Discuss the physical, chemical, and physicochemical industrial and hazardous waste treatment technologies.

Characterization of Soil
Used as a Deposit for
Waste Originating From
the Manufacturing of
Products Based on

Use of Energy

Dispersive X-Ray


Spectrometry Proves

Effective for



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


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,


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


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


• 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


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.,


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



169.30 165.53 164.69 176.14

Fe 2.25 1.13 115.36 138.42 147.44 127.84



167.24 180.38 115.36 152.94

Al 10.90 13.14 85.90 111.99 106.74 91.14



87.69 84.02 85.90 64.75

Ti 3.33 0.04 8.40 13.47 15.21 14.10



22.76 26.61 8.40 37.02

Ca 77.63 72.31 5.44 6.87 4.25 4.74



2.57 1.62 5.44 2.82

Ba nd nd 5.11 6.50 6.92 5.81



7.61 9.16 5.11 13.22

S 2,48 2.42 3.50 4.00 3.78 3.18



4.89 3.74 3.50 6.37

Mn 0.04 0.03 2.55 2.25 2.69 2.85



3.61 4.47 2.57 4.33

K 0.60 0.71 8.46 2.16 1.71 1.52



2.83 2.34 8.46 1.57

V nd nd 0.74 0.89 0.94 0.79



1.43 1.42 0.74 1.81

Cu 0.06 0.05 nd 0.42 0.47 0.42



0.42 0.48 nd 0.43

Zr 0.03 nd 0.37 0.42 0.41 0.35



0.55 0.64 0.37 0.71

Zn 0.03 0.04 0.14 0.20 0.20 0.16



0.19 0.22 0.14 0.22

Cr nd nd 0.11 0.14 0.15 0.15



0.09 0.11 0.11 0.14

Sr 0.16 0.36 0.05 0.08 0.08 0.12



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



0.990 0.988 0.973

RBA 1.000 0.997 0.331 0.296 0.268 0.292



0.246 0.219 0.331

RF – 1.000 0.353 0.317 0.285 0.310



0.255 0.223 0.353

P1 – – 1.000 0.997 0.999 1.000



0.995 0.989 0.987

P2 – – – 1.000 0.999 0.999



0.988 0.979 0.986

P3 – – – – 1.000 0.997



0.991 0.986 0.976

P4 – – – – – 1.000



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.

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


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.

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


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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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