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Modelling and evaluation of productivity and economic feasibility of a combined production of tomato and algae in Dutch greenhouses
b i o s y s t e m s e n g i n e e r i n g 1 2 2 ( 2 0 1 4 ) 1 4 9 e1 6 2
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Research Paper
Modelling and evaluation of productivity and economic feasibility of a combined production of tomato and algae in Dutch greenhouses Bart Slager a,b, Athanasios A. Sapounas a, Eldert J. van Henten a,b,*, Silke Hemming a a
Wageningen University and Research Centre, Greenhouse Horticulture, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands b Wageningen University and Research Centre, Farm Technology Group, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
article info
Combination of production of algae and tomato increases efficient use of available re-
Article history:
sources of greenhouse enterprises, such as controlled environment, water and nutrients,
Received 2 July 2013
carbon dioxide, greenhouse space and infrastructure and knowledge. No information is
Received in revised form
available, however, about the potential productivity and related costs of a combined to-
26 November 2013
mato and algae production in Dutch greenhouses. The objective was to determine the algae
Accepted 6 April 2014
productivity in tubular photobioreactors (PBRs) and the economic feasibility of combined
Published online
production of tomato and algae in Dutch greenhouses. A model was developed to predict greenhouse climate from outside climate, to predict tomato and algae biomass production
Keywords:
and to analyse scenarios of different locations and dimensions of tubular PBR in the
Photobioreactor (PBR)
greenhouse with regard to algae productivity and cost price of algae production. The re-
Light
sults show that algal productivity is low if PBRs are installed under a tomato crop due to
Temperature
limited light levels. Areal algal productivity was calculated to be 5e6.5 kg DM m2 if PBRs
Economic analysis
are installed in a separate greenhouse compartment next to tomato. In this case the minimum cost prices of algae production was calculated to be V11 kg1 DM algae, which give perspectives for the future. The proposed model is important because it gives insight into the feasibility of algae and tomato production in Dutch greenhouses. This novel model approach and the scenario results provide better knowledge about the potential productivity and related costs and returns of algae production in greenhouses. ª 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
1.
Introduction
The quest for non-fossil based chemicals and fuels has strongly renewed research interest in algae during the last two
decades (Luque, 2010; Norsker, Barbosa, Vermue¨, & Wijffels, 2011). Algae are a potential resource for food, feed, pharmaceutics, cosmetics, pigments, chemicals, fuel, bio-fertilisers and they can be used for waste water treatment (Becker, 1994; Barbosa, 2003). Between 8000 and 10,000 tons of
* Corresponding author. Wageningen University and Research Centre, Greenhouse Horticulture, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands. E-mail addresses: [email protected], [email protected] (E.J. van Henten). http://dx.doi.org/10.1016/j.biosystemseng.2014.04.008 1537-5110/ª 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
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Nomenclature
a
English symbols Concentration of algae biomass in PBR kg m3 Cb Cp Specific heat capacity of the algae fluid J kg1 DM Algae dry matter production m2 m2 dt Integration time step 1 s Diameter of the PBR tube m dtube Maximum algae growth rate at temperature T h1 gmax L Length of the PBR tube m LAI Leaf area index of tomato crop m2 m2 h Heat transfer coefficient 10 W m2 K1 Iav Average intensity of PAR inside the PBR mmol m2 s1 Iin Intensity of total solar radiation inside the greenhouse above Tomato crop W m2 I0 Intensity of PAR incident on PBR mmol m2 s1 Iopt Optimum radiation received by the algae at temperature T h1 Qra,sol Radiation flux reaching the PBR directly mmol m2 s1 Qre,sol Radiation flux reaching the PBR after reflection from the Greenhouse floor mmol m2 s1 Qc Convective energy exchange between PBR and greenhouse air W Reflexivity of the greenhouse floor surface 0.5 [e] rg T Temperature K or C t Time 1 h V Volume of the PBR system m3 Wp Electrical pump power kW
bI g bT bIT g DPtotal 3
hp hm g
q0 g
qopt qI0 qIopt r rI swall 4v
Light absorption coefficient of the algae biomass 0.0752 m2 g1 Shape factor for limitation by radiation 0.50 [e] Shape factor for limitation of algae growth rate by temperature 0.02 [e] Shape factor for limitation by Iopt0.56 [e] Maximum growth rate at optimal temperature 0.0583 h1 Total pressure differences in the PBR system Pa Emissivity of algae liquid 0.97 [e] Efficiency of pump 0.80 [e] Efficiency of electric engine driving the pump 0.90 [e] Temperature at which algae growth rate is zero 4.7 C Temperature at which algae growth rate is maximum 20.5 C Temperature at which Iopt is zero 4.7 C Temperature at which Iopt is maximum 12.3 C Density of the algae fluid kg m3 Maximum radiation flux value at the optimum temperature 538 mmol m2 s1 Transmittance of the polyethylene PBR wall 0.85 [e] Volume flux through PBR tubes m3 h1
Subscripts PBR Related to Air Related to Crop Related to Path Related to
the photobioreactor the greenhouse air PBR under crop PBR on path
Greek symbols
microalgae biomass are produced annually, having a market value of approximately $3000e4000 million (Tredici, Biondi, Ponis, Rodolfi, & Zittelli, 2009). The Dutch horticultural sector has shown interest in the production of algae. Pressure on economic margins and drive for innovation have triggered the interest of Dutch growers to exploit their resources and capital in a more effective way. The resources needed for production of vegetable crops and algae are quite comparable. Both need light and a properly controlled carbon dioxide concentration (CO2), nutrient concentrations and temperature for optimal production. Also similarities exist when it comes to required infrastructure, management and knowledge. Essentially, with all technology present and the knowledge and expertise of growers on resource management and optimised biomass production (Dieleman & Hemming, 2011), Dutch greenhouses should be able to facilitate both tomato and algae production effectively. The proposed combined cultivation fits in a wider range of recent developments, in which combinations of different agricultural activities have been studied or attempted. The combination of tomato and fish production, for example, was found to have distinct mutual advantages (Graber & Junge, 2009; Nichols & Savidov, 2012; Rakocy, 2012; Vergote & Vermeulen, 2012).
Currently, several Dutch growers combine the production of tomato with algae in small scale experiments on a very intuitive basis. A more systematic study of integrated production of vegetable crops and algae in Dutch greenhouses is still lacking and quite a range of questions are still unanswered. For instance, Wijffels, Barbosa, and Eppink (2010) estimated that 40e80 t algae dry matter could be produced in closed photobioreactors (PBRs) outdoors, but potential productivity in a greenhouse is yet unknown. The design of a tubular PBR has been studied by several authors (Acie´n Ferna´ndez, Garcı´a Camacho, Sa´nchez Pe´rez, Ferna´ndez Sevilla, & Molina Grima, 1997, 1998; Bosma, Van Zessen, Reith, Tramper, & Wijffels, 2007; Molina, Ferna´ndez, Acie´n, & Chisti, 2001; Slegers, van Beveren, Wijffels, Van Straten, & Van Boxtel, 2013), but no design has been studied for greenhouse conditions. The best location of an algae production system in relation to a tomato production system, the suitable dimensions of PBRs and influence of system scale are still unknown. Integration of the production of vegetable crops and algae does not only increase efficient utilisation of resources, but might also increase competition for resources, especially light. In view of light availability, the dimension as well as the location of algae PBRs in a combined production system has to
b i o s y s t e m s e n g i n e e r i n g 1 2 2 ( 2 0 1 4 ) 1 4 9 e1 6 2
151
Fig. 1 e Venlo type greenhouse with tomato crop (a) and tubular algae PBRs under the crop. PBR tube diameter 16 cm (b), 11 cm (c) and 6 cm (d).
be identified. Last but not least, together with productivity and consequently economic return, investment and running costs influence the PBR design. The first economic data for different PBR systems were collected by Norsker et al. (2011), but economic data of commercial PBRs in greenhouses are largely unknown yet. Moreover, no study has been carried out on the potential productivity and related costs and returns of an integrated production of crop and algae in greenhouses. The objective of this research was to determine the algae productivity in a tubular PBR as well as the economic feasibility of a combined production of tomato and algae in Dutch greenhouses. Similar to the work of Vanthoor et al. (2012), for this purpose a model was developed to predict greenhouse climate for tomato and algae production from outside climate, to predict tomato and algae biomass production and to analyse scenarios of different places and dimensions of tubular PBR in the greenhouse with regard to algae productivity and cost price of algae production. Different design configurations were studied and scenario analyses were performed.
2.
Materials and methods
2.1. System description of combined production of tomato and algae in a greenhouse In this desk study a typical Dutch Venlo-type greenhouse was considered with a total area of 1.04 ha. The greenhouse dimensions were 100 m length, 104 m width (13 sections of 8 m, each of them containing 5 crop rows), 4 m length of main path,
5 m gutter height and 22 roof angle. A crop row consisted of the gutter with tomato crop having a width of 1 m and a path for logistics and labour of 0.6 m. The crop gutters were mounted 0.80 m above the floor, leaving a space underneath in which an algae PBR might be located. A standard Dutch tomato crop was considered, with a production cycle running from December 15th of the year to November 15th the next year. The layout of algae PBRs was based on an existing algae production system implemented in a Dutch greenhouse, Fig. 1. With respect to the location of the algae PBR, in this study two distinctly different designs were considered. Firstly, integrated production was considered. Figure 2 displays this system graphically, with a continuous flow algae PBR integrated with the tomato crop in the same greenhouse compartment. The tubes of the PBR were aligned with the crop gutters and had the same length as the gutters (96 m). In this system layout, three cases were analysed (Table 1). The PBR tubes were placed on the floor under the tomato crop, or on the floor in the path between the tomato crop rows, or both underneath the crop and in the path. Since a dense algae biomass will result in self-shading, the diameter of the tubes was expected to affect the overall performance of the PBR. Both the diameter and number of tubes were varied between scenarios. This resulted in a PBR consisting of six, four or two tubes, with tube diameters of 6 cm, 11 cm and 16 cm respectively. For each scenario the tube diameter was kept constant. It was expected that the tomato crop would cause considerable shading of the PBR. Since the leaf area index (LAI) determines the interception of light by the crop, additional scenarios were analysed in which the LAI of the tomato was reduced by 5% or 10%.
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Fig. 2 e Schematic cross section of greenhouse with integrated production of a tomato crop and algae PBR under the crop and on the path between the crop (a) and with separated production of a tomato crop and algae (b).
Secondly, separated production was considered. In this case the continuous flow algae PBR was located in a separate compartment next to the compartment in which tomatoes were grown (Fig. 2). To allow a fair comparison with integrated production in relation to the dimensioning of the system, two different separate production scenarios were studied. In the first one, hereafter referred to as the small scale system, the algae compartment was given such a size that the productivity was equal to integrated production. This was done by calculating the algae dry matter yield for one tube in the separated compartment, and based on that result the amount of tubes needed to reach the same yield of certain integrated production system was calculated. In the second scenario, hereafter referred to as large scale system, the number of PBR tubes in the separated production was equal to the number of PBR tubes installed in integrated production, and thus installation and running costs of both systems were comparable. In both scenarios, the PBR tubes were mounted horizontally on the floor parallel to the gutters in the tomato compartment. Tube diameters were assumed to be 6 cm, 11 cm or 16 cm. The distance between the PBR tubes was taken equal to one third of the tube diameter. The floor surface was considered to exhibit diffuse reflection, reflecting direct and diffuse radiation homogeneously in
every direction. The reflectivity of the floor surface was defined as the ratio of the reflected flux to the incoming flux. In tomato production systems, in practice a white plastic film is used to cover the floor, which has a reflexivity of about 0.9. In the current study the reflectivity was set to 0.5, to account for dirt and dust and for possibly uneven reflection due to the spacing of the tubes.
2.2. Model of combined production of tomato and algae in a greenhouse A Matlab-based model was developed to determine productivity and economic feasibility of the combined production of tomato and algae in a Dutch greenhouse for different scenarios with respect to location and dimension of the PBR, as outlined in the previous section. The model consists of four sub-models: a greenhouse climate model, a tomato production model, an algae production model and an economic model (Fig. 3).
2.3.
Greenhouse climate model
For this sub-model, the existing and validated greenhouse simulation model KASPRO was used (Hemming, Sapounas, de
Table 1 e PBR dimensions in integrated and separated production systems. Integrated production system
Under crop 6 cm
Number of tubes Number of tubes per crop row Tube length [m] PBR volume [m3] PBR volume per area [m3 m2] Separated production system Number of tubes Tube length [m] PBR volume [m3] PBR volume per area [m3 m2] Area of separated compartment [m2]
On path
11 cm
16 cm
6 cm
11 cm
16 cm
195 130 6 4 2 96 2 96 106 237 0.0106 0.0237 Small scale system 6 cm 11 cm
65 2 2 96 251 0.0251
65 1 96 125 0.0125
16 cm
130 130 2 2 96 96 35 119 0.0035 0.0119 Large scale system 6 cm 11 cm
37 96 10 0.04 250
11 96 21 0.09 233
520 96 141 0.04 3525
195 96 376 0.09 4178
22 96 20 0.06 333
390 96 356 0.06 5933
16 cm
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153
Fig. 3 e Schematic data flow chart of the model built to evaluate productivity and economics of combined production of tomatoes and algae in a Dutch greenhouse.
Zwart, Ruijs, & Maaswinkel, 2010; Luo et al., 2005; de Zwart, 1996). KASPRO is a dynamic simulation model which simulates a full-scale virtual greenhouse based on the greenhouse construction elements, ventilation openings, greenhouse equipment, covering materials and their properties (transmission, reflection, and emission), set-points for inside climate and the outside climate of a given location. Yearround hourly data are used as input and the differential equations are solved with an integration time step of 1 s. An important feature of the KASPRO simulation model is that the modelled greenhouse climate is controlled by a replica of commercially-used climate controllers. Besides physics of the climate including control, it also contains models of dry matter production of various crops. The climate in a greenhouse is mainly dependent on the outdoor climate. As input data for KASPRO, hourly climate data of the so-called SEL-year were used (outdoor temperature, humidity, wind speed and direction, direct and diffuse solar radiation and sky temperature). The SEL-year contains the weather data of an ‘averaged’ year, using the methodology described by Breuer and van de Braak (1989). It is compiled of hourly data of the most representative seasonal weather conditions of the years 2000e2009, as measured by the Dutch meteorological institute KNMI (Swinkels, 2009). In the case of integrated production of tomatoes and algae, the energy balance of the PBR system was influenced by the conditions in the greenhouse, but it was assumed that the PBR was not influencing the greenhouse climate, which was controlled using set points 15 C for heating system and 20 C for ventilation (no cooling system was considered). For separated production it was assumed that the climate in the compartment with tomato was completely isolated from the climate in the compartment with algae. The climate in the compartment with the PBR was also simulated with KASPRO, yet without a crop, by setting the leaf area index of the crop (LAI) equal to zero. The absence of a crop allowed different
climate control set points, which in this case were set to 12 C for heating system and 18 C for ventilation (no cooling system was considered).
2.3.1.
Tomato production model
The tomato production sub-model is an integral part of the KASPRO model of de Zwart (1996) and predicts dry matter production of a tomato crop. The photosynthesis rate is calculated based on the solar radiation level in the greenhouse, temperature, CO2 concentration and the water vapour deficit of the greenhouse air. The interception of radiation by the crop was based on Goudriaan (1988). Canopy transpiration was based on Stanghellini (1987).
2.3.2.
Algae production model
This sub-model predicts dry matter production of algae in a tubular photobioreactor. A number of algae growth models have been described (e.g. Dermoun, Chaumont, Thebault, & Dauta, 1992; Quinn, de Winter, & Bradley, 2011; Zonneveld, 1998). Temperature and radiation are considered to be the two most important factors influencing algae growth (Carvalho, Monteiro, & Malcata, 2009). In the current study an empirical model, which describes the growth of the red alga Porphyridium cruentum influenced by temperature and radiation, was chosen (Dermoun et al. 1992). It was assumed that nutrient availability and carbon dioxide were non-limiting, the oxygen was easily removed, the pH was ideal/optimal and the algae suspension in the PBR was perfectly mixed. Data from the KASPRO model, such as inside solar radiation above the tomato crop (Iin), the leaf area index of the tomato crop (LAI) and the air temperature inside the greenhouse (Ti) were used as input for the algae production model.
2.3.2.1. Light. The solar radiation above the algae PBR is depending on LAI and light absorption by the tomato crop in case of Integrated production. The average solar radiation in
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the algae PBR is depending on PBR transmission, PBR dimensions and density and absorption of algae both in Integrated and Separated production. In the integrated production scenarios, solar radiation pass through the tomato canopy before it reaches the algae PBR. For the current simulations, exponential functions were used to calculate the absorption of light by the crop for shortwave and longwave radiation (de Zwart, 1996). The light incident on the algae PBR is related to the LAI of the tomato crop. Although these exponential functions describe the light absorption by the crop, it was observed that they overestimate the light available for PBRs under the crop because obstacles such as gutter with substrate, tubes, etc. are neglected. Measurements of the light extinction in a full grown tomato crop with LAI of 3, carried out by Kempkes (personal communication), showed that about 5% of the radiation present above the crop reaches the greenhouse floor under the crop, and about 20% reaches the path between the crop. In the current model it was assumed that when only a gutter without a crop was present, 95% of the radiation inside the greenhouse would reach the PBR. Since better alternatives were lacking, based on these preliminaries, radiation reaching the PBR under the crop (I0 crop), as a function of the radiation inside the greenhouse above the crop (Iin) and the LAI, was approximated with a linear relationship. I0 crop ¼ ð0:30$LAI þ 0:95Þ$Iin
mmol m2 s1
(1)
A similar relation was derived for the radiation reaching the PBR in the path (I0 path): I0 path ¼ ð0:25$LAI þ 0:95Þ$Iin
mmol m2 s1
(2)
In the separated production scenarios, no crop was present above the PBR and it was assumed that 100% of the radiation entering the greenhouse reaches the PBR. During their modelling experiments, Dermoun et al. (1992) considered only very low biomass concentrations to prevent self-shading of the algae. For those conditions, calculation of algae biomass production can be based on the incident radiation level on the PBR and the transmission properties of the PBR construction only. In this study however, in order to consider the influence of the biomass concentration on the light absorption by the biomass, the averaged light intensity (Iav) in the PBR was calculated according to Quinn et al. (2011). This approach is based on the assumption that the algae are adapted to this averaged light intensity. Both the light absorption coefficient of the algae biomass (a) and the biomass concentration (Cb) influence the average light intensity according to Eq. (3): Iav ¼ I0 $swall
1 expða$Cb $dtube Þ a$Cb $dtube
mmol m2 s1
(3)
where I0 is the PAR incident on the PBR wall [mmol m2 s1], swall is the transmittance of the PBR wall equal to 0.85 [e], a is the light absorption coefficient of the biomass equal to 0.0752 [m2 g1], Cb is the biomass concentration [g m3] and dtube is the diameter of the PBR tube [m], which equal to light path.
2.3.2.2. Temperature. The temperature of the algae fluid in the PBR is one of the key factors strongly influencing the algae growth rate (Be; chet et al. 2010). Solar radiation has the greatest influence on the PBR temperature as compared to air
temperature. In integrated production, no direct radiation reaches the PBR and total amount of radiation is rather low. It was assumed that the temperature of the PBR always equals the temperature of the greenhouse air. In separated production, full solar radiation reaches the PBR. The PBR temperature was, therefore, separately modelled following the approach described by Be´chet, Shilton, Fringer, Munoz, and Guieysse (2010). Eq. (4) describes the simplified energy balance of the PBR. rCp V
dTPBR ¼ Qra;sol þ Qre;sol þ Qc dt
(4)
W
where Qra,sol is the solar radiation flux reaching the PBR directly [W], Qre,sol is the first order solar radiation reflected by the floor [W], Qc is the convective energy flux between PBR and air [W], TPBR is the PBR temperature [K], r is the density of the algae fluid [kg m3], Cp is the specific heat capacity of the algae fluid [J kg1 K1] and V is the volume of the PBR [m3]. The solar radiation flux reaching the PBR directly (Qra,sol) was calculated according to Eq (5) as a function of inside solar radiation (Iin) projected at the surface of the PBR, emissivity of the algae fluid (3 ) and transmittance of the PBR (swall). The projected surface was equal to the PBR tube diameter (dtube) times its length (L). Qra;sol ¼ 3 $swall $Iin $dtube $L
W
(5)
where 3 is the emissivity of the algae fluid [e] equal to 0.97 (Be; chet et al. 2010), Iin is the solar radiation entering the greenhouse [W m2] and L is the length of the PBR tube [m]. The distance between the PBR tubes was one third of the tube diameter, so a quarter of the inside solar radiation was considered to reach the floor. The reflectivity of the greenhouse floor rg was assumed to be 0.5. The bottom half of the circumference of the PBR received solar radiation reflected from the floor (Qre,sol), which is calculated by Eq. (6). 1 p Qre;sol ¼ 3 $swall $rg $ Iin $ dtube $L W 4 2
(6)
Convection takes place at the PBR wall. The driving force for convection is the temperature difference between greenhouse air (Tair) and PBR (TPBR). Eq. (7) displays the convective energy flux (Qc). Qc ¼ aðTair TPBR Þp$dtube $L
W
(7)
where a is the heat transfer coefficient of the tube’s wall equal to 10 [W m2 K1], (Bot, Sapounas, Norsker, & de Winter, 2009). In order to be able to find a value of the PBR temperature for every hour of the year for every tube diameter Eq. (4) was converted to Eq. (8) and solved iteratively. The temperature gradient dTPBR/dt was calculated by Eq. (9). 0 ¼ rCp V
dTPBR þ Qra;sol þ Qre;sol þ Qc dt
dTPBR TPBR ðtÞ TPBR ðt 1Þ ¼ 3600 dt
K s1
W
(8)
(9)
2.3.2.3. Algae production. According to Dermoun et al. (1992) Eq. (10) describes the maximum algae growth rate (gmax) at a given temperature in the PBR (TPBR); Eq. (11) describes the
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g
g
gmax ðTPBR Þ ¼ 2g 1 þ bT
Iopt ðTPBR Þ ¼ 2rI 1 þ bIT
xTg g x2Tg þ 2bT $xTg þ 1
xTI x2TI þ 2bIT þ 1
gðIav ; TPBR Þ ¼ 2gmax ð1 þ bI Þ
h
1
mmol m2 s1
xI x2I þ 2bI $xI þ 1
h
1
(10)
(11)
(12)
dCb ðtÞ ¼ gðIav ; TPBR Þ$Cb ðtÞ dt
where TPBR is the temperature of the algae [ C]; Iav is the average light intensity in the PBR; g is the maximum growth rate at optimal temperature equal to 0.0583 [h1]; rI is the maximum radiation flux value of Iopt value at the optimum g temperature, equal to 538 [mmol m2 s1]; and bT , bIT and bI are shape factors for the limitation of algae growth rate by temperature and the limitation by radiation, respectively. These shape factors are temperature dependent, but the model is not sensitive to them, so they were set to fixed values of respectively 0.02, 0.56 and 0.50 [e]. The coefficients xT g, xT I and xI are represented by Eq. (13), Eq. (14) and Eq. (15) respectively. TPBR q0 g g qopt q0
e
(13)
xTI ¼
TPBR qI0 qIopt qI0
e
(14)
xI ¼
Iav Iopt
e
1
½kg m3 h
Cb ðtÞ ¼ Cb ðt 1Þ$expðgðIav ; TPBR Þ$tÞ
(16)
½kg m3
(17) 3
For Cb(0) the initial biomass concentration of 1 [kg m ] was chosen. An upper and lower limit was set for the biomass concentration. When the upper limit (3 kg m3) was reached, biomass was harvested until the lower limit (1 kg m3) was reached. The sum of all biomass harvests is the total biomass yield calculated per year.
2.3.3.
Economic model
The economic sub-model calculates costs and returns of a combined tomato and algae production in a Dutch greenhouse. For greenhouse tomato production, fixed and variable costs and benefits were obtained from Vermeulen (2010), which contains up-to-date information on average production, costs and benefits for different crops produced in Dutch greenhouses. In the current study, calculations were based on the economics of a truss tomato production using a combined heat and power generation system (CHP), a combination
g
xTg ¼
g
where q0 andqopt represent the temperatures at which the algae growth rate is zero and maximum equal to 4.7 and 20.5 [ C] for Porphyridium cruentum, qI0 and qIopt represent the temperatures at which Iopt is zero and maximum equal to 4.7 and 12.3 [ C]. For every hour of the year, an hourly algae growth rate g(Iav,TPBR) was calculated based on the average light intensity (Iav) and PBR temperature (TPBR) at that hour (t). The variation of algae concentration in time is given by Eq. (16) and the instantaneous concentration (Cb) at given t was calculated according to Eq. (17).
optimal radiation flux (Iopt) at that temperature; Eq. (12) calculates the actual algae growth rate (g) at the given temperature and average light intensity (Iav) in the PBR.
(15)
Table 2 e Costs and returns related to the production of truss tomato in combination with a CHP in a Dutch greenhouse (Vermeulen, 2010). Costs
Value
Plant material tomato Crop substrate Gas usage and transport
3.00 0.80 19.22
V m2 year1 V m2 year1 V m2 year1
Unit
Electricity delivery to net Crop protection Crop nutrients Crop materials (wires, clips) Labour Labour by third party Packaging Auction Removal of crop Interest on capital Durable production resources including greenhouse construction, equipment and ground Other costs Total costs Returns
14.91 0.75 1.15 0.65 19.25 0.25 0.26 2.31 0.50 0.46 18.20
V V V V V V V V V V V
2.00 53.89 Value
V m2 year1 V m2 year1 Unit
Tomato yield Price tomato trusses Total returns Tomato profit
64 0.72 46.08 7.81
kg m2 year1 V kg1 V m2 year1 V m2 year1
m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1
Remark
Gas usage is 71.6 m3 m2 year1 including CHP and 39.8 m3 m2 year1 for tomato crop only Electricity production by CHP
Remark
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Table 3 e Fixed and variable costs related to algae production in horizontal tubular PBR. Values were taken from Norsker et al. (2011) unless indicated otherwise. Indicated is how costs were adjusted to fit the system modelled in the current study. Fixed costs
Unit Costs
Units
Adjusted according to
Remark
Circulation pump Centrifuge Centrifuge feed pump Medium filter pump Medium feed pump Medium preparation tank Harvest fluid storage tank Seawater pump station Weighing station Air blower Installation costs Instrumentation and control Piping Variable costs
26,100 133,000 4800 13,500 4800 20,000 20,000 15,000 40,000 22,000 30 30 30 Unit costs
V V V V V V V V V V % % % Units
Model result Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor
Adjusted according to
Remark
Labour Maintenance CO2 Culture medium premix Medium filters Tubing Electricity price Power for algae harvest Power for pumping
62,653 4 0.33 18,040 10,355 0.03 0.09 1
V ha1 year1 % V kg DM algae V ha1 year1 V ha1 year1 V m1 year1 V kWh1 kWh m3 kWh
Area ratio
Two people ha1 Vermeulen (2010) Percentage of fixed costs after adjustment
Percentage of fixed costs after adjustment
Volume ratio Volume ratio Tube wall length
Model result
commonly used in the Netherlands. In Table 2, costs and benefits are given for a standard greenhouse tomato crop at an average price of V0.72 per kg fresh tomato. Norsker et al. (2011) analysed the costs of algae production systems, among others horizontal tubular PBR covering an area of 1 ha. Data from their analysis was used and adapted for our study. Fixed costs of the equipment were corrected by using a volume ratio, which expresses the volume of the systems in our study in relation to the volume of the systems analysed by Norsker et al. (2011). Fixed and variable costs are given in Table 3. Variable costs included labour, maintenance, CO2 supply, premix of algae medium and mix of nutrients, filtering and electricity for pumping and harvesting (Table 3). Labour costs were based on Vermeulen (2010) assuming that labour exchange between tomato and algae production can take place and that two persons are required per ha production. Pumping costs are a large proportion of the costs of algae production. The number of pumps and total pump capacity needed was therefore calculated in more detail. The pump capacity is dependent on the volume of the PBR system, the diameter and hydraulic properties of the PBR tubes and appendices, and the required liquid velocity. The operational characteristics of a commercial pump were considered. The total electrical pump power (Wp) was calculated according to Eq. (18). Wp ¼ DPtotal
fv 1 1 ½kW $ $ 3600 hp hm 1000
(18)
where DPtotal is the sum of the pressure difference resulting from losses in the PBR tubes with a given length, diameter, density and velocity of the algae fluid and friction coefficient, the pressure difference in the appendages and the pressure difference in the main distributions tubes [Pa]; 4v is the
volume flux through the PBR tubes [m3 h1]; hp is the pump efficiency equal to 0.8 [e] and hm is the efficiency of the electric engine driving the pump equal to 0.9 [e]. For calculation of the costs of the separated production scenario, two modifications were needed. Firstly, the minimum liquid velocity was doubled from 0.2 to 0.4 m s1, to prevent oxygen inhibition of the algae, resulting in increased fixed and variable pumping costs. Secondly, fixed costs of the greenhouse construction, floor and greenhouse equipment were added to algae production for every m2 of greenhouse occupied. In integrated production, all fixed costs were covered by the tomato production thus yielding an advantage in efficiency of resource use compared to separated production. The price for the algae produced is strongly dependent on the market. In the current study, a price of V50 kg1 DM was chosen which was considered to be representative for high quality algae produced in closed PBRs.
3.
Results
3.1.
Algae productivity
Table 4 shows the results of the integrated production and separated production scenarios for three different tube diameters. Essentially, two figures are of interest, volumetric productivity and areal productivity. Volumetric algae productivity in kg DM m3 year1 is a measure for the light use efficiency of the PBR. Areal productivity in kg DM m2 year1 indicates how effectively the greenhouse floor area is used for algae production and is a combination of volumetric productivity and the PBR volume per greenhouse floor area.
11 24 25 4 12 13 40 60 90 40 60 90 0.15 0.19 0.15 0.15 0.29 0.20 5.2 6.2 6.5 5.2 6.2 6.5 14.0 8.0 6.0 42.2 24.1 16.0 146.7 95.1 68.5 146.7 95.1 68.5 361
361
82.4
3.2 1.8 1.2 8.7 4.7 3.3 39.2 21.0 14.3 39.2 21.0 14.3 30.6 361 527
Large scale
Separated Small scale production
On path
6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm Integrated Under crop production
Year round Areal algae PBR volume Year round average Volumetric Year round average Year round average production per greenhouse algae production PAR radiation inside PAR radiation inside average PAR PAR radiation greenhouse above crop greenhouse radiation inside [kg DM m3 year1] [kg DM m2 year1] floor area [l m2] 2 1 outside incident on PBR [mmol m s ] PBR [mmol m2 s1] [mmol m2 s1] [mmol m2 s1] PBR diamter PBR location
Table 4 e Effect of PBR location and dimension on light conditions and algae areal and volumetric productivity at standard tomato LAI and standard algae biomass concentration.
b i o s y s t e m s e n g i n e e r i n g 1 2 2 ( 2 0 1 4 ) 1 4 9 e1 6 2
157
The volumetric productivity of algae in a PBR under a tomato crop in a Dutch greenhouse was 14.0 kg algae DM m3 year1 in a 6 cm PBR, 8.0 kg algae DM m3 year1 in a 11 cm PBR and 6.0 kg algae DM m3 year1 in a 16 cm PBR. The volumetric productivity was decreasing with increasing PBR diameter due to an associated increase of the light path and, consequently, a decrease of the light intensity inside the PBR. The average light intensity in the PBR was calculated to be 3.2 mmol m2 s1 in the 6 cm PBR, 1.8 mmol m2 s1 in the 11 cm PBR and 1.2 mmol m2 s1 in the 16 cm PBR. The volumetric productivity of the PBR mounted on the path between the tomato crop was higher than the productivity of the PBR under the crop and amounted to 42.2 kg algae DM m3 year1 in a 6 cm PBR, 24.1 kg algae DM m3 year1 in a 11 cm PBR and 16.0 kg algae DM m3 year1 in a 16 cm PBR. This higher production can be explained by the higher light intensities on the path. Light intensities on the path were 2.5 times higher than under the crop. In the separated production scenario even higher productivities were obtained. In that case volumetric algae production was 146.7 kg algae DM m3 year1 in a 6 cm PBR, 95.1 kg algae DM m3 year1 in a 11 cm PBR and 68.5 kg algae DM m3 year1 in a 16 cm PBR. This production is twelve times higher than the volumetric production obtained in integrated production under a tomato crop. This difference can be fully explained by the 12 times higher light intensities above the tube and the 12 times higher average light intensities in the tube in the separated production scenario. The specific volumetric productivity calculated was 0.40 g ll d1, 0.26 g ll d1 and 0.19 g ll d1, for PBRs with tube diameter 6 cm, 11 cm and 16 cm respectively. These values are of the same order of magnitude as that measured by other researchers using Porphyridium cruentum, although they cannot be compared directly because of different cultivation conditions. In particular, Dermoun et al. (1992) measured 0.50 g ll d1 for light intensity 350 mmol m2 s1, Muller-Feuga, Le Guedes, Herve, and Durand (1998) measured 0.58 0.12 g ll d1, Rebolloso Fuentes et al. (1999) measured 1.76 g ll d1 under outdoor conditions in Spain, You, Chen, and Wang (2006) measured 0.43 g ll d1 in a PBR continuously illuminated using light intensities 13.5e67.5 mmol m2 s1, and Oh et al. (2009) measured 0.042 g ll h1 in a PBR illuminated using light intensities 10.0e25.0 mmol m2 s1 and light:dark cycle of 18 h:6 h. The areal productivity of algae in a PBR under a tomato crop in a Dutch greenhouse was found to be 0.15 kg algae DM m2 year1 in a 6 cm PBR, 0.19 kg algae DM m2 year1 in a 11 cm PBR and 0.15 kg algae DM m2 year1 in a 16 cm PBR. The areal productivity of algae in a PBR mounted on the path was only little higher with 0.15 kg algae DM m2 year1 in a 6 cm PBR, 0.29 kg algae DM m2 year1 in a 11 cm PBR and 0.20 kg algae DM m2 year1 in a 16 cm PBR. The areal productivity of algae in the PBR mounted in the separated production scenario was much higher and amounted to 5.18 kg algae DM m2 year1 in a 6 cm PBR, 6.16 kg algae DM m2 year1 in a 11 cm PBR and 6.46 kg algae DM m2 year1 in a 16 cm PBR. Algae production is greater in separated production than under a tomato crop due to higher light availability and more tubes installed per floor area. While volumetric algae
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production increased with decreasing PBR tube diameter, areal algae production was greater in 11 cm PBR compared to 6 cm and 16 cm PBR. This optimum occurs for the following reasons: the light availability increases with decreasing PBR diameter; the amount of hours with too low or too high temperatures decreases with increasing PBR diameter; the installed PBR volume per greenhouse floor area increases with PBR diameter. The result is that a PBR diameter of 11 cm seems to have the optimal combination of volumetric productivity and installed volume per area. Decreasing the LAI of the tomato crop through extra leaf picking positively affected algae productivity in integrated production as shown in Fig. 4. Effects were most distinct for the PBR mounted under the crop. When the LAI was decreased by 5%, the volumetric algae productivity increased by 52% and when LAI was decreased by 10%, the volumetric algae productivity increased by 110%. For the PBR mounted on the path in an integrated production system, the increase was less pronounced and amounted to 12% and 26%, respectively. An increasing algae biomass concentration in the PBR has a negative influence on the growth rate because it reduces the average light intensity in the PBR. At the same time, however, a higher biomass concentration has a positive influence on the volumetric productivity at equal growth rate as can be seen in Eq. (17). In the integrated production scenario with the PBR mounted under the crop, the maximum volumetric algae productivity was reached at a biomass concentration of 0.5 kg m3. With the PBR mounted on the path it was reached at 1.0 kg m3. In separated production, maximum volumetric productivity is reached at a biomass of as high as 7 kg m3 or even higher.
3.2.
Cost price of algae production
In integrated production, the profit on the algae production part of the system was negative. At an assumed algae price of 50 V kg1 algae DM, as shown in Table 5, the profit from PBR placed under the tomato crop was V3.00 m2 year1 for a 6 cm PBR, V7.72 m2 year1 for a 11 cm PBR and
Fig. 4 e Effect of different tomato LAI and different PBR locations on the volumetric algae productivity in the 6 cm PBR at standard biomass concentration.
V10.38 m2 year1 for a 16 cm. For the same PBR diameters, the profit from PBR placed on the path was V2.76 m2 year1, V4.51 m2 year1 and V0.05 m2 year1 respectively. Since following Vermeulen (2010) the profit of an average tomato production was also negative, the total profit of integrated production of algae and tomato was negative. Increasing PBR tube diameter decreased profit mainly due to the increased volume and consequently the higher pumping costs on one hand, and due to the lower average light intensity in the PBR and associated lower productivity on the other hand. Cost price of algae produced per m2 is given by dividing the areal costs (V m2 year1, Table 5) by areal production (kg DM m2 year1, Table 4). When the PBRs are placed under the tomato crop, the cost price in the 6 cm PBR was V70 kg1 algae DM, in the 11 cm PBR was V91 kg1 algae DM and in the 16 cm PBR was V123 kg1 algae DM. When the PBRs are placed on the path, the cost price in the 6 cm PBR was V31 kg1 algae DM, in the 11 cm PBR was V34 kg1 algae DM and in the 16 cm PBR was V51 kg1 algae DM. Figure 5 shows the effect of varying the price of kg DM algae production on the total profit of algae and tomato in integrated production depending on the LAI of the tomato. Cost price of algae decreased when tomato LAI decreased, as the higher radiation incident on PBR results to higher productivity. Profit in separated production was related to the scale of the system (Table 5). The large scale variant resulted in larger profits per m2 greenhouse area than the small scale variant. The 11 cm PBR system had higher profits than 6 cm and 16 cm PBR systems. At an assumed algae price of V50 kg1 DM, the profit for a 11 cm PBR was V156 m2 for a small scale system and V231 m2 for a large scale system. For a small scale system, the cost price of algae produced in the 6 cm PBR was V23 kg1 algae DM, in the 11 cm PBR was V25 kg1 algae DM and in the 16 cm PBR was V30 kg1 algae DM. For a large scale system the cost price in the 6 cm PBR was V11 kg1 algae DM, in the 11 cm PBR was V12 kg1 algae DM and in the 16 cm PBR was V15 kg1 algae DM. Figure 6 shows the effect of varying the price of kg DM algae production on the total profit of algae and tomato in Separated production depending on the scale of the algae system. Systems smaller than 1000 m2 greenhouse floor area are only profitable if the price is higher than V40 kg1 DM algae. In integrated production, fixed costs comprised a share of 66% of the total cost of algae DM. Within the fixed costs, the pumps take a great share (21%). Within the variable costs, labour (13%) and maintenance costs (9%) take the greatest share (Fig. 7). In separated production, fixed costs comprise an even greater share of total costs in comparison with integrated production (76%). This is mainly due to costs for the greenhouse building which are accounted to the costs for algae production. Figure 7 is representative for other tube diameters (data not shown).
4.
Discussion
4.1.
Desk-study
This assessment exists as a desk-study only. Results in the study here are in line with literature data. It is very important
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Table 5 e Cost, returns and profit of an algae production system for different PBR locations and diameters and total profit for integrated and separated tomato and algae production, algae price of V50 kgL1 DM assumed. PBR location Integrated production
Under crop
On path
Separated production
Small scale
Large scale
PBR Costs algae Returns algae Profit algae [V m2 year1] Total profit tomato and algae 2 1 diameter [V m year ] [V m2 year1] [V m2 year1] 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm
10.44 17.23 18.38 4.69 9.78 10.13 118.00 152.00 198.00 59.00 77.00 97.00
3.00 7.72 10.38 2.76 4.51 0.05 141.00 156.00 125.00 200.00 231.00 226.00
7.44 9.51 7.55 7.45 14.29 10.08 259.00 308.00 323.00 259.00 308.00 323.00
10.81 15.53 18.64 5.05 3.30 7.86 3.65 2.60 4.76 54.58 79.66 54.61
to evaluate the model and its results with measurements in greenhouses. Experiments are planned to be carried out in the future.
requires as much light as possible. Studying the combination of algae production with crops requiring less light could be interesting.
4.2.
4.3.
System lay-out
Closed systems for algae production are of many types and layouts, and the best design and layout is still debated (e.g. Bitog et al. 2011). Systems design for integrated production of algae and tomato in greenhouses has not been carried out before. A stateeof-the-art tomato production system under Dutch conditions was used as reference for modelling tomato production and implementation of an algae production system. The layout of the algae production system and calculated scenarios were based on a system implemented by a Dutch tomato producer. This resulted in a limited number of scenarios analysed in integrated and separated production. With respect to the location of the PBR in the greenhouse for example, a vertical PBR placed along the greenhouse walls might be cost and space effective and worthy of study in the future. Especially for separated production, different system layouts can be thought of which make better use of the available space than the currently studied horizontal PBRs. One may think of vertically stacked horizontal PBRs. Finally, combination of algae production with tomato production could be seen as a worst case scenario, because a tomato crop
In the current study, light intensity in the PBR was calculated with the average light intensity method often used in literature (e.g. Quinn et al. 2011). This resulted in equal light intensity for the algae, rather than differentiating growth rate depending on the algae position in the light path in the PBR. This method is based on the assumption that the algae are adapted to the average light intensity and are perfectly mixed. In a real situation, light intensity is dependent on the position of the PBR: the light intensity decreases with the length of the light path, which may result in both light limited and light inhibited states of algae in one PBR. Especially for larger tube diameters, and under low or high light conditions, an overestimation of productivity is to be expected when the average light method is used. More accurate light models could be implemented in our study in the future (e.g. Slegers et al. 2013). New models based on ray-tracing should be developed. In integrated production, PBRs are placed under the crop rows or between them in the path. In these places, the light available for PBRs, cannot be calculated by using exponential functions, which describe light interception by the crop, since obstacles like crop gutter are neglected, and in the path the light available is about 4 times more than the light under the crop. The use of linear relations, which have been derived by preliminary experimental study, was a simplification to overcome the lack of knowledge regarding the light available at these places. More experimental research is needed, to accurately determine the light available for PBRs when these are placed under the crop rows or/and in the path between the crop rows.
4.4. Fig. 5 e Effect of varying the price per kg DM algae production on the total profit of algae and tomato in integrated production of algae in a 11 cm PBR under the tomato crop at different LAI of tomato.
Light modelling
Growth rate modelling
Tittel, Bissinger, Gaedke, and Kamjunke (2005) indicate that it is typical for phototrophically-grown algae that they exhibit negative growth rates due to maintenance respiration, when light intensities are below the compensation point. In the
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Fig. 6 e Effect of varying the price of algae (V kgL1 DM) on the total profit of algae and tomato in separated production depending on the greenhouse area occupied by the algae system (scale), algae production in a 11 cm PBR.
algae growth rate model of Dermoun et al. (1992) that we used, losses by respiration and negative growth are not included. Especially under low-light conditions in integrated production, productivity of the PBR will thus be overestimated by use of this model. The model of Dermoun et al. (1992) was specifically developed for the algae species Porphyridium Cruentum. It is not representative for other algae species with different optimal temperature, optimal light and maximum growth rate. In this study, algae production was modelled dependent on temperature and radiation only, assuming that nutrient, CO2 and O2 concentrations and pH were optimal or nonlimiting. In practice this will not be the case and therefore productivity is probably overestimated in this study. To improve modelling of combined production, a more complete growth rate model could be implemented and validated in the future (e.g. Geider, MacIntyre, & Kana, 1996; Quinn et al. 2011).
The modelling of the cost price of the algae production system in this study is mainly based on the work of Norsker et al. (2011). No economic data is available for the integrated production of algae and tomato in greenhouses. Often high market prices are mentioned for algae dry matter. Wijffels et al. (2010) for example mention an average value of 250 V kg1 DM. But high prices are mostly related to small markets and increasing interest in algae production will reduce the market value. However, we can conclude that the calculated cost price for algae production in greenhouses of V11 DM algae in a 6 cm PBR in separated production gives a reasonable perspective. This value is equal to yearly fixed and variable costs of about V60 m2 for the algae system only.
4.5.
The objective was to determine the algae productivity in tubular photobioreactors and the economic feasibility of combined production of tomato and algae in Dutch greenhouses. To this end, a Matlab-based model was developed and
Cost price of combined algae and tomato production
Little information on the economics of large-scale closed algae production systems is available in literature or from practice.
5.
Conclusion
Fig. 7 e Distribution of fixed and variable costs for algae production in a 11 cm PBR in integrated production of algae under the tomato crop and in a large scale system in separated production in different greenhouse compartments.
b i o s y s t e m s e n g i n e e r i n g 1 2 2 ( 2 0 1 4 ) 1 4 9 e1 6 2
a range of scenarios were analysed to identify the best location and size of a tubular PBR in a combined tomato and algae production system. With today’s technological advances and given assumptions, the combined production of algae and tomato in a Dutch greenhouse is economically feasible, when the PBRs (of 6 cm) are placed in a separated greenhouse compartment next to tomato. In this case the minimum cost price of algae was V11 kg1 algae DM. Algae production in PBRs (of 6 cm) in integrated production is not economically feasible since the V70 kg1 production costs are higher than the assumed algae price of 50 V kg1. Algae productivity was found to be too low under a tomato crop due to limiting light conditions. This novel model approach and the scenario results provide a better understanding of the potential productivity and related costs and returns of algae production and give insight into the feasibility of algae and tomato production in Dutch greenhouses.
Acknowledgements This study was supported by the Dutch Ministry of Economic Affairs, Agriculture and Innovation and by the Dutch Productboard of Horticulture. We would also like to thank the participating growers.
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Available online at www.sciencedirect.com
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Research Paper
Modelling and evaluation of productivity and economic feasibility of a combined production of tomato and algae in Dutch greenhouses Bart Slager a,b, Athanasios A. Sapounas a, Eldert J. van Henten a,b,*, Silke Hemming a a
Wageningen University and Research Centre, Greenhouse Horticulture, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands b Wageningen University and Research Centre, Farm Technology Group, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
article info
Combination of production of algae and tomato increases efficient use of available re-
Article history:
sources of greenhouse enterprises, such as controlled environment, water and nutrients,
Received 2 July 2013
carbon dioxide, greenhouse space and infrastructure and knowledge. No information is
Received in revised form
available, however, about the potential productivity and related costs of a combined to-
26 November 2013
mato and algae production in Dutch greenhouses. The objective was to determine the algae
Accepted 6 April 2014
productivity in tubular photobioreactors (PBRs) and the economic feasibility of combined
Published online
production of tomato and algae in Dutch greenhouses. A model was developed to predict greenhouse climate from outside climate, to predict tomato and algae biomass production
Keywords:
and to analyse scenarios of different locations and dimensions of tubular PBR in the
Photobioreactor (PBR)
greenhouse with regard to algae productivity and cost price of algae production. The re-
Light
sults show that algal productivity is low if PBRs are installed under a tomato crop due to
Temperature
limited light levels. Areal algal productivity was calculated to be 5e6.5 kg DM m2 if PBRs
Economic analysis
are installed in a separate greenhouse compartment next to tomato. In this case the minimum cost prices of algae production was calculated to be V11 kg1 DM algae, which give perspectives for the future. The proposed model is important because it gives insight into the feasibility of algae and tomato production in Dutch greenhouses. This novel model approach and the scenario results provide better knowledge about the potential productivity and related costs and returns of algae production in greenhouses. ª 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
1.
Introduction
The quest for non-fossil based chemicals and fuels has strongly renewed research interest in algae during the last two
decades (Luque, 2010; Norsker, Barbosa, Vermue¨, & Wijffels, 2011). Algae are a potential resource for food, feed, pharmaceutics, cosmetics, pigments, chemicals, fuel, bio-fertilisers and they can be used for waste water treatment (Becker, 1994; Barbosa, 2003). Between 8000 and 10,000 tons of
* Corresponding author. Wageningen University and Research Centre, Greenhouse Horticulture, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands. E-mail addresses: [email protected], [email protected] (E.J. van Henten). http://dx.doi.org/10.1016/j.biosystemseng.2014.04.008 1537-5110/ª 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
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Nomenclature
a
English symbols Concentration of algae biomass in PBR kg m3 Cb Cp Specific heat capacity of the algae fluid J kg1 DM Algae dry matter production m2 m2 dt Integration time step 1 s Diameter of the PBR tube m dtube Maximum algae growth rate at temperature T h1 gmax L Length of the PBR tube m LAI Leaf area index of tomato crop m2 m2 h Heat transfer coefficient 10 W m2 K1 Iav Average intensity of PAR inside the PBR mmol m2 s1 Iin Intensity of total solar radiation inside the greenhouse above Tomato crop W m2 I0 Intensity of PAR incident on PBR mmol m2 s1 Iopt Optimum radiation received by the algae at temperature T h1 Qra,sol Radiation flux reaching the PBR directly mmol m2 s1 Qre,sol Radiation flux reaching the PBR after reflection from the Greenhouse floor mmol m2 s1 Qc Convective energy exchange between PBR and greenhouse air W Reflexivity of the greenhouse floor surface 0.5 [e] rg T Temperature K or C t Time 1 h V Volume of the PBR system m3 Wp Electrical pump power kW
bI g bT bIT g DPtotal 3
hp hm g
q0 g
qopt qI0 qIopt r rI swall 4v
Light absorption coefficient of the algae biomass 0.0752 m2 g1 Shape factor for limitation by radiation 0.50 [e] Shape factor for limitation of algae growth rate by temperature 0.02 [e] Shape factor for limitation by Iopt0.56 [e] Maximum growth rate at optimal temperature 0.0583 h1 Total pressure differences in the PBR system Pa Emissivity of algae liquid 0.97 [e] Efficiency of pump 0.80 [e] Efficiency of electric engine driving the pump 0.90 [e] Temperature at which algae growth rate is zero 4.7 C Temperature at which algae growth rate is maximum 20.5 C Temperature at which Iopt is zero 4.7 C Temperature at which Iopt is maximum 12.3 C Density of the algae fluid kg m3 Maximum radiation flux value at the optimum temperature 538 mmol m2 s1 Transmittance of the polyethylene PBR wall 0.85 [e] Volume flux through PBR tubes m3 h1
Subscripts PBR Related to Air Related to Crop Related to Path Related to
the photobioreactor the greenhouse air PBR under crop PBR on path
Greek symbols
microalgae biomass are produced annually, having a market value of approximately $3000e4000 million (Tredici, Biondi, Ponis, Rodolfi, & Zittelli, 2009). The Dutch horticultural sector has shown interest in the production of algae. Pressure on economic margins and drive for innovation have triggered the interest of Dutch growers to exploit their resources and capital in a more effective way. The resources needed for production of vegetable crops and algae are quite comparable. Both need light and a properly controlled carbon dioxide concentration (CO2), nutrient concentrations and temperature for optimal production. Also similarities exist when it comes to required infrastructure, management and knowledge. Essentially, with all technology present and the knowledge and expertise of growers on resource management and optimised biomass production (Dieleman & Hemming, 2011), Dutch greenhouses should be able to facilitate both tomato and algae production effectively. The proposed combined cultivation fits in a wider range of recent developments, in which combinations of different agricultural activities have been studied or attempted. The combination of tomato and fish production, for example, was found to have distinct mutual advantages (Graber & Junge, 2009; Nichols & Savidov, 2012; Rakocy, 2012; Vergote & Vermeulen, 2012).
Currently, several Dutch growers combine the production of tomato with algae in small scale experiments on a very intuitive basis. A more systematic study of integrated production of vegetable crops and algae in Dutch greenhouses is still lacking and quite a range of questions are still unanswered. For instance, Wijffels, Barbosa, and Eppink (2010) estimated that 40e80 t algae dry matter could be produced in closed photobioreactors (PBRs) outdoors, but potential productivity in a greenhouse is yet unknown. The design of a tubular PBR has been studied by several authors (Acie´n Ferna´ndez, Garcı´a Camacho, Sa´nchez Pe´rez, Ferna´ndez Sevilla, & Molina Grima, 1997, 1998; Bosma, Van Zessen, Reith, Tramper, & Wijffels, 2007; Molina, Ferna´ndez, Acie´n, & Chisti, 2001; Slegers, van Beveren, Wijffels, Van Straten, & Van Boxtel, 2013), but no design has been studied for greenhouse conditions. The best location of an algae production system in relation to a tomato production system, the suitable dimensions of PBRs and influence of system scale are still unknown. Integration of the production of vegetable crops and algae does not only increase efficient utilisation of resources, but might also increase competition for resources, especially light. In view of light availability, the dimension as well as the location of algae PBRs in a combined production system has to
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Fig. 1 e Venlo type greenhouse with tomato crop (a) and tubular algae PBRs under the crop. PBR tube diameter 16 cm (b), 11 cm (c) and 6 cm (d).
be identified. Last but not least, together with productivity and consequently economic return, investment and running costs influence the PBR design. The first economic data for different PBR systems were collected by Norsker et al. (2011), but economic data of commercial PBRs in greenhouses are largely unknown yet. Moreover, no study has been carried out on the potential productivity and related costs and returns of an integrated production of crop and algae in greenhouses. The objective of this research was to determine the algae productivity in a tubular PBR as well as the economic feasibility of a combined production of tomato and algae in Dutch greenhouses. Similar to the work of Vanthoor et al. (2012), for this purpose a model was developed to predict greenhouse climate for tomato and algae production from outside climate, to predict tomato and algae biomass production and to analyse scenarios of different places and dimensions of tubular PBR in the greenhouse with regard to algae productivity and cost price of algae production. Different design configurations were studied and scenario analyses were performed.
2.
Materials and methods
2.1. System description of combined production of tomato and algae in a greenhouse In this desk study a typical Dutch Venlo-type greenhouse was considered with a total area of 1.04 ha. The greenhouse dimensions were 100 m length, 104 m width (13 sections of 8 m, each of them containing 5 crop rows), 4 m length of main path,
5 m gutter height and 22 roof angle. A crop row consisted of the gutter with tomato crop having a width of 1 m and a path for logistics and labour of 0.6 m. The crop gutters were mounted 0.80 m above the floor, leaving a space underneath in which an algae PBR might be located. A standard Dutch tomato crop was considered, with a production cycle running from December 15th of the year to November 15th the next year. The layout of algae PBRs was based on an existing algae production system implemented in a Dutch greenhouse, Fig. 1. With respect to the location of the algae PBR, in this study two distinctly different designs were considered. Firstly, integrated production was considered. Figure 2 displays this system graphically, with a continuous flow algae PBR integrated with the tomato crop in the same greenhouse compartment. The tubes of the PBR were aligned with the crop gutters and had the same length as the gutters (96 m). In this system layout, three cases were analysed (Table 1). The PBR tubes were placed on the floor under the tomato crop, or on the floor in the path between the tomato crop rows, or both underneath the crop and in the path. Since a dense algae biomass will result in self-shading, the diameter of the tubes was expected to affect the overall performance of the PBR. Both the diameter and number of tubes were varied between scenarios. This resulted in a PBR consisting of six, four or two tubes, with tube diameters of 6 cm, 11 cm and 16 cm respectively. For each scenario the tube diameter was kept constant. It was expected that the tomato crop would cause considerable shading of the PBR. Since the leaf area index (LAI) determines the interception of light by the crop, additional scenarios were analysed in which the LAI of the tomato was reduced by 5% or 10%.
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Fig. 2 e Schematic cross section of greenhouse with integrated production of a tomato crop and algae PBR under the crop and on the path between the crop (a) and with separated production of a tomato crop and algae (b).
Secondly, separated production was considered. In this case the continuous flow algae PBR was located in a separate compartment next to the compartment in which tomatoes were grown (Fig. 2). To allow a fair comparison with integrated production in relation to the dimensioning of the system, two different separate production scenarios were studied. In the first one, hereafter referred to as the small scale system, the algae compartment was given such a size that the productivity was equal to integrated production. This was done by calculating the algae dry matter yield for one tube in the separated compartment, and based on that result the amount of tubes needed to reach the same yield of certain integrated production system was calculated. In the second scenario, hereafter referred to as large scale system, the number of PBR tubes in the separated production was equal to the number of PBR tubes installed in integrated production, and thus installation and running costs of both systems were comparable. In both scenarios, the PBR tubes were mounted horizontally on the floor parallel to the gutters in the tomato compartment. Tube diameters were assumed to be 6 cm, 11 cm or 16 cm. The distance between the PBR tubes was taken equal to one third of the tube diameter. The floor surface was considered to exhibit diffuse reflection, reflecting direct and diffuse radiation homogeneously in
every direction. The reflectivity of the floor surface was defined as the ratio of the reflected flux to the incoming flux. In tomato production systems, in practice a white plastic film is used to cover the floor, which has a reflexivity of about 0.9. In the current study the reflectivity was set to 0.5, to account for dirt and dust and for possibly uneven reflection due to the spacing of the tubes.
2.2. Model of combined production of tomato and algae in a greenhouse A Matlab-based model was developed to determine productivity and economic feasibility of the combined production of tomato and algae in a Dutch greenhouse for different scenarios with respect to location and dimension of the PBR, as outlined in the previous section. The model consists of four sub-models: a greenhouse climate model, a tomato production model, an algae production model and an economic model (Fig. 3).
2.3.
Greenhouse climate model
For this sub-model, the existing and validated greenhouse simulation model KASPRO was used (Hemming, Sapounas, de
Table 1 e PBR dimensions in integrated and separated production systems. Integrated production system
Under crop 6 cm
Number of tubes Number of tubes per crop row Tube length [m] PBR volume [m3] PBR volume per area [m3 m2] Separated production system Number of tubes Tube length [m] PBR volume [m3] PBR volume per area [m3 m2] Area of separated compartment [m2]
On path
11 cm
16 cm
6 cm
11 cm
16 cm
195 130 6 4 2 96 2 96 106 237 0.0106 0.0237 Small scale system 6 cm 11 cm
65 2 2 96 251 0.0251
65 1 96 125 0.0125
16 cm
130 130 2 2 96 96 35 119 0.0035 0.0119 Large scale system 6 cm 11 cm
37 96 10 0.04 250
11 96 21 0.09 233
520 96 141 0.04 3525
195 96 376 0.09 4178
22 96 20 0.06 333
390 96 356 0.06 5933
16 cm
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Fig. 3 e Schematic data flow chart of the model built to evaluate productivity and economics of combined production of tomatoes and algae in a Dutch greenhouse.
Zwart, Ruijs, & Maaswinkel, 2010; Luo et al., 2005; de Zwart, 1996). KASPRO is a dynamic simulation model which simulates a full-scale virtual greenhouse based on the greenhouse construction elements, ventilation openings, greenhouse equipment, covering materials and their properties (transmission, reflection, and emission), set-points for inside climate and the outside climate of a given location. Yearround hourly data are used as input and the differential equations are solved with an integration time step of 1 s. An important feature of the KASPRO simulation model is that the modelled greenhouse climate is controlled by a replica of commercially-used climate controllers. Besides physics of the climate including control, it also contains models of dry matter production of various crops. The climate in a greenhouse is mainly dependent on the outdoor climate. As input data for KASPRO, hourly climate data of the so-called SEL-year were used (outdoor temperature, humidity, wind speed and direction, direct and diffuse solar radiation and sky temperature). The SEL-year contains the weather data of an ‘averaged’ year, using the methodology described by Breuer and van de Braak (1989). It is compiled of hourly data of the most representative seasonal weather conditions of the years 2000e2009, as measured by the Dutch meteorological institute KNMI (Swinkels, 2009). In the case of integrated production of tomatoes and algae, the energy balance of the PBR system was influenced by the conditions in the greenhouse, but it was assumed that the PBR was not influencing the greenhouse climate, which was controlled using set points 15 C for heating system and 20 C for ventilation (no cooling system was considered). For separated production it was assumed that the climate in the compartment with tomato was completely isolated from the climate in the compartment with algae. The climate in the compartment with the PBR was also simulated with KASPRO, yet without a crop, by setting the leaf area index of the crop (LAI) equal to zero. The absence of a crop allowed different
climate control set points, which in this case were set to 12 C for heating system and 18 C for ventilation (no cooling system was considered).
2.3.1.
Tomato production model
The tomato production sub-model is an integral part of the KASPRO model of de Zwart (1996) and predicts dry matter production of a tomato crop. The photosynthesis rate is calculated based on the solar radiation level in the greenhouse, temperature, CO2 concentration and the water vapour deficit of the greenhouse air. The interception of radiation by the crop was based on Goudriaan (1988). Canopy transpiration was based on Stanghellini (1987).
2.3.2.
Algae production model
This sub-model predicts dry matter production of algae in a tubular photobioreactor. A number of algae growth models have been described (e.g. Dermoun, Chaumont, Thebault, & Dauta, 1992; Quinn, de Winter, & Bradley, 2011; Zonneveld, 1998). Temperature and radiation are considered to be the two most important factors influencing algae growth (Carvalho, Monteiro, & Malcata, 2009). In the current study an empirical model, which describes the growth of the red alga Porphyridium cruentum influenced by temperature and radiation, was chosen (Dermoun et al. 1992). It was assumed that nutrient availability and carbon dioxide were non-limiting, the oxygen was easily removed, the pH was ideal/optimal and the algae suspension in the PBR was perfectly mixed. Data from the KASPRO model, such as inside solar radiation above the tomato crop (Iin), the leaf area index of the tomato crop (LAI) and the air temperature inside the greenhouse (Ti) were used as input for the algae production model.
2.3.2.1. Light. The solar radiation above the algae PBR is depending on LAI and light absorption by the tomato crop in case of Integrated production. The average solar radiation in
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the algae PBR is depending on PBR transmission, PBR dimensions and density and absorption of algae both in Integrated and Separated production. In the integrated production scenarios, solar radiation pass through the tomato canopy before it reaches the algae PBR. For the current simulations, exponential functions were used to calculate the absorption of light by the crop for shortwave and longwave radiation (de Zwart, 1996). The light incident on the algae PBR is related to the LAI of the tomato crop. Although these exponential functions describe the light absorption by the crop, it was observed that they overestimate the light available for PBRs under the crop because obstacles such as gutter with substrate, tubes, etc. are neglected. Measurements of the light extinction in a full grown tomato crop with LAI of 3, carried out by Kempkes (personal communication), showed that about 5% of the radiation present above the crop reaches the greenhouse floor under the crop, and about 20% reaches the path between the crop. In the current model it was assumed that when only a gutter without a crop was present, 95% of the radiation inside the greenhouse would reach the PBR. Since better alternatives were lacking, based on these preliminaries, radiation reaching the PBR under the crop (I0 crop), as a function of the radiation inside the greenhouse above the crop (Iin) and the LAI, was approximated with a linear relationship. I0 crop ¼ ð0:30$LAI þ 0:95Þ$Iin
mmol m2 s1
(1)
A similar relation was derived for the radiation reaching the PBR in the path (I0 path): I0 path ¼ ð0:25$LAI þ 0:95Þ$Iin
mmol m2 s1
(2)
In the separated production scenarios, no crop was present above the PBR and it was assumed that 100% of the radiation entering the greenhouse reaches the PBR. During their modelling experiments, Dermoun et al. (1992) considered only very low biomass concentrations to prevent self-shading of the algae. For those conditions, calculation of algae biomass production can be based on the incident radiation level on the PBR and the transmission properties of the PBR construction only. In this study however, in order to consider the influence of the biomass concentration on the light absorption by the biomass, the averaged light intensity (Iav) in the PBR was calculated according to Quinn et al. (2011). This approach is based on the assumption that the algae are adapted to this averaged light intensity. Both the light absorption coefficient of the algae biomass (a) and the biomass concentration (Cb) influence the average light intensity according to Eq. (3): Iav ¼ I0 $swall
1 expða$Cb $dtube Þ a$Cb $dtube
mmol m2 s1
(3)
where I0 is the PAR incident on the PBR wall [mmol m2 s1], swall is the transmittance of the PBR wall equal to 0.85 [e], a is the light absorption coefficient of the biomass equal to 0.0752 [m2 g1], Cb is the biomass concentration [g m3] and dtube is the diameter of the PBR tube [m], which equal to light path.
2.3.2.2. Temperature. The temperature of the algae fluid in the PBR is one of the key factors strongly influencing the algae growth rate (Be; chet et al. 2010). Solar radiation has the greatest influence on the PBR temperature as compared to air
temperature. In integrated production, no direct radiation reaches the PBR and total amount of radiation is rather low. It was assumed that the temperature of the PBR always equals the temperature of the greenhouse air. In separated production, full solar radiation reaches the PBR. The PBR temperature was, therefore, separately modelled following the approach described by Be´chet, Shilton, Fringer, Munoz, and Guieysse (2010). Eq. (4) describes the simplified energy balance of the PBR. rCp V
dTPBR ¼ Qra;sol þ Qre;sol þ Qc dt
(4)
W
where Qra,sol is the solar radiation flux reaching the PBR directly [W], Qre,sol is the first order solar radiation reflected by the floor [W], Qc is the convective energy flux between PBR and air [W], TPBR is the PBR temperature [K], r is the density of the algae fluid [kg m3], Cp is the specific heat capacity of the algae fluid [J kg1 K1] and V is the volume of the PBR [m3]. The solar radiation flux reaching the PBR directly (Qra,sol) was calculated according to Eq (5) as a function of inside solar radiation (Iin) projected at the surface of the PBR, emissivity of the algae fluid (3 ) and transmittance of the PBR (swall). The projected surface was equal to the PBR tube diameter (dtube) times its length (L). Qra;sol ¼ 3 $swall $Iin $dtube $L
W
(5)
where 3 is the emissivity of the algae fluid [e] equal to 0.97 (Be; chet et al. 2010), Iin is the solar radiation entering the greenhouse [W m2] and L is the length of the PBR tube [m]. The distance between the PBR tubes was one third of the tube diameter, so a quarter of the inside solar radiation was considered to reach the floor. The reflectivity of the greenhouse floor rg was assumed to be 0.5. The bottom half of the circumference of the PBR received solar radiation reflected from the floor (Qre,sol), which is calculated by Eq. (6). 1 p Qre;sol ¼ 3 $swall $rg $ Iin $ dtube $L W 4 2
(6)
Convection takes place at the PBR wall. The driving force for convection is the temperature difference between greenhouse air (Tair) and PBR (TPBR). Eq. (7) displays the convective energy flux (Qc). Qc ¼ aðTair TPBR Þp$dtube $L
W
(7)
where a is the heat transfer coefficient of the tube’s wall equal to 10 [W m2 K1], (Bot, Sapounas, Norsker, & de Winter, 2009). In order to be able to find a value of the PBR temperature for every hour of the year for every tube diameter Eq. (4) was converted to Eq. (8) and solved iteratively. The temperature gradient dTPBR/dt was calculated by Eq. (9). 0 ¼ rCp V
dTPBR þ Qra;sol þ Qre;sol þ Qc dt
dTPBR TPBR ðtÞ TPBR ðt 1Þ ¼ 3600 dt
K s1
W
(8)
(9)
2.3.2.3. Algae production. According to Dermoun et al. (1992) Eq. (10) describes the maximum algae growth rate (gmax) at a given temperature in the PBR (TPBR); Eq. (11) describes the
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g
g
gmax ðTPBR Þ ¼ 2g 1 þ bT
Iopt ðTPBR Þ ¼ 2rI 1 þ bIT
xTg g x2Tg þ 2bT $xTg þ 1
xTI x2TI þ 2bIT þ 1
gðIav ; TPBR Þ ¼ 2gmax ð1 þ bI Þ
h
1
mmol m2 s1
xI x2I þ 2bI $xI þ 1
h
1
(10)
(11)
(12)
dCb ðtÞ ¼ gðIav ; TPBR Þ$Cb ðtÞ dt
where TPBR is the temperature of the algae [ C]; Iav is the average light intensity in the PBR; g is the maximum growth rate at optimal temperature equal to 0.0583 [h1]; rI is the maximum radiation flux value of Iopt value at the optimum g temperature, equal to 538 [mmol m2 s1]; and bT , bIT and bI are shape factors for the limitation of algae growth rate by temperature and the limitation by radiation, respectively. These shape factors are temperature dependent, but the model is not sensitive to them, so they were set to fixed values of respectively 0.02, 0.56 and 0.50 [e]. The coefficients xT g, xT I and xI are represented by Eq. (13), Eq. (14) and Eq. (15) respectively. TPBR q0 g g qopt q0
e
(13)
xTI ¼
TPBR qI0 qIopt qI0
e
(14)
xI ¼
Iav Iopt
e
1
½kg m3 h
Cb ðtÞ ¼ Cb ðt 1Þ$expðgðIav ; TPBR Þ$tÞ
(16)
½kg m3
(17) 3
For Cb(0) the initial biomass concentration of 1 [kg m ] was chosen. An upper and lower limit was set for the biomass concentration. When the upper limit (3 kg m3) was reached, biomass was harvested until the lower limit (1 kg m3) was reached. The sum of all biomass harvests is the total biomass yield calculated per year.
2.3.3.
Economic model
The economic sub-model calculates costs and returns of a combined tomato and algae production in a Dutch greenhouse. For greenhouse tomato production, fixed and variable costs and benefits were obtained from Vermeulen (2010), which contains up-to-date information on average production, costs and benefits for different crops produced in Dutch greenhouses. In the current study, calculations were based on the economics of a truss tomato production using a combined heat and power generation system (CHP), a combination
g
xTg ¼
g
where q0 andqopt represent the temperatures at which the algae growth rate is zero and maximum equal to 4.7 and 20.5 [ C] for Porphyridium cruentum, qI0 and qIopt represent the temperatures at which Iopt is zero and maximum equal to 4.7 and 12.3 [ C]. For every hour of the year, an hourly algae growth rate g(Iav,TPBR) was calculated based on the average light intensity (Iav) and PBR temperature (TPBR) at that hour (t). The variation of algae concentration in time is given by Eq. (16) and the instantaneous concentration (Cb) at given t was calculated according to Eq. (17).
optimal radiation flux (Iopt) at that temperature; Eq. (12) calculates the actual algae growth rate (g) at the given temperature and average light intensity (Iav) in the PBR.
(15)
Table 2 e Costs and returns related to the production of truss tomato in combination with a CHP in a Dutch greenhouse (Vermeulen, 2010). Costs
Value
Plant material tomato Crop substrate Gas usage and transport
3.00 0.80 19.22
V m2 year1 V m2 year1 V m2 year1
Unit
Electricity delivery to net Crop protection Crop nutrients Crop materials (wires, clips) Labour Labour by third party Packaging Auction Removal of crop Interest on capital Durable production resources including greenhouse construction, equipment and ground Other costs Total costs Returns
14.91 0.75 1.15 0.65 19.25 0.25 0.26 2.31 0.50 0.46 18.20
V V V V V V V V V V V
2.00 53.89 Value
V m2 year1 V m2 year1 Unit
Tomato yield Price tomato trusses Total returns Tomato profit
64 0.72 46.08 7.81
kg m2 year1 V kg1 V m2 year1 V m2 year1
m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1 m2 year1
Remark
Gas usage is 71.6 m3 m2 year1 including CHP and 39.8 m3 m2 year1 for tomato crop only Electricity production by CHP
Remark
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Table 3 e Fixed and variable costs related to algae production in horizontal tubular PBR. Values were taken from Norsker et al. (2011) unless indicated otherwise. Indicated is how costs were adjusted to fit the system modelled in the current study. Fixed costs
Unit Costs
Units
Adjusted according to
Remark
Circulation pump Centrifuge Centrifuge feed pump Medium filter pump Medium feed pump Medium preparation tank Harvest fluid storage tank Seawater pump station Weighing station Air blower Installation costs Instrumentation and control Piping Variable costs
26,100 133,000 4800 13,500 4800 20,000 20,000 15,000 40,000 22,000 30 30 30 Unit costs
V V V V V V V V V V % % % Units
Model result Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor Cost factor
Adjusted according to
Remark
Labour Maintenance CO2 Culture medium premix Medium filters Tubing Electricity price Power for algae harvest Power for pumping
62,653 4 0.33 18,040 10,355 0.03 0.09 1
V ha1 year1 % V kg DM algae V ha1 year1 V ha1 year1 V m1 year1 V kWh1 kWh m3 kWh
Area ratio
Two people ha1 Vermeulen (2010) Percentage of fixed costs after adjustment
Percentage of fixed costs after adjustment
Volume ratio Volume ratio Tube wall length
Model result
commonly used in the Netherlands. In Table 2, costs and benefits are given for a standard greenhouse tomato crop at an average price of V0.72 per kg fresh tomato. Norsker et al. (2011) analysed the costs of algae production systems, among others horizontal tubular PBR covering an area of 1 ha. Data from their analysis was used and adapted for our study. Fixed costs of the equipment were corrected by using a volume ratio, which expresses the volume of the systems in our study in relation to the volume of the systems analysed by Norsker et al. (2011). Fixed and variable costs are given in Table 3. Variable costs included labour, maintenance, CO2 supply, premix of algae medium and mix of nutrients, filtering and electricity for pumping and harvesting (Table 3). Labour costs were based on Vermeulen (2010) assuming that labour exchange between tomato and algae production can take place and that two persons are required per ha production. Pumping costs are a large proportion of the costs of algae production. The number of pumps and total pump capacity needed was therefore calculated in more detail. The pump capacity is dependent on the volume of the PBR system, the diameter and hydraulic properties of the PBR tubes and appendices, and the required liquid velocity. The operational characteristics of a commercial pump were considered. The total electrical pump power (Wp) was calculated according to Eq. (18). Wp ¼ DPtotal
fv 1 1 ½kW $ $ 3600 hp hm 1000
(18)
where DPtotal is the sum of the pressure difference resulting from losses in the PBR tubes with a given length, diameter, density and velocity of the algae fluid and friction coefficient, the pressure difference in the appendages and the pressure difference in the main distributions tubes [Pa]; 4v is the
volume flux through the PBR tubes [m3 h1]; hp is the pump efficiency equal to 0.8 [e] and hm is the efficiency of the electric engine driving the pump equal to 0.9 [e]. For calculation of the costs of the separated production scenario, two modifications were needed. Firstly, the minimum liquid velocity was doubled from 0.2 to 0.4 m s1, to prevent oxygen inhibition of the algae, resulting in increased fixed and variable pumping costs. Secondly, fixed costs of the greenhouse construction, floor and greenhouse equipment were added to algae production for every m2 of greenhouse occupied. In integrated production, all fixed costs were covered by the tomato production thus yielding an advantage in efficiency of resource use compared to separated production. The price for the algae produced is strongly dependent on the market. In the current study, a price of V50 kg1 DM was chosen which was considered to be representative for high quality algae produced in closed PBRs.
3.
Results
3.1.
Algae productivity
Table 4 shows the results of the integrated production and separated production scenarios for three different tube diameters. Essentially, two figures are of interest, volumetric productivity and areal productivity. Volumetric algae productivity in kg DM m3 year1 is a measure for the light use efficiency of the PBR. Areal productivity in kg DM m2 year1 indicates how effectively the greenhouse floor area is used for algae production and is a combination of volumetric productivity and the PBR volume per greenhouse floor area.
11 24 25 4 12 13 40 60 90 40 60 90 0.15 0.19 0.15 0.15 0.29 0.20 5.2 6.2 6.5 5.2 6.2 6.5 14.0 8.0 6.0 42.2 24.1 16.0 146.7 95.1 68.5 146.7 95.1 68.5 361
361
82.4
3.2 1.8 1.2 8.7 4.7 3.3 39.2 21.0 14.3 39.2 21.0 14.3 30.6 361 527
Large scale
Separated Small scale production
On path
6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm Integrated Under crop production
Year round Areal algae PBR volume Year round average Volumetric Year round average Year round average production per greenhouse algae production PAR radiation inside PAR radiation inside average PAR PAR radiation greenhouse above crop greenhouse radiation inside [kg DM m3 year1] [kg DM m2 year1] floor area [l m2] 2 1 outside incident on PBR [mmol m s ] PBR [mmol m2 s1] [mmol m2 s1] [mmol m2 s1] PBR diamter PBR location
Table 4 e Effect of PBR location and dimension on light conditions and algae areal and volumetric productivity at standard tomato LAI and standard algae biomass concentration.
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The volumetric productivity of algae in a PBR under a tomato crop in a Dutch greenhouse was 14.0 kg algae DM m3 year1 in a 6 cm PBR, 8.0 kg algae DM m3 year1 in a 11 cm PBR and 6.0 kg algae DM m3 year1 in a 16 cm PBR. The volumetric productivity was decreasing with increasing PBR diameter due to an associated increase of the light path and, consequently, a decrease of the light intensity inside the PBR. The average light intensity in the PBR was calculated to be 3.2 mmol m2 s1 in the 6 cm PBR, 1.8 mmol m2 s1 in the 11 cm PBR and 1.2 mmol m2 s1 in the 16 cm PBR. The volumetric productivity of the PBR mounted on the path between the tomato crop was higher than the productivity of the PBR under the crop and amounted to 42.2 kg algae DM m3 year1 in a 6 cm PBR, 24.1 kg algae DM m3 year1 in a 11 cm PBR and 16.0 kg algae DM m3 year1 in a 16 cm PBR. This higher production can be explained by the higher light intensities on the path. Light intensities on the path were 2.5 times higher than under the crop. In the separated production scenario even higher productivities were obtained. In that case volumetric algae production was 146.7 kg algae DM m3 year1 in a 6 cm PBR, 95.1 kg algae DM m3 year1 in a 11 cm PBR and 68.5 kg algae DM m3 year1 in a 16 cm PBR. This production is twelve times higher than the volumetric production obtained in integrated production under a tomato crop. This difference can be fully explained by the 12 times higher light intensities above the tube and the 12 times higher average light intensities in the tube in the separated production scenario. The specific volumetric productivity calculated was 0.40 g ll d1, 0.26 g ll d1 and 0.19 g ll d1, for PBRs with tube diameter 6 cm, 11 cm and 16 cm respectively. These values are of the same order of magnitude as that measured by other researchers using Porphyridium cruentum, although they cannot be compared directly because of different cultivation conditions. In particular, Dermoun et al. (1992) measured 0.50 g ll d1 for light intensity 350 mmol m2 s1, Muller-Feuga, Le Guedes, Herve, and Durand (1998) measured 0.58 0.12 g ll d1, Rebolloso Fuentes et al. (1999) measured 1.76 g ll d1 under outdoor conditions in Spain, You, Chen, and Wang (2006) measured 0.43 g ll d1 in a PBR continuously illuminated using light intensities 13.5e67.5 mmol m2 s1, and Oh et al. (2009) measured 0.042 g ll h1 in a PBR illuminated using light intensities 10.0e25.0 mmol m2 s1 and light:dark cycle of 18 h:6 h. The areal productivity of algae in a PBR under a tomato crop in a Dutch greenhouse was found to be 0.15 kg algae DM m2 year1 in a 6 cm PBR, 0.19 kg algae DM m2 year1 in a 11 cm PBR and 0.15 kg algae DM m2 year1 in a 16 cm PBR. The areal productivity of algae in a PBR mounted on the path was only little higher with 0.15 kg algae DM m2 year1 in a 6 cm PBR, 0.29 kg algae DM m2 year1 in a 11 cm PBR and 0.20 kg algae DM m2 year1 in a 16 cm PBR. The areal productivity of algae in the PBR mounted in the separated production scenario was much higher and amounted to 5.18 kg algae DM m2 year1 in a 6 cm PBR, 6.16 kg algae DM m2 year1 in a 11 cm PBR and 6.46 kg algae DM m2 year1 in a 16 cm PBR. Algae production is greater in separated production than under a tomato crop due to higher light availability and more tubes installed per floor area. While volumetric algae
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production increased with decreasing PBR tube diameter, areal algae production was greater in 11 cm PBR compared to 6 cm and 16 cm PBR. This optimum occurs for the following reasons: the light availability increases with decreasing PBR diameter; the amount of hours with too low or too high temperatures decreases with increasing PBR diameter; the installed PBR volume per greenhouse floor area increases with PBR diameter. The result is that a PBR diameter of 11 cm seems to have the optimal combination of volumetric productivity and installed volume per area. Decreasing the LAI of the tomato crop through extra leaf picking positively affected algae productivity in integrated production as shown in Fig. 4. Effects were most distinct for the PBR mounted under the crop. When the LAI was decreased by 5%, the volumetric algae productivity increased by 52% and when LAI was decreased by 10%, the volumetric algae productivity increased by 110%. For the PBR mounted on the path in an integrated production system, the increase was less pronounced and amounted to 12% and 26%, respectively. An increasing algae biomass concentration in the PBR has a negative influence on the growth rate because it reduces the average light intensity in the PBR. At the same time, however, a higher biomass concentration has a positive influence on the volumetric productivity at equal growth rate as can be seen in Eq. (17). In the integrated production scenario with the PBR mounted under the crop, the maximum volumetric algae productivity was reached at a biomass concentration of 0.5 kg m3. With the PBR mounted on the path it was reached at 1.0 kg m3. In separated production, maximum volumetric productivity is reached at a biomass of as high as 7 kg m3 or even higher.
3.2.
Cost price of algae production
In integrated production, the profit on the algae production part of the system was negative. At an assumed algae price of 50 V kg1 algae DM, as shown in Table 5, the profit from PBR placed under the tomato crop was V3.00 m2 year1 for a 6 cm PBR, V7.72 m2 year1 for a 11 cm PBR and
Fig. 4 e Effect of different tomato LAI and different PBR locations on the volumetric algae productivity in the 6 cm PBR at standard biomass concentration.
V10.38 m2 year1 for a 16 cm. For the same PBR diameters, the profit from PBR placed on the path was V2.76 m2 year1, V4.51 m2 year1 and V0.05 m2 year1 respectively. Since following Vermeulen (2010) the profit of an average tomato production was also negative, the total profit of integrated production of algae and tomato was negative. Increasing PBR tube diameter decreased profit mainly due to the increased volume and consequently the higher pumping costs on one hand, and due to the lower average light intensity in the PBR and associated lower productivity on the other hand. Cost price of algae produced per m2 is given by dividing the areal costs (V m2 year1, Table 5) by areal production (kg DM m2 year1, Table 4). When the PBRs are placed under the tomato crop, the cost price in the 6 cm PBR was V70 kg1 algae DM, in the 11 cm PBR was V91 kg1 algae DM and in the 16 cm PBR was V123 kg1 algae DM. When the PBRs are placed on the path, the cost price in the 6 cm PBR was V31 kg1 algae DM, in the 11 cm PBR was V34 kg1 algae DM and in the 16 cm PBR was V51 kg1 algae DM. Figure 5 shows the effect of varying the price of kg DM algae production on the total profit of algae and tomato in integrated production depending on the LAI of the tomato. Cost price of algae decreased when tomato LAI decreased, as the higher radiation incident on PBR results to higher productivity. Profit in separated production was related to the scale of the system (Table 5). The large scale variant resulted in larger profits per m2 greenhouse area than the small scale variant. The 11 cm PBR system had higher profits than 6 cm and 16 cm PBR systems. At an assumed algae price of V50 kg1 DM, the profit for a 11 cm PBR was V156 m2 for a small scale system and V231 m2 for a large scale system. For a small scale system, the cost price of algae produced in the 6 cm PBR was V23 kg1 algae DM, in the 11 cm PBR was V25 kg1 algae DM and in the 16 cm PBR was V30 kg1 algae DM. For a large scale system the cost price in the 6 cm PBR was V11 kg1 algae DM, in the 11 cm PBR was V12 kg1 algae DM and in the 16 cm PBR was V15 kg1 algae DM. Figure 6 shows the effect of varying the price of kg DM algae production on the total profit of algae and tomato in Separated production depending on the scale of the algae system. Systems smaller than 1000 m2 greenhouse floor area are only profitable if the price is higher than V40 kg1 DM algae. In integrated production, fixed costs comprised a share of 66% of the total cost of algae DM. Within the fixed costs, the pumps take a great share (21%). Within the variable costs, labour (13%) and maintenance costs (9%) take the greatest share (Fig. 7). In separated production, fixed costs comprise an even greater share of total costs in comparison with integrated production (76%). This is mainly due to costs for the greenhouse building which are accounted to the costs for algae production. Figure 7 is representative for other tube diameters (data not shown).
4.
Discussion
4.1.
Desk-study
This assessment exists as a desk-study only. Results in the study here are in line with literature data. It is very important
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Table 5 e Cost, returns and profit of an algae production system for different PBR locations and diameters and total profit for integrated and separated tomato and algae production, algae price of V50 kgL1 DM assumed. PBR location Integrated production
Under crop
On path
Separated production
Small scale
Large scale
PBR Costs algae Returns algae Profit algae [V m2 year1] Total profit tomato and algae 2 1 diameter [V m year ] [V m2 year1] [V m2 year1] 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm 6 cm 11 cm 16 cm
10.44 17.23 18.38 4.69 9.78 10.13 118.00 152.00 198.00 59.00 77.00 97.00
3.00 7.72 10.38 2.76 4.51 0.05 141.00 156.00 125.00 200.00 231.00 226.00
7.44 9.51 7.55 7.45 14.29 10.08 259.00 308.00 323.00 259.00 308.00 323.00
10.81 15.53 18.64 5.05 3.30 7.86 3.65 2.60 4.76 54.58 79.66 54.61
to evaluate the model and its results with measurements in greenhouses. Experiments are planned to be carried out in the future.
requires as much light as possible. Studying the combination of algae production with crops requiring less light could be interesting.
4.2.
4.3.
System lay-out
Closed systems for algae production are of many types and layouts, and the best design and layout is still debated (e.g. Bitog et al. 2011). Systems design for integrated production of algae and tomato in greenhouses has not been carried out before. A stateeof-the-art tomato production system under Dutch conditions was used as reference for modelling tomato production and implementation of an algae production system. The layout of the algae production system and calculated scenarios were based on a system implemented by a Dutch tomato producer. This resulted in a limited number of scenarios analysed in integrated and separated production. With respect to the location of the PBR in the greenhouse for example, a vertical PBR placed along the greenhouse walls might be cost and space effective and worthy of study in the future. Especially for separated production, different system layouts can be thought of which make better use of the available space than the currently studied horizontal PBRs. One may think of vertically stacked horizontal PBRs. Finally, combination of algae production with tomato production could be seen as a worst case scenario, because a tomato crop
In the current study, light intensity in the PBR was calculated with the average light intensity method often used in literature (e.g. Quinn et al. 2011). This resulted in equal light intensity for the algae, rather than differentiating growth rate depending on the algae position in the light path in the PBR. This method is based on the assumption that the algae are adapted to the average light intensity and are perfectly mixed. In a real situation, light intensity is dependent on the position of the PBR: the light intensity decreases with the length of the light path, which may result in both light limited and light inhibited states of algae in one PBR. Especially for larger tube diameters, and under low or high light conditions, an overestimation of productivity is to be expected when the average light method is used. More accurate light models could be implemented in our study in the future (e.g. Slegers et al. 2013). New models based on ray-tracing should be developed. In integrated production, PBRs are placed under the crop rows or between them in the path. In these places, the light available for PBRs, cannot be calculated by using exponential functions, which describe light interception by the crop, since obstacles like crop gutter are neglected, and in the path the light available is about 4 times more than the light under the crop. The use of linear relations, which have been derived by preliminary experimental study, was a simplification to overcome the lack of knowledge regarding the light available at these places. More experimental research is needed, to accurately determine the light available for PBRs when these are placed under the crop rows or/and in the path between the crop rows.
4.4. Fig. 5 e Effect of varying the price per kg DM algae production on the total profit of algae and tomato in integrated production of algae in a 11 cm PBR under the tomato crop at different LAI of tomato.
Light modelling
Growth rate modelling
Tittel, Bissinger, Gaedke, and Kamjunke (2005) indicate that it is typical for phototrophically-grown algae that they exhibit negative growth rates due to maintenance respiration, when light intensities are below the compensation point. In the
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Fig. 6 e Effect of varying the price of algae (V kgL1 DM) on the total profit of algae and tomato in separated production depending on the greenhouse area occupied by the algae system (scale), algae production in a 11 cm PBR.
algae growth rate model of Dermoun et al. (1992) that we used, losses by respiration and negative growth are not included. Especially under low-light conditions in integrated production, productivity of the PBR will thus be overestimated by use of this model. The model of Dermoun et al. (1992) was specifically developed for the algae species Porphyridium Cruentum. It is not representative for other algae species with different optimal temperature, optimal light and maximum growth rate. In this study, algae production was modelled dependent on temperature and radiation only, assuming that nutrient, CO2 and O2 concentrations and pH were optimal or nonlimiting. In practice this will not be the case and therefore productivity is probably overestimated in this study. To improve modelling of combined production, a more complete growth rate model could be implemented and validated in the future (e.g. Geider, MacIntyre, & Kana, 1996; Quinn et al. 2011).
The modelling of the cost price of the algae production system in this study is mainly based on the work of Norsker et al. (2011). No economic data is available for the integrated production of algae and tomato in greenhouses. Often high market prices are mentioned for algae dry matter. Wijffels et al. (2010) for example mention an average value of 250 V kg1 DM. But high prices are mostly related to small markets and increasing interest in algae production will reduce the market value. However, we can conclude that the calculated cost price for algae production in greenhouses of V11 DM algae in a 6 cm PBR in separated production gives a reasonable perspective. This value is equal to yearly fixed and variable costs of about V60 m2 for the algae system only.
4.5.
The objective was to determine the algae productivity in tubular photobioreactors and the economic feasibility of combined production of tomato and algae in Dutch greenhouses. To this end, a Matlab-based model was developed and
Cost price of combined algae and tomato production
Little information on the economics of large-scale closed algae production systems is available in literature or from practice.
5.
Conclusion
Fig. 7 e Distribution of fixed and variable costs for algae production in a 11 cm PBR in integrated production of algae under the tomato crop and in a large scale system in separated production in different greenhouse compartments.
b i o s y s t e m s e n g i n e e r i n g 1 2 2 ( 2 0 1 4 ) 1 4 9 e1 6 2
a range of scenarios were analysed to identify the best location and size of a tubular PBR in a combined tomato and algae production system. With today’s technological advances and given assumptions, the combined production of algae and tomato in a Dutch greenhouse is economically feasible, when the PBRs (of 6 cm) are placed in a separated greenhouse compartment next to tomato. In this case the minimum cost price of algae was V11 kg1 algae DM. Algae production in PBRs (of 6 cm) in integrated production is not economically feasible since the V70 kg1 production costs are higher than the assumed algae price of 50 V kg1. Algae productivity was found to be too low under a tomato crop due to limiting light conditions. This novel model approach and the scenario results provide a better understanding of the potential productivity and related costs and returns of algae production and give insight into the feasibility of algae and tomato production in Dutch greenhouses.
Acknowledgements This study was supported by the Dutch Ministry of Economic Affairs, Agriculture and Innovation and by the Dutch Productboard of Horticulture. We would also like to thank the participating growers.
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