282 research outputs found
How can the crisis of liberalization trade be overcome?
Since the seventies the existing order of international economic relations has been exposed to ever stronger pressures. Access to foreign markets must once again be regarded as a scarce commodity, since the far-reaching removal of tariff barriers has been more than compensated for by non-tariff restrictions
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The mutual dependence of negative emission technologies and energy systems
While a rapid decommissioning of fossil fuel technologies deserves priority, most climate stabilization scenarios suggest that negative emission technologies (NETs) are required to keep global warming well below 2 °C. Yet, current discussions on NETs are lacking a distinct energy perspective. Prominent NETs, such as bioenergy with carbon capture and storage (BECCS) and direct air carbon capture and storage (DACCS), will integrate differently into the future energy system, requiring a concerted research effort to determine adequate means of deployment. In this perspective, we discuss the importance of energy per carbon metrics, factors of future cost development, and the dynamic response of NETs in intermittent energy systems. The energy implications of NETs deployed at scale are massive, and NETs may conceivably impact future energy systems substantially. DACCS outperform BECCS in terms of primary energy required per ton of carbon sequestered. For different assumptions, DACCS displays a sequestration efficiency of 75–100%, whereas BECCS displays a sequestration efficiency of 50–90% or less if indirect land use change is included. Carbon dioxide removal costs of DACCS are considerably higher than BECCS, but if DACCS modularity and granularity helps to foster technological learning to <100$ per tCO2, DACCS may remove CO2 at gigaton scale. DACCS also requires two magnitudes less land than BECCS. Designing NET systems that match intermittent renewable energies will be key for stringent climate change mitigation. Our results contribute to an emerging understanding of NETs that is notably different to that derived from scenario modelling
The mutual dependence of negative emission technologies and energy systems
While a rapid decommissioning of fossil fuel technologies deserves priority, most climate stabilization scenarios suggest that negative emission technologies (NETs) are required to keep global warming well below 2 °C. Yet, current discussions on NETs are lacking a distinct energy perspective. Prominent NETs, such as bioenergy with carbon capture and storage (BECCS) and direct air carbon capture and storage (DACCS), will integrate differently into the future energy system, requiring a concerted research effort to determine adequate means of deployment. In this perspective, we discuss the importance of energy per carbon metrics, factors of future cost development, and the dynamic response of NETs in intermittent energy systems. The energy implications of NETs deployed at scale are massive, and NETs may conceivably impact future energy systems substantially. DACCS outperform BECCS in terms of primary energy required per ton of carbon sequestered. For different assumptions, DACCS displays a sequestration efficiency of 75–100%, whereas BECCS displays a sequestration efficiency of 50–90% or less if indirect land use change is included. Carbon dioxide removal costs of DACCS are considerably higher than BECCS, but if DACCS modularity and granularity helps to foster technological learning to <100$ per tCO2, DACCS may remove CO2 at gigaton scale. DACCS also requires two magnitudes less land than BECCS. Designing NET systems that match intermittent renewable energies will be key for stringent climate change mitigation. Our results contribute to an emerging understanding of NETs that is notably different to that derived from scenario modelling.TU Berlin, Open-Access-Mittel - 201
The technological and economic prospects for CO2 utilization and removal
The capture and use of carbon dioxide to create valuable products might lower the net costs of reducing emissions or removing carbon dioxide from the atmosphere. Here we review ten pathways for the utilization of carbon dioxide. Pathways that involve chemicals, fuels and microalgae might reduce emissions of carbon dioxide but have limited potential for its removal, whereas pathways that involve construction materials can both utilize and remove carbon dioxide. Land-based pathways can increase agricultural output and remove carbon dioxide. Our assessment suggests that each pathway could scale to over 0.5 gigatonnes of carbon dioxide utilization annually. However, barriers to implementation remain substantial and resource constraints prevent the simultaneous deployment of all pathways
Climate action for health and wellbeing in cities: a protocol for the systematic development of a database of peer-reviewed studies using machine learning methods [version 1; peer review: awaiting peer review]
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Climate action for health and wellbeing in cities: a protocol for the systematic development of a database of peer-reviewed studies using machine learning methods [version 1; peer review: awaiting peer review]
Kristine Belesova https://orcid.org/0000-0002-6160-50411, Max Callaghan https://orcid.org/0000-0001-8292-87582, Jan C Minx https://orcid.org/0000-0002-2862-01782, Felix Creutzig2, Catalina Turcu https://orcid.org/0000-0003-2663-25863, Emma Hutchinson1, James Milner1, Melanie Crane https://orcid.org/0000-0002-3058-22114, Andy Haines https://orcid.org/0000-0002-8053-46051, Michael Davies5, Paul Wilkinson1
Author details
1 Department of Public Health, Environments and Society and Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, WC1H 9SH, UK
2 Mercator Research Institute on Global Commons and Climate Change, Berlin, 10829, Germany
3 Bartlett School of Planning, University College London, London, WC1H 0QB, UK
4 Charles Perkins Centre, Sydney School of Public Health, University of Sydney, Sydney, Australia
5 Bartlett School Environment, Energy & Resources, University College London, London, WC1H 0QB, UK
Kristine Belesova
Roles: Conceptualization, Data Curation, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing
Max Callaghan
Roles: Data Curation, Investigation, Methodology, Software, Writing – Review & Editing
Jan C Minx
Roles: Conceptualization, Investigation, Methodology, Software, Writing – Review & Editing
Felix Creutzig
Roles: Conceptualization, Investigation, Methodology, Software, Writing – Review & Editing
Catalina Turcu
Roles: Investigation, Methodology, Writing – Review & Editing
Emma Hutchinson
Roles: Investigation, Methodology, Writing – Review & Editing
James Milner
Roles: Methodology, Writing – Review & Editing
Melanie Crane
Roles: Methodology, Writing – Review & Editing
Andy Haines
Roles: Conceptualization, Funding Acquisition, Methodology, Supervision, Writing – Review & Editing
Michael Davies
Roles: Conceptualization, Funding Acquisition, Methodology, Writing – Review & Editing
Paul Wilkinson
Roles: Conceptualization, Funding Acquisition, Methodology, Supervision, Writing – Review & Editing
Abstract
Cities produce more than 70% of global greenhouse gas emissions. Action by cities is therefore crucial for climate change mitigation as well as for safeguarding the health and wellbeing of their populations under climate change. Many city governments have made ambitious commitments to climate change mitigation and adaptation and implemented a range of actions to address them. However, a systematic record and synthesis of the findings of evaluations of the effect of such actions on human health and wellbeing is currently lacking. This, in turn, impedes the development of robust knowledge on what constitutes high-impact climate actions of benefit to human health and wellbeing, which can inform future action plans, their implementation and scale-up. The development of a systematic record of studies reporting climate and health actions in cities is made challenging by the broad landscape of relevant literature scattered across many disciplines and sectors, which is challenging to effectively consolidate using traditional literature review methods. This protocol reports an innovative approach for the systematic development of a database of studies of climate change mitigation and adaptation actions implemented in cities, and their benefits (or disbenefits) for human health and wellbeing, derived from peer-reviewed academic literature. Our approach draws on extensive tailored search strategies and machine learning methods for article classification and tagging to generate a database for subsequent systematic reviews addressing questions of importance to urban decision-makers on climate actions in cities for human health and wellbeing
Mapping global research on climate and health using machine learning (a systematic evidence map)
Climate change is already affecting health in populations around the world, threatening to undermine the past 50 years of global gains in public health. Health is not only affected by climate change via many causal pathways, but also by the emissions that drive climate change and their co-pollutants. Yet there has been relatively limited synthesis of key insights and trends at a global scale across fragmented disciplines. Compounding this, an exponentially increasing literature means that conventional evidence synthesis methods are no longer sufficient or feasible. Here, we outline a protocol using machine learning approaches to systematically synthesize global evidence on the relationship between climate change, climate variability, and weather (CCVW) and human health. We will use supervised machine learning to screen over 300,000 scientific articles, combining terms related to CCVW and human health. Our inclusion criteria comprise articles published between 2013 and 2020 that focus on empirical assessment of: CCVW impacts on human health or health-related outcomes or health systems; relate to the health impacts of mitigation strategies; or focus on adaptation strategies to the health impacts of climate change. We will use supervised machine learning (topic modeling) to categorize included articles as relevant to impacts, mitigation, and/or adaptation, and extract geographical location of studies. Unsupervised machine learning using topic modeling will be used to identify and map key topics in the literature on climate and health, with outputs including evidence heat maps, geographic maps, and narrative synthesis of trends in climate-health publishing. To our knowledge, this will represent the first comprehensive, semi-automated, systematic evidence synthesis of the scientific literature on climate and health
A vertebrate case study of the quality of assemblies derived from next-generation sequences
The unparalleled efficiency of next-generation sequencing (NGS) has prompted widespread adoption, but significant problems remain in the use of NGS data for whole genome assembly. We explore the advantages and disadvantages of chicken genome assemblies generated using a variety of sequencing and assembly methodologies. NGS assemblies are equivalent in some ways to a Sanger-based assembly yet deficient in others. Nonetheless, these assemblies are sufficient for the identification of the majority of genes and can reveal novel sequences when compared to existing assembly references
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