Instrumental Techniques for

Environmental Analysis

Chapter 1 : Introduction

Rezaul Karim

Environmental Science and Technology

Jessore Science and Technology University

1

Chapter outline

Analytical chemistry; its scope

and application;

instrumental analysis;

instruments for analysis,

representative sample; sample

storage, its pre-treatment and

preparation,

sample pre-treatment,

calibration of instrumental

methods;

selecting an analytical methods

2

Reference

Skoog, Holler & Crouch 2007,

Instrumental Analysis, Brooks Cole

Cengage Learning, USA.

Gray, Cakvin & Bhatia, 2009,

Instrumental Methods of Analysis, 1st

edition, CBS, New Deli, India

3

Analytical chemistry

Analytical Chemistry deals with methods

for determining the chemical composition

of samples of matter.

A qualitative method yields information

about the identity of atomic or molecular

species or the functional groups in the

sample.

A quantitative method provides numerical

information as to the relative amount of

one or more of these components.

4

Classification of analytical

methods

Classical

methods

◦ sometimes

called wet-

chemical

method

◦ preceded by a

century or more

◦ Gravimetric or

by volumetric

measurements

Instrumental

methods

◦ physical properties

as conductivity,

electrode potential,

light absorption or

emission, mass-to-

charge ratio

◦ paralleled the

development of the

electronics and

computer

industries.

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Types of instrumental methods

Characteristic

Properties

INSTRUMENTAL

METHODS

Radiation

e.g. Emission,

adsorption,

scattering, refracting,

rotating,

Diffraction, refraction

Spectrophotometer and

photometry

Electrical charge coulometry

Electrical current Amperomtry; palaeography

Mass Gravimetric

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Instruments for analysis

An instrument for chemical analysis converts

information about the physical or chemical

characteristics of the analyte to information

that can be manipulated and interpreted by a

human.

An analytical instrument can be viewed as a

communication device between the system

under study and the investigator.

To retrieve the desired information from the

analyte, it is necessary to provide a stimulus,

which is usually in the form of

electromagnetic, electrical, mechanical, or

nuclear energy.

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responseStimulus

System

under study

Data domain

The measurement process is aided by a wide

variety of devices that convert information from

one form to another.

It is important to understand how information can

be encoded (represented) by physical and

chemical characteristics and particularly by

electrical signals, such as current. voltage, and

charge.

The various modes of encoding information are

called data domains.

types of domain

nonelectrical domains

electrical domains8

Nonelectrical domains The measurement process begins and ends

in nonelectrical domains.

The physical and chemical information / characteristics are length, density, chemical composition, intensity of light. pressure, and etc.

The information representing the mass of the object in standard units is encoded directlyby the experimenter who provides information processing by summing the masses to arrive at a number.

Home task: TABLE 1-2 Some Examples of Instrument Components

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Data domain Map

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Electrical domains The modes of encoding information as electrical

quantities are :

analog domains

time domains,

the digital domain

For example,

◦ the measurement of the molecular fluorescence

intensity of a sample of tonic water containing a

trace of quinine

◦ The intensity of the fluorescence is significant

in this context because it is proportional to the

concentration to the quinine in the tonic water,

which is ultimately the information that we desire.

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A block diagram of fluorometer

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(a) a general diagram of the instrument,

(b) a diagrammatic representation of the flow of information through

various data domains in the instrument

(c) the rules governing the data-domain transformations during the

measurement process.

The intensity of the fluorescence

emission, which is nonelectrical

information, is encoded into an

electrical signal by a special type of

device, called an input transducer.

◦ In this example, the input transducer converts

the fluorescence from the tonic water to an

electrical current I, proportional to the

intensity of the radiation.

◦ The current is then passed through a resistor

R, which according to Ohm's law produces a

voltage V that is proportional to I, which is in

turn proportional to the intensity of the

fluorescence.13

◦ The mathematical relationship between the electrical output and the input radiant power impinging on its surface is called the transfer function of the transducer

Finally, V is measured by the digital voltmeter to provide a readout proportional to the concentration of the quinine in the sample.◦ Devices that serve to convert data from

electrical to non-clectrical domains are called output transducers e.g. Voltmeters, alphanumeric displays, electric motors, computer screens

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Analog-Domain Signals

is encoded as the

magnitude of one of the

electrical quantities -

voltage, Current, charge,

or power.

These quantities are

continuous in both

amplitude and time.

Magnitudes of analog

quantities can be

measured continuously,

they can be sampled at

specific points in time

dictated by the needs at

a particular experiment

or instrumental.

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Time-Domain Information

Information is stored in the

time domain as the time

relationship of signal

fluctuations.

The time relationships

between transitions of

the signal from HI to LO

or from LO to HI contain

the information of

interest.

For instruments that

produce periodic signals,

the number of cycles of

the signal per unit time

is the frequency and the

time required for each

cycle is its period.16

Digital information

Data are encoded in the

digital domain in a two-

level scheme.

The characteristic that

these devices share is that

each of them must be in

one of only two states.

For example, lights and

switches may be only ON

or OFF and logic-level

signals may be only HI or

LO.

The measurement task is

to count the pulses during

a fixed period of time

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Detector

Detector refers to a mechanical,

electrical or chemical device that

identifies, records. or indicates a

change in one of the variables in its

environment, e.g.

◦ pressure,

◦ temperature,

◦ electrical charge,

◦ electromagnetic radiation,

◦ nuclear radiation.

An example is the UV (ultraviolet)

detector often used to indicate and

record the presence of eluted analytes

in liquid chromatography.

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Transducer

those devices that convert

information in nonelectrical

domains to information in

electrical domains and the

converse.

◦ photodiodes,

◦ photomultipliers, and

◦ other electronic photodetectors

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Sensor

analytical devices that are

capable of monitoring specific

chemical species continuously

and reversibly.

◦ the glass electrode

◦ ion-selective electrodes,

◦ the Clark oxygen electrode, and

◦ liber-optic sensors (optrodes)

Sensors consist of a transducer

coupled with a chemically

selective recognition phase.

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Readout device

A readout device is a transducer that

converts information from an

electrical domain to a form that is

understandable by a human observer.

Usually, the transduced signal takes

the form of

the alphanumeric or graphical output of

a cathode-ray tube,

a series of numbers on a digital display,

the position of a pointer on a meter

scale,

a tracing on a recorder paper.

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Computer in instruments

Most modern analytical

instruments contain or are

attached to one or more

sophisticated electronic devices

and data-domain converters.

operational amplifiers,

integrated circuits,

analog-to-digital

digital-to-analog converters,

microprocessors, and

Computers.

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A complete analysis

five main steps:

Sampling; selecting a

representative sample of the

material to be analyzed

Dissolution of the sample

Conversion of the analyte into a

form suitable for measurement

Measurement and

Calculation and interpretation of

the measure.

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Representative sample

The aims of analysis are

understood and an appropriate

sampling procedure adopted.

Heterogeneous material have to

be homogenized prior to obtaining

a laboratory sample if an average

or bulk composition is required.

Typical examples

Surface water, rivers, seawaters

Ores, minerals and alloys

Laboratory , industrial or urban

atmosphere

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Sample storage After collecting sample, it may

elapse several days or weeks

before they are received by the

laboratory.

The working load

Sample containers and storage

conditions must be controlled

◦ Temperature,

◦ humidity,

◦ light levels and

◦ exposure to the atmosphere

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Effects for consideration

i. Increases temperature leading to the loss

of volatile analytes

ii.Decrease in temperature that lead to the

formation of deposits or the precipitation

iii.Changes in humidity that affect the

moisture content of hygroscopic solids

and liquids

iv.UV radiation that induces photochemical

reactions, photo-decompostion, or

polymerisation

v. Air induced oxidation

vi.Physical separation of the sample

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Sample pre-treatment

Samples arriving in an analytical

laboratory come in a very wide

assortment of sizes, conditions, and

physical forms

They can contain analytes from major

constituents down to ultra-trace levels.

They have moisture content

Examples of pre-treatment

Dry at 100-120ºC to remove moisture

Weighing before and after drying

Separating into groups e.g. Distillation,

filtration

Concentrating analytes

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Sample preparation A laboratory sample generally needs

to be prepared for anlytical

measurement by treatment with

reagents, that converts the analyte

into an appropriate chemical form for

the selected technique and method.

◦ if the material are readily soluble in

aqueous or organic solvents, a simple

dissolution step may suffice.

◦ Some solution need to be decomposed to

release the analyte and facilitate specific

reactions in solution.

◦ Need to be diluted or concentrated

◦ Stabilizations of solutions

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Calibration of instrumental

methods Calibration determines the relationship

between the analytical response and

the analyte concentration.

Usually this is determined by the use

of chemical standards.

Almost all analytical methods require

some type of calibration with chemical

standards.

do not rely on calibration

◦ Gravimetric methods and

◦ some coulometric methods

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Several types of calibration

procedures Comparison with Standards

Direct comparison

Titrations

External standard calibration

The least Squares methods

Errors in external calibrations

Multivariate calibration

Standard addition methods

The internal standard methods

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Direct comparison

Some analytical procedures involve comparing a property of the analyte (or the product of a reaction with the analyte) with standards such that the property being tested matches or nearly matches that of the standard.

For example, colorimeters, the colorproduced as the result of a chemical reaction of the analyte was compared with the color produced by reaction of standards.

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Titrations

In a titration, the analyte reacts

with a standardized reagent (the

titrant) in a reaction.

Usually the amount of titrant is

varied until chemical equivalence is

reached, as indicated by the color

change of a chemical indicator or by

the change in an instrument

response.

The titration is thus a type of

chemical comparison.32

External standard calibration

An external standard is prepared

separately from the sample.

External standards are used to

calibrate instruments and

procedures when there are no

interference effects from matrix

components in the analyte solution.

A series of such external standards

containing the analyte in known

concentrations is prepared.

Ideally, three or more such solutions

are used in the calibration process.

However, in some routine analyses,

two-point calibrations can be

reliable. 33

Calibration is accomplished by obtaining

the response signal (absorbance, peak

height, peak area) as a function of the

known analyte concentration.

A calibration curve is prepared

◦ by plotting the data or

◦ by fitting them to a suitable mathematical

equation e.g. the method of linear least squares.

In the prediction step, the response signal is

◦ obtained for the sample and

◦ used to predict the unknown analyte

concentration, cx

from the calibration curve or

best-fit equation.

The concentration of the analyte in the original

bulk sample is then calculated from cx, by

applying the appropriate dilution factors from

the sample preparation steps.

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The Least-Squares Method:

two assumption i. there is actually a linear relationship

between the measured response and

the standard analyte concentration:

regression model, Y= mx + b; where b

is the y intercept (the value of y when

x is zero), m is the slope of the line.

ii. We also assume that any deviation of

the individual points from the straight

line arises from error in the

measurement.

we assume there is no error in the x

values of the points (concentrations).

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Basic least-squares analysis may not be

appropriate

i. whenever there is significant uncertainty in

the x data, a more complex correlation

analysis may be necessary.

ii. when the uncertainties in the y values vary

significantly with x. In this case, it may be

necessary to apply a weighted least-squares

analysis

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the determination of isooctane

in a hydrocarbon sample.Here, a series of isooctane standards was

injected into a gas chromatograph.

the area of the isooctane peak was obtained

as a function of concentration.

The ordinate is the dependent variable, peak

area, and the abscissa is the independent

variable, mole percent (mol %) of isooctane.

As is typical and usually desirable, the plot

approximates a straight line, because of the

indeterminate errors in the measurement

process to draw the "hest“ straight line

among the data points.

Regression analysis provides the means for

objectively obtaining such a line and also

for specifying the uncertainties associated

with its subsequent Line.

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38

Errors in External-Standard Calibration

When external standards are used, it

is assumed that the same responses

will be obtained when the same

analyte concentration is present in

the sample and in the standard.

Thus, the calibration functional

relationship between the response

and the analyte concentration must

apply to the sample as well.

Usually, in a determination, the raw

response from the instrument is not

used. Instead, the raw analytical

response is corrected by measuring

a blank.

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An ideal blank is identical to the

sample but without the analyte.

In practice, with complex samples, it

is too time-consuming or impossible

to prepare an ideal blank and a

compromise must be made.

Most often a real blank is used in

sample preparation

a solvent blank , containing the same

solvent in which the sample is dissolved,

a reagent blank, containing the solvent

plus all the reagents

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Matrix effects, due to extraneous species in

the sample that are not present in the

standards or blank, can cause the same

analyte concentrations in the sample and

standards to give different responses.

systematic errors can occur during the

calibration process.

i. if the standards are prepared incorrectly,

an error will occur.

ii. errors can occur if the calibration function

is obtained without using enough

standards to obtain good statistical

estimates of the parameters.

Random errors can also influence the

accuracy of results obtained from calibration

curves.

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Standard-Addition Methods Standard-addition methods are

particularly useful for analyting complex

samples in which the likelihood of

matrix effects is substantial.

A standard-addition common forms

involves adding one or more increments

of a standard solution to sample aliquots

containing identical volumes. This

process is often called spiking the

sample.

Each solution is then diluted to a fixed

volume before measurement.

Measurements are made on the original

sample and on the sample plus the

standard after each addition.

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The internal standard method An internal standard is a substance that is

added in a constant amount to all samples,

blanks, and calibration standards in an

analysis.

Alternatively, it may be a major constituent of

samples and standards that is present in a

large enough amount that its concentration

can be assumed to be the same in all cases.

Calibration then involves plotting the ratio of

the analyte signal to the internal-standard

signal as a function of the analyte

concentration of the standards.

This ratio for the samples is then used to

obtain their analyte concentrations from a

calibration curve.

An internal standard, if properly chosen and

used, can compensate for several types of

both random and systematic errors.

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selecting an analytical

method Defining the Problem

To select an analytical method intelligently, it

is essential to define clearly the nature of

the analytical problem. Such a definition

requires answers to the following questions:

1. What accuracy is required?

2. How much sample is available?

3. What is the concentration range of the

analyte?

4. What components of the sample might

cause interference?

5. What are the physical and chemical

properties of the sample matrix?

6. How many samples are to be analyzed?

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Performance Characteristics of

Instruments: Numerical Criteria i. Precision: Absolute standard

deviation, relative standard deviation,

coefficient of variation. variance

ii. Bias: Absolute systematic error,

relative systematic error

iii. Sensitivity: Calibration sensitivity.

analytical sensitivity

iv. Detection limit: Blank plus three times

standard deviation of the blank

v. Dynamic range: Concentration limit of

quantitation (LOQ) to concentration

limit of linearity (LOL)

vi. Selectivity: Coefficient of selectivity

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Other Characteristics to Be

Considered in Method Choicei. Speed

ii. Ease and convenience

iii. Skill required of operator

iv. Cost and availability of

equipment

v. Per-sample cost

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Precision

Precision provides a measure of the

random, or indeterminate, error of an

analysis.

Figures of merit or precision include

◦ Absolute standard deviation (S=

◦ Relative standard deviation, RSD

◦ Standard error of the mean, Sm

◦ Coefficient of variation, CV and

◦ Variance, S2

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Bias

Bias provides a measure of the

systematic, or determinate,

error of an analytical method.

Bias , is defined hy the

equation:

Δ=μґ

Where μ is the population mean

for the concentration of an

analyte in a sample and ґ is

the true value,

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Sensitivity

There is general agreement that the

sensitivity of an instrument or a

method is a measure of its ability to

discriminate between small

differences in analyte concentration.

Two factors limit sensitivity:

◦ the slope of the calibration curve and

◦ the reproducibility or precision of the

measuring device.

A corollary to this statement is that

if two methods have calibration

curves with equal slopes, the one

that exhibits the better precision will

be the more sensitive.

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Detection Limit

Detection limit is that it is the

minimum concentration or mass of

analyte that can be detected at a

known confidence level.

This limit depends on

◦ the ratio = the magnitude of the

analytical signal

◦ the size of the statistical

fluctuations in the blank signal.

The analytical signal is larger than the

blank by some multiple k of the

variation in the blank due to random

errors, it is impossible to detect the

analytical signal with certainty.

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Dynamic Range the delinition of the

dynamic range of an

analytical method

It extends from the

lowest concentration

at which quantitative

measurements can be

made (limit of

quantitation, or LOQ)

to the concentration at

which the calibration

curve departs from

linearity by a specified

amount (limit of

linearity, / LOL).

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Dynamic Range Usually, a deviation of

5 % from linearity is

considered the upper

limit.

Deviations from

linearity are common

at high concentrations

because of no ideal

detector responses or

chemical effects.

The lower limit of

quantitative

measurements is

generally taken to be

equal to ten times the

standard deviation of

repetitive

measurements on a

blank.

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Selectivity

Selectivity of an analytical method refers to the degree to which the method is free from interference by other species contained in the sample matrix.

Unfortunately, no analytical method is totally free from interference from other species

Frequently steps must be taken to minimize the effects of these interferences.

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