the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessment of current methane emission quantification techniques for natural gas midstream applications
Yunsong Liu
Jean-Daniel Paris
Gregoire Broquet
Violeta Bescós Roy
Tania Meixus Fernandez
Rasmus Andersen
Andrés Russu Berlanga
Emil Christensen
Yann Courtois
Sebastian Dominok
Corentin Dussenne
Travis Eckert
Andrew Finlayson
Aurora Fernández de la Fuente
Catlin Gunn
Ram Hashmonay
Juliano Grigoleto Hayashi
Jonathan Helmore
Soeren Honsel
Fabrizio Innocenti
Matti Irjala
Torgrim Log
Cristina Lopez
Francisco Cortés Martínez
Jonathan Martinez
Adrien Massardier
Helle Gottschalk Nygaard
Paula Agregan Reboredo
Elodie Rousset
Axel Scherello
Matthias Ulbricht
Damien Weidmann
Oliver Williams
Nigel Yarrow
Murès Zarea
Robert Ziegler
Jean Sciare
Mihalis Vrekoussis
Philippe Bousquet
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We compared near real-time and benchtop XRF spectrometers measuring trace elements in airborne particles across three European cities. Results show filter material dictates accuracy: Teflon yielded strong inter-instrument agreement, while quartz caused systematic attenuation errors for light elements. Because empirical corrections left residual biases, using optimal substrates—preferably Teflon—is essential for accurately tracking pollution sources.
The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.