Efficient control of building heating systems relies on accurate and spatially comprehensive indoor temperature monitoring. However, conventional sensor deployments suffer from limited spatial coverage, high cost, and occupant intrusiveness. This study proposes a non-intrusive indoor temperature estimation method using unmanned aerial vehicle-based infrared thermography (UAV-IRT). Firstly, optimal UAV measurement parameters-including solar radiation, wind speed, UAV-to-window distance, and measurement location-were systematically determined. Subsequently, representative reference rooms within apartment units were identified based on orientation and room size, revealing that south-facing large rooms provided the highest inference accuracy. Principal component analysis was further applied to determine baseline user units, demonstrating that horizontal temperature variability was minimal within floors, whereas significant vertical temperature gradients required at least one representative user per floor. Field experiments validated that the proposed method, relying on infrared measurements from only 8 % of the building's rooms, achieved a mean absolute error of 0.70 degrees C, with over 95 % of room-level predictions falling within +/- 2 degrees C. This study provides a practical and efficient monitoring solution, offering significant potential for scalable indoor environmental assessment and intelligent heating management in buildings.

Clothing adjustment is commonly treated as a low-cost adaptive mechanism in energy-efficient building operation and is frequently invoked to justify widened indoor temperature setpoints. However, whether clothing-based adaptation is effectively cost-free under real operating conditions remains unclear. Using large-scale field data from the Chinese Thermal Comfort Database across 49 cities, this study estimates the average and conditional causal effects of clothing insulation on thermal comfort acceptability using a domain-informed causal machine learning framework. A directed acyclic graph is used to represent environment–behavior–comfort interactions, and Double Machine Learning is applied to address high-dimensional confounding. The results indicate a small but statistically robust negative average effect: a 1-clo increase is associated with an approximately 4 percentage-point reduction in comfort probability. The effect is also highly context-dependent, becoming more negative in naturally ventilated buildings and among older occupants, while approaching zero near thermal-neutral conditions. These results suggest that clothing adjustment should be treated as a finite adaptive resource rather than a cost-free comfort buffer, and that explicit consideration of behavioral cost can support more robust energy-efficient building operation.

The varied roughness of building clusters makes the urban wind rather complex. The current exponential wind profile may not accurately capture the spatial variation of urban wind. This study aims to develop urban morphology-based exponents for the exponential wind profile model to improve the assessment of wind energy in urban areas. The Weather Research and Forecasting (WRF) model, combined with Local Climate Zones (LCZ), was used to simulate wind fields, validated with field data. The study then analyzed wind field distribution urban morphology, introducing wind shear coefficients adapted for various urban morphologies. The results were compared with the existing wind shear coefficients by assessing the wind power potential. The results indicated that wind shear coefficients increase from urban outskirts to centers, with minimal seasonal variation. The annual average wind shear coefficient peaked at 0.50 in Harbin and 0.49 in Guangzhou. Building density, height, and plot ratio (PR), significantly impacts wind fields. PR showed the strongest correlation with the wind shear coefficient as the determining factor. Wind shear coefficients for low (0.0-1.0), medium (1.0-2.0), and high PR zones (2.0+) were 0.33, 0.38, and 0.41 in Harbin, and 0.30,0.35, and 0.40 in Guangzhou, respectively, providing more accurate estimate of urban wind speed.

The spatial heterogeneity of building clusters creates a highly complex urban wind environment, making it difficult for traditional wind profile models to capture the spatial characteristics of urban wind. This study aims to investigate the impact of complex urban morphology on the wind environment characteristics, and thereby to establish an urban wind profile at local scale. Firstly, the Weather Research and Forecasting (WRF) model combined with Local Climate Zone (LCZ) method was used to simulate the urban wind field. Subsequently, the simulated data was validated against wind speed data from meteorological stations and sounding data. Finally, the logarithmic law wind profile parameters were analyzed corresponding to each LCZ type (LCZ1LCZ6) within varying spatial extent by statistical methods, and thus the optimal parameters were obtained applicable to these types. The results indicated that roughness length and friction velocity were strongly correlated with the LCZ type; based on the spatial layout, the optimal ranges for each LCZ type were determined, with roughness length ranging from 5.70 m to 11.95 m and friction velocity ranging from 0.783 m/s to 0.883 m/s. Logarithmic law wind profiles were established applicable to each LCZ type.

With China’s socio-economic growth, the demand for enhanced residential comfort in northern urban areas has surged. Traditional district heating systems often fail to meet modern users’ diverse needs, leading to inefficiencies and significant heat loss. This paper investigates optimization and transformation methods for demand-side-oriented heating systems. We propose key design parameters that facilitate a shift from source-end to demand-end dominance and develop a bi-level planning model for operational scheduling. The model integrates building thermal storage and adjustable user temperature ranges to optimize multi-thermal source systems. Key contributions include identifying critical renovation parameters and establishing the relationship between temperature control range and system capacity. Results demonstrate that the optimized system provides interval temperature control for 96.02% of the heating season and increases the full-load duration ratio of heat source equipment by 29.54% compared to traditional systems. These improvements enhance operational efficiency, reduce heat loss, and better align heating provision with users’ dynamic thermal demands. This research offers a robust theoretical foundation and practical guidelines for transitioning to demand-end dominated district heating systems, contributing to more sustainable and responsive heating solutions.

The natural ventilation strategy is gaining increasing attention from architects due to its advantages in reducing energy consumption and maintaining a healthy indoor environment. For supertall buildings, the vertical vari-ation in outdoor meteorology has inspired us to explore the energy-saving potential by adopting natural ventilation strategy. This study investigates the impact of vertical variation in urban meteorology on the natural ventilation potential (NVP) of supertall buildings based on numerical simulation and field observation. Firstly, the Weather Research and Forecasting (WRF) model is used to simulate the urban meteorology of the study region by integrating the local climate zone (LCZ) map. Next, meteorological data from sounding experiments by unmanned aerial vehicle (UAV) and monitoring stations are used to validate the simulated result, and thereby to explore the vertical meteorology in urban area. Finally, the vertical NVP in supertall buildings is quantitatively assessed considering the impact of LCZ in urban areas based on thermal comfort models. The findings reveal that atmospheric temperature decreases approximately linearly with increasing altitude, with a maximum temper-ature gradient of up to-0.82 degrees C/100 m. Static models underestimated the annual natural ventilation hours (NVHs) by at least 348 h compared to the adaptive thermal comfort model. Compared to low-density building regions, the higher NVP is indicated in high-density building regions. This study aims to illustrate the importance of considering the vertical variations of urban meteorology, and is expected to assist architects and policy makers in quantifying the energy saving potential of natural ventilation in supertalls.

Urban wind energy is gaining increasing recognition for its environmentally friendly nature, particularly in the context of energy shortages. Predicting wind speed in urban environments is challenging due to the varying roughness and drag caused by obstacles on the ground. The complexity of urban morphology significantly disrupts the wind field and hampers the utilization of wind energy. This study aimed to investigate the diverse impacts of highly heterogeneous urban environment on the urban wind energy by innovatively establishing spatially varying power law wind profiles. Firstly, long-term LIDAR observations were conducted to measure the vertical wind profile in the study area. Then, a high-resolution LCZ map was created and integrated into the Weather Research and Forecasting (WRF) model to reproduce the urban wind field, which was validated using the observational data. Finally, the spatial characteristics of the urban wind field and wind energy were analyzed based on 3 representative points and the urban LCZ categories. The results show that the average power law exponents of each LCZ classification ranges from 0.29 to 0.75, with the average power law exponent of the high-volume building area being larger than 0.6. The highest wind power density in the study area can reach 343.3W/m2 at 200m height. Further, significant negative correlation coefficients were found between wind power density and building height, as well as building density, with values of approximately −0.6 and −0.35, respectively. Overall, the high-volume-ratio built-up areas with higher roughness had a notable impact on the wind speed by increasing the power law exponents. These spatially varying wind profiles are expected to provide technical support for the utilization of urban wind energy.

The natural cooling capacity of the environment can effectively reduce the building energy consumption by natural ventilation (NV). For architects, developing NV strategies requires a comprehensive understanding of the distribution characteristics of urban meteorology. This study investigates the vertical characteristics of urban local-scale meteorological parameters across climatic zones. It aims to assess the climatic potential for NV of outdoor air in high-rise buildings. Firstly, using Weather Research and Forecasting (WRF) model coupled with Local Climate Zone (LCZ) data and sounding data, the vertical distribution of meteorological parameters are explored in typical urban areas across different climatic zones. Then, based on an adaptive thermal comfort model, the climatic potential is assessed for NV in high-rise buildings via the indicator of annual natural ventilation hour (NVH). Finally, the characteristics of urban meteorology is further is analyzed in terms of its impact on the natural ventilation potential (NVP) in each climatic zone. Results indicate that air temperature decreases with height from 0 to 500 m, with more pronounced temperature gradients in compact building areas. Near the ground level, Kunming (Temperate Zone) has the most NVH, reaching 4,840 h annually. However, when building height exceeds 100 m, Guangzhou (Hot Summer and Warm Winter, HSWW) becomes more suitable for NV. In cold regions, low temperatures limit NVP during winter, while high humidity constrains it in Temperate and HSWW zones. Overall, the annual NVP in high-rise building areas exceeds that of low-rise building areas. These distribution characteristics of NVP are anticipated to promote the utilization of natural resources for sustainable urban development.

District heating is a major contributor to urban air pollution due to the massive emissions from fossil fuel combustion. This paper investigates the diffusion characteristics of air pollutants from district heating sources (DHS) driven by the urban wind field. Firstly, the urban air quality was simulated using the coupled Weather Research and Forecasting model - Community Multiscale Air Quality model (WRF-CMAQ) based on the actual heating emissions in the study region. the results were validated using observed meteorological and environmental data. Next, the study regions were divided into sub-regions based on the prevailing wind direction during the heating season. numerical experiments were designed by planning the heating emission into sub-regions as optimized layouts for DHS. Finally, the air quality was predicted for different layouts using WRF-CMAQ and assess the output of PM2.5 as the indicator. The findings reveal that moving the DHS close to the suburban areas can significantly improve overall air quality, and the best improvement can be obtained by arranging all DHS within the defined windward or leeward sub-regions. It is expected that these findings will provide guiding principles for planning DHS from the perspective of environmental management.

This paper investigates the wind pressure distribution of a thousand-meter scale megatall building through a wind tunnel test. One key challenge is that the power-law wind profiles are not applicable due to the height limitation. Therefore, a mesoscale meteorological model WRFv3.4 (Weather Research & Forecasting Model) was used to explore the wind profile covering the height of the thousand-meter scale megatall building. Then the wind profile was reproduced in the wind tunnel representing the actual vertical distribution of wind speed by a passive simulation method, and thereby the wind pressure test was conducted in the wind tunnel. Moreover, to investigate the effect of the inlet wind profile on the wind pressure, a wind tunnel test using the power-law wind profile was carried out for comparison as well. It was revealed that the wind pressure distribution was greatly influenced by the inlet wind profile, which should be investigated with accuracy in the wind tunnel.

As the increasing hub height of modern wind turbine, wind shear model is generally adopted as a useful tool to extrapolate wind speed available to higher levels for wind power assessment. This paper conducts a data-driven study to examine the power law model in assessing the wind power in forested regions featured with seasonally-varied roughness. Specifically, wind speeds are observed using a laser lidar mounted in forested regions in the northeast of China, ranging from 80 m to 200 m with a constant interval of 20 m. Subsequently, comparisons are made between the wind profiles established based on the power law model and field observations. The exponents used include the empirical exponents and the fitted exponents, the former are derived from the standard codes, and the latter are fitted based on the seasonal and annual data collections. Results indicate that the power law model is unable to fully capture the vertical distribution of wind speed in forested regions, it is the exponent that plays a decisive role influencing the reliability representing the real wind profile. Compared with the empirical exponents, the seasonally-fitted exponents exhibits much better suitability for wind speed extrapolation in forested regions, as well as for the wind power assessment.

Open field burning of crop residue has been intentionally prohibited due to the undesired air pollution in urban regions. To better balance the urban environment and agricultural activity, this paper conducted a feasibility study of prescribed burning for crop residues based on air quality assessment in urban regions. Firstly, emission inventories were established using the top-down approach based on designed sub-regional fire as prescribed burning. Subsequently, the air qualities in urban regions were simulated by the coupled Weather Research and Forecasting Model-Community Multi-scale Air Quality Model (WRF-CMAQ) covering different sensitivity experiments. Finally, PM2.5 is selected as the main indicator of air quality, and the feasibility was assessed by controlling the factors influencing the diffusion of pollutants from prescribed burning, including burning ratio, meteorological factors (wind speed and direction), distance from burning area and burning duration. It is revealed that prescribed burning would achieve highly efficient disposal of crop residues under the premise of ensuring the air quality in urban regions by controlling the factors. Results in the study can be further exploited for designing burning scheme for crop residue, which is expected to promote a sustainable development of agriculture and urban environment.

Typhoons have caused considerable damage to individual tree and forest ecosystems. To reduce wind-induced tree damage and better predict the risk of damage, improving our understanding of wind-tree interactions during strong wind conditions is important. To this purpose, wind characteristics and movements of an individual Betula platyphylla Suk. in a forest stand were monitored during three typhoons (Bavi, Maysak and Haishen). Results revealed that the average wind twists with increasing height, with a large twist gradient within the canopy and a small twist gradient outside the canopy. The maximum wind twist angle was approximately 110°. The disturbance of trees increases the turbulence intensity of the wind field in the canopy. The maximum power of the wind spectra and the turbulence anisotropy of the three turbulence components decrease with increasing height. B. platyphylla did not resonate with the wind in any of the typhoons but responded strongly to gusts near its free vibration peak frequencies. The peak frequency of the mechanical transfer function of B. platyphylla is essentially the same as the peak frequency of the response power spectra. The mechanical transfer function of the wind-induced response of the tree is almost the same as the transfer function of the damped harmonic oscillator which has similar characteristics to coniferous trees.

The increasing human activity in forested regions requires a better understanding of the wind conditions. This paper aims to improve the wind simulation in forested regions of complex terrain, and thereby to investigate the effect of forest on wind characteristics. Considering the complexity of the surface, simulations were carried out covering different parameterization schemes sets using Weather Research and Forecasting model (WRF). The results indicate that Noah-MP scheme and YSU scheme are recommended for a mesoscale wind simulation in forested regions of complex terrain. Moreover, due to the complexities of land surface with seasonally-varied roughness length (RL) and leaf area index (LAI), localized LAIs and RLs would significantly improve wind field simulation. Comparisons demonstrated that the modified RLs, which can reshape the wind speed distribution, have greater impact than LAI on the wind field simulation in the near-surface level. The findings can be further exploited in the wind damage assessment for the infrastructures, as well as wind power assessment in forested regions.

The rapid growth of population has promoted the construction of the megatall buildings taller than 600 m whose height might bring new issues to the building energy saving. To investigate the effect of the building height on the distribution of thermal pressure in megatall buildings, we simulated the thermal pressure distribution and air infiltration using the multi-zone network model CONTAMNv3.2. The building models were set up considering the typical conditions with height interval of 200 m ranging from 600 to 1000 m, and the outdoor meteorological parameters were set up based on the temperature ranges according to the cold region and the sever cold region in China. It is revealed that the thermal pressure increases with the increase in the building height, together with the decrease in the outdoor temperature. Besides, the energy consumptions from the air infiltrations were calculated based on the same conditions, among which the variation of air density was considered. The findings can be exploited to reduce the energy consumption of air infiltration in the megatall buildings.

为了解决传统空调直接引入室外空气作空调新风导致制冷能耗过高的问题,文中分别将北京奥森公园和杭州某学院路两侧的绿化树木为研究对象,通过植物的遮阳和蒸腾作用对室外空气降温调节,利用降温了的室外空气作空调的新风.增大绿化区域范围,可以大大降低空调的新风负荷;地理位置也是影响空调新风负荷的又一因素之一.此技术最大程度降低了夏季建筑物的空调能耗,综合实现了绿色建筑的理念和节能减排可持续发展.

Pedestrian-level wind environment in urban areas has a significant impact on the quality of urban dwellers' daily life. For pedestrian-level wind studies in severe cold regions, the cooling effect of wind and related thermal discomfort in winter is quite significant. However, thermal effects of wind are not considered in most wind comfort studies and wind comfort generally only refers to the mechanical effects of wind on people. Therefore, particular consideration is given to the chilling effect of wind on exposed skin and risk of frostbite in winter, and a wind chill criterion based on the wind chill temperature is proposed in this study. The pedestrian-level wind conditions in seven representative residential areas summarized from cities in severe cold regions of China are assessed based on the wind mechanical comfort criterion of NEN 8100 and the wind chill criterion. CFD simulations are performed to provide the pedestrian-level aerodynamic information, and the simulation results are validated by wind tunnel experiments. The assessment results show that the wind mechanical comfort or wind chill criterion need to be combined when assessing the wind conditions in severe cold regions. From the perspective of wind mechanical comfort and wind chill, the multi-storey residential areas with hybrid-type and the enclosed-type layout are recommended in severe cold regions. Moreover, a strict control of building height in residential areas is important to improve the pedestrian-level wind mechanical comfort, but not very helpful to reduce the occurrence of frostbite in winter.

The new generation of tall buildings is going much higher than before. This paper evaluates the effect of air intake height on the fresh air load for the plan of constructing thousand-meter scale megatall buildings in the cold region of China. The central difference from the conventional research is the consideration of vertical variations of outdoor atmospheric parameters around the air intakes at higher levels, and a mesoscale meteorological model, Weather Research & Forecasting Model (WRFv3.4), is introduced into this research to explore the vertical variation trend of atmospheric parameters in the cold region. Additionally, considering the common feature of cold region, the evaluation is illustrated based on the representative coastal and continental locations, as represented by Dalian and Beijing City in the region. The results indicate that the fresh air loads for heating and cooling increase approximately +0.15 W.m(-3).100.m(-1) and -0.8 W.m(-3).100.m(-1) with air intake height, respectively. Furthermore, the optimal air intake height is analyzed from the perspective of the minimum fresh air load. It is revealed that the comprehensive fresh air loads with different ratios of the heating period to the whole conditioning period have the minimum value when air intake is placed at the height of 1000 meters (m). The results in this paper can be exploited to reduce the energy consumption of fresh air system in the megatall buildings constructed in the cold region. (C) 2017 Elsevier Ltd. All rights reserved.

The next decades will be a golden period for the utilization of wind power in buildings. This paper assesses the wind power resource for constructing a thousand-meter scale megatall building in China. Considering there is no existing documentation of more detailed sources for upper level wind data, we elaborated on using the mesoscale meteorological model Weather Research and Forecasting Model (WRFv3.4) to investigate the wind characteristics at different levels within the thousand-meter scale megatall building's height. At the first step, the WRF model is validated through the comparisons between the simulated wind data and meteorological observations, including the ground-based observatory data and radiosonde data. At the second step, the results from the WRF model are used in the assessment of directional wind power densities, based on which the directional electric powers at the corresponding heights of the platforms are estimated as well. The results indicate that the maximum wind power density and electric power occur at 300 and 200 m above the ground, respectively. Additionally, both the wind power density and electric power from the north and south are significantly larger than those from the other two directions. (C) 2017 Elsevier B.V. All rights reserved.