Indoor Outdoor Research Articles

Particle removal efficiency of a household portable air cleaner in real-world residences: A single-blind cross-over field study

Portable air cleaners are commonly used to reduce indoor air particles in China, but few studies have evaluated the treatment efficiency under real living conditions. We aimed to evaluate the efficiency of a portable air cleaner in common residences under normal living conditions. A single-blind cross-over field study was conducted in 20 urban residences in Chongqing, China. In each residence, one portable air cleaner was operated without a high-efficiency particulate air (HEPA) filter (sham filtration) for the first 48 h and with a HEPA filter (true filtration) for the next 48 h in the living room. Concentrations of PM1.0, PM2.5, respirable suspended particulate matter (RESP), PM10, and total suspended particulate matter (TSP) were measured simultaneously in indoor and ambient outdoor air. Compared to sham filtration, the average concentrations of indoor air particles were significantly lower when true filtration was used according to paired-sample t-tests (all p-values <0.05). However, indoor concentrations of PM2.5 in 16 (80%) residences were still higher than the World Health Organization's (WHO) air quality guideline during true filtration. The removal efficiencies of the portable air cleaners with HEPA filters for these particles were about 40%. The removal efficiencies for PM1.0, PM2.5, and RESP had significant associations with the room volume, but not with the residence district, season, age of the building, floor level of the apartment, or ambient weather. Our results indicate that a portable air cleaner is effective in improving household air quality, but is not enough to ensure the air quality meeting WHO guideline in all real-world residences in polluted areas.

Distribution characteristics of and personal exposure with polycyclic aromatic hydrocarbons and particulate matter in indoor and outdoor air of rural households in Northern China

Gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) and size-segregated particulate matter (PM) in indoor air and outdoor air, along with personal exposure, were monitored in rural households of Northern China. The daily average concentrations of 28 species were 1310 ± 811, 738 ± 321, 465 ± 247, and 655 ± 250 ng/m3 in kitchen air, bedroom air, and outdoor air, and for personal exposure, respectively. PAHs tended to occur in the particulate phase with increasing molecular weight. Absorption by particulate organic carbon was dominant in the gas-particle partitioning process. The daily averaged concentrations of PM2.5 and PM1.0 were 104 ± 39.5 and 88.4 ± 39.3 μg/m3 in kitchen air, 79.0 ± 63.2 and 65.7 ± 57.5 μg/m3 in bedroom air, 52.9 ± 16.5 and 41.5 ± 12.5 μg/m3 in outdoor air, and 71.7 ± 30.8 and 61.5 ± 28.4 μg/m3 for personal exposure, respectively. The non-priority components contributed 5.5 ± 2.8% to the total PAHs, while their fraction of carcinogenic risk reached 85.6 ± 6.9%. The mean cancer risk posed to rural residents via inhalation exposure to PAHs exceeded the current acceptable threshold of 1.0 × 10−6 and the national average estimated in China. The personal exposure levels of PAHs and PM in households using clean energy were lower than those in households using traditional biomass by 30.0%, 29.4%, and 38.5% for PAH28, PM2.5, and PM1.0, respectively. However, the cancer risk of personal inhalation exposure to PAH28 from using liquid petroleum gas (LPG) was higher than that from using firewood, implying the adoption of LPG may not effectively reduce the cancer risk despite the decreasing exposure levels of PAH28 and PM with respect to the use of firewood. Cooking individuals suffered higher exposure levels of PAH28 and PM1.0 compared with non-cooking individuals, and the cancer risk of personal inhalation exposure to PAH28 for cooking individuals was 1.7 times that for non-cooking individuals. Cooking was a critical factor that affected the personal exposure levels of the local male and female residents.

Data-driven model for cross ventilation potential in high-density cities based on coupled CFD simulation and machine learning

Effective urban ventilation through decent urban planning and building design can alleviate the deterioration of the urban built environment. However, natural ventilation requirements and guidelines in current building codes and standards are either qualitative or quantitative but subject to an absolute indoor airspeed threshold without considering the outdoor wind environment. To fill this gap, this paper develops an urban-scale coupled indoor and outdoor computational fluid dynamics (CFD) model and defines a novel ventilation index to assess natural ventilation potential. The index considers wind environments of both indoor and outdoor spaces. First, the coupled CFD model is developed to study wind-driven cross ventilation in high-density cities. A 3D isothermal CFD simulation is solved using the RNG k-ε turbulent model. The simulation results are compared with wind tunnel experiment data from literature. Second, six key design variables are used to generate 3840 parametric design variations for natural ventilation assessment. Third, a novel integrated index CIOIv (coupled indoor and outdoor interaction) is proposed to evaluate the wind speed ratio between the indoor area and outdoor reference area. For demonstration, CIOIv,F1 is used to represent CIOIv on the ground level. Data-driven CIOIv,F1 models are developed to predict indoor building ventilation potential for quick early design support. Compared with multivariate linear regression model, the Gradient Boosting non-linear model displays much higher prediction accuracy (mean absolute percentage error = 0.16 with R2 = 0.8). In early design stage, designers and engineers can skip the computational expensive CFD simulations and use this data-drive model to quickly check the building natural ventilation potentials of different design options in an urban environment.

Thermal environment perceptions considering length of stay for cardiovascular inpatients in hospitals: a statistical approach

Cardiovascular patients are one of the highest population groups affected by elevated external temperatures. Many research studies highlight the impact of three main indicators: mortality rates, morbidity, and admissions to hospitals. Most research determined that cardiovascular patients were among the top admissions to hospitals. The external temperature needs to be evaluated while the patients are hospitalised to reveal the extent of its impact. This study also seeks to evaluate the impact of the length of stay periods on the perceived thermal environment of cardiovascular inpatients when the external temperatures are elevated particularly in summer periods. To do so, longitudinal data analysis of indoor air temperatures, relative humidity and outdoor air temperatures linked with recorded patients’ responses, was undertaken for three months in cardiology and cardiac surgery wards in a hospital in Saudi Arabia, i.e. a hot, arid dessert climate (BWh) based on the Köppen Geiger climate zones map. Patient questionnaires were administrated during the daytime, specifically the afternoon hours to obtain the best results when outdoor temperatures exceeded 40°C. The gathered data was analysed using several statistical tests for correlations and differences to validate the results. The patients who were hospitalised for more than one week and one month felt more neutral compared to other shorter periods of stay; this was interpreted as patients having sufficient time acclimatise to their environment.

Numerical investigation of particle distribution in a floor heated room with different air change rates

Airborne particles have a significant effect on human health in enclosed volumes like rooms and office areas. Particle distribution in these spaces should be well known to understand how heating systems may harm to human regarding to respirable particles. In this study, being a major low temperature system aiming energy efficiency, the floor heating system was examined in terms of on particle distribution in a room numerically. When particle concentration come into question, floor heating systems should be evaluated and compared with other heating choices. The effects of five different air change rates on five different particle size were investigated by finite volume method using Eulerian-Lagrangian model. In this study, the effect of drag, lift, thermophoretic and Brownian forces were considered. It is found that, air change rate is a critical factor to obtain desired indoor air quality but outdoor air conditions may worsen the indoor quality due to air pollution.

Detection of Basic Human Physical Activities With Indoor–Outdoor Information Using Sigma-Based Features and Deep Learning

The devices created on account of the developments in wearable technology are increasingly becoming a part of our daily lives. In particular, sensors have enhanced the usefulness of such devices. The aim of this paper is to detect human physical activity along with indoor/outdoor information by using mobile phones and a separate oxygen saturation sensor. There is no relevant dataset in the literature for this type of detection. For this purpose, data from four different types of human physical activity was collected through mobile phone and oxygen saturation sensors; 12 people aged between 20-65 years participated in the study. During the data collection process, different physical activities under different environmental conditions were performed by the subjects in 10 min. As a next step, a novel deep neural network (DNN) model specifically designed for physical activity recognition was proposed. In order to improve accuracy and reduce the computational complexity, standard deviation (sigma)-based features were introduced. To evaluate its efficacy, we conducted comparisons with selected machine learning algorithms on our proposed dataset. The results on our dataset indicate that the multimodal sigma-based features give the best classification accuracy of 81.60% using our proposed DNN method. Furthermore, the accuracy of the classification made with our proposed DNN method without sigma-based features was 79.04%.

Exposure to Bacterial and Fungal Aerosols: Microorganism Indices in A Waste-Sorting Plant in Poland.

An increased understanding of airborne microorganism populations should enable a better interpretation of bioaerosol exposure found in a working environment. An assessment of the contamination levels of mesophilic bacterial aerosol (MBA) and fungal aerosol (FA) was carried out using two evaluation indices for microbiological pollution—the total index of microbiological contamination per cubic meter (TIMC/m3) and the indoor–outdoor index (IOI). An advantage of selected indices is the inclusion of several co-existing factors that have an impact on the formation of bioaerosol. When properly used, they also highlight the low efficiency of the ventilation system caused by an insufficient air exchange. In this study, the microbial air quality (MAQ) of the working environment was assessed during the spring season at a sorting plant located in Southern Poland. Sampling was undertaken in the plant using an Andersen six-stage impactor which allows the obtainment of information about the size distribution of the air microflora. The value of average concentrations of MBA and the average concentration of FA collected in the preliminary cabin of the sorting plant (PCSP) and the cleaning cabin of the sorting plant (CCSP) were analyzed. The obtained values of MBA were 1.6 times higher indoors, compared to outdoors, while FA was 1.7 times higher outdoors than indoors. The maximum TIMC/m3 value was obtained in PCSP (2626). The calculated IOI in this study suggests that MBA concentrations are influenced by internal sources, as opposed to FA. The purpose of this work was to present the usefulness of using indices in assessing air quality.

Perceived participation and its determinants among young and middle-aged stroke survivors following acute care one month after discharge

Purpose To describe the perceived participation and assess its determinants among young and middle-aged stroke patients following acute care one month after discharge in mainland China. Methods Two hundred and twenty-three patients were consecutively recruited from two tertiary hospitals and were followed up 1 month after discharge in the outpatient department or their communities to assess their participation by using the Impact on Participation and Autonomy Questionnaire, with 23 patients lost to follow-up. Determinants (i.e., sociodemographic, diseased-related, physical, psychological, and social factors) of participation were identified in four domains: indoor autonomy; outdoor autonomy; family role; and social life. Results The overall perceived participation of our respondents was good to fair. Forty-six (23.0%), 32 (16.0%), 13 (6.5%), and 19 (9.5%) perceived their participation as “very good” in the domains of indoor autonomy, family role, outdoor autonomy and social life, respectively. Stroke severity, depressive symptoms, and social support were the common determinants of participation for all the domains, with stroke severity being the strongest correlate. Activities of daily living was associated with indoor autonomy, family role, and outdoor autonomy, but not associated with social life. Conclusions The perceived participation of our respondents is relatively optimistic. Physical health along with mental and social status can affect participation. Tailored strategies should be implemented early in the rehabilitation phase to promote stoke survivors’ participation in all the domains. Implications for rehabilitation Although the overall perceived participation of young and middle-aged stroke patients was fair to good, attention should be paid to their family roles. The strategies should be mainly focused on reducing the stroke severity to improve patients’ participation. Improving patients’ depressive symptom and social support can also be helpful for improving their participation.

What Lies Beneath One’s Feet? Terrain Classification Using Inertial Data of Human Walk

The objective of this study was to investigate if the inertial data collected from normal human walk can be used to reveal the underlying terrain types. For this purpose, we recorded the gait patterns of normal human walk on six different terrain types with variation in hardness and friction using body mounted inertial sensors. We collected accelerations and angular velocities of 40 healthy subjects with two smartphones embedded inertial measurement units (MPU-6500) attached at two different body locations (chest and lower back). The recorded data were segmented with stride based segmentation approach and 194 tempo-spectral features were computed for each stride. We trained two machine learning classifiers, namely random forest and support vector machine, and cross validated the results with 10-fold cross-validation strategy. The classification tasks were performed on indoor–outdoor terrains, hard–soft terrains, and a combination of binary, ternary, quaternary, quinary and senary terrains. From the experimental results, the classification accuracies of 97% and 92% were achieved for indoor–outdoor and hard–soft terrains, respectively. The classification results for binary, ternary, quaternary, quinary and senary class classification were 96%, 94%, 92%, 90%, and 89%, respectively. These results demonstrate that the stride data collected with the low-level signals of a single IMU can be used to train classifiers and predict terrain types with high accuracy. Moreover, the problem at hand can be solved invariant of sensor type and sensor location.

Localization Approach Based on Ray-Tracing Simulations and Fingerprinting Techniques for Indoor–Outdoor Scenarios

The increase of the technology related to radio localization and the exponential rise in the data traffic demanded requires a large number of base stations to be installed. This increase in the base stations density also causes a sharp rise in energy consumption of cellular networks. Consequently, energy saving and cost reduction is a significant factor for network operators in the development of future localization networks. In this paper, a localization method based on ray-tracing and fingerprinting techniques is presented. Simulation tools based on high frequencies are used to characterize the channel propagation and to obtain the ray-tracing data. Moreover, the fingerprinting technique requires a costly initial learning phase for cell fingerprint generation (radio-map). To estimate the localization of mobile stations, this paper compares power levels and delay between rays as cost function with different distance metrics. The experimental results show that greater accuracy can be obtained in the location process using the delay between rays as a cost function and the Mahalanobis distance as a metric instead of traditional methods based on power levels and the Euclidean distance. The proposed method appears well suited for localization systems applied to indoor and outdoor scenarios and avoids large and costly measurement campaigns.

Effects of various operating conditions on the performance of a CO2 air conditioning system for trains

This paper aims to investigate the effects of different operating parameters on the performance of a transcritical CO2 air conditioning system for trains. Similar designs of automotive CO2 air conditioning system are used in the train system such as internal heat exchanger (IHX) to improve the system efficiency. Experimental results are presented for the performance characteristics of the CO2 train air conditioning system with two independent circuits under different test conditions such as different refrigerant charge amount, compressor working frequency, indoor air volume flow rate and outdoor chamber temperature. Two different operating modes of the two circuits are also included in this research. For mode I while only one circuit is working, the test results show that the maximum cooling capacity and coefficient of performance (COP) is 24.3 kW and 2.7, during 55 Hz and 40 Hz compressor working frequency conditions respectively. Also, the cooling capacity and COP reach the minimum, 16.2 kW and 1.5, when the outdoor chamber temperature is 45 °C. For mode II while both two circuits are working, the results show that the cooling capacity and COP are 42.0 kW and 2.4, respectively. The system performance error between the test and numerical modeling which directs the design of the system is within ±5%. Furthermore, an optimum high pressure control algorithm for the transcritical CO2 cycle of the train AC system is also presented.

Indoor Versus Outdoor Occurrence in Mortality of Accidental Hypothermia in Japan: The J-Point Registry.

The impact of the location where accidental hypothermia (AH) occurs has not been fully investigated thus far. This was a multicenter retrospective study of patients with a body temperature ≤35°C obtained at the emergency department of 12 hospitals in Japan between April 2011 and March 2016. We divided the patients into two groups according to the location where AH occurred (indoor group versus outdoor group). The association between each location of the occurrence of AH and in-hospital mortality was evaluated via a multivariable logistic regression analysis. The primary outcome of this study was in-hospital death. The secondary outcomes were the lengths of ICU and hospital stay. A total of 572 patients were enrolled in the hypothermia database, and 537 patients were included in the analyses. A total of 119 and 418 patients experienced hypothermia with outdoor and indoor occurrence, respectively. The indoor group was older and had worse activities of daily living compared with the outdoor group. With regard to the outcome, the proportion of in-hospital death was higher in the indoor group than in the outdoor group (28.2% [118/418] vs. 10.9% [13/119], p < 0.001). The multivariable logistic regression analysis showed that the adjusted odds ratio of the indoor group was 2.48 (95% confidence interval, 1.18-5.17). In terms of secondary outcomes, both the lengths of ICU and hospital stay of the survivors were longer in the indoor group than in the outdoor group. Hypothermia with indoor occurrence accounts for ∼78% of the total AH cases in this study, and the proportion of in-hospital deaths was higher in the indoor group than in the outdoor group. Warnings about the indoor onset of AH must be provided, and countermeasures for the prevention and early recognition of AH with indoor occurrence must be taken.

Vapor intrusion evaluation for redevelopment of former industrial facilities

Former industrial facilities in our cities are finding new life as they are repurposed for use as nonindustrial commercial or even residential spaces. Often, these buildings are brownfield properties, complicating redevelopment because of past industrial uses that led to soil and/or water contamination at the site. In case site contaminants include volatile chemicals (VCs), concerns about air quality at the site may arise. VCs can vaporize from the subsurface and migrate through soil to outdoor air or into indoor spaces of overlying buildings, where they may accumulate.Vapour intrusion is a relevant problem especially at sites where building modernization and revitalization is to be carried out, as environmental investigations may be complicated by the structure of the built environment, and the contamination may remain undetected. Moreover, upgrading structures to meet building codes and energy conservation requirements can create tight buildings that may enhance the effects of vapor intrusion.For accurately predicting whether indoor air quality is being or will be adversely affected by subsurface contaminations a multiple lines of evidence approach should be used. Many issues can in fact introduce uncertainty in predicting indoor air concentrations related to vapor intrusion, including i) sampling and analytical methods ii) modelling of fate & transport from subsurface into building, iii) indoor/ambient background sources.This work refers about the risk management strategy at a site in Milan (Italy) where soil remediation (excavation and off-site disposal) left a residual volume of soil polluted with petroleum-derived hydrocarbons next to redeveloped buildings. Furthermore, the site was also affected by an extended plume of chlorinated solvents in groundwater from an unknown source, likely external to the site. Indoor air, outdoor air, crawl-space air and soil gas samplings were carried out to collect robust information for evaluating decisions points in the vapor intrusion process. Despite few ambient air and crawl-space measurements resulted in episodic high values, as a general trend, the average outdoor and indoor concentrations did not differ significantly from the background values, suggesting other sources than soil pollution were affecting the quality of the air at the site. Although not strictly necessary in terms of time-averaged health risk, a mitigation system of the residual soil contamination was, however, installed to prevent future uncontrolled exposure.

Study on winter indoor thermal environment of temporary shelters built in Nepal after massive earthquake 2015

After massive earthquake 2015, thousands of Nepalese who lost their permanent houses by the hardest hits were forced to live in makeshift temporary shelters. The people residing in these shelters are facing extreme coldness that causes various health-related problems in winter. The field measurement on indoor thermal environment was conducted in one of the district hit by massive earthquake, Lalitpur. The indoor and outdoor air temperatures of five shelters were measured by a set of thermometers with digital data loggers at the ten minute intervals in winter. The mean indoor and mean outdoor air temperatures during the measured night-time were found to be from 10.3°C and 7.6°C; they were lower than lower limit value of acceptable indoor temperature at 11°C found from our previous research. We analyzed the thermal characteristics of those shelters measured for seeking whether the improvement is possible or not and also how much of it is affordable. Thus, in this study, we evaluated the indoor thermal environment by estimating the heat-transmission characteristics of the used materials in these investigated shelters. The total heat loss coefficient estimated in five shelters per respective floor areas ranged from 11.2 to 15.4 W/(m2·K). These values obtained are very large due to low thermal insulation materials used. The paper ends with important lesson that reduce the total heat loss coefficient needs to reduce down to 2∼7 W/(m2·K) for realising the need to indoor air temperature above at 11°C could be 70% of nighttime hours. Such reduction of heat loss was found to be realized by adding affordable materials, i.e. cellular polyethylene foam and clothes for respective walls and roof.

Ragam Spesies dan Karakteristik Habitat Nyamuk di Kecamatan Juai, Kabupaten Balangan, Provinsi Kalimantan Selatan

Filariasis is a mosquito borne disease which caused by filarial worm. In addition, beside causing ahigh morbidity rate and socioeconomic losses, the disease may also decrease the human productivity. Thecontrol efforts have been done by vector control program, yet still not effective. This is due to a lack ofunderstanding of the biology of mosquito vector. The aim of this research was to determine diversity ofmosquitoes, density, behavior, characteristic habitat and their role of filariasis transmission. The researchwas conducted from Januari to April 2015 in Hamarung and Hukai Villages, Juai Subdistrict, BalanganDistrict, South Kalimantan Province. Collection of mosquitoes was done by bare leg bait indoor collectionmethod and outdoor collection method from 06.00 pm–06.00 am. In additon, larvae were collected in theirpotencial habitats. There were 15 species mosquitoes comprising of 5 genera i.e. genus of Culex, Mansonia,Anopheles, Armigeres, and Aedes. There were 5 dominant species of mosquitoes i.e. Cx. tritaeniorhynchus(36.80%), Cx. quinquefasciatus (29.60%), Ma. dives (11.73%), Ma. annulata (10.04%) dan Ma. uniformis(4.62%). The peak activity of Cx. tritaeniorhynchus and Cx. quinquefasciatus in both villages occurred at21.00–00.45. Based on the habitat of mosquitoes, genus of Culex, Mansonia and Anopheles were found inswamps. Mosquitoes dissection did not show any microfilaria stages (L1, L2, L3).

Uncertainty-Based Vibration/Gyro Composite Planetary Terrain Mapping.

Accurate perception of the detected terrain is a precondition for the planetary rover to perform its own mission. However, terrain measurement based on vision and LIDAR is subject to environmental changes such as strong illumination and dust storms. In this paper, considering the influence of uncertainty in the detection process, a vibration/gyro coupled terrain estimation method based on multipoint ranging information is proposed. The terrain update model is derived by analyzing the measurement uncertainty and motion uncertainty. Combined with Clearpath Jackal unmanned vehicle—the terrain mapping accuracy test based on ROS (Robot Operating System) simulation environment—indoor Optitrack auxiliary environment and outdoor soil environment was completed. The results show that the proposed algorithm has high reconstruction ability for a given scale terrain. The reconstruction accuracy in the above test environments is within 1 cm, 2 cm, and 6 cm, respectively.

A Human-assistive Robotic Platform with Quadrupedal Locomotion.

Mobility impairment is becoming a challenging issue around the world with a rapid increase on aging population. Existing tools of walking assistance for mobility-impaired people include passive canes or wheeled rollators which increase energy consumption on the users and disturb the users' walking rhythm, and powered wheeled chairs which could preclude the muscle activities and accelerate the degeneration of the lower limbs. The research in this paper aiming at helping mobility-impaired people proposes a novel robotic platform with quadrupedal locomotion. With motorized actuation, the quadruped robotic platform could accompany the user at the center and provide protection and possible walking assistance if needed. As the robotic platform is equipped with a leg locomotion, it can enlarge the user's activity environments, such as both indoor flat floor and outdoor uneven terrain. It can even assist the user to involve in some mobility challenging activities, such as climbing stairs. In this paper, we illustrate the mechanical design of the robotic platform. A continuous gait planning is proposed to create a smooth locomotion for the robot. To quantify the performance, a system-level walking experimentation was conducted, and the results showed that quadruped robotic platform can maintain a statically stability which demonstrate the feasibility and capability of the robotic application for walking assistance.

Detection of metallic iron in urban dust by using high-temperature measurements supplemented with microscopic observations and Mössbauer spectra

This paper presents a thermomagnetic study of fresh, unheated indoor dust, outdoor dust, street dust and dust from the cabin air filters of cars. Detailed analysis of thermomagnetic curves clearly indicated the presence of two magnetic transitions: the first identified at the Curie temperature TC ~ 585 °C for magnetite; the second TC detected at about ~765 °C, indicating the presence of metallic iron and/or iron-based alloys. The ‘tail,’ i.e., the substantial decreasing of κ visible on the heating curves of κ(T) between 600 °C and 700 °C, was attributed to the metallic iron or iron-based alloys. The presence of a high-temperature Fe-phase is not dependent on the types of urban dust or the sampling method, as variable amounts of metallic iron were detected in material collected from different environments: both indoor dust and outdoor dust, and dust gathered by sweeping indoor floor surfaces as well as dust collected with a vacuum cleaner.The presence of metallic iron in different types of dust was confirmed by non-magnetic methods. Electron microscopic observations with Energy-Dispersive X-ray Spectroscopy revealed elongated shaving-like particles comprised of metallic iron. A component with a magnetic hyperfine field of Bhf ~ 33 T and an almost zero value for isomeric shift as well as zero quadrupole splitting typical of metallic α-Fe at micrometer size or Fe-based alloys was recognized in all the Mössbauer spectra.Additional measurements of hysteresis properties at high temperatures (up to 750 °C) and after step-wise annealing indicated the process of oxidation of iron to magnetite. This has a strong effect on the run of κ(T) and M(T) curves during heating and cooling because M and κ are strongly dependent on the apparent concentration of both ferromagnetic phases (magnetite and metallic iron).

Experiment‐based supervised learning approach toward condition monitoring of PV array mismatch

Unprecedented mismatch occur frequently in the photovoltaic (PV) array systems, challenging the classical monitoring systems. However, the study of artificial intelligence methods lacks some well-designed experiments for a systematic verification because mismatch are influenced by many aspects such as the PV array, the DC–DC converter, the DC–AC inverter, the loads as well as the environmental variables. The objective has two folds. One is to design some identical apparatuses to emulate the ‘same’ real-world solar power station that is operated under multiple mismatch for a controllable, repeatable and comparable experimental study. Another is to propose a novel condition monitoring strategy based on the backward propagation neural network and a decision-making formula. Some controllable indoor experiments and uncontrollable outdoor experiments are carried out to verify the ideas. Such work has never been studied before. The experimental results show that the derived monitoring systems identify and classify accurately different mismatch in both indoor tests and outdoor experiments. Moreover, real-time experimental results infer that the data-driven approach with the self-learning capabilities is adaptive to the environmental changes. Therefore, the supervised learning-based condition monitoring strategy is promising in the solar power industry in terms of operation management and performance enhancement.

Effect of building façade on indoor transportation noise annoyance in terms of frequency spectrum and expectation for sound insulation

This study explored the effect of building façade on indoor transportation noise annoyance in terms of frequency spectrum and expectation for sound insulation. The stimuli for transportation noise (road, rail, and aircraft noise) consisted of the original sound recorded outdoors, and the indoor sounds involved sounds filtered by filters using frequency responses of the insulation of the façades. The first experiment, which was conducted to reveal the effect of the frequency spectrum, compared the relative annoyance due to indoor noise and outdoor noise, both presented at 45 and 65 dB (LAeq). The results showed that in most cases, the indoor noise with lower sound energy in the high-frequency range produced lower annoyance than the outdoor noise for equal sound levels. In the second experiment, the participants were asked to rate the annoyance due to transportation noises presented at sound levels ranging from 35 to 75 dB (LAeq) in a specific imagined hearing situation (indoors or outdoors). Contrary to the first experiment, the results showed that in most cases, the annoyance due to indoor noise in an imagined indoor hearing situation, where sound insulation of the façade is expected, was higher than that due to outdoor noise in an imagined outdoor hearing situation for equivalent sound levels. The results of the two laboratory experiments demonstrate that the building façade has influences on the indoor transportation noise annoyance due to the frequency spectrum and the expectation for sound insulation.