International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
Experimental results and spatial simulation of climate in a greenhouse
with insect screens
T. Bartzanas & D. Fidaros
N. Katsoulas & C. Kittas
T. Boulard
Centre for Research and
Technology-Thessaly,
ITEMA, 1st Industrial Area
of Volos, 38500 Volos,
Greece;
bartzanas@cereteth.gr
University of Thessaly, Dept. of
Agriculture Crop Production &
Rural Environment, LACEC,
Fytokou St., N. Ionia, GR38446, Magnesia, Greece,
ckittas@uth.gr
INRA UR880, 400,
Route des Chappes,
BP 167, 06903 Sophia
Antipolis, France
Keywords: greenhouse climate heterogeneity, air speed profiles, air temperature, relative
humidity, CFD modelling
Abstract
Aim of the present paper was to present, analyze and compare detailed
experimental data and CFD simulation results in a greenhouse equipped with insect
screens. The studied greenhouse was a round arch type with vertical side walls. A tomato
crop was cultivated inside the greenhouse with a mean height during the period of
measurements of 1.8 m. Air velocity, temperature and humidity measurements at 72
positions equally distributed inside the greenhouse were carried out by means of a 3-D
sonic anemometer and a fast response temperature and humidity sensor, while in parallel,
outside climate variables were also recorded. For the numerical part, the commercial CFD
code Fluent was used as a basis, where the required external source code for the various
sub-models and boundary conditions were embedded. Good overall agreement, both
quantitative and qualitative was found between the experimental and simulated data. The
differences between measured and computed by the CFD model values were between
0.01 m s-1 to 0.18 m s-1 for air velocity, 0.1°C to 1.3°C for air temperature and 0.15 kPa to
0.6 kPa for air vapour pressure. Quantitative understanding of the climate heterogeneity
induced by ventilation and insect screens on greenhouse can help to improve the design of
vent openings and thus, to optimize greenhouse production in terms of cost efficiency,
crop quality and quantity.
INTRODUCTION
In the latest part of our century, crop protection in European greenhouses became
strongly chemically oriented. However, the fast evaluation and introduction of a number
of natural enemies in situations where chemical control was either insufficient, impossible
or undesired, has taught growers and crop protection specialists that biological control,
within IPM programs, is a powerful option in pest control (Albajes et al., 1999).
Theoretically, greenhouses are ideal for the implementation of IPM programs (isolated
from outside environment, cultural measures and pest management programs can be
organised for each separate greenhouse, little interference with pest management in
neighbouring greenhouses). However, in warm climates like in Mediterranean regions,
greenhouses are usually rudimentary equipped, growers are often less specialised than
those of temperate zones, little attention is paid to farm hygiene; and climate control is
International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
usually based on natural ventilation (Luo et al., 2005). In fact, in these greenhouses,
protecting the crop from insects is regarded as more important than protecting them from
excessive heat (Teitel, 2005). The use of insect screens on ventilation openings can
significantly reduce the pressure of insects and thus, enable a more biological crop
production (Teitel, 2007).
Although the application of screens has proved cost-effective for both growers and
consumers (Teitel et al. 1999; Taylor et al., 2001), their incorporation in greenhouses
causes a problem since screens act as an extra barrier to natural airflow and impede
ventilation (Miguel and Silva 2000; Kittas et al., 2002; Katsoulas et al., 2005); and thus,
strongly interfere with greenhouse microclimate. Ventilation is essential for a satisfactory
crop growth, since good ventilation limits the increase in internal temperature and
humidity, there has been a worldwide effort to improve the performance of screens with
regard to these parameters. For these purpose, several studies were carried out in order to
optimise the use of insect screens in greenhouses. In most of the studies computational
fluid dynamics is used to enable study of various structural (greenhouse and screens)
modifications, while keeping the same outside climate conditions (Bartzanas et al., 2002;
Fatnassi, 2003; Fatnassi et al., 2006). However, most of the available numerical studies
compare the ventilation rate obtained for different vent configurations and climatic
conditions but few of them focus on the local climate generated at plant level, since in the
majority of them the contribution of the crop on internal climate has taken into account
via very simplified models. Moreover, the majority of the studies dealing with the
experimental validation of CFD codes considered only measurements of the global
exchange rate and not the detailed climate distribution.
The present paper provides experimental results for air velocity, air temperature
and air vapour pressure deficit (the main greenhouse climate parameters) in the whole
greenhouse volume (3-D), compares these results with the results obtained from a CFD
code; and uses later the CFD code for case studies, aiming to optimise screens use in
greenhouses.
MATERIALS AND METHODS
Experimental greenhouse and measurements
The experiments were performed in a round arch with vertical side walls, plastic
covered greenhouse, NE/SW oriented (36° declination from north), located at the
University of Thessaly near Volos (latitude 39°44΄; longitude 22°79΄; altitude 85 m), on
the continental area of Eastern Greece. The geometrical characteristics of the greenhouse
were as follows: eaves height of 2.4 m; ridge height of 4.1 m; total width of 8 m; total
length of 20 m; ground area of 160 m2, and volume of 572 m3. The greenhouse was
equipped with two side roll-up windows located at a height of 0.6 m above the ground
with a maximum opening area of 27 m2 (2 vents of 15 m length × 0.9 m opening height)
for both vents (about 17% of the greenhouse ground area). The prevailing wind of the
region has a north-south direction. The greenhouse soil was totally covered by a doubleside (black downwards - white upwards) plastic film. During the measurements, which
were carried out during summer, ventilation openings were covered with an anti-aphid
insect screen (55 × 27 mesh size, 265 μm wire diameter, 150 × 150 μm hole size and 50%
porosity). The greenhouse was occupied by a tomato crop, planted in double rows, with
an average height of about 1.8 m and leaf area index of 2.5 m2 [leaf] m-2 [ground] during
the period of measurements was about. Air velocity, temperature and relative humidity
measurements were carried out in total 72 positions inside the greenhouse. The air
International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
temperature T and the three components of air velocity (Ux, Uy and Uz) were measured by
means of a 3-D sonic anemometer with a sampling frequency of 5 Hz. The air relative
humidity near the sonic anemometer was recorded with measuring frequency of 1 Hz, by
means of a fast response relative humidity probe connected to a data logger. Air
temperature, vapour pressure and total radiation at the centre of the greenhouse were also
measured. Ambient weather conditions were continuously collected and stored in a data
logger. A detailed description for the experimental greenhouse and the measurements can
be found in Kittas et al. (2008). Average values from the experimental measurements
were used to obtain realistic boundary conditions (table 1).
Numerical Model
The commercial CFD code Fluent was used as a basis in which the required
external source codes for the various sub-models and boundary conditions were
embedded. The flow inside the greenhouse was assumed to be two dimensional (2-D),
steady-state, incompressible and turbulent (Ferziger & Peric, 1996) for all the case
studies. For the validation of the numerical model a 3D model was used. The effect of
turbulence on the flow was implemented via the high Re k-ε model (standard) model
(Launder & Spalding, 1972). The density variation is calculated according to the
Boussinesq model in order to take into account the natural convection effects. Crop was
modelled using the porous medium approach (Boulard and Wang, 2002). The
convergence criterion was set to 10-7 for the continuity, momentum and turbulence
equations while for energy and radiation equations the criterion was 10-8. More
information about the numerical model can be found in Bartzanas et al. (2002; 2004). To
investigate the effect of different insect screens on greenhouse microclimate and
ventilation, a parametric study was carried out. The aerodynamic properties of the screens
(permeability and pressure loss coefficient) were calculated as suggested by Miguel
(1998). Table 2 presents the types of screens investigated along with their aerodynamic
properties.
RESULTS
Numerical model validation
In order to compare the different climate parameters measured in several positions
inside the greenhouse and since the outside climate characteristics varied during the
period of measurements normalized values were used calculated as follows:
where Uj-i is the resultant air velocity measured
 Normalized air velocity U n  Uj  i
U o,t
at each position (j) inside the greenhouse by the 3-D sonic anemometer and Uo is the
outside wind speed measured during the same time period
T T
 normalized air temperature Tn  j i o,t where Tj-i is the temperature measured at
Ti ,t  To,t
each position inside the greenhouse, To,t, and Ti,t are the air temperature measured
outside (o) and at the centre (i) of the greenhouse, respectively, during the same time
period (t).
 air vapour pressure deficit Dn  D j i  Di ,t where Dj-i is the air VPD measured at each
position inside the greenhouse and Di,t is the air VPD measured at the middle of the
greenhouse during the same time period (t).
International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
Table 3 presents experimental and calculated with the CFD model (in parenthesis)
mean values of the three above-mentioned climate parameters in the three different
measuring heights (1.1 m, 2 m and 2.8 m). The mean value of the normalised air velocity
measured was 0.023 (while the simulated one was 0.019), almost 50% lower than the
value of air velocity measured in the same greenhouse without screen (Kittas et al. 2008).
Concerning the air velocity differences found between the three heights levels inside the
greenhouse it was found that the higher air velocity values were observed at the lower
level (1.1 m), which corresponds to the middle of the side vent in full opening screens
while the lower values were observed at 2.8 m. Similar results were obtained with the
numerical model.
Concerning the air temperature a significant vertical gradient was observed
between the three horizontal measuring levels. Tj-i was always higher than air temperature
at the centre of the greenhouse. At the level of 1.1 m the mean value of Tn was 0.461,
increased at the level of 2.0 m ( Tn , 2.0 = 1.322) and slightly more at the level of 2.8 m
( Tn , 2.8 = 1.340). It should be noted that for the same greenhouse but without screen the air
at the level of 1.1 was cooler than the outside air and the air at the centre of the
greenhouse (Kittas et al. 2008). Again, as for air velocity, a general good agreement was
found between measured and calculated values.
Finally, the average value of Dn was 0.417 kPa almost 50% lower than in the case
of the greenhouse without screen (Kittas et al. 2008). A gradual increase of Dn from
greenhouse ground to greenhouse roof (table 3) was observed with this increase to be
larger in the case of the greenhouse without screens. A good agreement was found
between computed and experimental values (table 3).
In general, a good agreement between measured and numerically obtained results was
found. The differences between values computed by the CFD model and measured values
were between 0.01 m s-1 to 0.18 m s-1 for air velocity, 0.1°C to 1.3°C for air temperature
and 0.15 kPa to 0.6 kPa for air vapour pressure.
Case studies for insect screen optimisation
Having obtained a good agreement between measured and simulated results, the
CFD model was used to investigate the influence of different screen materials on
greenhouse microclimate. In total 8 different screens were tested with porosities varied
from 4% to 90% (table 2). The vertical distributions of the air velocity inside the
greenhouse; and of the air temperature difference between inside and outside air, at the
middle of the greenhouse, are presented in Figs. 1 & 2, respectively. As excepted, the
presence of an insect-proof screen over the ventilation openings reduces the air velocity in
the greenhouse. For the tested case (i.e. outside wind speed of 2 m s-1), mean air velocity
inside the greenhouse for the case without screen was 0.23 m s-1 and it was reduced to 0.1
m s-1 for a screen with a porosity 4%. For an insect screen with a commonly found
porosity (i.e a porosity of 50% such as of an anti-aphid insect screen) internal air velocity
was reduced up to 40% compared to a greenhouse without screen.
With regard to the temperature distribution, a strong thermal gradient was
observed from the windward to the leeward part of the greenhouse (data not shown) and
also from greenhouse ground to greenhouse roof (Fig. 2). Mean air temperature difference
between inside and outside air without screen was 1.85ºC and it was increased for a
greenhouse with a screen with 4% porosity to 4.14ºC. Moreover hot air accumulation was
observed near the greenhouse corners where the airflow was lower. As the porosity of the
tested insect screen was decreased, the areas with hot air accumulation were increased.
International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
Apart from mean values someone has to note the maximum values of air temperature
observed which was in the range of 8.2°C for a greenhouse with a 4% screen porosity and
6.8°C for a greenhouse with a50% screen porosity.
Concerning the variation of the vapour pressure, higher values of Dn were
observed in the greenhouse without screen. The average value of Dn was 0.41 kPa for the
greenhouse with 50% screen porosity and it was increased to 0.8 kPa for the greenhouse
without screen. For the greenhouse with 4% screen porosity the value of Dn was reduced
to 0.18 kPa indicating strong stress conditions for the plants. A gradual increase of Dn
from greenhouse ground to greenhouse roof was observed for both greenhouses.
However, this increase was larger in the case of the greenhouse without screens.
When a screen is installed to ventilation openings it is advisable to know in
advance the potential reduction on air velocity and consequently the additional increase of
cooling load to dissipate. This can be done easily if we correlate an easily measurable
screens characteristic with the relative ventilation rate. Porosity is a screen characteristic
easily found since can be either measured using a stereoscope microscope, or is provided
by screen manufacturer. Fig. 3 presents the correlation of the tested screen materials with
the ventilation rate. Final aim of this on-going study is to correlate screen porosity with
the potential increase of temperature and the additional cooling load in order to dissipate
the surplus of heat. A recapitulation of the main results is presented in table 4.
CONCLUSIONS
The influence of insect screens on airflow, air temperature, and vapour pressure
deficit distribution in a round arch, mono span greenhouse was experimentally
investigated. The numerical code was successfully validated against experimental
measurements. Proportionally to screen porosity air velocity was reduced from up to
85%, air temperature up to 78% and air vapour pressure deficit up to 82% compared with
a greenhouse without screen. A simple relation was proposed which correlates screen
porosity with the achieved ventilation rate.
Literature Cited
Albajes, R., Gullino, M.L., van Lenteren, J.C. and Elad, Y. (Eds.) 1999. Integrated pest
and disease management in greenhouse crops. Kluwer Publishers, Dordrecht.
Bartzanas, T., Boulard, T. and Kittas, C. 2002. Numerical simulation of airflow and
temperature patterns in a greenhouse equipped with insect-proof screen. Comp. Electr.
Agric. 34: 207 – 221.
Bartzanas, T., Kittas, C. and Boulard, T. 2004. Effect of vent arrangement on windward
ventilation of a tunnel greenhouse. Biosyst. Eng. 88 (4): 479-490.
Boulard, T. and Wang, S. 2002. Experimental and numerical studies on the heterogeneity
of crop transpiration in a plastic tunnel. Comp. Electr. Agric. 34: 173-190
Fatnassi, H., Boulard, T. and Bouirden, L. 2003. Simulation of climatic conditions in fullscale greenhouse fitted with insect-proof screens. Agr. For. Meteorol. 118: 97–111
Fatnassi, H., Boulard, T., Poncet, C., Chave M. 2006. Optimisation of Greenhouse Insect
Screening with computational fluid dynamics. Biosyst. Eng.93 (3), 301–312
Ferziger, J.H. and Peric, M. 1996. Computational methods for fluid dynamics. Springer,
London.
Katsoulas, N., Bartzanas, T., Boulard, T., Mermier, M. and Kittas, C. 2005. Effect of vent
openings and insect screens on greenhouse ventilation. Biosyst. Eng.93 (4), 427-436.
International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
Kittas, C., Boulard, T., Bartzanas, T., Katsoulas, N. and Mermier, M. 2002. Influence of
an insect screen on greenhouse ventilation. Tr. ASAE 45(4): 1083-1090.
Kittas, C., Katsoulas, N., Bartzanas, T., Mermier, M. and Boulard, T. 2008. Greenhouse
microclimate distribution under different vents’ openings and insect screen. Tr.
ASABE, 51(6): 2151-2165
Launder, B.E. and Spalding, D.B. 1972. Lectures in mathematical models of turbulence.
Academic Press, London, England.
Luo,W., Stanghellini, C., Dai, J., Wang, X., De Zwart, H.F. and Bu, C. 2005. Simulation
of greenhouse management in the subtropics, Part II: Scenario study for the summer
season. Biosyst. Eng. 90(4): 433-441.
Miguel, A.F. 1998. Airflow through porous screens: from theory to practical
considerations. Energy Building, 28: 63–69.
Miguel, A.F. and Silva, A.M. 2000. Porous materials to control climate behavior of
enclosures: an application to the study of screened greenhouses. Energy Buildings 31:
195–209.
Taylor, R.A.J., Shalhevet, S., Spharim, I., Berlinger, M., and Lebiush- Mordechi, S. 2001.
Economic evaluation of insect-proof screens for preventing tomato yellow leaf curl
virus of tomatoes in Israel. Crop Protect. 20: 561–569.
Teitel, M., Barak, M., Berlinger, M.J., and Lebiush-Mordechai, S. 1999. Insect-proof
screens in greenhouses: their effect on roof ventilation and insect penetration. Acta
Hort. 507: 25–34
Teitel, M., Tanny, J., Ben-Yakir, B., and Barak. M. 2005. Airflow patterns through roof
openings of a naturally ventilated greenhouse and their effect on insect penetration.
Biosyst. Eng. 92 (3): 341-353.
Teitel M. 2007. The effect of screened openings on greenhouse microclimate. Agr. For.
Meteorol. 143: 159-175
Tables
Table 1. Boundary conditions used in the CFD model.
Parameter
Air velocity, m/s
Wind direction, o
Outside air temperature, ° C
Solar radiation, Wm-2
Relative humidity, %
Roof temperature, 0C
Soil temperature, 0C
Greenhouse walls, 0C
Greenhouse floor, 0C
3D model
4.1
Perpendicular to
greenhouse axis
27
720
39
33
28
Adiabatic
30
2D model
2
Perpendicular to ventilation
openings
27
750
45
37
33
Adiabatic
37
International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
Table 2. Aerodynamic and geometrical properties of the tested screens (after Miguel,
1998).
Tested
screen
1
2
3
4
5
6
7
8
Yarn width,
(mm)
0.20
0.15
0.12
0.25
0.15
0.20
0.45
0.10
Porosity,
%
4
7
14
25
36
50
63
90
Permeability,
m2
1.90E-11
2.14E-11
6.93E-11
2.54E-10
1.82E-10
1.44E-09
3.52E-09
1.16E-09
Pressure loss
coefficient 51.02
18.00
4.66
0.94
0.56
0.24
0.10
0.10
Table 3. Comparison between experimental and numerical results. Averaged values of
normalised air velocity, normalized air temperature and air vapour pressure deficit.
Values in parenthesis present calculated (CFD) values.
Normalised values
Measured height
(m)
Air velocity
Air temperature
Air vapour pressure
deficit [units?]
1.1
0.033 (0.028)
0.461 (0.385)
0.057 (0.062)
2.0
0.020 (0.018)
1.322 (1.258)
0.749 (0.810)
2.8
0.012 (0.009)
1.340 (1.247)
0.465 (0.520)
Average
0.023 (0.019)
0.996 (0.925)
0.417 (0.480)
Table 4. Mean values of air velocity ( U ), air temperature difference ( i,o ) and air
vapour pressure difference ( Di,o ) and air exchanges rate per hour (N) for all the tested
cases.
Screen
4%
7%
14%
25%
36%
50%
63%
90%
No screen
U , m/s
0.01
0.01
0.02
0.02
0.02
0.07
0.08
0.10
0.23
i,o , °C
4.14
4.05
3.97
3.92
3.72
3.53
3.35
3.12
2.09
Di,o , kPa
0.18
0.22
0.24
0.29
0.35
0.41
0.65
0.71
0.80
N, h-1
2.70
2.95
3.80
3.77
4.61
14.33 16.50 20.61
46.71
International Symposium on High Technology for Greenhouse Systems GreenSys 2009
Université Laval - Québec City – Canada
14-19 June 2009
Figures
4,50
4,00
Greenhouse heigth, m
3,50
3,00
vel
vel
vel
vel
vel
vel
vel
vel
vel
2,50
2,00
1,50
1,00
0,50
0,00
0,00
0,10
0,20
0,30
0,40
0,50
4%
7%
14%
25%
36%
50%
63%
90%
no screen
0,60
0,70
Air velocity, m/s
Fig. 1. Numerically obtained air velocity distribution along greenhouse height at the
middle of greenhouse.
4,50
4,00
Greenhouse height, m
3,50
3,00
ΔΤ i,o 4%
ΔΤ i,o 7%
2,50
ΔΤ i,o 14%
ΔΤ i,o 25%
2,00
ΔT i,o 36%
1,50
ΔΤ i,o 50%
ΔΤ i,o 63%
1,00
ΔΤ i,o 90%
0,50
ΔΤ no screen
0,00
0,00
0,50
1,00
1,50
2,00
2,50
3,00
Air temperature difference, °C
Fig. 2. Numerically obtained air temperature difference distribution between inside and
outside air along greenhouse height at the middle of greenhouse
50,00
45,00
y = 2,3289e
2,8263x
2
R = 0,9375
-1
Air exchanges rate, (h )
)
40,00
35,00
30,00
25,00
20,00
15,00
10,00
5,00
0,00
0%
20%
40%
60%
80%
Screen porosity, %
Fig. 3. Correlation between screen porosity and ventilation rate .
100%