Title Page
Abstract
Contents
Ⅰ. Introduction 14
Ⅱ. Literature Review 21
1. Three dimensional heat simulation model 21
2. The cooling effect of green infrastructure 24
Ⅲ. Scope of study 27
1. Study process 27
2. Spatial, temporal scope 28
Ⅳ. Methods 29
1. Three-dimensional urban surface model 29
1.1. Model description 29
1.2. Radiative transfer 30
1.3. Main parameters 32
1.4. Energy balance of leaf 36
2. Model validation and application 46
2.1. Validation 46
2.2. Simulation 51
2.3. Green infrastructure scenario 53
3. Evaluation of Effectiveness of storage system with latent heat flux for maximizing thermal performance of green roof 56
3.1. Climate conditions 56
3.2. Experimental set-up 57
3.3. Measurements 59
3.4. Statistical analysis 60
3.5. Heat balance 61
Ⅴ. Results 63
1. Three-dimensional urban surface model 63
1.1. Model performance 63
1.2. Urban heat simulation 72
1.3. MRT 73
1.4. Cooling effect of tree planting scenario 76
2. Effect of storage system of Blue Green roof for maximizing cooling effect 79
2.1. Upper surface temperatures 79
2.2. Lower surface temperatures 81
2.3. Performance evaluation 82
2.4. Heat balance 86
Ⅵ. Discussion & Conclusion 89
1. Developing a 3D urban surface model for accurate thermal evaluation with simple input 89
2. Planting strategy for maximizing cooling effect of urban green infrastructure 92
3. Blue green roof strategy for improving thermal performance in outdoor and indoor spaces 94
Ⅶ. Bibliography 98
Abstract in Korean 117
Appendix 121
Table 1. Values, units, and sources of the parameters for resistances 43
Table 2. Meteorological data for simulation 52
Table 3. Climatic data of Seoul, South Korea (2022) 57
Fig. 1. Previous urban heat simulation model 23
Fig. 2. Study scope 27
Fig. 3. Model flow for calculating the mean radiant temperature 29
Fig. 4. Algorithm for calculating the three main parameters 32
Fig. 5. Four cases of surface relationship for calculating view factors. 33
Fig. 6. Validation site for sky view factor 46
Fig. 7. Validation site for radiation 47
Fig. 8. Validation site for surface temperature. 48
Fig. 9. Validation site. 49
Fig. 10. Three streets distinguished by the angle of rotation. 51
Fig. 11. Street tree planting scenario. 53
Fig. 12. Green wall planting scenario. 54
Fig. 13. Schematic cross-section of the studied roof types with sensors for environmental monitoring. 58
Fig. 14. Experimental site. 60
Fig. 15. Sunlit/shaded algorithm validation 63
Fig. 16. Validation of sky view factor. 64
Fig. 17. Measured data in mid-rise residential area at 1 June, 2018. 65
Fig. 18. Measured data in high-rise commercial area at 28 April, 2018. 66
Fig. 19. Validation of surface temperature. 67
Fig. 20. Model validation results showing estimated MRT in sunlit and shaded areas. 68
Fig. 21. Sensitivity test of averaged MRT in Street 2 at 1300 LST 70
Fig. 22. Model output set. 72
Fig. 23. Three dimensional result of USM 72
Fig. 24. Changes in mean radiant temperature at the sidewalks (red: northern, orange: southern) according to time and street. 74
Fig. 25. Different shadow orientations formed according to the rotation angles 75
Fig. 26. Changes in average mean radiant temperature with time due to the cooling effect of trees 76
Fig. 27. Mean MRT according to planting height of green wall 77
Fig. 28. Mean MRT according to planting area of green wall 78
Fig. 29. Variations in upper surface temperature. 79
Fig. 30. Variation in the lower surface temperatures. 81
Fig. 31. Differences in surface temperatures. 83
Fig. 32. Summary of thermal performance of roof type. 85
Fig. 33. Energy partition of solar radiation according to roof type. 86