| Title |
Impact of Biomass Ratio as a Synthetic Parameter in Soft Computing Approaches for a Decision-Making Tool for Biogas Plants in Urban Areas |
| ID_Doc |
8438 |
| Authors |
Pracucci, A; Zaffagnini, T |
| Title |
Impact of Biomass Ratio as a Synthetic Parameter in Soft Computing Approaches for a Decision-Making Tool for Biogas Plants in Urban Areas |
| Year |
2023 |
| Published |
Sustainability, 15.0, 12 |
| DOI |
10.3390/su15129423 |
| Abstract |
The EU's energy transition strategy highlights the significance of developing innovative energy models to encourage the utilization of renewable energy sources in urban areas. Utilizing local urban biomasses, including food waste, sewage, and green waste, can contribute to the establishment of energy systems that harness bio-waste for energy generation, thereby promoting circular economy principles and urban metabolisms. This paper proposes using a pre-design tool (based on soft computing approaches) that incorporates an initial analysis of the multidisciplinary feasibility of such systems as an effective strategy and valuable support for preliminary studies. It focuses on validating three "biomass ratio" parameters, integrating urban morphology and district characteristics with the amount of bio-waste in a peri-urban district comprising multifamily buildings. These parameters can be incorporated into a pre-design tool that facilitates multi-criteria decision analyses, aiding the design of innovative models that promote renewable energy sources in urban areas. The findings suggest that synthetic parameters can guide initial considerations, but they may overestimate the energy potential and should be further investigated. Hence, future research should explore complementary strategies for estimating biomass energy potential and extend the application of this methodology to other types of districts. |
| Author Keywords |
renewable energy source; energy efficiency; resilient cities; sustainability; adaptation; optimized design; bio-waste; urban district typology; decision support tool; multi-criteria decision analysis |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:001015937200001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
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