1. Introduction
Negative air ions (NAI) is a generic term for the negatively charged gas molecules and ions in the air [
1]. Negative air ions are also known as negative oxygen ions since they form negative ions based on their ability to acquire electrons, most of which are acquired by oxygen. Numerous studies have shown that NAI has many beneficial effects on human health, both physical and psychological effects [
2]. Physically, NAI have a beneficial effect on the cardiovascular and respiratory systems [
3,
4,
5]. Psychologically, NAI can improve sleep quality [
6], improve mood states [
7], and alleviate chronic depression [
8]. NAI are mainly generated by pathways involving cosmic rays [
9], radiation (emitted by the radon element of minerals) [
10], solar ultraviolet radiation [
11], lightning [
12], water shearing forces (the Lenard effect) [
3] and plants [
13]. Therefore, factors such as vegetation cover, flowing water bodies, and air humidity can be considered as important influencers of the anion content [
14]. Forests are thought to be the environments that produce large amounts of NAI. Currently, health and wellness programs involving NAI-based forests have become popular in China. At present, the concentration of NAI has become an important factor influencing the selection of forest healthcare sites. There are specific requirements for the concentration of NAI in the establishment of standards for relevant forest healthcare sites.
Along with the continuous increase in the attention focused on NAI, many researchers have successively conducted detailed studies on their biological effects [
15], clinical efficacy [
13,
16,
17,
18], effects on air quality [
19,
20,
21,
22,
23], concentration variations [
24,
25,
26,
27,
28,
29] and factors that influence this [
27,
30,
31,
32], the environment and mechanisms that produce NAI [
33,
34,
35], and the development and use of NAI resources [
36,
37,
38]. Studies have shown that the NAI concentrations in forests are much higher than indoors and in cities [
24,
31,
39], with concentrations being up to 160 times higher [
24].
Prior studies have focused more on monitoring the NAI concentrations in forests and analyzing the influence of different environmental factors on the dynamic change in forest NAI concentrations [
26,
27,
29,
32,
39,
40,
41,
42]. Among them, the main environmental factors considered were the influence of meteorological factors and stand structure on the NAI concentrations in forests. In the process of studying the diurnal distribution characteristics of NAI concentrations in forest parks, it was found that the law of diurnal variation would differ with different environmental conditions [
27,
39,
40,
41]. Although many studies have been conducted on forest NAI, current research is mainly concentrated in plains [
24,
27,
43], and related research on mountain forests is lacking, so the influence of factors such as mountain topography and altitude has not been sufficiently considered. In addition, due to the cross-influence of terrain, altitude, ecology, and environmental factors on NAI concentrations, the research conclusions are often quite varied.
Three reasons support the study of NAI in mountain forests. Firstly, with the development of urbanization and agriculture, the land resources of plains are suitable for urban construction, and arable land is in short supply [
44]. Tension due to plains land resources has caused plains forests to be continuously depleted. The area and quality of forests in plains have seriously declined [
45]. Only mountain forests, having human health value, are better preserved. It is therefore necessary to study mountain forests thoroughly in order to make the most of this resource. Secondly, existing studies have only discussed the relationship between meteorological factors and NAI concentrations [
27]; however, meteorological factors are relatively abstract and difficult to intuitively feel and judge, so it is necessary to determine NAI concentrations with the help of certain instruments and equipment. Moreover, it is difficult to directly observe these factors in mountain forests because of their complex terrain, large area, and poor accessibility, since it difficult for humans to directly reach these areas. Therefore, it is necessary to explore some easy-to-observe, non-instrument modes of measurement and indirect and direct arrival factors suitable for mountain forest characterization for use in determining the NAI concentrations in mountain forests. These indicators or factors can include terrain, altitude, forest canopy density, etc. Third, the existing studies on NAI concentration were rarely carried out in mountain forests. There are no relevant or quantitative studies on factors such as terrain and altitude. Therefore, there is an obvious need for this to be conducted.
Based on the above reasons, we selected some easy-to-observe and easy-to-judge mountain forest characteristic factors to evaluate their potential in screening the forest environment with a view to promoting health. The environment we selected for study was Taibai Mountain National Forest Park, a typical mountain forest in central China with a beautiful forest environment, rich tourism resources, and high demand in terms of forest healthcare from the surrounding urban population. We studied this park during the tourist season in 2021 under different site conditions, whereby the NAI concentration variation characteristics were analyzed, and we explored the NAI concentration change rule of the park, which can serve as a reference for the study of NAI in mountain forests.
2. Materials and Methods
2.1. Study Site Selection
The study was conducted in the Taibai Mountain National Forest Park of Shaanxi Province in China. The geographical coordinates are 107°41′23″–107°51′40″ E and 33°49′31″–34°08′11″ N. With altitudes ranging from 620 to 3511 m, it is the national forest park with the highest point of elevation in China. It is one of the mountain forests with the richest flora in temperate China. The forest area in the district is 45,725 hectares, with a forest coverage rate of 81.2%. There are about 1800 species of seed plants, belonging to 122 families and 660 genera. The main forest vegetation includes Quercus variabilis, Quercus aliena var. Acuteserrata, Quercus liaotungensis, Betula albosinensis, Betula albosinensis var. Septentrionalis, Abies fargesii, and Larix chinensis. We used the Negative Air Ions monitors in the Taibai Mountain National Forest Park, which monitors the real-time concentration of NAI.
2.2. Orthogonal Experiment Design
The experimental design was an L9 (3
3) orthogonal array [
46], as shown in
Table 1. The three factors of experimental design were terrain, altitude, and canopy density. Each factor was divided into three levels, coded as 1, 2, and 3, and a total of nine combinations were set up in this experiment, as shown in
Table 2. In addition, a control sample point was set up in the square outside the mountain forest park in front of the visitor center. As the research site (Taibai Mountain National Forest Park) is located on the northern slope of the Qinling Mountains in China, all the monitoring sites in the study belong to the forests in the northern part of the terrain. A total of 10 experimental monitoring sample points were measured synchronously to study the influence of various factors on the NAI concentrations, and the results were analyzed by range, variance, and multiple comparative analyses to determine the optimal combination with the highest NAI concentration, and the optimal combination was tested and verified. The data collection period was 1–5 May 2021, during which the NAI concentrations were calculated at different sample points. According to the time of recreational activities, we chose daytime observation. The data were collected from 6:31 a.m. to 18:30 p.m. Three samples were selected for each array combination. The statistical data is the average of the three samples. Additionally, meteorological data were collected to investigate the influence of meteorological factors on NAI.
2.3. Instrumentation
The NAI concentrations were measured using the KEC900+II negative oxygen ion monitor (Wanyi Technology Co., Ltd., Shenzhen, China). This instrument is usually calibrated in real time and has a high measurement accuracy of ≤5%. The measuring range was 10–2,000,000 ions/cm3 and ion mobility was ≥0.4 cm2/(V.s). The instrument meets the requirements of the functional specifications of the China Meteorological Administration. Air temperature, relative humidity, and wind velocity were measured using the Kestrel 5500 portable meteorological instrument (Nielsen-Kellerman Instruments Ltd., Boothwyn, PA, USA). Air temperature can be measured in a range of −10~60 °C with 0.1 °C resolution, and relative humidity is measured in the range of 0~100% with 0.1% resolution. The measurement range of wind velocity is 0.1–40 m/s with a resolution of 0.1 m/s. The atmospheric pressure was assessed using a CS106 sensor produced by Campbell Scientific, Inc., New York, NY, USA. The atmospheric pressure is measured in the range of 500~1100 hPa with a resolution of 0.3 hPa. In this test, 10 sets of monitoring instruments were used for synchronous measurement, and unified correction was performed before instrument measurement. The test time of each instrument was strictly controlled to basically ensure the synchronization of different measurement points.
2.4. Statistical Analysis
A statistical analysis system (SPSS 22.0, Chicago, IL, USA) was used to analyze the data. Functional mapping software (Origin 2019, OriginLab Ltd., Northampton, MA, USA) was used to draw the data analysis diagrams. Range analysis was used to evaluate the results of the nine different combinations [
47,
48].
2.5. Validation of the Improved Protocol
The results of the orthogonal test were used to establish an improved scheme consisting of the optimal levels of site conditions to evaluate the effectiveness of the orthogonal test method. Verification tests were then conducted during 7–12 May 2021. Two combinations were compared: (a) the improved combination based on the orthogonal array test results, and (b) the best of the nine combinations tested in the orthogonal array matrix.
4. Discussion
Forest environments have important healthcare value. NAI are important active ingredients in forest environments, playing an important role in promoting physical rehabilitation [
14,
41]. NAI have been described as vitamins found in air [
14]. Studies show that NAI can reduce the concentration of environmental particulate matter [
22], purify air [
49], kill bacteria [
50], reduce inflammation [
3], fight depression [
51,
52], and promote physical recovery [
53] and antioxidant activity [
54]. Therefore, the concentration of NAI is the basis of evaluating the health quality of forest environments. Given that China’s aging population is increasing the medical expenditure burden [
55], the need for health promotion through the healing function provided by forest environments is increasing [
56]. However, due to the expansion of cities and the development of farmland, the natural forests in the plains are gradually being destroyed and are disappearing [
44,
45]. Therefore, mountain forests will be key sites for attaining health benefits, to use the beautiful natural environment of mountain forests and take advantage of the health factors in forest environments for physical and psychological healing in many countries and regions [
56]. The concentration of NAI is one of the key environmental factors creating the healing effect of mountain forest environments [
26]. It is important to study the effect of site conditions on the concentration of NAI and to quickly identify locations with high NAI concentrations in mountain forests according to site conditions.
We found that NAI concentrations have a distinct diurnal variation profile. Specifically, NAI concentrations were highest at 14:00 p.m.–16:00 p.m. and lowest at 7:00 a.m.–9:00 a.m. This may be due to the distribution of meteorological factors during the day. We conducted correlation analysis and linear regression analysis between NAI and meteorological factors based on hourly data and found significant correlations between NAI and relative air humidity and air temperature. Relative air humidity is an important factor affecting NAI concentrations. In addition, it can be seen from the formula of oxygen-based NAI that water can produce NAI by Lenard force, and oxygen-based NAI can react with water [
9,
10,
11,
12,
13].
The forest canopy density had an important effect on NAI concentrations. The results of an earlier study [
27] on a forest environment in a plain showed that the higher the canopy density of the forest in the same area, the higher the NAI concentration. In this study, forest with a high canopy density (>0.7) was most favorable for NAI concentration. This is consistent with the results of previous studies [
40,
41], showing that the NAI concentration of mountain forest was also affected by forest canopy density. Because of the very strong positive correlation between moisture content in the air and the production of NAI [
26,
42], a high canopy density in a mountain forest has increased air moisture due to plant transpiration; simultaneously, the dense canopy cover blocks the sun’s rays, reducing water evaporation in the forest and thereby resulting in higher water content in the air of the mountain forest [
27], which is conducive to the generation of NAI. The effect of the forest canopy density on the NAI concentration in mountain forest was different at different times of day. The forest canopy density had the highest effect on the NAI concentration at noon, and the effect in the morning and afternoon was low. This is consistent with the influence of canopy density on the air humidity in the forest. Our results show that a high canopy density promoted the release of NAI, and thus enhanced the health-promoting capacity of the forest environment. This finding is similar to those obtained in earlier studies [
24,
27,
31]. In our study, we also found that the NAI concentration in the mountain forest environment with the same canopy density was significantly different at different altitudes. This indicates that the elevation and canopy density of mountain forest affect the NAI concentration. This link has not been reported in previous studies. We think that the reason for this finding may be that the superposition of two environmental factors, altitude and canopy density, in the mountain forest changed the conditions for the generation of NAI in the forest, which led to the significant difference in the NAI concentration observed in the forest. Such changes may include the following aspects: (1) temperature and humidity changes caused by altitude, (2) changes in vegetation species and leaf tip morphology caused by vertical landscape changes, and (3) changes in oxygen concentrations at different elevations.
Altitude had a significant effect on the NAI concentration. In mountain forests, elevation can not only directly affect the change in meteorological factors [
57], but also indirectly affect the distribution and morphology of plant species [
58]. All these effects can further affect the NAI concentration in mountain forests [
29]. In this study, the average NAI concentration in the sample plot at low altitude (1000 m) was the highest, and that the sample plot at low altitude (1000 m) was the highest in the morning, noon, and afternoon, a trend which is similar to previous reports [
26,
41]. Our results indicate that the mountain forest at low altitude had the highest NAI concentration and was therefore the most suitable for forest health-related activities. The reasons why altitude affects the NAI concentration were analyzed in detail and found to depend on how NAI are produced in the air. NAI can be grouped according to the different ways in which they are produced and their main compositions as natural NAI, corona NAI (generated by the corona discharge ionization), and Lenard NAI (generated by the shearing force of water) [
12,
33,
59,
60,
61]. Natural NAI are the main NAI in the forest [
33]. The production of natural NAI is affected by the activity of oxygen molecules [
33,
61]. The higher the altitude, the lower the temperature and activity of oxygen molecules, and less natural NAI are produced [
61]. In addition, with increasing altitude, the oxygen concentration in the environment gradually decreases, and so fewer oxygen molecules are available for conversion to NAI [
2,
61]. Therefore, given these many reasons, the NAI concentration at high altitude is significantly lower than that at low altitude. Therefore, health activities in mountain forests should be performed in low-altitude areas.
Terrain has a strong effect on the NAI concentration. In this study, the average NAI concentration in the sample plot in a valley was the highest, whereas that on the ridge was the lowest. At noon and in the afternoon, the NAI concentration in the valley topography was the highest; in the morning, the NAI concentration in the hillside topography was the highest; and the NAI concentration on the ridge was the lowest at all time periods. Previous studies have not reported the effect of topographic factors on the NAI concentration. However, we can infer and predict the influence of topographic factors on the NAI concentration by considering the influence of topographic factors on microclimate factors. Topographic factors of mountain forests affect forest microclimate such as air temperature, relative humidity and wind velocity [
62]. The change in these factors affects the accumulation and diffusion of anions in mountain forests, which leads to the change in the NAI concentration [
41]. The mountain forest in the valley area had the highest concentration of NAI, indicating it is the most suitable for forest human-health-related activities. In addition, the mountain forest in the ridge area had the lowest NAI concentration, indicating it to be the most unsuitable for activities to gain health benefits from the forest. Therefore, health-related activities in mountain forests should preferentially be conducted in the valley area.
In conclusion, our findings show that different site selection conditions and environments have different effects on NAI concentrations. For example, the concentration of NAI was the highest in the S6 combination, but the lowest in the S7 combination. Our findings also suggest that altitude and crown density have significant effects (
p ≤ 0.01) on NAI concentrations (
Figure 3). The results of this study provide a theoretical basis for the rapid selection of the best healthcare sites in mountainous forests.
The limitation of this study is that only a short-term monitoring and analysis of NAI concentration in mountain forests was conducted, and no comparative study was conducted on NAI concentration in mountain forests of the northern and southern slopes. Future studies should establish long-term monitoring stations and comparative studies of mountain forests on the northern and southern slopes, which are conducive to a comprehensive analysis of NAI concentration in mountain forests affected by terrain, altitude and community.