Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 29th July 2021, 04:27:14am CEST

Session Overview
Session 14: IAQ measurement
Monday, 21/June/2021:
1:00pm - 2:30pm

Session Chair: Hans Martin Mathisen
Session Co-chair: Britt ann Kåstad Høiskar
Location: Zoom room #2
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1:00pm - 1:12pm

Reducing infection risk and optimization of airing concepts for indoor air quality by accurate aerosol & CO2 measurements

Ann-Kathrin Gossmann, Stefan Hogekamp, Frederik Weis, Maximilian Weiss

Palas GmbH, Karlsruhe, Germany

Since the outbreak of the SARS-CoV-2 pandemic and the findings about the virus transmission route through aerosols, indoor air quality is a major topic when it comes to efforts to contain the spread of SARS-CoV-2 in the population.

Most calculations of infection risk, however, still rely on CO2 as a proxy for exhaled aerosols. This assumption is no longer valid when air filtration devices are used, arising the need to include actual measured aerosol concentration into the calculation of indoor infection risk. To close this gab, a version of Wells-Riley equation, extended to include the effect of air filtration into determination of reproductive number, is introduced and applied to measurement data from indoor air quality during school lessons. The results show, that taking only CO2 into account will overestimate the real infection risk from aerosols by 20% in the cases without air filtration and by 60% in the cases with air filtration.

Furthermore, measurement results varied strongly between different classrooms. This indicates that general airing recommendation, as applied during these tests, are not enough to assure a healthy environment and more individual measurements are necessary.

1:12pm - 1:17pm

Measurement and simulations of the influence of green wall systems on indoor air quality

Janine Bardey1,2,3, Marcel Schweiker1, Dirk Müller2,3, Marc Baranski4

1University Hospital RWTH Aachen, Institute for Occupational, Social and Environmental Medicine; 2Heinz Trox Wissenschafts gGmbH; 3RWTH, E.ON ERC, Institute for Energy Efficient Buildings and Indoor Climate; 4aedifion GmbH

BACKGROUND: Heating, ventilation and air conditioning (HVAC) systems are decisive for the resource consumption of buildings and the indoor air quality (IAQ). A new approach in research and industry is to embed plants into these systems. Research regarding plant-based systems developed from the investigation of the effects of individual potted plants to the evaluation of complex plant-based systems.

AIMS: This paper continues this line of research by investigating the performance of plant walls within a real-life office environment. The aim is to quantify the potential contribution of plant-based systems to resource savings and IAQ improvements in comparison and in combination with conventional HVACs.

KEY PROBLEMS: To ensure health, well-being and low resource demand, the influence of novel and alternative air conditioning systems need to be tested and optimised.

These new systems must also meet the technical requirements of building automation system to enable the integration into these systems. Criteria and tools are needed for the comparison between different system configurations and to evaluate the efficiency of plant-based systems.

METHODS: The testing procedure involves both experimental testing and simulations. The experimental setup consisted of an office room with mechanical ventilation, a plant wall and a source of pollution. A test person or a printer are used as typical pollutant sources of an office environment. The plant wall tested, includes an automated watering and fan system.

IAQ was evaluated based on concentration of CO2, volatile organic compounds (VOC), particulate matter (PM) and relative humidity. For consumption analysis, the electrical and heat demand as well as water consumption are considered. Based on this set of parameters, we compared the temporal behavior of the four possible ventilation combinations of plant wall and ventilation system.

The simulation model represents all components of the experimental setting and the resource consumption. It was calibrated according to the measurement results.

MAIN RESULTS: The experiment and the simulation show that the plant wall has a supporting effect on humidification and reduction of VOC. The effect of CO2 reduction is negligibly small. Thus, the plant wall tested cannot serve as standalone air purifier but as support for conventional ventilation systems.

A plant wall model for Modelica was developed and will be available in the Modelica AixLib library. This model enables the comparison of the resource efficiency for water and energy of the plant wall with other building systems, to estimate its effects on the overall building resource demand .

1:17pm - 1:22pm

Intrinsic dimension estimation as a tool to sensor selection for an indoor air quality multisensory system

Luiz Miranda1, Caroline Duc1, Nathalie Redon1, Marie Verriele1, Bernadette Dorizzi2, Jérôme Boudy2, Jugurta Montalvão3

1IMT Lille-Douai, France; 2Telecom SudParis, France; 3Univesidade Federal de Sergipe, Brazil

Indoor air quality (IAQ) is a growing and multidisciplinary research field domain involving professionals with various expertise, from Materials Sciences, Instrumentation, Electronics, Physics, Chemistry and many more. One of the current hot topics of this field is to equip private accommodation with air quality monitors. For that, it is crucial to develop and choose the more suitable sensors capable of detecting and discriminate different types of gases and volatile organic compounds. The number of needed sensors is related to which substances are going to be monitored. However, this choice is not obvious as the intrinsic information of sensors is not always well understood.

The main objective of this work is to understand and provide a framework on how this choice can be made. Several different types of signals are generated when using multisensory systems, but not all the signals are useful for detecting the aimed substances. By analyzing these signals, it is possible to select the sensors presenting the best match with a given substance detection task.

To analyze the collected data, a technique of intrinsic dimension estimation was used. This technique allows the estimation of how many dimensions (independent variables) are necessary to synthesize equivalent signals. In the case of multisensory systems, the dimensions can be interpreted as the number of sensors present in it. However, the intrinsic dimension estimation of a dataset collected via multisensory systems may reveal a smaller effective dimension, thus possibly allowing the estimation of the minimum number of sensors needed for a given task.

The dataset analyzed in this work is composed by the responses of 40 RUBIX-PODs with 19 sensors each, during 6 experiments where specific gas injections are done to represent different indoor activities (cleaning, cooking, etc.). The intrinsic dimension (ID) of this dataset is estimated. The data was arranged accordingly to an injection discrimination task, i.e., detecting what experiment (here called injection) generated each data point. Preliminary results showed an ID of 3 for the given dataset and indeed when only three specific sensors were used, all the injections could visibly be separated. Although this result shows that ID estimation is a good indication of the number of sensors needed, this experiment is very simple compared to what the multisensory systems face during day-to-day use, more experiments using real world data collected by those systems should provide a better understanding on what they are detecting and what sensors are really needed.

1:22pm - 1:27pm

A method for determining the time-dependent indoor CO2 concentration to evaluate air hygiene

Anica Jasmin Mayer, Christian Menges, Roland Göttig

Technical University of Munich, Germany

Max von Pettenkofer, one of the first hygiene engineers, evaluated the indoor air quality by means of the carbon dioxide content. As long as humans are the main source of air pollution through their continuous release of metabolic products such as CO2, carbon dioxide can still be used as a good indicator for evaluating the indoor air quality. However, rooms with a high rate of occupancy, such as classrooms or lecture halls, often do not have sufficient indoor air quality and therefore an increased demand for fresh air is necessary. The trend towards open-plan offices also highlights this problem. The German workplace guidelines (ASR) as well as the Association of German Engineers deal with ventilation requirements as well as the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). They define indoor limit values for CO2 concentrations.

Unfortunately, the verification of compliance with the limit values during the use of buildings is often only carried out randomly or not at all. Although independent requirements of necessary minimum air change rates exist, they refer for example to the avoidance of mold growth. The requirements to indoor air quality in terms of low CO2-concentrations, often remain unconsidered. A sufficient air quality is indispensable for a high concentrativeness and corresponding work efficiency of the users. Therefore, it is of great importance especially in classrooms, lecture halls and offices. Yet, there is no quantity that represents the indoor air quality over a given period of time to evaluate the air-hygienic comfort of rooms, for example, over an entire year. This paper presents a method for the determination of a time-dependent variable for the assessment of indoor air quality with regard to the comfort of the users.

Using measurements or dynamic building simulations over longer periods of time, CO2 concentrations can be determined as a function of occupancy and air exchange rate. In order to be able to evaluate indoor air hygiene with the newly developed method, the concentration values are integrated as a time-dependent variable in CO2 hours using a calculation tool. This results in an easy understandable and applicable new parameter for the assessment of indoor air hygiene on the basis of CO2 concentrations. Using dynamic building simulations, the new method can be applied in the planning phase to gain a parameter which indicates to what extent a ventilation system or a ventilation concept offers sufficient indoor air comfort.

1:27pm - 1:32pm

Interaction between controlled natural lighting and IEQ; Integrated double skin facades approach applied on an office building

Hadil H. S Alsafadi, Touraj Ashrafian

Ozyegin University, Turkey

Double skin facades can be used as a balanced solution to facilitate natural lighting into buildings and control the amount of admitted solar radiation. This study aims to identify an optimal solution for daylight and energy performance within an office building by optimizing the façade's opening size and panel rotation. The goal is to generate a flexible model that contributes to the overall performance and thermal comfort.

The paper provides a methodology using parametric tools of Grasshopper via Energy-plus/ladybug to analyze and evaluate the thermal performance of different iterations of a double skin façade. Although various IEQ aspects affect comfort levels, few studies have investigated the interaction between IEQ and thermal performance levels regulated by double-skin façade.

The results concluded that the proposed skin façade could reduce 30% of the total radiation of the original office building. While, the rotation of the façade panels proved to be a significant factor as it resulted in the highest reduction in radiation, up to 32%.

1:32pm - 1:44pm

Big Data in IAQ research, an example of the application in IEA EBC Annex 86

Jelle Laverge1, Marc Delghust1, Klaas De Jonge1, Loes Lokere1, Mathias Vandenberghe1, Timon Gryson1, Ivan Pollet2, Steven Delrue2

1Ghent University, Belgium; 2Renson Ventilation NV, Belgium

In the IEA EBC annex 86 project, we are developing a classification/reporting guideline on IoT-data for energy efficient IAQ management strategies.

We are exploring the potential of the new generation of IoT connected devices (both standalone and embedded in eg. AHU’s) for smart IAQ management. What can we learn from big data? Can we benchmark system energy and IAQ performance based on this data? How can we make sure that the data is available and can be accessed? Can we update what we think we know about what happens in dwellings based on what we see in big data rollouts? What are the best protocols and ontologies? How to create viable services out of the data/business plans? How can we integrate data with smart grids?

These issues will be addressed by reporting experiences from a series of implementation case studies and overview of available (types of) datasets.

We address these questions by exploring real life case studies and deriving 'lessons learned' and good practices. In this paper, we use a case study where we analyse CO2, Humidity and TVOC concentrations measured through the onboard sensors of an IoT connected residential air handling unit as an example of this methodology.

In this particular case study, we were able to check common assumptions on occupancy and pollution loads at a cross-sectional level with highly time resolved data for a full year, based on the data of over 5000 units.

1:44pm - 1:56pm

Optimal sensor positioning for monitoring indoor air quality in a simulated office environment

Seoyeon Yun, Dusan Licina

EPFL (École Polytechnique Fedérale de Lausanne), Switzerland

In an office environment, ventilation system and indoor and quality (IAQ) strongly influence occupants' productivity and satisfaction. Among prominent sources on indoor air pollution, humans and their activities have been the most dominant. Spatio-temporal variation of human-associated air pollutants could strongly influence the ventilation performance. Despite recent technological advancements in low-cost IAQ monitoring, the current monitoring practices are limited and typically exclude conditions that are relevant to, and experienced by, building occupants. Dynamic variations of occupants’ number and activities influence spatio-temporal variations of indoor air pollutants. Capturing those variations and identifying an optimal sensor placement can be important for improved ventilation performance.

In this study, we aim to investigate optimal sensor placement for IAQ monitoring in a simulated office environment. We conducted a total of 32 experiments in a controlled climate chamber with different number of human participants (2, 4, 6 and 8) performing typical office activities and four space types (two types of shared offices, meeting room and cafeteria). Two different mechanical ventilation strategies (mixing and displacement) and air change rates (2.4 – 2.6 and 3.5 – 3.6 h⁻¹) were studied to evaluate their impact on spatio-temporal variation of indoor air pollutants. The IAQ parameters (CO₂, TVOC and size-resolved PM) were measured at seven locations (wall, center of workstation, near a source, on each participant’s desk, side of the desk near an abdomen of seated participant, breathing zone). Preliminary results show that airborne concentration of CO₂/PM recorded in the breathing zone is considerably higher than ambient (background) concentrations from the other sensor locations. For example, approximate exposure concentration to CO₂ (1500 ppm) was over 2 times higher than background concentrations (600-800 ppm), and to PM₂.₅ was 1.5 – 3 times higher than the background levels. For further analysis, multi-logistic regression model will be introduced to identify optimal sensor placement in the office that can approximate human exposure to CO₂/PM. The final results are expected to advance knowledge of spatio-temporal variability of indoor environment combined with identifying optimal sensing location. This is important not only for improving understanding of indoor environments and energy saving potential, but also for developing of control algorithms that can ultimately be incorporated into ventilation control logic on a wider scale.

1:56pm - 2:08pm

A new simplified daylight evaluation tool, description and validation against the standard method of EN 17037

Bertrand Deroisy1, Nicolas Dupin3, Sabine Pauquay2, Jens Christoffersen3

1Belgian Building Research Institute; 2VELUX Belgium; 3VELUX A/S

The Daylight Evaluation tool uses a simplified assessment method to determine the daylight quantity provided to a room. Its calculation method is based on formulas integrating the main factors characterizing the space and its context. As it is meant to be used by persons with no specific knowledge in daylight calculations methods its results are expressed in a more abstract “Daylight score” rather than a physical value. The Daylight Evaluation tool uses a corrected Glazing-to-Floor ratio (GFR) as a proxy for the daylight provision in a space according to the recommendation in EN 17037 Daylight in Buildings. In principle, the results of the assessment methods are not directly comparable, but the relative classification of different configurations should be equivalent. The verification of daylight provision is assessed for a set of 124 cases which are considered representative for residential buildings in Belgium and Luxemburg. The main purpose of this study is to verify the simplified evaluation method using the Daylight Evaluation tool and to check results against those obtained through a detailed evaluation with Daylight Factors, according to EN 17037.

A sensitivity analysis is carried out to identify the effect of several parameters on daylight provision in an indoor space. One of the main findings is that some parameters have significantly more impact than others. The total area of daylight openings, the light transmittance of glazing and the room depth are obviously important factors. But external obstruction due to site conditions are certainly as essential and frequently overlooked. Masking elements, on the other hand, are relatively less impacting, except for unusual situations, such as extreme protruding elements in relation to the size of the daylight openings.

The main finding of this study is that the simplified method for assessing daylight provision as proposed in the ‘Daylight Evaluation’ tool is an easy and reliable estimation for daylight provision. A comparison of the simplified tool with daylight simulations show a high correlation and the tool is applicable for any case which has conditions matching closely to the models and situations defined.

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