All the reagents were commercially available and were used as received without further purification. Copper nitrate (Cu(NO₃)₂·3H₂O, 98%), diphenylamine (99%), N, N-Dimethyl formamide (DMF, 99%), methanol (CH₃OH, 99.5%), and ethanol (EtOH) were purchased from Shanghai Chemical Reagent Co. Ltd.

Wastewater samples were digested on a hot plate heating apparatus using round bottom flasks. Borosilicate volumetric flasks (25, 50, and 100 ml), pipettes (Pyrex, United States), measuring cylinders (Duran, Germany), and micropipettes (Dragonmed, 1–10 μl, 100–1,000 μl, Shanghai, China) were used for measuring different quantities of sample solution, acid reagents, and standard metal solutions. Graphite furnace atomic absorption spectroscopy (GFAAS) equipped with a deuterium background corrector was employed to quantify the heavy metals before and after absorption; iodine number analysis, X-ray diffraction (XRD), and Fourier transform infrared radiation (FTIR) were used to characterize the adsorbent.

A wastewater sample was collected from Gamo Gofa zone, Arba Minch town, from the car wash labajo area. The sampling area is defined geographically as 6°01′–7°12′ N, and 37°32′–38° 02′ E. Composite samples were collected in 2-a-week intervals during March–April 2017 and analyzed for Pb, Cd, and Cr levels. The concentrations of these heavy metals were determined using GFAAS before and after treatment.

Wastewater samples were digested with HNO₃ and HClO₄ in the ratio of 5:3. Digestion was done on a hot plate at a temperature of 93 °C for 1 h following a method reported by Fanta et al. (2019).

To determine the concentrations of metals in the untreated and treated effluent sample solutions, calibration curves were created. The GFAAS instrument was calibrated using four series of working standards (0.1, 0.5, 1.0, 1.5 mg/L). A correlation coefficient of 0.999 and above was obtained for the three metals. The detection limits for the metals tested in this study were calculated by multiplying the weighted average of standard deviations of the reagent blank by three. The wavelengths at which analysis was done, the correlation coefficients of the calibration curve for each of the metals, and the method detection limits of each metal are given in Table 1. The results clearly show that the calibration curves with good correlation coefficients and lower method detection limits were obtained during the analysis.

The validity of the above-optimized digestion procedure toward analyzing the wastewater samples concerning each of the selected metals (Pb, Cr, and Cd) could be made possible via conducting spiking experiments. Accordingly, the efficiency of the optimized procedure was checked by adding fixed volumes of standard solutions containing 5 ml of 0.5 mg/L of each metal into 50 ml wastewater. The spiked samples were then digested in the same manner as the original sample. Then the digests were diluted to 25 ml with deionized water. Finally, the solutions were analyzed for metal concentration with GFAAS. As used for the original samples, triplicate spiked samples were prepared, and the readings were recorded, and recovery was calculated using Eq. 1. R = C s − C n S × 100 % , (1) where R is percent recovery, C s is metal concentration of spiked sample, C n is the metal concentration of the non-spiked sample and S is the concentration equivalent of analyte added.

Copper metal-organic framework (Cu-DPA MOF) was prepared from Cu(NO₃)₂·3H₂O and diphenylamine ligand following a solution-based method. Briefly, 1 g of diphenylamine was dissolved in 5 ml of ethanol, and 1 g of copper nitrate trihydrate was dissolved in 5 ml of distilled water. The two solutions were mixed and stirred by a magnetic stirrer on a hot plate for 1 h until a homogeneous mixture was observed. The mixture was then kept for 3 days until a blue precipitate was formed. The resulting precipitates were isolated by centrifugation, washed four times with de-ionized water, DMF, and ethanol, respectively, and dried at 40°C for 24 h. The obtained precipitate, named Cu-DPA MOF afterward, was kept for further characterization and experimentation.

The metal to ligand ratio of the copper metal-organic framework was optimized by taking a different metal to ligand ratio (1:1, 2:1, 3:1, and 4:1). The synthesized MOFs were then subjected to an optical microscope, and the iodine number was determined following the American Society for Testing and Materials methods. The one with the smallest particle size and largest iodine number value was taken as the optimum ratio.

The prepared Cu-DPA MOF was characterized by XRD, FTIR, GFAAS, and iodine number analysis. XRD measurements were taken on a D2 phaser XRD-300 W using Cu K α radiation at 40 kV and 100 mA. A linear silicon strip ‘Lynx Eye’ detector was used to record X-ray patterns from 10° to 80° at a scan rate of 0.1° min⁻¹. The FTIR spectra were obtained using a Nicolet NEXUS-670 FT-IR spectrometer in transmission mode. Each sample in the KBr blend was scanned 64 times with a resolution of 4 cm⁻¹ from 4,000 to 400 cm⁻¹. The morphology of the samples in this study was studied with field emission FEI Nova NanoSEM 450 scanning electron microscope (SEM). The wastewater samples’ Pb, Cd, and Cr content were measured using GFAAS. The surface area associated to pore volume was characterized using iodine number analysis. The American Society for Testing and Materials (ASTMD4607-94) method is used to calculate the iodine number. In a nutshell, a typical iodine solution was treated with three different weights of adsorbent and 10.0 ml of 5% HCl under controlled conditions. This mixture was brought to boil for 30 s before being cooled. Following that, 100.0 ml of 0.1 N iodine solution was added and agitated for 30 s. The resulting solution was filtered, and 50.0 ml of the filtrate was titrated with 0.1 N sodium thiosulfate, using starch as an indicator. Finally, the iodine number, X/M value was calculated by using Eq. 2: X M = ( N 1 × 126.93 × V 1 ) − [ V 1 + V H C l V F ] × ( N 2 × 12693.0 × V 2 ) M , (2)

Batch adsorption experiments were carried out to determine the effect of the adsorbent dose, contact time, pH, initial metal ion concentration, and time of mixing to reach equilibrium for Pb, Cd, and Cr adsorbed by Cu-DPA MOF. About 0.5–3.5 g of adsorbent (as synthesized Cu-DPA MOF) was added into a synthetic solution of each metal and stirred for 4 h, and then kept for 24 h until equilibrium could be achieved and filtered. The experiment was conducted three times. The optimum mass of the adsorbent was obtained by plotting the percentage removal vs the mass of the adsorbent. The effect of contact time in the removal of Pb, Cd, and Cr from wastewater using Cu-DPA MOF is studied in a contact time range of 20–120 min. Removal of metal ions was also carried at a different initial concentration of metals (5–80 mg/L) and pH (2–10). Following the optimized procedure, 1.5 g of Cu-DPA MOF was added to 50 ml of the composite wastewater containing the Cd (0.0098 mg/L), Cr (0.3027 mg/L), and Pb (0.1021 mg/L) metals (at pH 2 for Cr and 6 for Pb and Cd). The solution was shaken for 80 min in the case of Cd and Cr (60 min for Pb), filtered using Whatman filter paper stored in refrigeration prior to GFAAS analysis. The adsorption capacity and removal efficiency were calculated using Eqs 3, 4, respectively: q e = ( C o − C e ) V m , (3) where q_e is heavy metal ions concentration adsorbed on adsorbent at equilibrium (mg of metal ion/g of adsorbent), C_o and C_e are the initial and equilibrium concentration or final concentration of metal ions in the solution (mg/L), V is the initial volume of metal ions solution used (in L) and m is the mass of adsorbent (in g). The removal efficiency was calculated using Eq. (4): %   R e m o v a l = ( C o − C e ) C o × 100 , (4) where C₀ and Ce are the initial concentration of heavy metals (mg/L) and the equilibrium concentration of heavy metals (mg/L), respectively.

The synthetic process was conducted at five different (i.e., for 1, 2, 3, 4 and 5 days) times of reaction. The copper nitrate trihydrate and diphenylamine precursors were completely dissolved in ethanol and distilled water, respectively prior to mixing and stirring. The two solutions with 1:1 M ration were then mixed, stirred for 1 h, and allowed to settle for 1, 2, 3, 4, and 5 days. The separated yield (based on metal precursor) increases from 38 to 92% as the reaction time increases from 1 d to 3 days. However, further increase in reaction time up to 5 days did not show significant improvement in yield, indicating the saturation level of the synthetic route. Analysis of iodine adsorption number is used to investigate the pore nature (e.g., microporous, mesoporous, and macroporous) of most adsorbents. The type of pores is an indication of adsorption capacity. Furthermore, the iodine adsorption number is used to evaluate the level of activation (a higher degree indicates stronger activation), and it is commonly provided in mg/g (with a typical range of 500–1,200 mg/g). The metal to ligand precursor ratio and their corresponding iodine number and isolated yield are shown in Table 2. The 1:1 metal to ligand ratio provided maximum iodine value (635 mg/g) and yield (92%), indicating good adsorption capacity with high porosity and high surface area. The adsorption capacity of Cu-DPA MOF decreases with increasing metal to ligand precursor ratio from 1:1 to 4:1. This is because the macropore structure of Cu-MOF deteriorated due to excessive copper metal that leads to the formation of a macropore in the MOF and basically due to the effect of pore widening that leads to the destruction of pore walls between neighboring pores, which decreases adsorption performance (Gupta et al., 2003). The iodine number value obtained for the 1:1 Cu-DPA MOF is comparable with zeolite-based adsorbents (641.7 mg/g) and twofold higher than activated carbon-based adsorbent from tamarind seeds (300 mg/g) reported before (Mopoung et al., 2015; Fanta et al., 2019). On the other hand, relatively higher iodine number (895 mg/g) was reported for activated carbon obtained from bean husk (Evwierhoma et al., 2018). Based on the determined iodine value and isolated yield, the 1:1 ratio is considered to be the optimal combination ratio. Fascinated by this observation, we fully characterized the prepared Cu-DPA MOF using a 1:1 ratio of metal to ligand combination.

The crystal structure of the as-synthesized Cu-DPA MOF was examined using XRD measurements of the samples. Figure 1 displays XRD patterns of as-prepared Cu-DPA MOF. As visibly evidenced in Figure 1A, a strong diffraction peak observed at 2 Theta values of 12.8°, 18.6°, and 20.2° are characteristics of Cu-DPA MOF and have good similarity with the diffraction patterns of other Cu-based MOF (Loera-Serna et al., 2012), indicating the profound crystalline nature of the prepared MOF. The calculated relative grain size (i.e., using the Scherer equation) was found to be 22.3 nm, indicating a mesoporous characteristic nature of the prepared MOF. This agrees well with the iodine adsorption number analysis. To examine the synthesized MOF’s structural information, we also measured FT-IR spectra of the prepared Cu-DPA MOF in the region from 400 cm⁻¹ to 4,000 cm⁻¹ in KBr using an FTIR spectrometer. Figure 1B shows the FTIR spectra of Cu-DPA MOF. As clearly displayed in Figure 1B, the presence of a broad peak at 3,384 cm⁻¹ in the as-prepared Cu-DPA MOF sample can be assigned to the N–H stretching. The diminished feature of this peak is a solid indicative for the linkage formed between copper and diphenylamine ligand. The peaks located at 1,497 and 1,319 cm⁻¹ are assigned to the N–H stretching vibrations of the aromatic ring. The Cu-diphenylamine ligand asymmetric stretching is observed at 749 cm⁻¹. The existence of NH functional group could act as a chemical binding agent via its dissociation into a negatively charged surface which could attract positively charged ions like metals. It can be seen that the IR-spectra indicated the presence of ionizable functional groups; their ionization leaves vacant sites which can be replaced by metal ions. This gives an indication that this material could be used as adsorbents for heavy metals removal (Aziz et al., 2005).

Before quantifying the metals in the wastewater samples, the MDL of the GFAAS was evaluated by analyzing six blank samples. It was found that the MDL of Pb, Cd, and Cr was 0.0615 mg/L, 0.0231 mg/L, and 0.0535 mg/L, respectively. By adding known concentrations of each element to the wastewater sample, the efficiency of the digestion technique and analytical method (GFAAS) was tested. In the same way, the spiked and non-spiked samples were digested and examined. By spiking 2.0 ml of 12.5 mg/L of each metal into a 50 ml wastewater sample, the efficiency of the optimized procedure was tested. As shown in Table 3, the calculated percent recoveries for studied metals in the wastewater sample (i.e., 93.26–98.2%) lie within the acceptable range (Mico et al., 2006).

Fascinated by the above findings, we also carried out investigation of removal efficiency of the as prepared Cu-DPA MOF toward Cd, Pb, and Cr in real wastewater samples collected from the car wash Labajo area located at Gamo Gofa zone, Arba Minch town, Ethiopia. The experiments were conducted under optimized conditions shown in the previous section. As clearly demonstrated in Table 4, the concentration of Pb (0.1021 mg/L), Cd (0.0098 mg/L), and Cr (0.3027 mg/L) in the wastewater before treatment was much higher than the permissible limit set by the World Health Organization. However, the corresponding concentration of Pb, Cd, and Cr was reduced to 0.0056, 0.0024, and 0.0015 mg/L after the treatment with the Cu-DPA MOF adsorbent. As a result, the removal efficiency of Cu-DPA MOF adsorbent for heavy metals in a real sample was calculated to be 97.6%, 99.5%, and 99.5% for Cd, Pb, and Cr, respectively. This indicates the as-prepared metal organic framework is very powerful and promising toward treatment of wastewater. Motivated by these findings, we also studied the regeneration of the Cu-DPA MOF after adsorption experiment. Herein a methanol solution followed by irradiation of the sample with low power UV was used to regenerate the used Cu-DPA MOF (Gupta et al., 2021). We first submerged and stirred the used MOF in 10 ml of methanol for 24 h at 500 rpm, followed by centrifugation and drying at ambient temperature for 24 h. Then, the dried MOF was illuminated with a low power UV lamp using a Pyrex tube fitted in an acryl reactor. About 91%, 94%, and 93.5% of the Cd, Cr, and Pb, respectively, could be removed from the used Cu-DPA MOF based on GFAAS analysis from the supernatant solution. Next, we reuse the regenerated Cu-DPA MOF under the same condition, the corresponding Cd, Cr, and Pb removal efficiency was reduced to 81%, 86%, and 87%, respectively, indicating that the MOF still exhibits efficient removal efficiency after regeneration. We further conducted scanning electron microscopy measurements to examine the morphology and microstructure of the 1:1 Cu-DPA MOF. As clearly displayed in Figure 5A, the as-prepared MOF before adsorption experiment exhibited a bright surface with octahedral and triangular particle features. However, when the MOF was taken to the adsorption experiment (Figure 5B), the small particles are observed over the octahedral and triangular structures of the MOF, indicating the adsorption of the metals over the MOF surface. Regardless of the coverage of the MOF surface with a small particle, there was no significant change in morphology after adsorption experiment.

To further investigate the relationship between adsorbent and adsorbate, we also underwent analysis of the adsorption process via the most commonly used models such as Langmuir and Freundlich isotherms. Adsorption happens at homogeneous locations, forming a monolayer, according to the Langmuir isotherm. In other words, once an adsorbate has been linked to a site, no additional adsorption can occur. Mathematically, the Langmuir isotherm is given by the following equation: C e q e = 1 b L q m + C e q m , (5) where qm is to the adsorption capacity (mg/g), qe is the equilibrium concentration of metals in the adsorbed phase (mg/g), Ce is the equilibrium concentration in the liquid phase (mg/L), and Langmuir constants, which are related to the adsorption capacity (qm) and energy of adsorption ( b L ), can be calculated from the slope of the linear plot of Ce/qe vs Ce; a straight line with slope 1/q_max and intercept of 1/q_max b L is obtained. The dimensionless factor, R _L, which is given by Eq. (6), is an essential feature of the Langmuir isotherm used to predict whether the Langmuir isotherm is favorable or unfavorable. R L = 1 1 + b L C o , (6) where C_o is initial concentration of adsorbate (mg/L), b L is Langmuir constant (L/mg). If R L >1.0, the sorption isotherm is unfavorable, R L = 1.0 (linear), 0 < R L < 1.0 (favorable), and R L = 0 (irreversible). In determining the nature of the adsorption process, whether favorable or unfavorable, the dimensionless constant separation term R L was investigated from Eq. 6. The obtained result ( R L = 0.357, 0.436, 0.271 for Cd, Pb, and Cr, respectively) shows that the sorption of Cd, Pb, and Cr onto the Cu-DPA MOF was favorable. On the other hand, the Freundlich isotherm is used to characterize heterogeneous surface and for description of multilayer adsorption properties of adsorbed molecules. The linear form of Freundlich isotherm is given by Eq. (7): log ⁡ q e = log ⁡ K f + 1 n log ⁡ C e , (7) where qe is the amount adsorbed at equilibrium (mg/g), K f and n are the Freundlich constant, 1/n is the heterogeneity factor which is related to the capacity and intensity of the adsorption, and Ce is the equilibrium concentration (mg/L). The values of K f and 1/n can be obtained from the slope and intercept of the plot of log ⁡ q e vs log ⁡ C e . The magnitude of the exponent, n, gives an indication of the favorability and capacity of the adsorbent/adsorbate system. Table 5, summarizes isotherm parameters of Langmuir and Freundlich models for adsorption Pb, Cd, and Cr over Cu-DPA MOF. The findings clearly reveal that the adsorption of Pb, Cd, and Cr metals on Cu-DPA MOF fits well with the Freundlich model. The fact that the Freundlich model is a good fit to the experimental adsorption data suggests physical adsorption as well as a heterogeneous distribution of active sites on the Cu-DPA MOF surface. The observed correlation coefficients for Freundlich isotherms were 0.995, 0.997, and 0.996 for Cd, Pb, and Cr, respectively. If the value of n is equal to unity, the adsorption is linear. If the value of the constant n is less than unity, the adsorption process is unfavorable; if the value of n is greater than unity, the adsorption process is favorable (Thamilarasu and Karunakaran, 2013). In the present study, the value of n at equilibrium was above unity, suggesting favorable adsorption. Furthermore, the values of the dimensionless factor, R L, were between 0 and 1 which suggest a favorable adsorption between Cu-DPA MOF and each metal. The Freundlich adsorption capacity ( K f ) shows easy separation of heavy metal ions from wastewater. The higher K f value the greater the adsorption intensity (Esrafili et al., 2018).

The adsorption capacity of the Cu-DPA MOF after optimizing all the parameters was estimated to be 2.19, 1.33, and 3.21 mg/g for Pb, Cd, and Cr, respectively. More interestingly, the obtained adsorption capacity is much higher than the reported values Cr (0.5–0.6 mg/g). Pb (1.9 mg/g) and Cd (0.63 mg/g) used activated carbon made from bamboo materials and carbon nanotube (Atieh et al., 2010; Lo et al., 2012). Furthermore, these adsorption capacity values are also comparable with activated carbon made from maize cob, 1.89 and 1.98 mg/g for Pb²⁺ and Cd²⁺, respectively (Igwe and Abia, 2007). On the other hand, the adsorption capacity obtained in the present study is relatively lower than the reported values for adsorbents such as natural zeolite (>9.0 mg/g). Synthetic zeolite (500 mg/g) and activated carbon made from the coffee husk and rice husk (3.0–38 mg/g) (Oliveira et al., 2008; Srivastava et al., 2008; Hamidpour et al., 2010; Agarwal and Singh, 2017).