Ceiling‐Mounted CO2 Sensing: Effect of Location and Stratification Temperature

My research team and I have been working on a research project, which finishes in August 2013. This project was the first awarded research project for which I served as the Principle Investigator during the beginning of my career. It holds a unique position in my heart and I would like to take this opportunity to share the significances and the main findings of this project with you. Demand-controlled ventilation (DCV) is a ventilation control strategy that provides automatic reduction of outdoor air (OA) intake below designed rates when the actual occupancy of spaces served by the system is less than the designed occupancy. American Society for Heating, Refrigeration, Air-conditioning Engineers (ASHRAE) Standard 90.1 [1] requires installation of DCV for densely occupied spaces and that the DCV system should comply with ASHRAE Standard 62.1 [2]. Many engineers have applied DCV in large office buildings, lecture rooms or conference rooms. However, there are many complexities and issues in applying DCV in multiple zones (MZs) with a recirculating heating, ventilation and air-conditioning (HVAC) system. Until the completion of this project, there was no recommended DCV control method for MZs in ASHRAE Standard 62.1 for design engineers to adopt or apply. Therefore, this research project was conducted to: (1) develop the fundamental equations for CO2-based DCV; (2) propose a CO2-based DCV for MZ HVAC systems and (3) evaluate the proposed DCV control strategies with energy simulation and airflow simulation. First of all, the validity of assumptions underlying CO2based DCV was validated. The literature review concluded that: (1) since the CO2 generation rate and odour generation rate are proportional,CO2 concentration can be adopted as a signifier of human odours in a space; (2) the bioeffluent generation rate is proportional to the number of occupants and their activity levels and (3) even though this research projectdoesnot include researching the types andaccuracyof CO2 sensors, we are aware of the facts thatmany commercial CO2 sensors that have been installed in the field have errors greater than 75ppm [3]. Therefore, more research work and development to optimize the CO2 sensors and to improve accuracy and reliability would be highly recommended. There are three control logics proposed and developed in this research project. They are:

A compensation model for an NDIR-based CO2 sensor and its energy implication on demand control ventilation in a hot and humid climate

In recent years, the quest has been focused on energy efficient building design. To achieve this in terms of high efficiency air conditioning schemes for hot climate cooling, the combination of variable refrigerant volume (VRV) with variable air volume (VAV) systems have become popular. In this paper, attention is focused on achieving good thermal comfort and indoor air quality (IAQ) combined with energy savings by using multi-zone VAV air conditioning (A/C) that incorporates a genetic based fuzzy logic controller (FLC). Experimental analysis based on a combined demand controlled ventilation (DCV) with economizer cycle (EC) was performed on an inverter driven multi-zone direct expansion (DX) VAV A/C system integrated with a fuzzy logic controller and optimized by a genetic algorithm (GA). The opening of the VAV box damper was controlled using the fuzzy logic controller. Based on the test results, the proposed fuzzy logic operated system maintained supply air temperature close to 13°C and an occupant zone at a consistent temperature of around 24 °C. In DCV mode, the concentration of CO2 was maintained between 950 ppm and 1040 ppm while, when the system was operated under a combined DCV-EC ventilation scheme, the CO2 concentration was maintained at between 350 ppm and 970 ppm. The experimental results suggested that CO2 concentration obtained experimentally was well within the permissible limit for the varying load conditions. Under the combined DCV-EC mode of ventilation, using a fuzzy-genetic algorithm, the maximum power obtained for the supply air fan and variable speed compressor was 415 W and 3.4 kW respectively. The compressor was totally turned OFF during the economizer cycle thus contributing to total power savings. The energy savings potential of the proposed fuzzy controlled multi-zone DX VAV A/C system yielded 70% and 89% under DCV and combined DCV economizer cycle ventilation modes respectively when compared with a constant air volume (CAV) A/C system operated under the DCV technique. The test results suggested that it was feasible for this fuzzy control methodology, integrated with the developed genetic algorithm, to provide a proper control of IAQ, thermal comfort and energy conservation.

PurposeAt the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).Design/methodology/approachThe method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.FindingsThe discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO2) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.Originality/valueFinally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO2 based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

With the advancement of communication system over the last 10 years, indoor air quality (IAQ) monitoring technology has advanced significantly, improving the monitoring system's real-time performance and lowering the possible effects of pollutants linked to health. "Incorporating the Internet of Things into these cutting-edge developing technologies therefore offers a great opportunity for the development of air quality systems, which require new networking models, strategies, and processes for multiple constraints with sophisticated sensing and communication abilities. A thorough analysis of the hardware requirements, communication methods, and architectures is necessary to handle reasonable data related to building inhabitants' daily activities. Research and understanding of the existing air quality systems serve in making choices by assisting in the matching of appropriate intelligent, adaptive, and reasoning technologies with data flow management. This article will include further details and a detailed examination of new communications protocols, networking systems, sensors, topologies, and technologies related to indoor and outdoor air quality systems. This article uses an intelligent communication system in the living environments to examine and evaluate the advancements in IAQ monitoring technology and the usage of communication technology in this area. The issues and difficulties with the IAQ monitoring system are also covered in this paper, which serves as a resource for researchers and encourages the quick and comprehensive advancement of IAQ monitoring.

Indoor air quality (IAQ) is a crucial determinant of health, which is of particular concern for low-income Black children, who are disproportionately exposed to asthma triggers in their indoor housing environment and have higher rates of asthma and poorer outcomes from the disease, indicating an environmental justice issue. However, guidelines for IAQ data collection vary between organizations, making assessments and comparisons difficult. This study consolidates recommended practices into one cohesive set of guidelines for monitoring IAQ. It outlines a structured approach for defining IAQ sampling objectives, identifying the most appropriate low-cost air sensors, determining optimal sensor placement in homes, developing data collection and analysis, and presenting and interpreting results. With indoor PM2.5 as a case study, the guidelines were used to determine sampling duration, analysis, and quality assurance in five households with pediatric asthma patients. The metrics illustrate PM2.5 concentration by the 90th percentile (with average concentration level from 4 to 109 μg/m3), daily average minutes of PM2.5 concentration exceeding recommended exposure limits of 0–134 min, daily average PM2.5 concentration of 1.8–82 μg/m3, and significant temporal variation across households. This study highlights the significance of employing low-cost air sensors to provide real-time notifications of IAQ, along with simplified monitoring guidelines for researchers, healthcare providers, and parents working to improve IAQ for households with asthmatic children, potentially reducing the frequency and severity of asthma attacks. The low-cost sensors and resulting metrics can direct interventions effectively and provide a basis for determining the efficacy of environment-based air quality interventions. Implications: People spend much of their time indoors, especially at home, making indoor air quality (IAQ) monitoring crucial for guiding actions that reduce asthma exacerbations, particularly among low-income households. Although low-cost air sensors are being widely used for real-time IAQ monitoring, most existing guidelines focus on occupational settings rather than residential environments, making implementation difficult. This study develops comprehensive and unified guidelines for deploying low-cost sensors for real-time IAQ monitoring in residential settings. A case study utilizing the developed guideline in this study was applied to demonstrate and evaluate PM2.5 concentration levels in some low-income residential homes in Southeastern Louisiana.

In demand-controlled ventilation (DCV), rates of outdoor air ventilation are automatically modulated as occupant density varies. The objective is to keep ventilation rates at or above design specifications and code requirements and also to save energy by avoiding excessive ventilation rates. DCV is most often used in spaces with highly variable and sometime dense occupancy. In almost all cases, carbon dioxide (CO{sub 2}) sensors installed in buildings provide the signal to the ventilation rate control system. People produce and exhale CO{sub 2} as a consequence of their normal metabolic processes; thus, the concentrations of CO{sub 2} inside occupied buildings are higher than the concentrations of CO{sub 2} in the outdoor air. The magnitude of the indoor-outdoor CO{sub 2} concentration difference decreases as the building's ventilation rate per person increases. The difference between the indoor and outdoor CO{sub 2} concentration is also a proxy for the indoor concentrations of other occupant-generated bioeffluents, such as body odors. Reviews of the research literature on DCV indicate a significant potential for energy savings, particularly in buildings or spaces with a high and variable occupancy. Based on modeling, cooling energy savings from applications of DCV are as high as 20%. With support from the California Energy Commission and the U.S. Department of Energy, the Lawrence Berkeley National Laboratory has performed research on the performance of CO{sub 2} sensing technologies and optical people counters for DCV. In addition, modeling was performed to evaluate the potential energy savings and cost effectiveness of using DCV in general office spaces within the range of California climates. The above-described research has implications for the specifications pertaining to DCV in section 121 of the California Title 24 Standard. Consequently, this document suggests possible changes in these specifications based on the research findings. The suggested changes in specifications were developed in consultation with staff from the Iowa Energy Center who evaluated the accuracy of new CO{sub 2} sensors in laboratory-based research. In addition, staff of the California Energy Commission, and their consultants in the area of DCV, provided input for the suggested changes in specifications.

A novel quantitative assessment framework of the IAQ resilience performance of buildings: The resilience score metric

The control of outdoor air intake rates in mechanically ventilated buildings based on indoor carbon dioxide (CO 2 ) levels, often referred to as CO 2 demand controlled ventilation (DCV), has the potential for reducing the energy consumption associated with building ventilation in some commercial and institutional buildings. Carbon dioxide DCV has been discussed, promoted, studied and demonstrated for about twenty years, but questions still remain regarding the actual energy savings potential as a function of climate, ventilation system features, and building occupancy. In addition, questions exist as to the indoor air quality (IAQ) impacts of the approach and the best way to implement CO 2 DCV in general and in a given building. This report presents a state-of-the-art review of CO 2 DCV technology and application including discussion of the concept and its application, and a literature review. In addition the regulatory and standard requirements impacting CO 2 DCV are also examined.

This study focuses on enhancing indoor air quality and thermal comfort in indoor swimming pool facilities through the investigation of ventilation system configurations. Creating a comfortable and healthy environment in these facilities is crucial for the well-being of occupants and overall operational efficiency. The performance of the ventilation system significantly influences user comfort, energy consumption, and air quality. This research aims to analyze the impact of different ventilation system configurations on indoor air quality and thermal comfort parameters using computational fluid dynamics (CFD) simulations.To achieve the research objectives, CFD simulations were conducted using ANSYS Fluent ®, a widely used commercial CFD package. The simulations involved solving the governing equations for continuity, momentum, energy, and species transport, along with employing the k-epsilon turbulence closure model. A high-resolution mesh with over 5.6 million elements accurately captured the flow regimes and related phenomena.The study investigated various aspects of ventilation system configurations, including the placement and design of inlets and outlets, airflow rates, and distribution patterns. Evaluations were made based on key performance indicators such as indoor air quality parameters, thermal comfort indices, and energy efficiency metrics. Comparisons were made between different configurations to identify the most effective strategies for enhancing indoor air quality and thermal comfort.The findings of the study demonstrate the importance of ventilation system design in achieving optimal indoor air quality and thermal comfort in indoor swimming pool facilities. The results indicate that specific configuration choices, such as the use of circular inlets in the ceiling for improved spectator comfort and rectangular inlets in the side walls for better performance in the swimming pool area, can significantly impact thermal conditions and air distribution. Additionally, the study emphasizes the need for appropriate inlet grille height to ensure adequate air mixing and thermal comfort.The outcomes of this research provide valuable insights for architects, engineers, and facility managers involved in the design, construction, and operation of indoor swimming pool facilities. By understanding the impact of different ventilation system configurations, stakeholders can make informed decisions to optimize indoor air quality, thermal comfort, and energy efficiency. Ultimately, this research contributes to the development of sustainable and comfortable indoor swimming pool environments that cater to the needs of occupants and enhance their overall experience.

Use of ductless split air conditioners in small workspaces leads to accumulation of carbon dioxide due to the absence of fresh air entry. Additional mechanical ventilation is required to meet the ASHRAE standard. Providing constant-rate ventilation would reduce the CO2 concentration but would lead to high energy consumption when there is variation in occupant density. Instead, demand-controlled ventilation, that is, ventilation rate linked with the occupant density, can reduce energy consumption and maintain adequate indoor air quality. The purposes of this study were to quantify the temporal variation of CO2 in a workspace, to determine the factors influencing the demand-controlled ventilation strategy, and to assess its performance in workspaces with flexible work environment (varying occupant density with time). A parametric study on demand-controlled ventilation design indicates that the ventilation cycle time depends significantly on the occupant density and the range of threshold levels of CO2. The occupants can decide the lower CO2 threshold level based on the requirements. Use of a lower CO2 threshold limit of 700 ppm in a typical workspace with varying occupant density resulted in an energy saving of around 90% when compared with the ventilation rate required by ASHRAE 62.1. The assessment would be helpful in identifying the workspaces that do not require external ventilation. The ventilation design strategy thus developed would help the building managers in improving indoor air quality and lowering energy costs when compared with the constant rate ventilation system.

This study applies indoor air quality modelling to investigate the potential advantages and drawbacks of demand-controlled ventilation as an indoor air quality control strategy. The study uses a multiple zone pollutant transport model to evaluate the performance of several indoor air quality control strate gies under a variety of conditions. The pollutant transport model is incorpo rated into the TRNSYS simulation program to allow simultaneous calculation of both building pollutant concentrations and building energy use. A specific office building situation consisting of a main zone and a conference room was studied. The simulations showed that a carbon dioxide-based demand con trolled ventilation system can provide better control of indoor air quality than a constant outdoor airflow at the ASHRAE Standard 62-1989 prescribed level under a wide range of building conditions. The constant outdoor air approach lacks the capability of providing additional outdoor air when required by poor building conditions such as a low pollutant removal effectiveness and a high occupant density. The demand-controlled ventilation system saves energy compared to the constant outdoor air approach under all conditions consid ered. It was also found that a demand-controlled ventilation strategy consist ing of a step controller combined with scheduled 100% outdoor air purges can protect building occupants from exposure to high concentrations of non-occu pant-generated pollutants while still providing energy savings.

Energy implications of meeting indoor air quality and thermal comfort standards in Mediterranean schools using natural and mechanical ventilation strategies

Predicting non-uniform indoor air quality distribution by using pulsating air supply and SVM model

The indoor air quality (IAQ) has an important impact on public health. Currently, the indoor air pollution, caused by gas, particle, and bio-aerosol pollutants, is considered as the top five environmental risks to public health and has an estimated cost of $2 billion/year due to medical cost and lost productivity. Furthermore, current buildings are especially vulnerable for chemical and biological warfare (CBW) agent contamination because the central air conditioning and ventilation system serve as a nature carrier to spread the released agent from one location to the whole indoor environment within a short time period. To assure the IAQ and safety for either new or existing buildings, real time comprehensive IAQ and CBW measurements are needed. With the development of new sensing technologies, economic and reliable comprehensive IAQ and CBW sensors become promising. However, few studies exist that examine the design and evaluation issues related to IAQ and CBW sensor network. In this paper, relevant research areas including IAQ and CBW sensor development, demand control ventilation, indoor CBW sensor system design, and sensor system design for other areas such as water system protection, fault detection and diagnosis, are reviewed and summarized. Potential research opportunities for IAQ and CBW sensor system design and evaluation are discussed.