WO2023007187A1

WO2023007187A1 - Pollution emissions monitoring method and system

Info

Publication number: WO2023007187A1
Application number: PCT/GB2022/052012
Authority: WO
Inventors: Freddie TALBERG; Steve STEELE; Ben MARTSON-RYDINGS; Debasree BANERJEE; Peter Whale
Original assignee: Emission Solutions Limited
Priority date: 2021-07-30
Filing date: 2022-07-29
Publication date: 2023-02-02
Also published as: GB2615507A; GB202111053D0

Abstract

The present disclosure provides a computer implemented method for associating pollution emissions with the pollution sources that produced the pollution emissions. The method comprises: receiving (101) pollution emissions data from at least one pollution emission sensor configured to sense pollution emissions, and determining at least one pollution emission level; receiving (103) an identification of at least one pollution source from at least one pollution source identifier to identify at least one pollution source and its location; associating (105) the received pollution emissions data with the at least one pollution source that produced the pollution emissions based upon the location of the at least one pollution emission sensor, the time the pollution emissions were sensed, the location of the at least one pollution source, and the time at which the at least one pollution source was identified; and determining (107) a mitigation action to reduce the at least one pollution emission level based upon the association between the pollution emissions data and the at least one pollution source. A corresponding system, computer program, and computer readable storage medium are also provided.

Description

POLLUTION EMISSIONS MONITORING METHOD AND SYSTEM

TECHNICAL FIELD

[0001] The present invention relates to the field of pollution emissions monitoring and management. In particular, the present invention provides methods and a system for monitoring and managing pollution emissions.

BACKGROUND

[0002] Many human activities create some form of pollution in the form of pollution emissions. For example, an industrial vehicle may emit noise as well as particulate and gaseous pollutants, such as carbon dioxide and nitrogen oxides (NOx). It may also emit light, which may be considered a pollution emission, particularly during the night.

[0003] Being able to monitor and manage the levels of pollution emissions emitted from various sources is useful for a variety of reasons. One important need is that of monitoring for compliance with regulations or other pollution emission limits. For example, maximum allowable pollution emission levels may be set for a given region, e.g. a building site, or for a given piece of equipment, e.g. a lorry. In the case of a building site, there may be limits on the total noise emitted by the site at certain times of the day, for example. Meanwhile, in the case of a lorry, limits may be set on the amount of particulate matter and nitrogen dioxide emitted. These limits may be set by national or international legislation, local authorities, or may be voluntary as part of a certification scheme, for example.

[0004] In order to enforce these limits and ensure compliance, it is important not just to be able to monitor pollution emission levels, but also to be able to identify the sources of the pollution emissions so that the responsible party can be identified. This can ensure that appropriate action can be taken again any party in breach of the requirements. For example, a fine could be issued to a company that breaches emissions thresholds.

[0005] In the past, pollution emissions have been recorded and correlated to specific vehicles to allow a general assessment of the causes of the pollution emissions. However, these studies have been limited to providing input for general decision-making or legislation.

SUMMARY OF INVENTION [0006] The invention is defined in the independent claims. Optional features are set out in the dependent claims.

[0007] According to a first aspect of the invention, a computer implemented method for associating pollution emissions with the pollution sources that produced the pollution emissions is provided. The method comprises: receiving pollution emissions data that has been sensed by at least one pollution emission sensor configured to sense pollution emissions, and determining at least one pollution emission level; receiving an identification of at least one pollution source, that has been determined by at least one pollution source identifier, to identify at least one pollution source and its location; associating the received pollution emissions data with the at least one pollution source that produced the pollution emissions based upon the location of the at least one pollution emission sensor, the time the pollution emissions were sensed, the location of the at least one pollution source, and the time at which the at least one pollution source was identified; and determining a mitigation action to reduce the at least one pollution emission level based upon the association between the pollution emissions data and the at least one pollution source.

[0008] Optionally, the pollution emissions data is received from the at least one pollution emission sensor. Optionally, the identification of at least one pollution source is received from the at least one pollution source identifier.

[0009] Associating the pollution emissions emitted by a pollution emissions source with that pollution emissions source means that effective actions can be taken to address the level of pollution emissions. Furthermore, accountability can be increased as it can be accurately determined what party is responsible for producing the pollution emissions.

[0010] Optionally, the method further comprises the step of determining whether the at least one pollution emission level exceeds a threshold level.

[0011] The threshold level can be used to give context to the pollution emission levels. It is often only of concern if pollution emission levels reach a certain point (e.g. a level considered dangerous), and so determining whether the at least one pollution emissions level exceeds a threshold can advantageously be used to output an alert or as the basis for determining the mitigation action.

[0012] Optionally, the method further comprises the step of outputting an alert when it is determined that the at least one pollution emission level exceeds the threshold level.

[0013] This information and/or a warning when pollution emission levels reach a threshold, allowing appropriate action to be taken. This is advantageous as it is often only when pollution emission levels reach or exceed a certain level (e.g. a level considered to be dangerous, or a level agreed to be a maximum acceptable level) that action needs to be taken. Hence, only outputting an alert when a threshold is reached reduces the information output to the necessary information, making it more likely it will be acted upon.

[0014] Optionally, the mitigation action is determined if the at least one pollution emission level exceeds the threshold level.

[0015] This provides an automatic suggested response when the threshold level is reached, allowing an operator to easily take action when necessary. By only determining a mitigation action if a threshold is exceeded then the overall resources (e.g. computing power) needed by the system can be reduced.

[0016] Optionally, the mitigation action is determined to reduce the at least one pollution emission level to or below the threshold level.

[0017] Determining a mitigation action such that it will reduce the pollution emission level to (or below) the threshold means that an appropriate mitigation action is proposed that allows pollution levels to be brought back to acceptable levels (i.e. to or below the threshold).

[0018] Optionally, the mitigation action is selected from a predetermined list of possible mitigation actions.

[0019] Having a predetermined list of possible mitigation actions means that the mitigation action can be ensured to be relevant to the pollution emission sources that are being monitored and the particular use case of the method. For example, the predetermined list of mitigation actions can be determined based upon the type of location in which the method is being implemented (e.g. a building site), the expected pollution sources, and the like.

[0020] Optionally, the mitigation action comprises one or more of: adjusting a state of the at least one pollution source, adjusting a schedule of pollution source activity, providing instructions to an operator of the at least one pollution source to inspect and/or change the operation of the at least one pollution source. Optionally, the state of the at least one pollution source may include on, off, idling, standby, low-power mode, and high-power mode.

[0021] Optionally, the method further comprises automatically implementing the mitigation action.

[0022] Automatically implementing the mitigation action means that the system can be used to ensure that pollution emissions stay below a desired level and that if they do reach or exceed this level then an appropriate action is automatically implemented to bring the pollution emissions level back down to acceptable levels. This allows pollution emission levels to be automatically and effectively controlled.

[0023] Optionally, the method further comprises receiving one or more environmental characteristics; and wherein the associating the received pollution emissions data with the at least one pollution source that produced the pollution emissions is further based upon the one or more environmental characteristics. Optionally, the one or more environmental characteristics are received from one or more sensors configured to measure each of the one or more environmental characteristics. Optionally, the one or more environmental characteristics include one or more of: wind speed, wind direction, humidity, ambient temperature, light intensity, and precipitation.

[0024] By taking into account environmental characteristics, the accuracy of the association between the pollution emissions and the pollution emission source that actually produced the measured emissions can be improved. This in turn allows for more effective mitigation actions to be proposed and implemented, increasing the effectiveness of the method at controlling pollution levels.

[0025] Optionally, the method further comprises the step of storing the association between the sensed pollution emissions and the at least one pollution source that produced the pollution emissions in a database.

[0026] Storing the association between sensed pollution emissions and pollution sources can mean that more accurate associations can be made in the future, e.g. by building up an emissions profile of different pollution sources, and that it can be checked that the method is being implemented effectively. For example, certain associations can be checked manually and compared with other, external measurements to check that the correct associations are being made.

[0027] Optionally, the step of receiving pollution emissions data that has been sensed by at least one pollution emission sensor configured to sense pollution emissions comprises receiving pollution emissions data that has been sensed by a plurality of pollution emission sensors. Optionally, the plurality of pollution emission sensors are distributed across at least two locations. Optionally, the at least two locations are within a predetermined site. Optionally, the plurality of pollution emission sensors include two or more types of pollution emission sensor, each type of pollution emission sensor configured to sense a different type of pollution emissions.

[0028] Using a plurality of pollution emissions sensors can provide a number of advantages. It can allow pollution emissions to be sensed in a number of different locations. This can help track the spatial distribution of the pollution emissions which can aid in correctly associating the sensed pollution emissions with the pollution emissions source that produced the pollution emissions. Additionally or alternatively, different types of pollution emissions can be sensed. For example, both noise pollution and light pollution could be measured and associated with a pollution source.

[0029] Optionally, the step of receiving an identification of at least one pollution source, that has been determined by at least one pollution source identifier, to identify at least one pollution source and its location comprises receiving an identification of a plurality of pollution sources, that have been determined by at least one pollution source identifier, to identify the plurality of pollution sources and their respective locations.

[0030] Receiving the location and identification of a plurality of pollution sources means that the pollution emissions can be attributed to an individual pollution emission source even when there may be multiple potential pollution emission sources in the vicinity. This enables better pollution emissions monitoring and management.

[0031] Optionally, the pollution emissions are one or more of: particulates, noise, light, nitrogen oxides, carbon monoxide, carbon dioxide, and vibration.

[0032] Optionally, the method can be applied to non-static pollution sources. In particular, it can be applied to vehicles and machinery which can be moved between locations.

[0033] Optionally, the at least one pollution emission sensor is configured to sense pollution emissions within a predetermined site; and the at least one pollution source identifier is configured to identify at least one pollution source that has entered the predetermined site. Optionally, the at least one pollution source identifier is configured to identify when the at least one pollution source leaves the predetermined site.

[0034] Monitoring pollution emissions in a predetermined site, and monitoring when pollution sources enter and/or leave the predetermined site allows pollution emissions in specific areas to be monitored, for example, pollution emissions within a building or construction site. This can ensure that any rule or regulations that provide a limit on pollution emissions generated by or within the predetermined site are complied with.

[0035] Optionally, the method further comprises the step of sensing pollution emissions with the one or more pollution emission sensors. Optionally, the method further comprises the step of identifying the at least one pollution source and its location with the at least one pollution source identifier. [0036] According to a second aspect of the invention, a system for associating pollution emissions with the pollution sources that produced the pollution emissions is provided. The system comprises: at least one pollution emission sensor configured to sense pollution emissions; at least one pollution source identifier for identifying at least one pollution source. The system is configured to perform the method of the first aspect of the invention.

[0037] Associating the pollution emissions emitted by a pollution emissions source with that pollution emissions source means that effective actions can be taken to address the level of pollution emissions. Furthermore, accountability can be increased as it can be accurately determined what party is responsible for producing the pollution emissions.

[0038] Optionally, the at least one pollution emission sensor comprises a plurality of pollution emission sensors. Optionally, the plurality of pollution emission sensors are distributed across at least two locations. Optionally, the at least two locations are within a predetermined site. Optionally, the plurality of pollution emission sensors include two or more types of pollution emission sensor, each type of pollution emission sensor configured to sense a different type of pollution emissions.

[0039] Using a plurality of pollution emissions sensors can provide a number of advantages. It can allow pollution emissions to be sensed in a number of different locations. This can help track the spatial distribution of the pollution emissions which can aid in correctly associating the sensed pollution emissions with the pollution emissions source that produced the pollution emissions. Additionally or alternatively, different types of pollution emissions can be sensed. For example, both noise pollution and light pollution could be measured and associated with a pollution source.

[0040] Optionally, the at least one pollution source identifier comprises at least one identification tag, configured to be affixed to and identify at least one pollution source; and at least one identification tag detector, configured to detect the at least one identification tag.

[0041] Using a system comprising an identification tag which is affixed to a pollution source and at least one detector for detecting the identification tag provides a flexible system which can be cheap and easy to implement and expand, for example, by providing more tags to new pollution sources. It also provides flexibility, as the tags are affixed to the pollution sources to identify them without requiring the pollution sources to have any particular pre existing characteristic or feature. [0042] Optionally, the at least one identification tag detector comprises a plurality of identification tag detectors. Optionally, the plurality of identification tag detectors are distributed across at least two locations.

[0043] Using a plurality of identification tag detectors allows pollution sources to be tracked around a (predetermined) site, providing more detailed information on their locations and aiding the attribution of emissions to the correct pollution sources.

[0044] Optionally, the at least one identification tag is a low energy Bluetooth tag, and wherein the at least one identification tag detector is a low energy Bluetooth tag detector.

[0045] Low energy Bluetooth can provide a high level of precision for location tracking pollution sources, whilst consuming relatively little power. It is also a flexible solution, allowing adaption to different size sites and numbers of pollution sources.

[0046] Optionally, each of the one or more pollution emission sensors is located within the same site as one of the one or more pollution source identifiers. Optionally, each of the one or more pollution emissions sensors is located within close proximity to the one of the one or more pollution source identifiers. Optionally, close proximity may mean within 5m, within 2m, within lm, within 0.5m, or within 0. lm.

[0047] Having the pollution sensors near to the identifier makes correlation easier.

[0048] According to a third aspect of the invention, a computer program is provided. When executed by a computer, the computer program causes a computer to perform the method of the first aspect of the invention.

[0049] According to a fourth aspect of the invention, a computer program is provided. When executed by the system of the second aspect of the invention, the computer program causes the system to perform the method of the first aspect of the invention.

[0050] According to a fifth aspect of the invention, a computer readable storage medium is provided. The computer readable storage medium has stored thereon the computer program of the third or fourth aspects of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The invention will be described with reference to the following figures. The same numerals will be used for the same feature throughout the figures where possible.

[0052] Figure l is a flow chart of a method according to an embodiment of the invention. [0053] Figure 2 is a flow chart of a method according to a further embodiment of the invention.

[0054] Figure 3 illustrates a system according to an embodiment of the invention.

[0055] Figure 4 illustrates an exemplary implementation of an embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

[0056] The present invention relates to methods and systems for monitoring pollution emissions and managing the pollution emission levels. Herein, the terms pollution and pollution emissions are used to refer to contaminants output into the environment as a result of human activity. They may or may not be directly harmful to human, animal or environmental health or wellbeing. They may be in the form of chemicals or energy. Examples of chemical pollutants include, but are not limited to, particulate matter, carbon dioxide, carbon monoxide and nitrogen oxides (NOx, including nitrogen oxide and nitrogen dioxide). Examples of energy pollution include noise pollution, heat pollution, vibrations and light pollution. Unless otherwise specified, the embodiments of the invention described below can be used with any form of pollution, or indeed with more than one type of pollution.

[0057] Figure 1 shows a flow chart of a method 100 according to an embodiment of the invention. The method 100 is a computer implemented method for associating pollution emissions with the pollution sources that produced the pollution emissions.

[0058] The method 100 begins at step 101. This step 101 comprises receiving pollution emissions data and determining at least one pollution emission level. The pollution emissions data is data sensed by at least one pollution emission sensor configured to sense pollution emissions. The pollution emissions data may be received from the at least one pollution emission sensor or from an intermediate source, such as a server configured to receive the pollution emissions data from pollution emission sensors.

[0059] At this step 101, pollution emissions data representing the pollution emission levels at or in the vicinity of a pollution emissions sensor is received by the computer implementing the method. The pollution emissions sensor may be remote from the computer implementing the method or may be integral to it.

[0060] The pollution emissions data may be received from a single pollution emissions sensor or from multiple pollution emissions sensors, and may be received in any format suitable for machine processing by a computer. The pollution emissions sensors may be operated by the same party that is performing the method described in Figure 1, or the pollution emission sensors may be operated by a third party, who send (e.g. broadcast or transmit) the sensed pollution emissions data to the party implementing the method of Figure 1

[0061] The particular format used is not limited by this disclosure. The pollution emissions data should include, however, a timestamp or other indication of the time at which the pollution emissions data was captured. This may be included as metadata in the pollution emissions data itself. Alternatively the computer implementing the method 100 could use the time at which the pollution emissions data is received as being representative of the time at which the pollution emissions data was captured. This may be done in particular when the pollution emissions sensor is configured to provide its output directly to the computer, or arranged such that the computer receives the pollution emissions data in essentially real-time. For example, the pollution emissions sensor may be configured to communicate with the computer such as by one or more networks and one or more communication protocols. The pollution emissions data may be received continuously, periodically or at some irregular or otherwise determined time interval.

[0062] Pollution emissions levels are determined from the pollution emissions data. The pollution emission level is indicative of the amount of the pollutant present in the environment, and, for example, allows a comparison with other data or with benchmarks, targets, and thresholds. The form will depend upon the pollutant measured. For example, for light pollution the pollution emission level that is determined may be a brightness value, for noise it may be a sound intensity level (e.g. measured in decibels), and for gasses or particulates it may be a concentration value.

[0063] The second step 103 comprises receiving an identification of at least one pollution source to identify at least one pollution source and its location. The identification is an identification that has been determined by at least one pollution source identifier. The identification data may be received from the at least one pollution source identifier or from an intermediate source, such as a server configured to receive the identifier from pollution source identifier. The pollution source identifiers may be operated by the same party that is performing the method described in Figure 1, or the pollution source identifiers may be operated by a third party, who send (e.g. broadcast or transmit) the identification of the at least one pollution source to the party implementing the method of Figure 1. [0064] At this step 103, one or more pollution sources are identified. For example, pollution sources could be vehicles or machinery. The identification step 103 may uniquely identify the pollution source, or may identify the pollution source as being part of a broader category, or some combination of the two. For example, the identification may identify that a vehicle is a specific individual vehicle, a vehicle of a particular type, or a vehicle belonging to a particular company. In some examples, only the specific identification may be desired, whilst in others only the general identification may be wanted, and yet in others a combination will be needed.

[0065] As well as identifying at least one pollution source, the location of the identified pollution sources is determined and the time at which the pollution sources were identified at that location recorded. It should be understood that, throughout this specification and unless otherwise stated, location can include any or all of the three dimensions of space. For example, it can encompass a position on the ground, such as a map coordinate, and may also (but not necessarily) include a height above that position on the ground.

[0066] Optionally, the location of the pollution source identifier that identifies the pollution source will be known, and this will provide sufficient location information for the method to be implemented. This may be the case, for instance, where the pollution source identifier is configured to identify pollution sources only in close proximity to the pollution source identifier or when the pollution source identifier is configured to identify pollution sources at a specific location, for example when the pollution source passes or moves through a specific area, such as an entrance or exit to a predetermined area or site. In other instances, the pollution source identifier may not be localised in this manner, and so the location of the pollution source is obtained through other means. For example, global navigation satellite system (GNSS) (e.g. Global Positioning System (GPS)) tracking could be used which could provide the location information of each pollution source of interest over a period of time, along with an identification of each pollution source. Alternatively, a real-time locating system (RTLS) may be used which employs the use of wireless tags (e.g. employing short range wireless communication such as Bluetooth, radio frequency (RF), infrared (IR), or ultrasound technologies) affixed to pollution sources which are located relative to fixed reference locations.

[0067] The present invention is not limited to the manner by which the identification is carried out, and a number of different technological implementations are contemplated. For example, as noted above, GNSS tracking of pollution sources may be employed. This could be implemented through attaching a GNSS tracking device to a pollution source which can determine the pollution source’s location and then transmit or broadcast this data to a receiver for use in the method. Alternatively, or in addition, a short range wireless network may be used. This could be in the form of Bluetooth (in particular Bluetooth Low Energy (BLE)) transmitters attached to pollution sources which are identified as they pass nearby to Bluetooth receivers to determine the location of the pollution source. The use of multiple receivers can be advantageous for triangulating the location of the pollution source to provide a more accurate location determination. Alternatively, or in addition, visual identification of pollution sources may be used, such as automatic number plate recognition (ANPR) on vehicles. This can identify vehicles that pass a particular location, providing information about their location when they do so. Machine learning (ML) and/or other artificial intelligence (AI) techniques could also be used to perform this identification in a manner known in the art.

[0068] As can be seen from the examples above, the pollution source identifier may be active, requiring the pollution sources to carry a transmitter or similar device, or passive in that it does not require pollution sources to have an active component (e.g. a component that must be powered). An example of an active system would be one requiring the pollution sources to carry Bluetooth tags which transmit signals picked up by receivers. An example of a passive system would be one utilising ANPR, which does not require the pollution sources to carry any active components.

[0069] The third step 105 of method 100 comprises associating the received pollution emissions data with the at least one pollution source that produced the pollution emissions. This is based upon the location of the at least one pollution emission sensor, the time the pollution emissions were sensed, the location of the at least one pollution source and the time at which the at least one pollution source was identified.

[0070] This step 105 involves making a link between the measured pollution - the pollution emissions data - and pollution sources. Through this step 105, the pollution emissions can be assigned to the pollution sources that emitted the pollution emissions.

[0071] In a simple example, wherein a pollution emission sensor and a pollution source identifier are located in the same position as one another, a vehicle can be identified as it drives past the pollution source identifier. The pollution measured by the pollution emissions sensor as the vehicle drives past (i.e. at the same time that the vehicle is identified by the pollution source identifier) is then associated with that vehicle. In other words, it is determined that the vehicle produced the pollution emissions that were measured as it drove past. It should be noted that it may not be that all of the pollution emissions measured as the vehicle drives past are associated with the vehicle, but rather the pollution emissions above a background level of pollution. That is, the additional pollution emissions measured over the background level are associated with the vehicle. This principle applies generally to all of the embodiments herein.

[0072] As can be seen in this example, the information that is used to make the association is the location of the pollution emission sensor and of the pollution source (which may be derived from the location of the pollution source identifier), as well as the times at which the pollution emissions were measured and at which the pollution source was identified. However, in practice, additional considerations will often give a more accurate link between the pollution emissions and their source, particularly if the pollution emissions sensor, the pollution source identifier and the pollution source are not all in close proximity when the measurements and identification take place; or when there are multiple pollution sources.

[0073] One factor which will often be important to take into consideration is the weather or more generally the atmospheric and environmental conditions, such as wind speed and direction, temperature, pressure, precipitation and so on. These considerations will often be useful for chemical pollutants, such as gaseous or particulate pollutants. For example, if pollution emissions are measured at a central location, a first pollution source is identified at a first location to one side of the central location and a second pollution source is identified at a second location at the opposite side of the central location, then information on wind direction can be used to determine which of the two pollution sources emitted the measured pollution emissions.

[0074] Another factor that can be taken into consideration is the type of pollution source identified. This can be particularly advantageous when multiple pollution sources are identified at similar times in similar locations. For example, if two types of pollution emissions are measured, and two types of pollution source are identified, the pollution emissions of each type may be associated with one of the pollution sources based on a known relationship between the pollution emissions produced by different pollution sources. This relationship may be obtained from a database. Advantageously, such a database can be created, or updated, based on associations made according to the method described herein, and optionally the method involves storing the associations between the received pollution emissions data and the identified pollution sources.

[0075] Step 107 of the method 100 illustrated in Figure 1 is the step of determining a mitigation action to reduce the pollution emission levels. The mitigation action is determined based upon the association between the pollution emissions data and the at least one pollution source.

[0076] The mitigation action is an action which will reduce the pollution emission levels at a location, such as a site, in the vicinity of the one or more pollution emission sensors. The mitigation action could be selected from a list of possible mitigation actions, with the selection being made based upon the association between the pollution emissions data and the pollution source. That is, this association indicates what it is that is causing the pollution emissions, and so an appropriate action can be determined that will reduce the pollution emissions. For example, optionally it may be determined that a particular vehicle which is idling is producing emissions, and so the determined mitigation action may be to turn off the engine of that vehicle. In another example, if two loud machines are operating at the same time causing large levels of noise pollution, the determined mitigation action may be to operate the machines individually, one at a time. It is noted that, as will be apparent from these examples, further information may also be used to determine the mitigation action. The particular further information that is used will depend upon the specific implementation and the purpose for which it is being used, but possible examples of further information that could be used include schedules and timetables of movement of pollution sources, the state (e.g. on, off, idling) of pollution sources, hierarchies of pollution sources (e.g. an order of importance, or preferred order for turning off etc.), and so on. This list is not exhaustive. The mitigation action may also comprise multiple parts, i.e. it may not be one single action but may comprise a plurality of sub-actions. For example, it may comprise both turning off a pollution source and adjusting a schedule.

[0077] As an example, the mitigation action may comprise one or more of: adjusting a state of the at least one pollution source, adjusting a schedule of pollution source activity, providing instructions to an operator of the at least one pollution source to inspect and/or change the operation of the at least one pollution source.

[0078] The instructions to an operator could be, for example, to inspect a particular pollution source and rectify the cause of its excess emissions; to inspect a particular location to identify which particular pollution source, amongst a number of co-located pollution sources, is the cause of increased pollution (for example, to determine the state of the pollution sources, which can then be input to determine an appropriate mitigation action to reduce the pollution levels); to inspect a particular location with a suggestion of the most likely pollution source, amongst a number of co-located pollution sources, being the cause of increased pollution and to take appropriately determined action; to reschedule the regular presence of multiple pollution sources to avoid future excessive pollution from pollution sources at particular times (e.g. at specific times of day, days of the week etc.); and to adjust operating processes, such as changing the utilisation of pollution sources (e.g. using more electric rather than diesel vehicles) to reduce future occurrences of excess emissions.

[0079] Optionally, the method 100 may conclude with the determined mitigation action being automatically implemented. For example, a schedule of when vehicles will arrive or when machines will be used could be automatically modified and updated, or a signal could be sent to cause a vehicle or machine to turn off or to instruct an operator to do so. Alternatively, the determined mitigation can be presented to a user or operator of a system implementing the method 100 or of a particular pollution source (or indeed to other relevant person) to inform them of the appropriate action to take.

[0080] Optionally, the method further comprises determining whether the pollution emission level exceeds a threshold level. This is advantageous as it is often the case that there are restrictions and limits placed that provide a maximum allowable level of pollution of a given type. Given that these are often legal limits, or limits imposed by an official authority (e.g. on a construction firm as part of planning permission), it is important to be able to determine when these levels are breached and additionally who is responsible for the breach such that appropriate action can be taken to reduce the pollution levels to acceptable levels and to prevent future breaches.

[0081] Figure 2 illustrates such a method 200 which includes the feature of determining whether the pollution emission level exceeds a threshold. It should be noted that the method of Figure 2 encompasses that of Figure 1, and that the discussion above in relation to Figure 1 is equally applicable to the method illustrated in Figure 2.

[0082] As with the method of Figure 1, the method 200 of Figure 2 comprises step 101 of receiving pollution emissions data and determining at least one pollution emission level, step 103 of receiving an identification of at least one pollution source to identify at least one pollution source and its location, and step 105 of associating the received pollution emissions data with the at least one pollution source that produced the pollution emissions. These steps are the same as those in Figure 1, and so are not discussed again in relation to Figure 2.

[0083] Additionally, the method 200 of Figure 2 comprises step 201 of determining whether the at least one pollution emission level exceeds a threshold. At this step 201, the level of pollution emissions determined from the pollution emissions data can be compared to a threshold level. The threshold level may not be a universal threshold, but may vary with time (e.g. a noise threshold may be higher during the day than at night), space (e.g. a noise threshold may be lower near residential buildings than near a factory), and may vary between different types of pollution (e.g. carbon dioxide may have a higher concentration threshold than nitrogen dioxide).

[0084] An example of thresholds that could be used is an average level of pollution emissions for a period of time, such as the average (e.g. mode, mean or other average) level measured over a day, week, etc. Additionally or alternatively, the threshold could be a certain factor of a reference level, for example 10% higher than the maximum value for the day before. The threshold could also be based upon other factors than just the pollution emissions level alone. For example, the number and/or types of pollution sources could also be taken into account - for the threshold to be breached both a certain level of pollution emissions could be required in addition to a certain number of pollution sources, or a certain category or mix of pollution sources.

[0085] As discussed above, the threshold level may be set by various entities, such as governments, NGOs, local authorities, and operators of a system according to the invention, for example. This aspect is not limited by the present disclosure.

[0086] Additionally or alternatively to the mitigation action being determined if the pollution emissions level exceeds a threshold level, the mitigation action could be determined if a certain type of pollution source is identified. For example, a mitigation action may be determined if a diesel vehicle is identified in a site that is reserved for electric vehicles. This may replace the determination of whether the pollution emission level exceeds a threshold level at step 201, or may be carried out in addition to it.

[0087] It is also noted that whilst step 201 is illustrated as coming after step 105 in Figure 2, it may in fact be performed in tandem with, or before, either one or both of steps 103 and 105. That is, provided that step 201 is performed after step 101, i.e. after the pollution emissions data has been received, then the ordering of step 201 with regards to step 103 and 105 is not limited by the method.

[0088] Returning to Figure 2, if, at step 201, the determined pollution emissions levels are not found to exceed (i.e. breach) a threshold level, then the method 200 ends at step 203. In practice, this may mean that no further action is taken at this time, until further pollution emissions data and pollution source identification(s) are received, in which case the method 200 may then begin again at step 101.

[0089] On the other hand, if, at step 201, the determined pollution emission levels are found to exceed the threshold level then at step 205 an alert is output. This alert informs a user that the pollution emission level exceeds a threshold level, and may be in the form of a warning. The alert may be output such that it warns a user or operator in real time, e.g. through a flashing light or pop-up on a screen, or the alert may be output into a log or in some other form that can be reviewed at a later time. The user to which the alert may be sent or presented may be an operator of a system implementing the method 200, a person responsible for setting and/or monitoring compliance with the threshold levels, an operator of a pollution source breaching the threshold and the like; to whom the alert is output is not limited in the present disclosure. The alert may also be output to multiple different people or devices in multiple forms. For example, the alert may be output as a pop-up on a screen belonging to the manager of a building site and it may also be output to an electronic log.

[0090] Additionally, as well as outputting an alert at step 205, a mitigation action is determined at step 207. It should be noted that this step 207 may be performed before, simultaneously with, or after step 205.

[0091] Step 207 is broadly the same as step 107 (and the discussion presented for step 107 above is equally applicable to step 207), except that in this example the mitigation action is specifically determined to reduce the pollution emission levels to or below the threshold level.

[0092] The effect that a mitigation action will have on the pollution emissions levels may be known from a database, and so the appropriate mitigation action can be chosen from a list of mitigation actions stored in the database based on this. The effect of a mitigation action may also, or alternatively, be based, at least in part, on a prediction or model, and this may involve the use of ML and/or other AI techniques. As discussed in relation to step 107 of Figure 1, the mitigation action may be determined based upon further information beyond the association of the pollution emissions with the pollution source, such as schedules and timetables of movement of pollution sources, the state (e.g. on, off, idling and so on) of pollution sources, hierarchies of pollution sources (e.g. an order of importance, or preferred order for turning off etc.), and so on. Similarly again, the mitigation action may also comprise multiple parts, i.e. it may not be one single action but may comprise a plurality of sub actions.

[0093] It should be noted that whilst in Figure 2 the mitigation action is only shown as being determined if the determined pollution emission levels exceed a threshold level, in other examples the mitigation action is always determined regardless of the outcome of the determination at step 201. Furthermore, as discussed in relation to Figure 1, in some embodiments the mitigation action may be automatically implemented. [0094] A system 300 will now be discussed in relation to Figure 3.

[0095] Figure 3 illustrates a system 300 for associating pollution emissions with the pollution sources that produced the pollution emissions having a number of pollution emission sensors 301 and pollution source identifiers 303. Also illustrated is a pollution source 305. Whilst three pollution emission sensors 301 and three pollution source identifiers 303 are shown in Figure 3, this is not limiting and any number of pollution emission sensors 301 and pollution source identifiers 303 may be included in the system, provided there is at least one of each. The number of pollution emission sensors 301 and pollution source identifiers 303 also does not need to be equal. For example, there may be more pollution emissions sensors 301 than pollution source identifiers 303 or there may be more pollution source identifiers 303 than pollution emission sensors 301. The numbers of each will be dependent upon the specific implementation of the system 300 used. Furthermore, whilst the pollution emission sensors 301 are shown as distinct from the pollution source identifiers 303, they may in fact be implemented in a single device. That is, the pollution emission sensors 301 and the pollution source identifiers 303 may be integral with one another.

[0096] The pollution emission sensors 301 are configured to sense pollution emissions. The particular details of the pollution emission sensors 301 will depend upon the individual use case of the system 300, for example the type of pollution that is to be sensed, the environment in which the pollution emission sensors 301 are to be placed, the desired level of accuracy and the cost of different types of pollution emission sensor 301. The placement of the pollution emission sensors 301 will also be dependent upon similar considerations. In some cases, it will be preferred for the pollution emission sensors 301 to be placed close to the pollution sources 305. For example, a NOx sensor may be placed nearby to a road or vehicle access point so that it will get a more accurate picture of the amount of pollutant emitted by vehicles that go past. On the other hand, a microphone may be placed away from a building site and nearby to residential buildings to give an indication of the amount of noise produced by the building site that is heard at the residential buildings.

[0097] Examples of types of pollution emission sensor 301 include microphones for sensing noise pollution, accelerometers for measuring vibration, and photoresistors or photodiodes for measuring light. The specific type of sensor used is not limited herein and may be any known sensor suitable for measuring the desired type of pollution emissions.

[0098] The pollution source identifiers 303 are for identifying pollution sources 305. The pollution source identifiers 303 may uniquely identify pollution sources 305, or may identify the pollution source 305 as being part of a broader category, or some combination of the two. For example, the pollution source 305 may be identified as a specific individual vehicle, a vehicle of a particular type, or a vehicle belonging to a particular company.

[0099] As well is identifying the pollution source 305, the pollution source identifiers 303 may determine the location of the pollution source 305, and record the time at which it was identified. However, it is not necessary that the pollution source identifier 303 determine the location of the pollution source 305 in all embodiments, as if the location of the pollution source identifier 303 is known then simply knowing that the pollution source 305 was identified by a particular pollution source identifier 303 may provide sufficient information about the location of the pollution source 305.

[0100] The pollution source identifiers 303 may be implemented in a number of different ways depending upon the desired use of the system. In particular, the pollution source identifiers 303, whilst shown as single units in Figure 3, may in fact each comprise separate parts which can work together to perform the required identification. In some instances, a part of the pollution source identifiers 303 may be attached to, or otherwise disposed on, the pollution sources 305. For example, GNSS tracking of the pollution sources 305 may be employed. In this case, the pollution source identifier 303 may comprise a GNSS tracking device attached to a pollution source 305 and a receiver. The GNSS tracking device can determine the pollution source’s location and then transmit or broadcast this data to the receiver. Alternatively, or in addition, a RTLS may be used employing a short range wireless network. This could be in the form of Bluetooth (in particular Bluetooth Low Energy (BLE)) transmitters (also known as tags) attached to pollution sources which are identified as they pass nearby to Bluetooth receivers to determine the location of the pollution source. Other technologies, however, can also be used, such as Bluetooth, RF, IR, or ultrasound technologies. Preferably, the tags in these embodiments are low cost, low power and also self-powered (i.e. it comprises its own power source).

[0101] The use of multiple receivers can be advantageous for triangulating the location of the pollution source to provide a more accurate location determination.

[0102] In other embodiments, the pollution source identifiers 303 may comprise a camera for visual identification of the pollution sources 305. For example, cameras may be used to perform automatic number plate recognition (ANPR) on vehicles. This can identify vehicles that pass a particular location, providing information about their location when they do so, since the location of the camera is known.

[0103] As can be seen from the examples above, the pollution source identifiers 303 may be active, requiring the pollution sources 305 to carry a transmitter or similar device, or passive in that it does not require pollution sources 305 to have an active component. An example of an active system would be one requiring the pollution sources 305 to carry Bluetooth tags which transmit signals picked up by receivers. An example of a passive system would be one utilising ANPR, which doesn’t require the pollution sources 305 to carry any active components.

[0104] Whilst Figure 3 illustrates a system 300 according to the invention at a very high level of generality, Figure 4 shows a scenario in which such a system 300 can be implemented. It is noted that a number of different types of pollution emission sensors 303 and pollution source identifiers are used in the example embodiment of Figure 4. This could be referred to as one system 300 having multiple different types of sensor, or as multiple individual systems.

[0105] Figure 4 illustrates a building site 401 having a perimeter and an entrance 403. Inside the building site 401, two machines 405a, 405b are illustrated. Each machine 405a, 405b may be tracked as it moves around the building site 401. This is done by providing each machine 405a, 405b with a transmitter 407. The transmitter 407 emits signals that are received by the receivers 409 disposed in the comers of the building site 401. The signals transmitted by the transmitter 407 of each machine 405a, 405b identify that machine, and the received signals are also used to determine the location of each machine 405a, 405b. This can be done using a Bluetooth system for example.

[0106] When being used, the machines 405a, 405b create a certain amount of noise. Often, nearby residents will find the noise of a building site such as building site 401 to be a nuisance. To ensure that the noise in residential area 421, located outside the perimeter of building site 401, does not become problematic, a microphone 419 is located near to the residential area 421. This microphone 419 will monitor the noise coming from the building site 401, and the system will determine which machines 405a, 405b are causing the noise. For example, changes to the noise level detected by the microphone 419 can be associated with changes in location of the machines 405a and 405b within the site 401. If the noise detected by the microphone 419 passes a threshold, the system will output a mitigation action such as indicating that one of the machines 405a, 405b that was found to be causing a portion of the noise should move away from the microphone or to be turned off.

[0107] As a further example, in front of the entrance 403 to the building site 401, a queue of vehicles 413a, 413b, 413c can be seen. Each vehicle 413a, 413b, 413c has an identification, such as a number plate, visible on a front of each vehicle 413a, 413b, 413c. A camera 411 is located by the entrance 403 to the building site 401 such that it can see the identification of each vehicle 413a, 413b, 413c and hence determine the position of each vehicle 413a, 413b, 413c.

[0108] Alongside the vehicles 413a, 413b, 413c are a number of sensors 415a, 415b, 415c configure to detect common exhaust fumes such as carbon dioxide and nitrogen oxides. These sensors 415a, 415b, 415c are disposed at intervals such that there will be approximately one sensors 415a, 415b, 415c next to each vehicle 413a, 413b, 413c in the queue, though in practice vehicles may not always queue in exactly the same places. The sensors 415a, 415b, 415c can monitor the air near the vehicles 413a, 413b, 413c to detect if the pollution levels of the pollutants that the sensors 415a, 415b, 415c are configured to detect are higher than the background level (i.e. a threshold level at or just above the background level). This information can be used to determine if one of the vehicles 413a, 413b, 413c in the queue is idling (i.e. has their engine on) whilst queueing. By using the location information from the camera 411 in combination with the pollution emissions data from the sensors 415a, 415b, 415c, if it is detected that a vehicle 413a, 413b, 413c is idling (i.e. a pollutant has breached the threshold level for that pollutant), it can be determined which vehicle 413a, 413b, 413c is the vehicle that does not have its engine off. In Figure 4, it can be seen that the middle vehicle 413b has its engine on and is producing emissions 417. Accordingly, a mitigation action can be determined, in this case an instruction that the vehicle 413b should have its engine turned off.

[0109] The methods and systems described herein are capable of wide application to many different situations and environments. For example, it is contemplated that such systems need not be confined to land-based implementations but may also include sea- or airborne sensors to monitor and manage pollution emissions due to shipping and aeroplanes, for example.

[0110] Furthermore, the method may be implemented on any suitable computer or computing system capable of carrying out the method and having the required programming thereon. This may be a single computer device having one or more processors, or a distributed computing system. In some instances, processing tasks may be performed by remotely and/or on cloud computing servers. It will be understood by the person skilled in the art that the present invention is not limited in this regard.

Claims

1. A computer implemented method for associating pollution emissions with the pollution sources that produced the pollution emissions, the method comprising: receiving pollution emissions data that has been sensed by at least one pollution emission sensor configured to sense pollution emissions, and determining at least one pollution emission level; receiving an identification of at least one pollution source, that has been determined by at least one pollution source identifier, to identify at least one pollution source and its location; associating the received pollution emissions data with the at least one pollution source that produced the pollution emissions based upon the location of the at least one pollution emission sensor, the time the pollution emissions were sensed, the location of the at least one pollution source, and the time at which the at least one pollution source was identified; and determining a mitigation action to reduce the at least one pollution emission level based upon the association between the pollution emissions data and the at least one pollution source.

2. The method of claim 1, wherein the method further comprises the step of determining whether the at least one pollution emission level exceeds a threshold level.

3. The method of claim 2, wherein the method further comprises the step of outputting an alert when it is determined that the at least one pollution emission level exceeds the threshold level.

4. The method of claim 2 or 3, wherein the mitigation action is determined if the at least one pollution emission level exceeds the threshold level, and/or optionally wherein the mitigation action is determined to reduce the at least one pollution emission level to or below the threshold level.

5. The method of any preceding claim, wherein the mitigation action is selected from a predetermined list of possible mitigation actions, and/or optionally wherein the mitigation action comprises one or more of: adjusting a state of the at least one pollution source, adjusting a schedule of pollution source activity, providing instructions to an operator of the at least one pollution source to inspect and/or change the operation of the at least one pollution source.

6. The method of any preceding claim, wherein the method further comprises automatically implementing the mitigation action.

7. The method of any preceding claims, wherein the method further comprises receiving one or more environmental characteristics; and wherein the associating the received pollution emissions data with the at least one pollution source that produced the pollution emissions is further based upon the one or more environmental characteristics.

8. The method of claim 7, wherein the one or more environmental characteristics are received from one or more sensors configured to measure each of the one or more environmental characteristics.

9. The method of claim 7 or 8, wherein the one or more environmental characteristics include one or more of: wind speed, wind direction, humidity, ambient temperature, light intensity, and precipitation.

10. The method of any preceding claim, wherein the method further comprises the step of storing the association between the sensed pollution emissions and the at least one pollution source that produced the pollution emissions in a database.

11. The method of any preceding claim, wherein the step of receiving pollution emissions data that has been sensed by at least one pollution emission sensor configured to sense pollution emissions comprises receiving pollution emissions data that has been sensed by a plurality of pollution emission sensors.

12. The method of any preceding claim, wherein the step of receiving an identification of at least one pollution source, that has been determined by at least one pollution source identifier, to identify at least one pollution source and its location comprises receiving an identification of a plurality of pollution sources, that have been determined by at least one pollution source identifier, to identify the plurality of pollution sources and their respective locations.

13. The method of any preceding claim, wherein the pollution emissions are one or more of: particulates, noise, light, nitrogen oxides, carbon monoxide, carbon dioxide, and vibration.

14. The method of any preceding claim applied to non-static pollution sources.

15. The method of any preceding claim wherein: the at least one pollution emission sensor is configured to sense pollution emissions within a predetermined site; and the at least one pollution source identifier is configured to identify at least one pollution source that has entered the predetermined site.

16. The method of any preceding claim, wherein the method further comprises the steps of: sensing pollution emissions with the one or more pollution emission sensors; and identifying the at least one pollution source and its location with the at least one pollution source identifier.

17. A system for associating pollution emissions with the pollution sources that produced the pollution emissions, the system comprising: at least one pollution emission sensor configured to sense pollution emissions; at least one pollution source identifier for identifying at least one pollution source; wherein the system is configured to perform the method of claim 16.

18. The system of claim 17, wherein the at least one pollution emission sensor comprises a plurality of pollution emission sensors, wherein optionally the plurality of pollution emission sensors are distributed across at least two locations.

19. The system of any preceding claim, wherein the at least one pollution source identifier comprises: at least one identification tag, configured to be affixed to and identify at least one pollution source; and at least one identification tag detector, configured to detect the at least one identification tag.

20. The system of claim 19, wherein the at least one identification tag detector comprises a plurality of identification tag detectors, wherein optionally the plurality of identification tag detectors are distributed across at least two locations.

21. The system of any of claims 17 to 20, wherein the at least one identification tag is a low energy Bluetooth tag, and wherein the at least one identification tag detector is a low energy Bluetooth tag detector.

22. The system of any of claims 17 to 21, wherein each of the one or more pollution emission sensors is located within the same site as the one or more pollution source identifiers.

23. A computer program that, when executed by a computer, causes the computer to perform the method of any of claims 1 to 16.

24. A computer program that, when executed by the system of claim 17, causes the system to perform the method of claim 16.

25. A computer readable storage medium having stored thereon the computer program of claim 24 or 25.