United States
Environmental Protection
Agency
Office of Wetlands,
Oceans and Watersheds
4503F
EPA841-B-96-003
September 1996
&ER&
The Volunteer
Monitor's Guide To
Quality Assurance
Project Plans
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The Volunteer Monitor's Guide to
Quality Assurance
Project Plans
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Dear Reader:
Across the country, volunteers are monitoring the condition of streams, rivers, lakes,
reservoirs, estuaries, coastal waters, wetlands, and wells. The number and variety of these
projects are continually on the rise. So, too, is the complexity of the monitoring volunteers
conduct and the uses of the data they collect.
One of the most difficult issues facing volunteer environmental monitoring programs
today is data credibility. Potential data users are often skeptical about volunteer data — they may
have doubts about the goals and objectives of the project, about how volunteers were trained,
about how samples were collected, handled and stored, or about how data were analyzed and
reports written. A key tool in breaking down this barrier of skepticism is the quality assurance
project plan.
The quality assurance project plan, or QAPP, is a document that outlines the procedures
that those who conduct a monitoring project will take to ensure that the data they collect and
analyze meets project requirements. It is an invaluable planning and operating tool that outlines
the project's methods of data collection, storage and analysis. It serves not only to convince
skeptical data users about the quality of the project's findings, but also to record methods, goals
and project implementation steps^br current and future volunteers and for those who may wish
to use the project's data over time.
Developing a QAPP is a dynamic, interactive process that should ideally involve quality
assurance experts, potential data users, and members of the volunteer monitoring project team.
It is not an easy process. This document is designed to encourage and facilitate the development
of volunteer QAPPs by clearly presenting explanations and examples. Readers are urged to
consult, as well, the additional resources listed in the appendices to this document, and to contact
their state or U.S. Environmental Protection Agency (EPA) Regional quality assurance staff for
specific information or guidance on their projects.
Sincerely,
Geoffrey H. Grubbs, Director
Assessment and Watershed Protection Division
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Executive Summary i
Chapter 1 Introduction 1
Chapter 2 Developing a QAPP 7
Chapter 3 Some Basic QA/QC Concepts 15
Chapter 4 Elements of a QAPP 23
Appendix A Glossary 41
Appendix B EPA Regional Contacts 45
Appendix C References 49
Appendix D Abbreviated QAPP Form 51
Acknowledgements
This manual was developed by the U.S. Environmental Protection Agency
through contract no. 68-C3-0303 with Tetra Tech, Inc. The project manager was
Alice Mayio, USEPA Office of Wetlands, Oceans, and Watersheds. Principal
authors include Margo Hunt, USEPA Region 2; Alice Mayio, USEPA; Martin
Brossman, USEPA; and Abby Markowitz, Tetra Tech, Inc.
The authors wish to thank the many reviewers who provided constructive and
insightful comments to earlier drafts of this document. This guidance manual
would not have been possible without their invaluable advice and assistance.
Original illustations by Dave Skibiak and Emily Faalasli of Tetra Tech, Inc., and
Elizabeth Yuster of the Maryland Volunteer Watershed Monitoring Association.
September 1996
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EXECUTIVE SUMMARY
The Quality Assurance Project Plan, or QAPP, is a written document that
outlines the procedures a monitoring project will use to ensure that the
samples participants collect and analyze, the data they store and manage,
and the reports they write are of high enough quality to meet project needs.
U.S. Environmental Protection Agency-funded
monitoring programs must have an EPA-approved
QAPP before sample collection begins. However,
even programs that do not receive EPA money
should consider developing a QAPP, especially if
data might be used by state, federal, or local
resource managers. A QAPP helps the data user
and monitoring project leaders ensure that the
collected data meet their needs and that the quality
control steps needed to verify this are built into the
project from the beginning.
Volunteer monitoring programs have long
recognized the importance of well-designed
monitoring projects; written field, lab, and data management protocols; trained
volunteers; and effective presentation of results. Relatively
few programs, however, have tackled the task of preparing a
comprehensive QAPP that documents these important
elements. programs must have an
EPA-funded monitoring
This document is designed to help volunteer program
coordinators develop such a QAPP.
Steps to Developing a QAPP
Developing a QAPP is a dynamic, interactive process that
should ideally involve state and EPA regional QA experts,
EPA-approved QAPP
before sample collection
begins. However, even
programs that do not
receive EPA money
should consider
developing a QAPP,
especially if data might
be used by state, federal,
or local resource
managers.
I
Executive Summary
-------
potential data users, and key members of the volunteer monitoring project. There
are 11 steps a volunteer monitoring project coordinator might take to prepare a
QAPP. These are:
Step 1: Establish a small team whose members will serve as advisors in
helping you develop the QAPP by offering feedback and guidance
throughout the entire process.
A QAPP helps the data
user and monitoring
project leaders ensure
that the data collected
meet their needs.
Step 2: Determine the goals & objectives of your project—why it's needed,
who will use the data, and how the data will be used.
Step 3: Collect background information to help you in designing your
project.
Step 4: Refine your project's goals once you've collected more information.
Step 5: Design your project's sampling, analytical & data requirements—
essentially, what, how, when, and where you'll be monitoring.
Step 6: Develop an implementation plan that lays out project logistics.
Step 7: Draft your standard operating procedures (SOPs) & QAPP.
Step 8: Solicit feedback on your draft SOPs & QAPP from state or EPA
regional QA contacts and potential data users.
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Step 9: Revise your QAPP based on review
comments and submit it for approval.
Step 10: Once your QAPP is approved, begin your
monitoring program.
Step 11: Evaluate and refine your project over time,
and reflect any major changes in a revised
QAPP.
Basic QA/QC Concepts
It is important to understand the terminology of
quality assurance and quality control in order to
develop a QAPP. Key definitions include:
The"PARCC"
Parameters
Taken together, the terms
Precision, Accuracy, " — „••
Representativeness, — •
Completeness, and •*
Comparability, comprise ;
the major data quality • —
indicators used to assess _*' ^
the quality of your data. , • —
It is essential to ^
understand these terms —
and to address them in ^ -x_L-*»'" >
your QAPP. Chapters ,r -I—-'"
of this document includes
a discussion of these indicators and gives
examples of how to evaluate the quality of your
data in relation to these terms.
Precision — the degree of agreement among repeated measurements of the
same characteristic. It may be determined by calculating the standard
deviation, or relative percent difference, among samples taken from the
same place at the same time.
Accuracy — measures how close your results are to a true or expected value
and can be determined by comparing your analysis of a
standard or reference sample to its actual value.
Representativeness — the extent to which
measurements actually represent the true
environmental condition or population at the time a
sample was collected.
Completeness — the comparison between the amount
of valid, or usable, data you originally planned to
collect, versus how much you collected.
Comparability -- the extent to which data can be
compared between sample locations or periods of time
within a project, or between projects.
Elements of a QAPP
According to EPA
guidance, 24 distinct
elements can be
included in a QAPP,
although not all
elements may be
necessary for all
programs.
According to EPA guidance, 24 distinct elements can be included in a QAPP,
although not all elements may be necessary for all programs. Which elements
you end up including in your QAPP depends on your project's goals,
objectives, scope, data uses, and on the guidance you receive from your state or
Executive Summary
m
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EPA regional quality assurance contacts. The 24 elements are grouped into four
overall categories and are listed below:
Project Management (elements 1-9)
1. Title and Approval Page
2. Table of Contents
3. Distribution List
4. Project/Task Organization
5. Problem Identification/ Background
6. Project/Task Description
7. Data Quality Objectives for Measurement Data
8. Training Requirements/Certification
9. Documentation and Records
Measurement/Data Acquisition (elements 10-19)
10. Sampling Process Design
11. Sampling Methods Requirements
12. Sample Handling and Custody Requirements
13. Analytical Methods Requirements
14. Quality Control Requirements
15. Instrument/Equipment Testing, Inspection, and Maintenance
Requirements
16. Instrument Calibration and Frequency
17. Inspection/Acceptance Requirements for Supplies
18. Data Acquisition Requirements
19. Data Management
Assessment and Oversight (elements 20-21)
20. Assessment and Response Actions
21. Reports
Data Validation and Usability (elements 22-24)
22. Data Review, Validation, and Verification Requirements
23. Validation and Verification Methods
24. Reconciliation with Data Quality Objectives
iv The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Chapter 1:
INTRODUCTION
Across the country, volunteers are monitoring the condition of streams,
rivers, lakes, reservoirs, estuaries, coastal waters, wetlands, and wells.
The number and variety of these projects is continually on the rise; so,
too, is the complexity of the monitoring they conduct and the
uses of the data they collect.
Most volunteer monitoring projects evaluate the chemical,
physical, or biological condition of waters in a given watershed.
They may address different kinds of waters—e.g., streams with
associated embayments—and they may conduct several types of
monitoring activities. Some projects may address only one type
of monitoring in one type of waterbody, e.g., nutrient sampling
in estuaries. More
comprehensive projects may
take basic chemical
measurements of conditions
such as dissolved oxygen levels,
pH, or salinity, evaluate the
physical condition of streamside
habitat, and evaluate the
biological condition of aquatic
insects or vegetation.
Not only do volunteer projects monitor many different
parameters and types of waters, they are also organized and
supported in many different ways. Volunteer monitoring
projects may be associated with state, interstate, local, or federal
agencies, with environmental organizations or universities, or may be entirely
independent. Financial support may come from government grants, partnerships
with business, endowments, independent fundraising efforts, corporate donations,
membership dues, or a combination of any and all of these sources. Most
volunteer projects are fairly small and have very
small budgets—based on EPA's latest Directory of
Volunteer Environmental Monitoring Programs,
4th Edition, we know that the median program
size is 25 volunteers, and the median annual
budget is under $5,000. However, there are also
volunteer programs with over 1,000 volunteers
and those with annual budgets of more than
$50,000.
Top 2O
Parameters
Assessed by
Volunteer
Monitors
Water temperature
pH
Dissolved Oxygen
Macroinvertebrates
Debris clean-up
Habitat assessments
Nitrogen
Phosphorus
Turbidity
Coliform bacteria
Secchi depth
Aquatic vegetation
Flow
Birds /Wildlife
Fish
Watershed mapping
Rainfall
Photographic surveys
Salinity
Sediment assessments
Source: Directory of Volunteer
Environmental Monitoring
Programs, 4th Edition
Chapter 1: Introduction
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Although the goals and
objectives of volunteer
projects vary greatly,
virtually all volunteers hope
to educate themselves and
others about water quality
problems and thereby
promote a sense of
stewardship for the
environment. Many projects,
in fact, establish these as
their goals. These projects
might be called primarily
education oriented.
Other projects seek a more
active role in the
management of local water
resources, and therefore
strive to collect data that can be used in making water quality management
decisions. Common uses of volunteer data include local planning decisions, such
as identifying where to route a highway; local priority setting, such as
determining which county lakes require restoration; screening for potential
pollution problems, which might then be investigated more thoroughly by water
quality agencies; and providing data for state water quality reports, which might
then be used for statewide or national priority setting. Projects doing this type of
monitoring might be called primarily data oriented. Data oriented volunteer
projects, in particular, must continuously wrestle with the issue of credibility.
They must prove to skeptics that their volunteers collect
good-quality data that is:
Although the goals and
Volunteer Monitoring Data Uses
Education
Problem Identification
Local Decisions
Research
NFS Assessment
Watershed Planning
Habitat Restoration
Water Classif/Stds
Enforcement
Legislation
305(b)
I i
200 300
Number of Programs
Source: Directory of Volunteer Environmental Monitoring
Programs, 4th Edition
objectives of volunteer
projects vary greatly,
virtually all volunteers
hope to educate
themselves and others
about water quality
problems and thereby
promote a sense of
stewardship for the
environment.
I
> consistent over time and within projects and group
members
> collected and analyzed using standardized and
acceptable techniques
> comparable to data collected in other assessments using
the same methods
These projects must adopt protocols that are straightforward
enough for volunteers to master and yet sophisticated
enough to generate data of value to resource managers.
This delicate and difficult path cannot be successfully
navigated without a quality assurance plan that details a
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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project's standard operating procedures in the field and lab,
outlines project organization, and addresses issues such as
training requirements, instrument calibration, and internal
checks on how data are collected, analyzed, and reported.
Just how detailed such a plan needs to be depends to a large
extent on the goals of the volunteer monitoring project.
What Is a Quality Assurance
Project Plan?
A Quality Assurance
Project Plan, or QAPP,
is a written document
outlining the procedures
a monitoring project
will use to ensure the
data it collects and
analyzes meets project
requirements.
A Quality Assurance Project Plan, or QAPP, is a written
document outlining the procedures a monitoring project will
use to ensure the data it collects and analyzes meets project
requirements. The U.S. Environmental Protection Agency
(EPA) has issued interim guidance that establishes up to 24
distinct elements of a QAPP (see Appendix C: References).
Together, these elements of a QAPP comprise a project's quality assurance
system. As we will discuss below, not all 24 elements need be addressed in every
QAPP.
By law, any EPA-funded monitoring project must
before it can begin collecting samples. The
purpose of this requirement is to ensure that the
data collected by monitoring projects are of
known and suitable quality and quantity.
Typical sources of EPA funding for volunteer
monitoring projects include Lake Water
Quality Assessment Grants (under Section 314
of the Clean Water Act) or grants under the
nonpoint source pollution control program
(Section 319 of the Clean Water Act). Quality
assurance staff in each of EPA's 10 regional
offices are available to review volunteer
monitoring QAPPs and have authority to
recommend approval or disapproval of QAPPs.
In addition, volunteer monitoring coordinators
and individual EPA project officers in the EPA
Regions may be able to assist projects seeking
advice on the preparation of QAPPs. (See
Appendix A, Regional Quality Assurance
Contacts.)
About This Document
The purpose of this document is to provide
volunteer monitoring programs with the
information they need to develop a quality
have an EPA-approved QAPP
Why Should You Develop
a QAPP?
The QAPP is an invaluable planning and
operating tool that should be developed in the early
stages of the volunteer monitoring project.
Even if a volunteer monitoring project does not
receive any EPA money through grants, the
coordinating group should still consider developing a
QAPP, especially if it is a data oriented
project and seeks to
have its information
used by state, federal, or
local resource
managers.
Few water quality
agencies will use
volunteer data unless
methods of data
collection, storage, and analysis can be documented.
Clear and concise documentation of procedures also
allows newcomers to the project to continue
monitoring using the same methods as those who
came before them.
This is particularly important to a volunteer project
that may see volunteers come and go and that intends
to establish a baseline of water quality information that
can be compared over time.
Chapter 1: Introduction
-------
The purpose of this
document is to provide
volunteer monitoring
programs with the
information they need to
develop a quality assurance
project plan.
assurance project plan. It does not suggest specific field,
laboratory, or analytical techniques or procedures, and is
not a "how to" manual. It is organized as follows:
Executive Summary introduces the reader to the steps
involved in developing a QAPP, fundamental QA/QC
concepts, and the basic elements of a QAPP.
Chapter 1: Introduction provides background on
volunteer monitoring, discusses the purposes of QAPPs,
and outlines the structure of this document.
Chapter 2: Developing a QAPP outlines the steps a
volunteer monitoring project should take as it moves toward developing a quality
assurance system, documenting its procedures in a QAPP, seeking approval of its
QAPP, and updating the QAPP over time.
Chapter 3: QA/QC: Basic Concepts introduces basic quality assurance/quality
control (QA/QC) concepts and definitions that are needed in developing a quality
assurance system and a QAPP. Examples from a fictional project—the Volunteer
Creek Monitoring Project—are used to illustrate these concepts.
Chapter 4: Elements of a QAPP presents the basic elements of a volunteer
monitoring quality assurance project plan (QAPP), again with examples from the
QAPP of the fictional Volunteer Creek Monitoring Project.
Appendix A: Glossary defines various terms and concepts associated with quality
assurance and control.
Appendix B: EPA Regional Contacts is a list of people within EPA who can
assist, and offer guidance to, volunteer monitoring programs. Each of the 10
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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EPA regions has a volunteer monitoring coordinator as well as QA staff. This
appendix also shows which states and U.S. territories are within each of the 10
regions.
Appendix C: References is a list of documents and
articles relevant to volunteer monitoring and quality
assurance issues. All EPA volunteer monitoring
documents are available by contacting the National
Volunteer Monitoring Coordinator at USEPA. The
address is given in the appendix.
Appendix D: Abbreviated QAPP Form is an example of
the layout and structure of a quality assurance project
plan. Some programs may wish to adapt this form to fit
their plan.
Volunteer monitoring
programs are strongly
urged to consult the
references listed in
Appendix C for further
information on quality
assurance/quality control
This document is not intended as a stand-alone reference
document. Volunteer monitoring programs are strongly
urged to consult the references listed in Appendix C for
further information on quality assurance/quality control and the Quality
Assurance Project Plan process.
and the Quality Assurance
Project Plan process.
Chapter 1: Introduction
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The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Chapter 2:
DEVELOPING A QAPP
The purpose of this chapter is to discuss the steps a volunteer monitoring
program might take in preparing a quality assurance project plan
(QAPP). If your plan does not need to be approved by EPA (that is, you
are not receiving EPA grant or contract money to conduct your monitoring), you
need not submit your QAPP for EPA
approval. In that case, consult your
data users, such as the state or county
water quality agency, regarding their
QAPP requirements.
Developing a QAPP is a dynamic,
interactive process. Seek as much
feedback as possible from those who
have gone before you in the QAPP
development process. You will be
investing a substantial amount of time
and energy, but don't be discouraged.
The person who writes the QAPP is
usually the one who ends up with the
most technical expertise and
monitoring insights. Your efforts will
pay off in a living document that
helps current and future volunteers,
staff, and data users understand
exactly how your project works.
STEPS TO DEVELOPING A
QAPP
step 1: Establish a QAPP team
step 2: Determine the goals & objectives of your project
step 3: Collect background information
step 4: Refine your project
step 5: Design your projects sampling, analytical & data
requirements
step 6: Develop an implementation plan
step 7: Draft your standard operating procedures (SOPs) &
QAPP
step 8: Solicit feedback on your draft SOPs & QAPP
step 9: Revise your QAPP & submit it for final approval
step 10: Begin your monitoring project
step 11: Evaluate and refine your QAPP
STEP 1
Establish a small QAPP team
It will be helpful to pull together a small team of two or three people who can
help you develop the QAPP. Include representatives from groups participating in
the monitoring project who have technical expertise in different areas of the
project.
Take the time to establish contact with your state, local or EPA Quality
Assurance Officer, or other experienced volunteer organizations. Remember, if
you are getting any EPA funding through a grant or contract, EPA must approve
your QAPP. However, even if EPA approval isn't needed, you can consult with
Chapter 2: Developing a QAPP
-------
EPA QA representatives if you need advice. Let them know a bit about your
project, and find out if they have any resources that might help you out (such as a
copy of an approved volunteer monitoring QAPP, or specific regional guidance
on preparing plans). Also ask your QA contact if he or she would be willing to
review your draft plan.
STEP 2
Determine the
goals and
objectives of your
project
Why are you developing this
monitoring project? Who will
use its information, and how will
it be used? What will be the basis
for judging the usability of the
data collected? If you don't have
answers to these questions, you
may flounder when it comes time
to put your QAPP down on paper.
Why are you developing
this monitoring project?
Who will use its
information, and how will it
be used? If you don't have
answers to these questions,
you may flounder when it
comes time to put your
QAPP down on paper.
Project goals could include, for example:
identifying trends in a lake to determine if nuisance
vegetation problems are on the rise
monitoring in conjunction with the county health
department to be sure a beach is safe for swimmers
teaching local elementary schoolers about stream
macroinvertebrates
monitoring the effectiveness of a stream restoration
project
Write down your goal. The more specific your project's
goal, the easier it will be to design a QAPP. Identify the
objectives of your project—that is, the specific statements
of how you will achieve your goal. For example, if your project's goal is to
identify trends in a lake plagued by nuisance vegetation, your objectives might be
to collect three years of data on weed beds, algae, and nutrients, and to develop
yearly reports for nearby lake residents.
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Knowing the use of the collected data will help you
determine the right kind of data to collect, and the level of
effort necessary to collect, analyze, store, and report it.
Volunteer monitoring data can be used to screen for
problems, educate youth and the community, supplement
state agency data, help set statewide priorities for pollution
control, and a myriad of other uses. Each use of volunteer
data has potentially different requirements.
Your project should be designed to meet the needs of your
data users. Data users can include the volunteers
themselves, state water quality analysts, local planning
agencies, parks staff, or many others. You will also
probably need to strike a balance between data quality and
available resources.
STEP 3
Collect background information
Knowing the use of the
collected data will help
you determine the right
kind of data to collect,
and the level of effort
necessary to collect,
analyze, store, and
report it...Each use of
volunteer data has
potentially different
requirements.
As you learn more about the area you are choosing to monitor, you will be better
able to design an effective monitoring project. Begin by contacting programs and
agencies that might already monitor in your area. Talk to the state water quality
agency, the county and/or city environmental office, local universities, and
neighboring volunteer monitoring programs. Ask about their sampling locations,
what parameters they monitor and what methods they use.
If they are already monitoring in your chosen area, find out if they will share their
data, and identify what gaps exist that your project could fill. If no monitoring is
ongoing, find out what kind of data your local or state agencies could use (if one
of your goals is that these agencies use your data), where they would prefer you
locate your sampling sites, and what monitoring
methods they recommend. Government
agencies are not likely to use your data
unless it fills a gap in their monitoring
network and was collected using
approved protocols.
A watershed survey can help you set the
foundation for your monitoring project
design. This is simply a practical
investigation of how the watershed works, its
history, and its stressors. For information on
conducting a watershed survey, consult Volunteer
Stream Monitoring: A Methods Manual (Draft,
April 1995, EPA 841-D-95-001).
Chapter 2: Developing a QAPP
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STEP 4
Refine your project
Once you've collected background information for your project and coordinated
with potential data users, you may find it necessary to refine your original project
goals and objectives. You may have found, for example, that the county already
regularly monitors weed and algae growth in your lake. In
that case, your project might better examine nutrient inputs
from tributaries, lake water clarity, or other parameters.
Once you 've collected
background information
for your project and
coordinated with
potential data users, you
may find it necessary to
refine your original
project goals and
objectives.
Don't hesitate to reevaluate your project goals and
objectives. Now is the best possible time to do so: before
you've invested time, money, and effort in equipment
purchases, training, grant proposals and quality assurance
plan development.
STEP 5
Design your project's sampling,
analytical, and data
requirements
Once you feel comfortable with your project's goals and objectives, and have
gathered as much background information as possible on the area you will be
monitoring, it is time to focus on the details of your project. Convene a planning
committee consisting of the project coordinator, key volunteers, scientific
advisors, and data users, along with your QAPP team. This committee should
address the following questions:
> What parameters or conditions will you monitor, and which are most
important to your needs? Which are of secondary importance?
> How good does your monitoring data need to be?
> How will you pick your sampling sites, and how will you identify them over
time?
> What methods or protocols will you use for sampling and analyzing samples?
> When will you conduct the monitoring?
> How will you manage your data and ensure your data are credible?
10
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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As a general rule, it is a good idea to start small and build to a more ambitious
project as your volunteers and staff grow more experienced.
STEP 6
Develop an implementation plan
You've done the hard part once you've developed your monitoring project design.
The next step is to decide the particulars — the logistics, if you will. These are,
essentially, the whos and whens of your project.
Determine who will carry out individual tasks such as volunteer training, data
management, report generation, assuring lab and field quality assurance, and
recruiting volunteers. If you send your samples to an outside lab, choose the lab
and specify why you chose it.
Set up schedules for when you will recruit and train
volunteers, conduct sampling and lab work, produce reports,
and report back to volunteers or the community.
STEP 7
Draft your standard operating
procedures and QAPP
Now it's time to actually write your standard operating
procedures and develop a draft QAPP. Your standard
operating procedures (SOPs) are the details on all the
methods you expect your volunteers to use and can serve as
the project handbook you give your volunteers. Remember,
there are many SOPs already available for sampling and
analytical procedures. Where possible,
adapt your procedures from existing
methods and modify them as needed to fit
your project objectives. Be sure to
reference and cite any existing methods
and documents you use in your project.
Your standard operating
procedures (SOPs) are
the details on all the
methods you expect
your volunteers to use.
This can serve as the
project handbook you
give your volunteers.
You should append your standard
operating procedures to your QAPP and
refer to them throughout the QAPP
document. Use the elements described in
Chapter 4 as your guide in developing a
draft QAPP. Your written plan can be
elaborate or simple, depending on your project goals.
Chapter 2: Developing a QAPP
11
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STEP 8
Solicit feedback on your draft SOPs and
QAPP
Draft QAPP in hand, your next step is to run the draft by people "in the know."
These are, primarily, state and EPA Regional volunteer monitoring coordinators
and Quality Assurance Officers, EPA project officers, and any other agency data
users (such as a representative from the county planning
office or Natural Resource Conservation Service, if you are
collecting data you hope they will use). Ask for their
feedback and suggestions. Expect their review to take up to
two or three months (times will vary).
Based on the comments
you receive from the
review of your draft
plan, you may have to
revise your QAPP.
While you are waiting for comments, you should probably
try out your procedures with volunteers on a trial basis, to
see if they really work. Don't plan to use the data at this
early stage, however; you will probably be finding quirks in
your plan, and the data will not be accepted by your data
users until the QAPP is approved and accepted.
You may find that some of your Q A contacts resist the idea of reviewing your
draft plan. This is because they are often quite overburdened. Don't give up;
after a reasonable time has elapsed since you submitted your plan, call back and
inquire if you should submit the draft elsewhere for review. Solicit all the
comments you can, from as many sources as possible.
STEP 9
Revise your QAPP and submit it for final
approval
Based on the comments you receive from the review of your draft plan, you may
have to revise your QAPP. This could involve simply being more specific about
existing methods and quality control procedures in the plan, or actually modifying
your procedures to meet agency requirements. Once you have revised or fine-
tuned your QAPP, submit it to the proper agency for formal approval.
Final review/approval can take a couple of months. During this time, you may be
asked to incorporate additional comments, although this is less likely if you had
previously asked the approving official to review your draft.
Note: If you are developing a QAPP simply to document your methods and are
not working in cooperation with a state, local, or federal agency, you need not
submit a QAPP for review and approval.
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The Volunteer Monitor's Guide to Quality Assurance Project Plans
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STEP 1O
Once the QAPP is approved, begin your
monitoring project
Once you've received EPA and/or state approval of your QAPP, your monitoring
project can begin. Follow the procedures described in your QAPP to train
volunteers and staff, conduct sampling, analyze samples, compile
results, and develop any reports.
STEP 1 1
Evaluate and refine
your project over time
As time goes on, you may decide to
improve on sampling techniques, site
selection, lab procedures or any of the other elements of your
monitoring project design. Project evaluation should occur
during the course of your project rather than after the project or a
sampling season is completed.
If you make any substantive changes in your QAPP, document them and seek
EPA/state approval for the changes. A phone call to your QA official can help
you determine if the changes require a new QAPP. Also, always be prepared for
formal audits or QC inquiries from data users during the course of your project.
Chapter 2: Developing a QAPP
13
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14 The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Chapter 3:
SOME BASIC QA/QC
As coordinator of a volunteer monitoring program, you are probably
involved in many aspects of project planning, sample collection,
laboratory analysis, data review, and data assessment. You should be
considering quality assurance and quality control activities in every one of these
steps.
Quality assurance (QA) refers to the overall management
system which includes the organization, planning, data
collection, quality control, documentation, evaluation, and
reporting activities of your group. QA provides the
information you need to ascertain the quality of your data
and whether it meets the requirements of your project. QA
ensures that your data will meet defined standards of quality
with a stated level of confidence.
Quality control (QC) refers to the routine technical activities
whose purpose is, essentially, error control. Since errors
can occur in either the field, the laboratory or in the
office, QC must be part of each of these functions. QC
should include both internal and external measures (see
side box).
QA ensures that your
data will meet defined
standards of quality
with a stated level of
confidence.
Together, QA and QC help you produce data of known
quality, enhance the credibility of your group in
reporting monitoring results, and ultimately save time
and money. However, a good QA/QC program is only
successful if everyone consents to follow it and if all
project components are available in writing. The Quality
Assurance Project Plan (QAPP) is the written record of
your QA/QC program.
This chapter is designed to introduce you to the
terminology of quality assurance/quality control. The
key terms we will be addressing are: precision, accuracy
(sometimes referred to as bias), representativeness,
completeness, comparability, and sensitivity. You will
QC Measures
Internal Quality Control is a set of
measures that the project undertakes
among its own samplers and within its
own lab to identify and correct analytical
errors. Examples include lab analyst
training and certification, proper
equipment calibration and
documentation, laboratory analysis of
samples with known concentrations or
repeated analysis of the same sample, and
collection and analysis of multiple
samples from the field.
External Quality Control is a set of
measures that involves laboratories and
people outside of the program. These
measures include performance audits by
outside personnel, collection of samples
by people outside of the program from a
few of the same sites at the same time as
the volunteers, and splitting some of the
samples for analysis at another lab.
External and internal QC measures are
described in more detail in the "QC
Samples" box at the end of this chapter.
T
Chapter 3: Some Basic QA/QC Concepts
15
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Measures of precision,
accuracy,
representativeness,
completeness,
comparability, and
sensitivity help us
evaluate sources of
variability and error and
thereby increase
confidence in our data.
be seeing these terms again, so you may want to spend some
time getting to know them.
In natural systems, such as streams, lakes, estuaries, and
wetlands, variability is a factor of life. Changes in
temperature, flow, sunlight, and many other factors affect
these systems and the animals that inhabit them. Variability
also occurs when we attempt to monitor such systems. Each
of us reads, measures, and interprets differently; we may
also apply different levels of effort in how we monitor. The
equipment we use may be contaminated, broken or
incorrectly calibrated. These and many other differences
can lead to variability in monitoring results. Measures of
precision, accuracy, representativeness, completeness,
comparability, and sensitivity help us evaluate sources of
variability and error and thereby increase confidence in our
data.
Because all projects have different goals, data users and uses, capabilities, and
methods, this document cannot tell you what levels of precision, accuracy,
representativeness, completeness, comparability, and sensitivity are acceptable for
your individual project. You will need to consult your advisory panel (in
particular, your data users), the laboratory you deal with, and peer reviewers to
determine acceptance criteria for your
monitoring project.
Precision
Precision is the degree of agreement
among repeated measurements of the
same characteristic on the same
sample or on separate samples
collected as close as possible in time
and place. It tells you how consistent
and reproducible your field or
laboratory methods are by showing
you how close your measurements are
to each other. It does not mean that
the sample results actually reflect the
"true" value, but rather that your
sampling and analysis are giving
consistent results under similar
conditions.
Typically, precision is monitored
through the use of replicate samples or
16
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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measurements. Replicate samples are
two or more samples taken from the
same place at the same time.
When you have many replicate
samples, determine precision by
calculating the standard deviation(s)
of the samples. The standard
deviation indicates the range of
variation in the measurements you've
taken. Many of today's calculators
perform the standard deviation
calculation.
The relative standard deviation
(RSD), or coefficient of variation,
expresses the standard deviation as a
percentage. This is generally easier
for others to understand. The smaller
the relative standard deviation (or
standard deviation), the more precise
your measurements.
When you have only two replicate
samples, determine precision by
calculating the relative percent
difference (RPD) of the two samples.
Again, the smaller the relative percent
difference, the more precise your
measurements.
RELATIVE STANDARD
DEVIATION
If we use the same replicate measurements as
above in the standard deviation example, we
can determine the Relative Standard
Deviation (RSD), or coefficient of variation,
using the following formula:
X
where s =
standard
deviation and x
= mean of
replicate
samples.
We knows = 0.5315 and that x = 20.68. So,
the RSD = 2.57. This means that our
measurements deviate by about 2.57%.
STANDARD DEVIATION
The Volunteer Creek Monitoring Project wants to determine the
precision of its temperature assessment procedure. They have
taken 4 replicate samples:
Replicate 1 (Xj) = 21.1° C
Replicate 2 (X2) = 21.1° C
Replicate 3 (X3) = 20.5° C
Replicate 4 (X4) = 20.0° C
To determine the Standard Deviation (s), use the following
formula:
s =
First, figure out the mean, or
average of the sample measurements. Mean = (Xt + X2 + X3 + X4)
-^ 4. In this example, the mean is equal to 20.68° C.
Then, for each sample measurement (Xt through X4), calculate the
next part of the formula. For Xl and X2, the calculation would
look like this:
(21.1 - 20.68)2 = (-0.42)2 = 0.1764 = 0.0588
4-1 3 3
For X3 the calculation would be 0.0108; and for X4 it would be
0.1541
Finally, add together the calculations for each measurement and
find the square root of the sum: 0.0588 + 0.0588 + 0.0108 +
0.1541 = 0.2825. The square root of 0.2825 is 0.5315.
So, the standard deviation for temperature is 0.532 (rounded off).
\
\
n
E
z = l
^_
(XrX?
where Xj = measured value of
the replicate, x = mean of
replicate measurements, n =
number of replicates, £ = the
sum of the calculations for each
measurement value— in this case,
X; through X4
RELATIVE PERCENT
DIFFERENCE
If the Volunteer Creek project had only two replicates (21.1° C
and 20.5° C) they would use Relative Percent Difference (RPD)
to determine precision.
RPD =
v 1 flfl
1UU
RPD= (21. 1-20.5) x 100 =60.00
(21.1+20.5)^2 20.8
where Xt = the larger of
the two values and X2 =
the smaller of the two
values. In this example,
X== 21.1° and X2 = 20.5°.
= 2.88
So, in this example, the RPD between our sample measurements is
2.88%.
Chapter 3: Some Basic QA/QC Concepts
17
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Accuracy
Accuracy is a measure of confidence in a measurement. The smaller the
difference between the measurement of a parameter and its "true" or expected
value, the more accurate the
measurement. The more precise or
reproducible the result, the more
reliable or accurate the result.
PRECISION, BIAS, AND
ACCURACY
Precision
High Low
CD
Accurate
N
a
Inaccurate
• • • •
,0'
Inaccurate
7.5
7.4
6.7
Measurement accuracy can be
determined by comparing a sample
that has a known value, such as a
standard reference material or a
performance evaluation sample, to a
volunteer's measurement of that
sample (see note below).
Increasingly, however, some
scientists, especially those involved
with statistical analysis of
measurement data, have begun to use
the term "bias" to reflect this error in
the measurement system and to use
"accuracy" as indicating both the
degree of precision and bias (see
"bullseye" figure at left). For the
purpose of this document, the term
"accuracy" will be used.
If you are concerned that other components of a sample matrix (e.g., soil or
sludge) may be interfering with analysis of a parameter, one way to measure
accuracy is to add a known concentration of the parameter to a portion of the
sample. This is called a spiked
sample. The difference between the
original measurement of the
parameter in the sample and the
measurement of the spiked sample
should equal (or be close to) the added
amount. The difference indicates
your ability to obtain an accurate
measurement.
ACCURACY
Attendance at QC training sessions is required for Volunteer
Creek monitors. In the field, monitors use a Jones Wide-Range
pH Kit, which covers a full range of expected pH values. During
a recent training session, the monitors recorded the following
results when testing a pH standard buffer solution of 7.0 units.
7.2
6.8
7.3
6.5
7.2
6.8
7.0
7.4
7.2
Accuracy = average value - true value
The average of these measurements is equal to 7.08 units. Since
we know that the reference or "true" value is 7.0 units, the
difference between the average pH value is off or biased by + 0.08
units. This level of accuracy is satisfactory for the data quality
objectives of the project.
\
For many parameters such as secchi
depth and macroinvertebrate
abundance, no standard reference or
performance evaluation samples exist.
In these cases, the trainer's results may
be considered the reference value to
18
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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which the volunteer's results are compared. This
process will help evaluate if the volunteer
measurements are biased as compared to the
trainer's.
If you are monitoring biological conditions by
collecting and identifying specimens, maintaining
a voucher collection is a good way to determine if
your identification procedures are accurate. The
voucher collection is a preserved archive of the
organisms your volunteers have collected and
identified. An expert taxonomist can then provide a "true"
value by checking the identification in the voucher collection.
It is important to note that the relationship between a voucher
collection and accurate identification cannot be expressed
numerically in your QAPP. Rather, the QAPP document should
indicate that you have a voucher collection and describe how it is
used to evaluate consistent accurate identification in your
program.
Note: Standard reference material (in the form of solids or solutions with a
certified known concentration of pollutant) can be obtained from a variety of
companies, including the National Institute of Standard and Technologies, that
sell quality control, proficiency, or scientific reference materials.
Representativeness
Representativeness is the extent to which measurements actually depict the true
environmental condition or population you are evaluating. A number of factors
may affect the representativeness of your data. For instance, are your sampling
locations indicative of the waterbody? Data collected just below a pipe outfall is
not representative of an entire stream. Minimizing the effects of variation is
critical in the development of your sampling design.
Completeness
Completeness is a measure of the number of samples you must take to be able to
use the information, as compared to the number of samples you originally
planned to take. Since there are many reasons why your volunteers may not
collect as many samples as planned, as a general rule you should try to take more
samples than you determine you actually need. This issue should be discussed
within your QAPP team and by peer reviewers before field activities begin.
Chapter 3: Some Basic QA/QC Concepts
19
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The Volunteer Creek Monitoring project planned to collect 20
samples, but because of volunteer illness and a severe storm, only
17 samples were actually collected. Furthermore, of these, two
samples were judged invalid because too much time elapsed
between sample collection and lab analysis. Thus, of the 20
samples planned, only 15 were judged valid.
The following formula is used to determine Percent
Completeness (%C).
%C=-;dOO
T
where v = the number of planned
measurements judged valid and T = the
total number of measurements.
In this example, v = 15 and T = 20. In
this case, percent completeness would
be 75 percent. Is this enough information to be useful?
To calculate percent completeness,
divide the number of measurements
that have been judged valid by the
total number of measurements you
originally planned to take and then
multiply by 100.
Remember, completeness
requirements can be lowered if extra
samples are factored into the project.
The extra samples in turn, increase the
likelihood of more representative data.
Comparability
Comparability is the extent to which
data from one study can be compared
directly to either past data from the current project or data from another study.
For example, you may wish to compare two seasons of summer data from your
project or compare your summer data set to one collected 10 years ago by state
biologists.
Using standardized sampling and analytical methods, units of reporting, and site
selection procedures helps ensure comparability. ___
However, it is important to keep in mind that some
types of monitoring rely heavily on best professional
judgement and that standard methods may not always
exist.
Detection Limit
The term detection limit can apply to monitoring and
analytical instruments as well as to methods. In general,
detection limit is defined as the lowest concentration of
a given pollutant your methods or equipment can detect
and report as greater than zero. Readings that fall below the detection limit are
too unreliable to use in your data set. Furthermore, as readings approach the
detection limit (that is, as they go from higher, easier-to-detect concentrations to
lower, harder-to-detect concentrations) they become less and less reliable.
Manufacturers generally provide detection limit information with high-grade
monitoring equipment such as meters.
Measurement Range
The measurement range is the range of reliable measurements of an instrument or
measuring device. Preassembled kits usually come with information indicating
20
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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the measurement range that applies. For example, you might
purchase a kit that is capable of detecting pH falling between 6.1
and 8.1. However, pH can theoretically range from 0.0 to 14.00.
If acidic conditions (below 6) are a problem in the waters you
are monitoring, you will need to use a kit or meter that is
sensitive to the lower pH ranges.
Quality Control (QC) Samples
Contamination is a common source of error in both sampling
and analytical procedures. QC samples help you identify when
and how contamination might occur. For most projects, there is
no set number of field or laboratory QC samples which must be
taken. The general rule is that 10% of samples should be QC
samples. This means that if 20 samples are
collected, at least one additional sample must
be added as a QC sample. The laboratory
must also run its own QC samples. For a new
monitoring project or for a new analytical
procedure, it is a good idea to increase the
4 number of QC samples
(up to 20%) until you
= have full confidence in
the procedures you are
using.
The general rule is that
10% of samples should
be quality control (QC)
samples.
When the project is over, determine data quality by
evaluating the results of all the QC samples and determining
precision and accuracy. For QC samples that are not blind
to the lab, require the lab to calculate and report precision and accuracy results.
Lab reported precision and accuracy results can then be checked during data
validation.
The decision to accept data, reject it, or accept only a portion of it is should be
made after analysis of all QC data. Various types of QC samples are described in
the box on the next page.
Chapter 3: Some Basic QA/QC Concepts
21
-------
QC SAMPLES
A field blank is a "clean" sample, produced
in the field, used to detect analytical
problems during the whole process
(sampling, transport, and lab analysis). To
create a field blank, take a clean sampling
container with "clean" water (i.e., distilled
or deionized water that does not contain
any of the substance you are analyzing
for) to the sampling site. Other sampling
containers will be filled with water from
the site. Except for the type of water in
them, the field blank and all site samples
should be handled and treated in the same
way. For example, if your method calls
for the addition of a preservative, this
should be added to the field blank in the
same manner as in the other samples.
When the field blank is analyzed, it
should read as analyte-free or, at a
minimum, the reading should be a
factor of 5 below all sample results.
An equipment or rinsate blank is a
"clean" sample used to check the
cleanliness of sample collection
equipment. This type of blank is
used to evaluate if there is
carryover contamination from reuse
of the same sampling equipment.
A sample of distilled water is
collected in a sample container
using regular collection
equipment and analyzed as a
sample.
A split sample is one sample that is divided
equally into two or more sample containers
and then analyzed by different analysts or
labs. Split samples are used to measure
precision. Samples should be thoroughly
mixed before they are divided. Large errors
can occur if the analyte is not equally
distributed into the two containers. A
sample can be split in the field, called a field
split, or in the laboratory, a lab split. The
lab split measures analytical precision while
the field split measures both analytical and
field sampling precision. In addition, a
sample split in the field and submitted to the
laboratory without informing the laboratory
represents a blind sample. Split samples can
also be submitted to two different
laboratories for analysis to measure the
variability in results between laboratories
independently using the same analytical
procedures.
> Replicate samples are obtained when two
or more samples are taken from the same
site, at the same time, using the same
method, and independently analyzed in
the same manner. When only two
samples are taken, they are sometimes
referred to as duplicate samples. These
types of samples are representative of the
same environmental condition.
Replicates (or duplicates) can be used to
detect both the natural variability in the
environment and that caused by field
sampling methods.
Spiked samples are samples to
which a known concentration of the
analyte of interest has been added.
Spiked samples are used to
measure accuracy. If this is done in
the field, the results reflect the
effects of preservation, shipping,
laboratory preparation, and
analysis. If done in the laboratory,
they reflect the effects of the
analysis from the point when the
compound is added, e.g. just prior
to the measurement step. Percent
recovery of the spike material is
used to calculate analytical accuracy.
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The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Chapter 4:
ELEMENTS OF A QAPP
This chapter discusses the 24 elements of a Quality Assurance Project Plan,
as outlined in EPA quality assurance guidance, EPA Requirements for
Quality Assurance Project Plans for Environmental Data Operations
(EPA QA/R-5, August 1994). It is very likely that not all elements will apply to
your project. This is an issue that should be discussed with your QAPP team and
any group who will be approving the QAPP. If your project does not require all
24 elements, indicate in your QAPP which elements you will not be including.
This will make review and approval of your QAPP faster and easier.
Throughout this chapter, brief examples
from a fictional monitoring project—the
They are not intended to be
comprehensive, but rather simply to
help illustrate the type of information
that might be included in the elements
of a QAPP. For more information, you
may wish to contact other volunteer
monitoring programs with approved
QAPPs.
TITLE AND
APPROVAL PAGE
Your title page should include the
following:
> title and date of the QAPP
> names of the organizations
involved in the project
> names, titles, signatures, and
document signature dates of all
appropriate approving officials
such as project manager, project
QA officer, and, if the project is
funded by EPA, the EPA project
manager and QA officer.
are included. The examples are drawn
Volunteer Creek Monitoring Project.
ELEMENTS OF A QAPP
Project Management
(elements 1-9)
1. Title and Approval Page
2. Table of Contents
3. Distribution List
4. Project/Task Organization
5. Problem Identification/ Background
6. Project/Task Description
7. Data Quality Objectives for Measurement Data
8. Training Requirements/ Certification
9. Documentation and Records
Measurement/Data Acquisition
(elements 10-19)
10. Sampling Process Design
11. Sampling Methods Requirements
12. Sample Handling and Custody Requirements
13. Analytical Methods Requirements
14. Quality Control Requirements
15. Instrument/Equipment Testing, Inspection, and
Maintenance Requirements
16. Instrument Calibration and Frequency
17. Inspection/Acceptance Requirements for Supplies
18. Data Acquisition Requirements
19. Data Management
Assessment and Oversight
(elements 20-21)
20. Assessment and Response Actions
21. Reports
Data Validation and Usability (elements 22-24)
22. Data Review, Validation, and Verification
Requirements
23. Validation and Verification Methods
24. Reconciliation with Data Quality Objectives
T
Chapter 4: Elements of a QAPP
23
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TABLE OF CONTENTS
A Table of Contents should include section headings with appropriate
page numbers and a list of figures and tables.
DISTRIBUTION LIST
List the individuals and organizations that will receive a copy of your
approved QAPP and any subsequent revisions. Include representatives
of all groups involved in your monitoring effort.
41 PROJECT/
I TASK
ORGANIZATION
Identify all key personnel
and organizations that are
involved in your program,
including data users. List
their specific roles and
responsibilities. In many
monitoring projects, one
individual may have
several responsibilities.
An organizational chart is
a good way to graphically
display the roles of key
players.
ELEMENT 4
Project/Task Organization
In addition to the project officers shown, the
Volunteer Creek Monitoring Project also has an
Advisory Panel consisting of representatives
from EPA, the state Department of
Environmental Conservation (DEC), and the
County Department of Public Works (DPW).
Each of the leaders shown serves on the
Advisory Panel. Major responsibilities of all
personnel are detailed in the Volunteer Creek
SOPs, attached to this document. The primary
data users are the state DEC and the County
DPW.
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The Volunteer Monitor's Guide to Quality Assurance Project Plans
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PROBLEM DEFINITION/ BACKGROUND
In a narrative, briefly state the problem your monitoring project is
designed to address. Include any background information such as
previous studies that indicate why this project is needed. Identify how your data
will be used and who will use it.
Gi PROJECT/TASK DESCRIPTION
| In general terms, describe the work your volunteers will perform and
where it will take place. Identify what kinds of samples will be taken,
what kinds of conditions they will measure, which are critical, and which are of
secondary importance. Indicate how you will evaluate your results—that is, how
you will be making sense out of what you find. For example, you may be
comparing your water quality readings to State or EPA standards, or comparing
your macroinvertebrate evaluations to State-established reference conditions or
historical information.
Chapter 4: Elements of a QAPP
25
-------
Include an overall project timetable that outlines beginning and ending dates for
the entire project as well as for specific activities within the project. The
timetable should include information about sampling frequency, lab schedules,
and reporting cycles.
ELEMENT 6
Project/Task Description
From January through March 1996, the Watershed Association will conduct initial volunteer recruitment and
training in conjunction with the county and state. A second recruitment drive as well as training and retraining
sessions will be held from August to October.
Monthly water sampling of temperature, pH, turbidity, and dissolved oxygen will occur throughout the calendar
year at each of 20 sites. At the same sites, macroinvertebrate and habitat assessments will be conducted in
March, July, and October. In order to characterize the stream and to create a baseline of data, each of these
evaluations is a critical component of the overall study. For informational and educational purposes, volunteers
will also record characteristics such as water odor and color during each assessment. Macroinvertebrate
taxonomy will take place in April, August, and November at the state university biology laboratory.
Following each assessment, all data will be entered into the computerized management system and analyzed.
Interim report of findings will be produced and distributed in May and September. A final, year-end report will
be produced and distributed in January 1997.
MAJOR TASK CATEGORIES
volunteer recruitment, training, and re-training
monthly pH, temp., turbidity, & dissolved oxygen sampling
seasonal macroinvertebrate & habitat assessments
lab analysis
data processing, analysis & reporting
J
X
X
F
X
X
M
X
X
X
A
X
X
M
X
X
J
X
X
J
X
X
A
X
X
X
S
X
X
X
o
X
X
X
X
N
X
X
X
D
X
X
DATA QUALITY OBJECTIVES FOR
MEASUREMENT DATA
Data Quality Objectives (DQOs) are the quantitative and qualitative terms you
use to describe how good your data need to be to meet your project's objectives.
DQOs for measurement data (referred to here as data quality indicators) are
precision, accuracy, representativeness, completeness, comparability, and
measurement range. Provide information on these indicators, in quantitative
terms if possible. See Chapter 3 for a further discussion of these terms.
Since it is important to develop a QAPP prior to monitoring, it may not be
possible to include actual numbers for some of the data quality measurements
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The Volunteer Monitor's Guide to Quality Assurance Project Plans
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ELEMENT 7
Data Quality Objectives for
Measurement Data
Precision, Accuracy, Measurement Range
The following table illustrates the precision, accuracy and
measurement range for the Volunteer Creek pH, temperature,
turbidity, and dissolved oxygen assessments.
Matrix Parameter
Precision Accuracy
MR*
water pH
±20%
±0.5
water temperature
±20%
water dissolved oxygen ±20% ±0.3mg/L 1 to 20 mg/l
water turbidity
±20% ±0.2mg/L 0 to 1000 MTU
within the first version of the
document. You will need,
however, to discuss your goals
or objectives for data quality
and the methods you will use
to make actual determinations
after monitoring has begun.
You must also discuss at what
point changes will be made if
project specifications are not
achieved. Data quality
indicators should be given for
each parameter you are
measuring, in each "matrix"
(i.e., substance you are
sampling from, such as water
or sediment). The easiest way
to present quantitative
information is in a table.
In some types of monitoring,
particularly macroinvertebrate
monitoring and habitat
assessment, some data quality
indicators cannot be
quantitatively expressed. In
that case, you can fulfill this
requirement of the QAPP by
citing and describing the
method used and by providing
as many of the data quality
indicators as possible (e.g.,
completeness,
representativeness, and
comparability) in narrative
form.
Precision is the degree of
agreement among repeated
measurements of the same
characteristic, or parameter, and gives information about the consistency of your
methods.
Accuracy is a measure of confidence that describes how close a measurement is
to its "true" value.
3 to 10.5 units
* MR = measurement range
Representativeness
In the Volunteer Creek project's assessment, representativeness
depends largely on randomized sampling. The creek is a high-
gradient stream with a predominance of riffle habitats. Monitoring
sites selected for this study are indicative of that habitat type and the
program uses sampling techniques developed for high-gradient
streams. In addition, for the macroinvertebrate collection, volunteers
sample at three locations within the riffle and then composite
(combine) the samples so as to be more generally reflective of the
entire riffle habitat.
Comparability
One of the ways that the Volunteer Creek program ensures
comparability is to follow the monitoring protocol established by the
State for assessment and analysis. Volunteers also use standardized
taxonomic keys to identify macroinvertebrates to the family level.
Completeness
There are no legal or compliance uses anticipated for the Volunteer
Creek data. In addition, there is no fraction of the planned data that
must be collected in order to fulfill a statistical criteria. It is expected
that samples will be collected from at least 90% of the sites unless
unanticipated weather conditions prevent sampling.
Chapter 4: Elements of a QAPP
21
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Measurement Range is the range of
reliable readings of an instrument or
measuring device, as specified by the
manufacturer.
Representativeness is the extent to which
measurements actually represent the true
environmental condition.
Comparability is the degree to which data
can be compared directly to similar
studies. Using standardized sampling,
analytical methods, and units of reporting
helps to ensure comparability.
Completeness is the comparison between
the amount of data you planned to collect
versus how much usable data you
collected, expressed as a percentage.
TRAINING REQUIREMENTS/ CERTIFICATION
Identify any specialized training or certification requirements your
volunteers will need to successfully
complete their tasks. Discuss how
you will provide such training, who
will be conducting the training, and
how you will evaluate volunteer
performance.
ELEMENT 8
Training Requirements/
Certification
Volunteer Creek monitors participate in a two-day field
training course conducted by state and local water quality
personnel. On the first day, volunteers are instructed
how to calibrate equipment and perform physical and
chemical tests and analyses. The second day is devoted to
macroinvertebrate and habitat sampling. Volunteers for
the taxonomy lab receive a separate day of training. All
participants are required to attend an annual refresher
course as well.
Performance is evaluated in the field and the lab. During
initial and renewal training sessions, volunteers perform
a simultaneous dip-in determination of pH, temperature,
and dissolved oxygen. Volunteers also determine
turbidity levels of water samples using meters at the lab.
In addition, during training, participants conduct
macroinvertebrate sampling in small groups with
trainers. To evaluate volunteer skill in the taxonomy lab,
volunteers are trained and re-trained using previously
identified samples from earlier assessments.
Volunteer Creek
Monitoring Project
Training Session
9:00 am
TODAY
28
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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DOCUMENTATION AND RECORDS
Identify the field and laboratory information and records you need for
this project. These records may include raw data, QC checks, field data
sheets, laboratory forms, and voucher collections. Include information on how
long, and where, records will be maintained. Copies of all forms to be used in the
project should be attached to the QAPP.
ELEMENT 9
Documentation and Records
Each Volunteer Creek field sampling sheet must be completed on-site at the time sampling occurs. Volunteers
record site number, location, the date and time the sample was collected, and the name of each team member.
Contact information for the team captain or monitor responsible for returning field sheets and
macroinvertebrate samples to the watershed association office is also included on each field sheet.
Volunteers make a copy of each field sheet and keep the copy with their records. The original is returned to the
Volunteer Creek Watershed Association office along with the macroinvertebrate sample (if taken). Field sheets
are archived for three years. After macroinvertebrate samples have been identified, laboratory record sheets are
maintained in the watershed association office for three years. Hard copies of all data as well as computer
back-up disks are
maintained by the
Association. A
macroinvertebrate
voucher collection is
maintained by the
state university
biology lab for five
years.
Site #:
Date: _
VOLUNTEER CREEK MONITORING PROJECT
Site Location:
Time: AM PM
Team Captain:
Address:
Phone #:
Other Monitoring Team Members:
Chapter 4: Elements of a QAPP
29
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SAMPLING PROCESS DESIGN
Outline the experimental design of the project including
information on types of samples required, sampling frequency,
sampling period (e.g., season), and how you will select sample sites and identify
them over time. Indicate whether any constraints such as weather, seasonal
variations, stream flow or site access might affect scheduled activities, and how
you will handle those constraints. Include site safety plans. You may cite the
sections of your program's SOPs which detail the sampling design of the project,
in place of extensive discussion.
ELEMENT 1 O
Sampling Process Design
Volunteer Creek monitoring sites are sampled monthly for pH, temperature, turbidity, and dissolved oxygen. In
March, July and October, a macroinvertebrate and habitat assessment is conducted at each site. Monitoring sites are
identified by a number and a location.
If possible, volunteers are asked to wait at least 10 days after a heavy rain or snowfall before sampling. If this is not
possible, they are instructed to contact the Field Leader so that this information can be noted immediately. In
addition, if volunteers cannot conduct the scheduled sampling, they are instructed to contact the Field Leader as
soon as possible, so that an alternative monitor can be found. Volunteers are instructed to work in teams of at least
two people. Three team members are recommended for the macroinvertebrate sampling. If a scheduled team
cannot conduct the sampling together, the team captain
is instructed to contact the Field Leader so that
arrangements can be made for a substitute.
Prior to final site selection, permission to access
the stream is obtained from all property owners.
If for some reason access to the site is a problem,
the team captain is instructed to contact the Field
Leader. All constraints and safety plans are
detailed in the Volunteer Creek SOPs.
Four, or 20%, of the sampling sites surround
Volunteer Creek Boulevard, which is being
widened to accommodate growing residential and
commercial development. They are located as
follows:
Site #1 adjacent to the new townhome
development in the Happy Lakes
Community
Site #2 downstream of the confluence with Urban
Creek
Site #3 at the crossing of Volunteer Creek
Boulevard
Site #4 within Volunteer Park, adjacent to the
picnic area
30
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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SAMPLING METHODS REQUIREMENTS
Describe your sampling methods. Include information on
parameters to be sampled, how samples will be taken, equipment
and containers used, sample preservation methods
used, and holding times (time between taking
samples and analyzing them). If samples are
composited (i.e., mixed), describe how this will
be done. Describe
procedures for
decontamination
and equipment-
cleaning. (For
example, kick nets
need to be
thoroughly rinsed
and examined for clinging organisms between
sampling events.) Most of this information can be
presented in a table or you may also cite any SOPs
that contain this information.
Ner\
y^ ELEMENT 1 1
U*~e^v Sampling Methods Requirements
The Volunteer Creek SOP, attached to this document, contains detailed information on all sampling protocols
and equipment. The table below summarizes a portion of this information.
Matrix Parameter Sampling Sample Holding Method Maximum
Equipment Container Sample Holding Time
Preservative
water pH Jones pH color screw top, glass none
comparator kits sample bottle
water temperature Smith armored none, measurement none
thermometer taken instream
water dissolved oxygen Jones DO kit screw top, glass none
sample bottle
water turbidity Jones turbidity meter screw top glass store on ice
sample bottle
substrate macroinvertebrates 3' X 3' kicknet; 500 1 liter plastic 90% ethyl
micron mesh wide-mouth bottle alcohol
immediately
immediately
immediately
48 hours
6 weeks
Chapter 4: Elements of a QAPP
31
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SAMPLE HANDLING AND CUSTODY
REQUIREMENTS
Sample handling procedures apply to projects that bring samples from the field to
the lab for analysis, identification, or storage.
These samples should be properly
labeled in the field. At a
minimum, the sample identification
label should include sample
location, sample number, date and
time of collection, sample type,
sampler's name, and method used
to preserve sample.
Describe the procedures used to x" —_. - '
keep track of samples that will be
delivered or shipped to a laboratory for analysis. Include any chain-of-custody
forms and written procedures field crews and lab personnel should follow when
collecting, transferring, storing, analyzing, and disposing of samples.
ELEMENT 12
Sample Handling and Custody Requirements
All macroinvertebrate samples collected as part of the
Volunteer Creek project are labeled in the field. The
chain-of-custody for these samples is as follows: In
the field, samples are the responsibility of, and stay
with, the team captain. Once samples have been
collected they are returned, by the monitoring team
captain, to the Volunteer Creek Watershed
Association office for temporary storage. The date
and time of arrival is recorded by the Field Leader
who is then responsible for transporting samples to
the university laboratory for analysis. The date and
time of arrival is also recorded at the lab by the
Laboratory Leader. After samples are analyzed,
laboratory information is added to the label. Samples
are then stored and maintained in the university's
biological lab for a minimum of three years. A chain-
of-custody form is used to record all transport and
storage information
VOLUNTEER CREEK PROJECT
MACROINVERTEBRATE SAMPLE LABEL
FIELD INFORMATION:
Site #: Location:
Sample Number of
Preservation Method:
Date: / / Time:
Team Captain:
Phone #:
Gear:
AM PM
LAB INFORMATION:
Date: / / Time:
Analyst:
Phone #:
AM PM
32
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ANALYTICAL METHODS REQUIREMENTS
List the analytical methods and equipment needed for the analysis
of each parameter, either in the field or the lab. If your program
uses standard methods, cite
these. If your program's
methods differ from the
standard or are not readily
available in a standard
reference, describe the
analytical methods or cite
and attach the program's
SOPs.
QUALITY CONTROL REQUIREMENTS
List the number and
types of field and
laboratory quality control samples
your volunteers will take. (See
Chapter 3 for a discussion of quality
control samples.) This information
can be presented in a table. If you use
an outside laboratory, cite or attach
the lab's QA/QC plan.
QC checks for biological monitoring
programs can be described
narratively, and, if appropriate, should
include discussion of replicate sample
collection, cross checks by different
field crews, periodic sorting checks of
lab samples, and maintenance of
voucher and reference collections.
Describe what actions you will take if
the QC samples reveal a sampling or
analytical problem.
Chapter 4: Elements of a QAPP
33
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INSTRUMENT/
EQUIPMENT
INSPECTION ,
TESTING ,
AND MAINTENANCE
REQUIREMENTS
Describe your plan for routine inspection
and preventive maintenance of field and
lab equipment and facilities. Identify what
equipment will be routinely inspected, and
what spare parts and replacement equipment will be on hand to keep field and lab
operations running smoothly. Include an equipment maintenance schedule, if
appropriate.
INSTRUMENT CALIBRATION AND
FREQUENCY
Identify how you will
calibrate sampling and
analytical instruments.
Include information on
how frequently
instruments will be
calibrated, and the types
of standards or certified
equipment that will be
used to calibrate
sampling instruments.
Indicate how you will
maintain calibration
ELEMENT 1 6
Instrument Calibration
and Frequency
The Volunteer Creek project's turbidity meters will be
calibrated, prior to each sampling event, according to
the manufacturer's instructions and using the
manufacturer's turbidity standards. Calibration results
are recorded in a log book and maintained by the Lab
Manager. Calibration procedures and standards are
contained in the SOP manual, available upon request.
34
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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records and ensure that records can be traced to each instrument. Instrument
calibration procedures for biological monitoring programs should include routine
procedures that ensure that equipment is clean and in working order.
INSPECTION
AND
ACCEPTANCE
REQUIREMENTS FOR
SUPPLIES
Describe how you determine if
supplies such as sample bottles, nets,
and reagants are adequate for your
program's needs.
DATA ACQUISITION REQUIREMENTS
Identify any types of
data your project uses
that are not obtained through your
monitoring activities. Examples of
these types of data include historical
information, information from
topographical maps or aerial photos,
or reports from other monitoring
groups. Discuss any limits on the use
of this data resulting from uncertainty
about its quality.
ELEMENT 1 8
Data Acquisition Requirements
For the Volunteer Creek macroinvertebrate assessment
analysis, pollution tolerance values assigned to
organisms and metric calculation formulas are taken
from the literature and documentation provided by the
state water quality agency. U.S.G.S. 7.5 minute
topographic maps are used to identify site locations,
land-use activities, and landscape features during an
initial watershed survey.
Chapter 4: Elements of a QAPP
35
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DATA
MANAGEMENT
Trace the path your data take, from field
collection and lab analysis to data storage
and use. Discuss how you check for
accuracy and completeness of field and
lab forms, and how you minimize and
correct errors in calculations, data entry to
forms and databases, and report writing.
Provide examples of forms and checklists.
Identify the computer hardware and
software you use to manage your data.
|2O
ASSESSMENTS AND
RESPONSE ACTIONS
Discuss how you evaluate field, lab, and data management
activities, organizations (such as contract labs) and individuals in
the course of your project. These can include evaluations of
volunteer performance (for example, through field visits by staffer
in laboratory refresher sessions); audits of systems such as
equipment and analytical procedures; and audits of data quality
(e.g., comparing actual data results with project quality objectives).
Include information on how your project will correct any problems
identified through these assessments. Corrective actions might
include calibrating equipment more frequently, increasing the
36
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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number of regularly scheduled training sessions, or rescheduling field or lab
activities.
(Ml
Identify the frequency, content, and distribution of reports to data
users, sponsors, and
partnership organizations that detail
project status, results of internal
assessments and audits, and how QA
problems have been resolved.
Chapter 4: Elements of a QAPP
37
-------
DATA REVIEW, VALIDATION AND
VERIFICATION REQUIREMENTS
State how you review data and make decisions regarding accepting, rejecting, or
qualifying the data. All that is needed here is a brief statement of what will be
done, by whom.
VALIDATION AND VERIFICATION
METHODS
Describe the procedures you use to validate and verify data. This can include, for
example, comparing computer entries to field data sheets; looking for data gaps;
analyzing quality control data such as chain of custody information, spikes, and
equipment calibrations; checking calculations; examining raw data for outliers or
nonsensical readings; and
reviewing graphs, tables
and charts. Include a
description of how errors,
if detected, will be
corrected, and how
results will be conveyed
to data users.
38
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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124
RECONCILIATION WITH
OBJECTIVES
DATA QUALITY
Once the data results are compiled, describe the process for determining whether
the data meet project objectives. This should include calculating and comparing
the project's actual data quality indicators (precision, accuracy, completeness,
representativeness, and comparability) to those you specified at the start of the
project, and describing what will be done if they are not the same. Actions might
include discarding data, setting limits on the use of the data, or revising the
project's data quality objectives.
Chapter 4: Elements of a QAPP
39
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40 The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Accuracy. A data quality indicator, accuracy is the extent of agreement between
an observed value (sampling result) and the accepted, or true, value of the
parameter being measured. High accuracy can be defined as a combination
of high precision and low bias.
Analyte. Within a medium, such as water, an analyte is a property or substance to
be measured. Examples of analytes would include pH, dissolved oxygen,
bacteria, and heavy metals.
Bias. Often used as a data quality indicator, bias is the degree of systematic error
present in the assessment or analysis process. When bias is present, the
sampling result value will differ from the accepted, or
true, value of the parameter being assessed. Data QuaUty Objectives
(DQOs) specify the quality
of the data needed in
order to meet the
monitoring project's
goals.
Blind sample. A type of sample used for quality control
purposes, a blind sample is a sample submitted to an
analyst without their knowledge of its identity or
composition. Blind samples are used to test the
analyst's or laboratory's expertise in performing the
sample analysis.
Comparability. A data quality indicator, comparability is the
degree to which different methods, data sets, and/or
decisions agree or are similar.
Completeness. A data quality indicator that is generally expressed as a
percentage, completeness is the amount of valid data obtained compared to
the amount of data planned.
Data users. The group(s) that will be applying the data results for some purpose.
Data users can include the monitors themselves as well as government
agencies, schools, universities, businesses, watershed organizations, and
community groups.
Data quality objectives (DQOs). Data quality objectives are quantitative and
qualitative statements describing the degree of the data's acceptability or
utility to the data user(s). They include indicators such as accuracy,
precision, representativeness, comparability, and completeness. DQOs
specify the quality of the data needed in order to meet the monitoring
Appendix A: Glossary
41
-------
project's goals. The planning process for ensuring environmental data are of
the type, quality, and quantity needed for decision making is called the DQO
process.
Detection limit. Applied to both methods and equipment, detection limits are the
lowest concentration of a target analyte that a given method or piece of
equipment can reliably ascertain and report as greater than zero.
Duplicate sample. Used for quality control purposes, duplicate samples are two
samples taken at the same time from, and representative of, the same site
that are carried through all assessment and analytical procedures in an
identical manner. Duplicate samples are used to measure natural variability
as well as the precision of a method, monitor, and/or analyst. More than two
duplicate samples are referred to as replicate samples.
Environmental sample. An environmental sample is a specimen of any material
collected from an environmental source, such as water or macroinvertebrates
collected from a stream, lake, or estuary.
Equipment or rinsate blank. Used for quality control purposes, equipment or
rinsate blanks are types of field blanks used to check specifically for
carryover contamination from reuse of the same sampling equipment (see
field blank}.
Field blank. Used for quality control purposes, a field blank is a "clean" sample
(e.g., distilled water) that is otherwise treated the same as other samples
taken from the field. Field blanks are submitted to the analyst along with
all other samples and are used to detect any contaminants that may be
introduced during sample collection, storage, analysis, and transport.
Instrument detection limit. The instrument detection limit is the lowest
concentration of a given substance or analyte that can be reliably detected by
analytical equipment or instruments (see detection limit}.
Matrix. A matrix is a specific type of medium, such as surface water or sediment,
in which the analyte of interest may be contained.
Measurement Range. The measurement range is the extent of reliable readings
of an instrument or measuring device, as specified by the manufacturer.
Method detection limit (MDL). The MDL is the lowest concentration of a given
substance or analyte that can be reliably detected by an analytical procedure
(see detection limit}.
42 The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Quality Assurance (QA) is
an integrated
management system
designed to ensure that a
product or service meets
defined standards of
quality with a stated level
of confidence.
Performance evaluation (PE) samples. Used for quality
control purposes, a PE sample is a type of blind
sample. The composition of PE samples is unknown to
the analyst. PE samples are provided to evaluate the
ability of the analyst or laboratory to produce analytical
results within specified limits.
Precision. A data quality indicator, precision measures the
level of agreement or variability among a set of
repeated measurements, obtained under similar
conditions. Precision is usually expressed as a
standard deviation in absolute or relative terms.
Protocols. Protocols are detailed, written, standardized
procedures for field and/or laboratory operations.
Quality assurance (QA). QA is an integrated management
system designed to ensure that a product or service meets defined standards
of quality with a stated level of confidence. QA activities involve planning
quality control, quality assessment, reporting, and quality improvement.
Quality assurance project plan (QAPP). A QAPP is a formal written document
describing the detailed quality control procedures that will be used to
achieve a specific project's data quality requirements.
Quality control (QC). QC is the overall system of technical activities designed to
measure quality and limit error in a product or service. A QC program
manages quality so that data meets the needs of the user as expressed in a
quality assurance project plan.
Relative standard deviation (RSD). RSD is the standard deviation of a parameter
expressed as a percentage and is used in the evaluation of precision.
Relative percent difference (RPD). RPD is an alternative to standard deviation,
expressed as a percentage and used to determine precision when only two
measurement values are available.
Replicate samples. See duplicate samples.
Representativeness. A data quality indicator, representativeness is the degree to
which data accurately and precisely portray the actual or true environmental
condition measured.
Sensitivity. Related to detection limits, sensitivity refers to the capability of a
method or instrument to discriminate between measurement responses
Appendix A: Glossary
43
-------
Standard Reference
Materials (SRMs) are
produced by the V. S.
National Institute of
Standards and
Technology (NIST) and
characterized for absolute
content independent of
any analytical method.
representing different levels of a variable of interest.
The more sensitive a method is, the better able it is to
detect lower concentrations of a variable.
Spiked samples. Used for quality control purposes, a spiked
sample is a sample to which a known concentration of
the target analyte has been added. When analyzed, the
difference between an environmental sample and the
analyte's concentration in a spiked sample should be
equivalent to the amount added to the spiked sample.
Split sample. Used for quality control purposes, a split
sample is one that has been equally divided into two or
more subsamples. Splits are submitted to different
analysts or laboratories and are used to measure the
precision of the analytical methods.
Standard reference materials (SRM). An SRM is a certified material or
substance with an established, known and accepted value for the analyte or
property of interest. Employed in the determination of bias, SRMs are used
as a gauge to correctly calibrate instruments or assess measurement methods.
SRMs are produced by the U. S. National Institute of Standards and
Technology (NIST) and characterized for absolute content independent of
any analytical method.
Standard deviation(s). Used in the determination of precision, standard deviation
is the most common calculation used to measure the range of variation
among repeated measurements. The standard deviation of a set of
measurements is expressed by the positive square root of the variance of the
measurements.
Standard operating procedures (SOPs). An SOP is a written document detailing
the prescribed and established methods used for performing project
operations, analyses, or actions.
True value. In the determination of accuracy, observed measurement values are
often compared to true, or standard, values. A true value is one that has
been sufficiently well established to be used for the calibration of
instruments, evaluation of assessment methods or the assignment of values
to materials.
Variance. A statistical term used in the calculation of standard deviation,
variance is the sum of the squares of the difference between the individual
values of a set and the arithmetic mean of the set, divided by one less than
the numbers in the set.
44
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Appendix B:
EPA REGIONAL CONTACTS
Each of EPA's 10 Regional offices has a volunteer monitoring coordinator
and quality assurance officers who can be of assistance to volunteer
programs. Listed below are the contact names for each region, as of
September 1, 1996. These contacts may change over time.
EPA Regional
Volunteer Monitoring
Coordinators
Diane Switzer
USEPA Region 1
(EMS-LEX)
60 Westview Street
Lexington, MA 02173
617-860-4377
Diane Calesso
USEPA Region II
Environmental Services Division
2890 Woodbridge Avenue
Raritan Depot Bldg. 10
Edison, NJ 08837-3679
908-906-6999
calesso.diane@epamail.epa.gov
Pete Weber
David Melgaard
USEPA Region IV
Watershed Section
345 Courtland Street
Atlanta, GA 30365
404-347-2126 (x6590)
Tom Davenport
USEPA Region V
77 W. Jackson Blvd.
Chicago, IL 60604
312-886-7804
Mike Bira
USEPA Region VI (6WQS)
1445 Ross Avenue
12th Floor, Suite 120
Dallas, TX 75202-2733
214-665-6668
USEPA Region ill
3WP13
841 Chestnut Bldg.
Philadelphia, PA 19107
215-566-5749
Chuck Kanetsky
USEPA Region III
841 Chestnut Bldg.
Philadelphia, PA 19107
215-566-2735
Which
Region 1:
Region 2:
Region 3 :
Region 4:
Region 5:
Region 6:
Region 7:
Region 8:
Region 9:
Region 10:
EPA region are you
CT, MA, ME, VT, NH, RI
NY, NJ, VI, PR
DE, DC, MD, PA, VA, WV
in?
AL, FL, GA, KY, MS, NC, SC, TN,
IL, IN, MI, MN, OH, WI
AR, LA, NM, OK, TX
IA, KS, MO, NE
CO, MT, ND, SD, UT, WY
AZ, CA, NV, GU, HI, AS
AK, ID, OR, WA
Appendix B: EPA Regional Contacts
45
-------
Jerry Pitt
USEPA Region VII
726 Minnesota Avenue
Kansas City, KS
913-551-7766
Paul Mclver
USEPA Region VIII
999 18th Street, Suite 500
Denver, CO 80202-2405
303-312-6056
Phil Johnson
USEPA Region VIII
999 18th Street, Suite 500
Denver, CO 80202-2405
303-312-6084
Ed Liu
USEPA Region IX
75 Hawthorne Street
San Francisco, CA 94105
415.744.1934
Andrea Lindsay
USEPA Region X
1200 Sixth Avenue
Seattle, WA 98101
206-553-1287
Drew Puffer
Gulf of Mexico Program
Building 1103
Stennis Space Ctr, MS 39529-620
601-688-3913
Alice Mayio, National Volunteer
Monitoring Coordinator
USEPA (4503F)
401 M Street, SW
Washington, DC 20460
202-260-7018
Regional Quality
Assurance Officers
Nancy Barmakian
USEPA Region I
New England Regional Lab
60 Westview Street
Lexington, MA 02173-3185
617-860-4684
Robert Runyon
USEPA Region II
2890 Woodbridge Avenue
Edison, NJ 08837
908-321-6645
Charles Jones, Jr.
USEPA (3ESOO) Region III
841 Chestnut Street, 8th Floor
Philadelphia, PA 19107
215-566-7210
Diann Sims
USEPA (3ES30) Region III
Central Regional Lab
201 Defense Highway, Suite 200
Annapolis, MD 21401
Claudia Walters
USEPA Region III
Chesapeake Bay Program Office
410 Severn Avenue, Suite 109
Annapolis, MD 21403
Gary Bennett
USEPA/Region IV
960 College Station Road
Athens, GA 30605-2720
706-546-3287
Willie Harris
MQAB/ESD/EPA (5SMQA)
Region V
77 West Jackson
Chicago, IL 60604
46
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Lisa Feldman
USEPA/ESD Region VI
10625 Fallstone
Houston, TX 77099
Alva Smith
USEPA (6EQ) Region VI
1445 Ross Avenue
Suite 1200
Dallas, TX 75202-2733
Ernest L. Arnold
USEPA/EST Region VII
25 Funston Road
Kansas City, KS 66115
913-551-5194
Rick Edmonds (SES-AS)
USEPA/ESD Region VIII
Suite 500
999 18th Street
Denver, CO 80202-3405
303-293-0993
Vance Fong
USEPA Region IX (MD P-3-2)
75 Hawthorn Street
San Francisco, CA 94105
415-744-1492
Barry Towns
USEPA (OEA-095) Region X
1200 Sixth Avenue
Seattle, WA 98101
206-553-1675
Appendix B: EPA Regional Contacts 47
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48 The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Directory of Volunteer Environmental Monitoring Programs, 4th Edition. EPA
841-B-94-001, January 1994. U.S. Environmental Protection Agency,
Office of Water, Washington, DC.
EPA Requirements for Quality Assurance Project Plans (QAPP)for
Environmental Data Operations.
EPA/QA/R-5. August 1994. U.S.
Environmental Protection Agency,
Office of Water, Washington, DC.
Generic Quality Assurance Project Plan
Guidance for Programs Using
Community Level Biological
Assessment in Wadable Streams and
Rivers. EPA 841-B-95-004, July 1995.
U.S. Environmental Protection Agency,
Office of Water, Washington, DC.
Guidance for Data Quality Assessment.
EPA QA/G-9, March 1995. U.S.
Environmental Protection Agency,
Office of Research and Development,
Washington, DC.
Guidance for the Preparation of Standard
Operating Procedures (SOPs) for
Quality-Related Documents. EPA
QA/G-6. November 1995. U.S.
Environmental Protection Agency,
Quality Assurance Division.
Integrating Quality Assurance into Tribal
Water Programs: A Resource Guide
for Reliable Water Quality Data
Collection. U.S. Environmental
Protection Agency Region 8, Denver,
Colorado.
The following presentation paper topics, specifically
relavant to quality assurance and quality control issues,
are contained in the proceedings documents from past
national volunteer monitoring conferences:
Proceedings of Third National Citizens' Volunteer
Water Monitoring Conference.
Goal Setting and Organizing
Study Design
Training Monitors
Integrated Monitoring Systems
Enforcement and Compliance Monitoring
Procedures for Collecting Quality Data
Meeting Scientific Standards for Biological
Monitoring
Deciding Data Objectives
River and Stream Monitoring Techniques
Lake Monitoring Techniques
Wetland Monitoring Techniques
Estuary Monitoring Techniques
Computer Data Management
Data Application and Presentation
Proceedings Fourth National Citizens' Volunteer
Monitoring Conference.
• Designing Your Water Quality Study
* Assuring Quality Data
* Defining Data Use
* Using Your Data to Evaluate Your Volunteer
Monitoring Program
• Geographic Information Systems and Volunteer
Monitoring Data
• Managing Your Data: Some Basic Principles
* Data Analysis for the Technically Impaired
* Macroinvertebrate Monitoring
* Bacteria Testing
* Monitoring Restoration and Pollution Prevention
Activities
Both of these documents are available upon request from
the EPA National Volunteer Monitoring Coordinator.
Appendix C: References
49
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Proceedings of the Fourth National Citizen's Volunteer Water Monitoring
Conference. EPA 841/R-94-003, February 1995. U.S. Environmental
Protection Agency, Office of Water, Washington, DC.
Proceedings of the Third National Citizen's Volunteer Water Monitoring
Conference. EPA 841/R-92-004, September 1992. U.S. Environmental
Protection Agency, Office of Water, Washington, DC.
Volunteer Estuary Monitoring: A Methods Manual EPA 842-B-93-004,
December 1993. U.S. Environmental Protection Agency, Office of Water,
Washington, DC.
Volunteer Lake Monitoring: A Methods Manual EPA 440/4-91 -002,
December 1991. U.S. Environmental Protection Agency, Office of Water,
Washington, DC.
The Volunteer Monitor: Building Credibility. Volume 4, number 2, Fall 1992.
Eleanor Ely, ed. San Francisco, CA.
The Volunteer Monitor: Managing and Presenting Your Data. Volume 7,
number 1, Spring 1995. Eleanor Ely, ed. San Francisco, CA.
Volunteer Stream Monitoring: A Methods Manual (Field Test Draft). EPA 841
D 95-001. April 1995. U.S. Environmental Protection Agency, Office of
Water, Washington, DC.
Volunteer Water Monitoring: A Guide for State Managers. EPA 440/4-90-010,
August 1990. U.S. Environmental Protection Agency, Office of Water,
Washington, DC.
50 The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Appendix D:
ABBREVIATED QAPP FORM
What follows is an example of an optional abbreviated quality assurance project plan
form. You may be able to use it as a model for your project's QAPP. However, be
sure to consult your state or EPA regional QA officers to determine if use of this form
(or a modified version) is acceptable to them, and for specific information on required elements
for your project.
1. Title and Approval Page
(Project Name)
(Responsible Agency)
(Date)
Project Manager Signature
Name/Date
Project QA Officer Signature
Name/Date
USEPA Project Manager Signature
Name/Date
USEPA QA Officer Signature
Name/Date
2. Table of Contents
List sections with page numbers, figures, tables, references, and appendices (attach pages).
Appendix D: Abbreviated QAPP Form
51
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3. Distribution List
Names and telephone numbers of those receiving copies of this QAPP. Attach additional page,
if necessary.
i.
ii.
iii.
iv.
v.
vi.
vii.
viii.
ix.
x.
4. Project/Task Organization
List key project personnel and their corresponding responsibilities.
Name
Project Title/Responsibility
Advisory Panel (contact)
Project Manager
QA Officer
Field/Sampling Leader
Laboratory Manager/Leader
5. Problem Definition/Background
A. Problem Statement
52
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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B. Intended Usage of Data
Project/Task Description
A. General Overview of Project
B. Project Timetable
Activity
Projected Start Date
Anticipated Date of
Completion
Appendix D: Abbreviated QAPP Form
53
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Measurement Quality Objectives
A. Data Precision, Accuracy, Measurement Range
Matrix
Parameter
Measurement
Range
Accuracy
Precision
B. Data Representativeness
C. Data Comparability
D. Data Completeness
Parameter
No. Valid Samples
Anticipated
No. Valid Samples
Collected &
Analyzed
Percent Complete
54
The Volunteer Monitor's Guide to Quality Assurance Project Plans
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Training Requirements and Certification
A. Training Logistical Arrangements
Type of Volunteer Training
Frequency of Training/Certification
B. Description of Training and Trainer Qualifications
Documentation and Records
1 O. Sampling Process Design
A. Rationale for Selection of Sampling Sites
Appendix D: Abbreviated QAPP Form
55
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B. Sample Design Logistics
Biological
Physical
Chemical
Type of
Sample/
Parameter
Number of
Samples
Sampling
Frequency
Sampling
Period
1 1. Sampling Method Requirements
Parameter
Sampling Equipment
Sampling Method
1 2. Sample Handling and Custody Procedures
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The Volunteer Monitor's Guide to Quality Assurance Project Plans
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1 3. Analytical Methods Requirements
1 4. Quality Control Requirements
A. Field QC Checks
B. Laboratory QC Checks
C. Data Analysis QC Checks
15. Instrument/Equipment Testing, Inspection, and
Maintenance Requirements
Equipment Type
Inspection Frequency
Type of Inspection
Appendix D: Abbreviated QAPP Form
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1 6. Instrument Calibration and Frequency
Equipment Type
Calibration Frequency
Standard or Calibration
Instrument Used
1 7. Inspection/Acceptance Requirements
1 8. Data Acquisition Requirements
1 9. Data Management
2O. Assessment and Response Actions
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The Volunteer Monitor's Guide to Quality Assurance Project Plans
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21. Reports
22. Data Review, Validation, and Verification
23. Validation and Verification Methods
24. Reconciliation with DQO's
Appendix D: Abbreviated QAPP Form 59
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