Building materials and components account for about 10% of the world's anthropogenic greenhouse gas emissions. Carbonate decomposition and fuel combustion from the cement production process are responsible for almost 7% of carbon dioxide emissions. Since clinker is the most impacting component of ordinary Portland cement, this paper presents a statistical analysis of the life cycle impacts of 41 recipes of grey clinker produced in Europe from 2015 to 2023 to identify the consumption impact categories (e.g., fossil fuels, renewable and non-renewable secondary fuels) which better explain the assessment of the Global Warming Potential (GWP), typically exploited to quantify the environmental impact of clinker production. More in detail, several regression methods are applied to the available dataset to build predictive models for GWP and to determine the most relevant impact categories. The regression models are then compared with respect to their statistical accuracy and goodness of fit. The results provide information that can support cement producers in developing low-impacting cement recipes.
Assessing the climate effects of clinker production: A statistical analysis to reduce its environmental impacts / Durastanti, C.; Moretti, L.. - In: CLEANER ENVIRONMENTAL SYSTEMS. - ISSN 2666-7894. - 14:(2024). [10.1016/j.cesys.2024.100204]
Assessing the climate effects of clinker production: A statistical analysis to reduce its environmental impacts
Durastanti C.
;Moretti L.
2024
Abstract
Building materials and components account for about 10% of the world's anthropogenic greenhouse gas emissions. Carbonate decomposition and fuel combustion from the cement production process are responsible for almost 7% of carbon dioxide emissions. Since clinker is the most impacting component of ordinary Portland cement, this paper presents a statistical analysis of the life cycle impacts of 41 recipes of grey clinker produced in Europe from 2015 to 2023 to identify the consumption impact categories (e.g., fossil fuels, renewable and non-renewable secondary fuels) which better explain the assessment of the Global Warming Potential (GWP), typically exploited to quantify the environmental impact of clinker production. More in detail, several regression methods are applied to the available dataset to build predictive models for GWP and to determine the most relevant impact categories. The regression models are then compared with respect to their statistical accuracy and goodness of fit. The results provide information that can support cement producers in developing low-impacting cement recipes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.