Nighttime indoor air temperature is one of the most important indicators for structural renewal and environmental control in Chinese solar greenhouses (CSGs). It is often required for the thermal contribution of heat transfer to the air temperature at nighttime. In this study, a qualitative analysis was conducted on three events influencing the nighttime air temperature: convective heat transfer between surfaces and room air, condensation on the south roof surface, and cold air infiltration between the interior and exterior. Three typical CSGs were also selected: the strawberry, the tomato, and the empty greenhouse. Specifically, the strawberry/tomato and empty greenhouses were used as 8 and 12 m spans, respectively. The strawberry and tomato greenhouses were employed for soil and substrate cultivation, respectively. The outdoor parameters were measured, including solar radiation, air temperature, relative humidity, and wind speed, whereas the indoor ones included air temperature, relative humidity, and surface temperatures. All the indoor surfaces were contacted directly with the room air, such as the surfaces of the north wall, north roof, south roof, soil ridge, soil furrow, and the crop leaf. The heat transfer was calculated for the south roof condensation and the indoor-outdoor cold air infiltration. The convection coefficients were derived for the convective heat transfer between the north wall and the ground surfaces and the air. The results showed that the largest sensible heat supply was the convection heat release to room air at night from the ground (ridges and gullies for cropped CSGs). The convection heat values were 63 and 55 W, respectively, for the unit length of the strawberry greenhouse on sunny and cloudy days from 18:00 to 07:00 the next morning; The tomato greenhouse averaged 53 W for sunny and cloudy days; While the empty greenhouse reached 145 and 120 W for sunny and cloudy days, respectively. The average convective heat release from the north wall surface was relatively low on sunny days. The strawberry, tomato, and empty greenhouse were 26, 24, and 15 W, respectively, where the average convective heat release on cloudy days was roughly half that of sunny ones. Averaged convective heat released from ridges and gullies at night on sunny and cloudy days in cropped greenhouses accounted for 50% of the total average convective heat release, while that from the ground of the empty greenhouse accounted for 90% to 95% on sunny or cloudy days. The averaged convective heat released from the crop canopy at night contributed about 30%-50% heat supply. The maximum heat loss at night was the convection or the condensation from the south roof. The findings can be expected to determine the key influencing factors of greenhouse nighttime air temperature.

Solar radiation can serve as the primary internal energy source for the winter production in the passive Chinese solar greenhouses (CSGs). The acquisition and storage of solar energy are significantly influenced by the complex, dynamic shadows cast by the greenhouse envelope (particularly the gable walls) and the growing crops inside. Therefore, it is often required to accurately predict these shadings for the thermal environment and energy efficiency of the CSGs. In this study, a dynamic analytical model was established for the shadow area of the direct solar radiation in CSGs. The dynamic evolution of the shadow areas was determined to incorporate the structural parameters (span, ridge height, length, and azimuth), geographical factors (latitude and longitude), temporal variables (solar altitude and solar azimuth), and crop canopy height. A systematic investigation was implemented to quantitatively characterize the synergistic shading between the gable wall geometry and the dynamically changing crop canopy on the key heat storage surfaces, specifically the ground and north wall. The physical analytical solutions were derived for the shadow boundaries of the curved gable surfaces, thereby revealing the precise mechanism of the shadow superposition. The geometric simplification was employed to balance the computational accuracy and efficiency. Among them, the shadow of the gable wall on the ground was approximated as a triangle, while its shadow on the north wall was approximated as a trapezoid. Additionally, the crop population was assumed to be a homogeneous rectangular prism, according to the average canopy height. Both field-measured data and simulations were selected to validate the theoretical derivation using the commercial software SketchUp. The experimental CSG was 60 m in length, 10.3 m in width, and 5 m in ridge height, with a north wall height of 3.2 m and an azimuth of 5° west of south. The south roof curve of the greenhouse was composed of two tangent arcs. Observation experiments on the gable wall and crop shadow were conducted on December 18, 2023, and December 11, 2024, from 09:00 to 12:00, respectively. Results indicated that in the gable wall shadow, the average relative errors between calculated and measured values were 0.3% on the ground and 6.8% on the north wall. In crop shadows, the calculation on the rear aisle perfectly matched the measurement. The average relative error on the north wall was 1.6%. A comparison was made between the theoretical derivation and SketchUp simulation. The maximum relative errors for the gable wall shadows were 5.3% (ground) and 6.1% (north wall), with the average relative errors of 2.3% and 5.2%, respectively. The theoretical derivation for the crop shadows on the rear aisle was consistent with the software simulations. The future research directions were also outlined, including the north roof shading incorporation, boundary precision via high-precision 3D scanning or image recognition, and numerical integration to balance the computational efficiency with the accuracy. In conclusion, the discrete numerical simulations provided the mathematical solution. The computational efficiency was improved after the geometric simplifications. A robust theoretical tool was offered for the precise quantification of solar energy acquisition. These findings can also provide the reference data for the solar energy utilization facilities and the greenhouse structural optimization for thermal performance.