Methane: a driver of current climate change

We use satellite observations of atmospheric methane from the TROPOMI instrument to estimate total annual methane emissions for 2019–2023 from four large Southeast US landfills with gas collection and control systems. The emissions are on average 6× higher than the values reported by the landfills to the US Greenhouse Gas Reporting Program (GHGRP) which are used by the US Environmental Protection Agency for its national Greenhouse Gas Inventory (GHGI). We find increasing emissions over the 2019–2023 period whereas the GHGRP reports a decrease. The GHGRP requires gas-collecting landfills to estimate their annual emissions either with a recovery-first model (estimating emissions as a function of methane recovered) or a generation-first model (estimating emissions from a first-order decay applied to waste-in-place). All four landfills choose to use the recovery-first model, which yields emissions that are one-quarter of those from the generation-first model and decreasing over 2019–2023, in contrast with the TROPOMI observations. Our TROPOMI estimates for two of the landfills agree with the generation-first model, with increasing emissions over 2019–2023 due to increasing waste-in-place or decreasing methane recovery, and are still higher than the generation-first model for the other two landfills. Further examination of the GHGRP emissions from all reporting landfills in the US shows that the 19% decrease in landfill emissions reported by the GHGI over 2005–2022 reflects an increasing preference for the recovery-first model by the reporting landfills, rather than an actual emission decrease. The generation-first model would imply an increase in landfill emissions over 2013–2022, and this is more consistent with atmospheric observations.

Monitoring methane (CH₄) emissions from terrestrial ecosystems is essential for assessing the relative contributions of natural and anthropogenic factors leading to climate change and shaping global climate goals. Fires are a significant source of atmospheric CH₄, with the increasing frequency of megafires amplifying their impact. Global fire emissions exhibit large spatiotemporal variations, making the magnitude and dynamics difficult to characterize accurately. In this study, we reconstruct global fire CH₄ emissions by integrating satellite carbon monoxide (CO)-based atmospheric inversion with well-constrained fire CH₄ to CO emission ratio maps. Here we show that global fire CH₄ emissions averaged 24.0 (17.7–30.4) Tg yr^‑1 from 2003 to 2020, approximately 27% higher (equivalent to 5.1 Tg yr^‑1) than average estimates from four widely used fire emission models. This discrepancy likely stems from undetected small fires and underrepresented emission intensities in coarse-resolution data. Our study highlights the value of atmospheric inversion based on fire tracers like CO to track fire-carbon-climate feedback.

This study presents a comprehensive investigation of Methane (CH₄) emissions in the wetlands of South Sudan, employing an integrated approach that combines TROPOMI satellite data, river altimetry, and hydrological model outputs. TROPOMI data show a strong increase in CH₄ concentrations over the Sudd wetlands from 2018 to 2022. We quantify CH₄ emissions using these data. We find a twofold emission increase from 2018 to 2019 (9.2 ± 2.4 Tg yr^‑1) to 2020 to 2022 (16.3 ± 3.3 Tg yr^‑1). River altimetry data analysis elucidates the interconnected dynamics of river systems and CH₄ emissions. We identify correlations and temporal alignments across South Sudan wetlands catchments. Our findings indicate a clear signature of ENSO driving the wetland dynamics and CH₄ emissions in the Sudd by altering precipitation patterns, hydrology, and temperature, leading to variations in anaerobic conditions conducive to CH₄ production. Significant correlations are found between CH₄ emissions and PCR-GLOBWB-simulated soil moisture dynamics, groundwater recharge, and surface water parameters within specific catchments, underscoring the importance of these parameters on the catchment scale. Lagged correlations were found between hydrological parameters and CH₄ emissions, particularly with PCR-GLOBWB-simulated capillary rise. These correlations shed light on the temporal dynamics of this poorly studied and quantified source of CH₄. Our findings contribute to the current knowledge of wetland CH₄ emissions and highlight the urgency of addressing the complex interplay between hydrology and carbon dynamics in these ecosystems that play a critical role in the global CH₄ budget.