Optimizing the Logistics of Anaerobic Digestion of Manure
Bibliographic record
Abstract
Electrical power production from the combustion of biogas from anaerobic digestion (AD) of manure is a means of recovering energy from animal waste. We evaluate the lowest cost method of moving material to and from centralized AD plants serving multiple confined feeding operations. Two areas are modeled, Lethbridge County, Alberta, Canada, an area of concentrated beef cattle feedlots, and Red Deer County, Alberta, a mixed-farming area with hog, dairy, chicken and beef cattle farms, and feedlots. We evaluate two types of AD plant: ones that return digestate to the source confined feeding operation for land spreading (current technology), and ones that process digestate to produce solid fertilizer and a dischargeable water stream (technology under development). We evaluate manure and digestate trucking, trucking of manure with return of digestate by pipelines, and pipelining of manure plus digestate. We compare the overall cost of power from these scenarios to farm or feedlot-based AD units. For a centralized AD plant with digestate return for land spreading the most economical transport option for manure plus digestate is by truck for the mixed-farming area and by pipelines for the concentrated feedlot area. For a centralized AD plant with digestate processing, the most economical transport option is trucking of manure for both cases.However, for the concentrated feedlot area, pipeline transport of manure is close in cost to trucking, and the impact of truck congestion would likely lead to selection of pipeline transport. For the mixed-farming area, centralized AD is more economical than for any individual farm or feedlot unit. For the concentrated feedlot area, a centralized AD plant is less economical than a feedlot-based AD unit more than 55,000 head (digestate return) and 300,000 head (digestate processing). The study demonstrates the viability of centralized AD plants vs farm-based units in most farming environments, and that careful analysis of the cost of pipeline vs truck transport of manure and digestate is required on a case-by-case basis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".