Thermal Comfort Research Research Articles

Thermal comfort and gender affirmation: A virtual ethnography of extreme heat among trans women in Rio de Janeiro

The multisensory experience of feeling hot, breathless, sweaty, and weak during heat spells among transgender people is a critically understudied area in both medical anthropology and thermal comfort research. This article contributes to the anthropology of heat and humidity by intersecting with health and thermal comfort studies. Through virtual ethnography with three trans women in Rio de Janeiro in 2021 and 2022, the research reveals that trans women in the city face heightened risks of heat stress and thermal discomfort due to unsafe living conditions, side effects of gender-affirming modifications, and social discrimination. These findings highlight the urgent need to address the specific challenges transgender individuals face in accessing thermal safety and underscore the importance of considering their unique needs.

Thermal preference and pleasantness of a students’ population in a coastal urban area during summer

In thermal comfort research, two main domains are identified: objective and subjective. This study focusses on the latter, examining various aspects of preference, sensation, and pleasantness. It also clearly distinguishes each concept and sets the groundwork for their standardised use in urban planning and urban climate studies. Additionally, this study emphasises the often-overlooked geographical perspective, aiming to address previous gaps in this research area. Environmental conditions were found to be the main determinants influencing pedestrians' thermal sensation, preference, and pleasure. Key factors include air temperature, solar radiation, and wind speed, which exhibit strong correlations with pleasure responses. Additionally, urban density, clothing type and colour, shading, sex, and weather type significantly impact thermal sensation and reported pleasantness. It was observed that people who overdressed for the season, wore dark or warmer clothes, experienced air temperature and solar radiation more intensely. Similarly, those in high-density urban areas, without shade, or when weak continental wind conditions were observed, reported stronger thermal sensations. Women generally sensed air temperature and solar radiation as more intense compared to men. These factors influence thermal pleasantness, varying in importance, spatial distribution, and statistical relationship. Higher wind speeds, particularly from an Atlantic direction, were found to enhance thermal pleasantness by balancing conditions and reducing thermal sensation votes for air temperature and solar radiation. Green areas also increased thermal pleasantness by lowering air temperature and solar radiation sensations and promoting a sense of happiness among pedestrians.

Ten questions concerning statistical data analysis in human-centric buildings research: A focus on thermal comfort investigations

Given the large amount of time we spend indoors, designing and operating buildings that are safe, comfortable, and conducive to productivity and well-being is essential. To achieve this goal, in the past decades, research has been conducted to investigate the influence of the indoor environment on occupants. Thermal comfort has been the subject of most investigations in this field. However, despite being a consolidated research topic since the 1920s, statistical practices for analysing thermal comfort data often rely on simplified premises, which may be due to several possible factors (e.g., limited computational capabilities and lack of training). Consequently, important aspects of data analysis are often absent or overlooked. Recent statistics and statistical software advances have provided more options for effectively modelling complex issues. However, properly using these tools requires a solid understanding of statistical analysis, increasing the risk of misuse in practice. This paper presents ten questions highlighting the most critical issues regarding statistical analysis for thermal comfort research and practice. The first four questions provide general perspectives concerning statistical data analysis, while the remaining ones address specific problems related to thermal comfort research, but that can extend to all human-centric research in the built environment. Additionally, the last five questions demonstrate the practical significance of analysis pitfalls (i.e., sampling variability, selection bias, variable selection, clustered/nested observations, and measurement error) through examples with synthetic data. This study provides insights into the current statistical ‘habits’ in thermal comfort research and, more importantly, help researchers better define and conduct their statistical analyses.

Thermal Comfort Research on the Rural Elderly in the Guanzhong Region: A Comparative Analysis Based on Age Stratification of Residential Environments

Addressing the thermal comfort of the elderly is a pressing concern amidst the escalating aging population in rural China. This study presents a comprehensive assessment of the thermal comfort within traditional and self-built dwellings in the Guanzhong region. Utilizing a mixed-methods approach encompassing both on-site measurements and questionnaire surveys, with a novel approach of segmenting the elderly population into three distinct age groups. The findings indicate that: (1) An average clothing thermal resistance of 1.83 clo among the elderly, which was found to be relatively higher when compared to other areas and positively correlated with age; (2) A thermal neutral temperature of 8.46 °C for traditional dwellings and 10.53 °C for self-built dwellings, both of which were lower than anticipated, indicating a discrepancy between current living conditions and elderly residents’ thermal expectations; (3) A positive correlation between age and the preferred neutral temperature, with the elderly showing a preference for warmer indoor environments. Additionally, we propose targeted strategies to enhance the thermal comfort of the elderly across different age groups and dwelling types. This study refines the thermal comfort evaluation system for the elderly in China’s cold climate regions, offering theoretical insights and practical guidance for the renovation of rural dwellings and the improvement of elderly living standards in the Guanzhong area.

Thermoregulatory differences in sex and time-of-day within naturally ventilated office environments

Thermal comfort research lacks continuous data collection on thermoregulation and adaptive behavior in real-world environments. This paper presents the findings of a field study that aimed at understanding the temporal and individual differences between humans’ thermoregulation and adaptation within a dynamic thermal environment. The dataset contains a 6-week long summer field study of 2022 observing nine participants in a naturally ventilated office without a cooling system. The data collection comprises a total of 43 measurement days (22,776 data points at 60s frequency). The results indicate that the overall trend in clothing insulation deviates from standard assumptions (0.5 clo), especially above air temperatures of 26 °C. The mean clothing insulation was 0.29 clo ±0.08, overall ranging from 0.20 to 0.73 clo. The data showed significant sex differences in tonic levels of electrodermal activity, the low-frequency to high-frequency heart rate variability ratio, and clothing insulation. Other heart rate variability data, like the root mean square of successive differences and beats per minute, as well as the distal skin temperature of the wrist, show significant sex differences and time-of-day variations in morning-to-afternoon comparisons. The findings indicate a nuanced relationship between air temperature and thermoregulatory responses, highlighting the need for future research with larger, more diverse participant cohorts and enhanced environmental monitoring to strengthen the validity and generalizability of the findings.

Assessment of the estimation methods of Tmrt in semi-outdoor spaces in humid sub-tropical climates: An empirical study in Wuhan, China

Studies have been conducted on the mean radiant temperature (Tmrt) estimation methods using globe thermometers for measuring outdoor thermal environments in various climate regions. Yet, given the unique thermal environments of semi-outdoor spaces, these Tmrt estimation methods may not be appropriate for the spaces with shading effects. This study aims to assess the thermometric and radiative methods for Tmrt estimation in semi-outdoor spaces in humid sub-tropical climates, taking data from six-directional radiation measurements as validations. During the typical summer and winter days in Wuhan, China, the measurements were carried out in semi-outdoor spaces facing south and west, with an open square for comparison, including air temperature, humidity, wind velocity, black-globe temperature, and long- and short-wavelength radiation fluxes obtained from four-component net radiometers. It was found the maximum mean deviation of diurnal Tmrt values estimated by the black-globe thermometer method in semi-outdoor spaces was 7.1 °C, which exceeded the threshold required by ISO7726, where the shortwave radiation was regarded as the dominant interference factor. To improve the accuracy and cost-effectiveness of Tmrt estimation, we proposed linear empirical equations to calibrate the Tmrt estimated by black-global thermometer method that the root mean square error (RMSE) of the Tmrt deviations can generally vary from 2.22 to 2.72 °C. Contributing to the thermal comfort research, this study proposed an empirical method for estimating Tmrt in semi-outdoor spaces in humid subtropical climates, which can generate satisfactory results in accordance with ISO7726 standards with cost-effective instrumentation.

A review of investigation of the metabolic rate effects on human thermal comfort

The precise analysis of the usage of thermal indices to evaluate and create an acceptable space is a research hotspot as thermal comfort increasingly comes to be the center of attention. The accurate measurement and calculation of the metabolic rate should be a top priority in research because it is the most important component of thermal indexmodels. This study includes a literature survey of the relevant fields to properly comprehend the present developments and flaws in calculating the metabolic rate. The ultimate objective is to apply the growth of human metabolic science to logical urban development. First, the interaction between the thermal environment and thermal comfort was analyzed, and then, the influence of the human metabolic rate on thermal comfort was discussed. The results show that the dynamic change of metabolic rate is the key human factor that directly affects the thermal regulation, and indirectly affects the evaluation accuracy of the thermal evaluation index standard. Through an inductive analysis of metabolic rate measurement methods that are widely used in various environments, this study identifies several issues with the current utilization of portable metabolic monitoring instruments in dynamic thermal comfort research, highlighting their limitations in addressing accuracy, portability, economy, and other relevant aspects. An essential future effort in this study path will be the continued research and development of a more portable, more affordable, more direct, and more efficient customized metabolic rate monitoring equipment. In addition, the fact that metabolic rate is represented as a constant or its impact on thermal comfort as a single factor in existing thermal index models also frequently results in incorrect findings in outdoor research. The fundamental condition for enhancing thermal comfort index forecast accuracy is accurate and continuous tracking of metabolic rate.

Causal thinking: Uncovering hidden assumptions and interpretations of statistical analysis in building science

Causal thinking emphasizes the understanding of asymmetric causal relationships between variables, requiring us to specify which variable is the cause (independent variable) and which is the effect (dependent variable). Reversing the causal relationship direction can lead to profoundly different assumptions and interpretations. We demonstrate this by comparing two linear regression approaches used in thermal comfort research: Approach (a), which regresses thermal sensation votes (y-axis) on indoor temperature (x-axis); Approach (b), which does the reverse, regressing indoor temperature (y-axis) on thermal sensation votes (x-axis). From a correlational perspective, they may appear interchangeable, but causal thinking reveals substantial and practical differences between them. Approach (a) represents occupants’ thermal sensations as responses to indoor temperature. In contrast, Approach (b), rooted in adaptive comfort theory, suggests that thermal sensations can trigger behavioral changes, which in turn alter indoor temperature. Using the same data, we found that two approaches lead to different neutral temperatures and comfort zones. Approach (b) leads to what we call a ‘preferred zone’, which is 10 °C narrower than the conventionally derived comfort zone using Approach (a). We hypothesize that the ‘preferred zone’ might be interpreted as thermal conditions that occupants are likely to choose when they have significant control over their personal and environmental thermal settings. This finding has important implications for occupant comfort and building energy efficiency. We highlight the importance of integrating causal thinking into correlation-based statistical methods, which have been prevalent in building science research, especially given the increasing volume of data in the built environment.

Effects of thermal and acoustic environments on human comfort in urban and suburban campuses in the cold region of China.

In this study, we investigated the effects of thermal-acoustic environments on human comfort in a cold region by focusing on Xi'an in China as a representative city. Four typical open spaces were identified within two universities, with one located in an urban area and the other in a suburban area. Surveys were conducted using questionnaires and environmental parameters were measured to assess thermal-acoustic perception. The physiological equivalent temperature (PET) and noise sound pressure levels were employed to measure the thermal-acoustic environments in the four open spaces. The results showed that the neutral PET was 19.1°C in Xi'an from March to May, and the neutral temperature range was 14.9-23.4°C. The preferred temperature was 20.0°C. Acoustic sensation votes were lower in suburban areas than urban areas. Respondents in urban areas exhibited significantly higher sensitivity to the thermal and acoustic environments compared with those in suburban areas. Sensitivity to the thermal environment decreased as the environmental noise levels decreased. The temperature perceived as most suitable increased as the sensitivity to the thermal environment decreased. Acoustic comfort evaluations were generally higher in colder and warmer environments. Warmer environments heightened the sensitivity to the acoustic environment and this effect gradually decreased as the sound pressure levels increased. Thus, based on empirical analyses, we compared the effects of outdoor thermal-acoustic parameters on comfort to provide experimental data support for further outdoor thermal comfort research.

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants’ thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants’ comfort.

Vernacular Passive Design With Natural Ventilation of Banjar Housing for Thermal Comfort

Thermal comfort research in Indonesia is known between 23 C and 25 C for dwelling buildings. As tropical weather is characterized by high humidity, high temperature, and intense solar insolation; therefore, traditional tropical housing is predominantly dependent on natural ventilation and passive cooling for thermal comfort. In the literature and practice, there is a gap in knowledge on traditional Banjar vernacular housing. Therefore, a thermal comfort field identification survey was conducted in the Balai Laki House one of the 11 types of traditional Banjar, which included information on the use of building space layout. The measurement results concluded that the category of thermal comfort is in the comfortably warm range, with the THI (Temperature Humidity Index) temperature range between 26,24 - 27,06 C . In addition, the upper threshold for comfortable warm conditions is indicated range of 27,29 - 31,28 C . The results revealed that the efficacy of traditional passive design techniques would not be sufficient to achieve thermal comfort in the predicted future climate scenario. For this reason, the authors suggested that the passive design techniques of Banjar vernacular housing need to be improved, with innovative solutions in order to cope with the changing climate.

A data-driven framework for thermal comfort assessment method based on user interaction

The rapid development of smart home systems requires a transition of thermal comfort studies. A feasible, user-friendly, consumer-oriented thermal comfort assessment method for large-scale residential applications is extremely urgent. However, most studies of thermal comfort models have focused on large commercial buildings. The application and deployment of such methods often rely on multiple prerequisites like relatively steady thermal conditions, regular energy consumption schedule, and additional sensor information. While situations are different in residential scenarios. In this paper, over 100 thousand air conditioner users were analyzed and a fundamental but overlooked question in thermal comfort research was established. In the household environment, the thermal condition is more complicated. Difference in age, gender, and usage preference leads to diversity in individual thermal comfort. Furthermore, introducing more sensors for better comfort prediction performance is not acceptable both from the cost perspective and the user perspective. To bridge the above missing gap, a novel thermal comfort assessment framework combining user interaction and metric learning was constructed. The proposed framework can be used to construct thermal comfort assessment systems by exploiting user interaction actions, which is a low-cost alternative and complementary to the traditional methods based on thermal equilibrium. The ease of construction makes the framework easy to integrate into smart home systems, addressing the difficulty of applying thermal comfort studies in residential scenarios.

Experimental evaluation of thermal adaptation and transient thermal comfort in a tropical mixed-mode ventilation context

Mixed-mode ventilation offers a promising solution for achieving comfortable indoor environments in an energy-efficient manner. However, in the tropics, characterized by a year-round hot and humid climate, opportunities for natural ventilation (NV) are typically limited to specific hours, necessitating operational mode switches on an intraday basis. Much of the thermal comfort research on mixed-mode ventilation relies either on cross-sectional data collected from different subjects or longitudinal data spanning a few seasons. This raises an open question: Can occupants thermally adapt when switching between NV and air-conditioning (AC) modes within a single day? To address the gap, our experimental study engaged 57 tropically acclimatized subjects, exposing them to combinations of five operational modes and four ceiling fan speeds (0.15-1.15 m/s) over an eight-hour timeframe. The results revealed that the subjects preferred a Standard Effective Temperature (SET*) that was 2-3 °C higher when operating in the NV mode compared to the AC modes, indicating thermal adaptation within the same day and in the same space. Specifically, the adaptation process was observed to stabilize between 35 to 45 mins following a mode switch. These findings contribute to the optimization of thermal comfort in mixed-mode controls, considering the dynamic characteristics of thermal adaptation.

Thermographic cameras for thermal comfort applications: simulated and experimental spectral response errors of various long-wave infrared detectors

Modern remote temperature sensing in the form of infrared imaging has become a widely used and important technique, with the ability to measure and characterize important but unseen Radiant heat. As more Long-wave Infrared (LWIR) detectors come to market aiming to meet a wide array of needs and goals, there is a need to differentiate and appraise LWIR detectors based upon the specific needs of thermal comfort research. While most detectors measure in the range of 8-14 μm, only 37.6% of the emitted energy of a blackbody at 300 K is contained in this spectral range. Thus, inherent to the operation of nearly all infrared detectors and cameras is an assumption about the emission curves of the objects sensed. Many materials in the built environment deviate significantly from the blackbody assumption, and the error due to this deviation is one which generic gray-body emissivity corrections are unable to fix — it is akin to taking black-and-white images with only the red channel of a camera, and using exposure compensation to correct the image to attempt a true monochrome rendition: there is simply missing information and the adjusted image will still be very clearly wrong. In this paper, we aim to evaluate by simulation and experiment the potential errors in infrared thermography used to drive thermal comfort heat transfer calculations due to intrinsic spectral assumptions of LWIR detectors.

Estimating local thermal insulation of clothing garments: Modelling and application

Clothing influences the heat exchange between the human body and the environment, and the thermal resistance of clothing is typically unevenly distributed across different body parts. The determination of local clothing insulation values is critical for the operation of multi-segment human thermoregulation models to obtain accurate thermophysiological parameters. As current standards only consider overall clothing insulation for the entire body, estimating local clothing insulation in field studies and human experiments remains difficult. In this study, a method for estimating the local thermal insulation values of garments using their overall insulation values was proposed, and its practical application for determining local insulation of ensembles was further presented. Eight garment types (excluding female-specific garments such as skirts and bras) were classified according to the main covered area of the human body. Based on the thermal manikin test results of 75 garments, prediction models for local insulation at different body parts were developed for various types of garments using the overall insulation values. For practical applications, the estimation method was applied to typical garments in the ISO 7730 standard to obtain reference local insulation values. The local insulation of ensembles can finally be calculated by combining the regression models between the local insulation of the ensemble and the sum of the local insulation of the contained garments. This study can help determine standardized local clothing insulation, providing validated input parameters for heat transfer analysis of the human-clothing-environment system and local thermal comfort research.

Occupancy and Thermal Preference-Based HVAC Control Strategy Using Multisensor Network

Human-in-the-loop Heating, Ventilation and Air Conditioning (HVAC) control-based methodologies have gained much attention due to continual discomfort compliance of occupants in residential and commercial buildings; spawning thermal comfort research interest in leveraging emerging advanced technologies to address the prolonged problem of discomfort and energy efficiency. In the past, thermal comfort studies have been conducted to determine the thermal sensation, preference and comfort based on the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database II and customized dataset through machine learning. The ASHRAE Database II is an open-source database that includes sets of objective indoor climatic observations with corresponding subjective evaluations by the building occupants who were used as subjects in experiments. Environmental parameters and occupants’ skin temperature have been used to develop machine learning algorithms to predict thermal comfort indices in both indoor and outdoor settings. However, none of these studies have investigated merging environmental parameters and thermal images to predict thermal comfort indices of occupants. In this study, the holistic understanding of individuals thermal comfort environment was considered by fusing analog environmental sensors and thermal images captured at the time of the subjective measurement. Wavelet scattering features were obtained from the occupants’ thermal image surroundings and joined to the environmental parameters. This research developed different machine learning models, processing methods and evaluated the results based on the fused dataset. The results show the possibility of real time prediction of occupancy and thermal preference through classical machine learning, and stacked models with high accuracy. The proposed framework achieved an estimated 45% mean energy savings during a ten-day energy analysis.

Examining thermal comfort levels and ASHRAE Standard-55 applicability: A case study of free-running classrooms in Abuja, Nigeria

Most thermal comfort research has traditionally focused on office and commercial buildings as opposed to educational facilities. Due to the high population density in schools and the undesirable impact an unsuitable thermal setting can have on performance, teaching and learning, providing thermal comfort in school facilities is crucial. Considering the above information, this study aims to collect empirical data from secondary schools in Abuja’s hot and dry climate to evaluate thermal comfort settings for students in naturally ventilated classrooms and the applicability of ASHRAE Standard-55 in the area. To achieve this, field investigations were conducted in free-running classrooms from four secondary schools. The study involved 1448 students drawn from 41 classrooms. Data collection involved measuring classroom thermal comfort variables and respondent survey, simultaneously performed while students were learning in the classroom. Findings revealed none of the studied classrooms’ thermal conditions met the ASHRAE Standard-55 comfort range. However, 44% of students felt comfortable. The study indicated a regression-neutral temperature of 28.8°C and a ‘comfort temperature’ range of 26 to 31°C. The findings of this research could form the foundation data for a local thermal comfort standard. However, the prior thermal experiences of respondents were not investigated in this study.

Modelling the Electric Bus Charging Network Requirements for HVAC Purposes

Wider use of electric buses is hindered by necessity to provide cabin heating for the passengers during winter months, which in cold climates uses up as much energy as driving, thus significantly reducing bus driving range and requiring larger traction batteries, which are expensive. When the lifetime operational costs are included, unless they are heavily subsidized, the battery electric buses have troubles competing with internal combustion engine (ICE) buses in cold weather conditions. For typical ICE buses, the power capacity for heaters is in the range of 50 kW. It would be possible to increase the driving range by using heat accumulators to provide energy for vehicle thermal requirements. These heat accumulators could be recharged in bus stops using wireless charging to minimize battery size. This article describes the results of a mathematical model developed to determine optimum wireless charging power requirements for heat accumulators. The model is created for public transportation system in Riga city based on weather data in years 2017–2022 to provide passenger thermal comfort. The model simulates energy flows for bus movement and heating purposes using worst-case scenario approach. The model analysed 198 916 bus stop data, which were pertinent for weekday travels in Riga city. The analysis covered 1716 individual bus stops and 448 routes. The results showed that the charging availability during the day varied from 3 % to 55 % and on average the total energy needed for heating would be 75.6 kWh. However, in the worst-case scenario, the number rises to 237 kWh making the system too expensive for practical applications. During the research there is a very limited availability of research regarding bus heating requirements. Most of the research on thermal comfort in busses are done in hot climate and consequently mostly concerns air conditioning. The thermal comfort research about cold weather is predominantly about buildings and indoor comfort and could not directly apply, as clothing should be considered. Also, the research shows that the temperatures for comfort are lower for short haul vehicles than for the long-haul ones. All these factors strongly indicate that current conventions on temperature requirements for buses are outdated and coming from ICE buses where the heat came from the engine and was free. Therefore, the next studies should include field research analysing passenger thermal comfort levels in buses in winter to explore if there are additional opportunities for energy savings in bus HVAC systems.

Urban Building Thermal Comfort Research Based on ArcGIS and Building Parameters: Analyzing and Improving Measures

Urban Building Thermal Comfort Research Based on ArcGIS and Building Parameters: Analyzing and Improving Measures

Natural ventilation versus air pollution: assessing the impact of outdoor pollution on natural ventilation potential in informal settlements in India

Despite the proven benefits of natural ventilation (NV) as an effective low-carbon solution to meet growing cooling demand, its effectiveness can be constrained by poor outdoor air quality. Here, we propose a modeling approach that integrates highly granular air pollution data with a coupled EnergyPlus and differential equation airflow model to evaluate how NV potential for space cooling changes when accounting for air pollution exposure (PM2.5). Given the high vulnerability of low-income populations to air pollution and the dearth of energy and thermal comfort research on informal settlements, we applied our model to a typical informal settlement residence in two large Indian cities: New Delhi and Bangalore. Our results indicate that outdoor PM2.5 levels have a significant impact on NV potential especially in highly polluted cities like New Delhi. However, we found that low-cost filtration (MERV 14) increased the NV potential by 25% and protected occupants from harmful exposure to PM2.5 with a minor energy penalty of 6%. We further find that adoption of low-cost filtration is a viable low-carbon solution pathway as it provides both thermal comfort and exposure protection at 65% less energy intensity—energy intensity reduced to 60 kWh m−2 from 173.5 kWh m−2 in case of adoption of potentially unaffordable full mechanical air conditioning. Our work highlights ample opportunities for reducing both air pollution and energy consumption in informal settlements across major Indian cities. Finally, our work can guide building designers and policymakers to reform building codes for adopting low-cost air filtration coupled with NV and subsequently reduce energy demand and associated environmental emissions.