Developing social capital in implementing a complex intervention: a process evaluation of the early implementation of a suicide prevention intervention in four European countries

<p>Background: Variation in the implementation of complex multilevel interventions can impact on their delivery and outcomes. Few suicide prevention interventions, especially multilevel interventions, have included evaluation of both the process of implementation as well as outcomes. Such evaluation is essential for the replication of interventions, for interpreting and understanding outcomes, and for improving implementation science. This paper reports on a process evaluation of the early implementation stage of an optimised suicide prevention programme (OSPI-Europe) implemented in four European countries.</p> <p>Methods: The process analysis was conducted within the framework of a realist evaluation methodology, and involved case studies of the process of implementation in four European countries. Datasets include: repeated questionnaires to track progress of implementation including delivery of individual activities and their intensity; serial interviews and focus groups with stakeholder groups; and detailed observations at OSPI implementation team meetings.</p> <p>Results: Analysis of local contexts in each of the four countries revealed that the advisory group was a key mechanism that had a substantial impact on the ease of implementation of OSPI interventions, particularly on their ability to recruit to training interventions. However, simply recruiting representatives of key organisations into an advisory group is not sufficient to achieve impact on the delivery of interventions. In order to maximise the potential of high level ‘gatekeepers’, it is necessary to first transform them into OSPI stakeholders. Motivations for OSPI participation as a stakeholder included: personal affinity with the shared goals and target groups within OSPI; the complementary and participatory nature of OSPI that adds value to pre-existing suicide prevention initiatives; and reciprocal reward for participants through access to the extended network capacity that organisations could accrue for themselves and their organisations from participation in OSPI.</p> <p>Conclusions: Exploring the role of advisory groups and the meaning of participation for these participants revealed some key areas for best practice in implementation: careful planning of the composition of the advisory group to access target groups; the importance of establishing common goals; the importance of acknowledging and complementing existing experience and activity; and facilitating an equivalence of benefit from network participation.</p&gt

Benefits of net-zero policies for future ozone pollution in China

Net-zero emission policies principally target climate change but may have a profound influence on surface ozone pollution. To investigate this, we use a chemistry–climate model to simulate surface ozone changes in China under a net-zero pathway and examine the different drivers that govern these changes. We find large monthly mean surface ozone decreases of up to 16 ppb in summer and small ozone decreases of 1 ppb in winter. Local emissions are shown to have the largest influence on future ozone changes, outweighing the effects of changes in emissions outside China, changes in global methane concentrations, and a warmer climate. Impacts of local and external emissions show strong seasonality, with the largest contributions to surface ozone in summer, while changes in global methane concentrations have a more uniform effect throughout the year. We find that while a warmer climate has a minor impact on ozone change compared to the net-zero scenario, it will alter the spatial patterns of ozone in China, leading to ozone increases in the south and ozone decreases in the north. We also apply a deep learning model to correct biases in our ozone simulations and to provide a more robust assessment of ozone changes. We find that emission controls may lead to a surface ozone decrease of 5 ppb in summer. The number of days with high-ozone episodes with daily mean ozone greater than 50 ppb will be reduced by 65 % on average. This is smaller than that simulated with the chemistry–climate model, reflecting overestimated ozone formation under present-day conditions. Nevertheless, this assessment clearly shows that the strict emission policies needed to reach net zero will have a major benefit in reducing surface ozone pollution and the occurrence of high-ozone episodes, particularly in high-emission regions in China

Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data

Wetlands are a major emission source of methane (CH4) globally. In this study, we evaluate wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates are investigated: (a) from an offline run driven with Climatic Research Unit–National Centers for Environmental Prediction (CRU-NCEP) meteorological data and (b) from the same offline run in which the modelled wetland fractions are replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH4 per annum over the period 1999–2007) is in line with other recently published estimates. There are regional differences as the unconstrained JULES inventory gives significantly higher emissions in the Amazon (by ~36 Tg CH4 yr−1) and lower emissions in other regions (by up to 10 Tg CH4 yr−1) compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we evaluate these JULES wetland emissions against atmospheric observations of methane. We obtain improved agreement with the surface concentration measurements, especially at high northern latitudes, compared to previous HadGEM2 runs using the wetland emission data set of Fung et al. (1991). Although the modelled monthly atmospheric methane columns reproduce the large-scale patterns in the SCIAMACHY observations, they are biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output results in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain the JULES-derived wetland fraction improves the representation of the wetland emissions in JULES and gives a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We find that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources cannot be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g. India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper show that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We identify areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation data sets used here will be of continued value in future evaluations of JULES and the HadGEM family of models

Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts

Effective radiative forcing and adjustments in CMIP6 models

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 13 contemporary climate models that are participating in CMIP6 and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global mean anthropogenic forcing relative to pre-industrial (1850) from climate models stands at 1.97 (± 0.26) W m−2, comprised of 1.80 (± 0.11) W m−2 from CO2, 1.07 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.04 (± 0.23) W m−2 from aerosols and −0.08 (± 0.14) W m−2 from land use change. Quoted uncertainties are one standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.17 W m−2 is likely to be from ozone. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the traditional stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing, but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4 × CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with equilibrium climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing

Measurement of the cross section for isolated-photon plus jet production in pp collisions at √s=13 TeV using the ATLAS detector

The dynamics of isolated-photon production in association with a jet in proton–proton collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset with an integrated luminosity of 3.2 fb−1. Photons are required to have transverse energies above 125 GeV. Jets are identified using the anti- algorithm with radius parameter and required to have transverse momenta above 100 GeV. Measurements of isolated-photon plus jet cross sections are presented as functions of the leading-photon transverse energy, the leading-jet transverse momentum, the azimuthal angular separation between the photon and the jet, the photon–jet invariant mass and the scattering angle in the photon–jet centre-of-mass system. Tree-level plus parton-shower predictions from Sherpa and Pythia as well as next-to-leading-order QCD predictions from Jetphox and Sherpa are compared to the measurements

A search for resonances decaying into a Higgs boson and a new particle X in the XH → qqbb final state with the ATLAS detector

A search for heavy resonances decaying into a Higgs boson (H) and a new particle (X) is reported, utilizing 36.1 fb−1 of proton–proton collision data at collected during 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider. The particle X is assumed to decay to a pair of light quarks, and the fully hadronic final state is analysed. The search considers the regime of high XH resonance masses, where the X and H bosons are both highly Lorentz-boosted and are each reconstructed using a single jet with large radius parameter. A two-dimensional phase space of XH mass versus X mass is scanned for evidence of a signal, over a range of XH resonance mass values between 1 TeV and 4 TeV, and for X particles with masses from 50 GeV to 1000 GeV. All search results are consistent with the expectations for the background due to Standard Model processes, and 95% CL upper limits are set, as a function of XH and X masses, on the production cross-section of the resonance