• Journal of Bio-Environment Control
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• v.29 no.1
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• pp.52-61
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• 2020

The natural change of winter night temperature from 00:00 to 04:30 O'clock with the different height of thermal screen in a venlo type glasshouse (W59×L68×H5.9 m) was studied using computational fluid dynamics (CFD). At the early stage of CFD analysis, the room temperature decrease of glasshouse with the 5.9 m height of thermal screen were faster than it with the 4.1m height of thermal screen, but at 2 hr after analysis it was slower than in it with the 4,1m, the temperature difference was 0.6℃ after 4 hr. If we consider that turn on the heater when the temperature were decrease below 13℃ at 1hr after CFD analysis, it is good for energy saving in the glasshouse with the 4.1 m height of thermal screen rather than in it with the 5.9 m height, because of the temperature decrease were slow during 2 hrs after analysis. The airflow at the height of 2 m which were grown tomato were fast and wide in the glasshouse with the 5.9 m height thermal screen rather than in it with the 4.1 m, the speed difference was 0.034m·s^-1 at 1hr after CFD analysis. The effect of temperature decrease in summer season were compared with the different height of shading screen from 12:00 to 14:30 O'clock. The height of shading screen were 5.7, 3.9 m, the gap of it were 30%. The air-inflow quantity by the fan with duct at lower part of venlo glasshouse was 0.67 ㎥·s^-1 until 1hr and to increase 3 times of it from 1hr after analysis. The roof window were open 100%. Until 1hr of CFD analysis, the temperature in the 30% open of shading screen was 0.9℃ higher than in the none shading screen. From 13:00 O'clock when the air-inlet quantity to increase 3 times, the temperature in case 30% gap of shading screen were decreased compare with the none shading screen, the temperature difference was 0.5℃ at 14:30 O'clock. The temperature on the floor surface in case 30% gap of shading screen were lower with it's height increase, the temperature difference was 8℃ compare with none shading screen. The relative humidity difference were insignificant by the height and gap of shading screen.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Journal of Bio-Environment Control
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• v.31 no.2
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• pp.90-97
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• 2022

This study was carried out to investigate the effect of side vent heights on temperature and relative humidity inside and outside the single-span plastic greenhouse (W: 7 m, L: 40 m H: 3.9 m) during natural ventilation. Four different heights (120, 100, 80, 60 cm) of the side vent were used as an experimental condition. Variations of temperature and relative humidity inside and outside the greenhouse and the differences between heights were compared by using one-way ANOVA. In the daytime, the difference in temperature between inside and outside the greenhouse was dropped from 14.0℃ to 7.1℃ as the side vent height increased. The temperature difference in the nighttime was less than 0.2℃ regardless of the height. One-way ANOVA on the temperature difference between heights presented that the statistical significance was founded between all of the combinations of height in the daytime. The difference in relative humidity between inside and outside the greenhouse was grown from -13.8% to -22.2% with a decrease in the side vent height. The humidity difference in the nighttime was less than 1% regardless of the height. One-way ANOVA on the humidity difference revealed that most of the side vent heights showed significance in the daytime but between 100 and 80 cm was not significant. It seemed because the external air became cooler during the experiment with a height of 80 cm. Conclusively, this study empirically demonstrated that the higher side vents resulted in the decrease of differences in temperature and relative humidity between inside and outside the greenhouse, and also the effect of side vent height was statistically significant. This study may be helpful for deciding the height of the side vent effective for controlling temperature and relative humidity in a single-span greenhouse during natural ventilation.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.604-617
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• 2018

As the depletion of forests became more widespread due to the increase in the number of roads, the research was conducted on the relationship between temperature and humidity in the forests, assuming that the forests around the roads were affected. Through the forest monitoring, the temperature and humidity of coniferous forests and broadleaf forests in Sedong and Gongju areas were observed at three point of 10m, 20m and 30m from the road boundary to the inside of the forest, respectively. In Yeongdong area, for more reliable results, it was observed from the point of 0m, 10m, and 20m. During the study period, so it was expected the change in tree growth was small, the change of temperature and humidity inside the forest by the road was compared with the temperature and humidity from the road to the inside of the forest from September 2017 to January 2018, the changes of temperature and humidity inside the forest due to linear development such as roads were quantitatively analyzed. Using the HOBO data logger (MX2301, Onset Corp.), the temperature and humidity changes of each site were measured, and the average of the changes have been analyzed monthly. In the case of Gongju coniferous forests in September 2017, the average weekly temperature is $0.57^{\circ}C$ higher than the forest outside from the forest boundary and $1.23^{\circ}C$ higher than the inside of the forest, at night in November 2017, in Sedong broadleaf forests. That is, the ability to control the temperature and humidity of the forests along the road was larger and less variable as the distance from the road boundary to the inside of the forest increased. In this study, it is considered that the high degree of change in temperature and humidity of the forest and the surrounding area due to artificial linear development such as roads will affect the growth of trees. This results could serve as a basis for studying the quantitative scope of linear development affecting forest growth and for managing forest change caused by linear development.

• Journal of Bio-Environment Control
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• v.5 no.2
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• pp.215-235
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• 1996

The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad ＆ fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH＋7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad ＆ fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).