Category: Smart cities
The UK’s first Urban Observatory, led by Newcastle University, has been designed to provide a digital view of how cities work. AQMesh air quality monitoring equipment is being deployed across Newcastle and Gateshead in conjunction with other instruments for monitoring parameters such as air and water quality, noise, weather, energy use, traffic and even tweets.
Forming part of a network of over 600 sensors, the Urban Observatory has already collected over half a billion data points and the information is now starting to shed light on the way different systems interact across the city and provide a baseline against which future cities can be developed and managed.
To date Air Monitors, UK AQMesh distributor, has supplied 55 AQMesh pods and 6 conventional air quality monitoring stations. The conventional stations employ standard reference method instruments to measure key air quality parameters such as Nitrogen Dioxide, Ozone, Carbon Monoxide and Particulates. The AQMesh pods monitor similar parameters, but are smaller, solar-powered, wireless, web-enabled devices that can be quickly and easily located in almost any location.
Commenting on Air Monitors’ involvement in the Urban Observatory project, Managing Director Jim Mills says: “The conventional stations are delivering precise, accurate data, and the AQMesh pods are providing the portability and flexibility to monitor air quality accurately and reliably in the locations of greatest interest.”
“Perhaps the most interesting aspect of this project is its ability to engage with the community, providing detailed local air quality data so that both authorities and citizens can make informed decisions on how to reduce exposure to air pollution. Looking forward, it is clear that work in Newcastle will serve as a model for other cities around the world to follow.”
The National Observatories facility was established in 2017 with the Newcastle Urban Observatory as the founding member, supported by £8.5 million investment from EPSRC (Engineering and Physical Sciences Research Council). The guiding principles are to be technology agnostic and vendor non-exclusive, open by default and transparent by design whilst developing a valued, long-term, sustainable platform. In order for the data to be useful to better understand cities and to facilitate evidence based decision-making across a range of scales and sectors, the data needs to be robust and reliable with known data quality that can be validated.
The AQMesh pods are also being used as part of the ‘Sense My Street’ tool box which enables local communities to deploy sensors and locate them on the streets, collecting evidence to inform or even change their communities.
Phil James, who co-leads the Urban Observatory research, explains: “Cities are complex environments and if we want to develop them sustainably we have to understand how everything interacts.
“By compiling observations and comparing the data, for the first time we are now able to make more informed decisions about designing our cities to work better for people and the environment. Through the Sense my Street project, we are able to give communities the power to gather data relevant to issues that are important to them at a very local scale.”
All of the data is freely available at Newcastle University’s website: www.urbanobservatory.ac.uk, and is being used by researchers, local authorities, regulators, developers, town planners, businesses and members of the public.
AQMesh has been measuring ozone (O3) using small sensors since 2011 and the readings from the latest generation electrochemical sensor, using AQMesh v4.2.3 processing, as compared to co-located certified reference readings, consistently show an R2 of over 0.9 with an accuracy ±10ppb (20µg/m3).
AQMesh pods have been measuring ozone levels around the world and co-location comparison studies show very good performance against reference equipment from the latest sensor and processing version. Ozone levels have been particularly high across Western Europe over this summer but are a regular concern in many parts of the world, including the USA. However, there are huge gaps between O3 monitoring points, to different degrees across the world, depending on monitoring equipment budgets. A lower cost small-sensor monitoring solution can provide valuable data within the areas currently lacking in this air quality information. Data validity is typically demonstrated by comparison with a local reference station, although AQMesh is also widely used where no reference data is available.
O3 at ground level is formed by reactions with nitrogen oxides (NOx) and volatile organic compounds (VOCs) from traffic and industrial emissions in the presence of sunlight. As such, hotter, sunnier weather can dramatically increase O3 pollution.
The World Health Organisation (WHO) currently states the daily limit of O3 levels to be 100μg/m3 over an 8-hour mean and advise that prolonged exposure to high levels of O3 can have severe effects on human health, including causing asthma, inflammation of the airways, reduced lung functionality and lung disease. Measuring O3 as a part of an air quality monitoring routine is therefore becoming increasingly important, especially in hotter climates and areas of increased VOC emissions.
O3 can be complicated to measure due to its high sensitivity to environmental conditions and cross-gas effects. Most small sensors for measuring O3 are either electrochemical or metal oxide, but electrochemical sensors (such as those used in AQMesh) have the advantage of low power requirements and can therefore be installed more flexibly. AQMesh pods are compact, wireless units and are available with a variety of power options, including solar panels, which allow them to be installed exactly where monitoring needs to take place.
During summer 2018 AQMesh has been measuring ozone at hundreds of locations across five continents and co-location comparisons show consistently high levels of accuracy. To quote two of many such studies, in an industrial region of the USA, AQMesh O3 measurements compared to FEM gave an R2 of 0.97, and in a similar comparison study in Western Europe the R2 value for O3 was 0.95. AQMesh pods measuring gases can run continuously for over two years using a battery but other power options are available, including solar. Particulate matter (TPC, PM1, PM2.5, PM10) can also monitored with an AQMesh pod, alongside gases including NO, NO2, O3, CO, SO2, CO2 and H2S, as well as pod temperature, RH% and pressure.
The accuracy of AQMesh readings has been proven through an extensive series of global co-location comparison trials and is the proven, commercially available low-cost air quality monitoring system for both pollutant gases and particulate matter, as well as simultaneously monitoring a range of environmental conditions.
London Mayor Sadiq Khan has launched a new, street-by-street monitoring system that will help to improve that capital’s air quality. From July 2018, and operating for a year, London will benefit from what is being described as the world’s most sophisticated air quality monitoring system. A consortium involving academia, an environmental charity, and commercial partners will install a network of 100 multiparameter AQMesh air quality monitors, whilst also operating two Google Street View cars that will map air pollution at an unprecedented level of detail.
Air Monitors Ltd will supply the AQMesh pods and manage data from all the sensor systems, so that air quality can be visualised and mapped in almost real-time. Working closely with the Greater London Authority, the project will be run by a team of air quality experts led by the charity Environmental Defense Fund Europe, in partnership with Air Monitors Ltd., Google Earth Outreach, Cambridge Environmental Research Consultants, University of Cambridge, National Physical Laboratory, King’s College London and the Environmental Defense Fund team in the United States.
Air Monitors Managing Director Jim Mills says: “It is difficult to underestimate the importance of this project – traditional monitoring networks provide essential information to check compliance against air quality standards, but this network will be ‘hyperlocal’ by which we mean that it will deliver street-level air quality data, which will be of tremendous interest to the public and also enable the effective assessment of air quality interventions.
“The Google Street View cars will take readings every 30 meters, helping us to find pollution hot-spots, so that AQMesh pods can be positioned in these locations. However, the pods are wireless and independently powered, so they can also be quickly and easily fixed to lamp posts in other sensitive locations such as schools.”
In addition to nitrogen dioxide and particulates, which are the pollutants of greatest concern, the pods will also measure ozone, nitric oxide, carbon dioxide, temperature, humidity and pressure. Data will sent, near real-time, to Air Monitors’ cloud-based data management system, which can be accessed by PC, tablet or smartphone by authorised partners, using an assigned login.
The monitoring data will provide baseline air quality data that will be essential in the assessment of mitigation measures, particularly in London’s expanding ultra-low emission zone. For example, on 20th June 2018, Sadiq Khan, announced the creation of the largest double-decker electric bus fleet in Europe, and the new monitoring network will enable the assessment of this initiative’s impact on air quality.
“This project will provide a step change in data collection and analysis that will enable London to evaluate the impact of both air quality and climate change policies and develop responsive interventions,” said Executive Director for Environmental Defense Fund Europe, Baroness Bryony Worthington. “A clear output of the project will be a revolutionary air monitoring model and intervention approach that can be replicated cost-effectively across other UK cities and globally, with a focus on C40 cities.”
Mark Watts, C40, Executive Director said: “Almost every major city in the world is dealing with the threat of toxic air pollution, which is taking an incredible toll on the health of citizens, public finances, quality of life and contributing to climate change. London is already a world leader in responding to this global threat and with this initiative it will set a new global standard for how street level air quality monitoring can inform strategic policy making. Cities across the C40 network and around the world will be watching closely to understand how this monitoring can deliver cleaner air for their citizens.”
About Environmental Defense Fund
Environmental Defense Fund Europe is a registered charity (1164661) in England and Wales. A recently established affiliate of leading international non-profit Environmental Defense Fund (EDF), the organisation links science, economics, law, and innovative private-sector partnerships to create transformational solutions to the most serious environmental problems. Connect with us at edf.org/europe, on Twitter and on our EDF Voices, EDF+Business and Energy Exchange blogs.
About Air Monitors Limited
Air Monitors is the UK’s leading air quality monitoring company, supplying and supporting instrumentation to central government, local authorities, research and industry. Air Monitors supplies and supports AQMesh in the UK and will also provide and maintain the equipment within the Google Street View cars in the project.
AQMesh is a fully developed and independently evaluated small sensor outdoor air quality monitoring system, manufactured in the UK by Environmental Instruments Ltd. and in use worldwide since 2012.
About Cambridge Environmental Research Consultants
Cambridge Environmental Research Consultants (CERC) are world leading developers of air quality modelling software. Their renowned ADMS-Urban model will be used together with the sensor data to generate hyper-local air quality mapping both for nowcasts and forecasts, and for policy studies.
About Google Earth Outreach
Google Earth Outreach is a program from Google designed specifically to help non-profit and public benefit organisations around the world leverage the power of Google Maps and Cloud technology to help address the world’s most pressing social and environmental problems.
About the National Physical Laboratory (NPL)
NPL is the UK’s National Measurement Institute, providing the measurement capability that underpins the UK’s prosperity and quality of life. Every day our science, engineering and technology makes a difference to some of the biggest national and international challenges, including addressing air quality issues. http://www.npl.co.uk/about/what-is-npl/
About University of Cambridge Department of Chemistry
The University of Cambridge Department of Chemistry is a world leading research and teaching institution. At Cambridge, the Centre for Atmospheric Science has played a primary role in the development of low-cost sensors for air quality monitoring and in the development of techniques for analysing and interpreting measurements from sensor networks.
About the C40 Cities Climate Leadership Group
Around the world, C40 Cities connects 96 of the world’s greatest cities to take bold climate action, leading the way towards a healthier and more sustainable future. Representing 700+ million citizens and one quarter of the global economy, mayors of the C40 cities are committed to delivering on the most ambitious goals of the Paris Agreement at the local level, as well as to cleaning the air we breathe. The current chair of C40 is Mayor of Paris Anne Hidalgo; and three-term Mayor of New York City Michael R. Bloomberg serves as President of the Board. C40’s work is made possible by our three strategic funders: Bloomberg Philanthropies, Children’s Investment Fund Foundation (CIFF), and Realdania.
Minnesota Pollution Control Agency (MPCA) has purchased fifty AQMesh pods to measure key air pollution gases and particulate matter across fifty different zip code areas. These small sensor air quality monitoring systems measure NO, NO2, O3, CO, SO2, PM1, PM2.5, PM10, temperature, pressure and relative humidity and will be installed – one per zip code – around the twin cities of Minneapolis and Saint Paul. The two-year project, funded by a legislative grant*, is to supplement the air quality information available to the public.
Deployment across the 50 zip codes has been mapped out after several public meetings involving the local community to determine where residents felt monitoring was needed. The small yellow triangles represent the points which local residents asked for sensors to be installed, and the green dots indicate the planned installation site based on the infrastructure available for mounting the AQMesh pods.
“This project is about understanding small-scale differences in air pollution in urban areas in order to minimise exposure to harmful air pollutants, particularly for vulnerable communities. The Assessing Urban Air Quality project will use new air monitoring sensors to broaden our knowledge about air quality in Minneapolis and St. Paul”, commented Monika Vadali, Ph.D, who is leading the project.
The pods are currently installed at the Blaine airport Federal Equivalent Method (FEM) station so that AQMesh readings can be compared to and validated against air quality readings taken using this US approved methodology, with scaling then applied if necessary. The MPCA team intends to install the pods in each zip code during the next month or two. The pods will be powered using a bespoke solar power pack: 30W panels have been specified for such a northern location, compared to the 15W normally required to supply the low-power AQMesh platform. The pods can be battery powered but 12V DC supply was specified, given the 2-year project timescale.
The pods were installed in November 2017 and have achieved 100% uptime to date, including during severe weather conditions, with temperatures below -25°C / -15°F and heavy snow. Initial comparisons against co-located pods show a high level of pod-to-pod precision, with an average R2 of 0.94 for NO2, 0.92 for O3 and 0.93 for PM2.5.
The 50 pods have been compared to the FEM station in two batches of 25, and the first batch of comparisons show an average co-location comparison correlation R2 of 0.74 for O3 and NO2, 0.86 for PM2.5, 0.93 for PM10 and 0.82 for NO. The reference CO showed a baseline shift part way through the comparison period, so that comparison is being reviewed. The SO2 R2 was depressed by a max FEM reading of 2.5ppb, with low FEM resolution, but AQMesh readings were within +/- 2ppb of reference.
The MPCA team is setting up an API connection to the AQMesh server, allowing air quality data to be streamed, near real-time, to the MPCA server, from which it can be published.
AQMesh is in use at various locations in the USA, as well as 35 other countries. The pods deployed in Minnesota are the current production version (v4.2.3).
More information about the MPCA project is available at https://www.pca.state.mn.us/air/assessing-urban-air-quality-project.
* The project is funded by a legislative grant: Environment and Natural Resources Trust Fund (ENRTF) M.L. 2017, Chp.96, Sec. 2. Subd.07b
The team at AQMesh continue to receive many enquiries from smart city initiatives and are concerned that integrators risk undermining entire projects by distributing meaningless or misleading air quality information.
“Many of the people I speak to are used to dealing with sensors that are easy to ‘plug and play’ and expect to be able to do the same with air quality sensors. This is not helped by the fact that most air quality sensors, sensor systems or ‘nodes’, on the face of it, offer very similar specifications”, comments Amanda Billingsley, AQMesh Director. “Quite understandably, IoT professionals do not generally have a background in air quality measurement and are not aware how notoriously difficult it is to get good air quality readings from small sensors, particularly nitrogen dioxide which is known to be so harmful and a key component of diesel fumes – now classified by WHO as a carcinogen.”
Most of the air quality sensors that are small, cheap and low enough energy for IoT applications also have limitations, such as the influence of rapidly changing temperature and cross-gas effects, and a significant level of experience is required to apply the corrections needed to get useable real-time air quality data. At this stage there are two options: one is to try to deal with the challenge in the measurement hardware, such as managing the conditions in which the sensors operate, but this often leads to large and expensive hardware. The other option is smart cloud-based correction algorithms.
Because of the length of time it has been in the field and the huge variation in environments in which AQMesh has been used and validated / corrected, AQMesh is acknowledged through independent studies to be further down this route than any other small sensor system. Even smart city projects which aim to deliver ‘high level’ air quality information, such as ‘the air quality is better here than there’ or some traffic light system, need to be confident that such conclusions are correct if they are not to be challenged by local authorities and stakeholders.
AQMesh is being used in various smart city and IoT projects around the world. In a collaborative smart city project in Cambridge, UK, AQMesh data was analysed by Professor Rod Jones from the University of Cambridge. “Because we know that all the pods read the same and because we have a comparison between one pod and a reference instrument we can say that all pods are working equivalently across the city. What we are seeing is correspondences in excess of 0.7, 0.8, against reference – and that is very good for straight out of the box”, commented Professor Jones.” The study shows that AQMesh can help cities manage air quality, for example by distinguishing between locally and regionally generated pollution, as well as publishing air quality information for the public.
AQMesh measures NO, NO2, O3, NOx, CO, SO2, PM1, PM2.5, PM10, temperature, pressure and relative humidity in a small pod which can be mounted in a post, on a wall, outdoor or indoor. Batteries, solar power or 12V DC power options give flexibility of mounting to capture air quality data from any point in a smart city or elsewhere.
At the IAPSC in May 2017, Professor Rod Jones of the University of Cambridge presented his case study on large scale deployment of sensors, which included showing how AQMesh can be used to discriminate between local sources of pollution and regional sources of pollution.
The study also found how modelling captures the magnitude of an event, but not the timing, and concluded that AQMesh captures spatial gradients very well.
Smart city projects pursue the vision of instrumenting a city with a large number of measurement ‘nodes’ and distributing this information to a range of stakeholders. But at that point different priorities emerge: IT teams are attracted by how readily data can be integrated and communicated whilst air quality professionals focus on how meaningful the air quality readings are.
Air quality readings from traditional air quality monitoring instruments – those which offer the most accurate readings – are generally accessed by direct download from the hardware or by hard-wired data infrastructure. A new generation of cloud-based air quality monitoring devices offers cheaper, smaller, more flexibly located measurement nodes, with all the benefits of cloud data management and integration. Leading air quality small sensor system, AQMesh, offers smart city partners an API data stream, which allows straightforward integration of real-time pollution gas and particle measurements into the smart city platform, and many low cost sensor systems offer something similar.
This is all very appealing and appears to bring air quality measurements into line with the array of city-wide measurements that the Internet of Things is expected to offer to a smart city. However, what if the air quality readings communicated to the public and other stakeholders are misleading, suggesting that air is clear when it is not, or suggesting that the city has a pollution problem that it does not? Either of these scenarios undermine the core case for smart city integration of air quality information. Read more…
Air quality professionals quite rightly demand evidence of accuracy from any new source of air quality readings. The most practical measure of accuracy is to compare a small sensor system which is co-located with – so measuring the same air sample as – a validated air quality station using reference method equipment. Laboratory test results are sometimes offered but small sensors may perform well in lab tests which use single, dry gases, but not in real-world monitoring where gases and particles are mixed and subjected to rapidly changing environmental conditions, such as temperature and humidity. The AQMesh study in Cambridge demonstrates the legitimacy of some small sensor air quality data.
AQMesh uses cloud-based correction for these influences to offer the best accuracy currently demonstrated by micro-sensing units. Teams of leading air quality experts are working worldwide with AQMesh and years of challenge and shared experience in a range of climates and conditions has allowed data processing to be refined to give reliable readings. This accuracy is combined with a robust platform and smooth data integration package to give the lowest possible risk and fastest solution for smart cities.
Smart city projects increasingly seek to include air quality measurements. If city authorities and the public are being asked to act based on air quality readings they must be credible. Whilst cheap sensors may offer easily integrated readings, they offer poor value for money if the information they produce cannot be trusted by the public, smart city project managers and stakeholders.
The search is on for low cost air quality sensors which can be easily integrated into the chosen IT platform. Many commercially available sensors for key air pollutants such as NO2 and PM2.5 are working at their limits and, although these may seem “low cost”, often disappoint if adequate correction is not applied. Even sensors that are sensitive enough in a laboratory may struggle to distinguish a signal from the target gas or particulate matter from noise due to platform electronics, environmental conditions or interfering gases. Failure to adequately manage or compensate for these effects can mean that inaccurate readings from monitoring nodes are published.
Unfortunately individual air quality sensors used in isolation are not able to accurately measure air pollutants at the parts per billion levels required by current air quality legislation. A smart sensor system is currently the only way to overcome these issues and obtain data with any real value.
AQMesh is a sensor system which measures NO, NO2, O3, CO, SO2, PM1, PM2.5, PM10, TPC, noise, temperature, humidity and pressure in a single, compact unit with independent power and communication. Years of development have fine-tuned the performance of processing algorithms to give proven precision and accuracy. Multiple examples can be seen at https://www.aqmesh.com/performance/co-location-comparison-trials/, as well as a real-time feed comparing live AQMesh pod readings against those from a co-located reference station. The system has the added benefits that it is very quick and easy to install, is robust, can operate in environmental conditions from -20°C to +40° and has various data integration options.
Indoor air quality can also be controlled by smart buildings. In many cases HVAC systems bring in ‘fresh’ air to address CO2 build-up, but in cities that air is likely to be polluted – from NO2 and possibly from particulates. A smart system can control where air is drawn in and ventilation rates, depending on air quality at the various inlets, allowing optimisation of the internal CO2, temperature and humidity whilst minimising external pollutants brought into the indoor space. AQMesh pods can be readily installed at various heights outside and inside buildings, all feeding near-live data to a central control system. Read more…
Early versions of AQMesh were used across eight cities in a European funded Citi-Sense project ending in 2016, and performance has improved significantly since then, to the results seen in a recent Cambridge smart city pilot study (see https://www.aqmesh.com/cambridge/). AQMesh is now being widely used by national, regional and local government authorities across Europe to supplement their much more expensive reference monitoring locations and is providing valuable information to inform smart city and smart building strategies leading to better air quality for all.
At the RSC AAMG event on ‘Air Quality Monitoring: Evolving Issues and New Technologies’ Professor Rod Jones of the University of Cambridge presented a paper showing very encouraging results. “Because we know that all the pods read the same and because we have a comparison between one pod and a reference instrument we can say that all pods are working equivalently across the city. What we are seeing is correspondences in excess of 0.7, 0.8, against reference and that is very good for straight out of the box”, commented Professor Jones.
These findings are from a project in Cambridge where 20 pods, initially co-located at the AQMesh UK factory, were placed at key points around Cambridge. The objective was to demonstrate what could be shown about ambient air quality at key points in the city, using a larger number of measurement nodes to understand how air quality varies across the city, particularly in relation to key transport corridors and areas of construction activity.
The 20 AQMesh pods measure gases (NO, NO2, O3, CO and SO2, particulate matter (PM1, PM2.5 and PM10) and environmental conditions (atmospheric pressure, relative humidity and pod temperature). 19 of the pods are powered by lithium battery and have been gathering data at 15 minute reading averages since June 2016, without any need to visit the sites to change batteries or carry out maintenance. The twentieth pod is currently running at one minute reading intervals, mounted at a Cambridge City Centre reference station, using a high capacity lithium battery. Each pod is small enough to be easily mounted to a post, wall or enclosure and all pods have been functioning without fault throughout the project.
As part of the project, data has also been pushed directly from the AQMesh server to a University of Cambridge server where it is automatically displayed in near real time. A further aspect of this initial project is to compare collected AQMesh data with ADMS-Urban modelled data for the same area and then use the real-time AQMesh data to improve the airTEXT air quality forecasts for Cambridge.
The next steps are to calibrate the pods and to analyse the data in more detail. Co-locating one of the pods with the reference station has allowed slope and offset values to be calculated, as all pods had already been co-located, allowing the same scaling to be applied to all pods. These values can then be applied to the AQMesh server, improving the accuracy of all data gathered after that point. Initial analysis using wind rose plots has shown the extent to which pollution can be attributed to local road traffic at each point. Further analysis of data will show how pollution varies across the locations and by time of day or week.
It is generally accepted that whilst measurements from air quality reference stations are highly accurate, they are not sufficiently location-specific. Key pollutants – such as NO2 and PM2.5 – vary dramatically over short distances and time intervals, but the large size, maintenance requirements and relatively high cost of reference equipment limits the places it can be installed. Diffusion tubes can offer a very cheap alternative and are much easier to install in specific locations, however they only offer a single reading over a number of weeks, and air quality professionals therefore rely on modelling techniques to fill the gaps. With research continuing to prove the extent to which air pollution varies significantly over space and time, the answer would be a reliable and accurate tool for taking real-time, localised measurements.
A number of new low-cost air quality monitoring systems are available, each with benefits and shortcomings. It is fair to say that the available sensors, whether electrochemical, optical or metal oxide, are all working at or close to their limit of detection to provide the low ppb or µg/m3 level of sensitivity required for any of the common ambient air quality applications. However, several systems offered for these applications provide readings in ppm or even % level readings – which clearly makes them inappropriate for ambient air monitoring. Some are also not fit for long-term outdoor use, as they are not fully weather proof or cannot cope with the expected temperature ranges. However, at least one system – AQMesh – does operate across a wide range of conditions and territories, so having established that a viable product exists, can it deliver the accuracy required?
Performance is clearly a major consideration for any user and comparing readings from a lower cost system against a reference station is the obvious place to start. One immediate challenge is ensuring meaningful results. Particularly in roadside applications or where there is an immediate source of pollution, all sensors and intakes must be within a metre of each other and at an equal distance from the immediate source. Most sensors, not unreasonably, also require an uninterrupted air flow around them – mounting immediately above hot or wet surfaces will not give accurate readings. On the other hand, some limitations of reference equipment come to the fore when comparing with a different type of measurement. For example, single channel NOx analysers switch between measuring NO and NOx, calculating NO2 as the difference. This switching can have dramatic effects on readings for the two gases (which are measured separately and directly by other sensors) at short reading intervals, such as 1 minute. Similarly, any differences in clock synchronisation or reading averaging protocol (time beginning or time ending) can make the difference between a regression comparison R2 of 0.9 and 0.1, which can render comparisons meaningless.
Comparisons of particulate measurements are also problematic due to the range of reference-equivalent methods available and the limitations, in many ways, of the reference method itself. Since the expanded uncertainty of the reference equivalent measurements for PM10 and PM2.5 allows up to 25%, this should be borne in mind when making comparisons with lower cost particulate sensors. Overall, for both gases and particulate matter, if several identical low cost systems are co-located, the user should expect a high level of repeatability (R2 > 0.9) and should expect to be able to adjust accuracy by ‘calibrating’ – adjusting slope and offset – against a co-located reference/equivalent station. Some systems, such as AQMesh, then allow this scaling adjustment to be applied automatically to all future readings, minimising the need for manual data correction. Access to a calibrated reference station and careful co-location is currently key to getting value out of any of the current generation of emerging sensor systems, although the objective of good accuracy without the need for a reference station is being actively pursued.
First questions about these systems often include ‘How do I run gas through it to calibrate it?’ and ‘Can I calibrate (or test) it in the laboratory?’ In systems such as AQMesh the air sample is not pumped, for good power-saving reasons (low power is essential for battery operation), and so it is not obvious how a conventional gas calibration would work. More importantly, although the sensors generally do give very good results in laboratory tests with known dry, single gases, these bear no relation to real ambient field measurements with a combination of damp, humid gases at potentially varying temperature and pressure. Overall, there is no proven substitute for co-location with a reference station. Even with all of these considerations, some of these small, lower cost air quality systems, such as AQMesh, can deliver very impressive comparison results and provide a new source of air quality data. Those with in-built power and communications offer genuine freedom to gather measurements from any location and research teams worldwide are using such systems to understand pollution around cities, inside and outside buildings, at different heights, in street canyons, around industrial facilities and within neighbourhoods, at different times of day, and so on. This new granularity of measurement and flexibility of location gives air quality management teams a real tool to carry out ‘before and after’ studies and evaluate a range of policy or pollution mitigation activities. Where a number of sensor systems are used, and particularly in combination with wind speed and direction information, the relative measurements and source distribution can provide very powerful insights about where to target pollution mitigation activity.
One such low cost outdoor air quality monitoring system offering this type of flexibility is AQMesh, which has proven its repeatability, accuracy and performance through a series of these careful co-location comparisons with calibrated reference stations in a variety of global locations and applications. The small size, battery power and wireless communications technology mean users can benefit from reliable and accurate real-time, localised air quality measurements in a broad range of studies.
How accurate is ‘accurate’?
One area of discussion is what level of accuracy is ‘good enough’. Although this depends on the application, it is still tempting to look for a very high level of agreement between the low cost sensor system and reference equipment. Whilst this may be the goal, the lower cost systems are considerably cheaper and have the benefit of being correctly located so perhaps it is better to have slightly less accurate readings from the right location than highly accurate readings from the wrong location? For some applications it is really only the relative readings which are required, and systems like AQMesh provide very high levels of precision between identical systems. Or it may only be appropriate to provide a ‘traffic light’ indication for communicating air quality to the public. Until more general guidance is available, users will have to take a view on accuracy relevant to their application.
Publishing air quality data
Another area of confusion is regarding data privacy vs online publication of air quality data. Most of the new air quality systems take advantage of remote data management and online access. This makes sense for a number of reasons. Hard-wired communications infrastructure is a barrier to freedom of location and new systems generally communicate either using the mobile network, radio or wi-fi. Online access to data is also very convenient and less resource hungry. Few of us who readily use mobile phones, online banking and many of the commonplace applications of modern life fully understand security of communications and the reality of data hosting. The bottom line is that air quality data from sensor systems using wireless communications can be as secure as any other online application. Confusion is caused by the systems which are focused on citizen engagement and offer automated sharing and publication of data, but these are the exception and in most cases, such as AQMesh, data is private and secure.
Current low cost air quality sensor systems are a very mixed bag. Some products may well appear to offer the same measurements and even claimed accuracy as the more thoroughly developed and tested systems and the user has little choice but to ask searching questions and ask for demonstration of performance and reference projects before purchasing. But the need for such systems is clear and performance is already good enough for many leading institutions and organisations to be actively using the technology. Sensor and sensor system manufacturers are seizing on every new shared comparison dataset and development in technology to make further improvements. The insights that these sensor systems can offer are real and relevant and there is no substitute for trying the technology in any given application to see what it can offer. Many users have found that one insight can lead to another and, working with a clear understanding of the strengths and weaknesses of the systems, the benefits of making a start with this new tool are overwhelming.