QSAR Models for Climate Impact Assessment: Born to Be Sustainable
Arianna Sgariboldi, Nicola Chirico, Ester Papa · 2026
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Description
Arianna Sgariboldi, Nicola Chirico, and Ester Papa build prediction models for chemicals' climate impact in a 2026 study. Life-cycle assessors need each substance's global warming potential, yet measured values exist for few. Their structure-activity models infer warming potential straight from a molecule's shape, using plain regression on a small set of readable input clues.
The models follow the OECD rules for official acceptance: open maths, checked validity, a defined zone where predictions hold, and input clues a chemist can read. They stay simpler than rival models of similar accuracy. A test run screened over thirteen thousand candidate replacement chemicals, ranking safer options by predicted climate cost. Sgariboldi's team offers the tools as practical support for assessors and for industry hunting replacements for harmful substances before new products lock in avoidable warming.
Catalog record
| CREATOR | Arianna Sgariboldi, Nicola Chirico, Ester Papa |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 51 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |