Quality Assurance
& Documentation
"One way to open your eyes is to ask yourself,
'What if I had never seen this before?
What if I knew I would never see it again?'"
-Rachel Carson
&EPA
EPA 206-B-18-001
United States
Environmental Protection
Agency
https://go.usa.gov/xEw43

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Examples for Citizen Science
Quality Assurance and Documentation
March 2019
Disclaimer: EPA is distributing this information solely as a public service. The inclusion of companies and their
products in this document does not constitute or imply endorsement or recommendation by the EPA. EPA
retains the sole discretion as to what extent it will use data or information produced or resulting from use of this
document.
This document does not define, or otherwise limit, the purpose to which citizen scientists may seek to apply
their data or information.

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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Introduction
This Compendium of Examples includes text (narrative statements) and tables adapted from several Citizen
Science Quality Assurance Project Plans or planning documents. Many are from volunteer water quality
monitoring programs, but we also included examples (or "samples") from air quality and biological
monitoring projects. We have tried to use examples that follow the recommended tables and narratives found
in the Templates document. In some cases, we have provided more than one example for each template, to
capture the range of information that can be provided in the QAPP. We have removed names of individuals
and replaced them with standard titles such as project manager, or quality assurance manager. And, we
have changed the formats of the original QAPPs to better align the information to the Templates, and to
illustrate specific principles highlighted in the Handbook and Templates. Finally, we have populated the
tables with typical, or suggested, quality control performance goals or acceptance criteria. These goals,
however, are not meant to be prescriptive, as projects should evaluate goals based on project purpose,
funding, number of volunteers, and other factors.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Examples for Templates 1-19
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #1: Title and Preparer Page
Title: Environmental Monitoring Program QAPP
Revision Number: 2
Date: Month x, 20XX
Page x of xx
Project Name: Citizen Science Environmental Monitoring Program
Effective Date of Plan: Month x, 20XX
Name(s) who prepared the plan:
Printed Name and Title: Environmental Monitoring Program Citizen Science Coordinator
Signgture gnd Dgte:	
Printed Ngme gnd Title: Environmentol Monitoring Program Quglity Assurance Mgngger
Signgture gnd Dgte:	
Printed Ngme gnd Title: Stgte Depgrtment of Environmentol Protection Section Leoder
Signgture gnd Dgte:	
Printed Ngme gnd Title: Environmentol Monitoring Lgborotory Director
Signgture gnd Dgte:	
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #2: Example Table of Contents
Title and Preparer Page 	x
Table of Contents	x
Problem Definition, Background and Project Description	x
A.	Problem Definition 	x
B.	Background	x
C.	Project Description	x
Data Quality Objectives and Data Quality Indicators 	x
A.	Data Quality Objectives	x
B.	Data Quality Indicators	x
Project Schedule	x
Training and Specialized Experience	x
A.	Training	x
B.	Specialized Experience 	x
Documents and Records	x
Existing Data and Data from Other Sources	x
Sampling Design and Data Collection Methods 	x
A.	Sampling Design 	x
B.	Data Collection Methods	x
Sample Handling and Custody	x
Equipment List, Instrument Maintenance, Testing, Inspection and Calibration 	x
Analytical Methods	x
Field and Analytical Laboratory Quality Control Summary	x
Data Management	x
Reporting, Oversight and Assessments	x
Data Review and Usability	x
Project Organization Chart	x
Project Organization	x
Project Distribution List	x
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #3: Problem Definition, Background, and Project Description
Problem Definition:
Invasive species are a global problem, with potentially high economic costs, and the potential to change
ecosystem functioning and diversity. This project monitors a subset of invasive species selected for their
relative ease in identification, as well as their potential for negative impacts to our coastal communities and
habitats.
Background:
This is a volunteer invasive species monitoring program operated by the State Office of Coastal Zone
Management. The program was conceived as a citizen-based complement to the intensive surveys of the
Marine Invasive Species Rapid Assessment, which are conducted by a group of state, federal, non-profit and
academic partners every three years.
The main goal of the program is to provide early detection of newly arrived non-native species soon after
introduction and before populations become established, as well as track the abundance and distribution of
invaders already established such as the Green Crab. Because marine systems are open (as compared to
lakes and ponds for example), management and eradication of marine invasives once they have been found
in the environment is extremely difficult. The majority of marine invasives are spread internationally through
aquaculture or shipping, necessitating national or international regulatory changes rather than individual
actions.
This project train citizens to monitor invasive species at three islands. Results from the first two years of
monitoring show that island sites show higher abundances for several invasive tunicates, than the mainland
sites.
Project Description:
The program monitors in three distinct coastal "habitats" which are docks and marinas, tide pools, and
cobble shores, in coastal waters, using protocols developed by the program. Volunteers are given 23
Species Identification Cards for sixteen known invaders (like the star tunicate), and seven potential invaders
(like the Chinese mitten crabs) selected because of their status as invaders and are relatively easy to identify
without the use of microscopy or dissection.
Project Objectives:
The main goal of the program is to provide early detection of newly arrived non-native species soon
after introduction and before populations become established, as well as track the abundance and
distribution of invaders already established such as the Green Crab.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Project Sites:
Site Name
Island
Descriptions
Tidepool 1
Island 1
Tidepool on backshore of Island
Tidepool 2
Island 2
Tidepool on southern end of Island
Dock 1
Island 1
Main ferry dock on Island 1
Dock 2
Island 2
Main ferry dock on Island 2
Pier 1
Island 3
Main ferry dock on north end of Island
Time Period:
The volunteer team visits the same site(s) monthly for six consecutive months, from May through October.
Data Users:
The program educates the public (e.g. boaters, fishermen, aquaculturists, teachers) on preventing the spread
of marine invasives, especially the Chinese Mitten Crab which attaches to fishing gear, or tunicates that cling
to lobster traps, which could be spread by power washing directly into the water.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #4: Data Quality Objectives and Data Quality Indicators
Data Quality Objectives
For a water quality project:
Sufficient and accurate water quality and macroinvertebrate data are collected to document the locations of
high quality and impaired stream segments in our state.
For a continuous air monitoring project:
Continuous measurements of ozone are collected on an hourly basis so that variability and uncertainty are
minimized; the likelihood of decision errors is reduced when comparing results statistically to the national 8-
hour standard; and data can be used for screening purposes.
For a biodiversity research study using volunteers:
Plant species in the study area's impacted wetlands are accurately identified by the volunteers.
Data Quality Indicators
Typical Data Quality Indicator (DQI) activities and performance goals for in situ measurements
(temperature using a sonde), discrete bottle samples analyzed in a laboratory (for chlorophyll a, a
measure of algal biomass, using a standard EPA method)
Data Quality Indicator
Quality control activities and
checks
Performance Goal
PRECISION
Field data
Duplicate temperature profiles will be
taken at three sampling stations during
each sampling event. Field duplicate
bottle samples will be collected at
25% of stations.
Relative percent difference (RPD)
of temperature readings <0.2 °C.
RPD for field duplicate algae
(chlorophyll a) samples <25%.
Laboratory data
Laboratory duplicates (i.e. splits) for
10% of samples.
RPD for laboratory duplicate
algae (chlorophyll a) samples
<25%.
BIAS
Field data
Check calibration records for sonde
temperature sensor.
Return to vendor for annual
calibration.
Laboratory data
Blank filters and calibration standards
from 0.05|jg/L- 200|jg/L will be used.
RPD for chlorophyll a calibration
standard < 10% of known
concentration. Blank filters show
no contamination.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
REPRESENTATIVENESS
Field data
Evaluate sample design in terms of
spatial (e.g. upstream and
downstream, mid-point and edge of
river) and temporal (or seasonal)
variability for both baseline
(unimpacted) and impacted conditions.
We are sampling within a 1 km
section of the river, upstream, at
the discharge and downstream to
capture temperature and algae
(chlorophyll a). We are only
assessing during summer, so data
are meant to be representative of
summer months only. Upstream
samples should represent
unimpacted conditions.
All our sampling locations are in
the middle of the river. We will
collect one out of 10 samples
simultaneously at both mid-point
and edge of river to capture
variation in temperature and
chlorophyll a, to determine
whether mid-point samples are
sufficiently representative of the
river segment.
Laboratory data
N/A
N/A
COMPARABILITY
Field data
Compare methods to previous or
existing studies.
The selected sonde model is a
commonly used instrument and
similar in specifications (e.g.
sensitivity, range) to sondes from
other studies, including the
continuous monitoring sonde on
the University buoy located in the
river segment. Data from this
sonde will be evaluated for
usable data during the same time
periods.
Laboratory data
Compare methods to previous or
existing studies.
Standard EPA Method 445.0 is
comparable to data collected
using similar methodology.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
COMPLETENESS
Field data
Evaluate percent of samples collected.
Temperature profiles will be
conducted at 100% of the
stations. We expect to collect 42
chlorophyll a samples, including
14 duplicates. If weather or other
issues impede a sampling event,
the event will be rescheduled.
Laboratory data
Evaluate percent of samples collected.
100% of all collected samples will
be analyzed.
SENSITIVITY OR DETECTION (REPORTING) LIMITS
Field data
Evaluate specifications for sonde.
The sonde has a sensitivity of
0.1 °C for a temperature range of
-5 ° C to 95 °C. Depth
measurements will be made in cm.
Laboratory data
Evaluate detection limit of laboratory
methods.
EPA Method 445.0 has a method
detection limit of 0.05|jg
chlorophyll a/L.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Data Quality Indicators and Performance Goals for Screening Stormwater Quality in New England
Parameter
Method
Reporting Limits
or Measurement
Range
Water
Quality
Criteria or
Guidelines
(MA or EPA)
Precision or
Resolution
Accuracy
Completeness
Field measurements
PH
Sonde
4 to 10 pH units
6.5-8.3
0.02 units
+ 0.3 units
90%
Temperature
Sonde
0 to +40°C
28.3°C
0.1 °C
+ 0.15°C
90%
Specific Conductivity
Sonde
0 to 100 mS/cm
N/A
5 uS/cm
+ 10% cal std
(|jS/cm)
90%
Dissolved Oxygen
(DO)
Sonde
0.5mg/L to Sat
>5 mg/L,
>60%
saturation
0.02mg/L
± 0.5 mg/L
90%
Surfactants
Chemetric
s Field Kit
0.25 mg/L1
0.25 mg/L
Field dup 30%
RPD
See SOP
90%
Ammonia
Test Strip
0.25 mg/L1
1.0 mg/L
Field dup 30%
RPD
See SOP
90%
Chlorine
Hach Field
Kit
0.02 mg/L
N/A
Field dup 30%
RPD
See SOP
90%
Laboratory measurements
Total Phosphorus

5.0 ug/l
N/A
Field dup 30%
RPD
MS 70-
130%
90%
Total Suspended
Solids (TSS)

5 mg/L
N/A
Field dup 30%
RPD
See SOP
90%
Biochemical Oxygen
Demand (BOD)

2 mg/L
N/A
Field dup 30%
RPD
See SOP
90%
Total Petroleum
Hydrocarbons (TPH)

Variable
N/A
Field dup 30%
RPD
See SOP

E. coti

4 colonies per
100 ml
<=126
col./lOO ml*
<= 235
col./l00 ml
+ 100
col/100ml or
30% RPD
N/A
90%
Enterococcus

1 colony per
100ml
<=33
col./l00 ml*
<=61
col./l00 ml
+ 100
col/100ml or
30% RPD
See SOP
90%
1 Needs field verification to confirm; * = geometric mean criterion; N/A = not applicable
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Examples of Suggested Data Quality Indicators and Performance Goals for Air Sensors for 4 Types of
Citizen Science Applications
Purpose of Monitoring
Pollutants
Precision and
Bias Goals
Data
Completeness
Goals
Rationale
Education and
Information
All
<50%
> 50%
Measurement error is not as
important as simply demonstrating
that the pollutant exists in some
wide range of concentration.
Hotspot Identification
and Characterization
All
<30%
> 75%
Higher data quality is needed here
to ensure that not only does the
pollutant of interest exist in the
local atmosphere, but also at a
concentration that is close to its
true value.
Supplemental
Monitoring
Criteria
pollutants,
Air Toxics
(incl. VOCs)
<20%
> 80%
Supplemental monitoring might
have value in potentially providing
additional air quality data to
complement existing monitors. To
be useful in providing such
complementary data, it must be of
sufficient quality to ensure that the
additional information is helping to
"fill in" monitoring gaps rather than
making the situation less
understood.
Personal Exposure
All
<30%
> 80%
Many factors can influence
personal exposures to air
pollutants. Precision and bias
errors suggested here are
representative of those reported in
the scientific literature under a
variety of circumstances. Error
rates higher than these make it
difficult to understand how, when,
and why personal exposures have
occurred.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Additional Data Quality Indicator Activities and Performance Goals for Discrete, Integrated (e.g. composites over
24-hour periods) or Continuous Air Measurements
Data Quality Indicator
Activity
Performance Goal
Precision
Duplicate or collocated instruments are run
concurrently (or side by side).
See previous table for goals based on
purpose of study.
Bias
Instrument verification for continuous measures in
the field include weekly side-by-side comparisons
of similar field instruments and daily comparisons
of sensors' response to known standards or
reference devices (i.e. calibration).
See previous table for goals based on
purpose of study.
Representativeness
Evaluate significant events that may impact
results.
Information about significant events
near the site that may affect the
representativeness of the sample will
be noted so unusual sample
concentration data can be identified.
Representativeness
Evaluate seasonal representativeness.
To be temporally representative of the
annual concentration at a given site,
the sample dates must be as evenly
distributed as possible to capture
concentrations that fluctuate seasonally
or according to weather patterns.
Comparability
Compare data collected using an air sensor to a
co-located federal reference method (FRM) so
that the data produced by the sensor are
comparable to approved methods.
Similar Relative Percent Difference
(RPD) as for co-located measures.
Note that this applies to this study only;
does not imply that this method is
comparable to FRM in all cases.
Completeness
Evaluate the percentage of field measurements
(discrete or continuous) made within the time
range of interest. If a sample result is missing or
has been invalidated because of validation
checks, it may not be counted toward
completeness.
See previous table for goals based on
purpose of study.
Sensitivity
Compare manufacturer specifications or
instrument detection limits to appropriate action
levels.
The sensitivity of the instrument in use is
the minimum detection limit of the
instrument. This can be based upon
manufacturer specifications or studies
to determine the minimum detection (or
reporting) limit of the instrument.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Data Quality Indicators for Biological Sampling
Parameter
Units
Accuracy
Precision
Measurement Range
Macroinvertebrates (rivers,
lakes, wetlands)
Individual organism
95% voucher specimens
accurately identified to family or
order level, verified by experts.
N/A
N/A
Aquatic plant characterization
Individual organism for
ID, % area for
distribution
All specimens identified to genus
or species with positive
taxonomic confirmation of
voucher specimens by experts for
100% of samples for first crew
survey (% for successive surveys
dependent on initial QC)
N/A
N/A
Macroinvertebrates
N/A
All preserved specimens
accurately identified to family or
order level; taxonomic
confirmation of voucher
specimens by experts.
Standard laboratory
procedures; 90%
Accuracy of identification
when Invertebrate
Scientific Advisor examines
a minimum of 10% of the
original samples

Nekton
N/A
100% Accuracy of identification
evaluated by the Scientific
Advisor(s)
N/A
N/A
Birds
N/A
100% Accuracy of identification
evaluated by the Scientific
Advisor(s)
N/A
N/A
Presence/absence of various
species of vegetation (grasses,
sedges, eelgrass, macroalgae,
etc.)
Present or absent
100% Accuracy of identification
evaluated by the Scientific
Advisor(s); taxonomic
confirmation of voucher
specimens by experts
N/A
0	= Absent
1	= Present
Vegetation Abundance
Percent cover (%) /
quadrat (0.25 m2)
N/A
N/A
0-100 m2
Canopy Height
cm
100% Accuracy of identification
evaluated by the Scientific
Advisor(s)
1 cm
1-150 cm
Vegetation Density
Shoots per quadrat
(0.25 m2)
N/A
N/A
0-500 m2
Location and depth of deep
water and shallow water edge
(of eelgrass bed)
Meters from shore and
meters below surface
(water depth)
N/A
0.1 m
from shore:
0-1000 m;
water depth:
0-15 m
N/A = not applicable
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #5: Project Schedule
Project Activities and Schedule
Activity
Person responsible
Dates
For Annual Activities
Anticipated Date(s)
of Initiation
Anticipated Date(s) of
Completion
Plan Volunteer Program
Program manager
and coordinator
January 1
April 30
Revise QAPP and SOPs, as
necessary
Program coordinator
February 1
April 15
Inventory supplies and
equipment
Coordinator
February 1
March 31
Test water quality equipment
Coordinator
February 1
March 31
Conduct training sessions for
volunteer monitors and
distribute water quality
sampling equipment
Coordinator
April 1
June 30
Receive and review water
quality data
Quality Assurance
Manager
April 1
December 31
Input data to water quality
database
Coordinator
June 1
December 31
Conduct field Audits
Coordinator
June 1
September 30
Synthesize data and create
water quality reports
Coordinator
September 30
February 15 after sampling
year
Perform annual audit
QA Manager
January 1 after
sampling year
February 15 after sampling
year
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #6: Training and Specialized Experience
A. Training
Training Requirements for Interns and Volunteer Monitors
Project Function
Description of Training
Training Provided by
Training
Provided to
Frequency
Water Sample
Collection
Handheld instrument,
datalogger, and laboratory
sample and data collection
procedures, provided in the
field
Program
Manager/Coordinator
Interns
Annually
Water Sample
Analysis
Analysis of water samples in
the laboratory
Program
Manager/Coordinator
Interns
Annually
Data
Management
Logging in samples into
database
Database Manager
Interns
Annually
Water Sampling
Water sample collection
procedures (annual training
sessions)
Program Manager
and/or Program
Coordinator
Volunteer
Monitors

Water Sampling
Water sample collection
procedures in the field during
an annual field audit for
volunteer groups
Program staff
Volunteer
Monitors

Water Sampling
When samples are dropped
off at the laboratory by
volunteers the chain of custody
form is used to determine if
any corrective actions are
needed in sample
documentation.
Laboratory Managers
and
Interns
Volunteer
Monitors

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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Volunteer Training Narrative Statement
All program volunteers (i.e. new, returning and youth) are required to attend annual training prior to
participating in the current year's monitoring activities. Training is directed by the state coordinator or a
currently Certified Local Trainer. Training is based upon the methodology outlined in the most current version
of the program training manual (and associated training materials) and the most current program QAPP.
New and youth volunteers must complete both classroom and field-based training activities. During classroom
training volunteers are provided with program background and overview information, including a review of
the program objectives, field safety, and monitoring protocols via standardized Microsoft PowerPoint
presentations. During the field-based training, volunteers travel to a nearby monitoring station to complete the
protocol under the supervision of the trainer. Successful completion of annual training for new and youth
volunteers is measured as 100% classroom attendance and demonstration in the field of the ability to
implement the protocol (i.e. sample collection, sorting, identification, voucher preparation, and
documentation.)
All experienced volunteers must complete, at a minimum, annual field-based training under the supervision of
a Certified Local Trainer. Experienced volunteers may be allowed, at the discretion of the Local Trainer, to
review classroom presentation materials remotely (e.g. online/electronically) in lieu of classroom training.
Successful completion of annual training for Experienced Volunteers is measured as either 100% classroom
attendance or remote review of classroom materials with electronic confirmation, along with field
demonstration of the ability to implement the protocol (i.e. sample collection, sorting, identification, voucher
preparation, and documentation.)
B. Specialized Experience
Specialized Experience Narrative Statement
Volunteers with the marine invasives program get significant support from the state coordinators and scientific
community who act as "identification experts". The program manager has 10 years of experience running
the program, has a degree in marine biology and has assisted with the marine invasive rapid assessment
program.
Volunteers are also encouraged to send photographs of anything unusual back to marine biological
specialists at the state office of coastal zone management. Academic experts are sometimes consulted to
identify species. Starting in 2016, volunteers are also encouraged to upload any photographs of
observed species onto the program page on iNaturatist which provides an additional way to verify
identifications made.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #7: Documents and Records
Documents and Records Narrative Statement
This section briefly describes the documents, forms and records utilized by the program and procedures for
handling and storing program records. All program data and documents are subjected to QA/QC review
before being disseminated to end users. Procedures for reviewing, validating and where necessary qualifying
or excluding the information contained in program records are discussed below.
Data Sheets: Field data sheets include information about the site location (program ID number), which
specific equipment was used to make measurements (thermometer number), the sampling method used (direct
fill, pole, or "Bridge Buddy") and equipment calibration results. The field data sheets are also used to record
temperature, velocity, depth, color, odor, and turbidity information (see appendix). A separate field data
sheet is used by dissolved oxygen monitors (see appendix). Both data sheets will be completed and
relinquished to the site coordinator at the drop-off site. Field data sheets are archived by sampling season in
a permanent file. Field data are also entered into an event spreadsheet and retained by the organization in
hard and digital form.
Lab data sheets for specific conductance and pH are kept by the data manager and entered into an Excel
spreadsheet that is saved and printed for review and permanent archiving (see appendix). Outside lab data
sheets are sent in electronic format from the outside labs to the Data Manager. Sheets are saved on the
organization's hard drive, entered into an excel spreadsheet that contains all other site information, and
printed for review and permanent archiving. See the appendix for copies of the various data sheets used in
the program.
Chain of Custody Forms: Chain of custody forms (see Template #10) are completed for each sample.
Forms are provided by the lab supplying analytical services. Copies of these forms will be archived in the
organization's office. The original chain of custody forms will be retained and archived by the appropriate
laboratory. See the appendices for sample chains of custody.
Sample Labeling: All samples are labeled with site ID#, lab site ID # (if different), monitor's initials, date,
time of collection, and parameters to be analyzed. See the appendix for full labeling procedure.
Equipment Custody Form: Equipment custody forms will be completed by volunteers upon receipt of the
sampling kit. This checklist lists all the equipment that was given to the volunteer and inventory numbers of the
individual instruments. This allows the organization to keep a constant record of equipment possession.
Equipment custody forms are stored indefinitely. New forms will be completed following each annual
equipment inspection.
Training and Evaluation Form: Volunteer monitors are evaluated at the time of initial training, upon annual
renewal training, and again if questions arise about performance. Volunteer training and evaluation forms
are archived with other project documents. See the appendix for the various training and evaluation forms.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Water Sampling Field Data Sheet
Lake Monitoring Project
Observation/Assessment
Data Sheet
Observation ID#*: _
Lake / Pond Name:
Town / Count:	
AssessmentID#*:
Invasive Observation Description
Observation1
GPS
coordinates2
Invasive Species Name
Size of plant bed3
Inbasive
Distribution4
Substrate5
Depth (feet)







1.	The number of invasive species locations you find beginning with 1.
2.	If known, please enter the Datum of your GPS unit. Example: NAD83 or WGS84 are most common.
3.	Estimate bed size in feet as length x width. Example: 45x30 feet
4.	Single plant or clump, scattered plants/clumps, dense plants/clumps, linearly scattered, or monoculture
5.	Mud, Sand, Gravel, Rock, Wetland, or Mixture
* These ID #s are given to you
after you enter Observation and
Assessment information online
using iMaplnvasives; if you are
not entering your data online,
leave blank.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Citizen Science Air Monitoring Collaboration Community Field Data Sheet
Citizen Science Air Monitoring Collaboration Field Data Sheet
Name:
Address:
Describe location (nearby industries, childcare centers, restaurant, etc.):
Date
Time
Battery Status
(Changed)
Calibration
number
Flow Rate
General Observations of
the day/location (Bad
smell, lots of trucks, etc.
1.





2.





3.





4.





5.





6.





7.





8.





9.





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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #8: Existing Data and Data from Other Sources
Limitations on Use of Existing Data
Existing
Data Source
How Data Will
Acceptance Criteria
Limitations on
Data

Be Used

Data Use
Water
University buoy
To determine
1. Temperature data
1. Temperature
temperature
located upstream
baseline
must be collected from
data collected from
data
from the power
temperatures of
a properly calibrated
a buoy located

generation plant
the river for the
and functional buoy
downstream


past 2 years





2. Temperature data
2. Temperature



were collected from
data exceed



within V2 km of power
sensitivity



generation plant
acceptance criteria



3. Sensitivity of the




temperature data from




the buoy is less than




0
O
n

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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #9: Sampling Design and Data Collection Methods
A: Sampling Design
Sample Design for a Marine invasives Monitoring Project
Sample Design: The volunteers implement the program monitoring protocols, searching on piers and
adjacent rocky shores for twenty-three non-native species of concern. The protocol is described in a guidance
document, prepared by the program. Generally, volunteers are trained early in the late spring or early
summer. On each visit, the volunteer team (usually two to three people) records the presence and abundance
of target species. A typical site is a piling or underside of a dock float at a pier, which can be viewed by
leaning over and peering into the water. Site selection and monitoring protocols for each habitat are
described in the overarching program guidance document.
Methods: Handfuls of fouling organisms are gathered and sorted in trays looking for target species.
Volunteers use small nets to search for epibenthic fauna such as shrimps, crabs, or isopods. Large laminated
information cards with photos are used to identify species. Volunteers are also encouraged to record any
other species, including native species, they observe and there is room on the data sheet to add in additional
species that are not on the monitoring list. Abundance is measured qualitatively using the following
guidelines:
•	Abundant: present almost everywhere you look
•	Common: present at most of the monitoring site (present in most locations or over half of the
area looked)
•	Few: present, but at low abundance (found less than half of places looked)
•	Rare: one to two specimens present at site
•	Absent: not observed at the site
At each visit, water temperature and salinity are recorded using hand-held thermometers and refractometers,
and notes are made on weather conditions and tidal stage. Results are recorded on datasheets and sent to
the project manager.
Locations: See project description, and map in the Appendix.
Schedule of the Project (frequency of sampling): The volunteer team visits the same site(s) monthly for six
consecutive months, from May through October. It is anticipated that this project will be funded for the
foreseeable future.
Quality Assurance and Quality Control: The thermometers and refractometers are calibrated by the
project manager at the beginning of the year and checked by volunteers before each monitoring event.
Refractometers are checked using deionized water. There is no chain of custody for the datasheets, but each
datasheet requires identification of the volunteer collecting the information. The project manager will
periodically call volunteers to check on any data that seem unusual or any identification that are in question.
Volunteers are instructed to collect a sample and/or photographs if they are not confident in the
identification. Factors used by the project manager to identify a potential misidentification are the history of
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
that species at the site (historical abundance/presence), and if the species in question has close resemblance
to native species, etc.
Sample Design for a Water Quality Stream Monitoring Project
Sample Design: Routine sampling activities consist of collecting in-stream samples. As discussed above,
routine sampling sites are divided among "indicator" sites and "subwatershed sites" to meet the dual
objectives of the program. Indicator sites are selected to be representative of overall water quality and are
relatively unchanging over time to allow comparison to past and future investigations. Sites have generally
been selected at the downstream ends or key segmentation points of major subwatersheds and at or near
locations where there is a longstanding data record.
Methods: Sample types include grab samples and direct measurement. Water quality characteristics that are
measured and/or observed directly include: temperature, color, odor, turbidity, velocity, depth, specific
conductance, and dissolved oxygen. Laboratory-measured indicators may include fecal coliform, E. coti
and/or Enterococcus, along with total nitrogen, ammonia, nitrate/nitrite, total phosphorus, ortho-phosphate,
pH, salinity, specific conductance, surfactants and total suspended solids. Bacteria samples analyzed using
the Colilert method may also include results for total coliform. This total coliform data is used only as a QC
control in the Colilert analysis process and is not used for the direct assessment of water quality. Additional
indicators may be evaluated during follow-up and special study sampling as needed.
Location: See map in appendix.
Schedule: Routine sampling operations are generally scheduled every four weeks, starting in May, and are
typically held early on a Wednesday or Thursday morning. The reason for this sampling schedule is to meet
new Surface Water Quality Standards for bacteria which stipulate that at least five samples be taken within a
six-month period to make a use determination.
Quality Control: Field duplicates, field splits, field and lab blanks are collected routinely. See sections below
for more information.
Sample Design for a Community-based Air Monitoring Project
Important Considerations for Air Monitor Placement: Appropriate placement of air monitoring devices is
critical for collecting useful data. Air pollution concentrations can vary considerably due to factors such as
proximity of the pollutant sources, buildings and other obstructions, and atmospheric conditions. For these
reasons, you must plan monitoring locations carefully to make sure the collected data are representative of
the community you are monitoring and that meet your study objectives. EPA and the community group will
work together to identify the locations for this study. The following are some important considerations for
choosing representative sampling sites:
• Local atmospheric conditions. Factors such as rain, wind, sunlight, clouds, temperature, and humidity
can affect your data.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
S Make sure the unit is protected from the effects of weather using the individual EPA-
developed aluminum shields that accompany your monitoring unit.
S Temperature and humidity can particularly affect the performance of the monitoring unit. The
recommended operating ranges for temperature and Relative Humidity (RH) are 0-40 2C
(32- 104 2F) and 0-90% RH (with no formation of water droplets), respectively.
S Wind speed and direction can also affect measurements. For example, stagnant air can
lead to pollutant concentrations that gradually increase, whereas strong winds can decrease
concentrations by spreading pollutants over a larger area. Higher winds can also lead to
higher concentrations of other pollutants such as dust. Wind direction can affect your results
by increasing or decreasing concentrations depending on whether your air monitor is
located upwind or downwind of the prevailing wind at the time of data collection.
Understanding the effects of wind can aid in choosing a monitoring site and in recognizing
when your results might have been affected by wind.
•	Primary or secondary source. Some pollutants are emitted directly by a source (primary pollutants),
while others are formed as the products of chemical reactions in the air (secondary pollutants).
Primary pollutants are often more localized (i.e., near the source) and can have a greater variability
over distances than secondary pollutants. It is important to consider whether a pollutant of interest is
primary or secondary when deciding where and how to collect monitoring data. More information
can be found at: http://www.epa.gov/air/criteria.html.
•	Location of pollutant sources relative to the pollutant of interest. N02 and PM, for instance, might
have much higher concentrations closer to a roadway as both come from automobile emissions. If
you want to find out how a roadway influences N02 and PM concentrations, you could locate one
monitoring unit close to the road and one some distance downwind of the roadway to determine the
changes in concentrations.
•	Location of the air monitor relative to the exposed population. If the aim of your study, for example,
is to measure the impact of industrial emissions of N02 and PM on a neighborhood, the monitoring
units could be placed within the neighborhood at varying distances from the facility rather.
•	Air flow. Make sure air flows freely to your monitoring unit by placing it far enough away from the
ground (at least 1 meter above the surface) and away from building surfaces, trees, or any other
obstructions to flow (ideally at least 1 meter away).
•	Reactions and interferences. Sensors can experience interference from other chemicals in the
atmosphere, as well as heat and cold, which can lead to erroneous concentration estimates. Avoid
placing the monitoring unit near sources of heat or cold and gases that can react with the pollutant
of interest. Possible interferences for the N02 component include high concentrations of chlorine (a
commonly used disinfectant for swimming pools) and ozone (often formed during warm, dry, and
cloudless days with low wind speeds).
EPA's Air Sensor Guidebook provides additional details and considerations for choosing sites for air
monitoring studies.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
B. Data Collection Methods
Surface Water Field Sample Summary for a River Water Quality Monitoring Project
Analytes
Sample Type
Number of
Sampling
Stations
Sampling
Frequency
Number of
Field
Replicates
Total
Number of
Samples to
Lab
• Alkalinity
Surface Grab,
Variable
Typically, a
>10% of
Variable,
•	Chlorides
•	Chlorophyll
•	Dissolved
Oxygen
•	Metals
•	Nutrients
•	Solids
see SOP in
appendix
year to year
depending
on number
of
volunteers
but typically
5 to 25
minimum of
monthly from
May through
October
samples
based on
sampling
frequency
but ranges
from 50 to
200 per
year
• Dissolved
In-situ
Variable
Typically,
>10% of
N/A
Oxygen
•	pH
•	Specific
Conductance
•	Turbidity
•	Water Level
•	Water
measurements
See SOP in
appendix
year to year
depending
on number
of
volunteers
but typically
5 to 25
every 15
minutes for a
minimum 5-
day
deployment
profiles are
repeated

Temperature





N/A = not applicable
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Sampling Summary for the Three Components of the Cyanobacteria Monitoring Collaborative
Program

Potential
Purpose
Sample
Sample
Sample
Parameters

Program Use

Location
Frequency
Type

Bloom Watch
All State &
Determine
Wherever a
Whenever a
Smartphone
Waterbody

Federal water
high
bloom
suspected bloom
image & data
name, weather

programs,
probability
appears to
occurs;
submittal via
conditions,

general public at
that a
be
anywhere,
the
water surface

large, Citizen
cyanobacteria
occurring.
anyplace,
Bloom Watch
conditions,

Scientists, beach
bloom is
This could
anytime
App (see
public access,

monitors,
occurring (i.e.
be in open

Cyanos.org)
smartphone

educational
Vs pollen),
water and

images, local

institutions, lay
utilize an
widespread,


Lat/Lon

monitoring
educational
or a distinct




programs
tool, document
scum line




frequency of
located at





occurrence,
the





possible
shoreline.





hotspots,
Any surface





report
water body,





occurrence to
anywhere





state





All State &
To track and
Any surface
Anytime,
Concentrated
Location data
CyanoScope
Federal water
document the
water
anywhere, any
53-micron
(waterbody

programs, local
locations and
bodies
frequency
plankton net
name, town,

and state boards
occurrence of


sample
Lat/Lon), digital

of health, public
potentially


microscope

surface drinking
toxic



image submittal

water suppliers,
cyanobacteria





concerned
genera





citizens, Citizen






Scientists,






academia &






educators





Cyanomonitoring
All State and
Track spatial
Minimum of
Minimum
Integrated
Chlorophyll a

Federal water
and temporal
one site per
baseline of one
tube sample
concentration,

monitoring
distribution of
waterbody
sample collected
from the
Phycocyanin

programs, public
cyanobacteria
from the
every other week
surface to a
concentration,

drinking water
pigments,
deep hole
from June 1
depth of 3
possible toxin

supplies, lake &
frequency of
area or
through
meters, or a
analysis

river
occurrence,
specific
September 30.
one-meter


associations,
long term
shoreside
Additional
integrated


various
trends,
location
samples may be
tube sample


stakeholders,
concentration

collected from
if collected


researchers
levels, and

other
from the



potential

waterbodies,
shoreline



toxicity

other sites, other






depths, and






other






frequencies, if






minimum






baseline is






completed. Long






term monitoring


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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Field Sample Summary for a Coastal Wetland Biological Monitoring Project
Indicators
Number of
Site location
Frequency,
Field survey QC

sample
rationale
duration,


locations

special
conditions

Macroinvertebrates -
3 creek
Representative
Once/year, late
Any combination of qualified
presence
bank sites
of marsh
summer or fall
supervisor, multiple samplers,

near 0-150-
condition at

voucher specimens, photo

300 feet
study &
reference

documentation
Nekton (fish, shrimp,
3 equally
Representative
Three times June
Any combination of qualified
crabs)- presence,
spaced
of marsh
- September
supervisor, multiple samplers,
relative abundance
along
condition at

voucher specimens, photo

evaluation
study &

documentation

area
reference



gradient



Birds - point counts
Single
Representative
Five times June -
Any combination of qualified
of all species seen or
vantage
of marsh
September
supervisor, multiple samplers
heard
point
overlooking
evaluation
area
condition at
study &
reference


Vegetation -
6 transects,
Representative
Once August or
Any combination of qualified
community
randomly
of marsh
September
supervisor, multiple samplers,
composition, percent
stratified
condition at

voucher specimens, photo
abundance per

study &

documentation
species

reference


Tidal hydrology -
Two fixed
Representative
Once, every 1 5
Any combination of qualified
difference in tidal
locations:
of tidal flow
minutes for 6
supervisor, multiple samplers
range
one
between study
hours from low


upstream
& reference
to high spring


and one

tide


downstream




of tidal




restriction



Land Use
Map and
Representative
Once, unless
Any combination: Two or more

orthophoto
of land use
alterations in
personnel conduct separate

analysis
effects on
land use
mappings of same area, compare

using three
marsh

results, discuss to resolve differences

concentric
conditions



buffers



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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #10: Sample Handling and Custody
Sample Handling and Record Keeping Narrative Statement
Record keeping serves numerous purposes vital to produce reliable data. In general, all procedures,
observations, subjective decision-making, and unusual circumstances are recorded in at least one of the
records described below.
Sample Labeling: Baseline samples analyzed by the outside lab are labeled with the site name, date, and
time of collection. Since the glass bottles used to collect baseline DO samples are reused, the DO bottle needs
to have only the site name written on it. All other samples (e.g. for Hot Spot or NPS Assessment) should, at a
minimum, be labeled with the date, time of collection, site name, and sample number. Volunteer monitors are
instructed to use pens or permanent marker that will not smear if the bottles come in contact with water.
Field Notebook: The field notebook is a blank notebook in which all notes and observations are recorded
and serves as a duplicate of all information on the data sheet. All entries are initiated by writing the date and
initials of the volunteer making the entry. Periodically field notebooks are returned to the Project Manager for
review and permanent storage.
Data Sheets: Data sheets are preprinted forms on which calibration checks, field measurements and
observations are documented. When used in the field, data sheets are completed and relinquished to the
Sample Coordinator at the drop-off site. Data sheets are archived by month in a permanent file. Hardcopy
and electronic copies of these data are maintained permanently by the program office.
Chain of Custody Forms: Chain of custody (COC) forms are completed for each sample shipped to a fixed
laboratory for analysis. Copies of these forms are archived permanently in the program office. The original
chain of custody forms is retained and archived by the appropriate laboratory.
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Example of a Chain of Custody Form for a Water Quality Monitoring Project
Organization Coast Watch		Project Name Bacteria Sampling
Laboratory North Shore Bacteria Laboratories
Sampler's Signature 	
Sample
ID
Site
name/number
Date
Time
Type or
Volume
# of
Samples
Analysis
Comments
1
CW-1
8/4/2018
0730
100 mL
1
Enterococci

2
CW-2
8/4/2018
0812
100 mL
1
Enterococci
High turbidity
3
CW-3
8/4/2018
0915
100 mL
1
Enterococci

































Relinquished by: Signature
Received by: Signature
Condition when received:
Date/Time
Relinquished by: Signature
Received by: Signature
Condition when received:
Date/Time
Relinquished by: Signature
Received by: Signature
Condition when received:
Date/Time
Additional Comments:
Page	of_
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #11: Equipment List, Instrument Maintenance, Testing, Inspection and
Calibration
Equipment Inspection, Calibration, and Maintenance for Water Quality Project
Equipment
Inspection
Type of
Calibration
Post
Available
Maintenance
Record
Type, Make
Frequency
Inspection
Frequency
Check
Parts

Keeping
and Model



Criteria



Thermometer,
Each
Visually check
Annually
n/a
Spare
Annually or as
Logbook
Enviro-Safe
monitoring
for
against triple

thermometer
needed
notation
"Easy Read"
event
separations in
point of water




Armor Case

column
Annually




Thermometers


against







traceable







thermometer




pH meter,
Each
Battery life,
3-point
PH
Spare
Annually or as
Logbook
Oakton
monitoring
electrolyte,
calibration at
standard
batteries,
needed
notation
Waterproof
event
probe
beginning of
7
electrolyte,


pHTestr 2

integrity
each
solution
and electrodes





sampling day,
reads 7.0






reconfirm
+/_






after every 25
0.2 SU






samples







and at end




Specific
Each
Battery life
At beginning
Standard
Spare
Annually or as
Logbook
Conductance
monitoring

of each
1000
batteries
needed
notation
meter, YSI 85
event

sampling day,
uS/cm






reconfirm
solution






after every 25
reads






samples and
1 000 +/_






at end
1%



Dissolved
Each
Battery life,
Saturated air
+ 0.5
Spare
Annually or as
Logbook
oxygen meter,
monitoring
electrical
and zero- DO
mg/L of
membranes,
needed
notation
YSI 550 or
event
connections,
(< 0.5 mg/L)
sat. value,
batteries


YSI 85

membrane
checks at
<0.5





condition
beginning of
mg/L for






day, reconfirm
zero std






after every 25







samples







and at end




Depth Gauge
Each
Visual for knot
None
None
Sting,
Annually or as
None
(plumb bob)
Monitoring
and tangle


replacement
needed


Event
problems


bob


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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Air Sensor Field Monitoring Record
Sensor Monitoring Record
Sensor Unit #	Date:	Data recorded by:
Test Location (descriptic
Fresh Batteries installed?
	 Yes	Date_
No
~
Data logging interval
Start date:
Start time:
_End date:
End time:
Operation mode:
AC power
Battery
Total run time:
~
~
hoi
Pre-test Instrument Setup
PM2.5 zero check	Performed by:.
PM2.5 flow rate check	Performed by:.
NO2 zero and span check Performed by:	
Date:
Date:
Date:
Post-test Instrument Operations
Data downloadedYes No
Performed by:	
File ~
Date:	
Comments
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #12: Analytical Methods
Water Quality Monitoring Parameters Analyzed at Outside Laboratories
Matrix
Parameter
Reporting
Limit
Analytical &
Preparation
Method/
SOP Reference
Sample
Volume
Containers
(number,
size, type)
Preservation
Requirements
(chemical,
temperature,
light
protected)
Maximum
Holding Time
(preparation
/ analysis)
Seawater
Chlorophyll a
0.1 ug/l
EPA Method
445.0
Acetone
extraction
1 liter
500 to 800
polyethylen
e acid
washed
24 hours on ice
in dark/collect
on filter, frozen
or extracted
1 20 days
once filtered
Seawater
Total Dissolved
Nitrogen
1 uM
(14 ug/l)
Standard method
4500-P
Persulfate
digestion
1 liter
500 to 800
polyethylen
e acid-
washed
Field filter, store
dark at -20 °C
28 days
Seawater
and
Fresh-
water
Total
Phosphorus
1 um
(31 ug/l)
Persulfate
digestion
60 mL
50 to 100
polyethylen
e acid-
washed
Acidify, store
dark at -20 °C
28 days
Seawater
Enterococci
1 per 100
mL
Standard
Method 1 600
Membrane
filtration
100 mL
100 to 300
sterilized
polyethylen
e
Store on ice
6 hours
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Water Quality Parameters Analyzed In Situ
Matrix
Parameter
Reporting Limit (Resolution)
Analytical &
Preparation Method/
SOP Reference
Freshwater
PH
0.1 units
Hydrolab sonde
Freshwater
Dissolved oxygen
0.01 mg/L
Hydrolab sonde
Freshwater
Temperature
0.01 °C
Hydrolab sonde
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #13: Field and Analytical Laboratory Quality Control (QC) Summary
Quality Control (QC) Summary for In Situ Water Monitoring
Water
Quality
Parameter
QC Sample type
Frequency
QC Acceptance
Criteria or
Performance
Goals
Corrective Action
Person
Responsible for
Corrective
Action
Dissolved
Oxygen
Measurement
replicate
10% or each
sampling
event
RPD<10%
or
ABS (absolute
difference) < 0.4
mg/L or < 4%
Recalibrate
instrument, repeat
measurement
Volunteers;
Program Staff
Initial Calibration
Value
Pre and post
sampling
event
± 5.0% of
calibration
saturation
Recalibrate
instrument, repeat
measurement
Volunteers;
Program Staff
Temperature
Measurement
replicate
Precision
RPD < 1 0 %
Repeat measurement
Volunteers;
Program Staff
PH
Measurement
replicate
10% or each
sampling
event
ABS <0.3
standard (std)
units
Recalibrate
instrument, repeat
measurement
Volunteers;
Program Staff
Known buffer
Initial Calibration
Value
(e.g., pH = 6.0)
Pre and post
sampling
event
+ 0.3 std units
Recalibrate instrument
repeat measurement
Volunteers;
Program Staff
Specific
Conductance
Measurement
replicate
10% or each
sampling
event
RPD < 10%
or
ABS < 25 |jS/cm
Recalibrate
instrument, repeat
measurement
Volunteers;
Program Staff
ICV
(e.g., 100
|jS/cm)
Pre and post
sampling
event
+ 25.0 |jS/cm
Recalibrate
instrument, repeat
measurement
Volunteers;
Program Staff
Turbidity
Measurement
replicate
10% or each
sampling
event
ABS < 1.0 NTU
Recalibrate
instrument, repeat
measurement
Volunteers;
Program Staff
Field blank
Pre and post
sampling
event
+ 0.1 NTU
Recalibrate
instrument, repeat
measurement
Volunteers;
Program Staff
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
Typical Quality Control Measures for Biological Sampling
Sample Type
Instrument/Parameter
Accuracy Checks
Precision Checks
% Field QC Samples
(blanks and field
duplicates)
Physical/visual
Habitat assessments
NA
Different personnel
conduct side-by-side
assessments, compare
10%
Physical/visual
Aquatic plants
2 personnel conduct separate
mappings of same area,
compare results, discuss to
resolve differences.
2 personnel ID plants
separately.
Discrepancies/unknowns taken
to expert for ID confirmation.
Different personnel
conduct side-by-side
assessments, compare
10%
Physical/visual
Benthic macroinvertebrates
IDs verified by external expert.
90% Accuracy of identification
when Invertebrate Scientific
Advisor examines a minimum of
10% of the original samples
Different personnel
conduct side-by-side
assessments, compare
10%
Physical/visual
Nekton
100% Accuracy of identification
evaluated by the Scientific
Advisor(s)
N/A
N/A
Physical/visual
Birds
100% Accuracy of identification
evaluated by the Scientific
Advisor(s)
N/A
N/A
Physical/visual
Vegetation
100% Accuracy of identification
evaluated by the Scientific
Advisor(s)
N/A
N/A
Inventory, quadrat and
line transects
Algae, Eelgrass, Invertebrates
100% Accuracy to genus or
species; taxonomic verification
of voucher specimens by
Scientific Advisor(s).
Different personnel
conduct side-by-side
assessments, compare
10%
N/A = not applicable
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Examples for Citizen Science Quality Assurance and Documentation - Version 1
EXAMPLE TEMPLATE #14: Data Management
Data Management Narrative Statement
Below is a summary of data management procedures, including handling and statistical analyses.
Data management process and procedures: Data from field observations is recorded on standardized
data sheets on-site at the time the measurements are taken. The volunteers are asked to check that all data is
accurate and legible before making a copy and mailing it in on a bi-weekly basis. Volunteers may submit
data in a word document copy of the standardized field data sheet via email to the Water Quality
Monitoring Coordinator on a weekly basis, however all original field data sheets will also be submitted at the
completion of the sampling season. As the data are received by the WQM Coordinator and WQM
Assistant, they are reviewed, and the volunteers are contacted to clarify any numbers, issues or if any
information is missing. The WQM Coordinator maintains the weekly basic parameter field dissolved oxygen
and nutrient data sheets at the BBC office as hard copies of data as well as computer back-up of entered
data. Copies of field data sheets are provided to associated laboratories performing the analysis.
The nutrient sampling field observations are recorded on the data sheet/chain of custody form on-site at the
time the samples are collected. The volunteers are asked to check that all data is accurate and legible before
signing and relinquishing the data sheets with the sample coolers to the WQM Coordinator and the lab. The
nutrient analysis data are provided back to the WQM Coordinator in a predefined spreadsheet format. Data
entry is checked by laboratory personnel and the QA/QC checks by the Project QA Officer. This nutrient
spreadsheet is checked by the WQM Coordinator and if any unusual findings are noted, laboratory
personnel will be contacted to discuss data. The nutrient spreadsheet is finally directly imported into the
Water Quality Database and the whole of the data rechecked and merged into the Index spreadsheet.
All field data will be reviewed by the WQM Coordinator before being entered by the WQM Coordinator or
WQM Assistant into a computer spreadsheet. Upon being entered, the data sheets will be checked against
the spreadsheet on a regular basis and against a final print out. As the Water Quality Monitoring Program
has been underway, a linked spreadsheet program has been developed to facilitate the data synthesis and
display aspects of the project. The program includes automatic calculations of percent oxygen saturation for
each entry which allow an additional mechanism for identifying unusual dissolved oxygen or temperature
readings or potential data entry errors. If an unusual or unbelievable recording is noted, the volunteer will be
contacted to discuss the data. Unusual data will be flagged for further discussion with the Project QA officer.
Volunteers are also instructed to take replicate samples if an unusual reading is recorded in the field and
record comments on data sheets.
Upon completion of data entry and data checks, the following will be calculated for each parameter:
averages, minimum value, maximum value, standard deviation, and any other required calculation. The
averages for percent oxygen saturation (using only lowest 20% of readings for any station), Secchi disk,
chlorophyll, organic and inorganic nitrogen will be scored and combined to form the Health Index by which
embayments will be compared. The linked spreadsheet program is used to produce the annually updated
time series graphics and calculations of Bay Health Index. Statistical methods will be used to determine
significant trends.
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EXAMPLE TEMPLATE #15: Reporting, Oversight and Assessments
Reports
For an Early Stage, Small Monitoring Program
Reports to Management Narrative Statement
The Project Manager will submit quarterly progress reports and a final project report to the Project Officer for
approval. This final report will include a complete discussion regarding the appropriate use and limitations of
the data in terms of quality, as well as all datasets developed within the scope of this project. Additional
reports or other information related to project status, concerns, completed deliverables, or any other project
needs will be provided when requested.
For an Experienced Long-Term Monitoring Program with State Funding
Reports to Management Narrative Statement
An annual QA memorandum is written at the end of the data collection period. This memorandum
summarizes the QA activities conducted during that year, including:
•	Summary of QA/QC objectives;
•	Description of training activities;
•	Conformance to QAPP requirements/procedures, and descriptions of deviations, if any, from the
approved QAPP and approved amendments, if any, to the QAPP;
•	Limitations of data;
•	Documentation of usable data versus amount of data actually collected;
•	List of reasons why data are not usable. This includes a review of any of the following
o Precision
o Accuracy
o Representativeness
o Completeness
o Comparability
o Sensitivity
•	Summary of conflicts, and subsequent resolution of conflicts, associated with sampling; and
•	Use and effectiveness of corrective actions, if corrective actions were taken.
Copies of the memorandum are retained in the program files for reference when preparing the 303(d) list
and 305(b) reports. Copies are also transmitted to the state Quality Assurance Manager. Program data are
consistently reviewed during the sampling period to determine sampling efficiency.
Quality Assurance System Program Self-Audits are conducted annually for the general operation of program,
pursuant to Chapter 9 and Chapter 10 of the state Quality Management Plan (QMP). These assessments
document the deviations, if any, between the operation of program during any year, and the consistency with
the approved QAPP. The results of the self-audits are transmitted to the state QA Manager.
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Though frequent QA management reports will not be generated, frequent review of program data will be
conducted to determine sample efficiency. In addition, information is provided to each program group in
their annual report documenting any QA issues and flagging data that has been deemed invalid for water
quality assessments.
Assessment
Assessment of Data input and Volunteer Field Sampling
Assessment
Type
Frequency of
Assessment
What is Being Assessed
Who Will
Conduct the
Assessment
How Issues or
Deviations will
be Addressed
Data Checks and
Assessments
1 /month
Field data entries into
spreadsheet and
database
Quality
Assurance
Manager
Verify with
sampling team
On-Site Field
Inspection
2 weeks into
sampling season
and mid-season
Field sampling
procedures by
volunteers compared to
the QAPP and SOPs
Quality
Assurance
Manager
Re-train if
necessary
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EXAMPLE TEMPLATE #16: Data Review and Usability
Data Review and Usability Narrative Statement
Data Review: As part of the data review and validation, all field and lab data will be reviewed and
discussed by the Program Coordinator to determine if the data meet the objectives as outlined in the QAPP.
Decisions will be made to accept or reject the data before presenting the information in any presentations or
reports. Errors in data entry will be corrected and any outliers will be flagged for further review. Any data
deemed to be not acceptable will be noted in the comments fields of the Program database and will be
removed from any statistical calculations.
Data Verification and Validation: All data reported for the program will be subject to checks by the
Program Coordinator for errors in transcription, calculation, or computer input. Additionally, all data forms will
be reviewed to ensure that they are complete and signed by the volunteers. All data forms must be signed and
dated on the back of the original data form by the reviewer. Any changes made to the data form must be
initialed and dated, and any action taken because of the data review must be recorded on the data form
below the reviewer's signature. Only data that meets the following conditions will be accepted and entered
into the Monitoring Project Data File:
•	Monitors have appropriate levels of training for the tests being conducted.
•	Monitors have successfully participated in required training or QA reviews.
•	Equipment has been checked and approved prior to or during an annual QA review.
•	Data forms are signed by monitors, and date, time, station number, and station description are
recorded.
•	All required equipment calibrations have been completed and recorded.
•	Data entries are legible.
All data that is manually entered into monitoring project database will be verified by a second person. Errors
will be immediately corrected.
Data Usability: Data quality objectives and validation procedures for this program have been designed to
ensure that volunteers and/or the Program Coordinator will be able to identify and correct problems in data
collection and reporting. Should the results of data validation measures or quality assurance reviews indicate
that the integrity of data is questionable and data quality objectives are not being met, the data set (or that
portion which is deficient) must be flagged as unacceptable for inclusion in the Program Data File.
The responsibility for deciding to take any corrective action rests with the Program Coordinator. The Program
Coordinator is responsible for ensuring that all corrective measures recommended from QA reviews are
implemented by monitors. The Program Coordinator has the authority to question data, call for re-training, and
recommend replacement of monitors when necessary.
Data Presentation: Graphic representation of the data will be provided in the final report.
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EXAMPLE TEMPLATE #17: Project Organization Chart
Project Manager
QA Manager
External Laboratories
Sample Coordinator
Volunteer Samplers
Watershed Association
Local Regulatory
Agencies
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EXAMPLE TEMPLATE #18: Project Organization
Project Organization Table
Name
Title
Organizational
Affiliation
Responsibilities

Project Manager
Watershed
Association
The Project Manager is responsible for the
management of the monitoring program. At a
minimum, the Project Manager is responsible for
obtaining adequate equipment and supplies,
training personnel, managing the volunteer
sampling process, scheduling, reporting, and
taking constructive corrective actions when
required.

QA Manager
Watershed
Association
The QA Manager is an individual with adequate
expertise in analytical chemistry and field
operations to review the procedures and data
generated by this project. When necessary, the
QA Officer will consult outside experts, including
appropriate State Department of Environmental
Protection and Environmental Protection Agency
(EPA) staff, on relevant technical issues. The QA
Officer will ensure that every provision of the
QAPP is conducted to the maximum extent
practicable. The QA Manager will report any
problems to the monitoring program Project
Manager after sampling events, and work with
the Project Manager to document and correct
any deviations, consulting outside experts and
advisers as necessary. As appropriate,
significant deviations will be reviewed for
approval by signatories.

Sample
Coordinator
Watershed
Association
For a given sampling event, the Sample
Coordinator is responsible for orchestrating the
collection of samples and organizing them for
pickup by the QA officer for delivery to labs and
for other testing. The Sample Coordinator
receives samples from volunteer samplers at the
watershed association office or other location.
The Sample Coordinator is responsible for
maintaining proper preservation of samples prior
to transport to the lab and supervises volunteer
monitors filling out chain of custody forms. The
Sample Coordinator will have access to a
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telephone during the monthly sampling event for
last minute problems or scheduling. In addition,
the Sample Coordinators will replenish supplies
for the Volunteer Samplers for the next sampling
round.
For a given event, the role of Sample
Coordinator may be executed by the QA officer,
Project Manager, or other trained watershed
association staff member, or by a suitably
trained volunteer.

Instructor
Watershed
Association
Instructors train and evaluate Volunteer
Samplers. They must be familiar with the
monitoring program QAPP and the Water
Quality Manual. It is recommended that
instructors who are not trained staff members of
watershed association conduct at least one year
of independent sampling and field analysis for
the monitoring program or any other institution
before assuming the role of Instructor. At the
training, topics discussed include: proper
sampling techniques and locations, safety, and
handling of samples.

Volunteer
Samplers
Watershed
Association
Volunteer Samplers perform all field
measurements, complete all records, and
coordinate the actual collection of samples
during a sampling event. The Volunteer
Samplers are required to read, understand, and
perform all procedures in the Mystic Monitoring
Network Water Quality Manual. In addition,
they are required to participate in the monitoring
program Training Program.
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EXAMPLE TEMPLATE #19: Project Distribution List
Project Contact Information
Name/Title
Contact Information
Project Manager
Phone Number (xxx) xxx-xxxx
Email: ProjectLead@email.com
Project QA Manager
Phone Number (xxx) xxx-xxxx
Email: PrjoectQA@email.com
Field Sample Coordinator
Phone Number (xxx) xxx-xxxx
Email: SampleCoord@email.com
Laboratory Contact
Phone Number (xxx) xxx-xxxx
Email: Samples@TestLab.com
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