Feasibility of Bioremediation of Iron-Contaminated Water Using Trichonephila Clavipes Spider Webs

Abstract

Heavy metals are of great environmental and sanitary importance due to the toxicity they generate; therefore, a wide variety of methods for elimination in water has been studied. One of the approaches employed is bioremediation, which involves the use of biomass (microorganisms or plants), living plants (phytoremediation), or biomaterials to eliminate these elements. In this study, we investigated the technical feasibility of using the Trichonephila clavipes spider web as a biomaterial for iron removal from water by bioremediation. A bibliometric analysis was carried out, where the process variables and experimental design were defined using the Response Surface Methodology, and the iron concentrations were measured before and after the experiment using X-ray fluorescence spectroscopy by dispersive energy. The model predicted an iron removal of 91.82% using 28.09 hr, 81.42 ppm of iron, and 0.062 g of spider web, with a relative error of 0.043 of the true value. This work is novel and presents a new methodology for the bioremediation of water contaminated with iron using spider webs. The results indicate a high efficiency in the removal of iron, which could have important implications in solving environmental and health problems associated with the presence of heavy metals in water.

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DOI: 10.1177/11786221241272388
Introduction
Many communities lack access to good quality drinking water
because of the use of raw water from rivers (Calderón Núñez,
2020). Pollution of rivers usually occurs due to the release of sub-
stances derived from human activities, such as mining waste that
contains heavy metals and other harmful agents for health and
the natural environment (Guillén Pérez, 2020; Vergara Buitrago &
Rodríguez-Aparicio, 2021). Iron is one of the common contami-
nants in rivers due to mining (Vergara Buitrago & Rodríguez-
Aparicio, 2021), and its presence can affect the color, taste, and
smell of the water (Organizacin Mundial de la Salud [OMS],
2018), as well as cause poisoning in high concentrations
(Bustamante-Cristancho, 2011).
Iron ingestion causes a disease called hemochromatosis,
which causes liver and heart failure, vomiting, skin damage,
joint pain, and weight loss (Dey, Kotaru etal., 2022). The nor-
mal level of iron in the blood can vary depending on age, sex,
and other factors. However, the level recommended by the
Food and Agriculture Organization of the United Nations for
irrigation water is 5 mg/L = 5 ppm. The US EPA secondary
drinking water standard, MCL, is 0.3 mg/L = 0.3 ppm.
(Standard Methods Committee of the American Public Healt
h Association, American Water Works Association, and Water
Environment Federation, 2018).
For the treatment of contaminated water, bioremediation
has been used using plants, microorganisms, and biomaterials
(Carreño-Sayago, 2015; Paredes & Ñique, 2016). In particular,
to remove iron, biosorption has been used (Dey, Sreenivasulu
etal., 2022).
Currently, spider web-shaped electrospun nanofibers are
being fabricated to separate water from oil in wastewater treat-
ment. (Ning et al., 2023). Natural spider webs of Pholcus
phalangioides (Pholcidae), Eratigena atrica and Agelena labiryn-
thica (Agelenidae) and Linyphia triangularis (Linyphiidae)
have been used for magnetic biomonitoring of iron in air
(Górka etal., 2018; Rachwał etal., 2018) . However, in the lit-
erature, few reports address the use of spider webs as a method
to remove iron from contaminated water.
The spider web has a diversity of mechanical, thermal and
biomedical properties that have been widely studied (Mann
etal., 2023); however, to date, there are no reports in the litera-
ture on its capabilities as a bioremediation agent for contami-
nated waters. Resistance studies of this type of fabric have
reported values of 6308.84 kPa (Carbonell Plata, 2008), a ther-
mogravimetric stability lower than 210°C (Xing etal., 2014),
and its biocompatibility evidenced the growth of animal cells
on the fabric (Bergmann etal., 2022).
This silk composed of amino acids such as glycine, allain,
and sericin, which have the possibility of charging and interact-
ing with metal ions (Römer & Scheibel, 2008). Adsorption can
occur due to various mechanisms, such as electrostatic attrac-
tion, the formation of complex chemicals, and the interaction
of covalent bonds between the spider web and contaminants.
Currently, among the technological advances, PCL and PUR
Feasibility of Bioremediation of Iron-Contaminated
Water Using Trichonephila Clavipes Spider Webs
Valentina Martinez Ruiz1, Victoria Eugenia Pizza Londoño1,
Marisol Gordillo Suarez1, Javier Jurado-Rosero1 and
Martha Constanza Daza Torres2
1Universidad Autónoma de Occidente, Cali, Colombia. 2Universidad del Valle, Cali, Colombia.
ABSTRACT: Heavy metals are of great environmental and sanitary importance due to the toxicity they generate; therefore, a wide variety of
methods for elimination in water has been studied. One of the approaches employed is bioremediation, which involves the use of biomass
(microorganisms or plants), living plants (phytoremediation), or biomaterials to eliminate these elements. In this study, we investigated the tech-
nical feasibility of using the Trichonephila clavipes spider web as a biomaterial for iron removal from water by bioremediation. A bibliometric
analysis was carried out, where the process variables and experimental design were defined using the Response Surface Methodology, and the
iron concentrations were measured before and after the experiment using X-ray fluorescence spectroscopy by dispersive energy. The model
predicted an iron removal of 91.82% using 28.09 hr, 81.42 ppm of iron, and 0.062 g of spider web, with a relative error of 0.043 of the true value.
This work is novel and presents a new methodology for the bioremediation of water contaminated with iron using spider webs. The results indi-
cate a high efficiency in the removal of iron, which could have important implications in solving environmental and health problems associated
with the presence of heavy metals in water.
KEYWORDS: Iron-polluted water, biomaterial, adsorption, response surface methodology
RECEIVED: March 19, 2024. ACCEPTED: July 12, 20 24.
TYPE: Research Article
CORRESPONDING AUTHOR: Marisol Go rdillo Su arez, Faculty of Engi neerin g, Univers idad
Autónoma de Occidente, Cali 760030, Colombia. Email: mgordillo@uao.edu.co
1272388ASW0010.1177/11786221241272388Air, Soil and Water ResearchRuiz et al.
research-article2024

2 Air, Soil and Water Research
polymer membranes for water treatment, with the aim of
detoxifying waters contaminated with heavy metals (Tran-Ly
etal., 2020).
The iron removal can be explained through a process called
biosorption, in which biological materials such as spider webs
can adsorb and concentrate heavy metals or other water pollut-
ants. Adsorption can be caused by several mechanisms, such as
electrostatic attraction, the formation of chemical complexes,
and the interaction of covalent bonds between the spider web
and contaminants (Tran-Ly etal., 2020).
In the specific case of spider web, it has been shown that its
ability to adsorb metals such as Fe is due to the presence of
proteins, carbohydrates, and other organic components con-
taining functional groups such as carboxyls, amines, and sulfhy-
dryls. These functional groups have a high affinity for metal
binding, and the spider web structure provides a porous and
fibrous surface for metal adsorption (Zhou et al., 2021). In
addition, the negative charge of the carboxyl and sulfhydryl
groups present on the spider web attract the positively charged
Fe ions. The electrostatic interaction between the functional
groups and Fe ions, as well as the formation of chemical com-
plexes between them, also contribute to the adsorption of Fe on
the spider web (Pelit etal., 2011).
Specifically, the functional groups of the Trichonephila clavi-
pes spider web may refer to the biochemical characteristics or
chemical compounds present in their body tissues or silks.
Some functional groups that could be present in Trichonephila
clavipes include fibrous proteins, lipids, carbohydrates, nucleic
acids, and enzymes.
We propose the analysis methodology for this research
through Response Surface Methodology (RSM), which allows
us to obtain optimal removal values through the effects of time
(hr), iron concentration (ppm), and spider silk weight (g).
There is a specific research gap in this case because the condi-
tions for the remediation of iron in water have been evaluated
using different materials, and they have not used spider webs
for this purpose. Nevertheless, the results obtained demon-
strate the remedial capacity of spider web and possible biore-
mediation mechanisms used by this process.
The objective of this study was to determine the technical
feasibility of using the spider web Trichonephila clavipes as an
innovative and effective method to remove iron from contami-
nated water, thus providing a potentially affordable and sustain-
able solution to improve water quality in affected communities.
Materials and Methods
First, a bibliometric network was used, specifically the Science
Direct database, which consisted of 622 articles, for the selec-
tion of process variables based on the keywords: Biomaterial,
bioremediation, iron, and adsorption. In this study, we found
that the examined articles used the variables reaction time,
heavy metal concentration, and biomaterial weight more fre-
quently in the tests. Therefore, we decided to select these
variables and based on them we considered the experimental
design. Subsequently, we conducted a pilot test to evaluate the
biomaterial’s behavior in terms of iron adsorption. In this test,
we established the following experimental conditions: a dura-
tion of 8 (hr), 0.1 g of cobweb, and three concentrations of iron
(1, 2, and 3 ppm). Based on the results obtained in this test, we
conclude that it is necessary to increase both the exposure time
and the initial concentration. The duration of the study was
approximately 12 months.
We used the following materials: Cobweb obtained from
the Trichonephila clavipes species, PanReac brand iron analyti-
cal grade (High purity 97% anhydrous iron (III) chloride solu-
tion, analytical grade), and deionized water. We collect the
cobwebs manually at the Cali Zoo Foundation, avoiding con-
tact with spiders. We took extra care to minimize any distur-
bance to their environment and ensure their safety and
well-being. In the collection, we use a 10 cm × 10 cm box and a
1.5 m stick to access the spider webs in different areas. In addi-
tion, we collect the spider web once a month so as not to affect
the population of individuals.
We transport the collected spider webs to the laboratory to
remove food remains, branches, and larger leaves. For cleaning,
we use a Leica S6D stereoscope to eliminate any element that
could affect the results. In addition, we ensured that the collec-
tion process did not alter the quality of the spider silk samples
obtained, thus guaranteeing the validity and reliability of the
research results.
Materials
We used an Energy Dispersive X-ray F luorescence Spectroscope
(EDX Shimadzu 7000) to obtain the readings of the initial and
final iron content (ppm) in each of the water samples. When
preparing ferric chloride, iron is in the Fe + 3 state and oxi-
dized to Fe + 2. The pH of the tests was between 3.0 and 3.2.
An acid pH generated by the ferric chloride reagent. The
experiment was carried out in a beaker, at a volume of 40 ml, to
quantify the remaining ferric iron (Fe2⁺) in a solution, we per-
form a chemical oxidation using a reducing agent; we use titri-
metric titration with potassium dichromate. (Bosch Ariño,
1954; Szabó & Sugár, 1952) With the initial iron results, we
adjusted the actual iron concentrations proposed in the experi-
ment design (Figure 1).
Methods
Based on the results of the pilot study, we established the
experimental conditions that were determined and described in
Table 1. As a response and/or dependent variable, we measured
the percentage of iron removal in water and found that the
selected variables (time, iron concentration, and spider silk
weight) directly influenced the response variable. We employed
a central composite design within the framework of response
surface methodology (RSM) for forecasting and enhancing the
elimination of iron from water (Y). This process considers

Ruiz et al. 3
time (hr) (X1), iron concentration (ppm) (X2), and weight of
the spider web (g) (X3) as influencing factors. To maximize the
percentage of iron removal, in this design, we secured eight (8)
factorial points, six (6) centered points, and six (6) axial points.
These 20 combinations of factor levels were executed randomly
to conduct the experiment.
According to the central composite design, we proceeded to
perform various tests. We prepared samples with the corre-
sponding iron concentrations and contact times between the
solution and spider silk. Once the reaction time elapsed, we
removed the spider web and filtered the sample to remove any
residue. Then, we proceeded with the chemical oxidation and
finally performed the reading of the samples using EDX.
Efficiency of the Removal Determination
To determine the percentage of iron removal in the contami-
nated water samples, through the treatment with spider web,
we proceeded to perform the readings in the dispersive energy
X-ray fluorescence spectroscope, located in the Optoelectronics
laboratory of the Universidad Autónoma de Occidente.
To determine the iron removal percentage, Equation 1 was
used, where E.R is the removal efficiency (%), C.I is the initial
iron concentration (ppm), and C.F is the final iron concentra-
tion (ppm).
ER CI CF CI.((. .)/.)=− *%100 (1)
Measurement of Iron From a Spider Web
We proceeded to measure the pre-established quantities of spi-
der web, exposed to 40 ml of each prepared iron solution. We
subjected these samples to observation during the contact time
established according to the experimental design. After the
reaction period, we removed the spider web and proceeded to
filter the resulting sample. We quantified the iron samples
using the EDX technique. This method enables precise deter-
mination of iron concentrations in the samples, offering valu-
able insights into the interaction and adsorption of iron by the
spider web.
Analysis of Response Surface Methodology (RSM)
In the experimental plan, we employed a central composite
design within the RSM, which is well suited for modeling a
quadratic surface commonly used in process optimization. To
validate the model’s appropriateness for optimizing iron
removal in water, we conducted hypothesis tests, including
assessments for lack of fit, linearity, and quadratic effects. We
analyzed the prediction equation using analysis of variance
(ANOVA) to test the hypotheses associated with RSM. In
Equation 2, shows that the second-order polynomial model
optimizes the variables considered.
Yb bx bx bxx
i
n
ii
i
n
ii i
i
n
ji
n
ij ij
=+ ++
== =
−
=+
∑∑ ∑∑
0
11
2
1
1
1
(2)
Where Y is the response variable (percentage of elimination), b0
is the coefficient of the constant, bi are the linear coefficients, bii
are the quadratic coefficients, bij are the interaction coefficients
of the variables, and xi and xj are the original values of the
variables.
Initially, we validated the assumptions about the model
error ij ~ N (0, 2), with constant and independent vari-
ance. Once these have been fulfilled, we proceed to the
analysis of variance (ANOVA), with which we analyze the
hypotheses associated with the adjusted regression model,
such as the hypothesis of non-significant lack of adjust-
ment (adequate model), which must be significant in favor
of this hypothesis. We propose a polynomial model that is
associated with the following hypotheses: the nonlinearity
hypothesis (Ho: 1 = 2 = 3 = 0), the quadratic effects
hypothesis (Ho: 4 = 5 = 6 = 0) and finally the interaction
hypothesis (Ho: 7 = 8 = 9 = 0).
We obtained the coefficient of determination R2 to evalu-
ate the quality of the fitted polynomial model, which indicates
the percentage of variability between the observed values and
the fitted model. To perform this evaluation, we used Fisher’s
Figure 1. Result of initial and nal iron content (ppm) in each sample.
Table 1. Response Surface Methodology Design.
FACTORS LEVELS CENTERED
POINTS
AXIAL POINTS
X1: Time (hr) (−): 12; (+): 24 18 (−1): 8; 28
X2: Iron
concentration
(pp m)
(−): 50 ± 5; (+): 100 75 (−1): 33; 117
X3: Spider web
weight (g) (−): 0.08; (+): 0.1 5 0115 (−1): 0.06; 0.17

4 Air, Soil and Water Research
“F” test and the level of significance (p-value). We evaluate the
terms of the model by considering a level of significance of 5%
or less. It is essential to highlight that the non-significant
terms in the model (with significance levels greater than 5%),
which contributed in some way to the fit of the model, were
maintained in it.
For the optimization of the removal percentage, we use the
predictability function method (Cornell, 1982). This approach
allows the optimization of the statistical model having as its
main objective to maximize the response variable removal (%).
From the data of the experimental design, we obtained the
optimal levels of the factors.
We performed three additional experiments in the
Environmental Sciences and Optoelectronics laboratories to
verify the optimal values. With these results, we calculated the
relative error of the experiments and evaluated the capacity of
the model to predict the optimal levels of factors (time, weight
of the spider web, and iron concentration) to obtain the highest
iron removal percentage. We performed the calculations using
the statistical package MINITAB 19 (variance analysis, con-
tour plots, and optimization) (Minitab Inc, 1972).
Results
Figure 2a shows the results of the averages related to the iron
concentrations (ppm) and the weight of the spider web used
for the removal of heavy metals in an aqueous medium. We
observed that the removal efficiency was maximal when using
a weight of 0.06 g and an iron concentration of 111 ppm. In
Figure 2b, we present the averages of the reaction time and the
weight of the spider web. A maximum value was obtained
when the time was 18 hr, being this a centered point within the
RSM design. In Figure 2c, we have the time and iron concen-
tration, where the time 18 hr presents a maximum removal at
an iron concentration of 111 ppm.
We obtained very promising results from the iron removal
test in contaminated water using spider webs, with a removal
efficiency close to 80%. These results are significant because
spider web is a natural and readily available material, and it can
be an economical and sustainable solution for the removal of
contaminants from water.
From the removal results (%) acquired in the experimenta-
tion, we obtained the regression equation, which was elabo-
rated on the basis of the predictor variables time, real iron
concentration, and web weight.
Based on these results, we found that the data fit perfectly
into a regression model (RSM), which complies with the
assumptions about the model error at significance levels
greater than 10% (p-value). The selected model generally pre-
sented a good fit (R2: 81.78%) (Equation 3). The model coef-
ficients were initially selected at significance levels lower than
Figure 2. (a–c) Removal averages (percentage) of Fe-polluted water using a spider web.

Ruiz et al. 5
5% (p-value), but since there were two interaction terms
(time [hr] × Real Fe concentration [mg kg-1] and Time
[hr] × Weight [g]) with slightly high significances of 0.13
and 0.154, they were included because they helped to fit the
model.
Removalpercentage Time
Conc FeReal
%
We
[]
=− +
++
342 4728
637 1604
,,
,i
ight
*
*
−
()
−
()
−
0 0311
5802 0
,
,
Conc Fe Real Conc Fe Real
Weight Weight 00458
31 7
Time
ConcFe Real Time
**
Weight−,
(3)
Table 2 presents the main statistical results of the regres-
sion obtained by ANOVA. The results indicate that the
regression has a greater impact in the explanation of the
percentage of removal compared with the random effects,
(sums of squares of the regression = 7465.63 and sum of
squares of the errors = 1663.45). The evaluation of the hypoth-
esis test for lack of fit was not significant, indicating that the
model is appropriate, at a significance level of 0.619 (p-value).
The hypotheses associated with the coefficients of the quad-
ratic terms were significant for concentration and weight
(0.01 and 0.053 respectively).
Optimization of the removal rate
Once the model with significant quadratic effects has been
obtained, we proceed to optimize the removal percentage
(maximize). To this end, we established the following condi-
tions: A target value of 75% and a lower limit of 20%. The
optimization presents high predictability values (D:1), in
Figure 3, the X components that maximize the removal
Table 2. Analysis of Variance of Removal.
SOURCE OF VARIATION DEGREES OF FREEDOM SUM OF SQUARES p-VALUE
Regression 7746 5 .63 .002
Time [hr] 156.82 .552
ConcFe real [ppm] 1 401 7. 9 3 .000
Weight [g] 11515.98 .009
ConcFe real [ppm] × ConcFe
real [ppm]
1146 2.2 6 .010
Weight [g] × Weight [g] 1710.68 .053
Time [hr] × ConcFe real [ppm] 1403.86 .13 0
Time [hr] × Weight [g] 1353.78 .15 4
Error 11 1663.45
Lack of t 6 804.97 .619
Pure error 5858 .47
Tot a l 18 9129.0 8
Figure 3. Graph of the prediction of the model with the highest percentage of Fe removal.

6 Air, Soil and Water Research
percentage are shown. The optimizations of the surface
obtained for the experiments are as follows:
 (Time: 28.09 (hr), Real Fe CONC: 81.42 (ppm), Weight:
0.062 (g) with these values, one of the best removal per-
centages is predicted (91.82%).
 Note that the removal percentage tends to increase with
time (over 20 hr).
 Concerning the actual Fe concentration, it can take val-
ues between 76.02 and 88.63 that the removal is not sig-
nificantly affected, taking values to predict the removal
percentage between 90.46% and 89.15%.
 Regarding the weight, it can take values between 0.056
and 0.075 that the removal is not significantly affected,
taking values to predict the percentage of removal
between 90.46% and 89.15%.
In general, when analyzing the results of the removal optimiza-
tion (%), we observe a relationship between different variables.
Regarding the weight, when it decreases or increases outside the
ranges (0.056 and 0.075), the removal tends to decrease. Likewise,
we found a direct relationship between time and removal, which
means that as time increases, removal increases. On the other
hand, when the iron concentration is outside the established
ranges (76.02 and 88.63), the removal also tends to decrease. In
addition, the results obtained show high predictability, indicating
that it is possible to predict the result with high precision.
We present the optimization results through a contour plot
depicting the removal percentage (Figure 3). The first graph
here, we note that actual iron (Fe) concentrations fall within an
approximate range of 66 to 98 mg/kg for extended times
exceeding 20 (hr), achieving elimination percentages surpass-
ing 80%. In the second graph, illustrating the relationship
between weight and time, we observe weights below approxi-
mately 0.1 g, requiring durations exceeding 20 (hr) to achieve
removal percentages exceeding 80%. In the third graph, repre-
senting the relationship between weight and actual iron (Fe)
concentration, we observe weights below 0.1 g and Fe concen-
trations ranging between 61 and 98 ppm, resulting in removal
rates exceeding 80%.
Verification of the predictions produced by the model
To ascertain the predictive capability of this model, three
experiments were conducted (Table 3), demonstrating that the
values forecasted by the regression equation closely align with
the actual values obtained in the laboratory. We attribute this
close correspondence to the good fitting observed in the mod-
eling process, resulting in values that closely mirror those
depicted in Figure 4a to c.
Table 3 shows the relative errors of the three experiments
using the optimization values established by the RSM. We
obtained relative percentage error values of less than 4.34, indi-
cating high precision in the results of test two with a relative
percentage error of 0.39. This means that the results obtained
are very close to the real value and that the technique used
(RSM) to model the percentage of Fe removal from contami-
nated water.
The removal of 88% of iron water is of great importance in
terms of water quality and public health. Iron is a metal that
can significantly affect the taste, odor, and color of water, mak-
ing it less attractive for human consumption. In addition,
excessive consumption of iron in water can have negative health
effects, such as gastrointestinal and cardiovascular problems.
As indicated by the information from the WHO (2003), and
Resolution 2115 of June 22, 2007, bottled water or water for
human consumption must comply with a maximum permissi-
ble iron value of 0.3 ppm. Therefore, the removal of 88% of iron
achieved in this study demonstrates that the treatment tech-
nology used can be an effective solution to ensure that drinking
water meets the quality and safety requirements established by
regulations. These results can have a significant impact on the
protection of public health and the promotion of safer and
more reliable access to drinking water (Ministerio de Vivienda
y Desarrollo Terr itorial y Ministerio de Protección Social de Col
ombia, 2007).
Discussion
Previous research, such as that carried out (Seid & Gonfa,
2022; Yusuf etal., 2023), has raised that the removal of contami-
nants depends on the specific characteristics of the sample and
that bioremediation technologies offer a promising alternative
for water decontamination. The removal of iron is a critical pro-
cess in the management of water and its contamination because
it can affect people’s quality of life (OMS, 2018). The results
obtained in this study support the efficacy of the chemical treat-
ment used and its applicability in drinking water treatment sys-
tems, which can have a significant impact on the health and
well-being of the population as well as on the protection of the
environment and the sustainability of water resources
Table 3. Summary of the Experiments and Calculation of the Relative Error of the Optimized Treatments.
EXPERIMENT TIME [HR] CONCENTRATION
OF IRON [PPM]
WEIGHT SPIDER
WEB [G]
REMOVAL (%)
PREDICTION
REMOVAL REAL (%) RELATIVE ERROR
PERCENTAGE
1 28.09 81.42 0.0 621 91. 82 88 4.34
228 88.62 0.0754 89 .15 88.8 0.39
328 76.02 0.0561 90.46 87.4 3.5

Ruiz et al. 7
(Ministerio de Vivienda y Desarrollo Terr itorial y Ministerio de
Protección Social de Colombia, 2007).
Based on the results obtained from the RSM modeling, we
can affirm that neither the time (h) should not be decreased,
nor should the iron concentration (ppm) be decreased or
increased outside the range of approximately 76.02 and
88.62 ppm. With respect to the weight of the spider web, values
between 0.056 and 0.075 g generated optimal removal values of
approximately 91%.
This study evaluated the efficiency of iron removal from
contaminated water using spiderwebs as a bioremediation
material. The results showed high precision, with a relative error
of less than 4.34%. We achieved 88% iron removal, which is
significant in terms of water quality and public health. Although
this percentage, lower than that in other studies (Fito etal.,
2023).
However, there is room for improvement in the iron removal
process. We recommend exploring additional approaches that
can enhance efficiency, such as the consideration of a “mul-
tiphase” bioremediation technique. This innovative strategy
involves the implementation of two or more sequential high-
capacity filters, similar to spider webs, to optimize the removal of
contaminants present in the water. Thanks to this methodology,
it is possible to increase the effectiveness of the treatment. This
technique is relevant in compliance with drinking water quality
standards (Ministerio de Vivienda y Desarrollo Territorial y Mini
sterio de Protección Social de Colombia, 2007), because it is pos-
sible to obtain high removal percentages of 88% in the initial
phase.
In other studies related to bioremediation of water with
heavy metals, using other biomaterials (carbon), we found very
short process times (15, 25, and 90 min) and that the bioreme-
diation time under the technique of this research is considera-
bly longer. However, similar removal percentages were found in
other research articles (72%, 86.49%, among others), which
indicates that the removal efficiency of this work is within the
average of the analyzed (Benila Smily & Sumithra, 2017; Cisner
os Gómez & Laura Pezo, 2019; Fito etal., 2023).
By applying a second phase of treatment, we hope to
achieve even greater removal. In addition, this technique
would be beneficial for treating water contaminated with iron
concentrations greater than 88.0 ppm. To perform this large-
scale project, we must consider several important factors. First,
we must consider the breeding of spiders because they are in
charge of producing the spider web used in bioremediation.
The breeding of spiders requires a specific space and habitat
Figure 4. (a–c) Contour plot of iron removal percentage.

8 Air, Soil and Water Research
for their development (Foong etal., 2020); therefore, it requires
a careful way of breeding and maintaining spiders in large
numbers.
Another factor to consider is the amount of spider web
required to perform the bioremediation process on a large scale.
According to the results of this investigation, approximately 15
spider webs of 1 m diameter are required to produce 1 g of spi-
der web. This low production density makes implementation
on a large scale difficult because large numbers of spiders and
spider webs must achieve the desired goals. These calculations
should consider planning the scale of the project and the
amount of resources needed.
Limitations of is Study
The tests in this experiment were carried out on the web of the
species Trichonephila clavipes. There are other species of
weaver spiders that could be used to test whether the property
of adsorbing elements dissolved in water is specific to this spe-
cies or if it is a property that most spider webs have. The exper-
iment was carried out with iron and we worked with a single
layer of spider web using a bioremediation technique. It would
be advisable to test other heavy metals of major health and
environmental importance (chromium, lead, mercury, and cad-
mium) as well as the “multiphase” spider web. The results
obtained in a controlled laboratory environment are promising,
but further research is needed to explore both its practical
application, which could be limited by the real conditions of
treating large volumes of water, and its large-scale application.
Conclusion
Is confirmed the efficacy of chemical treatment with spider
webs for the removal of iron from contaminated water, sup-
porting its applicability in drinking water treatment systems,
with a significant impact on public health and environmental
protection. The study demonstrated that it is possible to use
the spider web for iron removal. We found a relative error of
less than 4.34% and a removal efficiency of 88%, this percent-
age is lower than other studies with other types of materials,
but it is significant for water quality and public health.
Based on the statistical tool used RSM, to obtain the maxi-
mum iron removal (%), mixtures with iron concentrations
between approximately 76.02 to 88.62 ppm, with a weight
between 0.056 and 0.075 g, should be prepared for a period of
28 (hr), the experiment was performed in a beaker, at a volume
of 40 ml. Although the bioremediation time in this study is
longer compared to other biomaterials that achieve very short
process times (15, 25, and 90 min), the removal percentages are
comparable (72%, 86.49%, etc.), indicating that the removal
efficiency is within the average of other studies.
We recommend exploring additional approaches to improve
efficiency, such as the “multiphase” bioremediation technique,
which involves the implementation of sequential high capacity,
cobweb-like filters to optimize contaminant removal and meet
drinking water quality standards. Validation of the optimized
iron removal for the three selected specimens corroborated that
the ratios obtained through the RSM design allowed the high-
est removals with a predictability of one. The high removal
rates obtained support the feasibility of this technique, which
has important implications for environmental protection and
public health. The existing relationship between the selected
variables reinforces its suitability for the study of bioremedia-
tion of iron-contaminated waters.
Acknowledgements
The Universidad Autónoma de Occident, the Zoological
Foundation of Cali, and the SEMAP-Applied Mathematics
research group supported this work, and A.C. contributed to
the interpretation and review of the manuscript. All authors
have read and approved the final content of the manuscript and
preprint of this manuscript.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
Studies in Humans and Animals
This collection approach is respectful of the spiders and their
habitat, and we adopted it to preserve the integrity of the
research and minimize any negative impact on the spider pop-
ulation studied.
Data Availability
Data is available upon request.
ORCID iD
Marisol Gordillo Suarez https://orcid.org/0000-0003-
1602-5547
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