Life Cycle Assessment of Central Solar Heating Plants with Seasonal Storage
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.
Bibliographic record
Abstract
Renewable energies can play a very important role in the development of a new energy model contributing effectively towards a more sustainable development in the mid and long term. In this context Central Solar Heating Plants with Seasonal Storage (CSHPSS) are able to provide space heating and Domestic Hot Water (DHW) to residential buildings with high solar fractions (>50%). These systems are already being used in Central and Northern Europe, as well as in Canada, where there is an important experience in district heating systems. Life Cycle Assessment (LCA) is an objective methodology that evaluates the environmental loads associated with a product, process, or activity, identifying and quantifying the use of mass and energy as well as environmental emissions over its life cycle. It provides a comprehensive view of the environmental aspects of a product or process and a more accurate picture of the true environmental trade-offs in product and process selection. In this paper is presented a LCA of a CSHPSS, which should cover the space heating and DHW demand of 500 dwellings of 100 m 2 , located in Zaragoza, Spain. Environmental burdens through the life cycle of the system are estimated based on relevant emissions to the atmosphere, e.g. greenhouse gases, NO x , SO x , and comprehensive environmental indicators as, for instance, the IMPACT 2002+ and CED (Cumulative Energy Demand). These indicators allow to evaluate the reduction of the environmental load achieved by the CSHPSS analyzed with respect to conventional space heating and DHW systems, as well as to identify the most critical aspects since an environmental perspective.
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.
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 it