UAV-based lidar systems operate at low power and are sensitive to environmental conditions that affect signal strength, penetration, and classification reliability. Nighttime acquisition removes solar background noise and is often assumed to improve lidar performance, but night humidity, dew, and fog may counteract these benefits. This study evaluates the combined effects of illumination and atmospheric moisture on UAV lidar data quality in vegetation-rich peatland environments. Daytime and nighttime lidar surveys were conducted at two eastern Canadian peatlands with contrasting surface wetness: Alfred Bog (Ontario) and Quinces Bog (Nova Scotia). Flights were flown at 40, 75, and 100 m above ground level using a UAV-mounted multi-beam lidar system. Flight-time microclimate variables were recorded using nearby automated weather stations and averaged over each mission to characterize atmospheric stability and condensation potential. Data quality was assessed using return structure metrics, intensity distributions within dense shrub cover, point duplication rates, and ground surface accuracy evaluated against independent GNSS checkpoints. At the drier Quinces site, nighttime acquisition increased third-return counts by up to 50%, increased mean intensity by approximately 20-40%, and reduced ground surface RMSE by up to 0.6 m relative to daytime flights. In contrast, nighttime flights at the wetter Alfred site exhibited increased point duplication, altered return structure, and reduced ground detection in dense vegetation, particularly during periods of fog or canopy-level moisture. These results demonstrate that the benefits of nighttime UAV lidar acquisition depend strongly on atmospheric moisture conditions. Nighttime surveys can improve data quality under dry conditions but may reduce reliability in humid or fog-prone environments.