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.

SEPA monitors impact of gas flaring on air quality

23-May-2024Fenceline | Gas flaring | Industrial | Oil & Gas | PetrochemicalUK

SEPA monitors impact of gas flaring on air quality

Air quality monitoring stations have been used by the Scottish Environment Protection Agency (SEPA) to form a new air quality monitoring network around the Mossmorran Complex near Cowdenbeath and Lochgelly, Fife.

The network of 8 AQMesh pods was deployed in addition to a fixed air quality monitoring station to help address the concerns of the local community about the impact of operational activity at ExxonMobil Chemical Limited Natural Liquids Plant and Fife Ethylene Plant in Fife, Scotland. Both plants use flaring processes to burn off excess gas, and SEPA set out a series of regulations aimed at reducing the amount – and impact – of flaring, as well as being able to provide local residents with accurate, real-time information about pollution levels in the wider community.

Commenting on using the AQMesh pods, SEPA have stated that “these analysers are easier to locate than the reference analysers due to their size and power requirements and can be installed in more accessible locations. They are useful in assessing short-term trends in pollutants; provide greater geographical coverage both up and down wind of the site; and monitor for a wider range of pollutants.”

So far, all the pods and fixed station continue to show that there have been no breaches of any air quality standards since monitoring began.

The quality of the data produced by the AQMesh pods at the Mossmorran facility has been optimised using a proprietary network calibration method known as ‘long distance scaling’, which identifies and separates hyperlocal events from individual pods in order to determine the common pollutant trends seen on each pod in the network. These data trends are then directly comparable on each pod, showing the background/baseline pollution levels across the network and can also be used to provide calibration – or scaling – factors that can be applied to each pod. The method is similar to that developed by Professor Rod Jones of the University of Cambridge, which was used for calibration and quality control of 100 AQMesh pods in the Breathe London pilot.

For more information about SEPA’s air quality monitoring network at Mossmorran, or about AQMesh, contact us today.

Looking behind the scenes of dust & PM monitoring

20-May-2024Industrial | Particle monitoring | PM | Product

Looking behind the scenes of dust & PM monitoring

Measuring particulate matter (PM) accurately comes with a number of challenges, including effects from humidity and differing particle sizes. Technological considerations are also a factor, such as variable sample flow rates and the physical size and diameter of the sample path, which could affect the number of particles able to be measured.

AQMesh has been able to overcome many of these challenges through its proprietary OPC development, making it a robust, reliable and accurate solution for PM monitoring. From sample inlet to final data output, each design requirement for precise measurement of particles in ambient air has been carefully thought out to result in a truly bespoke and fit-for-purpose optical particle counter (OPC) – a solution that only AQMesh can offer. There are a few key aspects:-

Active sampling using a pump

By using a pump instead of a fan, the AQMesh OPC samples at a steady flow rate from the inlet to sensor, which provides a more consistent air sample than other methods used. Systems which use fans run the risk of creating vacuums, which can interrupt the flow rate and affect the sample measurement.


A funnelled inlet helps the OPC taper the particle samples to a focal point, and then a straight line sample path from this focal point to the laser bench means larger particles are not ‘stuck’ in a bend and ensures all particles within the sample pass through the laser path, allowing for complete capture of particles, categorised by diameter from 0.3 – 30um. This means the laser OPC in AQMesh gives a true PM10 measurement, which many systems – including nephelometers – cannot offer.

Heating the sample to reduce deliquescence

The optional heated inlet allows AQMesh to reduce the effects of humidity on particle sizes. Known as deliquescence, this effect can make particles larger in diameter due to the absorption of moisture. The heated inlet overcomes this by drying the sample as it is drawn in, bringing the particles back down to their true size and therefore resulting in more accurate measurement. Additionally, AQMesh can detect when deliquescence is likely to have happened during data processing and can ‘flag’ the data point – including with non-heated samples – allowing it to be easily identified and redacted. Use of the heated inlet results in less than 1% of data points being flagged in this way.

Autonomous power for uninterrupted sampling

Using AQMesh’s bespoke smart solar pack for autonomous power allows for uninterrupted PM monitoring, with no need to change the sampling regime to take fewer readings – a process which could potentially void an instrument’s MCERTS certification. The AQMesh solar pack provides consistent, smooth power all year round for AQMesh pods.

Minimal maintenance

Other benefits of the AQMesh OPC include reduced maintenance – there is no need to change any filters, and there is no need to replace the whole OPC unit when it requires servicing. We simply advise the pump and laser is replaced every two years, which can be carried out by the user without returning the instrument to factory. Exceedance alerts can also be set for PM fractions, alongside any other pollutants being measured, which enable users to receive immediate information if levels breach a user-defined level over a user-defined period.

MCERTS indicative

AQMesh has been accurately measuring PM for over 10 years, and offers the added reassurance of MCERTS Indicative measurements for PM2.5 and PM10.

For more information on how AQMesh can support your PM monitoring requirements, contact our experienced team today.

You really want to measure that H2S range??

29-Apr-2024Emissions monitoring | Fenceline | H2S | H2S monitoring | Industrial | Oil & Gas

You really want to measure that H2S range??

Requests to measure hydrogen sulphide (H2S) in ambient air at unthinkably high levels seem to be at odds with our efforts to detect and report single-figure parts per billion H2S emissions. So, why are we asked for such high ranges?

We think this may be explained by operators who are used to measuring high concentration in a gas stream – typically biogas or industrial – and then simply transferring the range across when looking at fenceline monitoring. It’s great to see the growing interest in monitoring fugitive emissions at site boundaries – including H2S – but we need to dial back the gas range expected when looking at ambient pollution.

H2S sensors for gas stream measurement are offered at parts per million ranges from 0-50ppm to 0-10,000ppm. Bear in mind that US Department of Labor guidelines say that H2S odour becomes offensive at only 3-5ppm, with prolonged exposure causing headaches, nausea and insomnia, and causes “nearly instant death” at 1,000-2,000pm. Dilution of any emission in swirling ambient air means that parts per million measurements are inappropriate, and even significant H2S leaks usually register peaks of just a few parts per billion by the time gas has reached the fence line.

That’s why the AQMesh sensor measures from 0-10,000ppb (0-10ppm), with a limit of detection of less than 1ppb. Measuring at such low levels means operators can pick up emissions much earlier and much further away from the source than would be the case with the higher range sensor typically used for measuring the gas stream. Picking up a low level at a suitable point on the industrial boundary should avoid dangerous levels of H2S building up near the source.

Monitoring in ambient air is gentler on sensors, too, so if you are used to sensor poisoning and condensate problems, that benefit does offset the ‘needle in a haystack’ challenge of picking up fugitive H2S emissions. With the potential to move an AQMesh pod from location to location, and add a wind speed and direction sensor to help with source apportionment, it is very satisfying to support our users doing just that.

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.


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.


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.

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.

Check H2S, SO2 and VOC emissions continuously around your sites

06-Mar-2024Fenceline | Industrial | Oil & Gas | Perimeter

Check H2S, SO2 and VOC emissions continuously around your sites

If you are responsible for air pollution around an oil, gas or industrial site, you have a range of options at different price points. AQMesh offers a cost-effective way to continuously monitor ambient air quality, as frequently as every minute, with readings accessed securely online and user-settable alerts. This system offers an ideal, confidential first step to understanding whether you – or your neighbours – have an emissions problem, particularly as the equipment is available on a rental basis, anywhere in the world.

AQMesh has been used in a wide range of applications – from the coldest to hottest conditions – for over ten years, and 15 different pollutant and environmental measurements can be provided by a single pod, using bespoke sensor configurations. The most popular measurements for petrochemical customers are hydrogen sulphide, sulphur dioxide and volatile organic compounds.

H2S, SO2 and TVOC – including EtO – can be measured down to single figure ppb, with a high level of accuracy, and CO2 readings provide a real-time, accurate measurement of local combustion. AQMesh pods can be quickly and easily deployed around petrochemical fence lines, landfill boundaries, wastewater site perimeters and around mining facilities to provide completely confidential real-time air pollution data.

One requirement we see regularly is for monitoring around vulnerable communities, such as housing areas or schools, to understand potential exposure. Pods are being used in a variety of oil & gas, manufacturing and processing applications to detect and identify sources of pollution and inform potential mitigation strategies. Although not a regulatory instrument – so readings are not generally reportable – various data management techniques can offer traceability back to an approved methodology, providing data quality assurance.

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.

Do air quality people love holidays more than everyone else?

12-Dec-2023Environmental | Hybrid networks | Industrial | Networks | Traffic

Do air quality people love holidays more than everyone else?

Everyone loves holidays, whether Christmas or anything else, right? So what’s special about ‘air quality’ people? What we get so excited about are ‘free’ experiments, where distinct changes in activity help to peel away the layers of air pollution measured. Over the years, various studies have been published, showing residual air pollution levels when other sources drop – or increase – significantly.

Around this time of year there are changes in emissions activity around schools, businesses and industry, roads (both increases and decreases), burning of solid fuel in households, domestic heating, and so on. As well as looking at changes in measurement over time (hourly or shorter intervals) and space (hyperlocal monitoring means you can literally measure at any point you wish, from a specific point on a specific road junction to a school playground), measurement of multiple parameters is an eye-opener.

Studies by the University of Cambridge have shown how small sensor air quality measurements can be used in conjunction with their scale separation technique to distinguish between local and regional or background sources. Comparing the proportion of different pollutants in this way can give a ‘fingerprint’. CO2 measurements provide a baseline combustion level against which generally traffic-related NO / NO2 / NOx can be compared. Looking at PM fractions against CO2 and other gases can also provide more insights than individual measurements alone can provide. And, of course, dramatic shifts over time – like holidays – sharpen that focus.

A network of sensor systems has the additional benefit of showing whether pollution is being displaced from one location to another, with this forming part of the analysis around other behavioural change triggers, such as the introduction of a traffic Low Emission Zone (LEZ). It can also help identify hyperlocal sources of pollution, where high levels of pollutants are only seen by one of the monitoring points.

One memorable headline from several years ago was that a higher amount of PM2.5 in one London borough over the Christmas period could be attributed to domestic solid fuel combustion (cosy wood-burners) than road traffic. So, whether it is reduced traffic around schools, increased traffic at shopping centres or chestnuts roasting on all those open fires, the holidays can provide a curious insight to local air quality data and pollution patterns.

Happy holidays from the team at AQMesh.

What area does an air quality sensor system cover?

13-Nov-2023Fenceline | Industrial | Networks | Urban

What area does an air quality sensor system cover?

Or how many air quality measurement points do I need?

Annoying as it is, the answer is ‘it depends’. The list of factors which affects this not exhaustive but is based on our experience and we’ll try to be a bit more helpful afterwards.

  • Size, location and topography of site
  • Position and range of pollution sources and ‘receptors’ (such as communities or schools)
  • Wind direction and strength
  • Complexity of area being monitored, including multiple sources and street canyons
  • Analysis capability
  • Your budget!

Generally, the limiting factor will be budget. The clue is in the name with hyperlocal air quality monitoring, and pollution levels can vary hugely over short distances. NO measurements around streets, for example, are often significantly different from one side of the road to the other, particularly if there isn’t much wind and/or a street canyon effect. It is important to agree objectives and priorities in any city monitoring project, as it is simply not possible to meaningfully instrument the entire city, even with the biggest budgets. Even should budgets be effectively unlimited, the challenges of data management, quality assurance and interpretation get harder and harder the more nodes you have.

When monitoring air quality at the fence line at remote or industrial facilities, dilution of pollutants mixing with air around the site reduces the chance of a ‘spike’ being picked up from a plume, so generally the more measurement points that can be afforded, the higher the likelihood of detecting fugitive emissions, whether CO2, NOx, SO2, H2S, TVOC or particulate matter.

In either scenario, a hybrid network can help optimise the return on investment, so mixing a range of sensors with reference stations can help to fill gaps cost-effectively. The limiting factor with this is that any sensor used in the network has to provide comparable data. In theory a (very) low cost sensor could be used in high numbers to provide wide coverage, but if the cheap sensor does not have the necessary sensitivity (particularly when looking for low concentrations in a plume), data accuracy or comparability with other technologies (or even precision between themselves) in the network, there is a serious danger that project objectives will not be met and money will be wasted.

In our experience, the best way to achieve optimal coverage is the following recipe:

  • At least one well-maintained reference station (if a reference station is not available, diffusion tubes/passive samplers can be used to good effect)
  • As many good quality small sensor systems as you can afford
  • Normally one wind speed and direction sensor per site (this may be more complex if the wind direction is obstructed by topography or buildings) or local wind data may be available
  • Data analysis and quality assurance resource, with complete traceability
  • Calibrate small sensors against reference
  • Position small sensor systems precisely where required, free of infrastructure limitations, with autonomous power and communications
  • Carry out analysis to identify sources and distinguish background from locally-generated pollution
  • Stick to the sensor system manufacturer’s recommended maintenance procedures, however minimal, to ensure data reliability over the longer term
  • Follow local and international advice on quality assurance of data
  • Beware of big promises offered by AI – current local training of sensors comes with significant drawbacks

We are happy to provide more advice, dependent on your situation.