African rice cultivation linked to rising methane

Africa has been identified as a major driver of the current rise in atmospheric methane, and this has been attributed to emissions from wetlands and livestock. Here we show that rapidly increasing rice cultivation is another important source, and estimate that it accounts for 7% of the current global rise in methane emissions. Continued rice expansion to feed a rapidly growing population should be considered in climate change mitigation goals. More detail in Nature Climate Change (2024).

Satellite quantification of methane emissions and oil/gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action

We show that oil/gas methane emissions for individual countries are not related to production, invalidating a basic premise in the construction of activity-based bottom-up inventories. Instead, local infrastructure and management practices appear to be key drivers of oil/gas emissions, emphasizing the need for including top-down information from atmospheric observations in the construction of oil/gas emission inventories. We examined the methane intensity, defined as the upstream oil/gas emission per unit of methane gas produced, as a measure of the potential for decreasing emissions from the oil/gas sector, and using as reference the 0.2% target set by industry. We find that the methane intensity in most countries is considerably higher than this target, reflecting leaky infrastructure combined with deliberate venting or incomplete flaring of gas. However, we also find that Kuwait, Saudi Arabia, and Qatar meet the industry target and thus show that the target is achievable through capture of associated gas, modern infrastructure, and concentration of operations. More detail in ACP (2023).

Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations

We quantify methane emissions in China and the contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. Emissions are optimized with a Gaussian mixture model (GMM) at up to 0.25o×0.3125o resolution. The optimization is done analytically assuming lognormally distributed errors on prior emissions. We are in particular better able to separate coal and rice emissions. Our higher livestock emissions are attributed largely to northern China where GOSAT has little sensitivity. Gas emissions in China are mostly from distribution, in part because of low emission factors from production and in part because 42% of the gas is imported. Our estimate of emissions per unit of domestic gas production indicates a low life-cycle loss rate of 1.7 (1.3-1.9) %, which would imply net climate benefits from the current coal-to-gas energy transition in China. However, this small loss rate is somewhat misleading considering China’s high gas imports, including from Turkmenistan where emission per unit of gas production is very high. More detail in ACP (2022)!

Five years of variability in the global carbon cycle: comparing an estimate from the Orbiting Carbon Observatory-2 and process-based models

Year-to-year variability in CO2 fluxes can yield insight into climate-carbon cycle relationships, a fundamental yet uncertain aspect of the terrestrial carbon cycle. In this study, we use global observations from NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite for years 2015–2019 and a geostatistical inverse model to evaluate 5 years of interannual variability (IAV) in CO2 fluxes and its relationships with environmental drivers. OCO-2 launched in late 2014, and we specifically evaluate IAV during the time period when OCO-2 observations are available. We then compare inferences from OCO-2 with state-of-the-art process-based models (terrestrial biosphere model, TBMs). Results from OCO-2 suggest that the tropical grasslands biome (including grasslands, savanna, and agricultural lands within the tropics) makes contributions to global IAV during the 5 year study period that are comparable to tropical forests, a result that differs from a majority of TBMs. Overall, the findings of this study highlight large uncertainties in process-based estimates of IAV during recent years and provide an avenue for evaluating these processes against inferences from OCO-2. More results in ERL (2021) .

Linking global terrestrial CO2 fluxes and environmental drivers: inferences from the Orbiting Carbon Observatory 2 satellite and terrestrial biospheric models

Observations from the Orbiting Carbon Observatory 2 (OCO-2) satellite have been used to estimate CO2 fluxes in many regions of the globe and provide new insight into the global carbon cycle. We point to the limitations of current space-based observations for inferring environmental relationships but also indicate the potential to help inform key relationships that are very uncertain in state-of-the-art TBMs. Read more in ACP (2021).