LIFE CYCLE IMPACTS OF NORTH AMERICAN WOOD PANEL MANUFACTURING
Bibliographic record
Abstract
Manufacturing building products such as wood panels impacts the environment, including contributing to climate change.This study is a compilation of four studies quantifying these impacts using the life cycle assessment (LCA) method on five wood-based panel products made in North America during 2012.LCA is an internationally accepted and standardized method for evaluating the environmental impacts of products.With LCA, holistic environmental impacts were calculated based on survey data from mills on emissions to air and water, solid waste, energy consumption, and resource use.This study incorporated cradle-to-gate production of nonwood materials including additives and energy products, such as natural gas and coal, consumed at the production facilities.In addition, primary transport of wood materials to the production facilities was included.These primary data were entered in LCA modeling software on a production unit of 1 m 3 of the panel to estimate manufacturing gate-to-gate life cycle inventory (LCI) flows and major environmental impacts.The LCI flows and environmental impacts were converted to a functional unit of 1 m 2 of the wood panel (ie final product) produced.The following products were evaluated with their stated panel thicknesses in millimeters: oriented strandboard (9.5), Southeast (SE) and Pacific Northwest (PNW) softwood plywood (9.5), cellulosic fiberboard (12.7), and hardboard (3.2). Results are provided on cumulative primary energy consumption (CPEC) and global warming impacts (GWI).CPEC was 74.0, 73.5 (SE), 68.7 (PNW), 76.0, and 88.3 MJ/m 2 , with biomass-derived energy percentage of 50, 50 (SE), 64 (PNW), 12, and 47, respectively.GWI was 1.97, 1.90 (SE), 1.23 (PNW), 3.91, and 2.47 kg CO 2 equivalent/m 2 , respectively.Densities and panel thicknesses have the greatest impacts on converting from a cubic meter to a square meter basis.The panel products evaluated here are mostly not interchangeable.Thus, results for the panel products should not be compared.Using woody biomass energy for panel production decreases their contribution to climate change.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.026 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".