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Building Ventilation and Air Quality: Integrated Approaches for Human Health,...
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Building Ventilation and Air Quality: Integrated Approaches for Human Health, Energy Efficiency and Sustainable Environment

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 371

Special Issue Editors

Dr. Muhammad Azher Hassan

E-Mail Website
Guest Editor
Tianjin Key Laboratory of Indoor Air Environmental Quality Control, Tianjin University, Tianjin 300072, China
Interests: indoor air pollution; volatile organic compounds; ozone and particulate matters environmental pollution; machine learning; simulations and modelling
Dr. Tariq Mehmood

E-Mail Website
Guest Editor
Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Department Sensors and Modeling, Max-Eyth-Allee 100, 14469 Potsdam, Germany
Interests: environmental pollution; air quality monitoring; pollution control
Special Issues, Collections and Topics in MDPI journals
Dr. Chenhua Wang

E-Mail
Guest Editor
School of Civil Engineering, University of South China, Hengyang 421001, China
Interests: HVAC; CFD; indoor air quality; ventilation

Special Issue Information

Dear Colleagues,

The importance of building ventilation and indoor/outdoor air quality has grown dramatically with more frequent extreme weather, heightened post-pandemic health awareness, and the fact that people spend approximately 90% of their time indoors. Indoor pollutant levels often exceed outdoor concentration due to lower ventilation rates as well as emissions from building materials, occupant activities, and chemical reactions. Also, high rise and modern buildings contribute to the urban heat island (UHI) effect through heat-absorbing materials and impervious surfaces, which worsen local air quality by increasing ozone formation, pollutant concentrations, and higher energy demands for cooling.

Indoor and outdoor environments are tightly coupled through infiltration, natural pressure differences, and mechanical ventilation. Pollutants, heat, moisture, bioaerosols, and pathogens readily move across the building envelope. This reality calls for an integrated indoor–outdoor air quality approach to create healthier, comfortable, energy-efficient, and climate-resilient buildings that support Sustainable Development Goals.

Recent advances in artificial intelligence (AI), machine learning (ML), low-cost sensors, and digital twins make it possible to monitor indoor and outdoor air quality in real time, predict future conditions, provide occupant-centered control, and apply demand-controlled ventilation for comfort — all while protecting health and reducing energy use in nearly zero-energy buildings. Hence, we welcome original research articles, review papers, and meta-analyses on topics including, but not limited to, the following:

  • Indoor–outdoor pollutant exchange and coupled exposure dynamics;
  • Performance of natural, mechanical, and hybrid ventilation systems under present and future climates;
  • Low-cost sensor networks, real-time monitoring, and data fusion methods;
  • Modeling airborne pathogen transmission and ventilation strategies for infection control;
  • Filtration, removal, and infiltration of PM2.5, PM1, ultrafine particles, and other aerosols;
  • Sources, fate, infiltration, and control of VOCs, O3, CO2, NOx, or emerging pollutants;
  • AI/ML applications for predictive modeling, fault detection, and personalized ventilation;
  • Energy-efficient ventilation and thermal comfort in nearly zero-energy and passive modern buildings;
  • Effects of urban greenery, green walls, and building design on indoor and local air quality;
  • Effects of building designs on UHI, air quality, thermal stress, or indoor environments;
  • Outdoor air quality modeling, long-term monitoring, and its impact on indoor infiltration;
  • Indoor air quality modeling (ML/AI, CFD) for source apportionment and control;
  • Policy, standards, life-cycle assessment, and post-occupancy evaluation of ventilation performance;
  • AI-driven smart buildings, demand-controlled ventilation, climate-resilient indoor environments, and low-carbon buildings.

We look forward to receiving your valuable contributions.

Dr. Muhammad Azher Hassan
Dr. Tariq Mehmood
Dr. Chenhua Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • indoor air quality
  • outdoor air quality
  • AI/ML applications
  • smart buildings
  • thermal comfort
  • pollutants removal
  • energy efficient ventilation

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Published Papers (1 paper)

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Research

39 pages, 6701 KB  
Article
Multi-Velocity Ceiling Diffuser for Orthopedic Procedures or Ventilation: An Integrated CFD, Performance Assessment, and Surrogate Modeling Framework
by Hasan Mhd Nazha, Hanan Mukhaiber, Mhd Ayham Darwich and Marah Salamie
Buildings 2026, 16(10), 1937; https://doi.org/10.3390/buildings16101937 - 13 May 2026
Viewed by 77
Abstract
Operating room ventilation is a key engineering factor in maintaining clean air environments. This study presents an integrated three-part methodology combining Computational Fluid Dynamics parametric analysis, performance assessment with effect size analysis and multi-criteria decision analysis using quantitative engineering metrics, and surrogate modeling [...] Read more.
Operating room ventilation is a key engineering factor in maintaining clean air environments. This study presents an integrated three-part methodology combining Computational Fluid Dynamics parametric analysis, performance assessment with effect size analysis and multi-criteria decision analysis using quantitative engineering metrics, and surrogate modeling for thermal effect propagation in an orthopedic operating room. Simulations were conducted in ANSYS Fluent 2020 R2, benchmarking an existing local operating room against an ASHRAE 170-2021 compliant model, followed by parametric evaluation of four ceiling inlet configurations. The existing system exhibited critically low velocities (0.05–0.10 m/s) with a coefficient of variation of 0.73, indicating severe flow non-uniformity. The proposed Multi-Velocity Ceiling Diffuser—featuring a high-velocity core (0.40 m/s) over the surgical area and a low-velocity peripheral frame (0.20 m/s)—achieved 85% coverage of the ASHRAE-recommended velocity range (0.20–0.30 m/s), a coefficient of variation of 0.14 (81% improvement), and 62 air changes per hour, representing an 86% reduction in supply airflow compared to a full-ceiling system. Effect size analysis confirmed that MVCD performance shows large practical differences from smaller inlet designs (Cohen’s d ≥ 0.41) and negligible difference from full-ceiling systems (Cohen’s d = 0.05). Multi-criteria decision analysis—with feasibility and cost quantified using engineering estimates (ductwork area, downtime days, standardized cost data)—ranked MVCD as optimal under the modeled assumptions (composite score = 0.84), outperforming the existing system (0.59) and full-ceiling design (0.51). To address the isothermal assumption limitation, a Random Forest surrogate model was implemented as a differentiable approximation strategy for parametric uncertainty propagation. Under non-isothermal conditions, the MVCD is predicted to maintain a spatial median velocity of 0.19 m/s (5th–95th percentile range: 0.17–0.21 m/s) and 71% ASHRAE compliance (parameter sampling range across literature-derived distributions: 63–78%). Achieving ASHRAE velocity criteria is an engineering surrogate for ventilation effectiveness; the relationship between these metrics and clinical infection outcomes depends on multiple factors beyond airflow, including surgical technique, patient factors, and antimicrobial prophylaxis. No clinical inference is permitted from the present results. Experimental measurement in a physical MVCD-equipped operating room is required to validate these predictions prior to clinical implementation. Full article
(This article belongs to the Special Issue Building Ventilation and Air Quality: Integrated Approaches for Human Health, Energy Efficiency and Sustainable Environment)
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