Identification of the pollutants’ removal and mechanism by microalgae in saline wastewater

Accepted Manuscript Identification of the pollutants’ removal and mechanism by microalgae in saline wastewater Hoang Nhat Phong Vo, Huu Hao Ngo, Wenshan Guo, Yiwen Liu, Soon Woong Chang, Dinh Duc Nguyen, Phuoc Dan Nguyen, Xuan Thanh Bui, Jiawei Ren PII: DOI: Reference:

S0960-8524(18)31670-5 https://doi.org/10.1016/j.biortech.2018.12.026 BITE 20783

To appear in:

Bioresource Technology

Received Date: Revised Date: Accepted Date:

17 October 2018 7 December 2018 9 December 2018

Please cite this article as: Vo, H.N.P., Ngo, H.H., Guo, W., Liu, Y., Chang, S.W., Nguyen, D.D., Nguyen, P.D., Bui, X.T., Ren, J., Identification of the pollutants’ removal and mechanism by microalgae in saline wastewater, Bioresource Technology (2018), doi: https://doi.org/10.1016/j.biortech.2018.12.026

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Identification of the pollutants’ removal and mechanism by microalgae in

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saline wastewater

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Hoang Nhat Phong Voa, Huu Hao Ngoa,*, Wenshan Guoa, Yiwen Liua, Soon Woong Changb,

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Dinh Duc Nguyenb, Phuoc Dan Nguyenc, Xuan Thanh Buic, Jiawei Rena

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aCentre

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University of Technology Sydney, Sydney, NSW 2007, Australia

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bDepartment

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cFaculty

for Technology in Water and Wastewater, School of Civil and Environmental Engineering,

of Environmental Energy Engineering, Kyonggi University, 442-760, Republic of Korea

of Environment & Natural Resources, Ho Chi Minh City University of Technology (HCMUT)-

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Vietnam National University, Dist. 10, Ho Chi Minh city, Vietnam

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*Correspondence

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Abstract

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This study investigated the growth dynamics of a freshwater and marine microalgae with

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supported biochemical performance in saline wastewater, the pollutants assimilation by a

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developed method, and the mechanism of salinity’s effect to pollutants assimilation. Maximal

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biomass yield was 400 to 500 mg/L at 0.1 to 1% salinity while the TOC, NO3--N, PO43--P

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were eliminated 39.5-92.1%, 23-97.4% and 7-30.6%, respectively. The biomass yield and

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pollutants removal efficiencies reduced significantly when salinity rose from 0.1 to 5%. The

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freshwater Chlorella vulgaris performed its best with a focus on TOC removal at 0.1%

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salinity. The marine Chlorella sp. was prominent for removing NO3 - N at 0.1 to 1% salinity.

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Through the developed method, the freshwater C. vulgaris competed to the marine

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microalgae referring to pollutants assimilation up to 5% salinity. This study unveiled the

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mechanism of salinity’s effect with evidence of salt layer formation and salt accumulation in

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microalgae.

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Keywords: saline wastewater, microalgae, pollutants assimilation, salinity

authors: Huu Hao Ngo, Email: [email protected]

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1.

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Saline wastewater is a recalcitrant source of various pollutants and inorganic salts (Al‐Jaloud

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et al., 1993). Of the inorganic salts, they encompass NaCl, Na2SO4, MgSO4, KNO3 and

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NaHCO3 typically (Kester et al., 1967). Those inorganic salts are generated from several

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sources, including, but not limited to, agricultural run-off in saline soil zones (McCool et al.,

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2013), coastal areas (Feng et al., 2004), industrial activities (Abou-Elela et al., 2010;

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Figueroa et al., 2008; Guo et al., 2018; Lefebvre and Moletta, 2006; Lefebvre et al., 2005;

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Song et al., 2018) and secondary streams, such as concentrated effluent of membrane and

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physical/chemical processes (Wen et al., 2018). Salinity of saline wastewater varies in a

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broad range and inconsistently of its sources. Most authors report salinity of saline

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wastewater from 3% (Adenan et al., 2013) to 15% (Kubo et al., 2001). Of the tannery

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factories in Nigeria, the TDS concentration is from 65.4 to 1281.1 mg/L (Akan et al., 2007).

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Also, in the soaking and tanning wastewater streams, the TDS concentrations are 22,000 –

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33000 and 29,000 – 67,000 mg/L, respectively (Sundarapandiyan et al., 2010).

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Saline wastewater is a major environmental problem occurring in both terrain and water

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reservoir contexts. Inorganic salts are known to severely compromise crop production, reduce

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water infiltration capacity of saline land and increase salinization of freshwater (NSW

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Government, 2003; QLD Government, 2013). Furthermore, nutrients, heavy metals and

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organic pollutants of saline wastewater are responsible for eutrophication and toxic to

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ecological systems and human health (Lefebvre and Moletta, 2006; Liang et al., 2017). Saline

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wastewater costs Australian government up to $100 million per year for its consequences

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(NSW Government, 2003).

Introduction

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For these reasons the treatment of saline wastewater is a very critical issue. The high

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concentrations of inorganic salts make saline wastewater a refractory one. Interest has grown

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in developing advanced technologies to manage these concerns. Zeolite (Wen et al., 2018),

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anaerobic processes (Xiao and Roberts, 2010) and membrane process (Nguyen et al., 2018)

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are being increasingly reported as able to treat saline wastewater efficiently. However, saline

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wastewater treatment is a costly process (Wen et al., 2018). For example, the synthetic

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zeolites’ price was US$2,000,000 per metric ton (Wen et al., 2018).

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Among those options, microalgae process is a low cost and ‘green’ or eco-friendly one.

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Microalgae possess prominent characteristics for biofuel, biomaterial production and

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wastewater remediation. Of the biofuel production, they contain abundant feedstocks, such as

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lipid, fatty acid and carbohydrate (Sudhakar et al., 2017). Microalgae are also a profound

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source of agar, alginates and carrageenan serving for biomaterial production (Mata et al.,

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2010). Regarding environmental applications, microalgae have been implemented in the

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remediation of wastewater. Those harmful nutrients, micro-pollutants, heavy metals and

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organic pollutants can be removed by microalgae extensively (Escapa et al., 2015; Fan et al.,

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2018; Qiu et al., 2017). Under saline conditions, microalgae can adjust their biochemical

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identity, change biomass yield, pigment formation, and the efficiency of pollutants removal

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(Babatsouli et al., 2015; Church et al., 2017; Zhou et al., 2017). Unlike other processes,

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microalgae offer encouraging revenue from their biomass and pigments. Therefore,

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microalgae are the right choice for saline wastewater treatment.

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Although microalgae have been established for saline wastewater treatment, there are still

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shortcomings identified from the previous researches and they are highlighted as below:

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 Limited types of microalgae have been employed for saline wastewater treatment. The

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performance of freshwater and marine strains is also not compared sufficiently. For

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instance, Church et al. (2017) and Shen et al. (2015) utilized marine Chlorella

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vulgaris. Zhou et al. (2017) applied freshwater Spirulina platensis while Kim et al.

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(2016) employed Acutodesmus obliquus, but none information of strain was given.

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Thus, it is not possible to generate an accurate and comprehensive comparison of

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microalgae’s ability for saline wastewater treatment.  The pollutants assimilation efficiency of microalgae is inconsistent and deviant

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because of calculation methods. It is computed by the discrepancies of pollutants that

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appear in the influent and effluent concentrations. It ignores other processes such as

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precipitation, biosorption, and hydrolysis which can occur in a reactor. Therefore, it

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would affect the results of assimilation efficiency.  Most authors report that salinity impairs the pollutants assimilation of microalgae

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(Chen et al., 2017; Church et al., 2017). Nevertheless, the mechanism of the issue was

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not fully identified.

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Therefore, to clarify these drawbacks, the objectives of this research paper are to: (1)

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investigate the growth dynamics with supported biochemical performance; (2) examine

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pollutants’ assimilation with developed methods; and (3) study the mechanism of salinity

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affected pollutants’ assimilation of freshwater and marine microalgae strains in different

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salinities.

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2.

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2.1 Materials

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2.1.1 Microalgae strains

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In this research, three types of microalgae were purchased from National Algae Supply

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Service (Tasmania, Australia). The algae species included Chlorella vulgaris (freshwater

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microalgae), Chlorella sp. and Stichococcus sp. (marine microalgae) with respective strains

Materials and methods

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of CS-41, CS-436 and CS-437. Those microalgae strains were cultivated in 50 ml mediums

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and transferred to new cultures every 4 weeks for the purpose of creating stock solutions. The

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freshwater C. vulgaris was cultured in the MLA medium while the marine microalgae

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Chlorella sp. and Stichococcus sp. were fed in the f/2 medium. AusAqua Company

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(Australia) supplied the mentioned mediums. These stock cultures were operated in the

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following conditions: temperature of 20±1 oC; and continuous illumination intensity of 4.35 ±

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0.03 klux. The illumination was provided by a LED light bulb (11W, 220-240v) (Philip,

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Australia). The illumination level was measured by a light meter, model QM1584 (Digitech,

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Australia).

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2.1.2 Artificial wastewater

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In this study, artificial wastewater was experimented and it was prepared by distilled water

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with spiked chemicals. The values of total organic carbon (TOC), NO3--N and PO43--P were

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adjusted to 300, 60 and 15 mg/L in the artificial wastewater, respectively. The chemicals

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C6H12O6, KH2PO4, NH4Cl were used to create TOC, NO3--N and PO43--P in artificial

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wastewater. The trace elements were purchased from AusAqua Company (Australia) and it

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was applied in the artificial wastewater with an advised dose of 1ml per 1000L medium.

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2.1.3 Chemicals

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The chemicals used here, C6H12O6, KH2PO4, NaNO3, NaCl and Aceton, were purchased from

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Merck (Australia) and they were of analytical grade quality.

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2.2

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The stock microalgae were cultured in media until they were stabilized given that their

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concentration varied from 50 to 100 mg/L. Subsequently, 25 ml stock microalgae were

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transferred to experimental bottles of 1 L, which were capped to prevent air penetration.

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These bottles had been sterilized and filled with artificial wastewater. The magnetic stirrers

Experimental design

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were used to gently mix these cultures at a steady rate of 50 rpm. The applied temperature

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and light intensity were similar to those of the stock cultures. The hydraulic retention time

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(HRT) was 10 d with sampling being done every 2 d. The artificial wastewater was spiked

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with 4 levels of salinity, these being 0.1, 1, 3.5 and 5% NaCl.

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2.3 Analytical methods

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2.3.1 Biomass yield, optical density and growth rate

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2.3.1.1 Biomass determination

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For biomass yield determination, a 150 mL sample was filtered through a pre-weighed 1.2

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µm glass fiber filter paper GF/C (Whatman, Australia) (m1). The sample was then dried at

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105 °C in 24 h until a constant weight was achieved and completely dehydrated. The sample

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was re-weighted (m2). The biomass yield was calculated according to the formula below:

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Biomass yield =

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where

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m2: sample weight after drying (mg)

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m1: weight of filter paper (mg)

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v: volume of sample (L)

𝑚2 ‒ 𝑚1 𝑣

(mg/L) (Eq. 1)

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2.3.1.2 Optical density

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Optical density (OD) at 680 nm was used to quantify cell density by a spectrophotometer

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(DR1900, Hach). A correlation of OD680 and dry biomass weight in synthetic wastewater was

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pre-determined as written in Eq. 2-4.

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C. vulgaris: y = 0.0016x + 0.0075 (R² = 0.95) (Eq. 2) 6

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Chlorella sp.: y = 0.0021x + 0.0222 (R² = 0.95) (Eq. 3)

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Stichococcus sp.: y = 0.002x - 0.0049 (R² = 0.98) (Eq. 4)

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where

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x: biomass yield (mg/L)

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y: optical density

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During the experiments, microalgae samples were collected as a scheduled time, analysed for

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OD values and converted to biomass yields via Eq. 2-4.

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2.3.1.3 Specific growth rate

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The specific growth rate(s) (µ) (SGR(s)) is calculated using the following equation:

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µ=

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where

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X: the dry biomass weight at time t (mg/L)

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X0: the initial biomass weight at time t0 (mg/L)

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2.3.2 Pollutants’ assimilation rates

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The pollutants’ assimilation rates were computed following Eq. 6 as written below:

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RC, N, P = X (mg/L)  %mC, N, P/d (Eq. 6)

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Where

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RC, N, P: assimilation rate of C, N, P at time t (mg/d)

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X: biomass weight at time t (mg/L)

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%mC, N, P: portion weight of element C, N, P measured at time t, described in sub-section

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2.3.5.

(lnX ‒ ln𝑋0) (t ‒ 𝑡0)

(/d) (Eq. 5)

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d: desired HRT to estimate assimilation rate (10 d in this case)

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2.3.3 TOC, NO3--N, PO43--P concentrations

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The TOC concentration was analysed by Multi N/C 3100 (Analytikjena, Germany). The NO3-

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-N, PO43--P concentrations were analysed by test kits produced by Merck (Australia), coded

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114942 and 100798, respectively. The Photometer Nova 60 (Merck, Australia) was used for

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NO3--N, PO43--P analysis accordingly. All the samples were filtered by RC caps filter 0.2

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microns (Merck, Australia) beforehand.

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2.3.4 Chlorophyll a content

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The chlorophyll a analysis followed the procedure as recently used by Zhou et al. (2017). A

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10 ml sample was centrifuged at 10,000 rpm in 10 min. The pellets were re-suspended in 10

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mL of 90% acetone solution at 4 oC in 24 h in darkness, and then centrifuged at 4 oC, 4000

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rpm in 15 min. The received supernatant was measured at four wavelengths: 750 nm, 664 nm,

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647 nm and 630 nm with a spectrophotometer. The 90% acetone solution was used as the

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blank. The level of chlorophyll a was calculated as shown below:

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Chlorophyll a (mg/L) = 11.64*(OD663-OD750) - 2.16*(OD647-OD750) + 0.1*(OD630-OD750)

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(Eq. 7)

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where

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ODλ: optical density at wavelength λ (nm).

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2.3.5 SEM and EDS

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The surface and elemental analyses of microalgae cells were done using Scanning Electron

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Microscopy (SEM) and Energy Dispersive X-Ray Spectroscopy (EDS), respectively (Zeiss

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Supra 55VP, Carl Zeiss AG). Samples were filtered through glass fiber filter paper GF/C

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(Whatman, Australia), heated for 24 h at 105 oC for dehydration, and then coated by Au/Pd 8

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prior to SEM. The SEM images were operated at an accelerating voltage of 10 kV, and

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multiple image magnifications at various areas were achieved for each sample. The SEM

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analyses were employed to investigate the effect of salinities on pollutant’s assimilation of

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microalgae. The EDS was for quantifying the pollutants’ assimilation rates and salts

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accumulation.

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2.3.6 Statistical analyses

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The analyses of variance (ANOVA) was applied for statistical purposes. In details, the

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repeated measures ANOVA was employed to examine the effect of salinities on biomass

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yield, TOC, NO3--N and PO4--P and chlorophyll a according to the cultured time. For

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pollutants’ assimilation, the factorial ANOVA served to investigate the impact of salinities on

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C, N, P, Na and Cl assimilation efficiencies. All the data were presented as mean value ±

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standard deviation (Mean ± SD) with duplicated samples.

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3.

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3.1 Biomass yield and growth rate

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As can be seen from Fig. 1, the biomass yield of microalgae reduced significantly when

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salinity increased. At 0.1 and 1% salinity, the maximum biomass yields were recorded at a

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range from 400 to 500 mg/L, which were twice as high than 3.5 and 5% salinity. Of all

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microalgae species, the 5% salinity was observed with the lowest biomass yields that were

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below 200 mg/L. Similar results were achieved with salinity of 3.5%; however, the biomass

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yield rose steadily after day 8 indicating that the microalgae could adapt. Looking at the

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performance of each strain, the salinity of 0.1% was well-suited for C. vulgaris because this

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strain preferred the freshwater environment (F(3,15)= 3.48, p<0.05). A sudden rise was noted

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on day 4 when the biomass yield reached a maximum of 462 mg/L. The marine microalgae

Results and discussion

9

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Chlorella sp. (F(3,15)= 5.73, p<0.05) and Stichococcus sp. (F(3,15)= 3.65, p<0.05) grew

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substantially in saline conditions from 0.1 to 1%.

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Compared to other studies, the achieved biomass yield was competitive. As such, Zhou et al.

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(2017) explored the biomass yield of Spirulina platensis in salinities from 0.93 to 3.2%. After

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10 d, the maximum biomass yield was approximately 800 mg/L, which corresponded to a

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salinity of 2.24%. Although Zhou et al. (2017) applied the higher nutrient concentrations

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(COD=900 mg/L, TN=130 mg/L, TP=15 mg/L) and different light:dark cycle of 14:10 h, the

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resulting biomass yield was comparable. In another study, Kim et al. (2016) witnessed a

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biomass yield of A. obliquus as being 6 g/L at 4 d HRT with salinity of 5.2%. This biomass

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yield was significantly higher than reported in this study; it could be reasonably explained

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because Kim et al. (2016) experimented with piggery wastewater of the extremely high

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nutrient concentration (TOC = 3935 mg/L, TN = 981 mg/L, TP = 81 mg/L). Thus, the effect

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of salinity could be alleviated by utilizing high-loading nutrient concentration. To ensure its

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accuracy and validation, this observation requires more in-depth research. Church et al.

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(2017) also remarked that higher salinity decreased biomass yield accordingly and it agreed

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to the findings of this present study.

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[Insert Fig. 1]

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With reference to SGR, a similar trend was reported wherein an increase of salinity would

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reduce SGR of microalgae (Fig. 2) (Pandit et al., 2017; Shen et al., 2015) .

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The correlation of SGRs and saline levels fitted well with high reliability (R2>0.81). The

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achieved SGRs were in the range of 0.1 to 0.6/d. For C. vulgaris, Church et al. (2017)

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discovered its SGR was from 0.06 to 0.27/d which was lower than that reported in this study.

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When salinity ranged from 0 to 2.3%, Pandit et al. (2017) also explored the highest SGRs of

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C. vulgaris and A. obliquus were 0.127/d. Based on this data, this suggests that C. vulgaris is 10

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a better option for removing saline wastewater, and especially when the salinity ranged from

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0.1 to 1%. Alternatively, Chlorella sp. and Stichococcus sp. are applicable for higher salinity

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application.

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[Insert Fig. 2]

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3.2 Performance of the biochemical system

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The photosynthesis process of microalgae includes photosystem (PSI) and photosystem II

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(PSII) (Kebede, 1997). For PS I, the light-harvesting efficiency of photosynthetic activity is

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related to chlorophyll a pigment. The performance of chlorophyll a is important for

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evaluating the adaptation of microalgae in environmental stress conditions, including salinity.

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In this study, the production of chlorophyll a was initiated actively on day 2 of three

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microalgae; however, chlorophyll a concentrations of each microalga were different (Fig. 3).

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For C. vulgaris, its maximum chlorophyll a concentration was 13.6 mg/L at 0.1% salinity

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indicating it preferred this saline level (F(3,15)= 7.66, p<0.05). Regarding Chlorella sp., the

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gradual increase of chlorophyll a was identified at salinity of 0.1 and 1% (F(3,15)= 6.57,

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p<0.05). Likewise, Stichococcus sp. produced a significant amount of chlorophyll a at

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salinity of 0.1 and 1%. Its chlorophyll a concentration was higher compared to the other

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microalgae (F(3,15)= 8.44, p<0.05). After day 8, chlorophyll a concentration started to impair

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which coincided with the reduction of biomass yield. At 3.5 and 5% salinity, the chlorophyll

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a concentration of microalgae was very low and this explained the low nutrient consumption

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of those salinities.

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[Insert Fig. 3]

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It was previously highlighted that the chlorophyll a and c concentrations in brackish algae

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were higher than the marine one of 25% and 60%, respectively (Gylle et al., 2009). Based on

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this evidence, marine algae were more adaptable to salinity stress because their biochemical 11

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systems fluctuated less. According to Gu et al. (2012), the increment of salinity diminished

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Nannochloropsis oculata’s growth rate and pigment contents (e.g., chlorophyll a, and

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carotenoid), especially from 45 to 55 g/L of salinity concentration. The chlorophyll a

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concentration decreased to 2.03 mg/g (Gu et al., 2012). In this study, the results explored that

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salinity exerted a great impact on biomass yield and pigment concentration. In addition, the

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combined effect of salinity and other environmental stresses (e.g., temperature, acid rain)

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could worsen the effect. For example, low salinity and acid rain inhibited the

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photosynthesis process through the reduction of chlorophyll a concentration in Ulva

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prolifera (Li et al., 2017).

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3.3 Pollutants’ removal

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3.3.1 TOC removal

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For microalgae, organic carbon is an important nutrient source of cell build up and it presents

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in numerous saline wastewater types, such as food processing (Qin et al., 2017), agricultural

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run-off (Karimov et al., 2009) and mariculture (Feng et al., 2004). The TOC removal

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efficiency of microalgae differs among salinities that illustrates in Fig. 4.

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The observed trend of TOC removal efficiency was consistent with received biomass yield.

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The highest TOC removal efficiency happened for salinities of 0.1 and 1%. Typically for C.

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vulgaris, 92% of TOC was removed in 10 d and this corresponded to 0.1% salinity (F(3,15)=

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14.15, p<0.05). At 1% salinity and similar HRT, it eliminated approximately 50% of TOC.

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For Chlorella sp., a similar amount of TOC was removed (60-80%) when salinity was 0.1

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and 1% (F(3,15)= 14.84, p<0.05), while Stichococcus sp. illustrated better TOC removal at 1%

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salinity (F(3,15)= 9.35, p<0.05). With regard to 3.5 and 5% salinity, TOC removal efficiency

280

improved gradually in 10 d; however, its values were less than 50%. The TOC removal

12

281

efficiency could increase after 10 d but this increased the HRT, reactor volume and

282

associated costs.

283

From those results, it can be seen that salinity wielded a critical influence on TOC removal

284

efficiency of all microalgae species. Evidently, each microalga strain adopted its own

285

particular salinity. The freshwater microalgae removed TOC competitively at high salinity

286

(e.g., 3.5 and 5%) compared to marine microalgae. In another study, Kim et al. (2016)

287

discovered that Acutodesmus obliquus eliminated 70% of dissolved organic carbon in piggery

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wastewater at a salinity of 5.2%. Elsewhere, S. platensis removed 62 to 96% COD in mixed

289

saline wastewater (Zhou et al., 2017). As mentioned earlier, the nutrient concentrations in

290

influent wastewaters documented by Kim et al. (2016) and Zhou et al. (2017) were much

291

higher than in this study. Thus, the comparison was relatively easy to make. Pollutants’

292

removal efficiencies undertaken in our study provided better outcomes because the effects of

293

different salinities were considered.

294

[Insert Fig. 4]

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3.3.2 NO3--N removal

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Apart from C, N is a much needed element for microalgae growth in which NO3--N was used

297

in this work as a nutrient source. Both C. vulgaris (F(3,15)= 17.8, p<0.05) and Chlorella sp.

298

(F(3,15)= 19.5, p<0.05) removed 95% NO3--N at salinity of 0.1 and 1% (Fig. 5). During the

299

first two days, Chlorella sp. consumed NO3--N rapidly while C. vulgaris only did so

300

gradually. Stichococcus sp. utilized more NO3--N at salinity of 0.1% compared to 1% (F(3,15)=

301

12.43, p<0.05). Therefore, it can be suggested that Chlorella sp. has the potential to treat

302

NO3--N because its rapid consumption rate reduces the reactor/pond volume substantially.

303

Referring to von Alvensleben et al. (2013), Picochlorum atomus was stated as removing NO3-

304

-N more than 85% (Co=60-70 mg/L) in a saline environment of 0.2 to 3.6% salinity. Notably,

13

305

the used microalgae strain was halo-tolerant and the optimal salinity for microalgae was

306

1.1%. Congruent to von Alvensleben et al. (2013), the marine microalgae of this work

307

performed their best at a salinity of around 1% even though they associated with salinity of

308

3%.

309

[Insert Fig. 5]

310

3.3.3 PO43--P removal

311

In this study, the best removal efficiency of PO43--P was 30% that being moderately low (Fig.

312

6). With reference to C. vulgaris (F(3,15)= 18.86, p<0.05) and Chlorella sp. (F(3,15)= 13.12,

313

p<0.05), the effect of salinity on PO43--P removal efficiency was the same as TOC and NO3--

314

N. Specifically, they removed 30% of PO43--P at salinity of 0.1% which was higher than other

315

salinity. However, Stichococcus sp. consumed PO43--P differently. Among salinities of 0.1 to

316

5%, PO43--P removal efficiencies were unlikely different (F(3,15)= 3.250.05). It

317

can be concluded that Stichococcus sp. removed PO43--P independently to a wide range of

318

salinity from 0.1 to 5%.

319

[Insert Fig. 6]

320

To date, regarding PO43--P removal by microalgae, the results have been controversial and

321

non-conclusive. For example, after 5 d, C. vulgaris and Chlamydomonas reinhardtii removed

322

dissolved inorganic phosphorus in very small amounts at the initial concentration of 15 mg/L

323

(Shriwastav et al., 2017). Later on, in 3 d, the bacteria and microalgae consortium increased P

324

removal efficiency to 100% with an initial concentration of 6.53 mg/L (Shriwastav et al.,

325

2018). Thus, the bacterial consortium played an important part in P consumption and it was

326

more significant than microalgae. Compared to Shriwastav et al. (2017), Al Ketife et al.

327

(2016) remarked that P removal performance was notably better given that, within 10 d,

328

microalgae removed 90% of initial P concentrations of 4 to 6 mg P/L. This was due to the 14

329

higher biomass concentration of 200-500 mg/L whereas Shriwastav et al. (2017) could only

330

generate a biomass yield less than 120 mg/L. Interestingly enough, both studies used a model

331

with the same microalgae, that is C. vulgaris (Al Ketife et al., 2016; Shriwastav et al., 2017).

332

Other authors agreed with Al Ketife et al. (2016) in that P was removed substantially

333

regardless of the microalgae species involved (Shen et al., 2015; von Alvensleben et al.,

334

2013; Zhou et al., 2017).

335

This study agreed with Shriwastav et al. (2017) in that P removal by microalgae was limited.

336

As mentioned previously, calculating the efficiency of removing P through the difference

337

between influent and effluent concentration could entail errors being hidden (Vo et al., 2018).

338

Hence, the EDS technique was employed in this study to explain the issue. Additionally, the

339

Redfield constant also noted the C:N:P ratio for microalgae consumption was 106:16:1. In

340

this study, the moderate P removal efficiency complied with the Redfield ratio accordingly.

341

3.3.4 Pollutants’ assimilation rates

342

The pollutants’ assimilation rates as supported by EDS are illustrated in Table 1. Generally,

343

these assimilation rates decreased when the saline levels increased (F(3,24) = 6.15, p<0.05).

344

The C and N assimilations were affected slightly by salinity, especially at 5%, in which the

345

assimilation rate reduced by 35 to 50% compared to assimilation rates of 0.1% salinity. For

346

C. vulgaris and Chlorella sp., the C and N assimilation rates were the highest of the 0.1 and

347

1% salinity. With reference to Stichococcus sp., the assimilation rates were the most

348

significant when salinity ranged from 1 to 3.5%.

349

Regarding P uptake, C. vulgaris and Chlorella sp. suffered severely from salinity given that

350

the assimilation rates diminished from 50 to 77%. Nevertheless, it was observed that

351

Stichococcus sp. wielded only a slight influence, specifically, the assimilation rate reduced by

15

352

35%. This confirmed the P removal efficiency described in sub-section 3.3.3. Salinity had a

353

much less significant impact on P uptake of Stichococcus sp.

354

According to Kim et al. (2016), the respective N and P assimilation rates of A. obliquus were

355

175 and 1.5 mg/g biomass.d. As noted earlier, the applied N and P concentrations in the

356

influent were higher, these being 981 and 81 mg/L, respectively. Also, the N and P

357

consumption rates as summarized by Shriwastav et al. (2017) were 600 and 80 mg/g

358

biomass.d. Elsewhere, Al Ketife et al. (2016) modelled pollutants’ assimilation with total C,

359

N, P yield coefficiencies of 500, 200 and 24 mg/g biomass. It should be noted that this study

360

investigated the assimilation rates of pollutants based on the EDS technique. The

361

experimental platform and calculated unit were, consequently, different. Doing this

362

eliminated the potential errors due to the involvement of other processes such as biosorption

363

and precipitation. The influence of inlet organic loading levels on pollutants’ assimilation

364

rates needed to be examined extensively.

365

[Insert Table 1]

366

3.4 Effect of salinity on pollutants’ assimilation

367

Most authors have agreed that salinity hindered the pollutants’ assimilation by microalgae

368

(Borecka et al., 2016; Zhang et al., 2016). Previously, the numerous hypotheses and findings

369

on this issue are not conclusive (Pandit et al., 2017; Shen et al., 2015; von Alvensleben et al.,

370

2013; Zhou et al., 2017). Through the literature, the effects of salinity on pollutants’ removal

371

efficiency were highlighted with an emphasis on two major topics: (i) the competition of salt

372

ions and pollutants in the bulk liquid; and (ii) the internal accumulation of salt ions in

373

microalgae cells.

16

374

With reference to the first assumption, via the SEM technique, an unsaturated salt layer was

375

found as attached on microalgae cells’ surface at salinity levels of 3.5 and 5%. These layers

376

might be responsible for the reduction of pollutants’ accumulation efficiency. For instance,

377

salinity increased from 0.5 to 3% and its ionic strength rose from 0.10 to 0.61 mol/L, which

378

diminished the activity coefficient of Cu2+ from 0.35 to 0.23 (Chen et al., 2017). The

379

increment of ionic strength probably caused salt crystal attached on microalgae surface and

380

impaired the pollutants assimilation. Also, Zhang et al. (2016) reported that the organic

381

matters layer reduced 5 - 10% the pollutant assimilation efficiency of microalgae, being

382

similar to the salt layer of this study.

383

For the second mechanism, Na+ has been known to be involved in the co-transport of P into

384

microalgae cells; however, this was limited to a salinity below 100 mg/L (Mohleji and

385

Verhoff, 1980). Church et al. (2017) agreed that Na+ would impair the assimilation rate,

386

especially at 4.5% salinity because Na+ would stream into microalgae cells and inhibited the

387

photosynthesis reaction accordingly. The high Na+ ion concentration in the chloroplasts

388

would reduce the quantum yield of photosystem II, diminish the protein synthesis and reduce

389

the biomass yield (Müller et al., 2014). In the chloroplast of plant, the concentration of ion Cl-

390

was from 1-50 mM (Schroppel-Meier and Kaiser, 1988). The over increase of Cl- can lead to

391

cells toxic.

392

Of the Na+ and Cl- concentration in microalgae cell, the solid evidence is provided in Table 2.

393

Of Stichococcus sp., the highest Na+ and Cl- accumulations were 15.77 and 25.66 mg/L,

394

respectively. The concentration of Na+ and Cl- ions in cells increased steadily when the

395

salinity rose accordingly (F(3,15)= 28.29, p<0.05). C. vulgaris accumulated those ions

396

competitively with Chlorella sp. and Stichococcus sp (F(5,15)= 0.59, p>0.05) until salinity of

397

5%. At 5% salinity, the broken cells of C. vulgaris were found. On the other hand, the cells of

17

398

Chlorella sp. and Stichococcus sp. stayed normal and this underlines their good adaptation in

399

salinity of 5%.

400

[Insert Table 2]

401

This work is the first to unlock the salt layer on microalgae cells’ surface. It updates previous

402

assumptions and observations and also establishes a background for extensive research on

403

saline wastewater treatment by microalgae. Saline wastewater removal includes two major

404

objectives which are: the removal of pollutants and desalination. Salinity is the main obstacle

405

to pollutants’ removal undertaken by biological processes. To remove pollutants efficiently,

406

the salts in wastewater need to be eliminated simultaneously. Although bioprocesses such as

407

activated sludge and anaerobic processes have been commented on as having great capability

408

in removing pollutants’ in saline wastewater (Ahmadi et al., 2017; Gebauer and Eikebrokk,

409

2006; Lefebvre et al., 2005), desalination is still a major technical challenge.

410

4. Future perspectives and practical applications

411

In this study, the results have fixed the shortcomings of previous research and offered the

412

practical applications. Firstly, the appropriate microalgae species for saline wastewater

413

treatment have been identified. C. vulgaris was implemented in salinity of 0.1% with the

414

focus on TOC removal. If the saline wastewater contained high N concentration and salinity

415

from 0.1 to 1%, Chlorella sp. was the ideal candidate. The fast N consumption rate by

416

Chlorella sp. will help in reducing reactor volume and operational costs. When microalgae

417

are employed for pigment, instead of removing the pollutants, Stichococcus sp. produces

418

superior chlorophyll a content.

419

Those microalgae are applicable to petrochemical wastewater treatment. The petrochemical

420

wastewater contained salinity of 3% and COD of 1100 – 1300 mg/L (Ahmadi et al., 2017). 18

421

Microalgae process is an option compared to the activated sludge process of Ahmadi et al.

422

(2017) because it would reduce the operation cost. The microalgae can also combine with a

423

sponge biocarrier osmotic membrane bioreactor of Nguyen et al. (2018). The influent

424

wastewater contained 2.4% NaCl, 300 mg/L dissolved organic carbon, 36 mg/L NH4+-N and

425

22 mg/L PO43--P, given it fits microalgae process. With mariculture saline wastewater, it

426

possessed the respective TOC, TN and salinity of 100-125 mg/L, 40-50 mg/L and 3.45% (Song

427

et al., 2018). Similarly, those microalgae are feasible for treatment of this mariculture saline

428

wastewater

429

Furthermore, the pollutants’ assimilation rates and SGR estimated in this study can serve as a

430

manual for future saline wastewater treatment designs. The HRT, biomass retention time

431

(BRT) and reactor/pond volume can be calculated accordingly. In continuous operation, the

432

BRT, which was calculated from the maximum specific growth rate (1/μmax ~ BRT), was

433

computed. The μmax could be retrieved with a known influent salinity of wastewater from Fig.

434

2. The BRT should be maintained in the reactor/pond by harvesting the excess microalgae

435

biomass in order to sustain the maximum microalgae growth rate.

436

This study clearly describes the impact of salinity with evidence of salt layer formation and

437

salinity accumulation in microalgae cells. This established a platform for in-depth research

438

tailored at reducing salinity’s influence and enhancing biomass yield and pollutants’

439

assimilation efficiency. Another objective is to achieve higher organic loading because the

440

literature and some prior studies’ comparisons have indicated that the impact of salinity can

441

be alleviated.

442

5.

443

Saline wastewater treatment by microalgae is proved feasible. However, high salinity

444

concentration resulted in low removal efficiency of TOC, NO3--N, PO43--P. The freshwater C.

Conclusion

19

445

vulgaris demonstrated its capability to compete in assimilating pollutants’ compared to

446

marine microalgae. The new approach to explore microalgae’s assimilation of pollutants

447

could help to document the underlying effects of salinity. Future research of investigating the

448

efficiency of assimilating pollutants in high saline conditions is necessary.

449 450

E-supplementary data for this work can be found in e-version of this paper online.

451 452

Acknowledgement

453

This research was supported by the Centre for Technology in Water and Wastewater,

454

University of Technology, Sydney, Australia (UTS, RIA NGO) and “Korean Ministry of

455

Environment as a “Global Top Project”, Project No. 2016002200005” .

456 457 458 459 460 461 462

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593

26

594

[Figure captions]

595

Fig. 1. Biomass yield of (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus sp. at various

596

salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard deviation of two

597

samples

598

Fig. 2. Correlation of SGRs and salinities (0.1, 1, 3.5, 5%).

599

Fig. 3. Chlorophyll a performance of (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus

600

sp. at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

601

deviation of two samples

602

Fig. 4. Remained TOC removed by (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus sp.

603

at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

604

deviation of two samples

605

Fig. 5. Remained NO3--N removed by (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus

606

sp. at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

607

deviation of two samples

608

Fig. 6. Remained PO43--P removed by (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus

609

sp. at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

610

deviation of two samples

611

27

612

Table 1. Pollutants assimilation rates at day 10th (mg/d) Element/

C. vulgaris

Chlorella sp.

Stichococcus sp.

Salinity (%)

C

N

P

0.1

1

3.5

5

0.1

1

3.5

5

0.1

1

3.5

5

15.55

15.41

14.72

3.32

18.82

19.8 ±

16.06

2.00 ±

9.01 ±

9.51 ±

17.32

6.00 ±

± 0.19

± 0.14

± 0.18

0.03

± 0.13

0.16

± 0.21

0.03

0.8

0.5

± 0.23

0.4

5.29 ±

5.35 ±

4.91 ±

0.77 ±

6.25 ±

5.41 ±

5.40 ±

0.71 ±

3.14 ±

2.98 ±

5.86 ±

1.79 ±

0.06

0.01

0.04

0.02

0.08

0.07

0.04

0.03

0.07

0.1

0.08

0.04

0.64 ±

0.58 ±

0.28 ±

0.05 ±

0.77 ±

0.39 ±

0.45 ±

0.05 ±

0.31 ±

0.21 ±

0.39 ±

0.13 ±

0.05

0.04

0.02

0.003

0.03

0.02

0.04

0.004

0.01

0.01

0.02

0.01

613

28

614 615

Table 2. Weight of salts accumulation in microalgae cells (mg/L) Salt ion/

C. vulgaris

Chlorella sp.

Stichococcus sp.

Salinity (%)

0.1

1

3.5

5

0.1

1

3.5

5

0.1

5.19

Na

3.5

5

3.39

3.26 ±

4.77 ±

15.77

7.90 ±

5.87 ±

±

14.08

5.79 ±

4.75 ±

±

15.79

8.94 ±

0.27

0.35

± 0.63

0.58

0.34

0.47

± 1.13

0.36

0.51

1.73

± 1.06

0.61

3.42

Cl

1

1.73

0.87 ±

3.71 ±

20.93

15.57

1.57 ±

±

18.68

8.75 ±

0.51 ±

±

25.66

14.77 ±

0.05

0.27

± 0.86

± 0.93

0.09

0.39

± 0.72

0.47

0.06

0.17

± 1.26

0.94

616 617

29

[List of figures] Biomass Yield (mg/L)

618

600 500 400 300 200 100 0 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

Biomass Yield (mg/L)

(a) 600 500 400 300 200 100 0 0

2

4

6

8

10

HRT (d)

Biomass Yield (mg/L)

0.10%

1%

3.50%

5%

(b) 600 500 400 300 200 100 0 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

(c) 619

Fig. 1. Biomass yield of (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus sp at various

620

salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard deviation of two

621

samples 30

0.7

SGRs (/d)

0.6 0.5 0.4 0.3 0.2 0.1 0 0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

Salinity (%)

622 623

C. vulgaris

Chlorella sp.

Stichococcus sp.

Fig. 2. Correlation of SGRs and salinities (0.1, 1, 3.5, 5%).

624

31

5.00

Chlorophyll content (mg/L)

625

25 20 15 10 5 0 0

2

4

6

8

10

HRT (d)

Chlorophyll content (mg/L)

0.10%

1%

3.50%

5%

(a) 25 20 15 10 5 0 0

2

4

6

8

10

HRT (d)

Chlorophyll content (mg/L)

0.10%

1%

3.50%

5%

(b) 25 20 15 10 5 0 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

(c) 626

Fig. 3. Chlorophyll a performance of (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus

627

sp at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

628

deviation of two samples 32

Remained Concentration (%)

120 100 80 60 40 20 0 0

2

4

6

8

10

HRT (d)

Remained Concentration (%)

0.10%

1%

3.50%

5%

(a) 120 100 80 60 40 20 0 0

2

4

6

8

10

HRT (d)

Remained Concentration (%)

0.10%

1%

3.50%

5%

(b) 120 100 80 60 40 20 0 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

(c) 629

Fig. 4. Remained TOC removed by (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus sp.

630

at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

631

deviation of two samples

632

33

Remained Concentration (%)

120 100 80 60 40 20 0 0

2

4

6

8

10

HRT (d)

Remained Concentration (%)

0.10%

1%

3.50%

5%

(a) 120 100 80 60 40 20 0 0

2

4

6

8

10

HRT (d)

Remained Concentration (%)

0.10%

1%

3.50%

5%

(b) 120 100 80 60 40 20 0 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

(c) removed by (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus

633

Fig. 5. Remained NO3

634

sp. at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

635

deviation of two samples

--N

636

34

Remained Concentration (%)

110 90 70 50 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

Remained Concentration (%)

(a)

110 90 70 50 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

Remained Concentration (%)

(b)

110 90 70 50 0

2

4

6

8

10

HRT (d)

0.10%

1%

3.50%

5%

(c) 637

Fig. 6. Remained PO43--P removed by (a) C. vulgaris, (b) Chlorella sp. and (c) Stichococcus

638

sp. at various salinities (0.1, 1, 3.5, 5%). Value and error bars are the average and standard

639

deviation of two samples. 35

640

Highlights

641

 Freshwater C. vulgaris is comparable to marine microalgae in pollutants removal.

642

 Unsaturated salt forms layer on microalgae cells’ surface.

643

 Microalgae accumulate salt ions in cells proportionally to salinities in culture.

644

 Statistic well-confirms the negative effect of salinities on pollutant assimilation.

645

 Organic loading levels might alleviate salinities effect but not yet proved.

646 647

36