Interactive chemistry in the Laboratoire de Météorologie Dynamique general circulation model: model description and impact analysis of biogenic hydrocarbons on tropospheric chemistry

We present a description and evaluation of LMDz-INCA, a global three-dimensional chemistry-climate model, pertaining to its recently developed NMHC version. In this substantially extended version of the model a comprehensive representation of the photochemistry of non-methane hydrocarbons (NMHC) and volatile organic compounds (VOC) from biogenic, anthropogenic, and biomass-burning sources has been included. The tropospheric annual mean methane (9.2 years) and methylchloroform (5.5 years) chemical lifetimes are well within the range of previous modelling studies and are in excellent agreement with estimates established by means of global observations. The model provides a reasonable simulation of the horizontal and vertical distribution and seasonal cycle of CO and key non-methane VOC, such as acetone, methanol, and formaldehyde as compared to observational data from several ground stations and aircraft campaigns. LMDz-INCA in the NMHC version reproduces tropospheric ozone concentrations fairly well throughout most of the troposphere. The model is applied in several sensitivity studies of the biosphere-atmosphere photochemical feedback. The impact of surface emissions of isoprene, acetone, and methanol is studied. These experiments show a substantial impact of isoprene on tropospheric ozone and carbon monoxide concentrations revealing an increase in surface O₃ and CO levels of up to 30 ppbv and 60 ppbv, respectively. Isoprene also appears to significantly impact the global OH distribution resulting in a decrease of the global mean tropospheric OH concentration by approximately 0.7×10⁵ molecules cm^-3 or roughly 8% and an increase in the global mean tropospheric methane lifetime by approximately seven months. A global mean ozone net radiative forcing due to the isoprene induced increase in the tropospheric ozone burden of 0.09 W m^-2 is found. The key role of isoprene photooxidation in the global tropospheric redistribution of NO_x is demonstrated. LMDz-INCA calculates an increase of PAN surface mixing ratios ranging from 75 to 750 pptv and 10 to 250 pptv during northern hemispheric summer and winter, respectively. Acetone and methanol are found to play a significant role in the upper troposphere/lower stratosphere (UT/LS) budget of peroxy radicals. Calculations with LMDz-INCA show an increase in HO_x concentrations region of 8 to 15% and 10 to 15% due to methanol and acetone biogenic surface emissions, respectively. The model has been used to estimate the global tropospheric CO budget. A global CO source of 3019 Tg CO yr^-1 is estimated. This source divides into a primary source of 1533 Tg CO yr^-1 and secondary source of 1489 Tg CO yr^-1 deriving from VOC photooxidation. Global VOC-to-CO conversion efficiencies of 90% for methane and between 20 and 45% for individual VOC are calculated by LMDz-INCA

Large-scale gene-centric analysis identifies novel variants for coronary artery disease

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ~2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p&lt;10-33; LPA:p&lt;10-19; 1p13.3:p&lt;10-17) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p&lt;5×10-7). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06-1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ~4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes.</p

A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk

Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases that may not be apparent from genome-wide association studies alone. Recent advances in rat genomics are facilitating systems-genetics approaches. Here we report the use of integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)-driven inflammatory network (IDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and which was regulated in multiple tissues by a locus on rat chromosome 15q25. We show that Epstein-Barr virus induced gene 2 (Ebi2, also known as Gpr183), which lies at this locus and controls B lymphocyte migration, is expressed in macrophages and regulates the IDIN. The human orthologous locus on chromosome 13q32 controlled the human equivalent of the IDIN, which was conserved in monocytes. IDIN genes were more likely to associate with susceptibility to type 1 diabetes (T1D)-a macrophage-associated autoimmune disease-than randomly selected immune response genes (P = 8.85 x 10(-6)). The human locus controlling the IDIN was associated with the risk of T1D at single nucleotide polymorphism rs9585056 (P = 7.0 x 10(-10); odds ratio, 1.15), which was one of five single nucleotide polymorphisms in this region associated with EBI2 (GPR183) expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D

Large-scale gene-centric analysis identifies novel variants for coronary Artery disease

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ∼2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10−33; LPA:p<10−19; 1p13.3:p<10−17) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10−7). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06–1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ∼4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes

EVEREST: A design environment for extreme-scale big data analytics on heterogeneous platforms

High-Performance Big Data Analytics (HPDA) applications are characterized by huge volumes of distributed and heterogeneous data that require efficient computation for knowledge extraction and decision making. Designers are moving towards a tight integration of computing systems combining HPC, Cloud, and IoT solutions with artificial intelligence (AI). Matching the application and data requirements with the characteristics of the underlying hardware is a key element to improve the predictions thanks to high performance and better use of resources. We present EVEREST, a novel H2020 project started on October 1, 2020, that aims at developing a holistic environment for the co-design of HPDA applications on heterogeneous, distributed, and secure platforms. EVEREST focuses on programmability issues through a data-driven design approach, the use of hardware-accelerated AI, and an efficient runtime monitoring with virtualization support. In the different stages, EVEREST combines state-of-the-art programming models, emerging communication standards, and novel domain-specific extensions. We describe the EVEREST approach and the use cases that drive our research

CityDelta: A Model Intercomparison Study to Explore the Impact of Emission Reductions in European Cities in 2010

This paper gives an overview of the set up, methodology and the obtained results of the CityDelta (phase 1 and 2) project. In the context of the Clean Air For Europe programme of the European Commission, the CityDelta project was designed to evaluate the impact of emission-reduction strategies on air quality at the European continental scale and in European cities. Ozone and PM are the main components that have been studied. To achieve this goal, a model intercomparison study was organised with the participation of more than 20 modelling groups with a large number of modelling configurations. Two following main topics can be identified in the project. First, in order to evaluate their strengths and weaknesses, the participating models were evaluated against observations in a control year (1999). An accompanying paper will discusses in detail this evaluation aspect for 4 European cities. The second topic is the actual evaluation of the impact of emission reductions on levels of Ozone and PM, with particular attention to the differences between large-scale and fine-scale models. An accompanying paper will discuss this point in detail. In this overview paper the main input to the intercomparison is described as well as the use of the ensemble approach. Finally, attention is given to the policy relevant issue on how to implement the urban air quality signal into large scale air quality models through the use of functional relationships.JRC.F.8-Sustainable Transpor