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Record W4229777402 · doi:10.1002/ejlt.201700460

Fats and Oils as Renewable Feedstock for the Chemical Industry

2018· article· en· W4229777402 on OpenAlexaboutno aff
Jürgen O. Metzger, Michaël A. R. Meier

Bibliographic record

VenueEuropean Journal of Lipid Science and Technology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energySustainable developmentReuseBusinessRaw materialRenewable resourceSustainabilityNatural resource economicsNatural resourceEnvironmental economicsWaste managementEngineeringEconomicsPolitical scienceChemistry

Abstract

fetched live from OpenAlex

During their General Assembly on September 25, 2015, the United Nations adopted the resolution “Transforming our world: the 2030 Agenda for Sustainable Development” with 17 Sustainable Development Goals. Goal 12 claims to ensure sustainable consumption and production patterns, inter alia to achieve a sustainable management and efficient use of natural resources by 2030, substantially reduce waste generation through prevention, reduction, recycling, and reuse. An environmentally sound management of chemicals and all wastes throughout their life cycle, in accordance with agreed international frameworks, and to significantly reduce their release to air, water, and soil in order to minimize their adverse impacts on human health and the environment are explicitly mentioned.1 Renewable feedstocks are an important aspect for the implementation of Goal 12. The utilization of renewables in general, and fats and oils in particular, as feedstock for the chemical industry and the use of products based on renewables is steadily advancing. Scientists are challenged to contribute to this important development goal. Necessarily, and nevertheless remarkably, the sustainable use of renewable resources has become a hot topic of research during the last years. Let's have a look on the development of the key word “renewable resources” in Web of Science from the sixties of the last century until today, being the period of petrochemistry (Figure 1). During the sixties, seventies, eighties renewables were almost unknown to the scientific community and without any significant scientific interest. However, beginning in the seventies we can observe a very slight increase of the number of manuscripts dealing with renewables that turns out to be the start of an exponential growth. In the year 2016, “Web of Science” lists more than 2400 manuscripts on the topic. The doubling time is about 4–5 years. Thus, in 2020 we can expect about 5000 papers if the trend continues, which can be expected. Several important events stimulated the scientific interest in renewable resources. The first United Nations Conference on the Human Environment was held in Stockholm, Sweden in 1972 and in the same year “The Limits to Growth” by the Club of Rome appeared.2 In 1973 the first and in 1979 the second oil crisis occurred, increasing the awareness to the topic. Thus, the seventies exhibited already 82 papers dealing with renewables. In the eighties, the most important stimulus was the Brundlandt-Report in 1987.3 It discussed a sustainable development for our common future and prepared the United Nations Conference on Environment and Development held in 1992 in Rio de Janeiro. The Climate convention, the Rio declaration on sustainable development and Agenda 21, the comprehensive plan of action for the 21st century were adopted by more than 170 governments. One year later, the Agency of renewable resources was founded in Germany. The climate convention of Rio de Janeiro established the yearly “Conferences of the Parties (COP)” to assess progress in dealing with climate change. COP 1 started in Berlin 1995 and was followed by many others such as Kyoto 1997, Montreal 2005 and Paris 2015. We should not forget the Johannesburg Conference 2002 and Rio + 20 in 2012. All these events give evidence that the environmentally sound and sustainable use of renewable natural resources is essential on the way to a sustainable development. The 9th Workshop on Fats and Oils as Renewable Feedstock for the Chemical Industry took place March 19–21, 2017 in Karlsruhe, Germany, organized by abiosus e.V. in cooperation with the Agency of Renewable Resources (FNR), Germany. Thirty lectures and forty posters provided an update on the newest developments in the field of fats and oils as renewable feedstock for the chemical industry. Some of them are summarized in this special issue, demonstrating the advances made in the field and that “oleochemistry” remains a very active field of research that can provide very valuable contributions for a sustainable development. Eventually, we would like to invite you to participate at the 10th workshop on ”Fats and Oils as Renewable Feedstock for the Chemical Industry,” which will be held again at the Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, from March 17–19, 2019. Hopefully you will have the opportunity to participate. We are looking forward to exciting and fruitful discussions with you, the fats and oils community. The program and additional information will be available in September 2018 (http://abiosus.org/meetings.html.de). Jürgen O. Metzger Jürgen O. Metzger Jürgen O. Metzger studied chemistry at the universities of Tübingen, Erlangen, Berlin, and Hamburg, Germany. He received his Ph.D. under the supervision of H. Sinn in 1970 at the University of Hamburg, and completed his habilitation in 1983. In 1991, he was appointed professor of organic chemistry at the University of Oldenburg, Germany, and he retired in 2006. He is chairman of abiosus e.V., a non-profit association for the advancement of research on renewable raw materials. His research areas include sustainability in chemistry, environmentally benign organic synthesis, renewable raw materials, radical chemistry, and mass spectrometry. Michael A. R. Meier is full professor at the Karlsruhe Institute of Technology (KIT, Germany) since 2010. He received his diploma degree (M.Sc.) in chemistry in 2002 from the University of Regensburg (Germany) and his PhD under the supervision of Prof. Ulrich S. Schubert from the Eindhoven University of Technology (The Netherlands) in 2006. His research interests include the sustainable use and derivatization of renewable resources for polymer chemistry as well as the design of novel highly defined macromolecular architectures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.213
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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