Chromatography

Sampling - what can go wrong?

Wrong location, depth, timing → sample never represented population

Preservation - what can go wrong?

Analyte degrades, volatilizes, or reacts before getting to lab

Sample prep - what can go wrong?

extraction, digestion, or dilution introduces loss/contamination

Separation - what can go wrong?

Poor resolution means overlapping peaks are misquantified

Detection - what can go wrong?

Even perfect instrument reports what was put in. Garbage in garbage out

Variance equation

Sigma²=sigma² sampling + sigma² prep + sigma² analysis

What are five sampling failures?

Representativeness (Real) Design (Dogs) Contamination (Can’t) Preservation (Play) Documentation (Dominoes)

Category of failure matters more than…

Mistake

Grab Sample

Single sample taken at one place at one time

Composite Sample

Multiple grab samples taken and combined before analysis

Incremental Design

Small increments collected and combined systematically

If I double the particle size how much does the sample mass multiply by?

d³… so 8x (Gy’s)

What does a larger sample mass do to the random sampling variability?

Lowers random sampling variability

What does a small sample size do to variance?

Increases it

Compositional heterogeneity

Particles are different to each other in composition

Distributional heterogeneity

Particles of a given composition are not randomly distributed

What could go wrong with preservation of volatile organics?

Volatilization, biodegradation

What could go wrong with preservation of trace metals?

Adsorption to container walls, precipitation

What could go wrong with preservation of microbial/biological?

Growth or die-off before analysis

What could go wrong with preservation of pesticides

Photodegradation, adsorption

Mu - population parameters

Population mean - mean of entire population

Sigma - population parameters

Population std dev - variability of target pop.

x bar - population parameters

Sample mean - best estimate of pop. mean

S - population parameters

Sample std. dev. - best estimate of population std. dev

Standard error of mean shrink with..

Square root of n

What to do other than run Q-test?

Document investigation, follow QC plan. Do not remove results due to inconvenience

What does compositing reduce?

Variance (and hides information)

What do more samples do to mean?

Improve confidence in it.

What does more samples NOT improve?

Uniformity among individual results

Steps of creating sampling plan?

State problem, identify decision, specify tolerable error, design the plan

Systematic sampling grid

Regular spacing across whole grid.

Stratified sampling grid

Subareas with 3 identical spots each

Judgemental sampling grid

All dots in hot spot area

Coning and quartering

Preserves representativeness by reducing mass

Flow-proportional not time-proportional

Flow → standard for wastewater

Time → over represents low-flow periods and under represents pollutant load

Active: sampling gases

Pulls known volume of air through filter over defined time

Passive: sampling gases

Diffusion, no pump, trades precision for implicity

Container choice for trace metals

Acid washes HDPE

Container choice for volatile organics

Sealed glass vial

Container choice for light sensitive organics

Amber glass

Solid - dominant heterogeneity

Compositional and distributional

Liquid - dominant heterogeneity

Mostly temporal, flow, discharge cycles

Gas - dominant heterogeneity

Mostly temporal, low spatial variation

Field blank

Water taken to field exposed to air. Catches contamination

Trip blank

Clean water goes with samples but unopened

Field duplicate

2 samples same location. Measures precision and combined sampling

Matrix spike

Known amount of analyte added to sample

Mistake - Convenience bias

Sampling where its easy

Mistake - undersized n

Skipping sample size calculation

Mistake - Ignoring particle size

Using too little mass for coarse sample

Mistake - Over-compositing

Compositing away hot spot signal

Mistake - Custody gaps

Missed documentation

Stationary phase

Particles or liquid film held inside column

Mobile phase

Gas or liquid thar flows through column and carries solutes

Distribution constant K formula

K=Cs/Cm (C concentration in ____ phase)

Low distribution constant means:

Less time spent in column

K constants can be only compared to K constants from…

samples from same instrument

tm

dead time → time for unretained solute to pass thru column

tR

retention time → time from injection to peak max of given solute

tR’

adjusted - tR’=tR-tM

Retention factor k’

k’=(tR-tM)/tM

Retention volume

VR=tR x F

Selectiity - comparing solutes with a (alpha)

alpha = k’2/k’1 (k’2>k’1)

Permanent gas case

Adsorption - separate gases on solid (porous)

Inorganic ions case

ion exchange, separate Na+ K+ and Ca2+

Target protein case

affinity, capture one tagged protein from cell lysate

Organic solute case

partition, separate neutal organic solutes by polarity

Packed column chromatography

Mobile phase flows thru particles held inside tube

TLC

mobile phase climbs coated plate by capillary action

Normal phase

Stationary: polar silica surface

Reversed phase

Stationary: non polar c18 surface

Gas v liquid chromatography

Carrier gas moves vaporized sample thru heated column. Liquid solvent pumped thru packed column

Column efficiency and band width

H=L/N → higher plate number means less band broadening

Peak width → calc. plate Number

Baseline width: w=4 sigma N=16 (tR/w)² . Half height width: w1/2=2.35 sigma

Effective plates → correcting N for dead time

N eff = 16 (tR’ / w)²

Fronting

Stationary phases become saturated, analytes skip steps and crowd up front

Multiple paths

different routes around packing particles

Longitudinal diffusion

band diffuses forwards and backwards

Mass transfer

molecules do not equilibrate instantly