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]

Home Browse Climate action for health and wellbeing in cities: a protocol for... ALL METRICS 99 VIEWS 11 DOWNLOADS Get PDF Get XML Cite Export Track Email Share ▬ STUDY PROTOCOL 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

The draft genome of the parasitic nematode Trichinella spiralis

Genome evolution studies for the phylum Nematoda have been limited by focusing on comparisons involving Caenorhabditis elegans. We report a draft genome sequence of Trichinella spiralis, a food-borne zoonotic parasite, which is the most common cause of human trichinellosis. This parasitic nematode is an extant member of a clade that diverged early in the evolution of the phylum, enabling identification of archetypical genes and molecular signatures exclusive to nematodes. We sequenced the 64-Mb nuclear genome,which is estimated to contain 15,808 protein-coding genes,at ~35-fold coverage using whole-genome shotgun and hierarchal map–assisted sequencing. Comparative genome analyses support intrachromosomal rearrangements across the phylum, disproportionate numbers of protein family deaths over births in parasitic compared to a non-parasitic nematode and a preponderance of gene-loss and -gain events in nematodes relative to Drosophila melanogaster. This genome sequence and the identified pan-phylum characteristics will contribute to genome evolution studies of Nematoda as well as strategies to combat global parasites of humans, food animals and crops

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

A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector

To track progress towards keeping global warming well below 2 ºC or even 1.5 °C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO2 emissions, CH4 emissions, N2O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF6, NF3) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (∼ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO2 eq. consisting of CO2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO2, CO2-LULUCF 5.7 ± 4.0 GtCO2, CH4 10 ± 3.1 GtCO2 eq., N2O 2.6 ± 1.6 GtCO2 eq., and F-gases 1.3 ± 0.40 GtCO2 eq. Initial estimates suggest further growth of 1.3 GtCO2 eq. in GHG emissions to reach 59 ± 6.6 GtCO2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr−1) compared to 2000–2009 (2.4 % yr−1), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761