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Record W7071479436

The state of the Latvian wood pellet industry : a study on production conditions and international competitiveness

2014· other· en· W7071479436 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEpsilon Archive for Student Projects (University of Southampton) · 2014
Typeother
Languageen
FieldComputer Science
TopicQR Code Applications and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsLatvianPelletPelletsRaw materialBiomass (ecology)Production (economics)BioenergyTorrefactionResource (disambiguation)
DOInot available

Abstract

fetched live from OpenAlex

In the last decade, member states of the European Union have adopted a range of measures to decrease the dependency on fossil fuels. This has led to an increased use of biomass in heat and power production. In some countries, the lack of forest resource has led to large scale power producers importing their biomass needs. Due to high energy content and homogeneity, wood pellets have become an internationally traded commodity used for large scale power production. 
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\nThe Baltic States have emerged as one of the largest wood pellet exporting regions in Europe. This study focused on the case of Latvia, the country with the largest wood pellet production in the region. The purpose was to investigate the production conditions and the competitiveness of the Latvian wood pellet industry. The study was limited to industrial wood pellets for large scale utilities. Three import countries; Belgium, the Netherlands and the UK were identified as large industrial pellet importers for further research. Coal was seen as the major competing alternative energy source on these markets.
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\nThe global wood pellet industry, the wood pellet value chain and Latvian conditions for pellet production was first researched through a literature study. Coupled with theories on competition, it formed the framework for the empiric data gathering through qualitative semi-structured interviews with actors in the Latvian wood pellet industry. 
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\nThe study revealed that raw material costs were a weakness for the pellet industry. Pellets contracts were made for 1-3 years and there was no way to hedge against increases in raw material. The result further suggests that the current size of the Latvian wood pellet industry might not be sustainable, based on future raw material availability and increased raw material competition. Changes in freight rates could also affect the competitiveness of Latvian pellet producers as the currently low rates are thought to increase. However, the industry is doing well at the moment experiencing a steady demand and good FOB (free on board) prices at the ports of export. 
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\nCalculations showed that wood pellet mills under Latvian conditions had a total cost of 103-110 €/tonne FOB Riga and 117-124 €/tonne CIF ARA (cost, insurance and freight to Antwerp-Rotterdam-Amsterdam), which suggests they could compete based on the average spot price of 125 €/tonne CIF ARA. Calculations also revealed that the cost of producing and transporting Latvian pellets was competitive with the coal price under the current market situations and the existing support schemes for biomass in biomass dedicated energy producing utilities. The result further showed that Latvian pellet producers were able to compete at profit against the coal price in co-firing utilities in Belgium and the UK. However, the power plants profitability of co-firing wood pellets was proportional to the share of biomass used.
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\nLatvian pellet producers had an advantage on Scandinavian markets, large storage abilities to handle demand fluctuations and some had the possibility to switch between residential and industrial pellets. The geographical location coupled with their storage options also resulted in a possible niche towards the large scale industrial consumers in flexibility and delivery speed. However, the energy producers on the selected markets required large volumes of wood pellets and had infrastructure capable of handling the large North American bulk shipments of 40.000 tonnes. Based on the scale of operations and price, the pellet producers in the US and Canada will probably continue to be the main suppliers for the large scale consumers on these markets. 
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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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.018
GPT teacher head0.257
Teacher spread0.239 · 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