A bioassimilation and bioaccumulation model for the removal of heavy metals from wastewater using algae: New strategy
Introduction
Water and wastewaters contaminated with heavy metals (HMs) from industrial effluents can cause serious health problems for human and biotic organisms (Almomani et al., 2019b; Jawed et al., 2020; Li and Song, 2020; Rahman and Singh, 2019; Shen et al., 2020; Siddiqui et al., 2019; Yuan et al., 2018; Zhong et al., 2019). Different studies have reported that the presence of HMs in water even at very low concentrations have various effects on human including nervous system damage, kidney failures, and cancer (Ahmad and Mirza, 2017; Dahiya et al., 2008; Ghaemi et al., 2017; Shin et al., 2011; Visa, 2016). Therefore, their treatment and removal from water resources is an essential priority.
Bioassimilation (BS) and bioaccumulation (BC) represent the two mechanisms by which metals are removed from media by algal cells. Many transitional metals, including cobalt, copper, iron, molybdenum, nickel, vanadium and zinc, are considered essential micro-nutrients in supporting algal growth (Almomani et al., 2019a; Almomani, 2019; Brownell and Nicholas, 1967; Takahashi et al., 2011). As essential nutrients, metals are often added to commercial algal media, together with chelating agents such as EDTA (Fogg and Thake, 1987; Znad et al., 2018) to enhance their uptake by the microalgae. However, these metals may be bio-assimilated at concentrations exceeding those determined by biostoichiometry, bioaccumulating without being required for growth (Thronson, 2008); uptake under such circumstances is thus by adsorption.
Metals and nutrient addition can significantly add to the operating costs of microalgal cultivation technology (MCT). As such, consideration has been given to the fate of metals in both the MCT and downstream algae hydrothermal liquefaction (AHTL) processes (Al Ketife et al., 2019; Almomani et al., 2019c; Jiang and Savage, 2019; Judd et al., 2017; Leng et al., 2018), AHTL being used to recover the microalgae latent energy. However, whilst it is known that biochemical composition affects the AHTL behavior, the potential for metals recycling from the aqueous waste stream of this process is yet to be investigated.
Transitional metals uptake has been explored most extensively for copper, cadmium, and chromium (Birungi and Chirwa, 2014; Corrêa et al., 2017; Mehta and Gaur, 2005; Siegel and Siegel, 1973), though rare earth metals have also been studied (Dirbaz and Roosta, 2018; Kwak et al., 2015; Markou et al., 2015b; Xie et al., 2014). A literature review related to the capacities and removals of transitional metals and other micronutrient species by algae is presented in
Table 1 In summary, results revealed that the metals uptake is promoted through anionic functional groups such as the carboxylic, hydroxyl, phosphoryl and sulfhydryl groups which form part of the algal cell wall and the associated exopolysaccharide chemistry (Mehta and Gaur, 2005; Siegel and Siegel, 1973). These groups complex with the cationic metal ions, providing adsorption capacities (q) of between 26 and 910 along with removal efficiencies generally exceeding 80 % for various algal strains. Unicellular algal cells appear to have higher capacities due to their higher surface to volume ratio, with capacity also increased by increasing the pH (Mehta and Gaur, 2005). Regression analysis of the available literature data suggests that the maximum adsorption capacity (qmax) as a function of the initial concentration of metals can be successfully correlated with R2 ≥ 0.9 to the empirical relationship presented in Eq. (1)qmax = 0.74 Co – 22where Co is the initial concentration of HM in the wastewater
The influence of metals and other macros–nutrient on algal growth over a range of metals species and concentrations has been frequently reported as presented in Table 2. The parameters listed include the degree of importance (DOI) that reflects the influence of these parameters on cell metabolism and growth. The data indicate that the DOI, expressed as the mass of metal as a percentage of the algal weight concentration (DWC), does not correlate with the concentration of metal in the biomass. For example, although the DWC potassium (K+) is more than three-fold higher than magnesium (Mg2+), their DOI values are in the same order of magnitude. Moreover, the DWC of both these species is several orders of magnitude greater than that of selenium, reported as being 5 × 10−5 %, the DOI value is nonetheless only half of that of metals species present at concentrations around 0.4–1.4 % (e.g. Ca2+, Fe3+, K+, Mg2+, Na+).
It has been reported that metal ions accumulate inside cells in cellular compartments, for instance, the cell vacuole (space/vesicle within the cytoplasm of a cell) and organelles (the small cellular structure embedded within the cell cytoplasm) (Giles et al., 1974; Malkoc and Nuhoglu, 2006). The metabolism-driven metal efflux systems of the algal microorganisms maintain low intracellular metals concentrations, thereby avoiding metal toxicity (Malik, 2004). In the case of toxic metals such lead (Pb2+), known to have an inhibitory effect on the growth, a less toxic form of the species or else volatilization can take place within the algal cells via enzymatic transformation of metal ions (Malik, 2004).
Table 3 presents the effect of micronutrient on the growth of Chorella Vulgaris (C.v) the most used algae in wastewater treatment applications. In addition to the growth parameters (Xmax and μ), metal yield coefficients (Y) have been identified as the second important parameter affecting the cell growth and metals uptake. The Y values have been determined based on either direct experimental data (Ex) or through biokinetic modeling (Biok). Literature shows that the yield values are proportional to the mass of metal uptake and tend to increase with decreasing hydraulic residence time (HRT). For instance, the Y value obtained for Cu2+ and Fe3+ at Xmax of 1.72 g L−1 was 58, while 2.9 was recorded at Xmax of 1.8 for Mg2+.
The previous literature review indicated high discrepancies in the reported BS and BC, an unclear explanation on the effect of the process variables (micronutrient, growth rate, metal yield coefficients, temperature (T), water content (W) and algal load(A)) on the HMs removal, BS and BC via algae process. There is limited research work on the capability of the algae processes to accomplish complete HM removal, and no well-established strategies to determine the optimum conditions for these two mechanisms. Besides, during the operation of the algae-based treatment process, the fluctuation in the influent water quality parameters may have a direct influence on the process performance and operational control. All the previous lack of knowledge highlight the importance of a well-developed mathematical model that can be used for predicting the kinetic behavior of HMs removal, BS and BC of algal technology. Accordingly, in the current study, a mathematical model for BS combined with BC based on the MCT-AHTL process is presented for Chorella Vulgaris. Specific attention is given to the coupling of both energy and metals recovery in the treatment of wastewater. The effect of process parameters on the percentage HM removals (%HMr), BS and BC to fulfil rigorous discharge limitations were evaluated. The developed model is capable of forecasting the process efficiency under different operational conditions. With such a model, optimal conditions over an operational period can be determined, which saves both time and energy.
Section snippets
Selected microalgae
In the current study Chlorella vulgaris, (C.v) was selected to investigate metals treatment and recovery from an algal bioreactor (Danièle et al., 2016; Kucuker et al., 2016; Birungi and Chirwa, 2014; Sayadi et al., 2019). This strain has been reported to be resistant to high loads of metals, and to allow excessive accumulation inside the cell. This is thought to relate to heavy metal-binding ligands present in algal cells associated with proteins such as phytochelatins (PCs) and
AHTL yields analysis
Response surface methodology (RSM) and Box Behnken Design (BBD) were used to determine the maximum values for the biofuel yield (BY), biosolid and liquid yields (SY and LY) from the AHTL process based on the key input parameters of temperature (T = 350−450 °C), water content (W = 16–55 vol %) and algal load (A = 5−15 wt%). Fig. 4 presents the contour plots for BY, SY, and LY as a function of temperature (T), water content (W) and algal load (A). The corresponding prediction formulas of these process
Conclusion
Bioassimilation (BS) combined with bioaccumulation (BC) phenomena using the microalgae cultivation process were simulated using combined RSM-BBM methodologies. Percentage removal (%RE), and the products of the algae hydrothermal liquefaction process were investigated. Metals recovered was mainly retained from the aqueous and solid phase. The RSM-BBM results revealed that the %RE of Cd2+> Cu2+> Pb2+ reported at 74 %, 73 % and 69 %, respectively. The BC of Cu2+ was 6 folds higher than BS, while
Declaration of Competing Interest
I wish to confirm that there are no known conflicts of interest associated with this publication. We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.
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