Gaining CO2 Reduction Insights with SHAP: Analyzing a Shower Heat Exchanger with Artificial Neural Networks DOI Creative Commons
Sabina Kordana, Beata Piotrowska, Mariusz Starzec

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(8), P. 1904 - 1904

Published: April 9, 2025

The application of shower heat exchangers (SHEs) allows for a reduction in the amount energy necessary to domestic hot water (DHW). As result, not only costs heating DHW but also emission harmful products fuel combustion is reduced. However, identification key areas determining resulting carbon dioxide remains an unexplored issue. For this reason, main purpose paper was comprehensively analyze impact parameters characterizing operation horizontal SHE cooperating with electric heater on potential CO2 emission. part research study, 16,200 values corresponding different conditions installation were determined. analysis carried out considering location countries European Union. Artificial neural networks and SHAP used as tools. This study showed that intensity, world map, total daily length are importance prediction reduction. efficiency turned be least important parameter. proved greatest environmental benefits using SHEs will visible where fossil fuels account large share electricity production, such Poland, buildings significant consumption.

Language: Английский

Gaining CO2 Reduction Insights with SHAP: Analyzing a Shower Heat Exchanger with Artificial Neural Networks DOI Creative Commons
Sabina Kordana, Beata Piotrowska, Mariusz Starzec

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(8), P. 1904 - 1904

Published: April 9, 2025

The application of shower heat exchangers (SHEs) allows for a reduction in the amount energy necessary to domestic hot water (DHW). As result, not only costs heating DHW but also emission harmful products fuel combustion is reduced. However, identification key areas determining resulting carbon dioxide remains an unexplored issue. For this reason, main purpose paper was comprehensively analyze impact parameters characterizing operation horizontal SHE cooperating with electric heater on potential CO2 emission. part research study, 16,200 values corresponding different conditions installation were determined. analysis carried out considering location countries European Union. Artificial neural networks and SHAP used as tools. This study showed that intensity, world map, total daily length are importance prediction reduction. efficiency turned be least important parameter. proved greatest environmental benefits using SHEs will visible where fossil fuels account large share electricity production, such Poland, buildings significant consumption.

Language: Английский

Citations

0