Comparative study on asphalt performance grading using different pavement temperature prediction models

To address more frequent extreme high temperatures under climate warming, this study evaluates the responsiveness and applicability of asphalt PG grading models under warming scenarios. Three models, SHRP, LTTP bind 2.1 and LTTP bind 3.1, are systematically compared across 342 Chinese cities and seven typical regions. LTTP bind 3.1 shows the strongest sensitivity to rising temperatures, with its dominant grade shifting to PG64. LTTP bind 2.1 mainly yields PG52-10, while the conventional SHRP model is dominated by PG46-10 and poorly adapts to continuous warming. A shorter meteorological statistical period increases high-temperature grades for all models. Pavement high-temperature effects decay with structural depth. A tiered comparison scheme demonstrates model discrepancies under identical climate inputs. Since national pavement temperature field data are lacking, these findings reflect relative differences among empirical models rather than validated engineering selection criteria. This work supports developing climate-adaptive PG grading systems for asphalt pavements.