Methods for the preparation of the test
sample from the laboratory sample
(Part 1 – Material & Methods)
Work Package 6 – Task 6.4
Validation of prCEN/TS 15413 (WI 343027)
Paolo de Zorzi
APAT - Italian Environmental Protection Agency,
Environmental Metrology Unit
Workshop on “Classification, characterization and quality management of
solid recovered fuels”
Contents
Objectives
Material & Methods
Method to be
validated
Samples tested
Experimental design
Objective
Validation of prCEN/TS 15413 (WI 343027)
Evaluation of the “robustness” of the method for
preparation of test sample, that is its ability to give
consistent results under controlled variations of key
analytical parameters/conditions
Experimental activity performed by ENEL GEM AT Ricerca
(Brindisi) and by APAT (Italian Environmental Protection
Specifies the correct sequence of operations
to control and maximize the
representativeness of the test portions
prepared from the laboratory sample, prior to
physical and/or chemical analysis of solid
samples.
It is largely based on EN 15002 developed by CEN
TC 292 for waste samples.
Content of prCEN/TS 15413
(1)
A flow sheet for the definition of sequence of operations:
applied on the laboratory sample,
repeated on all sub-samples subsequently obtained,
iterative cycle until all analytical requirements are fulfilled;
Guidelines for choosing and applying sample treatment techniques:
Homogenization and fraction separation,
drying,
particle size reduction and sub-sampling (Annex A – normative);
Relationship between minimum amount of sample, particle size and
(sub-)sampling error
application of a statistical formula (Annex B).
Content of prCEN/TS 15413
(2)
From Laboratory Sample to the
measurement result
A lot of operation can be performed using different
devices modifying:
Sample size (e.g. splitting, rieffling, cone and quartering)
Particle size (comminution)
Heterogeneity
Laboratory
sample
Sub
sample
sample
Test
portion
Test
Evaluation of robustness
Wood sample
3
MSW sample
3
Type of particle
size reduction
system
6
Two kind of materials (MSW and
wood)
2
Composition
Total
levels
Notes
No of levels
Key variables
Key variables must be selected among the main degrees of
freedom of each method;
For each key variable, conservative conditions should be met; i.e.
when the methods “passes” the ruggedness testing in those
conditions, it will be actually “robust” in most real life cases.
The kind of sample to be assigned to each method should
emphasize the influence of the key variable under control.
demolition wood (QR-B):
Residual of wood at different size,
generally as flashes, blocks, lamellas
and flakes, often longer > 10 cm
together with wood powder.
municipal solid waste (QR-D):
Produced from the combustible fraction of
msw, containing small pieces of tyre
residues, passing through a 10 cm grid.
Samples chosen for the evaluation
of ruggedness
Experimental (1)
Preliminary tests
identification of applicable treatment procedures (tests on
milling, freeze-milling and cutting devices with different sieve)
evaluation of most interesting chemical parameters to be
tested, and their approximate levels (moisture, ash, LOI,
minor/major elements)
approximate assessment of the actual heterogeneity of the
Experimental (2)
Actual evaluation of ruggedness
Application and verification of the statistical formula for the
determination of the minimum mass of sample as function of
particle size, for a number of analytes (Ash, Moisture, several
elements)
Evaluation of effect of different particle size reduction
devices on: loss of analytes (mostly volatile ones, like
moisture, Hg, other volatile elements…), mass recovery,
resulting homogeneity on two different kind of samples
The statistical formula (Annex B)
Equation, based on the Gy’s sampling theory, used
for the estimation of the minimum mass of sample
to be analysed as function of some characteristics
(particle size, shape, etc.) and some errors
The statistical formula (Annex B)
( )
p
C
p)
-(1
g
2
3
95
sam
×
×
×
×
×
×
V
s
D
6
1
=
M
π
ρ
M
sam: the mass of the sample in g;
D
95: the “maximum” particle size (defined as the 95-percentile), in cm;
s: the shape factor of particles (s = V95 / D95l
3);
ρ: the average density of the particles in the material, in g/cm3;
g: the correction factor for the particle size distribution of the material;
p: the fraction of the particles with the property of interest; generally, this value is
assumed to be relatively high (p ≥ 0.1) for major parameters, that are likely to be
homogeneously distributed, and lower for less homogeneously distributed
and/or minor components (p ≤ 0.01 or less);
CV: the desired coefficient of variation caused by the fundamental error.
The
lower
CV (Coefficient of variation) the
better
representativeness
Application and verification of the
statistical formula
The formula applied on original
sample (D
95= 10 cm) leads to
minimum mass of sample too
high; it has been necessary to
reduce the particle size (D
95=
0.95 cm), in order to allow more
“practical” mass of test portion
.
331630 2988 M (g) 0.1 0.1 CV 0.013 0.013 s 10 10 D95 (cm) 0.001 (minor) 0.1 (major) p
(MSW sample has been used, ρ = 2 g/cm3 and g = 0.25 are assumed)
Sample (D95 = 10 cm) Cutting 0.4 cm 0.95 cm sieve Sample (D95 = 0.95 cm) > 0.95 cm < 0.95 cm 50 50 50 50 M (g) 0.38 0.17 0.12 0.0365 CV 0.0328 0.0328 0.0328 0.0328 s 0.95 0.95 0.95 0.95 D95 (cm) 0.001 0.005 0.01 0.1 p
A “practical” mass of test portion has been fixed to about 50
g, the expected CV has been calculated for several cases
of p-factor:
for major and homogeneously distributed components a
CV less than 0.1 (i.e. RSD<10%);
for less homogeneously distributed components, a CV
of 0.17 or higher (i.e. RSD>17%).
Sub-sampling for verification
of statistical formula
1000 g 500 g 500 g 250 g 250 g 125 g 125 g 62.5 g 62.5 g 187.5 g 812.5 g 400 g 400 g 200 g 200 g 100 g 100 g 50 g 50 g 50 g 50 g 100 g 100 g 50 g 50 g 50 g 50 g 200 g 200 g 100 g 100 g 50 g 50 g 50 g 50 g 100 g 100 g 50 g 50 g 50 g 50 g 800 g = A 47.06 g B 48.1 g C 55.4 g D 49.13 g E 35.3 g G 46.20 g L 57.18 g I 53.15 g H M 51.26 g N 48.28 g O 51.75 g P 50.17 g Q 50.28 g R F 52.27 gSamples used for evaluation of the statistical formula
16 sub-samples (A .. R) of about 50 g each have
been prepared from 1 kg of material (D95=0.95 cm). Five of them (A, D, G, L, O) have been used for the verification of the statistical formula. The others will be used later for evaluation of ruggedness.
Treatment and analysis
(verification of statistical formula)
Sample SM 2000 2 mm Cutting mill 0.5 mm ZM-1 centrifugal mill Moisture + ash (WI 343012) CHN (WI 343020) X 6 X 6 Elements(ICP-OES)
Considerations on statistical
formula (1)
compromise between the mass of (sub) sample to be
analyzed, its main physical characteristics (i. e. particle size
and shape), and the expected fundamental error associated
with (sub) sampling.
Overall variability includes the variability due to sampling,
preparation and analysis; Preparation and analysis
contribute to the overall estimated variability for about 5% for
most of components determined in this study. This must be
taken into account in evaluation of analytical results
For major components (i. e. ash, moisture, C, Ca, K, Mg, Na, Si), the
RSD associated with (sub) sampling is about 10% or less, as expected
with factor p from 0.1 to 0.01.
For other major components (Al, Cu, Fe and Ti), RSD is above 25%,
despite their high concentration. Even an application of factor p = 0.01 is
inadequate.
For minor elements (Mn, Ni, Sr, and W) the RSD is 10% - 30% as
expected with p = 0.001; Cr, Zn and mostly Ba show higher RSD.
For the application of the statistical formula, criteria for the choice of factor p can not be limited to
the relative abundance of the analytes of interest (the higher concentration
the higher p), because
there might be some dramatic exceptions of “heterogeneous” major components (like Cu, Al, Fe in
this case).
Therefore, a good knowledge of the sample and its nature is necessary.
Considerations on statistical
Devices for particle size reduction
Retsch SM 2000 Cutting Mill
Retsch SR 300 Rotor Beater Mill
Retsch ZM-1 Centrifugal Mill
•
Size reduction by cutting and shearing forces•
Low speed low heating•
Final particle size depending on the grid/sieve installed; coarse to mid size cutting (order of magnitude: mm)•
Feed: soft, medium-hard, tough, elastic, fibrous materials•
Low to mid throughput•
Size reduction by hammering, impact and shear effects•
High speed some heating is developed during processing•
Final particle size depending on the grid/sieve installed; coarse to mid size cutting (order of magnitude: mm)•
Feed: soft, medium-hard; low performances on tough, elastic and fibrous materials•
Mid to high throughput•
Size reduction by high speed impact and shear effects•
High speed heating may be developed during processing, depending on the type of material•
Final particle size depending on the grid/sieve installed; mid to fine size cutting (order of magnitude: below mm)•
Feed: soft, medium-hard, brittle, fibrous materials•
Low throughputFirst step
Final step
Evaluation of the effect of particle
size reduction devices
Low stress
Mid stress
High stress
Sample
2 mm
SM 2000
cutting mill
0.5 mm
0.5 mm
0.5 mm
X 3 X 3 X 3A
n
a
l
y
s
e
s
ZM-1
centrifugal mill
6 mm
SR 300 rotor
beater mill
2 mm
SR 300 rotor
beater mill
ZM-1
centrifugal mill
ZM-1
centrifugal mill
Low stress
Mid stress
High stress
Sample
2 mm
SM 2000
cutting mill
0.5 mm
0.5 mm
0.5 mm
X 3 X 3 X 3A
n
a
l
y
s
e
s
ZM-1
centrifugal mill
6 mm
SR 300 rotor
beater mill
2 mm
SR 300 rotor
beater mill
ZM-1
centrifugal mill
ZM-1
centrifugal mill
