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BackgroundAn outbreak of COVID-19 occurred on the Diamond Princess cruise ship in January and February 2020. We analysed information about cases to infer transmission dynamics and potential modes of transmission.MethodsWe collected the daily number of 197 symptomatic cases, and that of the 146 passenger cases in two categories, i.e. those who stayed and did not stay in the same stateroom. We retrieved the quarantine details and the ship’s 14-day itinerary. We searched the websites of national/local health authority along the cruise routes and local news using Google for locally confirmed cases associated with the ship. We obtained the design of air conditioning and sewage treatment of the ship from literature. We back-calculated the dates of infection from the epidemic curve and compared with the start of on-board quarantine.ResultsMajor infections started on Jan 28 and completed by Feb 6 for passengers except those who stayed in the same stateroom with infected individual(s). No other confirmed cases were identified among the disembarked people in Hong Kong except an 80 years old passenger. No confirmed cases were reported in three other stopovers between Jan 27-31 associated with disembarked passengers or visitors from the ship, however two Okinawa taxi drivers became confirmed cases in association with driving the ship passengers. Infection among passengers after Feb 6 was limited to those who stayed in the same stateroom with an infected passenger. Infections in crew members peaked on Feb 7, suggesting significant transmission among crew members after quarantine on Feb 5.ConclusionsWe infer that the ship central air conditioning system did not play a role, i.e. the long-range airborne route was absent in the outbreak. Most transmission appears to have occurred through close contact and fomites.Significance StatementTransmission by the long-range airborne route for SARS-CoV-2 in the 2020 Diamond Princess Covid-19 outbreak has been debated with significant implication for intervention. We found that the transmission by close contact and fomite explains the outbreak, and the central air-conditioning system did not play a role, demonstrating the importance of social distancing, good hygiene and maintaining good building ventilation for intervention.

This study examined indoor air pollutants and their health effects on allergic rhinitis in 3194 employees of 226 bus station halls and then constructed a nomogram model to predict allergic rhinitis risk in those employees. Indoor air temperature, relative humidity, PM10 , PM2.5 , total bacteria, and total fungi were measured, and questionnaires were used to collect basic station information and employee health information. The results revealed that the over-standard rates of PM10 , PM2.5 , total bacteria, and total fungi were 18.16%, 31.13%, 2.22%, and 55.89%, respectively. Seasonal variations were found in temperature, relative humidity, and PM2.5 . Passenger flow could affect temperature, and total bacteria. Central air conditioning could affect total bacteria. A total of 15.90% of the employees were diagnosed as allergic rhinitis by physicians. Relative humidity, fungi, self-reported allergic rhinitis symptoms, and exposure to smoking were the influencing factors for allergic rhinitis. These four variables were incorporated to construct a nomogram. The concordance index of the nomogram was 0.775 (95% CI: 0.745-0.806) and 0.749 (95% CI: 0.715-0.783) for the training cohort and test cohort, respectively. The calibration plot revealed that the nomogram model exhibited good discrimination and consistency. This nomogram model may help predict the occurrence of allergic rhinitis.

Peak shaving can be realized by applying appropriate control on central air conditioning loads due to their large proportion and thermal energy storage characteristics. Simplified model of single central air conditioner is established by analyzing its operating principle. Based on individual model, optimal control model of central air conditioning loads for participating in peak shaving is proposed. Objective is to obtain maximum loads of peak shaving. Constraints take peak shaving and users’ comforts into consideration. It should be noted that this optimization model is a mixed integer linear programming and can be solved conveniently. Based on the test platform for central air conditioner, the correctness of individual model can be verified. The effectiveness of optimal control model for peak shaving is verified by simulation results.

This paper presents a study on a mechanically ventilated Trombe wall that adds additional windows to the storage wall. The mechanically ventilated Trombe wall is located on the south side of the house with a central air conditioning and air circulation system. To reduce the heating load, during the heating period, the heat from the Trombe wall air channel is sent to the air conditioning room, from where it is then distributed and stored throughout the house by way of air circulation. Taking a house located in Miyazaki, Japan as an example, we conducted an actual survey to understand the situation of heat utilization of the Trombe wall and used numerical simulations to examine the effective method of heat utilization of the Trombe wall. Results showed that in all-day air conditioning, even when sending the air in the Trombe wall to the air-conditioned room, the temperature of the Trombe wall remained high. The heating load was reduced by sending the air from the Trombe wall to the central air-conditioned room and installing the large heat capacity material on the floor in the Trombe wall.

Liquid desiccant technology in central air conditioning system is very promising, however, rare researchers proposed to carry out it on household liquid desiccant air conditioner. In this paper, a two-dimensional heat and mass transfer theoretical model of cross flow dehumidifier for household split air conditioner has been established, and it is shown that the model established has a good accuracy and the relative error is less than 3.72% by comparing the simulation results with the experimental data in the literature. Based on the model, a series of experiments are conducted and the experiment data is adopted to fit the correlation formula of NTU m and Le . The results show that the model established has a good reaction to the actual situation. Furthermore, the influence of air, solution inlet conditions on the dehumidification performance of the system has been discussed in the paper.

Real-time optimal control is widely adopted in central air-conditioning systems to improve the building energy management efficiency by adjusting system controllable variables according to system o...

This paper takes a data center air-conditioning cold source system as the research object. According to the historical operating data of the cold source system in the transition season, a cold source model is built on the EBSILON platform. The total energy consumption of the cold source system is the research goal. This paper establishes an overall optimization strategy based on PSO-SA. A simulation experiment was conducted on a typical day in the transition season, and the results showed that the optimization strategy can achieve 21.68% energy saving based on the original operation mode when the wet bulb temperature in the transition season is low.

This study investigated, using validated computational fluid dynamics techniques, the actual performance of portable air purifiers for reducing the infection risks of airborne respiratory diseases such as COVID-19, by properly installing air purifiers in complicated large public spaces of primary concern, such as restaurants and ballrooms. The research results reveal that portable air purifiers with HEPA filtration provide an effective solution to help mitigate virus-carrying particles/droplets in large spaces where the central air conditioning system with HEPA filtration may not provide adequate dilution and/or effective ventilation. Deploying portable air purifier changes the local flow directions, and thus, reduces the cross-table airflows that may enhance the possibility of cross-infection. A field experiment was further conducted in a restaurant and a ballroom to verify the on-site performance. This study indicates that each space is unique in furniture, occupant and system layouts and capacities, and thus, requires individualized investigation of appropriate purifier number, capacities, and locations. Flexible solutions such as portable air purifiers are important and low-cost supplements to more elaborate solutions installed in central air systems.

Central air conditioning type ultraviolet light air purifier, its sterilization and disinfection is mainly through ultraviolet sterilization. Ultraviolet rays penetrate the cell membranes of various microorganisms, and destroy their DNA structure, resulting in the destruction of their nucleic acid molecular bonds, so as to achieve a variety of bacteria or immediately die or reproduce the purpose of the offspring.

In order to reduce the energy consumption of houses, it is essential to reduce heating and hot water supply energy, which accounts for about 60% of energy consumption. Therefore we propose a new air conditioning and solar heat collection system to supplement 50% or more of the heating and hot water supply energy. We constructed 6 test houses in 6 regions of different climate characteristics and measured temperature, humidity and energy consumption. Based on these studies it was concluded that an indoor temperature and humidity environment variation is constantly affected by air circulation system. The measured energy conservation effectiveness of solar heat utilization for reduction of heat load requirements are over 50% at 5 locations in winter. The effects of using passive method in summertime is studied. Two types of analysis evaluated as an external air load reduction rate of the total heat exchanger exceeds 60% in each area, and the air conditioner operates with low load and high efficiency in the system. The measurement and numerical simulation were shown the accuracy of the numerical simulation was confirmed with the observation results.

The TRNSYS software is used to study the control method of the central air-conditioning system in a university classroom building. First of all, the paper analyzes the principles and defects of the original control method of central air-conditioning in teaching building. A new type of air conditioning control scheme based on the number of classes is proposed. The program is connected with the teaching system to read the class status and the number of people in the classrooms. The TRNSYS software is used to simulate the air-conditioning system of the two kinds of control scheme. The PMV/PPD index of the new scheme is better than that of the original scheme, and the energy consumption of the new scheme is lower than that of the old scheme. The energy saving rate is 15.27%.

A central air conditioning system based on low-grade energy-bus is studied, which adopts a highly efficient water-cooled air conditioner combined with heat pipe and a bus-type water loop. Low-grade energy is used as the cold or heat source of the system, and heat recovery and utilization in the inner and outer zones is realized. Taking an office building as the object, the operating characteristics of the system are simulated. The results show that in inner zones, the average coefficient of performance ( COP ) of the heat pipe composite units is 5.88; in outer zones, the cooling COP of the heat pipe composite units is 3.65 and the mean heating COP is 3.58. It shows the operating performance of the air conditioning system based on energy-bus is efficient and reliable.

This paper proposes a group control method for central air conditioning system based on reinforcement learning to save energy. This method does not depend on the mathematical model of the system, and can automatically improve the control strategy through continuous interaction between the controller and the system. Find the optimal working point of each device under different external conditions by continuous online learning. Even in the case that system parameters changes, the devices can still be guaranteed to work at its optimal performance point. Simulation experiments verify the effectiveness of the proposed method.

In the Northeastern U.S., future heatwaves will increase in frequency, duration, and intensity due to climate change. A great deal of the research about the health impacts from extreme heat has used ambient meteorological measurements, which can result in exposure misclassification because buildings alter indoor temperatures and ambient temperatures are not uniform across cities. To characterize indoor temperature exposures during an extreme heat event in buildings with and without central air conditioning (AC), personal monitoring was conducted with 51 (central AC, n = 24, non-central AC, n = 27) low-income senior residents of public housing in Cambridge, Massachusetts in 2015, to comprehensively assess indoor temperatures, sleep, and physiological outcomes of galvanic skin response (GSR) and heart rate (HR), along with daily surveys of adaptive behaviors and health symptoms. As expected, non-central AC units (Tmean = 25.6 &deg, C) were significantly warmer than those with central AC (Tmean = 23.2 &deg, C, p &lt, 0.001). With higher indoor temperatures, sleep was more disrupted and GSR and HR both increased (p &lt, 0.001). However, there were no changes in hydration behaviors between residents of different buildings over time and few moderate/several health symptoms were reported. This suggests both a lack of behavioral adaptation and thermal decompensation beginning, highlighting the need to improve building cooling strategies and heat education to low-income senior residents, especially in historically cooler climates.

Recent work suggests that evaporative coolers increase the level and diversity of bioaerosols, but this association remains understudied in low-income homes. We conducted a cross-sectional study of metropolitan, low-income homes in Utah with evaporative coolers (n = 20) and central air conditioners (n = 28). Dust samples (N = 147) were collected from four locations in each home and analyzed for dust-mite allergens Der p1 and Der f1, endotoxins, and β-(1 → 3)-d-glucans. In all sample locations combined, Der p1 or Der f1 was significantly higher in evaporative cooler versus central air conditioning homes (OR = 2.29, 95% CI = 1.05-4.98). Endotoxin concentration was significantly higher in evaporative cooler versus central air conditioning homes in furniture (geometric mean (GM) = 8.05 vs 2.85 EU/mg, P

The traditional algorithm is a combination of fuzzy dynamic programming and priority-based heuristic rules. The optimization performance of interruptible load scheduling is poor. For this reason, the central air conditioning load interruptible scheduling algorithm is proposed based on big data analysis. The algorithm adopts the characteristics of central air conditioning load management and selects the time scale of central air conditioning load scheduling. By optimizing the flexibility of interruptible scheduling, based on the central air conditioning load interruptible scheduling model, the optimal individual in the last generation population is decoded by binary coding, so as to realize the central air conditioning load interruptible scheduling algorithm. The experiment proves that the central air conditioning load interruptible scheduling algorithm has strong optimization performance.

With the rapid development of intelligent buildings and the continuous improvement of management requirements, demand for real-time information management and rationality of the storage strategy design in a central air conditioning system are increased simultaneously. Aiming at the characteristics of the central air conditioning data management system with large numbers of detecting points, large capacity of storage, variety in subsystems, and management complexity in intelligent buildings, the data acquisition module was constructed and the data management system was designed and implemented in the research based on OPC remote access server technology and the zero configuration and high efficiency of SQLite database. The experimental and practical results show that the designed system can be used for data acquisition and information management in central air conditioning monitoring systems and improve the level and efficiency of management to a certain degree.

Karaoke is a popular form of entertainment in Taiwan, considering the sound quality and noise control in such places, most of them are confined spaces. They must rely on central air conditioning for ventilation and ventilation to maintain good indoor air quality. However, the scope of the regulation and control of this announcement is limited to the entrance, the hall, and the waiting area. The purpose of this study was to conduct a comprehensive survey on a chain of Karaoke Club and analyze the different properties of the hall and box space by comparing the data of formaldehyde, TVOC, CO2, and other factors.

Despite the advantages of building enclosure systems for improving ventilation efficiency and reducing energy consumption, there is a large difference in performance from the central heating, ventilating, and air-conditioning (HVAC) system. This study investigated the performance of a smart window-integrated ventilation (SWV) system in conjunction with a centralized HVAC system for enhancing indoor air quality (IAQ) and thermal comfort in a typical single-occupancy office. To evaluate the performance of two coupled systems, IAQ and thermal comfort in an office were analyzed for satisfying seasonally optimal ventilation scenarios using computational fluid dynamics simulations. A set of scenarios for case study was determined by outdoor temperature, supply airflow rate and temperature, and operation strategy of the two systems. Numerical results showed that using the SWV system as an aid to the HVAC system was more effective in winter than in summer for improving IAQ and thermal comfort. Only in the summer, the SWV led to poor IAQ. In spring and autumn, there were scenarios in which the SWV system performed similar to the HVAC system. Therefore, depending on indoor and outdoor conditions, the SWV system can be a good choice as an auxiliary means of the HVAC system or for single operation.

A new comprehensive evaluation method for assessing the sustainability credential of central air-conditioning systems is proposed in this paper. The method is based on the relative coefficient index ( K) of costs and benefits of the air-conditioning system. The paper introduces the concept and defined the parameters of costs (energy consumption costs, economic running costs and environmental impact) and benefits (indoor air quality and thermal comfort) and the mathematical principles for the determination and evaluation of these parameters. The parameters are then ranked with an index value for each component that make up the air-conditioning system, and the total index value would be used for the overall evaluation of the costs and benefits to determine the overall index, K. The feasibility of the method is illustrated by three case studies included in this paper. The evaluation index can identify shortcomings of components in the air-conditioning system and to identify the relative environmental impacts and costs as well as the performance in using the system. The evaluation index would thus allow designers and building managers to target performance improvements and guide designers to optimize functions in terms of costs and benefits to minimize environmental impacts. The index method would provide a rating classification of air-conditioning systems for standard specification and selection in terms of cost effectiveness for appropriate building service required.

The aim of this study was to determine the concentration of Legionella pneumophila in the surface dust of the air ducts of central air conditioning systems and evaluate its effects on indoor air quality. Thirty dust samples were collected from thirty air ducts and analyzed using real-time TaqMan PCR targeting the mip gene. The concentration of surface dust, PM10 mass concentration of air, total plate count of surface dust, and total plate count of supply air were also investigated. Legionella pneumophila microorganisms were detected in 20 of the 30 samples (66.7%) with a mean copy number of 6212 copies/g surface dust. The Spearman’s rank correlation coefficient between Legionella pneumophila concentration and total plate count in surface dust of the air duct was 0.834 (P=0.000). The pollutants in the air ducts in central air conditioning systems were found to affect indoor air quality.

Modern society is facing an increasingly serious energy crisis, and building energy conservation has been paid more and more attention. In recent years, the country has attached great importance to the development of energy conservation and environmental protection industries. Therefore, central air conditioning energy conservation technology has become an emerging industry in the construction industry everywhere. It has played an important role in supporting economic and social development, driving the rise of related industries, and promoting energy conservation and emission reduction. The traditional central air-conditioning control system consumes a lot of energy while controlling a more suitable temperature. According to statistics, the energy consumption of central air conditioning accounts for more than 40% of the energy consumption of the entire building. The control technology of the traditional air-conditioning system is backward, which not only wastes a lot of energy, but also fails to meet the requirements of the new technology conditions. This article takes the central air-conditioning enterprises such as Yatai Group Co. Ltd., Zhongda Air Conditioning Group Co. Ltd, Shandong GRAD Group Co. Ltd. as the representative, to conduct the application research of the central air-conditioning energy-saving control technology to promote the application and development of the central air-conditioning energy-saving control technology.

A partition scheduling system of central air-conditioning based on Wireless Local Area Network (WLAN) positioning is designed. The system can quickly update the personnel density of the partition by WLAN positioning algorithm, and obtain the actual load by integrating the temperature and humidity and the surrounding partition information. Therefore, the rotating speeds of the fans and water pumps of the air conditioning in this area are automatically adjusted, so as to realize the intelligent scheduling of the air conditioning in different areas based on personnel density. At the same time of regional differentiation, the overall cooperative operation can truly achieve the energy-saving effect of distribution on demand.

The article presents an entropy-statistical analysis of losses in the mixing section of a central air conditioner. The temperature and humidity of the outdoor and recirculating air were measured. The methodology for determining losses using the entropy-statistical method is presented in the work. The calculation of losses in the mixing section of the central air conditioner due to the mixing of air flows depending on the flow rate of the supply and recirculation air as well as due to hydraulic losses. A comparative analysis of the results is carried out and the distribution diagrams of the component losses are presented. Proposed conclusions regarding the way to reduce losses.

As the main energy consumption of modern buildings, it is still an important research direction of energy conservation to reduce the power consumption of central air-conditioning. In this study, a prediction model was established between the power of central air-conditioning and some controllable as well as environmental parameter by Neural Networks, and then we use the model as fitness function of Genetic Algorithm, search for optimal values to get a minimum power. And experiment shows this method can reduce power consumption.

In this paper, the thermal performance of a sunspace attached to a house with a central air conditioning system was experimentally investigated. The house with a south-facing sunspace is located in Miyazaki, Japan, where heating is required in winter. In order to reduce the heating energy in winter, the hot air from the attached sunspace is sent to the central air conditioning room, from where it is then distributed and stored throughout the house by way of air circulation. Only when the temperature in the sunspace exceeds 24 °C is the hot air in the sunspace sent to the central air conditioning room. The air circulation between the attached sunspace and central air conditioning room is 500 m3/h. The temperature of the attached sunspace and each room were measured. The results showed that a house with a sunspace can save about 12.2% of energy compared to a house without a sunspace.

This paper uses a variety of machine learning methods to predict the hourly power consumption of a central air-conditioning system in a public building. It is found that the parameters of the central air-conditioning system are different at different times, so is the corresponding power consumption. The paper applies the time series to predict the power consumption on account of the time, which predicts the hourly power consumption based on historical time series data. Comparing the prediction accuracy of multiple machine learning methods, we find that the Gradient Boosting Regression Tree (GBRT), one of the ensemble learning methods, has the highest prediction accuracy.

In this paper, Simulink model is built to simulate the chilled water system of a real building. The optimal chilled water flow rate and chilled water supply temperature are found out by traversing the constrained parameter values under different working conditions. The simple optimal control rules are developed based on the optimal solutions. Optimal control rules can reduce the total energy consumption of the chillers, chilled water pumps, and air handling units by 17.55% compared with tradition control.

189 conditioned residential single-family and multi-family homes in the cooling-dominated climate of Texas were instrumented with home energy management systems (HEMS) to collect sub-metered data on HVAC operations. This study analyses the HVAC operation from these homes over a 1-year period to determine the duty cycles of the HVAC systems. This includes annual, monthly, and hourly HVAC ON-OFF operation patterns. Regression analysis was used to determine the relationship to HVAC energy use and whole-home energy use, and the influence of building and occupant characteristics. HVAC runtimes are found to be approximately 20% per year, but vary, depending on the season and time of day. Daily and monthly runtime fractions are lowest (10%) at average outdoor temperatures of 15°C, and increase with increasing or decreasing temperature. Hourly runtime peaks at 7 pm in the cooling season, while in the heating and transition seasons, it peaks at 7 am. The number of occupants and the indoor cooling set point temperature were found to most strongly influence the HVAC runtime. The results are formatted to be used in various building and indoor air quality applications where the studied phenomena are influenced by HVAC operation.

The energy-saving optimization control strategies of central air-conditioning system widely used now is according to the operation parameters of the cold source side to adjust the load supply. But the operation parameter describes the centralized and hysteresis effect about the central air conditioning system in current load. The effects can’t well reflect the actual change about the user load and ensure the comfort of all users. It will be better if directly regulate the cold source of central air conditioning load according to the needs of the terminal users. Based on this idea, the study calculates the load of the terminal air-conditioning equipment according to its operating parameters, and then the dynamic load forecasting methods is used to establish the forecasting model that can forecast in real-time the load demand in the next time. The load forecasting methods do not need to analyze the factors that directly affect indoor load changes and to establish the load changes physical model. It use “the degree of load changes” to describe the load variation influence so to avoid the randomness and uncertainty about the change of the air-conditioning system load. The experimental results show that the forecasting model has well prediction effect. With the support of network control technology, all the terminal user load demand can be got, so the total load about the central air-conditioning based the terminal user forecasting load can be got. The better energy-saving optimization control strategies of central air-conditioning system will be get to use the forecasting load as the basis of the energy saving control for the central air conditioning cold source system.

Due to the complexity and diversity of energy conversions in HVAC systems, this paper is focused on the central air conditioning systems with water-cooled chiller and its operational energy consumption. Through analyzing the energy flows of the five consecutive loops which extract energy from the conditioned spaces and rejects it to the environment, the global energy intensity index is first to be put forwarded and then the decomposition method which analyzes the influence of the specific consumption (e) and delivered fluid ratios (p) on global energy intensity is proposed. The important conclusion drawn from this method is that it is necessary to decrease both the specific consumption and delivered fluid ratios of the main energy users in order to decrease the global energy intensity of HVAC system. Finally, the global energy intensity of central air conditioning system of a twenty six-story office building in Guangzhou, China in design and real condition is compared and analyzed by e–p decomposition method as a case study.

With the improvement of living standards, air conditioning becomes the requisite of people’s life; the central air conditioning has become each big building of major appliances[1]. In the whole air conditioning cooling water treatment system, such as scale and sludge which is formed by the metal corrosion phenomenon, will seriously affect the use efficiency of air conditioning. One of the effective solution is adding scale inhibitor to the circulating water. Calcium carbonate deposition method is used to evaluate the scale inhibition rate of PASP, PESA and poly glutamic acid. then evaluate the scale inhibition rate of two compound formula. Results show that PESA with the best scale inhibitor performance, on the basis of its, respectively, compound with PASP and poly glutamic acid. The compound repice can improve the efficiency of scale inhibition. The optimized prescription is that, the PASP is 4mg/L, the PESA is 6mg/L, at this time of scale inhibition efficiency can reach 93.43%.

To achieve the centralized monitoring and integrated management of the central air-conditioning system, taking the characteristics of data communications and control complexity in the air-conditioning system into consideration, and combined with the OPC (OLE(Object Linking and Embedding) for Process Control) technology, an intelligent central airconditioning supervisory system is developed and designed. In this paper, after searching the OPC technology standard, the overall structure diagram of the monitoring system is designed, and the OPC server program is also developed by using Knight OPC Server Rapid Development Toolkits. The OPC client application program and man-machine interface are exploited by KingView configuration software. The monitor and control system whose interface is opened is designed for the central air-conditioning. In the end, the experiment result proves that the system operation has good performance for temperature-controller and humidity-controller clustered controlling as well as data communications, thus, satisfying the requirements.

Nowadays, the power load has been well increased and the differences between the crest and the valley of the load has become larger and larger. At the same time, the central air conditioning system plays a more important role in modern life and it has the potential to change these differences. In this paper, in view of a building’s central air conditioning system, central air conditioning system’s power load unload model have been built. A method of calculation of the ability of central air conditioning to unload the load which is based on comfort has been proposed. And it uses the enumeration method for solving optimization of the unloading. Via this research, we can figure out how much load can be unloaded to ease the crest and the valley of the load. And how can we minimize the loss of comfort can also be published.

At present, with the development of science and technology, central air conditioning systems had made great progress. Because of the earlier central air conditioning system have some shortcomings. Such as hunge energy consumption, water cycle equipment wear. Now engineer put forward a variety of solutions. One of the most mainstream solutions is technology of frequency conversion water cycle central air-conditioning system and the central air conditioning system of intelligent sending wind energy saving technology. This design is for central air conditioning system of a company's actual renovation project. It is equipped with technology of frequency conversion water cycle central air-conditioning system. Mainly consist of the control part, frequency converter part and the water cycle part. This paper firstly introduces the working principle of general frequency converter PID control central air conditioning system. And from the control cabinet part, motor start part, PLC control part, and the frequency converter set part introduces the design. And analyzed the operating results. Because of using negative feedback, the temperature of system become stable. Through PLC intelligent control, can also make the system more energy conservation and environmental protection. Through the analysis of the actual system running data, verified the system has a considerable energy saving ability.

The El Paso Children's Health Study examined environmental risk factors for allergy and asthma among fourth and fifth grade schoolchildren living in a major United States-Mexico border city. Complete questionnaire information was available for 5210 children, while adequate pulmonary function data were available for a subset of 1874. Herein we studied indoor environmental health risk factors for allergy and asthma. Several indoor environmental risk factors were associated with allergy and asthma. In particular, we found that ant and spider pest problems, pet dogs, fireplace heat, central air conditioning, humidifier use, and cooking with gas stoves were positively associated with both allergy and asthma prevalence. With regards to asthma severity, our analysis indicated that exposure to pet dogs increased monotonically with increasing asthma severity while the lack of any heat source and gas stove use for cooking decreased monotonically with increasing asthma severity. Lung function also decreased among children who lived in homes with reported cockroach pest problem in the past year without concurrent use of pesticides. These effects on pulmonary function were present even after excluding children with a current physician's diagnosis of asthma. Clinicians and public health professionals may need to look closely at the contribution of these indoor risk factors on pulmonary health and quality of life among susceptible populations.

To avoid some unnecessary energy waste of the central air-conditioning system automatically, a design of intelligent controllers and the related control algorithm are proposed to close fan coils at certain times of the day. As many temperature controllers are not qualified with timing function, the timing function is added to temperature controllers by this method without replacing the original devices. The intelligent controller can check the on/off state of fan coil units at set times. If some fan coil unit is found in “on” state at the set time, the fan coil unit will be shut down. Air conditioners will not be left “on” because of human negligence by setting the closed time. According to the result of experimental tests, the design and control algorithm can meet requirements of daily use.

The microbial contamination of central air conditioning system is one of the important factors that affect the indoor air quality. Actual measurement and analysis were carried out on microbial contamination in central air conditioning system at a venue in Dalian, China. Illumina miseq method was used and three fungal samples of two units were analysed by high throughput sequencing. Results showed that the predominant fungus in air conditioning unit A and B were Candida spp. and Cladosporium spp., and two fungus were further used in the hygrothermal response experiment. Based on the data of Cladosporium in hygrothermal response experiment, this paper used the logistic equation and the Gompertz equation to fit the growth predictive model of Cladosporium genera in different temperature and relative humidity conditions, and the square root model was fitted based on the two environmental factors. In addition, the models were carried on the analysis to verify the accuracy and feasibility of the established model equation.