The role of amino acids in the nitrogen cycle of peatlands

Future release of carbon from peatlands in response to climate change may be impacted by nitrogen limitation. The current study considers the role of amino acids as a nitrogen source in peatlands. The total free amino acid (TFAA) concentration for peats ranged from 0-2.3 µM, and leucine was the primary contributor. The dominance of sedge or ericaceous shrub plant types did not significantly impact the TFAA pool. Ammonium concentrations were much greater than TFAA and nitrate concentrations. TFAA concentrations were greatest in spring and least in fall. The springtime maxima and summer decrease in concentrations were simulated in a modeling study; however, the model over predicted concentrations. The model was shown to be sensitive to microbial process rates which is likely contributing to model uncertainty. Amino acids may still be considered an important nitrogen source even at low concentrations, and further research on peatland amino acid cycling is needed

Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area

China's anthropogenic methane emissions are the largest of any country in the world. A recent study using atmospheric observations suggested that recent policies aimed at reducing emissions of methane due to coal production in China after 2010 had been largely ineffective. Here, based on a longer observational record and an updated modelling approach, we find a statistically significant positive linear trend (0.36 &plusmn; 0.04 () Tg CH4 yr&minus;2) in China's methane emissions for 2010&ndash;2017. This trend was slowing down at a statistically significant rate of -0.1 &plusmn; 0.04 Tg CH4 yr&minus;3. We find that this decrease in growth rate can in part be attributed to a decline in China's coal production. However, coal mine methane emissions have not declined as rapidly as production, implying that there may be substantial fugitive emissions from abandoned coal mines that have previously been overlooked. We also find that emissions over rice-growing and aquaculture-farming regions show a positive trend (0.13 &plusmn; 0.05 Tg CH4 yr&minus;2 for 2010&ndash;2017) despite reports of shrinking rice paddy areas, implying potentially significant emissions from new aquaculture activities, which are thought to be primarily located on converted rice paddies. &nbsp;</p

Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area

China’s anthropogenic methane emissions are the largest of any country in the world. A recent study using atmospheric observations suggested that recent policies aimed at reducing emissions of methane due to coal production in China after 2010 had been largely ineffective. Here, based on a longer observational record and an updated modelling approach, we find a statistically significant positive linear trend (0.36 ± 0.04 ( $\pm1\sigma$ ) Tg CH _4 yr ^−2 ) in China’s methane emissions for 2010–2017. This trend was slowing down at a statistically significant rate of -0.1 ± 0.04 Tg CH _4 yr ^−3 . We find that this decrease in growth rate can in part be attributed to a decline in China’s coal production. However, coal mine methane emissions have not declined as rapidly as production, implying that there may be substantial fugitive emissions from abandoned coal mines that have previously been overlooked. We also find that emissions over rice-growing and aquaculture-farming regions show a positive trend (0.13 ± 0.05 Tg CH _4 yr ^−2 for 2010–2017) despite reports of shrinking rice paddy areas, implying potentially significant emissions from new aquaculture activities, which are thought to be primarily located on converted rice paddies

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition

Global high-resolution observations of atmospheric composition from satellites can greatly improve our understanding of surface emissions through inverse analyses. Variational inverse methods can optimize surface emissions at any resolution but do not readily quantify the error and information content of the posterior solution. The information content of satellite data may be much lower than its coverage would suggest because of failed retrievals, instrument noise, and error correlations that propagate through the inversion. Analytical solution of the inverse problem provides closed-form characterization of posterior error statistics and information content but requires the construction of the Jacobian matrix that relates emissions to atmospheric concentrations. Building the Jacobian matrix is computationally expensive at high resolution because it involves perturbing each emission element, typically individual grid cells, in the atmospheric transport model used as the forward model for the inversion. We propose and analyze two methods, reduced dimension and reduced rank, to construct the Jacobian matrix at greatly decreased computational cost while retaining information content. Both methods are two-step iterative procedures that begin from an initial native-resolution estimate of the Jacobian matrix constructed at no computational cost by assuming that atmospheric concentrations are most sensitive to local emissions. The reduced-dimension method uses this estimate to construct a Jacobian matrix on a multiscale grid that maintains a high resolution in areas with high information content and aggregates grid cells elsewhere. The reduced-rank method constructs the Jacobian matrix at native resolution by perturbing the leading patterns of information content given by the initial estimate. We demonstrate both methods in an analytical Bayesian inversion of Greenhouse Gases Observing Satellite (GOSAT) methane data with augmented information content over North America in July 2009. We show that both methods reproduce the results of the native-resolution inversion while achieving a factor of 4 improvement in computational performance. The reduced-dimension method produces an exact solution at a lower spatial resolution, while the reduced-rank method solves the inversion at native resolution in areas of high information content and defaults to the prior estimate elsewhere

Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations

Atmospheric methane mixing ratio rose by 15 ppbv between 2019 and 2020, the fastest growth rate on record. We conduct a global inverse analysis of 2019–2020 Greenhouse Gases Observing Satellite observations of atmospheric methane to analyze the combination of sources and sinks driving this surge. The imbalance between sources and sinks of atmospheric methane increased by 31 Tg a ^−1 from 2019 to 2020, representing a 36 Tg a ^−1 forcing (direct changes in methane emissions and OH concentrations) on the methane budget away from steady state. 86% of the forcing in the base inversion is from increasing emissions (82 ± 18% in the nine-member inversion ensemble), and only 14% is from decrease in tropospheric OH. Half of the increase in emissions is from Africa (15 Tg a ^−1 ) and appears to be driven by wetland inundation. There is also a large relative increase in emissions from Canada and Alaska (4.8 Tg a ^−1 , 24%) that could be driven by temperature sensitivity of boreal wetland emissions

National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations

Abstract Reducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a−1 for oil-gas and 32.7 ± 5.2 Tg a−1 for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a−1 or 18%

Replication Data for: Satellite discovery of anomalously large methane point sources from oil/gas production

GHGSat-D methane data for: Satellite discovery of anomalously large methane point sources from oil/gas production, Figure 1. The data are stored as Python Numpy .npy files