COVER STORY: GRANDPERSPECTIVE GMBH
Data-driven continuous monitoring
But let’ s now focus on the wider benefits of greatly enhanced visibility and how it can transform process safety and risk management programmes. I have already demonstrated the importance of sensor technology that offers multi-compound, wide-site coverage at low detection limits. But for HSEQ Managers like Peter Schmitz, and his team of highly skilled professionals he manages, it is only one piece of the puzzle. Talk to them and they’ ll tell you that world-class HSE programmes are premised on not what just is happening in the present, but what also might happen in the future and the advance preparations that must be made to mitigate it. The only way you can achieve a full and comprehensive process safety picture is through data-centric continuous monitoring.
What do I mean by this? Well, let ' s first look at an average chemical or petrochemical plant. Having worked in the sector over twenty years, I have visited many facilities. Most plants still use legacy sensor systems which coupled with quarterly inspections, do not provide blanket coverage.
Process safety teams at Fibrant, and the other five chemical companies covered by Grandperspective at Chemelot, use six sensors, each of which collects one million spectra a day. This means that every year Chemelot receives close to 33 terabytes( TB) of data, which is 33, 000, 000, 000, 000 bytes. To put that number in perspective, that is the equivalent of 33 million high resolution images, over two and half years of video, 11 million songs, or 12 million ebooks.
Each spectrum has hundreds of usable data points. In addition, the sensors provide video images, precise azimuth and elevation angles, humidity, temperature and wind information.
When this rich dataset is entered into generative AI models, it can provide a total emission picture, which can improve safety guidelines and processes. This is because it enables process safety teams to carry out data-driven post-event analysis, which is largely unprecedented due to the vast majority of plants choosing to keep conventional monitoring in place.
In doing so, they can ' t revisit the events that led to an incident and cannot therefore learn what caused it. But facilities with real-time monitoring capability, can gauge what happened, when, where and how. They can then communicate that feedback to frontline engineering staff, and feed any learnings back into their processes, which generates continuous improvement. But, most importantly, the data derived from real-time monitoring allows process safety teams to identify potential emission patterns, which may not be evident using sensor technology and periodic manual LDAR campaigns. That’ s because these campaigns, even if they are partly data-centric, won ' t provide a full picture that clearly tracks emissions against the set safety thresholds.
The views and opinions expressed in this article are those of the profiled company and may not reflect the position of Fugitive Emissions Journal.
Why the digital twin can flourish with datadriven continuous monitoring
In the future, some process safety teams will use AI-built data models to create sophisticated digital shadows or digitals twins. By feeding the Digital Shadow with continuous emission data, safety teams will be able to gain a much clearer understanding of the emission landscape as the digital shadow becomes a 3D virtual representation of the plant. This will allow them to carry out much more detailed monitoring, predictive analysis and decision-making.
How would a digital twin add value? Imagine that a ground-based remote sensing system detects a smallscale leak at a pump sealing. The true power of a digital twin is that it gives engineers the ability to feed hundreds of terabytes of data into the system to simulate the future health of the surrounding pipe network. The simulation could predict further vulnerabilities, allowing the team to proactively replace weak sections of pipework before they lead to more serious failures.
Indeed, this combination of remote sensing and digital twin technology will re-define predictive maintenance, enable data-driven decision-making that reduces downtime, enhance safety, and improve long-term asset integrity.
While it may take some time for the industry to inculcate cutting edge technology like digital twins into their process safety programmes, they, along with state-of-the-art continuous monitoring remote sensing technology, shows what can be achieved when pioneering HSEQ teams think out of the box.
I believe advanced monitoring is the direction of travel that the industry is moving in – particularly in multi-compound environments. It will not only enrich their HSE and risk management processes, but, if used correctly, will greatly enhance safety both behind and beyond the fence line. At Grandperspective, we are incredibly proud to play a role in helping chemical and petrochemical plants formulate and deliver even more robust and effective safety cultures.
ABOUT THE AUTHOR
Peter Maas is Chief Executive Officer of Grandperspective GmbH, a Berlin-based company he co-founded with Rene Braun in November 2018. Grandperspective provides next-generation remote monitoring solutions for gas detection.
Before co-creating Grandperspective, Peter worked for Bruker Optic as its Global Application Manager for Remote Sensing and Gas Analytics.
Peter studied at the prestigious Hamburg University of Technology, where he completed a Master’ s degree in mechatronics, robotics and automation technology.
APRIL 2025 • FUGITIVE EMISSIONS JOURNAL 9