991. Macroscopic Model of Indoor Air Quality and

Automatic Control of Ventilation Airflow. ASHRAE Transactions 97 (2): 1020-1030.

Kulmala, V., A. Salminen, G. Graeffe, K. Janka, J. Keskinen, and M. Rajala. 1984. Long-Term

Monitoring of Indoor Air Quality and Controlled Ventilation in Public Buildings. Proceedings of

the 3rd International Conference on Indoor Air Quality and Climate. Vol. 5: 435-441.

Kusuda, T. 1976. Control of Ventilation to Conserve Energy While Maintaining Acceptable

Indoor Air Quality. ASHRAE Transactions 82 (1): 1169-1181.

Mansson, L. 1989. Annex 18 Demand Controlled Ventilating Systems. Proceedings of the 10th

AIVC Conference Progress and Trends in Air Infiltration Research: 25-43

Mansson, L. 1994. Demand Controlled Ventilation Systems in Non-industrial Buildings.

Proceedings of the European Conference on Energy Performance and Indoor Climate in

Buildings.

Meckler, M. 1994. Demand-Control Ventilation Strategies for Acceptable IAQ.

Heating/Piping/Air Conditioning. May: 71-74.

Meier, S. 1993. Mixed-Gas or CO2 Sensors as a Reference Variable for Demand-Controlled

Ventilation. Proceedings of the 6th International Conference on Indoor Air Quality and Climate.

Vol. 5: 85-90.

Meier, S. 1995. Demand-Based Ventilation: Indoor Comfort at Lower Cost. Proceedings of

Healthy Buildings ’95, 1743-1750.

Meier S. 1998. Demand-Controlled Ventilation – Requirements and Control Strategies.

Proceedings of Roomvent ’98.

Nakahara, N. 1996. How to Design and Evaluate the HVAC for Better Indoor Air Quality with

Sufficient Energy Saving. Proceedings of Indoor Air ‘96. Vol. 2: 3-15

NIOSH. 1987. A Guide to Safety in Confined Spaces. Cincinnati, OH: National Institute of

Occupational Safety and Health, DHHS Publication No. 87-113.

Ogasawara, S., H. Taniguchi, and C. Sukehira. 1979. Effect of Energy Conservation by

Controlled Ventilation: Case Study in a Department Store. Energy and Buildings 2: 3-8.

Okamoto, S., Muramatsu, S., Jeng, D.Y., Hadano, H., Nagawa, Y., and H. Futata. 1996. The

Exploration of the Use of a Carbon Dioxide Sensor for Indoor Air Control. Proceedings of

Indoor Air ‘96. Vol. 3: 333-338.

Persily, A.K. and W. S. Dols. 1990. The Relation of CO2 Concentration to Office Building

Ventilation. Air Change Rate and Airtightness in Buildings, ASTM STP 1067: 77-92.

Persily, A.K. 1993. Ventilation, Carbon Dioxide and ASHRAE Standard 62-1989. ASHRAE

Journal. 35: 40-44.

Persily, A.K. 1997. Evaluating Building IAQ and Ventilation with Indoor Carbon Dioxide.

ASHRAE Transactions. 103 (2): 193-204.
37

Potter, I.N. and W.B. Booth. 1994. CO2 Controlled Mechanical Ventilated Systems. Technical

Note. Bracknell, Berkshire: Building Services Research and Information Association, TN 12/94.

Raatschen, W., ed. 1990. Demand Controlled Ventilating System. State of the Art Review.

Stockholm, Sweden: Swedish Council for Building Research, D9.

Rajhans, G.S. 1983. Indoor Air Quality and CO2 Levels. Occupational Health in Ontario. 4: 160-

167.

Rasmussen, C., G.H. Clausen, B. Berg-Munch and P.O. Fanger. 1985. The Influence of Human

Activity on Ventilation Requirements for the Control of Body Odor. CLIMA 2000. Vol. 4: 357-

362.

Reardon, J.T. and C.Y. Shaw. 1993. Carbon Dioxide Concentrations and Minimum Air Change

Rates in a High-Rise Office Building. Indoor Environment 2: 337-343.

Reardon, J.T., C.Y. Shaw, and F. Vaculik. 1994. Air Change Rates and Carbon Dioxide

Concentrations in a High-Rise Office Building. ASHRAE Transactions 100 (2): 1251-1263.

Ruud, S.H., P. Fahlen, and H. Andersson. 1991. Demand Controlled Ventilation - Full Scale

Tests in a Conference Room. Proceedings of the 12th AIVC Conference Air Movement &

Ventilation Control within Buildings: 187-200.

Schell, M.B., S.C. Turner, and R.O. Shim. 1998. Application of CO2-Based Demand-Controlled

Ventilation Using ASHRAE Standard 62: Optimizing Energy Use and Ventilation. ASHRAE

Transactions 104: 1213-1225.

Schell, M. 2001. Proven Energy Savings with DCV retrofits. HPAC Engineering, February 2001.

Schell, M. and D. Int-Hout. 2001. Demand Control Ventilation Using CO2. ASHRAE Journal. 43

(2): 18-29.

Schultz, K.J. and B.C. Krafthefer. 1993. CO2-Based Ventilation Control: Choice of CO2

Setpoint. ASHRAE Transactions 99 (1): 1548-1553.

Seppanen, O.A., W.J. Fisk and M. J. Mendell. 1999. Association of Ventilation Rates and CO2

Concentrations with Health and Other Responses in Commercial and Institutional Buildings.

Indoor Air. 9 (4): 226-252.

Shirey, D.B. and K. Rengarajan. 1996. Impacts of ASHRAE Standard 62-1989 on Small Florida

Offices. ASHRAE Transactions 102 (1): 153-165.

Sodergren, D. 1982. A CO2-Controlled Ventilation System. Environment International 8: 483-

486.

Sorensen, B.R. 1996. Simulation of a Small VAV Plant. Proceedings of Indoor Air ‘96. Vol. 2:

199-204.

Strindehag, O., L. Norell, and S. Kvarnstrom. 1990. Improved Indoor Air Quality by Supervision

of the CO2 Content. Proceedings of the 5th International Conference on Indoor Air Quality and

Climate. Vol. 4: 437-441.

Strindehag, O., and L. Norell. 1991. Long Term Experience with Demand-Controlled Ventilation

Systems. Proceedings of ASHRAE IAQ 91, Healthy Buildings: 108-110.

Stymne, H., A. Mellin, and M. Sandberg. 1990. Dispersion Pattern of Carbon Dioxide from

Human Sources - A Factor to Consider in Demand Controlled Ventilation Systems. Proceedings

of the 5th International Conference on Indoor Air Quality and Climate. Vol. 4: 317-322.
38

Stymne, H., M. Sandberg, and M. Mattsson. 1991. Dispersion Pattern of Contaminants in a

Displacement Ventilated Room - Implications for Demand Control. Proceedings of the 12th

AIVC Conference Air Movement & Ventilation Control within Buildings: 173-189.

Telaire Systems, Inc. n.d. Application Guide for Carbon Dioxide (CO2) Measurement & Control.

Goleta, CA.

Turiel, I., C.D. Hollowell, and B.E. Thurston. 1979. Variable Ventilation Control Systems:

Saving Energy and Maintaining Indoor Air Quality. Berkeley, CA: Lawrence Berkeley

Laboratory. LBL- 9380.

Vaculik, F. and E.G. Plett. 1993. Carbon Dioxide Concentration-Based Ventilation Control.

ASHRAE Transactions 99 (1): 1536-1547.

Walton, G. 1989. AIRNET - A Computer Program for Building Airflow Network Modeling.

Gaithersburg, MD: National Institute of Standards and Technology, NISTIR 89-4072.

Wang S. and X. Jin. 1998. CO2-Based Occupancy Detection for On-Line Outdoor Air Flow

Control. Indoor & Built Environment; 7:165-181.

Wang S. and X. Jin. 1999. Experimental Validation of CO2-Based Occupancy Detection for

Demand-Controlled Ventilation. Indoor & Built Environment; 8:377-391.

Warren, B.F. 1982. Energy Savings in Buildings by Control of Ventilation as a Function of

Indoor Carbon Dioxide Concentration. Building Services Engineering Research & Technology 3

(1): 4-12.

Warren, B.F. and N.C. Harper. 1991. Demand Controlled Ventilation by Room CO2

Concentration: A Comparison of Simulated Energy Savings in an Auditorium Space. Energy and

Buildings 17: 87-96.

Woods, J.E., G. Winakor, E.A.B. Maldonado, and S. Kipp. 1982. Subjective and Objective

Evaluation of a CO2-Controlled Variable Ventilation System. ASHRAE Transactions 88 (1):

1385-1393.

Wright, G. 1997. DCV expands options for improving IAQ. Building Design & Construction,

January 1997.

Zamboni, M., O. Berchtold, C. Filleux, J. Fehlmann, and F. Drangsholt. 1991. Demand

Controlled Ventilation - An Application to Auditoria. Proceedings of the 12th AIVC Conference

Air Movement & Ventilation Control within Buildings: 143-155.

Zmeureanu, R., and F. Haghighat. 1995. Computer Simulation of the Impact of CO2-based

Ventilation Control. Proceeding of Building Simulation ‘95: 206-212.
39

Appendix A: CEC RFP Issues

The California Energy Commission (CEC) Public Interest Energy Research (PIER) Request for

Proposals for the Buildings Energy Efficiency Program Area identified four key issues of

concern. These four issues identify energy problems facing buildings in California and present

opportunities to have a significant positive impact. This appendix discusses the relationship of

the application of CO2-based DCV systems to the four key issues based on information in this

report.

Issue #1 Energy consumption is rapidly increasing in hotter, inland areas as new building

construction increases in these areas.

A key intent of CO2-based DCV systems is the reduction of energy consumed to cool and heat

ventilation air in buildings. As discussed in the review of case studies in this report, they are

capable of achieving such reductions for many building types in a variety of climates.

Fortuitously, DCV systems may be very well suited to reducing energy consumption in the

hotter, inland areas of California as evidenced by a recent simulation study (Brandemuehl and

Braun 1999).

Brandemuehl and Braun simulated the energy impacts of DCV systems and economizers for four

building types (office, retail, school, and restaurant) in a variety of locations including

Sacramento. They reported potential electrical energy savings of 17 % for the restaurant in

Sacramento with both a DCV system and an economizer. Equal savings were due to the DCV

system and the economizer. For the other building types in Sacramento, the combined DCV and

economizer systems reduced electrical energy consumption by 10 % for the office, 19 % for the

retail, and 18 % for the school. Since Brandemuehl and Braun and others have reported larger

potential savings for humid locations and hotter locations, a DCV system with an economizer is

likely to save even more electrical energy in locations such as Fresno and Palm Springs, climates

combining warm weather and high humidity levels. The use of carefully scheduled purge

ventilation with DCV could also increase energy savings by reducing ventilation during the

hottest times of the day.

Issue #2 Development of energy efficient products and services needs to adequately consider

non-energy benefits, such as comfort, productivity, durability, and decreased maintenance.

Since CO2-based DCV systems directly affect building ventilation rates, the potential exists to

have a significant impact on occupant comfort and productivity. That impact could be either

positive or negative depending on the DCV system design, installation, operation and

maintenance. CO2-based DCV systems can indeed have a positive impact on IAQ that is not

always considered, when building zones are occupied by more people than the number on which

the ventilation system design is based. At such times, a DCV system will result in improved IAQ

by providing an appropriate amount of ventilation to the space. Additionally, ventilation systems

may operate with lower ventilation effectiveness than the design criteria. Again, a DCV system

can increase ventilation rates in such situations. While it is not possible to estimate potential

impacts on productivity for any given building, Fisk and Rosenfeld (1997) have estimated that

nationwide impacts of better indoor environments are in the billions of dollars.

Since DCV systems adjust ventilation rates based on measured concentrations of CO2 generated

by building occupants, they do not directly guarantee satisfactory indoor air quality (IAQ) due to

the presence of non-occupant generated contaminants. This issue results in a concern by some

that DCV could result in poor IAQ, which could negatively impact comfort and productivity.

Certain steps need to be taken to avoid the occurrence of such a negative impact. The most
40

fundamental step is to implement the same good IAQ practices that should be applied to all

commercial buildings. These practices include reduction of contaminant sources, proper

installation and maintenance of equipment, etc. Additional steps that should be taken for DCV

systems include appropriate selection of control algorithms and setpoints, thoughtful

consideration of expected contaminant sources, establishment of minimum base and/or purge

ventilation rates and schedules, system commissioning, and proper maintenance and calibration

of CO2 sensors.

Issue #3 Building design, construction, and operation of energy-related features can affect

public health and safety.

The above discussion addressing Issue #2 also applies to public health. CO2-based DCV systems

could have either a negative or positive impact on public health, and therefore care needs to be

taken in their application. In addition, DCV can have a very positive impact in lessening the

moisture load in non-residential buildings in humid climates. Since most of the moisture load for

many non-residential buildings is brought into a building through ventilation, reducing excess

ventilation during times of reduced building occupancy can reduce this moisture load. This

reduction in moisture load can save energy and money by eliminating the need for special

equipment.

Issue #4 Investments in energy efficiency can affect building and housing affordability and value,

and the state’s economy.

As discussed in response to Issue #1, CO2-based DCV systems can reduce building heating and

cooling energy use and, therefore, reduce operating costs to improve building affordability and

value. However, these potential savings will vary widely depending on building type, climate,

occupancy density and patterns, other HVAC system characteristics, and other factors. While

knowledge of these important parameters is growing, more work is needed to identify the best

opportunities for energy savings. No significant impacts are expected on the energy-related costs

of construction.

References

Brandemuehl, M.J. and J.E. Braun. The Impact of Demand-Controlled and Economizer

Ventilation Strategies on Energy Use in Buildings (1999) ASHRAE Transactions 105 (2): 39-50.

Fisk, W.J. and A.H. Rosenfeld. Estimates of Improved Productivity and Health from Better

Indoor Environments (1997) Indoor Air 1997; 7:158-172.
41

Appendix B: Preliminary Application Guidance

The intent of this section is to summarize the currently available guidance on the application of

CO2-based DCV while acknowledging that significant knowledge gaps still remain. This

summary is based on guidance in various publications including lessons learned from published

case studies. Future phases of this study are intended to fill in many of these knowledge gaps and

to develop more definitive guidance. Furthermore, it is not the intent of this section to describe a

system that meets ASHRAE Standard 62 or any other ventilation standard.

Target buildings

The intent of a CO2-based DCV is to save cooling, heating, and fan energy use compared to

ventilation at a constant rate based on design occupancy, while assuring adequate ventilation

rates for IAQ control. While CO2-based DCV systems are likely to save at least some energy for

nearly all buildings and climates, the amount of energy saved can vary dramatically depending

on the climate, occupancy, operating hours, and other building and HVAC system features. The

greatest energy savings are likely to occur in buildings with large heating loads or large cooling

loads that have dense occupancies that vary unpredictably. This section highlights circumstances,

specifically buildings and spaces, where CO2 DCV appears to make the most sense.

Good candidates

Building or spaces where the occupants are likely to be the only significant source of CO2.

Buildings or spaces with dense, unpredictably variable occupancies.

Buildings or spaces in climates that have significant heating or cooling loads.

Variably occupied spaces that have independent outdoor air supply capability such as a

conference rooms within buildings in which the building as a whole may not be a good

candidate.

Poor candidates

Buildings or spaces where ventilation requirements are dominated by non-occupant generated

pollutants.

Buildings or spaces with significant sources of CO2 other than occupants. Using CO2 as the

control variable in such applications will not necessarily result in unacceptable IAQ but rather

could cause excessive ventilation rates. In such cases, it may be possible to control the

ventilation rate based on another measured parameter.

Buildings or spaces with any CO2 removal mechanisms other than ventilation, such as air

cleaning of CO2.

Remaining Issues/Questions

Is it economical for CO2-based DCV to be applied in mild climates even with an economizer?

While CO2-based DCV may not be cost-effective for most buildings with no heating demand in

low humidity climates, CO2-based DCV may still be considered for potential IAQ benefits or

ensuring ‘adequate’ ventilation. How significant are these IAQ benefits?

CO2 DCV Technology

Most CO2 sensors used in DCV systems today are based on non-dispersive infrared (NDIR) or

photometric detection. Both technologies can be affected by light source aging. The former

approach may be sensitive to particle buildup on the sensor while the latter could be affected by

vibration or atmospheric pressure changes.
42

Good sensor attributes and application

Appropriate measurement ranges for ventilation control.

Calibrated according to manufacturer recommendations. An automated calibration system that

uses overnight baseline CO2 readings may be considered.

Located in occupied zones when an appropriate location is available..

Poor sensor attributes and application

Should not use CO2 monitors that are not intended for control systems.

Should not be located near doors, windows, air intakes or exhausts, or in close proximity to

occupants.

A single sensor located in a common return should not be used to control ventilation rates for

spaces with very different expected occupancies.

Remaining Issues/Questions

Is it acceptable to use a single sensor in a common return to control the ventilation rate for

multiple zones with similar expected occupancies? Can a lower setpoint compensate for

differences in concentrations between zones? How much could this approach reduce energy

savings?

Are there significant advantages to using a single sensor with multiple measurement locations

compared to multiple sensors?

Control Algorithms

Control strategies for CO2-based DCV include simple setpoint control where the ventilation rate

is increased or decreased depending on the indoor CO2 concentration, proportional control in

which the ventilation rate is proportional to the CO2 concentration, PI (proportional-integral) or

PID (proportional-integral-derivative) control which can adjust more quickly to changes in the

CO2 concentration, and algorithms that aim to maintain a constant ventilation rate per person at

all times.

Good practice

Control strategies should be chosen based on the expected occupancy patterns. Control

algorithms that can adjust ventilation rates more quickly should be considered for spaces with

low density occupancy or where changes in occupancy may be gradual .

Remaining Issues/Questions

Should CO2 setpoints be varied for buildings with occupants whose CO2 generation is expected

to vary significantly from that of adults doing office work? It is necessary to account for the

lower CO2 generation of children in schools or the higher generation of very active adults? Is a

control algorithm that maintains a constant ventilation rate per person necessary for acceptable

IAQ?

Other Contaminants

CO2-based DCV systems should include a strategy to provide for sufficient ventilation, or other

means, to control concentrations of non-occupant generated contaminants. Ideally, an analysis of

non-occupant sources would indicate the appropriate ventilation and other IAQ control

technologies needed to maintain the resulting concentrations of contaminants within acceptable

limits. However, the information needed to perform such an analysis will not likely be available

in most situations.
43

Good practice

CO2-based DCV should include a strategy of ventilation and other IAQ control technologies to

control non-occupant generated contaminants. It may be possible to control known pollutant

sources through local ventilation or air cleaning.

Poor practice

CO2-based DCV may not be appropriate in spaces where smoking is permitted.

Remaining Issues/Questions

What level of minimum ventilation, if any, is needed? Although recommendations have been

made to maintain a minimum ventilation rate of 10 % to 50 % of the design rate, no general rule

of thumb is available. Minimum ventilation rates should be established based on expected types

and strengths of pollutant sources, and other IAQ control technologies employed.

Can scheduled purges replace the minimum ventilation rate? It may be possible to maintain

average contaminant concentrations below the same limits that would result from a constant

ventilation rate by scheduling purges at appropriate times, such as prior to occupancy. Such a

strategy may save energy if the purges can be scheduled in the afternoon during heating season

and during the morning in the cooling season.

Other Considerations

The selection and design of a CO2-based DCV system cannot be viewed in isolation. The air

quality and energy performance of a DCV system will impact and be impacted by other building

and HVAC systems. While no comprehensive listing of potential interactions is available,

significant interactions can occur with economizers, displacement ventilation, and other

technologies.

Good practice

In buildings with an economizer cycle, the economizer should be allowed to override the DCV

system at times when the additional ventilation would provide ‘free’ cooling.

Consider installation of an outdoor CO2 sensor if outdoor levels are expected to deviate

significantly (more than about 20 %) from 720 mg/m

3

(400 ppm(v)). The outdoor CO2

concentrations can be assumed to be 720 mg/m

3

(400 ppm(v)) for most applications, but urban

areas may have local effects resulting in higher levels. The higher outdoor level could result in

overventilation and it may be economical to install an additional sensor to control the difference

between indoor and outdoor concentration directly. Such an installation could also be required by

applicable standards or codes.

“Poor” practice

CO2-based DCV may not be appropriate in buildings in mild climates (little or no heating

demand and low humidity) unless an economizer is also used.

Remaining Issues/Questions

If a displacement ventilation system is used, where should the sensor be located and can the

setpoint be lowered?