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Future energy technologies will be key for a successful reduction of man-made greenhouse gas emissions. With demand for electricity projected to increase significantly in the future, climate policy goals of limiting the effects of global atmospheric warming can only be achieved if power generation processes are profoundly decarbonized. Energy models, however, have ignored the fact that upstream emissions are associated with any energy technology. In this work we explore methodological options for hybrid life cycle assessment (hybrid LCA) to account for the indirect greenhouse gas (GHG) emissions of energy technologies using wind power generation in the UK as a case study. We develop and compare two different approaches using a multiregion input-output modeling framework - Input-Output-based Hybrid LCA and Integrated Hybrid LCA. The latter utilizes the full-sized Ecoinvent process database. We discuss significance and reliability of the results and suggest ways to improve the accuracy of the calculations. The comparison of hybrid LCA methodologies provides valuable insight into the availability and robustness of approaches for informing energy and environmental policy.

Global GHG emissions continue to rise, with nearly a quarter of it due to trade that is not currently captured within global climate policy. In the context of current trade patterns and limited global cooperation on climate change, the feasibility of consumptionbased emissions accounting to contribute to a more comprehensive (national) policy framework in the UK is investigated. Consumption-based emissions results for the UK from a range of models are presented, their technical robustness is assessed, and their potential application in national climate policy is examined using examples of policies designed to reduce carbon leakage and to address high levels of consumption. It is shown that there is a need to include consumption-based emissions as a complementary indicator to the current approach of measuring territorial emissions. Methods are shown to be robust enough to measure progress on climate change and develop and inform mitigation policy. Finally, some suggestions are made for future policy-oriented research in the area of consumption-based accounting that will facilitate its application to policy. Policy relevanceEmissions embodied in trade are rapidly increasing and there is thus a growing gap between production emissions and the emissions associated with consumption. This is a growing concern due to the absence of a global cap and significant variation in country-level mitigation ambitions. Robust measurements of consumption-based emissions are possible and provide new insights into policy options. This includes trade-related policy (e.g. border carbon adjustments) and domestic policies (e.g. resource efficiency strategies). As climate policy targets deepen, there is a need for a broad range of policy options in addition to production and technological solutions. Consumption-based emissions are complementary to production-based emissions inventories, which are still the most accurate estimate for aggregated emissions at the global level. However, without consumption-based approaches, territorial emissions alone will not provide a complete picture of progress in regional and national emissions reduction.

Keratinocyte-derived TNF-a acts as an endogenous tumour promoter and can also regulate AP-1 activity in mouse epidermis. To gain further insight into TNF-a signalling during skin tumour formation, mice deficient in TNFR1 (TNFR1 À/À mice) or TNFR2 (TNFR2 À/À mice) were subjected to chemical carcinogenesis. Tumour multiplicity was significantly reduced in TNFR1 À/À and TNFR2 À/À mice compared to wild-type (wt) mice, suggesting that both receptors have protumour activity. However, TNFR1 À/À mice were markedly more resistant to tumour development than TNFR2 À/À mice indicating that TNFR1 is the major mediator of TNF-a-induced tumour formation. TNFR1 and TNFR2 were both expressed in wt epidermis during tumour promotion and by primary keratinocytes in vitro. TPA-induced c-Jun expression was transient in TNFR1 À/À and TNFR2 À/À compared to wt epidermis and this was reflected by reduced induction of the AP-1-responsive genes granulocyte/macrophage-colony stimulating factor, matrix metalloproteinase-9 and matrix metalloproteinase-3. These genes were differentially regulated in TNFR1 À/À compared to TNFR2 À/À epidermis, suggesting that the TNF-a receptors act independently via different AP-1 complexes to transduce TNF-a signals during tumour promotion. In addition, TNFR2 cooperated with TNFR1 to optimise TNFR1-mediated TNF-a bioactivity on keratinocytes in vitro. Our data provide further insight into TNF-a signalling in malignancy and provide some rationale for the use of TNF-a antagonists in the treatment of cancer.

The ubiquity of systems using artificial intelligence or "AI" has brought increasing attention to how those systems should be regulated. The choice of how to regulate AI systems will require care. AI systems have the potential to synthesize large amounts of data, allowing for greater levels of personalization and precision than ever before-applications range from clinical decision support to autonomous driving and predictive policing. That said, our AIs continue to lag in common sense reasoning [McCarthy, 1960], and thus there exist legitimate concerns about the intentional and unintentional negative consequences of AI systems [Bostrom, 2003, Amodei et al., 2016, Sculley et al., 2014.How can we take advantage of what AI systems have to offer, while also holding them accountable? In this work, we focus on one tool: explanation. Questions about a legal right to explanation from AI systems was recently debated in the EU General Data Protection Regulation [Goodman and Flaxman, 2016, Wachter et al., 2017a], and thus thinking carefully about when and how explanation from AI systems might improve accountability is timely. Good choices about when to demand explanation can help prevent negative consequences from AI systems, while poor choices may not only fail to hold AI systems accountable but also hamper the development of much-needed beneficial AI systems.Below, we briefly review current societal, moral, and legal norms around explanation, and then focus on the different contexts under which explanation is currently required under the law. We find that there exists great variation around when explanation is demanded, but there also exist important consistencies: when demanding explanation from humans, what we typically want to know is whether and how certain input factors affected the final decision or outcome.These consistencies allow us to list the technical considerations that must be considered if we desired AI systems that could provide kinds of explanations that are currently required of humans under the law. Contrary to popular wisdom of AI systems as indecipherable black boxes, we find that this level of explanation should generally be technically feasible but may sometimes be practically onerous-there are certain aspects of explanation that may be simple for humans to provide but challenging for AI systems, and vice versa. As an interdisciplinary team of legal scholars, computer scientists, and cognitive scientists, we recommend that for the present, AI systems can and should be held to a similar standard of explanation as humans currently are; in the future we may wish to hold an AI to a different standard.

Internationally, allocation of responsibility for reducing greenhouse gas emissions is currently based on the production-based (PB) accounting method, which measures emissions generated in the place where goods and services are produced. However, the growth of emissions embodied in trade has raised the question whether we should switch to, or amalgamate PB accounting, with other accounting approaches. Consumption-based (CB) accounting has so far emerged as the most prominent alternative. This approach accounts for emissions at the point of consumption, attributing all the emissions that occurred in the course of production and distribution to the final consumers of goods and services. This review has a fourfold objective. First, it provides an account of the logic behind attributing responsibility for emissions on the basis of consumption instead of production. Issues of equity and justice, increased emissions coverage, encouragement of cleaner production practices, and political benefits are considered. Second, it discusses the counterarguments, focusing in particular on issues of technical complexity, mitigation effectiveness, and political acceptability. Third, it presents the spectrum of implementation possibilities-ranging from the status quo to more transformative options-and considers the implications for international climate policy that would accrue under various scenarios of adopting CB accounting in practice. Fourth, it looks at how CB accounting may be adjusted to fit with current political realities and it identifies policy mechanisms that could potentially be utilized to directly or indirectly address CB emissions. Such an approach could unlock new opportunities for climate policy innovation and for climate mitigation. © 2016 The Authors. WIREs Climate Change published by Wiley Periodicals, Inc. How to cite this article:WIREs Clim Change 2017Change , 8:e438. doi: 10.1002 INTRODUCTIONF or nearly two decades, the international community has been struggling to find a strategy to allocate responsibility for reducing greenhouse gas (GHG) emissions. Equity and justice concerns have been of paramount significance in international negotiations on climate change ever since the adoption of the 1992 United Nations Framework Convention on Climate Change (UNFCCC). Underwriting the UNFCCC is the principle of common but differentiated responsibility (CBDR), which acknowledges that countries have contributed by varying scales to the mounting problem of climate change, will be exposed to different levels of impacts, and have different capabilities (e.g., financial and technological) to mitigate emissions. Under the 1997 Kyoto Protocol, developed countries agreed to take on legally binding emissions reduction targets for 2012, recognizing their dominant role as historic polluters. However, as emission targets by developed countries alone would evidently be insufficient to address climate change, the 2011 Durban Platform recast equity and differentiation in the climate regime by calling for a roadmap toward an agre...

Leukocyte extravasation into tissues is a multi‐step process culminating in the migration of cells through the basement membrane. This requires the production of matrix‐degrading enzymes, in particular matrix metalloproteinases (MMP). We investigated the role of chemokines in regulating MMP production in the monocytic cell line THP‐1 and in peripheral blood monocytes (PBM). The CC chemokines CCL2 (MCP‐1), CCL3 (MIP‐1α), and CCL5 (RANTES) stimulated the release of monocyte MMP‐9 protein in a bell‐shaped dose‐dependent manner. The increase in MMP‐9 protein detected at 24 h was due to de novo synthesis, confirmed by Northern blotting, with MMP‐9 mRNA detectable at 6–8 h. Autocrine TNF‐α was necessary for chemokine stimulation of MMP‐9. Chemokines increased TNF‐α mRNA levels and protein release in monocytes and THP‐1 cells, and neutralizing anti‐TNF‐α antibodies inhibited CCL2‐induced MMP‐9 release. Furthermore, the broad spectrum MMP inhibitor BB 2516, which inhibits TNF‐α release, abrogated CCL2‐ and CCL5‐induced MMP‐9 release in both THP‐1 cells and freshly isolated monocytes. Monocyte production of MMP is of major importance in the pathology of cancer, asthma, and rheumatoid arthritis. An understanding of the mechanisms by which these MMP are produced may lead to novel therapies to modulate extravasation of leukocytes in disease.

Radical changes to current national energy systems-including energy efficiency and the decarbonization of electricity-will be required in order to meet challenging carbon emission reduction commitments. Technology explicit energy system optimization models (ESOMs) are widely used to define and assess such low-carbon pathways, but these models only account for the emissions associated with energy combustion and either do not account for or do not correctly allocate emissions arising from infrastructure, manufacturing, construction and transport associated with energy technologies and fuels. This paper addresses this shortcoming, through a hybrid approach that estimates the upstream CO2 emissions across current and future energy technologies for the UK using a multiregional environmentally extended input-output model, and explicitly models the direct and indirect CO2 emissions of energy supply and infrastructure technologies within a national ESOM (the UK TIMES model). Results indicate the large significance of nondomestic indirect emissions, particularly coming from fossil fuel imports, and finds that the marginal abatement cost of mitigating all emissions associated with UK energy supply is roughly double that of mitigating only direct emissions in 2050.