Plant stomatal conductance determined transpiration and photosynthesis both contribute to the enhanced negative air ion (NAI)

Negative air ion (NAI) has been widely recognized to be regulated by plant photosynthesis. However, their quantified relationship had seldom been validated. In this study, plant photosynthesis-related traits (including leaf area-specific photosynthesis An, transpiration rates El, stomatal conductance gs, photosynthetic electron transport rate ETR) and leaf area-specific NAI (NAIc) were measured to qualify their relations with ten different species in a thermostat. Sap flow measurement was conducted on 15 individuals of Camellia japonica L. in an open-top chamber (OTC) to inverse sap flow based-stomatal conductance (GSf), as a proxy of whole individual photosynthesis. We also conducted gas exchange measurements on these individuals and compared them with their GSf. Three micro-meteorological parameters, including air temperature (Ta), relative humidity (RH) and radiation (Ra) and NAI were synchronously monitored with sap flow measurement. Significant differences were observed in NAIc among the 10 species, and was highly determined by their An, El and gs. However, since RH in the thermostat was stable at 70%, we could concluded that the NAIc difference among species was determined by the gs-related photosynthesis, rather than the El- related transpiration. In the OTC experiment, before the C. japonica individuals were moved in, Ta, RH and Ra accounted for 89% of the total NAI variation. However, after the C. japonica were moved in, the contribution of the three parameters decreased to 40%, and the new model only provided 46% of NAI variation. Since gs and An of C. japonica individuals were well explained by the GSf (R2 = 0.94 and 0.91 respectively), which proved GSf a good proxy of gs and An. GSf during the daytime was then considered in the model, and 76.88% of NAI variances were accounted. Even though some limitations such as the disturbance of air quantity index (AQI) still exist in our study, we provided a more efficient way to inverse the NAI dynamics in the region of vegetation.