Midterm part II

Midterm part II - 
 
 Midterm
Part
II.
 


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 Midterm
Part
II.
 
 See
attached
your
and
all
your
colleagues
crib
sheets.
Please
review
each
one
and
 grade
them
according
to:
 
 ‐
Clarity
 ‐
Conciseness
 ‐
Completeness
 ‐
Style
 
 
 For
each
of
these
please
decide
on
a
weight
(out
of)
as
you
consider
appropriate.
 
 E.g.:
you
may
decide
to
give
equal
weight
to
each
element
and
grad
each
out
of
100;
 Or
you
may
weigh
them
differently
for
a
maximum
sum
of
100
 
 For
your
convenience
I
also
attached
the
grading
sheet
in
doc
format.
 
 Due
On
Nov
5th.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Student
 1
 2
 3
 4
 5
 6
 7
 8
 9
 10
 11
 12
 13
 
 Clarity
 Out
of
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Conciseness
 Out
of
 
 Completeness
 Out
of
 
 Style
 Out
of
 
 Total
 Out
of
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Specific
comments
in
support
of
your
grading:
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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STUDENT
1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Cribs Sheet Lecture 1 Objectives for Environmental Sampling and Analysis include Determining how much pollutant/pollution enters the environment from a source. To identify short/long term trends in terms of ambient background concentration and assess degree of pollution. To detect accidental releases and evaluate the risk from toxicity to humans/biota To study the fate and transport of contaminants and evaluate efficiency of remediation techniques. Risk Assessment: 1) Contaminant identification 2) Assessment of the probability of contamination 3) Assessment of potential consequences. -Must be scientifically reliable and able to be presented in court. QC=A system of technical Activities aimed at controlling the quality of the data so that it meets the needs of data users. QA= a management system that assures that QC is working as intended. Scope of sampling includes: How much, when, where, how, How many, how often, how to preserve samples, how long to store samples, what to sample, what to analyze, who samples. Lecture 2 Concentration Units: ppm=mg/L= 10^-6, ppb= micrograms/L = 10^-9, ppt=ng/L= 10^12 (mg/m^3 = ppm*MW/22.4) <=Valid for standard conditions=>(ppm= mg/m^3*24.5/MW) ppm = Vm/MW*gas(ug)/airl(L) (Volume/Density) (1ppm/1mg/m^3)(10^3ppb/1ppm) Lecture 3 = population variance s = estimate of population standard deviation based on sampled data s2 = estimate of population variance based on sampled data The population variance is defined as: = Sample Mean: In order to standardize a concentration of sorts: [z=(x-u)/ σ] S/√N (SEM) Outliers= observations that appear to be inconsistent with the remainder of the collected data Z score= (x- )/s Lecture 4 Sampling: Understanding sampling and analysis plan, preparing equipment and supplies, identifying sampling points, collecting field and QA/QC samples, completing field documentation, packaging samples, shipping samples to laboratory. Heterogeneity: species, age, size, sex, mobility, mortality and growth, tissue variations… When and where? Professional opinion based on prior knowledge Wk => weight of the stratum r => number of strata S^2k => Variance within each stratum Each stratum (k) is assigned the same number of samples (nk) in equal allocation Hence nk= n/r Lecture 5 NIOSH (National Institute for Occupational Safety and Health) OSHA (Occupational Health and Safety Administration) ASTM (American Society for Testing and Materials) 11.01-11.02 water assessment standard procedures Volume 11.03 involves air standards Volume 11.04 involves Environmental assessment (Phase I and II) AOAC (Association of Analytical communities Lecture 6 Brownfield Site: a parcel of land that contains or once contained abandoned or underutilized commercial or industrial facilities, the expansion or redevelopment of which may be complicated by the presence of potential hazardous substances, pollutants, or contaminants. CERCLA: Comprehensive Environmental Response Compensation and Liability Act ESA Phase I requirements: Environmental Setting, Historic Records Review, Review of the hazardous bulding material, site and area reconnaissance, A regulatory Agency Review, Interviews Lecture 8 Identify Decision Types => Identify Data Uses /needs => Design Data Collection Program Support - sampling unit – Soil as heterogeneous system – Non-discrete distribution of contaminant – Variability issues Action Level? – defined as concentration over a particular support and location versus the ground surface = action support • T y p e I e r r o r = r e je c t H 0 w h e n H 0 is t r u e ( p r o b a b ilit y = 〈 ) • T y p e II e r r o r = a c c e p t H 0 w h e n H 0 is fa ls e ( p r o b a b ility = ) H y p o t h e s is s e t t in g : H 0 = # H y p o t h e s is s e t t in g : D ir e c t io n a l h y p o t h e s is (i.e . H a < # o r H a > # ) - o n e -t a ile d t e s t N o n -d ir e c t io n a l h y p o t h e s is (i.e . H a ≠ # ) - t w o -t a ile d t e s t H is to r ic a l in fo o f a H g c o n ta m in a te d a r e a s u g g e s ts a r a n g e o f 2 - 2 0 µ g /k g a n d a s ta n d a r d d e v ia tio n o f 3 .2 5 µ g /k g E s tim a te th e n u m b e r o f s a m p le r e q u ir e d a s s u m in g th a t th e s a m p le m e a n w o u ld b e ± 1 .5 µ g /k g fr o m th e p o p u la tio n m e a n a t 9 5 % c o n fid e n c e le v e l. S o lu tio n : n = ? ; s = 3 .2 5 ; e = 1 .5 ; t = ? S te p 1 . E s tim a te a n n v a lu e o f 1 0 ; h e n c e td f = 9 , 0 . 0 5 = 2 .2 6 2 [(2 .2 6 2 x 3 .2 5 )/1 .5 ]2 = 2 4 .0 1 S te p 2 . U s e th e t v a lu e fo r n = 2 4 a t 9 5 % ; td f = 2 3 , 0 . 0 5 = 2 .0 6 9 [(2 .0 6 9 x 3 .2 5 )/1 .5 ]2 = 2 0 .1 S te p 3 . U s e th e t v a lu e fo r n = 2 0 a t 9 5 % td f = 2 0 , 0 . 0 5 = 2 .0 9 3 [(2 .0 9 3 x 3 .2 5 )/1 .5 ]2 = 2 0 .5 6 ≈ 2 1 A P C B c o n ta m in a te d s ite n e e d s to b e a n a ly z e d d u e to c o m p la in ts . H is to r ic a l m e a s u r e m e n ts ( 3 0 y r s a g o ) in d ic a te a m e a n o f ≈ 0 .7 0 m g /k g ( a v g o f 5 s a m p le s ) a n d a s ta n d a r d d e v ia tio n o f 0 .1 2 m g /k g . T h e R T fo r P C B is 0 .7 4 m g /k g . A t a n 8 0 % C I e s tim a te : a . th e n u m b e r o f s a m p le s r e q u ir e d b . th e n u m b e r o f s a m p le s r e q u ir e d if th e m e a n w a s 0 .5 8 m g /k g S o lu tio n : a . t d f= 4 , 0 .2 = 1 . 5 3 3 ; e = ( 0 . 7 4 - 0 . 7 0 ) ; s = 0 . 1 2 m g / k g [1 .5 3 3 x 0 .0 4 / ( 0 .7 4 - 0 .7 0 ) ]2 = 2 1 s a m p le s b . t d f= 4 , 0 .2 = 1 . 5 3 3 ; e = ( 0 . 7 4 - 0 . 5 8 ) ; s = 0 . 1 2 m g / k g [1 .5 3 3 x 0 .1 2 / ( 0 .7 4 - 0 .5 8 ) ]2 = 2 s a m p le s 
 
 
 
 
 
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STUDENT
2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Liquid
 (mass/ vol)
 CONVERSIONS
AND
CHEMISTRY
 Solid
 Gas
(mass/vol)
 (mass/
 mass)
 ‐6 ppm
 mg/kg
 ml/L
 10 ‐9
 ppb
 µg/kg
 µL/L
 10 ‐12
 ppt
 ng/kg
 nL/L
 
 Dry
wt
vs.
 wet
wt
 mg/m3 = ppm ⋅ MW /24.5 ppm = mg/m3 ⋅ 24.5 /MW
 
 10 
 
 Conversion
to
molarity
 
 Molecules

Present
 
 
 STATISTICS
 Accuracy
is
the
degree
of
 agreement
of
a
measured
value
 with
the
true
or
expected
value
 (%
Recovery):
 Precision
is
the
degree
of
mutual
agreement
among
individual
 measurementsas
a
result
of
repeated
testing
under
the
same
 conditions
 Standard
Dev
 (finite
set
of
data)
 
 2 Population
Variance
–
(ơ )variance
is
addative
 
 Relative
Stand.
Dev
 (eval
multiple
 replicate
data
points)
 Relative
%
Difference
 (measures
precision
 btw
2
duplicate
data
 measurements)
 RPD=

 [(A‐B)/(A+B)/2]*100
 
 
 
 
 
 2 2 Sample
Variance‐
(s )

sample
variances
target
the
true
value
of
ơ .
 The
square
of
the
standard
deviation
s.
 Normalized
data‐
guassian
like
 curve.

Mean
=
0,
SD
=
1.

 Normalization
converts
x
to
z
 
 f‐distributions
Compares
 dispersion
of
2
distributions
 ‐F<F
null
accepted
 ‐F>F
null
rejected
 Confidence
intervals‐the
degree
 of
freedom
(df)
is
n‐1,
and
1‐α/2
 is
one
sided
confidence
level.
 
 
 
 
 Standard
error
of
 mean
 
 z‐score‐
calculated
for
each
 data
pnt.
 ‐if
z>3
point
is
an
outlier
 
 Sampling
Plans
and
Concerns
 7
steps
of
a
sample’s
life
 PARCC
 7
Step
of
sampling
 1. Sample
planning
 
 ‐understanding
sampling
 2. Identification
of
pts
 Precision
 &
analysis
plan
 3. Sample
collection
 Accuracy
 ‐
preparing
equip
and
 Representativeness
 4. Sample
transfer

lab
 supplies
 Comparability
 5. Sample
analysis
 ‐identifying
sampling
 Completeness
 6. Sample
expire/trash
 points

 7. Sample
is
data
pnt.
 ‐collecting
field
and
 QA/QC
samples
 ‐completing
field
.doc
 ‐Packaging
samples
 ‐transport
samples
to
lab
 
 Project
Plans
and
Concerns
 
 Developing
a
Sampling
Protocol
 
 
 Judgemental
Sampling‐cost
saver,
no
randomization
=
no
statistical
interpretation,
 not
applicable
when
confidence
interval
needed
to
be
calculated
 Simple
Random
Sampling‐Pros‐
sampling
cost
vs.
effectiveness
is
a
benchmark,
 straightfoward
statistics.
Cons‐
difficult
to
achieve
representativeness,
only
good
for
 static
systems
(eg
soil)
 WK
=
weight
of
the
stratum
 
 R
=
number
of
strata
 
 2 S K
=
variance
within
each
stratum
 
 
 
 
 Composite
sampling‐
cost
saving
when
interested
in
the
mean,
useful
when
variability
 is
not
important,
can
be
combined
with
search
sampling
 Search
Sampling‐
Variation
of
systematic
grid
sampling,
hot
spot
detection,
#
of
 samples
dependent
on
the
allowable
risk
of
missing
hot
spot
 “.
..
the
user
must
first
specify
the
data
he/she
needs;
then
the
degree
of
quality
 control
necessary
to
assure
that
the
resultant
data
satisfy
his/her
specifications
must
 be
determined”
 Methodology
 
 EPA

Method
Series
 1000‐
ignitability,
corrosion,
toxicity
 3000‐
extractions
 4000‐screenings,
immunoassays
 5000‐VOCs
and
SVOCs
 6000‐
spectrometry
 7000‐
atomic
absorbtion
spectrmtry
 8000‐
gas
chromatography
 9000‐distillation
 
 How
Many
Samples
 
 
 QA/QC
Reporting
 Field
blank‐
exposed
throughout,
no
analyte,
used
to
detect
contamination
 Spiked
extract‐
media
spiked
with
known
amount
then
extracted,
%recovery
 Reagent
blank‐
DDI
water
analyzed
as
a
sample
to
test
carryover,
and
reagent
contamination
 Duplicate
sample‐
additional
sample
taken
to
determine
total
within‐batch
error
 Calibration
standard‐
a
material
to
check
instrument
calibration
 Lab
control
standard‐
sample
carried
through
analytical
proceedure
to
protocol
method.
 Total
recoverable‐
a
second
aliquot
of
sample
is
test
more
rigorously
to
test
protocol
method
 Field
rinsate‐
a
sample
rinsed
with
DDI
water
pass
over
equip
after
cleaning
to
check
hygiene
 Sample
blank
rinsate‐
DDI
water
passed
over
sample
container
to
check
hygiene
 Ext/int
lab
audit‐well
categorized
sample
is
tested
to
see
accuracy
and
precision
of
lab
analysis
 Field
audit‐
well
known
sample
is
tested
sent
and
recovered
from
the
field
to
test
sampling
 
 
 
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STUDENT
3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Objectives: determine how much pollutant enters the environment; measure ambient background concentration and assess the degree of pollution and identify trends (short-long); study fate and transport of contaminants and evaluate efficiency of remediation techniques. Concentration Units Liquids- (m/v) Solids-(m/m) Gas 1mg/L=1mg/kg=1mg/m^3=1ppm=10^-6 1µg/L=1µg/kg=1µg/m^3= 1ppb=10^-9 1ng/L=1ng/kg=1µg/m^3=1ppt=10^-12 Wet Basis vs. Dry Basis Gas Detection limit MDL=SD x Students T Students T distribution t= (mean-µ)/(SD/(n^1/2)) Confidence interval Accuracy is the degree of agreement of a measured value with the true or expected value. It is expressed as %Rec Accuracy is determined by spiking sample: Precision is the degree of mutual agreement among individual measure. SD- used for finite set of analytical data Relative SD- for evaluation of multiple replicate measurements Sample Size-if no prior information σ- estimated variability δ-acceptable error (1/2 of the width of 95% Cl of mean 7 Steps of Sampling Sampling & Analysis Plan Preparing equipment & supplies Identifying Sampling Points Collecting field and QA/QC samples Completing field documentation Packaging Samples Shipping sample to Lab The chain-of-custody form: Sample number Signature of collector Date and time of sample collection Place and address of sample collection Sample type (water, soil, air, etc.) Signature of persons involved in the chain of possession Inclusive dates of possession DQO-tolerable potential of errors 1) State & define problem, examine budget& schedule 2) Identify decision, state & study decision, define alternative actions 3)Identify inputs in decision, info. Needed for the decision, basis for action level 4) Define spatial/temporal limits and units 5) Define statistical parameter; specify action level 6) Specify tolerable limits on decision errors 7) optimize the design for sample DQO-STAGE 1 A) ID and identify data users; assemble and evaluate background data (background date, site visit, evaluate existing data), develop model of site, and specify RI/FS objectives DQO-STAGE 2 A)Evaluate sampling options; acceptance criteria; data quality and quality needs (PARCC) DQO-STAGE 3 Design program& develop data collection documentation Sampling Plan/Design Where to take sample Sampling Techniques &Preparations Sampling & Data analysis QA/QC-PARCC Solid Waste Samples Treatments are not diff. REALITY Judgmental Sampling- If you are performing a screening phase of an investigation of a relatively small-scale problem, and you have a budget and/or a limited schedule. Your goal is to assess whether further investigation including a detailed follow-up sampling is warranted. Simple random sampling-assumes that variability of a sample medium is insignificant, and hence it is appropriate for relatively uniform or homogeneous populations. Little background info. or for site where obvious contaminated areas do not exist or are not evident. Statistical analysis is simple Stratified random sampling-If you are estimating a population mean and you have known the existence of spatial or temporal patterns of the contaminant. Your goal is to increase the precision of the estimate with the same number of samples, or achieve the same precision with fewer samples and lower cost. Systematic sampling- if you are estimating populations mean and you have an adequate budget. In the meantime, you are also interested in understanding the spatial or temporal pattern. Composite sampling -if you are estimating a population mean and you have budget constraints. The analytical costs are much higher than the sampling costs. Your goal is to produce an equally precise or a more precise or a more precise estimate of the mean with fewer analyses and lower costs. Search sampling- If you are developing an understanding of the location of contamination and you have an adequate budget for the number of samples needed, you goal is to acquire coverage of the area of concern with a given level of confidence that you would have detected a hot spot of a given size. Transect sampling-If you are developing an understanding of where contamination is present and you have an adequate budget for the number of samples needed; your goal is to acquire coverage of time periods of interest. Cluster Sampling- use when population is spread across a wide area such that simple random sampling would be difficult to implement in accessing the selected sample. QC = system of tech activities to control the quality of data to meet the needs of the data users QA= a management system that makes sure QC in working. Phase I ESA Identifies potential environmental concerns. Environmental Assessment involves a review of records, a site reconnaissance (walk-through), and interviews to evaluate whether past or current activities at the site raise environmental concerns. Phase II ESA Evaluates potential concerns identified in the Phase I ESA. PhaseII ESAs are tailored to meet site-specific needs and, at a minimum, may involve limited sampling and analysis to confirm or rule out potential environmental concerns. Phase III ESA Site characterization & Remedial investigations. Treatments are different Null Hypothesis (H0) is true Treatments are different Decision Treatments are the same Accept Null Hypothesis Reject Null Hypotheses Right decision Wrong decision (Type II) FN Wrong Decision (Type I) FP Outlier Detection Alternative Hypothesis (H1)is true Right decision .-+ Field blank Sample blank rinsate Field rinsate Reagent blank Calibration check spiked extract Spiked sample Total recoverable Lab control standard Re-extraction Split extract Triplicate samples(splits) Duplicate sample Field audit External lab audit Internal lab audit Type of QA/QC samples or procedures A sample container filled with distilled water, exposed during sampling then analyzed to detect accidental or incidental contamination Sample of DDI water, passed over the sample preparation apparatus, after cleaning to check for residual contamination Sample of DDI water, passed over the sampling apparatus after cleaning, to check for residual contamination A DDI water sample analyzed as a routine sample to check for reagent contamination A standard material to check instrument calibration A separate aliquot of extract to which a known amount of analyte is added to check for extract matrix effects on the recovery of added analyte A separate aliquot of the soil sample having an appropriate standard reference material added to check for soil and extract matrix effects on recovery second aliquot of the sample which is analyzed by a more rigorous method to check the efficacy of the protocol method A sample of a soil standard carried though the analytical procedure to determine overall method bias Re-0065traction of the residue from the first extraction to determine extraction efficiency An additional aliquot of the extract which is analyzed to check injection and instrument reproducibility The prepared sample is split into 3 portions to provide blind duplicates for the analytical laboratory and a third replicate for the referee laboratory to determine interlaboratory precision. An additional sample taken near the field sample to determine within-batch measurement error A sample of well-characterized soil that is taken into the field with the sampling crew, sent through the sample back to lab with the field samples to detect bias in the entire measurement process and to determine batch to batch variability A sample well-characterized soil sent directly to the lab analysis. The analyte concentrations are unknown to the lab. This type of sample is used to estimate lab bias and batch to batch variability. It may also be used for external quality control of the lab. A sample of well-characterized soil, whose analyte concentrations are kn0wn to the laboratory, to be used for internal lab quality control Criteria for QA/QC samples & procedures Equal Discharge Increment samples are obtained from centroids of equal discharge increments. This method can save time and labor especially with large streams, because fewer verticals are required. Equal Width Increment method requires equal spacing between verticals across the stream a& sampling at an equal transit rate at all vertical yields a gross sample volume proportional to the total stream flow. (Water discharge in stream flow is not stable. 
 
 
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STUDENT
4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Developing Data Quality Objectives Stage1 Identify Decision Types Identify and involve data users Evaluate available data Develop conceptual model Specify RI/FS objectives Stage 2 Identify Data Uses/Needs Identify data uses Identify data types Evaluate sampling/analysis options Indentify data quantity needs Identify data quality needs Specify PARCC goals Stage 3 Design Data Collection Program Design Program Develop Data Collection documentation Scientific Reliability: Incorrect sampling protocol (bad sampler) Incorrect analytical protocol (bad analyst) Lack of good lab practice (GLP) Falsification of results Components of Legally defensible data: Custody or Control Documentation Traceability Two Types of Errors: Determinate errors – can be traced to source (improper sampling and analytical protocols) Indeterminate errors –random fluctuations that cannot be identified or corrected for. The Seven Steps of Sampling Step 1: Understand sampling and analysis plan Step 2: Prepare equipment and supplies Step 3: Identify sampling points Step 4: Collect field and QA/QC samples Step 5: Complete field documentation Step 6: Packaging samples Step 7: Shipping samples to lab Field Audits The primary obj. to determine the status of sampling operations. Emphasis placed on: -Verify operational aspects/procedure are in accordance with protocols and QA/QC. -Verify collection of samples including duplicates, rinsates, and blanks -Versify documentation is in order/sufficient to establish collection location of any sample collected -Determine discrepancies that exist and initiating corrective action needed -Collecting independent samples QC = system of tech activities to control the quality of data to meet the needs of the data users QA= a management system that makes sure QC in working. Scope of Enviro Sampling: Where to take samples When to take samples How to take samples How many samples to take How often sample will be taken How much sample is needed How to preserve the samples How long sample will be stable What to take (air, soil, water) What to analyze (Physical, Chemical, Biological) Who will take samples (sample custody)? Environmental Sampling: 1.) sample planning 2.) Identify sampling pt. 3.) Sample collection 4.) Sample transfer to lab 5.) Sample analysis 6.) Sample expires and discarded 7.) Sample is reincarnated as data pt. Concentration Units: Chemicals in liquids – mass/volume 1mg/L=1ppm=10-6 1µg/L=1ppb=10-9 1ng/L=1ppt=10-12 Chemicals in solids – mass/volume 1mg/kg=1ppm=10-6 1µg/kg=1ppb=10-9 1ng/kg=1ppt=10-12 Wet basis vs. dry basis mg / kg _ dry mg / kg _ wet (1 %MC ) Concentration Units: Chemicals in gases – mass/volume 1mg/m3=1ppmv=1ml/L=10-6 1µg/m3=1ppbv=1µl/L=10-9 1ng/m3=1pptv=1nl/L=10-12 Source Var. Hyp. test Pathway Recept Contam Conc Time -Exits -Can be contain -Remove /dispose Media Rate of Migrate Time -Exits -Can be contain - Remove /dispose Type Sensitiv Time -not impacted by migrate contam. -Relocate Type of QA/QC Sample or Procedures Procedure Descrip. Exposed during sampling Field Blank Prep check of Residue contaminate Sample Blank Rinsate Sample check for residue on apparatus Field Rinsate after cleaning Routine check for reagent Reagent Blank contamination Std material to check calibrate Calib. Check std Separate aliquot to known amount Spiked Extract analyte for extract matrix Separate aliquot to known amount Spike sample analyte for extract matrix for recover Separate aliquot of soil to known Total Recoverable reference material to check for extract matrix of recovery Std carried through procedure to Lab Control Std determine bias Re-extract of residue from first Re-extract extraction to determine extract eff. Addition aliquot of extract to check Split Extract instrument accuracy Three blind duplicates to different lab Triplicate samples precision Additional samples taken near the field Duplicate Sample to measure batch error Sample blank sent to lab to check bias Field audit of all measure ments Known sample conc sent to ext. lab to External Lab check bias Audit Internal Lab audit Known sample conc checked int lab to check quality control Data Quality Objectives 1. State the problem, define the problem, identify the sampling technique, examine budge; schedule 2. Identify the decision; state decision; identify study question; define alternative actions 3. Identify inputs to decision; identify info needed for decision (info sources, basis for action level, sampling analysis method 4. Define the boundaries of study; specify sample characteristics; define special/temporal limits, units of decision making 5. Develop a decision rule; define statistical parameter (mean, median), specify action level; develop logic for action 6. Specify tolerable limits on decision errors; set actionable limits for decision errors relative to consequences (health effect, costs) Judgmental Sampling If you are performing a screening phase of an investigation of a relatively small-scale problem, and you have a budget and/or a limited schedule. Your goal is to assess whether further investigation including a detailed follow-up sampling is warranted. Simple random Sample assumes that variability of a sample medium is insignificant, and hence it is appropriate for relatively uniform or homogeneous populations. Little background info. or for site where obvious contaminated areas do not exist or are not evident. Statistical analysis is simple If you are estimating a population mean and you have known the existence of spatial or temporal patterns of the contaminant. Your goal is to increase the precision of the estimate with the same number of samples, or achieve the same precision with fewer samples and lower cost. if you are estimating populations mean and you have an adequate budget. In the meantime, you are also interested in understanding the spatial or temporal pattern. if you are estimating a population mean and you have budget constraints. The analytical costs are much higher than the sampling costs. Your goal is to produce an equally precise or a more precise or a more precise estimate of the mean with fewer analyses and lower costs. If you are developing an understanding of the location of contamination and you have an adequate budget for the number of samples needed, you goal is to acquire coverage of the area of concern with a given level of confidence that you would have detected a hot spot of a given size. If you are developing an understanding of where contamination is present and you have an adequate budget for the number of samples needed; your goal is to acquire coverage of time periods of interest. use when population is spread across a wide area such that simple random sampling would be difficult to implement in accessing the selected sample. Stratified Random Sampling Systematic/Transect sampling Composite Sampling Search Sampling Transect Sampling Cluster Sampling Data Quality Objectives 1. What is the project purpose? 2. What is the problem that needs data collection? 3. What types of data are relevant for the project? 4. What is the intended use of the data? 5. What is the budget, schedule, resources? 6. What decisions and actions will be based on the collected data? 7. What are the consequences of a wrong decision? 8. What are the action levels? 9. What are the contaminants of concern and target analysis? 10. What are the acceptance criteria for the PARCC parameters? 11. Who are the decision makers? 12. Who will collect the data? 13. Why do we need to collect the particular type of data, and not the other? STARTING
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STUDENT
5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 B a s ic 
C o n c e p t s 
 P u r p o s e s 
o f 
S a m p lin g / A n a ly s is ‐ H a z a r d 
ID ,
R is k 
A s s e s s m e n t ,
R is k 
M a n a g e m e n t ,
R is k 
C o m m u n ic a t io n ,
 S c ie n t if ic 
R e lia b ilit y ,
a n d 
L e g a l
D e f e n s ib ilit y ‐ E s t a b lis h 
Q A / Q C ,
C h a in 
o f 
C u s t o d y ,
D o c u m e n t 
E v e r y t h in g ,
 A v o id 
S a m p lin g 
a n d 
A n a ly t ic a l
E r r o r s ,
S t a n d a r d 
C a lib r a t io n 
C u r v e s .

 
 T h e s e v e n s te p s o f a s a m p le ’s life : 1 ) s a m p le p la n n in g 2 ) id e n tific a tio n o f a s a m p lin g p o in t 3 ) s a m p le c o lle c tio n 4 ) s a m p le tra n s fe rre d to th e la b o ra to ry 5 ) s a m p le a n a ly s is 6 ) s a m p le e x p ire s a n d is d is c a rd e d 7 ) th e s a m p le is re in c a rn a te d a s a d a ta p o in t % 
R e c o v e r y = a n a ly t ic a l
x 
1 0 0 / T r u e 
 % 
R e c o v e r y 
S p ik e = 
S p ik e ‐ 
S a m p le 
 
 
 
 S a m p le 
 M in im u m 
D e t e c t io n 
 L im it = 
s t a n d a r d 
 d e v ia t io n 
x 
t 
v a lu e 
 D a t a 
Q u a l it y 
I n d ic a t o r s 
‐ 
P A R C C 
‐ 
P r e c is io n ,
A c c u r a c y ,
R e p r e s e n t a t iv e ,
C o m p a r a b l e ,
C o m p l e t e .
 
 C o n c e n t r a t io n s 

 M e a s u r in g 
C e n t r a l
T e n d e n c y ‐ 
M e a n ,
M e d ia n ,
M o d e 
 m g / m 3 
= 
p p m 
× 
M W 
/ 2 4 .5 
 M e a s u r in g 
D is p e r s io n ‐ S t a n d a r d 
D e v ia t io n ,
v a r ia n c e ,
R a n g e ,

 p p m 
= 
m g / m 3 
× 
2 4 .5 
/ M W 
 P u r p o s e 
o f 
S a m p lin g 
D e s ig n s 
 
 
‐ 
T o 
s u p p o r t 
a 
d e c is io n 
a b o u t 
w h e t h e r 
c o n t a m in a t io n 
le v e ls 
e x c e e d 
a 
 M o l a r i t y = m g / L 
 x 
 ( 1 g / 1 0 3m g ) 
 x 
 T h r e s h o ld 
o f 
u n a c c e p t a b le 
r is k 
 (1 m o le / M W )
 ‐ 
T o 
d e t e r m in e 
w h e t h e r 
c e r t a in 
c h a r a c t e r is t ic s 
o f 
t w o 
p o p u la t io n s 
d if f e r 
 b y 
s o m e 
a m o u n t 
 E n v i ro n m e n t a l 
S t a t s 
 ‐ T o 
e s t im a t e 
t h e 
m e a n 
c h a r a c t e r is t ic s 
o f 
a 
p o p u la t io n 
o r 
t h e 
p r o p o r t io n 
 Z = x ‐m e a n 
 o f 
a 
p o p u la t io n 
t h a t 
h a s 
c e r t a in 
c h a r a c t e r is t ic s 
o f 
in t e r e s t 
 







S 
 ‐ T o 
id e n t if y 
t h e 
lo c a t io n 
o f 
“ h o t 
s p o t s ” 
( a r e a s 
h a v in g 
h ig h 
le v e ls 
o f 
 C o m p a r in g 
t w o 
d if f e r e n t 
d a t a 
 C o n t a m in a t io n ) 
o r 
p lu m e 
d e lin e a t io n 
 F 
 D i s t r i b u t i o n = s 2a/ s 2b
 ‐ T o 
c h a r a c t e r iz e 
t h e 
n a t u r e 
a n d 
e x t e n t 
o f 
c o n t a m in a t io n 
a t 
a 
s it e ,
o r 
 F c a l> f c r it = H 
r e je c t e c t e d = d if f e r e n t 

 ‐ T o 
m o n it o r 
t r e n d s 
in 
e n v ir o n m e n t a l
c o n d it io n s 
o r 
in d ic a t o r s 
o f 
h e a lt h .


 T y p e 
I
e r r o r 
= 
r e je c t 
H 0 
w h e n 
H 0 
is 
 
 S t e p 
1 .
U n d e r s t a n d in g 
S a m p lin g 
a n d 
A n a ly s is 
P la n 
 t r u e 
( p r o b a b ilit y 
= 
α ) 
 
 S t e p 
2 .
P r e p a r in g 
E q u ip m e n t 
a n d 
S u p p lie s 
 T y p e 
II
e r r o r 
= 
a c c e p t 
H 0 
w h e n 
H 0 
is 
 
 S t e p 
4 .
C o lle c t in g 
f ie ld 
a n d 
Q A / Q C 
s a m p le s 
 f a ls e 
( p r o b a b ilit y 
= 
β ) 
 
 S t e p 
3 .
Id e n t if y in g 
S a m p lin g 
P o in t s 
 
 
 S t e p 
5 .
C o m p le t in g 
F ie ld 
D o c u m e n t a t io n 
 O u t lie r s ‐ 
c a lc u la t e 
z 
s c o r e 
( 3 
o r 
le s s 
 
 S t e p 
6 .
P a c k a g in g 
S a m p le s 
 a c c e p ta b le )
 
 S t e p 
7 .
S h ip p in g 
S a m p le s 
t o 
L a b o r a t o r y 
 C I = m e a n 
 + / ‐ ( t n ‐ 1 
) x ( 
 s / n 0 . 5 ) 
 
 T r u e 
o u t lie r 
d u e 
t o 
s a m p lin g 
e r r o r ,
 
 a n a ly t ic a l
e r r o r ,
 T y p e s 
o f 
S a m p lin g 
D e s ig n s 
a n d 
W h y 
 t r a n s c r ip t io n ,
d a t a ‐ e n t r y 
o r 
d a t a ‐ J u d g m e n t a l
‐ in it ia l
a s s e s s m e n t s 

 c o d in g 
e r r o r 
 S im p le 
R a n d o m ‐ s im p le 
s t a t s 
f o r 
s t a t ic 
s y s t e m 
a n d 
lo w 
c o s t s 
 S t r a t if ie d 
R a n d o m ‐ d iv id e s 
d a t a 
in t o 
m o r e 
h o m o g e n o u s 
g r o u p s 
f o r 
m o r e 
a c c u r a c y 

 S y s t e m a t ic 
G r id ‐ a llo w s 
f o r 
t e m p o r a l
p a t t e r n s 
a n d 
f u ll
c h a r a c t e r iz a t io n 
o f 
s o il,
h o t 
s p o t s 
lo c a t io n s 
 C o m p o s it e ‐ c o s t 
e f f e c t iv e ,
c r e a t e s 
m o r e 
p o s s ib le 
e r r o r s 
in 
c h a r a c t e r iz a t io n 
 S e a r c h 
S a m p lin g ‐ h o t 
s p o t 
d e t e c t io n ,

 Transect
Sampling‐variation
of
systematic,
acceptable
for
waste
pilesClhoosi,ngoProp
er
c.

 gulatory
Methods
 ,
 a k e s 
p 
 n d s , e t R e 
 W a t e r 
a n d 
A ir ‐ A P H A 
a n d 
E P A 
e x .
 
 U S E P A - w a s te te s t m e th o d s S W -8 4 6 ( S o lid W a s te 
 D is p o s a l A c t, R e s o u r c e R e c o v e r y A c t) M e t h o d o lo g y 
a n d 
Q A / Q C 
 F o r to x ic ity c h a r a c te r is tic s le a c h in g p ro c e d u re s (T C L P ) - M e th o d 1 3 1 1 O S H A /N IO S H , U S G S 
 M e th o d = a b o d y o f p r o c e d u r e s a n d te c h n iq u e s fo r p e r fo r m in g a n a c tiv ity ( s a m p lin g , c h e m ic a l a n a ly s is , q u a n tific a tio n … ) , s y s te m a tic a lly p r e s e n te d , in th e o r d e r in w h ic h th e y a r e to b e e x e c u te d .

 Q C = a s y s te m o f te c h n ic a l a c tiv itie s a im e d a t c o n tr o llin g th e q u a lity o f th e d a ta s o th a t T y p e s o f C o m m o n E rro rs - A n a ly te c a r r y o v e r fr o m s a m p lin g it m e e ts th e n e e d s o f d a ta u s e r s e q u ip m e n t Q A = a m a n a g e m e n t s y s te m th a t a s s u re s • In c o m p le te d e c o n ta m in a tio n o f th a t Q C is w o r k in g a s in te n d e d .

 F ie ld 
Q C 
S a m p le s 
 F ie ld 
B la n k s 
 E q u ip t m e n t 
B la n k s 
 T r a v e l
B la n k s 
 F ie ld 
D u p lic a t e s 

 C o llo c a t e d 
S a m p le s 
 A n a ly t ic a l
S a m p le s 
 S a m p le 
S p ik e 
 S u r r o g a t e 
S p ik e 
 R e a g e n t 
B la n k s 
 C a lib r a t io n 
C u r v e s 
 C o n t r o l
S a m p le s 
 L a b o r a t o r y 
D u p lic a t e s 
 T h in g s 
t o 
R e s e a r c h 
F o r 
E S A 
 e q u ip m e n t b e tw e e n s a m p lin g tr ip s • C r o s s - c o n ta m in a tio n b e tw e e n s a m p le s • A b s o r p tio n o f v o la tile c h e m ic a ls fr o m a ir d u r in g tr a n s p o r ta tio n o r s to r a g e 
 
 E S A 
P h a s e s 
a n d 
P u r p o s e s 
 P h a s e 
 I ‐ D e t e r m i n e s t h e "r e c o g n i z e d e n v i r o n m e n t a l c o n d i t i o n s . " - - - - - E n v ir o n m e n ta l s e ttin g ( g e o g r a p h y & h y d r o g e o lo g y ) H is to r ic r e c o r d s r e v ie w Re v i e w o f t h e h a z a r d o u s b u i l d i n g m a t e r i a l s Site and area reconnaissance A r e g ul a t o r y a g e n c y r e v i e w In te r v ie w s P h a s e II- T h e p h y s ic a l s a m p lin g o f th e s ite , a s r e c o m m e n d e d in th e P h a s e I r e p o r t ( m i n i m u m g u i d e l i n e ) . T h e n C o m p r e h e n s i v e D e t a i l e d Re p o r t P h a s e III- d e s ig n a n d im p le m e n ta tio n o f th e r e m e d ia tio n o f th e s ite . 
 C ur r e n t a n d p r i o r us e s H a z a r d o us s ub s t a n c e s p r e s e n t 
 Signs of property misuse E f f l ue n t a n d a i r e m i s s i o n s R iv e r 
S e d im e n t 
S a m p lin g 
 W a s t e d i s p o s a l t e c h n i q ue s S u s p e n d e d 
lo a d 
a n d 
B e d 
lo a d 
t y p e s 
 Surface water T ra n s form ers V a r ia t io n s ‐ 
t im e ,
s e a s o n s ,
d e p t h ,
 Surrounding area use a c r o s s 
c h a n n e ls ,

 P r e s e n c e a n d lo c a tio n o f Is o k in e t ic 
T e c h n iq u e s 
O .3 
f r o m 
b e d 

 Sanitary sewers D e p t h 
In t e g r a t in g 
v s 
P o in t 
In t e g r a t in g 
 W a te r w e lls D r i n k i n g w a t e r s o ur c e s a n d q ua n t i t y E q u a l
D is c h a r g e 
In c r e m e n t 
M e t h o d 
 De b r i s ‐ s a m e 
t r a n s it 
r a t e s 

a c r o s s 

 C h e m i c a l s t o r a g e d r um s E q u a l
W id t h 
In c r e m e n t 
M e t h o d 
 Soil mounds ‐ d if f 
t r a n s it 
r a t e s 

 Gr o u n d d e p r e s s i o n s Di s t r e s s e d , s t a i n e d s o i l P o o r o r n o g r o w th o f v e g e ta tio n De a d w i l d l i f e E v i d e n c e o f s ur f a c e w a t e r c o n t a m i n a t i o n Surface impoundments (pits, ponds, lagoons…) A b o v e g r o un d s t r uc t ur e s o t h e r t h a n b ui l d i n g s Signs of subsurface structures O d ors E f f l ue n c e f r o m b ui l d i n g s A ir e m is s io n s Signs of mining / quarrying E l e c t r i c a l s up p l i e s e q ui p m e n t ( i . e . P C B ’ s ) Ce m e te r ie s 
 
 
 
 
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ON
NEXT
PAGE

‐

STUDENT
6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 S A 
D e f in it io n :
“ a 
m u lt i‐ s t a g e 
p r o c e s s 
t h a t 
in c lu d e s 
t h e 
id e n t if ic a t io n / 
c h a r a c t e r iz a t io n 
o f 
a 
h a z a r d 
o r 
r is k 
f a c t o r ,
r is k 
a s s e s s m e n t 
o f 
t h e 
lik e lih o o d 
o f 
 o c c u r r e n c e ,
e v a lu a t io n 
o f 
im p a c t s 
a s s o c ia t e d 
w it h 
t h a t 
h a z a r d ,
e v a lu a t io n 
o f 
m it ig a t io n 
m e a s u r e s 
( r is k 
m a n a g e m e n t ) ,
a n d 
c o m m u n ic a t io n 
o f 
r is k s ” . 
 D a t a 
a c q u is it io n 
p r o c e s s :
S a m p lin g 
d e s ig n 
( p la n ) ‐ S a m p lin g 
T e c h n iq u e s 
[m e t h o d o lo g y 
c h e c k ]‐ S a m p le 
p r e p a r a t io n 
[m e t h o d o lo g y 
c h e c k ]‐ S a m p le 
 a n a ly s is 
[m e t h o d o lo g y 
c h e c k ]‐ D a t a 
a n a ly s is 
[a ll
h a v e 
Q A / Q C 
c h e c k s ].
 C o n c e n t r a t io n 
u n it s :
S O L ID S :
m a s s / m a s s 
{ m g / k g = 1 p p m = 1 0 ^ ‐ 6 ;
1 u g / k g = 1 p p b = 1 0 ^ ‐ 9 ;
1 n g / k g = 1 p p t = 1 0 ^ ‐ 1 2 } { m g / k g 
o n 
d r y 
w e ig h t = ( m g / k g 
w e t ) / ( 1 ‐ % m ) } — L IQ U ID :
m a s s / v o lu m e 
{ 1 m g / L = 1 p p m = 1 0 ^ ‐ 6 ;
e t c } ,
o t h e r 
t h a n 
H 2 O ‐ 
1 p p m = ( 1 m g 
c o n t / 1 
k g 
liq ) = ( 1 / D ) * ( 1 
m g 
c o n t / 1 L 
liq ) . 
G A S :
 { 1 m g / m ^ 3 ≠ 1 p p m V = 1 m l/ L = 1 0 ^ ‐ 6 ;
e t c } 
{ m g / m ^ 3 = p p m * M W / 2 4 .5 } { p p m = m g / m ^ 3 * 2 4 .5 / M W } 
O N L Y 
V A L ID 
F O R 
2 5 C 
 E X A M P L E 
f o r 
G A S :
M C L 
a c c o r d in g 
t o 
t h e 
E P A 
d io x in 
in 
D W 
c is 
0 .0 0 0 0 0 0 0 3 
m g / L .
M W = 3 2 2 g / m o l— f in d 
P P T 
a n d 
m o la r it y :
0 .0 0 0 0 0 0 0 3 
 m g / L * ( 1 p p m / 1 m g / L ) * ( 1 0 ^ 6 p p t / 1 p p m ) = 0 .0 3 
p p t ;
0 .0 0 0 0 0 0 0 3 
m g / L * ( 1 g / 1 0 ^ 3 m g ) * ( 1 m o l/ 3 2 2 g ) = 9 .3 2 x 1 0 ^ ‐ 1 4 — C a lc u la t e 
t h e 
n u m b e r 
o f 
d io x in 
 m o le c u le s 
p e r 
lit e r 
o f 
w a t e r :
9 .3 2 x 1 0 ^ ‐ 1 4 m o l/ L 
* 6 .0 2 2 x 1 0 ^ 2 3 
l/ m o l= 5 .6 1 x 1 0 ^ 1 0 
m o le c u le s / L 
 A n a ly t ic a l
a c c u r a c y :
t h e 
d e g r e e 
o f 
a r g u m e n t 
o f 
a 
m e a s u r e d 
v a lu e 
w it h 
t h e 
t r u e 
o r 
e x p e c t e d 
v a lu e ;
% R e c o v e r y = a n a ly t ic a l
v a lu e * ( 1 0 0 / t r u e 
v a lu e ) ;
 R e c o v e r y 
:
M e t h o d 
c a lib r a t io n ;
% 
r e c o v e r y 
o n 
s p ik e = ( s p ik e d 
s a m p le ‐ s a m p le 
v a lu e / s p ik e d 
v a lu e ) [0 .5 
t o 
2 ];
P r e c is io n :
t h e 
d e g r e e 
o f 
m u t u a l
a g r e e m e n t 
 a m o n g 
in d iv id u a l
m e a s u r e 
a s 
a 
r e s u lt 
o f 
r e p e a t in g 
t e s t in g 
u n d e r 
t h e 
s a m e 
c o n d it io n s ;
S t D e v ,
R e l
S t a D e v ,
R e l
% d if f 
 A c c u r a c y 
is 
im p o s s ib le 
w it h o u t 
P r e c is io n / 
p r e c is io n 
d o e s 
n o t 
g u a r a n t e e 
a c c u r a c y ::D a t a 
Q u a lit y 
In d ic a t o r s :
P r e c is io n ,
A c c u r a c y ,
R e p r e s e n t a t iv e n e s s ,
 C o m p a r a b ilit y ,
a n d 
C o m p le t e n e s s ::S e c o n d a r y 
D Q I’S :
D e t e c t io n 
L im it 
a n d 
Q u a n t it a t io n 
L im it ;;d e t e c t io n 
lim it 
is 
“ t h e 
m in im u m 
c o n c e n t r a t io n 
t h a t 
c a n 
 b e 
m e a s u r e d 
a n d 
r e p o r t e d 
w it h 
9 9 % 
c o n f id e n c e 
t h a t 
t h e 
a n a ly t ic 
c o n c e n t r a t io n 
is 
g r e a t e r 
t h a n 
0 ” ::
M in im u m 
d e t e c t io n 
L im it :
M D L = s t a n d a r d 
 d e v ( s ) * s t u d e n t 
t 
( t ) ;
Q u a n t it a t io n 
L im it 
is 
“ t h e 
lo w e s t 
c o n c e n t r a t io n 
t h a t 
c a n 
b e 
r e lia b ly 
a c h ie v e d 
w it h in 
s p e c if ie d 
lim it s 
o f 
p r e c is io n 
a n d 
a c c u r a c y 
 d u r in g 
r o u t in e 
o p e r a t in g 
c o n d it io n s ” 
 S t a n d a r d 
c a lib r a t io n 
c u r v e :
p lo t 
o f 
in s t r u m e n t a l
r e s p o n s e 
v s .
t h e 
c o n c e n t r a t io n 
o f 
t h e 
c h e m ic a l
o f 
in t e r e s t .y = a x + b 

 C o m m o n 
O r g a n ic 
P o llu t a n t s :
M e t a ls ( C u ,
Z n ,P b ,C d ,N i,H g ,C r ) ,
M e t a llo id s ( A s ,S e ) ;
In o r g a n ic 
C o m p u n d s :
C y a n id e ,
C O ,
N O x ,
A s b e s t o s ;
O r g n o ‐ M e t a llic :
 T e t r a e t h y l
le a d ,
t r ib u t y l
t in ;
H y d r o c a r b o n s :
B T E X ’s 
( b e n z e n e ,
t o lu e n e ,
e t h y lb e n z e n e ,
x y le n e ) ,
P A H ’s ( N a p h t h a le n e ,
P h e n a t r e n e ,
P y r e n e ) ,
H a lo g e n a t e d 
 a lip h a t ic 
h y d r o c a r b o n s 
( t e t r a c h lo r o e t h ly e n e ,
t r ic h lo r a e t h le n e ,
d ic h lo r o e t h le n e ,
v in a l
c h lo r id e ) ;
O x y g in a t e d 
c o m p o u n d s :
A lc o h o l,
A ld e h y d e ,
E t h e r ,
 O r g a n ic 
a c id ,
e s t e r ,
k e t o n e ,
p h e n o l;
N it r o g e n 
c o m p o u n d s :
A m in e ,
A m id e ,
n it r o a r o m a t ic 
h y c a r ,
n it r o s a m in e ;
O r g a n o ‐ s u lp h u r :
T h io ls ,
t h io p h e n e s ,
 m e r c a p t a n s ,
p e s t ic id e s ;
P h o s p h o r u s 
c o m p o u n d s :
p e s t ic id e s 

 C la s s if ic a t io n 
b y 
p r o p e r t ie s :
D e n s it y ,
v o la t ilit y 
( ( v o c ’s 
b p < 2 0 0 C ) ,S V O C ’s ( s lo w ly 
v o l
a t 
r o o m 
t e m p ) ) ,
E x t r a c t a b ilit y 
( B / N ,
A ) 
 A 
p o p u la t io n 
c a n 
b e 
d e s c r ib e d 
a s :
c e n t r a l
t e n d e n c y 
a n d 
d is p e r s io n ;
m e a s u r e m e n t 
o f 
c e n t r a l
t e n d e n c y :
p o p 
m e a n ( µ ) ,
G e o m e t r ic 
m e a n ( G M ) ,
M e d ia n 
 ( x ) 
,
M o d e . 
D is p e r s io n :
P o p u la t io n 
v a r ia n c e ( ơ ^ 2 ) 
a n d 
s im p le 
v a r ia n c e 
( s ^ 2 ) ,
S t a a n d a r d 
d e v ia t io n 
( ơ 
o r 
s ) ,
r a n g e 
( m a x ‐ m in ) ,
in t e r q u a r t ile 
r a n g e 
( Q 7 5 ‐ Q 2 5 ) ;;V a r ia n c e 
is 
a d d it iv e :
ơ ^ 2 ( o v e r a ll) ‐ ơ ^ 2 ( s a m p lin g ) 
+ ơ ^ 2 ( a n a ly s is ) 
 P r o b a b ilit y 
d is t r ib u t io n s ‐ 
G a u s s ia n :
e n v ir o n m e n t a l
d a t a 
g e n e r a lly 
s k e w e d ‐ d a t a 
is 
g e n e r a lly 
lo g ‐ t r a n s f o r m e d = lo g ‐ n o r m a l
d is t r ib u t io n :
S T A N D A R D 
 N O R M A L 
D IS T R IB U T IO N :
6 8 ‐ 9 5 ‐ 9 7 .7 
r u le 
e x a m p le 
p r o b le m :

 E .g .:
t h e 
b a c k g r o u n d 
c o n c e n t r a t io n 
o f 
Z n 
in 
s o ils 
o f 
H o u s t o n 
a r e a 
is 
n o r m a lly 
d is t r ib u t e d 
w it h 
a 
m e a n 
o f 
6 6 m g / k g 
a n d 
a 
s t .
d e v 
o f 
5 
m g / k g ::
% 
o f 
s o il
 s a m p le s 
w it h 
a 
c o n c . 
o f 
< 7 2 
m g / k g 
? ,

% 
o f 
s o il
s a m p le s 
w it h 
a 
c o n c . 
o f 
> 7 2 m g / k g 
? ,

% 
o f 
s o il
s a m p le s 
w it h 
a 
c o n c . 
b t w .
6 1 
a n d 
7 2 
m g / k g 
? S o lu t io n :
 S t a n d a r d iz e 
t h e 
c o n c e n t r a t io n s 
[ z = 
(x ‐ μ )/ σ ] :
F o r 
x = 7 2 ,
z = ( 7 2 ‐ 6 6 ) / 5 = 1 .2 ,,
F o r 
x = 6 1 ,
z = ( 6 1 ‐ 6 6 ) / 5 = ‐ 1 
[ a )
P ( x < 7 2 ) 
= 
P ( z < 1 .2 ) 
= 
P ( ‐ ∞ < z < 0 ) 
+ 
 P ( 0 < z < 1 .2 ) 
= 
0 .5 + 0 .3 8 4 9 
= 
0 .8 8 4 9 
( 8 8 .4 9 % ) 
b )
P ( x > 7 2 ) 
= 
P ( z > 1 .2 ) 
= 1 ‐ P ( z < 1 .2 ) 
= 1 ‐ 0 .8 8 4 9 
= 
0 .1 1 5 1 
( 1 1 .5 1 % ) 
c )
P ( 6 1 < x < 7 2 ) 
= 
P ( ‐ 1 < x < 1 .2 ) 
P ( ‐ 1 < z < 0 ) 
+ 
P ( 0 < z < 1 .2 ) 
= 
P 
( 0 < z < 1 ) 
+ 
P ( 0 < z < 1 .2 ) 
= 
0 .3 4 1 3 
+ 
0 .3 8 4 9 
= 
0 .7 2 6 2 
( 7 2 .6 2 % ) 
 A n d e r s o n ‐ D a r lin g 
t e s t :
d is t a n c e 
t e s t ,
s t a n d a r d iz e s 
d a t a 
a n d 
t e s t s 
f o r 
d e p a r t u r e 
f r o m 
e x p e c t e d 
c u r v e 
f it ;
S h a p ir o ‐ W ilk s 
t e s t :
r e g r e s s io n 
t y p e 
t e s t ,
 a s s e s s e s 
h o w 
w e ll
t h e 
o b s e r v e d 
c u m u la t iv e 
f r e q u e n c y 
d is t r ib u t io n 
c u r v e 
f it s 
t h e 
e x p e c t e d 
c u m u la t iv e 
f r e q 
c u r v e ;
S h e w n e s s 
a n d 
K u t o s is 
in d ic e s :
f ir s t 
 in s t a n c e 
in d ic a t o r s ,
u s e f u l
w it h 
la r g e 
d a t a 
s e t s .
 S t u d e n t 
t 
d is t r ib u t io n :
t = ( x ‐ u ) / ( s / n ^ ‐ 1 ) ;
s y m m e t r ic 
a r o u n d 
) ,
d e v is e d 
f o r 
s m a ll
s a m p le 
s iz e s 
( n ≤ 3 0 ) 
 C o n f id e n c e 
in t e r v a ls :
( x ± t ^ n ‐ 1 ) * s / n ^ ‐ 1 ;;
s t a n d a r d 
e r r o r 
o f 
m e a n :
s / n ^ ‐ 1 = S E M 
 E X A M P L E :
m e a n = 6 6 m g / k g ,
s = 
5 m g / k g ,
n = 8 ;;T w o 
s id e d 
C I
9 0 % = 
9 0 % 
( 2 ‐ s id e d ) 
= 
9 5 % 
( 1 ‐ s id e d ) 
→ 
1 ‐ α / 2 
= 
0 . 9 5 
 t d f = 7 ,
α = 0 .1 = 
1 .8 9 5 ;
C I
= 
6 6 ± 1 .8 9 5 
x 
5 / √ 8 
= 
6 6 ± 3 .3 5 m g / k g 
( i. e . 6 2 . 6 5 
t o 
6 9 .3 5 ) ;
T w o 
s id e d 
C I
9 9 % = 9 9 % 
( 2 ‐ s id e d ) 
= 
9 9 .5 % 
( 1 ‐ s id e d ) 
→ 
1 ‐ α / 2 
= 
0 . 9 9 5 
 t d f = 7 ,
α = 0 .0 1 = 
3 . 4 9 9 
C I
= 
6 6 ± 3 . 4 9 9 
x 
5 / √ 8 
= 
6 6 ± 6 .1 8 m g / k g 
( i. e .
5 9 .8 2 
t o 
7 2 . 1 8 ) 
 F ‐ v a lu e s 
w ill
s h o w 
w h e t h e r 
t h e 
d if f e r e n c e 
in 
v a r ia n c e s 
in s ig n if ic a n t 
o r 
n o t .;
T h e 
d if f e r e n c e 
is 
s ig n if ic a n t 
if 
t h e 
c a lc u la t e d 
F ‐ v a lu e 
is 
g r e a t e r 
t h a n 
t h e 
 F c r it ic a l
v a lu e . :
U S E S :
c o m p a r e 
a n a ly t ic a l
m e t h o d s ,
c o m p a r e 
la b 
p e r f o r m a n c e 
a g a in s t 
o t h r 
la b s ,
c o m p a r e 
s a m p le 
s e t s 
c o lle c t e d 
a t 
2 
d if f e r e n t 
 lo c a tio n s .
 T y p e 
I
e r r o r 
= 
r e je c t 
H 0 
w h e n 
H 0 
is 
t r u e 
( p r o b a b ilit y 
= 
α ) ,
T y p e 
II
e r r o r 
= 
a c c e p t 
H 0 
w h e n 
H 0 
is 
f a ls e 
( p r o b a b ilit y 
= 
β ) 
 O u t lie r s :
o b s e r v a t io n s 
t h a t 
a p p e a r 
in c o n s is t e n t 
w it h 
t h e 
r e m a in d e r 
o f 
t h e 
c o lle c t e d 
d a t a ,
T r u e 
o u t lie r 
d u e 
t o 
s a m p lin g 
e r r o r ,
a n a ly t ic a l
e r r o r ,
 t r a n s c r ip t io n ,
d a t a ‐ e n t r y 
o r 
d a t a ‐ c o d in g 
e r r o r 
:
C o r r e c t in g :
r e p la c e 
in c o r r e c t 
d a t a ,
r e m o v e 
b a s e d 
o n 
s t a t is t ic a l
t e s t :
Z 
t e s t = x ‐ 
x / s ,
d a t a 
p o in t 
is 
 r e je c t e d 
if 
z > 3 
 S A M P L IN G :
W h e r e ,
w h e n ,
h o w 
m a n y . 
7 
s t e p s 
o f 
s a m p lin g :
U n d e r s t a n d in g 
s a m p lin g 
a n d 
a n a l
p la n ,
p r e p a r in g 
e q u ip m e n t 
a n d 
s u p p lie s ,
Id e n t if y in g 
 s a m p lin g 
p o in t s ,
c o lle c t in g 
f ie ld 
a n d 
Q A / Q C 
s a m p le s ,
c o m p le t in g 
f ie ld 
d o c u m e n t s ,
p a c k in g 
s lip s ,
s h ip p in g 
s a m p le s 
t o 
la b 
 D a t a 
q u a lit y 
o b je c t iv e s 
‐ 
q u a lit a t iv e 
a n d 
q u a n t it a t iv e 
s t a t e m e n t s 
t h a t 
d e f in e 
t h e 
a p p r o p r ia t e 
t y p e 
o f 
d a t a 
,
a n d 
s p e c if y 
t h e 
t o le r a b le 
le v e ls 
o f 
 p o t e n t ia l
e r r o r s 
t h a t 
w ill
b e 
u s e d 
a s 
b a s is 
f o r 
e s t a b lis h in g 
t h e 
q u a lit y 
a n d 
q u a n t it y 
o f 
d a t a 
n e e d e d 
t o 
s u p p o r t 
d e c is io n 
[ S t e p 
1 :
s t a t e 
t h e 
p r o b le m ,
 d e f in e 
t h e 
p r o b le m ,
id e n t if y 
s a m p lin g 
t e a m ,
e x a m in e 
b u d g e t / s c h e d u le ] ;[ 
s t e p 
2 :
Id e n t if y 
t h e 
d e c is io n ;
s t a t e 
d e c is io n ;
id e n t if y 
s t u d y 
q u e s t io n ;
d e f in e 
 a lt e r n a t iv e 
a c t io n s ] ;[ 
S t e p 
3 . 
Id e n t if y 
in p u t s 
t o 
t h e 
d e c is io n ;
id e n t if y 
in f o r m a t io n 
n e e d e d 
f o r 
t h e 
d e c is io n 
( in f o r m a t io n 
s o u r c e s ,
B a s is 
f o r 
a c t io n 
le v e l,
 s a m p lin g / a n a ly s is / 
m e t h o d ];
[S t e p 
4 .
D e f in e 
t h e 
b o u n d a r ie s 
o f 
t h e 
s t u d y ;
s p e c if y 
s a m p le 
c h a r a c t e r is t ic s ;
d e f in e 
s p a t ia l/ t e m p o r a l
lim it s ,
u n it s 
o f 
 d e c is io n 
m a k in g ] . [ 
S t e p 
5 . 
D e v e lo p 
a 
d e c is io n 
r u le ;
d e f in e 
s t a t is t ic a l
p a r a m e t e r 
( m e a n ,
m e d ia n ) ;
s p e c if y 
a c t io n 
le v e l;
d e v e lo p 
lo g ic 
f o r 
a c t io n ] ;
[ S t e p 
 6 .
S p e c if y 
t o le r a b le 
lim it s 
o n 
d e c is io n 
e r r o r s ;
s e t 
a c c e p t a b le 
lim it s 
f o r 
d e c is io n 
e r r o r s 
r e la t iv e 
t o 
c o n s e q u e n c e s 
( h e a lt h 
e f f e c t ,
c o s t s … ) ];[
S t e p 
7 .
 O p t im iz e 
t h e 
d e s ig n 
f o r 
o b t a in in g 
d a t a :
s e le c t 
r e s o u r c e ‐ e f f e c t iv e 
s a m p lin g 
a n d 
a n a ly s is 
p la n 
t h a t 
m e e t s 
t h e 
p e r f o r m a n c e 
c r it e r ia ]
 R e p r e s e n t a t iv e n e s s :
u lt im a t e ‐ H o w 
w e ll
t h e 
p r o je c t 
d e s ig n 
r e p r e s e n t s 
a 
c h a r a c t e r is t ic s 
o f 
a 
p o p u la t io n 
a n d 
t h e 
e n v ir o n m e n t a l
c o n d it io n s 
a t 
t h e 
s it e 
 ( s a m p lin g 
a n d 
a n a ly s is 
d e s ig n ) ;
s a m p lin g 
p o in t :
H o w 
w e ll
a 
s a m p le 
r e p r e s e n t s 
t h e 
c h a r a c t e r is t ic s 
o f 
a 
s a m p lin g 
p o in t ;
C o lle c t e d 
s a m p le :
H o w 
w e ll
a 
 s u b s a m p le 
r e p r e s e n t s 
a 
c o lle c t e d 
s a m p le 
( m e a s u r e 
o f 
p r o p e r 
h a n d lin g 
d u r in g 
t h e 
a n a ly t ic a l
p h a s e 
o f 
t h e 
p r o je c t ) ;;P R O P E R 
C O N T A IN E R S 
F O R 
 S A M P L E S ‐ G L A S S ,
P L A S T IC ,
T E F L O N 
( V O C ’S ,
A V O IL D 
H E A D S P A C E ,
M E T A L S ,P L A S T IC ) 
 S o lid 
s a m p le s :
m ic r o 
a n d 
m a c r o 
s c a le ;
A ir 
s a m p le s :
w in d 
d ir e c t io n 
a n d 
v e lo c it y ;
w a t e r 
s a m p le s :
s e a s o n a l
a n d 
s p a t ia l;
b io lo g ic a l:
s p e c ie s ,
s iz e ,
a g e ,
 s e x ,
m o b ilit y ,
m o r t a lit y ,
a n d 
g r o w t h ,
t is s u e 
v a r ia t io n s 
 S im p le 
r a n d o m 
S a m p lin g :
a r b it r a r y 
c o lle c t io n 
o f 
s a m p le s 
b y 
a 
p r o c e s s 
t h a t 
g iv e s 
e a c h 
s a m p le 
u n it 
in 
t h e 
p o p u la t io n 
t h e 
s a m e 
c h a n c e 
o f 
s a m p lin g .
 ( B A D 
o n ly 
p r a c t ic a l
f o r 
s t a t ic 
s y s t e m s ,
s o il) .s t r a t if ie s 
r a n d o m 
s a m p lin g :
d iv id e s 
s a m p lin g 
p o p 
in t o 
s e v e r a l
n o n ‐ o v e r la p p in g 
s t r a t a ,
t h e n 
r a n d o m 
 s a m p lin g 
is 
e m p lo y s 
( n ^ k = n / r ) ;
T e m p o r a l
s t a r a :
s a m p le s 
t o 
b e 
s e le c t e d 
f o r 
s p e c if ic 
t im e 
p e r io d s 
( d a y 
v s .
n ig h t ) ;
s p a t ia l
s t r a t a :
s a m p lin g 
a 
v a r ie t y 
o f 
 c o n t in g e n t s 
( d e p t h 
( s o il,
s e d im e n t 
c o r e ,
a g e s ,
s e x ) .E q u a l
a llo c a t io n :
e a c h 
s t r a t u m 
is 
a s s ig n e d 
t h e 
s a m e 
n u m b e r 
o f 
s a m p le s . 
P r o p o r t io n a l
a llo c a t io n :
 s a m p le s 
a r e 
p r o p o r t io n a l
t o 
t h e 
s iz e 
o f 
t h e 
s t r a t u m .
O p t im a l
a llo c a t io n :
c o s t 
is 
c o n s id e r e d 
f o r 
o p t im a l
p r e c is io n 
o r 
o p t im a l
c o s t .
S y s t e m a t ic 
s a m p lin g :
 s e le c t in g 
s a m p le 
u n it s 
a c c o r d in g 
t o 
s p e c if ie d 
p a t t e r n 
in 
t im e 
o r 
s p a c e .
S y s t e m a t ic 
g r id :
s u b d iv id e s 
in t o 
s m a lle r 
a r e a 
a n d 
c o lle c t s 
f r o m 
e q u a liz e d 
f ix e d 
 lo c a t io n s .
S y s t e m a t ic 
r a n d o m :
c o lle c t in g 
s a m p le s 
f r o m 
t h e 
s m a lle r 
a r e a s 
a t 
r a n d o m 
a r e a s 
w it h in 
t h e 
g r id .
C o m p o s it e 
s a m p lin g :

C o s t ‐ s a v in g 
w h e n 
w e 
 a r e 
in t e r e s t e d 
in 
t h e 
m e a n 
a n d 
t h e 
c o s t 
o f 
s a m p lin g 
is 
s ig n if ic a n t ly 
lo w e r 
t h a n 
t h e 
c o s t 
o f 
a n a ly s is . 
S e a r c h 
s a m p lin g :
v a r ia t io n 
o f 
s y s 
g r id 
s a m p le ,
“ h o t 
 s p o t 
d e t e c t io n ” . 
T r a n s e c t 
s a m p lin g :
c h e a p e r ,
w a s t e 
p ile s ,
la r g e 
la k e s ,
la r g e 
liq u id 
w a s t e . 
H O W 
M A N Y 
S A M P L E S ? 
N = ? ,
s = 3 . 2 5 ,
e = 1 . 5 ,
t = ? 
1 ) 
t d f = 9 ,
0 . 0 5 

 [ ( 2 . 2 6 2 x 3 . 2 5 ) / 1 . 5 ] 2 
= 
2 4 .0 1 ;
2 ) 
n = 
2 4 
@ 9 5 % 
‐ t d f = 2 3 ,
0 .0 5 
= 
2 .0 6 9 [ ( 2 . 0 6 9 x 3 . 2 5 ) / 1 .5 ] 2 
= 
2 0 . 1 
3 ) 
n = 2 0 
a t 
9 5 % 
t d f = 2 0 ,
0 . 0 5 
= 
2 . 0 9 3 [ ( 2 .0 9 3 x 3 .2 5 ) / 1 .5 ] 2 
= 
 2 0 .5 6 
≈ 
2 1 ‐ ‐ R e s u lt 
= 
2 1 
s a m p le s 
r e q u ir e d 
 M e t h o d 
= 
a 
b o d y 
o f 
p r o c e d u r e s 
a n d 
t e c h n iq u e s 
f o r 
p e r f o r m in g 
a n 
a c t iv it y 
( s a m p lin g ,
c h e m ic a l
a n a ly s is ,
q u a n t if ic a t io n … ) ,
s y s t e m a t ic a lly 
p r e s e n t e d ,
in 
 t h e 
o r d e r 
in 
w h ic h 
t h e y 
a r e 
t o 
b e 
e x e c u t e d .
2 .
W h a t 
a r e 
t h e 
h a z a r d o u s 
c h a r a c t e r is t ic s 
d e s c r ib e d / t a r g e t e d 
b y 
S W ‐ 8 4 6 ? 
W h ic h 
m e t h o d 
in 
S W ‐ 8 4 6 
is 
 u s e d 
t o 
t e s t 
t h e 
t o x ic it y 
c h a r a c t e r is t ic s 
o f 
w a s t e ? = 
t o x ic it y ,
ig n it a b ilit y ,
r e a c t iv it y 
a n d 
c o r r o s iv e ly 

( s e e 
a b s t r a c t 
S W 8 4 6 ) M e t h o d 
1 3 1 1 
( N O T E :
M e t h o d 
 1 3 1 0 B 
is 
a n 
e x t r a c t io n 
p r o c e d u r e 
– 
n o t 
a n 
a c c e p t e d 
a n s w e r ) 
3 .
D e s c r ib e 
t h e 
d if f e r e n c e 
b e t w e e n 
E P A 
m e t h o d 
6 2 4 
a n d 
6 2 5 .
M e t h o d 
6 2 4 
– 
d e v is e d 
f o r 
 e x t r a c t io n 
o f 
v o la t ile 
o r g a n ic s 
– 
p u r g in g 
u s in g 
in e r t 
g a s e s 
‐ M e t h o d 
5 2 5 
‐ 
d e v is e d 
f o r 
e x t r a c t io n 
o f 
s e m i‐ v o la t ile 
o r g a n ic s 
– 
b y 
e m p lo y in g 
o r g a n ic 
 s o lv e n t s 4 . 
W h ic h 
E P A 
m e t h o d 
w o u ld 
y o u 
u s e 
f o r 
t h e 
a n a ly s is 
o f 
in d u s t r ia l
w a s t e w a t e r 
s lu d g e 
f o r 
c a d m iu m ,
m e r c u r y 
a n d 
c h r o m iu m 
t o 
e v a lu a t e 
 w h e t h e r 
t h e 
s lu d g e 
c a n 
b e 
d is p o s e d 
in 
a 
n o n ‐ h a z a r d o u s 
la n d f ill.
a ) 
D ig e s t io n :
m e t h o d s 
3 0 0 5 A 
t h r o u g h 
3 0 6 0 A 
d e p e n d in g 
o n 
t h e 
d e t e r m in a t io n 
 m e t h o d 
c h o s e n 
( o r 
a n a ly t ic a l
e q u ip m e n t 
a v a ila b le ) 
( S W 
8 4 6 
C h 
3 . ,
P a g e s 
2 4 ‐ 2 4 ) A N D b ) 
D e t e r m in a t io n :
M e t h o d s 
6 0 1 0 C ,
6 0 2 0 A ,
6 2 0 0 ,
6 5 0 0 ,
6 5 0 0 ,
 6 8 0 0 ,
7 0 0 0 B ,
7 0 1 0 ,
7 1 9 5 ,
7 1 9 6 A ,
7 1 9 7 ,
7 1 9 8 ,
7 1 9 9 ,
7 4 7 0 A ,
7 4 7 1 B ,
7 4 7 2 ,
7 4 7 3 ,
7 4 7 4 .
 E n v ir o n m e n t a l
p o llu t a n t :
“ A n y 
e le m e n t ,
s u b s t a n c e ,
c o m p o u n d 
o r 
m ix t u r e ,
in c lu d in g 
d is e a s e 
c a u s in g 
a g e n t s ,
w h ic h 
a f t e r 
r e le a s e 
in t o 
t h e 
 e n v ir o n m e n t 
a n d 
u p o n 
e x p o s u r e ,
in g e s t io n ,
in h a la t io n ,
o r 
a s s im ila t io n 
in t o 
a n y 
o r g a n is m ,
e it h e r 
d ir e c t ly 
f r o m 
t h e 
e n v ir o n m e n t 
o r 
in d ir e c t ly 
b y 
 in g e s t io n 
t h r o u g h 
f o o d 
c h a in s ,
w ill
o r 
m a y 
r e a s o n a b ly 
b e 
a n t ic ip a t e d 
t o 
c a u s e 
d e a t h ,
d is e a s e ,
m a lf u n c t io n s 
( in c lu d in g 
m a lf u n c t io n s 
in 
r e p r o d u c t io n ) 
 o r 
p h y s ic a l
d e f o r m a t io n s 
in 
s u c h 
o r g a n is m s 
o r 
t h e ir 
o f f s p r in g ;
e x c e p t 
t h a t 
t h e 
t e r m … s h a ll
n o t 
in c lu d e 
p e t r o le u m … [ o r ] 
n a t u r a l
g a s ,
liq u e f ie d 
n a t u r a l
 g a s ,
o r 
s y n t h e t ic 
g a s 
o r 
p ip e lin e 
q u a lit y … ” B r o w n f ie ld 
s it e 
= 
a 
p a r c e l
o f 
la n d 
t h a t 
c o n t a in s 
o r 
c o n t a in e d 
a b a n d o n e d 
o r 
u n d e r u t iliz e d 
c o m m e r c ia l
o r 
 in d u s t r ia l
f a c ilit ie s 
E S A 
p h a s e 
1 :
r e d u c e s 
lia b ilit y 
f o r 
a 
s it e 
c le a n u p ‐ A 
v is u a l
in s p e c t io n 
o f 
t h e 
p r o p e r t y ,
in c lu d in g 
w a lk in g 
o v e r 
t h e 
e n t ir e 
s it e ,
id e a lly 
 w it h 
t h e 
o w n e r / m a n a g e r / u s e r 
p r e s e n t 
t o 
a n s w e r 
q u e s t io n s .‐ 
A 
c o m p r e h e n s iv e 
p h o t o g r a p h ic 
lo g 
In t e r v ie w s 
w it h 
t h e 
o w n e r / m a n a g e r / u s e r 
o f 
a ll
 a d ja c e n t 
p r o p e r t ie s .
‐ A 
t h o r o u g h 
r e v ie w 
o f 
a ll
" p r a c t ic a lly 
r e v ie w a b le " 
r e c o r d s 
p e r t a in in g 
t o 
t h e 
p r o p e r t y 
a n d 
s u r r o u n d in g 
p r o p e r t ie s 
w it h in 
A S T M 
 r a d ii. 
‐ A 
c o m p r e h e n s iv e 
w r it t e n 
r e p o r t .
P h a s e 
2 :
t h e 
p h y s ic a l
s a m p lin g 
o f 
t h e 
s it e 
a n d 
c o m p r e h e n s iv e 
w r it t e n 
r e p o r t 
d e t a ilin g 
r a t io n a l,
p r o t o c o ls ,
 e x p la n a tio n .
 D e v e lo p in g 
s a m p lin g 
p r o t o c o l:
… t h e 
u s e r 
m u s t 
f ir s t 
s p e c if y 
t h e 
d a t a 
h e 
n e e d s ;
t h e n 
t h e 
d e g r e e 
o f 
q u a lit y 
c o n t r o l
n e c e s s a r y 
t o 
a s s u r e 
t h a t 
t h e 
 r e s u lt a n t 
d a t a 
s a t is f y 
h is 
s p e c if ic a t io n s 
m u s t 
b e 
d e t e r m in e d ” :
S t a g e 
1 :
id e n t if y 
d e c is io n 
t y p e s .
s t a g e 
2 :
id e n t if y 
d a t a 
u s e s / n e e d s .
S t a g e 
3 :
d e s ig n 
d a t a 
 c o lle c t io n 
p r o g r a m 
 F ie ld 
b la n k s :
D e t e c t s 
s a m p le 
c o n t a m in a t io n 
d u e 
t o 
s a m p lin g 
p r o c e d u r e s 
a n d 
t r a n s p o r t 
c o n d it io n s 
( H P L C ‐ g r a d e 
c a r b o n 
f r e e 
w a t e r 
f o r 
o r g a n ic s ,
 d e io n iz e d 
w a t e r 
f o r 
in o r g a n ic s ,
c e r t if ie d 
c le a n 
s a n d 
o r 
s o il) ,
H o w :A 
b la n k 
s a m p le 
t h a t 
u n d e r g o e s 
t h e 
f u ll
h a n d lin g 
a n d 
s h ip p in g 
p r o c e s s 
o f 
a n 
a c t u a l
 s a m p le 
O n e 
f ie ld 
b la n k 
p e r 
d a y . 
T r ip 
(t r a v e l)
b la n k s 
( V O C ’s 
O N L Y ) :
c o n t a m in a t io n 
d u e 
t o 
t r a v e l
c o n d it io n s ,
H o w :
P r e p a r e d 
in 
t h e 
la b 
p r io r 
t o 
le a v in g ;
 s a m p le 
is 
c a r r ie d 
t o 
a n d 
f r o m 
t h e 
s a m p lin g 
s it e .
O n e 
t r ip 
b la n k 
p e r 
s h ip m e n t ;
if 
m o r e 
s t o r a g e 
c o n t a in e r s 
a r e 
u s e d 
t h e n 
a ls o 
o n e 
p e r 
c o n t a in e r .
F ie ld 
 r e p lic a t e 
s a m p le s 
( d u p lic a t e 
o r 
s p lit 
s a m p le s ) :
H e t e r o g e n e it y 
a s s o c ia t e d 
w it h 
s a m p lin g 
a n d 
H a n d lin g 
H o w :
S a m p le s 
o b t a in e d 
f r o m 
o n e 
s a m p lin g 
 p o in t 
a r e 
h o m o g e n iz e d ,
d iv id e d 
in 
d if f e r e n t 
c o n t a in e r s 
a n d 
t r e a t e d 
a s 
in d iv id u a l
s a m p le s . 
C o llo c a t e d 
s a m p le s :
A s s e s s e s 
lo c a l
v a r ia b ilit y 
H o w :
 N u m b e r 
o f 
s a m p le s 
t o 
b e 
d e t e r m in e d 
o n 
a 
s t a b ly ‐ 
s it e 
b a s is 
C o lle c t e d 
n e a r 
e a c h 
o t h e r .
B a c k g r o u n d 
s a m p le s :

E .g .
u p s t r e a m 
f r o m 
c o n t a m in a t io n 
 s o u r c e .
R e f e r e n c e 
s a m p le s :
C o lle c t e d 
f r o m 
a n 
a r e a 
o u t s id e 
o f 
t h e 
t e s t 
 a r e a 
( e .g .
b io lo g ic a l
s a m p le s ) .
S p ik e d 
s a m p le / m a t r ix 
s p ik e :
A d d in g 
a 
s m a ll
q u a n t it y 
o f 
a 
k n o w n 
c o n c e n t r a t io n 
o f 
t h e 
a n a ly t e 
t o 
t h e 
m a t r ix .
S u r r o g a t e 
 S p ik e :
S u r r o g a t e s 
a r e 
o r g a n ic 
n o n ‐ t a r g e t 
c o m p o u n d s 
s im ila r 
t o 
t h e 
a n a ly t ic 
o f 
in t e r e s t 
in 
c o m p o s it io n ,
e x t r a c t io n 
a n d 
c h r o m a t o g r a p h y 
b u t 
n o t 
 n o r m a lly 
f o u n d 
in 
t h e 
e n v ir o n m e n t 
A r e 
u s e d 
t o 
t r a c e 
o r g a n ic 
d e t e r m in a t io n 
m e t h o d ( G C ,
G C / M S ,
H P L C ) 
U s e d 
t o 
a s s e s 
r e t e n t io n 
t im e s ,
% 
r e c o v e r y ,
 a n d 
m e t h o d 
p e r f o r m a n c e 
H o w :
S p ik e d 
in t o 
a ll
b la n k s ,
s a m p le s 
a n d 
s p ik e d 
s a m p le s 
p r io r 
t o 
p u r g in g 
o r 
e x t r a c t io n .
R e a g e n t 
b la n k s :
D e t e c t io n 
o f 
f a ls e 
 p o s it iv e s 
H o w :
A n a ly t ic 
f r e e 
w a t e r / m a t r ix 
W h y :
C a r r y o v e r 
c o n t a m in a t io n 
H o w :
R u n 
in 
b e t w e e n 
s a m p le s 
( S p e c if ic 
c a s e 
‐ 
in s t r u m e n t 
b la n k s ) .
R e a g e n t 
 w a t e r 
s p ik e s :
M o n it o r 
t h e 
e f f e c t iv e n e s s 
o f 
t h e 
m e t h o d 
H o w :
A n a ly t e 
f r e e 
w a t e r 
s p ik e d 
w it h 
a 
k n o w n 
a m o u n t 
o f 
a n a ly t e .
P e r f o r m a n c e 
 e v a lu a t io n (P E )
/ la b o r a t o r y 
c o n t r o l
s a m p le s 
(L C S ):
P r o v id e 
a 
m e a s u r e 
o f 
t h e 
la b o r a t o r y 
e r r o r 
H o w :
P E 
‐ 
p r e p a r e d 
b y 
a 
t h ir d 
p a r t y 
– 
c o n c e n t r a t io n 
 u n k n o w n 
t o 
t h e 
la b 
L C S 
‐ 
p r e p a r e d 
b y 
t h e 
la b 
– 
c o n c e n t r a t io n 
k n o w n 
t o 
t h e 
la b .
L a b o r a t o r y 
d u p lic a t e s :
E v a lu a t e 
a n a ly t ic a l
p r e c is io n 
 T e c h n ic ia n / e q u ip m e n t 
e r r o r 
P o o r 
s a m p le 
h o m o g e n iz a t io n 
in 
t h e 
f ie ld 
H o w :
A liq u o t s 
o f 
t h e 
s a m e 
s a m p le 
a n a ly z e d 
a t 
t h e 
s a m e 
t im e .
R e f e r e n c e 
 m a t e r ia ls :
V a lid a t io n 
o f 
t h e 
a n a ly t ic a l
s y s t e m 
a n d 
p e r f o r m a n c e 
o f 
t h e 
a n a ly s t 
H o w :
B lin d 
Q C 
s a m p le s 
‐ 
u s u a lly 
p u r c h a s e d 
w it h 
a 
k n o w n 
c o n c .
 C a lib r a t io n 
S t a n d a r d s :
T o 
o b t a in 
c a lib r a t io n 
c u r v e s 
H o w :
S p e c ia l
c a s e 
‐ 
In t e r n a l
s t a n d a r d s 
‐ 
a d d e d 
t o 
a ll
s t a n d a r d s ,
Q C 
s a m p le s ,
a n d 
a ll
o t h e r 
s a m p le s 
 N o t 
n o r m a lly 
f o u n d 
in 
t h e 
s a m p le 
D o e s 
n o t 
in t e r f e r e 
w it h 
t h e 
a n a ly t ic .
Q C 
c h e c k 
s t a n d a r d s :
V e r if y 
c a lib r a t io n 
s t a n d a r d s 
a c c u r a c y 
a n d 
c o n f ir m 
 c a lib r a t io n 
c u r v e s 
H o w :
S t a n d a r d 
s o lu t io n s 
w it h 
k n o w n 
c o n c .
p u r c h a s e d 
o r 
o b t a in e d 
f r o m 
a 
s o u r c e 
in d e p e n d e n t 
f r o m 
t h e 
c a lib r a t io n 
s t a n d a r d s 
± 1 0 % 
 e r r o r 
a c c e p t a b le 
 
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7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Environmental sampling and analysis planning Sampling and analysis is done to determine how much pollutant enters into the environment, to measure ambient background concentration and to study the fate and transport of contaminants. Each sampler and analyst should be aware of the information about the sampling and analysis planning. The data quality depends on the good work of both sampler and analyst. During data acquisition process, errors can occur through out the process which is divided into sampling error and analytical error. These errors can be minimized through the proper design and implementation of quality programs such as quality control (QC) and quality assurance (QA). QC is generally a system of technical activities aimed at controlling the quality of data. QA is a management system that ensures the QC is working as intended. There is no any rule regarding the quantity/ frequency of sampling. The best sample number is the largest number possible. But the quantity should not be increased at the expense of quality. The Stockholm convention, signed by more than 90 countries in Sweden in may 2001, listed 12 key persistent organic pollutants (Pops). In USA, EPA administrates all the environmental regulations. FIFRA, TSCA, FDCA and OSHA are the other environmental regulations governing the protocols of sampling and analysis. The U.S. EPA published 129 priority pollutants (organic-114 and inorganic-15) in water. The data quality indicators (DQI) (Precision, Accuracy, Representativeness, Comparability and completeness) enable us to determine the validity of environmental data. Both accuracy and precision are needed to determine the data quality in a quantitative way. The U.S. EPA defines Method detection limit (MDL) and Practical quantitation limit (PQL), secondary DQIs, which defines the lowest concentration that can be accurately measured during the routine laboratory analysis. The use of descriptive statistics is important in sampling and analysis process when consider a large data set. Data from populations or samples can be characterized by two important descriptive statistics; the center (the central tendency) and variation (dispersion) of the data. The central tendency is measured by 3 general methods; the mean, the median and the mode. Three common methods of describing the dispersion are variance, standard deviation and range. For small sample size (n<30) student’s t distribution can be used. It is identical to normal distribution when n is large (n ∞). Mathematical equation for the t-distribution is given in the appendix. It also can be used to calculate the confidence interval. To compare the dispersion of two distributions F-distribution can be used. There are many statistical tests to identify the outliers of the data set. The incorrect data find out by outliers can be replaced by re-doing sampling or the mistake can be corrected and correct value can be inserted. Sampling approaches are commonly used in environmental data collection defining where and when to collect samples. One of the sampling approaches has to be selected among judgmental sampling, simple random sampling, stratified random sampling, systematic sampling, composite sampling and search sampling using the prior information on the sampling site. QA and QC help us to produce data of a known quality and enhance the credibility of reported results. Field QC/QA samples are categorized as Equipment (rinsate) blank, Field blanks, Trip blanks (For VOC’s only), Field replicate samples (duplicate or split samples), Collocated samples, Background samples and Reference samples. Analytical(Laboratory) QA/QC samples are classified as Reagent blanks, Reagent water spikes, Performance evaluation(PE)/laboratory control samples (LCS), Matrix spikes and matrix spike duplicates (MS/MSD’s), Laboratory duplicates, Reference materials, Calibration Standards and QC check standards. Additional concerns for sediment sampling include factors that affect sample representativeness, such as waterway width, flow and bottom characteristics. Coarser grain sediments are found near the head waters of the reservoir, while bed sediments are composed of fine-grained materials that have elevated contaminant concentrations. Contaminant tend to concentrate in the fine grained sediment in depositional zones. Samples are collected in nozzles for sediment sampling. Isokinetical flow should be inside the nozzle and it should reach maximum depth of 0.3 ft above stream bed. Lowering and raising velocity should be near to 0.4 times mean velocity. Either EDI(Equal Discharge Increment) or EWI(Equal Width Increment) methods can be used for sediment sampling. There are some methodologies, procedures and techniques for performing an environmental sampling (Regulatory method and Consensus methods). OAQPS (Office of Air Quality Planning and Standards), OW (Office of Water), OSW (Office of Solid Waste) are some of the USEPA methods. There are some other methods for workplace/indoor, The National Institute for Occupational Safety and Health (NIOSH) and Occupational Health and Safety Administration(OHSA). Air test methods (Clean Air Act), water test methods (The Federal Water Pollution Control Act and The Safe Drinking Water Act), waste test methods SW-846 (Solid Waste Disposal Act, Resource Recovery Act), APHA (American Public Health Association) method - “Standard Methods for the Examination of Water and Wastewater” are some of other methods defined by U.S. EPA. Appendix (1)Concentration units in Environmental reporting 1. Chemicals in liquid: 1mg/L = 1 ppm, 1 µg/L = 1 ppb, 1 ng/L = 1 ppt (for fresh water) (for liquid other than water) 2. Chemicals in solids: 1 mg/kg = 1 ppm, 1 µg/kg = 1 ppb, 1 ng/kg = 1 ppt 3. Chemicals in gaseous samples: ppm = x x (in standard conditions) ppm = (in standard conditions) (2) % Recovery = 100 x analytical value / true value % Recovery on spike = (Spiked sample value – sample value) / spiked value RSD (Relative standard deviation) = s/ x 100 = CV x 100 CV – Coefficient of Variation (3) Method Detection Limit (MDL) = s x t s – Standard deviation t – Student’s t value (4) Use of descriptive statistics: Sample mean, = S2 = , s =√s2 Population Variance σ 2 = , σ =√ σ 2 Sample variance, Confidence interval , CI = ± tn-1 To compare the dispersion of two distributions: F= s12/ s22 
 
 
 
 
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8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Crib Sheet – Environ. S&A: ID risk, likelihood of occurrence, impact of, risk mgmt, communication of risks Risk Assessment: 1. ID 2. Probability of contamination 3. Consequences Sources of Error: sampling(Determinate/Systematic or Indeterminate/Random) and/or analytical protocol, bad lab practice, falsification *For Sample to be Legally Defensible-chain of custody, documentation, paper-trail/traceability *Representativeness of sample = essential, otherwise sample is irrelevant Quality Control: ensure data meets user needs Quality Assurance: checks that QC is working 7 Steps of a Sample’s Life: 1. Planning 2. ID Sampling Pt. 3. Collection 4. Transport 5. Analysis 6. Discard 7. Data Pt. Concentration Units: Chems in Liquid-mass/vol incl ppb & ppm etc (direct conversion for water); Chems in Solids-mass/mass; Chems in Gas-mg/m3 = ppm x MW/24.5 (@ STP) ppm = Vm/MW x gas(ug)/air(L) @ non-STP, sub Vn(= Rx T/P) for Vm Data Quality Indicators: Accuracy- degree of agreement btwn measured & expected values % Recovery – analytical value x (100/true value) Precision- degree of agreement btwn multiple measurements % Recovery on Spike(for method calibration)- diff btwn values/spiked value Detection Limit- min concentration that can be picked up w/ 99% conf. (MDL = SD from spiked matrix x Student t) Practical Quantitation Limit- lowest conc that can be achieved w/ precision & accuracy during routine operation PARCC Measures of Cnetral Tendency: -Population Mean(µ), sample mean(x-bar) for non-skewed data; -Geometric mean for skewed data; Median(x-tilde), Mode, Measures of Dispersion: Population variance (σ2), sample variance (s2); SD; Range; IQR Transforming Data to Log Scale: y = (e.5(x-µ/σ)^2^)/(σ x sqrt(2π)) Normalization of Curve: z = x - xbar/s Normal Curve Percentiles: 86-95-99.7 Student’s t: (xbar-µ)/(s/sqrt n) CI: xbar +/- t x (s/sqrt n) F-Distr: *bigger s divided by smaller s; shows whether diff. in variances is significantif F-value is bigger than F critical from table Type I Error- reject null hypothesis when it’s true (α) Type II Error- accept null hypothesis when it’s false (β) Outliers- due to errors mentioned in Lec.1 or spatial/temporal variations of practical importance; affect mean and SD; if z-score > 3, generally considered outlier; can also use modified z, Grubb’s test, Dixon’s test 7 Steps of Sampling: 1. Understand S&A plan 2. Prepare equip. & supplies 3. ID sampling pts 4. Collect field & QA/QC samples 5. Complete field documents 6. Package samples 7. Ship samples to lab Data Quality Objectives: define appropriate data type, tolerable error levels, quality needed to support decision; also use list of appropriate questions Basic Considerations: 1. Objectives 2. Variability 3. Cost factors 4. Nontechnical factors How many, when, where * A sampling area can be 1, 2 or 3 dimensions *Representativeness can be ‘ultimate’, ‘sampling pt’ or ‘collected sample’ representativeness Sampling Approaches: 1.Judgmental Sampling- cost saver, no randomization, can’t calculate CI’s 2.Simple Random Sampling- benchmark, simple statistics, difficult to achieve representativeness, only use w/ static systems 3.Stratified Random Sampling- homogeneous strata, more intensive sampling can target only more heterogeneous strata reduce cost and increase precision (Equal allocation = each stratum has sample # samples, Proportional allocation = sample # proportional to stratum size) 4.Systematic Sampling- grid or random, easier to manage period sampling, must make sm. enough to locate hot spot 5.Composite Samplingcost saving, only calc. mean, use when sampling cost is much lower than analysis cost 6.Transect Samplingcheaper than grid, use for large areas Methodology of QA/QC: Regulatory Method-approved by EPA for certain activities in order of operation Consensus Method-published by professional organization *Separate EPA offices for air (CAA), water (CWA), & solid wastes (RCRA) * Other agencies w/ S&A methods-NEMI, USGS, ASTM, AOAC, NIOSH, OSHA, APHA, ASA, SSSA, DOE, NOAA * Sometimes reg. and cons. methods overlap Generally Selected Methods: EPA-compliance or regulatory monitoring, USGS-water resource surveys, OSHA/NIOSH- industrial hygiene testing, AOAC- food &agriculture products *EPA is starting online system that will recommend system for cases requiring 2+ protocols QC- routine activities to control error w/ blanks & spikes can determine CI of data QA- incl. review QC data, evaluate parameters, take corrective actions, plan process *EPA funded project must have EPA approved QAPP(Quality Assurance Project Plan) before sampling starts *QA/QC required for all steps of sampling less data pts required because its better quality Sampling Error Types- 1. Analyte carry-over from sampling equip. 2. Incomplete decontamination of equipment between sampling trips 3. Cross-cont. between samples 4. Absorbtion of volatile chems from air during transportation or storage Types of QA/QC Collection Samples- 1.Equipment rinsate 2.Field blanks 3.Travel blanks 4.Field replicate samples(tests heterogeneity) 5.Collocated samples 6.Background samples(upstream) 7.Reference samples(outside test area) Analytical QA/QC From Lab- 1. Cross-cont. between glassware & chems used 2.Cont. loss from sorption or volatilization 3. Matrix interference 4.Incomplete digestion or extraction Analytical Blanks- 1.Spiked sample/matrix spike 2.Surrogate spike(organic non-target chem.) 3.Reagent blanks 4.Reagent water spikes 5.Lab control samples(from same lab)/Performance evaluation(from 3rd party) 6.Lab duplicates(eval precision) * EPA looks for 5% total samples for QA/QC – additional control samples may bring it up to 25% Environmental Site Assessment: Environmental Pollutant- substance that may cause illness or death in organism or offspring after direct or indirect exposure; doesn’t include petrol. products Parties Responsible for Cleanup- current owners, owner @time of contamination, hazardous waste generator, person who accepted substance for subsequent release *Innocent Landowner Defense- protects buyer who is inquisitive about environ. issues; ‘Due Dilligence-EPA’ ESA: Phase I- Determines environ. conditions/physical sampling Phase II- Comprehensive written report Phase III- Design & implementation of remediation ESA Phase I: 1. Identify need of client 2. Obtain info from other sources; Min. Components – Environmental setting - Historic usage of property - Regulatory agency info - Site Reconnaissance – Interviews; Contaminants from Buildings - Asbestos – Lead – PBCs – Radon – Pesticides – EM Fields Developing Data Quality Objectives: Stage 1 ID Decision Types- data users, background data, site visit & conceptual model, RI/ES objectivessee flow chart & list of RI/ES questions Stage 2 ID Data Users & Needs- sampling options, acceptance criteria, data quality needs Stage 3 Design of the Data Collection Program- QAPP:1. Title pg w/ appropriate signatures 2. TOC 3.Project Description 4.Project Organization & Responsibility 5.QA Objectives 6.Sampling Procedures 7.Sample Custody 8.Calibration Procedures & Frequency 9.Analytical Procedures 10.Data Analysis, Validation & Reporting 11.Internal Quality Control Checks 12.Performance & System Audits 13.Preventive Maintenance 14.Procedures to Assess Precision, Accuracy & Completeness 15.Corrective Actions 16.QA Reports to Mgmt Soil Sampling Measurement Concepts: Sampling unit details and assumptions-heterogeneous system, nondiscrete, distribution of contaminant, variability issues 1.Background Sampling (follow CERCLA & RCRA) 2. Preliminary Site Investigation *Type II Errors are of greater importance for 1. & 2. 3. Emergency Cleanup 4. Planned Removal & Remedial Response *Type I & Type II Errors are of equal importance for 3. & 4. 5. Monitoring 6. Research/Tech Transfer Studies 
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9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 RISK ASSESSMENT- This is the characterization of risk based on an evaluation of the evidence to estimate the likelihood and consequences of an adverse event, and the associated uncertainty. The “adverse event” can be in a chemical spill, surface runoff from a farm, septic tank failure, wastewater treatment plant failure, deposition of contaminants, natural erosion of deleterious minerals (As,U) RISK MANAGEMENT:- Refers to the analytical process used to identify risk mitigation options and evaluate these for efficacy, feasibility and impacts in order to decide or recommend the most appropriate means to mitigate risks that are found to be unacceptable as a result of risk. The uncertainty noted in the assessments of economic consequences and probabilities of contamination are also considered. Sample Variance: Standard deviation: s = Probability distribution: Student’s t test Confidence error: Probability dispersion: F-test: Judgmental sampling- Professional opinion based on prior knowledge Simple random sampling- Not haphazard! Data Quality Indicators -PARCC Precision Accuracy Representativeness Comparability Completeness The method detection limit is “the minimum concentration that can be measured and reported with 99% confidence that the analyte concentration is greater than 0” (EPA, 1984). Stratified random sampling- Divides sampling population into non-overlapping. Strata and simple random sampling is employed in each stratum. Each stratum is more homogeneous than the whole. Intensive sampling can be targeted to more heterogeneous Systematic sampling- Choose the correct grid. Small enough to detect spatial/temporal variations or hot spots. Composite sampling- Cost-saving when we are interested in the mean and the cost of sampling is significantly lower than the cost of analysis MDL = s × t Determination of minimum detection limit (MDL): Spike an analyte free matrix with the target analyte at concentration 3 to 5 times the estimated MDL. Measure the sample a minimum of 7 times. Practical Quantitation Limit is “the lowest concentration that can be reliably achieved within specified limits of precision and accuracy during routine operating conditions” (EPA, 1996). PQL~2 to 10 times > MDL Measurement of central dispersion, Mean, median and mode. Search sampling- Variation of systematic grid sampling. This is for hot spot detection. The method’s sampling grid dependent on possible size of hot spot and number of samples dependent on the allowable risk of missing the hot spot. Transect sampling- Cheaper than grid sampling. This is acceptable for waste piles, large lakes and large / liquid waste impoundments. Method = a body of procedures and techniques for performing an activity (sampling, chemical analysis, quantification etc. ), systematically presented, in the order in which they are to be executed. Methods for ambient air – http://www.epa.gov/ttn/amtic Sample mean: Median- Half of the values are above and half of the value are below median. Mode- Most frequent value in the dataset Measures of central tendency Criteria Pollutants (Reference and Equivalent Methods for particulates [TSP, PM10, PM2.5], SO2, CO, NO2, O3 and lead), TO Compendium (air toxics - hazardous air pollutants) and IO Compendium Water Test Methods- (The Federal Water Pollution Control Act and The Safe Drinking Water Act) http://www.epa.gov/waterscience/methods waste test methods- Solid Waste Disposal Act, Resource Recovery Act method commonly used is SW486 http://www.epa.gov/epawaste/hazard/testmethods/sw846/on line/index.htm Other methods- APHA, ASTM, OSHA/NIOSH, USGS, AOAC, DOE, NOAA. Quality Assurance- a management system that assures that QC is working as intended. Quality Control- a system of technical activities aimed at controlling the quality of the data so that it meets the needs of data users. CERCLA- Comprehensive Environmental Response, Compensation and Liability Act amended in 1986 with the Superfund. Amendments and Reauthorization Act. Contains regulatory mandates: • Identify and classify hazardous waste sites • Defines limits of liability • Establishes a trust fund for the management of site cleanups ESA phase I- A visual inspection of the property, including walking over the entire site, ideally with the owner/manager/user present to answer questions. A comprehensive photographic log Interviews with the owner/manager/user of all adjacent properties. A thorough review of all "practically reviewable" records pertaining to the property and surrounding properties within ASTM radii. A comprehensive written report. ESA phase II1. The physical sampling of the site, as recommended in the Phase I report (minimum guideline). 2. A comprehensive written report detailing: the rationale for the sampling that took place, the sampling protocols and procedures employed, explanation of the analytical results, [if necessary], a description of the recommended remedial action needed to restore the site to the appropriate condition for its intended use. ESA phase III- Based on a Phase II report: The design and implementation of the remediation of the site. All necessary reports and permits to achieve cleanup of the site to agree upon site specific standard. Data Quality objectives DQO - Stage 1 ID decision types 1. ID and identify data users 2. Assemble and evaluate background data 1. Background data 2. Site visit 3. Evaluate existing data 3. Develop a conceptual model of the site (see p 39) 4. Specify the RI/FS objectives (see p 41) DQO - Stage 2 Identify data uses and needs (see table on p 44) 1. Evaluate sampling options 2. Acceptance criteria 3. Data quality and quality needs 1. Detection limits 2. Precision 3. Accuracy 4. Representativeness 5. Completeness 6. Comparability DQO Stage 3- set up QAPP - Quality Assurance Project Plan – Project description – Project organization & responsibilities – Sampling procedures – Sampling custody – Calibration procedures and frequency – Analytical procedures – Data reduction/validation and reporting – Internal quality control checks and frequency – Performance and system audit and frequency – Specific routine procedures used to assess data precision, accuracy and completeness, corrective actions – QA report and management 
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 A s s ig n m e n t 8 – M id te r m C r ib S h e e t L e c t. 1 R is k a s s e s s m e n t is s p lit in to th re e in te rre la te d s te p s : 1 . c o n ta m in a n t id e n tific a tio n 2 . a s s e s s m e n t o f th e p ro b a b ility o f c o n ta m in a tio n 3 . a s s e s s m e n t o f p o te n tia l c o n s e q u e n c e s (h e a lth , e n v iro n m e n t, e c o n o m ic ). S c ie n tific re lia b ility , le g a l d e fe n s ib ility , g o o d la b p ra c tic e s , c h a in o f c u s to d y . D e te rm in a n t v . in d e te rm in a te (ra n d o m ) e rro rs . L e c t. 2 : D a ta q u a lity in d ic a to rs : % R e c o v e ry = A n a ly tic a l V a lu e * 1 0 0 /T ru e v a lu e . % R e c o v e ry o n s p ik e = S p ik e d s a m p le v a lu e -S a m p le v a lu e /S p ik e d v a lu e . P re c is io n A c c u ra c y R e p re s e n ta tiv e n e s s C o m p a ra b ility C o m p le te n e s s (P A R C C ). D e te c tio n lim it m in im u m c o n c . th a t c a n b e m e a s u re d a n d re p o rte d w ith 9 9 % c o n fid e n c e th a t th e a n a ly te c o n c e n tra tio n is g re a te r th a n 0 . Q u a n tita tio n lim it lo w e s t c o n c . th a t c a n b e re lia b ly a c h ie v e d w ith in s p e c ifie d lim its o f p re c is io n a n d a c c u ra c y d u rin g ro u tin e o p e ra tin g c o n d itio n s L e c t. 3 S ta t: E n v iro n m e n ta l d a ta g e n e ra lly s k e w e d d a ta is g e n e r a lly lo g - tr a n s f o r m e d = lo g - n o r m a l d is tr ib u tio n . 9 0 % ( 2 - s id e d ) = 9 5 % ( 1 - s id e d ) 1 - α /2 = 0 .9 5 td f = 7 , α = 0 .1 = 1 .8 9 5 C I = 6 6 ± 1 .8 9 5 x 5 /√ 8 = 6 6 ± 3 .3 5 m g /k g . T y p e I e r r o r = r e je c t H 0 w h e n H 0 is tr u e ( p r = a lp h a ) T y p e I I e r r o r = a c c e p t H 0 w h e n H 0 is f a ls e (p r= b e ta ). L e c t. 4 D Q O , S a m p lin g R e p re s e n ta tiv e n e s s S te p 1 . U n d e rs ta n d in g S a m p lin g a n d A n a ly s is P la n S te p 2 . P re p a rin g E q u ip m e n t a n d S u p p lie s S te p 4 . C o lle c tin g fie ld a n d Q A /Q C s a m p le s S te p 3 . Id e n tify in g S a m p lin g P o in ts S te p 5 . C o m p le tin g F ie ld D o c u m e n ta tio n S te p 6 . P a c k a g in g S a m p le s S te p 7 . S h ip p in g S a m p le s to L a b o ra to ry . S a m p lin g a p p ro a c h e s : J u d g m e n ta l, S im p le ra n d o m , S tra tifie d ra n d o m , S y s te m a tic C o m p o s ite , S e a rc h , A d a p tiv e c lu s te r, R a n k e d s e t, T ra n s e c t. L e c t . 5 .E P A M e th o d s O W (O ffic e o f W a te r) O A Q P S (O ffic e o f A ir Q u a lity P la n n in g a n d S ta n d a rd s ) O S W (O ffic e o f S o lid W a s te )S W -8 4 6 (S o lid W a s te D is p o s a l A c t, R e s o u rc e R e c o v e ry A c t) to x ic ity c h a ra c te ris tic s le a c h in g p ro c e d u re s (T C L P ) - M e th o d 1 3 1 1 m o s t Im p o rta n t R e g u la to ry m e th o d = a p p r o v e d b y th e U .S . E P A a n d a r e m a n d a to r y u n d e r a c e r ta in p r o g r a m o r la w – C o n s e n s u s m e th o d s = p u b lis h e d b y p r o f e s s io n a l o r g a n iz a tio n s s u c h a s A S T M ( A m e r ic a n S o c ie ty o f T e s tin g M a te r ia ls ) , U S G S ( U .S . G e o lo g ic a l S u r v e y ) , A O A C A s s o c ia tio n o f O ffic ia l A n a ly tic a l C h e m is ts a k a . A s s o c ia tio n o f A n a ly tic a l C o m m u n itie s ). – U S G S - fo r w a te r re s o u rc e s s u rv e y s – O S H A /N I O S H - f o r in d u s tr ia l h y g ie n e te s tin g – A O A C - f o r f o o d a n d a g r ic u ltu r a l p r o d u c ts S V O C ’ s a r e e x tr a c te d n o t p u r g e d ( i.e . m e th y le n e c h lo rid e C H 2 C l2 ): M e th y le n e c h lo rid e e x tra c tio n = n e u tra l fra c tio n (P A H ’s , e th e rs , d i- a n d tri- h a lo b e n z e n e , p h ta la te s ) E x tra c t a c id ifie d to p H = 2 a n d s e c o n d a rily e x tra c te d w ith m e th y le n e c h lo rid e a c id fra c tio n (p h e n o lic c o m p o u n d s : p h e n o l, h a lo g e n a te d p h e n o ls , n itro p h e n o ls ) E P A 5 0 0 , 6 0 0 a n d 8 0 0 0 s e rie s (n o te E P A 6 2 5 fo r S V O C a n a ly s is u s in g G C -M S A P H A 6 0 0 0 U S G S O x x x x -x x V O C ’s : p u rg e d w ith a n in e rt g a s b u b b le d th ro u g h a 5 m L s a m p le = v o la tile c o m p o u n d s a re re c o v e re d in th e v a p o r p h a s e ; G C b u t n o t H P L C a n a ly s e s E P A 5 0 0 , 6 0 0 a n d 8 0 0 0 s e rie s (n o te E P A 6 2 4 fo r V O C a n a ly s is u s in g G C -M S ) A P H A 6 0 0 0 U S G S O x x x x -x x B io lo g ic a l p a ra m e te rs A P H A s e rie s (m o re c o m p le te a n d w id e ly u s e d th a t th e lim ite d E P A m e th o d s ) A P H A 8 0 0 0 s e rie s : to x ic ity te s tin g u s in g s e d im e n t p o re w a te r, a lg a e , D a p h n ia , fis h , fa th e a d m in n o w , a n d m u ta g e n e s is A P H A 9 0 0 s e rie s : m ic ro b io lo g ic a l e x a m in a tio n : h e te ro tro p h ic p la te c o u n t, m ic ro b ia l c o u n t, E . c o li a n d to ta l c o lifo rm s A P H A 1 0 0 0 0 s e rie s : b io lo g ic a l e x a m in a tio n : P e rip h y to n , m a c ro p h y to n , b e n th ic m a c ro in v e rte b ra te s , A g g re g a te o rg a n ic a n a ly s e s C O D , B O D , T O C , to ta l re c o v e ra b le p e tro le u m h y d ro c a rb o n s (T R P H ), a n io n ic s u rfa c ta n ts , o il a n d g re a s e E P A 4 0 0 s e rie s A P H A 5 0 0 0 s e rie s U S G S O -x x x x -x x m e ta l a n a ly s e s F la m e a to m ic a d s o rp tio n G ra p h ite fu rn a c e a to m ic a d s o rb tio n In d u c tiv e ly c o u p le d p la s m a E P A s e rie s 2 0 0 a n d th e E P A S W -8 4 6 s e rie s 6 0 0 0 (IC P ) a n d 7 0 0 0 A P H A 3 0 0 s e rie s U S G S I-x x x x -x x m e th o d s P h y s ic a l: p H , s o lid s (S S , T D S , T S , V S ), te m p e ra tu re , tu rb id ity In o rg a n ic a n d n o n m e ta llic : B r, C l, C N , F , I, N , P , S , to ta l N & P , a c id ity , a lk a lin ity , D O M e a s u re m e n t m e th o d s : p o te n tio m e tric (p H ), g ra v im e tric (s o lid s ), th e rm o m e tric (te m p ), titrim e tric (a c id ity , a lk a lin ity ), m e m b ra n e e le c tro d e (D O ), io d o m e tric (W in k le r m e th o d fo r D O ) A n a ly tic a l m e th o d s fo r th e s e p a ra m e te rs a re fo u n d in E P A 1 0 0 a n d 3 0 0 s e rie s , A P H A 2 0 0 0 a n d 3 0 0 0 s e rie s , U S G S , A S T M a n d A O A C Q C = a s y s te m o f te c h n ic a l a c tiv itie s a im e d a t c o n tro llin g th e q u a lity o f th e d a ta s o th a t it m e e ts th e n e e d s o f d a ta u s e rs Q A = a m a n a g e m e n t s y s te m th a t a s s u re s th a t Q C is w o rk in g a s in te n d e d . Q A P P - Q u a lity A s s u ra n c e P ro je c t P la n – P ro je c t d e s c rip tio n – P ro je c t o rg a n iz a tio n & re s p o n s ib ilitie s – S a m p lin g p ro c e d u re s – S a m p lin g c u s to d y – C a lib ra tio n p ro c e d u re s a n d fre q u e n c y – A n a ly tic a l p ro c e d u re s – D a ta re d u c tio n /v a lid a tio n a n d re p o rtin g – In te rn a l q u a lity c o n tro l c h e c k s a n d fre q u e n c y – P e rfo rm a n c e a n d s y s te m a u d it a n d fre q u e n c y – S p e c ific ro u tin e p ro c e d u re s u s e d to a s s e s s d a ta p re c is io n , a c c u ra c y a n d c o m p le te n e s s , c o rre c tiv e a c tio n s – Q A re p o rt a n d m a n a g e m e n t fie ld Q C /Q A s a m p le s E q u ip m e n t (rin s a te ) b la n k W h y : T e s ts c o n ta m in a tio n fro m s a m p lin g e q u ip m e n t F ie ld b la n k s W h y : D e te c ts s a m p le c o n ta m in a tio n d u e to s a m p lin g p ro c e d u re s a n d tra n s p o rt c o n d itio n s (H P L C g ra d e c a rb o n fre e w a te r fo r o rg a n ic s , d e io n iz e d w a te r fo r in o rg a n ic s , c e rtifie d c le a n s a n d o r s o il) T rip (tra v e l) b la n k s - F o r V O C ’s o n ly W h y : c o n ta m in a tio n d u e to tra v e l c o n d itio n s F ie ld re p lic a te s a m p le s (d u p lic a te o r s p lit s a m p le s ) W h y : H e te ro g e n e ity a s s o c ia te d w ith s a m p lin g a n d H a n d lin g C o llo c a te d s a m p le s W h y : A s s e s s e s lo c a l v a r ia b ility B a c k g r o u n d s a m p le s – E .g . u p s tr e a m f r o m c o n ta m in a tio n s o u r c e R e f e r e n c e s a m p le s – C o lle c te d f r o m a n a r e a o u ts id e o f th e te s t a r e a ( e .g . b io lo g ic a l s a m p le s ) A n a ly t ic a l Q A /Q C S p ik e d s a m p le /m a trix s p ik e - A d d in g a s m a ll q u a n tity o f a k n o w n c o n c e n tra tio n o f th e a n a ly te to th e M a trix C 1 V 1 = C 2 V 2 V 1 = C 2 V 2 /C 1 C 1 = c o n c . o f th e s to c k s o lu tio n V 1 = v o l. o f th e s to c k s o lu tio n to b e c a lc u la te d C 2 = d e s ire d s p ik e c o n c e n tra tio n V 2 = v o l. o f th e s a m p le to b e s p ik e d S u rro g a te S p ik e W h y : S u rro g a te s a re o rg a n ic n o n -ta rg e t c o m p o u n d s s im ila r to th e a n a ly te o f in te re s t in c o m p o s itio n , e x tra c tio n a n d c h ro m a to g ra p h y b u t n o t n o rm a lly fo u n d in th e e n v iro n m e n t A re u s e d to tra c e o rg a n ic d e te rm in a tio n m e th o d (G C , G C /M S , H P L C ) U s e d to a s s e s re te n tio n tim e s , % re c o v e ry , a n d m e th o d p e rfo rm a n c e d u r in g a n a ly s is R e a g e n t b la n k s W h y : D e te c tio n o f fa ls e p o s itiv e s R e a g e n t w a te r s p ik e s W h y : M o n ito r th e e ffe c tiv e n e s s o f th e m e th o d P e rfo rm a n c e E v a lu a tio n (P E )/la b o ra to ry c o n tro l s a m p le s (L C S ) W h y : P ro v id e a m e a s u re o f th e la b o ra to ry e rro r M a trix s p ik e s a n d m a trix s p ik e d u p lic a te s (M S /M S D ’s ) W h y : a c c u ra c y (% re c o v e ry ) L a b o ra to ry d u p lic a te s W h y : E v a lu a te a n a ly tic a l p re c is io n T e c h n ic ia n /e q u ip m e n t e rro r P o o r s a m p le h o m o g e n iz a tio n in th e fie ld R e fe re n c e m a te ria ls W h y : V a lid a tio n o f th e a n a ly tic a l s y s te m a n d p e rfo rm a n c e o f th e a n a ly s t C a lib ra tio n S ta n d a rd s W h y : T o o b ta in c a lib ra tio n c u rv e s Q C c h e c k s ta n d a rd s W h y : V e rify c a lib ra tio n s ta n d a rd s a c c u ra c y a n d c o n firm c a lib ra tio n c u rv e s L e c t. 6 E n v . s ite a s s e s s m e n t-P h a s e I C o m p re h e n s iv e E n v iro n m e n ta l R e s p o n s e , C o m p e n s a tio n a n d L ia b ility A c t (C E R C L A , 1 9 8 0 ) a m e n d e d in 1 9 8 6 w ith th e S u p e rfu n d A m e n d m e n ts a n d R e a u th o riz a tio n A c t. D u e d ilig e n c e - E S A P h a s e I - re d u c e s lia b ility fo r a s ite c le a n u p p re s e n c e o r lik e ly p re s e n c e o f a n y h a z a rd o u s s u b s ta n c e s o r p e tro le u m p ro d u c ts o n a p ro p e rty v is u a l in s p e c tio n o f th e p ro p e rty , in c lu d in g w a lk in g o v e r th e e n tire s ite , id e a lly w ith th e o w n e r/m a n a g e r/u s e r p re s e n t to a n s w e r q u e s tio n s . c o m p re h e n s iv e p h o to g ra p h ic lo g In te rv ie w s w ith th e o w n e r/m a n a g e r/u s e r o f a ll a d ja c e n t p ro p e rtie s . th o ro u g h r e v ie w o f a ll " p r a c tic a lly r e v ie w a b le " r e c o r d s p e r ta in in g to th e p r o p e r ty a n d s u r r o u n d in g p r o p e r tie s w ith in A S T M r a d ii.A c o m p re h e n s iv e w ritte n re p o rt. E S A - P h a s e II (e n v iro n m e n ta l p ro fe s s io n a ls / e n g in e e rs ) B a s e d o n a P h a s e I re p o rt a d v is in g a P h a s e II re p o rt: 1 . P h y s ic a l s a m p lin g o f th e s ite , a s re c o m m e n d e d in th e P h a s e I re p o rt (m in im u m g u id e lin e ). 2 . c o m p re h e n s iv e w ritte n re p o rt d e ta ilin g :th e ra tio n a le fo r th e s a m p lin g th a t to o k p la c e , th e s a m p lin g p ro to c o ls a n d p ro c e d u re s e m p lo y e d , e x p la n a tio n o f th e a n a ly tic a l re s u lts , [if n e c e s s a ry ] , a d e s c rip tio n o f th e re c o m m e n d e d re m e d ia l a c tio n n e e d e d to re s to re th e s ite to th e a p p ro p ria te c o n d itio n fo r its in te n d e d u s e . E S A - P h a s e III (e n g in e e rs / e n v iro n m e n ta l p ro fe s s io n a ls ) B a s e d o n a P h a s e II re p o rt: T h e d e s ig n a n d im p le m e n ta tio n o f th e re m e d ia tio n o f th e s ite . A ll n e c e s s a ry re p o rts a n d p e rm its to a c h ie v e c le a n u p o f th e s ite to a g re e d u p o n s ite s p e c ific s ta n d a rd s . E S A P h a s e I A s s e s s th e c lie n t’s p u rp o s e / s c o p e o f w o rk . P la n a n d o rg a n iz e b y d e v e lo p in g c h e c k lis t, s y s te m to k e e p tra c k o f th e v o lu m in o u s a m o u n t o f m a te ria l to b e g a th e re d . S c o p e o f th e w o rk : E n v iro n m e n ta l a u d it / e n v iro n m e n ta l e v a lu a tio n / p re a c q u is itio n s ite a s s e s s m e n t / re a l e s ta te e n v iro n m e n ta l s tu d y / e n v iro n m e n ta l im p a irm e n t ris k . E S A p h a s e I - m in im u m c o m p o n e n ts E S A p h a s e I m in im u m c o m p o n e n ts E n v ir o n m e n ta l s e ttin g : T o p o g r a p h y G e o lo g y H y d r o g e o lo g y G e o g r a p h ic lo c a tio n . S o il s u r v e y S o il p h y s ., c h e m . p ro p e rtie s S u b s u rfa c e g e o lo g y F lo o d a re a m a p s , S e p tic ta n k s A b a n d o n e d w e lls , L e a k y p ip e s Im p ro p e rly d is p o s e d w a s te s C e m e te rie s D e ic in g s a lt A g ric u ltu ra l d ra in a g e h o le s Im p ro p e r fa rm s to ra g e a re a s H is to ric u s a g e o f th e p ro p e rty T itle s e a rc h A t le a s t 5 0 y rs , o r a ro u n d W W IIH is to ric a l [a e ria l] p h o to g ra p h s (U S G S , U S D A , E P A )F ire in s u ra n c e m a p s (S a n b o rn m a p s )L o c a l s tre e t d ire c to ry P ro p e rty ta x re c o rd s Z o n in g R e c o rd s B u ild in g p e rm its H is to ric S a fe ty a n d h e a lth re c o rd s S ta te a n d fe d e ra l e n v iro n m e n ta l re c o rd s W a s te m a n a g e m e n t p e rm its S to rm d is c h a rg e w a te r p e rm its H a z a rd o u s m a te ria ls C h e m ic a l in v e n to ry re c o rd s , tra n s p o rt m a n ife s t, p ro c e s s flo w c h a rt, s a fe ty a n d h e a lth a u d its , p u rc h a s in g re c o rd s N e w s p a p e rs N a tu ra l re s o u rc e s re c o rd s M in in g re c o rd s O il/g a s re c o rd s . R e g u la to ry A g e n c ie s In fo : N P L - N a tio n a l P rio rity L is t H a z a rd R a n k in g S c o re :T h e c a te g o rie s u s e d fo r th e H R S a re b a s e d o n N P L in c lu d e s : In itia l re s p o n s e ; S ite s tu d ie s ; R e m e d y s e le c te d ; R e m e d y d e s ig n ; C le a n u p o n g o in g ; C o n s tru c tio n C E R C L IS C o m p re h e n s iv e E n v iro n m e n ta l R e s p o n s e C o m p e n s a tio n a n d L ia b ility In fo rm a tio n S y s te m C o n ta in s d a ta o n p o te n tia l a n d k n o w n h a z a rd o u s w a s te . H a z d a t R C R A - R e s o u rc e C o n s e rv a tio n a n d R e c o v e ry A c t (1 9 7 6 ) lis ts (R C R IS = R C R A in fo rm a tio n s y s te m ) T S D F ’s - T re a tm e n t, S to ra g e a n d D is p o s a l F a c ilitie s . G e n e ra te s > 1 0 0 0 k g o f h a z a rd o u s w a s te / c a le n d a r m o n th , O R > 1 k g o f a c u te ly h a z a r d o u s w a s te ( e .g . m a n u f a c tu r in g p la n t) S Q G - S m a ll Q u a n tity G e n e r a to r G e n e r a te s < 1 0 0 0 k g o f h a z a r d o u s w a s te / c a le n d a r m o n th , O R < 1 k g o f a c u te ly h a z a r d o u s w a s te T r a n s p o r te r s E R N S - E m e r g e n c y R e s p o n s e N o tif ic a tio n S y s te m ( i.e . s p ills ) T R I S - T o x ic R e le a s e In v e n to ry S y s te m S ta te d a ta b a s e s - U n d e rg ro u n d s to ra g e h a z a rd o u s s u b s ta n c e s u n d e r C E R C L A (n o t u n d e r R C R A M in im u m s e a rc h d is ta n c e s T y p e o f lis t R a d iu s f r o m s ite N a tio n a l p r io r ity lis t ( N P L ) 1 m ile S ta te p r io r ity lis t 1 m ile N a tio n a l a n d s ta te C E R C L I S 0 .5 m ile R C R A L is ts T r e a tm e n t, s to r a g e , a n d d is p o s a l f a c ilitie s C O R R A C T S 1 m ile N o n C O R R A C T S 0 .5 m ile E f f lu e n t a n d a ir e m is s io n s W a s te d is p o s a l te c h n iq u e s S u rfa c e w a te r T ra n s fo rm e rs S u rro u n d in g a re a u s e G e n e ra l d e s c rip tio n o f s tru c tu re s , ro a d s , lo c a tio n P re s e n c e a n d S a n ita ry s e w e rs , W a te r w e lls , D rin k in g w a te r s o u rc e s , C h e m d e b ris , In te rv ie w s . L e c t. 8 D e v e lo p in g D a ta Q u a lity O b je c tiv e s S ta g e 1 : Id e n tify D e c is io n T y p e s – ID & in v o lv e d a ta u s e rs , e v a lu a te a v a ila b le d a ta , d e v e lo p c o n c e p tu a l m o d e l, s p e c ify R I/F S o b je c tiv e s . S ta g e 2 : ID D a ta U s e s /N e e d s – ID d a ta u s e s & ty p e s , e v a lu a te s a m p lin g /a n a ly s is o p tio n s , ID d a ta q u a n tity & q u a lity n e e d s , s p e c ify P A R C C g o a ls . S ta g e 3 : D e s ig n D a ta C o lle c tio n P ro g ra m – d e s ig n p ro g ra m , d e v e lo p d a ta c o lle c tio n d o c u m e n ta tio n R I/F S S tu d y : Is a re a c o n ta m in a te d w ith h a z . C h e m ic a ls ? D is t. C h e m . O v e r s ite ? T h re a t o f im m e d ia te life -th re a te n in g e x p o s u r e ? D o m in a n t r o u te s o f s o il e x p . a t s ite ? A t c o n c . S e e n , m in . s iz e a r e a p o s in g r is k to e n v . O r s u r r . P o p .? A r e a s tr e a te d to r e d u c e ris k to a c c e p ta b le ? R e m e d ie s to c le a n u p s o il? V o l. m a te ria l to b e tre a te d ? S o u rc e o f p o llu ta n ts ? O th e r s o u rc e s w h e re c h e m c o u ld h a v e m ig ra te d ? 
 
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 Environmental Sampling and Analysis (Crib sheet) Objectives – Determine pollutant entering into environment, asses’ degree of pollution & identify trends, detect accidental releases & evaluate the risk and toxicity, study the fate and transport of contaminants& efficiency of remediation techniques. Important terms: Hazard Identification, Risk Assessment- split into 3 steps1.Contamination identification, 2. Assessment of the probability of contamination, 3. Assessment of potential consequences. , Risk management and communication, QC- system of technical activities aimed at controlling the quality of the data. QA- management system that assures QC is working as intended. Concentration Units: 1mg/L= 1ppm= 10-6, 1µg/L = 1ppb = 10-9,1ng/L = 1ppt = 10-12 Liquids other than water = (1ppm = 1mg contaminant/1kg.liquid) = (1/ρ)*(1mg contaminant/1L liquid). Wet basis vs dry basis = mg/kg of dry basis = mg/kg on wet basis/ (1-%moisture) mg/L = ppm * MW/24.5, ppm = 24.5 mg/m3/M.W (@ STP) Chemicals in gaseous samples@ STP ppm = Vm /M.W *gas (µg)/air (L) Vm – Standard molar vol of ideal gas @ STP (22.711mg/L),M.W- molecular weight of gas(g/mol). In molar terms1ppm = 1µmole gas/1 mole air = (Vm/M.W)*(gas (µg)/air (L)) Chemicals in gaseous samples @ non-STP Vn= V/n = R*(T/P) Vn – specific molar volume of ideal gas @ Pressure P and temp T (L/mol) V – volume of the gas(L), n- no of molecules (mol), R- universal gas const 8.314JK-1mol1 or m3Pak-1mol-1, T- Temperature K, P-Pressure Pa. Data Quality Indicator’s: Precision, Accuracy, Representativeness, Comparability, Completeness. Secondary DQI’s Detection limit and Quantitation Limit. MDL- Minimum concentration that can be measured and reported with 99% confidence that the analyte concentration is greater than 0. MDL = s*t , s- stdev, t = t0.98 ,df=n-1 Practical Quant. Limit: lowest conc that can be reliably achieved within specified limits of precision and accuracy during routine operating conditions. PQL~ 2to 10times> MDL % Recovery = Analytical value *100/True value. % recovery on spike = (Spike sample value- Sample value)/Spiked value. Seven steps of sampling: 1.Understanding sampling and Analysis plan, 2.Preparing Equipment & supplies, 3.Identifying Sampling points,4. Collecting field and QA/QC samples. 5. Completing field documentation, 6.Packaging Samples, 7.Shipping Samples to laboratory Data Quality objecitves – 19 Question’s Sampling representativenessUltimate representativeness, Sampling point representativeness, collected sample representativeness. Sampling approaches- Judgmental sampling, Simple random sampling, stratified random sampling, Systematic sampling, Composite sampling, Search sampling, Adaptive cluster sampling, Ranked set sampling. USEPA methods OAQPS – Office of air quality planning and Standards OW office of water OSW –Office of solid waste. Air test methods (clean air act) Stationary sources Cat A, B, C, D Workplace/indoor: The national institute for occupational safety & Health (NIOSH), Occupational Health & Safety Administration (OSHA). Water test methods – The federal water Pollutional Control Act & the safe drinking water act. Waste test methods – SW-846;Solid waste disposal act; Resource Recovery act. Others ASTM,APHA,Standard methods for the examination of water and wastewater. Soil methods- “methods of analysis”. Published by ASA & SSSA. Brownfield site: piece of land abandoned due to contamination and further development is complicated by the potential hazardous substances. CERCLA – Comprehensive Environmental Response, Compensation and Liability Act (CERCLA, 1980) - identify and classify hazardous waste sites, defines liability limits. Establish trust fund for management of site cleanups. ESA phase I Main components– Environmental setting, Historic records review, Review of the hazardous building materials, site and area reconnaissance, A regulatory agency review, Interviews. Hazard Ranking score: HRS > 25 or 30 site added to NPL. Categories used for the HRS based on points given for : Likelihood of release; Waste characteristics; Environmental threat. Suspended samples used for reservoir design, maintenance, channel dredging, total max daily load, dam alluvial stream restoration, contaminant transport in the solid phase. Sediment load – total mass passed for a given time period; 2 types suspended & bed load. Collecting samples – Isokinetic flow into the nozzle. Nozzle should reach max depth (0.3 foot above the bed). Water enters nozzle slower than ambient velocitysample conc is greater that ambient due to inertia; water enters faster lower concentration enters the nozzle. Sampler’s naming – DH depth integrating Handheld; number indicates year; P point integrating. Sampler characteristics: Color coded to match he nozzle and body. Bag samplers used for depth greater than 15 feet. Why isokinetic flow pressure inside the sample to equate with pressure outside. Bag samples created to overcome depth compression limit. 2 methods used to sample cross section of streams; Equal discharge Increment and Equal width increment. EDI: Equal increments of discharge, samples collected at centroids; transit can be varied at each vertical, requires knowledge of distribution of stream flow across channel. EWI: equal width, samples collected at Centre, Samples replaced when full, knowledge of flow distribution not required. Less time required is less. 
 
 
 
 
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 *Accuracy- Degree of closeness to the actual “true” value. *Precision- the degree to which several measurements provide answers very close to each other. It is an indicator of the scatter in the data. The lesser the scatter, higher the precision. Determinate (systematic) errors - can usually be traced to a technician or equipment and are usually discarded Indeterminate (random errors) - hard to track down and eliminate - random errors are usually identified by using statistical tools. Sample Statistical Significant difference at % CI. F Calculated = where S1>S2. F Critical at % . CI. dfA= nA-1=Denominator degrees of freedom and dfB=nB-1=Numerator degrees of freedom. F Calculated < F Critical =>Accept Null Hypothesis. If opposite Reject Null. *(St. Dev.) * *Calculating Confidence Intervals: CI= * Normal Distribution: z = Population. {Normalizing X) *Coefficient of Variation: CV = Precision, not accuracy) *T-Test: t = For a * RSD=CVx100% {Measure of For sample size less than or equal to 30 *Sampling and Analysis: I. Hazard Identification II. Risk Assessment (Potential Consequences) III. Risk Management IV. Risk Communication Regulatory overview and action levels QC = a system of technical activities aimed at controlling the quality of the data so that it meets the needs of data users QA = a management system that assures that QC is working as intended. *Chain of custody : Sample number Signature of collector Date and time of sample collection Place and address of sample collection Sample type (water, soil, air, etc.) Signature of persons involved in the The The seven steps of sampling chain of possession Inclusive dates of possession Step 1. Understanding Sampling Chemicals in gaseous samples mg/m3 = ppm × MW /24.5 and Analysis Plan 1 mg/m3 ≠ 1ppmv = 1ml/L = 10-6 ppm = mg/m3 × 24.5 /MW Step 2. Preparing Equipment and 1µg/m3 ≠ 1ppbv = 1µL/L = 10-9 Note : valid for standard Supplies conditions (25°C, 1atm) 1ng/m3 ≠ 1pptv = 1nL/L = 10-12 Sampling approaches Judgmental sampling Simple random sampling Stratified random sampling Systematic sampling *Judgmental: using prior information on the sampling site. For emergency spill response and tight budget. *Stratified: ‘‘Strata’’ could be ‘‘temporal’’ or ‘‘spatial.’’ Temporal strata permit different samples to be selected for specified time periods *Systematic: extrapolation from the same period to future periods is easier with a systematic sample; (b) seasonal cycles can be easily identified and accounted for in the data analysis *Composite: the goal is to estimate the average concentration rather than the variability Weight of a Sample: Step 4. Collecting field and QA/QC samples Step 3. Identifying Sampling Points Step 5. Completing Field Documentation Sampling Sampling Representativeness! Ultimate representativeness How well the project design represents a characteristics of a population and the environmental conditions at the site (sampling and analysis design) Sampling point representativeness How well a sample represents the characteristics of a sampling point Collected sample representativeness How well a subsample represents a collected sample How How many samples?! samples?! n f(project goal) f(s) f(cost) f(tolerable error) Method Method = a body of procedures and techniques for performing an activity (sampling, chemical analysis, quantifiation…),systematically presented, in the order in which they are to be executed. – Regulatory method = approved by the U.S. EPA and are mandatory under a certain program or law – Consensus methods = published by professional organizations such as ASTM (American Society of Testing Materials), USGS (U.S. Geological Survey), AOAC SW-846 for sludge matrix. Method 1311 to see if industrial wastewater sludge for Cd, Hg, and Cr would pose leaching Lab QC Samples: a. b. c. d. e. To determine the effect of matrix interferences on analytical accuracy of a sample Matrix Spikes & Matrix Spike Duplicates; used to obtain percentage recovery recovery and therefore accuracy To determine the analytical precision of a sample batch Laboratory Duplicates; used to determine analytical precision To determine whether memory (carryover) effects are present in an analytical run with an instrument. Instrument Blanks; used to determine whether memory effect (carry over) over) are present in system To establish that laboratory contamination does not cause false positives Blanks/Method Preparation Blanks/Method Blanks; used to detect any contamination (false (false positives) To know whether an extraction procedure is appropriate or not. Surrogate Spikes; used to assess method performance STARTING
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 information relevant to sampling and analysis planning. The data life cycle comprises three steps: planning, implementation, and assessment. Planning: the Data Quality Objectives (DQO) Process (or any other systematic planning procedure) is used to define criteria for determining the number, location, and timing of samples to be collected in order to produce a result with the desired level of certainty. This,along with the sampling methods, analytical procedures, and appropriate quality assurance (QA) and quality control (QC) procedures, is documented in the QA Project Plan. DQA involves five steps that begin with a review of the planning documentation and end with an answer to the question posed during the planning phase of the study. These steps roughly parallel the actions of an environmental statistician when analyzing a set of data. The five steps, are: 1. Review the project objectives and sampling design. 2. Conduct a preliminary data review. 3. Select the statistical method. 4. Verify the assumptions of the statistical method. 5. Draw conclusions from the data-------------------------------------------------------------------------------------------------------------Sampling/ Sampling-Design include PARCC: Precision, Accuracy, Representativeness, Comparability, Completeness. Representativeness is addressed through the sampling design: may be considered as the measure of the degree to which data accurately and precisely represent a characteristic of a population, parameter variations at a sampling point, a process condition, or an environmental condition (ANSI/ASQC 1994).A complete sampling design indicates the number of samples and identifies the particular samples (for example, the geographic positions where samples will be collected or the time points when samples collected). Along with this information, a complete sampling design will include explanation/ justification for number and positions/timings of samples. Probability-based sampling designs apply sampling theory and involve random selection of sampling units. Judgmental sampling designs involve the selection of sampling units on the basis of expert knowledge or professional subjective judgment. TYPES OF SAMPLING DESIGNS Judgmental Sampling // Simple Random Sampling, Stratified Sampling Systematic and Grid Sampling, Ranked Set Sampling, Adaptive Cluster Sampling Composite Sampling. DQO. The DQO Process is a seven-step planning approach based on the scientific method that is used to prepare for data collection activities such as environmental monitoring efforts and research. It provides the criteria that a sampling design should should satisfy, where to collect samples; tolerable decision error rates and the number of samples to collect.(see fig right) QA/QC: basically is first QC, then QA(see table below) Remember: there is field (sampling) QA/QC and there is its lab (analysis) QA/QC, which follows correspondingly.Both must be performed. This also makes up EPA methods in a double set of methods (each EPA method for one sampling has a co-respective method for its analysis) --------------------------------------------------------------------------------------------------------Statistics: Criteria for QA/QC procedure: Sampling protocol: Specify needed data. Specify degree of QC needed to satisfy specs. Specify PARCC goals .Specify DOQ (type of analysis needed): Chemical (metals, VOCs, SVOCs, etc) Physical (density, particle size, material composition, etc) Biological (microrganisms) Vapors.In addition, (EPA required) QAPP: (quality assurance project plan: must contain 16 issue elements. Specific for Soil sampling Data acquisition Flows; Data Monitoring Flows; Tech Data Transfer Flows(flow charts) --------------------------------------------------------------------------------------------------------------------------------------------------------------# of SAMPLES: When variance and acceptable error are known: ---------------------------------------------------------------------------------------------------------------------------------Chemistry: most common contaminants: Main Environmental Laws: Occupational Safety Health Act (1970) OSHA Clean Water Act(1972)CWA Hazardous Material Transportation Act (1975)HMTA Resource Conservation & Recovery Act ( 1976)RCRA Comprehensive Environmental Response Compensation and Liability Act(1980) CERCLA also called Superfund Superfund Amendment Reauthorization Act (1986) SARA Clean Air Act(1990) CAA Specific for Sediment Sampling in a Channel or Stream (USGS method) see note below: ...
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