Chemical
Characterization of Soil
Used as a Deposit for
Waste Originating From
the Manufacturing of
Products Based on
Fiberglass
Use of Energy
Dispersive X-Ray
Fluorescence
Spectrometry Proves
Effective for
Contaminant
Monitoring
Companies need to follow
environmental laws as
they affect their manu-
facturing systems, waste
handling, and the man-
agement of soil on their
properties to ensure that
their properties are either
improved or altered as
little as possible. Thus,
the objective of this
study was to evaluate
the use of energy disper-
sive X-ray fluorescence
spectrometry (EDXRF) to determine the
concentrations of elements present in the
soil at a manufacturer of products based
on fiberglass where wastes from produc-
tion activities have been deposited on the
property.
Introduction
The effects of inappropri-
ate landfilling of waste on
soil and in surface waters
are recognized as among
the most serious problems
of our time. The effects of
the release of waste into
nature are incalculable and
are reflected primarily by
Genesio Mario da Rosa
Arci Dirceu Wastowski
Angela Maria Mendonça
Márcia Gabriel
Renato Beppler Sphor
© 2017 Wiley Periodicals, Inc.
Published online in Wiley Online Library (wileyonlinelibrary.com)
DOI: 10.1002/tqem.21492
Environmental Quality Management / DOI 10.1002/tqem / Spring 2017 / 125
contamination of the water and soil and,
in turn, on the increasing prevalence of dis-
eases associated with environmental pollu-
tion (Oliveira & Jucá, 2004).
The presence of metals in the soil occurs
naturally from the weathering of an area’s
original rocks. However, elevated metals con-
tents have frequently been observed in some
areas as a result of anthropogenic activities,
primarily involving the deposition of indus-
trial wastes directly onto the ground (Reis
et al., 2007).
The proper disposal of wastes
is necessary to avoid
environmental pollution and
contamination, and predictions
must be made of the behavior
of heavy metals that have been
deposited on the soil.
There is the possibil-
ity that heavy met-
als can leach into the
soils where they were
applied or deposited
(Bertoncini & Matti-
azzo, 1999). Thus, the
proper disposal of wastes is necessary to
avoid environmental pollution and contam-
ination, and predictions must be made of
the behavior of heavy metals that have
been deposited on the soil. The redistri-
bution of the metals within the soil as
they transform from unstable forms to
more stable forms depends on the metal
species, the soil properties (e.g., pH, cation-
exchange capacity, and organic matter), and
the duration of exposure (McBride, 1995).
Metals Used in the Manufacture of
Fiberglass-Based Products
According to Araúja, Araúja, Pereira,
Ribeiro, and deMelo (2006), the increasing
production of consumer goods generates a
large volume of waste from the manufactur-
ing and sale of goods. While the recycling
of materials is an alternative to the reuse
of these “wastes,†and consequently plays
a role in reducing the environmental im-
pact that such wastes can cause, Araújo et al.
(2006) claim that just 50% of such wastes ar-
rive at sanitary landfills. Furthermore, a large
quantity of industrial wastes include plastics,
which are mixed with other materials and
additives to form composites. In this con-
dition, recycling of the component materi-
als becomes more difficult (Forlin & Faria,
2002).
In this context, fiberglass, a plastic matrix
reinforced with glass fibers, which is made
by the agglomeration of extremely thin glass
filaments added to polyester resin or other
types of resins, has a chemical composition
consisting primarily of 52–56% silicon diox-
ide or silica (SiO2), 12–16% aluminum oxide
(Al2O3), 16–25% calcium oxide (CaO), and
8–13% boron trioxide (B2O3) (Orth, Baldin,
& Zanotelli, 2014; Smith, 2000).
In the process of manufacturing
fiberglass-based products, the glass fibers
used to reinforce the product receive a cov-
ering called “encimagem,†which improves
resistance and is made with coupling agents
compatible with the polyester resins, vinyl
ester, and epoxy. The short glass fiber type E
(E-glass), obtained from a mixture of oxides
of silicon (Si), aluminum (Al), boron (B),
calcium (Ca), and magnesium (Mg) (e.g.,
borosilicate of alumina and calcium), is usu-
ally used as thermoplastic reinforcements as
low-cost alternatives to aramid and carbon
(Larena, De la Ordem, & Urreaga, 1992),
and it results in improved material proper-
ties, such as impact resistance and rigidity
(Pizzitola, Machado, & Wiebeck, 2011;
Wambua, Ivens, & Verpoest, 2003).
Other commercialized glass fibers were
analyzed by Dovlitova, Boldyreva, and
Malakhov (2011). One of these had in its
composition sodium and aluminum silicates
in concentrations of 75–77% SiO2, 17–19%
sodium oxide (Na2O), 3–5% Al2O3, and
<1% CaO. Another had as its composition
126 / Spring 2017 / Environmental Quality Management / DOI 10.1002/tqem Genesio Mario da Rosa, Arci Dirceu Wastowski, Angela Maria
Mendonça, Márcia Gabriel, and Renato Beppler Sphor
sodium zirconium silicate and titanium with
concentrations of 66–70% SiO2, 12–24%
Na2O, and 9–14% zirconium dioxide (ZrO2).
In addition to these main components, the
commercial glass fibers showed impurities
in the form of oxides: Ca, Mg, iron (Fe), and
titanium (Ti), with total concentrations of
1.0–2.0%.
Analytical Techniques for Characterizing
Glass Fiber
Many analytical techniques may be used
to determine the chemical composition
and structure of glass fiber, including in-
frared spectroscopy, X-ray photoelectron
spectroscopy, nuclear magnetic resonance
spectroscopy, and atomic emission spec-
troscopy by inductively coupled plasma
(Glazneva et al., 2012).
The conventional techniques used for
determining the chemical composition are
time consuming, result in high costs for
reagents, and require several steps to quan-
tify all of the elements. EDXRF stands out as
an important alternative method to stream-
line the process of chemical characteriza-
tion of fiberglass waste by allowing for more
rapid analysis than other methods. Increas-
ingly, it is being used in the chemical char-
acterization of various materials, such as
soil, rocks (Dantas, Dantas, Van’t Dack, &
Van Griekem, 1981; Wastowski, da Rosa,
Cherubin, & Rigon, 2010), ceramics, biolog-
ical materials (Albers, Melchiades, Machado,
Baldo, & Boschi, 2002; Ferreira, Fabris, San-
tana, & Curi, 2003), particles suspended in
the air (Adeloju, Bond, & Briggs, 1985; Bona,
Sarkis, & Salvador, 2007), and liquids (Pataca,
Bortoleto, & Bueno, 2005). This new EDXRF
technique offers several advantages in the
chemical analysis of elements, such as:
• Adaptability to automation,
• Multielement quick analysis (very im-
portant because of the interdependence
among the micronutrients in biological
systems),
• Simplified sample preparation,
• Detectability limits within those required
for many biological samples, and
• Low reagent and time costs.
EDXRF stands out as an
important alternative method to
streamline the process of
chemical characterization of
fiberglass waste by allowing for
more rapid analysis than other
methods.
For analyses of glass fiber composition,
Luo et al. (2011) successfully used a portable
X-ray fluorescence spectrometer by disper-
sive energy to identify the elements Na and
Mg that were used in the characterization of
58 glass vase fragments found in Xinjiang,
China. Mashin,
Onicheva, Tumanova,
and Rudnevskii (2000)
conducted a procedure
for determining chalco-
genide glass composition
using X-ray fluorescence
spectrometry. The developed methodol-
ogy was used to monitor the technological
conditions for the production of chalco-
genide glasses and subsequent monitoring
of the composition in the preparation
process; this control is performed with
high speed, without destruction of the
sample, and with the necessary precision.
The objective of this study was to use
EDXRF to identify the possible accumula-
tion of chemical elements in the soil due to
the deposition of residues of fiberglass-based
products by industry.
Study Location
This study was conducted at the Bakof In-
dustry and Trade of Fiberglass Ltda in the
city of Frederico Westphalen, in the Brazil-
ian state of Rio Grande do Sul (RS). The
company is involved in the manufacturing
of water tanks, dish antennas, septic tanks,
Chemical Characterization of Soil Used for Waste Deposition Environmental Quality Management / DOI 10.1002/tqem / Spring 2017 / 127
tanks for washing, among other items. These
products are manufactured using chemical
components derived from polyethylene and
fiberglass. The study area is located at coordi-
nates 27◦ 23’06.86 South, 53◦ 23’45.08 West,
at an altitude of 658 meters (m) above mean
sea level, in the city of Frederico Westphalen.
Materials and Methods
Sample Collection
Samples of soil and deposited waste were
collected from the studied area to assess the
concentrations of chemicals in the soil. Col-
lection of soil samples was performed using
an auger at 11 sampling points (P1–P11) that
best represent the area under study as shown
in Exhibit 1. These sampling points were
georeferenced with a GARMIN global posi-
tioning satellite device.
At every point, two
samples were collected
at depths of 0–15 cen-
timeters (cm) and 15–
30 cm. Each sample
was placed in a plastic bag and marked with
its location and depth. At points 5 and 9, the
samples were collected at depths of 0–2 cm,
and at point 7, at a depth of 0–10 cm. These
variations in sampling depth were required
due to the presence of an outcropping of ma-
trix rock of basaltic formation (the C hori-
zon), which made it impossible to collect soil
samples at greater depths in these locations.
Samples of soil and deposited
waste were collected in the
studied area to assess the
concentrations of chemicals in
the soil.
“Witness†and Offsite Soil Sample Collection
Sampling point P12 was chosen to func-
tion as a “witness†or control sample be-
cause its location is some distance away
from the waste disposal area on the com-
pany’s property. According to the company’s
historical records of soil use, that partic-
ular area has not been influenced by an-
thropogenic activities, such as the disposal
of wastes or scraps from its manufactur-
ing processes. In addition, soil from a na-
tive forest, which was collected 2 kilometers
distant from the study area (sample ST), was
used to confirm the presence of chemical el-
ements in the soil of the region, and thus
provide a comparison to the observed results
from analyses of the samples collected in the
study area.
Waste Sample Collection
Samples of wastes from the company’s
manufacturing processes, which are being
deposited on the ground in the study area,
were also collected for analyses. These wastes
were defined as basic blue residue (RBA) and
fiber waste (RF), and its physical composi-
tion is formed by the agglomeration of very
thin glass filaments added to polyester resin
or other resins. These wastes were analyzed,
and the results of their chemical composi-
tions were used for statistical evaluation with
the values observed in the soil samples by us-
ing Pearson’s correlation coefficient.
Sample Analyses
Analyses were performed in the Research
and Chemical Analysis Laboratory (LAPAQ),
located on the premises of the Center for
Higher Education North (CESNORS) of Fed-
eral University of Santa Maria (UFSM). Soil
chemical composition was evaluated with an
emphasis on those chemical elements that
are detrimental to organic elements. Before
analysis, the samples were oven-dried at 105
degrees Celsius (â—¦C) for 24 hours until they
achieved constant weights. Posteriorly, they
were ground and pressed (10 tons for 10 min-
utes) to form tablets. These tablets were used
for chemical analysis in the EDX-720 equip-
ment of the EDXRF (Wastowski et al., 2010).
128 / Spring 2017 / Environmental Quality Management / DOI 10.1002/tqem Genesio Mario da Rosa, Arci Dirceu Wastowski, Angela Maria
Mendonça, Márcia Gabriel, and Renato Beppler Sphor
Exhibit 1. Georeferenced Sketching of the Study Site
and the Sample Collection Points
Results and Discussion
The table in Exhibit 2 shows the chem-
ical element concentrations present in the
soil profile in the layers from 0–15 cm to
15–30 cm along with the chemicals found in
the industrial wastes (RBA and RF) collected
at the site.
The studied soil is classified as red latosol,
and it has in its structural composition high
concentrations of iron oxide and clay (Streck
et al., 2008), which explains the high lev-
els of iron and silicon found in the analyses
of soils collected from all sampling points.
As Exhibit 3 shows, at the points where
the iron and silicon contents are signifi-
cant, we can observe the declivity of the
terrain, where an increased flow of rain-
fall water and consequent surface runoff has
resulted in decreased soil organic matter.
The quantification of the flows and their
directions reveal the composition and ori-
gin of the sediments. A key challenge in
this context is the quantification of human
impacts caused in the area (Brown et al.,
2009).
The table in Exhibit 2 shows a great
presence of silicon and calcium in the
composition of the RBA and RF, but these el-
ements have not contributed significantly to
the alteration of the elements in the soil. This
statement was confirmed by the analysis of
the correlation between the elements present
in the soil of the study area with the elements
present in the nonanthropic soil, a correla-
tion between the factors of 0.97.
The chemicals commonly associated
with toxicity or soil pollution are arsenic
(Ar), cadmium (Cd), cobalt (Co), chromium
(Cr), copper (Cu), lead (Pb), mercury (Hg),
molybdenum (Mo), nickel (Ni), selenium
(Se), and zinc (Zn) (Nellessen & Fletcher,
1993). The table in Exhibit 2 shows that Ar,
Cd, Co, Pb, Hg, Mo, Ni, and Se were not
found in the soil analyzed for this study. In
fact, from the elements cited by Nellessen
and Fletcher (1993), only Cr, Cu, and Zn
were found. Of these, only Cu and Zn are
present in the composition of RBA and RF
(Nellessen & Fletcher, 1993). Cr is not de-
tected in the composition of the latter two
Chemical Characterization of Soil Used for Waste Deposition Environmental Quality Management / DOI 10.1002/tqem / Spring 2017 / 129
Exhibit 2. Results of Soil Analyses of the Soil Profiles Collected at Depths of 0–15 cm and 15–30 cm
Determined by EDXRF
Depth 0–15 cm milligrams per kilogram (mg/kg)
RBA RF P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 ST
Si 53.80 55.66 157.08 156.02 152.01 123.49 150.92 167.86 148.06 144.01 119.12 169.50 178.5 171.66 176.14
Fe 2.25 1.13 147.53 143.51 158.70 112.79 112.87 128.33 142.58 163.24 119.56 189.06 182.4 121.98 152.94
Al 1.,90 13.14 99.95 110.74 110.07 80.51 82.44 102.40 84.73 108.98 76.21 89.88 88.46 88.26 64.75
Ti 3.33 0.04 16.96 13.04 14.79 13.32 12.09 9.91 14.44 19.59 13.93 24.74 25.97 10.79 37.02
Ca 77.63 72.31 5.65 6.84 7.07 3.61 16.34 7.60 3.53 2.77 4.95 2.79 1.68 5.71 2.82
Ba nd nd 4.50 7.77 8.72 4.05 5.50 2.81 6.40 4.85 7.61 11.08 11.68 5.02 13.22
S 2.48 2.42 3.71 3.28 5.64 2.76 2.34 4.40 5.03 3.56 3.07 7.51 3.93 4.22 6.37
Mn 0.04 0.03 2.37 2.30 3.11 2.15 2.04 2.02 3.00 2.98 2.61 4.17 4.28 2.98 4.33
K 0.60 0.71 1.55 2.15 1.42 1.20 2.08 5.26 2.87 1.10 1.83 2.41 2.70 8.59 1.57
V nd nd 0.97 1.03 1.07 0.78 0.77 0.63 0.90 1.07 0.98 1.52 1.50 0.69 1.81
Cu 0.06 0.05 0.51 0.44 nd 0.36 nd 0.45 0.40 0.47 0.32 0.50 0.45 0.41 0.43
Zr 0.03 nd 0.40 0.41 0.44 0.32 0.35 0.39 0.42 0.51 0.38 0.64 0.66 0.38 0.71
Zn 0.03 0.04 0.21 0.20 0.21 0.15 nd 0.19 0.16 0.21 0.15 0.29 0.20 0.16 0.22
Cr nd nd 0.12 0.12 0.14 0.11 0.09 0.15 0.12 0.14 0.09 0.09 0.10 0.10 0.14
Sr 0.16 0.36 0.09 0.09 0.09 0.07 0.16 0.08 0.04 nd 0.06 nd nd 0.07 0.04
Depth 15–30 cm milligrams per kilogram (mg/kg)
Si 53.80 55.66 164.69 157.08 152.06 141.88
*
159.87
*
149.30
*
169.30 165.53 164.69 176.14
Fe 2.25 1.13 115.36 138.42 147.44 127.84
*
132.86
*
172.93
*
167.24 180.38 115.36 152.94
Al 10.90 13.14 85.90 111.99 106.74 91.14
*
92.76
*
110.22
*
87.69 84.02 85.90 64.75
Ti 3.33 0.04 8.40 13.47 15.21 14.10
*
12.87
*
19.08
*
22.76 26.61 8.40 37.02
Ca 77.63 72.31 5.44 6.87 4.25 4.74
*
9.81
*
2.82
*
2.57 1.62 5.44 2.82
Ba nd nd 5.11 6.50 6.92 5.81
*
5.78
*
7.81
*
7.61 9.16 5.11 13.22
S 2,48 2.42 3.50 4.00 3.78 3.18
*
6.84
*
5.26
*
4.89 3.74 3.50 6.37
Mn 0.04 0.03 2.55 2.25 2.69 2.85
*
2.70
*
3.22
*
3.61 4.47 2.57 4.33
K 0.60 0.71 8.46 2.16 1.71 1.52
*
4.50
*
1.26
*
2.83 2.34 8.46 1.57
V nd nd 0.74 0.89 0.94 0.79
*
7.98
*
1.10
*
1.43 1.42 0.74 1.81
Cu 0.06 0.05 nd 0.42 0.47 0.42
*
0.47
*
0.51
*
0.42 0.48 nd 0.43
Zr 0.03 nd 0.37 0.42 0.41 0.35
*
0.38
*
0.53
*
0.55 0.64 0.37 0.71
Zn 0.03 0.04 0.14 0.20 0.20 0.16
*
0.30
*
0.20
*
0.19 0.22 0.14 0.22
Cr nd nd 0.11 0.14 0.15 0.15
*
0.12
*
0.14
*
0.09 0.11 0.11 0.14
Sr 0.16 0.36 0.05 0.08 0.08 0.12
*
0.09
*
nd
*
nd nd 0.05 0.0
Abbreviations: RBA, blue base residue; F, fiber residue; ST, witness soil; nd, not detected.
∗Values of points 5, 7, and 9 in the depth of 15–30 do not exist because of rock outcrop (C horizon).
wastes. However, the levels of Cu and Zn
found in the soil samples collected from the
sampling area do not differ statistically from
the values observed in the soil collected from
the witness or control soil sample, P12, or
in the soil collected in the native forest area,
ST, meaning that Cr, Cu, and Zn are part of
the natural composition of the soil.
The chemical element Al showed in-
creases in concentrations in the soil collected
from points 6 to 8 when compared to the
soil collected from the native forest site, ST;
however, Al was not present in the sam-
ples in concentrations that would character-
ize it as a soil contaminant. The increase
in aluminum levels can be related to the
reduction of organic matter in that portion
of the study area, as the soil area is uncov-
ered (without vegetation coverage) and sub-
ject to the action of runoff. Such a result was
also observed by Lima et al. (2007), where the
authors claimed that with the reduction the
130 / Spring 2017 / Environmental Quality Management / DOI 10.1002/tqem Genesio Mario da Rosa, Arci Dirceu Wastowski, Angela Maria
Mendonça, Márcia Gabriel, and Renato Beppler Sphor
Exhibit 3. Tracks of Concentrations of Iron and Silica Over the Area in the Di-
rection of Land Declivity
organic matter, the aluminum content in the
analyzed soil increased.
According to Sharpley et al. (2008), losses
of nutrients in the soil happen because the
nutrients are connected to the soil parti-
cles, thereby reaffirming that erosion control
measures should be prioritized, both to avoid
the loss of nutrients and to avoid contamina-
tion of disposal areas.
Correlation Analysis
A correlation analysis between the pro-
files of soil collected from 0 to 15 cm deep
and from 15 to 30 cm deep revealed differ-
ences between the depth profiles. A change
in soil texture, which is characterized as pe-
dogenic evolution (Kalbus et al., 2012), is ap-
parent. In contrast, there was no leaching of
chemicals from the surface horizon to the
subsurface horizon, thereby demonstrating
that the elements present in the composition
of the RBA and RF wastes did not contribute
to soil contamination.
The data from the statistical correla-
tion analysis, which is shown in the ta-
ble in Exhibit 4, allow us to conclude
that contamination by elements from the
products used at the study location is not
present in the soil. In the soil samples
collected at the two analyzed depths (i.e.,
0–15 cm and 15–30 cm), the observed
correlation between the soil collected in the
study area and the soil from the witness
and control samples (P12 and ST) was on
average 0.90, and the correlation between
these soils and the waste products analyzed
(i.e., RBA and RF) was on average 0.30 for
the two sampling depths. These results dif-
fer from what we expected regarding the
classification of waste, a II A-class of pol-
lutants, which is not inert, and that, over
time, undergoes some sort of change or de-
composition (Zilber, Caruzzo, & De Abreu
Campanário, 2011).
We can infer that these results are due
to the fact that the wastes deposited and in
contact with the soil in the study area were
not deposited in a particle size that would
allow for its immediate weathering, or that
the exposure time of these products to the
soil (less than 15 years) has been insufficient
to have allowed the weathering of elements
Chemical Characterization of Soil Used for Waste Deposition Environmental Quality Management / DOI 10.1002/tqem / Spring 2017 / 131
Exhibit 4. Correlation Between Chemical Elements Present in the Sample Profiles at Depths 0–15 cm
and 15–30 cm in the Soil With Wastes (RBA and RF)
Depth 0–15 cm milligrams per kilogram (mg/kg)
RBA RF P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
Soil 0.298 0.309 0.977 0.965 0.965 0.975 0.974 0.968 0.984 0.962 0.978 0.985 0.991 0.976
RBA 1.000 0.997 0.285 0.289 0.240 0.285 0.349 0.335 0.276 0.202 0.273 0.216 0.236 0.348
RF – 1.000 0.302 0.308 0.250 0.303 0.362 0.359 0.292 0.210 0.287 0.221 0.243 0.372
P1 – – 1.000 0.998 0.998 1 0.991 0.994 0.999 0.995 0.999 0.989 0.991 0.988
P2 – – – 1.000 0.998 0.999 0.990 0.995 0.994 0.994 0.997 0.980 0.983 0.986
P3 – – – – 1.000 0.997 0.982 0.987 0.996 0.998 0.999 0.988 0.987 0.977
P4 – – – 1.000 0.991 0.995 0.997 0.994 0.998 0.986 0.989 0.989
P5 – – – – – – 1.000 0.997 0.988 0.971 0.986 0.968 0.977 0.997
P6 – – – – – – – 1.000 0.990 0.979 0.989 0.970 0.976 0.997
P7 – – – – – – – – 1.000 0.993 0.999 0.995 0.996 0.987
P8 – – – – – – – – 1.000 0.997 0.989 0.987 0.967
P9 – – – – – – – – – – 1.000 0.993 0.994 0.983
P10 – – – – – – – – – – – 1.000 0.999 0.968
P11 – – – – – – – – – – – 1.000 0.977
P12 – – – – – – – – – – – – – 1.000
Depth 15–30 cm milligrams per kilogram (mg/kg)
Soil 0.298 0.309 0.973 0.963 0.969 0.975
*
0.978
*
0.964
*
0.990 0.988 0.973
RBA 1.000 0.997 0.331 0.296 0.268 0.292
*
0.331
*
0.199
*
0.246 0.219 0.331
RF – 1.000 0.353 0.317 0.285 0.310
*
0.351
*
0.205
*
0.255 0.223 0.353
P1 – – 1.000 0.997 0.999 1.000
*
0.997
*
0.994
*
0.995 0.989 0.987
P2 – – – 1.000 0.999 0.999
*
0.995
*
0.992
*
0.988 0.979 0.986
P3 – – – – 1.000 0.997
*
0.991
*
0.998
*
0.991 0.986 0.976
P4 – – – – – 1.000
*
0.997
*
0.993
*
0.993 0.986 0.988
P5 – – – – – –
* * * * * * * *
P6 – – – – – – – 1.000 – 0.970 – 0.983 0.969 0.997
P7 – – – – – – – –
* * * * * *
P8 – – – – – – – – – 1.000
*
0.983 0.970 0.997
P9 – – – – – – – – – –
* * * *
P10 – – – – – – – – – – – 1.000 0.994 0.986
P11 – – – – – – – – – – – – 1.000 0.965
P12 – – – – – – – – – – – – – 1.000
Abbreviations: RBA, blue base residue; F, fiber residue; ST, witness soil; nd, not detected.
∗Values of points 5, 7, and 9 in the depth of 15–30 do not exist because of rock outcrop (C horizon).
from the RBA and RF wastes and their subse-
quent leaching into the soil.
Conclusions
The chemical elements in the wastes of
the blue base and fiber residues that make
up fiberglass products did not contaminate
the soil where they were deposited. One
can infer that the absence of correlation
between the chemical elements of the in-
dustrial waste and the soil may be related
to the short exposure time at the study
site.
The variations in the concentrations of
the chemical elements among the sampling
points in the study area (points P1 to P11)
are related to weathering (runoff of rainfall
water) caused by anthropogenic influence on
site and not to the leaching of the chemical
elements from the wastes deposited there.
132 / Spring 2017 / Environmental Quality Management / DOI 10.1002/tqem Genesio Mario da Rosa, Arci Dirceu Wastowski, Angela Maria
Mendonça, Márcia Gabriel, and Renato Beppler Sphor
Finally, use of the EDXRF is efficient for
monitoring areas with possible environmen-
tal contamination by chemicals.
Acknowledgments
We are thankful to the company Bakof In-
dustry and Trade of Fiberglass Ltda for their
aid and their permission to use the area for
study.
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134 / Spring 2017 / Environmental Quality Management / DOI 10.1002/tqem Genesio Mario da Rosa, Arci Dirceu Wastowski, Angela Maria
Mendonça, Márcia Gabriel, and Renato Beppler Sphor
Genesio Mario da Rosa is an agronomist and a doctor in agricultural engineering in the Department of Forest Engineering,
Federal University of Santa Maria, ZIP 98400-000 Frederico Westphalen, RS, Brazil.
Arci Dirceu Wastowski is an industrial chemist and a doctor of chemistry, Department of Agronomy, Federal University of
Santa Maria, ZIP 98400-000 Frederico Westphalen, RS, Brazil.
Angela Maria Mendonça is a forest engineer with a master in environmental engineering, Department of Forest Engineering,
Federal University of Santa Maria, ZIP 98400-000 Frederico Westphalen, RS, Brazil.
Márcia Gabriel is an agronomist with a master in agronomy and environment, Department of Agronomy, Federal University
of Santa Maria, ZIP 98400-000 Frederico Westphalen, RS, Brazil.
Renato Beppler Sphor is an agronomist and a doctor in agricultural engineering, Department of Forest Engineering, Federal
University of Santa Maria, ZIP 98400-000 Frederico Westphalen, RS, Brazil.
Chemical Characterization of Soil Used for Waste Deposition Environmental Quality Management / DOI 10.1002/tqem / Spring 2017 / 135
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