A L I A G R I D
Working Process

If you know, you can do it.

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Satellite CH4 emission data

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Proprietary IoT sensors for city gates and decompression stations

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One integrated solution Manager

80-140
Mt
estimated emissions on natural gas value chain
90
%
up to site-level measurements
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Included Capabilities

Features designed for you

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Sensors

Designed for continuous monitoring of methane emissions:

  • Low power: battery life exceeding 12 months
  • Low cost: proprietary technology that scales costs
  • ATEX proof: installable everywhere
  • Modular design: it can integrate other measurements like intrusions, maintenance using AI-on-edge algorithms
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Platform

Integrate all the information in a user friendly interface:

  • Manage emissions results and actions to reduce them
  • Report the complete set of information according to OGMP2.0
  • Easily integrate through API with existent architecture
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Satellites images

Integrate open-source data collected by satellites:

  • Map methane emissions using proprietary algorithms at scale
  • Reconciliate measurements and satellite data
  • Classify emissions coming from fossils
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Digital twin

Run-time calculation for transportation and distribution grids:

  • Evaluate expected states for the grid
  • Classify malfunctions
  • Extends measurements to the whole grid
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Proprietary design for a low-cost,
low-power methane emissions sensor

  • Installable everywhere thanks to ATEX certification

  • Modular design that can integrate multiple measurements

Frequently asked questions from our users

ch4eco integrates site-level measurements to top-down measurements to give you an overall size with high accuracy

ch4eco functionalities can be integrated through API to your current architecture. Contact us to have access to the complete API documentation.

ch4eco has been tested with third parties blind tests and results will be disclosed soon in a white paper. Contact us for further information.

Create with a click your OGMP2.0 report

Ch4eco automatically integrates measurements coming from all the sensors placed on equipments and reconciliate them with top-down estimations. The results are easily displayed in a report according to OGMP2.0 framework from UNEP.

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