Arc Re-Entry:

Guide to Measuring CO2
By Kristina Koh, Chris Pyke, and Dagny Carlsson

ArcSkoru.com • November 2021

Guide to Measuring CO2Introduction
To improve the well-being of students or be recognized for their healthy environments, schools canmeasure indoor air quality (IAQ). Examples of factors that make up IAQ include particulate matter (PM),thermal comfort, and carbon dioxide (CO2). High levels of CO2 have proven to play a negative role instudent performance. From a study of 60 schools in Scotland, CO2 demonstrated an inverse relationshipwith school attendance. An incremental increase of 100 ppm of CO2 over 1000 ppm was associatedwith half a day of absence per school year (Gaihre et al. 2014). High concentrations can have animpact on grades too. A study of a Latvian school used student surveys and tests to examine CO2 andacademic performance. There was a moderately negative correlation between CO2 concentrationand test performance as students performed worse when exposed to higher concentrations of CO2.
However, simple measures such as opening doors and windows for at least 15 minutes were enoughto maintain low CO2 levels (Bogdanovica et al. 2020). The decrease in students’ attention intensity inclassrooms with an average of 2909 ppm CO2 has been found to be of similar magnitude to that ofstudents skipping breakfast (Coley et al. 2016).
Much of the exceedances of CO2 derive from issues with HVAC systems or low ventilation rates. Thus,
CO2 can be a great indicator for HVAC performance (Johnson et al. 2018). Given the numerous typesof HVAC system types, HVAC operating conditions, and seasonal variation, measuring CO2 is essential
in ensuring well-maintained ventilation equipment. HVAC systems both new and old are susceptible
to improper ventilation of schools. In 104 classrooms in California that were retrofitted with new HVAC
equipment, there were maintenance issues in 51% of the studied classrooms. Some were improperly
installed or lacked commissioning, but all of them were associated with under-ventilated classrooms(Chan et al. 2020 and Fisk et al. 2012). CO2 measurement, therefore, is necessary to ensure HVAC
systems are delivering sufficient ventilation.
With the risk associated with high concentrations of CO2, particularly for children, and the lack ofguarantee of HVAC function, CO2 levels need to be measured in schools accurately and efficiently tosupport the health, comfort, and productivity of students and faculty. Ideally, every classroom, office,gym, and library would be measured across all hours to best illustrate a school’s IAQ. Due to financial
and time constraints, this may not be achievable. This guide provides directions and thresholds to help
gauge a school’s air quality without requiring air monitoring in every room all the time as to reduce
equipment costs and time and to ensure that schools of various abilities can still maintain good air
quality for their students. It also includes our approach to defining whether a school has “good”,“better”, or “best” occupied time or floor area measurement and “good” or “acceptable” CO2
performance levels.

Instructions
Schools have varying HVAC systems, classrooms, and schedules that result in each school measuring
their air quality in different ways. In order to streamline this process better, suggestions are given forwhere in a school and where within a classroom to measure.

Placement of CO2 Sensors in a School
With a finite quantity of monitors, schools have limited options for which locations to place theirmonitors. Below are some potential goals a school may want to achieve and suggestions for sensor
placement to achieve these goals.
1. Finding the school’s average CO2
As the primary source for CO2 indoors is occupant respiration, sensors should be placed in rooms whereoccupants spend the majority of their time. For those who want to focus on classroom monitoring
specifically, a random sampling of classrooms’ CO2 levels can provide the school’s average CO2.
For those who want to investigate non-classroom settings such as offices or libraries that have highArc Skoru

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Guide to Measuring CO2
occupancy times, monitors can be placed both in random classrooms and in those non-classrooms.
If users want to sample based on occupancy, they can also weight classrooms based on theiroccupancy such that higher occupied classrooms are more likely to be sampled than lower occupied
classrooms. After classrooms are weighted, monitors can be randomly deployed where classrooms withgreater occupancy are more likely to be measured.
2. Finding the school’s maximum CO2
Best practices would be to sample spaces with high occupancy and/or low ventilation rates. Maximum
CO2 levels are found in occupied classrooms with low ventilation or poorly operating HVAC systems. If
a space has peak occupancy and low ventilation simultaneously, high CO2 should be expected. For
example, if a cafeteria had no running ventilation system and closed windows during lunch hours, theschool’s maximum CO2 could be found there.
3. Determining HVAC operating conditions
To determine HVAC operating conditions, measurements in air ducts under the same HVAC zone need
to be compared to determine whether they are operating as intended. Areas with unusually high levels
should have their HVAC installation checked.

Placement of CO2 Sensors within a Classroom
In general, sensors should be placed in the breathing zone (ie. the height of a sitting student) of around1 meter (3.3 feet) as illustrated in Stazi et al. 2017, Razali et al. 2015, and Jan et al. 2017. Because
classroom activities and student tampering can compromise the accuracy of a sensor, there is lessagreement on where exactlya classroom sensor should be placed. Some suggest placing sensors
beside a teacher’s desk (Deng and Lau 2019), away from windows in the middle of the classroom(Branco et al. 2015), and in the back wall away from the door (Fromme et al. 2007). Sensors placed inlower areas of movement and wind in the breathing zone are ideal for more accurate measurements.

Measuring CO2
CO2 will be assessed by determining the fraction of occupied space and time covered bymeasurements. In turn, these data are interpreted to estimate the fraction of occupied hours whenconditions are in the good, better, or best ranges.

CO2 Comprehensiveness Score
Arc will generate a CO2 Comprehensiveness Score (“CO2 Comp Score”) by adding together 1-100
scores for floor area coverage (floor area, rooms, or HVAC zones), occupied time coverage (operatinghours), and performance (time in “good” or “acceptable” range).
A few details about how this is computed:
Floor area coverage indicates the fraction of the project covered by each type of sensor. There are twoways to achieve this.
1. Users can assume that an individual sensor covers approximately 500 square meters (5,280 squarefeet) (RESET Air Standard for Commercial Interiors) or following guidance from their vendor or
product manufacturer (e.g., arbnco Best Practice Guide). While sensor coverage will differ basedon building layouts and installation practicalities, projects should aim for the smallest effective
coverage area of a sensor, and the coverage area of a single sensor should not exceed 500 m2.
For example, at least one sensor in each HVAC zone or enclosed room could suffice for adequate
coverage, provided those zones or enclosed rooms are smaller than 500 m2 each.
As examples:• Measurements from one sensor covering 500 m2 in a 5,000 square meter open space would bepresumed and documented to provide a coverage of 10% (500 m2 / 5000 m2).

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Guide to Measuring CO2• Estimate an effective radius around each sensor and derive the covered area based on
manufacturer or vendor guidance (e.g., arbnco Best Practice Guide).
• Follow and reference guidance from a third-party standard, such the RESET Air Standard 2.0 for thedesign and operation of monitoring networks.
2. Depending on the school’s measuring goal, users can divide their school into zones in accordancewith the PNNL education building prototypes’ occupied zones such that each floor area coveragecan be calculated as a fraction of the number of zones measured compared to the total numberof zones. They can also determine floor area coverage as a fraction of classrooms measured,
HVAC zones, or other functional units.
PNNL Building Prototypes considers the following as an occupied zone:• Classroom• Computer Lab• Office space• Gym, stadium (play area)• Kitchen• Cafeteria, dining• Library
Arc assumes that coverage continues from the last reported value through the present unless this value
is changed due to reorganisation of space or sensor layouts. Arc combines values as an average ofdaily values to provide an estimate for a given time period.
Figure 2. Draft thresholds used to categorize floor area coverage: good, better, best. These thresholds
are subject to further review and adjustment based on sensor uncertainty.

Floor Area Coverage %Good0Better

25Best75

100

Tips for Entering Floor Area Data Coverage
Some users may not be able to provide a quantitative estimate of floor area data coverage. We
know that there are many potentially confounding factors and unknowns (e.g., the area coveredby any given sensor). It is important to remember that the purpose is to provide a rough estimateof the fraction occupied space associated with each measurement (i.e., are you covering asmall fraction of the area, most of the space, or all of the space).
If a quantitative estimate is not possible, users may estimate coverage and enter the following values:• Low Coverage: <25% of occupied space is associated with measurements• Enter 25% for the applicable date range• Medium Coverage: 25%-75% of occupied space is associated with measurements• Enter 50% for the applicable date range• High Coverage: >75% of occupied space is associated with measurements• Enter 100% for the applicable date range
Describe your estimate with a piece of document. This can be a simple note explaining your rationale.

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Guide to Measuring CO2Occupied time coverage indicates the fraction of time covered by IAQ measurements during the last 90days. For Arc, a time period is “covered” if at least one measurement is taken during the period in a project.
For the purpose of measuring schools, we are assuming 8 occupied hours a day of operations and 1hour as a fundamental unit of occupied time coverage (a.k.a., freshness period for measurements).
Consequently, occupied time coverage is defined as the percentage of hours within a period thathave one or more readings for a given parameter. Additional measurements during a given period do
not increase coverage (i.e., occupied time coverage has a maximum value of 100% which is satisfied
by at least one reading each hour). This means that 1 day has a maximum of 8 readings that will counttowards occupied time coverage.
A high measurement rate, e.g., those recommended by standards such as WELL and RESET, are betterfor a richer, more representative characterisation of CO2 measurement. To keep this metric simple, Arcrequires a report only every hour (i.e., the reporting interval).
Arc assumes that coverage continues from the last reported value through the present unless this value
is changed with new value. Arc combines values as an average of daily values to provide an estimate
for a given time period.
Figure 2. Draft thresholds used to categorize occupied time measured: good, better, best. Thesethresholds are subject to further review and adjustment based on sensor uncertainty.

Occupied Time Coverage %Good0Better

25Best75

100

Tips for Entering Occupied Time Data Coverage
Some users may not be able to provide a quantitative estimate of occupied time data coverage.
We know that there are many potentially confounding factors and unknowns. It is importantto remember that the purpose is to provide a rough estimate of the fraction occupied hours
associated with each measurement (i.e., are you covering a small fraction, most hours, or all ofthem).
If a quantitative estimate is not possible, users may estimate coverage and enter the followingvalues:
If a quantitative estimate is not possible, users may estimate coverage and enter the following values:• Low Coverage: <25% of occupied hours are associated with a measurement• Enter 25% for the applicable date range.
• Medium Coverage: 25%-75% of occupied hours are associated with a measurement• Enter 50% for the applicable date range.
• High Coverage: >75% of occupied hours are associated with a measurement• Enter 100% for the applicable date range.
Describe your estimate with a piece of document. This can be a simple note explaining your rationale.

Performance is divided by thresholds into three categories: good, better, and best. Each period isassigned to one of the three categories.

Arc Skoru4Guide to Measuring CO2
Performance is typically integrated over some period of time, most often hours or days. These periods
may contain any number of sensor readings. The intent is to communicate the percentage of occupied
time in each category. For example:• If hourly (for sub-hourly) occupied data are available, Performance would be calculated as theaverage of hourly values. Missing values would be excluded from Performance, because they are
already accounted for in the preceding metrics.
• If daily data during occupied hours are available, Performance would be calculated as theaverage of daily values. Again, missing values would be excluded.
The result would be the average fraction of periods in each of the three categories over the last 90days. Data older than 90 days do not contribute to the CO2 Comprehensiveness Comp Score.
The CO2 Comprehensive Score combines the three equal elements:• Floor Area Coverage• Occupied Time Coverage• Performance (as the fraction of time in the “good” or “acceptable” condition)
Figure 3. Draft thresholds used to assign time in each condition: good and acceptable. 0-800 ppm
is deemed good as the CDC, ASHRAE, and CIBSE 2018 all recommend ventilation rates that result in800 ppm CO2. The upper limit is 1000 ppm as effects on cognitive performance begin for short term
exposure exceeding 1000 ppm (Azuma et al. 2018). These thresholds are subject to further review andadjustment based on sensor uncertainty.

CO2 Indoor Measurement Performance (ppm)
Good

Acceptable350

8001000

Note on Data Quality
Objective measures of data quality are not currently part of the CO2 Comp Score. However, the qualityof CO2 measurements is a significant management issue, and it varies significantly based on a varietyof factors, including sampling design, sensor placement, sensor capabilities, sensor maintenance,data processing, and more (RESET Standard). Extensive peer-reviewed literature is emerging in this areawith publications such as Sun et al. 2019 and Chojer et al. 2020, and the U.S. Environmental Protection
Agency Air Sensor Toolbox. Arc Re-Entry users may consider the benefits of third-party accredited
hardware as one element of a comprehensive strategy to promote data quality.

CO2 Comp Score Example
Floor Area Coverage• CO2 is measured in 2 out of 20 classrooms and occupied spaces.
• The floor area coverage is estimated at 10%Occupied Time coverage• CO2 measurements occurred over 2 hours per school day for 90 days
• The school operates 40 hours a week
• The occupied time coverage is estimated at 25% for the week
Performance• CO2 measurements ranged from 500 ppm to 1500 ppm in an equal number of hours.
• The performance value is 30% “good” (≤800 ppm), 20% in “acceptable” (≤1000 ppm)
Total CO2 Comp Score = 10/100 + 25/100 + 50/100 = 85/300
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Guide to Measuring CO2Performance Reports
Projects can input their floor area coverage, temporal coverage, and CO2 performance data into Arc
Re-Entry. Arc Re-Entry provides tools to help facility managers use indoor air quality measurements toinform operations. Every Arc user can collect, manage, and score data through the Re-Entry section
under Meters & Surveys. Arc Essentials users can create, download, and share customized reports forprojects and portfolios.

Contact
Contact Chris Pyke (cpyke@arcskoru.com) to provide feedback or get more information.

About Arc
Arc™ is a global technology platform that allows teams overseeing the sustainability of buildings andplaces to collect data, manage and benchmark progress, measure impact and improve performance.
Created and operated by Green Business Certification Inc. (GBCI), Arc empowers its users tounderstand and enhance their sustainability performance, promote human health and wellbeing andcontribute to a higher quality of life.
Learn more at www.arcskoru.com.

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