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Article

Evaluation of the Toxicity of Cafeteria Wastewater Treated by a Coupled System (ARFB-SD)

by
Hannia Hernández-Aguilar
1,
Carlos M. García-Lara
1,*,
Hugo A. Nájera-Aguilar
1,*,
Rubén F. Gutiérrez-Hernández
2,
Rebeca I. Martínez-Salinas
1 and
Juan A. Araiza Aguilar
1
1
Environmental Engineering Program, University of Sciences and Arts of Chiapas, Lajas, Maciel, Tuxtla Gutierrez 29000, Chiapas, Mexico
2
Chemical and Biochemical Engineering Department, National Technology of Mexico-Technological Institute of Tapachula, Tapachula 30700, Chiapas, Mexico
*
Authors to whom correspondence should be addressed.
Processes 2022, 10(8), 1442; https://doi.org/10.3390/pr10081442
Submission received: 18 June 2022 / Revised: 14 July 2022 / Accepted: 20 July 2022 / Published: 23 July 2022
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Versions Notes

Abstract

:
In developing countries, achieving greater coverage in the treatment and safe reuse of graywater is a pending task. Therefore, this article presents the results obtained from cafeteria wastewater treatability tests and effluent toxicity tests. For the treatment, a serial system was applied: an aged refuse filled bioreactor (ARFB) and a solar distiller (SD). In the first stage (ARFB), two hydraulic loads (HLs) were tested (200 and 400 L/m3·day), the latter being the best of them, with an average decrease of 95.7% in chemical oxygen demand (COD). In the second stage (SD), the decrease was 62.8%, resulting in a final effluent with 67.7 mg/L COD, which corresponded to a global COD decrease of 97.4%. For the toxicity tests, radish seeds were used in the serial system effluent, obtaining a relative seed germination (RSG) rate of 93.3% compared to 80% obtained in the ARFB effluent. For the percentage germination index (PGI), it was determined that both effluents (ARFB and ARFB-SD) presented a toxicity considered low, especially the ARFB-SD effluent whose PGI value was close to zero (−0.0667). The results obtained showed not only that the ARFB-SD system is efficient in removing the high organic load that can go along with cafeteria wastewater, but also that it can provide an effluent with a very low toxicity level based on the PGI close to zero.

1. Introduction

The reuse of treated graywater has been increasing as a measure to reduce the problem of water scarcity and due to the need for its purification before being discharged to the environment. Its reuse also offers an economic benefit derived from the management of nutrients such as nitrogen and phosphorus, in addition to practical applications in hydroponics or agriculture [1,2,3]. Despite these benefits, its management carries risks to health and the environment, which is why it is important to examine different technologies so that its treatment and reuse are sustainable [4].
According to data from the National Water Commission of 2016, in Mexico, by the year 2020 [5], of the 196,749 L/s of domestic wastewater (DWW) that could be treated, a coverage of 67.2% was achieved. Of this flow, it is estimated that 75% is represented by gray wastewater [6]. In the context of the state of Chiapas, the DWW treatment situation is less encouraging, since only 41% (1255 L/s) of the flow is treated [7], so the estimation of the volume and origin of the wasted greywater is important [8]. For example, in educational centers such as the University of Sciences and Arts of Chiapas (UNICACH, acronym in Spanish), the water required for various services (sanitation, laboratories, irrigation of green areas, etc.) is supplied by the municipal drinking water network, and the different graywater currents are dislodged without any treatment or use.
One of the main sources of graywater generation at UNICACH is the water produced by the cafeteria services, where an estimated 5 m3/d is generated on business days, which is equivalent to an estimated annual generation of 800 m3. This volume of water, if subjected to adequate treatment for later use, would reduce the water supplied by the municipal network and provide environmental and economic benefits.
There are different techniques used in wastewater treatment, which are based on chemical, biological and physical processes. Electrodialysis is a chemical technique which reports COD removal efficiencies from 49% to 62% and biochemical oxygen demand (BOD) from 38% to 52% [9]. As for the biological techniques, there is one based on activated sludge accompanied by membrane filtration, with COD decrease efficiencies from 89% to 98% and BOD greater than 97% [10]. Another biological process whose first reported studies date from the beginning of this century is known as the ARFB [11]. This process was developed seeking to give economic value or utility to the old garbage deposited in sanitary landfills and as an alternative treatment for the leachate from the same sanitary landfills. As reported by [12,13], aged garbage is the product that remains of municipal solid waste after at least eight years of being confined in landfills and where the organic matter present in the waste has been degraded. For this reason, waste at this age can be conceived as old or stabilized waste (aged refuse). These materials contain a broad spectrum and large number of microbial populations (1.40 × 106 CFU/g), which have adapted over the years to high concentrations of contaminants [11] and favor this technology in the removal of organic load in different aqueous matrices.
The application of ARFBs has focused mainly on the treatment of leachate, such as the study reported by [14] which worked with an HL of 14 L/m3·day, spraying 10 times a day every 30 min, with decreases of 64% in COD, 95.8–99.8% in BOD and 90% in color; in another study reported by [15], with an HL of 55 L/m3·day, they reached a 75–95% decrease in COD and BOD with the application of two sprays per day. The ARFB has also been tested to treat less complex wastewater, such as domestic wastewater, with a decrease of 73.8% in COD [16]. More recent applications of this technology have been in the purification of wastewater from sugarcane processing, where the decrease in COD achieved was between 89% and 98.8% [17]. The versatility of the application of aged refuse (AR) can be evidenced by its recent application in the decontamination and remediation of oil-contaminated soils, where the removal of total oil hydrocarbons was 59.89% under the optimal operating conditions found (AR and contaminated soil ratio = 1.6; water content = 41%; oil content = 3.8%) [18].
Regarding physical techniques, SD use has shown COD decrease efficiencies of 86.8% and 90% when testing with sanitary wastewater [19] and oil mill wastewater [20], respectively. Once the wastewater has been treated, in order to reuse it, different studies are required to determine the sector in which it can be used [21], with the intention of taking advantage, for example, of the source of nutrients that it may contain without this representing a risk, before the possible contribution of toxic agents and any other unwanted compound in its application, such as high concentrations of salts. Another physical technique is the use of activated carbon to remove impurities such as pharmaceutical micropollutants [22]. An inexpensive technique that allows to determine the degree of toxicity of the salts present in water is through seed germination and the development of seedlings during the first days of growth [23].
Different bioassays have been carried out using water from treatment plants diluted at different percentages as an inflow in which toxicity has been evaluated based on the germination efficiency of a wide variety of seeds. For example, treated wastewater from Sfax in Tunisia was evaluated using oat seeds, obtaining a germination percentage greater than 80% while achieving 46% with untreated wastewater [24]. Gassama et al. [25] evaluated treated wastewater from Kuala Lumpur, Malaysia, using rice seeds, obtaining germination percentages greater than 90% at concentrations that varied from 0% to 25%, whereas for higher concentrations (50% and 100%), germination percentages of 85.6% and 74.6% were obtained. Another work [26] that evaluated treated wastewater in the Czech Republic using white mustard seeds at different concentrations obtained germination percentages below 30%.
Red radish seeds have also been used in toxicity bioassays and have shown better results as a static test of acute toxicity to evaluate the phytotoxic effects of pure compounds or complex mixtures of these in the process of seed germination and in seedling development during the first days of growth [27]. Some advantages of using agricultural species over others is their dormancy and viability despite adverse conditions. Under favorable conditions, these species present changes in their metabolism, nutrient transport and cell division in a short period of time; furthermore, they are associated with a low cost and require simple analysis equipment. Thus, the main goal of this study was to evaluate first a new combination of treatment processes for the removal of pollutants from cafeteria service wastewater through a serial system (ARFB–SD), and secondly, the toxicity of the effluents of the studied system. This system was arranged in series and its efficiency was monitored by evaluating the COD decrease in both the ARFB and the SD. The phytotoxic effects of the effluent obtained from these treatments were also evaluated using the germination technique in radish seeds (Raphanus sativus L.).

2. Materials and Methods

2.1. Extraction, Drying and Classification of the AR

The AR used to pack the bioreactor was acquired from the closed area of the landfill in the city of Tuxtla Gutiérrez, Chiapas, Mexico (16°45′11″ north latitude and 93°06′56″ west longitude), specifically from the points indicated in Figure 1, where the samples were extracted at a depth of 1 to 2 m with the help of a backhoe. For its preparation and drying, the methodology and recommendations established by Bautista-Ramírez et al. [28] were followed. The AR was separated into two different particle sizes: >40 mm and ≤40 mm.

2.2. Reagents

All chemical reagents used for the preparation of aqueous working solutions were of analytical grade and obtained from JT Baker. Distilled and deionized water was used in the preparation of all aqueous solutions.

2.2.1. Collection and Characterization of Graywater

The UNICACH cafeteria offers its service to a population of approximately 6000 people, including students, teachers and administrative staff. From August to November 2019, a period of high academic activity, around 24 L of graywater was collected from the discharge point in 4-liter polyethylene bottles. The water samples were refrigerated at 4 °C until later use and they were characterized with the following physicochemical parameters: COD, BOD, color, turbidity, chlorides, total nitrogen (TN), total phosphorus (TP) and pH. COD was quantified via the closed reflux micro method by digesting the sample at 150 °C for 2 h and subsequently read in a HACH DR-5000 spectrophotometer at 620 nm. BOD was determined by quantifying the difference between the initial dissolved oxygen concentration and the concentration after five days of incubation at 20 ± 1 °C. Color determination was carried out using a HACH DR/890 colorimeter, while turbidity was determined using a Lamotte 2020WE instrument. Finally, to determine the chloride content, TP and TN, the HACH8113, HACH 8190 and Kjeldahl methods were used, respectively.

2.2.2. Construction of the ARFB-SD System

The ARFB was built using a PVC tube of cylindrical geometry (Ø = 0.16 m and h = 1.6 m) as shown in Figure 2a. A 0.20-meter section filled with 1″ gravel was installed at the bottom of the bioreactor as support material; then, 1.30 m of AR with particle size ≤ 40 mm was placed, followed by 0.10 m of freeboard, giving a total height of 1.6 m. To contain the bioreactor material, the bottom was closed with a perforated PVC lid. In addition, to avoid the dragging of fine materials, the support material of the bioreactor was placed inside a shade-net bag.
As a complementary and final purification stage, a basin-type SD was used (Figure 2b) due to its ability to reduce inorganic and organic substances from wastewater [19]. The SD is similar to the ones employed for seawater desalination. It consists of three basic parts: a water basin, a transparent cover and thermal insulation. The water basin had an area of 1 m2; the remaining section of 0.1 m length, part of a collecting system named SD effluent (Figure 2–7), was constructed from a galvanized steel sheet with a thickness of 0.002 m. The sides and the bottom were painted black in order to prevent deterioration and increase the absorptance of incident solar radiation, which reaches average values above 800 W/m2; meanwhile, the transparent cover, made of 0.003 m thick glass, had a slope of 30°. Finally, thermal insulation of wood (0.02 m thickness) was placed down the SD in order to reduce thermal losses. The water basin had a maximum allowable height of 0.005 m of water, reaching a maximum of 5 L of wastewater to treat and giving a capacity of 3.27 L/m2·day of wastewater to be treated [29]. The sludge obtained was not quantified, although it was thickened, stabilized and disposed of safely into the environment [19].

2.3. Operation and Monitoring of the ARFB-SD System

The ARFB was fed with graywater from the cafeteria at room temperature under three HLs: 100, 200 and 400 L/m3·day. The first two were fed for 6 weeks each and the third for 5 weeks, a period that matched the academic activity season. The first of these three HLs was used as the ARFB conditioning stage and the last two as the HLs to be studied. Feeding was carried out by spraying over the entire ARFB visible surface twice a day (7 and 19 h), and the effluent obtained with the best HL was exposed to the SD.
The organic load removal efficiencies for the ARFB and ARFB-SD effluents were determined weekly by estimating the decrease in COD in accordance with Equation (1).
%   D e c r e a s e   i n   C O D = C i − C f C i   100
where Ci is the initial COD concentration (mg/L) and Cf is the final COD concentration (mg/L). Additional parameters such as chlorides, TN and TP were also measured in the final effluents.

2.4. Conducting Toxicity Bioassays

The water samples evaluated were divided into two groups: ARFB-treated water and ARFB-SD-treated water, as well as graywater (positive) and distilled water (negative) as controls.
For the toxicity bioassay, radish was used according to the plant species recommended by the Environmental Protection Agency [30], as well as for its tolerance to the presence of pollutants [31], which allowed for evaluating the phytotoxic effects on the seedling development during the first days of growth. Thirty scarified and unscarified radish seeds were placed on cotton in eight different Petri dishes of 100 mm diameter. In each Petri dish, 9 mL of water from the site sample was applied. The dishes were sealed with flexible plastic wrap to prevent desiccation. The seeds germinated with graywater were considered as a positive control and those germinated with distilled water as a negative control [32]. They were kept at a temperature below 30 °C to obtain better germination results [33]. After the exposure time, the number of germinated seeds was counted over a 5-day period. The results obtained were expressed as the RSG according to Equation (2).
RSG ( % ) = Number   of   seeds   germinated   in   cafeteria   wastewater Number   of   seeds   germinated   in   negative   control * 100
The normalized residual PGI was determined using Equation (3) [34].
P G I = G S − G C G C
where Gs is the average percentage of germinated seeds with the graywater in the study and GC is the percentage of germinated seeds in the control.
The PGI establishes toxicity values from −1 to >0 under the following criteria: 0 to −0.25, low toxicity; −0.25 to −0.5, moderate toxicity; −0.5 to −0.75, high toxicity; −0.75 to −1, very high toxicity; values >0 indicate radicle growth or hormesis [23].
The results obtained from the treatability (12 repetitions for each HL) and germination tests were statistically analyzed using a one-way analysis of variance (ANOVA) with an α = 0.05 level of significance, and Fisher’s test was used to determine a significant association between control groups and germination percentage. Prior to the analysis, the assumptions of the ANOVA were verified.

3. Results and Discussion

3.1. AR Extraction, Drying and Classification

The AR presented a certain odor after its extraction and laying, which quickly dissipated in the first two days; furthermore, bulky materials such as tire chips, wood, stones and plastics were removed during the drying period [28].
Regarding the AR classification, rigid and light plastics represented around 10% and 11%, respectively (Table 1), and thin materials represented 57.4% (fines fraction). The bulk density on a dry basis of the aged refuse generated a value of 893 kg/m3. In the case of particle size, as shown in Table 1, about 85% of the materials had a size of <40mm, a value slightly higher than the 75% reported previously [35]. As mentioned by [36], the particle size information is important since it allows to perceive the amount of AR that can be used as packing material in ARFB systems.

3.2. Cafeteria Wastewater Characterization

The cafeteria wastewater characterization for the parameters analyzed is displayed in Table 2.
Table 2 shows that the average COD and BOD concentrations were 3167 and 1990 mg/L, respectively, showing high values in organic load and variable ranges. These values are similar to those reported for wastewater from Chinese restaurants (COD: 292–3390 mg/L; BOD: 58–1430 mg/L) and American fast-food restaurants (COD: 980–4240 mg/L; BOD: 405–2240 mg/L) [37], in which a high variability in the concentrations found can also be observed. Authors such as Su et al. [38] mention that cafeteria wastewater drags waste from different foods (vegetables, milk, eggs, cereals, etc.), so a variety of compounds such as cellulose, starch, saccharides, fats, proteins, amino acids, etc., are expected. This largely explains the high organic load found and the variation that can arise. The turbidity values obtained were also high (549.2 UTN)—triple the values reported [25] for DWW (130 UTN).
Regarding the biodegradability found (BI: 0.63), it is within the values reported for cafeteria wastewater (0.40–0.69) [37,39]. This BI value reflects highly biodegradable wastewater, where biological processes can be considered as one of the first treatment options. As for the pH values found, they were very close to neutrality (6.9) and thus also favorable for biological systems.

3.3. Operation and Monitoring of the ARFB-SD System

3.3.1. Stage 1: ARFB

Figure 3 shows an initial fluctuation in the decrease in COD (46.4–78.1%) for the first 4 weeks of monitoring, a behavior that can be considered as expected given that the ARFB stabilizes 3 to 5 weeks after the process starts [28]. Bearing in mind that ARFBs operate under semi-aerobic conditions, this relatively short stabilization period may represent an advantage of the system, especially when compared to anaerobic-type biological processes which may require stabilization periods of 2 to 9 months [40,41] or even longer when an initial inoculum is not considered. According to [42], AR has an improved biodegradation capacity, without the need for microbiological consortiums to require an acclimatization period; it is a spectrum of microbes with a high capacity for biodegradable and refractory organic matter degradation.
Overall, the decreases in COD percentage average were 94.6% and 95.7% for HLs of 200 and 400 L/m3·day, respectively. According to the variance analysis, there was not a statistically significant effect (p < 0.05) on the decrease in COD among the largest HLs (200 and 400 L/m3·day), so when projecting the ARFB to treat cafeteria wastewater, the 400 L/m3·day HL would be recommended, doubling the treated wastewater volume with average removals of 95.7%. In terms of organic pollutants load, the total COD removed was 1212.2 g/m3·day with the HL of 400 L/m3·day, which is at least two times greater than that achieved with the HL of 200 L/m3·day at 599.2 g/m3·day. These removal percentages are comparable to the one achieved by [38] (94% in COD) when treating cafeteria wastewater but under the Fenton process, and much higher than the 73.8% achieved by [16] when using an ARFB but treating wastewater with a lower organic load, such as domestic wastewater. In this manner, the ARFB effluent for the best HL considered (400 L/m3·day) was exposed to SD.

3.3.2. Stage 2: SD

An initial quantity of 1 L was placed inside the water basin of the SD and was left outdoors for one day. With the onset of solar radiation and the increase in temperature, evaporation and subsequent condensation started and continued throughout the day. This process was repeated for 5 days, during which the seeds were watered.
The final effluent obtained after exposure to the SD registered an average COD concentration of 67.7 mg/L, which corresponded to decrease of 62.8%. Thus, considering the removals obtained in both stages, the ARFB-SD showed a global COD decrease of 97.4%.
In general, the 62.8% reduction in COD in the SD was lower than the 86.83% reported by [19] for sanitary wastewater, which went from an initial concentration of 342.9 to 44.6 mg/L, or the 90% decrease in COD reported by [20] for oil mill wastewater. This difference can be explained by the exposure times handled; for this study, it was only one day, while for the cited studies [20,43], it was 22 and 5 days, respectively.

3.4. Toxicity Bioassays

For the toxicity evaluation, a total of 240 radish seeds were used, which were divided into two working groups: normal seeds (without scarification) and scarified seeds. Seeds were placed in four different Petri dishes for each working group, both fed with the control groups, using approximately 9 mL daily for five days—i.e., the necessary time to reach total germination for the control group.
Figure 4 indicates that both groups of seeds showed 100% germination with the negative control water, which indicates the efficiency in the response of the chosen seed. Regarding the treatment groups, the ARFB-SD group presented the best germination response, and in both work groups, the same germination percentage (93.3%) was obtained, similar to [44], where wastewater was treated with ozone, achieving a germination rate of 90%. Meanwhile, for the ARFB group, the best germination response (80%) was obtained with the scarified seeds, as was the case for the positive control, only with a much lower percentage (42.33%).
When performing Fisher’s test with a 0.05 confidence level, a significant difference was observed only between the positive control and the ARFB-SD group. This is attributed to small variations in the germination index of the seeds on different days: for the ARFB-SD group, there was an oscillating response on different days, both in normal and scarified seeds, while the positive control had a clear downward trend.
The low response of the positive control in the RSG, according to what is shown in Figure 4, can be inferred to be related to the presence of components that inhibit germination, as well as a low concentration of micronutrients and macronutrients [44], while the ARFB-treated water removes the organic and inorganic loads from the water, which allows the seeds that are irrigated with said water to obtain the required nutrients.
Different authors, as presented in Table 3, have used radish or lettuce seeds to evaluate textile wastewater treated or polluted with antibiotics at different dilutions, obtaining germination percentages greater than 89%; however, the system proposed in this work evaluates the ARFB or ARFB-SD effluent without dilution.
Regarding the calculated PGI values, Figure 5 shows that the negative control had zero toxicity, which was expected due to its nature; contrarily, the positive control, with a registered PGI value of −0.5833 on average, indicated the presence of highly toxic pollutants considered as stressful agents that significantly inhibit seed germination. In the case of treated water, the ARFB water was close to the border between low toxicity and moderate toxicity, with an average value of −0.2167, and for the ARFB-SD water, a PGI value close to null toxicity of −0.0667 was observed. These results explain the difference in the germination percentages obtained and the advantages of using the effluent from the ARFB-SD system.
The concentrations of chlorides, TP and TN for the different types of water are presented in Figure 6, where a significant decrease can be observed in the chlorides graph (Figure 6a) in its concentration as the level of treatment increases; that is, the decrease between the positive control and the two treatment groups (ARFB and ARFB-SD) was 52.86% and 96.57%, respectively. Thus, the difference in the germination index of the treatment groups can be associated to the chemical load (inorganic ions) existing in the water used. According to [48], seeds that are exposed to high concentrations of chlorides can delay radicle and plumule growth, causing the development of the seedling to be affected, as observed in the RSG.
As for the concentration of phosphorus (Figure 6b), decreases of 96.06% and 97.49% were observed in the effluents of the ARFB and ARFB-SD, respectively, while for nitrogen (Figure 6c), the decreases were 91.37% for the ARFB effluent and 90.89% for the ARFB-SD effluent, which may indicate that the reduction in these two nutrients was not a determinant in the PGI between both treatment systems, as the concentration of chlorides seems to be.

4. Conclusions

The ARFB-SD serial system was evaluated for the treatment of cafeteria wastewater. For the first stage (ARFB), of the two HLs tested, the best was 400 L/m3·day, reaching a decrease in COD average of 95.7%, while for the second stage (SD), the decrease was 62.8%. Thus, the final effluent had an average COD concentration of 67.7 mg/L, which corresponded to a global COD decrease of 97.4%, which infers that the system could treat higher HLs.
Regarding the toxicity tests, the effluent obtained with the different HLs fed did not show significant differences between the total number of germinated seeds, but it did show a decrease in germination time. It was determined that the use of a serial treatment system improves the RSG (93.3%), compared to that of 80% obtained with a single treatment.
The ARFB-SD serial system presented an average PGI value of −0.0667, representing low toxicity, associated with chemical load removal (inorganic ions).
In short, according to the results obtained, the ARFB-SD system proved to be not only highly efficient in removing the high organic load that can accompany cafeteria wastewater but also a system that can provide, according to the PGI analysis, an effluent with a close to null toxicity level.

Author Contributions

Conceptualization, H.H.-A., C.M.G.-L., H.A.N.-A. and R.F.G.-H.; methodology, C.M.G.-L., H.A.N.-A. and R.I.M.-S.; validation, H.H.-A., C.M.G.-L. and H.A.N.-A.; formal analysis, C.M.G.-L., H.A.N.-A., R.F.G.-H., R.I.M.-S. and J.A.A.A.; investigation, H.H.-A., C.M.G.-L., R.I.M.-S. and J.A.A.A.; resources, R.F.G.-H., R.I.M.-S. and J.A.A.A.; writing – original draft and preparation, C.M.G.-L. and H.A.N.-A.; writing – review and editing, C.M.G.-L., H.A.N.-A. and R.F.G.-H.; visualization, R.I.M.-S. and J.A.A.A.; supervision, C.M.G.-L. and H.A.N.-A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Alvarenga, P.; Mourinha, C.; Farto, M.; Santos, T.; Palma, P.; Sengo, J.; Morais, M.C.; Cunha-Queda, C. Sewage Sludge, Compost and Other Representative Organic Wastes as Agricultural Soil Amendments: Benefits Versus Limiting Factors. Waste Manag. 2015, 40, 44–52. [Google Scholar] [CrossRef] [PubMed]
  2. De Sanctis, M.; Del Moro, G.; Chimienti, S.; Ritelli, P.; Levantesi, C.; Di Laconi, C. Removal of Pollutants and Pathogens by a Simplified Treatment Scheme for Municipal Wastewater Reuse in Agriculture. Sci. Total Environ. 2017, 580, 17–25. [Google Scholar] [CrossRef] [PubMed]
  3. Cui, B.; Liang, S. Monitoring Opportunistic Pathogens in Domestic Wastewater from A Pilot-Scale Anaerobic Biofilm Reactor to Reuse in Agricultural Irrigation. Water 2019, 11, 1283. [Google Scholar] [CrossRef] [Green Version]
  4. Leiva, A.M.; Albarrán, A.; López, D.; Vidal, G. Evaluation of Phytotoxicity of Effluents from Activated Sludge and Constructed Wetland System for Wastewater Reuse. Water Sci. Technol. 2019, 79, 656–667. [Google Scholar] [CrossRef]
  5. Comisión Nacional del Agua–Secretraría de Medio Ambiente y Recursos Naturales. Inventario Nacional de Plantas Municipales de Potabilización y de Tratamiento de Aguas Residuales en Operación. Ciudad de México. 2020. Available online: https://www.gob.mx/cms/uploads/attachment/file/703303/Inventario_2020.pdf (accessed on 20 January 2022).
  6. Murcia-Sarmiento, M.L.; Calderón-Montoya, O.G.; Díaz-Ortiz, J.E. Impacto De Aguas Grises En Propiedades Físicas Del Suelo. Tecnológicas 2014, 17, 57–65. [Google Scholar] [CrossRef] [Green Version]
  7. Instituto Estatal del Agua. Programa Estatal Hídrico 2019–2024: Gobierno del Estado de Chiapas; Instituto Estatal del Agua: Tuxtla Gutiérrez, México, 2019. [Google Scholar]
  8. Fichtner, T.; Ibrahim, S.I.; Hamann, F.; Graeber, P.-W. Purification Efficiency for Treated Waste Water in Case of Joint Infiltration with Water Originating from Precipitation. Appl. Sci. 2020, 10, 3155. [Google Scholar] [CrossRef]
  9. Albornoz, L.L.; Marder, L.; Benvenuti, T.; Bernardes, A.M. Electrodialysis Applied to The Treatment of a University Sewage for Water Recovery. J. Environ. Chem. Eng. 2019, 7, 9. [Google Scholar] [CrossRef]
  10. Melin, T.; Jefferson, B.; Bixio, D.; Thoeye, C.; De Wilde, W.; De Koning, J.; van der Graaf, J.; Wintgens, T. Membrane bioreactor technology for wastewater treatment and reuse. Desalination 2006, 187, 271–282. [Google Scholar] [CrossRef]
  11. Youcai, Z.; Hua, L.; Jun, W.; Guowei, G. Treatment of Leachate by Aged-Refuse-Based Biofilter. J. Environ. Eng. 2002, 128, 662–668. [Google Scholar] [CrossRef] [Green Version]
  12. Lei, Y.; Shen, Z.; Huang, R.; Wang, W. Treatment of Landfill Leachate by Combined Aged-Refuse Bioreactor and Electro-Oxidation. Water Res. 2007, 41, 2417–2426. [Google Scholar] [CrossRef]
  13. Hassan, M.; Xie, B. Use of Aged Refuse-Based Bioreactor/Biofilter for Landfill Leachate Treatment. Appl. Microbiol. Biotechnol. 2014, 98, 6543–6553. [Google Scholar] [CrossRef] [PubMed]
  14. Li, H.; Gu, Y.; Zhao, Y.; Wen, Z. Leachate Treatment Using a Demonstration Aged Refuse Biofilter. J. Environ. Sci. 2010, 22, 1116–1122. [Google Scholar] [CrossRef]
  15. Erabee, I.K.; Ethaib, S. Treatment of Contaminated Landfill Leachate Using Aged Refuse Biofilter Medium. Orient. J. Chem. 2018, 34, 1441–1450. [Google Scholar] [CrossRef]
  16. Zhang, H.H.; Tian, J.S.; Zhang, Y.M.; Wu, Z.L.; Kong, X.J.; Chao, J.; Hu, Y.; Li, D.L. Removal of Phosphorus and Nitrogen From Domestic Wastewater Using A Mineralized Refuse-Based Bioreactor. Environ. Technol. 2012, 33, 173–181. [Google Scholar] [CrossRef]
  17. Nájera-Aguilar, H.A.; Mayorga-Santis, R.; Gutiérrez-Hernández, R.F.; Araiza-Aguilar, J.A.; Martínez-Salinas, R.I.; García-Lara, C.M.; Rojas-Valencia, M.N. Aged Refuse Filled Bioreactor Using Like a Biological Treatment for Sugar Mill Wastewater. Sugar Tech 2021, 23, 201–208. [Google Scholar] [CrossRef]
  18. Chen, W.; Wang, F.; Zeng, L.; Li, Q. Bioremediation of Petroleum-Contaminated Soil by Semi-Aerobic Aged Refuse Biofilter: Optimization and Mechanism. J. Clean. Prod. 2021, 294, 125354. [Google Scholar] [CrossRef]
  19. Asadi, R.Z.; Suja, F.; Ruslan, M.H.; Jalil, N.A. The application of a solar still in domestic and industrial wastewater treatment. Sol. Energy 2013, 93, 63–71. [Google Scholar] [CrossRef]
  20. Jaradat, A.Q.; Ghawaibeh, S.; Abu Irjei, M. The Application of Solar Distillation Technique as a Mean for Olive Mill Wastewater Management. Water Environ. J. 2017, 32, 134–140. [Google Scholar] [CrossRef]
  21. Bagur-González, M.G.; Estepa-Molina, C.; Martín-Peinado, F.; Morales-Ruano, S. Toxicity Assessment Using Lactuca sativa L. Bioassay of the Metal (Loid)S As, Cu, Mn, Pb and Zn in Soluble-in-Water Saturated Soil Extracts from an Abandoned Mining Site. J. Soils Sediments 2011, 11, 281–289. [Google Scholar] [CrossRef]
  22. Ray-Mafull, C.A.; Hotza, D.; García-Gallardo, R.; Cruz Junior, O.F.; Serafin, J. Adsorption and Thermodynamic Parameters of Activated Carbon-Diazepam Systems in Simulated Gastric Fluid. Adv. Mater. Lett. 2021, 12, 1–9. [Google Scholar] [CrossRef]
  23. Priac, A.; Badot, P.M.; Crini, G. Treated Wastewater Phytotoxicity Assessment Using Lactuca Sativa: Focus on Germination and Root Elongation Test Parameters. Comptes Rendus Biol. 2017, 340, 188–194. [Google Scholar] [CrossRef] [PubMed]
  24. Fendri, I.; Ben Saad, R.; Khemakhem, B.; Ben Halima, N.; Gdoura, R.; Abdelkafi, S. Effect of Treated and Untreated Domestic Wastewater on Seed Germination, Seedling Growth and Amylase and Lipase Activities in Avena sativa L. J. Sci. Food Agric. 2012, 93, 1568–1574. [Google Scholar] [CrossRef] [PubMed]
  25. Gassama, U.M.; Puteh, A.B.; abd-Halim, M.R.; Kargbo, B. Influence of Municipal Wastewater on Rice Seed Germination, Seedling Performance, Nutrient Uptake, and Chlorophyll Content. J. Crop Sci. Biotech 2015, 18, 9–19. [Google Scholar] [CrossRef]
  26. Adamcová, D.; Vaverková, M.D.; Brousková, E. The Toxicity of Two Types of Sewage Sludge from Wastewater Treatment Plant for Plants. J. Ecol. Eng. 2016, 17, 33–37. [Google Scholar] [CrossRef] [Green Version]
  27. Ravindran, B.; Sheena Kumari, S.K.; Stenstrom, T.A.; Bux, F. Evaluation of Phytotoxicity Effect on Selected Crops Using Treated and Untreated Wastewater from Different Configurative Domestic Wastewater Plants. Environ. Technol. 2016, 37, 1782–1789. [Google Scholar] [CrossRef]
  28. Bautista-Ramírez, J.A.; Gutiérrez-Hernández, R.F.; Nájera-Aguilar, H.A.; Martínez-Salinas, R.I.; Vera-Toledo, P.; Araiza-Aguilar, J.A.; Rojas-Valencia, M.N. Biorreactor Empacado Con Materiales Estabilizados (ARFB), Como Pretratamiento Para Lixiviados De Rellenos Sanitarios. Rev. Mex. De Ing. Química 2018, 17, 561–571. [Google Scholar] [CrossRef] [Green Version]
  29. García Pérez, J.; García-Lara, C.M.; Nájera-Aguilar, H.A.; Vera Toledo, P.; Vázquez-Sánchez, R.A. Desarrollo Y Caracterización De Un Destilador Solar Para Su Aprovechamiento En El Tratamiento De Agua Contaminada. Lacandonia 2010, 4, 71–77. [Google Scholar]
  30. United States Environmental Protection Agency. Ecological effects test guidelines. In Seedling Emergence and Seedling Growth; OPPTS 850.4100; EPA: Washington, DC, USA, 2012; p. 32. [Google Scholar]
  31. Oleszczuk, P. Testing of Different Plants to Determine Influence of Physico-Chemical Properties and Contaminants Content on Municipal Sewage Sludges Phytotoxicity. Environ. Toxicol. 2008, 25, 38–47. [Google Scholar] [CrossRef]
  32. Mañas, P.; de las Heras, J. Phytotoxicity Test Applied to Sewage Sludge Using Lactuca sativa L. and Lepidium sativum L. Seeds. Int. J. Environ. Sci. Technol. 2017, 15, 273–280. [Google Scholar] [CrossRef]
  33. Hoekstra, N.J.; Bosker, T.; Lantinga, E.A. Effects of Cattle Dung from Farms with Different Feeding Strategies on Germination and Initial Root Growth of Cress (Lepidium sativum L.). Agric. Ecosyst. Environ. 2002, 93, 189–196. [Google Scholar] [CrossRef]
  34. Walter, I.; Martínez, F.; Cala, V. Heavy Metal Speciation and Phytotoxic Effects of Three Representative Sewage Sludges for Agricultural Uses. Environ. Pollut. 2006, 139, 507–514. [Google Scholar] [CrossRef] [PubMed]
  35. Zhao, Y.; Song, L.; Huang, R.; Song, L.; Li, X. Recycling of Aged Refuse from a Closed Landfill. Waste Manag. Res. 2007, 25, 130–138. [Google Scholar] [CrossRef] [PubMed]
  36. Gutiérrez-Hernández, R.F.; Nájera-Aguilar, H.A.; Araiza-Aguilar, J.A.; Martínez-Salinas, R.I.; García-Lara, C.M.; González-Vázquez, U.; Cruz-Salomón, A. Novel Treatment of Sugar Mill Wastewater in a Coupled System of Aged Refuse Filled Bioreactors (ARFB): Full-Scale. Processes 2021, 9, 516. [Google Scholar] [CrossRef]
  37. Chen, G.; Chen, X.; Yue, P.L. Electrocoagulation and Electroflotation of Restaurant Wastewater. J. Environ. Eng. 2000, 126, 858–863. [Google Scholar] [CrossRef]
  38. Su, R.; Wang, P.; Jiang, L. Study on Advanced Oxidation of Cafeteria Wastewater Using Fenton Reagent. Adv. Mater. Res. 2012, 424, 1322–1325. [Google Scholar] [CrossRef]
  39. Radin Mohamed, R.M.S.; Apandi, N.; Matias Peralta, H.M.; Kasim, A.H.M. Removal of Nutrients from Cafeteria Wastewater Using Varying Concentrations of Microalga Scenedesmus Sp. Proceedia Environ. Sci. 2015, 2–6. [Google Scholar] [CrossRef] [Green Version]
  40. Melidis, P.; Vaiopoulou, E.; Athanasoulia, E.; Aivasidis, A. Anaerobic Treatment of Domestic Wastewater Using an Anaerobic Fixed-Bed Loop Reactor. Desalination 2009, 248, 716–722. [Google Scholar] [CrossRef]
  41. Méndez Novelo, R.; Mena Velázquez, R.; Castillo Borges, E.R.; Sauri Riancho, M.R. Evaluación De Un Reactor UASB Para Aguas Porcinas Inoculado Con Líquido Ruminal. Ingeniería 2013, 17, 41–55. [Google Scholar]
  42. Song, L.; Shi, L.; Zhao, Y.; Li, H. Novel Engineering Controls to Increase Leachate Contaminant Degradation by Refuse: From Lab Test to In Situ Engineering Application. Ecol. Eng. 2011, 37, 1914–1919. [Google Scholar] [CrossRef]
  43. Rojas-Valencia, M.N.; Orta de Velásquez, M.T.; Franco, V. Urban Agriculture, Using Sustainable Practices That Involve the Reuse of Wastewater and Solid Waste. Agric. Water Manag. 2011, 98, 1388–1394. [Google Scholar] [CrossRef]
  44. Dhaouefi, Z.; Toledo-Cervantes, A.; Ghedira, K.; Chekir-Ghedira, L.; Muñoz, R. Decolorization and Phytotoxicity Reduction In an Innovative Anaerobic/Aerobic Photobioreactor Treating Textile Wastewater. Chemosphere 2019, 234, 356–364. [Google Scholar] [CrossRef] [PubMed]
  45. Rehman, A.; Bhatti, H.N.; Athar, A.R. Textile Effluents Affected Seed Germination and Early Growth of Some Winter Vegetable Crops: A Case Study. Water Air Soil Pollut 2009, 198, 155–163. [Google Scholar] [CrossRef]
  46. Gouider, M.; Feki, M.; Sayadi, S. Bioassay and use in irrigation of untreated and treated wastewaters from phosphate fertilizer industry. Ecotoxicol. Environ. Saf. 2010, 73, 932–938. [Google Scholar] [CrossRef]
  47. Pan, M.; Chu, L.M. Phytotoxicity of Veterinary Antibiotics to Seed Germination and Root Elongation of Crops. Ecotoxicol. Environ. Saf. 2016, 126, 228–237. [Google Scholar] [CrossRef] [PubMed]
  48. Lamz Piedra, A.; González Cepero, M.C. Salinity as a problem in agriculture: Plant breeding an immediate solution. Cultiv. Trop. 2013, 34, 31–42. [Google Scholar]
Processes 10 01442 g001 550
Figure 1. Extraction, preparation and drying of AR from sanitary landfill (Tuxtla Gutiérrez, Chiapas, México).
Figure 1. Extraction, preparation and drying of AR from sanitary landfill (Tuxtla Gutiérrez, Chiapas, México).
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Processes 10 01442 g002 550
Figure 2. ARFB-SD integrated system for wastewater treatment. (a) ARFB; (b) SD; (1) influent; (2) stabilized material; (3) support material; (4) ARFB effluent; (5) SD influent; (6) reservoir; (7) SD effluent.
Figure 2. ARFB-SD integrated system for wastewater treatment. (a) ARFB; (b) SD; (1) influent; (2) stabilized material; (3) support material; (4) ARFB effluent; (5) SD influent; (6) reservoir; (7) SD effluent.
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Figure 3. Decrease in COD behavior in cafeteria wastewater with the ARFB system under different HLs: (a) 100, (b) 200 and (c) 400 L/m3-d. o, influent; □, effluent; ◊, % decrease in COD. The figure shows the high organic load variability that cafeteria wastewater can have. For this study, the concentrations went from 725 mg/L in week 4 to 5092 mg/L in week 14. Despite this high variability, removal efficiencies were fairly consistent from week 5 to week 17, which marked the end of the monitoring period.
Figure 3. Decrease in COD behavior in cafeteria wastewater with the ARFB system under different HLs: (a) 100, (b) 200 and (c) 400 L/m3-d. o, influent; □, effluent; ◊, % decrease in COD. The figure shows the high organic load variability that cafeteria wastewater can have. For this study, the concentrations went from 725 mg/L in week 4 to 5092 mg/L in week 14. Despite this high variability, removal efficiencies were fairly consistent from week 5 to week 17, which marked the end of the monitoring period.
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Figure 4. Relative radish seed germination.
Figure 4. Relative radish seed germination.
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Figure 5. Water toxicity level of the different control groups used.
Figure 5. Water toxicity level of the different control groups used.
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Figure 6. Analyzed parameters of different treatment groups. (a) Chlorides, (b) phosphorus and (c) nitrogen.
Figure 6. Analyzed parameters of different treatment groups. (a) Chlorides, (b) phosphorus and (c) nitrogen.
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Table
Table 1. Composition and particle size distribution in dry excavated materials.
Table 1. Composition and particle size distribution in dry excavated materials.
AR Composition (%)Particle Size Diameter (%)
Nylon BagsRigid PlasticsOthers *Thin MaterialsTotal> 40 mm≤ 40 mmTotal
11.110.221.357.410015.0584.95100
(*) Pieces of stone, wood, other cellulosic materials, etc.
Table
Table 2. Physicochemical characterization of cafeteria wastewater.
Table 2. Physicochemical characterization of cafeteria wastewater.
ParameterUnitsAverage and Range
CODmg/L3167 (725–5092)
BODmg/L1990 (711–2933)
Biodegradability Index (BI)---0.63
pH---6.9 (6.7–7.0)
TurbidityUTN549.2 (456–622)
ColorPt-Co554 (506–602)
Chloridesmg/L180 (163–191)
Phosphorusmg/L25.1 (21.8–32.7)
Nitrogenmg/L11.676 (8.5–15.3)
Table
Table 3. Comparison of different studies on toxicity.
Table 3. Comparison of different studies on toxicity.
EffluentVolume (ml)Number of SeedsTime (Days)SeedsRelative Seed Germination
(No Dilution Unless Specified)		Reference
Textile43514RadishDWTreatedDWUntreated[45]
89.391.289.389.83
WWTP51003 DWWWTP 1WWTP 2[46]
Lettuce58.5333.78
Radish B.89.358.431.8
WWTP6107LettuceWWTP 1WWTP 2[27]
TreatedUntreatedTreatedUntreated
DU
1:4		NDDU
1:4		NDDU
1:4		NDDU
1:4		ND
96.494.490.368.898.494.490.283.3
VAs5205-7LettuceAqueous solutions of the five VAs: 0.01 to 1 mg/L[47]
TCSMZNORERYCAP
9393959395
WWTP4307LettuceQuality of Water[23]
Reverse OsmosisDistilled
9894
DW: distilled water; WWTP: wastewater treatment plant; DU: dilutions used; ND: no dilution; VAs: veterinary antibiotics; TC: tetracycline; SMZ: sulfamethazine; NOR: norfloxacin; ERY: erythromycin; CAP: chloramphenicol.
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Hernández-Aguilar, H.; García-Lara, C.M.; Nájera-Aguilar, H.A.; Gutiérrez-Hernández, R.F.; Martínez-Salinas, R.I.; Aguilar, J.A.A. Evaluation of the Toxicity of Cafeteria Wastewater Treated by a Coupled System (ARFB-SD). Processes 2022, 10, 1442. https://doi.org/10.3390/pr10081442

AMA Style

Hernández-Aguilar H, García-Lara CM, Nájera-Aguilar HA, Gutiérrez-Hernández RF, Martínez-Salinas RI, Aguilar JAA. Evaluation of the Toxicity of Cafeteria Wastewater Treated by a Coupled System (ARFB-SD). Processes. 2022; 10(8):1442. https://doi.org/10.3390/pr10081442

Chicago/Turabian Style

Hernández-Aguilar, Hannia, Carlos M. García-Lara, Hugo A. Nájera-Aguilar, Rubén F. Gutiérrez-Hernández, Rebeca I. Martínez-Salinas, and Juan A. Araiza Aguilar. 2022. "Evaluation of the Toxicity of Cafeteria Wastewater Treated by a Coupled System (ARFB-SD)" Processes 10, no. 8: 1442. https://doi.org/10.3390/pr10081442

APA Style

Hernández-Aguilar, H., García-Lara, C. M., Nájera-Aguilar, H. A., Gutiérrez-Hernández, R. F., Martínez-Salinas, R. I., & Aguilar, J. A. A. (2022). Evaluation of the Toxicity of Cafeteria Wastewater Treated by a Coupled System (ARFB-SD). Processes, 10(8), 1442. https://doi.org/10.3390/pr10081442

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