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Utilizing a Vertical Garden to Reduce Indoor Carbon Dioxide in an
Indoor Environment Kao-Feng Yarn, Kuang-Cheng Yu, Jeng-Min Huang, Win-Jet Luo (Corresponding author) and
Pei-Cheng Wu Graduate Institute of Precision Manufracturing, National Chin-Yi University of Technology,
Taichung City 41170, Taiwan PO box Graduate Institute of Precision Manufracturing, National Chin-Yi University of
Technology, Taichung City 41170, Taiwan Tel: 886-4-23924505 ext 5110 (office) E-mail: [email protected]
The research is financed by: The author gratefully acknowledges the financial support provided
for this study by the National Science Council of Taiwan, under Grant No. NSC 99-2218-E-167-001 and No. NSC 98-2218-E-167-001. Abstract
This study constructed a vertical garden in an indoor environment to absorb the Carbon dioxide (CO2) exhaled from human breathing, in order to improve the indoor air quality through plant photosynthesis. This study used Spathiphyllum kochii as the subject plant, and conducted experimental analysis of individual plant to obtain the absorption rates under different environmental CO2 concentration levels in the range from 500ppm to 5000ppm. Simulation on flow field of air passing through the individual plant was conducted using a porous medium modeling. The absorption rates obtained from the experiments were substituted into the absorption rates of the porous medium modeling to simulate CO2 absorption efficiency of the individual plant and compare the experimental results with the simulation results. Furthermore, in an environmental room with a vertical garden consisting 240 plants and a human being, the CO2 concentration distribution in the room was also experimentally and numerically investigated. By the theoretical modeling developed in this study, the CO2 concentration distribution in the vertical garden can be simulated. The experimental results showed that, after 150 minutes, 13% of CO2 generating from the human breathing can be absorbed by the 240 plants and the numerical results were well consistent with the experimental measured results. The theoretical modeling obtained in the study can afford useful references to the designers for indoor CO2 purification. Keywords: Carbon dioxide, Vertical garden, Photosynthesis, Theoretical modeling 1. Introduction
In the past, for the purpose of saving energy, buildings were usually of high air tightness and high heat resistance, resulting in poor natural ventilation. In modern times, with the upgrading of the living quality, people have increasing requirements regarding the building indoor decoration. Gases caused by the paints and coatings used in indoor decoration and furniture such as HCHO, benzene, toluene, xylene, fill the room, leading to higher concentration levels of these harmful VOCs (Volatile Organic Chemicals) concentration than outdoor environment [1]. As modern people spend more than 80% of their time indoor, such VOCs may cause chronic or acute diseases and the factors leading to SBS (Sick Building Syndrome) and SHS (Sick House Syndrome). Except VOCs, carbon dioxide (CO2) is another
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common pollutant gas. Excessive CO2 concentration in indoor environments can make the people lethargic and is unhealthy to the people staying in the environments for a long period of time. In addition, due to the global energy crisis in 1970, energy prices have been going up to the present, and energy consumption is facing challenges. To improve indoor air quality, air conditioning system is used to introduce outside air to dilute the indoor harmful substances and stale air, however, this has highly increased energy consumption for air conditioning systems.
There are three common ways to improve indoor air quality; these include source control, good ventilation systems to exhaust contaminated air, and air cleaning. Other methods include photocatalytic oxidation [2-7], photoelectrochemical approach [8-9], photosynthetic bioreactor [10], structural composite hybrid systems[11-12], and adsorption by using plants. Recently, using plants as a biofiltering system is widely advised. Plants not only serve as an ornament but they can also promote a better indoor air condition. This does not apply only to indoor environment but also the outdoor (Jim & Chen, 2008)[13]. Most plants transpire through their stomata. Gaseous pollutants could be absorbed into plant tissues through the stomata, together with CO2 in the process of photosynthesis, and with O2 in respiration. After entering the plant, transfer and assimilation could fix the pollutants in the tissues. During the process, plants absorb indoor air pollution.
For the study of air pollutant removal by plant absorption, Wood et al. (2002) [14] presented of an investigation into the capacity of the indoor potted-plant/growth medium microcosm to remove air-borne volatile organic compounds (VOCs) which contaminate the indoor environment, using three plant species. They found that the micro-organisms of the growth medium were the "rapid-response" agents of VOC removal, the role of the plants apparently being mainly in sustaining the root micro-organisms. The use of potted-plants as a sustainable biofiltration system can be promoted to improve indoor air quality. Orwell et al. (2004) [15] made a comparison of benzene removal rates by seven potted-plant species. They indicated that the removal rate of the species per pot ranged from 12-27ppm d-1, and demonstrated that micro-organisms of the potting mix rhizo-sphere were shown to be the main agents of removal. Liu et al. (2007) [16] screened ornamental plants for their ability to remove volatile organic compounds from air by fumigating 73 plant species with 150 ppb benzene. The 10 species found to be most effective at removing benzene from air were fumigated for two more days (8 h per day) to quantify their benzene removal capacity. Kim et al. (2011) [17] conducted a case study to the indoor air quality in a newly-built building and an aged building. They indicated, by the combined application of individual ventilation and indoor-plant placement, the concentration of formaldehyde can be reduced from 80.8 to 66.4 μg m-3 in the newly-built building and from 23.3 to 18.6 μg m-3 in the aged building. Pegas et al. (2012) [18] investigated the ability of plants to improve indoor air quality in schools. They indicated that, after 6 potted plants were hung from the ceiling, the mean CO2 concentration decreased from 2004 to 1121 ppm. The total VOC average concentrations in the indoor air during periods of occupancy without and with the presence of potted plants were, respectively, 933 and 249 μg/m3. The daily PM 10 levels in the classroom during the occupancy periods were always higher than those outdoors. The presence of potted plants likely favored a decrease of approximately 30% in PM10 concentrations.
Furthermore, plants were often applied to cooling of buildings through vertical greenery systems (VGSs). Alexandri and Jones (2008) [19] evaluated the thermal impacts on the performance of buildings for different vertical greenery systems (VGSs) and their immediate environment based on the surface and ambient temperatures. Fernández-Cañero et al. (2012) [20] studied the influence of an indoor living wall on the temperature and humidity in a hall inside a school in Spain. They indicated the cooling effect of the living wall was proven, with an average reduction of 4°C over the room temperature though maximum decrements of 6°C have been observed in warmer conditions.
In the past, less literature mainly focused on the issue of CO2 removal capacity of plants. Raza et al. (1991) [21] investigated the ability of certain succulent plants in absorbing CO2 in different types of rooms inhabited by household members. They indicated the number of persons, along with many other
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parameters, plays a prominent role in the maintenance of CO2 levels in indoor conditions. The plants grown in pots and placed in the bedrooms can lower CO2 levels to a considerable extent. Akbari et al. (2002) [22] indicated urban trees play a major role in sequestering CO2 and thereby delay global warming. He estimated that per-tree reduction in carbon emissions is about 10-11 kg per year, and planting an average of four shade trees per house of 50 m2 would lead to an annual reduction in carbon emissions from power plants of 16,000, 41,000, and 9000 t, respectively. Oh et al. (2011) [23] proposed an improved experimental method to reveal the ability of indoor plants to reduce CO2 concentrations, as well as to display the individual CO2 reduction characteristics of various indoor plants. In this study, we proposed to use the numerical and experimental methods to investigate the effect of the photosynthesis of the plants in a vertical garden on the indoor CO2 purification in order to afford useful references to the designers, and construct a useful theoretical modeling for the engineers to design comfortable environments. 2. Experimental and numerical methods 2.1 Experimental and numerical methods of CO2 absorption for individual tested plant
First, this study selected four common indoor plants including Dieffenbachia 'Camilla', Pachira aquatica, Chlorophytumcomosum, Spathiphyllum kochii as the experimental subjects to measure the CO2 absorption rate by photosynthesis. The purchased plants were placed in a room for several weeks to adapt to the indoor environment. The individual plant, small fan and CO2 sensor were placed in a closed and transparent acrylic case sized 0.5m in length, 0.5m in width and 1m in height, as shown in Figure 1. With given light and temperature, the diurnal variation was simulated. Photosynthesis will occur in plants under sunlight. The photosynthesis process will absorb CO2, by which the CO2 absorption rates of plants under different concentration levels can be determined.
To obtain the absorption rate distributions of tested plant under different CO2 background concentration levels , this study conducted 9 groups of experiments under different CO2 concentration by inputting into the box of CO2 concentration levels in the range from 500 ppm to 5000 ppm. CO2 and air in the box were fully mixed using a small fan, and continuous lighting was applied to produce the photosynthesis to absorb the CO2. The CO2 absorption rates of plants under different initial concentrations were determined by calculating the initial variation slop in time of the CO2 concentration degradation at the beginning of the experiments through linear regression method.
Then, according to the physical geometry of the box, this study constructed a three-dimensional geometric model for calculation. The acrylic box dimension of length × width × height is 0.5×0.5×1 (m), the dimension of plant pot is 0.1 ×0.1 ×0.1 (m), the plant dimension is 0.3×0.3×0.4 (m), and a fan sized 0.1×0.1×0.2 (m) is installed at the height of 0.7(m) above the bottom of the acrylic box. The corresponding boundary conditions were set according to real experimental status. In the simulation, the flow field and the concentration field inside the acrylic box are assumed as below:
1. The fluid is incompressible ideal gas. 2. Inner walls of the box are adiabatic. 3. The lighting equipment and its heat generation are overlooked. 4. The vegetation area is assumed as of porous medium which satisfies the Darcy effect. 5. The working fluids consist of air and CO2, and other factors produced by plants are neglected.
This study used the fluid dynamics software package FLUENT for simulation and established the model according to the experimental conditions. In addition, this study drew the computational domain and specified the corresponding types of boundary conditions before importing them into FLUENT for numerical simulation. The governing equations used in this article included a continuity equation, momentum equations, mass transfer equations and k turbulence model equations. The momentum equations are expressed in the generalized Darcy-Brinkman-Forchheimer model. The governing equations are stated here in indicial notation form valid for all coordinate systems [24, 25]:
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Continuity: Momentum:
Here j the fluid velocity components, respectively in the directions
j (j = 1, 2, 3 in 3-D problem), p
the average pressure. The physical properties in the above equations include the fluid density ρ, the fluid dynamic viscosity μ, the effective viscosity , the permeability K, the Forchheimer coefficient, also known as the form-drag term F, the porosity . Other parameters are the volumetric body force in the j direction. Forchheimer coefficient F depend on the geometry of the permeable membrane and thus cannot be measured directly nor determined analytically due to lack of model equation relating them to basic quantities [26]. For a packed-sphere bed, the permeability and the Forchheimer coefficient are related to the porosity and the diameter of the solid particle,
p , of the porous
p ,
213150
BF ,

C .
In the above equations, C , 2C , k , and are 0.085, 1.68, 0.7179 and 0.012,
respectively.
0
Concentration equation:
,
where diffD is the diffusion coefficient, and mS is the source term of the concentration equation.
By applying the boundary conditions, this study obtained reasonable settings according to the experimental parameters. The numerical calculation was conducted following the PISO rule, the turbulence model is standard k model, and the fan pressure was 8 Pascal. The plant area was assumed of porous medium at porosity at 0.9.
2.2 Experimental and numerical methods of indoor environmental control room
To test the indoor CO2 removal effect of plants in a large scale environment, this study established an indoor environmental control room with refrigerator boards as the external walls to reduce the impact of outdoor temperature changes on the indoor temperature. The indoor environmental control room is as shown in Figure 2. One wall of the room was an airtight soundproof glass door for easy access to the room and observation of the indoor situation during the experiments. The indoor space was divided into plant cultivation area and human activity area separated by a transparent glass sliding door. Three cyclic fans were installed on top of the glass sliding door and three return air inlets were installed at the bottom of the sliding door for the air exchange of the two areas. In the human activity area, a split-type air conditioner and humidifier were installed to control the indoor temperature and humidity to meet the thermal comfort of the person in the area. An external fan with switch was installed beside the air conditioner. In the plant cultivation area and the human activity area, the temperature sensors and humidity sensors were installed at the outlets of the cyclic fans to record the changes in the CO2 concentration and humidity of the indoor environment. An anemograph was installed to measure the air speeds around personnel. At the initial of the experiments, the airtight soundproof glass door of the environmental control room was open and the external fan was turned on. The measured outdoor CO2 concentration level was around 400 to 450 ppm. Until the indoor CO2 concentration level dropped below 500ppm, a person entered into the environmental control room to conduct experiments. The glass door was then closed to ensure its tightness to compare the concentration levels for indoor environmental control room with or without plants. The CO2 sensors were installed in the plant cultivation area and the area of human activity to record the data every five minutes during the experiments.
In the simulation, according to the physical geometry of the room, this study constructed a three-dimensional geometric model for calculation. The plant cultivation area accounts for 3.4 ×0.55 ×2.4 (m), and area of 3.4×0.4×1.65 (m) was the vertical garden. The dimensions of the three cyclic ventilators at the top of the transparent glass that separated the plant cultivation area and the human activity area were 0.5m×0.25m. The dimension of the three return air inlets at the bottom was 1.1m×0.25m. On the wall of the human activity area, there was an air conditioner sized 0.8m×0.3m×0.2m. At the bottom of the air conditioner, there was a lateral outlet sized 0.6m×0.05m. Besides the air conditioner, there was a 0.15×0.15(m) ventilation fan. The human was represented by three cubes. The bottom part of the body was sized 0.5m×0.5m×0.5m, the upper part of the body was sized 0.5m×0.3m×0.5m, and the head was sized 0.2m×0.3m×0.2m. There was an opening sized 0.05m×0.05m in the head as the outlet of CO2 of the breathing. The constructed model is as shown in Figure 3.
m j
diff jj
The conditions and assumptions of plants in this simulation were the same with the settings for individual plants. The porosity rates of the different plants were set as 0.5 in all cases. Considering the effect of the dense vertical garden on the air flow, the setting value of the porosity rate was smaller in order to simulate the resistance to the air flow passing through the vertical garden. In the simulation, the other boundary conditions were set as below. The pressure of the three cyclic fans at the top was set as 8 Pascal, the outlet pressure of the air conditioner was set as 20 Pascal. According to the experimental data of ASHEAR Standard 62, the amount of CO2 exhalation per person was 0.3L/min, the turbulence intensity in human mouth during breathing was 0.036, and the exhaling wind velocity was set as 0.17617m/s, with reference to Hyun and Kleinstreuer (2001) [30]. The initial indoor CO2 concentration level was set as 500ppm. 3. Results and discussion
The experimental results of CO2 absorption effect for the flour common indoor plants within two days are as shown in Fig. 4. In the experiments, in order to simulate the daytime and nighttime in the box, the lights turned on for 15 hours and turned off for 9 hours. The CO2 absorption rate of the individual plant was measured with the box for several days. The plants proceed to breathing effect during night, and proceed to photosynthesis effect during daytime. Thus, as shown in Fig. 4, in all cases, the CO2 concentrations within the box gradually increased at night and gradually decreased in daytime due to the breathing and photosynthesis effect of the plants. From the results, it can be seen that the plant of Spathiphyllum kochii is relatively more efficient in removing CO2 as compared with other plants. For the plant, the CO2 concentration can reach its minimum value of 150ppm at the end of the daytime. Hence, this study selected Spathiphyllum kochii for the experiment.
Figure 5 shows the variation of CO2 concentrations with time for Spathiphyllum kochii at different initial CO2 background concentrations while the light in the box turned on. With the increase in the CO2 concentration, the CO2 absorption rate of the individual plant at the beginning of the experiment also increases, and a longer concentration stable time is also required. Finally, a stable value at about 400ppm can be reached. After the measurement unit conversion, the analysis results were used to obtain the instant CO2 absorption rates of Spathiphyllum kochii under different concentration levels of CO2, as shown in Table 1. The instant absorption rate is defined as the concentration variation slop on time at the beginning of the measurement. As shown in Table 1, when the initial CO2 concentration level is higher, the instant absorption rate of Spathiphyllum kochii is relatively higher. The R2 values of the linear regressions in table 1 are all very close to 1 with the greatest deviation less than 0.0102.
The comparison of the experimental and simulation results of individual Spathiphyllum kochii was conducted under two different initial concentration of CO2, as shown in Figs. 6 and 7. As seen above, although different instant absorption rates according to the different concentration levels of CO2 obtained from table 1 are inputted in simulation, it cannot fully simulate the trend of gradually declining absorption rate of the CO2 under low concentration levels. However, while the initial CO2 concentrations are lower, the numerical concentration results are well consistent with the experimental ones as the calculating time less than 1500 minutes. This phenomenon indicates that the mathematical modeling of inputting the absorption rates according to different CO2 concentration levels into the porous medium using in this study can be effectively used to simulate the CO2 concentration decline in a living room.
Figure 8 illustrates the simulated air flow along a cross section inside the indoor environmental control room at X=1.7m. As seen in the figure, a large recirculating flow results in the human activity area and a small one results in the top of the plant cultivation area. These two recirculating flows may alleviate the air cycle between the activity area and cultivation area, resulting in longer time of
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lingering of CO2 in the areas. Figure 9 shows the flow field along a cross section at Z=1.8m. From the numerical results, the flow velocity surrounding the personnel is in the range of 0.2 to 0.4 m/s. The experimental measurement of flow velocity by using the anemograph is also in the range from 0.2 to 0.4 0.4m/s, which will not cause discomfort to people inside the room. Figure 10 illustrates the CO2 concentration distributions with time within the environmental room in the cases with plants and without plants in the room. From the results, it can be seen that, at the beginning of the measurement and simulation, the CO2 concentration is about 500ppm which equilibrated to the outside CO2 concentration. In the case without plants in the room, due to the CO2 exhalation of the personnel in the room, the CO2 concentration within the room gradually increases with time and attains to a high value about 2700ppm after 2.5 hours in the experiment. In the case with plants cultivating in the room, the CO2 exhalation rate of the personnel through breathing effect was greater than CO2 absorption rate of the plants through photosynthesis effect. Thus, the CO2 concentration within the room also gradually increases with time. However, after 2.5 hours in the experiment, a CO2 concentration value about 2350ppm was attained, which was 350ppm less than that in the case without plants. A longer experimental time results in greater difference in CO2 concentration level between the two cases. From the figure, it also can be seen that the numerical results were well consistent with the experimental measured results, despite of the slight differences between the experimental and the simulation results. The differences may be caused by the amount of exhaled CO2 obtained from previous studies, rather than measurements, and the amount of exhaled CO2 may differ from person to person.
Figure 11 illustrates the comparison of the purification effects under three different ventilation rates (ACH) with and without plants in simulations. ACH is defined as the times the air within a defined space is replaced in one hour. The simulations depend on the introduction of external air to improve the indoor air quality with the help of indoor planting. The indoor concentration level of CO2 with or without plants is compared when external air is introduced. From fig. 11, it can be seen that the initial CO2 concentrations within the room were 500ppm in all cases, and after 1 hour ventilation operation, the concentrations within the room could approach to stable values. Due to better ventilation effect in the case with higher ACH value, the stable CO2 concentration is much less in comparison to the case with lower ACH value. For the cases with the same ventilation effect, the stable CO2 concentrations of the case with cultivating plants within the room was always about 30ppm less than that of the case without plants. This indicated that, while the ventilation system was used, about 30ppm CO2 concentration can be absorbed by the cultivating plants. It can be conjectured that, because the dilution effect of the ventilation system is more effective in quantity and time than the absorption effect of the cultivating plants, the absorption effect of the plants is not obvious accompanied with a ventilation system. 4. CONCLUSION
In this study, a theoretical modeling was developed. By inputting the absorption rates under different environmental CO2 concentration levels into the theoretical model, CO2 concentration distribution within an environmental room with a vertical garden can be simulated. The numerical results were well consistent with the experimental measured results. The results showed that, after 150 minutes, 13% of CO2 generating from the human breathing can be absorbed by the 240 plants. The experimental results proved that indoor planting can be applied to purify indoor air; however, the effect in not severe unless a great amount of plants was cultivated in the vertical garden. Vertical gardens can also be used to reduce the air change rate of the ventilation system in a living room and are beneficial to the energy saving of the ventilation system.
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Table 1 Instant absorption rates under different CO2 concentration levels.
CO2 (ppm) linear regression R2 value absorption rate
5000 y= -19.278x +4988.5 R2= 0.9898 4.63E-7 /m3s
4500 y= -14.732x +4528.5 R2 = 0.9957 3.54E-7 /m3s
4000 y= -11.588x +4024.7 R2 = 0.9988 2.78E-7 /m3s
3500 y= -11.008x +3522.2 R2 = 0.9988 2.64E-7 /m3s
3000 y= -10.635x +2998.2 R2 = 0.9992 2.55E-7 /m3s
2500 y= -8.4239x +2517.7 R2 = 0.9992 2.02E-7 /m3s
2000 y=-7.5396x +1996.2 R2 = 0.9959 1.81E-7 /m3s
1500 y=-7.211x +1500.9 R2 = 0.9989 1.73E-7 /m3s
1000 y =-6.2541x +994.61 R2=0.9971 1.50E-7 /m3s
Figures
Fig. 1 The CO2 absorption rate experiment of individual tested plant.
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Fig. 2 Three-dimensional geometric model of the indoor environmental control room.
Fig. 3 Indoor environmental control room in experiment.
plant cultivation area
human activity area
split-type air conditioner
Fig. 4 Change in CO2 concentration of different kinds of plants.
Fig. 5 Variation of CO2 concentrations with time for Spathiphyllum kochii at different initial CO2
background concentrations.
Time (minutes)
C O
Fig. 6 Comparison of experimental and simulation results of individual Spathiphyllum kochii under initial CO2 concentration at 3500ppm.
Fig. 7 Comparison of experimental and simulation results of individual Spathiphyllum kochii under initial CO2 concentration at 2500ppm.
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Fig. 8 Indoor flow field in the cross section at X=1.7m.
Fig. 9 Front view of the flow field in the human activity area at Z=1.8m.
plant cultivation area
split-type air conditioner
return air inlet
Fig. 10 Comparison of measured CO2 concentrations with or without plants.
Fig. 11 Comparison of concentration level of CO2 for different ACH with or without plants.
Time (min)

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