(1) Woody plant species selection for urban forests is one of the key factors in reducing traffic noise in urban areas, and the ability of sound wave attenuation by leaves is one of the foundations for species selection. However, less references regarding the relationships between leaf morphological traits and noise reduction have been reported, especially the relationships between leaf texture (LT), leaf surface roughness (LSR), and noise reduction. (2) Eighteen arbors and shrubs were selected based on leaf texture and surface roughness characteristics, and noise reduction was measured using white noise sources in a self-designed device in a quiet laboratory at night. Then, the changes in noise reduction with LT and LSR were analyzed. (3) The noise reduction was significantly affected by LT, LSR, and their interaction (p < 0.05). The coriaceous leaf was usually more efficient in noise reduction than the chartaceous leaf, and LSR had an auxiliary effect on noise reduction. The effects of noise reduction were mainly influenced by leaf texture through physical blocking and by leaf surface roughness through interference. (4) The findings demonstrate that leaf texture and leaf surface roughness are the suitable predictors for selecting highly efficient woody plants for establishing and improving noise-reduction-oriented forests.

Creating sustainable cities requires effective traffic noise reduction strategies that use urban green spaces as nature-based solutions. Regional studies highlight the role of GSA in coping with noise annoyance, leaving knowledge gaps using day/night records of compliance rates to detect spatiotemporal mitigations across cities with varied socioeconomic states on the national scale. It was initially agreed that the COVID pandemic led to noise reduction, but this was learnt as a lesson using data from 31 Chinese cities (2018–2021). The relationships between GSA, socioeconomic factors, and daytime/nighttime compliance were examined using multivariate linear regression and maximum likelihood estimation. Novel GAI integrated with GSA and socioeconomic data. The results showed a counterintuitive negative correlation between total GSA and compliance but a positive correlation between GPC and daytime compliance. The pandemic initially boosted compliance, but this effect was not sustained. The compliance rate increased in national cities from 2018 to 2021, predominantly during the day. The positive pandemic-induced compliance increased the importance of considering human behavioral changes in urban greening in a socioeconomic background. We recommend incorporating socioeconomic factors, such as GPC, in the preparation for policymaking to reduce traffic noise when suffering unforeseen events. It is time to move beyond the sole focus on the role of green space areas in a sustainable city with quiet traffic.