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Why air pollution matters and what data can do about it

Edward Kulperger, VP Europe, Geotab on the major health issues posed by air pollutants and how telematics can help provide data for change.

In recent years, governments around the world have increasingly woken up to the public health threat posed by air pollutants. In just the last month, South Korea passed a set of bills designating air pollution a ‘social disaster’ in order to unlock emergency funding; China announced that air particulate matter has fallen by 9.3% year-on-year, partly as a result of increasingly stringent pollution fines; and London launched the Ultra Low Emission Zone (ULEZ), designed to limit exhaust emissions from transport and delivery fleets in the most polluted areas.

However, even as such measures have been stepped up, the scale of the air pollution problem has rapidly grown for the simple reason that research is still uncovering and unveiling the significance of the health threat it poses. Just one day before South Korea passed its bills, a new report published in the European Heart Journal indicated that the number of early deaths caused by air pollution is double previous estimates: at a rate of 8.8m deaths per year, air pollution is now considered to pose a greater threat to health than smoking tobacco.

Making invisible pollution visible

While we generally recognise carbon dioxide as the pollutant that vehicles contribute to the atmosphere, the key issues for both this impact research and the governmental measures responding to it are nitrogen oxide and particles known as PM2.5. These particles are so called because they measure less than 2.5 micrometres around, or roughly 3% of the diameter of a human hair. The effects of breathing PM2.5 – which can be solid particles or liquid droplets from a broad variety of sources – are still poorly understood, but their role in exacerbating lung and heart conditions, as well as mental health issues, has become increasingly clear.

While fears around air pollution are nothing new – the landmark Clean Air Act in the US was passed in 1970 – recent developments make it clear that there is an urgent need for more data such as that employed by the European Heart Journal study if we are to unravel the full story of this health crisis. According to Transport for London (TfL), around half of the emissions which contribute to dangerously poor air quality in London come from transport. The dangers are easy to overlook because unlike, for example, road collisions, air pollution is by its very nature invisible. Although media coverage of air pollution is often circulated with images of smog-bound cities, the fact is that life-threatening levels of PM2.5 will be just as present on a clear summer’s day.

One encouraging fact in all of this is that data has never been easier to collect, analyse, and share. In an era of big data, we can work to make the invisible visible in more significant ways than ever before, monitoring air quality and health at a hyper-local level and creating the potential for profound conclusions about our urban environments.

Data for change

Data also has another role to play in remedying this situation. As with many industry sectors, data analytics is becoming increasingly embedded in our transportation systems. Through the use of telematics systems which record acceleration, position, engine workload, and other data points, feedback can be given to drivers which leads to long-term behaviour changes to increase efficiency while reducing the impact of burning fossil fuels.

Perhaps more significantly, data also has a key role to play in the truly fundamental shift of moving to fleets composed entirely of electric vehicles. The benefit here is clear: with EVs having zero tailpipe emissions, there is possibly no more significant single action for the improvement of urban air quality. However, EVs also pose problems which fleets must adapt to such as managing battery health, arranging time to recharge in a way which doesn’t interrupt operation, and enhancing infrastructure which meets their needs. These issues are compounded by the inevitable interim period in which EVs, internal combustion engines and hybrid vehicles are all in use.

By providing centralised fleet oversight, telematics can ease this transition. For example, deep insight into usage patterns can identify the most opportune periods at which to charge a particular vehicle in a fleet, while also feeding data into an organisation’s estimates of transit time or helping drivers make effective use of the fleet. Some telematics systems can also provide an EV Suitability assessments to determine which ICE vehicles can be swapped out.

It took decades for the built environment to fully adapt to the internal combustion engine, and a century for us to start to understand the full impact of those vehicles on our health; with intelligent use of data, we have the opportunity to make the next big change with the speed that the severity of the situation demands. With 89% of UK fleets planning to go electric by 2030, now is the time for the industry to educate itself and talk about how best to make that vision a reality.