Negative air ions (NAIs) are a natural component of air and have a positive impact on the health of urban residents. Few studies have focused on the relationship between NAI concentration (NAIC) in the urban atmosphere and environmental factors, such as meteorological factors and air pollutants. Therefore, we established observation points in Zhongshan Park in downtown Shanghai, China, and continuously measured and recorded changes in NAIC for one year. We also monitored nine meteorological factors and six atmospheric pollutants. Through correlation analysis and multiple linear regression analysis, the key factors influencing NAIC were screened, and the effects of those factors on NAIC were explored using the random forest algorithm. The results show that NAIC is most sensitive to humidity, followed by radiation and temperature, and finally to PM2.5. Humidity is the most critical factor, primarily because it directly affects the formation of NAIs from both the environment and vegetation. Furthermore, our results reveal that the mechanisms through which NAIC is influenced by the same factor varies seasonally. We analyzed the relationship between NAIC in an urban atmosphere and environmental factors by using big data, which is a new method for studying the relationships between NAIs and environmental factors. Our results indicate potential explanations for the mechanisms underlying NAI response to various environmental factors.

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Negative air ions (NAIs) exert positive effects on human health. Urban green spaces produce NAIs and perform valuable ecological functions; this phenomenon has attracted much attention. However, NAIs in urban green spaces are influenced by many factors, leading to extremely large variability in their concentrations and complicating their measurement. Therefore, we collected observational data on NAI concentrations (NAICs), as well as on other environmental factors for one year in Shanghai City Park. We then used this data to construct an indicator of NAI variability (NAIV); we understand NAIV to be dependent upon NAIC, and study of the derivative can better reflect the driving force and dominant factors of the original function. Based on a preliminary investigation of correlation, and on a multiple linear regression analysis, we used a random forest algorithm to evaluate the influence of various factors that affect the variability of NAIs. The results show that “water factors,” whose main contribution is humidity, exert the most influence, followed by “phenology factors,” whose main contribution is temperature, and “particulate factors,” whose main contribution is PM2.5. High humidity, high temperature, and low PM2.5 concentration enrich NAI generation and extend their lifetimes, thus helping to maintain them within a relatively stable range. In this study, the main driving forces that govern NAI changes were shown to be humidity, temperature and particulate matter. Our results may help to deepen our understanding of NAI characteristics and applications in urban green spaces.

Polymer membranes with fixed pore size or narrow pore size distribution can be used for special separation. However, polymer membranes prepared by conventional method usually have wide pore size distribution and the pore size is hard to control. Here we prepared a porous polymer membrane with uniform pore size via spraying a blend of polystyrene (PS) and polyethylene oxide (PEO) on a filtration paper. Dissolving the water-soluble component (PEO) forms the pore and varying the ratios of PEO in the blend controls the pore size. The pore size and size distribution are also affected by processing parameters, such as the flow rate of solution and carrier gas, and gap length. The morphologies of the membrane are observed using scanning electron microscopy (SEM). The novel polymer membrane with controllable and uniform pore size will be used for the separation of solutes with predictable sizes.