We conducted a field study to monitor CO2 concentrations spatiotemporally in a lecture theatre, to explore its implications for Indoor Air Quality (IAQ), particularly in relation to airborne pathogen transmission. It is widely recognized that ensuring adequate ventilation in buildings can reduce the probability of airborne transmission, with indoor CO2 levels serving as a valuable indicator of ventilation effectiveness. While the temporal evolution of CO2 concentrations has been well-documented in the literature, to the best of our knowledge, the spatiotemporal distribution remains less understood, especially in large spaces (>10 m) that are poorly ventilated (air change rates below approximately 1.0 h(-)(1)) and air-conditioned buildings. Hence, we analyzed spatiotemporal CO2 variations across four cases with different occupancy levels and seating arrangements using field study data. Our data reveal how factors such as number of people and their seating configurations, asymmetrical airflow vents in a tiered seating-designed room, and buoyancy-driven ventilation flow through an open doorway influenced spatiotemporal CO2 variations for a given room geometry of our testbed. Moreover, we developed a spatiotemporal reduced-order model that can simulate the spatiotemporal distribution of pathogen quanta using real-world data of CO2 concentrations. This derived model presented a linear relationship between CO2 concentrations and pathogen dispersion. Moreover, we explore the IAQ-energy trade-off by using airborne infection probability as a proxy for health outcomes and sensible ventilation load as a proxy for energy demand. Based on this analysis, we propose design guidelines that aim to balance IAQ with energy.

This study addresses the urgent need for comprehensive climate education amid a climate emergency. Human (energy) behaviors are developed from childhood and early adulthood. This study hypothesizes that transcending a nation’s net-zero energy ambition can be accomplished through experiential education. An Urban Governance Lab plus nEt-Zero Energy league model is introduced. Various behavioral interventions are designed based on the principles of serious games. Discussions provide rich narratives on how a nation with so many diverse communities can forge a rapid net-zero transition. The blended multi-disciplinary STEM education can drive energy citizenship in campus-like communities. A scenarios-based analysis demonstrating the potential of the proposed model in shaping energy behavior in young citizens leading to net zero is presented. The results from the scenario analysis present optimistic evidence underlining how campus-like communities driven by bottom-up initiatives can realize net-zero ambition beyond hope.

Abstract. Low-cost sensors for particulate matter (PM) monitoring have gained popularity due to their affordability, compact size, and low power requirements. These sensors typically offer the capability to collect data at sampling rates that can be adjusted according to the application. However, the effect of varying the sampling frequency on sensor performance has not been thoroughly examined. This study explores how variations in sampling frequency influence the performance of low-cost PM sensors and identifies some possible use cases for different sampling rates. During this study conducted over a one-month period, data from five SPS30 sensors was collected at 15-second intervals and then aggregated into 5, 10, 15, 30, and 60-minute intervals. During the study, hourly PM2.5 levels ranged from 117 µg/m3 to 303.3 µg/m3, with significant diurnal variations, influenced by temperature and humidity. It was found that changes in sampling frequency had minimal impact on sensor performance, as evidenced by comparable linearity and error metrics across different sampling intervals. However, the study also revealed that short-lived plume events could be missed at lower sampling frequencies. This suggests that for monitoring gradual changes in PM2.5 levels, higher sampling frequencies do not necessarily improve measurement accuracy, but are crucial for capturing transient events. This study underscores the importance of optimizing sampling frequency based on specific monitoring objectives and the need to balance power consumption with data resolution, particularly in remote or battery-based deployments.

Climate warming is raising global temperatures by 0.2°C every decade, generating severe heat waves and health risks. In India, urbanization has increased heat and humidity. The Urban Heat Island effect in Delhi puts many people at risk for heat-related health issues. This research identifies Delhi’s high-vulnerability zones based on people’s environmental, demographic, and socioeconomic conditions. The study analyzed vulnerability variables such as land surface temperature, land use, land cover, population density, and income level to identify high-risk zones in Delhi using the “unweighted additive overlay” approach. It is found that heat stress is most prevalent in 40 wards in Delhi’s central-western and eastern regions. These findings underline the necessity for adaption methods and specialized urban design strategies and policies for heat reduction for those with weak adaptive ability. The study would assist officials in providing heat relief to high-vulnerability wards and include heat mitigation methods in Delhi’s new master plan.

Heat waves are rising in intensity and frequency. They could break the human survivability limit in India in the coming years. The goal of this paper is to understand the extreme thermal comfort adaptation of ascetics from Jain Svetambara sects in hot and dry as well as warm and humid weather in India to help the vulnerable populations beat the heat. A total of 65 subjects were interviewed in Delhi, Jodhpur, Siriyari and Ahmedabad between May and September 2023. Surveys were carried out with measurements of the indoor environment according to the adaptive thermal comfort methodology. Around 75% of the subjects had a neutral or a cooler thermal sensation while the thermal comfort index, UTCI, was in the strong to very strong heat stress range. Ninety percent of the subjects found these thermal environments to be acceptable. Two-third of the subjects preferred no change in the humid conditions when more than 50% of them acknowledged the presence of higher humidity in their indoor environment. An adaptive thermal comfort model proposed in this study suggests that it is possible to go beyond the IMAC-R model to further reduce the cooling needs of the warming world.

Climate change is leading to severe heat waves in India, affecting a large vulnerable population and impacting their health and well-being. The recent adaptive thermal comfort research for Indian climates suggested that the people living in residential buildings can adapt to indoor temperatures upto 35 ℃. The Jain ascetics in India have been leading their life without the use of electricity for hundreds of years, irrespective of the temperatures. In this study, thermal comfort surveys with 20 monks and nuns were carried out during summer for the composite climate of Delhi. 90% of the subjects expressed acceptability of the thermal conditions while the indoor operative temperatures varied between 35 ℃ and 40 ℃. This study should offer hope to people globally that if we can gradually adapt to the rising temperatures, we may be able to move on with our lives without affecting our comfort or health.

In India, the ill effects of a poor indoor environment are seen as the cause of about 2 million premature deaths per year, wherein 44% are due to pneumonia, 54% from chronic obstructive pulmonary disease (COPD), and 2% from lung cancer. Conventional studies typically take lesser consideration of indoor occupancy than would be found in real surroundings. These studies often evolve in artificial conditions, which lack authenticity. This work uses field research and a data-driven approach to assess contaminants in inhabited indoor spaces, such as carbon dioxide (CO2) and particulate matter (PM2.5) along with indoor climate measurements of Indoor Operative Temperature (IOT), Relative Humidity (RH), and air velocity. This paper reports the findings of a pilot field study carried out to understand the effect of CO2, IOT, PM2.5, RH, age, sex, general health condition, and perception of odours on occupant’s perception of IAQ and perceived thermal comfort, during the summer monsoon season in the composite climate of Delhi. Participants were asked to rate their perceived thermal comfort on standardized scales and provide PIAQ votes based on their satisfaction with indoor air quality. Data analysis included correlation analyses and multiple regression modelling. Our findings reveal a statistically significant inverse relationship between perceived Indoor Air Quality (PIAQ) votes and perceived thermal comfort. Building occupants who rated the indoor air quality more favourably (higher PIAQ votes) tended to report lower levels of perceived thermal comfort, while those who expressed dissatisfaction with indoor air quality reported higher thermal comfort levels.

Presently, 2–3% of the middle-aged urban Indian population is diagnosed with obstructive sleep apnea (OSA). This paper aims to design and develop a low-cost mini-CPAP device using design thinking principles. The user research reveals that the significant challenge of the continuous positive airway pressure (CPAP) device used to treat OSA is its cost and size, making it challenging for the user to make it a part of their routine. It discusses the various CPAP devices available in the market, the working of the existing CPAP, prototyping and testing of developed low-cost mini-CPAP devices. The proposed device is a newly designed low-cost manual CPAP for people diagnosed with OSA. The proposed mini-CPAP would reduce the manufacturing cost by two times the price of existing CPAP devices. The experimental results show that the proposed device works similarly to the existing device in all aspects, such as the pressure and the flow rate. This work would pave way for improving the user experience by building an auto-CPAP device in future.

Improving the workspaces for “environmental ergonomics” is essential for better occupational health and safety, especially in populated and developing countries like India. Moreover, controlling airborne diseases in indoor environments has become one of the significant concerns during the recent COVID-19 pandemic. Enhancing indoor ventilation is one of the most effective ways to mitigate the airborne transmission risk. In this study, experiments were planned and carried out in smaller volume rooms inside a university building, such as faculty cabins, using CO2 sensor monitoring. CO2 measurements are taken in 16 different ventilation instances including doors, windows, and exhaust fans. Using the ASTM tracer gas equation, these CO2 values are used to determine the ventilation rates in each circumstance. The Wells-Riley probability model is used to determine the probability of infection, and the findings for all the 16 instances are provided. When all the doors and windows are closed, the exhaust is switched off, and the mask is not worn; the mean CO2 concentration is the highest, thereby increasing the risk of airborne transmission. This study finally exhibits and proposes a design paradigm that specifies which method to use under certain scenarios.

The COVID-19 pandemic forced everyone to isolate themselves and confine their lives to enclosed spaces to protect themselves from the outbreak and spread of the virus. Contrary to this, recent studies have shown that restricting ventilation in a space can lead to health risks resulting from CO2 build-up from exhaled breath. There have also been a substantial number of multidisciplinary research studies that have established CO2 exhalation in an enclosed room as a proxy for COVID-19 and other similar variants of viruses. We conducted experiments to understand the spatio-temporal spread of CO2 inside a car in the hot and dry climate of Jodhpur and a bedroom in the composite climate of New Delhi during the winter season. The experiments were carried out using reference-grade sensors and custom-built devices for indoor use, which measured the ambient temperature, relative humidity, and CO2 levels. On analyzing the findings from our studies, we observed that even seemingly harmless situations, such as an enclosed vehicle and a non-ventilated bedroom space, could lead to harmful levels of CO2 built-up of over nine times and three times over the acceptable threshold of 1000 ppm for a car and a bedroom, respectively. Reassessment of the design guidelines underlying environmental ergonomics is advised for automobiles and residential spaces.

During endotracheal intubation and bronchoscopy medical operations, healthcare professionals are more susceptible to airborne infections such as COVID-19, tuberculosis, and flu. In response, the authors of this paper attempted to develop a product idea that could reduce this infection risk during these types of procedures. This study utilizes the “intubation box” infection control model as the basic design. The authors investigated its limitations and proposed a redesign of it by adding certain elements/functions to match specific user research and literature study requirements. This study is based on the intersection of “design thinking” and “concept development procedure,” which includes design research techniques like product critiquing, contextual user research, literature review, design-centred domain expert meetings, affinity diagram, scamper sketch methodology, concept development methodology, concept screening, and model-based design (MBD) techniques. Finally, this conference paper offers a fundamental design concept that designers may use to work on this problem statement in the future.

Building energy benchmarking is a proven energy management strategy that can positively quantify - and relatively quickly provide objective and reliable information on building energy use and the benefits of improvements. Energy benchmarking is a growing practice in many cities across the world as part of the energy disclosure policy. Many cities have already started to reap the benefits of energy benchmarking with up to 8% energy savings. However, there remains a gap in the widespread adaptation of benchmarking methodologies in terms of their scalability and standardization (data acquisition, analytics, validation, reporting, and automation). Several government organizations, industry practitioners, and researchers are working towards building a holistic and standardized energy benchmarking system.

India is witnessing unprecedented urban growth with 30% of its population already residing in urban areas. With forecasts that this rate will increase in the near future, the energy demand of the country will be enormous. In order to meet the national and international energy targets, it is crucial that India focuses on its energy policies across sectors. A proven way forward is to introduce energy benchmarking in the policy mainstream for all sectors. In this paper, we discuss the challenges, opportunities and the strategic way forward for energy benchmarking, particularly in the building sector. We look into the existing situation concerning public governence, awareness, regulations, and energy certification and propose the way forward in terms of business oportunities, and synergistic collaboration between stakeholders. Finally, we introduce The Collective Voices for Buildings in India (CVBi) and present the strategic plans going forward.

Building energy benchmarking is a proven energy management strategy that can positively quantify - and relatively quickly provide objective and reliable information on building energy use and the benefits of improvements. Energy benchmarking is a growing practice in many cities across the world as part of the energy disclosure policy. Many cities have already started to reap the benefits of energy benchmarking with up to 8% energy savings. However, there remains a gap in the widespread adaptation of benchmarking methodologies in terms of their scalability and standardization (data acquisition, analytics, validation, reporting, and automation). Several government organizations, industry practitioners, and researchers are working towards building a holistic and standardized energy benchmarking system. The first ACM international workshop on "Advances in Building Energy Benchmarking" invited papers on the current developments in building energy benchmarking. Researchers and practitioners working on data acquisition technology and processes, data sharing protocols and policies, benchmarking modeling methodologies, standardization and widespread adoption, strategy and collaboration, case studies, open source platforms and crowdsourcing are invited to participate. The inaugural edition of this workshop series aims to explore the existing challenges in data acquisition techniques in emerging economies. The workshop format is designed to foster discussion on the widespread adoption of energy benchmarking methods and forge new collaboration and strengthen existing ones by bringing together researchers and practitioners from diverse backgrounds to address related challenges and guiding new low-carbon transition pathways relevant to developing nations.

In a previous paper, we presented a novel approach to validate the capability of the biometeorological index, Universal Thermal Climate Index (UTCI), to predict the likelihood of urban dwellers to be outside in a public space for the heating dominated climate of Cambridge, MA. Occupancy patterns were recorded based on Wi-Fi data. The present study extends this approach to the hot and arid climate of United Arab Emirates (UAE) to evaluate the effect of outdoor evaporative coolers on resident presence in a public courtyard. Over a period of ten months, outdoor Wi-Fi access point data was collected in the public courtyard located on a university campus in Abu Dhabi. An analysis of the resulting MacID probes yields a population of 1200 regulars and 3800 visitors present in the courtyard at some point during the study period. Coincident UTCI simulations using ENVI-met strongly correlated with the number of regulars present during lunchtime both during times when the evaporative coolers were on (R-2 = 75%) and off (R-2 = 61%). Lunchtime attendance peaked for UTCI values in the thermal comfort range of around 24 degrees C during all seasons. The outdoor evaporative coolers were able to bring the UTCI down from very strong heat stress to between thermal comfort and moderate heat stress range. These findings confirm that UTCI can be used as a reliable environmental performance metric to support the design and preservation of comfortable outdoor spaces both in a hot and a cold climate, across a variety of cultural settings.

Air-conditioning represents the major component of energy consumption in commercial buildings in India. A methodology is proposed to reduce the space cooling load by optimizing the building design using incremental integrated design approach and experimental design methods. This methodology is applied over a three story building in New Delhi climate. For the building, passive strategies are able to reduce the cooling load by 50% over the base case and low energy cooling techniques are able to reduce the cooling load by 50% over the passive case using incremental integrated design. Building is then optimized to use natural ventilation to the extent possible, while considering the uncertainty in input parameters, using design of experiments based methods. It is found that during winter months, building can be operated just using natural ventilation during office hours, while maintaining thermal comfort. Natural ventilation is able to reduce the energy consumption by about 15% over the incremental design case. The final achieved mixed mode design consumes 55% less energy, better daylighting, views and uses natural ventilation for 30% more hours as compared to the baseline case.

This study presents a novel approach to validate the capability of biometeorological indices to predict the likelihood of urban dwellers to be outside during midday. Over a period of ten months three Wi-Fi scanners were used in a public courtyard in Cambridge, MA, to record outside dwelling patterns. Based on encrypted MacIDs courtyard attendees could be divided into 16,000 regulars and 676,000 visitors. Universal Thermal Climate Index (UTCI) predictions based on a combination of measured microclimatic conditions and mean radiant temperature simulations using ENVI-met were shown to strongly correlate with the number of regulars present during lunchtime with coefficients of determination (R2) of 92% during spring and 70% during summer/fall, respectively. Lunchtime attendance peaked for UTCI values in the thermal comfort and moderate heat stress ranges. In parallel, the probability for regulars to have lunch outside more than doubled during those UTCI conditions and the median lunchbreak length increased from 8 min to 12 min. These findings suggest that UTCI can be used as a reliable environmental performance metric to support the design and preservation of comfortable outdoor spaces. The reported use of public Wi-Fi data can help city governments to better understand – and potentially improve – the use of outdoor spaces while maintaining the privacy of their constituents.

Building simulation based optimization involves direct coupling of the optimization algorithm to a simulation model, making it computationally intensive. To overcome this issue, an approach is proposed using a combination of experimental design techniques (fractional factorial design and response surface methodology). These techniques approximate the simulation model behavior using surrogate models, which are several orders of magnitude faster than the simulation model. Fractional factorial design is used to identify the significant design variables. Response surface methodology is used to create surrogate models for the annual cooling and lighting energy with the screened significant variables. The error for these models is less than 10%, validating their effectiveness. These surrogate models speed up optimization with genetic algorithms, for single- and multi-objective optimization problems and scenario analyses, resulting in a better solution. Thus, optimization becomes possible within reasonable computational time with the proposed methodology. This framework is illustrated using the case study of a three-storey office building for New Delhi.

Building thermal simulation based parametric methods are computationally intensive for optimizing the building design. This work uses experimental design techniques, i.e. fractional factorial design and response surface methodology, for sensitivity analysis and surrogate modeling respectively. These techniques find the solution in a reasonable time. Their application for building design optimization has not been found in the literature before. Fractional factorial design has been used to identify the significant design variables. These variables are used to form a correlation for annual cooling load prediction, using response surface methodology. These methods are illustrated using two cases to minimize the life cycle cost of a single-storeyed, air-conditioned, solar powered, detached home, with 64 sq. m. floor area, for the warm and humid Mumbai climate. For this climate, window solar heat gain coefficient, window to wall ratio, overhang depth and roof reflective coatings turn out to be the most important among the design variables used for this case study. The created response surface models show an error of less than 5% for more than 99% of the test data, which is comparable to other such models. Strategies are suggested to bring the error for the entire search space to less than 10%. Life cycle cost minimization using the model for case 2 does 12 million iterations as opposed to 250 iterations using a parametric EnergyPlus simulation run at the same time. The solution is better and the design achieved is also different. The optimum design has a cooling load of 55 kWh m-2 yr-1, while it varies from 46 to 118 kWh m-2 yr-1. This work adds an intuitive method for building design and opens up possibilities for optimization.

Appropriate building design for natural ventilation can reduce discomfort, while saving energy on airconditioning. Parametric building simulation analysis for natural ventilation typically consists of several design variables and input parameters with uncertainty, making it computationally intensive. For optimizing the building design within a reasonable timeframe, design of experiment techniques based methodology is proposed. Firstly, the significant design variables and input parameters are identified. For these significant factors, correlations are formed to predict the statistical distribution of indoor operative temperatures. These correlations are used to find the design, which minimizes discomfort hours, as per adaptive comfort guidelines.