Relative Humidity Dominances in Negative Air Ion Concentration: Insights from One–Year Measurements of Urban Forests and Natural Forests

Abstract

Forests are one of the most important sources of negative oxygen ions (NAIs). NAIs have been recognized as beneficial for both physical and mental well–being, and higher concentrations of NAIs have been associated with improved health. However, the environmental factors that predominantly influence NAI concentration and their relationship with NAIs remain uncertain. This study aims to investigate the dominant factors and their impact on NAI concentration by observing NAIs and various environmental factors in two different environments (natural forest and urban forest) in the Beijing region over a one–year period. Through our investigation, we aimed to identify the key factor as well as other influential variables affecting NAI concentration. Our analysis encompassed the examination of dynamic concentration changes over multiple time scales, revealing uniform trends in both forest types. Notably, natural forests consistently demonstrated higher NAI concentration across these time scales, attributable to greater vegetation density and the stability of the forest microenvironment. By utilizing regression, correlation analysis, and structural equation analysis, we determined that relative humidity (RH) has the most significant effect on NAI concentration. Notably, both NAI concentration and RH displayed similar patterns across multiple time scales. When considering hourly average daily variation, the lowest values for both NAI concentration and RH were observed at noon, followed by an increase that persisted throughout the night. Seasonal average variation showed that both NAI concentration and RH peaked in the summer, followed by autumn. In terms of daily average annual variation, summer exhibited more days with high NAI concentration and high RH, which can be attributed to the increased rainfall during that season. Rainy weather was found to contribute to higher NAI concentration and RH levels. Furthermore, our findings revealed that on a daily scale, high RH and high NAI concentration occurred more frequently under conditions of high air temperature and low wind speed. However, the air quality index demonstrated only a minor effect in urban forest, while net radiation exhibited no significant influence on NAI concentration and RH. The fitted equations and trends of the aforementioned environmental factors with NAI concentration and RH were found to be comparable. The path analysis further corroborates these conclusions. The findings of this study indicate that RH is the primary factor driving the fluctuations in NAI concentration across various time scales, including hourly, daily, and seasonal variations. The study revealed that wind speed indirectly impacts NAI concentration by modulating RH. In contrast, air temperature influences NAI concentration both indirectly through RH and directly. The environmental factors affecting NAI concentration in the two types of forests are similar, but the degrees vary; in urban forests, wind speed, air quality index, and RH are slightly higher, while in natural forests, air temperature is slightly higher. This discovery further enhances our understanding of the underlying mechanisms and dynamic changes in NAI concentration within urban forests and natural forests. Moreover, it confirms the reliability and effectiveness of using RH as an indicator to monitor changes in NAI concentration over time.