IGERTSummary

Real-time Formaldehyde
Monitoring System

IGERT Sensor Science, Engineering
and Informatics (SSEI)
Clint Eaton
J.C. Whittier
Stacy Doore
Delia Massey
Paul Smitherman

• Introduction
• Project Goal and Objectives
• Phase I
– Device Testing
– Network Testing
– System Informatics
• Phase II
– Site Testing
• Commercialization Applications
• Conclusions and Future Work
Formaldehyde Monitoring in Built Environments
O
C
H
H

Problem:
• Formaldehyde emissions and
toxic exposure concerns,
• Formaldehyde Standards Act (2010)
• EPA regulations: all wood based
building materials meet new, lower
emissions standards by 2013,
• Can we detect formaldehyde
emission levels in real time and
provide a web-based user interface
for facility managers?

Agency/Industry Group Exposure Limit
(TWA-8hr average)
Short-term
Exposure Limit (15
minute maximum)
Threshold
Limit Value
(Ceiling)
NIOSH/CDC (2009) 0.016 ppm (REL) 0.10 ppm 0.10 ppm
ACGIH (2009) ----- ----- 0.30 ppm (TLV)
OSHA (2008) 0.75 ppm (PEL) 2.0 ppm 5.0 ppm
FEMA (2008) 0.016 ppm 0.10 -----
HUD (1985) 0.40 ppm ---- -----
Effective Date Hardwood
Plywood
Particleboard Medium density
fiberboard
By 1/1/2011 0.05ppm (veneer) 0.09ppm 0.11ppm (MDF)
By 7/1/2012 0.08ppm
(composite)
----- 0.13ppm
(Thin MDF)
U.S. Agency Formaldehyde Exposure Limits
Formaldehyde Standards Act (2010) based on CARB standards

Objectives:
1. Compare the performance of commercially available sensors
and their ability to detect formaldehyde within a dynamic range
of 0.01 and 0.80 ppm.
2. Design and build wireless network architecture to transmit
real-time formaldehyde concentration data.
3. Identify formaldehyde emission patterns in a real world
environment.
4. Develop prototype model for assessing low-level
formaldehyde environmental exposures in real-time.
5. Explore possible changes in existing engineering controls and
exposure assessment processes to improve worker safety.

Goal: Design and build wireless sensor network to
detect/monitor formaldehyde emissions in industry setting.

Issues raised during alpha test…
• Office question: Were the high readings result of
power flux, lighting, cleaning products, etc.?
• Device Calibration: Could personal exposure badges help?
• Previous EHS testing at AEWC?
• Formaldehyde emissions from human breath?
• Could we use RFID badges to track the location of people?

•Phase I
– Device Testing
– Network Design
– System Informatics

• Sensor interface – RSR-232 serial with USB adapter
• Sampling method – 10 mL snatch-sample of air taken
by internal pump
• Programmable data collection scheduler
• Supplied calibration standard
• Temperature and humidity corrected
• Response time < 10 sec
• Cost range: $1,100-$3,700
• High sensitivity
• Linear response
• Stable sensitivity
Formaldemeter htV-M

• Anode: where oxidation occurs,
positive polarity contact
• Cathode: where reduction occurs,
negative polarity contact
• First experiments by Sir William
Grove in 1839
• Electrons generated flow from
anode to cathode
Formaldemeter Electrochemical Sensor
Operation

Formaldemeter System Block diagram
PRECISION
AMPLIFIER
HIGH RESOLUTION
A-D CONVERTER
MICROPROCESSOR
DISPLAY
EXHAUST
VANEPU
MP
FUEL
CELL
GAS INLET
ELECTRICAL
SIGNAL
• Electrochemical technology
• Snatch sampling via micro pump
• Air drawn into sensor
• Formaldehyde oxidizes to generate
a small current
• Three amplification stages
• High resolution digital sampling
system

Advantages
•High sensitivity to low
vapor concentrations
•Linear response over wide
conc. range
•Small, rugged and reliable
•Stable sensitivity over long
period of time
•Long working life
Disadvantages
•High cost of production materials
(e.g. precious metals)
•Can be susceptible to
interference effects from certain
other compounds capable of
oxidation
•Different modes of calculating
concentrations
(peak, area, time)
Formaldemeter Summary

Calibration Method
The Formaldemeter htV-M:
• calibrated bi-weekly with calibration tool supplied by the
manufacturer
• exposed to formaldehyde using a permeation tube from
Vici at 5 concentrations (.03, .05, .075, .10, .15 ppm)

Dart HCHO Sensor
• 11 mm two-electrode diffusion sensor
• 250-300 nA/ppm output signal
• Response time is 15 seconds at 20o
C
• Dynamic Range: 0-25 ppm
• Cost: $30-$110
Commercialization Potential
• Circuitry for current to voltage required
• Combine with temperature/humidity
sensors
• Develop concentration curves that are
temperature/humidity dependent
• Algorithm development for marriage of
output voltage to temperature and
humidity data

ACS Badge:
• Adsorption technology consisting of
2,4 Dinitrophenylhydrazine
• Lab analyzed with GC-MS
• OSHA gold standard
• provides 8 hour TWA, however...
Scenario 1: .09, .09, .09, .09, .09, .09, .09, .09 = .09 ppm
Scenario 2: .02, .02, .12, .2, .2, .13, .02, .02 = .09 ppm
Mean ppm exposure statistics obscure the actual risk
associated with shorter term exposure to higher level
formaldehyde emissions.

Phase I: Device Calibration, Validation and Selection

Network Design/Configuration
• The network consists of 5 wireless sensor node network, a
base station, a Sensor Observation Service (SOS), database
system, and a web-based user interface.
• Each Formaldemeter was connected to an XBee radio.
Readings were output from the serial port to the XBee UART.
• Base station (laptop) collected data from all nodes and pass
it onto the SOS to be stored in a database.
• Web-based user interface displayed latest readings and
could be queried for historical analysis.

Node Radio Design
PPM RS232
Voltage
11 V peak to peak
Xbee Radio
TTL
Voltage
0-5 V
To Base Station
Voltage
Conversion
Max232a
Voltage
Conversion
Max232a

Sensor nodes
DetectReceive/TransmitProcess/AnalyzeKnowledge/Actio
Base station Web-based
User Interface
ase I: Network Design and Testing
SOS/SQL Server
Database
Raw Data = Package/StringProcessed Data = Dashboard

Use case 1:
Data
Discovery
Unit of
Measurement
Unit of
Measurement
Feature &
Properties
Feature &
Properties
ObservationsObservations
Use case 2:
Sensor
Selection &
Discovery
Sensor typesSensor types
Sensor
capabilities/
restrictions
Sensor
capabilities/
restrictions
Deployment
Systems
Deployment
Systems
Use case 3:
Provenance &
Diagnostics
Use case 4:
Tasking &
Programming
Operating
Restrictions
Operating
Restrictions
Process
model
Process
model
ensor Network Uses Cases and Concepts

Why an Ontology?
Ontology: Provides standardized vocabulary and specification
of concepts and relationships within or across domains.
Expressed in Web Ontology Language (OWL) which is grounded
in Description Logics (DLs). Defines concepts, properties
(relationships), and logical combinations of concepts to support
inference.
Advantages:
• Can use existing ontologies, languages, querying, and
reasoning tools
• W3C standards and guidelines in process
• Need system to be able to store and query very large
dynamic datasets
• Semantic modeling of multiple domains allows for creation
of reusable data and interoperability across domains

Ontology based Linked Data Approach
Domain
ontology
Domain
ontology
Observation
ontology
Observation
ontology
Sensor
Network
ontology
Sensor
Network
ontology
Spatio-
temporal
ontology
Spatio-
temporal
ontology
Exposure
ontology
Exposure
ontology
System &
sensors node
capabilities
Measurement units
Sensor/Person
location
Properties of Entity
Exposure
events
Units
ontology
Units
ontology
hase I: System Informatics

Database System
• Records observations from
sensors at nodes
• Simplified schema based on
OGC sensor ontologies
• Can store data for PPM,
DART, badge, and location
• Supports changes to the
sensors deployed at a node
and location of the node

User Interface

Phase I Accomplishments
• Built wireless sensor network for formaldemeters
• Calibrated the formaldemeters to Vici permeation device
• Investigation into Dart sensor properties
• Conceptual framework guided database development

Resin
Blender
• Phase II
– Site Testing
Resin
blender

Resin
Blender
Press
Office
lient Facility: AEWC

Exploratory Questions for Site
Tests:
1. Under what conditions is it safe to open the blender
door during the resin application process?
2. Where/when are the highest HCHO concentrations
occurring?
3. How do existing HVAC controls impact the HCHO
emissions during typical processes?
4. Are sensors/badges accurately reflecting
concentration measurements?
5. Is there evidence that other work areas are being
impacted by HCHO emissions during manufacturing
processes?
6. Can the system help to identify environmental events

~8’
~8’
N2
Breathing Zone=
~1ft of nose/mouth
N3
~6’
N4
Side views 1 and 2
N1
N2
N3
N4
N5
Top View
N5N4
esting Variables:
Sensor Placement
short, long, plume, break)
Resin Type and Volume
Wood Total
Engineering Controls
N1
Test 1,4 and 5
Test 2 and 3

Alpha Test April 20-21
Mean = 0.0244
Median = .0103
Mode = .007
SD = .022
SEM = .0004
Variance = .00
Skew = .89
Range .068
Min = .005
Max = .073
“Dry Run” Test conducted during AEWC client testing.
Formaldehyde resin used with all normal engineering controls in place.
OSHA exceed PEL events (≥ 0.75 ppm)
NIOSH exceed REL events (≥ 0.016 ppm)
OSHA exceed STEL events (≥ 2.0 ppm)
NIOSH > STEL/ceiling events (≥ 0.1 ppm)
Event 1
(4/21 12:32am-8:32am)

Blender Tests April 26
Tests used 5 node wireless system deployed inside/outside blender.
Formaldehyde resin used both with/without normal engineering controls.
Potential Event Thresholds
OSHA exceed PEL events (≥ 0.75 ppm)
NIOSH exceed REL events (≥ 0.016 ppm)
OSHA exceed STEL events (≥ 2.0 ppm)
NIOSH exceed STEL/ceiling events (≥ 0.1 ppm)
Test Hood
Fan
Blender
Fan
Start
Time
Stop
Time
Sensor
Height
(ft)
Fan on
Hood (s)
Time
Door
Open
Resin
Type
1 ON ON 903 907 5 15 910 PUF
2 ON ON 924 927 5 15 930 PUF
3 OFF OFF 951 954 5 0 956 PUF
4 OFF OFF 1044 1047 5 0 1050 PUF
5 OFF OFF 1144
(1147)*
1149 5 0 1151 PUF

Blender Tests (1-5)
Inside Blender

Test 1
Door open
9:10
Test 2
Door open
9:30
Test 3
Door open
9:56
Test 4
Door open
10:50 Test 5
Door open
11:51
Outside Blender

Blender
Test 1
Event
(4/26 9:02am-9:17am)
Test 1
Door open
9:10
Outside Blender (Nodes 2-5)
Inside Blender (Node 1)
Mean = .077
Median = .0688
Mode = .068
SD = .017
SEM = .0027
N = 40
Variance = .000
Skew = .863
Range .049
Min = .058
Max = .107
Descriptives Peak PPM (Nodes 2-5)

Event
(4/26 9:20am-9:35am)
Test 2
Door open
9:30
Blender
Test 2
Mean = .071
Median = .065
Mode = .066
SD = .016
SEM = .002
N = 56
Variance = .000
Skew = 1.00
Range .048
Min = .055
Max = .103

Event
(4/26 9:56am-10:18am)
Test 3
Door open
9:56
Blender
Test 3
Mean = .088
Median = .084
Mode = .085
SD = .026
SEM = .022
N = 116
Variance = .001
Skew = 1.486
Range .149
Min = .056
Max = .205

Event
(4/26 10:50am-11:10am)
Test 4
Door open
10:50
Blender
Test 4
Outside Blender (Nodes 2-5)Inside Blender (Node 1)
Mean = .087
Median = .0733
Mode = .073
SD = .038
SEM = .004
N = 72
Variance = .001
Skew = 2.228.
Range .179
Min = .056
Max = .235

Event
(4/26 11:51am-12:10am)
Test 5
Door open
11:51
Blender
Test 5
Outside Blender (Nodes 2-5)Inside Blender (Node 1)
Mean = .086
Median = .079
Mode = .060
SD = .0311
SEM = .003
N = 88
Variance = .001
Skew = 1.708
Range .130
Min = .060
Max = .190

Outside Press/Inside Curtain(Nodes2-Inside Press (Node 1)
Board Press
Test 6
Mean = .182
Median = .094
Mode = .060
SD = .350
SEM = .035
N = 96
Variance = .123
Skew = 4.959
Range 2.00
Min = .057
Max = 2.057

Tues. April 26 Wed. April 27
Board
Emission Test
Mean = .190
Median = .190
Mode = .15
SD = .036
SEM = .0006
N = 2960
Variance = .001
Skew = -0.388
Range .26
Min = .01
Max = .27

Office Test
Conducted over 8 days to assess ambient air quality in
non-lab areas using only 1 node in data logging mode.
No formaldehyde resin was directly introduced into the
environment at any time.
Event (≥ 2.0 ppm) on 4/26
Events (≥ 0.016 ppm) on 4/21, 4/23, 4/26, 4/27
Events (≥ 0.1 ppm) on 4/23, 4/24, 4/26, 4/27

Mean = 0.018 Mean = 0.018 Mean = 0.016
Mean = 0.03 Mean = 0.094 Mean = 0.013
Mean = 0.188 Mean = 0.163

Office Test MEAN PPM by Day
* sig. at .01 level
*
*
*
*
One way ANOVA
Post Hoc: Tukey HSD
Bonferroni

Office Test HCHO, Temp, Humidity (Zscores)

Office Test HCHO, Temp, Humidity (Zscores)
Pre-Weekend

No Maps?
Insufficient Number of Data Points!

• Engineering controls (hood, fan, door) seem to
be working well to protect lab area during
blender process
• Possible emission issues may arise once
boards are pressed and left in lab to dry
• Highest HCHO concentrations occurred during
press processes
• Unexplained HCHO events in office
• System functioned with few node failures
hase II Exploratory Findings

Next Steps
• Work on new circuit board for DART to design
implement, and test second sensor network
• Concentration verification
• Continue data analysis to identify events
• Collect more data from AEWC offices
• Submit proposals to NSF and EPA for additional R
& D funding

Unique product to meet identified industry need for
indoor air quality/exposure assessment tools/methods:
• wood product manufacturing
• manufactured homes and RVs
• furniture, carpet, wallboard, paint manufacturing
• mortuary supplies
• hair care products
ommercialization Applications

So why is this important?
International Center for Toxicology and Medicine
http://www.ictm.com/Investigation/Root-Cause.aspx

Conclusions
• Identified immediate need for wireless
formaldehyde monitoring application,
• Tested several commercially available
sensors to deploy in network,
• Designed and implemented wireless network
to collect formaldehyde data in real world
setting, and
• Exploratory analysis and representation of
formaldehyde emissions and exposure
processes.

Acknowledgements
• NSF IGERT Sensor Science, Engineering and Informatics
DGE Award number 0504494
• Dr. Kate Beard, SSEI Director
• Dr. Brian Frederick, Project Advisor
• Dr. Steven Shaler, Dr. Doug Gardner, Russell Edgar,
and UMaine’s Advanced Structure & Composite Center

Questions?
Abby NormalAbby Normal

Calibration Calculations
C(ppm) = (P * (24.46/MW))/Fc)
C = the concentration in PPM by
volume
P = the permeation rate in ng/min
MW = the molecular weight of the
pollutant gas
Fc = the total flow of the calibration
mixture in cc/min
The constant 24.46 is the molar
volume at the reference conditions.
P (ng/min) 29
MW (g/mol) 30
24.46
Fc
(ppm)
Fc
(ppm)
Fc
(ppm)
Fc
(ppm)
Fc
(ppm)
0.03 0.05 0.075 0.1 0.15
23.6 23.6 23.6 23.6 23.6
788.2 472.9 315.3 236.4 157.6
mL/min mL/min mL/min mL/min mL/min

Calibration Calculations
Log P1 = log P0 + a (T1 - T0)
P0 = Rate at temp T0 (°C)
P1 = New rate at temp T1 (°C)
a = 0.030 for high emission tubes
estimate 1°C decrease in
temperature decreases the rate by
10%.
rate in ng/min
P1 29 1.46
P0 60 1.46
T1 19.5
T0 30

Sensitivity and Selectivity of
Formaldemeter
Formaldehyde Sensor Type Electrochemical, two noble
metal electrodes and electrolyte
(proprietary)
Formaldehyde Sensor Dynamic
Range
0.05 -10 ppm
Formaldehyde Sensor
Resolution
0.001 ppm
Formaldehyde Sensor Precision 10% at 2ppm level
Temperature/Humidity Interchangeable digital
CMOSens®
Temperature/Humidity Range -40 to 128 °C, 0-100%
Temperature/Humidity
Accuracy
±0.4°C, ±3% RH
Temperature/Humidity
Calibration
Calibrated to ISO/IEC17025 by
manufacturer

Interference
Compound 1 ppm interference
concentration
Comments
Acetone, Acetic
Acid, Butanol
-- --
Acetaldehyde 8-12 Linear
Ammonia 71000 High Concentration
Carbon Monoxide 100 Linear
Ethylene 160 --
Ethanol, Methanol 12-20, 50 Linear
Phenol, Resorcinol 5,5 Filterable

Performance Characteristics of Sensors
Technology Specification Chemisresistive Sensor Optical Sensor Biological Sensor
Sensing Mechanism Metal Oxide Semiconductor Difference Frequency Generator Biological enzymatic reaction
Transduction Process Resistivity change results in
electrical output
MCT Detector Photomultiplier Tube (PMT)
Signal Processing Principal Component Analysis Spectral analysis Algorithms for photon counts
Sensitivity 10’s of ppb (part per billion) 10’s of ppt (parts per trillion) 1’s of ppb
Response/analysis time < 1 minute (ppm) >1 minute
(ppb)
1 minute 2 minutes
Sampling system Micro pump and tubing Multipass absorption cell fed
with ambient air by vacuum
pump
Flow cell comprised of silicone
tube and PMMA cell
Selectivity constraints Poor selectivity Unaffected by humidity Highly selective with minimal
interference

Formaldehyde detection competitors
Sensor
Company
Real
Time
Data
LCD
Display
Wireless
Network
Data
storage/
analysis
Compute
r
Interface
Portable Threshol
d Alarm
OSHA
certified
List
Price
($)
Enmet PPM X X X X X X X 3800
CEA
Instruments
X X X X 2000
Advance
Chemical
Sensors
X X 40
Interscan X X 2000
Environmental
Sensor
Company
X X 1200

Dart Performance Characteristics
Dynamic Range 0.01-25 ppm
Expected Life 5 years in non-corrosive environment
Output signal 250-300 nA/ppm
Temperature Range -10 to 40°C
Pressure Range Up to 10 atmospheres pressure
T90 response time 15 seconds at 20°C
Relative humidity range 15%-90% non-condensing
Typical baseline offset (20°C) 0.02 ppm formaldehyde equivalent
Typical baseline offset (20°C-40°C) 0 to -0.30 ppm (Economy) Premium TBA
Repeatability <+/-2%
Output Linearity Linear
Position Sensitivity None
Storage Life 2 years at 20°C

Need Context for...
• Entity of Interest: Object (Sensor)
• Observation and Measurement
• Entity of Interest: Object (Person)
• Location Context
• Intersection of Person-Location Event and Noteworthy O&M-Location
Event = Exposure Event

o CHEMICAL ENERGY -> ELECTRICAL ENERGY
o Typically consist of two electrodes in contact with an
electrolyte
o ANODE: where oxidation occurs
o CATHODE: where reduction occurs
o Electrons generated flow from anode to cathode
o Similar to galvanic cell (battery): reactions occur
spontaneously
o Reactants are supplied from outside rather than
forming an integral part of its construction
Electrochemical Introduction

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