Abstract
Asphalt pavement will emit Volatile Organic Compounds (VOCs) during life cycle, posing environmental and health risks. Precise understanding of the emission characteristics of asphalt VOCs will facilitate the formulation of targeted measures for reducing emissions. Simulating the emission characteristics of VOCs from asphalt under laboratory conditions is an effective method for predicting asphalt VOCs pollution and implementing effective control measures. In this study, a quality control method for qualitative and quantitative detection of asphalt VOCs in laboratory settings was established based on sample storage time, asphalt sources, and temperature sensor positions. Furthermore, the study investigated the influence of mixing speed and sampling pump speed during asphalt VOCs generation on the emission characteristics. The results demonstrate that the quality control methods exhibit excellent reproducibility and reliability, making them valuable for future research and emission control strategies. Furthermore, the total concentration of asphalt VOCs increases with higher mixing speeds, but stabilizes when the mixing speed reaches 750–1250 r/min. As mixing speed increases, the proportion of alkane groups significantly decreases, while the proportion of aldehydes markedly increases, with the overall proportion remaining relatively stable. Decreasing sampling pump speed leads to a gradual increase in asphalt VOCs concentration. At lower pump speeds, a nonlinear increase in concentration occurs due to VOCs enrichment effects. Asphalt VOCs concentrations exhibit a proportional increase with sampling pump speeds exceeding 1000 ml/min. Finally, based on the results of the three-level analysis of "total concentration-group-substance" and taking into account the energy consumption, it is recommended that the mixing speed be set at 1000 r/min and the sampling pump speed be set at 1000 ml/min for the generation and collection of asphalt-related VOCs. This study can provide a reliable method for generating and collecting asphalt-related VOCs and offer critical insights for optimizing VOCs emission reduction strategies.
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