Explore AQMesh

Community monitoring vs. industrial monitoring

06-Jun-2024Community | Community monitoring | Industrial | Industrial monitoring | Networks

Community monitoring vs. industrial monitoring

Communities and industry are monitoring air quality around the same areas, so they both want the same thing, right? Er, no, not really ..

Even though both types of AQMesh user may measure the same pollutants using the same instrument, their objectives and needs are often different. The community users we deal with – mostly in the UK and USA, but plenty of other places too – tend to be more interested in identifying pollution events and relating that to what they are experiencing. The first step is a sort of validation of what they believe to be happening all around them. This is not to say that the review of data is selective or unscientific, it’s just experience-focused. For example, school monitoring projects are generally focused on identifying periods of elevated air pollution outside and around the school at different times in the school day and finding the cause / source.

On the other hand, air quality monitoring around communities by the industries that may be the source of the pollution takes a different approach. Our industrial customers – from oil and gas, construction, mining, landfill and other sectors – want accurate air pollution measurements to demonstrate that they are within compliance of local environmental regulations. Another aspect is that there is often more than one potential source of pollution in an area so an industrial AQMesh user may be keen to understand more about what pollution is coming from where (and hopefully proving that a neighbouring facility is causing the issue, not them). Accurate wind data is required to carry out such source apportionment analysis. AQMesh offer a wind speed and direction sensor option and normally only one pod in an area needs to be gathering this information.

Whilst communities and industries may have slightly different air pollution monitoring objectives, they recognise the benefit of using the same instruments, so the data is comparable. A version of this desire to be able to make meaningful comparisons is where government monitoring uses a particular type of equipment and the potential industrial polluters being monitored choose to use the same technology. For example, a community in Texas, USA, installed AQMesh pods outside suspected polluters, so the industrial facility (or rather a consultancy they hired) bought AQMesh systems to monitor themselves. This helps to build trust that data collection and analysis will be done correctly and in an unbiased manner. Another factor bringing all parties together is when there is a natural cause for the pollution affecting people, such as volcanoes (see our news items about airport and community in Iceland) and wildfires.

In the USA, industrial companies are aware that use of uncertified equipment – other than FRM / FEM – means they cannot be obliged to report on data. This creates a ‘safe space’ for potential polluters to understand the air quality around their operations and their impact on it, ahead of compliance demands.

And then there are data centres, where the focus is not on the potential for pollutants to harm people but infrastructure. Hydrogen sulphide monitoring can warn of potential damage to sensitive copper circuits and HVAC maintenance intervals can be managed by monitoring of PM levels, helping to prevent machinery failures.

So, whilst different customers are all using the same air quality monitoring systems and measuring the same pollutants, the reasons driving the project may be entirely different. Either way, our experienced team can support a range of objectives and help interpret your data with meaningful context.

ASIC discussions look at AI vs non-AI calibration

22-May-2024ASIC | Calibration | Hybrid networks | Network calibration | Networks

ASIC discussions look at AI vs non-AI calibration

So how do you do it? Many presentations at the recent ASIC conference revolved around calibration of small sensor air quality systems, including that given by AQMesh Technical Business Development Manager, John Downie. Offered the opportunity to poll the ASIC audience, we chose to ask delegates ‘Please indicate which of these calibration methods for small sensors you would consider for your small sensor network’. Whilst numbers responding were not huge, ‘periodic co-location of each instrument with FRM/FEM creating seasonal correction factors’ came out top, indicating a thorough – if labour-intensive – approach is generally most common and taken as the ‘norm’.

So what if you don’t have the ‘boots on the ground’ to carry out the many instrument movements that would be necessary with a network of any size? Is there a short-cut? Can AI help? The poll did show that about a quarter of respondents were considering ‘desk-based calibration, using machine learning or AI’, about twice the proportion thinking about ‘desk-based calibration using network calibration method without machine learning or AI’.

We tried using AI on electrochemical sensor output a few years ago but found that – at the time – the machine learning was very good at latching onto interfering factors, such as temperature, and less good at finding the weak (valid) signal in amongst the noise. We were greatly impressed by the later (non-AI) network calibration work done by University of Cambridge, our partners in the Breathe London pilot, and have developed our own approach. This series of repeatable calculations can be applied to a network of five instruments upwards and we feel there are some clear differences (advantages, of course) comparing the AQMesh approach to local calibration with AI-driven approaches:

 

AQMesh LDS

AI / Machine Learning

Confidence in repeatability of measurements from individual instruments

Yes

?

Confidence in repeatability across seasons & locations

Yes

?

Traceability back to only self-contained* measurements

Yes

No

Calibration method repeatable with the same output

Yes

?

Drift correction / interpolation between calibration intervals

Yes

No

Method approved by DEFRA / Environment Agency

Yes

No

The fundamental issue with machine learning and AI being used either for compensation of sensor interferences or for calibration adjustments is that their whole premise is to “evolve”: they spot differences and change to account for those changes. This means that over time the results may be closer to reference, but they will never follow the same process for adjustment as they did previously. This raises significant traceability questions about when processing changes and makes it impossible for these methods to become certified to a standard which require a fixed processing of inputs, managed by a version number.

It’s worth noting that PAS 4023 (Annex D) distinguishes between sensor systems that are ‘self-contained’ – with readings derived by the system alone, using a series of repeatable calculations – and those that require training against a reference station. The PAS also emphasises how important it is that individual sensor systems should perform very similarly to one another, so that remote comparisons across a network can be made with confidence. Another reason why a proven, global correction algorithm used by every instrument has the edge over individual site-based AI. Strong inter-instrument comparability also means that a network can be meaningfully compared against itself, in the absence of a reference station, as offered by AQMesh’s network normalisation option.

Supporting your air quality monitoring system when you can’t get to it

24-Apr-2024Fenceline | Hybrid networks | Industrial | Networks | Product | Support

Supporting your air quality monitoring system when you can’t get to it

Each time we think we have found a spectacularly remote monitoring location, an even more inaccessible spot is reported by one of our users. Full-day trips to visit a location have now been beaten by customers who need to charter a plane to reach them. So, remote diagnostics and support are very important.

Luckily, IoT communications, cloud data management and over 10 years of experience supporting AQMesh have allowed us to continually improve our ability to supply and support AQMesh in remote locations. Pods have been used from the edges of the arctic to undeveloped deserts – as well as on ships – with the help of a few features.

Robust design, low maintenance intervals

AQMesh was designed to be rugged, for use all over the world and with an expected maintenance interval of two years. We have always understood that field maintenance requirements must be kept to a minimum, and pods operating for year after year, in the harshest environments – from deserts to extreme cold – demonstrate design effectiveness. This includes protecting electronics from the elements and mitigating electromagnetic interferences, as well as taking measures to keep insects, wildlife and birds out/off.  The unobtrusive pod design has also ensured a very low rate of vandalism and theft.

QA flags and notifications

The AQMesh data stream includes vital pieces of information which allow users and the AQMesh support team to check that pods are functioning correctly and provide an early warning system. Users can register for email notifications for their pods – it is always better to find out that power is running low or data is no longer being transmitted at the time, rather than when the project ends and it’s time to review data.

Remote scaling / calibration

Whilst AQMesh was a leader in co-location comparison and the ‘gold pod’ technique for in-field calibration, these approaches do require regular site visits to move pods around. We have now developed a method that can provide remote calibration of a sensor network, with or without an available reference station, that does not rely on artificial intelligence.

Diagnostic information

The AQMesh team can access additional diagnostic information remotely, such as performance indicators from the optical particle counter, solar pack battery voltage or sensor failures. Some of these indicators are available to users via their secure online or API access, and some can be used by our global technical support team. The team uses the full range of diagnostic information available, including SIM connection attempts, to provide free support for the life of the equipment. Their over-riding goal is to fix any problem without asking users to visit the site.

Over the wire intervention and updates

AQMesh firmware developments now allow power cycles to be triggered remotely, firmware to be updated over the wire or remote sampling and transmissions interval changed.

Power

We have learned from the many challenges that power supplies can present to remote operation. Whilst the original lithium thionyl chloride battery offered unbeaten long-term autonomous operation of gas sensors, increasing shipping limitations have turned our focus to direct power supply and solar. We invested in a full technical investigation to identify a mains to 12V DC transformer that could cope with ‘dirty’ power supplies, as well as in-pod measures to manage spiky or intermittent power.

Having seen so many problems from simple solar-panel-plus-battery arrangements, we designed our own smart solar pack, which squeezes the most power out of any location, manages power delivery and provides online voltage measurements. We are mindful that sampling and reading rates are defined by the project – and potentially certification – and the power supply must deliver the same sampling throughout the year. Readings should not be compromised by the difficulty of providing autonomous power.

Communications

The global SIM supplied with a standard AQMesh pod will roam across networks to find the best connection at each transmission, and has proven to be a very reliable way of transferring sensor output from hardware to our cloud server for over 10 years in more than 70 countries. Occasionally, we find that only a single, specific network is available – or a customer would prefer to use their own SIM – in which case we can programme the pod to work with a locally-sourced SIM contract. To achieve autonomous communication, the AQMesh LTE CAT M1 modem uses the latest LTE communications standard, including support for NB-IoT where available. In the most extreme cases, satellite communication is the only viable option and AQMesh can connect via an ethernet port to a suitable modem to connect this way. Reliable communications are key to remote data access and support.

The growing need for remote, long-term monitoring, in all conditions, drives our continuous development from data QA to comms, and we welcome challenges.

“Maintenance-free air quality monitoring” – is it a myth?

12-Apr-2024Maintenance | Networks | Performance | Product

“Maintenance-free air quality monitoring” – is it a myth?

There’s no doubt that small sensor systems can have an advantage over their cumbersome reference station cousins – in terms of maintenance requirements. We are often asked about ‘service’ requirements for our pods and the honest answer is that the default position, in normal working conditions, is ‘none’. However ..

There are consumables, conditions can have an impact and sometimes ‘stuff happens’. We have seen small sensor systems claiming they require no maintenance at all, so would like to offer some thoughts on these three areas:

Consumables

Some sensors and sensor components need to be replaced at a defined interval (two years for AQMesh). This may be because the product is designed to optimise accuracy and component duty cycle, such as the AQMesh pump sampling particulate matter, which is expected to last two years on standard settings. If the pump is not replaced at two years, in-field failure is the likely outcome at some point. AQMesh uses a pump to provide reliable sampling over a set period. An alternative, such as a fan, may not be offered with a finite duty cycle, or with one that is theoretically longer, but failure modes can be undetectable remotely and readings affected. Is that better?

Many small sensor systems use Alphasense’s electrochemical sensors, which come with a recommended two-year life. Sure, they last longer than two years and keep producing numbers, but who has tested the sensors beyond two years and will be answerable for accuracy after two years? Users of these systems need to look ‘under the hood’ here – is the system claiming to be maintenance-free ignoring sensor manufacture advice? Are they reducing operation or sampling to extend the duty cycle?

Monitoring conditions

In a nice, clean monitoring location it is possible to predict performance of a monitoring system over several years. But, when the system is faced with tough conditions – such as sandstorms or an acidic environment – some intervention may be necessary to keep the system running. Good design and remote diagnostics can help to minimise this, but it is often the pods installed in the most remote locations (hardest to reach if necessary) that are hit by the toughest conditions.

‘Stuff happens’

Most of the stuff that happens to AQMesh pods is hard to predict. One academic study, monitoring air quality around treated road surfaces, mounted pods a few centimetres above the road and they were swamped in a rainstorm. One contractor installed a pod on its side. Solar-powered pods are sometimes installed with great difficulty, only to find the system is constantly in shade. We encourage as much pre-installation planning as possible – and provide a wealth of manuals, guides and videos to avoid these scenarios – but there are sometimes situations which require on-site intervention. We have seen ‘maintenance free’ fulfilled by offering replacement equipment under warranty, instead of maintenance, but customers still have to make a site visit anyway, so we don’t really buy that one.

AQMesh started out offering uninterrupted 2-year gas monitoring with autonomous power but we quickly found that much monitoring was project-based and that users preferred to have the comfort of planned maintenance arrangements that would maximise the chances of achieving high data capture and high data quality throughout the project.

Why do air quality consultants love AQMesh?

25-Mar-2024Consultants | Networks

Why do air quality consultants love AQMesh?

Our pods continue to be pretty popular among environmental and engineering consultancies, both here in the UK and further afield, so we asked some of them what appeals to them most about AQMesh. We were pleasantly surprised by the range of responses we received although there were a number of recurring themes.

  • AQMesh is a brand synonymous with quality in precision of data, robustness and support
  • Pods are compact and easy to install with a range of reliable power options, including a smart solar pack for year-round monitoring
  • Particle (PM) readings are almost instant – available as soon as the first transmission interval, for confidence the unit is working when leaving site
  • LTE-backed communications are reliable in almost any monitoring location, from urban areas to remote industrial sites
  • Sensors and power supplies are changeable in the field, without the need to return to factory
  • Downloading data from the platform is easy and intuitive
  • Data ownership and security is never an issue – client data is always 100% confidential

Are you an AQMesh user? What’s your favourite feature?

Some projects run more smoothly than others – what makes the difference?

13-Mar-2024Hybrid networks | Networks

Some projects run more smoothly than others – what makes the difference?

We have some thoughts here at AQMesh about the common features of successful, well-run small sensor air quality monitoring projects. This is our list, but we’d love to hear your ideas.

  • One main contact who remains constant throughout the project
  • Clear project objective(s) and timescale, even if the client doesn’t share them with us
  • The main contact requests and distributes relevant information to all the right people – guides, videos, manuals
  • Planned installation locations are reviewed – by the client and by our team – on Google maps and using photos
  • Direct communication between installation staff is actively encouraged
  • Regular data reviews, so any issues are addressed quickly
  • All available resources are used, such as our site technicians’ ‘app’

These points seem to be critical, wherever the project is, and whether it is totally confidential, ‘typical’ or novel.

What would you add to the list for successfully running a small sensor air quality monitoring network?

Anodes and anemometers for harsh winter air quality monitoring

11-Mar-2024Accuracy | Fenceline | Industrial | Networks | ProductIceland

Anodes and anemometers for harsh winter air quality monitoring

We are often asked by customers whether AQMesh can operate in cold conditions. Long-term use at temperatures well below freezing, with ice and snowfall, is indeed challenging. Cold weather operation has been key to AQMesh – improved upon and proven in the field – for over 10 years. The main features, described below, have been most recently been put to the test in Iceland.

Ölfus, a municipality in Iceland, installed a number of AQMesh pods during December to measure local air quality across the town in relation to the region’s volcanic activity. The pods – supported by Vista, AQMesh distributor for Iceland – will monitor NO, NO2, CO, H2S, SO2 and particulate matter and report the data to the local Environment Agency.

A monitoring network has also been recently installed on a construction site in Reykjavík, measuring dust (PM), NO, NO2, NOx and wind speed and direction, powered by the smart solar pack. AQMesh was chosen because of successful performance in previous deployments in Iceland, as well as ease of installation and minimal maintenance requirements.

The successful operation of AQMesh pods in extremely cold temperatures can be attributed two main factors: power management and weatherproof design.

Power management

Many small sensor air quality monitoring systems use lithium batteries, which carry a recommendation for use only down to 15°C. Lithium ion batteries should not be charged below 0°C – there are risks in trying to do so – and performance is also significantly poorer at low temperatures. This is because lithium ions can plate the anode surface in freezing conditions, reducing battery capacity and increasing resistance.

The AQMesh solar pack uses the heavier but more practical 22Ah lead acid battery, which performs reliably in such temperatures. The AQMesh battery has 264Wh capacity, compared to lithium-based systems which store less than 100Wh solar power. With the battery built into the smart solar pack, capable of powering the pod for 1.5 to 2 weeks without sunlight, the pod can be powered at full capacity over the whole year at surprisingly high and low latitudes. This is particularly significant for relatively power-hungry sampling of PM: AQMesh will continue to sample at the optimal rate and not reduce sampling, which would deviate from MCERTS test conditions, voiding certification. Lead acid batteries are also easier to ship than lithium: a major consideration if you are moving pods around the UK or internationally.

Weatherproof design

Simple design considerations can be vital. Right from the first deployments across North America and Scandinavia, AQMesh design has shown that equipment cannot just survive but provide full functionality through a harsh winter, without maintenance visits. The shape of the pods prevents water, ice and snow building up on the surface, and there are no moving parts that can be affected by freezing temperatures. The AQMesh wind speed and direction sensor option is an ultrasonic anemometer, with no moving parts to wear or recalibrate, making it reliable and low maintenance.

AQMesh pods use a pump for drawing in particles, as opposed to a fan. Fans are more likely to be affected by snow and ice, potentially recirculating the same air if even partially blocked, whereas a pump will still actively draw an air sample.

Data processing on the secure AQMeshData.net server uses correction algorithms based on over 10 years of real-world testing which can compensate for extreme environmental conditions and flag affected data points if necessary.

A network of 50 AQMesh pods in Minnesota, USA, continues to operate smoothly in temperatures as low as -25°C, despite the area being under several feet of snow for long periods of the year. Other deployments include Alaska, Mongolia and Scandinavian regions, all of which experience harsh winter conditions.

For more information and to discuss your potential air quality network deployment contact our experienced team today.

UK local authority uses AQMesh for cost-saving NO2 monitoring network

28-Feb-2024Accuracy | Hybrid networks | Local authorities | Networks | PerformanceUK

UK local authority uses AQMesh for cost-saving NO2 monitoring network

A UK local authority installed nine AQMesh systems at different points across a busy town, measuring nitrogen dioxide (NO2) at 15 minute intervals, monitoring 24/7. These locations were established monitoring points, where measurements had been taken previously using diffusion tubes, limited to one average reading every few weeks.

AQMesh – in common with all lower cost air quality systems – can provide near real-time air quality information, with high frequency measurements that allow daily and weekly patterns to be seen. However such systems are not certified, as are reference stations or diffusion tubes. As a result, AQMesh readings need to be ‘calibrated’ against certified readings, at some point in the network, to provide confidence in data accuracy and traceability to an approved standard.

Typically such ‘calibration’ is carried out by mounting at least one AQMesh ‘pod’ very close to a reference station, so pod and reference are sampling the same air and readings can be compared. However this approach does require staff to move pods from position to position, which can be time-consuming and therefore costly. An alternative approach was used for this network, similar to the one developed by the University of Cambridge and used in a major project in London (Breathe London pilot). One of the authority’s reference stations (location in red on map) was used to ‘calibrate’ the network of pods and the other (location in green on map) was used to cross-check network accuracy.

AQMesh network deployment (BELOW): AQMesh locations marked in blue, reference station used for calibration in red, reference station used for control co-location in green

The four-month project demonstrated that the AQMesh network showed that stakeholders could have the same high confidence in readings when the network was calibrated remotely as when pods were co-located for calibration (the gold standard for this technology), but with significant savings in field support and reduced data loss.

Six hidden costs to look out for when choosing a small sensor air quality monitoring system

14-Feb-2024Construction | Environmental | Fenceline | Industrial | Local authorities | Mining | Networks | Oil & Gas

Six hidden costs to look out for when choosing a small sensor air quality monitoring system

Anybody in the market for purchasing a small sensor air pollution monitoring system will need to consider budgets, but it’s not always obvious how the products being reviewed actually compare across their full operational life. A small sensor air quality monitoring system or network can be a significant purchase, so whether project-based or with ongoing monitoring in mind, it is likely that the equipment will be in use for several years. There are six main areas of cost highlighted here, all of which kick in after initial purchase.

Without direct experience of a product, it’s natural that the focus is on the initial price tag, but that may only reveal part of the total cost. The weeks or even months spent researching products is a fraction of the time – up to 10 years – of expected product use and experience. A typical timeline of product experience will start pre-sale and run through installation, project set-up and data access arrangements, data quality assurance, planned and unplanned maintenance, co-locations and re-locations, updates, upgrades, reconfiguration, and so on. How much will you have spent – directly or indirectly – by the end of the product’s life?

Over the product’s span of operation, hidden costs can include:

  1. ‘Boots on the ground’ – field staff for installation, co-location, maintenance, repairs, product replacements, and so on. Some of this will be essential, but it can add huge cost if uncontrolled, particularly if units are installed far away from the team’s base.
  2. Consumables – sensors need to be replaced periodically, but how often and at what cost? Some systems require that sensors are replaced after a short time, can only be replaced as part of a multi-sensor cartridge, are very expensive, or a combination of these.
  3. Data services – whilst the charge is to cover the real cost of data processing and storage (not access), annual data prices vary considerably and add up over the years.
  4. SIM – an annual charge for a global SIM to connect the unit to a server is often cost-effective and convenient, but charges vary. This may depend on where in the world the unit is installed, but it’s worth checking prices and whether you have the option to use a local SIM, if that would be cheaper.
  5. Support – what is included in support? Is it limited in any way? Ask for examples of committed support of networks in challenging situations, well after year one.
  6. Length of warranty – this is a clear commitment from the manufacturer of what you should expect from their product: putting their money where their mouth is.

We have worked out that for two of the most popular AQMesh models (or specification) other products may be as much as 29% cheaper than AQMesh at initial purchase, but that flips to 31% to 70% more expensive overall – including the initial purchase – after five years of use. This is based on quoted consumables, data and SIM costs, so there may be even more indirect costs that we have not included in our calculation. Whilst these additional costs can possibly be accommodated within budgets for a small number of pods, hidden costs can scale at a rather alarming rate for larger networks.

It’s also worth checking how much flexibility you may have in the future:

  • You may only be able to renew data services if you purchase replacement sensors
  • Support may be limited in some way
  • You may not be able to use a SIM of your choice

Your expectation of the product life may be different to the manufacturer’s, and that can apply in both directions. We have been asked to quote AQMesh pods, which we expect to function happily for 10 or more years, by customers who really want to buy a disposable product for a short project. If that is the case, rental is a great option. With all costs wrapped up into a single price, from three months to years at a time, costs are totally predictable and full support ensured, right through to free product replacement, should it be required.

AQMesh pods, with their robust and proven design, are expected to function in the field with minimal intervention for at least 10 years. The pods automatically come with a 5 year manufacturers’ pod warranty. We commit to – and deliver – lifetime remote support, included in the price. Remote firmware and gas processing algorithm upgrades come as part of any purchase, ensuring pods can always be updated to latest and improved versions for free.

The pods are designed to be user-serviceable, meaning only consumable components need to be replaced, rather than expensive cartridges which add cost through packaging and electronics. Consumables and yearly contracts can be purchased up front – with the initial pod order – ensuring visibility and security when it comes to future costs and maintenance, as well as appropriate discounts. Practical maintenance videos ensure that any time spent by your team is as efficient as possible, so you can plan ahead with resources and avoid unexpected demands. The team at AQMesh have been supporting pods in remote locations for over a decade, learning from our experiences along the way to ensure you get the right support exactly when you need it.

Why we love PAS4023

13-Feb-2024Data validity | Networks | Performance

Why we love PAS4023

Is it normal to get excited about a Publicly Available Standard? For us it feels like a long time coming, and this first step on the long road towards an ISO standard for small sensor air quality monitoring is very welcome.

Whether you are using small sensor systems (with or without MCERTS) or reference grade equipment, you need a clear and agreed process for data, to show that data is trustworthy and reliable. PAS4023 is now freely available to the public to guide users on how to get accurate and valid data from small sensor systems. The standard essentially aims to provide a method for using small sensor systems which ensures any data produced is consistent and comparable to a known standard.

This takes a lot of the risk out of use of this type of monitoring equipment, especially where it has held back adoption in applications where it would add real value.

A QA plan makes all the difference. Without one, data is always open to challenge, however ‘good’ it is. If it can be demonstrated that a project is using the same equipment in the same place, at the same time, and following the PAS4023 document, data is more meaningful and can be used by government bodies.

In the 10+ years that AQMesh has been commercially available, it is the lack of this sort of clear guidance – put together by a team of experts – that has undermined confidence. So, a big thank you from us to the team behind the Standard.

Learn more about PAS4023 here and chat to us about how we can help you manage an air quality monitoring network you can rely on.