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buildings
Article
Monitored Indoor Environmental Quality of a Mass
Timber Office Building: A Case Study
Jason Stenson 1, 2, *, Suzanne L. Ishaq 2, Aurélie Laguerre 3, Andrew Loia 1, Georgia MacCrone 2,
Ignace Mugabo 4, Dale Northcutt 1,2, Mariapaola Riggio 5, Andre Barbosa 4, Elliott T. Gall 3
and Kevin Van Den Wymelenberg 1,2
1Energy Studies in Buildings Laboratory, Department of Architecture, University of Oregon, Eugene,
OR 97403, USA; andrewloia@gmail.com (A.L.); tdnorth@uoregon.edu (D.N.);
kevinvdw@uoregon.edu (K.V.D.W.)
2Biology and the Built Environment Center, University of Oregon, Eugene, OR 97403, USA;
sueishaq@uoregon.edu (S.L.I.); gmaccro5@uoregon.edu (G.M.)
3Mechanical and Materials Engineering, Portland State University, Portland, OR 97201, USA;
aurelie@pdx.edu (A.L.); gall@pdx.edu (E.T.G.)
4School of Civil & Construction Engineering, Oregon State University, Corvallis, OR 97331, USA;
nkurikim@oregonstate.edu (I.M.); Andre.Barbosa@oregonstate.edu (A.B.)
5Department of Wood Science & Engineering, Oregon State University, Corvallis, OR 97331, USA;
mariapaola.riggio@oregonstate.edu
*Correspondence: jstenson@uoregon.edu
Received: 14 May 2019; Accepted: 11 June 2019; Published: 13 June 2019
Abstract:
A broad range of building performance monitoring, sampling, and evaluation was
conducted periodically after construction and spanning more than a year, for an occupied office
building constructed using mass timber elements such as cross-laminated timber (CLT) floor and
roof panels, as well as glue-laminated timber (GLT) beams and columns. This case study contributes
research on monitoring indoor environmental quality in buildings, describing one of the few studies of
an occupied mass timber building, and analyzing data in three areas that impact occupant experience:
indoor air quality, bacterial community composition, and floor vibration. As a whole, the building
was found to perform well. Volatile organic compounds (VOCs), including formaldehyde, were
analyzed using multiple methods. Formaldehyde was found to be present in the building, though
levels were below most recommended exposure limits. The source of formaldehyde was not able
to be identified in this study. The richness of the bacterial community was affected by the height of
sampling with respect to the floor, and richness and composition was affected by the location within
the building. Floor vibration was observed to be below recognized human comfort thresholds.
Keywords: mass timber; cross laminated timber; air quality; bacterial community; vibration
1. Introduction
Mass timber wood products are gaining adoption in US buildings through changes to
building codes and standards [
1
,
2
], as well as specialized manufacturing facilities coming on-line.
Prefabricated panelized products like Cross-Laminated Timber (CLT), Dowel-Laminated Timber (DLT),
Nail-Laminated Timber (NLT) and Mass Plywood Panels (MPP) are now able to be used as structural
floor, roof and wall assemblies. These structural elements impact the type and distribution of major
materials used throughout a mass timber building as compared to other construction types. They
often take the place of concrete or steel, and their relatively lightweight may impact floor vibrational
performance (serviceability). They often remain exposed as interior finished surfaces, changing the
Buildings 2019,9, 142; doi:10.3390/buildings9060142 www.mdpi.com/journal/buildings
Buildings 2019,9, 142 2 of 15
makeup of surface to air volume of interior materials, and possibly impacting indoor air chemistry and
indoor microbial community dynamics.
Indoor Environmental Quality (IEQ) of buildings include aspects of the built environment that
affect occupant health and well-being, and commonly includes factors such as indoor air quality, thermal
comfort, visual comfort and acoustic comfort [
3
]. Occupant satisfaction and productivity are common
metrics of IEQ, with short-term and long-term health effects for occupants being more challenging
to quantify, and understanding of source characterization and exposure assessment continuing to
evolve [
4
]. The contribution of wood in creating healthy environments is discussed in several studies,
many of which are based on occupant feedback rather than on quantitative monitoring data (acoustic
comfort in residential timber buildings [
5
], thermal comfort and air quality [
6
], general ‘perceived’
IEQ [
7
]). Most quantitative IEQ studies are limited to measurements in a laboratory environment or in
unoccupied buildings (acoustic performance of assemblies [
8
], floor vibration performance [
9
,
10
]). In a
few exceptions IEQ data were collected in occupied buildings, however, in most cases these full-scale
studies monitored data related to one single IEQ performance indicator (thermal comfort [
11
,
12
];
contribution of wood nonstructural elements to air quality [13]).
This case study contributes to research on monitoring IEQ in buildings, describing one of the few
studies of an occupied mass timber building, and using exposure measurement methods for three
important factors: indoor air quality, indoor bacterial community and vibrational comfort. Other IEQ
indicators such as acoustic performance and occupant response were investigated in the study, but
data were too limited; therefore, these indicators are omitted in this paper.
A newly constructed and occupied building offers layers of building performance complexity.
Simply adding finishes and furnishings to a wood structure successively changes the Volatile organic
compound (VOC) profile and concentrations, with barrier and sink effects reducing or delaying some
emissions [
14
]. Introducing occupants, occupant behavior, and variable environmental conditions
such as temperature and humidity fluctuations also affect indoor air quality. Monitoring indoor air
quality of an occupied mass timber building, including characterizing VOCs that are present, will help
to inform future research on primary emissions from CLT and secondary reaction products in indoor
air that may be sourced in part from CLT.
The indoor microbial community is primarily sourced from indoor occupants and from outdoor
microbial communities which are dispersed indoors from outdoor-sourced ventilation or occupant
traffic [
15
]. It is unknown whether the use of CLT building materials would directly contribute to the
indoor microbial community, either by direct deposition of microorganisms from materials into general
dust, or through the contribution of solid or gaseous chemicals which might affect microorganisms.
Due to the unique combination of occupants, building materials, local environmental conditions,
and geographic location, the microbial communities in buildings tend to be highly variable between
different structures. Thus, we sought to compare passive sampling height and open office location for
the implications each may have on indoor microbial community.
The mass of CLT buildings, when compared to conventional concrete buildings, might pose a
challenge for vibrational serviceability design. Some design criteria for controlling floor vibrations are
difficult to incorporate in general design guides, as they are dependent on variable conditions, such as
live loads [
16
]. Monitoring floor vibration of mass timber systems is therefore important to inform
serviceability design criteria for new types of construction systems.
This case study investigates performance of a mass timber building; how building materials
and assemblies impact indoor air quality, indoor bacterial community, and vibration in an office
environment of an occupied mass timber building. The case study site is Albina Yard, which was
constructed in Portland, Oregon in 2016 and was the first mass timber office building in the U.S. to use
domestically sourced and produced CLT [
17
]. It is a 1500 m
2
, four-story building with a footprint of
approximately 14 m
×
26 m and is comprised of office and ground floor retail space. Its rectangular
building form is elongated in the east-west direction with predominately glazed east and west façades.
Floor and roof assemblies at Albina Yard use 105 mm thick three-lamella (3-lam) CLT as structural
Buildings 2019,9, 142 3 of 15
diaphragm with panels spanning in the E-W direction, and are supported by glue-laminated timber
(GLT) beams and columns. GLT beams are 171 mm
×
610 mm and 171 mm
×
457 mm, and columns
are 222 mm
×
305 mm and 222 mm
×
229 mm, with larger cross-sections of both occurring at the
perimeter of the building. All three structural components are left unfinished and exposed at the
ceiling. Light-framed shear walls constitute the lateral load resisting system. East and west exposures
are floor to ceiling structural GLT window walls with small operable awning units at the floor level.
The majority of the fourth floor is an open-plan office layout with computer workstations, a kitchen
area and an adjacent alcove housing server, copier and printer equipment. Other spaces include large
and small conference rooms, a laser cutter room and restrooms. Finish surface materials found on this
level include painted gypsum wall board, carpet floor covering and exposed unfinished CLT ceiling.
The floor assembly is comprised of 105 mm 3-lam CLT, 25 mm gypcrete topping, and carpet squares
without a pad.
2. Materials and Methods
2.1. Indoor Air Quality
A range of direct-measurement continuous monitoring air quality sensors were deployed during
four week-long periods spread over more than a year and capturing predominantly heating season
building operation in December 2016 (week 1), March 2017 (week 2), October 2017 (week 3) and
January 2018 (week 4). Sensors were deployed as a contained air quality monitoring kit at two indoor
locations, in the northeast and southwest corners of the fourth-floor open office space (Figure 1), to
capture potential influence of window operation as well as differences in solar orientation. Indoor air
quality monitoring kits included sensors measuring the following: air velocity, barometric pressure,
carbon dioxide, carbon monoxide, formaldehyde, ozone, particulate matter, radon, relative humidity,
solar radiation, temperature, and total volatile organic compounds. A similar air quality monitoring
kit, excluding radon and including wind speed and direction sensors was deployed in an outdoor
ground-level patio location onsite. Table 1lists air quality sensors and samplers with results reported
in this study.
Table 1. Air quality monitoring and sampling instrumentation used in reported results.
Make Model Parameter(s)
Entech BLV1A & HDS-F03 Bottle-Vac Helium Diffusion Whole Air Sample (1 L)
Entech BLV1A & RS-QTS1 Evacuated Bottle-Vac Whole Air Grab Sample (1 L)
Entech CS1200ES7 Evacuated Canister Whole Air Outdoor Sample (6 L)
GrayWolf FM-801 Formaldehyde (<20–1000 ppb, +/−4 ppb <40 ppb,
+/−10% of reading ≥40 ppb)
TSI Velocicalc IAQ Probe 986 Carbon Dioxide (0–5000 ppm, +/−3% of reading or
50 ppm whichever is greater)
During sampling weeks 3 and 4, passive whole air helium diffusion sampling (HeDS) for analysis
of VOCs was added to the indoor kits [
18
]. 1-liter canisters (Entech, Bottle-Vac) filled with helium to a
slight positive pressure were deployed in triplicate at each location. A calibrated orifice exchanged a
portion of the helium in each canister with ambient air over the week, providing, in theory, a near
constant sampling rate. After the collection period, canisters were again filled with helium to the initial
pressure and weighed to calculate helium dilution factors. An outdoor whole air sample was captured
on the roof using a 6-liter evacuated canister (Entech, Silonite Canister) and flow controller. Additional
one-minute grab samples were also captured at various indoor locations using 1-liter evacuated
canisters with a calibrated orifice. In the laboratory, proton transfer reaction-time of flight-mass
spectrometry (PTR-TOF-MS) [
19
,
20
] was used for quantification of VOCs following a described method
with specific operational parameters described elsewhere [
21
,
22
], connecting canisters directly to the
PTR-TOF-MS (PTR-TOF 1000, Ionicon Analytik GmbH, Innsbruck, Austria) inlet for analysis.
Buildings 2019,9, 142 4 of 15
Buildings 2019, 9, x FOR PEER REVIEW 4 of 15
(Figure 1). One location, the northeast corner of the open office, was a location common to the sample
weeks with full monitoring equipment. A storage closet with no mechanical ventilation was
monitored, as was the laser cutter room with additional dedicated mechanical exhaust.
Figure 1. Annotated Level 4 Plan of Albina Yard showing air quality and microbial, monitoring and
sampling locations.
2.2. Bacterial Community
Dust was collected from the indoor open office environment in three locations and from one
outdoor ground-level patio location with passive sampling integrated into the air quality monitoring
kits. Samples were collected using 150 mm × 15 mm sterile polystyrene petri dishes. Both petri dish
lids and bases were used as settling dishes, with 6 collection plate surfaces per sample. At each indoor
monitoring kit, plates were deployed at three heights: on top of the kit at 1.12 m above finish floor,
on a shelf within the kit enclosure at 0.88 m above finish floor, and below the kit at finish floor level.
Only the shelf within the kit was used for sampling at the outdoor location. Plates were allowed to
sit at ambient conditions for a period of one week, then sealed with parafilm and stored in sampling
bags for transport to the laboratory.
Plates were stored at −20 °C in the laboratory until DNA extraction was performed, at which
point, dust from all six plate surfaces per sample was collected using sterile nylon-flocked swabs and
100 µL of phosphate-buffered solution per dish surface. Swab tips and PBS solution were added
directly to bead tubes for extraction. Nucleic acids were extracted using the MoBio PowerSoil DNA
Extraction Kit (MoBio, Carlsbad, CA, USA) following kit instructions.
The V3 and V4 (319F-806R) regions of the 16S rRNA gene were polymerase chain reaction (PCR)
-amplified following a previously described protocol [23], and amplicons were purified with a bead-
based clean-up using Mag-Bind RxnPure Plus (Omega Bio-tek, Norcross, GA, USA). Cleaned DNA
was quantified using Quant-iT dsDNA assay kit, and pooled with equal concentrations of amplicons
for Illumina Miseq ver 4 paired-end sequencing using a 250-cycle kit. Sequence data is available from
Figure 1.
Annotated Level 4 Plan of Albina Yard showing air quality and microbial, monitoring and
sampling locations.
Outside of these four weeks of intensive monitoring, GrayWolf FM-801 formaldehyde monitors
were also deployed for longer periods in three indoor locations that varied in use and ventilation
rate (Figure 1). One location, the northeast corner of the open office, was a location common to the
sample weeks with full monitoring equipment. A storage closet with no mechanical ventilation was
monitored, as was the laser cutter room with additional dedicated mechanical exhaust.
2.2. Bacterial Community
Dust was collected from the indoor open office environment in three locations and from one
outdoor ground-level patio location with passive sampling integrated into the air quality monitoring
kits. Samples were collected using 150 mm
×
15 mm sterile polystyrene petri dishes. Both petri dish
lids and bases were used as settling dishes, with 6 collection plate surfaces per sample. At each indoor
monitoring kit, plates were deployed at three heights: on top of the kit at 1.12 m above finish floor, on
a shelf within the kit enclosure at 0.88 m above finish floor, and below the kit at finish floor level. Only
the shelf within the kit was used for sampling at the outdoor location. Plates were allowed to sit at
ambient conditions for a period of one week, then sealed with parafilm and stored in sampling bags
for transport to the laboratory.
Plates were stored at
−
20
◦
C in the laboratory until DNA extraction was performed, at which
point, dust from all six plate surfaces per sample was collected using sterile nylon-flocked swabs
and 100
µ
L of phosphate-buffered solution per dish surface. Swab tips and PBS solution were added
Buildings 2019,9, 142 5 of 15
directly to bead tubes for extraction. Nucleic acids were extracted using the MoBio PowerSoil DNA
Extraction Kit (MoBio, Carlsbad, CA, USA) following kit instructions.
The V3 and V4 (319F-806R) regions of the 16S rRNA gene were polymerase chain reaction
(PCR) -amplified following a previously described protocol [23], and amplicons were purified with a
bead-based clean-up using Mag-Bind RxnPure Plus (Omega Bio-tek, Norcross, GA, USA). Cleaned
DNA was quantified using Quant-iT dsDNA assay kit, and pooled with equal concentrations of
amplicons for Illumina Miseq ver 4 paired-end sequencing using a 250-cycle kit. Sequence data is
available from the National Center for Biotechnology Information (NCBI)’s Sequence Read Archive
(SRA) under BioProject Accession PRJNA532899.
DNA sequence filtering, noise reduction, dereplication, sequence variant picking, chimera removal
and taxonomic identification were performed within the DADA2 package [
24
] of the R statistical
platform (R Core Team 2018). The first and last 10 bases were trimmed from sequences, with an
additional 10 bases trimmed from the ends of reverse sequences to remove low-quality bases. Max
expected errors were 2 for forward and 3 for reverse sequences, with no ambiguous bases accepted,
and any residual phiX DNA removed. The Silva ver. 132 database was used for taxonomy [
25
], and
both DNA extraction and PCR negative controls were used to identify potential contaminants and
remove sequence variants from samples [
26
]. Sequences were rarified to 4450 per sample. Analysis
was performed with R packages phyloseq [
27
], vegan [
28
], DESEQ2 (on non-rarefied data) [
29
], and
visualized with ggplot2 [
30
]. Species’ richness was compared using generalized linear mixed effects
model via the lme4 package [31], with the year collected as a fixed effect.
2.3. Vertical Vibration
A floor vibration study was conducted during week 4 and focused on a section of the fourth-floor
open office area subject to footfall and various impacts from office activities, and followed a dynamic
monitoring study [
32
]. The purpose was to measure the vertical floor accelerations, capturing the
floor response to passersby. Acceleration response time-series were collected to measure peak vertical
floor acceleration responses associated with regular office activities and to understand the frequency
content of the response within the range of human comfort for comparison with existing design
standards [33–35].
Figure 2shows the northwest portion of the floor plan with locations where accelerometers were
installed. To measure the vertical accelerations triggered by footfall, four uniaxial accelerometers were
installed on the floor, which were placed close to the mid-span of three consecutive structural bays.
The accelerometers were secured in access points to the base of floor boxes that were fixed to the CLT
floor panels and then connected to a data acquisition system through BNC cables, and data stored in a
laptop computer. The laptop was remotely accessible, allowing for data to be monitored and stored.
Table 2below contains a summary of the equipment used.
A data-recording trigger was set for recording events of interest. When the floor vertical
acceleration at any of the accelerometers reached a value of +/
−
0.02 g (g =9.81 m/s
2
), all accelerometers
would record for a total duration of 10 seconds, starting 0.125 s before the triggering event to ensure
that the triggering signal was included in the data. The threshold value was selected by recording
normal walking at distances similar to the estimated distances between the on-site pathways and the
locations of accelerometers. An event was considered relevant if its time domain profile matched
the profile of a normal walk at approximately two steps per second. This was determined in a lab
environment and confirmed onsite during installation. Data collection was performed at 2048 Hz, over
a one-week period, totaling 1130 events.
To evaluate the frequency content of the signals collected, power spectral densities (PSDs) of
the signals were evaluated using the pwelch algorithm in MATLAB’s signal processing toolbox
(MathWorks, 2018). In the pwelch function, a data window size of two seconds and overlap size of
half-second was used for averaging purposes. The following processing steps were conducted before
the PSDs were evaluated: Band-pass finite impulse response (FIR) filter with cutoffrange of 0.5–20 Hz
Buildings 2019,9, 142 6 of 15
and filter order of 4098; Down-sampling from the original sampling frequency of 2048 Hz to a sampling
frequency of 256 Hz.
Buildings 2019, 9, x FOR PEER REVIEW 5 of 15
the National Center for Biotechnology Information (NCBI)’s Sequence Read Archive (SRA) under
BioProject Accession PRJNA532899.
DNA sequence filtering, noise reduction, dereplication, sequence variant picking, chimera
removal and taxonomic identification were performed within the DADA2 package [24] of the R
statistical platform (R Core Team 2018). The first and last 10 bases were trimmed from sequences,
with an additional 10 bases trimmed from the ends of reverse sequences to remove low-quality bases.
Max expected errors were 2 for forward and 3 for reverse sequences, with no ambiguous bases
accepted, and any residual phiX DNA removed. The Silva ver. 132 database was used for taxonomy
[25], and both DNA extraction and PCR negative controls were used to identify potential
contaminants and remove sequence variants from samples [26]. Sequences were rarified to 4450 per
sample. Analysis was performed with R packages phyloseq [27], vegan [28], DESEQ2 (on non-
rarefied data) [29], and visualized with ggplot2 [30]. Species’ richness was compared using
generalized linear mixed effects model via the lme4 package [31], with the year collected as a fixed
effect.
2.3. Vertical Vibration
A floor vibration study was conducted during week 4 and focused on a section of the fourth-
floor open office area subject to footfall and various impacts from office activities, and followed a
dynamic monitoring study [32]. The purpose was to measure the vertical floor accelerations,
capturing the floor response to passersby. Acceleration response time-series were collected to
measure peak vertical floor acceleration responses associated with regular office activities and to
understand the frequency content of the response within the range of human comfort for comparison
with existing design standards [33–35].
Figure 2 shows the northwest portion of the floor plan with locations where accelerometers were
installed. To measure the vertical accelerations triggered by footfall, four uniaxial accelerometers
were installed on the floor, which were placed close to the mid-span of three consecutive structural
bays. The accelerometers were secured in access points to the base of floor boxes that were fixed to
the CLT floor panels and then connected to a data acquisition system through BNC cables, and data
stored in a laptop computer. The laptop was remotely accessible, allowing for data to be monitored
and stored. Table 2 below contains a summary of the equipment used.
Figure 2. Uniaxial accelerometer layout. The dashed lines represent GLT beams and girders.
Dimensions refer to the center of the accelerometers.
Figure 2.
Uniaxial accelerometer layout. The dashed lines represent GLT beams and girders. Dimensions
refer to the center of the accelerometers.
Table 2. Description of vibrational test equipment used.
Item Description
Accelerometers 4–PCB 393B04
Data acquisition 1–NI cDaq 9178
Connectors 4–BNC cables
Data storage 1–Laptop equipped with NI LabVIEW SignalExpress 2014
3. Results & Discussion
3.1. Indoor Air Quality
Carbon dioxide (CO
2
) levels in indoor air are tied to occupancy and ventilation, as humans
exhale CO
2
and ventilation rate reduces indoor concentrations by exchanging indoor air with outdoor
air. A workplace exposure limit of 5000 ppm as an 8-hour time-weighted average (TWA) set by the
Occupational Safety and Health Administration (OSHA) has been the standard commonly referenced.
More recently CO
2
has been investigated as a direct indoor air pollutant and not just an indicator of
ventilation rate required for the dilution of other human associated indoor air pollutants in buildings.
It has been shown that CO
2
concentrations as low as 1000 ppm impact occupant decision making
performance [36] and demonstrated declines in cognitive test scores of office workers [37].
In reviewing week 1 of collected air quality monitoring data from this study, CO
2
levels were safe
and typical for an office. However, one-minute trend data revealed that the mechanical ventilation
system may not be operating as intended. It was discovered that an outside air damper for the ERV
was closed. The issue was remedied and the result can be seen in Figure 3, where weekday average
CO2concentrations are reduced from week 1 levels in subsequent monitored weeks.
Buildings 2019,9, 142 7 of 15
Buildings 2019, 9, x FOR PEER REVIEW 7 of 15
Figure 3. Weekday average indoor CO
2
and HCHO by time of day monitored in the northeast corner
of the fourth-floor open office area. Formaldehyde reported using GrayWolf FM-801.
Formaldehyde (HCHO) is a common indoor air pollutant that has been classified as a known
human carcinogen [38]. Indoor air sources include emissions from building materials, particularly in
new construction, as emission rates from new materials decrease over time. Secondary formation of
HCHO can also occur in indoor air, for example, from ozone-initiated reaction with terpenes [39,40].
There are numerous potential indoor as well as outdoor sources of HCHO, these include the use of
consumer products and human activities indoors, industrial and vehicle emissions are among urban
atmospheric sources outdoors. The 2010 World Health Organization (WHO) Guidelines for Indoor
Air Quality recommend a 30-minute exposure limit of 0.1 mg/m
3
(81 ppb) for formaldehyde to
prevent both short-term and long-term health effects [41]. Permissible and recommended exposure
limits do vary by agency, ranging both higher and lower than the WHO guideline. However, the
WHO guideline continues to be supported, even found to be “highly precautionary” [42].
HCHO results from week 3 & 4 captured with a GrayWolf FM-801 formaldehyde meter are
reported in Figure 3 as weekday average values by time of day and the maximum 30-minute value
recorded by time of day for both monitored periods. The overall maximum was 30 ppb in the open
office for these two weeks, below the WHO guideline.
The same sensors were deployed for longer monitoring periods in two additional spaces along
with the open office: the laser cutter room with additional exhaust ventilation and a storage closet
with no mechanical exhaust. No attempts were made to control access to either space or influence
occupant behavior and both rooms were accessed and used as required of normal business
operations. The laser cutter room, with dedicated exhaust ventilation, saw slightly lower HCHO on
average than the open office, and the storage closet saw higher values, with a maximum 30-minute
reading of 63 ppb recorded in the storage closet.
VOCs were also analyzed from various locations throughout the building using one-minute
grab samples captured with evacuated canisters. Grab samples offered a quick method of collecting
additional samples beyond the weeklong time-integrated HeDS samples collected at the monitoring
kit locations. They were also useful for sampling locations where monitoring equipment could not
be deployed for the week. Locations included the ground floor lobby which has some additional
natural ventilation from building occupants entering and exiting the building, the top of the main
stair constructed of CLT and without mechanical ventilation and the storage closet mentioned above.
Figure 3.
Weekday average indoor CO
2
and HCHO by time of day monitored in the northeast corner
of the fourth-floor open office area. Formaldehyde reported using GrayWolf FM-801.
Formaldehyde (HCHO) is a common indoor air pollutant that has been classified as a known
human carcinogen [
38
]. Indoor air sources include emissions from building materials, particularly in
new construction, as emission rates from new materials decrease over time. Secondary formation of
HCHO can also occur in indoor air, for example, from ozone-initiated reaction with terpenes [
39
,
40
].
There are numerous potential indoor as well as outdoor sources of HCHO, these include the use of
consumer products and human activities indoors, industrial and vehicle emissions are among urban
atmospheric sources outdoors. The 2010 World Health Organization (WHO) Guidelines for Indoor Air
Quality recommend a 30-minute exposure limit of 0.1 mg/m
3
(81 ppb) for formaldehyde to prevent
both short-term and long-term health effects [
41
]. Permissible and recommended exposure limits do
vary by agency, ranging both higher and lower than the WHO guideline. However, the WHO guideline
continues to be supported, even found to be “highly precautionary” [42].
HCHO results from week 3 & 4 captured with a GrayWolf FM-801 formaldehyde meter are
reported in Figure 3as weekday average values by time of day and the maximum 30-minute value
recorded by time of day for both monitored periods. The overall maximum was 30 ppb in the open
office for these two weeks, below the WHO guideline.
The same sensors were deployed for longer monitoring periods in two additional spaces along
with the open office: the laser cutter room with additional exhaust ventilation and a storage closet
with no mechanical exhaust. No attempts were made to control access to either space or influence
occupant behavior and both rooms were accessed and used as required of normal business operations.
The laser cutter room, with dedicated exhaust ventilation, saw slightly lower HCHO on average than
the open office, and the storage closet saw higher values, with a maximum 30-minute reading of 63 ppb
recorded in the storage closet.
VOCs were also analyzed from various locations throughout the building using one-minute
grab samples captured with evacuated canisters. Grab samples offered a quick method of collecting
additional samples beyond the weeklong time-integrated HeDS samples collected at the monitoring
kit locations. They were also useful for sampling locations where monitoring equipment could not
be deployed for the week. Locations included the ground floor lobby which has some additional
natural ventilation from building occupants entering and exiting the building, the top of the main stair
constructed of CLT and without mechanical ventilation and the storage closet mentioned above.
Buildings 2019,9, 142 8 of 15
Six common VOCs were selected for analysis: acetone, formaldehyde, methanol, benzene, toluene
and monoterpenes. All have outdoor and indoor sources and all of them except benzene and toluene
are known to be emitted from wood products, but each one has other possible sources and secondary
reactions also complicate identifying a specific source for any of them within the scope and methods of
this study. Monoterpenes are emitted from wood products [
43
] and also derived from the biosynthesis
of plants, as are acetone, formaldehyde and methanol [
44
,
45
]. Acetone and methanol are also often
related to urban and industrial activities [
46
] with many different sources. Formaldehyde is also known
to be among the VOCs emitted by cleaning products and detergents [
47
]. Benzene and toluene are
known as BTEX and mainly emitted from vehicle exhaust [
48
] but also from some detergents, rubbers,
resins, and cigarettes [
49
,
50
]. Figure 4shows results for toluene and monoterpenes, compounds with
indoor and outdoor sources, as each canister is connected and disconnected from the PTR-TOF-MS for
analysis. A field blank was also analyzed. Again, the storage closet with no intended ventilation, was
found to have the highest levels of both compounds (30 ppb Monoterpenes, 17 ppb Toluene).
Buildings 2019, 9, x FOR PEER REVIEW 8 of 15
Six common VOCs were selected for analysis: acetone, formaldehyde, methanol, benzene,
toluene and monoterpenes. All have outdoor and indoor sources and all of them except benzene and
toluene are known to be emitted from wood products, but each one has other possible sources and
secondary reactions also complicate identifying a specific source for any of them within the scope
and methods of this study. Monoterpenes are emitted from wood products [43] and also derived
from the biosynthesis of plants, as are acetone, formaldehyde and methanol [44,45]. Acetone and
methanol are also often related to urban and industrial activities [46] with many different sources.
Formaldehyde is also known to be among the VOCs emitted by cleaning products and detergents
[47]. Benzene and toluene are known as BTEX and mainly emitted from vehicle exhaust [48] but also
from some detergents, rubbers, resins, and cigarettes [49,50]. Figure 4 shows results for toluene and
monoterpenes, compounds with indoor and outdoor sources, as each canister is connected and
disconnected from the PTR-TOF-MS for analysis. A field blank was also analyzed. Again, the storage
closet with no intended ventilation, was found to have the highest levels of both compounds (30 ppb
Monoterpenes, 17 ppb Toluene).
Figure 4. Results for toluene and monoterpenes over PTR-TOF-MS analysis time for one-minute grab
samples from various building locations and one field blank canister.
HeDS is not an established sampling method for indoor air quality and further inter-comparison
with established methods is needed. This preliminary investigation of the method, paired with PTR-
TOF-MS analysis, was selected because it provided a low-cost, simple to deploy, silent method of
collecting a whole air sample [18]. Replicate samples were, on average, within 34% for five of six
VOCs selected: acetone, formaldehyde, methanol, benzene, and monoterpenes. Figure 5 shows HeDS
results from week 3 for the two open office monitoring kit locations as well as an outdoor sample
taken with an evacuated canister on the roof.
0.1 1 10 100 1000
m59.0439 (acetone H+)
m31.01783 (formaldehyde H+)
m33.03230 (methanol H+)
m79.05478 (benzene H+)
m137.1325 (terpenes H+)
Corrected average mixing ratio (ppb)
21402 (SW building) Avg. 21408 (NE building) Avg. Outdoor Avg.
Figure 4.
Results for toluene and monoterpenes over PTR-TOF-MS analysis time for one-minute grab
samples from various building locations and one field blank canister.
HeDS is not an established sampling method for indoor air quality and further inter-comparison
with established methods is needed. This preliminary investigation of the method, paired with
PTR-TOF-MS analysis, was selected because it provided a low-cost, simple to deploy, silent method
of collecting a whole air sample [
18
]. Replicate samples were, on average, within 34% for five of six
VOCs selected: acetone, formaldehyde, methanol, benzene, and monoterpenes. Figure 5shows HeDS
results from week 3 for the two open office monitoring kit locations as well as an outdoor sample taken
with an evacuated canister on the roof.
3.2. Bacterial Community
The mean number of bacterial species observed in dust was affected by the sampling location
within the room as well as the height of sampling, although there was a large amount of variation
among samples (Figure 6). The interior of the building hosted significantly fewer bacterial species than
either the northeast or southwest corners (glmer, p =0.001), and the northeast corner had a higher
number than the southwest corner. This may reflect both occupant usage and window ventilation
patterns, as both contribute to adding microorganisms to the indoor environment [
15
,
51
]. On average,
settled dust at the shelf level (0.88 m high) contained more bacterial species (p =0.001) than either the
floor or the top (1.12 m high) of the sampling unit (Figure 6).
Buildings 2019,9, 142 9 of 15
Buildings 2019, 9, x FOR PEER REVIEW 8 of 15
Six common VOCs were selected for analysis: acetone, formaldehyde, methanol, benzene,
toluene and monoterpenes. All have outdoor and indoor sources and all of them except benzene and
toluene are known to be emitted from wood products, but each one has other possible sources and
secondary reactions also complicate identifying a specific source for any of them within the scope
and methods of this study. Monoterpenes are emitted from wood products [43] and also derived
from the biosynthesis of plants, as are acetone, formaldehyde and methanol [44,45]. Acetone and
methanol are also often related to urban and industrial activities [46] with many different sources.
Formaldehyde is also known to be among the VOCs emitted by cleaning products and detergents
[47]. Benzene and toluene are known as BTEX and mainly emitted from vehicle exhaust [48] but also
from some detergents, rubbers, resins, and cigarettes [49,50]. Figure 4 shows results for toluene and
monoterpenes, compounds with indoor and outdoor sources, as each canister is connected and
disconnected from the PTR-TOF-MS for analysis. A field blank was also analyzed. Again, the storage
closet with no intended ventilation, was found to have the highest levels of both compounds (30 ppb
Monoterpenes, 17 ppb Toluene).
Figure 4. Results for toluene and monoterpenes over PTR-TOF-MS analysis time for one-minute grab
samples from various building locations and one field blank canister.
HeDS is not an established sampling method for indoor air quality and further inter-comparison
with established methods is needed. This preliminary investigation of the method, paired with PTR-
TOF-MS analysis, was selected because it provided a low-cost, simple to deploy, silent method of
collecting a whole air sample [18]. Replicate samples were, on average, within 34% for five of six
VOCs selected: acetone, formaldehyde, methanol, benzene, and monoterpenes. Figure 5 shows HeDS
results from week 3 for the two open office monitoring kit locations as well as an outdoor sample
taken with an evacuated canister on the roof.
0.1 1 10 100 1000
m59.0439 (acetone H+)
m31.01783 (formaldehyde H+)
m33.03230 (methanol H+)
m79.05478 (benzene H+)
m137.1325 (terpenes H+)
Corrected average mixing ratio (ppb)
21402 (SW building) Avg. 21408 (NE building) Avg. Outdoor Avg.
Figure 5.
VOC results for five compounds from PTR-TOF-MS analysis of week 3 HeDS canisters from
southwest and northeast indoor monitoring kit locations and from the outdoor evacuated canister
location on the roof.
Buildings 2019, 9, x FOR PEER REVIEW 9 of 15
Figure 5. VOC results for five compounds from PTR-TOF-MS analysis of week 3 HeDS canisters from
southwest and northeast indoor monitoring kit locations and from the outdoor evacuated canister
location on the roof.
3.2. Bacterial Community
The mean number of bacterial species observed in dust was affected by the sampling location
within the room as well as the height of sampling, although there was a large amount of variation
among samples (Figure 6). The interior of the building hosted significantly fewer bacterial species
than either the northeast or southwest corners (glmer, p = 0.001), and the northeast corner had a
higher number than the southwest corner. This may reflect both occupant usage and window
ventilation patterns, as both contribute to adding microorganisms to the indoor environment [15,51].
On average, settled dust at the shelf level (0.88 m high) contained more bacterial species (p = 0.001)
than either the floor or the top (1.12 m high) of the sampling unit (Figure 6).
(a) (b)
Figure 6. Bacterial species’ richness in indoor settled-dust from different (a) locations within the
building; (b) heights relative to the floor.
Disturbance of floor surfaces can resuspend settled or tracked-in microorganisms [52], which
distribute within a space based on air currents and thermal plumes, which can pose a differential
exposure to occupants relative to height above the floor and particle size [52,53]. The shelf level is
covered and minimally screened, though is otherwise quite similar in sampling location to the top of
the monitoring kit, suggesting this geometry may contribute to the sample collected. The increase in
species richness may reflect the positioning between two microbial populations; larger particles
which settle out of air to floor surfaces and are resuspended during traffic, and smaller particles
which are more apt to stay airborne but were less likely to be disturbed from the shelf settling dish,
leading to a combined accrual of more bacterial species. The bacterial community collected at shelf-
height was trending towards having fewer bacteria sourced from outdoor air than the floor (Figure
7), but only the top samples had significantly fewer bacterial species that were likely sourced from
outdoor air.
Figure 6.
Bacterial species’ richness in indoor settled-dust from different (
a
) locations within the
building; (b) heights relative to the floor.
Disturbance of floor surfaces can resuspend settled or tracked-in microorganisms [
52
], which
distribute within a space based on air currents and thermal plumes, which can pose a differential
exposure to occupants relative to height above the floor and particle size [
52
,
53
]. The shelf level is
covered and minimally screened, though is otherwise quite similar in sampling location to the top of
the monitoring kit, suggesting this geometry may contribute to the sample collected. The increase in
species richness may reflect the positioning between two microbial populations; larger particles which
settle out of air to floor surfaces and are resuspended during traffic, and smaller particles which are
more apt to stay airborne but were less likely to be disturbed from the shelf settling dish, leading to a
combined accrual of more bacterial species. The bacterial community collected at shelf-height was
trending towards having fewer bacteria sourced from outdoor air than the floor (Figure 7), but only the
top samples had significantly fewer bacterial species that were likely sourced from outdoor air.
Buildings 2019,9, 142 10 of 15
Buildings 2019, 9, x FOR PEER REVIEW 10 of 15
Figure 7. Similarity of indoor air bacterial communities to on-site outdoor air bacterial communities.
Communities sampled from the top of the unit were significantly less like outdoor bacterial
communities than those from the floor or shelf height.
The bacterial community in buildings is not often connected to the occupant experience with
several exceptions: visible microbial growth and building damage or odor complaints, triggering of
asthma or allergy symptoms or facilitating the spread of infectious disease. Due to the recency of this
building’s construction, microbial overgrowth was not a concern, and due to lacking occupant health
data, we are unable to comment. However, microbial communities may impact building occupants
in positive, neutral or negative ways which we are largely unaware of. Exploring these spatial
patterns can be used to form hypotheses about microbial accrual or transit in spaces, and determine
the potential for interaction with occupants.
3.3. Vertical Vibration
Figure 8 displays a ten second segment of footfall-triggered data. Accelerometers A1 through
A3 show the response of a person walking at an approximate pace corresponding to 1.7 Hz. The
recurring footfall signal is not as distinctly visible in accelerometer A4 data. The peak acceleration
measured in this data set is approximately 0.05 g at accelerometers A2, which is indicative that the
person was walking nearest to that accelerometer. In addition, it can be seen that as the amplitude of
the motion in A2 is reduced, at approximately t = 3 s, and increased at A3, indicating the direction of
the movement of the passerby from west to east.
Figure 7.
Similarity of indoor air bacterial communities to on-site outdoor air bacterial communities.
Communities sampled from the top of the unit were significantly less like outdoor bacterial communities
than those from the floor or shelf height.
The bacterial community in buildings is not often connected to the occupant experience with
several exceptions: visible microbial growth and building damage or odor complaints, triggering of
asthma or allergy symptoms or facilitating the spread of infectious disease. Due to the recency of this
building’s construction, microbial overgrowth was not a concern, and due to lacking occupant health
data, we are unable to comment. However, microbial communities may impact building occupants in
positive, neutral or negative ways which we are largely unaware of. Exploring these spatial patterns
can be used to form hypotheses about microbial accrual or transit in spaces, and determine the potential
for interaction with occupants.
3.3. Vertical Vibration
Figure 8displays a ten second segment of footfall-triggered data. Accelerometers A1 through A3
show the response of a person walking at an approximate pace corresponding to 1.7 Hz. The recurring
footfall signal is not as distinctly visible in accelerometer A4 data. The peak acceleration measured
in this data set is approximately 0.05 g at accelerometers A2, which is indicative that the person was
walking nearest to that accelerometer. In addition, it can be seen that as the amplitude of the motion in
A2 is reduced, at approximately t =3 s, and increased at A3, indicating the direction of the movement
of the passerby from west to east.
Figure 9shows the corresponding PSDs plots to the data records shown in Figure 8, in the
frequency range of 0 to 30 Hz. A major frequency peak is observed at a frequency of 9.90 Hz, and
smaller amplitudes for the frequency peaks in the range of 10–20 Hz, while the amplitudes in the
frequency ranging 0–8 Hz shows amplitudes at approximately 1.7 ×10−5g2/Hz and below.
Murray (1999) presented an extensive review of research aimed at quantifying the response of
humans to floor vibration [
54
]. The following factors, affecting the perception and tolerance level
of the human were identified: (a) the frequency of vibration, (b) the magnitude of vibration, (c) the
duration of motion, (d) the occupant’s body orientation and (d) the occupant’s activity. Procedures
for evaluation of the effect of vibrations on humans are presented in documents such as ISO 2631
(2003) and ISO 10137 (2007), where the peak acceleration is used as the threshold for human comfort
in offices or residences subjected to vibration frequencies between 4 Hz and 8 Hz is 0.005 g, or 0.5%
of gravity [
55
,
56
]. The lower threshold within the frequency range of 4 to 8 Hz can be explained by
studies showing that humans are particularly sensitive to vibrations with frequencies in the 5-8 Hz
range [54].
Buildings 2019,9, 142 11 of 15
Buildings 2019, 9, x FOR PEER REVIEW 10 of 15
Figure 7. Similarity of indoor air bacterial communities to on-site outdoor air bacterial communities.
Communities sampled from the top of the unit were significantly less like outdoor bacterial
communities than those from the floor or shelf height.
The bacterial community in buildings is not often connected to the occupant experience with
several exceptions: visible microbial growth and building damage or odor complaints, triggering of
asthma or allergy symptoms or facilitating the spread of infectious disease. Due to the recency of this
building’s construction, microbial overgrowth was not a concern, and due to lacking occupant health
data, we are unable to comment. However, microbial communities may impact building occupants
in positive, neutral or negative ways which we are largely unaware of. Exploring these spatial
patterns can be used to form hypotheses about microbial accrual or transit in spaces, and determine
the potential for interaction with occupants.
3.3. Vertical Vibration
Figure 8 displays a ten second segment of footfall-triggered data. Accelerometers A1 through
A3 show the response of a person walking at an approximate pace corresponding to 1.7 Hz. The
recurring footfall signal is not as distinctly visible in accelerometer A4 data. The peak acceleration
measured in this data set is approximately 0.05 g at accelerometers A2, which is indicative that the
person was walking nearest to that accelerometer. In addition, it can be seen that as the amplitude of
the motion in A2 is reduced, at approximately t = 3 s, and increased at A3, indicating the direction of
the movement of the passerby from west to east.
Figure 8. Accelerometers time records triggered by footfall.
Buildings 2019, 9, x FOR PEER REVIEW 11 of 15
Figure 8. Accelerometers time records triggered by footfall.
Figure 9 shows the corresponding PSDs plots to the data records shown in Figure 8, in the
frequency range of 0 to 30 Hz. A major frequency peak is observed at a frequency of 9.90 Hz, and
smaller amplitudes for the frequency peaks in the range of 10–20 Hz, while the amplitudes in the
frequency ranging 0–8 Hz shows amplitudes at approximately 1.7 × 10
−5
g
2
/Hz and below.
Figure 9. PSDs plots of footfall triggered responses. Human discomfort critical range in red.
Murray (1999) presented an extensive review of research aimed at quantifying the response of
humans to floor vibration [54]. The following factors, affecting the perception and tolerance level of
the human were identified: (a) the frequency of vibration, (b) the magnitude of vibration, (c) the
duration of motion, (d) the occupant’s body orientation and (d) the occupant’s activity. Procedures
for evaluation of the effect of vibrations on humans are presented in documents such as ISO 2631
(2003) and ISO 10137 (2007), where the peak acceleration is used as the threshold for human comfort
in offices or residences subjected to vibration frequencies between 4 Hz and 8 Hz is 0.005 g, or 0.5%
of gravity [55,56]. The lower threshold within the frequency range of 4 to 8 Hz can be explained by
studies showing that humans are particularly sensitive to vibrations with frequencies in the 5-8 Hz
range [54].
Eurocode 5 (2004) [34], which is viewed to be more stringent on floor vibrations than American
standards [55], places a serviceability limit for wood structures with a vertical natural frequency of
less than 8 Hz. HIVOSS (2008), although geared for footbridges, identifies the critical range for
vertical vibrations that produce discomfort, which includes frequencies in the range of 1.25 Hz to 4.6
Hz [35]. The measured floor vibrations at Albina Yard place the fundamental frequency at 9.90 Hz,
outside of the human discomfort range presented in [34,55,56]. The findings provide confidence in
the floor design solution and span lengths.
4. Conclusions
This case study investigated performance aspects of a mass timber building that relate to
occupant experience. Exposure measurements were conducted for three indoor environmental
quality (IEQ) factors to better understand how cross-laminated timber (CLT) and glue-laminated
timber (GLT) wood products and systems impact indoor air quality, indoor bacterial community,
and vibrational comfort in an office environment of a mass timber building.
Indoor air quality was analyzed using both direct-measurement continuous monitoring and
passive air sampling techniques. Indoor and outdoor concentrations were collected and compared.
Multiple data collection periods and locations in the building were considered. In locations with low
or no ventilation, like a storage closet, we observed elevated monoterpene levels compared to well-
Figure 9. PSDs plots of footfall triggered responses. Human discomfort critical range in red.
Eurocode 5 (2004) [
34
], which is viewed to be more stringent on floor vibrations than American
standards [
55
], places a serviceability limit for wood structures with a vertical natural frequency of less
than 8 Hz. HIVOSS (2008), although geared for footbridges, identifies the critical range for vertical
vibrations that produce discomfort, which includes frequencies in the range of 1.25 Hz to 4.6 Hz [
35
].
The measured floor vibrations at Albina Yard place the fundamental frequency at 9.90 Hz, outside
of the human discomfort range presented in [
34
,
55
,
56
]. The findings provide confidence in the floor
design solution and span lengths.
4. Conclusions
This case study investigated performance aspects of a mass timber building that relate to occupant
experience. Exposure measurements were conducted for three indoor environmental quality (IEQ)
Buildings 2019,9, 142 12 of 15
factors to better understand how cross-laminated timber (CLT) and glue-laminated timber (GLT) wood
products and systems impact indoor air quality, indoor bacterial community, and vibrational comfort
in an office environment of a mass timber building.
Indoor air quality was analyzed using both direct-measurement continuous monitoring and
passive air sampling techniques. Indoor and outdoor concentrations were collected and compared.
Multiple data collection periods and locations in the building were considered. In locations with
low or no ventilation, like a storage closet, we observed elevated monoterpene levels compared to
well-ventilated areas like an entryway. We speculate this difference is likely due to accumulation of
monoterpenes emitted from materials and potentially indoor chemistry occurring in these spaces.
Follow-up studies deploying real-time volatile organic compound instrumentation, like chemical
ionization - time of flight - mass spectrometry, in CLT buildings would shed light on the VOC sources
and chemistry occurring in buildings using substantial CLT structural elements. CO
2
data collected
during the first sampling week was used to initiate further investigation of the mechanical ventilation
system and correct a damper position issue. Formaldehyde, toluene and monoterpenes were observed
to vary in concentration across spaces that also varied by ventilation rate.
The height of passive bacterial sampling and the sampling location within the building had a
small but measurable effect on the bacterial communities in settled dust, confirming the effect of
localized conditions on the accrued microbial community. It also suggests the capacity to intentionally
select a microbial community by integrating environmental conditions (i.e. outdoor air), and holds
implications for individual occupant exposure to indoor microbial communities based on location
within a building.
Footfall triggered vibrational accelerations were observed in monitored data to be within the
serviceability range for human comfort. While it is well known that floor dynamic response depends
on both structural and non-structural components, the satisfactory vibration performance of the
studied floor mainly relies on structural features, such as relative short spans and thickness of the CLT
floor panels.
Author Contributions:
Conceptualization, M.R., A.B, E.T.G. and K.V.D.W.; methodology, J.S., S.L.I., A.L.
(Andrew Loia), D.N., I.M., M.R., A.B., E.T.G. andK.V.D.W.; validation, S.L.I., M.R., E.T.G. andK.V.D.W.; formal analysis,
J.S., S.L.I., A.L. (Aur
é
lie Laguerre), I.M. and D.N.; investigation, J.S., A.L. (Aur
é
lie Laguerre), A.L. (Andrew Loia), G.M.,
I.M., D.N., M.R. and A.B.; resources, M.R., A.B., E.T.G. and K.V.D.W.; data curation, J.S., S.L.I., A.L. (Aur
é
lie Laguerre),
I.M. and D.N.; writing—original draft preparation, J.S., S.L.I., A.L. (Aur
é
lie Laguerre) and I.M.; writing—review and
editing, J.S., S.L.I., A.L. (Aur
é
lie Laguerre), A.L. (Andrew Loia), G.M., I.M., D.N., M.R., A.B, E.T.G. and K.V.D.W.;
visualization, J.S., S.L.I., A.L. (Aur
é
lie Laguerre), I.M. and D.N.; supervision, M.R., A.B, E.T.G. and K.V.D.W.; project
administration, M.P. and K.V.D.W.; funding acquisition, M.R., A.B, E.T.G. and K.V.D.W.
Funding:
This work was funded by a grant with the U.S. Department of Agriculture’s Agricultural Research
Service [USDA ARS Agreement No. 58-0202-5-001], a grant to the Biology and the Built Environment Center
from the Alfred P. Sloan Foundation [grant no. G-2015-14023], and by start-up funds provided by Portland
State University.
Acknowledgments:
The authors wish to acknowledge the building owner, Reworks Inc., for providing access
to the building; the building architect and fourth-floor occupant, Lever Architecture, for providing access to
their office and occupant survey feedback. The authors would like to thank Leslie Dietz and Susie Nunez at the
University of Oregon for their contribution to molecular biology laboratory work; Mark Fretz, Alejandro Manzo,
and Daniel Roth at the University of Oregon for their contribution to fieldwork.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to
publish the results.
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