The concentration of negative air ions (NAIs) is an important indicator of air quality. Here, we analyzed the distribution patterns of negative air ion (NAI) concentrations at different time scales using statistical methods; then described the contribution of meteorological factors of the different season to the concentration of NAIs using correlation analysis and regression analysis; and finally made the outlook for the trends of NAI concentrations in the prospective using the auto regressive integrated moving average (ARIMA) models. The dataset of NAI concentrations and meteorological factors measured at the fixed stations in the Mountain Wuyi National Park were obtained from the Fujian Provincial Meteorological Bureau. The study showed that NAI concentrations were correlated with relative humidity spanning all seasons. Water was an important factor affecting the distribution of NAI concentrations in different time series. Compared with other ARIMA models, the outlook value of the ARIMA (, ) model was closer to the original data and the errors were smaller. This article provided a unique perspective on the study of the distribution of negative air oxygen ions over time series.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126208PMC
http://dx.doi.org/10.3390/ijerph18095037DOI Listing

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