Besides the velocity distribution, the effect of temperature is also a critical parameter for determining convective flow. Fig. 8 shows the two-dimensional temperature distributions in the x-y plane along the middle of the z-direction for all eight cases at a mass flow rate of 0.3 kg s−1. In our analysis, the temperature of the inlet flow is lower than that of the exit flow due to the heat generated from the LED light. For case BC, the inlet is located near the bottom and the exit is near the top. Due to the density difference, the exit warm stream tends to flow up. This allows the flow to reach the topmost tray more easily and, therefore, achieves more uniform temperature distribution among all trays. Combining the inlet flow along the long side of the tray, the helical flow effect, and the buoyancy, case BC is able to reach the maximum OU of 91.7%. Fig. 9 summarized the velocity and temperature contours for case BC at an inlet mass flow rate of 0.3 kg s−1. The velocity pro- files in Fig. 9a clearly show the spiral effect above each cultivation tray and the local velocity is close to the optimal speed of 0.4 m s−1. In addition, the temperature shows an increasing trend from bottom to top as the flow helically passing through the crops and moving towards the outlet.he distributions of temperature and gas species, such as water vapor and CO2, play an integral role in photosynthesis which, in turn, influences the quality of plant and its growth. Therefore, maintaining these critical parameters in a reasonable range to ensure reliable and efficient production is essential to environmental control of an IVFS. Evaluating the distribution of these parameters can also provide the effectiveness of inlet/exit location. It should be noted that the parameter OU provides an overall assessment of the air flow velocity over planting trays. An optimal design is to achieve desired local temperature and species distribution while maintaining high OU values in an IVFS. In the following discussion,micro green growing racks the four cases with highest values of OU at their corresponding mass flow rates are studied and compared to the baseline case AB.
Since CO2 is a reactant of photosynthesis, increasing CO2 concentration usually leads to enhancement of crop production. Reports show that increasing the CO2 concentration from the atmospheric average of 400 ppm to 1500 ppm can increase the yield by as much as 30%. In this IVFS analysis, the CO2 level of the inlet mass flow rate is increased by a CO2 generator to be 1000 ppm . Since the consumption rate of CO2 through the exchange zones is fixed, higher overall average CO2 concentration through the system is desirable. Fig. 10 shows the comparison of the average CO2 concentration between the highest OU cases and the baseline case AB at different inlet mass flow rate. A few general trends of CO2 concentration can be observed from Fig. 10. First, the CO2 concentration increases with inlet flow rate due to increasing supply of CO2 molecules. In addition, tray 1 has the highest CO2 concentration because most of the cold fresh inlet air dwells near the bottom of the IVFS due to the buoyancy effect. In contrast, tray 3 has the lowest CO2 concentration because the fresh inlet air has the highest flow resistance to reach tray 3due to the combination of sharp turns and buoyancy effect. This is particularly true at low inlet flow rates and when the inlet is located on the top, which lead to low flow circulation as cold inlet air flows downward directly. As a result, BC, BA, and DA at 0.3, 0.4, and 0.5 kg s−1, respectively, have relatively high CO2 concentrations. Even though the baseline case AB at 0.5 kg s−1 has the highest CO2 concentration, its OU is too low to be considered a good design. Temperature is also a critical parameter to control and monitor because it directly affects both relative humidity and plant growth. The temperature distribution in the system depends on the inlet/exit location, inlet mass flow rate, and amount of heat. Since the inlet temperature and heat flux conditions are fixed, the exit temperature increases with decreasing inlet mass flow rate.
Fig. 11 shows a comparison of the average temperatures of the higher OU cases and the baseline case AB at different inlet mass Fig. 12. Comparison of the average RH over each tray between the best OU cases and the baseline case at each inlet mass flow rate condition. flow rates. Three phenomena can be observed from the baseline case AB results at different inlet mass flow rates: the flow above tray 4 always has a lower temperature than that above tray 3 since it is closest to the inlet region; at low inlet mass flow rate , the flow above tray 3 has the highest temperature due to buoyancy effect; and at high inlet mass flow rate , the flow above tray 1 has the highest temperature because it is located closest to the exit. The temperature distribution for case AD is very similar to that of the baseline case due to similar inlet/exit location orientations so that buoyancy is the dominant effect at low inlet mass flow rate . On the other hand, cases BC, BA, and DA have different temperature distributions than the baseline because the inlet and exit are located near the bottom and the top, respectively. Therefore, the temperature of tray 1 is much closer to the inlet temperature and the temperature increases with height except at high mass flow rate where the temperature above tray 4 can be lower than that above tray 3. This is due to strong helical flow mixing inside the room at high inlet mass flow rate, which also explains that the temperature uniformity increases with increasing inlet mass flow rate. Previous studies show that the optimal germination temperature is between 294 K and 297 K. As can be observed from Fig. 11, cases BC, BA, and DA at 0.3, 0.4, and 0.5 kg s−1, respectively, exhibit the desirable temperature range and distribution for lettuce growth. Nevertheless, compared to the baseline at each mass flow rate, case BC at an inlet mass flow rate of 0.3 kg s−1 exhibits the most significant average temperature reduction . Furthermore, the average temperature of case BC at 0.3 kg s−1 is lower than that of the baseline case at 0.5 kg s−1, which demonstrates the design effectiveness of case BC. Relative humidity represents the water vapor partial pressure in the IVFS, which has a strong effect on crop growth. It is reported that the ideal RH for lettuce and leafy greens should be between 50–70%. High RH can cause pathogen issues, like mildew and botrytis, and low RH can induce an outer leaf edge burn due to dryness.
Therefore, the inlet RH is set to be 85% in this IVFS design. The comparison of RH for each tray between the highest OU and the baseline cases at different inlet mass flow rates is shown in Fig. 12. It can be observed from the baseline case that RH increases with increasing inlet mass flow rate due to the increase of water supply and decreasing room temperature. RH can be calculated from the ratio of the partial pressure of water vapor to the saturation vapor pressure at a given temperature. Therefore, RH can be increased by either increasing water partial pressure or decreasing temperature. In our study, temperature is the dominant parameter because the gas species composition in the system does not vary significantly. Therefore, the trend of RH distribution agrees with that of the temperature distribution in Fig. 11.Under such conditions, tray 3 has higher temperature and RH than tray 4. To explain this behavior, the results from the CO2 distribution analysis need to be considered. At the lowest inlet flow rate, the flow has lowest circulation and tray 3 is near the end of the fresh inlet flow stream. Therefore, tray 3 has the lowest CO2 and highest H2O concentrations due to photosynthesis as shown in Figs. 10 and 12. Overall, the average RH distributions for cases BC and BA fall within the optimal range.Modeling the dynamics of airborne particulate matter is a powerful tool for understanding how building design, occupancy, and operation affect human exposure to airborne particles . Key physical processes affecting indoor particles such as penetration, deposition, resuspension, filtration,plant grow rack and indoor emissions can each vary strongly with particle size . Size-dependent particle behavior often can be associated with specific chemical and biological constituents of particulate matter provided that the particle size distribution of the constituent is known. Due significantly to limitations of culture-based sampling and analysis that have constrained efforts to study the full microbial ecology of air , modeling tools for simulating indoor aerosols have not been systematically applied to the biological components of particulate matter. As a consequence, our knowledge of microbes in indoor air lags behind that of total particulate matter and its chemical constituents, even though the impacts of biological aerosol exposure on human health and well being are considerable . One important knowledge gap is in understanding how human occupancy results in the emission of bacterial and fungal particles into indoor air. Observational and mechanistic studies have demonstrated the importance of human occupancy as a source of total aerosol mass . More specifically, in the absence of combustion, cooking, and smoking, evidence indicates that resuspension can be a major source of total airborne particulate matter in occupied indoor environments, thereby suggesting a potentially important emission mechanism for indoor biological particles.
In addition, direct human emissions such as skin shedding , talking, coughing, and sneezing may play a significant, but less well-characterized role influencing the content and character of indoor microbiological aerosols. Investigators have previously noted both the significant content of desquamated human skin cells in aerosols in occupied settings , as well as the presence of bacteria, including Staphylococcus, Propionibacteria, Corynebacteria, and enteric bacteria, that are typically ascribed to human micro-flora . However, the size resolved emission rates of bacteria and fungi due to human occupancy of indoor environments have not been reported, which limits modeling efforts to predict the fate and transport of these important components of particulate matter. The goal of this research is to determine the human associated emission rates of bacteria and fungi in an occupied classroom. Particle size distributions of total airborne particulate matter, bacterial genomes, and fungal genomes were measured under occupied and vacant conditions, and a material balance model was applied to determine the per person emission rates of bacterial and fungal size-fractionated particles attributable to occupancy. Bacterial phylogenetic libraries were produced for aerosols sampled under occupied conditions, and the size-resolved emissions of human-associated bacterial taxa were estimated. The size-resolved emission rates and bacterial population characterization produced here represent an important step toward applying models to make inferences about the distribution of and human exposure to bacteria and fungi in occupied indoor settings.A university classroom located on the ground floor of a five-story building in the northeastern United States was selected as the test room. This location was selected because of consistent and readily characterized occupancy levels, along with proximity to the research team and relative ease of securing access. Experiments were conducted in the fall of 2009 and included 4 days when the classroom and building were occupied, and 4 days when the classroom and building were vacant. On occupied days, the room was frequently accessed with three to five classes per weekday. For the four test days when the room was occupied, the room held an average of 4.7 people during a total of 22.2 h of sampling for a cumulative occupancy of 104.2 person hours. Classes were conducted in a lecture format. Students typically sat in desks and the instructor stood or moved throughout the front half of the classroom. Although the floor is vacuumed regularly, no cleaning was conducted at least 1 day before or during the experimental days. The volume of the classroom is approximately 90 m3 , and the entire floor area was covered by lightly worn commercial medium pile level-loop carpet. No mold or moisture problems have been reported for this building, and none have been observed during sampling.