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Drone Technology enables three times faster Methane Emissions Monitoring in Landfills

Integrated Systems
April 9, 2024

The quest to monitor methane and carbon dioxide emissions from landfills has been revolutionized in recent years, thanks mainly to drone technology. Among growing concerns over greenhouse gas emissions from landfills—major sources of potent greenhouse gases—Maurizio De Molfetta, the UAV Activity Manager at Symbiotica (a University of Bari Aldo Moro spin-off), shares their innovative approach to tracking these emissions. Their work explicitly targets the reduction of landfill methane emissions, highlighting the critical intersection of organic waste management.

Challenge

Symbiotica sets its sights on solid waste landfills, oil & gas plants, and wastewater treatment facilities, confronting the intricate challenge of surveying emissions from these sites. The complexity of landfill surfaces and the sheer volume of greenhouse gas emissions necessitated a shift towards SPH Engineering's drone technology. This move aimed to enhance the accuracy and efficiency of monitoring landfill emissions, including the tons of methane released.

The deployment of drone technology marked a significant leap forward, introducing improvements in speed, safety, precise emissions mapping, and the automation of monitoring processes. For landfill operators and environmental scientists, this means a transformative approach to surveying landfill gas emissions without the risks and limitations of on-ground inspections.

SPH Engineering methane detector solution during the survey.

Solution

Symbiotica uses SkyHub, SPH Engineering onboard computer, integrated with methane detector. The technology allowed them to centralize the management of the acquired data and, simultaneously, allowed them to use different tools parallelly, such as the sensor mentioned above for methane detection and the radar altimeter for terrain following.

Your technology has allowed us to significantly speed up the survey workflow, being more efficient in the field and, at the same time, ensuring reliability and accuracy during surveying, says Maurizio.

Once familiarity with the survey type and the working environment is established, the UAV system becomes a valuable ally. The time required for a methane emissions screening activity varies from site to site. Still, except in special situations,

up to 60 hectares of surface can be probed in a working day. It is an impressive demonstration of the time-saving capabilities of drone-based methane emissions monitoring.

In contrast, the prevailing conventional approach involves a walkover survey employing a Flame Ionization Detector (FID) instrument. This traditional method demands a minimum of three full days of work to achieve coverage and resolution comparable to that of drones. Additionally, the landfill is an emissive body that tends to vary its emission regime over time (there are sometimes variations on an hourly scale), and such a protracted analysis over time risks producing insignificant data.

After screening the surface, it’s time for the next step: data processing.

As far as the software is concerned, our process of validation, purification (cut off, cut in, noise reduction, false positive), and analysis of data use algorithms and automation implemented by us, so we use purely calculation software such as Excel concatenated with GIS software for the spatial transposition of data, interpolation, and analysis of various kinds on a spatial or sometimes temporal scale if we can compare two surveys carried out on the same area, Maurizio shares.

This advancement is crucial, considering landfills are the largest source of methane, a highly potent greenhouse gas. The capability to swiftly monitor emissions from landfills is essential for the waste sector, aiming for substantial emissions reduction and effective management of the waste stream.

Process

Symbiotica conducts monitoring methane emissions in the following way. They start from a cognitive phase of the environment in which they intervene, studying all the details of the intervention ecosystem. Depending on the situation, they proceed to the right system setup. Since they move almost exclusively with automatic flights, the route design phase is fundamental; everything is done through the UgCS flight planning software. This preparation is critical for automated flights that efficiently identify areas with significant methane plumes, enabling subsequent data processing and interpretation phases.

This structured approach emphasizes the importance of Carbon Mapper technology in identifying and analyzing methane emissions from municipal landfills. It exemplifies the integration of advanced technologies for environmental monitoring and the commitment to emissions reduction within the waste sector.

Conclusions

Symbiotica's exploration into drone technology for monitoring landfill emissions heralds a new era in environmental stewardship. The ability to rapidly and safely monitor emissions from landfills, pinpoint methane leaks with high accuracy, and automate the process represents a significant innovation in the field. This technology offers landfill operators a safer, more efficient means to monitor landfill gas emissions. It contributes significantly to the global effort to reduce greenhouse gas emissions from the waste sector.

The positive correlation between drone-collected data and traditional methods, observed over five years of Symbiotica's research, underscores the reliability of drone technology in environmental monitoring. Maurizio's insights, supported by data samples and visual documentation, demonstrate the impact of drone technology in reducing emissions from landfills, thereby managing the environmental impact of organic waste and the broader waste stream more effectively.

This case study illuminates the critical role of technologies like Carbon Mapper in advancing the waste sector's capabilities for environmental monitoring and emissions reduction. It highlights the growing imperative for innovative solutions to manage landfill emissions and contribute to a sustainable future.

An excerpt of the drone survey results in a landfill identifying the emission points found. There was no interpolation in this case, so it’s possible to see how the exact emission points were identified.
Emissive areas obtained by short-range interpolation of the detected emission points. Several emission points in a small area indicate how that area can be defined as emissive. As shown in the screenshot, the result is not about a single emission point found, such as a badly closed biogas well, but an area with widespread emission.
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