Introduction

Over the past decades, water resources have been polluted at an increasing rate due to the parallel growth of human activities (Kumar et al. 2018), industrial and agricultural activities, and poor disposal of domestic waste, leading to eutrophication of lakes, streams, rivers, and reservoirs, and consequently to the massive spread of aquatic invasive species (Thamaga and Dube 2018). One of the most common invasive species in water bodies is WH, which is a clonal aquatic weed native to South America (Lyu et al. 2016). WH is considered a threat to biodiversity, ecosystem functionality, and human health and has been shown to cause economic impacts to regions where it proliferates (Segbefia et al. 2019; Ilo et al. 2020). WH has been listed as one of the 100 alien species with the highest invasive potential in the world (Pádua et al. 2022) with reported presence in tropical and subtropical regions in more than 50 countries in Asia, Europe, America, Africa, and Oceania (Gupta and Yadav 2020; Janssens et al. 2022). In Mexico, it is estimated that WH was introduced in the early 1900s and has a wide distribution in the tropical regions of the country (Montenegro-Calderón et al. 2011). In addition, it has been reported that more than 40,000 hectares of water bodies have been reported to have a proliferation of this species (Nwamo et al. 2022). In the state of San Luis Potosi, Mexico, the presence of WH has been reported in one of the main bodies of water that supplies 8% of the population of the capital city, known as the San Jose Dam (Vázquez 2012) which causes problems in the water supply system for the population.

In recent years, multispectral satellite data have become the main source of spatial information on the extent and spread of aquatic invasive plants replacing traditional field surveys as they are inexpensive techniques, take little time, and are not limited to the size or geographic barriers of water bodies (Dube et al. 2017a, 2017b). The new generation of non-commercial sensors, Landsat 8 Operational Land Imager (OLI), with enhanced sensing characteristics, has shown promising results in land cover mapping (Thamaga and Dube 2018). Continuous sampling in water bodies with satellite sensors provides information for long-term monitoring, which contributes to effective decision-making and control measures for spread of invasive species (Mukarugwiro et al. 2021).

WH control can be done through physical means involving manual or mechanical removal with specialized equipment and is the best short-term solution (Dechassa 2020), chemical control involving the use of herbicides is highly efficient; however, it can drastically affect the sustainability of aquatic systems (Karouach et al. 2022) and biological control that is performed by introducing natural predators of WH, but can cause affectations in aquatic life by the introduction of another species (Santibañez-Aguilar et al. 2013). As part of sustainable environmental management, WH biomass can be used as an adsorbent material for various pollutants such as heavy metals (Wang et al. 2022), dyes (Carneiro et al. 2022), and pharmaceuticals (Kabir et al. 2022). The water content in the WH structure varies between 90 and 95%. Diverse authors have reported that the dry mass of WH has a cellulose content of 7.80 to 34.19%, hemicellulose of 1.90 to 26.36%, and lignin of 17.66 to 49.20% (Bergier et al. 2012; Ruan et al. 2016; Tovar-Jiménez et al. 2019; Sharma and Aggarwal 2020). In addition, it possesses hydroxyl, phenolic, and carbonyl groups that can in interact with metal ions through hydrogen bonds, hydrophobic interaction, or complexation (Mahmood-ul-Hassan et al. 2018). On the other hand, heavy metals are very common pollutants in water bodies that reach waterways through discharges from various industrial activities, especially manufacturing and mining (Adebisi et al. 2017). Lead is one of the most dangerous pollutants to the environment and lead contamination in air, water, and agricultural soil is an ecological concern (Malar et al. 2014). In addition, Pb(II) is a toxic element, which causes damage to health when it accumulates in the body. It can cause alterations in the central nervous system, gastrointestinal diseases, headaches, dizziness, diarrhea, and vomiting (Araújo et al. 2018). Therefore, the aim of this work was to detect and map the presence of WH in the San Jose Dam, San Luis Potosi, Mexico, to know its seasonal behavior during 2 years and to evaluate the feasibility of its use in Pb(II) adsorption processes in aqueous solution by characterizing its biomass by means of physicochemical analytical techniques and to establish the mechanism of Pb(II) adsorption.

Materials and methods

Reagents

All reagents used were of analytical grade: Pb(NO3)2 (Fermont), NaOH 0.1 N (Hycel), HCl 0.1 N (Hycel), HNO3 (J.T. Baker), HF (J. T. Baker), HCl (J.T. Baker), H2SO4 (J.T. Baker), CTAB (Sigma-Aldrich), Decalin (Sigma-Aldrich), Na2SO3 (Sigma-Aldrich), and SDS (Sigma-Aldrich). The stock solution of Pb(II) 1000 mg L−1 was prepared by dissolving 1.6 g of Pb(NO3)2 in 1 L of deionized water. From this solution, the necessary dilutions were made to carry out the adsorption experiments at different concentrations in the range of 100–600 mg L−1.

NDVI-based detection and mapping of WH

Remote detection of WH above the surface of San Jose Dam was surveyed in the summer and fall of 2018 and 2019 and winter and spring of 2019 and 2020. Maps of WH monitoring over the dam surface were obtained by calculating the normalized difference vegetation index (NDVI) (Eq. 1). Landsat 8 OLI multispectral satellite data were used to differentiate hyacinth over the dam surface. Cloud-free satellite images covering the dam were obtained freely from each Landsat series online archive managed by the United States Geological Survey (USGS) website. NDVI calculation was performed using bands B4 (red) and B5 (infrared) with the “Raster Calculator” tool of ArcMap’s “Spatial Analyst Tools” toolkit in GIS software version 10.5.

$$\textrm{NDVI}=\frac{\textrm{B}5-\textrm{B}4}{\textrm{B}5+\textrm{B}4}$$
(1)

NDVI has a range from −1 to 1 where WH was discriminated from 0 to 1 values and assigned negative values to water.

Collection and identification of WH plants

WH plants were collected at the San Jose Dam located in the city of San Luis Potosi, S.L.P., Mexico (Fig. 1). Table 1 shows the sampling points that were established and identified by georeferencing.

Fig. 1
figure 1

Location of San Jose Dam, study site and collection of WH

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Table 1 Geographical coordinates of WH collection points
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For plant collection, sites were selected where WH formed abundant vegetation profiles and at a distance close to the dam bank. Plants were stored in polyethylene bags and transferred for pre-treatment. In addition, the abiotic characteristics of the collection sites were recorded: temperature and relief characteristics to identify the species.

Pretreatment of WH

The WH plants collected from the San Jose Dam were dried outdoors at room temperature for 48 h. They were then washed with abundant tap water to remove adhering debris and rinsed with deionized water. The plant root, stem, and leaf components (RO, ST, and LE) were separated to study them individually as biosorbents of Pb(II) in aqueous solution. RO, ST, and LE samples were dried in an oven at 80 °C for 24 h, then crushed to an average particle size of 0.25 mm, and stored.

Pb(II) removal tests on WH

The adsorption capacity of Pb(II) in aqueous solution on RO, ST, and LE was evaluated by performing batch adsorption experiments at pH values 3, 4, and 5; 0.1 g of each component was weighed and added to 40 mL of Pb(II) solution in centrifuge vials at different concentrations (100–600 mg L−1). The batch adsorption systems were placed in a water bath with agitation at 15, 25, and 35 °C and the solution was left in contact with the biosorbents for 5 days; this time was considered since the concentration of Pb(II) did not change as well as the pH of the solution, so it was considered as the equilibrium time. The solution pH was adjusted every 24 h by adding NaOH or 0.01N HCl. The concentration of Pb(II) in aqueous solution was determined by atomic absorption using a Varian spectrophotometer, model Spectra AA-20 and the mass of adsorbed Pb(II) was calculated by a mass balance represented mathematically as:

$$q=\frac{V\left({C}_0-{C}_e\right)}{m}$$
(2)

where q is the adsorbed mass of Pb(II) (mg g−1) at equilibrium, C0 and Ce are the initial and final concentration (mg L−1), respectively, V is the volume of the solution (L), and m is the mass of RO, ST, or LE (g).

Characterization of physicochemical properties of WH

The characterization of WH biomass was performed by elemental analysis of C, O, H, N, and S with a Thermo Scientific CHNS-O elemental analyzer, model FlashSmart, in order to know the chemical composition of the biomass and to evaluate compositional changes in the components. The determination of WH moisture content (free or absorbed water found in the biomass) was determined on a dry mass basis by method 967.03; AOAC 1990. The analysis of acid detergent fiber (ADF) and neutral detergent fiber (NDF) fractions was determined by the method developed by Van Soest (Van Soest and Wine 1968;Van Soets 1990). The surface and morphology of WH were observed by scanning electron microscopy (SEM) using the FEI-ESEM QUANTA-250 equipped with energy dispersive X-ray spectrometer. Textural properties (specific area, pore volume, and average pore diameter) were determined by N2 physisorption analysis (SBET) using Micromeritics ASAP 2020 equipment. The organic functional groups present on the biomass surface were obtained by infrared spectrophotometry (FT-IR) using Thermo Scientific equipment, model iS10. Thermogravimetric analysis (TGA) allowed to know the thermal stability of the WH components through the evaluation of the mass variation with respect to the increase of temperature and time. The surface charge distribution and point of zero charge (pHPZC) were evaluated using the potentiometric titration method proposed by Babic et al. (1999). The active sites were determined by the acid-base titration method proposed by Boehm (1994).

Results and discussion

Identification of WH

Figure 2 shows a schematic of the WH collected at the San Jose Dam which was identified as the species Eichhornia Crassipes, and which has been described morphologically by various authors as an aquatic macrophyte that floats freely on the surface of water bodies (Uremis et al. 2014). The flowers occur in spikes and are pale blue or violet, with a central yellow spot on the standard perianth lobe (America and Argentina 2008). The leaves are bright green and arranged in basal rosettes that are born from bulbous petioles of 30- to 100-cm high (Coetzee et al. 2017). The morphology of the roots is very plastic, shaped like black feathers, and these develop at the base of each leaf and form a dense mass, generally, 20- to 60-cm long (Coetzee et al. 2009; Correll and Johnston 1970). Reproduction can be vegetative by stolon formation or sexually through seeds, which can survive in water for 6 years (Su et al. 2018).

Fig. 2
figure 2

WH plant (Eichhornia crassipes)

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NDVI-based WH detection and mapping

Detection of the spatial distribution of WH over the total area of the San Jose Dam (0.82 km2) was observed employing Landsat 8 OLI multispectral satellite data and thus the vegetation cover was mapped based on NDVI values. The presence of WH on the San Jose Dam was determined with NDVI values from 0 to 1 and the absence of WH on the dam surface with negative values from −1 to −0.1. Table 2 shows the percentage of presence over San Jose Dam during the monitoring periods and it can be observed that the highest presence of WH was in the fall of 2019 with 84.2%. In addition, it can be seen that from the fall of 2018 to 2019, there was an increase in the cover by approximately 45%. Also, it can be seen that in the winter of these years, there is the greatest absence of WH in the dam. Remote monitoring during these seasons allowed us to evaluate the constant presence of WH on the dam, corroborating that it can persist despite the climatic differences that occur during the year. The presence of WH can be attributed to anthropogenic activities in the region, such as the constant runoff of domestic water that enriches the water with nutrients, organic matter, nitrates, and sulfates. These pollutants favor the proliferation of WH in polluting water bodies (Ingwani et al. 2010; Honlah et al. 2019).

Table 2 Percentage presence of WH on the surface of San Jose Dam during the monitoring dates
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In several studies, the spatial distribution of WH in various water bodies has been determined. Thus, the results obtained in this research of detecting and mapping WH using Lansat 8 agree with that reported by Al-lami et al. (2021) who detected and mapped the presence of WH in Tigris River, Iraq, employing OLI Landsat 8 sensors and considered it as a promising method of detecting this species to ensure the availability of drinking water. On the other hand, Dube et al. (2017a, 2017b) mentioned that with the Lansad 8 sensor, WH at different growth stages (young, intermediate, and old) in Lake Manyame, Zimbabwe, can be detected and mapped and corroborated that multispectral remote sensing is a valuable complementary data tool that can be considered as a suitable technique for detection and mapping.

Figure 3 shows the WH coverage over the San Jose Dam in the first stage corresponding to the summer and fall of 2018 and the winter and spring of 2019. In the summer of 2018 (Fig. 3a), the greatest presence is observed in the surroundings of the populations adjacent to the dam and there is little presence at the floodgate associated with the clearing of the dam and the rains. In the fall (Fig. 3b), the vegetation cover moved towards the floodgate area because the WH is in a mature stage where its life cycle is about to conclude. During the winter (Fig. 3c), no cover was observed due to the lack of optimal conditions for WH growth and the removal of WH from the dam. WH is cold hardy, but temperatures below 5 °C can cause plant death; however, seeds can survive over winter (Kriticos and Brunel 2016). In the spring (Fig. 3d), accumulation of WH was observed at the floodgate, which indicated a wider distribution, because weather conditions such as precipitation and average temperatures favor the growth of the species (Kariyawasam et al. 2021). In summer, the same behavior as that observed in 2018 was observed, and in fall, an increase in vegetation cover was observed over much of the dam surface. In the winter (Fig. 4c), a drastic decrease was observed with respect to fall 2019 and in the spring, vegetation cover is maintained mainly at the dam floodgate (Fig. 4d). The proliferation of vegetation cover observed during the monitoring stages of the surface of the San Jose Dam is favored by the geographical conditions of the city of San Luis Potosi, the semi-arid climate with a mean annual temperature of 17.5 °C and temporary precipitation with an annual mean of 402.6 mm (Ovalle et al. 2021). The monitoring showed that WH presents cyclical patterns of appearance growth, disappearance, and reappearance in periods of 1 year, which are attributed to the climatic conditions present in the study area and coincides with the results reported by Ongore et al. (2018) in a study conducted on the seasonal behavior of WH in Lake Victoria in Kenya.

Fig. 3
figure 3

First stage of WH monitoring above San Jose Dam. a, b Summer and fall 2018 and c, d winter and spring 2019

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Fig. 4
figure 4

Second stage of WH monitoring above San Jose Dam. a, b Summer and fall 2019 and c, d winter and spring 2020

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Elemental analysis and chemical composition of WH

Table 3 shows the elemental analysis (CHNSO) and chemical composition of RO, ST, and LE. Through the elemental analysis, the percentage of the elements C, H, N, S, and O that constitute the cell wall of WH was obtained. The values obtained in the present investigation are within the ranges obtained by various authors (Bergier et al. 2012; Hu et al. 2015; Sharma and Aggarwal 2020), who reported elemental composition values of 33 to 50% C, 5.30 to 6.61% H, 1.50 to 4.3% N, 27.5 to 39.70% O, and 0.25 to 0.59% S. Asadullah et al. (2007) mention that the discrepancies in the values can be attributed to the difference in the geographical location of the biomass used in the different studies.

Table 3 Elemental analysis (CHNSO) and chemical composition of RO, ST, and LE
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Cell wall composition determined from WH dry mass basis varied for all fractions, except for acid detergent fiber (ADF), which had similar values for all components. For LE, the composition is presented as hemicellulose>cellulose>lignin; for RO and ST, the order was presented as cellulose>hemicellulose>lignin, and this could be attributed to the cellular content, which is higher for these components in relation to those of LE. The values reported in this study are within the ranges reported by Bergier et al. (2012), Ruan et al. (2016), Tovar-Jiménez et al. (2019), and Sharma and Aggarwal (2020), who determined that the values of cellulose and hemicellulose content of WH range from 17.80 to 34.19% and 17.66 to 49.20%, respectively, and lignin content from 1.90 to 26.36%.

Scanning electron microscopy (SEM)

Figure 5a, c, and e correspond to the micrographs of RO, ST, and LE samples before the Pb(II) adsorption process, respectively. As can be seen, the fibrous texture and morphology correspond to the cell wall, with an irregular surface. Moreover, they exhibit a non-homogeneous shape at the fiber junctions, forming tabular reliefs and layers. On the other hand, Fig. 5b, d, and f correspond to the micrographs of RO, ST, and LE after the adsorption process where agglomerations were observed on the surface of the biosorbents corresponding to Pb(II) microprecipitation.

Fig. 5
figure 5

Micrographs of RO, ST, and LE before (a, c, e) and after (b, d, f) the Pb(II) adsorption process

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The presence of Pb(II) in RO, ST, and LE was obtained by energy dispersive X-ray spectroscopy (EDS analysis). In Fig. 6a, c, and e, the EDS spectra of RO, ST, and LE are shown, where the presence of Na, K, Ca, Mg, Si, Al, Cl, and S. In addition, the presence of C and O due to the organic nature of WH was observed. The presence of some elements is because this species is considered a bioaccumulator of both organic and inorganic molecules (Meitei and Prasad 2013). EDS spectra of RO, ST, and LE after Pb(II) adsorption are presented in Fig. 6b, d, and f; the appearance of peaks characterizing the presence of Pb(II) is observed.

Fig. 6
figure 6

EDS spectra of RO, ST, and LE before (a, c, e) and after (b, d, f) the Pb(II) adsorption process

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N2 physisorption (S BET)

The N2 physisorption analysis showed that the biosorbents are mesoporous and have low specific areas as the pore diameter values ranged from 16.8 to 23.4 nm and the specific areas were less than 1.7 m2/g. Several studies have reported similar values in WH-based adsorbents where the specific area is in the range of 0.30 to 4.50 m2 g−1 (Aswani and Kumar 2019; Allam et al. 2020; Pakutsah and Aht-Ong 2020). The specific area values determined for RO, ST, and LE were 1.1, 1.7, and 1.0 m2/g, respectively, and are within the ranges reported for water hyacinth-based materials. The N2 adsorption isotherms on RO, ST, and LE (Fig. 7a) exhibit type II behavior with H3-type hysteresis characteristic of non-porous materials (Condon 2020).

Fig. 7
figure 7

a N2 adsorption-desorption isotherms on RO, ST, and LE. b Total accumulated pore volume distribution on RO, ST, and LE

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On the other hand, the pore size distribution, determined through the BJH (Barrett-Joyner-Halenda) method for RO, ST, and LE, is presented in Fig. 7b, where the cumulative distribution of the volume of pores present in the biosorbents is observed. Specifically, the distribution of micropores is as follows: RO 1.92%, ST 3.01%, and LE 3.60%. As for mesopores: RO 33.30%, ST 44.9%, and LE 39.56%. Finally, macropores presented the following percentages: RO 64.68%, ST 52.90%, and LE 56.84%. This analysis revealed that approximately 50% of the total pore volume is in the macroporous region. Likewise, about 47% of the total pore volume is located in the mesoporous region. On the other hand, the microporous region is present in smaller amounts, representing only 1 to 3% of the total pore volume.

Infrared spectroscopy (FT-IR)

Figure 8 shows the comparison of infrared spectra of RO, ST, and LE before (a) and after (b) the Pb(II) adsorption process obtained in the spectral region 4000–600 cm−1. Figure 8a shows the spectra of RO, ST, and LE exhibiting a broad band around 3330 cm−1, which is attributed to the stretching vibration of the O-H bond of carboxylic groups generally present on the fiber surface of lignocellulosic materials (Neris et al. 2019). The bands at 2930 and 2925 cm−1 are associated with the stretching vibrations of methylene C-H bonds (Elangovan et al. 2008). At 1720 and 1730 cm−1, there are stretching vibrations of the C=O carbonyl group which is also related to the presence of carboxylic acids, ketones, and esters present in hemicellulose and cellulose (da Silva Correia et al. 2018). The curvature at 1610 and 1620 cm−1 can be assigned to the N-H bending vibration of amides present in WH lignin (Sarkar et al. 2017). The band at 1370 cm−1 is due to the bending of the C-H bond of the carboxylic acid structures (Munene et al. 2020). The bands at 1020 and 1030 cm−1 are assigned to the stretching vibration of C-O group, present in hydroxyl groups, esters, and ethers of lignin, cellulose, and hemicellulose, as major components of the cell wall of WH (Yi et al. 2016). As can be observed in the infrared spectra of RO, ST, and LE, no relevant differences between them are presented; this suggests that their composition is homogeneous.

Fig. 8
figure 8

Infrared spectra of RO, ST, and LE a before and b after Pb(II) adsorption process

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Figure 8b shows the shift of the infrared spectra of RO, ST, and LE after the Pb(II) adsorption process. For the hydroxyl group of RO, ST, and LE, a shift can be seen at 3332, 3330, and 3331cm−1; this acts as an important chelation center in the plant material and suggests the binding of Pb(II) in the -OH group (Komy et al. 2013). In the aliphatic C-H group, the spectra shifted to 2922 for RO and ST and 2924 cm−1 in LE. For the C=O group, a shift was presented at 1720 for RO and ST and at 1730 cm−1 for LE, which is attributed to the interactions between carbonyl groups and lead in solution (Medellín-Castillo et al. 2017). In the NH group, displacement can be seen at 1591, 1584, and 1595 cm−1; these can be attributed to the appearance of carboxylate groups product of the deprotonation of the carboxylic groups that are probably attached to the polymeric structures present in the amides (Balasubramanian and Burghard 2005). The band at 1320 cm−1 corresponding to the C-O stretching of the carboxylic acid group is reduced upon adsorption of Pb(II). Finally, the C-O stretching vibrations of the alcoholic hydroxyl group are shifted to 1028, 1018, and 1023 cm−1 and can be attributed to the associations of the hydroxyl group with lead ions (Lim et al. 2008).

Thermogravimetric analysis

TGA curves of RO, ST, and LE samples were obtained from 25 to 500 °C in an N2 atmosphere. In Fig. 9a, the first stage of weight loss corresponding to the loss of moisture present in the samples is observed for RO at 47, ST 45, and LE 41 °C. In the second stage, bimodal peaks are observed in RO at 334 °C that are associated with the volatilization of cellulose and hemicellulose. In ST, there is a homogeneous peak defined at 315 °C and for LE, the peak occurs at 317 °C; these peaks are attributed to a high content of cellulose, which is one of the compounds with the highest proportion of lignocellulosic fibers. In third stage is presented in RO at 477, ST at 480, and LE at 472 °C; this last stage is attributed to the degradation of lignin as the final component of the lignocellulosic material (Medellín-Castillo et al. 2017).

Fig. 9
figure 9

TGA analysis of RO, ST, and LE a before and b after the Pb(II) adsorption process

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TGA curves of RO, ST, and LE samples after the Pb(II) adsorption process are shown in Fig. 9b. The first stage occurred in RO at 52, ST at 53, and LE at 53 °C due to the change in thermal stability of the components with moisture loss (Blázquez et al. 2012). The second stage was only observed in ST at 244 and LE at 243 °C; this difference can be associated with a higher concentration of adsorbed Pb(II) in LE and ST as can be seen in the SEM analysis (Fig. 5d and f). Subsequently, the splitting of the curves into two stages (3 and 4), RO at 313, ST at 318, and LE at 322 °C and a temperature rise to a maximum degradation rate in RO at 343, ST at 348, and LE at 349 °C were observed; this can be explained by the cross-linking of the cellulose chains through intermolecular complexation of Pb(II) ions as it demonstrates a higher thermal stability of the components (Paduraru et al. 2015; Singha and Guleria 2014).

Charge distribution and zero charge point (pHPZC)

Figure 10 shows the surface charge distribution of the RO, ST, and LE samples, which can be related to the presence of active sites contained in the materials. Table 4 reports the concentrations of the acidic and basic sites of the biosorbents, which allow determining that the samples are of acidic character since the amount of acidic sites is higher than that of basic sites. The concentration of acid sites of RO, ST, and LE samples is 6, 5, and 4 times higher than that of the basic sites, respectively. Moreover, it is observed that the highest concentration of acid sites corresponds to that of phenolic sites, followed by lactonic and finally, carboxylic sites. The abundance of phenolic sites can be attributed to the presence of lignin, which is distinctive in lignocellulosic materials (Salazar-Rabago and Leyva-Ramos 2016). In the surface charge distribution figure, it is observed that the surface charge is positive as the pH of the solution decreases below pHPZC; this behavior can be attributed to the protonation of the functional groups of the acid sites (lactonic, carboxylic, and phenolic) present on the surface. On the other hand, as the pH of the solution increases, deprotonation of the acidic functional groups is possible, which favors the negative surface charge. The point of zero charge (pHPZC) corresponds to the pH at which the net surface charge is equal to zero, the concentration of H+ and OH− adsorbed on the surface is equal at pHPZC, and therefore, the surface charge is neutral. The surface charge is negative at pH>pHPZC and positive at pH<pHPZC (Kragović et al. 2019). The pHPZC determined was RO 6.4, ST 6.0, and LE 6.1; this means that, when pH is lower than pHPZC, the surface charge of the biosorbents is positive and there is electrostatic repulsion between Pb(II) ions and the surface, resulting in low adsorption capacity. If the pH is higher than pHPZC, the surface charge of the biosorbents is negative, so Pb(II) ions are attracted to the biosorbent surface (Ganesan et al. 2013).

Fig. 10
figure 10

Surface charge distribution of RO, ST, and LE samples

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Table 4 Active site concentrations and pHPZC of RO, ST, and LE samples
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Adsorption isotherms of Pb(II) on WH

Freundlich, Langmuir, and Redlich-Peterson isotherm models were used to interpret the experimental data for the adsorption equilibrium of Pb(II) in aqueous solution on RO, ST, and LE.

$$q=K{C}^{\frac{1}{n}}$$
(3)
$$q=\frac{q_m kC}{1+ kC}$$
(4)
$$q=\frac{aC}{1+b{C}^{\beta }}$$
(5)

where q (mg g−1) is the adsorption capacity and C (mg L−1). The parameters of the Freundlich isotherm, K (mg g−1 (mg L−1), 1/n), are related to the adsorption capacity and n is the adsorption intensity. The Langmuir isotherm parameters, qm (mg g−1) and k (mg L−1), are constants related to the maximum adsorption capacity and adsorption energy, respectively. The Redlich-Peterson isotherm parameters, a and b, are the counters of (L g−1 and L mg−1, respectively) and β is the Redlich Peterson isotherm constant.

Table 5 reports the parameters, coefficients of determination (R2), and percentage deviations (%D) of the Freundlich, Langmuir, and Redlich-Peterson models that were calculated using the experimental data of the effect of pH at values of 3, 4, and 5 at 25 °C in adsorption equilibrium of Pb(II) on RO, ST, and LE. R2 values obtained allowed us to evaluate the degree of fit between the observed values and the values predicted by the regression models. Consequently, the presence of high R2 values indicates that the theoretical model of adsorption isotherms is capable of explaining a considerable portion of the variability present in the observed data. The experimental data of the adsorption equilibrium were fitted to the Langmuir model in 9 cases, and the Redlich-Peterson model in 6 cases. Therefore, it was considered that the Langmuir isotherm interpreted the experimental data better percentages of deviation between 5.4 and 12.8%. The R2 values obtained (Langmuir 0.87 to 0.99, Redlich-Peterson 0.86 to 0.98, and Freundlich 0.85 to 0.98) are around a value of 1 for this coefficient, indicating that each of the models used in this work is able to adjust to the experimental data and adequately predict the adsorption capacity (q).

Table 5 Parameters of the Freundlich, Langmuir, and Redlich-Peterson isotherm models for Pb(II) adsorption on RO, ST, and LE components of WH at pH values of 3, 4, and 5 at 25 °C
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Effect of pH and temperature on adsorption capacity

The pH is an important control parameter that influences the nature of the adsorbent as well as the adsorbate and helps to elucidate the possible adsorption mechanisms (Katal et al. 2012). The pH values 3, 4, and 5 used in this work and lower than the pHPZC observed in Fig. 10 were considered taking into account that different Pb(II) adsorption mechanisms occur on WH biomass (electrostatic interactions, ion exchange, microprecipitation, and π-cation). Since at pH values above 5, Pb(II) tends to precipitate in aqueous solutions (Medellín-Castillo et al. 2017), it was chosen to work at pH below pHPZC. According to the distribution of Pb(II) species, it is observed that at pH<7, lead is found mainly in the form of Pb2+ in acidic solutions. At pH=7, Pb2+ remains the predominant form. When pH>7, lead has the ability to form precipitates such as lead hydroxide (Pb(OH)+) and (Pb(OH)2), and in concentrated alkaline solutions, the formation of (Pb(OH)3−) is possible. The effect of pH on the adsorption capacity of Pb(II) in aqueous solution on RO, ST, and LE biosorbents was determined at pH 3, 4, and 5 at 25 °C and interpreted by means of the adsorption isotherms (Fig. 11). The increase in adsorption capacity with increasing solution pH is attributed to the decrease in the surface positive charge of the biosorbents as the solution pH is close to pHPZC, as observed from the surface charge distribution curves of the biosorbents in Fig. 10. This indicates the presence of an electrostatic attraction adsorption mechanism.

Fig. 11
figure 11

Adsorption isotherms of Pb(II) in aqueous solution on a RO, b ST, and c LE at pH values 3, 4, and 5 at 25 °C. The lines represent the Langmuir model

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The maximum estimated Pb(II) adsorption capacity at pH 5 on RO, ST, and LE was 107.3, 136.8, and 120.8 mg g−1, respectively. These values were determined from the qm parameter of the Langmuir isotherm model and correspond to those reported in Table 5. This represents an increase in adsorption capacity of 31.7% and 11.9% in ST and LE, respectively, when the solution pH was increased from 3 to 5. In the case of RO, a decrease in adsorption capacity of 3.0% was obtained with this increase in pH. When comparing the adsorption capacities of RO, ST, and LE, it was observed that they are very similar and this is due to the cellulose, hemicellulose, and lignin content which are similar as reported in Table 3. The adsorption isotherms at solution temperatures of 15, 25, and 35 °C are shown in Fig. 12. According to the results obtained, the variation of temperature did not generate an effect on the adsorption capacity of Pb(II) as it did not increase or decrease with temperature. Table 6 reports the adsorption of various pollutants based on WH, which are in agreement with those reported in this study.

Fig. 12
figure 12

Adsorption isotherms of Pb(II) in aqueous solution on RO, ST, and LE at 15, 25, and 35 °C at pH 5. The lines represent the Langmuir model

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Table 6 Adsorption studies of various pollutants using WH-based adsorbents
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Mechanism of Pb(II) adsorption on WH

Sheng et al. (2004) mention that several mechanisms of Pb(II) adsorption (ion exchange, complexation, coordination, and microprecipitation) can occur, depending on the type of aqueous medium in which the WH is found and its chemical composition. In this study, it was observed that by increasing the pH in the solution from 3 to 5, the adsorption capacity increased, which was attributed to an electrostatic attraction mechanism because the positive charge on the biosorbent decreased as it was closer to the pHPZC and by increasing the negatively charged sites, these were available for Pb(II) adsorption (Fig. 10). Another mechanism that can occur in the adsorption of Pb(II) on RO, SR, and LE adsorbents is ion exchange. During the adsorption process, a steady decrease in solution pH was observed, which required the periodic addition of small amounts of 0.01 N NaOH or HCl solutions to maintain it at the established levels. This mechanism involves the transfer of H+ ions from the surface of the biosorbents to the solution and, simultaneously, the migration of Pb(II) ions from the solution to the surface of the biosorbents, as reported by Medellín-Castillo et al. (2017). The adjustment of the experimental adsorption equilibrium data to the Langmuir model confirms the formation of a monolayer, which is attributed to an ion exchange process (Anirudhan and Unnithan (2007)). In the micrographs of the biosorbents after the Pb(II) adsorption process (Fig. 5b, d and f), small agglomerations that can be attributed to Pb(II) microprecipitation are observed; these were mostly observed in the order LE>ST>RO, and this order could be associated with the chemical composition of the biosorbents (Table 3). Finally, the π-cation adsorption mechanism involving the aromatic rings of the polysaccharides present in the biosorbents was proposed, where the aromatic rings acted as π-donors to interact with Pb(II), which could serve as a π-acceptor due to its electron deficiency (Ding et al. 2016). This binding happens when the cations are attracted to the hydroxyl groups of cellulose and the phenolic, hydroxyl, and carboxylic groups of lignin present in the cell wall of WH (Table 4), which is corroborated by the peak shift of the FT-IR spectra in Fig. 8b.

Conclusions

The monitoring of WH on the surface of the San Jose Dam demonstrated the capacity and accuracy of remote sensing of the presence of vegetation cover, where the area of cover on the surface was observed, and the proliferation and distribution of WH are influenced by seasonal climatological factors, with spring and summer being the seasons with the highest percentage of cover on the surface. The physicochemical characterization of WH revealed that its textural properties are similar to those reported in the literature. Likewise, it was demonstrated that the surface of RO, ST, and LE has acidic characteristics, given the prevalence of phenolic groups present in the material, corroborated by PCC and FT-IR analysis. The results of the FT-IR analysis revealed that during Pb(II) adsorption amino, amide and hydroxyl groups may be involved since the intensity of the bands of these groups decreases in Pb(II)-saturated samples with respect to unsaturated adsorbents. The Langmuir isotherm model was best fitted to the experimental data, since it had a smaller percentage deviation. The adsorption capacity of Pb(II) was also observed to be affected by increasing pH in solution, suggesting the existence of ion exchange between Pb(II) ions and the biomass surface. The proposed adsorption mechanisms for Pb(II) adsorption on WH biomass include electrostatic interactions, ion exchange, microprecipitation, and π-cation. The use of WH biomass as a Pb(II) adsorbent, involving the use of an invasive species that affects aquatic ecosystems, is a beneficial, low-cost, and value-added environmental management alternative that leads to the reduction of the negative environmental and socioeconomic effects produced by this species. The present study provides guidelines for future strategies on the use of the water cation that has become a serious environmental problem in one of the bodies of water that supply the population of the capital of the state of San Luis Potosi, Mexico.