Natural Building Materials in Mainstream Construction: Lessons from the U. K.
Bibliographic record
Abstract
Abstract The concepts of “green building” and “sustainable construction” have received tremendous interest in North America in the past decade, as shown by the growth in the numbers of L.E.E.D.™ certified projects (Kibert 2005). Parallel to this has been a growing interest in “natural,” “vernacular,” or “traditional” building materials and techniques. Examples of these include straw bale construction and rammed earth construction. From an environmental point of view, these materials offer a low embodied energy and low embodied carbon alternative to conventional building materials such as concrete and steel (Woolley 2006, Walker 2007). In the case of straw bale construction, use is made of a waste material with excellent insulation properties. Other benefits of many natural materials include their ability to passively regulate humidity in a building, reduced toxicity, high thermal mass, and biodegradability at the end of life (Walker 2007). There remain many barriers to the use of natural building materials in the mainstream construction industry, including a lack of scientific data to quantify their true performance (Woolley 2006) and lack of experience by the mainstream construction industry in using these materials. This leads to the perception that these materials are low-tech and have poor performance. This perception, however, is changing. There is a growing body of research that is quantifying the performance of natural building materials and showing that they can compete with conventional building materials. There are also some excellent recent examples of the integration of natural building materials in mainstream construction projects. This paper describes three natural building material products that have been successfully integrated into mainstream construction projects in the United Kingdom: straw bale panels by ModCell; a hemp-lime composite called “hemcrete” and marketed by Tradical; and, rammed earth and unfired clay bricks. The information in this paper is based on interviews and site inspections undertaken by the author during February 2008. Some of the research supporting the use of these products will be described. Finally, some lessons and cautions for the use of these products in North America will be discussed. A caveat regarding the limitations of this paper is in order. This paper does not claim to be an exhaustive review of natural building materials and their performance. Other references should be consulted for more details on thermal or fire performance, for example.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".