DOI: 10.3303/CET2188078 
 

 
 

 
 

 

 
 

 
 
 

 
 

 

 
 
 

 
 
 

 
 
 
 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 

Paper Received: 17 June 2021; Revised: 20 July 2021; Accepted: 15 October 2021 
Please cite this article as: Hladíková M., Šulc R., 2021, A Tool for Modelling of One- or Two-Step Microalgae Harvesting Processes, Chemical 
Engineering Transactions, 88, 469-474  DOI:10.3303/CET2188078 

CHEMICAL ENGINEERING TRANSACTIONS

VOL. 88, 2021 

A publication of

The Italian Association
of Chemical Engineering
Online at www.cetjournal.it 

Guest Editors: Petar S. Varbanov, Yee Van Fan, Jiří J. Klemeš

Copyright © 2021, AIDIC Servizi S.r.l. 

ISBN 978-88-95608-86-0; ISSN 2283-9216

A Tool for Modelling of One- or Two-Step Microalgae
Harvesting Processes

Martina Hladíková*, Radek Šulc

Czech Technical University in Prague, Faculty of Mechanical Engineering, Department of Process Engineering,
Technicka 4, 160 00, Prague 6, Czech Republic
Martina.Hladikova@fs.cvut.cz

Separation of microalgae from aqueous solutions still requires further optimization and knowledge. The tool for
modelling of one- or two-step microalgae harvesting technology should provide a way to predict the final
concentration of microalgal suspensions. The presented spreadsheet-based tool enables to determine the mass
balance of the separation process and other parameters required for the equipment basic design. These
parameters are the mass flow rate of individual media, an agent consumption, and the estimation of energy
consumption. The tool allows a user to combine different separation processes of various separation
efficiencies. A pretreatment by coagulation or flocculation before the separation process can be also included.
The applicability of this approach was demonstrated on three cases.

1. Introduction

Harvesting of microalgae is an energy-intensive and expensive part of the production of microalgal biomass due
to the necessity to separate a large volume of culture medium from microalgal suspensions. According to the
Barros et al. (2015), the harvesting process usually accounts for about 20 to 30% of the total cost. Unlike this,
Fasaei et al. (2018) estimated the share of harvesting cost in the range from 3 to 15 % of total production costs.
They reported the cost range from 0.3 to 2 € kg-1 algae and the energy consumption up to 4.5 kWh kg-1 algae
for the treatment of 0.05 % cultivation suspension (an open cultivation system) to 15 % dry matter. Increasing
the cultivation concentration combined with a lower feeding shifts, the energy consumption towards to lower
values. They reported the production cost below 0.5 € kg-1 algae and the energy consumption below 0.5 kWh
kg-1 algae for the treatment of the algae suspension cultivated in closed cultivation systems (1.5 ÷ 2.5 kg m-3).
Selection of the adequate harvesting technology depends on many factors, mainly on the characteristics of the
target microorganism and on the type and value of the end product (Barros et al., 2015). Al Hattab et al. (2015)
used the following criteria: (a) dewatering efficiency, (b) cost, (c) toxicity, (d) suitability for a large-scale use, (e)
time, (f) species specificity, (g) reusability of media and (h) maintenance for the evaluation of 16 harvesting
techniques applied for biodiesel production in an industrial scale.
To achieve the highest possible final concentration of the microalgal suspension, the two-step harvesting
process is considered more effective than the one-step harvesting process. The first step of the two-step
harvesting process, commonly referred to as thickening, is used to remove a large amount of culture medium,
hereinafter referred to as water. For this stage, cheaper harvesting technologies, such as gravitational
sedimentation or flotation are used. Belohlav and Jirout (2019) developed a methodology for the equipment
basic design of gravitational settlers based on the measured settling velocity and the distribution of microalgae
cells. The operational parameters of various flotation techniques are presented in more detail in Hladíková and
Šulc (2021). The second step is performed by a more energy-intensive and expensive technology, such as
centrifugation or filtration. Abu-Shamleh and Najjar (2020) identified eight factors with the potential to affect the
energy consumption of the disc-stack centrifuge. They found that the particle size, the rotational speed, and the
outer radius of the centrifuge are the main three factors that have the largest impact on the energy consumption
of the centrifuge. Membrane filtration for microalgae harvesting has been used both in a single-step and two-
step process (Bilad et al., 2014). The harvesting performance should be improved by coagulation and
flocculation.

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Various computational approaches are used in various technico-economic studies to obtain rigorous mass
balances. Davis et al. (2011) used ASPEN software for a techno-economic analysis of autotrophic microalgae
for fuel production. Riós et al. (2013) combined ASPEN software, MATLAB software, and a spreadsheet model
for the modelling of different scenarios of harvesting, oil extraction, and transesterification of lipids for biodiesel
production. The ASPEN software was used for modelling of oil extraction and lipid transesterification. The
harvesting was modelled by a spreadsheet model. The MATLAB software was used for the interaction and data
exchange between all modules. The special and complex software, such as ASPEN and MATLAB, are relatively
easily available for academic purposes and for commercial purposes of large companies. Therefore, there is an
opportunity for spreadsheet-based tools for their simplicity and availability for a wide group of users.
This work aims to create a simple spreadsheet-based tool for process modelling of one- or two-step harvesting
processes enabled to determine the parameters for the equipment basic design, such as the mass flow rates of
individual components, the agent consumption, the final concentration of the microalgal suspension, and the
estimation of energy consumption for the following input data: the input volumetric flow rate of the microalgal
suspension, the input concentration of the microalgal suspension and the efficiencies of individual harvesting
methods. The process model also implements a coagulation/flocculation technique as a pretreatment method.
For the mass balancing, the methodology proposed by Ditl and Netušil (2018) was adopted and applied.

2. Separation process: tool overview

The separation process is performed at the end of the exponential growth phase of the phototrophic microalgal
cultivation. This process model consists of 3 stages: i) pretreatment, ii) separation technique 1 (noted as
Separation 1) and iii) separation technique 2 (noted as Separation 2). The block scheme of the algal technology
from cultivation to utilization is shown in Figure 1. The balanced harvesting technology is defined by the
balancing boundary. The streams and present components are described in Table 1. The harvesting technology
can be configured as a single-stage or two-stage process. In case of the one-step harvesting process, just
Separation 1 is performed. In case of the two-step harvesting process, both separation stages are performed.
Separation 1 and Separation 2 refer to various separation processes which can be used to harvest microalgae
from aqueous solutions. The used separation processes are defined by a user.
Optionally, a pretreatment by coagulation or flocculation of the microalgal suspension can be included. A
coagulant or flocculant, hereinafter referred to as an agent, can be applied to enhance the entire separation
process. During this stage, the agent is mixed with water in a stirred vessel and the mixture is transported to a
static mixer. In the static mixer, the mixture of the agent and the microalgal suspension are mixed. Aggregates
of microalgae cells are formed. The pretreatment has a positive effect on the harvesting efficiency of the
following separation processes.
Considered balanced components are biomass, coagulant or flocculant, and water. The numbering of defined
components is presented in Table 2. The following terms microalgal suspension and input microalgal
suspension are used in the next sections with this meaning: i) the microalgal suspension consists of biomass,
agent and water, and ii) the input microalgal suspension consists of biomass and water. The spreadsheet tool
utilizes MS EXCEL software.

Figure 1: The block scheme of the balanced harvesting technology defined by a balancing boundary (the red 

dashed line)  

The following assumptions are considered for the presented cases:
 Density of the cultivation medium is 1,000 kg m-3

 Streams no. 4 and 6 contain only water
 The added amount of coagulant/flocculant is directly proportional to the concentration of the microalgal

suspension
 If coagulation/flocculation is applied, a solid agent is mixed with water in a stirred vessel, and the agent

concentration of 0.1 % w/w is considered in the final aqueous solution

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Table 1: Balancing tool: the definition of streams and their composition 

Number of the stream Description of the stream Component
1 microalgal suspension feed biomass, water
2 agent feed (aqueous solution) an agent, water
3 feed of Separation 1 unit biomass, an agent, water
4 water removed by Separation 1 water
5 feed of Separation 2 unit biomass, an agent, water
6 water removed by Separation 2 water
7 microalgal suspension outflow biomass, an agent, water

Table 2: Balancing tool: the definition of components 

Number Component
1 biomass
2 an agent
3 water

Based on the following input parameters, the mass balance is calculated:
 Separation line performance (m3 h-1)
 Concentration of the microalgal suspension entering the separation line (gmic L-1)
 Density of the microalgal suspension (kg m-3)
 Dosage of coagulant/flocculant if applied (kg)
 Efficiency of separation process 1 (%)
 Efficiency of separation process 2 if applied (%)

3. Mass balance calculation

The mass balance calculation is based on the mass balance approach proposed by Ditl and Netušil (2018).
Using this methodology, the mass flow rates of individual components and the stream composition were
determined.
The steady state was assumed, i.e., the sum of the mass flow rates of input streams equals to the sum of the
mass flow rates of output streams. Mass balance in individual process units is described, in general, by the
equation Eq(1), where ṁj,i_IN (kg h-1) is the mass flow rate of the ith medium in the jth stream entering a process
unit and ṁj,i_OUT is the mass flow rate of the ith medium in the jth stream leaving a process unit.

∑ṁj,i_IN = ∑ṁj,i_OUT (1)

In the following text, all equations required for the mass balance calculation are listed. Total mass balan ce in
the pretreatment unit, separation unit 1, and separation unit 2 is described by the following equations Eq(2),
Eq(3), and Eq(4), respectively:

ṁ1 + ṁ2 = ṁ3 (2)

ṁ3 = ṁ4 + ṁ5 (3)

ṁ5 = ṁ6 + ṁ7 (4)

Mass balance of components in the pretreatment unit is calculated for biomass by Eq(5), for an agent by Eq(6),
and for water by Eq(7):

ṁ1,1 = ṁ3,1 (5)

ṁ2,2 = ṁ3,2 (6)

ṁ1,3 + ṁ2,3 = ṁ3,3 (7)

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Mass balance of components in the separation unit 1 is calculated for biomass by Eq(8), for an agent by Eq(9),
and for water by Eq(10):

ṁ3,1 = ṁ5,1 (8) 

ṁ3,2 = ṁ5,2 (9)

ṁ3,3 = ṁ4,3 + ṁ5,3 (10)

Mass balance of components in the separation unit 2 is calculated for biomass by Eq(11), for an agent by Eq(12),
and for water by Eq(13):

ṁ5,1 = ṁ7,1 (11)

ṁ5,2 = ṁ7,2 (12)

ṁ5,3 = ṁ6,3 + ṁ7,3 (13)

The total mass flow rates of streams 1 and 2 are expressed by Eq(14) and Eq(15), respectively,

ṁ1,1 + ṁ1,3 = F (14)

ṁ2,2 + ṁ2,3 = A (15)

where F is the separation line performance (kg h-1) and A is the mass flow rate of the aqueous solution including
the added agent (kg h-1). The feed mass flow rate of the biomass is expressed by Eq(16), where C1,1 is the mass
fraction of the biomass in the microalgal suspension feed. The mass flow rate of the dosed coagulant/flocculant
is described by Eq(17), where C2,2 is the mass fraction of the agent in the aqueous solution including
a coagulant/flocculant.

ṁ1,1 = C1,1 ∙ ṁ1,3 (16)

ṁ2,2 = C2,2 ∙ ṁ2,3 (17)

The impact of separation processes on the water outflow in the microalgal suspension is described by Eq(18)
for Separation 1, and by Eq(19) for Separation 2:

ṁ5,3 = (1 −
η1
100

) ∙ ṁ3,3 (18)

ṁ7,3 = (1 −
η2
100

) ∙ ṁ5,3 (19) 

where η1 is the efficiency of Separation 1 (%) and η2 is the efficiency of Separation 2 (%). The output volume
concentration of the microalgal suspension cF (g L-1) is calculated according to the following equation Eq(20):

cF =
ṁ7,1

V̇SUSP
(20)

where VSUSP (m3 h-1) is the volumetric flow rate of the microalgal suspension after the separation process, ṁ7,1
(kg h-1) is the mass flow rate of the biomass in the stream 7. In this case, the weight of 1 L of the microalgal
suspension equal to 1 kg was assumed.

4. Results: mass balance and energy consumption

The results of the following cases were calculated assuming the separation line capacity of 50 m 3 h-1. The
various separation technologies differ in separation efficiency. For example, the separation efficiency of flotation
is low if no agents are applied before the separation. In this case, the efficiency tends to be in the range from
50 to 60 %. If the membrane separation is applied, the harvesting efficiency of 70 % can be reached. Unlike
this, the centrifugation enables to reach the harvesting efficiency of 90 %.
In Case I, the effect of configuration and stage efficiency on the outflow stream flow rate and outflow microalgal
concentration is demonstrated in Table 3 for the input concentration of the microalgal suspension = 5 g L-1. The
following parameters such as the final volumetric flow rates in each stage VSUSP1 and VSUSP2 (m3 h-1), and the
final concentrations in each stage cF1, cF2 of the microalgal suspension (gmic L-1) are shown. In the next cases,

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the separation efficiency of 80 % was assumed for the stage Separation 1 (e.g., a membrane technology), and
90 % was assumed for the stage Separation 2 (e.g., centrifugation), and the coagulation/flocculation was used
as a pretreatment method. The results are presented in Table 4 for the input concentration of the microalgal
suspension of 1 g L-1(Case II), and in Table 5 for the input concentration of the microalgal suspension of 5 gL-1
(Case III).

Table 3: Case I: the effect of configuration and stage efficiency on outflow stream flowrate and outflow microalgal 

concentration for the input concentration of the microalgal suspension = 5 g L-1 and the separation line capacity 

= 50 m3 h-1 

Separation 1 (%) Separation 2 (%) VSUSP1 (m3 h-1) cF1 (gmic L-1) VSUSP2 (m3 h-1) cF2 (gmic L-1) 
50 80 25.124 9.9 5.224 47.6
50 90 25.124 9.9 2.736 90.1
60 80 20.149 12.4 4.229 58.8
60 90 20.149 12.4 2.239 111.1
70 80 15.174 16.4 3.234 76.9
70 90 15.174 16.4 1.741 142.9

Table 4: Case II: A two-step process with a pretreatment by coagulation or flocculation for the input 

concentration of the microalgal suspension = 1 g L-1 and separation line capacity = 50 m3 h-1  

Microalgae Coagulant/Flocculant (CF) CF dosage
(gC/F L-1)

VSUSP1
(m3 h-1)

cF1 
(gmic L-1)

VSUSP2
(m3 h-1)

cF2 
(gmic L-1)

Chlamydomonas sp. cationic guar gum 0.1 11.169 4.5 1.166 42.8
Chlorella sp. cationic locust bean gum 0.055 10.459 4.8 1.093 45.7
Chlorella vulgaris poly γ-glutamic acid 0.02 10.207 4.9 1.066 46.8
Chlorella protothecoides poly γ-glutamic acid 0.02 10.207 4.9 1.066 46.8
Micractinium sp. cationic locust bean gum 0.04 10.507 4.8 1.098 45.5
Scenedesmus sp. Al2(SO4)3 0.1 11.901 4.2 1.243 40.2
Scenedesmus sp. Ca(OH)2 0.4 17.397 2.9 1.827 27.3
Scenedesmus sp. FeCl3 0.15 12.831 3.9 1.341 37.3
Note: CF dosages were overtaken from Hladíková and Šulc (2021).

Table 5: Case III: A two-step process with a pretreatment by coagulation or flocculation for the input 

concentration of the microalgal suspension = 5 g L-1 and separation line capacity = 50 m3 h-1 

Microalgae Coagulant/Flocculant (CF) CF dosage
(gC/F L-1)

VSUSP1
(m3 h-1)

cF1 
(gmic L-1)

VSUSP2
(m3 h-1)

cF2 
(gmic L-1)

Chlamydomonas sp. cationic guar gum 0.1 15.845 15.7 1.834 135.7
Chlorella sp. cationic locust bean gum 0.055 12.293 20.2 1.463 170.1
Chlorella vulgaris poly γ-glutamic acid 0.02 11.037 22.5 1.331 186.9
Chlorella protothecoides poly γ-glutamic acid 0.02 11.037 22.5 1.331 186.9
Micractinium sp. cationic locust bean gum 0.04 12.536 19.8 1.488 167.2
Scenedesmus sp. Al2(SO4)3 0.1 19.505 12.8 2.216 112.3
Scenedesmus sp. Ca(OH)2 0.4 47.421 5.3 5.133 48.5
Scenedesmus sp. FeCl3 0.15 24.157 10.3 2.702 92.1

Table 6: Case III: A two-step process with a pretreatment by coagulation or flocculation for the input 

concentration of the microalgal suspension = 5 g L-1 and separation line capacity = 50 m3 h-1 

Microalgae  Coagulant/Flocculant Energy requirement (kWh m-3) 
Chlamydomonas sp. cationic guar gum 11.7
Chlorella sp. cationic locust bean gum 10.9
Chlorella vulgaris poly γ-glutamic acid 10.6
Chlorella protothecoides poly γ-glutamic acid 10.6
Micractinium sp. cationic locust bean gum 10.9
Scenedesmus sp. Al2(SO4)3 12.6
Scenedesmus sp. Ca(OH)2 12.1
Scenedesmus sp. FeCl3 13.7

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Finally, the energy demand of the harvesting process was estimated for Case III, see Table 6. For this purpose,
the following energy demands were adopted: i) the energy demand of coagulation/flocculation of 0.07 kWh m -3
of the microalgal suspension including the mixture of an agent and water (Danquah et al., 2009), ii) the energy
consumption of 2.9 kWh m-3 of permeate (Zhao et al., 2020) for membrane separation by a PVDF membrane
(stage Separation 1), and iii) the energy demand of 8 kWh m-3 of the input microalgal suspension (Danquah et
al., 2009) for centrifugation (stage Separation 2). The energy required for pumping between units was neglected.
Considering the equivalent length of 100 m, the velocity of 1.5 m s-1, and the pumping efficiency of 85 %, the
estimated pumping energy is 0.027 kWh m-3. The energy consumption is in the range of 10.6 to 13.7 kWh m-3
of the microalgal suspension feed, i.e., 2 ÷ 2.7 kWh kg-1 of algal feed. Compared to Fasaei et al. (2018), the
higher energy demand was estimated under the given assumptions.

5. Conclusions

A spreadsheet-based tool for modelling of one- or two-step harvesting process was presented. The harvesting
technology can be configured as a single-stage or two-stage process. The used separation processes are
defined by a user. Optionally, a pretreatment by coagulation or flocculation before the separation process can
be also included. In this case, it is important to consider the added volume of water because a coagulant and
flocculant are dosed as an aqueous solution. The tool enables to provide parameters for the equipment basic
design. These parameters are the mass flow rates of individual media, an agent consumption, and the estimation
of energy consumption. The applicability of this approach was demonstrated on three cases considering some
simplifying assumptions. The more accurate are the input data and the process model, the more accurate results
can be obtained. For future research, the database implemented in the model will be further extended.

Acknowledgments 

This research was supported by Student Grant Competition of CTU as part of grant no. SGS20/118/OHK2/2T/12
and by the Ministry of Education, Youth and Sports of the Czech Republic under OP RDE grant number
CZ.02.1.01/0.0/0.0/16_019/0000753 "Research centre for low-carbon energy technologies".

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