Characterising the distribution of methane and carbon dioxide emissions from the natural gas supply chain

Methane and CO2 emissions from the natural gas supply chain have been shown to vary widely but there is little understanding about the distribution of emissions across supply chain routes, processes, regions and operational practises. This study defines the distribution of total methane and CO2 emissions from the natural gas supply chain, identifying the contribution from each stage and quantifying the effect of key parameters on emissions. The study uses recent high-resolution emissions measurements with estimates of parameter distributions to build a probabilistic emissions model for a variety of technological supply chain scenarios. The distribution of emissions resembles a log-log-logistic distribution for most supply chain scenarios, indicating an extremely heavy tailed skew: median estimates which represent typical facilities are modest at 18 – 24 g CO2 eq./ MJ HHV, but mean estimates which account for the heavy tail are 22 – 107 g CO2 eq./ MJ HHV. To place these values into context, emissions associated with natural gas combustion (e.g. for heat) are approximately 55 g CO2/ MJ HHV. Thus, some supply chain scenarios are major contributors to total greenhouse gas emissions from natural gas. For methane-only emissions, median estimates are 0.8 – 2.2% of total methane production, with mean emissions of 1.6 - 5.5%. The heavy tail distribution is the signature of the disproportionately large emitting equipment known as super-emitters, which appear at all stages of the supply chain. The study analyses the impact of different technological options and identifies a set of best technological option (BTO) scenarios. This suggests that emissions-minimising technology can reduce supply chain emissions significantly, with this study estimating median emissions of 0.9% of production. However, even with the emissions-minimising technologies, evidence suggests that the influence of the super-emitters remains. Therefore, emissions-minimising technology is only part of the solution: reducing the impact of super emitters requires more effective detection and rectification, as well as pre-emptive maintenance processes

Disrupted in schizophrenia 1 and synaptic function in the mammalian central nervous system

This is the final version of the article. Available from the publisher via the DOI in this record.The disrupted in schizophrenia 1 (DISC1) gene is found at the breakpoint of an inherited chromosomal translocation, and segregates with major mental illnesses. Its potential role in central nervous system (CNS) malfunction has triggered intensive investigation of the biological roles played by DISC1, with the hope that this may shed new light on the pathobiology of psychiatric disease. Such work has ranged from investigations of animal behavior to detailed molecular-level analysis of the assemblies that DISC1 forms with other proteins. Here, we discuss the evidence for a role of DISC1 in synaptic function in the mammalian CNS.M. Kurihara was supported by a Medical Research Council Industrial collaborative studentship in collaboration with Pfizer, who also supported aspects of DISC1-related work in A. D. Randall’s laborator

Assessing the impact of future greenhouse gas emissions from natural gas production

Greenhouse gases (GHGs) produced by the extraction of natural gas are an important contributor to lifecycle emissions and account for a significant fraction of anthropogenic methane emissions in the USA. The timing as well as the magnitude of these emissions matters, as the short term climate warming impact of methane is up to 120 times that of CO 2 . This study uses estimates of CO 2 and methane emissions associated with different upstream operations to build a deterministic model of GHG emissions from conventional and unconventional gas fields as a function of time. By combining these emissions with a dynamic, techno-economic model of gas supply we assess their potential impact on the value of different types of project and identify stranded resources in various carbon price scenarios. We focus in particular on the effects of different emission metrics for methane, using the global warming potential (GWP) and the global temperature potential (GTP), with both fixed 20-year and 100-year CO 2 -equivalent values and in a time-dependent way based on a target year for climate stabilisation. We report a strong time dependence of emissions over the lifecycle of a typical field, and find that bringing forward the stabilisation year dramatically increases the importance of the methane contribution to these emissions. Using a commercial database of the remaining reserves of individual projects, we use our model to quantify future emissions resulting from the extraction of current US non-associated reserves. A carbon price of at least 400 USD/tonne CO 2 is effective in reducing cumulative GHGs by 30–60%, indicating that decarbonising the upstream component of the natural gas supply chain is achievable using carbon prices similar to those needed to decarbonise the energy system as a whole. Surprisingly, for large carbon prices, the choice of emission metric does not have a significant impact on cumulative emissions

Impact of drilling costs on the US gas industry: prospects for automation

Recent low gas prices have greatly increased pressure on drilling companies to reduce costs and increase efficiency. Field trials have shown that implementing automation can dramatically reduce drilling costs by reducing the time required to drill wells. This study uses the DYNamic upstreAm gAs MOdel (DYNAAMO), a new techno-economic, bottom-up model of natural gas supply, to quantitatively assess the economic impact of lower drilling costs on the US upstream gas industry. A sensitivity analysis of three key economic indicators is presented, with results quoted for the most common field types currently producing, including unconventional and offshore gas. While all operating environments show increased profitability from drilling automation, it is found that conventional onshore reserves can benefit to the greatest extent. For large gas fields, a 50% reduction in drilling costs is found to reduce initial project breakevens by up to 17 million USD per billion cubic metres (MUSD/BCM) and mid-plateau breakevens by up to 8 MUSD/BCM. In this same scenario, additional volumes of around 160 BCM of unconventional gas are shown to become commercial due to both the lower costs of additional production wells in mature fields and the viability of developing new resources held in smaller fields. The capital efficiency of onshore projects increases by 50%-100%, with initial project net present value (NPV) gains of up to 32%

Exploring research institutes: Structures, functioning and typology

Research institutes play an important role as part of the innovation landscape, which includes industrial, academic and governmental organisations. Although there is often much confusion over what constitutes an institute and there can even be a number of different terms associated with such organisational forms, including centres, networks, programmes and laboratories. Indeed institutes can enable multidisciplinary research and the translation of knowledge generated to deliver societal benefits and address industrial requirements. However, despite the benefits offered by establishing research institutes, there has been a distinct lack of studies in this area. Therefore, this paper provides the findings from an initial research study into the structure, functioning and typology of institutes. Following a literature review on institutes, a benchmarking study involving examination of 25 research institutes associated with the energy sector has been carried out. This study identified key features of the institutes, in regard to the research area, technology readiness level, funding, partners, organisational structure, leadership and governance arrangements. Subsequent analysis of these findings has resulted in three main types of institute being identified. The pros and cons for each institute type are provided along with recommendations on the development and management of research institutes

Effects of melting, subduction-related metasomatism, and sub-solidus equilibration on the distribution of water contents in the mantle beneath the Rio Grande Rift

The distribution of water in the upper mantle plays a crucial role in the Earth's deep water cycle, magmatism, and plate tectonics. To better constrain how these large-scale geochemical systems operate, peridotite and pyroxenite mantle xenoliths from Kilbourne Hole (KH) and Rio Puerco (RP) along the Rio Grande Rift (NM, USA) were analyzed for water, and major and trace element contents. These xenoliths sample a lithosphere whose composition was influenced by subduction and rifting, and can be used to examine the effects of melting, metasomatism, and sub-solidus equilibration on the behavior of water. The first result is that in KH xenoliths, olivines underwent negligible H loss during xenolith ascent, i.e. preserved their mantle water contents. These olivine water contents are used to calculate mantle viscosities of 0.5–184 · 1021 Pa·s. These viscosity values are more than 40 times higher than those of the asthenosphere and show that KH peridotites represent samples from the lithosphere. The preservation of olivine water contents is exceptional for off-cratonic xenoliths, and the KH peridotites provide the first estimate of the average concentration of water in Phanerozoic continental mantle lithosphere at 81 ± 30 ppm H2O. The mantle lithosphere beneath the Rio Grande rift is nevertheless heterogeneous with water contents ranging from <0.5 to 120 ppm H2O in peridotites and from 227 to 400 ppm H2O in pyroxenites. A composite KH xenolith of a harzburgite cross-cut by a clinopyroxenite vein shows this heterogeneity at the cm scale. The second contribution of this study stems from the majority of the KH peridotites and two of the RP peridotites having major and trace elements that can be explained by partial melting without any need to invoke metasomatic processes. This allows to show that, prior to modelling the water content variation of each peridotite mineral during melting, a correction for sub-solidus equilibration has to be applied to the water contents of the minerals. Sub-solidus equilibration also provides an explanation for the discrepancy between the clinopyroxene/orthopyroxene ratio of water contents in natural peridotites worldwide and in laboratory experiments on water partitioning in peridotite minerals. Finally, the cryptically metasomatized peridotites, rare at KH and abundant at RP, as well as the pyroxenites, permit to decipher the origin and water contents of the metasomatic melts that affected the continental lithosphere beneath the Rio Grande Rift. Trace element modelling of the metasomatized KH and RP peridotites are consistent with metasomatism via melts that are of subduction origin. Melts in equilibrium with peridotites contain more water at RP (∼1 wt.% H2O) than at KH (∼0.5 wt.% H2O), although this did not result in a more water-rich mantle lithosphere at RP. Rio Puerco lies within the northern Rio Grande rift, proposed to have been affected by a flat slab subduction, which may explain the more hydrous and extensive metasomatism compared to the south, where KH is located

The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity

The Developing Human Connectome Project (dHCP) is an Open Science project which provides the first large sample of neonatal functional MRI (fMRI) data with high temporal and spatial resolution. This data enables mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organisation in humans. Here, we characterise in unprecedented detail the maturation and integrity of resting-state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis (ICA) to define 11 RSNs in term-born infants scanned at 43.5-44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37-43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder which occur frequently in preterm children. Overall, we find a robust, modular, symmetrical functional brain organisation at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher-order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Development of microstructural and morphological cortical profiles in the neonatal brain

Interruptions to neurodevelopment during the perinatal period may have long-lasting consequences. However, to be able to investigate deviations in the foundation of proper connectivity and functional circuits, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a cohort of 241 term-born infants, we used magnetic resonance imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37-44 weeks postmenstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (morphometric similarity networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory-motor, limbic, and association regions, and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior regions became more morphometrically similar with increasing age, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with age: Within-network similarity increased over age suggesting emerging network distinction. These changes in cortical network architecture over an 8-week period are consistent with, and likely underpin, the highly dynamic processes occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development