## 4 Results and Discussion
### Optimal Solution Selection and Practical Interpretation  
While the Pareto front offers a diverse set of non-dominated solutions balancing cost and CO\({}_{2}\) emissions, practical implementation often necessitates a unique selection. To operationalize the model output for real-world application, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was employed. This method evaluates each Pareto-optimal solution based on its Euclidean distance to an ideal solution (minimum cost and minimum emission) and an anti-ideal (maximum values of both). The solution with the highest closeness coefficient (0.931) was selected as the optimal configuration, as shown in Figure 12.  
The selected solution exhibits the following parameter profile:  
Transport Distance (x\({}_{1}\)): 47 km  
Energy Intensity (x\({}_{2}\)): 1.21 kWh/ton  
Moisture Content (x\({}_{3}\)): 6.2%  
Gradation Adjustment Level (x\({}_{4}\)): Level 1  
Grid CO\({}_{2}\) Factor (x\({}_{5}\)): 0.47 kg CO\({}_{2}\)/kWh  
Total cost: 24.6 USD/m\({}^{3}\)  
Total CO\({}_{2}\) Emission: 74.8 kg/m\({}^{3}\)  
This configuration lies near the geometric center of the Pareto front, offering a 45% reduction in CO\({}_{2}\) emissions relative to the cost-optimal solution (Point A), with only a 33% increase in unit cost. It thus represents a balanced and cost-effective pathway toward decarbonization, particularly suited for regions with medium-carbon electricity grids.  
Compared to emission-optimal designs, which often demand short-haul sourcing, high-efficiency moisture control, and premium grid locations, this solution requires no extreme infrastructure adaptations. Transport distances under 50 km are feasible in peripurban and industrial zones with regional steel production, while moderate energy intensity (\(\approx\)1.2 kWh/ton) aligns with single-stage crushing equipment prevalent in many recycling plants  
Figure 12: Comparison of selected pareto and TOPSIS-optimal solutions.  
From a policy perspective, the selected configuration aligns well with the EU Taxonomy for Sustainable Activities, which encourages life-cycle CO\({}_{2}\) reduction without exceeding economic viability thresholds [82]. [PERSON] and [PERSON] [83] argue that optimal sustainability strategies must avoid extremes in either cost or emissions to ensure stakeholder acceptance--an outcome embodied by the selected solution. Nevertheless, it should be noted that the reported CO\({}_{2}\) values reflect a cradle-to-gate perspective and exclude potential downstream offsets such as avoided burdens or service-life carbonation, potentially rendering the emission figures conservative.  
The gradation level of 1 also offers meaningful insight. It reflects a single-pass sieving operation, avoiding the higher energy demands and equipment costs associated with fine particle control. This is consistent with the findings of [PERSON] et al. [84], who found that the over-processing of slag for particle uniformity has diminishing returns on mechanical performance while increasing environmental impact.  
Furthermore, the selected grid CO\({}_{2}\) factor (0.47 kg/kWh) represents a technologically realistic target. It is achievable through moderate decarbonization (e.g., 40-50% renewable mix), without requiring full transition to solar or hydro. This grid profile is now present in countries like Portugal and parts of Canada, making this solution replicable in multiple jurisdictions [85].  
In conclusion, the TOPSIS-selected configuration provides a technically feasible, environmentally advantageous, and economically moderate design solution. It reflects both engineering practicality and alignment with global sustainability frameworks, making it suitable as a baseline strategy for infrastructure authorities, policymakers, and material producers aiming to integrate circular economy principles into road base design.