Transcript GLUCOSIDIC & PROTEINACEOUS FRACTIONS OF DOM

ENVIRONMENTAL
ANALYTICAL CHEMISTRY
Winter 1999
Angela Chang
Mausami Desai
Katie Sovik
PRINCIPLES
To experience and practice a variety of
techniques useful in analyzing natural
environmental processes. This includes
complex biological, chemical, geological,
and physical phenomena.
 This
laboratory utilizes some of the state-ofthe-art instrumentation currently available,
noting the accuracy of results that can be
obtained.
 The
focus is split between a lesson on
instrumentation and results analysis.
OBJECTIVE
This course specifically focuses on
characterizing naturally occurring organic
matter (NOM) because of its influence on the
bioavailability and activity of pollution. The
following analyses provide an introduction to
important laboratory instrumentation while
addressing a significant environmental
material.
CONTENTS

Characterization of Total Organic Carbon

Capillary Electrophoresis

Potentiometric Methods

Glucosidic & Proteinaceous Fractions of DOM

DOM Fingerprinting by PY-GC-MS
CHARACTERIZATION OF
TOTAL ORGANIC CARBON
TOTAL ORGANIC CARBON
OBJECTIVE:
Quantify overall organic carbon
concentrations, and the dissolved and
particulate fractions.

This is a generalized starting point in
analyzing naturally occurring organic
matter. Subsequent procedures determine
more specific characterizations of the
types of organic material or carbon.
TOTAL ORGANIC CARBON ANALYSIS

by Automated Carbon Analyzer
(UV Persulfate Oxidation)

by UV Spectroscopy
Automated Carbon Analyzer
2 STEP TOC ANALYSIS PROCEDURE:
Principals
 By UV persulfate oxidation the sodium
persulfate and phosphoric acid reagents
convert all organic matter  CO2

Measuring CO2 concentrations suggests
organic carbon concentration
 The
infrared absorbance detector measures and
quantifies this CO2 as ppm total C
UV PERSULFATE OXIDATION
REACTIONS:


Excitation by UV light produces the primary
oxidants (sulfate and hydroxide radicals)
S2082- + v  2SO4- 
H20 +  v  H+ + OH
UV light also breaks down the organic material
into radical functional groups.
R +  v  R
UV PERSULFATE OXIDATION
The combination of these 2 types of radicals
oxidizes the organic matter releasing CO2.
R + SO4-  + H20  nCO2 + ...
 Ultimately a measure of the amount of
CO2 produced quantifies the TOC
Dohrman DC-180 Carbon Analyzer
Flow Diagram
See next page for system operations explanation
System Operations

A pump fills the pickup loop with sample

Specific amounts of sample and acid are injected into the sparger



Acidification with H3PO4 in the sparger strips the inorganic (IC)
and purgeable carbon (PuOC) from the sample. Separation of
these fractions is aided by a bubbling flow of O2(g)
The nonparticulate organic carbon (NPOC) remaining in the liquid
sample is sent to the UV reactor by another injection loop
UV radiation and the persulfate reagents oxidize all organics in
the sample
System Operations (continued)




The CO2(g) and OH-(g) are directed to the Gas/Liquid separator
and bubbled with acidified water. A pH of 3 is maintained to aid
the elimination of water from the CO2.
The infrared absorbance of water significantly overlaps with our
focus, CO2. The removal of water in an osmotic pressure dryer is
thus important.
In the Nondispersive Infrared Detector (NDIR) the absorbance of
infrared radiation measures CO2.
The computer calculates and displays this as ppm C.
Interferences
There are 3 significant types of interferences
related to the instrument procedure and
components of the samples :
 The
incomplete removal of inorganic and
purgeable carbon in the sparger
 The
incomplete oxidation of the organic
material in the UV reactor
 Chloride
radiation
present in the sample absorbing UV
Calibration Curve
counts = (15,500 +/- 102.4)conc - 540.6 +/- 1213
350,000
300,000
Counts
250,000
200,000
150,000
100,000
50,000
0
-
5
10
15
20
Concentration (ppm "C")
25
Calibration

5 standards of known C-concentration were
made from KHP (K-acid phtalate)



These concentrations ranged from 1-20 ppm
2 blank samples were also analyzed and used
to zero the calibration
The error on the intercept is larger than the
actual intercept estimate and insignificant with
respect to the origin
This intercept value can be disregarded
 Considering this was our first time doing error analysis,
we included all error estimates in our calculations.

Organic Carbon Calculations
Calculations are based on average values of triplicate
readings from the machine for each sample
UNFILTERED (TOC)
Sample
DASS
WDNR
RP
KCL
EP
MAY
NOV
NPOC
(ppm C)
FILTERED (DOC)
error
(+/-)
NPOC
(ppm C)
error
(+/-)
POC = TOC - DOC
POC
error
(+/-)
10.5839
10.6812
7.9751
7.776
7.8579
0.1741
0.1476
0.1585
0.17
0.1252
10.6414
10.5883
7.9088
5.3045
7.8291
0.1424
0.1507
0.1761
4.3133
0.132
-0.0575
0.0929
0.0644
2.4175
0.0288
0.2249
0.2109
0.2369
4.3166
0.182
4.5201
4.8705
0.1039
0.1349
4.8798
5.362
0.1616
0.1999
-0.3777
-0.4914
0.1921
0.2411
Organic Carbon Calculations


Dissolved particles are defined as that smaller
than 0.45 m by the filters used

Suspended/colloidal materials ineffectively separated by
filtration can thus be misrepresented as dissolved

This is a possible explanation for the large DOC values,
misleadingly close to the TOC
The resultant small POC calculations suggest
large amounts of colloidal material

The error carried over from the total and dissolved carbon
values is greatly amplified in the POC calculations making
them essentially insignificant
TOC - Sheboygan River
12.0
Corporate PCB’s
TOC
10.0
DOC
Kohler Company
ppm C
8.0
6.0
4.0
2.0
0.0
DASS
WDNR
RP
KCL
EP
TOC - Lake Depue
6.0
5.5
5.0
TOC
4.5
DOC
ppm C
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
MAY
NOV
Trends
Sheboygan River :



The organic carbon levels are greatest upstream of
the PCB’s input
The Kohler Co. does not seem to effect the carbon
levels
Overall there is about a 2 ppm downstream decrease
in TOC
Lake Depue :


No seasonal effects on TOC are noted
There is evidence that the lake is highly colloidal
UV SPECTROSCOPY
Principle : Different compounds at certain
wavelengths show unique and specific
absorbances. The following methods attempt
to quantify the fractions or concentrations of
different types of organic matter from
absorbance spectra.
UV SPECTROSCOPY

Correlation methods in particular, have been used as
estimates in characterizing :
Humidification
 % Aromaticity
 TOC


The UV-254 correlation with TOC useful for specific
water types has continued to be mentioned and
documented because of the simplicity of the procedure
and the portability of spectroscopy equipment. Even
though automated carbon analyzers are more widely
accurate, this method has shown some advantages.
UV SPECTROSCOPY

Transmittance is the fraction of incident light
transmitted by a solution
 This
cannot be measured directly in the lab due
to reflective interferences with any container
used to hold the sample

Beer’s Law (For use with dilute solutions only)
Absorbance = - log T = bc
  = molar absorptivity [L/mole*cm]
 b = the path length through the solution
 c = concentration
Spectrophotometer
1 - D2 lamp
2 - Grating 1
3 - Entrance Slit
4 - Grating 2
5 - Exit Slit
6 - Chopper
7 - Sample &
Reference
Positions
8 - Chopper
9 - Photo Tube
Spectrophotometry




Mirrors and gratings redirect and disperse the radiation
The slits limit the radiation range allowing successively
isolated wavelengths to be selected
The rotating chopper wheels alternately direct the light beam
through the sample and reference
A distilled water reference is required to zero the interference
effects of the cuvette
Other Interferences include :
chloride absorbance
particulate scattering
non-absorbing organic material
Absorption Ratios : Characterizations
NON-ACIDIFIED
Samples
DASS
WDNR
RP
KCL
EP
MAY
NOV
E4/E6 =
465/665
-1.80
-0.24
-0.61
-0.65
-0.16
-0.06
0.00
ACIDIFIED (1 drop HNO3)
E2/E3 =
254/365
4.78
6.38
5.13
4.98
6.00
5.70
7.50
Samples
DASS
WDNR
RP
KCL
EP
MAY
NOV
E4/E6 =
465/665
-2.33
-0.13
-0.69
-0.36
-1.47
0.00
-0.03
E2/E3 =
254/365
4.39
-0.02
4.05
1.50
8.43
2.52
5.75
Although negative values are useless, the ratios developed have
been used to characterize soil type and degree of humidification
E4/E6 & E2/E3 Ratios : Humic Substances
Humic
Substances


Fulvic Acid
Humin
soluble in
dilute alkali
soluble in dilute
alkali and acid
cannot be extracted
with either acid or base
Constitute a large portion of the organic matter in soils
Product of the degradation of plant and animal materials &
microorganism activity





Humic Acid
Aromatic
acidic
Hydrophilic
Flexible Polyelectrolytes
Lignin is the second most abundant polymer synthesized by
plants and a structural unit for humics
Biochemistry & Significance

The aromatic building blocks of humic
substances are connected by flexible low
energy bonds
 Reactions
and voids aggregate/trap other
materials
Metals ions and toxic organic pollutants are
stabilized in complexes
Humidification Analysis
E4/E6 & E2/E3 Ratios

Even though our results are inconclusive
 low
E4/E6 ratios have been found to indicate a
high degree of aromatic humic constituency
 High E4/E6 ratios indicate low aromaticity, or a
high degree of aliphatic structure
E4/E6
Humic Acids
3.8 - 5.8
Fulvic Acids
7.6 - 11.5
Humidification Analysis
E4/E6 & E2/E3 Ratios

Less data has been compiled for E2/E3 ratios
and thus they are less reliable although
certain characterizations have been
documented
E2/E3
Strongly humic and
oligotrophic lakes
4.0
Chlorolignin
4.2
Lignin
5.7
Absorption Ratios : Characterizations
NON-ACIDIFIED
Samples
DASS
WDNR
RP
KCL
EP
MAY
NOV
ACIDIFIED (1 drop HNO3)
Absorbance
% Aromaticity
@ 280nm
0.382
28.3
0.332
25.6
0.272
27.4
0.259
36
0.240
25.1
0.154
25.6
0.120
20.2
Samples
DASS
WDNR
RP
KCL
EP
MAY
NOV
Absorbance
% Aromaticity
@ 280nm
0.192
17.6
-0.173
n/a
0.070
12.1
-0.045
1.6
0.472
42.9
-0.013
5.1
0.040
11.2
Aromaticity

Aromaticity of organic matter is a specific structural
factor significant to interactions with pollutants, and
their stabilization


The higher the aromatic fraction of DOM, the higher the
xenobiotic binding capacity
A simple equation for % Aromaticity has been
developed that is dependant on molar absorptivity
 = A/bc
 Aromaticity = 0.05  + 6.74
Primary assumption : all organic matter absorbs the same at any
wavelength and that also absorbs as the KHP standard, i.e. the  of
all organic matter is the same. This assumption in actuality is not
valid, as  varies for different types of organic matter.
TOC Surrogate

UV absorbance at 254 nm is documented as
a widely used substitute for TOC
 We
analyzed the filtered samples in the
spectrophotometer and thus ultimately
compared DOC approximations from the 2
methods
Non-Acidified Pseudo Calibration Curve
abs =(0.01953 +/- 0.002089)(ppm C) - 0.01740 +/- 0.01393
Absorbance @ 254 nm
0.50
0.40
0.30
0.20
0.10
0.00
0
5
10
15
ppm C
20
25
Non-Acidified Pseudo Calibration Curve

Only 3 standards solutions ranging from 5 - 20
ppm C, and a blank were analyzed
 the
standards were diluted from a KHP stock
 the
samples were zeroed by the
spectrophotometer
 the
10 ppm standard introduced error
TOC - Comparisons
NPOC = TOC
Sample
Carbon Analyzer
DASS
WDNR
RP
KCL
EP
MAY
NOV
10.6414
10.5883
7.9088
5.3045
7.8291
4.8978
5.3620
error
(+/-)
0.1424
0.1507
0.1761
4.3133
0.1320
0.1616
0.1999
Non-Acidified
ppm C
Absorbance
UV - 254
@ 254nm (non-acidified)
0.382
0.332
0.272
0.259
0.240
0.154
0.120
20.1851
17.6826
14.6796
14.0290
13.0780
8.7737
7.0720
error
(+/-)
2.3382
2.1082
1.8455
1.7911
1.7136
1.4020
1.3033
Acidified
Absorbance
@ 254nm
0.325
-0.001
0.178
0.053
0.472
0.053
0.092
ppm C
26.8715
2.5845
15.9200
6.6075
37.8230
6.6075
9.5130
error
(+/-)
2.0767
1.1340
1.4812
1.1690
2.7694
1.1690
1.2363
The ppm C derived by the UV-254 correlation is doubly
overcompensated. Greater error values must also be noted as a
result of the limited calibration.
TOC Comparisons - Sheboygan River
25.0
Absorption at 254nm
20.0
ppm C
Persulfate Oxidation
15.0
10.0
5.0
0.0
DASS
WDNR
RP
KCL
EP
TOC Comparisons - Lake Depue
Absorption at 254 nm
10.0
Persulfate Oxidation
ppm C
8.0
6.0
4.0
2.0
0.0
MAY
NOV
Note

The effects of the colloidal particles noted in the POC
calculations is greatly amplified in the UV-254 method


The scattering action of the colloidal material is one
explanation for high absorbance readings and the
overcompensation for TOC
It is common belief that UV persulfate oxidation and
automated carbon analysis is the more accurate
method in determining TOC

Although this exercise allowed a realization of the potential
advantages and real limitations of experimental procedures
CAPILLARY
ELECTROPHORESIS
Capillary Electrophoresis
OBJECTIVE:
Determination of concentration
of specified ions in sample
waters
Introduction



Electrophoresis is the migration of ions in
solution under influence of electric field. In a
typical capillary electrophoresis (CE)
application, use an electric field of 15-30 kV to
separate the components inside a fused silica
capillary tube.
Since different solutes have different
mobilities, they will migrate through the
capillary at different speeds
This gives the extraordinary resolution and
separation of many ionic species.
Electrophoresis




When an ion with charge q is placed in an electric field E,
the force on the ion is:
F = q*E
In solution, the other major force on the ion is the retarding
frictional force f*vep, where vep is the electrophoretic
velocity and f is the coefficient of friction:
vep= q*E/f = µepE
The constant of proportionality between speed of ion and
the applied electric field is:
µep
µep is proportional to the charge on the ion and inversely
proportional to the friction coefficient.
Electroosmosis




The inside surface of the silica capillary is covered
with silanol (Si-OH) groups which carry a negative
charge above pH=2
These negative charges on surface induce cations
to neutralize some of the surface charge
The constant of proportionality between
electroosmotic velocity (veo) and applied field is the
electroosmotic mobility:
µeo
A relationship for the electrophoretic effect is:
veo=µeo*E
Diagram: Hydrodynamic Velocity Profile


(a) Positive charges move toward cathode,
absorbed on surface of glass
(b) More dispersion created by velocity profile
because pushed from middle
Apparent Mobility


The apparent (or observed) mobility (app)
of an ion is the sum of the electrophoretic
mobility of the ion and the electroosmotic
mobility of the solution:
app= ep+ eo
For a cation moving in the same direction
as the electroosmotic flow, the mobilities
have the same sign and then app is greater
than ep
Diagram: Solute Mobilities



(a) Optimize electrolyte conditions to make separation larger and
force ions out of system faster
(b) Use TTAB as reversal compound to separate anions out first
(c) Sum of all ions out of sides of capillary
Diagram: Apparatus







Both ends of capillary
placed into electrolyte
Sample injected by
siphon effect
Insert capillary into vial
and elevate
After injection, vial
returned to normal
height
Apply voltage of 15kV
Ions migrate through
electrolyte
Indirect detection
Standard 500uM Peaks
6.00E+00
Br-
Absorbance Units
5.00E+00
SO42-
Cl-
4.00E+00
NO3-
3.00E+00
2.00E+00
1.00E+00
0.00E+00
4.00E+00 4.20E+00 4.40E+00 4.60E+00 4.80E+00 5.00E+00 5.20E+00 5.40E+00 5.60E+00 5.80E+00 6.00E+00
Time (sec)
Standards Calibration
Concentration Bromide Chloride Sulfate
2000
2000
2000
1000
1000
1000
500
500
500
200
200
200
100
100
100
50
50
0
22809
22599
22150
12421
12196
12388
5950
6031
6095
2639
2703
2661
1490
1462
1256
584
528
0
23160
23078
22567
12784
12604
12475
5902
6036
6013
2727
2909
2846
1316
1256
1259
716
641
0
45510
45017
43970
25120
23917
24732
11305
10929
11299
5339
5570
5580
2639
2663
2616
1706
1518
0
Nitrate
25813
24817
23823
14383
13937
13167
5950
6094
6177
2910
2814
2846
1442
1641
1465
741
701
0
Bromide:
Slope
Intercept
11.261263 358.748442
0.139376 131.014062
Chloride:
Slope
Intercept
11.480147 348.184043
0.150664 141.624634
Sulfate:
Slope
Intercept
22.394186 660.936770
0.305920 287.566311
Nitrate:
Slope
Intercept
12.471486 294.383959
0.234302 220.245717
Calibration Curve for Bromide
y = 0.1394+11.2612x + 358.7484+131.0141
26000
24000
Counts (UV*sec)
22000
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
0
100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200
Concentration (uM)
Calibration Curve for Chloride
y = 0.1507+11.4801x +348.1840+141.6246
24000
22000
Counts (UV*sec)
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
0
100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200
Concentration (uM)
Calibration Curve for Sulfate
y = 0.3059+22.3942x + 660.9368+287.5663
44000
40000
Counts (UV*sec)
36000
32000
28000
24000
20000
16000
12000
8000
4000
0
0
100 200
300 400
500 600
700
800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100
Concentration (uM)
Calibration Curve for Nitrate
y = 0.2343+12.4715x + 294.3839+220.2457
28000
26000
24000
Counts (UV*sec)
22000
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
0
100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200
Concentration (uM)
Sample Data
DASS
Ions
ClSO4
NO3
Vial 1
Vial 2
Vial 3
Avg. Counts Std. Dev.
[Ion] in Sample
Error
15549
15164
15356.5000
272.2361
1304.26285
31.6763
12484
9732
11108.0000 1945.9579
464.089
87.8321
1416
1028
1222.0000
274.3574
67.1764
28.3113
WDNR
ClSO4
NO3
18678
12279
2099
17637
11650
1540
17468
10285
1463
17927.6667
11404.6667
1700.6667
655.2788
1019.3872
347.1085
1527.697233
477.2906667
105.3261333
61.5618
47.7068
33.0435
RP
ClSO4
NO3
17451
10046
1865
17522
9040
1126
17183
9689
1631
17385.3333
9591.6667
1540.6667
178.7857
510.0141
377.6908
1480.568467
396.6121667
92.57413333
27.6673
26.8244
35.0928
KCL
Cl-
18166
17200
17444
17603.3333
502.3239
1499.512667
49.3844
SO4
10411
9014
8149
9191.3333
1141.3791
378.7973333
52.7400
NO3
1708
1026
1433
1389.0000
343.1224
80.4863
32.7449
17574
18040
18514
18042.6667
470.0057
1537.690733
47.1218
SO4
9888
10402
9816
10035.3333
319.5768
416.3553333
20.2443
NO3
1668
1766
1345
1593.0000
220.2930
96.7451
25.1795
Cl-
15505
14956
16052
15504.3333
548.0003
1317.109567
52.1251
SO4
13183
13774
13423
13460.0000
297.2322
568.753
20.2856
NO3
6173
6123
7162
6486.0000
585.9667
486.7172
50.9483
Cl-
24968
24895
24260
24707.6667
389.4051
2116.879233
45.1900
SO4
61483
63259
61675
62139.0000
974.6876
2734.9685
58.6742
EP
MAY
NOV
Cl-
NO3
ERROR
SQRT((((C32*E32)*SQRT(((D32/C32)^2)+((F32/E32)^2)))^2)+(G32^2))
WDNR peaks
1.20E+01
Cl-
Absorbance Units
1.00E+01
8.00E+00
SO42-
6.00E+00
4.00E+00
NO32.00E+00
0.00E+00
4.00E+00
4.20E+00
4.40E+00
4.60E+00
4.80E+00
5.00E+00
5.20E+00
Time (sec)
5.40E+00
5.60E+00
5.80E+00
6.00E+00
[Ion] Along Sheboygan River
1800
1600
1. DASS
2. WDNR
3. RP
4. KCL
5. EP
1400
Ion (uM)
1200
1000
[Cl-]
[SO4]
[NO3-]
800
600
400
200
0
0
1
2
3
Sample points
4
5
6
Analysis



[NO3] drops significantly from May to
November
[Cl-] and [SO4] increased overall in Lake
Depue
[Cl-] a bit higher along entire Sheboygan
River compared to other ions
POTENTIOMETRIC
METHODS
Potentiometric Methods
OBJECTIVE:
Determination of
acid/base properties of
samples.
Alkalinity & CT

Representation of the buffer capacity
of a water sample or the ability of the
water to neutralize strong acid.
 Alk

= 2[CO32-] + [HCO3-] + [OH-] - [H+]
Measure of alkalinity due to carbonate
system
 CT
= [H2CO3] + [HCO3-] + [CO32-]
Computer Automated Titration System
ME-10 Analyzer
Components

Automatic burette

Potentiometer
 Glass


Electrode
Windows Interface program controls ME-10
Analyzer unit during titration and records data
(volume additions and potential)
Data analysis to determine the equivalent
volumes and equilibrium constants
Titration System Setup
Glass Electrode
Titrant
(w/ reference
electrode and ion
selective membrane)
Computer
Sample &
mixer
Burette
Glass Electrode
Measures pH


The indicator electrode measures potential
difference across a glass membrane
between 0.1 M HCl and the sample solution.
The glass electrode has two key components
reference
electrode
ion selective glass membrane
Reference Electrode
Within a tube in the indicator glass electrode:


The reference electrode contains a small volume
of dilute HCl and AgCl. The Ag wire forms a
reference electrode creating a link to the potential
measuring device. This electrode should obey
Nernst equation when constant temperature and
ionic strength are maintained.
The reference electrode provides a base potential
from which changes in potential can be measured.
Ion Selective Membrane
The ion selective glass membrane is sealed into one
end of the glass tube.

When hydrated, it allows for the interaction between
singly charged cations (electric conductivity) in the
glass and protons from the solution.


H+ + Na+Gl-  Na+ + H+Gl-
More specifically when [Na+] is low, conduction
within the hydrated layer involves the movement of
hydrogen ions by the following reactions
H+ + Gl-  H+Gl H+Gl-  H+ + Gl
(between glass and sample solution)
(between internal solution and glass)
Typical Electrode System for Measuring pH
Measurement through Electrode


The equilibrium position of these 2 reactions are
determined by {H+} in the solutions on the two sides
of the membrane.
The surface where greater dissociation occurs
becomes negative w/respect to other surface with
less dissociation.


A boundary potential Eb develops across the membrane
which is sensed by the analyzer and recorded by the
computer.
The potential change is recorded in mVolts along
with the corresponding volume of acid added
Measurement through Electrode


Since constant temperature and ionic
strength are maintained, the system
obeys the Nernst equation.
Eb is Emv where
Emv= EG + kT ln [H+]
EG = Potential normal of the glass electrode for [H+]=1M
Includes reference potential and corrects for
departure from ideal behavior
k = R/F (R = Gas constant, F = Faraday’s constant)
T = Room temperature in Kelvin
Calibration of Electrode System


Titrated solution of 5 mL 0.1 M KCl (to maintain ionic
strength) and distilled water with 0.1 M HCl at T = 22o C
or 295 K
Verifies Nernst Equation by obtaining linear
relationship by plotting pH vs.. change in potential
where pH is
ln [H+] = ln [(Vad * tHCl)/(Vo + Vad)]
Note: tHCl = [HCL]=0.1M

Theoretically under these conditions should be
kT = 58.54, the experimentally obtained value was
kT = 57.51 a variation of less than 2%
Calibration Curve-Glass Electrode
E =(-57.51+/-0.1633)pH + 349.92+/-0.5376
210
190
E(mV)
170
150
130
110
90
70
50
2
2.5
3
3.5
pH
4
4.5
5
Error Sources in Potentiometric Method


Variation in temperature of solution
possibly due to constant stirring
Variation in ionic strength
The Eppendorf was not sealed properly and
additions of KCL to samples may have varied

Junction Potential: Potential develops from the
difference in composition between sample and titrant. This
potential arises from the unequal distribution of cations
and anions and the different rates at which the species
migrate. As long as ionic strength is maintained this
potential is reduced.
Gran Method
Priniciple: Graphical procedure based on
knowledge that added increments of strong acid
linearly increase [H+] or decrease [OH-], likewise
added increments of strong base decrease [H+] or
increase [OH-].

A titration curve is obtained by plotting volume added
vs. potential E in mV. In this lab strong acid is added to
determine the alkalinity of our samples so we know that
the lower part of the curve is composed of base, while
the upper part of the curve is composed of acid.
Potentiometric Titration-DASS sample
acidic
V2 = 2.503+/- 0.0159
mV
200
180
160
140
120
100
80
60
40
20
0
-20 0
-40
-60
-80
-100
-120
-140
-160
0.2 0.4 0.6 0.8
1
1.2 1.4 1.6 1.8
2
2.2 2.4 2.6 2.8
basic
V1= 0.1204+/-0.0074
Volume Added
3
3.2 3.4 3.6 3.8
4
Gran Method cont.



At the midpoint the [base A-] = [ acid HA].
All base is titrated at the endpoint or
equivalence point of the titration and is
represented by an inflection point.
Thus, using this method, it is possible to
determine the carbonate system equivalence
points, assuming that the alkalinity of our
samples is due to the carbonate system.
 Determine equilibrium constant for carbonate system
Gran Plots

F1
For volumes > than the second equivalence
point, volume v2:
[H+] >> [HCO3-], [CO32-], and [OH-] together

So the following relationship is true
F1 = (vo+ vad)* [H+] = (vad - v2)*tHCl
Note: tHCl = [HCL]=0.1M

When plotted against vad, the function is
linear beyond v2 so
F1 = 0 for vad = v2
DASS-F1
y = (0.1002+/-0.0004)x - (0.2508+/-0.0012)
0.1600
0.1400
0.1200
F1
0.1000
0.0800
0.0600
0.0400
0.0200
0.0000
2
2.5
3
Volume added (mL)
3.5
4
Gran Plots

F2
Between the first and second equivalence points
volumes, v1 and v2:
[H2CO3] >> [H+] - [CO32-] - [OH-]
[HCO3-] >> [CO32-] + [OH-] - [H+]


Similarly the following relationship holds
F2 = (v2 - vad)*[H+] = (vad - v1)*K1
F2 is linear for volumes less than v2 when plotted
against vad and F2 = 0 for vad = v1, with the slope of F2 =
K1 the equilibrium constant for
H2CO3  HCO3- + H+
DASS -F2
y = (5.6075E-07+/-3.4238E-9)x - 6.7517E-08+/-4.1399E-9
0.0000012
0.000001
F2
0.0000008
0.0000006
K= 6.2512+/-2.65E-3
0.0000004
0.0000002
0
0
0.5
1
1.5
Volume added (mL)
2
2.5
Alkalinity & CT Results

Determined by the following relationships
[Alk] = (v2* tHCl)/ v0
CT = ((v2 - v1)* tHCl)/ v0
DASS
WDNR
RP
KCL
EP
MAY
NOV
Alkalinity
5.0007E-03
5.0060E-03
5.0271E-03
5.0620E-03
5.0870E-03
2.7100E-03
4.4810E-03
CT
4.7601E-03
4.8310E-03
4.7971E-03
4.8210E-03
4.8160E-03
2.5910E-03
4.2230E-03
both are molar values M
Lake Depue
5.0E-03
4.5E-03
4.0E-03
3.5E-03
M
3.0E-03
Alkalinity
2.5E-03
CT
2.0E-03
1.5E-03
1.0E-03
5.0E-04
0.0E+00
MAY
NOV
Sample dates
Sheboygan River
5.2E-03
5.1E-03
M
5.0E-03
4.9E-03
Alkalinity
CT
4.8E-03
4.7E-03
4.6E-03
4.5E-03
DASS
WDNR
RP
Sample site
KCL
EP
Analysis

Sheboygan River: Alkalinity increases
moving downstream along the, while CT
remains essentially constant varying around
4.8E-3 M

Lake Depue: Alkalinity and CT increase in
the winter nearly doubling, most likely due
to the course of productivity throughout the
year
GLUCOSIDIC &
PROTEINACEOUS
FRACTIONS OF DOM
GLUCOSIDIC & PROTEINACEOUS
FRACTIONS OF DOM
OBJECTIVE:
Qualitative analysis of simple
sugars and amino acid fractions
of DOM through colorimetric
and fluorescence methods.
These residuals of biological
activity and decay are
significant in determining COD.
GLUCOSIDIC FRACTION
COLORIMETRY/SPECTROSCOPY:
 Reaction of phenol and H2SO4 (Dubois reagents)
with the samples breaks down complex
sugars.


The attachment of phenol to the reduced sugar
monomers produces compounds of a stable
yellowish color.
Spectrometric measurement of the intensity of
color quantifies the specific fraction of sugars.
Spectrometer
1 - D2 lamp
2 - Grating 1
3 - Entrance Slit
4 - Grating 2
5 - Exit Slit
6 - Chopper
7 - Sample &
Reference
Positions
8 - Chopper
9 - Photo Tube
Spectrophotometry




Mirrors and gratings redirect and disperse the radiation
The slits limit the radiation range allowing successively
isolated wavelengths to be selected
The rotating chopper wheels alternately direct the light beam
through the sample and reference
A reference sample is required to zero the interference effects
of the cuvette.
Other Interferences include :
particulates scattering
non-absorbing organic material
GLUCOSIDIC CALIBRATION @ 480 nm
abs =(0.0035+/-0.0003)(conc) - 0.0133+/-0.0083
0.18
0.16
Absorbance (%)
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00
-0.02
0
10
20
30
40
50
60
Concentration [uM]
No distinction can be made between the 0 and 10 uM concentrations. Most of our
data points fall within this range. The calibration from this method therefore does
not lead to conclusive results.
GLUCOSIDIC CALIBRATION @ 490 nm
abs = (0.0037+/-0.0003)(conc) - 0.0166+/-0.0089
0.20
Absorbance (%)
0.15
0.10
0.05
0.00
0
10
20
30
40
-0.05
Concentration [uM]
50
60
GLUCOSIDIC RESULTS
480 nm
Sample
DASS
WDNR
RP
KCL
EP
MAY
NOV
Average
Glucosidic
Zeroed
Concentration
Absorbance
480 nm
[uM]
0.0203
6.0678
0.0386
6.1094
0.0213
6.6997
0.0346
8.6851
0.0293
10.8392
0.0273
11.5775
0.009
8.7679
error
0.2418
0.1433
0.2553
0.2140
0.2784
0.3018
0.4423
Glucosidic
ppm C
0.4369
0.4399
0.4824
0.6253
0.7804
0.8336
0.6313
Glucosidic
Fraction
%
4.1278
4.1182
6.0486
8.0418
9.9317
18.4416
12.9615
As noted, all of our data points refer to concentrations less than 10 uM with the
exception of samples EP and May. In general, this did not provide us with useful data
for analysis.
GLUCOSIDIC RESULTS
490 nm
Sample
DASS
WDNR
RP
KCL
EP
MAY
NOV
Average
Glucosidic
Zeroed
Concentration
Absorbance
490 nm
[uM]
0.0204
6.5329
0.0374
6.7531
0.0197
7.2294
0.032
9.139
0.0277
11.0402
0.027
12.2085
0.0244
7.8873
error
0.2432
0.1541
0.2772
0.2348
0.2950
0.3160
0.2565
ppm C
0.4704
0.4862
0.5205
0.6580
0.7949
0.8790
0.5679
Glucosidic
Fraction
%
4.4442
4.5521
6.5268
8.4620
10.1159
19.4467
11.6597
ANALYSIS

The glucosidic fraction of TOC increases
downstream in the Sheboygan River.
 The
TOC values previously determined show a
slight decreasing trend downstream.


The Lake Depue fraction is higher in May than
November.
Using glucose as a representation of all other
sugars is not a good quantitative method.
Total Hydrolyzable Free Amino Acids
(Proteinaceous Fraction)


Samples reacted with OPAMERC solution to bind with
aromatic compounds, such as
proteins
Fluorometric measurement
quantifies proteinaceous
fraction
FLUORESCENCE




The fluorometer energy source excites
electrons of organic compounds bound to
OPA-MERC
High energy state is unstable
As electrons return to a more stable ground
state, visible light is emitted
From the intensity of emitted light,
proteinaceous fractions can be determined
Fluorometer
Procedure

Simple, low-cost, and easy to use

Mercury lamp for fluorescence excitation



Source beam split near source into a reference beam
and a sample beam
Both beams pass through primary filter
Sample beam causes emission of fluorescent
radiation
Proteinaceous Calibration
intensity = (3.5374 +/- 0.3213)(conc) - 0.5472 +/- 0.9729
18.0
16.0
Intensity
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
Concentration [uM]
Like the glucosidic calibration the amount of scattering within the data
shows that this method is unreliable at these concentrations.
Proteinaceous Results
Average Proteinaceous
Samples
Intensity Concentration
WDNR
RP
KCL
EP
MAY
NOV
2.509
3.779
2.652
2.507
1.785
1.694
0.864
1.223
0.904
0.863
0.659
0.634
error
0.3370
0.6842
0.2968
0.3875
0.2420
0.2662
No apparent trends are noted.
Proteinaceous Proteinaceous
ppm C
Fraction (%)
0.0026
0.0037
0.0027
0.0026
0.0020
0.0019
0.2912
0.5521
0.4185
0.3954
0.5249
0.4686
DOM
FINGERPRINTING BY
PY-GC-MS
DOM FINGERPRINTING
OBJECTIVE:
To characterize the constituents
of dissolved organic matter,
accomplished by breaking down
the DOM through a 3-step
process.
The data obtained in this procedure is based on a
wetland sample taken on August 6,1998
PY-GC-MS METHOD
STEP 1: PYROLYSIS

In an inert environment and at a controlled
temperature, the organic matter from the
concentrated water samples is thermally
degraded
 Bonds
within the OM are broken and rearranged
 Predictable
and reproducible fragments form
PY-GC-MS METHOD
STEP 2: GAS CHROMATOGRAPHY


The pyrolyzed fragments are drawn into the
GC column
The fragments migrate through the column by
action of a He mobile phase flushing the
system
 affinity
to a stationary phase (the silica column)
results in varied migrations rates for the different
types of fragments
Gas Chromatograph
PY-GC-MS METHOD
STEP 3: MASS SPECTROMETRY



A detector senses when the organic matter
fragments reach the end of the column
This signal is plotted versus time producing a
chromatogram
Specific fragments can be identified by their
characteristic retention times
Chromatogram
100
1
90
1. Unknown aliphatic
2. Acetic Acid
3. Propanoic Acid
4. Dimethyl-Propanedioic Acid
5. Butanoic Acid
6. Hexanoic Acid
7. Butenoic Acid
8. Phenol
%full scale
80
70
60
50
40
2
30
8
20
3
10
4 56
7
0
20
40
60
80
Time (minutes)
100
120
PY-GC-MS METHOD
STEP 3 CONTINUED: MASS SPECTROMETRY



In the mass spectrometer the fragments are ionized
An alternating current through the 4 poles of the mass
spec separates the ionized fragments by their
mass/charge ratios
The mass spec plots the spectrum of the ionized
fragments; mass/charge ratio versus % abundance
Quadrupole Mass Spectrometer
the fragments of the specific mass/charge ratio wanted at any
one time pass between the rods without being neutralized
 the other fragments are neutralized by contact with the rod
walls

PY-GC-MS METHOD
STEP 3 CONTINUED: MASS SPECTROMETRY
 The software program used in conjunction
with this method performs an online library
(NIST) search to match the mass spectra of a
fragment to known compounds.

The compounds detected in our sample :
unknown aliphatic
acetic acid
propanoic acid
dimethyl-propanoic acid
butanoic acid
hexanoic acid
butenoic acid
phenol
Note:


If we had samples leftover to analyze, the PY-GCMS method would have been beneficial in providing
structural feature fingerprints serving as chemical
markers within our samples. Trends may be
depicted.
Analysis methods can allow results comparisons
with other methods. Such as with determination of
the glucosidic fraction. PY-GC-MS analysis is
enhanced when used in conjunction with data from
other methods.
Evaluation




We have improved our laboratory skills
Through this course we have gained an
understanding of analytical methods currently being
used in the environmental field
We not only have a more comprehensive
understanding of scientific terminology, we are
capable of analyzing data in a more applicable way
In previous laboratory courses, error analysis was not
required. We have gained an understanding of how
results are obtained and how error can limit their
relevance
References

C45 Winter 1999 Lab Manual

Samuel Webb, Jill Kostel, Tanita Sirivedhin - technical advice

Leary, Skoog. Principles of Instrumental Analysis

Chen, Senesi, Schnitzer. “Information Provided on Humic
Substances by E4/E6 Ratios,” Soil Science Society of America.



Aiken, Chin, O’Loughlin. “Molecular Weight, Polydisperity and
Spectroscopic Properties of Aquatic Humic Substances,”
Environmental Science & Technology.
Dean, Dobbs, Wise. “The Use of Ultra-Violet Absorbance fo
rMOnitoring the Total Organic Carbon Content of Water and
Wastewater,” Water Resources.
Kukkonen. “Effects of Lignin and Chlorolignin in Pulp Mill
Effluents on the Binding and Bioavailability of Hydrophobic
Organic Pollutants,” Water Resources.