A model proposal for emi̇ssi̇on management i̇n metropoli̇tan transport corri̇dors based on nati̇ve plant texture: A case study of Göztepe juncti̇on, D-100 Hi̇ghway

Rapid urbanization and the proliferation of fossil fuel-based vehicular mobility have escalated transportation-derived emissions (PM2.5, NOx, CO, and CO2) into a critical global threat to urban ecosystems and public health. This doctoral dissertation analyzes the efficacy of roadside afforestation strategies as a "Green Infrastructure" component in mitigating these pollutants through a data-driven, multi-dimensional decision-support framework. The primary originality of this research lies in its interdisciplinary modeling approach, which integrates biological ecosystem services with technical decision-making mechanisms. Within the scope of the study, i-Tree Eco-based carbon sequestration data and IPCC Tier 1 emission inventory protocols were synthesized with a hybrid weighting methodology comprising SWARA, DEMATEL, and Shannon's Entropy methods. Through this developed model, 32 alternative plant species including trees, shrubs, and groundcovers were optimized using the TOPSIS algorithm across 12 distinct environmental, economic, and structural criteria. Field analyses conducted at the Istanbul D-100 Highway Göztepe Junction revealed that Robinia pseudoacacia, Nerium oleander, and Hedera helix exhibited the highest performance indices. Furthermore, projections based on air quality data from Istanbul, Ankara, Izmir, and Bursa validated the regional applicability of the proposed model. The research findings confirm that "multi-layered vegetation" strategies yield a synergistic improvement in urban microclimate and air quality. This study provides a scalable and original methodological roadmap for the integration of green infrastructure solutions into transportation planning and urban design policies.