Concentrations Of Negative Air Ions Research Articles

Temporal Dynamics of Negative Air Ion Concentration and its Relationship with Environmental Factors: Results from Long-Term On-Site Monitoring

Temporal Dynamics of Negative Air Ion Concentration and its Relationship with Environmental Factors: Results from Long-Term On-Site Monitoring

Temporal Dynamics of Negative Air Ion Concentration and its Relationship with Environmental Factors: Results from Long-Term On-Site Monitoring

Temporal Dynamics of Negative Air Ion Concentration and its Relationship with Environmental Factors: Results from Long-Term On-Site Monitoring

Effects of Different Site Conditions on the Concentration of Negative Air Ions in Mountain Forest Based on an Orthogonal Experimental Study

The negative air ions (NAI) in a forest play an important and positive role in promoting the health of people using the forest for recreation. The purpose of this study was to explore the environmental characteristics that can effectively represent high concentrations of NAI in mountain forests to help the recreational users to seek out sites with high NAI concentrations for personal health reasons. In order to achieve this goal, we selected the mountain forest of Taibai Mountain National Forest Park, Shaanxi Province, China, as the research object and adopted an orthogonal experimental design with three factors and three levels to study the effects of terrain, altitude, and forest canopy density on the forest NAI concentrations. The results show that obvious peak–valley fluctuation occurs during 6:31 a.m. to 18:30 p.m., with the highest concentration of NAI at 8:00 a.m. (Average: 163 ions/cm3) and the lowest at 16:00 p.m. (Average: 626 ions/cm3). The altitude (p < 0.01) and canopy density (p < 0.05) were found to significantly affect NAI concentrations. The combination of site conditions in the mountain forest observed to have the highest NAI concentrations was valley topography, low altitude, and high canopy density. In addition, the highest NAI concentration was between 14:00 p.m. and 16:00 p.m., under this combination, which was thus identified as the most suitable time for health-promotion activities in mountain forests. The results provide insights into the NAI concentration characteristics and variations, along with identifying important environmental factors for the selection of health-promotion activities in mountain forests.

Modeling the response of negative air ions to environmental factors using multiple linear regression and random forest

Negative air ion (NAI) plays a vital role in promoting the psychological and physiological functions of the human body and is an essential indicator for measuring the air cleanliness of a given area. In this paper, we presented and compared the results of two methods for identifying the main environmental factors affecting changes of NAI in a warm-temperate region of China. NAI concentration was estimated based on measured data during the main growing season in a warm-temperate forest and was used as the dependent variable in the traditional multiple linear regression and random forest models. Air pollutants and certain weather, radiation, and soil factors were selected as predictors based on their potential influence on NAI. Two methods were applied for the analysis, and the latter was a non-parametric alternative based on an ensemble of classification and regression trees. We compared the precision of the two models, and the variables of each method on the basis of their levels of importance; Independent samples was used in model validation, then we discussed the important environmental factors affecting changes of NAI concentration for both linear and nonlinear perspectives, along with the potential implications of environmental factors on NAI. The random forest model showed a higher accuracy comparison with the multiple linear regression model. Furthermore, the analysis also indicated its better performance by using independent test data for 10-fold cross-validation of the random forest model, and showing that this method has potential for broad-scale application in the assessment of environmental-factor influence on NAI. Certain selected variables that were common to both models (particulate matter 2.5, soil moisture, and relative humidity) appeared to influence NAI to a relatively large extent, demonstrating the decidedly influential role of these parameters on NAI concentration.

Generation of Negative Air Ions by Use of Piezoelectric Cold Plasma Generator

The negative air ions (NAI) are used for the removal of particles or droplets from the air. In this study, three types of piezoelectric cold plasma generators (PCPG), in combination with cylindrical electrostatic ion filters, are applied for NAI production. The high voltage on the filter cylinder is induced by the electric field from the piezoelectric transformer of the PCPG. To achieve the dc bias, the cylinder of the electrostatic filter is connected to the ground over ultrafast switching diodes. The ion concentrations are measured for different airflows, PCPG powers, and electrostatic filter geometries. The NAI concentration in the order of magnitude of 107 cm−3, and a negative-to-positive ion concentration ratio of over 200 is reached. The production of ozone is evaluated and the PCPG configuration with a minimum ozone production rate is proposed. The ozone concentration below 60 ppb is reached in the airflow of 90 m3/h.

Pollution Index and Air Ion Variation in Different Vegetation area at the Rural Station Bhilawadi (16059’N, 740 28’E)

All are surrounded by air ions which shows the good and bad impact on us. These airborne particles have charge and conductivity. These are positive and negative air ions. The negative air ions have a positive effect on human health. We feel happy, relaxed, and breath easily due to them. But positive air ions are responsible for discomfort, headache, high blood pressure, nervousness in human life. The air ion concentrations in Grape, Sugarcane, Chickpea, and Onion vegetation in rural area Bhilawadi (16059’20” N, 74028’2” E) is measured with the help of a Gerdien condenser-based air ion counter developed and designed at A.C.S. College, Palus. Temperature, humidity, transpiration, radon exhalation, wind speed is responsible for variation in air ions. Onion, sugarcane, grapes, and chickpea have a higher concentration of negative air ions than positive air ions. Ionization by cosmic rays and gamma radiation is almost constant in daily cycles. Air ion concentration near the ground varies mostly with the exhalation of 222Rn and its progenies. Due to ionization, photosynthesis, transpiration, and radon exhalation process of vegetations ion concentration are different. The pollution index and air ion assessment coefficient show good air quality of sugarcane and onion as a natural air ionizer.

Different Time Scale Distribution of Negative Air Ions Concentrations in Mount Wuyi National Park.

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 (0, 1, 1) 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.

Air Quality and Key Variables in High-Density Housing

The high-rise and high-density housing development in nearby industry relocations is a general urban sprawl phenomenon in fast-growing cities in Southern China. Aside from the low price, the improved air quality in the suburban area is always a reason for home buyers, but the consistent monitoring of air quality and knowledge about how to plan housing estates are lacking. This paper investigates the relationship between the housing morphology and the air quality in three housing estates in Shenzhen. This research utilizes on-site monitoring equipment to examine negative air ions (NAIs) and fine particulate matter (PM2.5) and the Computational Fluid Dynamics (CFD) simulation to examine the air flow. This study reveals the effect of the urban form on the concentration of NAIs and PM2.5 in spatial variation. A correlation study between the configuration variables of the urban form and the CFD air flow pattern helps to identify the key variables influencing the air quality. This study concludes that in housing estates with good air quality of surroundings, the building density has no remarkable effect. However, the footprint of buildings, the layout of podiums, the roughness length of the building, the distance between buildings, the open space aspect ratio and the mean building height may have a remarkable impact on the air flow and quality. These findings may encourage high-density housing development and provide planning guidance for the configuration of housing forms in Southern China and subtropical climate regions around the world.

Comprehensive Evaluation of Healthcare Benefits of Different Forest Types: A Case Study in Shimen National Forest Park, China

Studies have shown that contact with nature plays a crucial role in the amelioration of human health. Forest therapy has recently received widespread attention as a novel and subsidiary treatment approach for stress recovery and health promotion. However, there is a lack of ample research on the comprehensive evaluation of the forest healthcare benefits. Moreover, it is not entirely clear what kind of forest types and seasons are suitable for forest therapy activities and how healthcare forests should be constructed and managed. From September 2019 to January 2020 and May to August 2020., five forest types of Phyllostachys edulis forest, subtropical evergreen broad-leaved forest, Liquidambar formosana forest, Cunninghamia lanceolata forest, coniferous and broad-leaved mixed forest and a forestless control group in Shimen National Forest Park, Guangzhou City, Guangdong Province, China were selected. Variations in the character of negative air ion concentration, air oxygen content, human comfort index and phytoncide relative content were analyzed. Principal component analysis and systematic clustering were used to construct forest comprehensive healthcare index and evaluation grade in order to assess the healthcare benefits of different forest types. In terms of negative air ion concentration, the subtropical evergreen broad-leaved forest was far ahead of the other forest types throughout the year, while the forestless control group was the worst. All stands reached the annual maximum in summer, followed by spring, autumn and winter. From the perspective of air oxygen content, summer > spring > autumn > winter, among them, all forest stands clearly exceeded the normal atmospheric oxygen content (20.9%) in the first three quarters. Moreover, the air oxygen content of coniferous and broad-leaved mixed forest was the highest in five forest types; the forestless control group was the lowest. Judging from the human comfort index, in the whole year, all forest types, including the forestless group, were at the comfortable level and above. However, the five forest types still differed greatly in diverse seasons, among which Phyllostachys edulis forest and subtropical evergreen broad-leaved forest were superior to Liquidambar formosana forest, Cunninghamia lanceolata forest, coniferous and broad-leaved mixed forest in spring and summer, while it was in reverse in autumn and winter. In view of the phytoncide relative content, the subtropical evergreen broad-leaved forest was the highest, followed by the Cunninghamia lanceolata forest. The relative content of phytoncide was released more in summer, second, by spring, autumn and winter. Furthermore, establishing forest comprehensive healthcare index (FCHI = 0.1NAICi + 0.35AOCi + 0.27HCIi + 0.28PRCi), according to the FCHI value, it was divided into five rating levels. Overall, the comprehensive healthcare index of the five forest stands distinctly outperformed the forestless control group in all seasons. In addition, the five forest types were at level I in spring and summer. From the comprehensive data of the whole year, the comprehensive healthcare index of the coniferous and broad-leaved mixed forest was the best, followed by the subtropical evergreen broad-leaved forest. The forest environment has a favorable influence on the human body and mind, so it is suggested that citizens go to the forest environment regularly for healthcare and physical and mental washing. In terms of the forest healthcare benefits, the best seasons for forest therapy in Shimen National Forest Park are spring and summer; autumn is suitable as well. When planning and constructing the forest therapy bases in Shimen National Forest Park in the future, coniferous and broad-leaved mixed forests should be allocated more in the stand transformation to promote forest healthcare benefits. Protecting and developing the landscape resources of the subtropical evergreen broad-leaved forests should be paid close attention, as well as making rational use of their health activity space.

The Impact of Using Interactive Panels in the Learning Process on the Main Parameters of the Indoor School Environment

Summary. Introduction: Active introduction of electronic learning tools in educational institutions poses new health risks to school-age children. Creating a modern and secure digital educational environment requires constant monitoring of the conditions and modes of use of new electronic tools, the diversity of which is changing rapidly. The purpose of this work was to assess certain parameters of indoor school environment influenced by the use of interactive panels (IPs), an e-learning tool of the latest generation. Materials and methods: We studied the parameters of electromagnetic radiation, microclimate (air temperature and relative humidity), artificial lighting levels, chemical composition of indoor air, concentrations of positive and negative air ions during the school day in classrooms with and without interactive panels. The measurements were carried out in accordance with the approved methods of laboratory and instrumental research, and the results were then assessed for compliance with current sanitary rules and regulations. Statistical processing of the results was carried out using parametric methods of statistical analysis. Results and conclusion: Indices of the microclimate and air ions in IP-equipped classrooms demonstrated a more pronounced negative dynamics during the school day. Our findings indicate the need for hygienists to pay close attention to the problem of using new electronic teaching aids and interactive panels in particular, to continue research in the area under study in order to elaborate hygienic regulations for applying IPs in the classroom and to prevent overwork and health risks to school-age children.

Analysis of Eco-Tourism Climate Resources in Xingwen, China Based on the Comfort Index and the Negative Air (Oxygen) Ion

The present work investigates an analysis of Eco-Tourism Climate Resources in Xingwen, China based on the Comfort Index and Negative Air (Oxygen) Ion (“NAI” for short in this article) concentration. The daily temperature, precipitation, wind speed, sunshine hours, and relative humidity data of the Xingwen National Meteorological Station from 1999 to 2018, as well as the NAI data of Feiwu Cave station and Shoushan Lake station in Xingwen of 2018 were used in this study. Based on the analysis of the characteristics of basic meteorological elements, the index of climate comfort of human living environment and the NAI variation in Xingwen, the eco-tourism climate resources in this area were evaluated comprehensively. The results show that: The climate is mild, the precipitation is abundant and the seasonal variation trend of precipitation and heat is similar in the study area. The annual average temperature of this area is 17.8°C, the annual average precipitation is 1096 mm, the annual average precipitation days are 186 days, the annual average relative humidity is 81%, the annual average wind speed is 1.3 m/s, and the annual average sunshine hours are 999 h. The living environment comfort level reaches the “comfort” level for 6 months per year. In addition, the concentration of NAI in Xingwen remains at the highest level 7 throughout the year, and the rate of good air quality is extremely high. Overall, the study area has high-quality ecological climate resources that are conducive to the development of forest recuperation, leisure and vacation and other ecological tourism activities.

Plant-based release system of negative air ions and its application on particulate matter removal.

Particulate matter (PM, especially PM2.5 with diameter 2.5 microns) has been regarded as the major air pollutant. Negative air ions (NAIs) could electrically charge PM and remove it much more efficiently. In this study, a bio-generator of NAIs has been developed, which helps plants to generate NAIs at around 100×106 ions/cm3 under pulsed electrical field (PEF) treatment. By using the bio-generator, PM2.5 concentration in a growth chamber could be reduced from around 500 to near 0µg/m3 within 5minutes. It could also be used to remove continuously generated PM. Upon PEF treatment, genes encoding oxidoreductases and other enzymes were up-regulated, some of which might contribute to the generation of superoxide anions (one of NAIs). On the other hand, the emission of large numbers of electrons from the surface/edge of plant leaves has been detected upon PEF treatment and these electrons might be captured by surrounding air molecules to generate high concentration of NAIs.

An inversion model for estimating the negative air ion concentration using MODIS images of the Daxing'anling region.

The negative air ion (NAI) concentration is an essential indicator of air quality and atmospheric pollution. The NAI concentration can be used to monitor air quality on a regional scale and is commonly determined using field measurements. However, obtaining these measurements is time-consuming. In this paper, the relationship between remotely sensed surface parameters (such as land surface temperature, normalized difference vegetation index (NDVI), and leaf area index) obtained from MODIS data products and the measured NAI concentration using a stepwise regression method was analyzed to estimate the spatial distribution of the NAI concentration and verify the precision. The results indicated that the NAI concentration had a negative correlation with temperature, leaf area index (LAI), and gross primary production while it exhibited a positive correlation with the NDVI. The relationship between land surface temperature and the NAI concentration in the Daxing’anling region is expressed by the regression equation of y = -35.51x1 + 11206.813 (R2 = 0.6123). Additionally, the NAI concentration in northwest regions with high forest coverage was higher than that in southeast regions with low forest coverage, suggesting that forests influence the air quality and reduce the impact of environmental pollution. The proposed inversion model is suitable for evaluating the air quality in Daxing’anling and provides a reference for air quality evaluation in other areas. In the future, we will expand the quantity and distribution range of sampling points, conduct continuous observations of NAI concentrations and environmental parameters in the research areas with different land-use types, and further improve the accuracy of inversion results to analyze the spatiotemporal dynamic changes in NAI concentration and explore the possibility of expanding the application areas of NAI monitoring.

Study on the change of negative air ion concentration and its influencing factors at different spatio-temporal scales

Many studies have shown that negative air ions (NAIs) are beneficial for human health. Therefore, the spatial and temporal variations of NAIs and their influencing factors have attracted much attention. The Wudalianchi Scenic Area was selected as the research area in which to determine the differences of environmental factors that influence NAIs at different time and space scales. The sampling frequency of the field observation data was 1 h. NAI, meteorological factors, gas pollutants, and particulate matter were monitored simultaneously. Pearson correlation analysis, linear regression analysis, principal component analysis, and the Random Forest algorithm were used to quantify the relationship between NAIs and the influencing factors. The results revealed the following: (1) The NAI concentration from least to greatest appeared in the following order: open space (blank) (843 ions cm−3) ≈ lake (892 ions cm−3) < forest (2871 ions cm−3); (2) The diurnal variation of NAIs generally presented a U-shaped distribution, and was high in the early morning, decreased at noon, and gradually increased in the evening, with a peak time from 7:00 to 11:00; (3) There may be seasonal variations in the correlation between NAI concentration and single environmental factors, and the correlation between NAI concentration and air temperature was found to be positive in the spring and negative in the summer and autumn, and the effect of wind speed was in contrast to that of temperature; thus, there were seasonal differences in the synergistic relationship between NAI concentration and some environmental factors. NAI concentration was susceptible to various environmental factors, such as gas pollutants and particulate matter, in the spring and autumn; (4) The sensitivity of the NAI concentration to different factors in order from greatest to least was found to be as follows: inside the forest, ozone > PM10 > temperature > radiation; outside the forest, humidity > ozone > NO. In general, the relationships between the NAI concentration and the influencing factors were greatly affected by the observed spatio-temporal scale. The research results are of great significance to the construction of forest healthcare.

Factors influencing the concentration of negative air ions during the year in forests and urban green spaces of the Dapeng Peninsula in Shenzhen, China

Negative air ions (NAIs) benefit the mental and physical health of humans, but rapid urbanization can decrease the abundance of NAIs. Quantifying the spatial and seasonal distribution of NAIs and determining the factors that influence the concentration during urbanization is thus essential. In the present study of a typical developing urban district in southern China, negative air ion concentrations (NAICs) in 60 forests sites and 30 urban green spaces were quantified on seven consecutive days in each of the four seasons. Large seasonal variations in NAIC were revealed in forests and urban green spaces with trough values in summer. NAIC progressively decreased from forests to urban green spaces and was influenced by local land morphology, vegetation characteristics, and climatic factors. The vast, heavily vegetated northeastern region was the richest area for NAIs, whereas the narrow central region (urbanized area) was the poorest, implying dramatic impacts of urbanization on the spatial distribution of NAIs. The relationship between air temperature and NAIC was better fitted with a quadratic equation than a linear equation. Moreover, the NAIC was more sensitive to local morphology in urban green spaces than in urban forests, indicating the vulnerability of NAIs in urbanized areas. Therefore, the appropriate design of local urban morphology is critical.

Generating Negative Air Ions in Construction Waterscapes at a Garden Scale

High concentrations of negative air ions (NAIs) and low concentrations of positive air ions (PAI), along with a low monopole coefficient (PAI/NAI), are likely to provide physiological and psychological benefits to the humans. A water body produces NAIs through the Lenard effect. This concept can be applied in designing garden waterscapes in residential buildings to provide fresh and healthy air for urban residents. In this study, we conducted several experiments to assess the effectiveness of different waterscape designs in producing air ions. The results revealed that increasing waterfall tiers, slopes, impact points, widths, and heights increased the NAI concentrations and reduced the values of monopole coefficients, thus providing health benefits to humans. In particular, increasing waterfall tiers and slopes increased the NAI concentrations most substantially. Moreover, we established a composite waterscape and determined that it produced fewer NAIs along with a less favorable monopole coefficient compared with the data observed at the experimentally adjusted tiers and slopes. Therefore, we suggest that simple waterscapes with multiple waterfall tiers or steep waterfall slopes should be favored over complex waterscapes. Such simple designs can help construct a garden that provides health benefits.

Relationship of plant abundance, air temperature and humidity with negative ions based on control experiment

Previous studies on negative air ion (NAI), an important index for evaluating atmospheric quality, has been focused on field observation, and less on NAI under controlled condition. In this study, the NAI concentrations of different individual abundance of Liquidambar formosana and Taxus wallichiana were continuously monitored under the same climatic conditions in Hushan Experimental Base of Qianjiangyuan Forest Ecosystem Research Station, Zhejiang Province from September to October 2018. Changes of NAI concentration were monitored under different levels of air temperature and relative humidity to explore the effects of forest vegetation and meteorological factors on NAI. The results showed that both species significantly increased the NAI concentration. Plant abundance was positively correlated with the NAI concentration, and the relationship between them fitted the quadratic function with the plant abundance ranging from 0 to 50. The fitting equations for L. formosana and T. wallichiana were as follows: y=-0.0484x2+4.7005x+345.7 (R2=0.62), y=-0.0207x2+1.9189x+365.91 (R2=0.34). There was a significant positive correlation between NAI concentration and air temperature in the range of 5-30 ℃ with a fitting equation of y=0.4139x2-9.2229x+89.919 (R2=0.92). The NAI concentration and the relative humidity of air in the range of 56%-87% were positively correlated with a fitting equation of y=3.6508e0.0526x(R2=0.94).

Review on Research of the Negative Air Ion Concentration Distribution and its Correlation with Meteorological Elements in Mountain Tourist Area

This paper focuses on the research progress of the negative air ion concentration distribution characteristics and its correlation with meteorological elements in mountain tourist areas for recent decades in China. Many researches showed that the distribution of negative air ion in mountain tourist areas has obvious daily and seasonal variations, and its space changes also have regularity. In a day, the NAI concentration will appear alternately with peaks and troughs. The changes of NAI concentration are the summer, autumn high, winter and spring low, the highest in summer, the lowest in winter. In the middle and low altitude areas, NAI concentration is positively correlated with elevation, and negative correlation in high altitude. The concentration of NAI is related to wind speed, air humidity, air temperature, solar radiation, weather conditions, and other meteorological elements. Most research results show that humidity is the most important meteorological factor affecting NAI concentration. The NAI concentration in mountainous scenic spots is significantly positively correlated with relative humidity and rainfall intensity, positively correlated with wind speed and solar radiation, negatively correlated with air temperature. However, due to different sources of monitoring data, observations difference in time, different sample size and other elements, the conclusions on negative air ion concentration distribution characteristics and its correlation with the meteorological factors are not entirely consistent. Negative air ion monitoring equipment should be gradually standardize to ensure the reliability of monitoring data in the future, while we should take advantage of years of continuous observations to carry the study of correlation between negative air ion and meteorological factors, and this will provide a theoretical basis for negative air ion concentration forecasts.

Random Forest Algorithm for the Relationship between Negative Air Ions and Environmental Factors in an Urban Park

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.

Studying and substantiation of the method for normalization of air­ionic regime at industrial premises at the ultrasonic ionization of air

We report results of investigations on normalization of the air-ionic mode at premises with ultrasonic ionization of humidified air. We substantiated an increase in the concentration of negative air-ions with complex influence of the balloelectric effect and ultrasonic cavitation. We established that the concentration of negative air-ions increases almost in six times at the use of distilled water as a source of air-ions under the action of an ultrasonic generator with a power of 10 W at a distance of 0.5 m. At the same time, there is no generation of ozone and nitrogen oxides due to the combined influence of ultrasonic cavitation in a surface layer of water and the balloelectric effect. We proved that the concentrations of negative and positive air-ions increase due to changes in physical-and-chemical properties of water and the emerging mechanical-and-chemical phenomena with a decrease in the degree of water mineralization of water. We proposed a mechanism for formation of air-ions in the humidified air of industrial premises under the combined action of the balloelectric effect and ultrasound. We substantiated that improvement in the quality of the air-ionic composition of air in industrial premises takes place at a temperature of demineralized water of 20‒25 °C and a directed airflow of 6 m/s towards a working zone, with the combined action of the balloelectric effect and ultrasound, which improves sanitary and hygienic working conditions. We proposed a structure of an automated control system for the air-ionic mode of a working area of industrial premises under artificial air-ionization with a use of an air-ions generator and a ventilation system. It will make possible monitoring and processing of information on technological, electrical and microclimatic parameters, adjusting, coordination of work and joint managing of devices of a ventilation system and an ultrasonic generator of air-ions