A State of Play Review of Methods to Define Net Zero Carbon Buildings
Bibliographic record
Abstract
Abstract As time pressure rises to cut down greenhouse gas (GHG) emissions, countries have defined net-zero carbon targets for their buildings for 2050 or earlier. In practice, a wide range of definitions for net zero and related approaches to achieving these targets co-exist. This study is carried out by IEA EBC Annex 89 Subtask 2, dedicated to carbon accounting methods for buildings. Here, we use a classification matrix to examine national carbon accounting approaches used for buildings in Norway, Germany, the Netherlands, Canada, and the UK. We explore the definitions they express and analyze how aspects like the main fronts for carbon storage and offsets, carbon credits, secondary materials, benchmarks, and limit values are tackled. We also define negative emissions in line with the IPCC. All methods are bottom-up approaches, aligned closely with EN15978/15804. Some of them are mandatory, other voluntary but widely used. Not all methods model negative emissions materials; some that do so, misclassify the ‘minuses’ in the whole life carbon equation, regarding e.g. biogenic carbon, exported energy, and benefits beyond the reference study period. Of the methods examined, the UK’s RICS PS is the only one that admits dynamic modelling (optional for reporting the benefits of carbon storage). Operational and embodied emissions are usually calculated, but not always coupled to provide whole-life carbon figures. The absence of benchmarks and limit values stresses the need to bridge the policy gap and link such methods to their countries emission reduction pathway.
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 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 | 0.022 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".