CEADEN
Grizel Pérez, Ibrahin Piñera
Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear
Septiembre 14, 2011

G. Pérez
Sept. 14
2011
 Introduction
 Nuclear Analytical Techniques in PM monitoring
• Physical Principles
• Main characteristics
• PM sampling
 Application example
 Conclusions

G. Pérez
Sept. 14
2011
Air pollution has become a matter of global concern, particularly in some of the world's largest cities. It is made up of many different components that affect the environment - and directly or indirectly the health of people. The main components include sulphur dioxide, particulate matter, carbon monoxide, reactive hydrocarbon compounds, nitrogen oxides, ozone, and lead.
Nuclear techniques have important applications in the study of nearly all of them. However, it is in the study of airborne particulate matter (APM) that nuclear analytical techniques find many of their most important applications.

G. Pérez
Sept. 14
2011
PM nuclear analysis methods
Airborne particulate matter retained on the filter may be examined or analyzed chemically by a variety of methods. In this presentation, only nuclear analytical techniques (NATs) are considered because of their advantages in analyzing many elements in air particulate matter nondestructively and simultaneously.
The key three NATs for analysis of particulate matter in air are:

G. Pérez
Sept. 14
2011
PM nuclear analysis methods
Airborne particulate matter retained on the filter may be examined or analyzed chemically by a variety of methods. In this presentation, only nuclear analytical techniques (NATs) are considered because of their advantages in analyzing many elements in air particulate matter nondestructively and simultaneously.
The key three NATs for analysis of particulate matter in air are:

G. Pérez
Sept. 14
2011
Neutron Activation Analysis (NAA)
In typical NAA, a sample is exposed to a high flux of thermal neutrons in a nuclear reactor or accelerator. NAA is based on the interaction of a neutron
(n) with a target nucleus ( A Z) where the neutron is captured and gamma rays are emitted.

G. Pérez
Sept. 14
2011
Neutron Activation Analysis (NAA)
In typical NAA, a sample is exposed to a high flux of thermal neutrons in a nuclear reactor or accelerator. NAA is based on the interaction of a neutron
(n) with a target nucleus ( A Z) where the neutron is captured and gamma rays are emitted.
 The spectrum of gamma rays energy determines the specific isotopes present in the sample.
 The intensity of the gamma rays is proportional to the amounts of elements present.
 Typically 5 counting regimes are required to detect these elements (300 s,
1 hr, 10 hr, 4 days and 15 days).
 It is highly sensitive (ppb), it does not quantify elements such as Si, Ni, Co, and Pb. Typical elemental detection limits range from 0.01 to 10 ng m -3 .
 NAA is a simultaneous, multi-element method that can be used to measure 40-45 elements.

G. Pérez
Sept. 14
2011
X-Ray Fluorescence (XRF)
XRF is based on the measurements of the energies and intensities of the characteristic X-rays excited in different materials by using an external source of electromagnetic radiation (usually X-ray tubes or radioisotope sources).

G. Pérez
Sept. 14
2011
X-Ray Fluorescence (XRF)
XRF is based on the measurements of the energies and intensities of the characteristic X-rays excited in different materials by using an external source of electromagnetic radiation (usually X-ray tubes or radioisotope sources).
 XRF can be used for all elements with Z from 11 (Na) to 92 (U).
 Typical elemental detection limits for this method range between 2 and
2000 ng m -3 .
 XRF depends on the availability of excellent PM standards.
 Shorter analysis time than NAA.
 XRF can be used for simultaneous determination of 20-25 elements.

G. Pérez
Sept. 14
2011
Ion Beam Analysis (IBA)
IBA is based on the interaction, at both the atomic and the nuclear level, between accelerated charged particles and the bombarded material.

G. Pérez
Sept. 14
2011
Ion Beam Analysis (IBA)
IBA is based on the interaction, at both the atomic and the nuclear level, between accelerated charged particles and the bombarded material.
 These techniques are used simultaneously as key analytical tools to assess PM pollution on a regular basis.
 The choice of analytical method depends on the inorganic compounds of interest and the detection limits desired.
 Using the four different analysis techniques (PIXE, PIGE, PESA, RBS),
IBA can measure more than 40 elements (H – U).

G. Pérez
Sept. 14
2011
Particle Induced X-ray Emission Analysis (PIXE)
 PIXE is a powerful and relatively simple analytical technique that can be used to identify and quantify trace elements typically ranging from Na to U.
 Sample irradiation is usually performed by means of 2-3 MeV protons produced by an accelerator.
 Xray detection is usually done by energy dispersive semiconductor detectors such as Si(Li) or HP Ge detectors.
 This multi-elemental analysis technique can measure more than 30 elements in short times due to higher cross-sections as compared to XRF.
 With the addition of PIGE and PESA, allows for the detection of light elements that is useful for source identification and apportionment and estimation of organic carbon.
 Typical detection limits range from 1 to 50 ng m -3 .

G. Pérez
Sept. 14
2011
Particle Induced X-ray Emission Analysis (PIXE)
The remaining three methods are used simultaneously to achieve additional information on elements that can not or hardly be measured with PIXE.

G. Pérez
Sept. 14
2011
Advantages
• multielemental (H – U)
• non-destructive
• minimal sample preparation
• short irradiation time ( less than 15 min )
• quick analysis for IBA ( typically 15 min
)
• high sensitivity
• good accuracy and precision
• can handle small samples (< 1 mg)
• IBA are cost effective for large sample numbers, more than 10
Disadvantages
• NAA is slow, requires multiple counting regimes to detect many elements
• NAA requires access to research nuclear reactor
• IBA requires access to particle accelerator
• impurities may be a problem
• matrix offsets and background
• standard/sample must match closely (matrix)
• XRF has particle size effects for low
Z elements

G. Pérez
Sept. 14
2011
APM: usually collected by air filtering




Typical load: 50 – 700 m g/cm 2
Composition: Soil, soot, salts, industrial released
Particle size: ~ 0.1 to 50 m m

Filter media: o Teflon o Cellulose o Membrane (non-coated, coated)
Dichotomous sampler (used under IAEA coordinated research projects and TC projects)
(i) two fractions: 10 to 2.5 m m and < 2.5 m m
(ii) 8 m m and 0.4 m m pore 47 mm Nuclepore Filters; Flow rate 16 lpm
(iii) sampling time: 24 h for particle mass concentrations smaller than 50 m g/m 3 ;
Two days – 10-15 m g/m 3

NAA is compatible with sampling by high-volume (TSP; PM10) and dichotomous samplers.
 Quartz filters used in high-volume samplers cause high background XRF and PIXE analysis, filters used in the dichotomous samplers are preferable.
 PM2.5 collection by dichotomous samplers is typically involved by PIXE analysis.

G. Pérez
Sept. 14
2011
IAEA ARCAL Project RLA/7/ 011, ARCAL LXXX :
ASSESSMENT OF ATMOSPHERIC POLLUTANTS
BY PARTICLES (2005-2008)
Argentina, Chile, Costa Rica, Cuba,
Dominican Republic, Mexico,
Uruguay, Venezuela.
General Objectives:
• To impel the research in the field of monitoring air pollution with emphasis on particles.
• Sample collection of airborne particulate matter (including course and fine) simultaneously.
• The use of nuclear technology to characterize airborne particulate matter.
CEADEN

Infanta Ave. & Manglar,
Centro Habana,
Havana City, Cuba.
Urban site with high traffic and densely populated
23.12 N 82.4 W

G. Pérez
Sept. 14
2011

G. Pérez
Sept. 14
2011
sampling site

G. Pérez
Sept. 14
2011
Air Sampler type GENT with stacked filter unit for collecting the aerosol in two size fraction (PM
2,5 simultaneously.
and PM
10
)
Sampling period:
November 14, 2006 to April, 2007.
Total 5 months.
Sampling frequency:
Every second day with 24 h duration.

G. Pérez
Sept. 14
2011
Microbalance: Cahn C-35
Resolution: 0.1 µg

G. Pérez
Sept. 14
2011
60
55
50
45
40
35
30
25
20
15
10
5
0
coarse fraction
fine fraction
November December January
Descriptive statistics of the data (µg/m 3 ).
15
12
9
February March
30
27
Linear Regression (R = 0.676):
PM
2.5
= (0.308 +/- 0.008) * PM
10
24 Higher and lower
extrem values
21
18
6
3
8 16 24 32 40 48 56 64
PM
10
( m g/m
3
)
April

G. Pérez
Sept. 14
2011
Tandetron Accelerator, PIXE Analysis Lab. ININ, Mexico.
I = 15 nA
Q = 6 m
C
Ortec Si(Li) detector active area = 80 mm 2 resolution = 200 eV at 5.9 keV (Mn-Kα, 55 Fe)
Protons
2.5 MeV x

G. Pérez
Sept. 14
2011
1000
100
10
S
Cl
K
Ca
K 
Ca
K 
Ti Mn
V
Cr
Fe
K 
Fe
K 
Ni
Cu
Zn
K 
Zn
K 
Pb
Espectro CUB01F07
PM2.5
Br
14 elements were consistently detected in the samples
1
36
10000
100
Cl
S
K
1000
100
200
Ca
Ca
K

K 
300 400 500
Espectro CUB03G07
PM10
Fe
K

Ti
V
Cr
Mn Fe
K  Zn
K 
Ni
Cu
Zn
K 
Pb
Br
600
10
1
36 100 200 300 canal
400 500 600

G. Pérez
Sept. 14
2011
Softwares for spectra processing
AXIL & WINAXIL_4.5.3

G. Pérez
Sept. 14
2011
Partícula Fina
Media Max Min

(ng/m
3
) (ng/m
3
) (ng/m
3
) (ng/m
3
) n
Elemento
(MDL)
Media
Partícula Gruesa
Max Min

(ng/m
3
) (ng/m
3
) (ng/m
3
) (ng/m
3
) n
658.83 1711.14
121.68
43.33
68 S (28.50) 429.03
1178.91
91.46
28.92 71
65.77
315.37
11.78
4.05
63 Cl (11.60) 1835.54
4108.18
38.51
123.73 71
42.98
209.80
5.82
110.62
515.40
37.42
2.89
68 K (4.40) 117.36
252.72
31.40
7.91 71
7.65
68 Ca (2.80) 2029.86
4763.29
312.31
136.83 71
5.02
26.32
21.71
115.35
3.05
12.15
2.08
0.17
1.47
10.48
131.54
0.87
60.75
655.98
15.52
4.72
21.65
2.43
10.49
0.99
1.01
0.20
32
1.35
63
Ti (2.03)
V (1.88)
0.18
55 Cr (1.38)
22.08
13.55
2.89
115.08
56.99
7.08
3.03
1.91
1.39
1.49 71
0.85 66
0.18 62
0.43
41 Mn (0.87) 10.54
146.74
1.08
0.70 70
3.96
67 Fe (0.88) 235.49
852.97
27.39
15.65 70
0.26
55 Ni (0.95)
0.14
53 Cu (1.00)
3.72
3.78
11.85
11.64
0.96
1.02
0.24 66
0.25 70
18.99
293.11
9.09
13.67
1.20
5.43
1.26
0.56
68
60
Zn (1.20)
Br (5.30)
18.35
7.14
86.26
11.74
1.78
5.41
1.24 71
0.32 24
10.59
55.63
4.77
0.43
35 Pb (4.70) 10.45
39.79
4.82
0.53 48
Todos los datos están referidos a los elementos que fueron encontrados por encima del LMD.

G. Pérez
Sept. 14
2011
7000
6000
5000
4000
3000
2000
1000
0
November
18000
15000
12000
9000
6000
3000
0
November
PM2.5
S
Cl
K
Ca
Ti
V
Cr
Mn
Fe
Ni
Cu
Zn
Br
Pb
December
PM10
S
Cl
K
Ca
Ti
V
Cr
Mn
Fe
Ni
January February
Collection date
Cu
Zn
Br
Pb
December January February
Collection date
March
March
April
22
20
18
16
14
12
6
4
2
0
10
8
45
40
35
30
25
20
5
0
15
10
April

G. Pérez
Sept. 14
2011
• Descriptive statistic.
• Correlation Matrix.
• Principal Component Matrix.
• Rotated Principal Component Matrix by the maximum variability criteria.
• Component profiles and identification of the main sources (Factors).
• Scores of the found Factors.
• Contributions from sources to element concentrations.

G. Pérez
Sept. 14
2011
fine mode

G. Pérez
Sept. 14
2011
fine mode
Ca
Ti
V
Cr
Mn
S
Cl
K
Fe
Ni
Cu
Zn
Br
Pb
0
Source 1
Source 4
Source 2
Source 5
Source 3
20 40 60 80
Source contribution (%)
100

G. Pérez
Sept. 14
2011
fine mode

G. Pérez
Sept. 14
2011
coarse mode

G. Pérez
Sept. 14
2011
coarse mode
Source 1
Source 3
Source 2
Source 4
Ca
Ti
V
Cr
Mn
S
Cl
K
Fe
Ni
Cu
Zn
Br
Pb
0 20 40 60 80
Source contribution (%)
100

G. Pérez
Sept. 14
2011
coarse mode

G. Pérez
Sept. 14
2011
 Nuclear Analytical Techniques can be used for determination of the elemental composition of coarse and fine particulate matter: neutron activation analysis,
X-ray fluorescence, and ion beam analysis (PIXE, PIGE, PESA, RBS).

G. Pérez
Sept. 14
2011
 Nuclear Analytical Techniques can be used for determination of the elemental composition of coarse and fine particulate matter: neutron activation analysis,
X-ray fluorescence, and ion beam analysis (PIXE, PIGE, PESA, RBS).
 Since the various types of sources of particulate air pollutants are characterized by the elemental composition of the particles, knowledge of the elements in particles allows the identification of the origin of the particles and, thereby, leads to a quantitative apportionment of the existing types of sources.

G. Pérez
Sept. 14
2011
 Nuclear Analytical Techniques can be used for determination of the elemental composition of coarse and fine particulate matter: neutron activation analysis,
X-ray fluorescence, and ion beam analysis (PIXE, PIGE, PESA, RBS).
 Since the various types of sources of particulate air pollutants are characterized by the elemental composition of the particles, knowledge of the elements in particles allows the identification of the origin of the particles and, thereby, leads to a quantitative apportionment of the existing types of sources.
 In consequence, most important source types can be identified and decisions can be made on which source types it is most appropriate to reduce emissions.

G. Pérez
Sept. 14
2011
 Nuclear Analytical Techniques can be used for determination of the elemental composition of coarse and fine particulate matter: neutron activation analysis,
X-ray fluorescence, and ion beam analysis (PIXE, PIGE, PESA, RBS).
 Since the various types of sources of particulate air pollutants are characterized by the elemental composition of the particles, knowledge of the elements in particles allows the identification of the origin of the particles and, thereby, leads to a quantitative apportionment of the existing types of sources.
 In consequence, most important source types can be identified and decisions can be made on which source types it is most appropriate to reduce emissions.
 This would constitute a valuable step forward in air quality management, particularly in cases where emissions inventories are not established.

G. Pérez
Sept. 14
2011
 Nuclear Analytical Techniques can be used for determination of the elemental composition of coarse and fine particulate matter: neutron activation analysis,
X-ray fluorescence, and ion beam analysis (PIXE, PIGE, PESA, RBS).
 Since the various types of sources of particulate air pollutants are characterized by the elemental composition of the particles, knowledge of the elements in particles allows the identification of the origin of the particles and, thereby, leads to a quantitative apportionment of the existing types of sources.
 In consequence, most important source types can be identified and decisions can be made on which source types it is most appropriate to reduce emissions.
 This would constitute a valuable step forward in air quality management, particularly in cases where emissions inventories are not established.
 In our case, the results provided by PIXE in combination with appropriated statistical analysis allow us to identify the source profiles and contribution, providing important information about atmospheric pollution in selected site, necessary to develop strategies and to establish appropriate policies on pollution control.