Transcript Lecture series - Civil and Environmental Engineering | SIU

CE 510
Hazardous Waste Engineering
Department of Civil Engineering
Southern Illinois University Carbondale
Instructor: Jemil Yesuf
Dr. L.R. Chevalier
Lecture Series 4: Source Analysis
Course Goals
 Review the history and impact of environmental laws in the
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United States
Understand the terminology, nomenclature, and
significance of properties of hazardous wastes and
hazardous materials
Develop strategies to find information of nomenclature,
transport and behavior, and toxicity for hazardous
compounds
Elucidate procedures for describing, assessing, and
sampling hazardous wastes at industrial facilities and
contaminated sites
Predict the behavior of hazardous chemicals in air, surface
impoundments, soils, groundwater and treatment systems
Assess the toxicity and risk associated with exposure to
hazardous chemicals
Apply scientific principles of hazardous wastes
management, remediation and treatment
Fundamental Concepts Covered
 Materials Balance/Waste Audits
 Hazardous Waste Site Assessments
 Source Sampling: Statistics
Materials Balance/Waste Audits
Water treatment
chemicals
Laboratory
chemical wastes
Industrial Facility
Catalyst
Lubricating Oils
Maintenance
Material
Spent Chemicals
Losses:
Incorporated into Product
Volatilization
Spillage
Spent and dirty
filters
Waste Oil
See Figure 4.2 p. 214
Materials Balance/Waste Audits
 Overall Strategy
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Convert to mass
Convert to mass flux
Cannot add concentrations
Mass In – Mass Out + Rxn = Accum.
Problem 4.2 in Text
The following records are available for a small company that
manufactures semi-conductors. The chemical used most at the plant
is TCA, and the primary loss mechanism is volatilization. Using the
following data, estimate the maximum volatilization rate.
Note: S.G. of TCA = 1.339
Acquisitions:
Date
Vol. (L)
8-Jan
208
6-Feb
833
26-Feb
416
15-Mar
208
11-Apr
208
2-May
625
Purity (%)
92
95
88
97
90
95
RCRA Manifests:
Date
Waste No.
28-Feb
F001
20-Apr
F001
21-May
F001
30-May
F001
Vol.(L)
1140
386
462
1287
Discharges:
Wastewater characteristics: 18.9 x 106 L/day (5 MGD) at 0.5 mg/L TCA
C (%)
22
13
45
36
Solution
1. Acquisitions:
(208 L)(1.339 kg/L)(0.92) + . . .
= 3122 kg
2. Wastewater discharges
= (18.9 x 106 L/day)(143 days)(0.5 mg/L)
(1kg/106 mg) = 1351 kg
3. RCRA Manifests:
= (1140 L)(1.339 kg/L)(0.22) + . . .
= 1302 kg
Solution
4. Total Mass of TCA leaving the facility:
= 1351 kg + 1302 kg
= 2653 kg
5. Total TCA volatilized:
= 3122 kg – 2653 kg = 469 kg
6. Volatilization rate:
= (469 kg)/(143 days) = 3.3 kg/day
......end of example
Problem 4.3 in Text
A plastic formulation facility receives one of its synthetic chemicals,
dimethyl phthalate, by steady flow through a supply pipe at a flow
rate of 200 L/day. The dimethyl phthalate is used in synthesis
reactors for making a plasticized polymer at a rate of 0.8
moles/min. Partially reacted polymers are precipitated from
specific reactions containing fluids with 1200 mg/kg (dry wt.)
dimethyl phthalate. If 30,000 kg of the sludge (with an average
water content of 85%) are generated each day, how much dimethyl
phthalate is unaccounted for?
Note: S.G. = 1.191, MW = 194 g/mole
Solution
1. Mass balance: In – Out + Rxn = Accum.
If Out = 0 then
In + Rxn = Accumulated
2. Determine the mass of dimethyl phthalate supplied
(200 L/day)(1.191 kg/L) = 238.2 kg/d
Solution
3. Determine the mass lost due to the reaction
(0.8 moles/min)(194 g/mol)(60 min/hr)(24 hr/d)
= 223.5 kg/d
In + (-Rxn) = 238.2 – 223.5 = 14.7 kg/d
4. Determine the mass of dimethyl phthalate in the sludge
(1200 mg/kg)(30,000 kg/d)(0.15) = 5.4 x 106 mg/d
= 5.4 kg/d
5. Mass unaccounted for:
14.7 kg/d – 5.4 kg/d = 9.3 kg/d
......end of example
Hazardous Waste Site Assessments
 Phase I
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Paper research (background search)
Chemical inventory evaluation
Interviews with current and former personnel
Interviews with community
Regulatory agency record searches
Title searches
Areal photographs
Permits and violations
If suspicions of hazardous waste contamination
are confirmed, Phase II is warranted
Hazardous Waste Site Assessments
 Phase II
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Finalizing any searches that were
incomplete in Phase I
Detailed evaluation of pathways and
potential receptors
Random sampling and analysis
If contamination occurred, Phase III
Hazardous Waste Site Assessments
 Phase III
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Determine the extent of contamination
 Area, volume, concentration
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With appropriate sampling designs,
contaminant concentration data over
depth and area
 Provides sufficient information to assess the
site hazard (need for site cleanup)
 Provides criteria for the design of remedial
process
Source Sampling: Statistics
 Homogeneous source
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Aqueous waste in a drum
No concentration gradients
No layering from density difference
One sample represents the waste
 Most hazardous waste is heterogeneous
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Sludges
Soils
Lagoons
Characterization of the waste is expensive
 Reliable analysis with sophisticated instrumentation
 Quality Assurance
 Report preparation
Source Sampling: Statistics
Two fundamental statistical concepts for sampling
plan:
 Accuracy
 How close a measured value is to the true value
 Error allowed, a
 Corresponding parameter is the confidence level
(1-a)
 Precision
 Measure of the variability between samples
 D, deviation from the true value – precision
requirement
Source Sampling: Statistics
 Population
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True value of global data
A number that describes a population is called a
parameter
Parameters include
 Mean, m; Variance, s2 ; Standard deviation, s
 Sample
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Data set collected from population
A number that describes a sample is called a
statistic
statistics include
 Average, x; Sample variance, s2 ; Sample Standard
deviation, S.
Source Sampling: Statistics
 Why sample the source material (population)?
 Sampling errors and analytical errors?
 Which one is greater and why?
 If we take a sample and calculate a statistic, we often use that
statistic to infer something about the population from which the
sample was drawn.
Source Sampling: Statistics
Degrees of freedom:
A parameter used in statistical distributions that
represents the sample size minus the number of
parameters being estimated
df = n-1
x 

Xi
n
S
2

 X
i
 X
n 1

2
Source Sampling: Statistics
 Sampling procedures
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Search sampling (historic information)
 Using prior knowledge of the site
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Probability sampling
 Designed so that samples which have an equal chance of
being chosen are collected
 Simple random sampling
 Stratified random sampling
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A series of simple random sampling stacked on top of one
another
Others
Probability Sampling
 Based on the t-distribution
 A probability density function that is used to
evaluate sample means when the population
variance (σ2) is not known but can be estimated by
S2.
This value is found in tables.
X m
Need to know the size of the
t 
S n
sample set and the confidence
level desired.
i.e., t = (df, α)
See Appendix E.
Determining sampling points
 Divide source area into a grid of
sampling units (blocks)
 Assign a number to each block of the
grid
 Use a random number generator to
determine sampling points
Determining the number of
samples
 Initial or previous data
 Determine average and S2
 Determine the student’s two sided t with n-1
degrees of freedom for a confidence level of (1-a)%
 Determine the regulatory threshold, RT (e.g.
toxicity characteristic leaching protocol (TCLP))
2
n
t S
D
2
2
where
D  X  RT
Confidence Interval (CI)
CI  X  t a S
2
n
1
2
This parameter is needed to determine whether or not
a hazardous chemical is present at concentrations
which are measured below RT.
Procedure for the Simple Randomized Sampling
of RCRA Hazardous Waste Sources
 Collect a 3-6 random samples to obtain
preliminary estimates of the average and variance
 Estimate the minimum number of samples using a
specified confidence interval
2
n
t S
D
2
2
where
D  X  RT
 Using a sampling grid and random number
assignments, collect and analyze at least the
minimum number of samples from the waste
source
Procedure for the Simple Randomized Sampling
of RCRA Hazardous Waste Sources
 Determine the average and variance from
the detailed sampling plan
 If the sample mean is ≥ the regulatory
threshold (RT), the compound is present in
hazardous concentrations
 If the sample mean is ≤ RT
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Determine the confidence interval
If the upper CI < RT, the compound is not present
Class example from Text:
A drying bed holding sludge from an electroplating
process is to be sampled for cadmium content. The
dimensions of the drying bed are 6 m X 6 m, and the
sample volume will require an area 40 cm X 40 cm. Five
preliminary samples were collected randomly with the
following results: 25, 36, 49, 28, and 48 mg/kg Cd. Based
on this information, develop a simple randomized
sampling scheme. Determine (1) number of samples
required for 95% confidence limits within 5 mg/kg of the
sample mean, and (2) the location of the samples in the
sludge bed.
Solution
For the five preliminary samples,
Xbar 
25  36  49  28  48
5
kg
5
S
2

 (X
i
 Xbar )
i 1
n 1
and
S 
123  11 . 1
 37
mg
2
 123
Cd
Solution
From the Student’s t table (Appendix E), for df =n-1=4,
and using α = 0.025, t95% = 2.776. Note that 2α=5%,
error level for 95% confidence level).
The number of samples (n) is:
n
t
2
95 %
D
S
2
2
2

( 2 . 776 ) (123 )
5
2
round up to 38 samples .
 37 . 9 samples
Solution
The number of sampling units in both directions is:
8 m/0.4 m = 20 unit, and
6 m/0.4 m = 15 units
Total sampling units is 20 x 15 = 300.
Then select 38 random number between 1 and 300.
MS Excel has a built-in function RANDBETWEEN().
RANDBETWEEN(1, 300) at 38 cells will generate 38
sampling locations in the 20x15 grid.
spreadsheet
......end of example
Stratified Random Sampling
 Strategy involves dividing a site into
layers or strata (subpopulations)
 Strata are evaluated separately
 Increases sampling precision for the
entire population
 For soils, the strata are simply
horizontal layers at different depths
Stratified Random Sampling
Mean for each strata is determined by:
 n

 yi
 i 1 
y 
n
The mean over all strata is:
 L

y    Nh y h  / N
 h 1

where
L = total number of strata
Nh = total number of sampling units in the
hth stratum
N = total number of sampling units in all
strata
Stratified Random Sampling
Sample variance within each stratum:
V y h  
2
Sh
nh
nh
1

nh
y

 n  1
i
 yh 
2
i 1
h
Variance of the sample mean over all strata:
2

S
2
V y   2  N h  h
N h 1  n h
1
L

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Summary of Important Points and
Concepts
 Waste audits, which are based on materials
balance, can be used to determine losses
from volatilization, spillage, authorized
removals to secure landfills or incineration,
or improper management.
 Waste audits also serve as a basis for waste
minimization and pollution prevention plans.
 Assessment of contaminated sites is based on
a multi-step approach, with each phase
characterized by succeeding complexity.
(Phase I, II, and III)
Summary of Important Points and
Concepts
 Source materials, such as soils and sludges,
are most effectively sampled using
probability sampling.
 Simplified random sampling is used in system
which there is no gradient in contaminant
concentration with depth. It is also the basis
for probability sampling.
 Stratified random sampling is used to sample
systems where different strata contain a
range of concentrations.