https://orcid.org/0000-0002-0814-8662
The ASHRAE IAQ 2020 conference was the 19th in the series begun in 1986. It was originally scheduled to be held in September 2020, but was postponed until May 2022 and convened as a hybrid event with 140 in-person and 45 virtual participants, making it the best attended ASHRAE IAQ conference since 2010. The conference theme was Indoor Environmental Quality Performance Approaches – Transitioning from IAQ to IEQ. Keynotes and papers presented at the conference addressed all aspects of indoor environmental quality (IEQ): air quality, thermal environment, sound, and light and their effects on comfort and wellbeing. A special topical section of Science and Technology for the Built Environment including four expanded versions of papers submitted to the initial call for papers was published in August 2022. Due to the postponement of the conference, a second call for papers was made. This special issue includes expanded versions of five additional papers submitted to the second call. They are summarized below.
Cappelletti et al. developed a comprehensive questionnaire composed of consistent questions among the thermal, visual, acoustic and air quality domains and obtained more than 900 students’ responses about sensation, preference and comfort. Based on the analysis of subjective and objective data recorded, they were able to obtain correlations of the environmental parameters and students’ perception in all comfort domains. They were also able to understand the students’ preferred environmental conditions as well as cross-domain effects. Their results showed that air temperature, illuminance and sound pressure level were fairly well correlated with the sensation in the corresponding domain. They also demonstrated interference of CO2 concentration and illuminance on the thermal sensation and the effect of the sound pressure level on the visual sensation.
Van Hove et al. used a dynamic multizone indoor climate and energy simulation model to present model validation results and lessons learned from an in-situ empirical validation study of common indoor climate parameters (indoor air temperature, relative humidity and CO2 concentration) for an inhabited case study dwelling in The Netherlands. Their simulation results show that the latest generation of indoor climate and energy models in Modelica have great ability to accurately predict common indoor climate parameters in multizone inhabited dwellings subject to the availability of user behavior information. Evaluation metrics for the three studied parameters show excellent calibration criteria and the accompanying graphs corroborate the findings. The authors caution that in-situ monitoring for empirical model validation continues to be a real challenge.
Mao et al. present the findings of their study with a twofold aim involving the analysis of the performance of a conventional HVAC system through data analytics, followed by the exploration of the use of interpretable machine learning techniques for HVAC predictive control. They present a new Interpretable Machine Learning (IML) algorithm called Permutation Feature-based Frequency Response Analysis (PF-FRA). Their results demonstrate that the proposed model can generate accurate forecasts of room temperature levels by taking into account their historical information, as well as additional environmental and timeseries features. They use tools such as surrogate models and Shapley graphs to interpret the model’s global and local behaviors with the aim of increasing trust in the model.
Won et al. simulated the effects of ventilation system characteristics in an office space on the ability of an upper-room UVGI system to inactivate viral aerosols with UV-C susceptibility representative of coronaviruses. They found that UVGI reduced viral aerosol concentration by two orders of magnitude relative to the concentration without UVGI. Air change rates and air distribution strategy (mixing vs. displacement) had notable effects on the effectiveness of the UVGI system. For mixing ventilation, as the recirculation airflow rate increased from 0 to 5.3 h-1 for a room volume of 108 m3 with a fixed outdoor air change rate of 0.7 h-1, UVGI inactivation increased by 96.7%. Mixing ventilation with 100% outdoor air of 0.7 h-1 yielded airborne virus inactivation that was double that of displacement ventilation, due to enhanced air mixing.
Sarran et al. explore successes and challenges with current retrofit efforts, focusing on indoor environmental quality and occupants’ satisfaction with the technical installations. They carried out a survey of indoor environmental monitoring and semi-structured interviews in a Danish social housing development undergoing a deep energy retrofit. They found that the retrofit considerably improved winter thermal comfort and indoor air quality, but noted that overheating was a major concern in summer. They attributed this to problems associated with faults in mechanical ventilation units and the impact of occupants’ lack of knowledge of ventilation on manual control decisions, leading to actions including obstructing diffusers or disconnecting the units. In order to avoid such behaviors, the authors note that new retrofit efforts should pay particular attention to user friendliness of technical installations, clear communication of technical information to the residents and close monitoring of the installations’ performance and occupants’ satisfaction after move-in.
Planning is underway for the next conference in the series, to take place in 2025, again with a scope that broadly encompasses IEQ.
Fellow ASHRAE
Department of the Built Environment
National University of Singapore, Singapore
[email protected]
William Bahnfleth
Presidential Fellow/Life Member ASHRAE
Department of Architectural Engineering
The Pennsylvania State University, USA
[email protected]