GB2563008A

GB2563008A - Air pollution management system and method

Info

Publication number: GB2563008A
Application number: GB1708298.3A
Authority: GB
Inventors: Glover Neil; Mceligott Richard
Original assignee: Future Decisions Ltd
Current assignee: Future Decisions Ltd
Priority date: 2017-05-24
Filing date: 2017-05-24
Publication date: 2018-12-05
Anticipated expiration: 2037-05-24
Also published as: GB2563008B; GB201708298D0

Abstract

An air pollution management system comprising a control system 22 and a ventilation system 12 for an enclosed space 14. The ventilation system has an air intake 13, an air extract 15 and ventilation devices for controlling flow of air through the enclosed space. The control system, using a plurality of sensors 40A-40C, determines pollution data for the external environment; determines current pollution data for the enclosed space; predicts pollution data for the enclosed space based on the external environment data and on the current pollution data; generates control data based on the predicted pollution data; and causes the ventilation system to control the ventilation devices using the control data. The external environment pollution data may be determined by measurements taken at the air intake by sensor 40A.The pollution data for the enclosed space may be determined by sensor 40B, a temperature sensor 37 and carbon dioxide sensor 38 may also be provided.

Description

Control Process

Flir-S

Air Pollution Management System and Method

Field of the Invention

The present invention relates to air pollution management in enclosed spaces. The invention relates particularly to the control of ventilation systems for enclosed spaces.

Background to the Invention

Air pollution worldwide is well documented and the adverse effects of air pollution in enclosed spaces with exposure toxicity has been quantified by the World Health Organisation. Air pollution comes from a number of sources with external pollutants commonly being carried by the prevailing wind. However in the immediate vicinity of enclosed spaces the pollution is a combination of windborne pollution and local vehicular transport pollution, with street canyoning effects determining its distribution around the enclosed spaces.

The combined external air pollutants for a city are often associated with a daily or weekly profile of peaks and troughs. This pattern has been recognised and extensively modelled by numerous academic publications to produce city pollution forecasts. However this method of forecasting pollution cannot be extended to local estimates of pollution around specific buildings. Studies on street canyoning effects have shown fourfold pollution variation within local regions. Such work and others have largely discredited the modelling approach for local pollution estimation around enclosed spaces.

Secondary and sometimes more toxic pollution sources are internal sources, often leached from items brought into the enclosed space like furnishings or people. An additional internal pollution source arises from the operation of the ventilation system, which can capture pollution and then react with ‘fresh’ air brought in at the start of the day. Without sufficient ventilation during periods of reduced occupancy pollution can also be trapped within the enclosed space, not dispersed as commonly assumed.

Enclosed spaces typically have air ventilation systems, designed to bring in ‘fresh’ air and expel stale air. This process is considered part of comfort management and wellbeing whose primary concern is typically temperature control, but also may include humidity control and air filtering. Filtering is used to remove insects, fine particles and dust, and in some environments such as hospitals it is used to remove pathogens. The rate of supply and removal of air has been typically designed to expel air contaminated with pollutants generated, but not measured, within the space such as carbon dioxide (CO2) and Volatile Organic Compounds (VOCs). Within modern enclosed spaces the standards stipulate the rate of supply of fresh air by the volume of fresh air supplied per occupant. For example within the EU and UK there are air quality directives associated with air pollution irrespective of location, e.g. 2008/50/EC. In addition in Europe/UK Part F ofthe building code stipulates that the internal CO2 should not exceed 1200 parts per million (ppm).

It would be desirable to provide an improved air pollution control system for enclosed spaces, more particularly an air pollution control system that takes into consideration internal and external industrial, commercial and vehicular pollution and its effects on enclosed spaces in towns and cities.

Summary ofthe Invention

From a first aspect the invention provides a method of controlling a ventilation system for an enclosed space, the ventilation system comprising at least one air intake through which air can be brought into the enclosed space from an external environment, at least one air extract through which air can be expelled from the enclosed space, and at least one ventilation device for controlling flow of air through the enclosed space, the method comprising:

determining pollution data for the external environment; determining current pollution data for the enclosed space;

generating control data based on said external pollution data and said current pollution data for said enclosed space; and controlling said at least one ventilation device using said control data.

From another aspect the invention provides an air pollution management system comprising a control system and a ventilation system for an enclosed space, the ventilation system comprising at least one air intake through which air can be brought into the enclosed space from an external environment, at least one air extract through which air can be expelled from the enclosed space, and at least one ventilation device for controlling flow of air through the enclosed space, the control system being configured to determine pollution data for the external environment; determine current pollution data for the enclosed space; generate control data based on said external pollution data and said current pollution data for said enclosed space; and cause said ventilation system to control said at least one ventilation device using said control data.

Advantageously determining said external environment pollution data involves determining pollution data at said at least one air intake, said pollution data preferably identifying at least one pollutant. Determining pollution data at said at least one air intake preferably comprises measuring the composition of the air at said at least one air intake in respect of at least one pollutant.

Typically the or each air intake comprises an air intake apparatus, wherein determining pollution data at said at least one air intake involves measuring the composition of the air within said air intake apparatus, or adjacent said air intake apparatus. In preferred embodiments measuring the composition of air involves providing at least one sensor at said air intake.

Preferred embodiments include predicting pollution data for the enclosed space based on said external environment data and on said current pollution data; and generating at least some of said control data based on said predicted pollution data. Said predicting pollution data advantageously involves predicting the composition of the air in the enclosed space. Predicting pollution data preferably involves identifying at least one pollutant in said external environment pollution data and determining the effect of mixing said at least one pollutant with said current pollution data. Preferably predicting pollution data involves identifying at least one pollution precursor in said external environment pollution data and determining the effect of mixing said at least one pollution precursor with said current pollution data.

Other preferred features of the invention are recited in the dependent claims appended hereto.

In arriving at the present invention, it is recognised that air including particular types of pollutants can be trapped within enclosed space, even when the space is ventilated. It is further recognised that the trapped air pollution can, when mixed with air containing a differing mix of air pollutants, produce toxic pollution within the enclosed space. The predicted pollution levels arising from a plurality of pollutants can be mathematically modelled with one or more measured or estimated internal pollution levels to aid suppression of internally generated pollution.

In arriving at the present invention it is further recognised that pollution in urban environments does not disperse as a function of concentration or in a predictable manner with enough metrological data. Localised effects in the urban environment can cause huge pollution variation within local regions. To obtain good information upon which pollution control can be achieved, the location of the pollution measurement system is instrumental. Accordingly, in preferred embodiments at least one sensor for measuring external pollution levels is located at one or more air intake of the ventilation system.

Systematic external urban pollutants do not diffuse into enclosed spaces, but are brought in or excluded by the operation of the ventilation system. Advantageously, using the ventilation system for pollution control involves considering both external pollution and internal pollution measurements, advantageously with learnt prediction or learnt estimates with prediction.

Embodiments of the invention may operate without predicting internal or external pollution levels, and may calculate control data based on determined current external pollution level(s) and/or on current determined internal pollution level(s). For example, if it is determined that external pollution is above a given threshold, or is worse than the internal pollution level, then control data may be generated to close the or each air intake.

It will be understood that the term “air” as used herein is intended to embrace not only fresh, or pure, air, but also air containing one or more pollutants.

In the present context, an enclosed space typically comprises all or part of the interior of a building, particularly but not exclusively an office building, commercial building or public building. The enclosed space may comprise one or more rooms, one or more corridors and one or more floors (levels), as applicable. More generally an enclosed space may be any space for use by people, e.g. vehicles, office buildings, homes, schools, hospitals and so on.

In preferred embodiments, continuous or regular measurement of air pollutants and their precursors is performed at the, or each, point of air intake and at a point of extract or a location between intake and extract. Continuous or regular measurement of carbon dioxide levels within the space and any occupied subdivided spaces is preferably also performed. Measurement at the intake may be achieved by providing at least one sensor within the gas intake air flow, preferably just outside or within the air intake apparatus. Similarly for the extract, at least one senor may be placed within the extract airflow, preferably in the space just before the extract duct or within the extract apparatus. Sensors intermediate the intake and extract are preferably located where gases are mixed within the enclosed space.

Control data derived from the measurements is used to regulate the airflow of the enclosed space, including any one or more of the airflow into the space, recirculation of air within the space, and extraction of air from the enclosed space. The airflow is advantageously regulated depending on the human toxicological potency of the pollutants within the space.

The toxicological potency of the air within the space is preferably calculated by considering not only the immediate pollution values (which may be measured, estimated or predicted) but also the predicted pollution caused by mixing any detected or predicted pollution precursors within the incoming air with the air already in the space.

The toxicological components of the air can be measured with a single indicative component such as Nitrogen dioxide. In preferred embodiments toxic and non toxic components are measured; toxic (Ozone, Nitrogen Dioxide, Carbon Monoxide, Particulate matter PM10, PM2.5 and PM1) non toxic (nitrogen oxide) and carbon dioxide toxic at high levels. The volume air flow can also measured to improve the model but is not necessary. A multi-sensor module may be used to measure all the components, but they could all be measured individually.

Optionally, the system may use one or more learnt or predicted pollution profiles and/or the level of one or more indicative pollutants to determine the required pollution data instead of or in addition to directly measured pollutant levels. This reduces the cost of implementation but usually at the expense of performance. In addition implementing a period of learning followed by partial monitoring can minimise operational cost at the expense of performance.

Advantageously, the system identifies pollution precursors and any resultant or other mixinggenerated internal pollution levels. The use of a system model and predicted outcomes from the model greatly facilitate the practical reduction of air pollution within enclosed spaces.

From one aspect the invention provides a pollution management system for enclosed spaces, which uses pollution data obtained from any one or more of a learnt pollution profile, at least one mathematical model for predicting pollution and/or direct measurement of pollutants to produce control information for controlling the operation of a ventilation system. Advantageously, the system uses a mathematical model of the enclosed space that predicts pollution levels at one or more locations in the space based on measured, learnt and/or predicted pollution data, including any identified or predicted pollution precursors. The pollution data is measured, learnt and/or predicted in respect of at least two locations of the encloses space, in particular at at least one air intake of the ventilation system, and at one or more location within the enclosed space, or at a ventilation extract.

Advantageously the system determines pollution data relating to external pollutant(s) brought into the space at the, or each, air intake, and internal pollutants that are released, produced or trapped within the enclosed space.

In preferred embodiments, the level of CO2 is measured at one or more locations in the enclosed space (e.g. at locations where CO2 might build up due to local events such as meetings) at one or more location in the enclosed space (e.g. at an air intake, at an air extract, and/or at one or more locations in between) is measured (as opposed to being learnt, estimated or predicted)

The preferred system includes means for measuring, and/or estimating from one or more learnt models and/or learnt profiles, at least one pollutant and at least one pollution precursor. The measurement means may comprise one or more sensor modules for measuring said pollutant(s) and pollutant precursor(s). Each sensor module may comprise one or more device for measuring one or more gaseous and/or particulate pollutants, e.g. NO2, NO, SO2, CO, 03, particulates defined as PM10, PM2.5, PM1. The estimation means may comprise a suitably programmed processor for estimating said pollutant(s) and pollutant precursor(s)

Optionally, said learnt profiles or predicted profiles or models are based on any one or more of the time of day, the day of the week, and may take into account meteorological information such as the prevailing wind, speed and direction along with precipitation information at the enclosed space.

Optionally said learnt profiles or predicted profiles or models are based on one or more indicative pollutants correlated with one or more model for other pollutant(s).

Preferred systems implement a control strategy that involves determining from the internal CO2 measurement and from the pollution data obtained by estimation or measurement how to adjust the ventilation system to minimise pollution in the enclosed space. Advantageously the system uses predicted future pollution levels at the air intake. Optionally the system uses predicted or forecasted pollution levels and uses them to offset the time delays inherent in building ventilation systems. This allows for sufficient operational time windows preventing high frequency stop/start operation and permitting the intake of low pollution air over an appropriate period of time.

Advantageously, the system uses a model of chemical reactions associated with fresh air brought into trapped air within the enclosure to regulate ventilation.

Brief Description of the Drawings

An embodiment of the invention is now described by way of example and with reference to the accompanying drawings in which:

Figure 1 is a schematic view of an air pollution management system embodying one aspect of the invention;

Figure 2 is a flow chart illustrating measurement, learning and prediction processes implemented by preferred embodiments of the system of Figure 1; and

Figure 3 is flow chart illustrating a preferred control process implemented by the system of Figure 1.

Detailed Description of the Drawings

Referring now to Figure 1 of the drawings there is shown, generally indicated as 10, an air pollution management (APM) system embodying one aspect of the invention. The APM system 10 comprises a ventilation system 12 for ventilating an enclosed space 14. The space 14 may for example comprise one or more rooms or floors of a building, or the cabin of a vehicle, and the ventilation system 12 is installed accordingly as would be apparent to a skilled person.

The ventilation system 12 includes at least one air intake 13 (only one provided in the illustrated embodiment) through which air can be drawn in use into the enclosed space 14 from an external environment, and at least one air extract 15 through which air can be expelled from the enclosed space 14 to the external environment. One or more air ducts 16 may be provided for transporting air from the intake 13 to the enclosed space 14. One or more air ducts 18 may be provided for transporting air from the enclosed space 14 to the extract 15. One or more air ducts 20 may be provided, in this example between the ducts 16, 18 for recirculating air within the enclosed space 14.

The ventilation system 12 includes a ventilation control system (VCS) 22 and a plurality of ventilation devices that are controlled, electrically or electromechanically, by the VCS 22 to ventilate the enclosed space. The VCS 22 may comprise any suitable computing device programmed or otherwise configured to perform the tasks described herein any other required tasks.

In the illustrated embodiment, the ventilation devices comprise an air intake damper 24, an air extract damper 26, a recirculation damper 28, an air filter 30, an air cooling device 32, an air heating device 34, and a fan 36. In this example, the intake damper 24 is located at the air intake 13, the extract damper 26 is located at the air extract 15 and the recirculation damper 28 is located in the recirculation duct 20. Each damper 24, 26, 28 is operable to control the flow of air at its location, and may therefore be said to act as a valve. Each damper is typically operable between an open state, in which it allows air to pass through it, and a closed state in which it prevents (or substantially prevents) air from passing through it. Each damper may be operable in the open state to control the volume of air that can pass though it. The filter 30 removes particulate contaminants from air passing though it and may be located in the duct 16. The cooling and heating devices 32, 34 may be used to control the temperature of the air in the system 12, and may be located in any convenient duct. The fan 36 is operable to move air through the system 12 and may be located in any convenient duct. It will be apparent that the specific configuration of the ventilation system 12 shown in Figure 1, and in particular the number, type and location of the ventilation devices is not limiting to the invention and alternative embodiments may have alternative configurations.

The APM system 10 typically includes at least one temperature sensor 37 for measuring the temperature in the enclosed space 14. Typical embodiments of the APM system 10 include at least one CO2 sensor 38 for measuring the level of CO2 in the enclosed space 14. Multiple CO2 sensors maybe spaced apart around the space to monitor CO2 at different locations.

The APM system 10 further includes a plurality of sensors 40, each sensor 40 being capable of measuring the level of one or more pollutants in the air to which it is exposed. Accordingly, each sensor 40 may comprise one or more devices for measuring gaseous and/or particulate pollutants. Conveniently, such measuring devices are of a conventional type. In preferred embodiments, each sensor 40 is capable of measuring any one or more of the following pollutants: CO2, CO, 03, NO2, NO, SO2, Volatile Organic Compounds (VOCs) such as Benzene, Formaldehyde and Polycyclic Aromatic Hydrocarbons, Esters, Ketones, Aldehydes and Particulates (PM10, PM2.5, PM1). VOCs may be measured individually or multiple VOCs may be represented by a single measurement based on a summation of the levels of the relevant VOCs. Typically, where the sensor 40 comprises more than one measuring device, it may be provided as a sensor module containing all of the relevant measurement devices.

At least one of the sensors 40A is located at the air intake 13. For example, it may be incorporated into, or located beside, the intake damper 24 (or other intake apparatus). If located beside the intake damper 24 it is preferably located at the external side of the damper 24 (as illustrated) although it may alternatively be located at the internal side.

Optionally, at least one of the sensors 40B is located within the enclosed space 14 between the air intake 13 and the air extract 15.

In preferred embodiments, at least one of the sensors 40C is located at the air extract 15. For example, it may be incorporated into, or located beside, the extract damper 26 (or other extract apparatus). If located beside the extract damper 26 it is preferably located at the internal side of the damper 26 (as illustrated) although it may alternatively be located at the external side.

In alternative embodiments (not illustrated) one or other of the sensors 40B, 40C may be omitted, e.g. there may be a sensor 40A at the intake 13 and a sensor at either the extract or between the intake and the extract. More generally, at least one (conveniently only one) sensor 40 is provided at the intake 13, and at least one (conveniently only one) other sensor 40 is provided either at the extract or between the intake and the extract.

The APM system 10 further includes a pollution control system (PCM) 42 for generating control information for controlling the operation of the VCS 22 based on data received from the sensors 40, preferably in combination with data received from one or more other sources. The other data sources may include any one or more of the temperature sensor 36, the CO2 sensor, and one or more external computer system 44. In the illustrated embodiment, the external computer system 44 is capable of providing meteorological data relating to the vicinity of the enclosed space, e.g. relating to current and/or forecasted conditions such as temperature, precipitation and/or wind.

The PCM 42 may comprise any suitable computing device(s) programmed or otherwise configured to perform the tasks described herein. In the illustrated embodiment, the PCM 42 is remotely located with respect to the enclosed space 14 and its ventilation system 12, and communicates with the VCS 22 and sensors 36, 38, 40 across a telecommunications network (which may be wired and/or wireless as convenient). It may also communicate with the external computing system 44 across a telecommunications network (which may be wired and/or wireless as convenient). In the illustrated embodiment, the PCM 42 may comprise a remote server configured to perform the tasked described herein. Alternatively, the PCM 42 may be located at the enclosed space 14, for example being incorporated with the VCS 22. Alternatively still, the PCM 42 may comprise distributed computing resources for performing the tasks described herein. For example, respective parts of the PCM may be implemented by appropriate computing resources provided at any one or more of a remote server, one or more of the sensor modules 40, and/or the VCS 22.

The PCM 42 may use pollutant data received from the sensors 40 in real time, i.e. current pollutant measurements taken by the sensors 40, and/or may use historical pollutant data from the sensors 40 that has been recorded to create one or more historical pollution profiles, i.e. learnt profiles. Such profiles may include pollution data profiling pollution over a given time cycle, e.g. a day, a week or a month. The profiles may indicate the level of one or more pollutants overtime. The profiles may relate to the specific location of the sensor 40 that provided the relevant data. The PCM 42 may also use predicted pollution data when generating the control information. Similarly one or more historical pollution profiles may be created using data provided by the temperature sensor 37 and/or the CO2 sensor 38. Alternatively, one or more historical pollution profiles may be provided to the PCM 42 from an external source, e.g. the computer system 44.

In preferred embodiments, the PCM 42 may be configured to generate predicted pollution data from current pollutant data received from the sensors 40 and/or from said historical pollution profile(s) using one or more mathematical model or other data prediction technique. The mathematical model may comprise a model of pollution levels overtime based on historical pollution data (e.g. from said pollution profiles), optionally also modelling the effects of meteorological conditions on pollution levels (in which case the data provided by the external computer system 44 may be taken as an input to the model). Alternatively, or in addition, the mathematical model may model the effects of the operation of the ventilation system 12 on pollution levels in the enclosed space 14. The predicted pollution data may comprise a predicted pollution profile, i.e. a prediction of pollution levels overtime. Similarly one or more predicted pollution profiles may be created using data provided by the temperature sensor 37 and/or the CO2 sensor 38.

In preferred embodiments, a mathematical model of the air (with pollutants) within the enclosed space is used to make a prediction based on the composition of the intake air (with pollutants). Optionally, the model may include one or more characteristics of the ventilation system, e.g. ventilation rate, and/or a mixing rate model.

It is particularly preferred that when generating predicted pollution data in respect of the enclosed space 14, the PCM 42 predicts the effects of the composition of the air at the intake when mixed with the air in the enclosed space 14. This may involve identifying one or more pollutants and/or one more pollutant precursors at the air intake and determining how these will affect pollution levels in the enclosed space 14 when mixed with the air in the enclosed space 14 having regard to the composition of the air in the enclosed space 14. Such considerations are preferably included in the mathematical model. For the purposes of generating the predicted pollution data in the enclosed space 14, the composition of the air at the intake 13 may be determined by current measurement(s) from the sensor 40A, and/or from estimated pollutant level(s) taken from a historical or learnt pollution profile, and/or from a predicted pollution profile for the intake 13. The composition of the air at the enclosed space may be determined by current measurement(s) from the sensor 40B and/or 40C, and/or from estimated pollutant level(s) taken from a historical or learnt pollution profile.

In preferred embodiments, a respective pollution profile (historical and/or predicted) is provided for each pollutant being monitored and/or controlled. In cases where a pollutant is not measured directly, its level may be inferred from the level of one or more other indicative pollutant. For example, the level of CO2 may be indicative of the presence of one or more VOCs.

In use, the PCM 42 determines pollution data in respect of the air intake 13, which is an indication of external pollution levels (i.e. the external environment around the enclosed space 14), and determines pollution data in respect of the enclosed space 14 (i.e. from one or more sensor 40 located at the extract 15 and/or located between the intake 13 and the extract 15), which is an indication of internal pollution levels. The PCM 42 evaluates both the external and internal pollution data to generate control data for the VCS 22. For each relevant pollutant, the external pollution data may comprise any one or more of: measured pollutant level(s) (e.g. as measured by sensor 40A); inferred pollution level(s); estimated pollutant level(s) (e.g. from a historical pollution profile); predicted pollutant level(s) (e.g. as predicted by a mathematical model). For each relevant pollutant, the internal pollution data may comprise any one or more of: measured pollutant level(s) (e.g. as measured by sensor 40B and/or 40C, or 38); inferred pollution level(s); estimated pollutant level(s) (e.g. from a historical pollution profile); predicted pollutant level(s) (e.g. as predicted by a mathematical model). The evaluation is typically performed overtime with the relevant pollution data being provided correspondingly overtime, e.g. continuously, in respect of regular intervals or in respect of particular time period(s).

The output of CO2 sensor(s) 38 are preferably monitored to ensure that CO2 levels in the enclosed space 14 do not exceed legal or other set limits.

In typical embodiments the evaluation performed by the PCM 42 involves the application of a time based pollution control algorithm to the relevant internal and external pollution data. The evaluation may be performed in respect of each of a plurality of time instants, using the respective internal and external pollution data for each instant and producing corresponding control data for each instant. A primary goal of the algorithm is typically to minimize or reduce the quantity of one or more pollutants in the enclosed space, especially those that are toxic. As such the algorithm may include a cost function with pollutant weighting values for minimizing toxic pollution in the enclosed space 14. The algorithm may also aim to minimize energy or resource usage; and/or to maintain CO2 levels within desired limits; and/or to maintain the temperature in the enclosed space within desired limits, and may include one or more cost functions for achieving any of these aims.

The control data generated by the PCM 42 is communicated to the VCS 22 which operates the ventilation system 12 accordingly. Typically this involves adjusting the flow of air through the enclosed space 14 by controlling the operation of any one or more of the fan(s) and/or damper(s).

With reference to Figure 2, an example of the measurement, learning and prediction performed by the PCM 42 is described. In respect of the air intake 13 (i.e. in connection with external pollution), for each relevant pollutant (1 to n) a measurement is taken by the sensor 40A (201). For each relevant pollutant, a time based pollution model (or profile) is maintained based on historical data and optionally adjusted to compensate for local weather conditions (202). For each relevant pollutant, predicted pollution data (e.g. predicted pollution profile) is generated based on the respective measurement (or an inferred pollution level) and the historical model/profile (203).

For each CO2 sensor 38 (1 to n), and/or optionally each relevant VOC, a measurement is taken by the sensor 38 (204). For each sensor 38, a time based CO2 model (or profile) and/or time based VOC model/profile is maintained based on historical data (205). For each sensor 38, predicted CO2 data (e.g. predicted CO2 profile) is generated based on the current measurement and the historical profile (206), and optionally predicted VOC data (e.g. predicted VOC profile) is generated based on the current measurement of the VOC (or an inferred value using CO2 as an indicator) and the historical profile (207).

In respect of the air extract 15 and/or internal sensor 40B (i.e. relating to internal pollution), for each relevant pollutant (1 to n) a measurement is taken by the sensor 40B or 40C (208). For each relevant pollutant, a pollution mixing model (or profile) is maintained based on current and historical pollution data, and on one or more air flow characteristics with respect to the enclosed space (e.g. ventilation rate and transport delay) (209). For each relevant pollutant, predicted pollution data (e.g. predicted pollution profile) is generated based on the respective measurement (or an inferred pollution level) and the historical model/profile (210).

Referring now to Figure 3 an example of the control process performed by the PCM 42 is described.

In respect of the air intake 13, i.e. in respect of the external pollution levels, the determined pollution data (301), which in this example comprises, for each pollutant, the determined current pollutant level (measured, estimated or inferred) and/or predicted pollutant level(s) (e.g. the predicted time profile), is assessed (302) to determine if the level exceeds, or may exceed within a given time period, a relevant limit (e.g. a legal limit). If so, control data is generated (303) to cause the ventilation system 12 to take appropriate action, which in this case may involve reducing ventilation (e.g. by closing or restricting the intake damper 24) and/or increasing recirculation around the enclosed space 14. Such control actions are aimed at restricting ingress to the enclosed space of certain pollutants.

In respect of the internal pollution levels, the determined pollution data (304) is assessed (305) to determine if the relevant pollutant(s) level(s) exceeds, or may exceed within a given time period, a relevant limit (e.g. a legal limit). In this case the pollution data may comprise, for each pollutant, the determined current pollutant level (measured, estimated or inferred) and/or predicted pollutant level(s) (e.g. the predicted time profile). If a relevant level is exceeded or it is deemed that it will be exceeded, then control data is generated (306) to cause the ventilation system 12 to take appropriate action, which in this case may involve increasing ventilation and/or by reducing recirculation, which may be achieved by appropriate control of the damper(s) and fan(s). Such control actions are aimed at flushing one or more pollutants from the enclosed space 14.

In respect of CO2 levels, the determined CO2 data (307) is assessed (308) to determine if the relevant CO2 level(s) exceeds, or may exceed within a given time period, a relevant limit (e.g. a legal limit). In this case the CO2 data may comprise, for each CO2 sensor location, the determined current CO2 level (measured, estimated or inferred) and/or predicted pollutant level(s) (e.g. the predicted time profile). If the level is exceeded or it is deemed that it will be exceeded, then control data is generated (309) to cause the ventilation system 12 to take appropriate action, which in this case may involve increasing ventilation and/or by reducing recirculation, which may be achieved by appropriate control of the damper(s) and fan(s). This may involve adding CO2 to the list of pollutants that need to be flushed from the space 14.

In cases where more than one pollutant needs to be restricted or flushed, or in the case of CO2 where CO2 limits are high in more than one location, then the PCM 42 may rank the pollutants in order of priority and generate control data to deal with the higher priority pollutants first.

Assessment of the pollution data may be performed using a weighted cost function.

The PCM 42 may evaluate how to minimize energy consumption or resource (e.g. pollution scrubber) usage (310). The resultant control data (311) typically comprises data to cause the ventilation system 12 to reduce ventilation and/or reduce circulation.

The PCM 42 may evaluate how to maintain thermal comfort levels in the enclosed space (312). The resultant control data (313) typically comprises data to cause the ventilation system 12 to increase ventilation or recirculation and/or to increase energy usage.

In preferred embodiments, at least one air measurement is taken at the, or each, or at least one air intake 13 to the enclosed space 14. This may involve measuring the composition of the air, and more particularly measuring the quantity (e.g. as a parts per million (ppm) or other suitable measure) of one or more pollutants in the air. Measuring or learning a pollution profile at one or more air intake locations can allow sufficiently accurate measures of pollution to enable airflow management to reduce pollution from external sources, within enclosed spaces. The pollutants are typically gaseous or particulate in form, and typically include any one or more of Ozone, Nitrogen dioxide, Nitrogen Oxide, Sulphur Dioxide, Carbon Monoxide, Carbon Dioxide, and particulates classified as PM10, PM2.5 and PM1.

Preferred embodiments take into account internal and external sources of pollutants, including any one or more of Ozone, Nitrogen dioxide, Nitrogen Oxide, Sulphur Dioxide, Carbon Monoxide, Carbon dioxide, and particulates classified as PM10, PM2.5 and PM1. Internal pollution may comprise leached and/or absorbed pollution, or pollution generated within the enclosed space from chemical reactions, any one or more of which may be managed by the preferred system. Leached pollutants may include VOCs from occupants of the enclosed space, and/or fabric and/or furnishings. Those from furnishings are considered transient and may be dealt with at the time they are installed. Air pollution from mould or other biological sources is also considered transient and may be tested for as part of on-going maintenance.

Preferred embodiments may also manage internal systemic pollutants associated with occupants such as VOCs and/or CO2. VOCs may be estimated by measuring CO2 concentrations and using same as an indication of VOCs. If other location-specific internal pollutants are not measured directly, such as Ozone or Carbon monoxide, they can be measured over a number of months (or other period) and their profile learnt. During operation of the ventilation system 12, a measured pollutant correlated with the location specific pollutant can be used as indicative with the learnt pollution profile to achieve pollution minimisation.

Preferred embodiments of the invention are configured to achieve one or more of he following targets: minimising the amount of pollution within the enclosed space 14 based on the toxicological potency of one or more pollutant; maintaining thermal comfort within one or more temperature band; minimising the amount of resources consumed (e.g. electrical energy and chemical scrubbers); maintaining the air quality as close to or below legal limits (or other set limits) for the duration of significant occupancy.

In preferred embodiments, external and internal air pollution is monitored and, by regulating the airflow of the ventilation system 12, air pollution is minimized in the enclosed space 14, advantageously with respect to one or more pollutants deemed to have the greatest toxicological potency.

In preferred embodiments, at least one sensor 40, but typically a plurality of sensors, is provided at a respective predefined location of the enclosed space 14 in order to control pollution in the enclosed space. The or each sensor 40 is configured to measure the quantity of one or more pollutant (gaseous and/or particulate) in the air, and to this end may comprise one or more gas or particulate measuring device as required. Conveniently the sensors 40 may comprise conventional gas, multigas and/or particulate measuring devices.

Estimation and prediction techniques may be used to compensate for ventilation transport delays and to predict possible internal pollution generation for old and new air interactions. Using resulting control data, the ventilation system 12 (conveniently via a standard interface) is controlled to minimise toxic pollution within the space, and preferably also to minimise energy or resource usage, maintain within set limits the CO2 within the space and maintain thermal comfort.

To minimise internal pollution the, or each, pollution source is advantageously determined. External pollution may be measured by a sensor 40A located at the air intake 13, and the resulting measurement(s) may be used in one or more mathematical models to predict future pollution levels. Internal pollution sources may be measured either at the air extract 15 and/or at one or more location within the enclosed space 14. For large multi-zone enclosed spaces, the most cost effective method is to measure at the air extract(s) of the ventilation system 12.

The preferred method of managing the internal pollution involves varying with time the rate of ventilation by controlling the ventilation system 12 of the enclosed space 14. The ventilation system 13 can be controlled to adjust intake, recirculation and/or extract fan speeds (as required), and/or to adjust one or more baffles (or dampers) to control the amount of air brought into the space and/or recycled within the space. This effectively determines the flushing rate of pollutants out of the space. CO2 is considered a pollutant and is preferably measured directly within the space to ensure the amount of air taken in at the intake is sufficient to maintain levels below legal or mandated values.

Preferred embodiments support data prediction and system modelling to optimise a cost function to minimise toxic pollution within the space, and preferably also to minimise energy or resource usage, to maintain within set limits the CO2 within the space and/or maintain thermal comfort.

Preferred embodiments involve controlling the ventilation system 12 to reduce the amount of air pollution occupants are exposed to within the enclosed space 14. This is advantageously achieved by using pollution measurements with learnt and/or predicted pollution profiles, or pollution estimates with learnt and/or predicted pollution profiles, with respect to the air intake 13 of the ventilation system, and measuring or estimating the pollution within the space 14 or at the ventilation air extract

15. The preferred estimation method used at these locations is based on learnt diurnal profiles with weekly patterns for individual pollutants and associated with correlated measured pollutants used as an indication of the estimated pollutant. Direct pollutant measurement can be performed by an appropriate sensor 40, e.g. a multi gas and particulate matter combined sensor module. The location and accuracy of the sensor module 40 provides effective operation of the system 10. The intake 13 and extract 15 and/or internal measurements preferably involve taking multiple and synchronised measurements throughout the relevant cycle, e.g. a diurnal cycle in preferred embodiments. In preferred embodiments appropriately placed internal CO2 sensors 38 continually monitor and report CO2 levels to ensure any required legal compliance. For legal compliance it is preferred that the pollution sensor is verifiably equivalent in accuracy to a reference sensor.

Due to airtransport delays and the need to flush carbon dioxide (CO2), and/or other pollutants, from enclosed spaces, prediction of the pollutant’s profile is advantageous to ensure the minimum pollution exposure for the occupants, preferably while maintaining thermal comfort and CO2 below any mandated levels.

Prediction methods can take any convenient conventional form, e.g. generated from conventional extrapolation techniques with state estimators such as the Kalman filter, or using any conventional mathematical modelling techniques, and may use learnt profiles for predictions over a longer timescales.

The ON/OFF cyclic operation of ventilation systems for energy saving during period of low occupancy traps pollutants which, when mixed with a differing pollution mix of the incoming air, can induce spikes in enclosed pollution levels. Trapped non toxic pollutants such as Nitrogen Oxide can be oxidised to the toxic Nitrogen Dioxide as ‘fresh’ air is drawn in at the start of the day. One reaction path associated Ozone in the ‘fresh’ air oxidises trapped Nitrogen Oxide generating a toxic pollution spike.

This interaction due to air mixing can be managed by measuring the pollutants in the incoming air and the pollutant mix trapped within the enclosed space. The airtransport delays associated with bringing in fresh air should also be accounted for to achieve effective pollution control. To account for these delays a prediction estimate is made of the likely future external pollutants. This future estimate should be sufficiently forward in time to allow sufficient air to be drawn in to maintain the appropriate flushing of internal pollutants. The rate of change profile of internal pollutants such as Carbon Dioxide associated with ventilation and occupancy periods should also be learnt to aid optimal energy and resource utilisation.

The preferred sensor positioning for measurement and learning of pollution profiles is as follows. Pollution localisation effects are accounted for by placing a sensor (e.g. a multi gas and particulate sensor module) at the air intake, typically just behind the intake grill. This enables a pollution profile of the specific intake to be measured and learnt.

Enclosed occupied spaces typically have diurnal pollution rhythms associated with their air intake.

For example, external traffic pollution typically results in a “double hump” in pollution levels (e.g. levels of NO2) at the air intake corresponding to morning and evening rush hours. Conventional control systems ventilate over a set period of time (5am-8pm BST). The air mix within the space over a period of time is a sum of the air within the space mixed with the air brought in over the same time period minus the air extracted and lost and is dependent on the mixing ability of the ventilation system. Time delays inherent in this process can introduce significant differences in the composition of the air mix within the enclosed space compared to the composition outside. In the present example these time delays, or air transport delays, result in the slow build up of NO2 pollution during the morning. The same delays prevent immediate pollution flushing allowing the pollution within the building during working hours (9am-5pmBST) to be greater on average than that seen at the intake.

Pollution can come from and be absorbed by the occupants and objects within the enclosed space. Pollution can also arise from interactions between occupants/objects and the air drawn into the space. Thus every space independently served by an air intake and isolated from others should preferably be monitored with a full range of pollution sensors but not necessarily within a single sensor module.

Advantageously, embodiments of the invention may use airtransport delays to find the source of the pollution. For example, two potential sources of pollutants, internal and external, may be distinguished from one another by measuring pollution at the point of air extraction from the enclosed space or within the extracted air flow. The, or each, pollution extract sensors can differentiate between internal and external pollution sources by comparing pollution levels with those measured by the intake sensor and/or the internal sensor(s). This facilitates effective pollution control as it can determine the appropriate control action. Counterintuitively, for high levels of pollution outside, the control system might decide to continue bringing in polluted air at a high rate to flush out trapped or generated pollution within the enclosed space or a particular zone thereof. The rate of internal pollution generation can be determined by comparing the incoming with outgoing pollution levels, advantageously taking into account air mixing and/or transport delays.

The performance of preferred embodiments is advantageously improved using data gathered from pollution control trials. For example a pollution control trial may be performed in which CO2, or other gas/pollutant, is used as an indicative internal pollutant. One or more pollution sensors may be placed at the air intake of the space and at the air extract. Data from the trial (which may for example take place for a month) may be used to create, or learn, a mathematical model of the dynamic behaviour of pollution within the enclosed space. The internal CO2 level may then be used to control the pollution within the enclosed space. For example the model may indicate when to allow the CO2 level to rise rapidly by reducing ventilation and when to suppress the CO2 level by increasing ventilation. Environmental comfort may be maintained within stipulated limits and result in pollution reduction of the order of 30% with associated energy saving in some systems of 50%. It will be apparent that the same or a similar modelling and control technique may be performed for each pollutant to be monitored and controlled.

Preferred embodiments of the system include a sensor module 40, typically comprising multi gas and particulate measuring device(s), located directly at (i.e. beside, within or otherwise incorporated into) the or each fresh air intake of the enclosed space. If the internal space is subdivided into separately ventilated zones, each is preferably provided with a similar sensor module at its air intake apparatus. Preferably, a sensor module 40, typically comprising multi gas and particulate measuring device(s), is located directly at (i.e. beside, within or otherwise incorporated into) the or each fresh air extract of the enclosed space, for example at (i.e. beside, within or otherwise incorporated into) an extract Air Handling Unit AHU. If there are separate AHU’s extracting from independent zones within the space, then a respective sensor module is preferably provided for each AHU or other air extract apparatus.

One or more CO2 sensors, or other sensor module, may be provided in one or more locations throughout the enclosed space.

The rate of data collection for each air pollutant preferably corresponds with the volume of air sampled and the rate of change of the pollutant. For relatively large spaces such as commonly found in buildings sampling at between 5 and 15 minutes has been found to be sufficient. This is due to the relatively large air volumes and associated air mixing time delays. Air quality information from all sensor modules may be collected together and used to determine the control actions of the ventilation system.

In preferred embodiments the ventilation system 12 has automated (e.g. electrical or electromechanical) control of all of its ventilation, or air control, devices (which may include any one or more of actuators such fans, actuators, valves, dampers, and heaters and coolers) via a ventilation control system. The ventilation system and its control system may themselves be intrinsically conventional but operated in accordance with the invention.

Preferred embodiments include a control system 42 (which is typically separate from the ventilation system control system but may control the operation of the ventilation control system) configured to learn and/or predict an external air pollution pattern. This information together with the known internal pollution state can be used to minimize the internal pollution toxicity, preferably while maintaining thermal comfort and CO2 levels within mandated limits. This process can be improved by learning a pollution and CO2 profile associated with the space. This understanding of the system dynamics allows a significant reduction in the consumption of resources to maintain thermal comfort as well as minimising pollution. A cost function can be constructed based on energy usage, pollution reduction, CO2 levels and thermal comfort to control the operation of the ventilation system.

In preferred embodiments, external and/or internal pollution measurement is performed by any one or more of the following techniques: by direct measurement at least one, but typically multiple, air pollutant(s) being monitored and controlled by the system; by use of multiple indicative pollutants or a single indicative pollutant; by learning or otherwise determining one or more local pollution profile, e.g. a daily and/or weekly profile. To maintain comfort and meet any legal requirements CO2 sensors may be placed appropriately within the space. A learnt CO2 profile can only aid optimisation and is not a substitute for real measurements.

In preferred embodiments, each sensor module comprises one or more device (such as a gas sensor or particulate sensor, which may be conventional) for measuring any one or more of the air pollutants being controlled, which typically include any one or more of the following pollutants: CO2, CO, 03, NO2, NO, SO2, Volatile Organic Compounds (VOCs) such as Benzene, Formaldehyde and Polycyclic Aromatic Hydrocarbons, Esters, Ketones, Aldehydes and Particulates (PM10, PM2.5, PM1). Any individual sensed gas or particulate can be measured directly and can subsequently have a learnt profile. The learnt profile can provide pollutant level data that can be substituted for an actual measurement. Internally generated VOCs are typically associated with large changes to the internal space so periodic learning is often sufficient. However gasses and particulates associated with vehicular transport require continual, or at least more frequent, learnt or measured monitoring. In addition toxic interactions between trapped pollution and incoming external pollution may be learnt.

The invention is not limited to the embodiments described herein which may be modified or varied without departing from the scope of the invention.

Claims

CLAIMS:

1. A method of controlling a ventilation system for an enclosed space, the ventilation system comprising at least one air intake through which air can be brought into the enclosed space from an external environment, at least one air extract through which air can be expelled from the enclosed space, and at least one ventilation device for controlling flow of air through the enclosed space, the method comprising:

2. The method of claim 1, wherein determining said external environment pollution data involves determining pollution data at said at least one air intake, said pollution data preferably identifying at least one pollutant.

3. The method of claim 2, wherein determining pollution data at said at least one air intake comprises measuring the composition of the air at said at least one air intake in respect of at least one pollutant.

4. The method of claim 2 or 3, wherein the or each air intake comprises an air intake apparatus, and determining pollution data at said at least one air intake involves measuring the composition of the air within said air intake apparatus, or adjacent said air intake apparatus.

5. The method of claim 3 or 4, wherein measuring the composition of air involves providing at least one sensor at said air intake.

6. The method of any preceding claim, wherein determining said current pollution data for said enclosed space involves determining pollution data at said at least one air extract, said pollution data preferably identifying at least one pollutant.

7. The method of claim 6, wherein determining pollution data at said at least one air extract comprises measuring the composition of the air at said at least one air extract in respect of at least one pollutant.

8. The method of claim 6 or 7, wherein the or each air extract comprises an air extract apparatus, and determining pollution data at said at least one air extract involves measuring the composition of the air within said air extract apparatus, or adjacent said air extract apparatus.

9. The method of claim 7 or 8, wherein measuring the composition of air involves providing at least one sensor at said air extract.

10. The method of any preceding claim, wherein determining said current pollution data for said enclosed space involves determining pollution data at at least one location between said at least one air intake and said at least one air extract.

11. The method of claim 10, wherein determining pollution data comprises measuring the composition of the air at said at least one location between said at least one air intake and said at least one air extract in respect of at least one pollutant.

12. The method of claim 11, wherein measuring the composition of air involves providing at least one sensor at said at least one location.

13. The method of any preceding claim further including predicting pollution data for the enclosed space based on said external environment data and on said current pollution data; and generating at least some of said control data based on said predicted pollution data.

14. The method of any preceding claim, wherein said predicting pollution data involves predicting the composition of the air in the enclosed space.

15. The method of any preceding claim, wherein said predicting pollution data involves identifying at least one pollutant in said external environment pollution data and determining the effect of mixing said at least one pollutant with said current pollution data.

16. The method of any preceding claim, wherein said predicting pollution data involves identifying at least one pollution precursor in said external environment pollution data and determining the effect of mixing said at least one pollution precursor with said current pollution data.

17. The method of any preceding claim, wherein said predicting pollution data involves applying at least one mathematical model to said external environment pollution data and said current pollution data to produce predicted pollution data for said enclosed space.

18. The method of claim 17, wherein said at least one mathematical model is configured to model overtime the composition of the air, including pollutants, in said enclosed space based on said external environment pollution data and said current pollution data.

19. The method of claim 18, wherein said at least one mathematical model is configured to model a ventilation rate of said ventilation system.

20. The method of claim 18 or 19, wherein said at least one mathematical model is configured to model a mixing rate of said ventilation system.

21. The method of any preceding claim, wherein said predicting pollution data involves predicting a profile of said pollution data for the enclosed space overtime.

22. The method of any preceding claim, wherein said determining pollution data for the external environment involves determining a profile of said external environment pollution data overtime.

23. The method of claim 22, wherein determining pollution data for the external environment involves determining a historical profile of external environment pollution overtime.

24. The method of claim 23 when dependent on any one of claims 2 to 5, wherein said external pollution data profile is determined from pollution data recorded in respect of said at least one air intake.

25. The method of claim 23 or 24, wherein said determining pollution data for the external environment involves determining a predicted profile of said external environment pollution data using said historical profile.

26. The method of any one of claims 22 to 25, wherein determining pollution data for the external environment involves estimating said external environment pollution data from said profile.

27. The method of any preceding claim, wherein said external pollution data identifies at least one pollutant, and typically the level, e.g. quantity or proportion, of said at least one pollutant.

28. The method of claim 27 wherein at least one of said at least one pollutant is measured by at least one sensor.

29. The method of claim 27 or 28 wherein at least one of said at least one pollutant is inferred by determining the presence of at least one other pollutant.

30. The method of any preceding claim wherein said external environment pollution data is adjusted to compensate for at least one meteorological characteristic ofthe external environment.

31. The method of any preceding claim wherein generating control data involves applying a time based pollution control algorithm at least to said predicted pollution data, and optionally to said external environment data and/or said current pollution data for the enclosed space.

32. The method of claim 31, wherein said algorithm is configured to evaluate said predicted pollution data, and optionally said external environment data and/or said current pollution data, in respect of each of a plurality of time instants and to produce corresponding control data for each instant.

5

33. The method of claim 31 or 32, wherein said algorithm is configured to minimize the quantity of one or more pollutants in the enclosed space, especially pollutants that are toxic.

34. The method of any preceding claim wherein controlling said at least one ventilation device involves adjusting the ventilation rate and/or the recirculation rate of said ventilation system.

35. The method of any preceding claim wherein controlling said at least one ventilation device involves opening or closing said at least one air intake and/or said at least one air extract.

36. An air pollution management system comprising a control system and a ventilation system for an

15 enclosed space, the ventilation system comprising at least one air intake through which air can be brought into the enclosed space from an external environment, at least one air extract through which air can be expelled from the enclosed space, and at least one ventilation device for controlling flow of air through the enclosed space, the control system being configured to determine pollution data for the external environment; determine current pollution data for the enclosed space; generate control

20 data based on said external pollution data and said current pollution data for said enclosed space; and cause said ventilation system to control said at least one ventilation device using said control data.

Intellectual

Property

Office