Indoor Temperature Variations Research Articles

Field measurement study of indoor thermal environment of badminton halls in a hot summer and cold winter region in different seasons in China

The indoor thermal environment has a direct impact on human thermal comfort and health. In order to assess the status of the indoor thermal environment of typical sports buildings in hot summer and cold winter climate zones in China, 14 badminton halls in 10 cities in Hubei Province (including 5 venues in Wuhan) in this climate zone are chosen as research objects for field testing of indoor thermal environment parameters in 4 seasons. All the tested stadiums are naturally ventilated in non-event conditions. The results reveal that the average indoor temperature of badminton halls in summer is excessively high (i.e., 31.89 °C), which is higher than the regulation specified in JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in summer, (i.e., (26–28 °C) or (22–28 °C), respectively). The average indoor temperature of badminton halls in winter is too low (i.e., 12.95 °C), and it is lower than the recommendations of JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in winter (i.e., (16–18 °C) or (16–24 °C), respectively), relative humidity and air velocity are in the thermal comfort interval for all seasons, and the indoor thermal environment factors of badminton courts in spring and autumn meet the comfort requirements. The indoor and outdoor temperatures and the relative humidity of badminton courts are highly correlated. The indoor temperature and relative humidity vary according to changes in those factors outdoors, whereas the air velocity is not affected by outdoor changes. In the hot summer and cold winter climate zones, some discrepancies in the indoor temperature variation patterns of badminton halls at various altitudes are detectable. The results of this study aim to provide a solid basis for the development of indoor thermal-comfort standards for sports stadiums in China.

Self-detection of thermal ambient parameters for air-conditioned space by learning operation data and self-prediction of indoor temperature and power consumption

For efficient energy use of air conditioning unit (AC), there is a need to find an optimal control method for operation. To deduce an optimal control algorithm, indoor temperature and power consumption need to be predicted according to given operating conditions. Among the key factors, the thermal ambient parameters such as thermal resistances of the operation sites are most difficult to identify. This study proposed a method for an AC to deduce these parameters for itself by learning operation data obtained from the embedded sensors and autonomously predict indoor temperature and power consumption by solving the transient energy conservation equation incorporating refrigeration cycle simulation. A novel aspect of this study is that the AC can autonomously perceive thermal ambient parameters of its surroundings and utilize these parameters to predict indoor temperature variations and power consumption. These data could be fed back to the control software of the AC in real time. To validate the proposed method, experiments were conducted in model house test facility using a real air-conditioner, and the results were compared with the simulation results. It was confirmed that the time to reach the air temperature setpoint was within 3 min and the power consumption could be predicted within 9 %.

Relationship between indoor and outdoor temperature and humidity in a residential building in Central Europe

Relative humidity and temperature in indoor spaces are two important environmental factors that not only determine the behaviour and well-being of building occupants but also influence airborne transmission of respiratory diseases in closed spaces. While recent studies have examined how well indoor conditions relate to outdoor ambient weather, most studies on weather-related health effects still use a single central site monitor such as a weather station since outdoor values are more convenient to measure. However, the correlation between indoor and outdoor values is not always straightforward. Our case study explores the relationships between indoor and outdoor temperature and humidity in a residential building apartment in a temperate climate in Central Europe. Measurements performed over the period of one year allow for a detailed comparison and analysis of correlations between both daily averages as well as daily profiles of indoor and outdoor variables. The results of this case study add further evidence to the observations that day-to-day variation in indoor temperature and relative humidity are not well-represented by outdoor measurements. It further adds to the growing body of data on indoor environmental variables and should thus prove useful in studies aiming to determine the influence of relative humidity and temperature on indoor transmission of airborne diseases as well as in studies examining the influence of these two variables on the well-being of building occupants.

The Impact of Indoor and Outdoor Air Temperature Variations on Upper Trapezius Muscle Activity

The Impact of Indoor and Outdoor Air Temperature Variations on Upper Trapezius Muscle Activity

The relationship between thermal comfort, performance, and electroencephalogram during cognitive tests at normal indoor temperatures in summer

Electroencephalograms have been proposed as potential physiological indicators to gauge the thermal comfort and cognitive performance of individuals in indoor environments, yet further experimental validation is required. In this study, a simulated experiment was conducted in a climatic room during summer, with temperatures set at 24 °C, 26 °C, 28 °C, 30 °C, and 32 °C. Twenty participants, attired in typical summer clothing (short sleeves and long pants totaling 0.39 clo), undertook cognitive tests assessing short-term memory and concentration while seated, alongside providing thermal comfort ratings. Electroencephalogram signals were continuously recorded from 14 electrode channels across the brain during the second cognitive test unit, spanning the 70th to 90th minute of experimental exposure. The relative power of electroencephalogram signals was computed and analyzed in conjunction with thermal comfort voting, revealing a significant impact of indoor temperature variations on α-band activity in the occipital lobe, with peak α-band relative power observed at 26 °C. Moreover, the whole-brain α-band relative power was significantly higher in states of thermal comfort compared to discomfort, particularly concentrated in the occipital lobe. Linear correlation analysis between cognitive test results and electroencephalogram signals indicated significant associations between the relative power of whole-brain β, δ, and θ bands and scores from the concentration-focused Flanker test. Channels O1 and P8 emerged as potential candidates for single-channel electroencephalogram signals, offering insights into thermal comfort status and cognitive performance related to concentration.

Green building adaptation in hot-humid climates: assessment of coconut and corn husk fiber composite bricks as energy-efficient building envelopes

PurposeThis study has assessed the thermal performance of locally fabricated bio-based building envelopes made of coconut and corn husk composite bricks to reduce building wall heat transmission load and energy consumption towards green building adaptation.Design/methodology/approachSamples of coconut fiber (coir) and corn husk fiber bricks were fabricated and tested for their thermophysical properties using the Transient Plane Source (TPS) 2500s instrument. A simulation was conducted using Dynamic Energy Response of Building - Lunds Tekniska Hogskola (DEROB-LTH) to determine indoor temperature variation over 24 h. The time lag and decrement factor, two important parameters in evaluating building envelopes, were also determined.FindingsThe time lag of the bio-based composite building envelope was found to be in the range of 4.2–4.6 h for 100 mm thickness block and 10.64–11.5 h for 200 mm thickness block. The decrement factor was also determined to be in the range of 0.87–0.88. The bio-based composite building envelopes were able to maintain the indoor temperature of the model from 25.4 to 27.4 °C, providing a closely stable indoor thermal comfort despite varying outdoor temperatures. The temperature variation in 24 h, was very stable for about 8 h before a degree increment, providing a comfortable indoor temperature for occupants and the need not to rely on air conditions and other mechanical forms of cooling. Potential energy savings also peaked at 529.14 kWh per year.Practical implicationsThe findings of this study present opportunities to building developers and engineers in terms of selecting vernacular materials for building envelopes towards green building adaptation, energy savings, reduced construction costs and job creation.Originality/valueThis study presents for the first time, time lag and decrement factor for bio-based composite building envelopes for green building adaptation in hot climates, as found in Ghana.

Developing a validated simulation model of micro-zonal air-conditioning to evaluate thermal comfort parameters

ABSTRACT Micro-Zonal Occupant-Centric Control (MZOCC) helps in reducing building energy consumption by conditioning only the occupied regions in a room. For this, MZOCC divides a large room such as open-plan offices into virtual micro-zones to allow independent diffuser level control. But, unplanned MZOCC can lead to heavy thermal gradients and deflection of air jets, leading to thermal discomfort. To evaluate thermal comfort at different regions of a room under MZOCC, there is a need to accurately model parameters of thermal comfort. Field studies, exploring the transient variations in air temperature, humidity and velocity at different regions of the room due to MZOCC, are limited. At the same time, developing validated simulation models or digital twins using experimental data helps in exploring micro-zonal strategies to arrive at the best strategy. The aim of this study is to create a digital twin of an open-plan office and model the parameters required to estimate thermal comfort. This study senses transient variations in air temperature, velocity and humidity using a wireless sensor network and develops a computational fluid dynamic (CFD) model that can accurately model the sensed transient variations. Field data, constituting external surface temperatures captured using thermal images, variations in air-conditioning control strategy, dynamic occupancy and location, are periodically updated in the digital twin. The CFD model accurately predicts the trends in variations in indoor temperature, velocity and humidity at different regions of the room. The developed digital twin can be used in future studies to evaluate thermal comfort and plan MZOCC control strategies.

Modeling Mushrooms’ Carbon Dioxide Emission and Heat Exchange Rates for Synergistic Cultivation with Leafy Greens

The cultivation of mushrooms in controlled environments generates a significant amount of CO2 as a by-product. This presents opportunities for carbon dioxide (CO2) enrichment in leafy green production. This study aimed to develop a model for CO2 emission and heat exchange rates that can be used to support the synergistic cultivation of mushrooms and leafy greens. This was achieved by aggregating data from literature with experimental data gathered in two different testing spaces. The average CO2 emission and heat exchange rates for shiitake incubated at 21 °C were determined and a CO2 emission rate model for mixed substrate in incubation was developed based on indoor temperature variations. The results indicated that oyster mushrooms have a notable CO2 enrichment potential, twice that of shiitake in the incubation stage and five times more in fructification. Additionally, oyster mushrooms released a significant amount of heat during incubation. In contrast, shiitake mushrooms with their minimal heat exchange rate during incubation could offer an energy-efficient option for synergistic cultivation with leafy greens in environments where cooling is required year-round. Moreover, it was observed that the CO2 emission rate of a full-scale incubation chamber is strongly correlated with indoor temperature. These findings offer valuable information for modeling the CO2 emission and heat exchange rates of mushroom and leafy green farms.

Novel functional materials capable of humidity regulation and thermal storage for building energy conservation

Functional materials with large hygrothermal inertia can passively mitigate indoor temperature and humidity variations, thus improving indoor environmental quality and reducing energy demand for heating, ventilation, and air-conditioning (HVAC) systems. In this study, a novel functional phase-change humidity control material (PCHCM) was developed based on the integration of microencapsulated phase-change material (MicPCM) and novel moisture adsorbent: Metal-Organic Frameworks (MOFs). The novel MOF-based PCHCM is a dual-functional composite material. It can simultaneously uptake/release heat and humidity from indoor air and control the hygrothermal environment passively. The materials characterizations show that the new MOF-based PCHCM has better thermal and moisture buffering ability than most conventional building materials. The effect of the new material on building energy conservation was calculated by a newly developed HAMT-enthalpy model. The simulation results show that MOF-based PCHCM can effectively moderate the fluctuations of temperature and relative humidity and reduce building energy consumption in most climates worldwide. The maximum energy-saving potential could reach up to 35% in hot-dry climates. The paper will guide the application and further development of dual-functional PCHCM composites under different climates.

Determination of the Effect of a Thermal Curtain Used in a Greenhouse on the Indoor Climate and Energy Savings

In order to reduce the impact of outdoor extreme weather events on crop production in winter, energy saving in greenhouses that are regularly heated is of great importance in reducing production costs and carbon footprints. For this purpose, the variations in indoor temperature, relative humidity and dew point temperature in the vertical direction (2 m, 4 m, 5.7 m) of thermal curtains in greenhouses were determined. In addition, depending on the fuel used, the curtains’ effects on heat energy consumption, heat transfer coefficient, carbon dioxide equivalents released to the atmosphere and fuel cost were investigated. To reach this goal, two greenhouses with the same structural features were designed with and without thermal curtains. As a result of the study, the indoor temperature and relative humidity values in the greenhouse with a thermal curtain increased by 1.3 °C and 10% compared to the greenhouse without a thermal curtain. Thermal curtains in the greenhouse significantly reduced fuel use (59.14–74.11 m3·night−1). Considering the heat energy consumption, the average heat energy consumption was 453.7 kWh·night−1 in the greenhouse with a curtain, while it was 568.6 kWh·night−1 in the greenhouse without a curtain. The average heat transfer coefficient (U) values were calculated at 2.87 W·m−2 °C with a thermal curtain and 3.63 W·m−2 °C without a thermal curtain greenhouse. In the greenhouse, closing the thermal curtain at night resulted in heat energy savings of about 21%, related to the decrease in U values. The use of a thermal curtain in the greenhouse reduced the amount of CO2 released to the atmosphere (116.6–146.1 kg·night−1) and fuel cost (USD 21.3–26.7·night−1). To conclude, extreme weather events in the outdoor environment adversely affect the plants grown in greenhouses where cultivation is performed out of season. A thermal curtain, used to reduce these adverse effects and the amount of energy consumed, is essential in improving indoor climate conditions, providing more economical greenhouse management and reducing the CO2 released into the atmosphere due to fuel use.

Field study of energy and environmental performance of ground source heat pumps retrofitted in a cluster of UK social housing dwellings

This paper uses an empirical field based approach to examine seasonal variation in heat pump electricity use and indoor temperatures across a cluster of 50 social housing dwellings retrofitted with ground source heat pumps (GSHP). The case study dwellings were co-located in a socially deprived housing estate in Oxford (UK). Time series monitoring data was collected on indoor, outdoor and target temperatures, heat pump electricity use (kWh), space heating and hot water operation status (on/off) in non-heating and heating seasons. Contextual data about the dwellings were gathered through heat pump surveys and energy performance certificates. Results showed 60% rise in electricity use during the heating season with statistically significant correlation observed between indoor and target temperatures, energy efficiency rating and monthly electricity use. When electricity use was normalised for outdoor temperature, lower electricity use per heating degree day (HDD) was observed in the heating season in the majority of dwellings, confirming the efficient running of the heat pumps. Mean daily indoor temperatures were found to be stable across majority of dwellings, with peak electricity use largely happening outside of the national evening peak period of 4pm-7pm. Despite there being a ‘Timer’ mode in relation to outside weather, most of the residents used the ‘Manual’ mode of operation to adjust target temperatures, possibly to overcome the low output temperatures of heat pumps. While resident training will help to enhance understanding of heating controls, smarter operation of heat pumps through automation based on optimisation of indoor and outdoor temperature, occupancy patterns, heating preferences and electricity price signals could result in further energy savings.

Examining the Risk of Summertime Overheating in UK Social Housing Dwellings Retrofitted with Heat Pumps

The UK government has announced its ten-point plan to annually install 600,000 low-carbon heat pumps by 2028. However, there is a lack of evidence showing potential overheating risk in dwellings retrofitted with heat pumps. This paper examines the prevalence and magnitude of summertime overheating across 24 naturally ventilated social housing dwellings retrofitted with ground source heat pumps (GSHPs). The dwellings are located in a socially deprived area in Oxford (UK). The empirical study included longitudinal monitoring of indoor temperatures in the living rooms and bedrooms during the non-heating seasons of 2021 and 2022 (May–September), which included a record-breaking heatwave in July 2022. Indoor temperature and CO2 levels in bedrooms were monitored across a subset of six dwellings alongside the monitoring of window opening state in three bedrooms to understand the effect of natural ventilation in removing excess heat. About 136 thermal comfort surveys were conducted to ascertain the subjective responses of residents. Overheating risk assessment was carried out using CIBSE static and adaptive methods, which revealed that summertime overheating was prevalent across half of the dwellings in the non-heating season of 2022, as compared to 17% overheated dwellings in 2021. Bungalows with upgraded cavity wall insulation and top floor flats facing south and south-west had a propensity to overheat. The variation in indoor temperature and CO2 levels across a small sample also indicated the relationship between overheating and residents’ behaviour. Given that the majority of the dwellings were occupied by retired elderly people with low incomes who are vulnerable to heat and cannot afford active forms of cooling, it is vital to deploy passive design measures, such as appropriate shading devices that are suitable for a heating-dominated climate and enhanced ventilation, as part of home energy retrofits. Implementing reversible heat pumps coupled with solar PVs can provide cooling during heatwaves while delivering low-carbon heat in the winter.

Short-term forecasting model for residential indoor temperature in DHS based on sequence generative adversarial network

With the rapid development of the economy and the continuous improvement of people's living conditions, building thermal comfort has become one of the essential objectives of the development of the smart district heating system (SDHS). The accurate prediction approach of indoor temperature is the primary prerequisite and basis for achieving optimal thermal comfort regulation. However, the buildings' indoor temperature has significant thermal inertia and nonlinear characteristics due to the influence of multiple factors. The traditional time-series prediction algorithm can hardly accurately extract the indoor temperature variation pattern and cannot fully meet the satisfactory regulation requirements of SDHS. Therefore, an indoor temperature prediction model based on a sequence generative adversarial network (SGAN) is proposed in this paper. The new SGAN algorithm is trained by iterative adversarial training of the generator and discriminator, and the LSTM model built into the generator can effectively extract the high-level nonlinear abstract features of indoor temperature to achieve its accurate prediction. The detailed comparative experimental results show that the proposed indoor forecasting algorithm based on SGAN has obvious performance advantages compared to state-of-the-art algorithms, such as random forest regression (RFR), gradient boosting regression (GBR), support vector regression (SVR), adaptive boost (AdaBoost), multilayer perception (MLP), and long-short term memory(LSTM). The SGAN's mean absolute percentage error (MAPE) index reaches 2.3%.

Hygrothermal Performance of Adobe Structures

Vernacular architecture incorporates many cooling and heating passive design strategies related to the structural envelope, the different architectural arrangements and the way of living of the inhabitants. Adobe walls are considered to be high thermal mass masonries, as they have the ability to store thermal energy. The high thermal inertia of these materials regulates indoor temperature variations through considerable time lags, thus contributing to the improvement of thermal comfort conditions. This study deals with the environmental behaviour of an adobe historic building in the rural area of Nicosia, Cyprus. The aim of this study is the investigation of the hygrothermal performance of the external adobe masonry walls of the structure under study. For this purpose, in-situ long-term monitoring is currently being carried out, focusing on the indoor and outdoor environmental conditions of a south wall of a room which has two exposed surfaces, the north towards the street and the south towards a courtyard. The south wall is being monitored with temperature/moisture sensors, installed at various locations along its thickness and height. In situ monitoring is complemented with laboratory measurements of the thermophysical (thermal conductivity, porosity, and sorptivity) properties of the main masonry material (adobes). Rising damp height, time of wetness, thermal inertia and decrement factor have all been calculated based on the laboratory and in-situ measurements. The results are analysed in terms of existing standards and analytical equations. The findings of this research may be used to evaluate the overall thermal performance of historic adobe buildings and the effectiveness of adobe walls in the improvement of indoor comfort conditions.

下沉式日光温室闷棚期间温湿度变化机制的研究

A sunken solar greenhouse is the original type of greenhouse in China, its soil wall thermal storage performance is better and low cost. Higher benefits of stereoscopic planting in sunken solar greenhouses, while repeated use of the substrate can produce pathogens, so high-temperature smothering is used for sterilization in the summer months of June to August. To investigate the mechanism of indoor temperature and humidity variation and fungicidal effect in a sunken solar greenhouse, a single cross-sectional test of temperature and humidity in sunken solar greenhouse during the smothering period was conducted using wireless sensors. The results showed that: The maximum value of indoor temperature at noon was 69.5°C the temperature value of all measurement points was greater than 50°C for 3h, when removing the measurement points at the upper surface of the ground, the relative humidity value of other measurement points was less than 60% for 5h. During the daytime period, when the indoor temperature is greater than 28°C in the interval 7:00-12:00, the initial relative humidity value of each measurement point is located at 70%-85%; when the weighted temperature of each measurement point starts to rise at a rate of 1.1°C/10min, the weighted humidity of each measurement point declining is 1.3%/10min; the determination of the rate of change of indoor temperature and humidity during the daytime and the starting value can provide a basis for indoor plants to take measures to sterilize at high temperature.

An XGBoost-Based predictive control strategy for HVAC systems in providing day-ahead demand response

Heating, ventilation and air-conditioning systems (HVAC), at demand side, are regarded as promising candidates to provide demand response to smart power grids by adjusting indoor temperature setpoint. However, the optimal control of indoor temperature setpoint with the constraint of indoor environment is a key issue. In this study, an XGBoost-based predictive control strategy is proposed for HVAC systems in providing day-ahead demand response. XGBoost (Extreme Gradient Boosting) models are developed to predict the variation of power use and indoor temperature. Several innovations are implemented to improve the performance of the control strategy, including dedicated generation of the initial population of genetic algorithm (GA) in rolling optimization, the use of a step-decreasing control horizon, and the separation of the sampling period and control action period. The strategy is validated on a TRNSYS-Python co-simulation test platform. Results show that the developed XGBoost models can achieve a high prediction performance of power use (CV-RMSE of 4.52%) and indoor temperature (CV-RMSE of 0.40%) in the coming 10 min with only using one-week historical data. The computation cost is reduced by 78% due to the dedicated generation of GA initial population while the control performance is not affected. Compared with the traditional operation, the proposed control strategy can reduce the total cost by as much as 27.30% and 33.6% while the weighted indoor temperature only increases by 0.14 K and 0.62 K, respectively. In test cases, the highest Predicted Mean Vote (PMV) is 0.72 and the corresponding Predicted Percentage of Dissatisfied (PPD) is 15.9%.

Demand Response with Electrical Heating in Detached Houses in Finland and Comparison with BESS for Increasing PV Self-Consumption

Distributed electric power production by small-scale customers is increasing continuously. Photovoltaic production is a popular method of producing self-energy for customers. Additionally, power systems require more flexibility when weather-dependent renewable energy production increases. Small-scale customers can increase the self-consumption of self-produced energy by using batteries or a demand response operation. However, batteries require high investment, and demand response operations induce a loss of comfort. Customers who heat their buildings using electric heaters are a good target for demand response operations because their heating can be controlled with limited changes in the indoor temperature. The demand response potential of a building can be defined by simply using customer load profiles and knowledge of the outdoor temperature. Any other information is not required in the proposed novel method. A tolerable variation in indoor temperature corresponds to considerably smaller battery capacity, though it is still a significant amount. With an optimally sized photovoltaic system, it is possible to use both methods simultaneously to increase self-consumption. Maximal benefits can be attained from both methods if the battery system is used as a primary control and the demand response is used as a secondary control. The defined novel method for determining the demand response potential of small-scale customers can also be used when estimating the flexibility of a large customer group. Small-scale customers together can provide significant flexible capacity when their electrical heating is centrally controlled.

Analysis of the rule of window-to-wall ratio on energy demand of residential buildings in different locations in China

Building energy demands are influenced by the window-to-wall ratio (WWR). The impact of the WWR on the energy demand in the same area has been researched by software. However, the impact of the WWR on the energy demand of buildings in different locations of China has not been investigated using the energy balance equation. The equation for the indoor temperature variation under various internal and external disturbances was provided in this study. The relationship between parameters A and B and the change in indoor temperature was proven. China's Harbin, Beijing, and Chengdu air-conditioning and heating loads, as well as the impact of changing WWR on the rate of energy savings for air-conditioning and heating energy demand, were studied. After investigating the changes in the cooling and heating loads in various cities under various WWRs, the suitable relationship between the cooling and heating loads and the WWR of three urban units was discovered. The findings indicated that despite the three cities' various climates and the diverse energy demands for air conditioning and heating in each city, with the same change in the WWR of urban buildings, the change rate of the air conditioning and heating loads in each city was near. Meanwhile, the heating and cooling loads were linear with WWR.

Analysis of thermal comfort experience using peak-end rule with air conditioner in heating season

Recent years have seen a significant increase in study on the thermal comfort offered by room air conditioners (RACs) when utilized as heaters, especially in the steady stage. Research indicates that convective terminals can form a comfortable environment using optimized control settings and strategies. Nevertheless, complaints about the thermal comfort experienced when using RACs persist, which is probably related to cognitive bias in psychology. The final seconds of an experience are given a lot of weight by the peak-end rule, which is typically characterized as the positive/negative peak. They were used to analyze how different heating experiences rated in terms of thermal comfort. Therefore, dynamic indoor temperature variations with six different terminals and control strategies were analyzed. Furthermore, an experiment with a thermal sensation, thermal comfort, thermal preference, and thermal adaptability vote (TSV, TCV, TPV and TAV) with different dynamic controlling characteristics was conducted in an artificial chamber. Three control methods with different peak moments were determined: slow start, interval downtime operation, and continuous heating. The comprehensive experience TCVs were 2.72, 2.28, and 1.12, and average-weighted TCVs were 1.94, 1.60, and 1.14, respectively. This exhibited a significant difference in terms of the heating process evaluation. In contrast, the TCVs based on the peak-end rule were 2.52, 2.31, and 1.11, respectively, which is more consistent with field evaluation. There is strong evidence that peak-end rule applies to TCV for air-conditioning systems. Other cognitive biases were also analyzed to evaluate the heating experience. Reasons for the thermal discomfort of RACs are also summarized.

Residential satisfaction of vertical urban settlements in Hong Kong

Purpose Vertical urban settlements are becoming the predominant form of contemporary urban design in response to population increase and rapid urbanization. These developments are, however, perceived to be poorly designed and incongruent with the users’ needs. The purpose of this study was to present a resident satisfaction assessment of Hong Kong’s vertical settlements. Design/methodology/approach A review of the literature was conducted on the concept of vertical urbanism, residential satisfaction and postoccupancy evaluation. Fifty performance indicators were classified into three groups including indoor environment, safety and maintenance; furniture, utilities and spaces; and privacy, appearance and city life. These indicators were used to develop a Web-based questionnaire administered to residents in the three administrative regions of Hong Kong. Ninety-eight respondents participated in the study, and the results were analyzed using the resident satisfaction index and the overall satisfaction index. A multilinear regression analysis was also made to develop a model describing the most relevant performance indicators for determining the overall residential satisfaction. Findings The results revealed that residents expressed dissatisfaction with performance indicators, including “level of noise generated from outside the building (neighboring buildings, traffic, noise, etc.),” “variation and stability of indoor temperature,” “sustainable design of the building’s environment (cyclability, walkability, electric charging stations, etc.),” “availability and capacity of car parking,” “size and adequacy of spaces for social interaction” and “considerations for occupants with special needs (disabled, aged people, children, occupants with a medical condition, etc.).” The results also revealed that some indicators such as the maintenance of elevators, adequate interior space and surrounding areas were considered as significantly influencing residential satisfaction. Similarly, the building height and wind-induced motion were not significantly influencing residential satisfaction. The results also revealed that a multilinear Regression model with five variables and an adjusted R2 value of 93% could estimate the overall residential satisfaction. Originality/value The concept of vertical urban design is the new paradigm in the shaping of future cities. The originality of this study is its adoption of post-occupancy evaluation to assess occupants’ residential satisfaction. As well as the determination of factors that should inform the planning, design and management of vertical urban settlements. Thus, the study has significant implications for research in vertical urban development, as well as the professional practice of building and urban planners, designers and managers.