METHOD FOR CHARACTERIZING CLEAN AIR DELIVERY TO AN INDOOR ENVIRONMENT VIA AN ENVIRONMENTAL CONTROL SYSTEM

Description

CROSS-REFERENCE

This Application claims the benefit of U.S. Provisional Application No. 63/735,219, filed on 17 Dec. 2024, which is incorporated in its entirety by this reference.

This Application is also related to U.S. patent application Ser. No. 18/244,775, filed on 11 Sep. 2023, which claims the benefit of U.S. Provisional Application No. 63/405,340, filed on 9 Sep. 2022, each of which is incorporated in its entirety by this reference. U.S. patent application Ser. No. 18/244,775 is a continuation-in-part application of U.S. patent application Ser. No. 18/077,185, filed on 7 Dec. 2022, which claims the benefit of U.S. Provisional Application No. 63/405,340, filed on 9 Sep. 2022, U.S. Provisional Application No. 63/355,949, filed on 27 Jun. 2022, U.S. Provisional Application No. 63/329,717, filed on 11 Apr. 2022, U.S. Provisional Application No. 63/286,821, filed on 7 Dec. 2021, U.S. Provisional Application No. 63/286,806, filed on 7 Dec. 2021, and U.S. Provisional Application No. 63/286,815, filed on 7 Dec. 2021, each of which is incorporated in its entirety by this reference. U.S. patent application Ser. No. 18/244,775 is also a continuation-in-part (or “bypass”) application of PCT Application No. PCT/US23/32351, filed on 8 Sep. 2023, which claims priority to U.S. Provisional Application No. 63/405,340, filed on 9 Sep. 2022, and U.S. patent application Ser. No. 18/077,185, filed on 7 Dec. 2022, each of which is incorporated in its entirety by this reference.

TECHNICAL FIELD

This invention relates generally to the field of building automation and, more specifically, to a new and useful method for estimating clean air-delivery rates in indoor environments regulated by environmental control systems in the field of building automation.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a flowchart representation of a method;

FIG. 2 is a flowchart representation of one variation of the method;

FIG. 3 is a flowchart representation of one variation of the method;

FIG. 4 is a flowchart representation of one variation of the method; and

FIGS. 5A, 5B, and 5C are flowchart representations of one variation of the method.

DESCRIPTION OF THE EMBODIMENTS

The following description of embodiments of the invention is not intended to limit the invention to these embodiments but rather to enable a person skilled in the art to make and use this invention. Variations, configurations, implementations, example implementations, and examples described herein are optional and are not exclusive to the variations, configurations, implementations, example implementations, and examples they describe. The invention described herein can include any and all permutations of these variations, configurations, implementations, example implementations, and examples.

1. Method: Environmental Controls

As shown in FIGS. 1-4, 5A, 5B, and 5C, a method S100 includes, during execution of a first air test in an indoor environment within a first test period: triggering release of a first tracer load into air in the indoor environment by a dispenser transiently arranged within the indoor environment, the first tracer load including a test concentration of aerosol tracer particles in Block S108; and recording a first timeseries of aerosol data via a set of sensors transiently arranged within the indoor environment, the first timeseries of aerosol data representing concentrations of aerosol particles present in air at the set of sensors during the first test period in Block S110. The method S100 further includes: based on the first timeseries of aerosol data and the test concentration, deriving a first decay rate of aerosol tracer particles detected in the indoor environment during the first test period in Block S114; deriving a clean air-delivery rate for the indoor environment based on the first decay rate in Block S120; accessing a set of building data defined for the indoor environment and including a volume of the indoor environment, an average occupancy level of the indoor environment, and a set of energy data defined for an environmental control system implemented in the indoor environment and configured to provide outdoor air and recirculated air within the indoor environment in Block S116; estimating an outdoor air-delivery rate for the indoor environment based on the clean air-delivery rate and the set of building data in Block S130; and accessing a target outdoor air-delivery rate defined for the indoor environment.

The method S100 further includes, in response to the outdoor air-delivery rate exceeding the target outdoor air-delivery rate: interpreting a pass outcome for the first air test in Block S140; characterizing a difference between the outdoor air-delivery rate and the target outdoor air-delivery rate; and, based on the difference and the set of energy data, calculating a first set of environmental controls for implementation at the environmental control system, the set of environmental controls predicted to drive the outdoor air-delivery rate toward the target outdoor air-delivery rate by reducing the outdoor air-delivery rate in Block S142.

One variation of the method S100 recites: accessing a timeseries of aerosol data captured via a set of sensors arranged within an indoor environment during execution of an air test, the timeseries of aerosol data representing concentrations of aerosol particles present in air in the indoor environment following dispensation of a tracer load, including aerosol tracer particles, into the indoor environment in Block S110; based on the timeseries of aerosol data, deriving a clean air-delivery rate for the indoor environment in Block S120; accessing a set of building data defined for the indoor environment in Block S116; estimating an outdoor air-delivery rate for the indoor environment based on the clean air-delivery rate and the set of building data in Block S130; and accessing a target outdoor air-delivery rate defined for the indoor environment. In this variation, the method S100 further includes, in response to the outdoor air-delivery rate exceeding the target outdoor air-delivery rate: interpreting a pass outcome for the first air test executed in the indoor environment during the first test period in Block S140; characterizing a difference between the outdoor air-delivery rate and the target outdoor air-delivery rate; and, based on the difference and the set of building data, calculating a set of environmental controls for implementation at the environmental control system within the indoor environment, the set of environmental controls predicted to drive the outdoor air-delivery rate toward the target outdoor air-delivery rate by reducing the outdoor air-delivery rate in Block S142.

In one variation, the method S100 further includes: generating an electronic notification indicating the pass outcome and including a prompt to implement the set of environmental controls at the environmental control system in Block S150; and transmitting the electronic notification to a user affiliated with the indoor environment via a native application executing on a device accessed by the user in Block S152.

1.1 Method: Occupancy Level

As shown in FIGS. 1-4, one variation of the method S100 includes, during execution of a first air test in an indoor environment within a first test period: triggering release of a first tracer load into air in the indoor environment by a dispenser transiently arranged within the indoor environment, the first tracer load including a test concentration of aerosol tracer particles in Block S108; and recording a first timeseries of aerosol data via a set of sensors transiently arranged within the indoor environment, the first timeseries of aerosol data representing concentrations of aerosol particles present in air at the set of sensors during the first test period in Block S110. In this variation, the method S100 further includes: based on the first timeseries of aerosol data and the test concentration, deriving a first decay rate of aerosol tracer particles detected in the indoor environment during the first test period in Block S114; deriving a clean air-delivery rate for the indoor environment based on the first decay rate in Block S120; accessing a set of building data defined for the indoor environment and including a volume of the indoor environment and a target occupancy level of the indoor environment in Block S116; and, based on the clean air-delivery rate and the volume of the indoor environment, estimating a first occupancy level supported by the indoor environment in Block S122.

The method S100 further includes, in response to the first occupancy level falling below the target occupancy level: interpreting a fail outcome for the first air test in Block S140; generating an electronic notification indicating the fail outcome and the first occupancy level supported by the indoor environment in Block S150; and transmitting the electronic notification to a user affiliated with the indoor environment via a native application executing on a device accessed by the user in Block S152.

2. Applications

Generally, Blocks of the method S100 can be executed by a computer system (e.g., a local or remote computer system, a computer network, a local or remote server) in conjunction with a pathogen detection system—including one or more aerosol dispensers and a set of tracer sensors—to: execute a brief (e.g., 10-minute) tracer-based air test in an indoor environment via automatic dispensation and detection of aerosol tracer particles in the indoor environment; derive a clean air-delivery rate for the indoor environment based on decay of aerosol tracer particles detected at the set of sensors; convert the clean air-delivery rate into a supported occupancy level for the indoor environment (e.g., based on one or more ventilation standards); leverage the clean air-delivery rate—in combination with supplied building data (e.g., volumetric data, occupancy data, energy data) to estimate an outdoor air-delivery rate supplied by an environment control system (e.g., an HVAC system) implemented within the indoor environment; and, based on differences between these measured values and corresponding targets, calculate modified environmental controls (e.g., damper position, fan speed) for implementation by the environmental control system within the indoor environment. Therefore, the system can trigger execution of an air test and automatically derive ventilation test results—characterized by clean air-delivery rate, outdoor air-delivery rate, etc.—that link directly to infection-risk thresholds, code requirements, and energy consumption for the indoor environment.

In one implementation, the pathogen detection system is transiently deployed to a commercial building—such as an office, school, healthcare facility, retail store, or manufacturing facility—that includes an environmental control system (e.g., an HVAC system) configured to provide outdoor air and recirculated air to one or more zones of the building. In this implementation, the system can: trigger release of a tracer load into air within a particular zone via one or more dispensers deployed in this particular zone; record a timeseries of aerosol data at the set of sensors—deployed within this particular zone—during a test period of less than an hour; derive a decay rate for aerosol tracer particles detected in the zone; and derive a clean air-delivery rate for the zone based on the decay rate and a volume of the zone. The system can then access and/or calculate a clean-air-per-person requirement defined in a ventilation standard (e.g., a clean-air standard for infection control) and derive a supported occupancy level for the zone by dividing the clean air-delivery rate by the clean-air-per-person requirement. The system can further compare the supported occupancy level to a target occupancy level recorded in building data—such as supplied by a user affiliated with the indoor environment and/or this particular zone—and interpret a “pass” outcome when the supported occupancy level exceeds the target occupancy level or a “fail” outcome when the supported occupancy level falls below the target occupancy level. The system can then report this “pass” or “fail” outcome to the user affiliated with the indoor environment via a native application executing on a device accessed by the user.

Additionally, the system can interpret an outdoor air-delivery rate from the same air test and link this outdoor air-delivery rate to energy performance of the environmental control system. For example, the computer system can: access building data including a filter efficiency and a supply airflow rate implemented by the environmental control system during execution of the air test; estimate an outdoor air-delivery rate for the zone based on a combination of outdoor air and filtered recirculated air that yields the measured clean air-delivery rate; access a target outdoor air-delivery rate derived from a ventilation standard (e.g., a standard such as ASHRAE 62.1 parameterized by space type, floor area, and design occupancy); and compare the estimated outdoor air-delivery rate to the target outdoor air-delivery rate. In response to the outdoor air-delivery rate exceeding the target outdoor air-delivery rate, the computer system can interpret a pass outcome for health and code compliance while also interpreting a surplus outdoor air-delivery rate representing over-ventilation in the zone.

The system can then leverage this surplus outdoor air-delivery rate to calculate replacement environmental controls—and corresponding energy savings—for implementation by the environmental control system. For example, the computer system can: calculate a target outdoor air-delivery rate for the zone that satisfies the ventilation standard; calculate a change in one or more environmental controls—such as an outdoor air damper position, a minimum outdoor airflow setpoint, or a supply fan speed—predicted to drive the outdoor air-delivery rate toward the target outdoor air-delivery rate; and, based on energy data and historical weather data for the building location, estimate a change in heating and cooling loads—and/or a corresponding changes in energy cost associated with implementing these environmental controls—at the environmental control system when implementing these changes to the environmental controls. Therefore, the computer system can: convert a single tracer-based air test into a quantitative estimate of both ventilation sufficiency for a given occupancy and energy savings achievable by reducing excess outdoor air while maintaining this occupancy; and translate these energy savings into implementable changes to environmental controls at the environmental control system.

In another implementation, the pathogen detection system can be deployed across multiple zones within a building to construct a building-wide ventilation and energy profile. In this implementation, the system can: execute a first air test in a first zone and a second air test in a second zone; derive clean air-delivery rates, supported occupancy levels, and outdoor air-delivery rates for each of these zones; and compare these values to zone-specific targets defined by building data. The computer system can then: identify zones that are over-ventilated and zones that are under-ventilated; calculate zone-level environmental controls that rebalance outdoor air while maintaining each zone at or above its target outdoor air-delivery rate or supported occupancy level; and compute building-level energy savings associated with this rebalancing over historical weather conditions. The computer system can assemble these results into a report that summarizes (e.g., for each zone): measured clean air-delivery rates; supported occupancy levels; outdoor air-delivery rates relative to target outdoor air-delivery rates; and recommended environmental controls and associated energy impacts.

Furthermore, in another implementation, the system can be implemented by building owners, tenants, or health authorities to generate auditable records of indoor-air performance over time. For example, the system can execute the method S100 on a periodic schedule—such as seasonally, after major HVAC changes, and/or in response to emerging respiratory-disease guidance—and log for each test: the decay rate, clean air-delivery rate, supported occupancy level, outdoor air-delivery rate, target values, test outcome, and/or calculated environmental controls. The system can thus maintain a history of field-verified tests that demonstrate how indoor environments meet or exceed clean-air and occupancy requirements while progressively reducing unnecessary outdoor air and associated energy consumption.

2.1 Aerosol Tracer Dispensation & Detection

In one implementation, the system can be configured to: dispense known concentrations of tracers (e.g., aerosolized tracer particles, volatile tracers) in solution into a defined, indoor environment (or “indoor environment”) via a dispenser transiently installed in a dispenser location within the indoor environment; concurrently capture timeseries tracer data—representing concentrations of tracers in air—via a set of sensor units transiently arranged about the dispenser in a target configuration; and derive timeseries concentrations—represented by a tracer concentration curve—of these tracers in the indoor environment over time, such as following dispensation of tracers into the indoor environment by the dispenser. The computer system can then leverage this tracer concentration curve to derive insights related to flow and/or removal of air—including gases and/or particles—in this particular environment.

In particular, during a test period, the system can execute an air test to derive insights related to aerosol behaviors—such as related to flow, movement, and/or distribution patterns—in a particular indoor environment within a facility. In preparation for execution of an air test, the tracer detection system can be deployed to a facility for installation within a particular indoor environment and/or throughout a group of indoor environments within the facility. In one implementation, the tracer detection system—such as including one dispenser and one or more sensor units—can be transiently deployed and installed within the indoor environment for a defined duration (e.g., 10 minutes, 30 minutes, 1 hour, 24 hours) to enable execution of a tracer or a series of air tests during this defined duration. Once installed in the indoor environment, the system can execute an air test accordingly and interpret a set of airflow values for the indoor environment based on timeseries aerosol data recorded during execution of the air test. The tracer detection system can then be retrieved from the indoor environment—such as for installation in another indoor environment within the facility and/or for storage elsewhere—upon completion of the air test or series of air tests.

For example, an operator affiliated with the indoor environment may locate the dispenser and the sensor unit in the indoor environment (e.g., in a target configuration) in preparation for execution of an air test. Once deployed within the indoor environment, the system can: initiate a test period of a target duration (e.g., 10 minutes, 30 minutes, 1 hour, 24 hours); execute one or more air tests—including release of an air test load by the dispenser and recording of timeseries aerosol data by the sensor unit—within this test period; and, in (near) real-time, output results—such as aerosol metrics (e.g., air-change range, aerosol reduction rate, air velocity and/or direction), risk levels associated with one or more pathogens, effectiveness of various interventions or environmental controls (e.g., HVAC settings, occupancy levels, activity levels)—of each air test; and report these aerosol metrics and/or additional insights to a manager affiliated with the indoor environment in (near) real-time. Therefore, the system can derive deep insights into flow and movement of aerosols in the indoor environment via execution of a (relatively) brief air test (e.g., a 10-minute test, 20-minute test, 1-hour test).

For example, the system can: derive a tracer concentration curve—representing decay in concentration of a tracer in air in the indoor environment over a decay period succeeding dispensation of an air test load into the indoor environment—based on timeseries aerosol data captured by one or more sensor units deployed in the indoor environment during execution of the air test; and extract characteristics from this concentration curve—such as including an area-under-the-curve (or “AUC”), a maximum concentration of tracers, a final concentration of tracers, a baseline concentration of tracers in the indoor environment, a decay rate (e.g., a slope of the cure), etc.—to derive an airflow value (e.g., a volumetric airflow rate) representing removal of tracer particles from the indoor environment during the air test. Furthermore, the system can: compare this airflow value to a target airflow value—such as a target removal rate and/or target air-change rate (e.g., a target volumetric airflow rate)—defined for the indoor environment; and interpret an outcome—such as a “pass” outcome or a “fail” outcome—of the air test based on a difference between the target airflow value and the (measured) airflow value. Based on the outcome, the system can selectively suggest implementation and/or modification of various removal pathways—such as related to capture, filtering, settling, ventilation, etc.—employed in the indoor environment.

Furthermore, based on this aerosol airflow value—such as corresponding to an air change rate and/or equivalent clean airflow (or “ECA”)—and an estimated outdoor air value calculated for the interior environment as described above, the system can interpret an indoor airflow value representing a proportion of indoor or “recirculated” air consumed by the HVAC system in the indoor environment. The system can thus: generate a report including the aerosol airflow value and/or the indoor airflow value; and send this report—representing a comprehensive view of airflow and/or air removal pathways within the indoor environment—to a building manager affiliated with the building including the indoor environment.

2.2 Native Application

Generally, the computer system can interface with a native application or web application executing on a computing device (e.g., a tablet, a smartphone, a laptop computer) accessed by a user affiliated with the indoor environment.

In one implementation, the computer system can prompt the user to generate a building profile for the building (i.e., the indoor environment)—including a set of zones distributed throughout the building—within the native application.

For example, the user may download a native application to her tablet or smartphone. The computer system can then: generate a prompt to create a building profile for the building within the native application and manually populate the building profile with various information, such as a building type, a quantity of building zones and/or names of each building zone, occupancy information for the building, activity types performed within the building, size information (e.g., room volume or dimensions) for each zone, HVAC information, etc.; and transmit the prompt to the user via the native application. The computer system can then: receive this information from the user via the native application; and store the building profile—populated with the building information provided by the user—in a remote database.

Furthermore, the computer system can enable the user to initiate an air test in a particular zone within the indoor environment within the native application. For example, the computer system can: receive a user input configured to trigger initiation of a first air test via the native application executing on a device accessed by a user affiliated with the indoor environment; and, in response to receiving the user input, automatically initiate the first air test and trigger release of a first tracer load into air in the indoor environment.

Then, during execution of the first air test, the computer system can: assemble a concentration curve representing change in concentration of aerosol tracer particles detected in air in the indoor environment based on timeseries of aerosol data captured by the set of sensors; and present this concentration curve (e.g., in near real time) to the user via the native application. Finally, in response to completion of the first air test, the computer system can: generate an electronic notification indicating a “pass” or “fail” outcome associated with the first air test; and transmit the electronic notification to the user via the native application accordingly.

Therefore, the computer system can provide (near) real-time alerts and/or notifications to the user via the native application indicating a current status of an air test executed within the indoor environment and/or immediate results of the air test.

3. Tracer Detection System

The tracer detection system can be semi-permanently and/or transiently deployed to a building for characterizing air circulation within “zones” of a building.

Generally, the tracer detection system 100 includes a set of dispensers and a set of sensor units transiently deployed within a facility for execution of one or more tracer tests. In particular, the tracer detection system 100 can include: a set of dispensers (e.g., one or more dispensers) configured to release known amounts (e.g., quantities, concentrations, volumes) of tracers in solution (i.e., tracer test loads) into air in a defined, indoor environment (hereinafter an “aerosol zone”) containing the set of dispensers; and a set of sensor units (e.g., one or more sensor units 120) configured to detect tracers in air at the set of sensor units and record timeseries amounts of these tracers.

More specifically, the tracer detection system can include a set of dispensers and a set of sensor units deployed within an aerosol zone, such as within a singular, defined aerosol zone (e.g., an office, a classroom, a kitchen, a hallway) and/or across multiple zones (e.g., a suite of offices, a floor of a building, adjacent classrooms, multiple shops within a shopping mall). Each dispenser, in the set of dispensers, can be configured to release known amounts of tracers (i.e., tracer test loads) into surrounding ambient air; and each sensor unit, in the set of sensor units, can be configured to ingest surrounding ambient air and detect presence of tracers (e.g., aerosolized tracer particles, tracer gases)—such as including aerosolized tracer particles (or “aerosol tracers”) released by the set of dispensers—present in ingested ambient air via a set of sensors (e.g., a particle or aerosol sensor, a gas sensor) integrated within the sensor unit.

Furthermore, in one implementation, the sensor unit and the dispenser can be configured to wirelessly communicate. For example, the dispenser can be configured to automatically trigger the sensor unit to initiate recording of timeseries tracer data via the set of sensors—such as in preparation for or responsive to dispensation of a tracer test load—responsive to receiving a command from the computer system. Additionally and/or alternatively, in another example, the sensor unit can be configured to automatically trigger the dispenser to dispense a tracer test load—in preparation or responsive to initiating capture of aerosol data by the set of sensors- responsive to receiving a command from the computer system and/or based on a dispense schedule or protocol loaded onto a (local) controller of the sensor unit.

3.1 Deployment

Generally, the tracer detection system 100 can be transiently deployed to an aerosol zone for execution of a tracer test in this aerosol zone.

In particular, the tracer detection system 100—including a set of dispensers 110 and a set of sensor units 120—can be transiently arranged in a target configuration within a particular aerosol zone (e.g., a room, an office, a hallway) for execution of a tracer test during a test period. During this test period, the system can: trigger release of the tracer test load—containing known amounts of aerosol tracers (e.g., aerosolized salt particles)—into air in the aerosol zone by one or more dispensers 110, in the set of dispensers 110, arranged in the aerosol zone; and record timeseries aerosol data—representing concentrations of aerosol particles in air—via a set of sensors 122 integrated into one or more sensor units 120, in the set of sensor units 120, arranged in the aerosol zone. The system can then leverage this timeseries aerosol data—collected during execution of the aerosol tracer test to derive insights related to airflow (e.g., removal rate and/or replacement rate, direction(s) of airflow) and/or flow of aerosol tracers (e.g., decay rate, flow direction) in the aerosol zone.

In one implementation, the tracer detection system 100—including one or more dispensers 110 and one or more sensor units 120—can be transiently deployed to and installed within the aerosol zone for a test period of a target duration (e.g., 10 minutes, 30 minutes, 1 hour, 24 hours) for execution of a tracer test and/or a series of tracer tests during the test period. Once installed in the aerosol zone, the system can execute a tracer test accordingly and interpret a set of airflow values for the aerosol zone based on timeseries aerosol data recorded during execution of the tracer test. The tracer detection system 100 can then be retrieved from the aerosol zone—such as for installation in another aerosol zone within the facility and/or for storage elsewhere—upon completion of the tracer test or series of tracer tests.

For example, an operator affiliated with the aerosol zone may locate a dispenser 110 and a set of sensor units 120 in the aerosol zone (e.g., a in a target configuration) in preparation for execution of a tracer test. Once deployed within the aerosol zone, the system can: initiate a test period of a target duration (e.g., 10 minutes, 30 minutes, 1 hour, 24 hours); execute one or more tracer tests—including release of a tracer test load by the dispenser 110 and recording of timeseries aerosol data by the sensor unit 120—within this test period; and, in (near) real-time, output results—such as airflow values (e.g., air-change range, aerosol reduction rate, air velocity and/or direction), risk levels associated with one or more pathogens, effectiveness of various interventions or environmental controls (e.g., HVAC settings, occupancy levels, activity levels)—of each tracer test.

In one example, the system can: trigger dispensation of a tracer test load to initiate a tracer test; derive a tracer signal from timeseries aerosol data collected during execution of the tracer test; derive a set of airflow values representing aerosol flow and/or movement in the aerosol zone based on the tracer signal; and report these airflow values and/or additional insights to a manager affiliated with the aerosol zone in (near) real-time. In this example, the system can therefore derive deep insights into flow and movement of aerosols in the aerosol zone via execution of a (relatively) brief tracer test (e.g., a 10-minute test, 20-minute test, 1-hour test).

Alternatively, in another implementation, the tracer detection system 100—such as including a set of dispensers 110 (e.g., one or more dispensers 110) and a set of sensor units 120 (e.g., one or more sensor units 120)—can be deployed to a facility for permanent or semi-permanent installation within one or more aerosol zones within the facility. In this implementation, once initially installed, the system can periodically execute tracer tests in the aerosol zone and/or within the facility as described above, such as based on a dispense schedule (or “test schedule”) defined for the facility and/or responsive to detected environmental changes within the facility.

4. Data Processing

Generally, the system can: access a timeseries of aerosol data—representing concentrations of aerosol particles present in air at the set of sensors during execution of the tracer test—output by the set of sensors during execution of the tracer test in Block S110; and assemble a tracer concentration curve representing change in tracer concentration at the set of sensor units or in the indoor environment and/or within the building based on the timeseries of aerosol data in Block S112.

As described above, the system can present this tracer concentration curve to the user affiliated with the indoor environment—such as via the native application—in near real time and/or upon completion of the tracer test.

In one implementation, the system can compile timeseries aerosol data captured at each sensor, in the set of sensors deployed throughout the indoor environment, and assemble a composite tracer concentration curve accordingly. Additionally or alternatively, the system can compile: timeseries aerosol data captured at each sensor, in a set of sensors deployed within a particular zone in the indoor environment; assemble a composite tracer concentration curve—representative of this particular zone—accordingly; and repeat this process for each other zone defined within the indoor environment.

4.1 Clean Air-Delivery Rate

Generally, the system can leverage the timeseries tracer data—and/or the assembled tracer concentration curve—to derive a clean air-delivery rate for the indoor environment during execution of the air test in Block S120.

In one implementation, the system can: derive a decay rate of aerosol tracer particles detected in the indoor environment during the test period based on the timeseries of aerosol data and the test concentration of aerosol particles dispensed in the tracer load during execution of the air test; and derive a clean air-delivery rate for the indoor environment based on the decay rate and building data defined for the indoor environment. For example, the system can access a set of building data—such as defined for the indoor environment in the building profile—including: a volume of the indoor environment (e.g., number of occupants, occupant density); an average occupancy level of the indoor environment; a set of energy data defined for an environmental control system implemented in the indoor environment and configured to provide outdoor air and recirculated air within the indoor environment; etc. The system can then leverage this set of building data—in combination with the decay rate derived from timeseries aerosol data—to derive the clean air-delivery rate for the indoor environment.

Additionally or alternatively, the system can leverage timeseries aerosol data—captured by multiple sensors installed within the indoor environment—to derive the decay rate based on each timeseries of aerosol data.

In one example, the system: accesses a first subset of timeseries of aerosol data captured by a first sensor, in the set of sensors, during a decay period within the first test period, the first sensor installed in a first location within the indoor environment; derives a first decay rate for aerosol particles detected at the first sensor based on the first subset of timeseries of aerosol data; accesses a second subset of timeseries of aerosol data captured by a second sensor, in the set of sensors, during a decay period within the first test period, the second sensor installed in a second location within the indoor environment; derives a second decay rate for aerosol particles detected at the second sensor based on the second subset of timeseries of aerosol data; and calculates the decay rate (e.g., an average decay rate) of aerosol tracer particles detected in the indoor environment during the test period based on the first decay rate and the second decay rate. In this example, the system can then: calculate a product of the decay rate and the volume of the indoor environment; and estimate the clean air-delivery rate based on this product.

4.2 Outdoor Air-Delivery Rate

Generally, the system can estimate an outdoor air-delivery rate based on the clean air-delivery rate derived for the indoor environment via execution of the tracer test and the set of building data in Block S130.

In particular, in one implementation, the system can: implement the methods and techniques described above to derive a clean air-delivery rate for the indoor environment; access a set of building data defined for the indoor environment and including a volume of the indoor environment, an average occupancy level of the indoor environment, and a set of energy data defined for an environmental control system implemented in the indoor environment and configured to provide outdoor air and recirculated air within the indoor environment; and estimate an outdoor air-delivery rate for the indoor environment based on the clean air-delivery rate and the set of building data.

For example, the system can access the set of energy data including: a filter efficiency of the environmental control system; and a known proportion of outdoor air mixed with recirculated air by the environmental control system during the test period. Then, the system can estimate the outdoor air-delivery rate for the indoor environment based on the clean air-delivery rate, the filter efficiency, and the known proportion of outdoor air mixed with recirculated air by the environmental control system during the test period.

5. Test Outcome

Generally, the system can interpret a “pass” or “fail” outcome for a particular test outcome associated with the air test and report this “pass” or “fail” outcome to the user affiliated with the indoor environment via the native application in Block S140.

In one implementation, the system can: access a target indoor air value defined for the indoor environment and/or building, such as calculated based on a set of environmental characteristics (e.g., size, occupancy, activity type or level) of the indoor environment; and, in response to the indoor air value corresponding to (e.g., matching a value, exceeding a threshold value) the target indoor air value, interpret a “pass” outcome for the indoor air test. Alternatively, in response to the indoor air value differing from the target indoor air value, the system can interpret a “fail” outcome for the indoor air test.

In another implementation, the system can: access a target outdoor air value defined for the indoor environment and/or building; and, in response to the outdoor air value meeting or exceeding (e.g., matching a value, exceeding a threshold value) the target indoor outdoor value, interpret a “pass” outcome for the outdoor air test. Alternatively, in response to the outdoor air value falling below the target outdoor air value, the system can interpret a “fail” outcome for the outdoor air test.

5.1 Test Outcome: Outdoor Air

In one implementation, the system verifies whether the outdoor air-delivery rate exceeds a target outdoor air-delivery rate defined for the indoor environment.

In particular, in this implementation, the system can: access a target outdoor air-delivery rate derived from a ventilation standard (e.g., a standard such as ASHRAE 62.1) and defined based on building data stored in the building profile, such as including a space type (e.g., office, school, recreational), a floor area, a volume of the indoor environment, occupant density, etc.; and, in response to the outdoor air-delivery rate estimated for the indoor environment exceeding the target outdoor air-delivery rate, interpret a pass outcome for the air test. Alternatively, in response to the outdoor air-delivery rate falling below the target outdoor air-delivery rate, the system can interpret a fail outcome for the air test. The system can then: generate an electronic notification indicating the “pass” or “fail” outcome for the air test; and transmit the electronic notification to the user affiliated with the indoor environment via the native application.

Therefore, the system can automatically alert the user that the indoor environment fails to meet minimum requirements—defined by the ventilation standard—for circulation of outdoor air within the indoor environment by the environmental control system.

5.1.1 Recommended Environmental Controls

In one implementation, the system can enable (near) real-time management of the building based on outdoor air values derived via execution of one or more air tests.

In particular, the system can selectively prompt the user to implement a set of environmental controls—such as including a particular damper position, a particular fan speed, etc.—at the environmental control system (e.g., the HVAC system) based on results of the air test. For example, in response to the outdoor air-delivery rate exceeding the target outdoor air-delivery rate, the system can: interpret a pass outcome for the air test; characterize a difference between the outdoor air-delivery rate and the target outdoor air-delivery rate; and, based on the difference and the set of energy data, calculate a first set of environmental controls for implementation at the environmental control system, the first set of environmental controls predicted to drive the outdoor air-delivery rate toward the target outdoor air-delivery rate by reducing the outdoor air-delivery rate. Alternatively, in response to the outdoor air-delivery rate falling below the target outdoor air-delivery rate, the system can: interpret a fail outcome for the first air test executed in the indoor environment during the first test period; characterize a second difference between the outdoor air-delivery rate and the target outdoor air-delivery rate; and, based on the second difference and the set of energy data, calculate a second set of environmental controls for implementation at the environmental control system within the indoor environment, the second set of environmental controls predicted to drive the outdoor air-delivery rate toward the target outdoor air-delivery rate by increasing the outdoor air-delivery rate.

In particular, in one example, in response to the outdoor air-delivery rate substantially exceeding the target outdoor air-delivery rate, the system can: access a first set of environmental controls implemented by the environmental control system during the test period and including a first damper position defining a first percentage of damper openness (e.g., 80%); characterize a difference between the air-delivery rate and the target outdoor air-delivery rate; and, based on the difference and the first set of environmental controls, calculate a second set of environmental controls—including a second damper position defining a second percentage of damper openness (e.g., 30%) less than the first percentage of damper openness. The system can then: generate an electronic notification including a prompt to adjust a damper position of the environmental control system from the first damper position to the second damper position in order to reduce energy costs by reducing the (actual) outdoor air-delivery rate, while maintaining the (actual) outdoor air-delivery rate at or above the target air-delivery rate.

In another example, in response to the outdoor air-delivery rate exceeding the target outdoor air-delivery rate, the system can: access a first set of environmental controls implemented by the environmental control system during the test period and including a first fan speed; characterize a difference between the air-delivery rate and the target outdoor air-delivery rate; and, based on the difference and the first set of environmental controls, calculate a second set of environmental controls—including a second fan speed falling below the first fan speed. The system can then: generate an electronic notification including a prompt to adjust a fan speed of the environmental control system from the first fan speed to the second fan speed in order to reduce energy costs by reducing the (actual) outdoor air-delivery rate, while maintaining the (actual) outdoor air-delivery rate at or above the target air-delivery rate.

Additionally or alternatively, in one implementation, the system can leverage weather data—stored in the building profile and/or accessed from a public database—to calculate and/or recommend specific environmental controls for implementation by the environmental control system. For example, the system can calculate a set of environmental controls—for implementation at the environmental control system - based on a difference, the set of energy data, and the set of historical weather data.

5.1.2 Energy Savings

Furthermore, in one variation, the system can calculate an energy performance metric associated with implementation of a set of environmental controls and present this energy performance metric to the user via the native application. In this implementation, the system can: access a baseline set of environmental controls implemented during the air test; access a recommended set of environmental controls calculated in response to the test outcome (e.g., pass or fail outcome); based on the baseline set of environmental controls and a set of historical or actual weather data, estimate a first energy consumption associated with operation of the environmental control system according to the baseline set of environmental controls; and, based on the recommended set of environmental controls and the set of historical or actual weather data, estimate a second energy consumption associated with operation of the environmental control system according to the recommended set of environmental controls. The system can then derive one or more energy performance metrics—such as a difference between the first and second energy consumptions, a corresponding difference in energy costs, and/or a percentage reduction in energy consumption—and assemble these metrics into an electronic notification including a description of the set of recommended environmental controls. The system can then transmit this electronic notification to the user via the native application, such as in a results view that concurrently displays the test outcome, the outdoor air-delivery rate relative to the target outdoor air-delivery rate, and the set of energy performance metrics.

5.1.3 Example: Outdoor Air Test+Energy Savings

In one example, as shown in FIGS. 5A, 5B, and 5C, the computer system leverages outdoor air-delivery rates derived for various zones throughout a building to: identify whether each zone “passes” an outdoor air test by exhibiting an outdoor air-delivery rate exceeding the target outdoor air-delivery rate defined for the zone by a ventilation standard (e.g., Standard 62.1); identify opportunities for reducing outdoor air-delivery rates in various zones within the building to reduce energy costs while maintaining outdoor air-delivery rates above target outdoor air-delivery rates; present these opportunities for energy savings—and associated energy costs—to the user (e.g., a building manager) affiliated with the building; and suggest modifications to environmental controls (e.g., damper position) implemented by the environmental control system (e.g., HVAC system) to reduce outdoor air-delivery rates and reduce energy costs accordingly.

In this example, the computer system accesses a building profile—such as defined by the user via the native application and/or derived from data supplied by various building systems—defining a list of zones in the building and a set of characteristics for each zone, such as including a volume of the zone, a space-type classification for each zone (e.g., office, conference room, break room), etc. The computer system then implements a ventilation standard (e.g., Standard 62.1) to calculate a target outdoor air-delivery rate for each zone based on characteristics of the zone (e.g., the space type, design occupancy, floor area of the zone). Upon completion of one or more air tests throughout each zone in the building, the computer system can: calculate an outdoor air-delivery rate for each zone in the building; compare the outdoor air-delivery rate to the target outdoor air-delivery rate calculated for the zone; and calculate a difference between the outdoor air-delivery rate to the target outdoor air-delivery rate calculated for the zone. As shown in FIG. 5A, the computer system then aggregates excess outdoor air-delivery rates across all zones into a building-level minimum outdoor air reduction value that, if implemented, reduces total outdoor airflow while retaining an outdoor air-delivery rate at or above the target outdoor air-delivery rate within each zone.

Additionally, in this example, the computer system can then calculate and/or select a new set of environmental controls—for implementation at the environmental control system—expected to achieve this minimum outdoor air reduction value at the environmental control system while preserving compliance with the ventilation standard in each zone. For example, the computer system can: identify which air-handling units and/or outdoor-air dampers serve each monitored zone; express the current outdoor air-delivery rate in each zone as a function of current damper positions, fan speeds, and/or supply flows; and calculate a new set of environmental controls (e.g., damper position, fan speed, supply flow) predicted to reduce outdoor air flow by the minimum outdoor air reduction value and maintain the outdoor air-delivery rate in each zone above the target outdoor air-delivery rate. The computer system thereby calculates a set of new environmental controls—such as revised minimum outdoor-air setpoints for one or more air-handling units—that, when implemented at the environmental control system, decrease outdoor airflow without reducing ventilation below code requirements (e.g., defined by the ventilation standard) in any monitored zone.

The computer system can then estimate a difference in energy consumption between operation of the building at the current set of environmental controls and operation at the new set of environmental controls. For example, the computer system can access weather data for a typical meteorological year at a location of the building, such as including hourly dry-bulb temperature and humidity values. For each hour, the computer system can apply a psychrometric model to calculate an enthalpy of outdoor air based on the hourly weather data and an enthalpy of supply air based on building setpoints (e.g., heating supply temperature, cooling supply temperature, and indoor humidity conditions). The computer system then: converts the building-level outdoor air-delivery rate reduction value into a mass-flow reduction in outdoor air for that hour; and then calculates a corresponding change in thermal load on the HVAC system due to conditioning less outdoor air. For heating hours, the computer system calculates a reduction in heating energy proportional to outdoor-air mass-flow reduction, a specific heat of air, and a temperature difference between outdoor air and indoor supply air. For cooling and dehumidification hours, the computer system calculates a reduction in cooling energy proportional to outdoor-air mass-flow reduction and the enthalpy difference between outdoor air and indoor supply air.

The computer system evaluates each hour of the typical meteorological year and sums the hourly thermal-load reductions into monthly and annual heating and cooling energy savings. The computer system can further transform the thermal energy savings into fuel-specific energy savings by dividing by equipment efficiencies for heating and cooling equipment (e.g., boiler efficiency, chiller coefficient of performance, or packaged rooftop-unit efficiency). The computer system thus generates separate estimates of annual heating energy savings and annual cooling energy savings associated with implementation of the new environmental controls.

Furthermore, the computer system can then convert these heating and cooling energy savings into projected cost savings based on utility tariff data for the building. For example, the computer system can: access electricity and gas tariff data for the building, such as including one or more volumetric rates for electricity and for fuel used for heating; decompose the annual heating energy savings and the annual cooling energy savings into fuel-specific quantities based on equipment efficiencies; apply corresponding volumetric rates to each fuel-specific savings quantity to calculate a first cost savings associated with heating energy savings and a second cost savings associated with cooling energy savings; and sum the first and second cost savings to derive an annual energy cost savings associated with implementing the new environmental controls. The computer system can then compile these results into a set of energy consumption metrics, including annual heating energy saved, annual cooling energy saved, peak-demand reduction, and corresponding annual cost savings. The computer system can then present these energy consumption metrics—including suggestions to implement the new set of environmental controls—to the user affiliated with the building.

Therefore, the computer system can: verify ventilation performance and code compliance based on air test results; quantify energy benefits—such as corresponding to reduced energy costs—of implementing new environmental controls; and surface these combined health and energy insights to the building manager directly within the native application.

5.1.4 Closing the Loop: Actual Energy Savings

Furthermore, in one variation, upon implementation of new environmental controls at the environmental control system (e.g., to reduce the outdoor air-delivery rate), the computer system tracks actual energy savings—such as represented by a set of energy performance metrics—based on observed operating conditions and observed weather conditions. The computer system can then: compare actual energy savings to predicted energy savings; report differences between actual energy savings and predicted energy savings to the user (e.g., via the native application); and/or refine a model for predicting energy savings (or other energy performance metrics) based on differences between actual energy savings and predicted energy savings.

For example, as shown in FIG. 5C, the computer system can access: actual outdoor temperature and humidity data (e.g., hourly data) for a tracking period (e.g., monthly, quarterly, or annually); and actual operating data for HVAC equipment (e.g., run hours, fuel consumption, electricity consumption) installed in a building, such as collected from utility meters or a building management system. For each hour in the tracking period, the computer system can calculate heating and cooling thermal loads by implementing psychrometric and equipment-efficiency models described above in combination with the actual weather data. The computer system then integrates these hourly loads over the tracking period to derive actual (or “realized”) heating energy savings and actual (or “realized”) cooling energy savings and converts these actual savings into actual cost savings. The computer system can present these actual savings metrics to the building manager via the native application, such as in a “performance to date” view that lists, for each tracking period, the projected annual savings, the actual savings over the elapsed portion of the year, the percentage of projected savings achieved to date. etc.

Additionally or alternatively, the computer system can also compare actual energy savings to the originally predicted energy savings and leverage this comparison to refine subsequent predictions and recommendations. In one example, the computer system calculates a prediction error metric—such as a difference or ratio between the predicted energy savings for the tracking period and the actual energy savings calculated from actual weather and meter data—and decomposes this prediction error metric into components attributable to weather variance, schedule variance (e.g., different occupancy or operating hours than assumed), model variance (e.g., differences between assumed and actual equipment efficiency), etc. The computer system can then update one or more model parameters—such as effective equipment efficiency, typical operating schedules, economizer usage thresholds, etc.—so increase accuracy of future energy savings predictions for this building (or for similar buildings).

5.2 Test Outcome: Occupancy Level

Additionally or alternatively, in another implementation, the system verifies whether the occupancy level supported by the indoor environment meets or exceeds a target occupancy level defined for the indoor environment.

In particular, in this implementation, the system can: access a target occupancy level defined for the indoor environment, such as by the user affiliated with the indoor environment via the native application; and calculate an actual occupancy level supported by the indoor environment—such as based on current ventilation metrics derived for the indoor environment (e.g., indoor air-delivery rate, outdoor air-delivery rate)—based on the clean air-delivery rate derived for the indoor environment and the volume of the indoor environment. Then, in response to the occupancy level exceeding the target occupancy level, the system can: interpret a pass outcome for the air test; generate an electronic notification indicating the “pass” outcome for the air test; and transmit the electronic notification to the user affiliated with the indoor environment via the native application.

Alternatively, in response to the occupancy level falling below the target occupancy level, the system can: interpret a fail outcome for the air test; generate an electronic notification indicating the “fail” outcome for the air test and including the actual occupancy level supported by the indoor environment; and transmit the electronic notification to the user affiliated with the indoor environment via the native application.

5.2.1 Recommended Occupancy Levels

In one variation, the system can automatically suggest new environmental controls for implementation at the environmental control system in order to increase the occupancy level supported by the indoor environment.

For example, the system can: access a first set of environmental controls implemented at an environmental control system implemented in the indoor environment and configured to provide outdoor air and recirculated air within the indoor environment; characterize a difference between the target occupancy level and the actual occupancy level supported by the indoor environment; and, based on the difference, calculate a second set of environmental controls for implementation at the environmental control system, the second set of environmental controls predicted to increase an occupancy level supported by the indoor environment.

Additionally or alternatively, in another variation, the system can automatically suggest new environmental controls for implementation at the environmental control system in order to reduce energy costs associated with the environmental control system and drive the actual occupancy level supported by the indoor environment toward the target occupancy level, such as in response to the actual occupancy level substantially exceeding the target occupancy level.

For example, the system can access a first set of environmental controls implemented at an environmental control system implemented in the indoor environment and configured to provide outdoor air and recirculated air within the indoor environment. Then, in response to the actual occupancy level exceeding the target occupancy level, the system can: interpret a pass outcome for the first air test; generate a second electronic notification indicating the pass outcome and the first occupancy level supported by the indoor environment; characterize a difference between the target occupancy level and the first occupancy level; based on the difference, calculate a second set of environmental controls for implementation at the environmental control system, the second set of environmental controls predicted to reduce energy consumption of the environmental control system and drive the first occupancy level toward the target occupancy level; append the second electronic notification with a prompt to implement the second set of environmental controls at the environmental control system; and transmit the second electronic notification to the user via the native application executing on the device accessed by the user.

The systems and methods described herein can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions can be executed by computer-executable components integrated with the application, applet, host, server, network, website, communication service, communication interface, hardware/firmware/software elements of a user computer or mobile device, wristband, smartphone, or any suitable combination thereof. Other systems and methods of the embodiment can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions can be executed by computer-executable components integrated by computer-executable components integrated with apparatuses and networks of the type described above. The computer-readable medium can be stored on any suitable computer readable media such as RAMs, ROMs, flash memory, EEPROMs, optical devices (CD or DVD), hard drives, floppy drives, or any suitable device. The computer-executable component can be a processor but any suitable dedicated hardware device can (alternatively or additionally) execute the instructions.

As a person skilled in the art will recognize from the previous detailed description and from the figures and claims, modifications and changes can be made to the embodiments of the invention without departing from the scope of this invention as defined in the following claims.