Hyperaware smart buildings: Healthy green buildings and indoor air quality


Digital transformation, by itself, is not that exciting nor does it motivate people unless it is connected to a bigger purpose. Post COVID-19, when employees are still wondering whether to go back into their workplaces, send their children to schools or travel to their favorite destinations, the office buildings, educational institutions and airports are under heavy scrutiny for highest performance standards. The health of these spaces and indoor air quality of these buildings are under a tight spotlight.

With climate change and greenhouse gas emissions, new and fresh thinking is needed from every global citizen who can play their role towards sustainability that reduces impact to the environment and climate change. This blog allows me to shed some light on healthy and efficient buildings of the future and hope to inspire a few more people to participate in this transformation journey. 

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Challenges

As office space workers and tenants are coming back to the buildings with great expectations the building owners, landlords and employee health and safety officials are having to provide adequate measures, transparency towards clean, healthy buildings and are required to promptly respond to occupant’s requests. The US Green Building Council, EPA and LEEDS have converged to a common set of indoor air quality standards that are governed by a key set of parameters such as:

  • CO2: A natural compound in the air with an average outdoor concentration of 300-400ppm. The indoor levels are higher. Anything beyond 900ppm can be considered not healthy. Future smart buildings should keep the CO2 level close to 600ppm.

  • CO: It is an odorless and colorless lethal gas and is one of the most dangerous compounds in the indoor environment. The National Institute for Occupational Safety and Health (NIOSH) has recommended an exposure limit of 35ppm for an eight hour workday.

  • VOC: Volatile organic compounds are chemicals found in many products we use in daily lives. They can cause irritation to the eyes, nose, throat and cause difficulty breathing. They are emitted by many common building materials, including carpeting, hardwood flooring, upholstery and even marble surfaces.

  • PM2.5: Particulate matter is a dangerous form of pollution as the size of the particle is so small (2.5 micrometer or less in diameter) that they can get into the lungs causing many adverse effects. Their threshold limit value is 25 μg / 3.
  • Radon: It is a radioactive gas formed by the decay of natural Uranium in the soil. It is carcinogenic and EPA recommends a level limit of 4 pCi/L. 

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Solution guidelines

LEED provides a framework for healthy, efficient, carbon and cost saving green buildings. They are a critical part of addressing the healthy buildings, climate crisis and meeting ESG goals. The ASHRAE (American Society for Heating, Refrigerating and Air-conditioning Engineers) advances the heating, cooling and ventilation design of buildings. Both of these frameworks play big roles in how we design, operate and service future smart buildings and today’s buildings that can be retrofitted with IoT sensors to achieve similar results.

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Let me take an example of how spaces in a building can be automated for LEED certified indoor air quality based on how the building is occupied.


Occupancy-based room control automation

We will build a building occupancy and floor area-based automation control function to regulate indoor air quality based on ANSI/ASHRAE 62.1 - 2019 standards. The purpose of the ASHRAE standard is - to specify minimum ventilation rates and other measures intended to provide indoor air quality (IAQ) that is acceptable to human occupants and that minimizes adverse health effects.

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Concepts
The occupancy density and floor area of a space or zone drives the outdoor airflow intake that is required in the breathing zone (Vbz) of the occupiable space. The amount of fresh outdoor air required for the ventilation zone should not be less than the value determined in the following equation. 

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Vbz = Rp * Pz + Ra *  Az

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Az = zone floor area, the net occupiable floor area of the ventilation zone, ft2 (m2)

Pz = zone population, the number of people in the ventilation zone during use

Rp = Outdoor airflow rate required per person

Ra = Outdoor airflow required per unit area

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Automation use case example: Assume there is an office building of Waylay in Austin, Texas with the following floors / occupiable spaces.

Waylay-Austin

 Floor 1
     Main entry lobby = 2000 sq. ft.
     Breakroom = 1000 sq. ft.

     Office space = 3000 sq. ft.

 Floor 2

     Breakroom = 1000 sq. ft.

     Office space = 3000 sq. ft.‍

Minimum ventilation required in specific breathing zones (ANSI/ASHRAE 62.1 specification).

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Anomaly condition: Assume the breakroom occupancy count reached 70 during a company event when employees from different organizations gathered to meet and eat lunch together. This event triggers an exceed in the occupancy threshold of 50 per 1000 sq. ft.. The condition persisted for 1hr (12pm – 2pm CST) and then occupancy fell below the threshold (50) by 3pm CST. Then the occupant density finally reached zero (0) by 6:00 pm CST. The ventilation rate needs to be adjusted at every threshold crossing and then set to minimum threshold for zero (0) occupancy. Additionally, for energy conservation the lights will need to be turned off in the breakroom when there is no occupancy (0).

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The below table calculates the ‘ventilation rate’ (cfm) required based on the occupancy level and space size:

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Low-code implementation:

  1. Model a resource ‘Waylay Austin. Create resources ‘floor 1’ and ‘floor 2’ as children of resource ‘Waylay Austin’ building.

  2. Model a resource ‘breakroom 1’ as child resource of foor 1 and another breakroom 2 as child resource for floor 2.

    a) Create metadata attributes (area_sqft) with value = 1000 for resources breakroom 1 and breakroom 2.

    b) Create meta data attribute (area_sqft) with value = 2000 for resources lobby 1 for floor 1.

  3. Write a Rule to run against the breakroom 1 of floor 1 where the occupancy sensor of breakroom 1 sends the data shown on the above table.

    For example: start with ‘occupancy’ density (medium = 40) where no thresholds are exceeded, set HVAC control system ‘ventilation_rate’ to 320 cfm. Then after some time at 12pm CST, ‘occupancy’ increases to 70 and exceeds the threshold (50). At this time, we increase the ‘ventilation_rate’ to 470 cfm - send a command to the VAV controller to supply extra air to the space by 470 cfm – 320 cfm = 150 cfm or +46.8% extra air supply. Also, raise a WARNING alarm (occupancy in the breakroom of building A / floor 1 has exceeded capacity threshold) for the facility manager.

When the occupancy goes down to 50, reduce the ‘ventilation_rate’ (air supply) to 370 cfm.

When the occupancy goes down to zero (0) then reduce the ‘ventilation_rate’ to 120 cfm or a difference of 370 cfm – 120 cfm / 370 cfm = -67.5%.


Note: In a more sophisticated algorithm or machine learning model the amount of outdoor ventilation air that is brought into the building will also depend on the outdoor air quality (presence of smoke particles, refuse, etc.). Similarly, the outdoor air intake will need to be optimized for relative humidity inside the building and the energy required to cool or heat the air so that the cost of heating/cooling vs. indoor air quality are balanced and optimized.

  1. Send a command to the building automation system light controller to turn off the lights and space occupancy reaches zero.

  2. If auditing is required by building owner’s policy, then send a notification to the facility

manager that the automation control has taken action to optimize the building performance.

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An example automation template built using the Waylay platform is shown below.

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Conclusion

Indoor air quality plays an important role in the overall health and well-being of building occupants as well as the environment. Poor air quality in the buildings can lead to numerous adverse health problems, such as nausea, headaches, breathing problems such as asthma, skin irritations and even cancer. In fact, since people spend almost 90% of their time indoors, indoor air quality has a significant impact on people’s health and productivity. 

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On the other hand, data from the U.S. Department of Energy shows buildings account for 40% of all U.S. energy use and waste 30% of the energy they consume. Therefore, the balancing act of energy consumption, wastage against the indoor air quality can be maintained by strictly following the ANSI/ASHRAE and LEED guidelines. This is achievable through hyper automation systems which can sense the real time occupant capacity, indoor air parameters, air flows in various building zones, and converge them with contextual data from IT systems, outdoor air quality and occupant feedback in real-time.

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References

https://www.usgbc.org/leed

https://www.usgbc.org/

https://www.ashrae.org/technical-resources/bookstore/standards-62-1-62-2+

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